Patient-derived tumor xenograft(PDX)models,a method involving the surgical extraction of tumor tissues from cancer patients and subsequent transplantation into immunodeficient mice,have emerged as a pivotal approach i...Patient-derived tumor xenograft(PDX)models,a method involving the surgical extraction of tumor tissues from cancer patients and subsequent transplantation into immunodeficient mice,have emerged as a pivotal approach in translational research,particularly in advancing precision medicine.As the first stage of PDX development,the patient-derived orthotopic xenograft(PDOX)models implant tumor tissue in mice in the corresponding anatomical locations of the patient.The PDOX models have several advantages,including high fidelity to the original tumor,heightened drug sensitivity,and an elevated rate of successful transplantation.However,the PDOX models present significant challenges,requiring advanced surgical techniques and resourceintensive imaging technologies,which limit its application.And then,the humanized mouse models,as well as the zebrafish models,were developed.Humanized mouse models contain a human immune environment resembling the tumor and immune system interplay.The humanized mouse models are a hot topic in PDX model research.Regarding zebrafish patient-derived tumor xenografts(zPDX)and patient-derived organoids(PDO)as promising models for studying cancer and drug discovery,zPDX models are used to transplant tumors into zebrafish as novel personalized medical animal models with the advantage of reducing patient waiting time.PDO models provide a cost-effective approach for drug testing that replicates the in vivo environment and preserves important tumor-related information for patients.The present review highlights the functional characteristics of each new phase of PDX and provides insights into the challenges and prospective developments in this rapidly evolving field.展开更多
Cancer cell membrane(CCM)derived nanotechnology functionalizes nanoparticles(NPs)to recognize homologous cells,exhibiting translational potential in accurate tumor therapy.However,these nanoplatforms are majorly gener...Cancer cell membrane(CCM)derived nanotechnology functionalizes nanoparticles(NPs)to recognize homologous cells,exhibiting translational potential in accurate tumor therapy.However,these nanoplatforms are majorly generated from fixed cell lines and are typically evaluated in cell line-derived subcutaneous-xenografts(CDX),ignoring the tumor heterogeneity and differentiation from inter-and intra-individuals and microenvironments between heterotopic-and orthotopic-tumors,limiting the therapeutic efficiency of such nanoplatforms.Herein,various biomimetic nanoplatforms(CCM-modified gold@Carbon,i.e.,Au@C-CCM)were fabricated by coating CCMs of head and neck squamous cell carcinoma(HNSCC)cell lines and patient-derived cells on the surface of Au@C NP.The generated Au@C-CCMs were evaluated on corresponding CDX,tongue orthotopic xenograft(TOX),immunecompetent primary and distant tumor models,and patient-derived xenograft(PDX)models.The Au@C-CCM generates a photothermal conversion efficiency up to 44.2% for primary HNSCC therapy and induced immunotherapy to inhibit metastasis via photothermal therapy-induced immunogenic cell death.The homologous CCM endowed the nanoplatforms with optimal targeting properties for the highest therapeutic efficiency,far above those with mismatched CCMs,resulting in distinct tumor ablation and tumor growth inhibition in all four models.This work reinforces the feasibility of biomimetic NPs combining modular designed CMs and functional cores for customized treatment of HNSCC,can be further extended to other malignant tumors therapy.展开更多
Severely immunocompromised NOD.Cg-PrkdcIl2rg(NOG)mice are among the ideal animal recipients for generation of human cancer models.Transplantation of human solid tumors having abundant tumor-i nfiltrating lymphocytes(T...Severely immunocompromised NOD.Cg-PrkdcIl2rg(NOG)mice are among the ideal animal recipients for generation of human cancer models.Transplantation of human solid tumors having abundant tumor-i nfiltrating lymphocytes(TILs)can induce xenogeneic graft-versus-host disease(xGvHD)following engraftment and expansion of the TILs inside the animal body.Wilms’tumor(WT)has not been recognized as a lymphocyte-predominant tumor.However,3 consecutive generations of NOG mice bearing WT patient-derived xenografts(PDX)xenotransplanted from a single donor showed different degrees of inflammatory symptoms after transplantation before any therapeutic intervention.In the initial generation,dermatitis,auto-amputation of digits,weight loss,lymphadenopathy,hepatitis,and interstitial pneumonitis were observed.Despite antibiotic treatment,no response was noticed,and thus the animals were prematurely euthanized(day 47 posttransplantation).Laboratory and histopathologic evaluations revealed lymphoid infiltrates positively immunostained with anti-human CD3 and CD8 antibodies in the xenografts and primary tumor,whereas no microbial infection or lymphoproliferative disorder was found.Mice of the next generation that lived longer(91 days)developed sclerotic skin changes and more severe pneumonitis.Cutaneous symptoms were milder in the last generation.The xenografts of the last 2 generations also contained TILs,and lacked lymphoproliferative transformation.The systemic immunoinflammatory syndrome in the absence of microbial infection and posttransplant lymphoproliferative disorder was suggestive of xGvHD.While there are few reports of xGvHD in severely immunodeficient mice xenotransplanted from lymphodominant tumor xenografts,this report for the first time documented serial xGvHD in consecutive passages of WT PDX-bearing models and discussed potential solutions to prevent such an undesired complication.展开更多
AIM To assess the viability of orthotopic and heterotopic patient-derived pancreatic cancer xenografts implanted into nude mice.METHODS This study presents a prospective experimental analytical follow-up of the develo...AIM To assess the viability of orthotopic and heterotopic patient-derived pancreatic cancer xenografts implanted into nude mice.METHODS This study presents a prospective experimental analytical follow-up of the development of tumours in mice upon implantation of human pancreatic adenocarcinoma samples. Specimens were obtained surgically from patients with a pathological diagnosis of pancreatic adenocarcinoma. Tumour samples from pancreatic cancer patients were transplanted into nude mice in three different locations(intraperitoneal, subcutaneous and pancreatic). Histological analysis(haematoxylin-eosin and Masson's trichrome staining) and immunohistochemical assessment of apoptosis(TUNEL), proliferation(Ki-67), angiogenesis(CD31) and fibrogenesis(α-SMA) were performed. When a tumour xenograft reached the target size, it was reimplanted in a new nude mouse. Three sequential tumour xenograft generations were generated(F1, F2 and F3).RESULTS The overall tumour engraftment rate was 61.1%. The subcutaneous model was most effective in terms of tissue growth(69.9%), followed by intraperitoneal(57.6%) and pancreatic(55%) models. Tumour development was faster in the subcutaneous model(17.7 ± 2.6 wk) compared with the pancreatic(23.1 ± 2.3 wk) and intraperitoneal(25.0 ± 2.7 wk) models(P = 0.064). There was a progressive increase in the tumour engraftment rate over successive generations for all three models(F1 28.1% vs F2 71.4% vs F3 80.9%, P < 0.001). There were no significant differences in tumour xenograft differentiation and cell proliferation between human samples and the three experimental models among the sequential generations of tumour xenografts. However, a progressive decrease in fibrosis, fibrogenesis, tumour vascularisation and apoptosis was observed in the three experimental models compared with the human samples. All three pancreatic patient-derived xenograft models presented similar histological and immunohistochemical characteristics.CONCLUSION In our experience, the faster development andgreatest number of viable xenografts could make the subcutaneous model the best option for experimentation in pancreatic cancer.展开更多
We recently reported several driver genes of biliary tract carcinoma(BTC) that are known to play important roles in oncogenesis and disease progression. Although the need for developing novel therapeutic strategies is...We recently reported several driver genes of biliary tract carcinoma(BTC) that are known to play important roles in oncogenesis and disease progression. Although the need for developing novel therapeutic strategies is increasing, there are very few BTC cell lines and xenograft models currently available for conducting preclinical studies. Using a total of 88 surgical BTC specimens and 536 immunodeficient mice, 28 xenograft models and 13 new BTC cell lines, including subtypes, were established. Some of our cell lines were found to be resistant to gemcitabine, which is currently the first choice of treatment, thereby allowing highly practical preclinical studies to be conducted. Using the aforementioned cell lines and xenograft models and a clinical pathological database of patients undergoing BTC resection, we can establish a preclinical study system and appropriate parameters for drug efficacy studies to explore new biomarkers for practical applications in the future studies.展开更多
The patient-derived xenografts (PDX) model is an animal model established by transplanting primary tumors or fresh tumor tissues of patient origin directly into immunodeficient mice, which preserves the heterogeneity ...The patient-derived xenografts (PDX) model is an animal model established by transplanting primary tumors or fresh tumor tissues of patient origin directly into immunodeficient mice, which preserves the heterogeneity and survival microenvironment of the primary tumor and is widely used in preclinical and precision medicine research of tumors. This article reviews the construction of the PDX model of human bladder cancer and the progress of the application of the PDX model in bladder cancer.展开更多
Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the curr...Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.展开更多
New fractional operators, the COVID-19 model has been studied in this paper. By using different numericaltechniques and the time fractional parameters, the mechanical characteristics of the fractional order model arei...New fractional operators, the COVID-19 model has been studied in this paper. By using different numericaltechniques and the time fractional parameters, the mechanical characteristics of the fractional order model areidentified. The uniqueness and existence have been established. Themodel’sUlam-Hyers stability analysis has beenfound. In order to justify the theoretical results, numerical simulations are carried out for the presented methodin the range of fractional order to show the implications of fractional and fractal orders.We applied very effectivenumerical techniques to obtain the solutions of themodel and simulations. Also, we present conditions of existencefor a solution to the proposed epidemicmodel and to calculate the reproduction number in certain state conditionsof the analyzed dynamic system. COVID-19 fractional order model for the case of Wuhan, China, is offered foranalysis with simulations in order to determine the possible efficacy of Coronavirus disease transmission in theCommunity. For this reason, we employed the COVID-19 fractal fractional derivative model in the example ofWuhan, China, with the given beginning conditions. In conclusion, again the mathematical models with fractionaloperators can facilitate the improvement of decision-making for measures to be taken in the management of anepidemic situation.展开更多
BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are p...BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are pivotal in identifying the most suitable transplant candidates.Traditionally,scoring systems like the model for end-stage liver disease have been instrumental in this process.Nevertheless,the landscape of prognostication is undergoing a transformation with the integration of machine learning(ML)and artificial intelligence models.AIM To assess the utility of ML models in prognostication for LT,comparing their performance and reliability to established traditional scoring systems.METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines,we conducted a thorough and standardized literature search using the PubMed/MEDLINE database.Our search imposed no restrictions on publication year,age,or gender.Exclusion criteria encompassed non-English studies,review articles,case reports,conference papers,studies with missing data,or those exhibiting evident methodological flaws.RESULTS Our search yielded a total of 64 articles,with 23 meeting the inclusion criteria.Among the selected studies,60.8%originated from the United States and China combined.Only one pediatric study met the criteria.Notably,91%of the studies were published within the past five years.ML models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values(ranging from 0.6 to 1)across all studies,surpassing the performance of traditional scoring systems.Random forest exhibited superior predictive capabilities for 90-d mortality following LT,sepsis,and acute kidney injury(AKI).In contrast,gradient boosting excelled in predicting the risk of graft-versus-host disease,pneumonia,and AKI.CONCLUSION This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT,marking a significant evolution in the field of prognostication.展开更多
Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochast...Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.展开更多
Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction me...Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.展开更多
In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems...In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.展开更多
The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication e...The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication efforts, malaria remains a serious threat, particularly in regions like Africa. This study explores how integrating Gregor’s Type IV theory with Geographic Information Systems (GIS) improves our understanding of disease dynamics, especially Malaria transmission patterns in Uganda. By combining data-driven algorithms, artificial intelligence, and geospatial analysis, the research aims to determine the most reliable predictors of Malaria incident rates and assess the impact of different factors on transmission. Using diverse predictive modeling techniques including Linear Regression, K-Nearest Neighbor, Neural Network, and Random Forest, the study found that;Random Forest model outperformed the others, demonstrating superior predictive accuracy with an R<sup>2</sup> of approximately 0.88 and a Mean Squared Error (MSE) of 0.0534, Antimalarial treatment was identified as the most influential factor, with mosquito net access associated with a significant reduction in incident rates, while higher temperatures correlated with increased rates. Our study concluded that the Random Forest model was effective in predicting malaria incident rates in Uganda and highlighted the significance of climate factors and preventive measures such as mosquito nets and antimalarial drugs. We recommended that districts with malaria hotspots lacking Indoor Residual Spraying (IRS) coverage prioritize its implementation to mitigate incident rates, while those with high malaria rates in 2020 require immediate attention. By advocating for the use of appropriate predictive models, our research emphasized the importance of evidence-based decision-making in malaria control strategies, aiming to reduce transmission rates and save lives.展开更多
The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can repr...The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.展开更多
Context/Objective: High blood pressure (HBP) currently represents the most widespread chronic non-communicable disease in Cameroon. The increase in its prevalence in the country is the result of multiple factors inclu...Context/Objective: High blood pressure (HBP) currently represents the most widespread chronic non-communicable disease in Cameroon. The increase in its prevalence in the country is the result of multiple factors including economic stress imposed by precariousness, poor living conditions, sources of anxiety, anguish, depression and other behavioral disorders. Economic stress is a globalizing concept that integrates into a purely hermeneutic approach, a particular functioning of the nervous system of an individual who faces employment problems and precarious remuneration conditions. The non-satisfaction by an individual of his basic needs due to insufficient financial means can cause him to become irritable, aggressive, and socially and symbolically isolated, thereby increasing the desire to resort to morbid life models such as excessive consumption of narcotics and other psychoactive substances often associated with high blood pressure. The fight against the emergence of BPH is a complex, multifaceted and multifactorial reality that requires taking into account economic stress. The main objective of this survey is to describe the situation of economic stress within the Cameroonian population, which imposes precariousness and life models at risk of high blood pressure. Specifically, we determined the level of household income and the sources of income. Methods: A cross-sectional survey with a descriptive aim among five hundred households in the Central Region of Cameroon was conducted. A probabilistic technique called simple randomness was used. The number of households to be surveyed was determined indirectly using the Cochrane formula. Data collection in face-to-face mode using a physical questionnaire took place from July 1 to August 31, 2023, after obtaining ethical clearance from the Regional Health Research Ethics Committee, Human from the Center and an administrative authorization for data collection. Regarding their processing, the data was grouped during processing in Excel sheets. Normality and reliability tests of the collected data were carried out. For this, the Chi-square test was used for data with a qualitative value and that of Kolmogorov-Sminorf for data with a quantitative value. Descriptive analysis was possible using R software version 3.2, SPSS version 25.0, XLSTAT 2016, PAST and EXCEL programs from Microsoft Office 2013. Results: The main results highlight economic stress, with 45.60% of households surveyed earning less than US$154 per month;55% of household heads were women in single-parent families;14% of household heads were unemployed, 22% worked in the private sector and 19% were self-employed. This general economic situation leads to precarious living conditions, thereby increasing the risk of high blood pressure among the Cameroonian population.展开更多
Oxidative stress has been associated with a number of physiological problems in swine,including reduced production efficiency.Recently,although there has been increased research into regulatory mechanisms and antioxid...Oxidative stress has been associated with a number of physiological problems in swine,including reduced production efficiency.Recently,although there has been increased research into regulatory mechanisms and antioxidant strategies in relation to oxidative stress-induced pig production,it remains so far largely unsuccessful to develop accurate models and nutritional strategies for specific oxidative stress factors.Here,we discuss the dose and dose intensity of the causes of oxidative stress involving physiological,environmental and dietary factors,recent research models and the antioxidant strategies to provide theoretical guidance for future oxidative stress research in swine.展开更多
Hepatitis E virus(HEV)is one of the leading causes of acute viral hepatitis worldwide.Although most of HEV infections are asymptomatic,some patients will develop the symptoms,especially pregnant women,the elderly,and ...Hepatitis E virus(HEV)is one of the leading causes of acute viral hepatitis worldwide.Although most of HEV infections are asymptomatic,some patients will develop the symptoms,especially pregnant women,the elderly,and patients with preexisting liver diseases,who often experience anorexia,nausea,vom-iting,malaise,abdominal pain,and jaundice.HEV infection may become chronic in immunosuppressed individuals.In addition,HEV infection can also cause several extrahepatic manifestations.HEV exists in a wide range of hosts in nature and can be transmitted across species.Hence,animals susceptible to HEV can be used as models.The establishment of animal models is of great significance for studying HEV transmission,clinical symptoms,extrahepatic manifestations,and therapeutic strategies,which will help us understand the pathogenesis,prevention,and treatment of hepatitis E.This review summarized the animal models of HEV,including pigs,monkeys,rabbits,mice,rats,and other animals.For each animal species,we provided a concise summary of the HEV genotypes that they can be infected with,the cross-species transmission pathways,as well as their role in studying extrahepatic manifestations,prevention,and treatment of HEV infection.The advantages and disadvantages of these animal models were also emphasized.This review offers new perspectives to enhance the current understanding of the research landscape surrounding HEV animal models.展开更多
Neurodegenerative diseases(NDs)are a group of debilitating neurological disorders that primarily affect elderly populations and include Alzheimer's disease(AD),Parkinson's disease(PD),Huntington's disease(...Neurodegenerative diseases(NDs)are a group of debilitating neurological disorders that primarily affect elderly populations and include Alzheimer's disease(AD),Parkinson's disease(PD),Huntington's disease(HD),and amyotrophic lateral sclerosis(ALS).Currently,there are no therapies available that can delay,stop,or reverse the pathological progression of NDs in clinical settings.As the population ages,NDs are imposing a huge burden on public health systems and affected families.Animal models are important tools for preclinical investigations to understand disease pathogenesis and test potential treatments.While numerous rodent models of NDs have been developed to enhance our understanding of disease mechanisms,the limited success of translating findings from animal models to clinical practice suggests that there is still a need to bridge this translation gap.Old World nonhuman primates(NHPs),such as rhesus,cynomolgus,and vervet monkeys,are phylogenetically,physiologically,biochemically,and behaviorally most relevant to humans.This is particularly evident in the similarity of the structure and function of their central nervous systems,rendering such species uniquely valuable for neuroscience research.Recently,the development of several genetically modified NHP models of NDs has successfully recapitulated key pathologies and revealed novel mechanisms.This review focuses on the efficacy of NHPs in modeling NDs and the novel pathological insights gained,as well as the challenges associated with the generation of such models and the complexities involved in their subsequent analysis.展开更多
Huntington'sdisease(HD)isahereditary neurodegenerative disorder for which there is currently no effectivetreatmentavailable.Consequently,the development of appropriate disease models is critical to thoroughly inve...Huntington'sdisease(HD)isahereditary neurodegenerative disorder for which there is currently no effectivetreatmentavailable.Consequently,the development of appropriate disease models is critical to thoroughly investigate disease progression.The genetic basis of HD involves the abnormal expansion of CAG repeats in the huntingtin(HTT)gene,leading to the expansion of a polyglutamine repeat in the HTT protein.Mutant HTT carrying the expanded polyglutamine repeat undergoes misfolding and forms aggregates in the brain,which precipitate selective neuronal loss in specific brain regions.Animal models play an important role in elucidating the pathogenesis of neurodegenerative disorders such as HD and in identifying potential therapeutic targets.Due to the marked species differences between rodents and larger animals,substantial efforts have been directed toward establishing large animal models for HD research.These models are pivotal for advancing the discovery of novel therapeutic targets,enhancing effective drug delivery methods,and improving treatment outcomes.We have explored the advantages of utilizing large animal models,particularly pigs,in previous reviews.Since then,however,significant progress has been made in developing more sophisticated animal models that faithfully replicate the typical pathology of HD.In the current review,we provide a comprehensive overview of large animal models of HD,incorporating recent findings regarding the establishment of HD knock-in(KI)pigs and their genetic therapy.We also explore the utilization of large animal models in HD research,with a focus on sheep,non-human primates(NHPs),and pigs.Our objective is to provide valuable insights into the application of these large animal models for the investigation and treatment of neurodegenerative disorders.展开更多
Global gridded crop models(GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far o...Global gridded crop models(GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national-and provincial-scale evaluation of the simulations by13 GGCMs [12 from the GGCM Intercomparison(GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops(wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national-and provincial-scale crop yield prediction in China.展开更多
基金The Science,Technology and Innovation Commission of Shenzhen,Grant/Award Number:JCYJ20220531093213030。
文摘Patient-derived tumor xenograft(PDX)models,a method involving the surgical extraction of tumor tissues from cancer patients and subsequent transplantation into immunodeficient mice,have emerged as a pivotal approach in translational research,particularly in advancing precision medicine.As the first stage of PDX development,the patient-derived orthotopic xenograft(PDOX)models implant tumor tissue in mice in the corresponding anatomical locations of the patient.The PDOX models have several advantages,including high fidelity to the original tumor,heightened drug sensitivity,and an elevated rate of successful transplantation.However,the PDOX models present significant challenges,requiring advanced surgical techniques and resourceintensive imaging technologies,which limit its application.And then,the humanized mouse models,as well as the zebrafish models,were developed.Humanized mouse models contain a human immune environment resembling the tumor and immune system interplay.The humanized mouse models are a hot topic in PDX model research.Regarding zebrafish patient-derived tumor xenografts(zPDX)and patient-derived organoids(PDO)as promising models for studying cancer and drug discovery,zPDX models are used to transplant tumors into zebrafish as novel personalized medical animal models with the advantage of reducing patient waiting time.PDO models provide a cost-effective approach for drug testing that replicates the in vivo environment and preserves important tumor-related information for patients.The present review highlights the functional characteristics of each new phase of PDX and provides insights into the challenges and prospective developments in this rapidly evolving field.
基金funded by The National Natural Science Foundation of China(81872199)Key Program of National Natural Science Foundation of China(82030085)+4 种基金The National Key Research and Development Program of China(2017YFC0908500)The National Natural Science Foundation of China(82002853)China Postdoctoral Science Foundation(2019M661565)Innovative Research Team of High-level Local Universities in Shanghai(SHSMU-ZLCX20212300,SSMU-ZLCX20180500)funded by“Shuguang Program”supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission(19SG13)。
文摘Cancer cell membrane(CCM)derived nanotechnology functionalizes nanoparticles(NPs)to recognize homologous cells,exhibiting translational potential in accurate tumor therapy.However,these nanoplatforms are majorly generated from fixed cell lines and are typically evaluated in cell line-derived subcutaneous-xenografts(CDX),ignoring the tumor heterogeneity and differentiation from inter-and intra-individuals and microenvironments between heterotopic-and orthotopic-tumors,limiting the therapeutic efficiency of such nanoplatforms.Herein,various biomimetic nanoplatforms(CCM-modified gold@Carbon,i.e.,Au@C-CCM)were fabricated by coating CCMs of head and neck squamous cell carcinoma(HNSCC)cell lines and patient-derived cells on the surface of Au@C NP.The generated Au@C-CCMs were evaluated on corresponding CDX,tongue orthotopic xenograft(TOX),immunecompetent primary and distant tumor models,and patient-derived xenograft(PDX)models.The Au@C-CCM generates a photothermal conversion efficiency up to 44.2% for primary HNSCC therapy and induced immunotherapy to inhibit metastasis via photothermal therapy-induced immunogenic cell death.The homologous CCM endowed the nanoplatforms with optimal targeting properties for the highest therapeutic efficiency,far above those with mismatched CCMs,resulting in distinct tumor ablation and tumor growth inhibition in all four models.This work reinforces the feasibility of biomimetic NPs combining modular designed CMs and functional cores for customized treatment of HNSCC,can be further extended to other malignant tumors therapy.
基金supported by the grant received from Tehran University of Medical Sciences(TUMS-38292)。
文摘Severely immunocompromised NOD.Cg-PrkdcIl2rg(NOG)mice are among the ideal animal recipients for generation of human cancer models.Transplantation of human solid tumors having abundant tumor-i nfiltrating lymphocytes(TILs)can induce xenogeneic graft-versus-host disease(xGvHD)following engraftment and expansion of the TILs inside the animal body.Wilms’tumor(WT)has not been recognized as a lymphocyte-predominant tumor.However,3 consecutive generations of NOG mice bearing WT patient-derived xenografts(PDX)xenotransplanted from a single donor showed different degrees of inflammatory symptoms after transplantation before any therapeutic intervention.In the initial generation,dermatitis,auto-amputation of digits,weight loss,lymphadenopathy,hepatitis,and interstitial pneumonitis were observed.Despite antibiotic treatment,no response was noticed,and thus the animals were prematurely euthanized(day 47 posttransplantation).Laboratory and histopathologic evaluations revealed lymphoid infiltrates positively immunostained with anti-human CD3 and CD8 antibodies in the xenografts and primary tumor,whereas no microbial infection or lymphoproliferative disorder was found.Mice of the next generation that lived longer(91 days)developed sclerotic skin changes and more severe pneumonitis.Cutaneous symptoms were milder in the last generation.The xenografts of the last 2 generations also contained TILs,and lacked lymphoproliferative transformation.The systemic immunoinflammatory syndrome in the absence of microbial infection and posttransplant lymphoproliferative disorder was suggestive of xGvHD.While there are few reports of xGvHD in severely immunodeficient mice xenotransplanted from lymphodominant tumor xenografts,this report for the first time documented serial xGvHD in consecutive passages of WT PDX-bearing models and discussed potential solutions to prevent such an undesired complication.
基金Supported by the Andalusian Public Foundation for the Management of Health Research in Seville(FISEVI)
文摘AIM To assess the viability of orthotopic and heterotopic patient-derived pancreatic cancer xenografts implanted into nude mice.METHODS This study presents a prospective experimental analytical follow-up of the development of tumours in mice upon implantation of human pancreatic adenocarcinoma samples. Specimens were obtained surgically from patients with a pathological diagnosis of pancreatic adenocarcinoma. Tumour samples from pancreatic cancer patients were transplanted into nude mice in three different locations(intraperitoneal, subcutaneous and pancreatic). Histological analysis(haematoxylin-eosin and Masson's trichrome staining) and immunohistochemical assessment of apoptosis(TUNEL), proliferation(Ki-67), angiogenesis(CD31) and fibrogenesis(α-SMA) were performed. When a tumour xenograft reached the target size, it was reimplanted in a new nude mouse. Three sequential tumour xenograft generations were generated(F1, F2 and F3).RESULTS The overall tumour engraftment rate was 61.1%. The subcutaneous model was most effective in terms of tissue growth(69.9%), followed by intraperitoneal(57.6%) and pancreatic(55%) models. Tumour development was faster in the subcutaneous model(17.7 ± 2.6 wk) compared with the pancreatic(23.1 ± 2.3 wk) and intraperitoneal(25.0 ± 2.7 wk) models(P = 0.064). There was a progressive increase in the tumour engraftment rate over successive generations for all three models(F1 28.1% vs F2 71.4% vs F3 80.9%, P < 0.001). There were no significant differences in tumour xenograft differentiation and cell proliferation between human samples and the three experimental models among the sequential generations of tumour xenografts. However, a progressive decrease in fibrosis, fibrogenesis, tumour vascularisation and apoptosis was observed in the three experimental models compared with the human samples. All three pancreatic patient-derived xenograft models presented similar histological and immunohistochemical characteristics.CONCLUSION In our experience, the faster development andgreatest number of viable xenografts could make the subcutaneous model the best option for experimentation in pancreatic cancer.
文摘We recently reported several driver genes of biliary tract carcinoma(BTC) that are known to play important roles in oncogenesis and disease progression. Although the need for developing novel therapeutic strategies is increasing, there are very few BTC cell lines and xenograft models currently available for conducting preclinical studies. Using a total of 88 surgical BTC specimens and 536 immunodeficient mice, 28 xenograft models and 13 new BTC cell lines, including subtypes, were established. Some of our cell lines were found to be resistant to gemcitabine, which is currently the first choice of treatment, thereby allowing highly practical preclinical studies to be conducted. Using the aforementioned cell lines and xenograft models and a clinical pathological database of patients undergoing BTC resection, we can establish a preclinical study system and appropriate parameters for drug efficacy studies to explore new biomarkers for practical applications in the future studies.
文摘The patient-derived xenografts (PDX) model is an animal model established by transplanting primary tumors or fresh tumor tissues of patient origin directly into immunodeficient mice, which preserves the heterogeneity and survival microenvironment of the primary tumor and is widely used in preclinical and precision medicine research of tumors. This article reviews the construction of the PDX model of human bladder cancer and the progress of the application of the PDX model in bladder cancer.
基金supported by Ministry of Science and Technology of China (Grant No. 2018YFA0606501)National Natural Science Foundation of China (Grant No. 42075037)+1 种基金Key Laboratory Open Research Program of Xinjiang Science and Technology Department (Grant No. 2022D04009)the National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility” (EarthLab)。
文摘Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.
基金Lucian Blaga University of Sibiu&Hasso Plattner Foundation Research Grants LBUS-IRG-2020-06.
文摘New fractional operators, the COVID-19 model has been studied in this paper. By using different numericaltechniques and the time fractional parameters, the mechanical characteristics of the fractional order model areidentified. The uniqueness and existence have been established. Themodel’sUlam-Hyers stability analysis has beenfound. In order to justify the theoretical results, numerical simulations are carried out for the presented methodin the range of fractional order to show the implications of fractional and fractal orders.We applied very effectivenumerical techniques to obtain the solutions of themodel and simulations. Also, we present conditions of existencefor a solution to the proposed epidemicmodel and to calculate the reproduction number in certain state conditionsof the analyzed dynamic system. COVID-19 fractional order model for the case of Wuhan, China, is offered foranalysis with simulations in order to determine the possible efficacy of Coronavirus disease transmission in theCommunity. For this reason, we employed the COVID-19 fractal fractional derivative model in the example ofWuhan, China, with the given beginning conditions. In conclusion, again the mathematical models with fractionaloperators can facilitate the improvement of decision-making for measures to be taken in the management of anepidemic situation.
文摘BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are pivotal in identifying the most suitable transplant candidates.Traditionally,scoring systems like the model for end-stage liver disease have been instrumental in this process.Nevertheless,the landscape of prognostication is undergoing a transformation with the integration of machine learning(ML)and artificial intelligence models.AIM To assess the utility of ML models in prognostication for LT,comparing their performance and reliability to established traditional scoring systems.METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines,we conducted a thorough and standardized literature search using the PubMed/MEDLINE database.Our search imposed no restrictions on publication year,age,or gender.Exclusion criteria encompassed non-English studies,review articles,case reports,conference papers,studies with missing data,or those exhibiting evident methodological flaws.RESULTS Our search yielded a total of 64 articles,with 23 meeting the inclusion criteria.Among the selected studies,60.8%originated from the United States and China combined.Only one pediatric study met the criteria.Notably,91%of the studies were published within the past five years.ML models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values(ranging from 0.6 to 1)across all studies,surpassing the performance of traditional scoring systems.Random forest exhibited superior predictive capabilities for 90-d mortality following LT,sepsis,and acute kidney injury(AKI).In contrast,gradient boosting excelled in predicting the risk of graft-versus-host disease,pneumonia,and AKI.CONCLUSION This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT,marking a significant evolution in the field of prognostication.
基金supported by the National Natural Science Foundation of China(Grant Nos.82173620 to Yang Zhao and 82041024 to Feng Chen)partially supported by the Bill&Melinda Gates Foundation(Grant No.INV-006371 to Feng Chen)Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.
基金Project supported by the National Natural Science Foundation of China(Nos.12272211,12072181,12121002)。
文摘Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.
基金partially supported by the National Natural Science Foundation of China(52375238)Science and Technology Program of Guangzhou(202201020213,202201020193,202201010399)GZHU-HKUST Joint Research Fund(YH202109).
文摘In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.
文摘The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication efforts, malaria remains a serious threat, particularly in regions like Africa. This study explores how integrating Gregor’s Type IV theory with Geographic Information Systems (GIS) improves our understanding of disease dynamics, especially Malaria transmission patterns in Uganda. By combining data-driven algorithms, artificial intelligence, and geospatial analysis, the research aims to determine the most reliable predictors of Malaria incident rates and assess the impact of different factors on transmission. Using diverse predictive modeling techniques including Linear Regression, K-Nearest Neighbor, Neural Network, and Random Forest, the study found that;Random Forest model outperformed the others, demonstrating superior predictive accuracy with an R<sup>2</sup> of approximately 0.88 and a Mean Squared Error (MSE) of 0.0534, Antimalarial treatment was identified as the most influential factor, with mosquito net access associated with a significant reduction in incident rates, while higher temperatures correlated with increased rates. Our study concluded that the Random Forest model was effective in predicting malaria incident rates in Uganda and highlighted the significance of climate factors and preventive measures such as mosquito nets and antimalarial drugs. We recommended that districts with malaria hotspots lacking Indoor Residual Spraying (IRS) coverage prioritize its implementation to mitigate incident rates, while those with high malaria rates in 2020 require immediate attention. By advocating for the use of appropriate predictive models, our research emphasized the importance of evidence-based decision-making in malaria control strategies, aiming to reduce transmission rates and save lives.
基金the support of Texas A&M University at Qatar for the 2022 Sixth Cycle Seed Grant Project。
文摘The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.
文摘Context/Objective: High blood pressure (HBP) currently represents the most widespread chronic non-communicable disease in Cameroon. The increase in its prevalence in the country is the result of multiple factors including economic stress imposed by precariousness, poor living conditions, sources of anxiety, anguish, depression and other behavioral disorders. Economic stress is a globalizing concept that integrates into a purely hermeneutic approach, a particular functioning of the nervous system of an individual who faces employment problems and precarious remuneration conditions. The non-satisfaction by an individual of his basic needs due to insufficient financial means can cause him to become irritable, aggressive, and socially and symbolically isolated, thereby increasing the desire to resort to morbid life models such as excessive consumption of narcotics and other psychoactive substances often associated with high blood pressure. The fight against the emergence of BPH is a complex, multifaceted and multifactorial reality that requires taking into account economic stress. The main objective of this survey is to describe the situation of economic stress within the Cameroonian population, which imposes precariousness and life models at risk of high blood pressure. Specifically, we determined the level of household income and the sources of income. Methods: A cross-sectional survey with a descriptive aim among five hundred households in the Central Region of Cameroon was conducted. A probabilistic technique called simple randomness was used. The number of households to be surveyed was determined indirectly using the Cochrane formula. Data collection in face-to-face mode using a physical questionnaire took place from July 1 to August 31, 2023, after obtaining ethical clearance from the Regional Health Research Ethics Committee, Human from the Center and an administrative authorization for data collection. Regarding their processing, the data was grouped during processing in Excel sheets. Normality and reliability tests of the collected data were carried out. For this, the Chi-square test was used for data with a qualitative value and that of Kolmogorov-Sminorf for data with a quantitative value. Descriptive analysis was possible using R software version 3.2, SPSS version 25.0, XLSTAT 2016, PAST and EXCEL programs from Microsoft Office 2013. Results: The main results highlight economic stress, with 45.60% of households surveyed earning less than US$154 per month;55% of household heads were women in single-parent families;14% of household heads were unemployed, 22% worked in the private sector and 19% were self-employed. This general economic situation leads to precarious living conditions, thereby increasing the risk of high blood pressure among the Cameroonian population.
基金supported by Guangzhou Science and Technology Planning Project(2023A04J0131)Special fund for scientific innovation strategyconstruction of high level Academy of Agriculture Science(R2020PY-JG009,R2022PY-QY007,202106TD)+2 种基金China Agriculture Research System-CARS-35the Project of Swine Innovation Team in Guangdong Modern Agricultural Research System(2022KJ126)Special Fund for Rural Revitalization Strategy of Guangdong(2023TS-3),China。
文摘Oxidative stress has been associated with a number of physiological problems in swine,including reduced production efficiency.Recently,although there has been increased research into regulatory mechanisms and antioxidant strategies in relation to oxidative stress-induced pig production,it remains so far largely unsuccessful to develop accurate models and nutritional strategies for specific oxidative stress factors.Here,we discuss the dose and dose intensity of the causes of oxidative stress involving physiological,environmental and dietary factors,recent research models and the antioxidant strategies to provide theoretical guidance for future oxidative stress research in swine.
基金This study was supported by grants from the National Natural Science Foundation of China(82272396)the Fundamental Research Funds for the Central Universities(226-2022-00061).
文摘Hepatitis E virus(HEV)is one of the leading causes of acute viral hepatitis worldwide.Although most of HEV infections are asymptomatic,some patients will develop the symptoms,especially pregnant women,the elderly,and patients with preexisting liver diseases,who often experience anorexia,nausea,vom-iting,malaise,abdominal pain,and jaundice.HEV infection may become chronic in immunosuppressed individuals.In addition,HEV infection can also cause several extrahepatic manifestations.HEV exists in a wide range of hosts in nature and can be transmitted across species.Hence,animals susceptible to HEV can be used as models.The establishment of animal models is of great significance for studying HEV transmission,clinical symptoms,extrahepatic manifestations,and therapeutic strategies,which will help us understand the pathogenesis,prevention,and treatment of hepatitis E.This review summarized the animal models of HEV,including pigs,monkeys,rabbits,mice,rats,and other animals.For each animal species,we provided a concise summary of the HEV genotypes that they can be infected with,the cross-species transmission pathways,as well as their role in studying extrahepatic manifestations,prevention,and treatment of HEV infection.The advantages and disadvantages of these animal models were also emphasized.This review offers new perspectives to enhance the current understanding of the research landscape surrounding HEV animal models.
基金supported by the National Key Research and Development Program of China (2021YFF0702201)National Natural Science Foundation of China (81873736,31872779,81830032)+2 种基金Guangzhou Key Research Program on Brain Science (202007030008)Department of Science and Technology of Guangdong Province (2021ZT09Y007,2020B121201006,2018B030337001,2021A1515012526)Natural Science Foundation of Guangdong Province (2021A1515012526,2022A1515012651)。
文摘Neurodegenerative diseases(NDs)are a group of debilitating neurological disorders that primarily affect elderly populations and include Alzheimer's disease(AD),Parkinson's disease(PD),Huntington's disease(HD),and amyotrophic lateral sclerosis(ALS).Currently,there are no therapies available that can delay,stop,or reverse the pathological progression of NDs in clinical settings.As the population ages,NDs are imposing a huge burden on public health systems and affected families.Animal models are important tools for preclinical investigations to understand disease pathogenesis and test potential treatments.While numerous rodent models of NDs have been developed to enhance our understanding of disease mechanisms,the limited success of translating findings from animal models to clinical practice suggests that there is still a need to bridge this translation gap.Old World nonhuman primates(NHPs),such as rhesus,cynomolgus,and vervet monkeys,are phylogenetically,physiologically,biochemically,and behaviorally most relevant to humans.This is particularly evident in the similarity of the structure and function of their central nervous systems,rendering such species uniquely valuable for neuroscience research.Recently,the development of several genetically modified NHP models of NDs has successfully recapitulated key pathologies and revealed novel mechanisms.This review focuses on the efficacy of NHPs in modeling NDs and the novel pathological insights gained,as well as the challenges associated with the generation of such models and the complexities involved in their subsequent analysis.
基金supported by the National Key Research and Development Program of China (2021YFA0805300,2021YFA0805200)National Natural Science Foundation of China (32170981,82371874,82394422,82171244,82071421,82271902)+1 种基金Guangzhou Key Research Program on Brain Science (202007030008)Department of Science and Technology of Guangdong Province (2021ZT09Y007,2020B121201006,2018B030337001)。
文摘Huntington'sdisease(HD)isahereditary neurodegenerative disorder for which there is currently no effectivetreatmentavailable.Consequently,the development of appropriate disease models is critical to thoroughly investigate disease progression.The genetic basis of HD involves the abnormal expansion of CAG repeats in the huntingtin(HTT)gene,leading to the expansion of a polyglutamine repeat in the HTT protein.Mutant HTT carrying the expanded polyglutamine repeat undergoes misfolding and forms aggregates in the brain,which precipitate selective neuronal loss in specific brain regions.Animal models play an important role in elucidating the pathogenesis of neurodegenerative disorders such as HD and in identifying potential therapeutic targets.Due to the marked species differences between rodents and larger animals,substantial efforts have been directed toward establishing large animal models for HD research.These models are pivotal for advancing the discovery of novel therapeutic targets,enhancing effective drug delivery methods,and improving treatment outcomes.We have explored the advantages of utilizing large animal models,particularly pigs,in previous reviews.Since then,however,significant progress has been made in developing more sophisticated animal models that faithfully replicate the typical pathology of HD.In the current review,we provide a comprehensive overview of large animal models of HD,incorporating recent findings regarding the establishment of HD knock-in(KI)pigs and their genetic therapy.We also explore the utilization of large animal models in HD research,with a focus on sheep,non-human primates(NHPs),and pigs.Our objective is to provide valuable insights into the application of these large animal models for the investigation and treatment of neurodegenerative disorders.
基金co-supported by the Guangdong Major Project of Basic and Applied Basic Research (Grant No. 2021B0301030007)the National Key Research and Development Program of China (Grant Nos. 2017YFA0604302 and 2017YFA0604804)+1 种基金the National Natural Science Foundation of China (Grant No. 41875137)the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (Earth Lab)。
文摘Global gridded crop models(GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national-and provincial-scale evaluation of the simulations by13 GGCMs [12 from the GGCM Intercomparison(GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops(wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national-and provincial-scale crop yield prediction in China.
