FibroScan-aspartate transaminase:A superior non-invasive model for diagnosing high-risk metabolic dysfunction-associated steatohepatitis

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)with hepatic histological NAFLD activity score≥4 and fibrosis stage F≥2 is regarded as“at risk”non-alcoholic steatohepatitis(NASH).Based on an international consensus,NAFLD and NASH were renamed as metabolic dysfunction-associated steatotic liver disease(MASLD)and metabolic dysfunction-associated steatohepatitis(MASH),respectively;hence,we introduced the term“high-risk MASH”.Diagnostic values of seven non-invasive models,including FibroScan-aspartate transaminase(FAST),fibrosis-4(FIB-4),aspartate transaminase to platelet ratio index(APRI),etc.for high-risk MASH have rarely been studied and compared in MASLD.AIM To assess the clinical value of seven non-invasive models as alternatives to liver biopsy for diagnosing high-risk MASH.METHODS A retrospective analysis was conducted on 309 patients diagnosed with NAFLD via liver biopsy at Beijing Ditan Hospital,between January 2012 and December 2020.After screening for MASLD and the exclusion criteria,279 patients wereincluded and categorized into high-risk and non-high-risk MASH groups.Utilizing threshold values of each model,sensitivity,specificity,positive predictive value(PPV),and negative predictive values(NPV),were calculated.Receiver operating characteristic curves were constructed to evaluate their diagnostic efficacy based on the area under the curve(AUROC).RESULTS MASLD diagnostic criteria were met by 99.4%patients with NAFLD.The MASLD population was analyzed in two cohorts:Overall population(279 patients)and the subgroup(117 patients)who underwent liver transient elastography(FibroScan).In the overall population,FIB-4 showed better diagnostic efficacy and higher PPV,with sensitivity,specificity,PPV,NPV,and AUROC of 26.9%,95.2%,73.5%,72.2%,and 0.75.APRI,Forns index,and aspartate transaminase to alanine transaminase ratio(ARR)showed moderate diagnostic efficacy,whereas S index and gamma-glutamyl transpeptidase to platelet ratio(GPR)were relatively weaker.In the subgroup,FAST had the highest diagnostic efficacy,its sensitivity,specificity,PPV,NPV,and AUROC were 44.2%,92.3%,82.1%,67.4%,and 0.82.The FIB-4 AUROC was 0.76.S index and GPR exhibited almost no diagnostic value for high-risk MASH.CONCLUSION FAST and FIB-4 could replace liver biopsy as more effectively diagnostic methods for high-risk MASH compared to APRI,Forns index,ARR,S index,and GPR;FAST is superior to FIB-4.

Non-invasive model for predicting high-risk esophageal varices based on liver and spleen stiffness

BACKGROUND Acute bleeding due to esophageal varices(EVs)is a life-threatening complication in patients with cirrhosis.The diagnosis of EVs is mainly through upper gastrointestinal endoscopy,but the discomfort,contraindications and complications of gastrointestinal endoscopic screening reduce patient compliance.According to the bleeding risk of EVs,the Baveno VI consensus divides varices into high bleeding risk EVs(HEVs)and low bleeding risk EVs(LEVs).We sought to identify a non-invasive prediction model based on spleen stiffness measurement(SSM)and liver stiffness measurement(LSM)as an alternative to EVs screening.AIM To develop a safe,simple and non-invasive model to predict HEVs in patients with viral cirrhosis and identify patients who can be exempted from upper gastrointestinal endoscopy.METHODS Data from 200 patients with viral cirrhosis were included in this study,with 140 patients as the modelling group and 60 patients as the external validation group,and the EVs types of patients were determined by upper gastrointestinal endoscopy and the Baveno Ⅵ consensus.Those patients were divided into the HEVs group(66 patients)and the LEVs group(74 patients).The effect of each parameter on HEVs was analyzed by univariate and multivariate analyses,and a noninvasive prediction model was established.Finally,the discrimination ability,calibration ability and clinical efficacy of the new model were verified in the modelling group and the external validation group.RESULTS Univariate and multivariate analyses showed that SSM and LSM were associated with the occurrence of HEVs in patients with viral cirrhosis.On this basis,logistic regression analysis was used to construct a prediction model:Ln[P/(1-P)]=-8.184-0.228×SSM+0.642×LSM.The area under the curve of the new model was 0.965.When the cut-off value was 0.27,the sensitivity,specificity,positive predictive value and negative predictive value of the model for predicting HEVs were 100.00%,82.43%,83.52%,and 100%,respectively.Compared with the four prediction models of liver stiffness-spleen diameter to platelet ratio score,variceal risk index,aspartate aminotransferase to alanine aminotransferase ratio,and Baveno VI,the established model can better predict HEVs in patients with viral cirrhosis.CONCLUSION Based on the SSM and LSM measured by transient elastography,we established a non-invasive prediction model for HEVs.The new model is reliable in predicting HEVs and can be used as an alternative to routine upper gastrointestinal endoscopy screening,which is helpful for clinical decision making.

Letter to editor‘Non-invasive model for predicting high-risk esophageal varices based on liver and spleen stiffness’

predicting high-risk esophageal varices based on liver and spleen stiffness".Acute bleeding caused by esophageal varices is a life-threatening complication in patients with liver cirrhosis.Due to the discomfort,contraindications,and associated complications of upper gastrointestinal endoscopy screening,it is crucial to identify an imaging-based non-invasive model for predicting high-risk esophageal varices in patients with cirrhosis.

Non-invasive model for predicting esophageal varices based on liver and spleen volume

BACKGROUND Upper endoscopy is the gold standard for predicting esophageal varices in China.Guidelines and consensus suggest that patients with liver cirrhosis should undergo periodic upper endoscopy,most patients undergo their first upper endoscopy when esophageal variceal bleeds.Therefore,it is important to develop a non-invasive model to early diagnose esophageal varices.AIM To develop a non-invasive predictive model for esophageal varices based on liver and spleen volume in viral cirrhosis patients.METHODS We conducted a cross-sectional study based on viral cirrhosis crowd in the Second Affiliated Hospital of Xi'an Jiaotong University.By collecting the basic information and clinical data of the participants,we derived the independent risk factors and established the prediction model of esophageal varices.The established model was compared with other models.Area under the receiver operating characteristic curve,calibration plot and decision curve analysis were used to test the discriminating ability,calibration ability and clinical practicability in both the internal and external validation.RESULTS The portal vein diameter,the liver and spleen volume,and volume change rate were the independent risk factors of esophageal varices.We successfully used the factors to establish the predictive model[area under the curve(AUC)0.87,95%CI:0.80-0.95],which showed better predictive value than other models.The model showed good discriminating ability,calibration ability and the clinical practicability in both modelling group and external validation group.CONCLUSION The developed non-invasive predictive model can be used as an effective tool for predicting esophageal varices in viral cirrhosis patients.

Diagnostic non-invasive model of large risky esophageal varices in cirrhotic hepatitis C virus patients

AIM To build a diagnostic non-invasive model for screening of large varices in cirrhotic hepatitis C virus(HCV) patients. METHODS This study was conducted on 124 post-HCV cirrhotic patients presenting to the clinics of the Endemic Medicine Department at Mansoura University Hospital for evaluation before HCV antiviral therapy: 78 were Child A and 46 were Child B(score ≤ 8). Inclusion criteria for patients enrolled in this study was presence of cirrhotic HCV(diagnosed by either biopsy or fulfillment of clinical basis). Exclusion criteria consisted of patients with other etiologies of liver cirrhosis, e.g., hepatitis B virus and patients with high MELD score on transplant list. All patients were subjected to full medical record, full basic investigations, endoscopy, and computed tomography(CT), and then divided into groups with no varices, small varices, or large risky varices. In addition, values of Fibrosis-4 score(FIB-4), aminotransferase-to-platelet ratio index(APRI), and platelet count/splenic diameter ratio(PC/SD) were also calculated.RESULTS Detection of large varies is a multi-factorial process, affected by many variables. Choosing binary logistic regression, dependent factors were either large or small varices while independent factors included CT variables such coronary vein diameter, portal vein(PV) diameter, lieno-renal shunt and other laboratory noninvasive variables namely FIB-4, APRI, and platelet count/splenic diameter. Receiver operating characteristic(ROC) curve was plotted to determine the accuracy of non-invasive parameters for predicting the presence of large esophageal varices and the area under the ROC curve for each one of these parameters was obtained. A model was established and the best model for prediction of large risky esophageal varices used both PC/SD and PV diameter(75% accuracy), while the logistic model equation was shown to be(PV diameter ×-0.256) plus(PC/SD ×-0.006) plus(8.155). Values nearing 2 or more denote large varices.CONCLUSION This model equation has 86.9% sensitivity and 57.1% specificity, and would be of clinical applicability with 75% accuracy.

Functional near-infrared spectroscopy in non-invasive neuromodulation

Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks,which have been widely applied in the field of central neurological diseases,such as stroke,Parkinson’s disease,and mental disorders.Although significant advances have been made in neuromodulation technologies,the identification of optimal neurostimulation paramete rs including the co rtical target,duration,and inhibition or excitation pattern is still limited due to the lack of guidance for neural circuits.Moreove r,the neural mechanism unde rlying neuromodulation for improved behavioral performance remains poorly understood.Recently,advancements in neuroimaging have provided insight into neuromodulation techniques.Functional near-infrared spectroscopy,as a novel non-invasive optical brain imaging method,can detect brain activity by measuring cerebral hemodynamics with the advantages of portability,high motion tole rance,and anti-electromagnetic interference.Coupling functional near-infra red spectroscopy with neuromodulation technologies offe rs an opportunity to monitor the cortical response,provide realtime feedbac k,and establish a closed-loop strategy integrating evaluation,feedbac k,and intervention for neurostimulation,which provides a theoretical basis for development of individualized precise neuro rehabilitation.We aimed to summarize the advantages of functional near-infra red spectroscopy and provide an ove rview of the current research on functional near-infrared spectroscopy in transcranial magnetic stimulation,transcranial electrical stimulation,neurofeedback,and braincomputer interfaces.Furthermore,the future perspectives and directions for the application of functional near-infrared spectroscopy in neuromodulation are summarized.In conclusion,functional near-infrared spectroscopy combined with neuromodulation may promote the optimization of central pellral reorganization to achieve better functional recovery form central nervous system diseases.

A Study on Near-Infrared Non-Invasive Blood Glucose Concentration Regression Prediction Based on PSO-MKL-SVR

To improve the accuracy of predicting non-invasive blood glucose concentration in the near-infrared spectrum, we utilized the Particle Swarm Optimization (PSO) algorithm to optimize hyperparameters for the Multi-Kernel Learning Support Vector Machine (MKL-SVR). With these optimized hyperparameters, we established a non-invasive blood glucose regression model, referred to as the PSO-MKL-SVR model. Subsequently, we conducted a comparative analysis between the PSO-MKL-SVR model and the PSO-SVR model. In a dataset comprising ten volunteers, the PSO-MKL-SVR model exhibited significant precision improvements, including a 16.03% reduction in Mean Square Error and a 0.29% increase in the Squared Correlation Coefficient. Moreover, there was a 0.14% higher probability of the Clark’s Error Grid Analysis falling within Zone A. Additionally, the PSO-MKL-SVR model demonstrated a faster operational speed compared to the PSO-SVR model.

Observation on the Effect of Non-Invasive Ventilator Combined with Conventional Therapy in the Treatment of Chronic Obstructive Pulmonary Disease Complicated with Respiratory Failure

Objective:To explore the clinical effect of a non-invasive ventilator combined with conventional therapy in the treatment of patients with chronic obstructive pulmonary disease(COPD)combined with respiratory failure.Methods:68 patients with COPD combined with respiratory failure treated in our hospital from September 2021 to October 2023 were selected as the research subjects.Using the random number table method,they were divided into a control group and an experimental group of 34 cases each.The control group received conventional symptomatic treatment,and the experimental group received non-invasive ventilator treatment based on the control group.The clinical effects,blood gas indicators(partial pressure of carbon dioxide(PaCO_(2)),partial pressure of oxygen(PaO_(2)),arterial oxygen saturation(SaO_(2))),lung function(forced expiratory volume in 1 second(FEV1),forced vital capacity(FVC),6 min walking distance),complications,and inflammatory factor levels(c-reactive protein(CRP),interleukin-6(IL-6),neutrophil-to-lymphocyte ratio(NLR))of the two groups of patients were observed.Results:(1)The clinical efficacy of the patients in the experimental group(33/97.06%)was more significant as compared with the control group(25/73.53%)(P<0.05);(2)After treatment,the clinical efficacy of the two groups of patients in terms of FEV1,FEV1/FVC,6-minute walking distance,PaO_(2)and SaO_(2)all increased in the experimental group as compared to that of the control group(P<0.05);(3)After treatment,the PaCO_(2),CRP,IL-6,and NLR of the two groups of patients decreased,and the decrease in the experimental group was higher than that of the control group(P<0.05);(4)The patients’complication rate in the experimental group(2/5.88%)was lower as compared to that of the control group(9/26.46%)(P<0.05).Conclusion:Non-invasive ventilators combined with conventional therapy achieved good clinical results in treating patients with COPD and respiratory failure.

Relationship Between Gene-Phenotype and Clinical Manifestations of Chromosomal Copy Number Variations Indicated by Non-Invasive Prenatal Testing

Objective:To analyze the clinical value of non-invasive prenatal testing(NIPT)in detecting chromosomal copy number variations(CNVs)and to explore the relationship between gene expression and clinical manifestations of chromosomal copy number variations.Methods:3551 naturally conceived singleton pregnant women who underwent NIPT were included in this study.The NIPT revealed abnormalities other than sex chromosome abnormalities and trisomy 13,18,and 21.Pregnant women with chromosome copy number variations underwent genetic counseling and prenatal ultrasound examination.Interventional prenatal diagnosis and chromosome microarray analysis(CMA)were performed.The clinical phenotypes and pregnancy outcomes of different prenatal diagnoses were analyzed.Additionally,a follow-up was conducted by telephone to track fetal development after birth,at six months,and one year post-birth.Results:A total of 53 cases among 3551 cases showed chromosomal copy number variation.Interventional prenatal diagnosis was performed in 36 cases:27 cases were negative and 8 were consistent with the NIPT test results.This indicates that NIPT’s positive predictive value(PPV)in CNVs is 22.22%.Conclusion:NIPT has certain clinical significance in screening chromosome copy number variations and is expected to become a routine screening for chromosomal microdeletions and microduplications.However,further interventional prenatal diagnosis is still needed to identify fetal CNVs.

Non-invasive optical characterization and estimation of Zn porosity in gas tungsten arc welding of Fe–Al joints using CR model and OES measurements

In this study,we employed a non-invasive approach based on the collisional radiative(CR)model and optical emission spectroscopy(OES)measurements for the characterization of gas tungsten arc welding(GTAW)discharge and quantification of Zn-induced porosity during the GTAW process of Fe–Al joints.The OES measurements were recorded as a function of weld current,welding speed,and input waveform.The OES measurements revealed significant line emissions from Zn-I in 460–640 nm and Ar-I in 680–800 nm wavelength ranges in all experimental settings.The OES coupled CR model approach for Zn-I line emission enabled the simultaneous determination of both essential discharge parameters i.e.electron temperature and electron density.Further,these predictions were used to estimate the Zn-induced porosity using OES-actinometry on Zn-I emission lines using Ar as actinometer gas.The OES-actinometry results were in good agreement with porosity data derived from an independent approach,i.e.x-ray radiography images.The current study shows that OES-based techniques can provide an efficient route for real-time monitoring of weld quality and estimate porosity during the GTAW process of dissimilar metal joints.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer(PanCa)presents a major concern and health burden.The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics;however,they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting.Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures.The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians.Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages.In this review,we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

Non-invasive prediction model for high-risk esophageal varices in the Chinese population

BACKGROUND There are two types of esophageal varices(EVs):high-risk EVs(HEVs)and lowrisk EVs,and HEVs pose a greater threat to patient life than low-risk EVs.The diagnosis of EVs is mainly conducted by gastroscopy,which can cause discomfort to patients,or by non-invasive prediction models.A number of noninvasive models for predicting EVs have been reported;however,those that are based on the formula for calculation of liver and spleen volume in HEVs have not been reported.AIM To establish a non-invasive prediction model based on the formula for liver and spleen volume for predicting HEVs in patients with viral cirrhosis.METHODS Data from 86 EV patients with viral cirrhosis were collected.Actual liver and spleen volumes of the patients were determined by computed tomography,and their calculated liver and spleen volumes were calculated by standard formulas.Other imaging and biochemical data were determined.The impact of each parameter on HEVs was analyzed by univariate and multivariate analyses,the data from which were employed to establish a non-invasive prediction model.Then the established prediction model was compared with other previous prediction models.Finally,the discriminating ability,calibration ability,and clinical efficacy of the new model was verified in both the modeling group and the external validation group.RESULTS Data from univariate and multivariate analyses indicated that the liver-spleen volume ratio,spleen volume change rate,and aspartate aminotransferase were correlated with HEVs.These indexes were successfully used to establish the noninvasive prediction model.The comparison of the models showed that the established model could better predict HEVs compared with previous models.The discriminating ability,calibration ability,and clinical efficacy of the new model were affirmed.CONCLUSION The non-invasive prediction model for predicting HEVs in patients with viral cirrhosis was successfully established.The new model is reliable for predicting HEVs and has clinical applicability.

耦合优化蚁群算法与P-Median model的选址模型设计

为节省城建部门对于公共体育设施的投入成本以及提高城市人民生活质量,以运动场所优化选址为例,提出一种新型设施选址模型。该模型主要基于P-Median model(最小化阻抗模型)根据需求点数量从全部候选设施选址中选择设施空间位置,让用户达到离自己最近设施距离成本总和最小的目的,对选址的基本原则和实际情况提出要求,构造目标函数用于优化后蚁群算法求解进行选址工作。优化蚁群算法实现基于Python语言模块,通过改进蚁群原始信息素,提升原有算法的收敛速度,求出目标函数最优解,可以很好地模拟对于运动场所的选址。用二者耦合进行优势互补所设计的选址模型来搜寻研究区蚁群信息素浓度残留最大的栅格像元,从而确定未被已有设施点服务半径覆盖的最佳设施点建立位置。实验结果表明,该新型选址模型相较于最小化阻抗模型与最大化覆盖模型,新增优化设施点使整体服务半径覆盖率分别高出10.42%和6.95%,适合求解较为精确且小规模空间下的选址问题。

Non-Invasive Approach to Early Diagnosis of the Formation of Oncological Neoplasms

The currently developed instrumental approaches for detecting pathological changes in the body have a number of disadvantages. The most important of them is that the equipment is sensitive to the detection of diseases only from a certain threshold level of destructive changes in the body. The present article discusses the possibility of using the new instrumental complex “Bioscope” for early and non-invasive diagnosis of the beginning of the formation of ontological neoplasm’s in the body.

Mshpy23:a user-friendly,parameterized model of magnetosheath conditions

Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind−Magnetosphere−Ionosphere Link Explorer(SMILE)will observe magnetosheath and its boundary motion in soft X-rays for understanding magnetopause reconnection modes under various solar wind conditions after their respective launches in 2024 and 2025.Magnetosheath conditions,namely,plasma density,velocity,and temperature,are key parameters for predicting and analyzing soft X-ray images from the LEXI and SMILE missions.We developed a userfriendly model of magnetosheath that parameterizes number density,velocity,temperature,and magnetic field by utilizing the global Magnetohydrodynamics(MHD)model as well as the pre-existing gas-dynamic and analytic models.Using this parameterized magnetosheath model,scientists can easily reconstruct expected soft X-ray images and utilize them for analysis of observed images of LEXI and SMILE without simulating the complicated global magnetosphere models.First,we created an MHD-based magnetosheath model by running a total of 14 OpenGGCM global MHD simulations under 7 solar wind densities(1,5,10,15,20,25,and 30 cm)and 2 interplanetary magnetic field Bz components(±4 nT),and then parameterizing the results in new magnetosheath conditions.We compared the magnetosheath model result with THEMIS statistical data and it showed good agreement with a weighted Pearson correlation coefficient greater than 0.77,especially for plasma density and plasma velocity.Second,we compiled a suite of magnetosheath models incorporating previous magnetosheath models(gas-dynamic,analytic),and did two case studies to test the performance.The MHD-based model was comparable to or better than the previous models while providing self-consistency among the magnetosheath parameters.Third,we constructed a tool to calculate a soft X-ray image from any given vantage point,which can support the planning and data analysis of the aforementioned LEXI and SMILE missions.A release of the code has been uploaded to a Github repository.

Invasive versus non-invasive ventilation in patients with COVID-19 pneumonia:A retrospective study

Objective:To compare the survival and length of stay of invasive ventilation(IV)with those of non-invasive ventilation(NIV)in patients with COVID-19 acute respiratory distress syndrome in a single hospital from May 2020 to March 2021.Methods:After obtaining approval from the Hospital Director,the data of COVID-19 patients including demographics,type of respiratory support(non-invasive ventilation or invasive ventilation),duration of ventilation,length of stay,discharge,and death were collected and analyzed.Results:Out of the 152 patients identified,134 patients were analyzed.The median intubation days were 10.0(Q1:3.5,Q3:13.5)in the IV group and 0.0(Q1:0.0,Q3:0.0)days in the NIV-only group.Out of the 101 patients who received NIV,43 patients were subsequently intubated due to failure of NIV.Of the 63 patients(47.01%)who died,22(66.66%)were from the IV group and 40(92.02%)were from the NIV-followed-by-intubation group,and 1(1.72%)were from the NIV-only group.Multivariate analysis showed that the presence of a respiratory comorbidity(OR=16.56,95%CI=1.56-175.48,P=0.02)was an independent predictor of survival.Conclusions:Respiratory co-morbidity is a significant adverse predictor of survival outcome.The decision on the type of respiratory support should be made on a patient-to-patient basis.

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

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.

Genetically modified non-human primate models for research on neurodegenerative diseases

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.

Evaluation of Non-Invasive Markers of Liver Fibrosis in Chronic Hepatitis B Patients in a Sub-Saharan African Setting: Transient Elastography versus APRI, FIB4, GTT/Platelet Scores

Background: Non-invasive markers which use routine laboratory tests are less expensive and highly needed to assess and stage liver fibrosis in chronic hepatitis B patients in Sub-Saharan Africa. We aimed at evaluating liver fibrosis, using the Aspartate aminotransferase to Platelet Ratio Index (APRI), Fibrosis Index Based on 4 factors (FIB4), and Gamma-glutamyl transpeptidase to Platelet Ratio (GPR) in chronic hepatitis B patients with transient elastography as the reference so as to choose an alternative to transient elastography. Method: We carried out a cross-sectional study using the records of patients who attended the Douala General Hospital and Marie O Polyclinic Douala from 2012 to 2017. Non-invasive tests were compared with Transient Elastography. The Spearman coefficient was used to determine correlation. The sensitivity, specificity, positive predictive values and negative predictive values were used to get the optimal cut-off values. The diagnostic accuracy was estimated by calculating the area under the Receiver Operating Characteristic Curve (ROC). P Results: Of the 243 patient records studied, the median age or interquartile range (IQR) was 35 (29 - 42) years with a male predominance of 73.7%. More than 60% of the study population had normal transaminases. Significant fibrosis was found in 88 (36.2%) patients and 32 (13.7%) patients had cirrhosis. APRI had the best cut-off values and highest area under the ROC Curve, for significant fibrosis and cirrhosis with 0.55 (0.823 95% CI [0.769 - 0.869], P Conclusion: APRI, had the best diagnostic properties to detect liver fibrosis and cirrhosis in patients with Chronic Hepatitis B in Douala. The cut-off values are 0.55 and 0.65 for significant fibrosis and cirrhosis respectively.