Humanization for neurological disease modeling:A roadmap to increase the potential of Drosophila model systems

Neuroscience and neurology research is dominated by experimentation with rodents.Around 75%of neurology disease-associated genes have orthologs in Drosophila mel-anogaster,the fruit fly amenable to complex neurological and behavioral investiga-tions.However,non-vertebrate models including Drosophila have so far been unable to significantly replace mice and rats in this field of studies.One reason for this situ-ation is the predominance of gene overexpression(and gene loss-of-function)meth-odologies used when establishing a Drosophila model of a given neurological disease,a strategy that does not recapitulate accurately enough the genetic disease condi-tions.I argue here the need for a systematic humanization approach,whereby the Drosophila orthologs of human disease genes are replaced with the human sequences.This approach will identify the list of diseases and the underlying genes that can be adequately modeled in the fruit fly.I discuss the neurological disease genes to which this systematic humanization approach should be applied and provide an example of such an application,and consider its importance for subsequent disease modeling and drug discovery in Drosophila.I argue that this paradigm will not only advance our un-derstanding of the molecular etiology of a number of neurological disorders,but will also gradually enable researchers to reduce experimentation using rodent models of multiple neurological diseases and eventually replace these models.

Studies on Molecular Mechanism of Human Early Cardiogenesis Using the Drosophila as a Model System

Recently,some of the genetic mechanisms of heart specification have been elucidated in Drosophila .However,genes involved in early cardiogenesis of human remain to be identified.Since the pathways that regulate early cardiac fate determination are conserved between Drosophila and vertebrates,flies can be used as a model test system to explore the genetic basis of cardiogenesis in human.In this project,about 3000 reccieve lethal gene lines were produced by P or EMS mutagenesis.With staining of antibodies against heart precussor cells of Drosophila ,about 200 lines were observed to show heart phenotype.In pilot studies of their function with RNAi technique,the RNAi phenotypes of several genes tested were observed,which were very similar to that of their mutants,showing heart tube defects or no heart precursors formation.Taking advantage of the advanced genetic information available in the Drosophila and human systems,we have identified about 50 human transcripts homologous to the Drosophila heart related gene candidates.Northern blot analysis for some of the human candidates showed that several genes were expressed in both adult and early embryonic tissues,which may help in the evaluation of candidate genes for human cardiogenesis.Our further experiments with transgenic flies generated with wild type and mutant forms of these candidate genes to examine for defects in cardiogenesis or cardiac function are under way.The candidate genes producing cardiac specific defects suggestive of similarities to the heart disease syndromes can then be pursued further as likely disease gene candidates.Such an approach is likely to provide a dramatic reduction of possible candidate genes,or to screen and identify mutations that may generate the disease in human.

Effect of pH,temperature and heating time on the formation of furan in sugar–glycine model systems

Furan(C4H4O)has been classified as a possible animal and human carcinogen by many international agencies.The formation of furan in three sugar–glycine models using glucose,fructose,and sucrose was investigated using headspace gas chromatography mass spectrometry method(HSGC–MS)with various dual combinations of three important heat processing conditions,i.e.pH,temperature,and heating time.Results indicated that furan levels from sugar–glycine model systems during the thermal processing can be attributed to selective sugar types,pH,temperature,and heating time.In glucose–glycine and fructose–glycine system,the lowest furan level was detected in acid condition but in sucrose–glycine system furan formed significantly lower(P<0.05)in acidic conditions the lowest furan level was found in alkaline conditions.The furan levels were observed to increase with heating time in all three model systems.Furthermore,less furan was generated in non-reducing sugar system(sucrose)than in reducing sugar system(glucose and fructose).Therefore,they demonstrate the possibility of limiting the formation of furan in heat processed foods by both the careful selection of carbohydrates(i.e.non-reducing sugars and reducing sugars)ingredients and appropriate processing conditions.©2013 Beijing Academy of Food Sciences.Production and hosting by Elsevier B.V.All rights reserved.

Hepatitis C Virus Experimental Model Systems and Antiviral drug Research

An estimated 130 million people worldwide are chronically infected with hepatitis C virus (HCV) making it a leading cause of liver disease worldwide. Because the currently available therapy of pegylated interferon-alpha and ribavirin is only effective in a subset of patients, the development of new HCV antivirals is a healthcare imperative. This review discusses the experimental models available for HCV antiviral drug research, recent advances in HCV antiviral drug development, as well as active research being pursued to facilitate development of new HCV-specific therapeutics.

Cloud Seedability Study with a Dual-Model System

In this research, one-dimensional stratiform a novel dual-model system, cold cloud model （1DSC） coupled to Weather Research and Forecast （WRF） model （WRF-1DSC for short）, was employed to investigate the effects of cloud seeding by silver iodide （AgI） on rain enhancement. Driven by changing environmental conditions extracted from the WRF model, WRF-1DSC could be used to assess the cloud seeding effects quantitatively. The employment of WRF- 1DSC, in place of a one-dimen- sional two-moment cloud seeding model applied to a three-dimensional mesoscale cloud-resolving model, was found to result in massive reduction of computational resources. Numerical experiments with WRF-1DSC were conducted for a real stratiform precipitation event ob- served on 4-5 July 2004, in Northeast China. A good agreement between the observed and modeled cloud system ensured the ability of WRF-1DSC to simulate the observed precipitation process efficiently. Sensitivity tests were performed with different seeding times, locations, and amounts. Experimental results showed that the optimum seeding effect （defined as the percentage of rain enhancement or rain enhancement rate） could be achieved through proper seeding at locations of maximum cloud water content when the updraft was strong. The optimum seeding effect was found to increase by 5.61% when the cloud was seeded at 5.5 km above ground level around 2300 UTC 4 July 2004, with the maximum AgI mixing ratio （As） equaling 15 ng kg-1. On the other hand, for an overseeded cloud, a significant reduction occurred in the accumulated precipitation （-12.42%） as Xs reached 100 ng kg^-1. This study demonstrates the potential of WRF- 1DSC in determining the optimal AgI seeding strategy in practical operations of precipitation enhancement.

Use of sensory substitution devices as a model system for investigating cross-modal neuroplasticity in humans

Blindness provides an unparalleled opportunity to study plasticity of the nervous system in humans.Seminal work in this area examined the often dramatic modifications to the visual cortex that result when visual input is completely absent from birth or very early in life（Kupers and Ptito,2014）.More recent studies explored what happens to the visual pathways in the context of acquired blindness.This is particularly relevant as the majority of diseases that cause vision loss occur in the elderly.

A New Lagrangian-Eulerian Coupling Model System

A new Lagrangian—Eulerian coupling model system is developed to study regional air quality. The system consists of mesoscale dynamical meteorological model (MM), Monte—Carlo model (MCM), parameterized model on planetary boundary layer (PBL) turbulent statistics, dry and wet removal model, and Eulerian nonlinear chemical model (ENCM). The physical, chemical and biological processes on air pollutants are considered comprehensively. 3—D distribution laws tor acidic gaseous pollutants (SO2 and NOx) emitted by Thai Mae Moh Power Plant and the secondary pollutants are studied in detail. The results simulated by the coupling model system are in good agreement with observational concentration data. Key words MM - MCM - ENCM - Coupling model system The authors wish to express their thanks to Prof. Zeng Q. C. for his support to this research and to Dr. Han Z. W. and Zhang M. G. for their help in programming and numerical calculation of IAP, Chinese Academy of Sciences. Thanks are also due to NSTD and EGAT in Thailand for supporting this research.

Reflections on Improvement of Utility Model System in China

Even since 1985 when the Patent Law was launched in China, the utility model patent has been playing a very important role. Over the two decades, the utility model system has played an active part in encouraging invention-creations, and promoting the progress and development of science and technology.

A Knowledge Model System for Wheat Production Management

A knowledge model with temporal and spatial characteristics for the quantitative design of a cultural pattern in wheat production, using systems analysis and dynamic modeling techniques, was developed for wheat management, as a decision-making tool in digital farming. The fundamental relationships and algorithms of wheat growth indices and management criteria to cultivars, ecological environments, and production levels were derived from the existing literature and research data to establish a knowledge model system for quantitative wheat management using Visual C^＋＋. The system designed a cultural management plan for general management guidelines and crop regulation indices for timecourse control criteria during the wheat-growing period. The cultural management plan module included submodels to determine target grain yield and quality, cultivar choice, sowing date, population density, sowing rate, fertilization strategy, and water management, whereas the crop regulation indices module included submodels for suitable development stages, dynamic growth indices, source-sink indices, and nutrient indices. Ewluation of the knowledge model by design studies on the basis of data sets of different eco-sites, cultiwrs, and soil types indicated a favorable performance of the model system in recommending growth indices and management criteria under diverse conditions. Practical application of the knowledge model system in comparative field experiments produced yield gains of 2.4% to 16.5%. Thus, the presented knowledge model system overcame some of the difficulties of the traditional wheat management patterns and expert systems, and laid a foundation for facilitating the digitization of wheat management.

Studying Some Physicochemical Characteristics of Crust Coated with White Egg and Chitosan Using a Deep-Fried Model System

In this paper, the effects of frying time, white egg (0%, 5% and 10% w/w) and chitosan (0%, 0.5% and 1.5% w/w) addition to the batter formulation on the quality of simulated crispy deep-fried Kurdish cheese nugget crusts was studied by using a deep-fried crust model. Moisture content, oil content, color and hardness of the samples were determined. Crust models were fried at 190℃ for 60, 120 and 180 s. Batter formulations and frying time significantly (p < 0.01) affected moisture, oil content, color and hardness of Crust models. Batter formulation contain 10% white egg was found to be an effective ingredient in decreasing oil content of Crust models. The mean moisture and fat content of Crust models formed with batter contained 10% white egg, fried at 190℃, for 180s were 6.207 ± 0.447 and 5.649 ± 0.394. Batters containing 5% white egg and 1.5% chitosan showed the lowest moisture content and the highest oil content among all the formulations. Crust models containing combination of white egg and chitosan were the darkest. Hardness of samples containing chitosan were the highest, specially for ch1.5 The mean hardness in 60, 120 and 180s of frying in this formulation were 21.518 ± 0.481, 36.871 ± 1.758 and 49.563 ± 1.847 respectively.

A GIS Integrated Water Quality Model System Based on SWMM,ECOM,and RCA

Water Quality Model System( WQMS) is an important approach to analyzing aquatic situation and supporting environmental decision. However,the usage and promotion of WQMS is largely limited by amounts of parameters,complex conditions and enormous operations. A GIS integrated system of urban water environment coupled with SWMM( storm runoff model),ECOM( hydrodynamic model) and RCA( water quality model) was constructed in this study,with the production and transformation of contaminants in large scale taken into consideration. This integrated system guaranteed an independent calculation and multi-model coupling calculation,including convenient pre-processing,fast and efficient model running and results visualization in different spatial and temporal scales,in the purpose of simplifying the usage and promotion of complex models and providing necessary understanding required in water resource managing and water pollution controlling,and ultimately improving decision making capability. The functionality of the proposed system was illustrated by a case of Wuhan city.

An in vitro infection model system to study proteins expressed during interaction of mycobacterium with murine macrophages

Resurgence of mycobacterial diseases particularly tuberculosis has caused a renewed interest to unravel the strategies employed by mycobacteria for intracellular survival. In spite of advancement in mycobacterial research, our knowledge about genes and their corresponding functional proteins involved during the interaction of mycobacterium with host’s macrophages is fragmentary. This study pertains to development of a suitable in vitro model using murine macrophages and Mycobacterium bovis BCG to study proteins expressed during macrophage-myco bacterium interactions. Peritoneal macrophages from BALB/c mice were infected with M. bovis BCG and intracellular replication was assessed by {3H} thymi- dine uptake assay which was maximal when macrophage to mycobacterium ratio was 1:10. SDS-PAGE was employed to study the proteins expressed and selected proteins were subjected to mass spectrometry. Seven proteins found to be upregulated during macrophage-mycobacterium interaction were identified by MALDI-TOF. The results indicate that the present in vitro infection model was able to support the growth of M. bovis BCG in murine macrophages and is an ideal model to determine the pattern of functions of gene expression during the interaction of mycobacterium with macrophages. The differentially expressed proteins will help in understanding the mycobacterial molecular basis of adaptation to intracellular macrophage environment.

On Single Compartment Pharmacokinetic Model Systems that Obey Michaelis-Menten Kinetics and Systems that Obey Krebs Cycle Kinetics

The integration of Michaelis-Menten kinetics results in a trancedental equation. The results are not in a form that is readily usable. A more usable form of the model solutions is developed. This was accomplished by using Taylor series expansion of dimensionless concentration u in terms of its derivatives. The infinite series expression for dimensionless concentration is given. It can be seen that for times t < , the Taylor series expression evaluated near the origin up to the third derivative is a reasonable representation of the integrated solution. More terms in the Taylor series expression can be added to suit the application. It can vary with the apparent volume, dosage, enzyme concentration, Michaelis constant and the desired accuracy level needed. The single compartment model solution was obtained by the method of Laplace transform. It can be seen from Figure 2 that the dimensionless drug concentration in the compartment goes through a maxima. The curve is convex throughout the absorption and elimination processes. The drug gets completely depleted after a said time. The curve is asymmetrical with a right skew. The systems under absorption with elimination that obey the kinetics that can be represented by a set of reactions in circle were considered. A system of simple reactions in circle was taken into account. The concentration profile of the reactants were obtained by the method of Laplace transforms. The conditions when subcritical damped oscillations can be expected are derived. A model was developed for cases when absorption kinetics exhibit subcritical damped oscillations. The solution was developed by the method of Laplace transforms. The solution for dimensionless concentration of the drug in single compartment for different values of rate constants and dimensionless frequency are shown in Figures 6-9. The drug profile reaches a maximum and drops to zero concen-tration after a said time. The fluctuations in concentration depends on the dimensionless frequency resulting from the subcritical damped oscillations during absorption. At low frequencies the fluctuations are absent. As the frequency is increased the fluctuations in concentration are pronounced. The fre-quency of fluctuations were found to increase with increase in frequency of oscillations during ab-sorption.

On Single Compartment Pharmacokinetic Model Systems that Obey Free Radical Copolymerization Kinetics and Multiplicity

This study examines the issues in development of pharmacokinetic single compartment model for systems that obey free radical copolymerization kinetics. Copolymer composition as a function of reactivity ratios of comonomers for well mixed case was derived. For some cases, such as DEF-AN, diethyl fumarate and acrylonitrile system multiplicity in composition were found. The analysis is extended to n monomers. State space model expressions are used and the QSSA assumption is stated in state space equation form. Conditions when damped oscillations can be expected are noted. In addition to multiplicity in product composition, an account of reactivity ratios and other instances of multi- plicity were found during the pharmacodynamics of the free radical polymerization reactions. A careful study of initiated case, thermal case, 1 CSTR and 2 CSTRS was undertaken and results were presented. Numerical integration techniques were employed on the desktop computer. Steady state and transient state conversion for initiated case and thermal case for 1 CSTR and 2 CSTRs were calculated and plotted in Figures 7-9 and 12. No multiplicity was found in the thermal case for 1 CSTR in the dynamics of transient monomer conversion. Multiplicity was found in the initiated case for 1 CSTR in the dynamics of transient conversion of monomer. The multiplicity was found in the second CSTR for the case of 2 CSTRs in series. No multiplicity was found in the case of initiator decay.

Development of a new cerebral ischemia reperfusion model of Mongolian gerbils and standardized evaluation system

Background:The Mongolian gerbil is an excellent laboratory animal for preparing the cerebral ischemia model due to its inherent deficiency in the circle of Willis.However,the low incidence and unpredictability of symptoms are caused by numerous complex variant types of the circle.Additionally,the lack of an evaluation system for the cer-ebral ischemia/reperfusion(I/R)model of gerbils has shackled the application of this model.Methods:We created a symptom-oriented principle and detailed neurobehavioral scoring criteria.At different time points of reperfusion,we analyzed the alteration in locomotion by rotarod test and grip force score,infarct volume by triphenyltetrazo-lium chloride(TTC)staining,neuron loss using Nissl staining,and histological charac-teristics using hematoxylin-eosin(H&E)straining.Results:With a successful model rate of 56%,32 of the 57 gerbils operated by our method harbored typical features of cerebral I/R injury,and the mortality rate in the male gerbils was significantly higher than that in the female gerbils.The suc-cessfully prepared I/R gerbils demonstrated a significant reduction in motility and grip strength at 1 day after reperfusion;formed obvious infarction;exhibited typi-cal pathological features,such as tissue edema,neuronal atrophy and death,and vacuolated structures;and were partially recovered with the extension of reperfu-sion time.Conclusion:This study developed a new method for the unilateral common carotid artery ligation I/R model of gerbil and established a standardized evaluation system for this model,which could provide a new cerebral I/R model of gerbils with more practical applications.

Effects of mesenchymal stem cell on dopaminergic neurons,motor and memory functions in animal models of Parkinson's disease:a systematic review and meta-analysis

Parkinson’s disease is chara cterized by the loss of dopaminergic neurons in the substantia nigra pars com pacta,and although restoring striatal dopamine levels may improve symptoms,no treatment can cure or reve rse the disease itself.Stem cell therapy has a regenerative effect and is being actively studied as a candidate for the treatment of Parkinson’s disease.Mesenchymal stem cells are considered a promising option due to fewer ethical concerns,a lower risk of immune rejection,and a lower risk of teratogenicity.We performed a meta-analysis to evaluate the therapeutic effects of mesenchymal stem cells and their derivatives on motor function,memory,and preservation of dopamine rgic neurons in a Parkinson’s disease animal model.We searched bibliographic databases(PubMed/MEDLINE,Embase,CENTRAL,Scopus,and Web of Science)to identify articles and included only pee r-reviewed in vivo interve ntional animal studies published in any language through J une 28,2023.The study utilized the random-effect model to estimate the 95%confidence intervals(CI)of the standard mean differences(SMD)between the treatment and control groups.We use the systematic review center for laboratory animal expe rimentation’s risk of bias tool and the collaborative approach to meta-analysis and review of animal studies checklist for study quality assessment.A total of 33studies with data from 840 Parkinson’s disease model animals were included in the meta-analysis.Treatment with mesenchymal stem cells significantly improved motor function as assessed by the amphetamine-induced rotational test.Among the stem cell types,the bone marrow MSCs with neurotrophic factor group showed la rgest effect size(SMD[95%CI]=-6.21[-9.50 to-2.93],P=0.0001,I^(2)=0.0%).The stem cell treatment group had significantly more tyrosine hydroxylase positive dopamine rgic neurons in the striatum([95%CI]=1.04[0.59 to 1.49],P=0.0001,I^(2)=65.1%)and substantia nigra(SMD[95%CI]=1.38[0.89 to 1.87],P=0.0001,I^(2)=75.3%),indicating a protective effect on dopaminergic neurons.Subgroup analysis of the amphetamine-induced rotation test showed a significant reduction only in the intracranial-striatum route(SMD[95%CI]=-2.59[-3.25 to-1.94],P=0.0001,I^(2)=74.4%).The memory test showed significant improvement only in the intravenous route(SMD[95%CI]=4.80[1.84 to 7.76],P=0.027,I^(2)=79.6%).Mesenchymal stem cells have been shown to positively impact motor function and memory function and protect dopaminergic neurons in preclinical models of Parkinson’s disease.Further research is required to determine the optimal stem cell types,modifications,transplanted cell numbe rs,and delivery methods for these protocols.

Implication of community-level ecophysiological parameterization to modelling ecosystem productivity:a case study across nine contrasting forest sites in eastern China

Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.

Neurophysiological, histological, and behavioral characterization of animal models of distraction spinal cord injury: a systematic review

Distraction spinal cord injury is caused by some degree of distraction or longitudinal tension on the spinal cord and commonly occurs in patients who undergo corrective operation for severe spinal deformity.With the increased degree and duration of distraction,spinal cord injuries become more serious in terms of their neurophysiology,histology,and behavior.Very few studies have been published on the specific characteristics of distraction spinal cord injury.In this study,we systematically review 22 related studies involving animal models of distraction spinal cord injury,focusing particularly on the neurophysiological,histological,and behavioral characteristics of this disease.In addition,we summarize the mechanisms underlying primary and secondary injuries caused by distraction spinal cord injury and clarify the effects of different degrees and durations of distraction on the primary injuries associated with spinal cord injury.We provide new concepts for the establishment of a model of distraction spinal cord injury and related basic research,and provide reference guidelines for the clinical diagnosis and treatment of this disease.

Research on the Relationship Between Environmental and Economic Coupling Systems in Bohai Bay Area Based on a Vector Autoregression(VAR)Model

This study analyzed the impact of land-based contaminants and tertiary industrial structure on economic development in the selected Bohai Bay area,China.Based on panel data spanning 2011-2020,a vector autoregressive(VAR)model is used to analyze and forecast the short-run and long-run relationships between three industrial structures,pollutant discharge,and economic development.The results showed that the environmental index had a long-term cointegration relationship with the industrial structure economic index.Per capital chemical oxygen demand(PCOD)and per capita ammonia nitrogen(PNH_(3)N)had a positive impact on delta per capita GDP(dPGDP),while per capita solid waste(PSW),the secondary industry rate(SIR)and delta tertiary industry(dTIR)had a negative impact on dPGDP.The VAR model under this coupling system had stability and credibility.The impulse response results showed that the short-term effect of the coupling system on dPGDP was basically consistent with the Granger causality test results.In addition,variance decomposition was used in this study to predict the long-term impact of the coupling system in the next ten periods(i.e.,ten years).It was found that dTIR had a great impact on dPGDP,with a contribution rate as high as 74.35%in the tenth period,followed by the contribution rate of PCOD up to 3.94%,while the long-term contribution rates of PSW,SIR and PNH3N were all less than 1%.The results show that the government should support the development of the tertiary industry to maintain the vitality of economic development and prevent environmental deterioration.

Use of machine learning models for the prognostication of liver transplantation: A systematic review

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.