Genome-edited rabbits:Unleashing the potential of a promising experimental animal model across diverse diseases

Animal models are extensively used in all aspects of biomedical research,with substantial contributions to our understanding of diseases,the development of pharmaceuticals,and the exploration of gene functions.The field of genome modification in rabbits has progressed slowly.However,recent advancements,particularly in CRISPR/Cas9-related technologies,have catalyzed the successful development of various genome-edited rabbit models to mimic diverse diseases,including cardiovascular disorders,immunodeficiencies,agingrelated ailments,neurological diseases,and ophthalmic pathologies.These models hold great promise in advancing biomedical research due to their closer physiological and biochemical resemblance to humans compared to mice.This review aims to summarize the novel gene-editing approaches currently available for rabbits and present the applications and prospects of such models in biomedicine,underscoring their impact and future potential in translational medicine.

Validation of a preclinical dry eye model in New Zealand white rabbits during and following topical instillation of 1% ophthalmic atropine sulfate

Background : The objective of this study was to validate an animal model for dry eye during and after the administration of 1% ophthalmic atropine sulfate(OAS) in New Zealand white(NZW) rabbits.Methods : OAS(1%) was applied three times per day to 30 eyes of 15 healthy NZW rabbits. Sacrifice, enucleation, and lacrimal gland removal took place on days 15, 21,and 30(OAS group). A second group(n = 5) was used as control. Clinical evaluations took place on days 3, 10, 15, 18, 21, 24 and 30. The primary endpoints were:Schirmer I test, tear break-up time(TBUT), and corneal fluorescein staining. As secondary endpoints, clinical changes including intraocular pressure, and histopathology were evaluated.Results : While OAS was administered, the Schirmer I test showed a statistically significant reduction for OAS group versus control( p < 0.001), and versus basal production( p < 0.001). TBUT showed statistically significant differences between groups(days 3 and 10;p = 0.001) and versus basal values(day 3;p < 0.001). Fluorescein staining showed a statistically significant difference(day 3;p = 0.001). The most frequent clinical finding was conjunctival hyperemia(76.9% OAS vs. 20% control). For histopathology, all OAS subjects presented some degree of inflammation(86.7% minimal;13.3% mild) whereas the control presented only 30% minimal inflammation. Goblet cell density showed no difference.Conclusions : The effectiveness of the OAS dry eye model in NZW rabbits as reported in previous studies was confirmed, provided that the application of the drug is maintained throughout the intervention;it is not a viable model after OAS administration is suspended.

Propofol Target-Controlled Infusion Modeling in Rabbits:Pharmacokinetic and Pharmacodynamic Analysis

This study aimed to establish a new propofol target-controlled infusion（TCI） model in animals so as to study the general anesthetic mechanism at multi-levels in vivo. Twenty Japanese white rabbits were enrolled and propofol（10 mg/kg） was administrated intravenously. Artery blood samples were collected at various time points after injection, and plasma concentrations of propofol were measured. Pharmacokinetic modeling was performed using Win Nonlin software. Propofol TCI within the acquired parameters integrated was conducted to achieve different anesthetic depths in rabbits, monitored by narcotrend. The pharmacodynamics was analyzed using a sigmoidal inhibitory maximal effect model for narcotrend index（NI） versus effect-site concentration. The results showed the pharmacokinetics of propofol in Japanese white rabbits was best described by a two-compartment model. The target plasma concentrations of propofol required at light anesthetic depth was 9.77±0.23 μg/m L, while 12.52±0.69 μg/m L at deep anesthetic depth. NI was 76.17±4.25 at light anesthetic depth, while 27.41±5.77 at deep anesthetic depth. The effect-site elimination rate constant（ke0） was 0.263/min, and the propofol dose required to achieve a 50% decrease in the NI value from baseline was 11.19 μg/m L（95% CI, 10.25–13.67）. Our results established a new propofol TCI animal model and proved the model controlled the anesthetic depth accurately and stably in rabbits. The study provides a powerful method for exploring general anesthetic mechanisms at different anesthetic depths in vivo.

A New Model of Experimental Cerebral Infarction in New Zealand White Rabbits

To develop an easy, reproducible experimental model of cerebral infarction(CI)without craniotomy in New Zealand white rabbits,a silicone rubber cylinder embedded in a nylon suture was delivered to the middle cerebral arteries through the internal carotid artery in anesthetized animals.Rabbits were sacrificed 0.5-5 h after embolization.CI size and location were ascertained by the tripheny1-2H-tetrazoliuni chloride(TTC)staining method;cerebral blood flow(CBF)was measured prior to and after embolization.Pco2,temperature and blood pressure were monitored and kept constant.CI occurred in all rabbits after 4 h of ischemia,in 50% after 3 h and only in 33% after 2.5 h.CI did not occur within less than 2.5 h of ischemia.No correlation was found between size and location of CI and occlusion time.CBF was maximally reduced in the right MCA territory but was also reduced in both anterior cerebral arteries and left MCA territories.This model is technically easy and the retrievable embolus allows the study of reperfusion by pulling on the nylon suture.It is suitable for studying chemical and molecular changes of the ischemic cells and/or for studying neuroimage changes after ischemic stroke.

Establishment of an animal model of ischemic type intrahepatic biliary lesion in rabbits

AIM:To explore a method to establish an animal model of ischemic type intrahepatic biliary lesion in rabbits. METHODS:Forty Japanese white rabbits of clean grade were divided randomly into four groups(10 rabbits per group)including sham operation(SO) group,and artery-bile obstruction(ABO)-1 h group, ABO-2 h group and ABO-3 h group.All the rabbits in this study underwent the same initial surgical procedure in which the liver was prepared as for graft removal during liver transplantation.Subsequently in the SO group,no additional vascular intervention was performed,while in groups ABO-1 h,ABO-2 h and ABO-3 h,the animals underwent combined clamping of the hepatic artery and common bile duct with microvascular clips for 1,2 and 3 h,respectively.After the scheduled occlusion time,the clip was removed to recover blood supply.The animals were killed 4 wk after operation.The survival rate,liver function, cholangiography and histopathological manifestation of the rabbits in each group were observed. RESULTS:The survival rate was 100%in groups SO,ABO-1 h and ABO-2 h,while it was 60%in group ABO-3 h.At each observation time,the change degree of the indexes of liver function was proportional to the clamping time(ABO-3 h>ABO-2 h>ABO-1 h> SO,P<0.05).Cholangiographical and histopathologic manifestations both showed that intrahepatic biliary lesion aggravated proportionally with the increase of the clamping time. CONCLUSION:An animal model of ischemic type intrahepatic biliary lesion in rabbits is successfully established,which may provide a reliable technique for basic and clinical research into the etiology, development and prophylaxis of ischemic type intrahepatic biliary lesion after liver transplantation.

Development and characterization of urethral stricture model in rabbits

Objective： To establish an experimental model of urethral stricture in rabbits. Methods： A total of 21 adult male New Zealand rabbits were included into group. After intravenous anesthesia, urethroscopy was performed with a pediatric resectoscope （F13）. Fifteen animals were randomly selected as the study group. A lcm-long circumferential electrocoagulation of the bulbar urethra was performed to these animals until ulceration of the mucosa. The remaining 6 animals underwent video urethroscopy without electrocoagulation, serving as controls. On the 30th day, retrograde urethrogram and urethroscopy were performed to evaluate urethral stricture formation, histological examinations （HE and Sirius Red staining） were done to assess urethral pathological change. Results： Two rabbits in study group died and no death occurred in controls. Based on urethrogram and urethroscopy, no rabbits in control group developed urethral stricture, while significant stricture formation was observed in every case of the study group. Histological examination showed a normal urethra in control cases, while at stricture site of the study group extensive fibrosis of muscle and submucous tis High collagen expression in fibrosis tissue was assayed sue by was observed with a large number of fibroblasts infiltration Sirius Red staining. Conclusion： A lcm-long endoscopic electrocoagulation can successfully induce urethral stricture formation in rabbit models. This method offers an ideal animal model for the fundamental and clinical study of urethral stricture

Establishing models of portal vein occlusion and evaluating value of multi-slice CT in hepatic VX2 tumor in rabbits

AIM： To establish models of portal vein occlusion of hepatic VX2 tumor in rabbits and to evaluate the value of multi-slice CT. METHODS： Forty New Zealand rabbits were divided into 4 groups according to digital table： Immediate group （group A; transplantation of tumor immediately after the portal vein occlusion）, 3-wk group （group B; transplantation of tumor at 3 wk after the portal vein occlusion）, negative control group （group C） and positive control group （group D）, 10 rabbits in each group. Hepatic VX2 tumor was transplanted with abdominalembedding innoculation immediately after the portal vein occlusion and at 3 wk after the portal vein occlusion. Meanwhile, they were divided into negative control group （Left external branch of portal vein was occluded by sham-operation, and left exite was embedded and inoculated pseudoly） and positive control group （Transplanted tumor did not suffer from the portal vein occlusion）. All rabbits were scanned with multi-slice CT. RESULTS： All 40 animals were employed in the final analysis without death. Tumor did not grow in both immediate group and 3-wk group. In 3-wk group, left endite was atrophied and growth of tumor was inhibited. The maximal diameter of tumor was significantly smaller than that in positive control group （2.55±0.46 vs 3.59±0.37 cm, t = 5.57, P 〈 0.001）. Incidences of metastasis in the liver and lung were lower in 3-wk group than those in positive control group （10% vs 400, and 90% vs 100%, respectively）. The expression intensities of the vascular endothelium growth factor （VEGF） in groups A, B, C and D were 0.10±0.06, 0.66±0.21, 0.28±0.09 and 1.48±0.32, respectively. VEGF expression level in the test group A was significantly lower than that in the negative control group C （t = 5.07; P 〈 0.001）.In addition, VEGF expression in the test group B was significantly lower than that in the positive control group D （t = 6.38; P 〈 0.001）. Scanning with multi-slice CT showed that displaying rate of hepatic artery branches was obviously lower in grade Ⅲ（40%） than that in grade Ⅰ（70%） and Ⅱ（100%） （P 〈 0.05）; but there was no significant difference in displaying rate of the portal vein at various grades. Values of blood flow （BF） of the liver, blood volume （BV）, mean transit time （MTT） and permeability of vascular surface （PS） were lower in the immediate group and 3-wk group than those in control groups, but values of hepatic arterial fraction （HAF） were increased. Significant positive correlations were existed between BF and BV （r = 0.905, P 〈 0.01）, and between BF and PS （r = 0.967, P 〈 0.01）, between BV and PS （r = 0.889, P 〈 0.01）. A significant negative correlation existed between PV and HAF （r = -0.768, P 〈 0.01）, between PS and HAF （r = -0.557, P 〈 0.01）. The values of BF, BV and PS had a positive correlation with VEGF （rBF = 0.842, rBV = 0.579, rPS = 0.811, P 〈 0.01） . However, there was no significant correlation between the values of MTT and HAF and the VEGF expression （rMTt = 0.066, rHAF = -0.027）. CONCLUSION： Ligating the left external branch of portal vein is an ideal way to establish models of portal vein occlusion in rabbits with hepatic VX2 tumor. Multi slice CT plays a key role in evaluating effect of portal vein occlusion.

Changes of the F-wave in the acute phase of permanent spinal cord ischaemic injury predict spinal cord function in animal models of rabbits

Objective:to explore the changes of the F-wave in the posterior tibial nerve of rabbits after different levels of lumbar spinal cord ischaemic injury and its correlation with motor function and the extent of lumbar spinal cord pathological damage.Methods:thirty New Zealand rabbits were randomly divided into 6 groups.The control group(n=5)was used to exclude the influence of anaesthesia and surgery on the F-wave.Different levels of lumbar arteries were ligated in the five experimental groups(n=5).The F-wave was recorded to observe the changes in the acute phase of spinal cord ischaemia.The correlation between the changes of the F-wave in the acute reversible phase and the motor function of the spinal cord was analysed.Motor functions were assessed after surgery and 2 d after vascular ligation.The specimens were taken 2 d after ligation for histopathologic observation.Results:the results for the control group indicated that anaesthesia and surgery did not affect the F-wave results.There was no statistically significant difference in the F-wave amplitudes and latency before and after ligation in the 1 and 2 level ligation groups.The F-wave changed immediately after ligation in the 3,4 and 5 ligation groups.The latency of the F-wave gradually extended,the amplitude of the F-wave gradually reduced.The amplitude variations of the F-wave were positively correlated with the motor function 2 d after ligation,there was a statistically significant difference.With the increase in the number of vascular ligation,the degree of destruction of the motor neurons in the anterior horn of the spinal cord in the pathological specimens increased.Conclusion:the F-waves in the posterior tibial nerve of rabbits were found to be sensitive to the lumbar spinal cord ischaemic injury and specific to predict motor function.

An improved GCN−TCN−AR model for PM_(2.5) predictions in the arid areas of Xinjiang,China

As one of the main characteristics of atmospheric pollutants,PM_(2.5) severely affects human health and has received widespread attention in recent years.How to predict the variations of PM_(2.5) concentrations with high accuracy is an important topic.The PM_(2.5) monitoring stations in Xinjiang Uygur Autonomous Region,China,are unevenly distributed,which makes it challenging to conduct comprehensive analyses and predictions.Therefore,this study primarily addresses the limitations mentioned above and the poor generalization ability of PM_(2.5) concentration prediction models across different monitoring stations.We chose the northern slope of the Tianshan Mountains as the study area and took the January−December in 2019 as the research period.On the basis of data from 21 PM_(2.5) monitoring stations as well as meteorological data(temperature,instantaneous wind speed,and pressure),we developed an improved model,namely GCN−TCN−AR(where GCN is the graph convolution network,TCN is the temporal convolutional network,and AR is the autoregression),for predicting PM_(2.5) concentrations on the northern slope of the Tianshan Mountains.The GCN−TCN−AR model is composed of an improved GCN model,a TCN model,and an AR model.The results revealed that the R2 values predicted by the GCN−TCN−AR model at the four monitoring stations(Urumqi,Wujiaqu,Shihezi,and Changji)were 0.93,0.91,0.93,and 0.92,respectively,and the RMSE(root mean square error)values were 6.85,7.52,7.01,and 7.28μg/m^(3),respectively.The performance of the GCN−TCN−AR model was also compared with the currently neural network models,including the GCN−TCN,GCN,TCN,Support Vector Regression(SVR),and AR.The GCN−TCN−AR outperformed the other current neural network models,with high prediction accuracy and good stability,making it especially suitable for the predictions of PM_(2.5)concentrations.This study revealed the significant spatiotemporal variations of PM_(2.5)concentrations.First,the PM_(2.5) concentrations exhibited clear seasonal fluctuations,with higher levels typically observed in winter and differences presented between months.Second,the spatial distribution analysis revealed that cities such as Urumqi and Wujiaqu have high PM_(2.5) concentrations,with a noticeable geographical clustering of pollutions.Understanding the variations in PM_(2.5) concentrations is highly important for the sustainable development of ecological environment in arid areas.

Comparative analysis of empirical and deep learning models for ionospheric sporadic E layer prediction

Sporadic E(Es)layers in the ionosphere are characterized by intense plasma irregularities in the E region at altitudes of 90-130 km.Because they can significantly influence radio communications and navigation systems,accurate forecasting of Es layers is crucial for ensuring the precision and dependability of navigation satellite systems.In this study,we present Es predictions made by an empirical model and by a deep learning model,and analyze their differences comprehensively by comparing the model predictions to satellite RO measurements and ground-based ionosonde observations.The deep learning model exhibited significantly better performance,as indicated by its high coefficient of correlation(r=0.87)with RO observations and predictions,than did the empirical model(r=0.53).This study highlights the importance of integrating artificial intelligence technology into ionosphere modelling generally,and into predicting Es layer occurrences and characteristics,in particular.

Comparative study of a rabbit model of spinal tuberculosis using different concentrations of Mycobacterium tuberculosis

BACKGROUND Tuberculosis is among the most devastating infectious diseases worldwide.Spinal tuberculosis is not easy to detect at an early stage,which without effective treatment often leads to spinal deformity and spinal cord damage which in turn cause complications such as paraplegia and quadriplegia.In this study,we established a model using three concentrations of bacteria and carried out a comprehensive evaluation of the model by imaging,general observations,and histopathological and bacteriological studies.AIM To establish a rabbit model of spinal tuberculosis and examine the effect on the model’s efficacy using different concentrations of Mycobacterium tuberculosis(M.tuberculosis)inoculum.METHODS New Zealand rabbits were randomly divided into experimental,control and blank groups.The experimental and control animals were sensitized with complete Freund′s adjuvant,a hole was drilled beneath the upper endplate of the L6 vertebral body and filled with gelfoam sponge.The experimental group was divided into three subgroups(experimental 1,experimental 2,experimental 3)and infused with M.tuberculosis suspension at various concentrations.The control group was inoculated with saline and the blank group received no treatment.The 12-week post-operative survival rates were 100%,80%and 30%in the experimental groups inoculated with concentrations of 106,107 and 108 CFU/mL bacteria,respectively.RESULTS The survival rate of the control and blank groups was 100%.Vertebral body destruction at 8 weeks in the three experimental groups as determined by X-ray analysis was 33.3%,62.5%and 66.7%,and by computed tomography(CT)and 3-dimensional CT 44.4%,75%and 100%,respectively.At 12 weeks,the figures were 44.4%,75%and 100%by X-ray analysis and 44.4%,100%and 100%by CT and 3-dimensional CT,respectively.All surviving rabbits of the experimental groups had vertebral destruction.The positive bacterial culture rates were 22.2%,75%and 66.7%,respectively,in the experimental groups.After being sensitized with complete Freund's adjuvant,large differences were observed in the extent of spinal tuberculosis after inoculation of the rabbits with different concentrations of H37RV standard M.tuberculosis.CONCLUSION The experimental 1 had a low success rate at establishing an infection.The experimental 3 resulted in high mortality and complication rates.The experimental 2 was optimum for establishing a spinal tuberculosis model based on the high level of symptoms observed and the low rabbit mortality.

Molecular mechanisms of early atrial remodeling by rapid atrial pacing in rabbits

Objective: To establish a rabbit atrial fibrillation model with rapid atrial pacing (RAP) and investigate its ultrastructural changes and expressions of L-type calcium channel subunits and potassium channel Kv4. 3. Methods: Thirty-six rabbits were performed electrical stimulation through bipolar endo-cardial led by surgical technique. 600 beat per min from 0 to 48 h. Atrial ultrastructure was observed by transmission electron microscope (TEM) after different pacing times. mRNA were measured by reverse transcription-polymera.se chain reaction (RT-PCR). Results: Atrial ultrastructure had alteration after 3 hours' pacing, such as mitochondria vacuolization, myofilament lysis and glucogen aggregation. The mRNA of the Ca2+ channel β1 and α1 subunits began to decrease after pacing of 6 h. which were paralleled with the change of Kv4. 3 mRNA. But the auxiliary subunit α2 were not affected. Conclusion: Ultrastructural changes and mRNA levels of L-type calcium channel subunits and potassium channel Kv4. 3 are decreased after RAP. with a mechanism of transcriptional down-regulation of underlying ion channels due to calcium overloading after RAP.

A New Model of Drug-Disease Interaction in Rabbits

Background： Drug-infection interaction should be considered in drug prescribing, particularly if potentiated byco-occuring drug-drug interactions. The effects of Candida and e-coli infections separately, and fluconazole administration weretested on cyclosporine blood level in rabbits. Methods： Three study designs were carried out, crossoversingle-dose-fluconazole-cyclosporine study testing fluconazole-cyclosporine interaction, multi-dosecandida-fluconazole-cyclosporine and multi-dose escherichia coli-cyclosporine study designs involving each rabbit acting as itscontrol; cyclosporine was given daily in both studies. Candida and e-coli infections were inoculated on day 5. In theMulti-Candida-Fluc-CyA, fluconazole-cyclosporine interaction was also considered, and flueonazole was administered daily fromday 9-18. In all three studies, Cyclosporine trough levels and serum creatinine were measured by CMIA and enzymatic assayrespectively, pre, during, post-infection and after fluconazole administration in the Candida study. Results： Both infections resulted insignificant rise in cyclosporine trough level （p = 0.018） and （p = 0.005） in fungal and bacterial studies, respectively. The median risein CyA level reached 52% （range 9-426%） in the Candida infection and reached 60 - 47.5% （mean） with the e-coli infection.Fluconazole also increased mean cyclosporine trough levels in the single-dose study by 70.3 - 45.3 and the concomitant rise inthemulti-dose study reached 76% （median, range 22-665%）. Conclusions： Cyclosporine trough levels increased during Candida ande-coli infections and also during fluconazole administration in the single and multi-dose studies. Fluconazole exerted an additiveeffect to the Candida inhibitory effect. Type of infection and inoculum size affected CyA levels differently. Monitoring cyclosporinelevel during episodes of infection as well as in therapy regimen involving interacting drugs is advisable.

Predictability Study of Weather and Climate Events Related to Artificial Intelligence Models

Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather and climate phenomena.In the past few decades,dynamical numerical models have been the primary tools for predictability studies,achieving significant progress.Nowadays,with the advances in artificial intelligence(AI)techniques and accumulations of vast meteorological data,modeling weather and climate events using modern data-driven approaches is becoming trendy,where FourCastNet,Pangu-Weather,and GraphCast are successful pioneers.In this perspective article,we suggest AI models should not be limited to forecasting but be expanded to predictability studies,leveraging AI's advantages of high efficiency and self-contained optimization modules.To this end,we first remark that AI models should possess high simulation capability with fine spatiotemporal resolution for two kinds of predictability studies.AI models with high simulation capabilities comparable to numerical models can be considered to provide solutions to partial differential equations in a data-driven way.Then,we highlight several specific predictability issues with well-determined nonlinear optimization formulizations,which can be well-studied using AI models,holding significant scientific value.In addition,we advocate for the incorporation of AI models into the synergistic cycle of the cognition–observation–model paradigm.Comprehensive predictability studies have the potential to transform“big data”to“big and better data”and shift the focus from“AI for forecasts”to“AI for science”,ultimately advancing the development of the atmospheric and oceanic sciences.

Dynamics of Advantageous Mutant Spread in Spatial Death-Birth and Birth-Death Moran Models

The spread of an advantageous mutation through a population is of fundamental interest in population genetics. While the classical Moran model is formulated for a well-mixed population, it has long been recognized that in real-world applications, the population usually has an explicit spatial structure which can significantly influence the dynamics. In the context of cancer initiation in epithelial tissue, several recent works have analyzed the dynamics of advantageous mutant spread on integer lattices, using the biased voter model from particle systems theory. In this spatial version of the Moran model, individuals first reproduce according to their fitness and then replace a neighboring individual. From a biological standpoint, the opposite dynamics, where individuals first die and are then replaced by a neighboring individual according to its fitness, are equally relevant. Here, we investigate this death-birth analogue of the biased voter model. We construct the process mathematically, derive the associated dual process, establish bounds on the survival probability of a single mutant, and prove that the process has an asymptotic shape. We also briefly discuss alternative birth-death and death-birth dynamics, depending on how the mutant fitness advantage affects the dynamics. We show that birth-death and death-birth formulations of the biased voter model are equivalent when fitness affects the former event of each update of the model, whereas the birth-death model is fundamentally different from the death-birth model when fitness affects the latter event.

Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence

Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).

Dynamics of a Stochastic Epidemic Model with Age-group

A stochastic epidemic model with two age groups is established in this study,in which the susceptible(S),the exposed(E),the infected(I),the hospitalized(H)and the recovered(R)are involved within the total population,the aging rates between two age groups are set to be constant.The existence-and-uniqueness of global positive solution is firstly showed.Then,by constructing several appropriate Lyapunov functions and using the high-dimensional Itô’s formula,the sufficient conditions for the stochastic extinction and stochastic persistence of the exposed individuals and the infected individuals are obtained.The stochastic extinction indicator and the stochastic persistence indicator are less-valued expressions compared with the basic reproduction number.Meanwhile,the main results of this study are modified into multi-age groups.Furthermore,by using the surveillance data for Fujian Provincial Center for Disease Control and Prevention,Fuzhou COVID-19 epidemic is chosen to carry out the numerical simulations,which show that the age group of the population plays the vital role when studying infectious diseases.

Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis

Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.

Solar flare forecasting based on a Fusion Model

Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model integrating Deep Residual Network(ResNet)and Support Vector Machine(SVM)for both≥C-class(C,M,and X classes)and≥M-class(M and X classes)flares.We collected samples of magnetograms from May 1,2010 to September 13,2018 from Space-weather Helioseismic and Magnetic Imager(HMI)Active Region Patches and then used a cross-validation method to obtain seven independent data sets.We then utilized five metrics to evaluate our fusion model,based on intermediate-output extracted by ResNet and SVM using the Gaussian kernel function.Our results show that the primary metric true skill statistics(TSS)achieves a value of 0.708±0.027 for≥C-class prediction,and of 0.758±0.042 for≥M-class prediction;these values indicate that our approach performs significantly better than those of previous studies.The metrics of our fusion model’s performance on the seven datasets indicate that the model is quite stable and robust,suggesting that fusion models that integrate an excellent baseline network with SVM can achieve improved performance in solar flare prediction.Besides,we also discuss the performance impact of architectural innovation in our fusion model.

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.