Practice of Infection Prevention and Control Strategies in Risk Departments during the COVID-19 Epidemic

Objective: To explore the practice and application of infection prevention and control strategies in risk departments during the COVID-19 epidemic, and to formulate the infection prevention and control measures to provide advice and guidance in risk departments. Methods: According to the latest plan of diagnosis and treatment, prevention and control issued by the National Health Commission, expert advice and consensus, combined with the actual situation in our hospital, a series of infection prevention and control measures of COVID-19 in risk department was formulated. Results: During the epidemic period, the prevention and control measures of nine risk departments including emergency operation, anesthesiology, endoscopy center, blood purification center, otolaryngology, stomatology, medical imaging department, medical cosmetology department and pulmonary function room were established from six aspects, including pre-examination and screening, medical technology control, personnel management, personal protection, environmental disinfection, medical waste disposal, etc. Conclusion: During the epidemic period, the infection prevention and control strategy of risk departments is one of the key links to control the spread of the epidemic, and risk departments must pay attention to and strictly implement various infection prevention and control measures.

Prevention and Control Strategies of Nosocomial Infection and Effectiveness Evaluation in a Tertiary Teaching Hospital during the Epidemic of COVID-19

Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital initiated an emergency plan involving multi-departmental defense and control. It adopted a series of nosocomial infection prevention and control measures, including strengthening pre-examination and triage, optimizing the consultation process, improving the hospital’s architectural composition, implementing graded risk management, enhancing personal protection, and implementing staff training and supervision. Descriptive research was used to evaluate the short-term effects of these in-hospital prevention and control strategies. The analysis compared changes in related evaluation indicators between January 24, 2020 and February 12, 2020 (Chinese Lunar New Year’s Eve 2020 to lunar January 19) and the corresponding lunar period of the previous year. Results: Compared to the same period last year, the outpatient fever rate increased by 1.85-fold (P P Conclusion: The nosocomial infection prevention and control strategies implemented during this specific period improved the detection and control abilities for the COVID-19 source of infection and enhanced the compliance with measures. This likely contributed significantly to avoiding the occurrence of nosocomial infection.

Evaluation of the Impact of Refined Quality Control Management Model on the Qualified Rate of Disinfection and Sterilization of Surgical Instruments in the Sterilization Supply Center

Objective:To evaluate the application value of a refined quality control management model for a sterilization supply center.Methods:A retrospective analysis was conducted on the work situation of the sterilization supply center from January 2021 to January 2023.The work situation before January 31,2022,was classified as the control group;a routine quality control management model was implemented,and the work situation after January 31,2022,was classified as the observation group.The quality of medical device management and department satisfaction between the two groups were compared.Results:The timely recovery and supply rate,classification and cleaning pass rate,disinfection pass rate,packaging pass rate,sterilization pass rate,and department satisfaction score in the observation group were all higher than those of the control group(P<0.05).Conclusion:Implementing a refined quality control management model in the sterilization supply center can improve the quality management level of medical devices and department satisfaction and is worthy of promotion.

Effects of SARS-CoV-2 infection on incidence and treatment strategies of hepatocellular carcinoma in people with chronic liver disease

BACKGROUND Chronic liver disease(CLD)was associated with adverse clinical outcomes among people with severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection.AIM To determine the effects of SARS-CoV-2 infection on the incidence and treatment strategy of hepatocellular carcinoma(HCC)among patients with CLD.METHODS A retrospective,territory-wide cohort of CLD patients was identified from an electronic health database in Hong Kong.Patients with confirmed SARS-CoV-2 infection[coronavirus disease 2019(COVID-19)+CLD]between January 1,2020 and October 25,2022 were identified and matched 1:1 by propensity-score with those without(COVID-19-CLD).Each patient was followed up until death,outcome event,or November 15,2022.Primary outcome was incidence of HCC.Secondary outcomes included all-cause mortality,adverse hepatic outcomes,and different treatment strategies to HCC(curative,non-curative treatment,and palliative care).Analyses were further stratified by acute(within 20 d)and post-acute(21 d or beyond)phases of SARS-CoV-2 infection.Incidence rate ratios(IRRs)were estimated by Poisson regression models.RESULTS Of 193589 CLD patients(>95%non-cirrhotic)in the cohort,55163 patients with COVID-19+CLD and 55163 patients with COVID-19-CLD were included after 1:1 propensity-score matching.Upon 249-d median follow-up,COVID-19+CLD was not associated with increased risk of incident HCC(IRR:1.19,95%CI:0.99-1.42,P=0.06),but higher risks of receiving palliative care for HCC(IRR:1.60,95%CI:1.46-1.75,P<0.001),compared to COVID-19-CLD.In both acute and post-acute phases of infection,COVID-19+CLD were associated with increased risks of allcause mortality(acute:IRR:7.06,95%CI:5.78-8.63,P<0.001;post-acute:IRR:1.24,95%CI:1.14-1.36,P<0.001)and adverse hepatic outcomes(acute:IRR:1.98,95%CI:1.79-2.18,P<0.001;post-acute:IRR:1.24,95%CI:1.13-1.35,P<0.001),compared to COVID-19-CLD.CONCLUSION Although CLD patients with SARS-CoV-2 infection were not associated with increased risk of HCC,they were more likely to receive palliative treatment than those without.The detrimental effects of SARS-CoV-2 infection persisted in post-acute phase.

Bacteriological Profile of Infections Encountered in a Pneumology Service in a Moderate-Income Country [Pneumology Department of CHU Cocody (Côte d’Ivoire)]

Introduction: Infections represent a real public health problem aggravating the morbidity and mortality of hospitalized patients. Methods: This was a retrospective study with descriptive purposes over a period of 05 years, in the Pneumology Department of the University Hospital of Cocody. Results: The average age in our population was 42 years. We observed a male predo- minance of 64.5%, with a sex ratio of 1.8. Medical history was dominated by HIV infection (23.5%), followed by tuberculosis (15.6%). Concerning lifestyle, smoking was found in 38% of cases. Symptoms progressed chronically in 80% of cases. An infectious syndrome was found in 75% of cases. Microbial culture was positive in 42% of cases. Pseudomonas aeruginosa and Klebsiella pneumoniae were encountered in 26.4% of cases each, followed by Echerichia coli in 10.4% of cases. Klebsiella pneumoniae in the first three years topped the list, but gradually. Pseudomonas aeruginosa maintained its leadership over the last three years. Pseudomonas aeruginosa isolates expressed a resistance rate of 9.8% to ceftazidime and 8.1% to imipenem;to aztreonam (36%), ticarcillin (33.3%) and levofloxacin. These strains were susceptible to fosfomycin (100%), mero- penem (96.6%) and amikacin (96%). For isolated strains of Entero- bacteria- ceae, resistance was observed about ticarcillin (83.3%) and amoxicillin clavula- nic acid (71.2%). Streptococcaceae showed resistance to tetracycline (69.2%) and erythromycin (50%). Over the years there has been an increase in re- sistance to amoxicillin-clavulanic acid ceftriaxone. The death rate was 14%. Conclusion: The bacterial profile of infections is dominated by germs respon- sible for nosocomial infection with significant mortality.

Management strategies for common viral infections in pediatric renal transplant recipients

Viral infections have been considered as a major cause of morbidity and mortality after kidney transplantation in pediatric cohort.Children are at high risk of acquiring virus-related complications due to immunological immaturity and the enhanced alloreactivity risk that led to maintenance of high immunosuppressive regimes.Hence,prevention,early detection,and prompt treatment of such infections are of paramount importance.Among all viral infections,herpes viruses(herpes simplex virus,varicella zoster virus,Epstein-Barr virus,cytomegalovirus),hepatitis B and C viruses,BK polyomavirus,and respiratory viruses(respiratory syncytial virus,parainfluenza virus,influenza virus and adenovirus)are common in kidney transplant recipients.These viruses can cause systemic disease or allograft dysfunction affecting the clinical outcome.Recent advances in technology and antiviral therapy have improved management strategies in screening,monitoring,adoption of prophylactic or preemptive therapy and precise treatment in the immunocompromised host,with significant impact on the outcome.This review discusses the etiology,screening and monitoring,diagnosis,prevention,and treatment of common viral infections in pediatric renal transplant recipients.

Urgent call for attention to diabetes-associated hospital infections

In this editorial,we discuss the recent article by Zhao et al published in the World Journal of Diabetes,which highlights the importance of recognizing the risk indicators associated with diabetes mellitus(DM).Given the severe implications of healthcare-associated infections(HAIs)in hospitalized individuals-such as heightened mortality rates,prolonged hospitalizations,and increased costs-we focus on elucidating the connection between DM and nosocomial infections.Diabetic patients are susceptible to pathogenic bacterial invasion and subsequent infection,with some already harboring co-infections upon admission.Notably,DM is an important risk factor for nosocomial urinary tract infections and surgical site infections,which may indirectly affect the occurrence of nosocomial bloodstream infections,especially in patients with DM with poor glycemic control.Although evidence regarding the impact of DM on healthcare-associated pneumonias remains inconclusive,attention to this potential association is warranted.Hospitalized patients with DM should prioritize meticulous blood glucose management,adherence to standard operating procedures,hand hygiene practices,environmental disinfection,and rational use of drugs during hospitalization.Further studies are imperative to explore the main risk factors of HAIs in patients with DM,enabling the development of preventative measures and mitigating the occurrence of HAIs in these patients.

Prospects and challenges for the application of tissue engineering technologies in the treatment of bone infections

Osteomyelitis is a devastating disease caused by microbial infection in deep bone tissue.Its high recurrence rate and impaired restoration of bone deficiencies are major challenges in treatment.Microbes have evolved numerous mechanisms to effectively evade host intrinsic and adaptive immune attacks to persistently localize in the host,such as drug-resistant bacteria,biofilms,persister cells,intracellular bacteria,and small colony variants(SCVs).Moreover,microbial-mediated dysregulation of the bone immune microenvironment impedes the bone regeneration process,leading to impaired bone defect repair.Despite advances in surgical strategies and drug applications for the treatment of bone infections within the last decade,challenges remain in clinical management.The development and application of tissue engineering materials have provided new strategies for the treatment of bone infections,but a comprehensive review of their research progress is lacking.This review discusses the critical pathogenic mechanisms of microbes in the skeletal system and their immunomodulatory effects on bone regeneration,and highlights the prospects and challenges for the application of tissue engineering technologies in the treatment of bone infections.It will inform the development and translation of antimicrobial and bone repair tissue engineering materials for the management of bone infections.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Risk Factors for Surgical Site Infections in Patients Operated at the University Clinic of Traumatology-Orthopedics and Restorative Surgery of the National Hospital and University Center Hubert Koutoukou Maga in Cotonou

Background: Operative site infections (ISO) are typically nosocomial. According to the WHO the incidence of ISO varies from 0.5% to 15% and exceeds 25% in developing countries. They result from the combined action of several factors and represent a concern for public health. To study the contributing factors of surgical site infections in patients operated at the University Clinic of Orthopedic Traumatology of CNHU-HKM of Cotonou. Method: This was an analytical cross-sectional study that involved 35 operated patients and ten nurses. Were included in our study: 1) All patients, without distinction of sex or age, having been operated on in the university clinic of orthopedic traumatology, during the survey period;2) Patients hospitalized for post-operative care during the survey period;3) The nursing staff on duty during our study period. The usual statistical measures were used according to the type of variables: means, standard deviations, percentages. Data analysis first involved calculating percentages for the qualitative variables and means followed by their standard deviations for the quantitative variables. Next, the Pearson Chi-square test was used to test the association between the dependent variable and the independent variables of interest. The significance level is set at p Results: The prevalence of surgical site infections was 28.58%. The main factors contributing to the occurrence of SSIs that were found were the patient’s level of education (p = 0.003) and the reuse of bandages used for dressing (p = 0.004). Other potential factors such as the economic status of the patient, the poor quality of technical dressings, and the preoperative stay were also highlighted. Conclusion: Surgical site infections remain a global concern. Risk factors were found on both the patient and nurse sides. It is urgent to address these various factors to minimize the occurrence of surgical site infections.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Experimental study on the effect of unloading rate on gneiss rockburst

Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of unloading rates.A high-speed photography system and acoustic emission(AE)system were used to monitor the entire process of rockburst process in real-time.The results show that the intensity of gneiss rockburst decreases with decrease of unloading rate,which is manifested as the reduction of AE energy and fragments ejection velocity.The mechanisms are proposed to explain this effect:(i)The reduction of unloading rate changes the crack propagation mechanism in the process of rockburst.This makes the rockbursts change from the tensile failure mechanism at high unloading rate to the tension-shear mixed failure mechanism at low unloading rate,and more energy released in the form of shear crack propagation.Then,less strain energy is converted into kinetic energy of fragments ejection.(ii)Less plate cracking degree of gneiss has taken shape due to decrease of unloading rate,resulting in the destruction of rockburst incubation process.The enlightenments of reducing the unloading rate for the project are also described quantitatively.The rockburst magnitude is reduced from the medium magnitude at the unloading rate of 0.1 MPa/s to the slight magnitude at the unloading rate of 0.025 MPa/s,which was judged by the ejection velocity.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic,intricately governed by natural selection and historically garnering considerable attention.Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain,ushering in an unprecedented era of mutation rate research.This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates.It examines various types of mutations,explores the evolutionary dynamics and associated theories,and synthesizes both classical and contemporary hypotheses.Furthermore,this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies,mutational patterns,molecular mechanisms,and driving forces influencing variations in mutation rates across species and tissues.Finally,it proposes several potential research directions and pressing questions for future investigations.

Exosomes in viral infection:Effects for pathogenesis and treatment strategies

Exosomes are small vesicles that carry molecules from one cell to another.They have many features that make them interesting for research,such as their stability,low immunogenicity,size of the nanoscale,toxicity,and selective delivery.Exosomes can also interact with viruses in diverse ways.Emerging research highlights the significant role of exosomes in viral infections,particularly in the context of diseases like COVID-19,HIV,HBV and HCV.Understanding the intricate interplay between exosomes and the human immune system holds great promise for the development of effective antiviral therapies.An important aspect is gaining clarity on how exosomes influence the immune system and enhance viral infectivity through their inherent characteristics.By leveraging the innate properties of exosomes,viruses exploit the machinery involved in exosome biogenesis to set replication,facilitate the spread of infection,and eliminate immune responses.They can either help or hinder viral infection by modulating the immune system.This review summarizes the recent findings on how exosomes mediate viral infection and how they can be used for diagnosis or therapy.This could lead to new clinical applications of exosomes in disease management.

Dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates

Interactive holography offers unmatched levels of immersion and user engagement in the field of future display.Despite of the substantial progress has been made in dynamic meta-holography,the realization of real-time,highly smooth interactive holography remains a significant challenge due to the computational and display frame rate limitations.In this study,we introduced a dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates.To our knowledge,this is the first reported practical dynamic interactive metasurface holographic system.We spa-tially divided the metasurface device into multiple distinct channels,each projecting a reconstructed sub-pattern.The switching states of these channels were mapped to bitwise operations on a set of bit values,which avoids complex holo-gram computations,enabling an ultra-high computational frame rate.Our approach achieves a computational frame rate of 800 kHz and a display frame rate of 23 kHz on a low-power Raspberry Pi computational platform.According to this methodology,we demonstrated an interactive dynamic holographic Tetris game system that allows interactive gameplay,color display,and on-the-fly hologram creation.Our technology presents an inspiration for advanced dynamic meta-holography,which is promising for a broad range of applications including advanced human-computer interaction,real-time 3D visualization,and next-generation virtual and augmented reality systems.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Klebsiella pneumoniae infections after liver transplantation:Drug resistance and distribution of pathogens,risk factors,and influence on outcomes

BACKGROUND Liver transplantation(LT)is the only curative treatment for end-stage liver disease.However,LT recipients are susceptible to infection,which is the leading cause of early mortality after LT.Klebsiella pneumoniae infections(KPIs)in the bloodstream are common in LT recipients.We hypothesized that KPIs and carbapenemresistant Klebsiella pneumoniae(CRKP)infections may affect the outcomes of LT recipients.AIM To assess KPI incidence,timing,distribution,drug resistance,and risk factors following LT and its association with outcomes.METHODS This retrospective study included 406 patients undergoing LT at The Third Xiangya Hospital of Central South University,a tertiary hospital,from January 2015 to January 2023.We investigated the risk factors for KPIs and assessed the impact of KPIs and CRKP infections on the prognosis of LT recipients using logistic regression analysis.RESULTS KPI incidence was 7.9%(n=32),with lung/thoracic cavity the most frequent site of infection;the median time from LT to KPI onset was 7.5 d.Of 44 Klebsiella pneumoniae isolates,43(97.7%)and 34(77.3%)were susceptible to polymyxin B or ceftazidime/avibactam and tigecycline,respectively;>70%were resistant to piperacillin/tazobactam,ceftazidime,cefepime,aztreonam,meropenem,and levofloxacin.Female sex[odds ratio(OR)=2.827,95%confidence interval(CI):1.256-6.364;P=0.012],pre-LT diabetes(OR=2.794,95%CI:1.070-7.294;P=0.036),day 1 post-LT alanine aminotransferase(ALT)levels≥1500 U/L(OR=3.645,95%CI:1.671-7.950;P=0.001),and post-LT urethral catheter duration over 4 d(OR=2.266,95%CI:1.016-5.054;P=0.046)were risk factors for KPI.CRKP infections,but not KPIs,were risk factors for 6-month all-cause mortality post-LT.CONCLUSION KPIs occur frequently and rapidly after LT.Risk factors include female sex,pre-LT diabetes,increased post-LT ALT levels,and urethral catheter duration.CRKP infections,and not KPIs,affect mortality.

Predictive model using four ferroptosis-related genes accurately predicts gastric cancer prognosis

BACKGROUND Gastric cancer(GC)is a common malignancy of the digestive system.According to global 2018 cancer data,GC has the fifth-highest incidence and the thirdhighest fatality rate among malignant tumors.More than 60%of GC are linked to infection with Helicobacter pylori(H.pylori),a gram-negative,active,microaerophilic,and helical bacterium.This parasite induces GC by producing toxic factors,such as cytotoxin-related gene A,vacuolar cytotoxin A,and outer membrane proteins.Ferroptosis,or iron-dependent programmed cell death,has been linked to GC,although there has been little research on the link between H.pylori infection-related GC and ferroptosis.AIM To identify coregulated differentially expressed genes among ferroptosis-related genes(FRGs)in GC patients and develop a ferroptosis-related prognostic model with discrimination ability.METHODS Gene expression profiles of GC patients and those with H.pylori-associated GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus(GEO)databases.The FRGs were acquired from the FerrDb database.A ferroptosis-related gene prognostic index(FRGPI)was created using least absolute shrinkage and selection operator–Cox regression.The predictive ability of the FRGPI was validated in the GEO cohort.Finally,we verified the expression of the hub genes and the activity of the ferroptosis inducer FIN56 in GC cell lines and tissues.RESULTS Four hub genes were identified(NOX4,MTCH1,GABARAPL2,and SLC2A3)and shown to accurately predict GC and H.pylori-associated GC.The FRGPI based on the hub genes could independently predict GC patient survival;GC patients in the high-risk group had considerably worse overall survival than did those in the low-risk group.The FRGPI was a significant predictor of GC prognosis and was strongly correlated with disease progression.Moreover,the gene expression levels of common immune checkpoint proteins dramatically increased in the highrisk subgroup of the FRGPI cohort.The hub genes were also confirmed to be highly overexpressed in GC cell lines and tissues and were found to be primarily localized at the cell membrane.The ferroptosis inducer FIN56 inhibited GC cell proliferation in a dose-dependent manner.CONCLUSION In this study,we developed a predictive model based on four FRGs that can accurately predict the prognosis of GC patients and the efficacy of immunotherapy in this population.

Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.