From the perspective of experimental practice: High-throughput computational screening in photocatalysis

Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.

Effect of solvent on the initiation mechanism of living anionic polymerization of styrene:A computational study

For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of solvent on the mechanism and kinetics of LAP was revealed through a strategy combining density functional theory(DFT)calculations and kinetic modeling.In terms of mechanism,it is found that the stronger the solvent polarity,the more electrons transfer from initiator to solvent through detailed energy decomposition analysis of electrostatic interactions between initiator and solvent molecules.Furthermore,we also found that the stronger the solvent polarity,the higher the monomer initiation energy barrier and the smaller the initiation rate coefficient.Counterintuitively,initiation is more favorable at lower temperatures based on the calculated results ofΔG_(TS).Finally,the kinetic characteristics in different solvents were further examined by kinetic modeling.It is found that in benzene and n-pentane,the polymerization rate exhibits first-order kinetics.While,slow initiation and fast propagation were observed in tetrahydrofuran(THF)due to the slow free ion formation rate,leading to a deviation from first-order kinetics.

Computation Offloading in Edge Computing for Internet of Vehicles via Game Theory

With the rapid advancement of Internet of Vehicles(IoV)technology,the demands for real-time navigation,advanced driver-assistance systems(ADAS),vehicle-to-vehicle(V2V)and vehicle-to-infrastructure(V2I)communications,and multimedia entertainment systems have made in-vehicle applications increasingly computingintensive and delay-sensitive.These applications require significant computing resources,which can overwhelm the limited computing capabilities of vehicle terminals despite advancements in computing hardware due to the complexity of tasks,energy consumption,and cost constraints.To address this issue in IoV-based edge computing,particularly in scenarios where available computing resources in vehicles are scarce,a multi-master and multi-slave double-layer game model is proposed,which is based on task offloading and pricing strategies.The establishment of Nash equilibrium of the game is proven,and a distributed artificial bee colonies algorithm is employed to achieve game equilibrium.Our proposed solution addresses these bottlenecks by leveraging a game-theoretic approach for task offloading and resource allocation in mobile edge computing(MEC)-enabled IoV environments.Simulation results demonstrate that the proposed scheme outperforms existing solutions in terms of convergence speed and system utility.Specifically,the total revenue achieved by our scheme surpasses other algorithms by at least 8.98%.

Mechanism of Universal Quantum Computation in the Brain

In this paper, the authors extend [1] and provide more details of how the brain may act like a quantum computer. In particular, positing the difference between voltages on two axons as the environment for ions undergoing spatial superposition, we argue that evolution in the presence of metric perturbations will differ from that in the absence of these waves. This differential state evolution will then encode the information being processed by the tract due to the interaction of the quantum state of the ions at the nodes with the “controlling’ potential. Upon decoherence, which is equal to a measurement, the final spatial state of the ions is decided and it also gets reset by the next impulse initiation time. Under synchronization, several tracts undergo such processes in synchrony and therefore the picture of a quantum computing circuit is complete. Under this model, based on the number of axons in the corpus callosum alone, we estimate that upwards of 50 million quantum states might be prepared and evolved every second in this white matter tract, far greater processing than any present quantum computer can accomplish.

Integration between Genomic and Computational Statistical Surveys for the Screening of SNP Genetic Variants in Inflammatory Bowel Disease (IBD) Pediatric Patients*

Inflammatory bowel diseases (IBD) are complex multifactorial disorders that include Crohn’s disease (CD) and ulcerative colitis (UC). Considering that IBD is a genetic and multifactorial disease, we screened for the distribution dynamism of IBD pathogenic genetic variants (single nucleotide polymorphisms;SNPs) and risk factors in four (4) IBD pediatric patients, by integrating both clinical exome sequencing and computational statistical approaches, aiming to categorize IBD patients in CD and UC phenotype. To this end, we first aligned genomic read sequences of these IBD patients to hg19 human genome by using bowtie 2 package. Next, we performed genetic variant calling analysis in terms of single nucleotide polymorphism (SNP) for genes covered by at least 20 read genomic sequences. Finally, we checked for biological and genomic functions of genes exhibiting statistically significant genetic variant (SNPs) by introducing Fitcon genomic parameter. Findings showed Fitcon parameter as normalizing IBD patient’s population variability, as well as inducing a relative good clustering between IBD patients in terms of CD and UC phenotypes. Genomic analysis revealed a random distribution of risk factors and as well pathogenic SNPs genetic variants in the four IBD patient’s genome, claiming to be involved in: i) Metabolic disorders, ii) Autoimmune deficiencies;iii) Crohn’s disease pathways. Integration of genomic and computational statistical analysis supported a relative genetic variability regarding IBD patient population by processing IBD pathogenic SNP genetic variants as opposite to IBD risk factor variants. Interestingly, findings clearly allowed categorizing IBD patients in CD and UC phenotypes by applying Fitcon parameter in selecting IBD pathogenic genetic variants. Considering as a whole, the study suggested the efficiency of integrating clinical exome sequencing and computational statistical tools as a right approach in discriminating IBD phenotypes as well as improving inflammatory bowel disease (IBD) molecular diagnostic process.

Reform and Practice of the Course“Introduction to Computer Science”in Universities Based on the Cultivation of Computational Thinking and Systematic Abilities

Introduction to Computer Science,as one of the fundamental courses in computer-related majors,plays an important role in the cultivation of computer professionals.However,traditional teaching models and content can no longer fully meet the needs of modern information technology development.In response to these issues,this article introduces the concept of computational creative thinking,optimizes course content,adopts exploratory teaching methods,and innovates course assessment methods,aiming to comprehensively enhance students’computational thinking and innovative abilities.By continuously improving and promoting this teaching model,it will undoubtedly promote computer education in universities to a new level.

Research on the Assessment System of Computational Mechanics Courses Based on the TOPSIS Entropy Weight Model

This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qualitative evaluation methods.The system not only pays attention to students’practical operation and theoretical knowledge mastery but also puts special emphasis on the cultivation of students’innovative abilities.In order to realize a comprehensive and objective evaluation,the assessment and evaluation method of the entropy weight model combining TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)multi-attribute decision analysis and entropy weight theory is adopted,and its validity and practicability are verified through example analysis.This method can not only comprehensively and objectively evaluate students’learning outcomes,but also provide a scientific decision-making basis for curriculum teaching reform.The implementation of this diversified course evaluation system can better reflect the comprehensive ability of students and promote the continuous improvement of teaching quality.

Subpopulations of regulatory T cells are associated with subclinical atherosclerotic plaques,levels of LDL,and cardiorespiratory fitness in the elderly

Background:Atherosclerosis forms the pathological basis for the development of cardiovascular disease.Since pathological processes initially develop without clinically relevant symptoms,the identification of early markers in the subclinical stage plays an important role for initiating early interventions.There is evidence that regulatory T cells(Tregs)are involved in the development of atherosclerosis.Therefore,the present study aimed to identify and investigate associations with Tregs and their subsets in a cohort of healthy elderly individuals with and without subclinical atherosclerotic plaques(SAP).In addition,various lifestyle and risk factors,such as cardiorespiratory fitness,were investigated as associated signatures.Methods:A cross-sectional study was performed in 79 participants(male:n=50;age=63.6±3.7 years;body mass index=24.9±3.1 kg/m2;mean±SD)who had no previous diagnosis of chronic disease and were not taking medication.Ultrasound of the carotids to identify SAP,cardiovascular function measurement for vascular assessment and a cardiorespiratory fitness test to determine peak oxygen uptake were performed.Additionally,tests were conducted to assess blood lipids and determine glucose levels.Immunophenotyping of Tregs and their subtypes(resting(rTregs)and effector/memory(mTregs))was performed by 8-chanel flow cytometry.Participants were categorized according to atherosclerotic plaque status.Linear and logistic regression models were used to analyze associations between parameters.Results:SAP was detected in a total of 29 participants.The participants with plaque were older(64.8±3.6 years vs.62.9±3.5 years)and had higher peripheral systolic blood pressure(133.8±14.7 mmHg vs.125.8±10.9 mmHg).The participants with SAP were characterized by a lower percentage of rTregs(28.8%±10.7%vs.34.6%±10.7%)and a higher percentage of mTregs(40.3%±14.7%vs.30.0%±11.9%).Multiple logistic regression identified age(odds ratio(OR)=1.20(95%confidence interval(95%CI):1.011.42))and mTregs(OR=1.05(95%CI:1.021.10))as independent risk factors for SAP.Stepwise linear regression could reveal an association of peak oxygen uptake(β=0.441),low-density lipoprotein(LDL)(β=0.096),and SAP(β=6.733)with mTregs and LDL(β=0.104)with rTregs.Conclusion:While at an early stage of SAP,the total proportion of Tregs gives no indication of vascular changes,this is indicated by a shift in the Treg subgroups.Factors such as serum LDL or cardiopulmonary fitness may be associated with this shift and may also be additional diagnostic indicators.This could be used to initiate lifestyle-based preventive measures at an early stage,which may have a protective effect against disease progression.

Quick and easy assessment of sarcopenia in cirrhosis: Can ultrasound be the solution?

Cirrhosis is frequently associated with sarcopenia,with reported rates of over 80%in patients with decompensated alcohol-related liver disease.Sarcopenia nega-tively impacts the prognosis of cirrhotic patients and affects the response to treatment of patients with hepatocellular carcinoma(HCC).For these reasons,identifying an easy-to-perform method to assess sarcopenia in is a key element in the optimization of care in this patient population.Assessment of muscle mass by computed tomography is considered the standard of care for the diagnosis of sarcopenia,but exposure to radiation and high costs limit its application in this setting,especially for repeated assessments.We believe that ultrasound,a cheap and harmless technique also used for HCC screening in cirrhotic patients,could have an expanding role in the diagnosis and follow-up of sarcopenia in these patients.

Prediction of the thermal conductivity of Mg–Al–La alloys by CALPHAD method

Mg-Al alloys have excellent strength and ductility but relatively low thermal conductivity due to Al addition.The accurate prediction of thermal conductivity is a prerequisite for designing Mg-Al alloys with high thermal conductivity.Thus,databases for predicting temperature-and composition-dependent thermal conductivities must be established.In this study,Mg-Al-La alloys with different contents of Al2La,Al3La,and Al11La3phases and solid solubility of Al in the α-Mg phase were designed.The influence of the second phase(s) and Al solid solubility on thermal conductivity was investigated.Experimental results revealed a second phase transformation from Al_(2)La to Al_(3)La and further to Al_(11)La_(3)with the increasing Al content at a constant La amount.The degree of the negative effect of the second phase(s) on thermal diffusivity followed the sequence of Al2La>Al3La>Al_(11)La_(3).Compared with the second phase,an increase in the solid solubility of Al in α-Mg remarkably reduced the thermal conductivity.On the basis of the experimental data,a database of the reciprocal thermal diffusivity of the Mg-Al-La system was established by calculation of the phase diagram (CALPHAD)method.With a standard error of±1.2 W/(m·K),the predicted results were in good agreement with the experimental data.The established database can be used to design Mg-Al alloys with high thermal conductivity and provide valuable guidance for expanding their application prospects.

Predicting the friction angle of clays using a multi-layer perceptron neural network enhanced by yeo-johnson transformation and coral reefs optimization

The accurate prediction of the friction angle of clays is crucial for assessing slope stability in engineering applications.This study addresses the importance of estimating the friction angle and presents the development of four soft computing models:YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and YJCSA-MLPnet.First of all,the Yeo-Johnson(YJ)transformation technique was used to stabilize the variance of data and make it more suitable for parametric statistical models that assume normality and equal variances.This technique is expected to improve the accuracy of friction angle prediction models.The friction angle prediction models then utilized multi-layer perceptron neural networks(MLPnet)and metaheuristic optimization algorithms to further enhance performance,including flower pollination algorithm(FPA),coral reefs optimization(CRO),ant colony optimization continuous(ACOC),and cuckoo search algorithm(CSA).The prediction models without the YJ technique,i.e.FPA-MLPnet,CRO-MLPnet,ACOC-MLPnet,and CSA-MLPnet,were then compared to those with the YJ technique,i.e.YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and YJ-CSA-MLPnet.Among these,the YJ-CRO-MLPnet model demonstrated superior reliability,achieving an accuracy of up to 83%in predicting the friction angle of clay in practical engineering scenarios.This improvement is significant,as it represents an increase from 1.3%to approximately 20%compared to the models that did not utilize the YJ transformation technique.

Misdiagnosis of hemangioma of left triangular ligament of the liver as gastric submucosal stromal tumor:Two case reports

BACKGROUND Extragastric lesions are typically not misdiagnosed as gastric submucosal tumor(SMT).However,we encountered two rare cases where extrinsic lesions were misdiagnosed as gastric SMTs.CASE SUMMARY We describe two cases of gastric SMT-like protrusions initially misdiagnosed as gastric SMTs by the abdominal contrast-enhanced computed tomography(CT)and endoscopic ultrasound(EUS).Based on the CT and EUS findings,the patients underwent gastroscopy;however,no tumor was identified after incising the gastric wall.Subsequent surgical exploration revealed no gastric lesions in both patients,but a mass was found in the left triangular ligament of the liver.The patients underwent laparoscopic tumor resection,and the postoperative diagnosis was hepatic hemangiomas.CONCLUSION During EUS procedures,scanning across different layers and at varying degrees of gastric cavity distension,coupled with meticulous image analysis,has the potential to mitigate the likelihood of such misdiagnoses.

Joint computation offloading and parallel scheduling to maximize delay-guarantee in cooperative MEC systems

The growing development of the Internet of Things(IoT)is accelerating the emergence and growth of new IoT services and applications,which will result in massive amounts of data being generated,transmitted and pro-cessed in wireless communication networks.Mobile Edge Computing(MEC)is a desired paradigm to timely process the data from IoT for value maximization.In MEC,a number of computing-capable devices are deployed at the network edge near data sources to support edge computing,such that the long network transmission delay in cloud computing paradigm could be avoided.Since an edge device might not always have sufficient resources to process the massive amount of data,computation offloading is significantly important considering the coop-eration among edge devices.However,the dynamic traffic characteristics and heterogeneous computing capa-bilities of edge devices challenge the offloading.In addition,different scheduling schemes might provide different computation delays to the offloaded tasks.Thus,offloading in mobile nodes and scheduling in the MEC server are coupled to determine service delay.This paper seeks to guarantee low delay for computation intensive applica-tions by jointly optimizing the offloading and scheduling in such an MEC system.We propose a Delay-Greedy Computation Offloading(DGCO)algorithm to make offloading decisions for new tasks in distributed computing-enabled mobile devices.A Reinforcement Learning-based Parallel Scheduling(RLPS)algorithm is further designed to schedule offloaded tasks in the multi-core MEC server.With an offloading delay broadcast mechanism,the DGCO and RLPS cooperate to achieve the goal of delay-guarantee-ratio maximization.Finally,the simulation results show that our proposal can bound the end-to-end delay of various tasks.Even under slightly heavy task load,the delay-guarantee-ratio given by DGCO-RLPS can still approximate 95%,while that given by benchmarked algorithms is reduced to intolerable value.The simulation results are demonstrated the effective-ness of DGCO-RLPS for delay guarantee in MEC.

Association between baseline levels of muscular strength and risk of stroke in later life:The Cooper Center Longitudinal Study

Background:Muscular strength is an important component of physical fitness.We evaluated the relationship between baseline muscular strength and risk of stroke among adults who were aged≥65 years during follow-up.Methods:We included 7627 healthy adults(mean age=43.9 years,86.0%male)underwent a baseline physical examination between 1980 and 1989.Muscular strength was determined by 1-repetition maximum measures for bench press and leg press and categorized into age-and sex-specific tertiles for each measure.Cardiorespiratory fitness(CRF)was assessed via a maximal treadmill exercise test.Those enrolled in fee-for-service Medicare from 1999 to 2019 were included in the analyses.Associations between baseline strength and stroke outcomes were estimated using a modified Cox proportional hazards model.In a secondary analysis,we examined stroke risk by categories of CRF where Quintile 1=low,Quintiles 2-3=moderate,and Quintiles 4-5=high CRF based on age and sex.Results:After 70,072 person-years of Medicare follow-up,there were 1211 earliest indications of incident stroke.In multivariable analyses,the hazard ratio(95%confidence interval(95%CI))for stroke across bench press categories were 1.0(referent),0.96(0.83-1.11),and 0.89(0.77-1.04),respectively(p trend=0.14).The trend across categories of leg press was also non-significant(p trend=0.79).Adjusted hazard ratio(95%CI)for stroke across ordered CRF categories were 1.0(referent),0.90(0.71-1.13),and 0.72(0.57-0.92)(p trend<0.01).Conclusion:While meeting public health guidelines for muscular strengthening activities is likely to improve muscular strength as well as many health outcomes in older adults,performing such activities may not be helpful in preventing stroke.Conversely,meeting guidelines for aerobic activity is likely to improve CRF and lower stroke risk.

Genetic benefits of female from extra-pair paternity are context dependent within the socially monogamous Tree Sparrow

Females actively seek extra-pair paternity(EPP)to acquire a fitness advantage for their offspring.The“contextdependence hypothesis”posits that female extra-pair mate choice has plasticity in response to environmental conditions,and therefore magnitude of female genetic benefits from EPP depends on the environmental variation.Furthermore,chronic heavy metal pollution can cause adverse effects on fitness-related traits of wild birds.However,few studies were available on the interactions between heavy metal pollution and EPP.We selected an area that was contaminated by heavy metals for more than 60 years(Baiyin,BY),a relatively unpolluted area(Liujiaxia,LJX),and Tree Sparrows(Passer montanus)as study species to explore the response of female extrapair mate choice and genetic benefits from EPP to heavy metal pollution in socially monogamous birds.The relatedness between social mates and extra-pair mates was investigated.Additionally,we compared the body size and heterozygosity of extra-pair offspring(EPO),within-pair offspring(WPO),social males and extra-pair males from the two Tree Sparrow populations.We found that at BY,female Tree Sparrows tended to choose extra-pair males with larger body size and lower genetic similarity,thereby producing higher heterozygosity and larger body size of EPO compared with those of WPO.However,no similar phenomenon was observed in the Tree Sparrow population from LJX.In addition,there was a significant interaction between population and paternity in the analyses of the fitness-related traits,suggesting that environmental variation could affect female genetic benefits from EPP.This study confirmed the existence of presumed interactions between environmental pollution and EPP within the natural population of socially monogamous Tree Sparrows.Our findings shed lights on the possible effects of long-term environmental stress on mating system in wild birds.

A statistical analysis of the Kappa-type energy spectrum distribution of radiation belt electrons observed by Van Allen Probes

The energy spectrum of energetic electrons is a key factor representing the dynamic variations of Earth’s Van Allen radiation belts.Increased measurements have indicated that the commonly used Maxwellian and Kappa distributions are inadequate for capturing the realistic spectral distributions of radiation belt electrons.Here we adopt the Kappa-type(KT)distribution as the fitting function and perform a statistical analysis to investigate the radiation belt electron flux spectra observed by the Van Allen Probes.By calculating the optimal values of the key KT distribution parameters(i.e.,κandθ2)from the observed spectral shapes,we fit the radiation belt electron fluxes at different L-shells under different geomagnetic conditions.In this manner,we obtain typical values of the KT distribution parameters,which are statistically feasible for modeling the radiation belt electron flux profiles during either geomagnetically quiet or active periods.A comparison of the KT distribution model results with those using the Maxwellian or Kappa distribution reveals the advantage of the KT distribution for studying the overall properties of the radiation belt electron spectral distribution,which has important implications for deepening the current understanding of the radiation belt electron dynamics under evolving geomagnetic conditions.

The Impact and Intervention of Handheld Tai Chi Water-Resistance Fitness Ball on Middle-Aged and Elderly Patients with Parkinson’s Disease

Through the use of a survey and statistical methods, this study explores the effects and interventions of handheld Tai Chi water resistance fitness balls on the elderly with Parkinson’s disease. Firstly, a questionnaire on exercise compliance for patients with Parkinson’s disease was developed, and its reliability and validity were tested. Then, a survey was conducted to investigate the current status of exercise compliance among Parkinson’s disease patients, including general information, scoring status, and single and multiple factor analyses of influencing factors [1]. The results of the study show that through qualitative research, the dimensions and item pools of the questionnaire were initially constructed, and the reliability analysis of the questionnaire was conducted through Delphi expert consultation, with favorable results in terms of its reliability and validity [2]. Regarding the current status of exercise compliance among Parkinson’s disease patients, the study found that the level of exercise compliance needs improvement, and there are significant differences in exercise compliance levels among patients under different circumstances. Finally, the research results were discussed and conclusions were drawn. The innovation of this study lies in the development of a questionnaire on exercise compliance for patients with Parkinson’s disease and the preliminary qualitative research and Delphi expert consultation conducted on it, providing new ideas and methods for the study of exercise compliance. However, the study also has limitations as it did not examine the effects of other interventions on Parkinson’s disease, so further research should be conducted [3].

IoT Task Offloading in Edge Computing Using Non-Cooperative Game Theory for Healthcare Systems

In this paper,we present a comprehensive system model for Industrial Internet of Things(IIoT)networks empowered by Non-Orthogonal Multiple Access(NOMA)and Mobile Edge Computing(MEC)technologies.The network comprises essential components such as base stations,edge servers,and numerous IIoT devices characterized by limited energy and computing capacities.The central challenge addressed is the optimization of resource allocation and task distribution while adhering to stringent queueing delay constraints and minimizing overall energy consumption.The system operates in discrete time slots and employs a quasi-static approach,with a specific focus on the complexities of task partitioning and the management of constrained resources within the IIoT context.This study makes valuable contributions to the field by enhancing the understanding of resourceefficient management and task allocation,particularly relevant in real-time industrial applications.Experimental results indicate that our proposed algorithmsignificantly outperforms existing approaches,reducing queue backlog by 45.32% and 17.25% compared to SMRA and ACRA while achieving a 27.31% and 74.12% improvement in Qn O.Moreover,the algorithmeffectively balances complexity and network performance,as demonstratedwhen reducing the number of devices in each group(Ng)from 200 to 50,resulting in a 97.21% reduction in complexity with only a 7.35% increase in energy consumption.This research offers a practical solution for optimizing IIoT networks in real-time industrial settings.

Comparison of engineering failures and seismic responses of 500 kV transformer-bushing systems in the 2022 Luding earthquake

Cemented and mechanically clamped types of end fittings(fitting-C and fitting-M)are commonly used in transformer bushings.During the Luding Ms 6.8 earthquake that occurred in China on September 5,2022,all transformer bushings with the two types of end fittings in a 500 kV substation were damaged.Post-earthquake field investigations were conducted,and the failures of the two types of bushings were compared.Two elementary simulation models of the transformer-bushing systems were developed to simulate the engineering failures,and further compute their seismic responses for comparison.The results indicate that the hitch lugs of the connection flange are structurally harmful to seismic resistance.Fitting-M can decrease the bending stiffness of the bushing due to the flexible sealing rubber gasket.Since it provides a more flexible connection that dissipates energy,the peak accelerations and relative displacements at the top of the bushing are significantly lower than those of the bushing with fitting-C.Compared with fitting-C,fitting-M transfers the high-stress areas from the connection flange to the root of the porcelain,so the latter becomes the most vulnerable component.Fitting-M increases the failure risk of the low-strength porcelain,indicating the unsuitability of applying it in high-intensity fortification regions.

Emphysematous Cystitis: Report of Two Cases and Review of the Literature

Emphysematous cystitis is a rare complication of lower urinary tract infection whose prognosis is conditioned by the delay in treatment. The predisposition of diabetic patients to urinary infections caused by gas-producing bacteria is considered one of the most common factors in the occurrence of emphysematous cystitis. The currently recommended diagnostic test is CT scanning, which has definite value in assessing gas accumulation in the bladder wall and lumen. The authors report the observations of two patients aged 68 and 80 who were treated for emphysematous cystitis complicating diabetes mellitus. The evolution was favorable under treatment with antibiotic therapy, insulin therapy and bladder drainage.