Cytokine release syndrome induced by anti-programmed death-1 treatment in a psoriasis patient:A dark side of immune checkpoint inhibitors

In recent years,cancer immunotherapy has introduced novel treatments,such as monoclonal antibodies,which have facilitated targeted therapies against tumor cells.Programmed death-1(PD-1)is an immune checkpoint expressed in T cells that regulates the immune system’s activity to prevent over-activation and tissue damage caused by inflammation.However,PD-1 is also expressed in tumor cells and functions as an immune evasion mechanism,making it a therapeutic target to enhance the immune response and eliminate tumor cells.Consequently,immune checkpoint inhibitors(ICIs)have emerged as an option for certain tumor types.Nevertheless,blocking immune checkpoints can lead to immune-related adverse events(irAEs),such as psoriasis and cytokine release syndrome(CRS),as exemp-lified in the clinical case presented by Zhou et al involving a patient with adva-nced gastric cancer who received sintilimab,a monoclonal antibody targeting PD-1.Subsequently,the patient experienced exacerbation of psoriasis and CRS.The objective of this editorial article is to elucidate potential immunologic mechanisms that may contribute to the development of CRS and psoriasis in patients receiving ICIs.It is crucial to acknowledge that while ICIs offer superior safety and efficacy compared to conventional therapies,they can also manifest irAEs affecting the skin,gastrointestinal tract,or respiratory system.In severe cases,these irAEs can lead to life-threatening complications such as circulatory shock or multiorgan failure.Consequently,it is recommended that patients receiving ICIs undergo regular monitoring to identify and manage these adverse events effectively.

How inflammation influences psychiatric disease

Recent studies highlight the strong correlation between infectious diseases and the development of neuropsychiatric disorders.In this editorial,we comment on the article“Anti-infective therapy durations predict psychological stress and laparoscopic surgery quality in pelvic abscess patients”by Zhang et al,published in the recent issue of the World Journal of Psychiatry 2023;13(11):903-911.Our discussion highlighted the potential consequences of anxiety,depression,and psychosis,which are all linked to bacterial,fungal,and viral infections,which are relevant to the impact of inflammation on the sequelae in mental health as those we are observing after the coronavirus disease 2019 pandemic.We focus specifically on the immune mechanisms triggered by inflammation,the primary contributor to psychiatric complications.Importantly,pathophysiological mechanisms such as organ damage,post-injury inflammation,and infectioninduced endocrine alterations,including hypocortisolism or autoantibody formation,significantly contribute to the development of chronic low-grade inflammation,promoting the emergence or development of psychiatric alterations in susceptible individuals.As inflammation can have long-term effects on patients,a multidisciplinary treatment plan can avoid complications and debilitating health issues,and it is crucial to recognize and address the mental health implications.

Insights into myelin dysfunction in schizophrenia and bipolar disorder

Schizophrenia and bipolar disorder are disabling psychiatric disorders with a worldwide prevalence of approximately 1%.Both disorders present chronic and deteriorating prognoses that impose a large burden,not only on patients but also on society and health systems.These mental illnesses share several clinical and neurobiological traits;of these traits,oligodendroglial dysfunction and alterations to white matter(WM)tracts could underlie the disconnection between brain regions related to their symptomatic domains.WM is mainly composed of heavily myelinated axons and glial cells.Myelin internodes are discrete axon-wrapping membrane sheaths formed by oligodendrocyte processes.Myelin ensheathment allows fast and efficient conduction of nerve impulses through the nodes of Ranvier,improving the overall function of neuronal circuits.Rapid and precisely synchronized nerve impulse conduction through fibers that connect distant brain structures is crucial for higher-level functions,such as cognition,memory,mood,and language.Several cellular and subcellular anomalies related to myelin and oligodendrocytes have been found in postmortem samples from patients with schizophrenia or bipolar disorder,and neuroimaging techniques have revealed consistent alterations at the macroscale connectomic level in both disorders.In this work,evidence regarding these multilevel alterations in oligodendrocytes and myelinated tracts is discussed,and the involvement of proteins in key functions of the oligodendroglial lineage,such as oligodendrogenesis and myelination,is highlighted.The molecular components of the axo-myelin unit could be important targets for novel therapeutic approaches to schizophrenia and bipolar disorder.

Performance Comparison of Deep and Machine Learning Approaches Toward COVID-19 Detection

The coronavirus(COVID-19)is a disease declared a global pan-demic that threatens the whole world.Since then,research has accelerated and varied to find practical solutions for the early detection and correct identification of this disease.Several researchers have focused on using the potential of Artificial Intelligence(AI)techniques in disease diagnosis to diagnose and detect the coronavirus.This paper developed deep learning(DL)and machine learning(ML)-based models using laboratory findings to diagnose COVID-19.Six different methods are used in this study:K-nearest neighbor(KNN),Decision Tree(DT)and Naive Bayes(NB)as a machine learning method,and Deep Neural Network(DNN),Convolutional Neural Network(CNN),and Long-term memory(LSTM)as DL methods.These approaches are evaluated using a dataset obtained from the Israelita Albert Einstein Hospital in Sao Paulo,Brazil.This data consists of 5644 laboratory results from different patients,with 10%being Covid-19 positive cases.The dataset includes 18 attributes that characterize COVID-19.We used accuracy,f1-score,recall and precision to evaluate the different developed systems.The obtained results confirmed these approaches’effectiveness in identifying COVID-19,However,ML-based classifiers couldn’t perform up to the standards achieved by DL-based models.Among all,NB performed worst by hardly achieving accuracy above 76%,Whereas KNN and DT compete by securing 84.56%and 85%accuracies,respectively.Besides these,DL models attained better performance as CNN,DNN and LSTM secured more than 90%accuracies.The LTSM outperformed all by achieving an accuracy of 96.78%and an F1-score of 96.58%.

玉米110 cm垄合理耕整地方式比较

[目的]研究不同耕整地方式对土壤物理性质和玉米产量的影响。[方法]在110 cm垄栽培模式下,对5种不同整地方式的土壤田间持水量、容重、孔隙度、饱和含水量和玉米产量进行分析。[结果]深翻、深松和旋耕均对各处理垄台土壤进行了扰动,土壤容重降低,孔隙度增大,田间持水量增加。垄台土层容重等物理性质的影响程度为秋灭茬旋耕+秋深翻>秋灭茬旋耕+秋深松>秋深翻>春灭茬旋耕+春深松>春旋耕;对垄沟容重等物理性质的影响程度为秋灭茬旋耕+秋深松>秋灭茬旋耕+秋深翻>春灭茬旋耕+春深松>秋深翻>春旋耕;产量表现为秋灭茬旋耕+秋深翻>秋灭茬旋耕+秋深松>秋深翻>春灭茬旋耕+春深松>春旋耕。[结论]综合分析不同耕整地方式对土壤物理性质的影响、玉米产量及生产成本,秋灭茬旋耕+秋深松、秋深翻为玉米大垄合理的耕整地方式。

土壤处理剂对土壤钾和重金属含量的影响

[目的]寻找能够改良土壤的土壤处理剂,探索不同土壤处理剂对土壤的改良效果。[方法]通过5种不同处理剂在豇豆的田间试验,研究不同土壤处理剂对豇豆产量和土壤中钾、砷、铅、汞和镉等含量的影响。[结果]施用土壤处理剂后豇豆产量均高于对照;土壤中重金属含量均有不同程度的下降。[结论]施用土壤处理剂有利于降解土壤中重金属。

中国人群肝癌筛查指南(2022,北京)

中国人群的肝癌存在生存率低、死亡率高的情况,如何有效降低肝癌相关负担仍是中国公共卫生和慢性病防控领域亟待解决的重大问题,而肝癌人群筛查策略优化是值得持续探索的重要抓手和方向。中国人群肝癌筛查指南受国家卫生健康委员会疾病预防控制局委托,由国家癌症中心发起,联合多学科专家,根据世界卫生组织推荐的指南制定原则和方法,整合肝癌人群筛查领域的国内外研究新证据,兼顾中国国情及实践经验,针对肝癌筛查过程中的筛查人群、筛查技术、监测方案等呈现循证推荐,以期为中国人群肝癌筛查实践的规范提供参考。

Mapping tree canopies in urban environments using airborne laser scanning (ALS):a Vancouver case study

Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and modulation of evapotranspiration. It also plays an important role filtering urban water systems and reducing storm water runoff.Methods: We investigate the capacity of ALS data to individually detect, map and characterize large(taller than15 m) trees within the City of Vancouver. Large trees are critical for the function and character of Vancouver’s urban forest. We used an object-based approach for individual tree detection and segmentation to determine tree locations(position of the stem), to delineate the shape of the crowns and to categorize the latter either as coniferous or deciduous.Results: Results indicate a detection rate of 76.6% for trees > 15 m with a positioning error of 2.11 m(stem location). Extracted tree heights possessed a RMSE of 2.60 m and a bias of-1.87 m, whereas crown diameter was derived with a RMSE of 3.85 m and a bias of-2.06 m. Missed trees are principally a result of undetected treetops occurring in dense, overlapping canopies with more accurate detection and delineation of trees in open areas.Conclusion: By identifying key structural trees across Vancouver’s urban forests, we can better understand their role in providing ecosystem goods and services for city residents.

钽对一种镍基单晶高温合金蠕变行为的影响

利用螺旋选晶法制备了不同钽含量的低成本镍基单晶高温合金,研究了在850℃,441MPa及950℃,250MPa条件下钽对合金的蠕变性能及蠕变机制的影响。结果表明:钽含量越多,合金中γ/γ′晶界处的位错网越完整,合金的蠕变寿命越长;随着钽含量的提高,850℃,441MPa时合金的蠕变机制由位错的滑移以及切割γ′向层错方式转变;950℃,250MPa时合金的蠕变机制由位错以层错方式切割γ′向攀移转变。

Numerical prediction of fiber motion in a branching channel flow of fiber suspensions

Fiber orientation and dispersion in the dilute fiber suspension that flows through a T-shaped branching channel are simulated numerically based on the slender-body theory. The simulated results are consistent qualitatively with the experimental data available in the literature. The results show that the spatial distribution of fibers is dependent on the fiber aspect ratio, but has no relation with the volume fraction of fiber. The content ratio of fibers near the upper wall increases monotonically with an increasing Re number, and the situation is reverse for the region near the bottom wall. The orientation of fibers depends on Re number, however, the function of fiber volume fraction and aspect ratio is negligible. The fibers near the wall and in the central region of the channel align along the flow direction at all times, but the fibers in the other parts of the channel tend to align along the flow direction only in the downstream region.

Clinical features of AIDS patients with Hodgkin's lymphoma with isolated bone marrow involvement:report of 12 cases at a single institution

Objective： To study the main clinical and histopathological features of 12 patients with Hodgkin＇s lymphoma （HL） diagnosed primarily from bone marrow （BM） involvement. Methods： We included 12 acquired immunodeficiency syndrome （AIDS） patients with HL assisted in the F. J. Mufiiz Infectious Diseases Hospital since January 2002 to December 2013. The diagnosis of ilL with primary BM involvement in patients was confirmed by clinical, histopathological, and immunohistochemical findings. Results： All patients presented ＂B＂ symptoms and pancytopenia. All of them had stage IV neoplasm disease because of BM infiltration. The median of CD4＋ T-cell counts was 114 cells/μL, and mixed cellularity （MC） was the most frequent histopathological subtype of 92% cases. Conclusion： When other causes are excluded, BM biopsy should be performed in AIDS patients with ＂B＂ symptoms and pancytopenia to evaluate BM infiltration by atypical lymphocytes.

Factors limiting the recruitment of Quercus schottkyana,a dominant evergreen oak in SW China

Quercus schottkyana is a dominant species of oak in the Asian evergreen broad-leaved forests in southwestern China but seedlings are uncommon and recruitment is rare. Annual acorn production by Q. schottkyana is variable and the acorns are exposed to a series of mortality risks. Understanding the factors that limit recruitment of the oak requires knowledge of the oak's life cycle from acorn production to germination and seedling establishment. In this study, we first tested the effects of acorn density on establishment of seedlings by placing batches of acorns at different densities throughout the study area.Second, we tested the effects of herbivores on seedling survival by erecting fences around both natural and transplanted seedling populations. Our results show that even though the rate of seedling establishment increases as acorn density increases(for 32-8000 acorns?m^(-2)), survival rates of seedlings in the field were generally low(0-0.6%). We show that seedling recruitment of Q. schottkyana is mainly limited to the acorn stage where 88% of the acorns died from the combined effects of desiccation and predation by weevils(Curculio) and bark beetles(Coccotrypes sp.). Herbivory results in the death of some seedlings and consequently also affects the recruitment of seedlings of Q. schottkyana.

Non-Painful Peripheral Inflammation Blocks Conditioned Place-Preference to Morphine and Nicotine through an Ibuprofen-Sensitive and an Ibuprofen Insensitive Pathway

The field of neuroimmunology has expanded in recent years providing new insights and therapies into pathologies like stroke, autism, and depression. However, few works explore the relationship between inflammatory stimuli and motivation. Thus, the aim of this study was to determine how non-painful inflammatory stimuli affect reward. To test reward-response, we used the morphine and the nicotine induced conditioned place-preference and place-aversion model in rats with non-painful inflammation. The following inflammatory models were used: non-painful infectious inflammation: 24 hrs prior to conditioning sessions, an injection with Calmette-Guerin bacillus (CGB) 1 × 107 cfu, ip, was administered. Non-painful non-infectious inflammation: 24 hrs prior to conditioning sessions, rats’ sciatic nerve was blocked and cut, followed by the injection of carrageenan (750 μl) in the paw. We then measured the cytokine concentration to determine the inflammatory profile of each of our models. Finally, we administered ibuprofen to determine if it could prevent the effect of inflammation over conditioned place-preference. We show that carrageenan significantly reduced the morphine-induced reward. Non-painful inflammatory stimulus, CGB and denervation + carrageenan, inhibit the conditioned place-preference to morphine and nicotine, CGB also block conditioned place-aversion to nicotine;carrageenan has no effect on CPA. The administration of ibuprofen reinstates conditioned place-preference to morphine and nicotine in the carrageenan model, but has no effect in the CGB model;finally ibuprofen has no effect on CPA. Our data suggest that non-painful-inflammatory stimuli inhibit the reward system, independent of cytokine concentration. Furthermore, the administration of a PGE 2 inhibitor can importantly modulate this phenomenon.

Model of Wetland Carbon Sequestration in the Venetian Lagoon, Italy

This research deals with an evaluation of the sink of greenhouse gas CO2 in a eutrophic area of the Venetian lagoon where fish is farmed （＂Valle da pesca＂）. Following CDM UNFCCC （Clean Development Mechanism United Nations Framework Convention on Climate Change） criteria, this can be considered relevant to the international standard for the voluntary evaluation of carbon credits on the basis of Annex a of Kyoto Protocol. To identify the ＂Valle da pesca＂ brackish lagoon properties regulating the carbon dioxide （CO2）, a survey has been performed during three seasons in one year and in four different locations. These places are located in the Italian Venetian Lagoon and in the Grado Lagoon in North Italy, Europe. To identify the CO2 sink capacity, a special index is calculated. The CO2 concentrations and sink are regulated by the balance of autotrophic and heterotrophic activities, and the sediment anoxic denitrification and macro algae are crucial tank of CO2 in the valley shallow waters. The ponds potential-CO2 yield of 80-124 kg/m2 per year and the value are related and proportional to the correct human environmental control （water flux control）.

Artificial Intelligence Based Sentiment Analysis for Health Crisis Management in Smart Cities

Smart city promotes the unification of conventional urban infrastructure and information technology (IT) to improve the quality of living andsustainable urban services in the city. To accomplish this, smart cities necessitate collaboration among the public as well as private sectors to install ITplatforms to collect and examine massive quantities of data. At the same time,it is essential to design effective artificial intelligence (AI) based tools to handlehealthcare crisis situations in smart cities. To offer proficient services to peopleduring healthcare crisis time, the authorities need to look closer towardsthem. Sentiment analysis (SA) in social networking can provide valuableinformation regarding public opinion towards government actions. With thismotivation, this paper presents a new AI based SA tool for healthcare crisismanagement (AISA-HCM) in smart cities. The AISA-HCM technique aimsto determine the emotions of the people during the healthcare crisis time, suchas COVID-19. The proposed AISA-HCM technique involves distinct operations such as pre-processing, feature extraction, and classification. Besides,brain storm optimization (BSO) with deep belief network (DBN), called BSODBN model is employed for feature extraction. Moreover, beetle antennasearch with extreme learning machine (BAS-ELM) method was utilized forclassifying the sentiments as to various classes. The use of BSO and BASalgorithms helps to effectively modify the parameters involved in the DBNand ELM models respectively. The performance validation of the AISA-HCMtechnique takes place using Twitter data and the outcomes are examinedwith respect to various measures. The experimental outcomes highlighted theenhanced performance of the AISA-HCM technique over the recent state ofart SA approaches with the maximum precision of 0.89, recall of 0.88, Fmeasure of 0.89, and accuracy of 0.94.

IL28B SNPs rs12979860 and rs8099917 Are Associated with Inflammatory Response in Argentine Chronic HCV Patients

Background: Hepatitis C virus (HCV) is a major cause of chronic liver disease, including cirrhosis and liver cancer. The aim of our study was to determine whether IL28B single nucleotide polymorphisms (SNPs) rs12979860 and rs8099917 can be considered a prognostic host factor in untreated chronic HCV patients. Methods: We set up a real-time Allele Specific PCR amplification to determine the allele present in each polymorphic site, and statistically grouped and compared this result with clinical data. Results: We determined rs12979860 and rs8099917 genotype and allele frequencies in a single cohort of untreated chronically HCV-infected patients. We found significant associations between higher inflammatory activity, measured as ALT levels or METAVIR scores and rs12979860 CC (P = 0.0013 and P = 0.0033, respectively) and rs8099917 TT (P = 0.0005 and P = 0.0264, respectively) genotypes. Interestingly, considering both genotypes together, we also found association with ALT levels (P = 0.0003;OR = 5.125) or METAVIR scores (P = 0.0038;OR = 5.179), suggesting and additive effect on liver inflammation in these patients. Conclusion: we show association between hepatic inflammatory activity in a single Argentinean untreated chronically HCV cohort and SNPs located in the interferon lambda gene region. The studied polymorphisms, together with further innate and adaptive immune responses, clearly play a role in modulating the HCV infected patients outcome, contributing to hepatic inflammation and possible fibrosis/cirrhosis.

Depressant effects of Agastache mexicana methanol extract and one of major metabolites tilianin

Objective:To determine the depressant-like effects and the possible mechanism of action of tilianin isolated from active methanol extract of Agastache mexicana(A.mexicana).Also,to establish the pharmacophoric requirements of tilianin,as a possible ligand of GABA_A/BZD receptor,by the alignment of diazepam.CGS-9896 and diindole,using a previously described pharmacophoric model.Methods:Tilianin(30 to 300 mg/kg.ip.and 300 mg/kg,pa.) and methanol crude extract(10 to 300 mg/kg,ip.and 300 mg/kg po.) from A.mexicana were evaluated for potential sedative and anxiolytic-like response drugs by using open-field,hole-board,cylinder of exploration,plus-maze and sodium pentobarbital-induced hypnosis mice methods.Results:Methanol extract and tilianin showed anxiolytic-like activity from a dosage of 30 mg/kg,ip.or 300 mg/kg,po.and were less potent than diazepam 0.1 mg/kg.a reference anxiolytic drug used.Moreover,depressant activity of both potentiates sodium pentobarbital(SP)-induced sleeping time.The anxiolytic-like effect of 30 mg/kg ip.observed for the extract and tilianin,by using the plus-maze model,was partially prevented in the presence of flumazenil(a GABA_A/BZD antagonist,5 mg/kg ip.) but not in the presence of WAY100635(a selective 5-HT_(1A) receptor antagonist,0.32 mg/kg.ip.).Pharmacophoric modeling alignments of three agonist of GABA_A/BZD allow identify seven chemical features.Tilianin contains six of the seven features previously determined.Conclusions:Results indicate that tilianin is one of the bioactive metabolites in the anxiolytic-like activity of 4.mexicana.reinforcing its central nervous system uses,where GABA_A/BZD,but not 5-HT_(1A),receptors are partially involved.

A Conceptual Framework for Commercial Property Price Indexes

The paper studies the problems associated with the construction of price indexes for commercial properties that could be used in the System of National Accounts. Property price indexes are required for the stocks of commercial properties in the Balance Sheets of the country and related price indexes for the land and structure components of a commercial property are required in the Income Accounts of the country if the Multifactor Productivity of the Commercial Property Industry is calculated as part of the System of National accounts. The paper suggests a variant of the capitalization of the Net Operating Income approach to the construction of property price indexes and uses the one hoss shay or light bulb model of depreciation as a model of depreciation for the structure component of a commercial property.

QoS Based Cloud Security Evaluation Using Neuro Fuzzy Model

Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network,and users can use them at any time.After assessing and choosing cloud providers,however,customers confront the variety and difficulty of quality of service(QoS).To increase customer retention and engagement success rates,it is critical to research and develops an accurate and objective evaluation model.Cloud is the emerging environment for distributed services at various layers.Due to the benefits of this environment,globally cloud is being taken as a standard environment for individuals as well as for the corporate sector as it reduces capital expenditure and provides secure,accessible,and manageable services to all stakeholders but Cloud computing has security challenges,including vulnerability for clients and association acknowledgment,that delay the rapid adoption of computing models.Allocation of resources in the Cloud is difficult because resources provide numerous measures of quality of service.In this paper,the proposed resource allocation approach is based on attribute QoS Scoring that takes into account parameters the reputation of the asset,task completion time,task completion ratio,and resource loading.This article is focused on the cloud service’s security,cloud reliability,and could performance.In this paper,the machine learning algorithm neuro-fuzzy has been used to address the cloud security issues to measure the parameter security and privacy,trust issues.The findings reveal that the ANFIS-dependent parameters are primarily designed to discern anomalies in cloud security and features output normally yields better results and guarantees data consistency and computational power.

Hyper-Convergence Storage Framework for EcoCloud Correlates

Cloud computing is an emerging domain that is capturing global users from all walks of life—the corporate sector,government sector,and social arena as well.Various cloud providers have offered multiple services and facilities to this audience and the number of providers is increasing very swiftly.This enormous pace is generating the requirement of a comprehensive ecosystem that shall provide a seamless and customized user environment not only to enhance the user experience but also to improve security,availability,accessibility,and latency.Emerging technology is providing robust solutions to many of our problems,the cloud platform is one of them.It is worth mentioning that these solutions are also amplifying the complexity and need of sustenance of these rapid solutions.As with cloud computing,new entrants as cloud service providers,resellers,tech-support,hardware manufacturers,and software developers appear on a daily basis.These actors playing their role in the growth and sustenance of the cloud ecosystem.Our objective is to use convergence for cloud services,software-defined networks,network function virtualization for infrastructure,cognition for pattern development,and knowledge repository.In order to gear up these processes,machine learning to induce intelligence to maintain ecosystem growth,to monitor performance,and to become able to make decisions for the sustenance of the ecosystem.Workloads may be programmed to“superficially”imitate most business applications and create large numbers using lightweight workload generators that merely stress the storage.In today’s current IT environment,when many enterprises use the cloud to service some of their application demands,a different performance testing technique that assesses more than the storage is necessary.Compute and storage are merged into a single building block with HCI(Hyper-converged infrastructure),resulting in a huge pool of compute and storage resources when clustered with other building blocks.The novelty of thiswork to design and test cloud storage using themeasurement of availability,downtime,and outage parameters.Results showed that the storage reliability in a hyper-converged system is above 92%.