Treatment endpoints in ulcerative colitis:Does one size fit all?

A treat-to-target strategy in inflammatory bowel disease(IBD)involves treatment intensification in order to achieve a pre-determined endpoint.Such uniform and tight disease control has been demonstrated to improve clinical outcomes compared to treatment driven by a clinician’s subjective assessment of symptoms.However,choice of treatment endpoints remains a challenge in management of IBD via a treat-to-target strategy.The treatment endpoints for ulcerative colitis(UC),recommended by the Selecting Therapeutic Targets in Inflammatory Bowel Disease(STRIDE)consensus have changed somewhat over time.The latest STRIDE-II consensus advises immediate(clinical response),intermediate(clinical remission and biochemical normalisation)and long-term treatment(endoscopic healing,absence of disability and normalisation of health-related quality of life,as well as normal growth in children)endpoints in UC.However,achieving deeper levels of remission,such as histologic normalisation or healing of the gut barrier function,may further improve outcomes among UC patients.Generally,all medical therapy should seek to improve short-and long-term mortality and morbidity.Hence treatment endpoints should be chosen based on their ability to predict for improvement in short-and long-term mortality and morbidity.Potential benefits of treatment intensification need to be weighed against the potential harms within an individual patient.In addition,changing therapy that has achieved partial response may lead to worse outcomes,with failure to recapture response on treatment reversion.Patients may also place different emphasis on certain potential benefits and harms of various treatments than clinicians,or may have strong opinions re certain therapies.Potential benefits and harms of therapies,incremental benefits of achieving deeper levels of remission,as well as uncertainties of the same,need to be discussed with individual patients,and a treatment endpoint agreed upon with the clinician.Future research should focus on quantifying the incremental benefits and risks of achieving deeper levels of remission,such that clinicians and patients can make an informed decision about appropriate treatment end-point on an individual basis.focus on quantifying the incremental benefits and risks of achieving deeper levels of remission,such that clinicians and patients can make an informed decision about appropriate treatment end-point on an individual basis.

How Interlinks Influence Federated over SPARQL Endpoints

As the Web of Data grows, the number of available SPARQL endpoints increases. SPARQL endpoints conceptually represent RPC-style, coarse-grained data access mechanisms. Nevertheless, through the potential interlinking of the contained entities, SPARQL endpoints should be able to over distinct advantages over plain Web APIs. To our knowledge, to date, there has been no study conducted that gauges the impact of the link on SPARQL query execution, especially in a federated set-up. In this paper, we investigate how the existence and types of typed links influences the execution characteristics of different SPARQL federation frameworks. In order to measure the query performance, we propose a combined cost model based on a statistic analysis of the query performance metrics that involves parameters such as type of link, the data catalogues and cache, number of links, and number of distinct subjects. As result, we show that number of distinct subject and number of links have significant impact on Federation over SPARQL Endpoints performance whereas type of link does not have significantly influence in federation query performance.

Accurate Measurement Method for Tube's Endpoints Based on Machine Vision

Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube＇s endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube＇s endpoints based on machine vision is proposed. First, reflected light on tube＇s surface can be removed by using photometric linearization. Then, based on the optimization model for the tube＇s endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube＇s endpoint are obtained. To confirm the feasibility, ll tubes are processed to remove the reflected light and then the endpoint＇s positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 ram. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube＇s endpoints without any surface treatment or any tools and can realize on line measurement.

Opportunities and challenges of clinical trials in cardiology using composite primary endpoints

In clinical trials, the primary efficacy endpoint often corresponds to a so-called "composite endpoint". Composite endpoints combine several events of interest within a single outcome variable. Thereby it is intended to enlarge the expected effect size and thereby increase the power of the study. However, composite endpoints also come along with serious challenges and problems. On the one hand, composite endpoints may lead to difficulties during the planning phase of a trial with respect to the sample size calculation, asthe expected clinical effect of an intervention on the composite endpoint depends on the effects on its single components and their correlations. This may lead to wrong assumptions on the sample size needed. Too optimistic assumptions on the expected effect may lead to an underpowered of the trial, whereas a too conservatively estimated effect results in an unnecessarily high sample size. On the other hand, the interpretation of composite endpoints may be difficult, as the observed effect of the composite does not necessarily reflect the effects of the single components. Therefore the demonstration of the clinical efficacy of a new intervention by exclusively evaluating the composite endpoint may be misleading. The present paper summarizes results and recommendations of the latest research addressing the above mentioned problems in the planning, analysis and interpretation of clinical trials with composite endpoints, thereby providing a practical guidance for users.

Prediction of Critical Endpoints Based on the PR Equation of State

In the design of chemical processes,such as catalytic cracking of bitumen and heavy oil,the knowledge of phase behavior at the critical endpoint is essential.Based on the PR equation of state,the algorithm developed by Heidemann and Khalil for calculating critical properties was used to compute critical points.An algorithm for determining the equilibrium phase of the critical point using the tangent plane criterion was developed,and was used to calculate the critical endpoints of different mixtures,including non-polar,polar and associating systems.The critical endpoint,representing the type of the phase behavior,was employed to fit the interaction parameter of mixtures in critical state at high pressure.Lines of critical endpoints for ternary mixtures were also determined with the algorithm.

Cervical spinal cord injury: tailoring clinical trial endpoints to reflect meaningful functional improvements

Cervical spinal cord injury （SCI） results in partial to full paralysis of the upper and lower extrem- ities. Traditional primary endpoints for acute SCI clinical trials are too broad to assess functional recovery in cervical subjects, raising the possibility of false positive outcomes in trials for cervical SCI. Endpoints focused on the recovery of hand and arm control （e.g., upper extremity motor score, motor level change） show the most potential for use as primary outcomes in upcoming trials of cervical SCI. As the field moves forward, the most reliable way to ensure meaningful clinical testing in cervical subjects may be the development of a composite primary endpoint that measures both neurological recovery and functional improvement.

On the Use of Local Assessments for Monitoring Centrally Reviewed Endpoints with Missing Data in Clinical Trials

Due to ethical and logistical concerns it is common for data monitoring committees to periodically monitor accruing clinical trial data to assess the safety, and possibly efficacy, of a new experimental treatment. When formalized, monitoring is typically implemented using group sequential methods. In some cases regulatory agencies have required that primary trial analyses should be based solely on the judgment of an independent review committee (IRC). The IRC assessments can produce difficulties for trial monitoring given the time lag typically associated with receiving assessments from the IRC. This results in a missing data problem wherein a surrogate measure of response may provide useful information for interim decisions and future monitoring strategies. In this paper, we present statistical tools that are helpful for monitoring a group sequential clinical trial with missing IRC data. We illustrate the proposed methodology in the case of binary endpoints under various missingness mechanisms including missing completely at random assessments and when missingness depends on the IRC’s measurement.

Endpoints of Multi-Valued Weak Contractions on the Metric Space of Partially Ordered Groups

The present work considers the endpoint in the abstract metric space. It firstly introduces the metric space of partially ordered groups and the metric space of partially ordered modules, respectively;and defines the convergence of sequences and the multi-valued weak contractions, etc., on the introduced space. And then, with the methods of functional analysis and abstract algebra, it successively establishes an endpoint theorem for the metric space of partially ordered groups and an endpoint theorem for the metric space of partially ordered modules. The contributions of this article extend the theory of cone metric space constructed by Huang and Zhang (2007) and some recent results on the fixed point and endpoint theory, such as the endpoint theorem given by Amini-Harandi (2010).

Enlightenment and Reference of Vaccine Clinical Trial Design Based on Immunological Surrogate Endpoints in the United States

Objectives To explore the optimization method of vaccine clinical trial design based on immunological surrogate endpoint to improve the quality and efficiency of vaccine clinical research and development.Methods As to the problems in the vaccine clinical research in China,the relevant guidelines and literatures of FDA and WHO were used to analyze and summarize the methods of optimizing the design of vaccine clinical trials.Results and Conclusion The adaptive design guidelines are established to guide clinical trial design,encourage the development and application of immunological surrogate endpoints,establish qualification process for drug development tools and information disclosure procedures to improve vaccine development efficiency.

Clinical Benefits as Endpoints in Advanced Non-Small Cell Lung Cancer Treated with Integrative Medicine

＂Living with cancer＂ and symptom control are the features and advantages of integrative medicine in advanced non-small cell lung cancer （NSCLC） treatment. However, with the current concept of response evaluation criteria by the WHO and RECIST, it is difficult to exhibit the above characteristics. Clinical benefit （CB） is designed as an endpoint recently widely understood and accepted in oncology clinical trials. With the review of its definition and development, we suggest CB to be used as an endpoint in advanced NSCLC treatment with integrative medicine. CB should encompass two connotations： one is improved quality of life and symptom control and the other is disease control rate （DCR）, including complete response （CR）, partial response （PR）, and stable disease （SD）. We need to design randomized controlled trials （RCT） to investigate the interrelationship of CB rate and survival to provide high-grade evidence proving that advanced lung cancer patients could really benefit from integrative medicine treatment.

Development of drugs for celiac disease:review of endpoints for Phase 2 and 3 trials

Celiac disease is a lifelong disorder for which there is currently only one known,effective treatment:a gluten-free diet.New treatment approaches have recently emerged;several drugs are in Phase 2 trials and results appear promising;however,discussion around regulatory endpoints is in its infancy.We will briefly discuss the drugs that are under development and then shift our attention to potential trial endpoints,such as patient-reported outcomes,histology,serology,gene expression analysis and other tests.We will outline the differing requirements for proof-of-concept Phase 2 trials and Phase 3 registration trials,with a particular emphasis on current thinking in regulatory agencies.We conclude our paper with recommendations and a glossary of regulatory terms,to enable readers who are less familiar with regulatory language to take maximum advantage of this review.

Risk assessment model for endpoints of ischemic stroke: A study protocol for a registry study

OBJECTIVE: To evaluate the risk of ischemic stroke endpoints by establishing risk assessment models that combine Traditional Chinese Medicine(TCM)and modern medicine indicators.METHODS/DESIGN: The proposed study is a registry-based participant survey conducted in seven hospitals nationwide in China. After obtaining informed consent, 3000 patients diagnosed with ischemic stroke will be recruited. One-year follow-ups will be performed on-site in hospitals and by telephone to track endpoint events. Comparative analysis of the prevalence of endpoint events and other TCM or modern medicine features in different groups will be conducted using frequency analysis and χ2tests, and the results will be expressed as composition ratios. Comparative analysis of quantitative scores and related patterns or symptoms will be conducted using a rank-sum test. Correlation analysis of endpoint events and TCM or modern medicine factors will be performed using a multivariate Cox proportional hazard model.DISCUSSION: Previous reports have described modern medicine indicator-based risk assessment models for ischemic stroke endpoint events, but no such studies have included TCM features. Our new risk assessment model combines TCM and modern medicine indicators and thus has the potential to facilitate early warning, early intervention, and early control of ischemic stroke endpoint events.

Immunological surrogate endpoints of COVID-2019 vaccines:the evidence we have versus the evidence we need

lIn response to the severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)pandemic,over 200 vaccine candidates againstcoronavirus disease 2019(COVID-2019)are under development and currently moving forward at an unparalleled speed.Theavailability of surrogate endpoints would help to avoid large-scale filed efficacy trials and facilitate the approval of vaccine candidates,which is crucial to control COVID-19 pandemic.Several phase 3 efficacy trials of COVID-19 vaccine candidates are underway,which provide opportunities for the determination of COVID-19 correlates of protection.In this paper,we review currentknowledge for existence of COVD-19 correlates of protection,methods for assessment of immune correlates of protection andissues related to COVID-19 correlates of protection.

Systematic analysis and modeling of the FLASH sparing effect as a function of dose and dose rate

Ultrahigh-dose-rate radiotherapy(FLASH-RT)is a revolutionary radiotherapy technology that can spare normal tissues without compromising tumor control.Although qualitative experimental results have been reported,quantitative and systematic analysis of data is necessary.Particularly,the FLASH effect response model to the dose or dose rate is still unclear.This study investigated the relationships between the FLASH effect and experimental parameters,such as dose,dose rate,and other factors by analyzing published in vivo experimental data from animal models.The data were modeled based on logistic regression analysis using the sigmoid function.The model was evaluated using prediction accuracy,receiver operating characteristic(ROC)curve,and area under the ROC curve.Results showed that the FLASH effect was closely related to the dose,mean dose rate,tissue type,and corresponding biological endpoints.The dose rate corresponding to a 50% probability of triggering cognitive protection in the brain was 45 Gy s^(-1).The dose rate corresponding to a 50% probability of triggering intestinal crypt survival and regeneration was 140 Gy s^(-1).For the skin toxicity effect,the dose corresponding to a 50% probability of triggering the FLASH effect was 24 Gy.This study helps to characterize the conditions underlying the FLASH effect and provides important information for optimizing experiments.

Patient-centric periodontal research:A pioneering application of patient-reported outcome measures

Conventional dentistry or periodontal research often ignores the human component in favor of clinical outcomes and biological causes.Clinical research is driven by the statistical significance of outcome parameters rather than the satisfaction level of the patient.In this context,patient-centric periodontal research(PCPR)is an approach that considers the patient´s feedback concerning their functional status,experience,clinical outcomes,and accessibility to their treatments.It is argued that data self-reported by the patient might have low reliability owing to the confounding effect of their personal belief,cultural background,and social and economic factors.However,literature has shown that the incorporation of“patient-centric outcome”components considerably enhances the validity and applicability of research findings.Variations in the results of different studies might be due to the use of different and non-standardized assessment tools.To overcome this problem,this editorial enlists various reliable tools available in the literature.In conclusion,we advocate that the focus of researchers should shift from mere periodontal research to PCPR so that the results can be effectively applied in clinical settings and the therapeutic strategy can also change from mere periodontal therapy to patient-centric periodontal therapy.

Clinical/Behavioral Monitoring of Rodents and Rabbits Undergoing Scientific Experiments

Background: We currently have international and national guidelines regarding the assessment and monitoring of clinical signs and humane endpoints in animals used in teaching and research, which make the performance of these activities mandatory for any experiment and professional working in this area. Assigning the severity of a research experiment is the result of an analysis of records of observations of the animal’s behavior, and clinical signs. The aim of this study was to describe the importance of carrying out a severity assessment associated with clinical and behavioral monitoring of rodents and rabbits during experimentation to maintain the welfare of these animals undergoing scientific research. Methods: The literature search was carried out using the following terms: “Monitoring”;“Humane endpoints”;“Animal welfare”, “Rodents”;“Rabbits”, and as connectors “and”;“or”, in the following databases: PubMed;LILACS/BIREME and SciELO. Results: A total of 987 articles were identified in the databases, and 20 of these studies were included in this review. Conclusions: Humane endpoint protocols and procedure severity tables are of the utmost importance, both from an ethical point and to refine the results of research conducted on laboratory animals. They should be drawn up jointly by the teams responsible for the project and the maintenance of the animals during the research period, and the data obtained should be published so that the scientific community can have access to it, helping to disseminate these practices, as well as helping to draw up new procedures. Monitoring and evaluating the welfare and clinical condition of animals undergoing scientific research procedures is the responsibility of the professors, researchers, veterinarians, and animal facility coordinators. The Ethics Committee on the Use of Animals must monitor all the activities conducted with the animals, by inspecting the experimental procedures and the physical environment of the laboratory animal facility where the animals are housed.

Multi-Binary Classifiers Using Optimal Feature Selection for Memory-Saving Intrusion Detection Systems

With the rise of remote work and the digital industry,advanced cyberattacks have become more diverse and complex in terms of attack types and characteristics,rendering them difficult to detect with conventional intrusion detection methods.Signature-based intrusion detection methods can be used to detect attacks;however,they cannot detect new malware.Endpoint detection and response(EDR)tools are attracting attention as a means of detecting attacks on endpoints in real-time to overcome the limitations of signature-based intrusion detection techniques.However,EDR tools are restricted by the continuous generation of unnecessary logs,resulting in poor detection performance and memory efficiency.Machine learning-based intrusion detection techniques for responding to advanced cyberattacks are memory intensive,using numerous features;they lack optimal feature selection for each attack type.To overcome these limitations,this study proposes a memory-efficient intrusion detection approach incorporating multi-binary classifiers using optimal feature selection.The proposed model detects multiple types of malicious attacks using parallel binary classifiers with optimal features for each attack type.The experimental results showed a 2.95%accuracy improvement and an 88.05%memory reduction using only six features compared to a model with 18 features.Furthermore,compared to a conventional multi-classification model with simple feature selection based on permutation importance,the accuracy improved by 11.67%and the memory usage decreased by 44.87%.The proposed scheme demonstrates that effective intrusion detection is achievable with minimal features,making it suitable for memory-limited mobile and Internet of Things devices.

Reverse Analysis Method and Process for Improving Malware Detection Based on XAI Model

With the advancements in artificial intelligence(AI)technology,attackers are increasingly using sophisticated techniques,including ChatGPT.Endpoint Detection&Response(EDR)is a system that detects and responds to strange activities or security threats occurring on computers or endpoint devices within an organization.Unlike traditional antivirus software,EDR is more about responding to a threat after it has already occurred than blocking it.This study aims to overcome challenges in security control,such as increased log size,emerging security threats,and technical demands faced by control staff.Previous studies have focused on AI detection models,emphasizing detection rates and model performance.However,the underlying reasons behind the detection results were often insufficiently understood,leading to varying outcomes based on the learning model.Additionally,the presence of both structured or unstructured logs,the growth in new security threats,and increasing technical disparities among control staff members pose further challenges for effective security control.This study proposed to improve the problems of the existing EDR system and overcome the limitations of security control.This study analyzed data during the preprocessing stage to identify potential threat factors that influence the detection process and its outcomes.Additionally,eleven commonly-used machine learning(ML)models for malware detection in XAI were tested,with the five models showing the highest performance selected for further analysis.Explainable AI(XAI)techniques are employed to assess the impact of preprocessing on the learning process outcomes.To ensure objectivity and versatility in the analysis,five widely recognized datasets were used.Additionally,eleven commonly-used machine learning models for malware detection in XAI were tested with the five models showing the highest performance selected for further analysis.The results indicate that eXtreme Gradient Boosting(XGBoost)model outperformed others.Moreover,the study conducts an in-depth analysis of the preprocessing phase,tracing backward from the detection result to infer potential threats and classify the primary variables influencing the model’s prediction.This analysis includes the application of SHapley Additive exPlanations(SHAP),an XAI result,which provides insight into the influence of specific features on detection outcomes,and suggests potential breaches by identifying common parameters in malware through file backtracking and providing weights.This study also proposed a counter-detection analysis process to overcome the limitations of existing Deep Learning outcomes,understand the decision-making process of AI,and enhance reliability.These contributions are expected to significantly enhance EDR systems and address existing limitations in security control.

嵌入式USB从设备驱动程序设计

本文通过基于S3C2410的嵌入式USB从设备驱动程序的实现,介绍嵌入式Linux系统中的USB从设备驱动程序的设计方法,同时介绍了USB接口的一般原理和USB通信的一般过程,以及嵌入式Linux中驱动程序开发的一般原理和方法。

Combination antiretroviral studies for patients with primary biliary cirrhosis

Following the characterization of a human betaretrovirus in patients with primary biliary cirrhosis(PBC),pilot studies using antiretroviral therapy have been conducted as proof of principal to establish a link of virus with disease and with the eventual aim to find better adjunct therapies for patients unresponsive to ursodeoxycholic acid.In the first open label pilot study,the reverse transcriptase inhibitor lamivudine had little demonstrable biochemical or histological effect after 1 year.Whereas,lamivudine in combination with zidovudine was associated with a significant reduction in alkaline phosphatase as well as improvement in necroinflammatory score,cholangitis and ductopenia over a 12 mo period.A double blind,multi-center randomized controlled trial using lamivudine with zidovudine for 6 mo confirmed a significant reduction in alkaline phosphatase,ALT and AST in patients on antiviral therapy.However,none of the patients achieved the stringent endpoint criteria for normalization of alkaline phosphatase.Furthermore,some patients developed biochemical rebound consistent with drug resistance.A major fault of these studies has been the inability to measure the viral load in peripheral blood and therefore,provide a direct correlation between improvement of hepatic biochemistry and reduction in viral load.Nevertheless,viral mutants to lamivudine with zidovudine were later characterized in the NOD.c3c4 mouse model of PBC that has been used to test other antiretroviral regimens to betaretrovirus.The combination of tenofovir and emtricitabine reverse transcriptase inhibitors and the HIV protease inhibitor,lopinavir were found to abrogate cholangitis in the NOD.c3c4 mouse model and the same regimen normalized the liver tests in a PBC patient with HIV and human betaretrovirus infection.This combination antiretroviral therapy has now been used in a double blind randomized controlled crossover study for patients with PBC followed by an open label extension study.Only a third of the PBC patients were able to tolerate the lopinavir but those maintained on tenofovir,emtricitabine and lopinavir experienced sustained and clinically meaningful reduction in hepatic biochemistry.While we await the histological and virological evaluation,it is clear that better tolerated regimens of antiretroviral treatment will be required in future clinical trials.