UNASSIGNED: The COVID-19 pandemic has created challenges with respect to HIV care services. Remote online services might provide an effective method for health service delivery to people living with HIV (PLHIV). Few studies have focused on the efficacy of telemedical services for PLHIV and the effect of antiretroviral treatment via online services in China.
UNASSIGNED: We developed a platform called the \"No. 8 Health\" for online antiretroviral drug collection and delivery services in Beijing from January 21 to June 30, 2022. We evaluated the online treatment service according to viral load suppression rates and compared differences in social characteristics between PLHIV who received antiretroviral drugs through online or offline treatment services.
UNASSIGNED: By June 2022, 9528 PLHIV had received outpatient treatment services, among which 44.6% (4031/9528) used the online treatment and drug delivery services for a total of 5590 person-times. The satisfaction rate was 100%. Rates of viral load suppression among PLHIV who initiated antiretroviral therapy (ART) in 2020 and 2021 were 96.4% and 93.1%, respectively. Results showed that the viral load suppression rate was 97.9%. Regarding HIV rapid self-testing, 4513 men who have sex with men used the online HIV rapid testing service. The number of users was approximately the same as in 2021, but both were slightly lower than those in 2020.
UNASSIGNED: This study was the first to evaluate the effect of online drug collection and delivery services and virologic outcomes among PLHIV in China. The online service helped with maintenance of ART services, but the COVID-19 pandemic still had some impacts on viral load suppression.

Pyrazinamide plays an important role in the treatment of tuberculosis. However, the microbiological test for pyrazinamide resistance is more complex and less reliable than testing of susceptibility to other anti-tuberculosis drugs due to the need to grow the pathogen at pH 5.5. Identification of mutations that cause resistance to anti-tuberculosis drugs can replace microbiological methods. Mutations in the pncA gene are responsible for the main mechanism of the resistance to pyrazinamide and are found in more than 90% of resistant strains. However, the genetic method for determining drug susceptibility is very complex, because mutations leading to pyrazinamide resistance are diverse and scattered throughout the gene. We have developed a software package for automatic data interpretation and prediction of the resistance to pyrazinamide based on Sanger sequencing results. The effectiveness of detection of pyrazinamide resistance in 16 clinical samples was compared using the BACTEC MGIT 960 automated system and pncA gene Sanger sequencing with automated analysis of the results. A significant advantage of the developed method over a single microbiological study was shown, due to greater reliability of the results irrespective of the purity of isolates.

Length of stay (LOS) is an important metric for evaluating the management of inpatients. This study aimed to explore the factors impacting the LOS of inpatients with type-2 diabetes mellitus (T2DM) and develop a predictive model for the early identification of inpatients with prolonged LOS.
A 13-year multicenter retrospective study was conducted on 83,776 patients with T2DM to develop and validate a clinical predictive tool for prolonged LOS. Least absolute shrinkage and selection operator regression model and multivariable logistic regression analysis were adopted to build the risk model for prolonged LOS, and a nomogram was taken to visualize the model. Furthermore, receiver operating characteristic curves, calibration curves, and decision curve analysis and clinical impact curves were used to respectively validate the discrimination, calibration, and clinical applicability of the model.
The result showed that age, cerebral infarction, antihypertensive drug use, antiplatelet and anticoagulant use, past surgical history, past medical history, smoking, drinking, and neutrophil percentage-to-albumin ratio were closely related to the prolonged LOS. Area under the curve values of the nomogram in the training, internal validation, external validation set 1, and external validation set 2 were 0.803 (95% CI [confidence interval] 0.799-0.808), 0.794 (95% CI 0.788-0.800), 0.754 (95% CI 0.739-0.770), and 0.743 (95% CI 0.722-0.763), respectively. The calibration curves indicated that the nomogram had a strong calibration. Besides, decision curve analysis, and clinical impact curves exhibited that the nomogram had favorable clinical practical value. Besides, an online interface ( https://cytjt007.shinyapps.io/prolonged_los/ ) was developed to provide convenient access for users.
In sum, the proposed model could predict the possible prolonged LOS of inpatients with T2DM and help the clinicians to improve efficiency in bed management.

OBJECTIVE: This study identifies the impact of the absence of dental support for patients with cancer whose clinical dental care was interrupted by the coronavirus disease 2019 (COVID-19) pandemic.
METHODS: Individuals with oncologic diseases were selected from a telephone list of a Clinical Research Center (CRC) that specialized in the care of patients with cancer at the Bauru School of Dentistry, University of São Paulo (FOB/USP). The convenience sample comprised 280 patients (aged > 18 years) with a history of cancer that underwent dental treatment at the FOB/USP CRC in 2019 and did not receive care in 2020 owing to the pandemic. The participants completed a questionnaire sent via email or a text messaging application. Individuals receiving treatment or who were already treated for cancer were divided into two groups for data tabulation. Statistical analyses were performed using Fisher\'s and chi-square tests.
RESULTS: Of the 280 patients, 104 answered the questionnaire, and 75 (72.1%) were women. Among the women, 45 (60.0%) were receiving antineoplastic treatment, and 30 (40.0%) had already been treated. Among the men, 15 (51.7%) were receiving antineoplastic treatment, and 14 (48.3%) had already been treated. Regarding oral problems that arose during the pandemic, dental pain when eating hot or cold food or drinks (57.0%), muscle pain (53.8%), and difficulties when chewing (51.0%) were the most common reported among patients. Furthermore, most individuals reported not having received any type of remote dental follow-up, before being contacted by our team, which could contribute to reducing these oral problems.
CONCLUSIONS: It is impossible to say whether the absence of dental support in cancer patients during the coronavirus disease 2019 (COVID-19) pandemic had a negative impact on oral issue rates.

Metagenomic data sets from diverse environments have been growing rapidly. To ensure accessibility and reusability, tools that quickly and informatively correlate new microbiomes with existing ones are in demand. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes in the global metagenome data space based on the taxonomic or functional similarity of a whole microbiome to those in the database. MSE 2 consists of (i) a well-organized and regularly updated microbiome database that currently contains over 250,000 metagenomic shotgun and 16S rRNA gene amplicon samples associated with unified metadata collected from 798 studies, (ii) an enhanced search engine that enables real-time and fast (<0.5 s per query) searches against the entire database for best-matched microbiomes using overall taxonomic or functional profiles, and (iii) a Web-based graphical user interface for user-friendly searching, data browsing, and tutoring. MSE 2 is freely accessible via http://mse.ac.cn For standalone searches of customized microbiome databases, the kernel of the MSE 2 search engine is provided at GitHub (https://github.com/qibebt-bioinfo/meta-storms).IMPORTANCE A search-based strategy is useful for large-scale mining of microbiome data sets, such as a bird\'s-eye view of the microbiome data space and disease diagnosis via microbiome big data. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes against the existing microbiome data sets on the basis of their similarity in taxonomic structure or functional profile. Key improvements include database extension, data compatibility, a search engine kernel, and a user interface. The new ability to search the microbiome space via functional similarity greatly expands the scope of search-based mining of the microbiome big data.

Internet hospitals show great potential for adequately fulfilling people\'s demands for high-quality outpatient services, and with the normalization of the epidemic prevention and control of COVID-19, internet hospitals play an increasingly important role in delivering health services to the public. However, the factors that influence patients\' intention to use the online inquiry services provided by internet hospitals remain unclear. Understanding the patients\' behavioral intention is necessary to support the development of internet hospitals in China and promote patients\' intention to use online inquiry services provided by internet hospitals during the prevention and control of the COVID-19 epidemic.
The purpose of this study is to identify the determinants of patients\' intention to use the online inquiry services provided by internet hospitals based on the theory of planned behavior (TPB).
The hypotheses of our research model were developed based on the TPB. A questionnaire was developed through patient interviews, verified using a presurvey, and used for data collection for this study. The cluster sampling technique was used to include respondents with chronic diseases. Structural equation modeling was used to test the research hypotheses.
A total of 638 valid responses were received from patients with chronic diseases. The goodness-of-fit indexes corroborated that the research model was a good fit for the collected data. The model explained 45.9% of the variance in attitude toward the behavior and 60.5% of the variance in behavioral intention. Perceived behavioral control and perceived severity of disease had the strongest total effects on behavioral intention (β=.624, P=.004 and β=.544, P=.003, respectively). Moreover, perceived convenience, perceived information risk, emotional preference, and health consciousness had indirect effects on behavioral intention, and these effects were mediated by attitude toward the behavior. Among the four constructs, perceived convenience had the highest indirect effect on behavioral intention (β=.207; P=.001).
Perceived behavioral control and perceived severity of disease are the most important determinants of patients\' intention to use the online inquiry services provided by internet hospitals. Therefore, internet hospitals should further optimize the design of online service delivery and ensure a reasonable assembly of high-quality experts, which will benefit the promotion of patients\' adoption intention toward online inquiry services for health purposes. Perceived convenience, emotional preference, and perceived risks also have effects on behavioral intention. Therefore, the relevant quality control standards and regulations for internet hospitals should be further developed and improved, and the measures to protect personal information should be strengthened to ensure the patient safety. Our study supports the use of the TPB in explaining patients\' intention to use online inquiry services provided by internet hospitals.

Online health communities allow doctors to fully use existing medical resources to serve remote patients. They broaden and diversify avenues of interaction between doctors and patients using Internet technology, which have built an online medical consultation market. In this study, the theory of supply and demand was adopted to explore how market conditions of online doctor resources impact price premiums of doctors\' online service. Then, we investigated the effect of the stigmatized diseases. We used resource supply and resource concentration to characterize the market conditions of online doctor resources and a dummy variable to categorize whether the disease is stigmatized or ordinary. After an empirical study of the dataset (including 68,945 doctors), the results indicate that: (1) the supply of online doctor resources has a significant and negative influence on price premiums; (2) compared with ordinary diseases, doctors treating stigmatized diseases can charge higher price premiums; (3) stigmatized diseases positively moderate the relationship between resource supply and price premiums; and (4) the concentration of online doctor resources has no significant influence on price premiums. Our research demonstrates that both the market conditions of online doctor resources and stigmatized diseases can impact price premiums in the online medical consultation market. The findings provide some new and insightful implications for theory and practice.

UNASSIGNED: This study aimed to evaluate the satisfaction level of inquirers of an internet-based drug information centre along with the internet usage abilities and habits of individuals who had previously utilised services from an internet-based drug information centre in Turkey.
UNASSIGNED: The first 100 individuals who received medication consultancy from the webpage entitled \"www.ilacpedia.com\" and consented to participate in the study were included in this study. This website is an internet-based drug information centre. Participants\' data were collected using a participant data form and the Internet Self-efficacy Scale.
UNASSIGNED: The mean age of participants was 37.92 ± 12.32 years (71 female). It was found that 89% of the individuals who received pharmaceutical consultation from the internet-based drug information service believed that the information that they received was enough to solve their problem. The internet self-efficacy scale scores indicated the highest score on the decomposition subscale (20.94 ± 6.18) and the lowest on the communication subscale (9.77 ± 3.57).
UNASSIGNED: The present study revealed that the internet-based drug information service provided by clinical pharmacists contributed positively to users\' satisfaction, thus indicating the importance of the involvement of clinical pharmacists in this process.
UNASSIGNED: تهدف هذه الدراسة إلى تقييم خدمة الاستشارات العلاجية عبر الإنترنت، من حيث تأثيرها على رضا المتلقين ومهارات وعادات استخدام الإنترنت للأفراد الذين يستخدمون الإنترنت ويستفيدون من هذه الخدمة في تركيا.
UNASSIGNED: أجريت هذه الدراسة على أول ١٠٠ شخص وافق على المشاركة فيها ممن حصلوا على خدمة الاستشارات العلاجية عبر موقع \'www.ilacpedia.com‘، وهو موقع إلكتروني معلوماتي للعلاج والدواء قائم على الإنترنت، وتم تجميع المعلومات من خلال نماذج معطيات الأفراد التي ملأها المشاركون باستخدام مقياس الكفاءة الذاتية.
UNASSIGNED: متوسط عمر المشاركين هو ٣٧.٩٢± ١٢.٣٢(٧١ من النساء)، أظهرت النتائج أن ٨٩٪ من الأفراد الذين حصلوا على خدمة الاستشارات العلاجية عبر الإنترنت استفادوا من المعلومات التي تحصلوا عليها لحل مشاكلهم، ويشير مقياس الكفاءة الذاتية للإنترنت إلى أعلى درجة من مقياس التحلل (٢٠.٩٤± ٦.١٨) وأدنى درجة من جانب الاتصالات (٩.٧٧ ± ٣.٥٧).
UNASSIGNED: أظهرت النتائج أن خدمة الاستشارات العلاجية التي تقدم عبر الإنترنت عن طريق الصيادلة السريريين تؤثر إيجابا على مستوى رضا الأفراد، لذلك نؤمن بأهمية مشاركة الصيادلة السريريين في هذه المراحل.

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.