Proteogenomics has revealed the translation of unannotated open reading frames (ORFs) present in mRNAs and in noncoding RNAs (ncRNAs). OpenProt annotates all ORFs with a minimum of 30 codons in the transcriptome of several species and displays many functional features associated with the corresponding proteins. Two types of proteins are annotated: reference or canonical proteins which are proteins already annotated in UniProt, RefSeq, or Ensembl and noncanonical proteins. Noncanonical proteins form two groups: predicted novel isoforms that display a significant level of homology with a reference protein and alternative proteins that are new proteins with no significant homology to known proteins. This chapter describes how to check whether a gene and/or transcript contains multiple open reading frames and how to use OpenProt databases for the detection of alternative proteins and novel isoforms by mass spectrometry-based proteomics.

In the process of oxygen reduction, reactive oxygen species (ROS) are generated as intermediates, including superoxide anion (O2-), hydrogen peroxide (H2O2), and hydroxyl radicals (OH-). ROS can be destructive, and an imbalance between oxidants and antioxidants in the body can lead to pathological inflammation. Inappropriate ROS production can cause oxidative damage, disrupting the balance in the body and potentially leading to DNA damage in intestinal epithelial cells and beneficial bacteria. Microorganisms have evolved various enzymes to mitigate the harmful effects of ROS. Accurately predicting the types of ROS-scavenging enzymes (ROSes) is crucial for understanding the oxidative stress mechanisms and formulating strategies to combat diseases related to the \"gut-organ axis.\" Currently, there are no available ROSes databases (DBs). In this study, we propose a systematic workflow comprising three modules and employ a hierarchical multi-task deep learning approach to collect, expand, and explore ROSes-related entries. Based on this, we have developed the human gut microbiota ROSes DB (http://39.101.72.186/), which includes 7,689 entries. This DB provides user-friendly browsing and search features to support various applications. With the assistance of ROSes DB, various communication-based microbial interactions can be explored, further enabling the construction and analysis of the evolutionary and complex networks of ROSes DB in human gut microbiota species.IMPORTANCEReactive oxygen species (ROS) is generated during the process of oxygen reduction, including superoxide anion, hydrogen peroxide, and hydroxyl radicals. ROS can potentially cause damage to cells and DNA, leading to pathological inflammation within the body. Microorganisms have evolved various enzymes to mitigate the harmful effects of ROS, thereby maintaining a balance of microorganisms within the host. The study highlights the current absence of a ROSes DB, emphasizing the crucial importance of accurately predicting the types of ROSes for understanding oxidative stress mechanisms and developing strategies for diseases related to the \"gut-organ axis.\" This research proposes a systematic workflow and employs a multi-task deep learning approach to establish the human gut microbiota ROSes DB. This DB comprises 7,689 entries and serves as a valuable tool for researchers to delve into the role of ROSes in the human gut microbiota.

BACKGROUND: The COVID-19 pandemic led to several surges in the mass hospitalization rate. Extreme increases in hospital admissions without adequate medical resources may increase mortality. No study has addressed the impact of daily census of ventilated patients on mortality in the context of the pandemic in a nationwide setting.
OBJECTIVE: This study aimed to determine whether daily census of ventilated patients affected COVID-19 mortality rates nationwide in Israel.
METHODS: We conducted a cohort study using nationwide, public-domain, population-based COVID-19 data of hospitalized patients from an Israeli database from March 11, 2020, until February 11, 2021. We included all COVID-19 hospital admissions, classified as mild to severe per the Centers for Diseases Control and Prevention classification irrespective of whether they were mechanically ventilated. Outcome measures were daily death rates and death rates expressed as a percentage of ventilated patients.
RESULTS: During the study period (338 days from March 11, 2020, to February 11, 2021), 715,743 patients contracted and were clinically confirmed as having COVID-19. Among them, 5577 (0.78%) patients died. In total, 3398 patients were ventilated because of severe COVID-19. Daily mortality correlated with daily census of ventilated patients (R2=0.828, P<.001). The daily percent mortality of ventilated patients also correlated with the daily census of ventilated patients (R2=0.365, P<.001)-backward multiple regression analysis demonstrated that this positive correlation was still highly significant even when correcting for the average age or gender of ventilated patients (R2=0.4328, P<.001) or for the surge in their number. Overall, 40% of the variation in mortality was explained by variations in the daily census of ventilated patients. ANOVA revealed that at less than 50 ventilated patients per day, the daily mortality of ventilated patients was slightly above 5%, and it nearly doubled (10%) with 50-149 patients; moreover, in all categories of ≥200 patients ventilated per day, it more than tripled at ≥15% (P<.001).
CONCLUSIONS: Daily mortality rates per ventilated patient increased with an increase in the number of ventilated patients, suggesting the saturation of medical resources. Policy makers should be aware that expanding medical services without adequate resources may increase mortality. Governments should perform similar analyses to provide indicators of system saturation, although further validation of these results might be needed to use this indicator to drive public policy.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are a class of widely used anthropogenic chemicals. Concerns regarding their persistence and potential adverse effects have led to multiple secondary research publications. Here, we aim to assess the resulting evidence base in the systematic secondary literature by examining research gaps, evaluating the quality of reviews, and exploring interdisciplinary connections.
METHODS: This study employed a systematic evidence-mapping approach to assess the secondary literature on the biological, environmental, and medical aspects of exposure to 35 fluorinated compounds. The inclusion criteria encompassed systematic reviews published in peer-reviewed journals, pre-prints, and theses. Comprehensive searches across electronic databases and grey literature identified relevant reviews. Data extraction and synthesis involved mapping literature content and narrative descriptions. We employed a modified version of the AMSTAR2 checklist to evaluate the methodological rigour of the reviews. A bibliometric data analysis uncovered patterns and trends in the academic literature. A research protocol for this study was previously pre-registered (osf.io/2tpn8) and published (Vendl et al., Environment International 158 (2022) 106973). The database is freely accessible through the interactive and user-friendly web application of this systematic evidence map at https://hi-this-is-lorenzo.shinyapps.io/PFAS_SEM_Shiny_App/.
RESULTS: Our map includes a total of 175 systematic reviews. Over the years, there has been a steady increase in the annual number of publications, with a notable surge in 2021. Most reviews focused on human exposure, whereas environmental and animal-related reviews were fewer and often lacked a rigorous systematic approach to literature search and screening. Review outcomes were predominantly associated with human health, particularly with reproductive and children\'s developmental health. Animal reviews primarily focused on studies conducted in controlled laboratory settings, and wildlife reviews were characterised by an over-representation of birds and fish species. Recent reviews increasingly incorporated quantitative synthesis methodologies. The methodological strengths of the reviews included detailed descriptions of study selection processes and disclosure of potential conflicts of interest. However, weaknesses were observed in the critical lack of detail in reporting methods. A bibliometric analysis revealed that the most productive authors collaborate within their own country, leading to limited and clustered international collaborations.
CONCLUSIONS: In this overview of the available systematic secondary literature, we map literature content, assess reviews\' methodological quality, highlight data gaps, and draw research network clusters. We aim to facilitate literature reviews, guide future research initiatives, and enhance opportunities for cross-country collaboration. Furthermore, we discuss how this systematic evidence map and its publicly available database benefit scientists, regulatory agencies, and other stakeholders by providing access to current systematic secondary literature on PFAS exposure.

Organogenesis, the phase of embryonic development that starts at the end of gastrulation and continues until birth is the critical process for understanding cellular differentiation and maturation during organ development. The rapid development of single-cell transcriptomics technology has led to many novel discoveries in understanding organogenesis while also accumulating a large quantity of data. To fill this gap, OrganogenesisDB (http://organogenesisdb.com/), which is a comprehensive database dedicated to exploring cell-type identification and gene expression dynamics during organogenesis, is developed. OrganogenesisDB contains single-cell RNA sequencing data for more than 1.4 million cells from 49 published datasets spanning various developmental stages. Additionally, 3324 cell markers are manually curated for 1120 cell types across 9 human organs and 4 mouse organs. OrganogenesisDB leverages various analysis tools to assist users in annotating and understanding cell types at different developmental stages and helps in mining and presenting genes that exhibit specific patterns and play key regulatory roles during cell maturation and differentiation. This work provides a critical resource and useful tool for deciphering cell lineage determination and uncovering the mechanisms underlying organogenesis.

Microorganisms are closely associated with human diseases and health. Understanding the composition and function of microbial communities requires extensive research. Metaproteomics has recently become an important method for throughout and in-depth study of microorganisms. However, major challenges in terms of sample processing, mass spectrometric data acquisition, and data analysis limit the development of metaproteomics owing to the complexity and high heterogeneity of microbial community samples. In metaproteomic analysis, optimizing the preprocessing method for different types of samples and adopting different microbial isolation, enrichment, extraction, and lysis schemes are often necessary. Similar to those for single-species proteomics, the mass spectrometric data acquisition modes for metaproteomics include data-dependent acquisition (DDA) and data-independent acquisition (DIA). DIA can collect comprehensive peptide information from a sample and holds great potential for future development. However, data analysis for DIA is challenged by the complexity of metaproteome samples, which hinders the deeper coverage of metaproteomes. The most important step in data analysis is the construction of a protein sequence database. The size and completeness of the database strongly influence not only the number of identifications, but also analyses at the species and functional levels. The current gold standard for metaproteome database construction is the metagenomic sequencing-based protein sequence database. A public database-filtering method based on an iterative database search has been proven to have strong practical value. The peptide-centric DIA data analysis method is a mainstream data analysis strategy. The development of deep learning and artificial intelligence will greatly promote the accuracy, coverage, and speed of metaproteomic analysis. In terms of downstream bioinformatics analysis, a series of annotation tools that can perform species annotation at the protein, peptide, and gene levels has been developed in recent years to determine the composition of microbial communities. The functional analysis of microbial communities is a unique feature of metaproteomics compared with other omics approaches. Metaproteomics has become an important component of the multi-omics analysis of microbial communities, and has great development potential in terms of depth of coverage, sensitivity of detection, and completeness of data analysis.

UNASSIGNED: Scabies is the second most common cause of disability among skin diseases in the Philippines as of 2019. There is no large nationwide study describing the epidemiologic profile of scabies in the country.
UNASSIGNED: This study aimed to describe the demographic, seasonal, and geographic profile of scabies in the Philippines.
UNASSIGNED: We compared secondary data of two local patient registries (Philippine Dermatological Society, PDS, 2010 to 2021; and Philippine Pediatric Society, PPS, 2009 to 2021) for reported cases of scabies in the Philippines. We reported the frequency and percentage distribution according to age, sex, month, year, and type of diagnosis, and region.
UNASSIGNED: The median annual frequency of scabies cases (mostly outpatient) for PDS (from year 2010) was 4087 (range ([QR], 342-6422 [3271.5]), while it was 183 (range [IQR], 64-234 [96.5]) (all inpatient) for PPS (from year 2009). There was a reduction to one-third (PDS) and one-fourth (PPS) of pre-pandemic numbers during the pandemic years (2020-2021). The peak months for scabies cases were the cooler months: January (median, 12.1% of annual cases; range [IQR], 2.6%-31.4% [3.6%]) to February (median, 10.0% of annual cases; range [IQR], 1.5%-27.8% [2.5%]) based on PDS data, and November (median, 10.0% of annual cases; range [IQR], 0.0%-24.3% [7.0%]) to January (median, 9.0% of annual cases; range [IQR], 0.0%-24.3% [6.6%]) for PPS data. Overall, for PDS, age 1-4 years is the most affected age group (median, PDS, 17.5% of annual cases; range [IQR], 11.9%-25.4% [8.1%]), while it was the less than 1-year-olds (median annual cases, 48.9%; range [IQR], 29.1%-67.3% [13.20%]) among PPS pediatric population aged 0 to 18 years. Males (median, 53.9% of annual cases; range [IQR], 45.0%-67.2% [8.8%]) were more affected than females in PPS. While for PDS during earlier years (prior to 2015), males (median, 51.6% of annual cases from 2010 to 2014; range [IQR], 47.4%-52.9% [0.2%]) were more affected than females. However, males became less affected than females with median, 44.7% of annual cases from 2015 onwards (range [IQR], 43.4%-46.5% [1.2%]). NCR was the region with the highest frequency of cases in PPS (median, 52.6% of annual cases; range [IQR], 22.7%-75.0% [20.4%]). The 2nd most affected regions were Central/Eastern Visayas (34.2%, 2009-2013; range [IQR], 17.9%-54.1% [5.3%]), Bicol region (12%; 2014 to 2018; range [IQR], 17.9%-54.1% [7.4%]), Central Luzon (18%; 2019), Central/Eastern Visayas (29%, 2020), and Northern/Central Mindanao (17%, 2021).
UNASSIGNED: Scabies was commonly seen in the younger age group, slightly more in females in the PDS, while slightly more among males in the PPS, in the cooler months of the year, and in the urbanized NCR.

Some herbal extracts contain relatively high amounts of lipopolysaccharide (LPS). Because orally administered LPS activates innate immunity without inducing inflammation, it plays a role as an active ingredient in herbal extracts. However, the LPS content in herbal extracts remains extensively unevaluated. This study aimed to create a database of LPS content in herbal extracts; therefore, the LPS content of 414 herbal extracts was measured and the macrophage activation potential was evaluated. The LPS content of these hot water extracts was determined using the kinetic-turbidimetric method. The LPS concentration ranged from a few ng/g to hundreds of μg/g (Standard Escherichia coli LPS equivalent). Twelve samples had a high-LPS-content of > 100 μg/g, including seven samples from roots and three samples from leaves of the herbal extracts. These samples showed high phagocytosis and NO production capacity, and further investigation using polymyxin B, an LPS inhibitor, significantly inhibited macrophage activation. This study suggests that some herbal extracts contain sufficient LPS concentration to activate innate immunity. Therefore, a new approach to evaluate the efficacy of herbal extracts based on their LPS content was proposed. A database listing the LPS content of different herbal extracts is essential for this approach.

BACKGROUND: Heart disease remains the leading cause of death in the United States, while chronic lower respiratory diseases (CLRD) are the sixth leading cause of death. Patients with CLRD have been shown to have an elevated risk of heart disease death. However, less is known regarding how this risk varies across demographic groups.
METHODS: We used the Multiple Cause of Death database from the Centers for Disease Control Wide-ranging ONline Data for Epidemiologic Research to obtain 1999-2020 information on deaths with heart disease as a primary cause of death and CLRD as a contributing cause. We calculated age-adjusted mortality rates (AAMR) over time and for demographic subgroups.
RESULTS: During 1999-2020, there were 1,178,048 heart disease deaths related to CLRD among people aged 45+. The AAMR for CLRD-associated heart disease deaths was 45.713 per 100,000 people. AAMR was highest among those aged 65+ (108.56 per 100,000). Elevated rates were seen among males (AAMR ratio = 1.744, 95% CI: 1.741-1.748), people living in the Midwest (AAMR ratio = 1.196, 95% CI: 1.190-1.202), and among people in rural areas (AAMR ratio = 1.309, 95% CI: 1.304-1.313) compared to their corresponding counterparts. Between 1999 and 2004 and 2016-2020 rates decreased among all demographic subgroups, except for among people aged 45-64, among whom deaths increased (AAMR ratio = 1.016, 95% CI: 1.003-1.030).
CONCLUSIONS: Rates of CLRD-associated heart disease deaths have declined over time, but significant disparities remain. Enhanced interventions particularly among older people (65+), people living in rural areas, people living in the Midwest, and men may reduce CLRD-associated heart disease deaths in the United States.

Due to the similarity and diversity among kinases, small molecule kinase inhibitors (SMKIs) often display multi-target effects or selectivity, which have a strong correlation with the efficacy and safety of these inhibitors. However, due to the limited number of well-known popular databases and their restricted data mining capabilities, along with the significant scarcity of databases focusing on the pharmacological similarity and diversity of SMIKIs, researchers find it challenging to quickly access relevant information. The KLIFS database is representative of specialized application databases in the field, focusing on kinase structure and co-crystallised kinase-ligand interactions, whereas the KLSD database in this paper emphasizes the analysis of SMKIs among all reported kinase targets. To solve the current problem of the lack of professional application databases in kinase research and to provide centralized, standardized, reliable and efficient data resources for kinase researchers, this paper proposes a research program based on the ChEMBL database. It focuses on kinase ligands activities comparisons. This scheme extracts kinase data and standardizes and normalizes them, then performs kinase target difference analysis to achieve kinase activity threshold judgement. It then constructs a specialized and personalized kinase database platform, adopts the front-end and back-end separation technology of SpringBoot architecture, constructs an extensible WEB application, handles the storage, retrieval and analysis of the data, ultimately realizing data visualization and interaction. This study aims to develop a kinase database platform to collect, organize, and provide standardized data related to kinases. By offering essential resources and tools, it supports kinase research and drug development, thereby advancing scientific research and innovation in kinase-related fields. It is freely accessible at: http://ai.njucm.edu.cn:8080.