FERREG: ferroptosis-based regulation of disease occurrence, progression and therapeutic response.

Ferroptosis is a non-apoptotic, iron-dependent regulatory form of cell death characterized by the accumulation of intracellular reactive oxygen species. In recent years, a large and growing body of literature has investigated ferroptosis. Since ferroptosis is associated with various physiological activities and regulated by a variety of cellular metabolism and mitochondrial activity, ferroptosis has been closely related to the occurrence and development of many diseases, including cancer, aging, neurodegenerative diseases, ischemia-reperfusion injury and other pathological cell death. The regulation of ferroptosis mainly focuses on three pathways: system Xc-/GPX4 axis, lipid peroxidation and iron metabolism. The genes involved in these processes were divided into driver, suppressor and marker. Importantly, small molecules or drugs that mediate the expression of these genes are often good treatments in the clinic. Herein, a newly developed database, named 'FERREG', is documented to (i) providing the data of ferroptosis-related regulation of diseases occurrence, progression and drug response; (ii) explicitly describing the molecular mechanisms underlying each regulation; and (iii) fully referencing the collected data by cross-linking them to available databases. Collectively, FERREG contains 51 targets, 718 regulators, 445 ferroptosis-related drugs and 158 ferroptosis-related disease responses. FERREG can be accessed at https://idrblab.org/ferreg/.

PROSCA: an online platform for humanized scaffold mining facilitating rational protein engineering.

Protein scaffolds with small size, high stability and low immunogenicity show important applications in the field of protein engineering and design. However, no relevant computational platform has been reported yet to mining such scaffolds with the desired properties from massive protein structures in human body. Here, we developed PROSCA, a structure-based online platform dedicated to explore the space of the entire human proteome, and to discovery new privileged protein scaffolds with potential engineering value that have never been noticed. PROSCA accepts structure of protein as an input, which can be subsequently aligned with a certain class of protein structures (e.g. the human proteome either from experientially resolved or AlphaFold2 predicted structures, and the human proteins belonging to specific families or domains), and outputs humanized protein scaffolds which are structurally similar with the input protein as well as other related important information such as families, sequences, structures and expression level in human tissues. Through PROSCA, the user can also get excellent experience in visualizations of protein structures and expression overviews, and download the figures and tables of results which can be customized according to the user's needs. Along with the advanced protein engineering and selection technologies, PROSCA will facilitate the rational design of new functional proteins with privileged scaffolds. PROSCA is freely available at https://idrblab.org/prosca/.

IL-6 Up-Regulates Expression of LIM-Domain Only Protein 4 in Psoriatic Keratinocytes through Activation of the MEK/ERK/NF-κB Pathway.

Psoriasis is a chronic inflammatory skin disease characterized by the activation of keratinocytes and the infiltration of immune cells. Overexpression of the transcription factor LIM-domain only protein 4 (LMO4) promoted by IL-23 has critical roles in regulating the proliferation and differentiation of psoriatic keratinocytes. IL-6, an autocrine cytokine in psoriatic epidermis, is a key mediator of IL-23/T helper 17-driven cutaneous inflammation. However, little is known about how IL-6 regulates the up-regulation of LMO4 expression in psoriatic lesions. In this study, human immortalized keratinocyte cells, clinical biopsy specimens, and an animal model of psoriasis induced by imiquimod cream were used to investigate the role of IL-6 in the regulation of keratinocyte proliferation and differentiation. Psoriatic epidermis showed abnormal expression of IL-6 and LMO4. IL-6 up-regulated the expression of LMO4 and promoted keratinocyte proliferation and differentiation. Furthermore, in vitro and in vivo studies showed that IL-6 up-regulates LMO4 expression by activating the mitogen-activated extracellular signal-regulated kinase (MEK)/extracellular signal-regulated kinase (ERK)/NF-κB signaling pathway. These results suggest that IL-6 can activate the NF-κB signaling pathway, up-regulate the expression of LMO4, lead to abnormal proliferation and differentiation of keratinocytes, and promote the occurrence and development of psoriasis.

SingPro: a knowledge base providing single-cell proteomic data.

Single-cell proteomics (SCP) has emerged as a powerful tool for detecting cellular heterogeneity, offering unprecedented insights into biological mechanisms that are masked in bulk cell populations. With the rapid advancements in AI-based time trajectory analysis and cell subpopulation identification, there exists a pressing need for a database that not only provides SCP raw data but also explicitly describes experimental details and protein expression profiles. However, no such database has been available yet. In this study, a database, entitled 'SingPro', specializing in single-cell proteomics was thus developed. It was unique in (a) systematically providing the SCP raw data for both mass spectrometry-based and flow cytometry-based studies and (b) explicitly describing experimental detail for SCP study and expression profile of any studied protein. Anticipating a robust interest from the research community, this database is poised to become an invaluable repository for OMICs-based biomedical studies. Access to SingPro is unrestricted and does not mandate a login at: http://idrblab.org/singpro/.

TheMarker: a comprehensive database of therapeutic biomarkers.

Distinct from the traditional diagnostic/prognostic biomarker (adopted as the indicator of disease state/process), the therapeutic biomarker (ThMAR) has emerged to be very crucial in the clinical development and clinical practice of all therapies. There are five types of ThMAR that have been found to play indispensable roles in various stages of drug discovery, such as: Pharmacodynamic Biomarker essential for guaranteeing the pharmacological effects of a therapy, Safety Biomarker critical for assessing the extent or likelihood of therapy-induced toxicity, Monitoring Biomarker indispensable for guiding clinical management by serially measuring patients' status, Predictive Biomarker crucial for maximizing the clinical outcome of a therapy for specific individuals, and Surrogate Endpoint fundamental for accelerating the approval of a therapy. However, these data of ThMARs has not been comprehensively described by any of the existing databases. Herein, a database, named 'TheMarker', was therefore constructed to (a) systematically offer all five types of ThMAR used at different stages of drug development, (b) comprehensively describe ThMAR information for the largest number of drugs among available databases, (c) extensively cover the widest disease classes by not just focusing on anticancer therapies. These data in TheMarker are expected to have great implication and significant impact on drug discovery and clinical practice, and it is freely accessible without any login requirement at: https://idrblab.org/themarker.

TTD: Therapeutic Target Database describing target druggability information.

Target discovery is one of the essential steps in modern drug development, and the identification of promising targets is fundamental for developing first-in-class drug. A variety of methods have emerged for target assessment based on druggability analysis, which refers to the likelihood of a target being effectively modulated by drug-like agents. In the therapeutic target database (TTD), nine categories of established druggability characteristics were thus collected for 426 successful, 1014 clinical trial, 212 preclinical/patented, and 1479 literature-reported targets via systematic review. These characteristic categories were classified into three distinct perspectives: molecular interaction/regulation, human system profile and cell-based expression variation. With the rapid progression of technology and concerted effort in drug discovery, TTD and other databases were highly expected to facilitate the explorations of druggability characteristics for the discovery and validation of innovative drug target. TTD is now freely accessible at: https://idrblab.org/ttd/.

RNAenrich: a web server for non-coding RNA enrichment.

MOTIVATION: With the rapid advances of RNA sequencing and microarray technologies in non-coding RNA (ncRNA) research, functional tools that perform enrichment analysis for ncRNAs are needed. On the one hand, because of the rapidly growing interest in circRNAs, snoRNAs, and piRNAs, it is essential to develop tools for enrichment analysis for these newly emerged ncRNAs. On the other hand, due to the key role of ncRNAs' interacting target in the determination of their function, the interactions between ncRNA and its corresponding target should be fully considered in functional enrichment. Based on the ncRNA-mRNA/protein-function strategy, some tools have been developed to functionally analyze a single type of ncRNA (the majority focuses on miRNA); in addition, some tools adopt predicted target data and lead to only low-confidence results. RESULTS: Herein, an online tool named RNAenrich was developed to enable the comprehensive and accurate enrichment analysis of ncRNAs. It is unique in (i) realizing the enrichment analysis for various RNA types in humans and mice, such as miRNA, lncRNA, circRNA, snoRNA, piRNA, and mRNA; (ii) extending the analysis by introducing millions of experimentally validated data of RNA-target interactions as a built-in database; and (iii) providing a comprehensive interacting network among various ncRNAs and targets to facilitate the mechanistic study of ncRNA function. Importantly, RNAenrich led to a more comprehensive and accurate enrichment analysis in a COVID-19-related miRNA case, which was largely attributed to its coverage of comprehensive ncRNA-target interactions. AVAILABILITY AND IMPLEMENTATION: RNAenrich is now freely accessible at https://idrblab.org/rnaenr/.

SISPRO: Signature Identification for Spatial Proteomics.

Spatial proteomics aims for a global description of organelle-specific protein distribution and dynamics, which is essential for understanding the molecular functions and cellular processes in health and disease. However, the application of this technique is seriously restricted by the neglect of robustness among proteomic signatures identified using standard statistical frameworks. Moreover, it is still a major bottleneck to automatically interpretate the identified proteomic signatures due to lack of integration of subcellular information. Herein, an online-tool SISPRO was constructed to (a) identify proteomic signatures with good robustness and accuracy via collectively evaluating relative weighted consistency (CWrel) & area under the curve (AUC) and (b) interpretate the identified signature based on comprehensive subcellular information from 9 organelles and 22 subcellular structures. All in all, SISPRO provides the endeavor to realize the simultaneous improvement of robustness and accuracy in signature identification and the unique capacity in biological annotation lies in its wide coverage of proteins and comprehensive spatial information. SISPRO is expected to be critical in spatial proteomic studies, which can be freely accessed without any login requirement at https://idrblab.org/sispro/.

DRESIS: the first comprehensive landscape of drug resistance information.

Widespread drug resistance has become the key issue in global healthcare. Extensive efforts have been made to reveal not only diverse diseases experiencing drug resistance, but also the six distinct types of molecular mechanisms underlying this resistance. A database that describes a comprehensive list of diseases with drug resistance (not just cancers/infections) and all types of resistance mechanisms is now urgently needed. However, no such database has been available to date. In this study, a comprehensive database describing drug resistance information named 'DRESIS' was therefore developed. It was introduced to (i) systematically provide, for the first time, all existing types of molecular mechanisms underlying drug resistance, (ii) extensively cover the widest range of diseases among all existing databases and (iii) explicitly describe the clinically/experimentally verified resistance data for the largest number of drugs. Since drug resistance has become an ever-increasing clinical issue, DRESIS is expected to have great implications for future new drug discovery and clinical treatment optimization. It is now publicly accessible without any login requirement at: https://idrblab.org/dresis/.

Association between semen collection time and semen parameters: an observational study.

The process of semen collection plays a key role in the quality of semen specimens. However, the association between semen collection time and semen quality is still unclear. In this study, ejaculates by masturbation from 746 subfertile men or healthy men who underwent semen analysis were examined. The median (interquartile range) semen collection time for all participants was 7.0 (5.0-11.0) min, and the median time taken for semen collection was lower in healthy men than that in subfertile men (6.0 min vs 7.0 min). An increase in the time required to produce semen samples was associated with poorer semen quality. Among those undergoing assisted reproductive technology (ART), the miscarriage rate was positively correlated with the semen collection time. After adjusting for confounders, the highest quartile (Q4) of collection time was negatively associated with semen volume and sperm concentration. A longer time to produce semen samples (Q3 and Q4) was negatively correlated with progressive and total sperm motility. In addition, there was a significant negative linear association between the semen collection time and the sperm morphology. Higher risks of asthenozoospermia (adjusted odds ratio [OR] = 2.06, 95% confidence interval [CI]: 1.31-3.25, P = 0.002) and teratozoospermia (adjusted OR = 1.98, 95% CI: 1.10-3.55, P = 0.02) were observed in Q3 than those in Q1. Our results indicate that a higher risk of abnormal semen parameter values was associated with an increase in time for semen collection, which may be related to male fertility through its association with semen quality.

M6AREG: m6A-centered regulation of disease development and drug response.

As the most prevalent internal modification in eukaryotic RNAs, N6-methyladenosine (m6A) has been discovered to play an essential role in cellular proliferation, metabolic homeostasis, embryonic development, etc. With the rapid accumulation of research interest in m6A, its crucial roles in the regulations of disease development and drug response are gaining more and more attention. Thus, a database offering such valuable data on m6A-centered regulation is greatly needed; however, no such database is as yet available. Herein, a new database named 'M6AREG' is developed to (i) systematically cover, for the first time, data on the effects of m6A-centered regulation on both disease development and drug response, (ii) explicitly describe the molecular mechanism underlying each type of regulation and (iii) fully reference the collected data by cross-linking to existing databases. Since the accumulated data are valuable for researchers in diverse disciplines (such as pathology and pathophysiology, clinical laboratory diagnostics, medicinal biochemistry and drug design), M6AREG is expected to have many implications for the future conduct of m6A-based regulation studies. It is currently accessible by all users at: https://idrblab.org/m6areg/.

NPCDR: natural product-based drug combination and its disease-specific molecular regulation.

Natural product (NP) has a long history in promoting modern drug discovery, which has derived or inspired a large number of currently prescribed drugs. Recently, the NPs have emerged as the ideal candidates to combine with other therapeutic strategies to deal with the persistent challenge of conventional therapy, and the molecular regulation mechanism underlying these combinations is crucial for the related communities. Thus, it is urgently demanded to comprehensively provide the disease-specific molecular regulation data for various NP-based drug combinations. However, no database has been developed yet to describe such valuable information. In this study, a newly developed database entitled 'Natural Product-based Drug Combination and Its Disease-specific Molecular Regulation (NPCDR)' was thus introduced. This database was unique in (a) providing the comprehensive information of NP-based drug combinations & describing their clinically or experimentally validated therapeutic effect, (b) giving the disease-specific molecular regulation data for a number of NP-based drug combinations, (c) fully referencing all NPs, drugs, regulated molecules/pathways by cross-linking them to the available databases describing their biological or pharmaceutical characteristics. Therefore, NPCDR is expected to have great implications for the future practice of network pharmacology, medical biochemistry, drug design, and medicinal chemistry. This database is now freely accessible without any login requirement at both official (https://idrblab.org/npcdr/) and mirror (http://npcdr.idrblab.net/) sites.

Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents.

Drug discovery relies on the knowledge of not only drugs and targets, but also the comparative agents and targets. These include poor binders and non-binders for developing discovery tools, prodrugs for improved therapeutics, co-targets of therapeutic targets for multi-target strategies and off-target investigations, and the collective structure-activity and drug-likeness landscapes of enhanced drug feature. However, such valuable data are inadequately covered by the available databases. In this study, a major update of the Therapeutic Target Database, previously featured in NAR, was therefore introduced. This update includes (a) 34 861 poor binders and 12 683 non-binders of 1308 targets; (b) 534 prodrug-drug pairs for 121 targets; (c) 1127 co-targets of 672 targets regulated by 642 approved and 624 clinical trial drugs; (d) the collective structure-activity landscapes of 427 262 active agents of 1565 targets; (e) the profiles of drug-like properties of 33 598 agents of 1102 targets. Moreover, a variety of additional data and function are provided, which include the cross-links to the target structure in PDB and AlphaFold, 159 and 1658 newly emerged targets and drugs, and the advanced search function for multi-entry target sequences or drug structures. The database is accessible without login requirement at: https://idrblab.org/ttd/.

A Review on Design and Mechanical Properties of Additively Manufactured NiTi Implants for Orthopedic Applications.

NiTi alloy has a wide range of applications as a biomaterial due to its high ductility, low corrosion rate, and favorable biocompatibility. Although Young's modulus of NiTi is relatively low, it still needs to be reduced; one of the promising ways is by introducing porous structure. Traditional manufacturing processes, such as casting, can hardly produce complex porous structures. Additive manufacturing (AM) is one of the most advanced manufacturing technologies that can solve impurity issues, and selective laser melting (SLM) is one of the well-known methods. This paper reviews the developments of AM-NiTi with a particular focus on SLM-NiTi utilization in biomedical applications. Correspondingly, this paper aims to describe the three key factors, including powder preparation, processing parameters, and gas atmosphere during the overall process of porous NiTi. The porous structure design is of vital importance, so the unit cell and pore parameters are discussed. The mechanical properties of SLM-NiTi, such as hardness, compressive strength, tensile strength, fatigue behavior, and damping properties and their relationship with design parameters are summarized. In the end, it points out the current challenges. Considering the increasing application of NiTi implants, this review paper may open new frontiers for advanced and modern designs.

Dengue Fever Outbreaks Caused by Varied Serotype Dengue Virus - Guangdong Province, China, 2019.

What is already known about this topic? Dengue fever (DF) outbreaks affect hundreds of millions of people worldwide and have increased significantly in Guangdong Province in 2019. What is added by this report? This paper described briefly DF outbreaks were attributed to several types of dengue virus (DENV) including DENV-1, DENV-2, and DENV-3 in 2019 in Guangdong, tracked the sources of viruses through phylogenetic analysis and epidemiological investigation, and primarily revealed the epidemiological links among the outbreaks. What are the implications for public health practice? The introduction of DENV from DF endemic areas increased pressure on the prevention and control of DF in Guangdong. Early detection of suspected cases and typing and genotyping of circulating viruses should be prioritized and enhanced to promptly assess the likelihood of local transmission, of introduction, and of subsequent sustained local transmission of the virus to implement optimal prevention and control strategies and measures.

[Estimating polysaccharide content with hyperspectral in Dendrobium of ficinale].

The objectives in the present paper were to study the relationship between the polysaccharide content and the spectrum, aimed at finding a non destructive testing method for the measurement of polysaccharide content Materials in this study were from tissue culture seedlings under different treatments and domesticated plants in different growth stages. In the study, 36 samples were used to build estimation models and another 11 as test samples to examine the models. The relationship between the spectrum and polysaccharide content was investigated by partial least squares regression (PLSR) and factor analysis. The results show that (1) there was stronger correlation between derivative reflectance and polysaccharide content, and the sensitive wavebands mainly concentrated in the visible region. (2) The PLSR model has a high precision, while its prediction accuracy is lower. The models of factor analysis have higher prediction accuracy, the RPD of the model based on spectral reflectance is 2.269 and that of derivative reflectance is 2.305.