xSiGra: Explainable model for single-cell spatial data elucidation.

Recent advancements in spatial imaging technologies have revolutionized the acquisition of high-resolution multi-channel images, gene expressions, and spatial locations at the single-cell level. Our study introduces xSiGra, an interpretable graph-based AI model, designed to elucidate interpretable features of identified spatial cell types, by harnessing multi-modal features from spatial imaging technologies. By constructing a spatial cellular graph with immunohistology images and gene expression as node attributes, xSiGra employs hybrid graph transformer models to delineate spatial cell types. Additionally, xSiGra integrates a novel variant of Grad-CAM component to uncover interpretable features, including pivotal genes and cells for various cell types, thereby facilitating deeper biological insights from spatial data. Through rigorous benchmarking against existing methods, xSiGra demonstrates superior performance across diverse spatial imaging datasets. Application of xSiGra on a lung tumor slice unveils the importance score of cells, illustrating that cellular activity is not solely determined by itself but also impacted by neighboring cells. Moreover, leveraging the identified interpretable genes, xSiGra reveals endothelial cell subset interacting with tumor cells, indicating its heterogeneous underlying mechanisms within the complex cellular communications.

Physiological and molecular bases of the nickel toxicity responses in tomato.

Nickel (Ni), a component of urease, is a micronutrient essential for plant growth and development, but excess Ni is toxic to plants. Tomato (Solanum lycopersicum L.) is one of the important vegetables worldwide. Excessive use of fertilizers and pesticides led to Ni contamination in agricultural soils, thus reducing yield and quality of tomatoes. However, the molecular regulatory mechanisms of Ni toxicity responses in tomato plants have largely not been elucidated. Here, we investigated the molecular mechanisms underlying the Ni toxicity response in tomato plants by physio-biochemical, transcriptomic and molecular regulatory network analyses. Ni toxicity repressed photosynthesis, induced the formation of brush-like lateral roots and interfered with micronutrient accumulation in tomato seedlings. Ni toxicity also induced reactive oxygen species accumulation and oxidative stress responses in plants. Furthermore, Ni toxicity reduced the phytohormone concentrations, including auxin, cytokinin and gibberellic acid, thereby retarding plant growth. Transcriptome analysis revealed that Ni toxicity altered the expression of genes involved in carbon/nitrogen metabolism pathways. Taken together, these results provide a theoretical basis for identifying key genes that could reduce excess Ni accumulation in tomato plants and are helpful for ensuring food safety and sustainable agricultural development.

Structure-based characterization and compound identification of the wild-type THF class-II riboswitch.

Riboswitches are conserved regulatory RNA elements participating in various metabolic pathways. Recently, a novel RNA motif known as the folE RNA motif was discovered upstream of folE genes. It specifically senses tetrahydrofolate (THF) and is therefore termed THF-II riboswitch. To unravel the ligand recognition mechanism of this newly discovered riboswitch and decipher the underlying principles governing its tertiary folding, we determined both the free-form and bound-form THF-II riboswitch in the wild-type sequences. Combining structural information and isothermal titration calorimetry (ITC) binding assays on structure-based mutants, we successfully elucidated the significant long-range interactions governing the function of THF-II riboswitch and identified additional compounds, including alternative natural metabolites and potential lead compounds for drug discovery, that interact with THF-II riboswitch. Our structural research on the ligand recognition mechanism of the THF-II riboswitch not only paves the way for identification of compounds targeting riboswitches, but also facilitates the exploration of THF analogs in diverse biological contexts or for therapeutic applications.

AcrR1, a novel TetR/AcrR family repressor, mediates acid and antibiotic resistance and nisin biosynthesis in Lactococcus lactis F44.

Lactococcus lactis, widely used in the manufacture of dairy products, encounters various environmental stresses both in natural habitats and during industrial processes. It has evolved intricate machinery of stress sensing and defense to survive harsh stress conditions. Here, we identified a novel TetR/AcrR family transcription regulator, designated AcrR1, to be a repressor for acid and antibiotic tolerance that was derepressed in the presence of vancomycin or under acid stress. The survival rates of acrR1 deletion strain ΔAcrR1 under acid and vancomycin stresses were about 28.7-fold (pH 3.0, HCl), 8.57-fold (pH 4.0, lactic acid) and 2.73-fold (300 ng/mL vancomycin) as that of original strain F44. We also demonstrated that ΔAcrR1 was better able to maintain intracellular pH homeostasis and had a lower affinity to vancomycin. No evident effects of AcrR1 deletion on the growth and morphology of strain F44 were observed. Subsequently, we characterized that the transcription level of genes associated with amino acids biosynthesis, carbohydrate transport and metabolism, multiple drug resistance and DNA repair proteins significantly upregulated in ΔAcrR1 using transcriptome analysis and quantitative reverse transcription-PCR (qRT-PCR) assays. Additionally, AcrR1 could repress the transcription of nisin post-translational modification gene, nisC, leading to a 16.3% increase in nisin yield after AcrR1 deletion. Our results not only refined the knowledge of the regulatory mechanism of TetR/AcrR family regulator in L. lactis, but presented a potential strategy to enhance industrial production of nisin.

3D genomic mapping reveals multifocality of human pancreatic precancers.

Pancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study1. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution. To elucidate genetic relationships between and within PanINs, we developed a workflow in which 3D modelling guides multi-region microdissection and targeted and whole-exome sequencing. From these samples, we calculated a mean burden of 13 PanINs per cm3 and extrapolated that the normal intact adult pancreas harbours hundreds of PanINs, almost all with oncogenic KRAS hotspot mutations. We found that most PanINs originate as independent clones with distinct somatic mutation profiles. Some spatially continuous PanINs were found to contain multiple KRAS mutations; computational and in situ analyses demonstrated that different KRAS mutations localize to distinct cell subpopulations within these neoplasms, indicating their polyclonal origins. The extensive multifocality and genetic heterogeneity of PanINs raises important questions about mechanisms that drive precancer initiation and confer differential progression risk in the human pancreas. This detailed 3D genomic mapping of molecular alterations in human PanINs provides an empirical foundation for early detection and rational interception of pancreatic cancer.

Identification of a marine-derived sesquiterpenoid, Compound-8, that inhibits tumour necrosis factor-induced cell death by blocking complex II assembly.

BACKGROUND AND PURPOSE: Tumour necrosis factor (TNF) is a pleiotropic inflammatory cytokine that not only directly induces inflammatory gene expression but also triggers apoptotic and necroptotic cell death, which leads to tissue damage and indirectly exacerbates inflammation. Thus, identification of inhibitors for TNF-induced cell death has broad therapeutic relevance for TNF-related inflammatory diseases. In the present study, we isolated and identified a marine fungus-derived sesquiterpenoid, 9α,14-dihydroxy-6ß-p-nitrobenzoylcinnamolide (named as Cpd-8), that inhibits TNF receptor superfamily-induced cell death by preventing the formation of cytosolic death complex II. EXPERIMENTAL APPROACH: Marine sponge-associated fungi were cultured and the secondary metabolites were extracted to yield pure compounds. Cell viability was measured by ATP-Glo cell viability assay. The effects of Cpd-8 on TNF signalling pathway were investigated by western blotting, immunoprecipitation, and immunofluorescence assays. A mouse model of acute liver injury (ALI) was employed to explore the protection effect of Cpd-8, in vivo. KEY RESULTS: Cpd-8 selectively inhibits TNF receptor superfamily-induced apoptosis and necroptosis. Cpd-8 prevents the formation of cytosolic death complex II and subsequent RIPK1-RIPK3 necrosome, while it has no effect on TNF receptor I (TNFR1) internalization and the formation of complex I in TNF signalling pathway. In vivo, Cpd-8 protects mice against TNF-α/D-GalN-induced ALI. CONCLUSION AND IMPLICATIONS: A marine fungus-derived sesquiterpenoid, Cpd-8, inhibits TNF receptor superfamily-induced cell death, both in vitro and in vivo. This study not only provides a useful research tool to investigate the regulatory mechanisms of TNF-induced cell death but also identifies a promising lead compound for future drug development.

Harnessing the potential of long non-coding RNAs in breast cancer: from etiology to treatment resistance and clinical applications.

Breast cancer (BC) is the most common malignancy among women and a leading cause of cancer-related deaths of females worldwide. It is a complex and molecularly heterogeneous disease, with various subtypes that require different treatment strategies. Despite advances in high-resolution single-cell and multinomial technologies, distant metastasis and therapeutic resistance remain major challenges for BC treatment. Long non-coding RNAs (lncRNAs) are non-coding RNAs with more than 200 nucleotides in length. They act as competing endogenous RNAs (ceRNAs) to regulate post-transcriptional gene stability and modulate protein-protein, protein-DNA, and protein-RNA interactions to regulate various biological processes. Emerging evidence suggests that lncRNAs play essential roles in human cancers, including BC. In this review, we focus on the roles and mechanisms of lncRNAs in BC progression, metastasis, and treatment resistance, and discuss their potential value as therapeutic targets. Specifically, we summarize how lncRNAs are involved in the initiation and progression of BC, as well as their roles in metastasis and the development of therapeutic resistance. We also recapitulate the potential of lncRNAs as diagnostic biomarkers and discuss their potential use in personalized medicine. Finally, we provide lncRNA-based strategies to promote the prognosis of breast cancer patients in clinical settings, including the development of novel lncRNA-targeted therapies.

[Distribution of Typical Resistant Bacteria and Resistance Genes in Source Water of the Middle and Lower Reaches of the Yellow River].

The Yellow River water of an urban area located in the middle and lower reaches of the Yellow River was taken as the research object， in which the seasonal and along-range distribution of total culturable bacteria， typical antibiotic resistant bacteria （amoxicillin resistant bacteria and sulfamethoxazole-resistant bacteria）， and their corresponding typical resistance genes ï¼»ß-lactam resistance gene （blaCTX-M） and sulfamamide resistance genes （sulI and sulⅡ）， as well as intⅠ1 were investigated. The results showed that the total culturable bacteria， ß-lactam-resistant bacteria and sulfonamide-resistant bacteria in the Yellow River Basin were significantly affected by temperature and human activities. The composition and quantity of their genera had obvious spatiotemporal distribution characteristics， in which Bacillus and Pseudomonas were dominant in the composition and number of bacteria. The abundance of resistance genes decreased with the decrease in temperature. The proportion of ß-lactam resistance genes in the total genes was higher than that of sulfanilamide genes， and sulI was the dominant gene in sulfanilamide genes. Correlation analysis showed that class Ⅰ integron played an important role in accelerating the spread of resistance genes. This study offers insight into the status quo of water resistance pollution in the Yellow River and provides theoretical support for the risk assessment of resistance genes in the middle and lower reaches of the Yellow River Basin.

The Effect of Peer Victimization During Adolescence on Depression and Gender Differences: A Systematic Review and Meta-analysis.

Peer victimization during adolescence has a detrimental impact on the mental health of victims throughout their lives. However, it remains unclear whether these effects are gender-specific. The present study conducted a systematic review to examine the effects of peer victimization on depression status, explore potential sources of heterogeneity, and investigate gender differences in these effects. We systematically searched four electronic databases (Web of Science, PubMed, Embase, and CNKI) for relevant articles that published as far as July 2022. We then extracted odds ratios (OR) and 95% confidence intervals (CI) to assess the association between peer victimization during adolescence and depression, and potential gender differences in the relation. Meta-analysis was performed, using fixed effects models and random effects models, to evaluate the association between each exposure and the outcome. A meta-analysis of 27 studies revealed that peer victimization during adolescence was significantly associated with higher risks of depression (OR = 2.79, 95% CI [2.43, 3.21], p < .001). This finding was consistent across subgroup analyses. In particular, the effect of peer victimization during adolescence on depression was found to be more pronounced in studies conducted in Asia (OR = 3.06, 95% CI [2.38, 3.92], p < .001). Furthermore, five studies focused on gender differences demonstrated that peer victimization has a stronger association with the risk of depression in women (OR = 2.84, 95% CI [2.49, 3.26], p < .001). Peer victimization during adolescence is a significant risk factor for depression, with a greater impact on women and individuals residing in Asia. Further prospective studies are needed to investigate the relationship between peer victimization and depression.

Oxygen-Activated Boron Nitride for Selective Photocatalytic Coupling of Methanol to Ethylene Glycol.

The controllable photocatalytic C-C coupling of methanol to produce ethylene glycol (EG) is a highly desirable but challenging objective for replacing the current energy-intensive thermocatalytic process. Here, we develop a metal-free porous boron nitride catalyst that demonstrates exceptional selectivity in the photocatalytic production of EG from methanol under mild conditions. Comprehensive experiments and calculations are conducted to thoroughly investigate the reaction mechanism, revealing that the OB3 unit in the porous BN plays a critical role in the preferential activation of C-H bond in methanol to form ⋅CH2OH via a concerted proton-electron transfer mechanism. More prominent energy barriers are observed for the further dehydrogenation of the ⋅CH2OH intermediate on the OB3 unit, inhibiting the formation of some other by-products during the catalytic process. Additionally, a small downhill energy barrier for the coupling of ⋅CH2OH in the OB3 unit promotes the selective generation of EG. This study provides valuable insights into the underlying mechanisms and can serve as a guide for the design and optimization of photocatalysts for efficient and selective EG production under mild conditions.

Discovery of WS-384, a first-in-class dual LSD1 and DCN1-UBC12 protein-protein interaction inhibitor for the treatment of non-small cell lung cancer.

Abnormally high expression of lysine-specific demethylase 1 A (LSD1) and DCN1 plays a vital role in the occurrence, development, and poor prognosis of non-small cell lung cancer (NSCLC). Accumulating evidence has shown that the development of small-molecule inhibitors dually targeting LSD1 and the DCN1-UBC12 interaction probably have therapeutic promise for cancer therapy. This work reported that WS-384 dually targeted LSD1 and DCN1-UBC12 interactions and evaluated its antitumor effects in vitro and in vivo. Specifically, WS-384 inhibited A549 and H1975 cells viability and decreased colony formation and EdU incorporation. WS-384 could also trigger cell cycle arrest, DNA damage, and apoptosis. Moreover, WS-384 significantly decreased tumor weight and volume in A549 xenograft mice. Mechanistically, WS-384 increased the gene and protein level of p21 by suppressing the neddylation of cullin 1 and decreasing H3K4 demethylation at the CDKN1A promoter. The synergetic upregulation of p21 contributed to cell cycle arrest and the proapoptotic effect of WS-384 in NSCLC cells. Taken together, our proof of concept studies demonstrated the therapeutic potential of dual inhibition of LSD1 and the DCN1-UBC12 interaction for the treatment of NSCLC. WS-384 could be used as a lead compound to develop new dual LSD1/DCN1 inhibitors for the treatment of human diseases in which LSD1 and DCN1 are dysregulated.

Proapoptotic effect of WS-299 induced by NOXA accumulation and NRF2-counterbalanced oxidative stress damage through targeting RBX1-UBE2M interaction in gastric cancers.

The abnormal activation of Cullin RING E3 Ligases (CRLs) is closely associated with the occurrence and development of various cancers. Targeting the neddylation pathway represents an effective approach for cancer treatment. In this work, we reported that WS-299, structurally featuring a coumarin moiety attached to the triazolopyrimidine, exhibited excellent anti-proliferative activity in MGC-803 and HGC-27 cells. WS-299 exerted potent anticancer effects by inhibiting clone formation, EdU incorporation and inducing cell cycle arrest. WS-299 inhibited CUL3/5 neddylation and caused an obvious accumulation of Nrf2 and NOXA, substrates of CRL3 and CRL5, respectively. Biochemical studies showed that WS-299 inhibited CUL3 neddylation by inhibiting RBX1-UBE2M interaction. The anti-proliferative effect of WS-299 was mainly induced by NOXA-mediated apoptosis. Of note, Nrf2 attenuated WS-299-induced reactive oxygen species (ROS) levels. Furthermore, Nrf2 accumulation also had an antagonistic effect on NOXA-induced apoptosis. Therefore, WS-299 and siNrf2 synergistically increased ROS levels, apoptotic cells and suppressed tumor growth in vivo. Taken together, our research clarified the anti-cancer mechanisms of WS-299 through targeting the RBX1-UBE2M protein-protein interaction and inhibiting the neddylation modification of CUL3 and CUL5. More importantly, our studies also demonstrated that combination of WS-299 with shNrf2 could be an effective strategy for treating gastric cancers.

The Cross-Regulation Between Set1, Clr4, and Lsd1/2 in Schizosaccharomyces pombe.

Eukaryotic chromatin is organized into either silenced heterochromatin or relaxed euchromatin regions, which controls the accessibility of transcriptional machinery and thus regulates gene expression. In fission yeast, Schizosaccharomyces pombe, Set1 is the sole H3K4 methyltransferase and is mainly enriched at the promoters of actively transcribed genes. In contrast, Clr4 methyltransferase initiates H3K9 methylation, which has long been regarded as a hallmark of heterochromatic silencing. Lsd1 and Lsd2 are two highly conserved H3K4 and H3K9 demethylases. As these histone-modifying enzymes perform critical roles in maintaining histone methylation patterns and, consequently, gene expression profiles, cross-regulations among these enzymes are part of the complex regulatory networks. Thus, elucidating the mechanisms that govern their signaling and mutual regulations remains crucial. Here, we demonstrated that C-terminal truncation mutants, lsd1-ΔHMG and lsd2-ΔC, do not compromise the integrity of the Lsd1/2 complex but impair their chromatin-binding capacity at the promoter region of target genomic loci. We identified protein-protein interactions between Lsd1/2 and Raf2 or Swd2, which are the subunits of the Clr4 complex (CLRC) and Set1-associated complex (COMPASS), respectively. We showed that Clr4 and Set1 modulate the protein levels of Lsd1 and Lsd2 in opposite ways through the ubiquitin-proteasome-dependent pathway. During heat stress, the protein levels of Lsd1 and Lsd2 are upregulated in a Set1-dependent manner. The increase in protein levels is crucial for differential gene expression under stress conditions. Together, our results support a cross-regulatory model by which Set1 and Clr4 methyltransferases control the protein levels of Lsd1/2 demethylases to shape the dynamic chromatin landscape.

Comparative efficacy and tolerability of probiotic, prebiotic, and synbiotic formulations for adult patients with mild-moderate ulcerative colitis in an adjunctive therapy: A network meta-analysis.

BACKGROUND & AIMS: Probiotics, prebiotics, and synbiotics (PPS) have been widely used as adjuvant treatments in patients with ulcerative colitis (UC) in recent years. However, the most effective formulations of PPS have yet to be identified. We thus aimed to compare the efficacy and tolerability of different PPS formulations for mild-moderate UC. METHODS: We searched PubMed, Embase, Web of Science, and Cochrane CENTRAL from inception to June 24, 2023 for double-blind randomized controlled trials. We used a frequentist approach in random-effects models for network meta-analysis and the Grading of Recommendations Assessment, Development, and Evaluation approach to evaluate the certainty of evidence. RESULTS: We analysed data from 20 trials involving 1153 patients. The combinations of specific strains of Lactobacillus and Bifidobacterium (CLB) (odds ratio (OR), 3.85; 95 % confidence interval (CI), 1.40-10.60; low certainty) and combinations of specific strains of Lactobacillus, Bifidobacterium, and Streptococcus (CLBS) (OR, 2.20; 95 % CI, 1.47-3.28; low certainty) significantly increased the clinical remission rate in intention-to-treat analysis (ITT) when compared to placebo. Similarly, compared with placebo, the two combinations significantly reduced clinical activity scores (standardized mean difference (SMD), -1.17 (95 % CI, -1.68 to -0.65), low certainty; and SMD, -1.33 (95 % CI, -1.81 to -0.86), low certainty, respectively). Hierarchical cluster analyses showed the two combinations formed clusters with high efficacy (clinical remission in ITT and clinical activity score) and tolerability (withdrawal due to worsening symptoms) within 12 weeks. CONCLUSION: In this systematic review, we found CLB and CLBS demonstrated a clinical benefit in adjuvant treatments, with a comparable tolerability and safety profile to placebo. Further trials are needed. TRIAL REGISTRATION NUMBER: CRD42022344905.

Modulating Charge Separation of Oxygen-Doped Boron Nitride with Isolated Co Atoms for Enhancing CO2 -to-CO Photoreduction.

To alleviate the greenhouse effect and address the related energy crisis, solar-driven reduction of carbon dioxide (CO2 ) to value-added products is considered as a sustainable strategy. However, the insufficient separation and rapid recombination of photogenerated charge carriers during photocatalysis greatly limit their reduction efficiency and practical application potential. Here, isolated Cobalt (Co) atoms are successfully decorated into oxygen-doped boron nitride (BN) via an in situ pyrolysis method, achieving greatly improved catalytic activity and selectivity to the carbon monoxide (CO) product. X-ray absorption fine spectroscopy demonstrates that the isolated Co atoms are stabilized by the O and N atoms with an unsaturated CoO2 N1 configuration. Further experimental investigation and theoretical simulations confirm that the decorated Co atoms not only work as the real active center during the CO2 reduction process, but also perform as the electron pump to promote the electron/hole separation and transfer, resulting in greatly accelerated reaction kinetics and improved activity. In addition, the CoO2 N1 coordination geometry is favorable to the conversion from *CO2 to *COOH, which shall be considered as a selectivity-determining step for the evolution of the CO products. The surface modulation strategy at the atomic level opens a new avenue for regulating the reaction kinetics for photocatalytic CO2 reduction.

Pathology steered stratification network for subtype identification in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by three neurobiological factors beta-amyloid, pathologic tau, and neurodegeneration. There are no effective treatments for AD at a late stage, urging for early detection and prevention. However, existing statistical inference approaches in neuroimaging studies of AD subtype identification do not take into account the pathological domain knowledge, which could lead to ill-posed results that are sometimes inconsistent with the essential neurological principles. PURPOSE: Integrating systems biology modeling with machine learning, the study aims to assist clinical AD prognosis by providing a subpopulation classification in accordance with essential biological principles, neurological patterns, and cognitive symptoms. METHODS: We propose a novel pathology steered stratification network (PSSN) that incorporates established domain knowledge in AD pathology through a reaction-diffusion model, where we consider non-linear interactions between major biomarkers and diffusion along the brain structural network. Trained on longitudinal multimodal neuroimaging data, the biological model predicts long-term evolution trajectories that capture individual characteristic progression pattern, filling in the gaps between sparse imaging data available. A deep predictive neural network is then built to exploit spatiotemporal dynamics, link neurological examinations with clinical profiles, and generate subtype assignment probability on an individual basis. We further identify an evolutionary disease graph to quantify subtype transition probabilities through extensive simulations. RESULTS: Our stratification achieves superior performance in both inter-cluster heterogeneity and intra-cluster homogeneity of various clinical scores. Applying our approach to enriched samples of aging populations, we identify six subtypes spanning AD spectrum, where each subtype exhibits a distinctive biomarker pattern that is consistent with its clinical outcome. CONCLUSIONS: The proposed PSSN (i) reduces neuroimage data to low-dimensional feature vectors, (ii) combines AT[N]-Net based on real pathological pathways, (iii) predicts long-term biomarker trajectories, and (iv) stratifies subjects into fine-grained subtypes with distinct neurological underpinnings. PSSN provides insights into pre-symptomatic diagnosis and practical guidance on clinical treatments, which may be further generalized to other neurodegenerative diseases.

Association between burnout and post-traumatic stress disorder among frontline nurse during COVID-19 pandemic: A moderated mediation analysis.

AIMS AND OBJECTIVES: The aim of this study was to investigate the relationship between burnout and post-traumatic stress disorder (PTSD) among frontline nurses who went to assist the epidemic situation in Wuhan, China, during the outbreak in 2020. The study also explored the mediating role of depression and the moderating role of age in the main relationship. BACKGROUND: The relationship between burnout and PTSD in nurse has rarely been investigated in the context of the COVID-19 pandemic. Understand the relationship between these variables can provide empirical evidence for developing interventions and protocols that improve the health of nurses in future public health emergencies. DESIGN: An online cross-sectional survey of targeted local 327 nurses who went to assist the COVID-19 epidemic situation in Wuhan during the initial outbreak. METHODS: This study was conducted in August 2020, the burnout scale, the PTSD scale and the depression scale were used to survey participants. The moderated mediation model was used to test research hypotheses. RESULTS: Burnout could affect the PTSD symptoms in nursing staffs and depression could mediate this relationship. Age moderated the relationship between burnout/depression and PTSD, and the effects was strong and significant among younger participants in the relationship between burnout and PTSD. CONCLUSIONS: Burnout was identified as a core risk factor of PTSD in nurses. Depression and age played significant roles in the relationship between burnout and PTSD. RELEVANCE TO CLINICAL PRACTICE: PTSD, as a symptom that manifests after experiencing a stressful event, should be a key concern among frontline healthcare professionals. This study suggests that PTSD in nurses can be further reduced by reducing burnout. Attention should also be paid to the PTSD status of nurses of different age groups. PATIENT OR PUBLIC CONTRIBUTION: Patients and the public were not involved in the design and implementation of this study. Frontline nurses completed an online questionnaire for this study.

Enabling the clinical application of artificial intelligence in genomics: a perspective of the AMIA Genomics and Translational Bioinformatics Workgroup.

OBJECTIVE: Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association-Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space. PROCESS: A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members. CONCLUSIONS: Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of larger datasets is crucial to emulating the success AI is achieving in other domains. It is important that AI methods do not exacerbate existing socio-economic, racial, and ethnic disparities. Genomic data standards are critical to effectively scale such technologies across institutions. With so much uncertainty, complexity and novelty in genomics and medicine, and with an evolving regulatory environment, the current focus should be on using these technologies in an interface with clinicians that emphasizes the value each brings to clinical decision-making.

DRMref: comprehensive reference map of drug resistance mechanisms in human cancer.

Drug resistance poses a significant challenge in cancer treatment. Despite the initial effectiveness of therapies such as chemotherapy, targeted therapy and immunotherapy, many patients eventually develop resistance. To gain deep insights into the underlying mechanisms, single-cell profiling has been performed to interrogate drug resistance at cell level. Herein, we have built the DRMref database (https://ccsm.uth.edu/DRMref/) to provide comprehensive characterization of drug resistance using single-cell data from drug treatment settings. The current version of DRMref includes 42 single-cell datasets from 30 studies, covering 382 samples, 13 major cancer types, 26 cancer subtypes, 35 treatment regimens and 42 drugs. All datasets in DRMref are browsable and searchable, with detailed annotations provided. Meanwhile, DRMref includes analyses of cellular composition, intratumoral heterogeneity, epithelial-mesenchymal transition, cell-cell interaction and differentially expressed genes in resistant cells. Notably, DRMref investigates the drug resistance mechanisms (e.g. Aberration of Drug's Therapeutic Target, Drug Inactivation by Structure Modification, etc.) in resistant cells. Additional enrichment analysis of hallmark/KEGG (Kyoto Encyclopedia of Genes and Genomes)/GO (Gene Ontology) pathways, as well as the identification of microRNA, motif and transcription factors involved in resistant cells, is provided in DRMref for user's exploration. Overall, DRMref serves as a unique single-cell-based resource for studying drug resistance, drug combination therapy and discovering novel drug targets.

A noninvasive multianalytical approach establishment for risk assessment and gastric cancer screening.

Effective screening and early detection are critical to improve the prognosis of gastric cancer (GC). Our study aims to explore noninvasive multianalytical biomarkers and construct integrative models for preliminary risk assessment and GC detection. Whole genomewide methylation marker discovery was conducted with CpG tandems target amplification (CTTA) in cfDNA from large asymptomatic screening participants in a high-risk area of GC. The methylation and mutation candidates were validated simultaneously using one plasma from patients at various gastric lesion stages by multiplex profiling with Mutation Capsule Plus (MCP). Helicobacter pylori specific antibodies were detected with a recomLine assay. Integrated models were constructed and validated by the combination of multianalytical biomarkers. A total of 146 and 120 novel methylation markers were found in CpG islands and promoter regions across the genome with CTTA. The methylation markers together with the candidate mutations were validated with MCP and used to establish a 133-methylation-marker panel for risk assessment of suspicious precancerous lesions and GC cases and a 49-methylation-marker panel as well as a 144-amplicon-mutation panel for GC detection. An integrated model comprising both methylation and specific antibody panels performed better for risk assessment than a traditional model (AUC, 0.83 and 0.63, P < .001). A second model for GC detection integrating methylation and mutation panels also outperformed the traditional model (AUC, 0.82 and 0.68, P = .005). Our study established methylation, mutation and H. pylori-specific antibody panels and constructed two integrated models for risk assessment and GC screening. Our findings provide new insights for a more precise GC screening strategy in the future.