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(±)-Elodeoidileons A-L (1-12), 12 pairs of previously undescribed filicinic acid based meroterpenoids were isolated from Hypericum elodeoides with unique linear or angular 6/6/6 ring core. Modern spectroscopic techniques, modified Mosher's method and quantum chemical calculations were used to identify the planner structures and configurations of 1-12. Additionally, the potential biosynthetic pathways for 1-12 were anticipated. Moreover, biological activity assessments suggested that 1a, 5a, and 11b could activate Retinoid X receptor-α (RXRα) transcription and enhance the ATP-binding cassette transporter A1 (ABCA1) protein's expression. Fluorescence titration assay suggested that 1a might have a direct interaction with the RXRα-LBD protein, with an estimated Kd value of 5.85 µM. Moreover, molecular docking study confirmed the binding of 1a to RXRα and further validated by cellular thermal shift assay (CETSA). Thus, compound 1a may promote ß-amyloid (Aß) clearance by targeting RXRα and upregulating the expression of the ABCA1 protein, showing promise as anti-Alzheimer's agent.

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Background: Synthetic lethality offers a promising strategy for cancer treatment by targeting genetic vulnerabilities unique to tumor cells, leading to selective tumor cell death. However, single-gene knockout screens often miss functional redundancy due to paralog genes. Multiplex CRISPR systems, including various Cas9 and Cas12a platforms, have been developed to assay genetic interactions, yet no systematic comparison of method to identify synthetic lethality from CRISPR screens has been conducted. Results: We evaluated data from four in4mer CRISPR/Cas12a screens in cancer cell lines, using three bioinformatic approaches to identify synthetic lethal interactions: delta log fold change (dLFC), Z-transformed dLFC (ZdLFC), and rescaled dLFC (RdLFC). Both ZdLFC and RdLFC provided more consistent identification of synthetic lethal pairs across cell lines compared to the unscaled dLFC method. Conclusions: The ZdLFC method offers a robust framework for scoring synthetic lethal interactions from paralog screens, providing consistent results across different cell lines without requiring a training set of known positive interactors.

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Intervention mapping (IM) is a planning approach that reflects the intricate decision-making process involved in the design of behavior interventions. The development and implementation of IM is complex in preventing HIV/AIDS transmission. Therefore, it is significant to conduct a perfect preliminary work to successfully implement HIV/AIDS prevention. The objectives of this review were to collect and evaluate the data of the first three steps using IM to prevent HIV/AIDS transmission, and summarize the key points in the preliminary steps of IM. A total of 18 studies were identified, and six studies completely described the tasks in the first three steps of IM. Three studies described the logic model of the problem (n = 3). Six studies reported the matrix of behavior changes (n = 6), including personal and environmental determinants. Among the selected determinants, most studies reported the personal level determinants (self-efficacy and skills, knowledge, attitudes, and norms). The most used practical applications in reducing HIV/AIDS risk behaviors were video roles (n = 8) and role-model stories (n = 5). The review may be helpful for healthcare professionals to carefully design and implement the key procedures of the first three steps of the IM programs for people with HIV/AIDS in preventing HIV/AIDS transmission.

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Skin identity is controlled by intrinsic features of the epidermis and dermis and their interactions. Modifying skin identity has clinical potential, such as the conversion of residual limb and stump (nonvolar) skin of amputees to pressure-responsive palmoplantar (volar) skin to enhance prosthesis use and minimize skin breakdown. Greater keratin 9 (KRT9) expression, higher epidermal thickness, keratinocyte cytoplasmic size, collagen length, and elastin are markers of volar skin and likely contribute to volar skin resiliency. Given fibroblasts' capacity to modify keratinocyte differentiation, we hypothesized that volar fibroblasts influence these features. Bioprinted skin constructs confirmed the capacity of volar fibroblasts to induce volar keratinocyte features. A clinical trial of healthy volunteers demonstrated that injecting volar fibroblasts into nonvolar skin increased volar features that lasted up to 5 months, highlighting a potential cellular therapy.

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The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-scale CNS scRNA-seq data still encounters challenges due to the complexity and heterogeneity among CNS cell types/subtypes. In this study, we introduce a self-supervised contrastive learning method, called scCM, for integrating large-scale CNS scRNA-seq data. scCM brings functionally related cells close together while simultaneously pushing apart dissimilar cells by comparing the variations of gene expression, effectively revealing the heterogeneous relationships within the CNS cell types/subtypes. The effectiveness of scCM is evaluated on 20 CNS datasets covering 4 species and 10 CNS diseases. Leveraging these strengths, we successfully integrate the collected human CNS datasets into a large-scale reference to annotate cell types and subtypes in neural tissues. Results demonstrate that scCM provides an accurate annotation, along with rich spatial information of cell state. In summary, scCM is a robust and promising method for integrating large-scale CNS scRNA-seq data, enabling researchers to gain insights into the cellular and molecular mechanisms underlying CNS functions and diseases.

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PURPOSE: Although several different parameters of PET/CT were reported to be predictive of survival in DLBCL, the best parameter remains to be elucidated and whether it could improve the risk stratification of IPI in patients with DLBCL. PROCEDURES: 262 DLBCL patients including in the training and validation cohort were retrospectively analyzed in this study. RESULTS: Among different parameters, MTV was identified as the optimal prognostic parameter with a maximum area under the curve (AUC) of 0.652 ± 0.112 than TLG and SDmax (0.645 ± 0.113 and 0.600 ± 0.117, respectively). Patients with high MTV were associated with inferior PFS (p < 0.001 and p = 0.021, respectively) and OS (p < 0.001 and p < 0.001, respectively) in both the training and validation cohort. The multivariate analysis revealed that high MTV was an unfavorable factor for PFS (relative ratio [RR], 2.295; 95% confidence interval [CI], 1.457-3.615; p < 0.01) and OS (RR, 2.929; 95% CI 1.679-5.109; p < 0.01) independent of IPI. CONCLUSIONS: Further analysis showed MTV could improve the risk stratification of IPI for both PFS and OS (p < 0.01 and p < 0.01, respectively). In conclusion, our study suggests that MTV was an optimal prognostic parameter of PET/CT for survival and it could improve the risk stratification of IPI in DLBCL, which may help to guide treatment in clinical trial.

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INTRODUCTION: Osimertinib (AZD9291) is a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that has shown significant clinical benefits in patients with EGFR-sensitizing mutations or the EGFR T790M mutation. The homologous recombination (HR) pathway is crucial for repairing DNA double-strand breaks (DSBs). Rad51 plays a central role in HR, facilitating the search for homology and promoting DNA strand exchange between homologous DNA molecules. Rad51 is overexpressed in numerous types of cancer cells. B02, a specific small molecule inhibitor of Rad51, inhibits the DNA strand exchange activity of Rad51. Previous studies have indicated that B02 disrupted Rad51 foci formation in response to DNA damage and inhibited DSBs repair in human cells and sensitized them to chemotherapeutic drugs in vitro and in vivo. However, the potential therapeutic effects of combining osimertinib with a Rad51 inhibitor are not well understood. The aim of this study was to elucidate whether the downregulation of Rad51 expression and activity can enhance the osimertinib-induced cytotoxicity in non-small cell lung cancer (NSCLC) cells. METHODS: We used the MTS, trypan blue dye exclusion and colony-formation ability assay to determine whether osimertinib alone or in combination with B02 had cytotoxic effects on NSCLC cell lines. Real-time polymerase chain reaction was conducted to measure the amounts of Rad51 mRNA. The protein levels of phosphorylated AKT and Rad51 were determined by Western blot analysis. RESULTS: We found that osimertinib reduced Rad51 expression by inactivating AKT activity. Rad51 knockdown using small interfering RNA or AKT inactivation through the phosphatidylinositol 3-kinase inhibitor LY294002 or si-AKT RNA transfection enhanced the cytotoxic and growth inhibitory effects of osimertinib. In contrast, AKT-CA (a constitutively active form of AKT) vector-enforced expression could mitigate the cytotoxic and cell growth inhibitory effects of osimertinib. Furthermore, B02 significantly enhanced the cytotoxic and cell growth inhibitory effects of osimertinib in NSCLC cells. Compared to parental cells, the activation of AKT and Rad51 expression in osimertinib-resistant cells could not be significantly inhibited by osimertinib treatment. Moreover, the increased expression of Rad51 is associated with the resistance mechanism in osimertinib-resistant H1975 and A549 cells. CONCLUSION: Collectively, the downregulation of Rad51 expression and activity enhances the cytotoxic effect of osimertinib in human NSCLC cells.

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The mitochondrial distribution and morphology family 33 gene (MDM33) regulates mitochondrial homeostasis by mediating the mitochondrial fission process in yeast. The wheat head blight Fusarium graminearum contains an FgMdm33 protein that is orthologous to Saccharomyces cerevisiae Mdm33, albeit its function remains unknown. We have reported here the roles of FgMdm33 in regulating fungal morphogenesis, mitochondrial morphology, autophagy, apoptosis, and fungal pathogenicity. The ΔFgmdm33 mutants generated through a homologous recombination strategy in this study exhibited defects in terms of mycelial growth, conidia production, and virulence. Hyphal cells lacking FgMDM33 displayed elongated mitochondria and a dispensable respiratory-deficient growth phenotype, indicating the possible involvement of FgMDM33 in mitochondrial fission. The ΔFgmdm33 mutants displayed a remarkable reduction in the proteolysis of GFP-FgAtg8, whereas the formation of autophagic bodies in the hyphal cells of mutants was recorded under the induction of mitophagy. In addition, the transcriptional expression of the apoptosis-inducing factor 1 gene (FgAIF1) was significantly upregulated in the ΔFgmdm33 mutants. Cumulatively, these results indicate that FgMDM33 is involved in mitochondrial fission, non-selective macroautophagy, and apoptosis and that it regulates fungal growth, conidiation, and pathogenicity of the head blight pathogen.

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OBJECTIVE: We aim to investigate the potential roles of key genes in the development of lupus nephritis (LN), screen key biomarkers, and construct the lncRNA XIST/miR-381-3P/STAT1 axis by using bioinformatic prediction combined with clinical validation, thereby providing new targets and insights for clinical research. METHODS: Gene expression microarrays GSE157293 and GSE112943 were downloaded from the GEO database to obtain differentially expressed genes (DEGs), followed by enrichment analyses on these DEGs, which were enriched and analyzed to construct a protein-protein interaction (PPI) network to screen core genes. The lncRNA-miRNA-mRNA regulatory network was predicted and constructed based on the miRNA database. 37 female patients with systemic lupus erythematosus (SLE) were recruited to validate the bioinformatics results by exploring the diagnostic value of the target ceRNA axis in LN by dual luciferase and real-time fluorescence quantitative PCR (RT-qPCR) and receiver operating characteristic (ROC). RESULTS: The data represented that a total of 133 differential genes were screened in the GSE157293 dataset and 2869 differential genes in the GSE112943 dataset, yielding a total of 26 differentially co-expressed genes. Six core genes (STAT1, OAS2, OAS3, IFI44, DDX60, and IFI44L) were screened. Biological functional analysis identified key relevant pathways in LN. ROC curve analysis suggested that lncRNA XIST, miR-381-3P, and STAT1 could be used as potential molecular markers to assist in the diagnosis of LN. CONCLUSION: STAT1 is a key gene in the development of LN. In conclusion, lncRNA XIST, miR-381-3P, and STAT1 can be used as new molecular markers to assist in the diagnosis of LN, and the lncRNA XIST/miR-381-3P/STAT1 axis may be a potential therapeutic target for LN.

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Wound rehabilitation is invariably time-consuming, scar formation further weakens therapeutic efficacy, and detailed mechanisms at the molecular level remain unclear. In this work, a Mo4/3B2-x nanoscaffold was fabricated and utilized for wound healing and scar removing in a mice model, while metabolomics was used to study the metabolic reprogramming of metabolome during therapy at the molecular level. The results showed that transition metal borides, called Mo4/3B2-x nanoscaffolds, could mimic superoxide dismutase and glutathione peroxidase to eliminate excess reactive oxygen species (ROS) in the wound microenvironment. During the therapeutic process, the Mo4/3B2-x nanoscaffold could facilitate the regeneration of wounds and removal of scars by regulating the biosynthesis of collagen, fibers, and blood vessels at the pathological, imaging, and molecular levels. Subsequent metabolomics study revealed that the Mo4/3B2-x nanoscaffold effectively ameliorated metabolic disorders in both wound and scar microenvironments through regulating ROS-related pathways including the amino acid metabolic process (including glycine and serine metabolism and glutamate metabolism) and the purine metabolic process. This study is anticipated to illuminate the potential clinical application of the Mo4/3B2-x nanoscaffold as an effective therapeutic agent in traumatic diseases and provide insights into the development of analytical methodology for interrogating wound healing and scar removal-related metabolic mechanisms.

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Piezoelectric catalysis could convert mechanical energy into chemical energy, which can combine with solar energy for a high-efficiency piezo-photocatalysis reaction. In this work, NiTiO3 nanorods were synthesized via the sol-gel method and initially employed for the removal of U(VI) from radioactive-contaminated water. The NiTiO3 nanorods will generate an internal electric field in an ultrasonic environment, which could greatly improve the performance of piezo-photocatalysis in reducing U(VI) by promoting the generation of photoexcited electrons and reactive oxygen species (ROS). After exposure to visible light and ultrasound for 3 h, the NTO-R-1 exhibited superb U(VI) degradation efficiency of 93.91%, which was 2.58, 6.15, and 6.68 times greater than those of visible light, ultrasonic irradiation, and dark, respectively. Moreover, photoexcited electrons and oxygen-active species play a decisive role in the piezo-photocatalysis process. Therefore, NiTiO3 with excellent piezo-photocatalysis properties exhibits good potential for the development of efficient wastewater purification catalysts and also helps to probe the possible mechanism of piezo-photocatalysis removal of U(VI) in wastewater.

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During malaria infection, Plasmodium sporozoites, the fast-moving stage of the parasite, are injected by a mosquito into the skin of the mammalian host. In the skin, sporozoites need to migrate through the dermal tissue to enter the blood vessel. Sporozoite motility is critical for infection but not well understood. Here, we used collagen hydrogels with tunable fiber structures, as an in vitro model for the skin. After injecting sporozoites into the hydrogel, we analyzed their motility in three-dimension (3D). We found that sporozoites demonstrated chiral motility, in that they mostly follow right-handed helical trajectories. In high-concentration collagen gel, sporozoites have lower instantaneous speed, but exhibit straighter tracks compared to low-concentration collagen gel, which leads to longer net displacement and faster dissemination. Taken together, our study indicates an inner mechanism for sporozoites to adapt to the environment, which could help with their successful exit from the skin tissue.

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It is generally acknowledged that antiviral therapy can reduce the incidence of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), there remains a subset of patients with chronic HBV infection who develop HCC despite receiving antiviral treatment. This study aimed to develop a model capable of predicting the long-term occurrence of HCC in patients with chronic HBV infection before initiating antiviral therapy. A total of 1450 patients with chronic HBV infection, who received initial antiviral therapy between April 2006 and March 2023 and completed long-term follow-ups, were nonselectively enrolled in this study. Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis was used to construct the model. The results were validated in an external cohort (n = 210) and compared with existing models. The median follow-up time for all patients was 60 months, with a maximum follow-up time of 144 months, during which, 32 cases of HCC occurred. The nomogram model for predicting HCC based on GGT, AFP, cirrhosis, gender, age, and hepatitis B e antibody (TARGET-HCC) was constructed, demonstrating a good predictive performance. In the derivation cohort, the C-index was 0.906 (95% CI = 0.869-0.944), and in the validation cohort, it was 0.780 (95% CI = 0.673-0.886). Compared with existing models, TARGET-HCC showed promising predictive performance. Additionally, the time-dependent feature importance curve indicated that gender consistently remained the most stable predictor for HCC throughout the initial decade of antiviral therapy. This simple predictive model based on noninvasive clinical features can assist clinicians in identifying high-risk patients with chronic HBV infection for HCC before the initiation of antiviral therapy.

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Tiny NiSnO3 nanoparticles with the assistance of polyvinylpyrrolidone (PVP) are prepared to uniformly and stably "bond" on the surface of graphene to form a stable NiSnO3/RGO-PVP structure. At the same time, the excellent performance of lithium-ion batteries (LIBs) with the use of NiSnO3/RGO-PVP structure is verified through a dual combination of experiment and theory. The resulting NiSnO3/RGO-PVP structure enhanced the performance of LIBs with high cycling stability and better rate capability; even after undergoing rate performance tests at different high current densities, the NiSnO3/RGO-PVP electrode can still reach a capacity of 624 mA h g-1 at 200 mA g-1 after 400 cycles. The superior electrochemical performance of NiSnO3/RGO-PVP nanocomposites can be attributed to the synergistic effects between tiny NiSnO3 nanoparticles synthesized with the assistance of PVP and RGO, which can be verified through first-principles calculations based on DFT. The charge transfer between NiSnO3 and RGO through an electron density difference indicates a strong interaction between the two. Meanwhile, the low adsorption energies (-3.914, -0.77, and -0.65 eV), low diffusion barriers (0.025, 0.49, and 0.141 eV), and high diffusion coefficients (1.79 × 10-3, 5.38 × 10-11, and 2.97 × 10-5 cm2 s-1) of lithium ions at three different positions indicate the excellent rate performance of the NiSnO3/RGO-PVP heterostructure, which is consistent with experimental results. This work analyzes the excellent electrochemical performance of NiSnO3/RGO-PVP from the experimental results and supports the reliability of the experimental results through theoretical calculations.

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BRCA1, a breast cancer susceptibility gene, has emerged as a central mediator that brings together multiple signaling complexes in response to DNA damage. The A, B, and C complexes of BRCA1, which are formed based on their phosphorylation-dependent interactions with the BRCA1-C-terminal domains, contribute to the roles of BRCA1 in DNA repair and cell cycle checkpoint control. However, their functions in DNA damage response remain to be fully appreciated. Specifically, there has been no systematic investigation of the roles of BRCA1-A, -B, and -C complexes in the regulation of BRCA1 localization and functions, in part because of cellular lethality associated with loss of CtIP protein, which is an essential component in BRCA1-C complex. To systematically investigate the functions of these complexes in DNA damage response, we depleted a key component in each of these complexes. We used the degradation tag system to inducibly deplete endogenous CtIP and obtained a series of RAP80/FANCJ/CtIP single-, double-, and triple-knockout cells. We showed that loss of BRCA1-B/FANCJ and BRCA1-C/CtIP, but not BRCA1-A/RAP80, resulted in reduced cell proliferation and increased sensitivity to DNA damage. BRCA1-C/CtIP and BRCA1-A/RAP80 were involved in BRCA1 recruitment to sites of DNA damage. However, BRCA1-A/RAP80 was not essential for damage-induced BRCA1 localization. Instead, RAP80/H2AX and CtIP have redundant roles in BRCA1 recruitment. Altogether, our systematic analysis uncovers functional differences between BRCA1-A, -B, and -C complexes and provides new insights into the roles of these BRCA1-associated protein complexes in DNA damage response and DNA repair.

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Accumulating evidence supports the concept that DNA damage response targeted therapies can improve antitumor immune response by increasing the immunogenicity of tumor cells and improving the tumor immune microenvironment. Ataxia telangiectasia mutated (ATM) is a core component of the DNA repair system. Although the ATM gene has a significant mutation rate in many human cancers, including colorectal, prostate, lung, and breast, it remains understudied compared with other DDR-involved molecules such as PARP and ATR. Here, we found that either gene knockout or drug intervention, ATM inhibition activated the cGAS/STING pathway and augmented MHC class I in CRC cells, and these effects could be amplified by radiation. Furthermore, we found that MHC class I upregulation induced by ATM inhibition is dependent on the activation of the NFκB/IRF1/NLRC5 pathway and independent of STING. Animal experiments have shown increasing infiltration and cytotoxic function of T cells and better survival in ATM-deficient tumors. This work indicated that ATM nonsense mutation predicted the clinical benefits of radiotherapy combined with immune checkpoint blockade for patients with CRC. It also provides a molecular mechanism rationale for ATM-targeted agents for patients with CRC.

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An autoencoder for video anomaly detection task is a type of algorithm with the primary purpose of learning an "informative" representation of the normal data that can be used for identifying the abnormal data by learning to reconstruct a set of input observations. Based on the encoding-decoding structure, we explore a novel dual ForkNet architecture that can dissociate and process the spatio-temporal representation. It is well-known in the information theory community that most autoencoders coding processes are inevitably accompanied by a certain loss of information. In this dual ForkNet, we focus on mitigating the information loss problem and propose a novel architectural recalibration approach, which we term the "Informetrics Recalibration" (IR). It can adaptively recalibrate latent feature representation by explicitly modeling the similarity between the corresponding feature maps of encoder and decoder, and retain more useful semantic information to generate greater differentiation between normal and abnormal events. Additionally, because the structure of the autoencoder itself determines the difficulty to obtain deep semantic information, we introduce a Secondary Encoder (SE) in each ForkNet, so as to recalibrate target features responses of latent feature representation. Our model is easy to be trained and robust to be applied, because it basically consists of some ResNet blocks without using complicated modules. Extensive experiments on the five publicly available benchmarks show that our model outperforms the existing state-of-the-art architectures, demonstrating our framework's effectiveness.

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Protein function prediction is crucial for understanding species evolution, including viral mutations. Gene ontology (GO) is a standardized representation framework for describing protein functions with annotated terms. Each ontology is a specific functional category containing multiple child ontologies, and the relationships of parent and child ontologies create a directed acyclic graph. Protein functions are categorized using GO, which divides them into three main groups: cellular component ontology, molecular function ontology, and biological process ontology. Therefore, the GO annotation of protein is a hierarchical multilabel classification problem. This hierarchical relationship introduces complexities such as mixed ontology problem, leading to performance bottlenecks in existing computational methods due to label dependency and data sparsity. To overcome bottleneck issues brought by mixed ontology problem, we propose ProFun-SOM, an innovative multilabel classifier that utilizes multiple sequence alignments (MSAs) to accurately annotate gene ontologies. ProFun-SOM enhances the initial MSAs through a reconstruction process and integrates them into a deep learning architecture. It then predicts annotations within the cellular component, molecular function, biological process, and mixed ontologies. Our evaluation results on three datasets (CAFA3, SwissProt, and NetGO2) demonstrate that ProFun-SOM surpasses state-of-the-art methods. This study confirmed that utilizing MSAs of proteins can effectively overcome the two main bottlenecks issues, label dependency and data sparsity, thereby alleviating the root problem, mixed ontology. A freely accessible web server is available at http://bliulab.net/ ProFun-SOM/.