Combining Flexible Region Design and Automatic Design to Enhance the Thermal Stability and Catalytic Efficiency of Leucine Dehydrogenase.

Leucine dehydrogenase (LeuDH, EC 1.4.1.9) can reversibly catalyze the oxidative deamination of l-leucine and some other specific α-amino acids to form the corresponding α-ketoacids. This reaction has great significance in the field of food additives and the pharmaceutical industry. The LeuDH from Exiguobacterium sibiricum (EsLeuDH) has high catalytic efficiency but limited thermal stability, hindering its widespread industrial application. In this study, a mutant N5F/I12L/A352Y of EsLeuDH (referred to as M2) was developed with enhanced thermal stability and catalytic activity through rational modification. The M2 mutant exhibits a half-life at 60 °C (t1/2(60 °C)) of 975.7 min and a specific activity of 69.6 U mg-1, which is 5.4 and 2.1 times higher than those of EsLeuDH, respectively. This research may facilitate the utilization of EsLeuDH at elevated temperatures, enhancing its potential for industrial applications. The findings offer a practical and efficient approach for optimizing LeuDH and other industrial enzymes.

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events.

Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, a data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK model`s performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.

Molecular Photoelectrochemical Energy Storage Materials for Coupled Solar Batteries.

ConspectusSolar-to-electrochemical energy storage is one of the essential solar energy utilization pathways alongside solar-to-electricity and solar-to-chemical conversion. A coupled solar battery enables direct solar-to-electrochemical energy storage via photocoupled ion transfer using photoelectrochemical materials with light absorption/charge transfer and redox capabilities. Common photoelectrochemical materials face challenges due to insufficient solar spectrum utilization, which restricts their redox potential window and constrains energy conversion efficiency. In contrast, molecular photoelectrochemical energy storage materials are promising for their mechanism of exciton-involved redox reaction that allows for extra energy utilization from hot excitons generated by superbandgap excitation and localized heat after absorption of sub-bandgap photons. This enables more efficient redox reactions with a less restricted redox potentials window and, thus, better utilization of the full solar spectrum. Despite these advantages, practical application remains elusive due to the mismatch between the short lifetime of the charge separation state (µs). This mismatch results in a significant portion of the photogenerated charges recombining before participating in desired electrochemical energy storage reactions, leading to diminished overall efficiency. It is therefore highly important to develop molecular materials with intrinsic prolonged charge separation state and extrinsic effective mass-electron transfer to enable efficient coupled solar batteries for practical applications.In this Account, we begin with an introduction of the general solar-to-electrochemical energy storage concept based on molecular photoelectrochemical energy storage materials, highlighting the advantages of periodic oxidative donor-reductive acceptor porous aggregate structures that have synergistic implications on charge separation state lifetime extension and mass-electron transfer. We then present our earliest trial on the design and application of molecular photoelectrochemical energy storage materials, which stimulated our subsequent studies on tuning electron donor and acceptor structures for enhanced charge separation and diverse photoelectrochemical redox reactions. Moreover, we introduce the best practices in the design and assembly of various coupled solar battery devices, along with our literature contributions and progresses in solar-to-electrochemical energy storage efficiency (ηSES) over nearly the past decade. Finally, we conclude by highlighting the universality of our strategies as essential design principles, spanning from regulating long-lived charge separation states and photocoupled ion transfer processes in molecular materials to the construction of efficient coupled solar batteries. We offer perspectives on the synergy between photovoltage and redox potentials and the practical significance of 3D printing, providing key evaluation indicators for large-scale application. This Account provides molecular level insights for the construction of high-efficiency photoelectrochemical energy storage materials and guidance for practical solar-to-electrochemical energy storage applications.

CT-based radiomics for predicting pathological grade in hepatocellular carcinoma.

Objective: To construct and validate radiomics models for hepatocellular carcinoma (HCC) grade predictions based on contrast-enhanced CT (CECT). Methods: Patients with pathologically confirmed HCC after surgery and underwent CECT at our institution between January 2016 and December 2020 were enrolled and randomly divided into training and validation datasets. With tumor segmentation and feature extraction, radiomic models were constructed using univariate analysis, followed by least absolute shrinkage and selection operator (LASSO) regression. In addition, combined models with clinical factors and radiomics scores (Radscore) were constructed using logistic regression. Finally, all models were evaluated using the receiver operating characteristic (ROC) curve with the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). Results: In total 242 patients were enrolled in this study, of whom 170 and 72 formed the training and validation datasets, respectively. The arterial phase and portal venous phase (AP+VP) radiomics model were evaluated as the best for predicting HCC pathological grade among all the models built in our study (AUC = 0.981 in the training dataset; AUC = 0.842 in the validation dataset) and was used to build a nomogram. Furthermore, the calibration curve and DCA indicated that the AP+VP radiomics model had a satisfactory prediction efficiency. Conclusions: Low- and high-grade HCC can be distinguished with good diagnostic performance using a CECT-based radiomics model.

Multiple non-covalent-interaction-directed supramolecular double helices: the orthogonality of hydrogen, halogen and chalcogen bonding.

In this study, a benzoselenadiazole- and pyridine-bifunctionalized hydrogen-bonded arylamide foldamer was synthesized. A co-crystallization experiment with 1,4-diiodotetrafluorobenzene showed that a new type of supramolecular double helices, which were induced by three orthogonal interactions, namely, three-center hydrogen bonding (O⋯H⋯O), I⋯N halogen bonding and Se⋯N chalcogen bonding, have been constructed in the solid state. This work presents a novel instance of multiple non-covalent interactions that work together to construct supramolecular architectures.

Topological valley Hall polariton condensation.

A photonic topological insulator features robust directional propagation and immunity to defect perturbations of the edge/surface state. Exciton-polaritons, that is, the hybrid quasiparticles of excitons and photons in semiconductor microcavities, have been proposed as a tunable nonlinear platform for emulating topological phenomena. However, mainly due to excitonic material limitations, experimental observations so far have not been able to enter the nonlinear condensation regime or only show localized condensation in one dimension. Here we show a topological propagating edge state with polariton condensation at room temperature and without any external magnetic field. We overcome material limitations by using excitonic CsPbCl3 halide perovskites with a valley Hall lattice design. The polariton lattice features a large bandgap of 18.8 meV and exhibits strong nonlinear polariton condensation with clear long-range spatial coherence across the critical pumping density. The geometric parameters and material composition of our nonlinear many-body photonic system platform can in principle be tailored to study topological phenomena of other interquasiparticle interactions.

Interfacial Engineering of MoS2@CoS2 Heterostructure Electrocatalysts for Effective pH-Universal Hydrogen Evolution Reaction.

The practical utilization of the hydrogen evolution reaction (HER) necessitates the creation of electrocatalysts that are both efficient and abundant in earth elements, capable of operating effectively within a wide pH range. However, this objective continues to present itself as an arduous obstacle. In this research, we propose the incorporation of sulfur vacancies in a novel heterojunction formed by MoS2@CoS2, designed to exhibit remarkable catalytic performances. This efficacy is attributed to the advantageous combination of the low work function and space charge zone at the interface between MoS2 and CoS2 in the heterojunction. The MoS2@CoS2 heterojunction manifests outstanding hydrogen evolution activity over an extensive pH range. Remarkably, achieving a current density of 10 mA cm-2 in aqueous solutions 1.0 M KOH, 0.5 M H2SO4, and 1.0 M phosphate-buffered saline (PBS), respectively, requires only an overpotential of 48, 62, and 164 mV. The Tafel slopes for each case are 43, 32, and 62 mV dec-1, respectively. In this study, the synergistic effect of MoS2 and CoS2 is conducive to electron transfer, making the MoS2@CoS2 heterojunction show excellent electrocatalytic performance. The synergistic effects arising from the heterojunction and sulfur vacancy not only contribute to the observed catalytic prowess but also provide a valuable model and reference for the exploration of other efficient electrocatalysts. This research marks a significant stride toward overcoming the challenges associated with developing electrocatalysts for practical hydrogen evolution applications.

CCR5 antagonist maraviroc alleviates doxorubicin-induced neuroinflammation and neurobehavioral deficiency by regulating NF-κB/NLRP3 signaling in a breast cancer mouse model.

The chemotherapeutic agent Doxorubicin (DOX) is known to cause chemotherapy-induced cognitive impairment (CICI). Maraviroc, a potent C-C chemokine receptor 5 (CCR5) antagonist, shows neuroprotective properties, while its role in CICI remains unclear. This study determined the therapeutic potential of maraviroc on CICI. Adult C57BL/6J mice with implanted breast cancer cells received four weekly intraperitoneal injections of saline (Control group), 5 mg/kg DOX (DOX group), 10 mg/kg maraviroc (MVC group), or 5 mg/kg DOX with 10 mg/kg maraviroc (DOX + MVC group). The Morris Water Maze (MWM) was used for neurobehavioural test. Western blot analysis and immunofluorescence were used to evaluate the expressions of inflammatory markers, apoptosis-related proteins, and synaptic-related proteins. The volume and weight of tumor were also evaluated after treatments. DOX treatment significantly increased chemokines (CCL3, CCL4) and inflammatory cytokines (IL-1ß, TNF-α) in tumor-bearing mice hippocampus. While maraviroc administration reduced hippocampal proinflammatory factors compared to the DOX group. Furthermore, it also lowered apoptosis markers, restored synaptic proteins levels, and inhibited the NF-κB/NLRP3 pathway. Accordingly, maraviroc treatment significantly improved DOX-induced neurobehavioural impairments as evidenced by an increased number of platform crossings and percentage of target quadrant time in the MWM test. Additionally, when combined with DOX, maraviroc had additional inhibitory effects on tumor growth. These findings suggest that maraviroc can mitigate DOX-induced CICI by suppressing elevated proinflammatory chemokines and cytokines through the NF-κB/NLRP3 pathway, potentially offering an anti-tumor benefit. This research presents a promising therapeutic approach for DOX-induced CICI, enhancing the safety and efficacy of cancer treatments.

O-GlcNAcylation Facilitates the Interaction between Keratin 18 and Isocitrate Dehydrogenases and Potentially Influencing Cholangiocarcinoma Progression.

Glycosylation plays a pivotal role in the intricate landscape of human cholangiocarcinoma (CCA), actively participating in key pathophysiological processes driving tumor progression. Among the various glycosylation modifications, O-linked ß-N-acetyl-glucosamine modification (O-GlcNAcylation) emerges as a dynamic regulator influencing diverse tumor-associated biological activities. In this study, we employed a state-of-the-art chemical proteomic approach to analyze intact glycopeptides, unveiling the critical role of O-GlcNAcylation in orchestrating Keratin 18 (K18) and its interplay with tricarboxylic acid (TCA) cycle enzymes, specifically isocitrate dehydrogenases (IDHs), to propel CCA progression. Our findings shed light on the mechanistic intricacies of O-GlcNAcylation, revealing that site-specific modification of K18 on Ser 30 serves as a stabilizing factor, amplifying the expression of cell cycle checkpoints. This molecular event intricately fosters cell cycle progression and augments cellular growth in CCA. Notably, the interaction between O-GlcNAcylated K18 and IDHs orchestrates metabolic reprogramming by down-regulating citrate and isocitrate levels while elevating α-ketoglutarate (α-KG). These metabolic shifts further contribute to the overall tumorigenic potential of CCA. Our study thus expands the current understanding of protein O-GlcNAcylation and introduces a new layer of complexity to post-translational control over metabolism and tumorigenesis.

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance.

Spatially resolved transcriptomics has revolutionized genome-scale transcriptomic profiling by providing high-resolution characterization of transcriptional patterns. Here, we present our spatial transcriptomics analysis framework, MUSTANG (MUlti-sample Spatial Transcriptomics data ANalysis with cross-sample transcriptional similarity Guidance), which is capable of performing multi-sample spatial transcriptomics spot cellular deconvolution by allowing both cross-sample expression-based similarity information sharing as well as spatial correlation in gene expression patterns within samples. Experiments on a semi-synthetic spatial transcriptomics dataset and three real-world spatial transcriptomics datasets demonstrate the effectiveness of MUSTANG in revealing biological insights inherent in the cellular characterization of tissue samples under study.

Redistribution of defective mitochondria-mediated dihydroorotate dehydrogenase imparts 5-fluorouracil resistance in colorectal cancer.

Although 5-fluorouracil (5-FU) is the primary chemotherapy treatment for colorectal cancer (CRC), its efficacy is limited by drug resistance. Ferroptosis activation is a promising treatment for 5-FU-resistant cancer cells; however, potential therapeutic targets remain elusive. This study investigated ferroptosis vulnerability and dihydroorotate dehydrogenase (DHODH) activity using stable, 5-FU-resistant CRC cell lines and xenograft models. Ferroptosis was characterized by measuring malondialdehyde levels, assessing lipid metabolism and peroxidation, and using mitochondrial imaging and assays. DHODH function is investigated through gene knockdown experiments, tumor behavior assays, mitochondrial import reactions, intramitochondrial localization, enzymatic activity analyses, and metabolomics assessments. Intracellular lipid accumulation and mitochondrial DHODH deficiency led to lipid peroxidation overload, weakening the defense system of 5-FU-resistant CRC cells against ferroptosis. DHODH, primarily located within the inner mitochondrial membrane, played a crucial role in driving intracellular pyrimidine biosynthesis and was redistributed to the cytosol in 5-FU-resistant CRC cells. Cytosolic DHODH, like its mitochondrial counterpart, exhibited dihydroorotate catalytic activity and participated in pyrimidine biosynthesis. This amplified intracellular pyrimidine pools, thereby impeding the efficacy of 5-FU treatment through molecular competition. These findings contribute to the understanding of 5-FU resistance mechanisms and suggest that ferroptosis and DHODH are promising therapeutic targets for patients with CRC exhibiting resistance to 5-FU.

PolyQ-expanded ataxin-2 aggregation impairs cellular processing-body homeostasis via sequestering the RNA helicase DDX6.

Ataxin-2 (Atx2) is a polyglutamine (polyQ) tract-containing RNA-binding protein, while its polyQ expansion may cause protein aggregation that is implicated in the pathogenesis of neurodegenerative diseases such as spinocerebellar ataxia type 2 (SCA2). However, the molecular mechanism underlying how Atx2 aggregation contributes to the proteinopathies remains elusive. Here, we investigated the influence of Atx2 aggregation on the assembly and functionality of cellular processing bodies (P-bodies) by using biochemical and fluorescence imaging approaches. We have revealed that polyQ-expanded (PQE) Atx2 sequesters the DEAD-box RNA helicase (DDX6), an essential component of P-bodies, into aggregates or puncta via some RNA sequences. The N-terminal like-Sm (LSm) domain of Atx2 (residues 82-184) and the C-terminal helicase domain of DDX6 are responsible for the interaction and specific sequestration. Moreover, sequestration of DDX6 may aggravate pre-mRNA mis-splicing, and interfere with the assembly of cellular P-bodies, releasing the endoribonuclease MARF1 that promotes mRNA decay and translational repression. Rescuing the DDX6 protein level can recover the assembly and functionality of P-bodies preventing targeted mRNA from degradation. This study provides a line of evidence for sequestration of the P-body components and impairment of the P-body homeostasis in dysregulating RNA metabolism, which is implicated in the disease pathologies and a potential therapeutic target.

The effect of cognitive impairment based on Mini-Mental State Examination (MMSE) on suicidal tendency in patients with schizophrenia: A large cross-sectional study.

BACKGROUND: The effect of cognitive function on suicidal tendency in patients with schizophrenia is still inconclusive. This study aimed to explore the effect of cognitive impairment on suicidal tendency in schizophrenia patients and the risk factors of suicidal tendency in schizophrenia patients with cognitive impairment. METHODS: A total of 988 subjects were recruited for this study and finally 517 patients were included in the statistical analysis. Sociodemographic information was collected for each subject. Mini-Mental State Examination (MMSE) was used to assess patients' cognitive functioning. In addition, the Positive and Negative Syndrome Scale (PANSS) positive subscale, Insomnia Severity Index (ISI), and Beck Scale for Suicide Ideation (BSI) were used to assess psychotic symptoms, severity of insomnia, and intensity of suicidal ideation, respectively. RESULTS: Schizophrenia patients with cognitive dysfunction were significantly less likely to develop suicidal tendencies than those without cognitive dysfunction (P < 0.05, OR = 0.58, 95%CI: 0.39-0.81). In patients with cognitive impairment, those with suicidal tendency had substantially higher scores on BSI, ISI, EC, PD, IRI, F1, and PANSS positive subscale, and took more types of antipsychotic drugs than those without suicidal tendency (all P < 0.05), and the results of binary logistic regression analysis showed that, PANSS positive subscale score (B = 0.06, p = 0.04, OR = 1.07, 95%CI: 1.00-1.13) was a risk factor for suicidal tendencies. CONCLUSIONS: Our findings suggest that schizophrenia patients with cognitive dysfunction are significantly less likely to develop suicidal tendencies. Moreover, positive symptom is a risk factor for suicidal tendencies in schizophrenia patients with cognitive dysfunction.

Multiplexed representation of others in the hippocampal CA1 subfield of female mice.

Hippocampal place cells represent the position of a rodent within an environment. In addition, recent experiments show that the CA1 subfield of a passive observer also represents the position of a conspecific performing a spatial task. However, whether this representation is allocentric, egocentric or mixed is less clear. In this study we investigated the representation of others during free behavior and in a task where female mice learned to follow a conspecific for a reward. We found that most cells represent the position of others relative to self-position (social-vector cells) rather than to the environment, with a prevalence of purely egocentric coding modulated by context and mouse identity. Learning of a pursuit task improved the tuning of social-vector cells, but their number remained invariant. Collectively, our results suggest that the hippocampus flexibly codes the position of others in multiple coordinate systems, albeit favoring the self as a reference point.

Targeting squalene epoxidase restores anti-PD-1 efficacy in metabolic dysfunction-associated steatohepatitis-induced hepatocellular carcinoma.

OBJECTIVE: Squalene epoxidase (SQLE) promotes metabolic dysfunction-associated steatohepatitis-associated hepatocellular carcinoma (MASH-HCC), but its role in modulating the tumour immune microenvironment in MASH-HCC remains unclear. DESIGN: We established hepatocyte-specific Sqle transgenic (tg) and knockout mice, which were subjected to a choline-deficient high-fat diet plus diethylnitrosamine to induce MASH-HCC. SQLE function was also determined in orthotopic and humanised mice. Immune landscape alterations of MASH-HCC mediated by SQLE were profiled by single-cell RNA sequencing and flow cytometry. RESULTS: Hepatocyte-specific Sqle tg mice exhibited a marked increase in MASH-HCC burden compared with wild-type littermates, together with decreased tumour-infiltrating functional IFN-γ+ and Granzyme B+ CD8+ T cells while enriching Arg-1+ myeloid-derived suppressor cells (MDSCs). Conversely, hepatocyte-specific Sqle knockout suppressed tumour growth with increased cytotoxic CD8+ T cells and reduced Arg-1+ MDSCs, inferring that SQLE promotes immunosuppression in MASH-HCC. Mechanistically, SQLE-driven cholesterol accumulation in tumour microenvironment underlies its effect on CD8+ T cells and MDSCs. SQLE and its metabolite, cholesterol, impaired CD8+ T cell activity by inducing mitochondrial dysfunction. Cholesterol depletion in vitro abolished the effect of SQLE-overexpressing MASH-HCC cell supernatant on CD8+ T cell suppression and MDSC activation, whereas cholesterol supplementation had contrasting functions on CD8+ T cells and MDSCs treated with SQLE-knockout supernatant. Targeting SQLE with genetic ablation or pharmacological inhibitor, terbinafine, rescued the efficacy of anti-PD-1 treatment in MASH-HCC models. CONCLUSION: SQLE induces an impaired antitumour response in MASH-HCC via attenuating CD8+ T cell function and augmenting immunosuppressive MDSCs. SQLE is a promising target in boosting anti-PD-1 immunotherapy for MASH-HCC.

CBP/P300 BRD Inhibition Reduces Neutrophil Accumulation and Activates Antitumor Immunity in TNBC.

Tumor-associated neutrophils (TANs) have been shown to promote immunosuppression and tumor progression, and a high TAN frequency predicts poor prognosis in triple-negative breast cancer (TNBC). Dysregulation of CREB binding protein (CBP)/P300 function has been observed with multiple cancer types. The bromodomain (BRD) of CBP/P300 has been shown to regulate its activity. In this study, we found that IACS-70654, a novel and selective CBP/P300 BRD inhibitor, reduced TANs and inhibited the growth of neutrophil-enriched TNBC models. In the bone marrow, CBP/P300 BRD inhibition reduced the tumor-driven abnormal differentiation and proliferation of neutrophil progenitors. Inhibition of CBP/P300 BRD also stimulated the immune response by inducing an IFN response and MHCI expression in tumor cells and increasing tumor-infiltrated CTLs. Moreover, IACS-70654 improved the response of a neutrophil-enriched TNBC model to docetaxel and immune checkpoint blockade. This provides a rationale for combining a CBP/P300 BRD inhibitor with standard-of-care therapies in future clinical trials for neutrophil-enriched TNBC.

A novel miR-466l-3p/FGF23 axis promotes osteogenic differentiation of human bone marrow mesenchymal stem cells.

BACKGROUND: MicroRNAs (miRNAs) regulate osteogenic differentiation processes and influence the development of osteoporosis (OP). This study aimed to investigate the potential role of miR-466 l-3p in OP. METHODS: The expression levels of miR-466 l-3p and fibroblast growth factor 23 (FGF23) were quantified in the trabeculae of the femoral neck of 40 individuals with or without OP using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The impact of miR-466 l-3p or FGF23 expression on cell proliferation and the expression levels of runt-related transcription factor 2 (RUNX2), type I collagen (Col1), osteocalcin (OCN), osterix (OSX) and dentin matrix protein 1 (DMP1) was quantified in human bone marrow mesenchymal stem cells (hBMSCs) overexpressing miR-466 l-3p. Furthermore, alkaline phosphatase (ALP) staining and alizarin red staining were performed to measure ALP activity and the levels of calcium deposition, respectively. In addition, bioinformatics analysis, luciferase reporter assays, and RNA pull-down assays were conducted to explore the molecular mechanisms underlying the effects of miR-466 l-3p and FGF23 in osteogenic differentiation of hBMSCs. RESULTS: The expression levels of miR-466 l-3p were significantly lower in femoral neck trabeculae of patients with OP than in the control cohort, whereas FGF23 levels exhibited the opposite trend. Furthermore, miR-466 l-3p levels were upregulated and FGF23 levels were downregulated in hBMSCs during osteogenic differentiation. Moreover, the high miR-466 l-3p expression enhanced the mRNA expression of RUNX2, Col1, OCN, OSX and DMP1, as well as cell proliferation, ALP activity, and calcium deposition in hBMSCs. FGF23 was found to be a direct target of miR-466 l-3p. FGF23 overexpression downregulated the expression of osteoblast markers and inhibited the osteogenic differentiation induced by miR-466 l-3p overexpression. qRT-PCR and Western blot assays showed that miR-466 l-3p overexpression decreased the expression levels of mRNAs and proteins associated with the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway, whereas FGF23 upregulation exhibited the opposite trend. CONCLUSION: In conclusion, these findings suggest that miR-466 l-3p enhances the osteogenic differentiation of hBMSCs by suppressing FGF23 expression, ultimately preventing OP.

Bulk and single-cell transcriptome profiling identify potential cellular targets of the long noncoding RNA Gas5 in renal fibrosis.

The long noncoding RNA growth arrest-specific 5 (lncRNA Gas5) is implicated in various kidney diseases. In this study, we investigated the lncRNA Gas5 expression profile and its critical role as a potential biomarker in the progression of chronic kidney disease. Subsequently, we assessed the effect of lncRNA Gas5 deletion on renal fibrosis induced by unilateral ureteral obstruction (UUO). The results indicated that loss of lncRNA Gas5 exacerbates UUO-induced renal injury and extracellular matrix deposition. Notably, the deletion of lncRNA Gas5 had a similar effect on control mice. The fibrogenic phenotype observed in mice lacking lncRNA Gas5 correlates with peroxisome proliferator-activated receptor (PPAR) signaling pathway activation and aberrant cytokine and chemokine reprogramming. Single-cell RNA sequencing analysis revealed key transcriptomic features of fibroblasts after Gas5 deletion, revealing heterogeneous cellular states suggestive of a propensity for renal fibrosis. Our findings indicate that lncRNA Gas5 regulates the differentiation and activation of immune cells and the transcription of key genes in the PPAR signaling pathway. These data offer novel insights into the involvement of lncRNA Gas5 in renal fibrosis, potentially paving the way for innovative diagnostic and therapeutic targets.

Artificial intelligence-based classification of breast lesion from contrast enhanced mammography: a multicenter study.

PURPOSE: The authors aimed to establish an artificial intelligence (AI)-based method for preoperative diagnosis of breast lesions from contrast enhanced mammography (CEM) and to explore its biological mechanism. MATERIALS AND METHODS: This retrospective study includes 1430 eligible patients who underwent CEM examination from June 2017 to July 2022 and were divided into a construction set (n=1101), an internal test set (n=196), and a pooled external test set (n=133). The AI model adopted RefineNet as a backbone network, and an attention sub-network, named convolutional block attention module (CBAM), was built upon the backbone for adaptive feature refinement. An XGBoost classifier was used to integrate the refined deep learning features with clinical characteristics to differentiate benign and malignant breast lesions. The authors further retrained the AI model to distinguish in situ and invasive carcinoma among breast cancer candidates. RNA-sequencing data from 12 patients were used to explore the underlying biological basis of the AI prediction. RESULTS: The AI model achieved an area under the curve of 0.932 in diagnosing benign and malignant breast lesions in the pooled external test set, better than the best-performing deep learning model, radiomics model, and radiologists. Moreover, the AI model has also achieved satisfactory results (an area under the curve from 0.788 to 0.824) for the diagnosis of in situ and invasive carcinoma in the test sets. Further, the biological basis exploration revealed that the high-risk group was associated with the pathways such as extracellular matrix organization. CONCLUSIONS: The AI model based on CEM and clinical characteristics had good predictive performance in the diagnosis of breast lesions.

Prevalence, demographics and clinical characteristics of Internet addiction among Chinese adolescents with schizophrenia.

Introduction: Several studies have reported that Internet addiction (IA) is more prevalent in the psychiatric disorder population. However, the prevalence of IA and its relationship with clinical variables among Chinese adolescents with schizophrenia is unclear. This study sought to investigate the prevalence of IA and its clinical correlates in Chinese adolescents with schizophrenia, which has not yet been reported. Methods: Seven hundred and six inpatient adolescents with schizophrenia were recruited. All patients underwent Young's Internet Addiction Test (IAT) to measure Internet addiction, as well as the Positive and Negative Syndrome Scale (PANSS) for psychopathology. Results: Our results showed that 186 patients had a total IAT score of 50 or more, bringing the prevalence of IA to 26.3%. Girls (21.7%, 92/424) were less likely to have combined IA than boys (33.3%, 94/282). Compared to those patients without IA, patients with IA had better socioeconomic status, higher probability of living in the city, higher levels of depressive symptoms, excited symptoms, and lower levels of concrete symptoms and PANSS total scores (all p<0.05). Further binary logistic regression analysis indicated that good socioeconomic status, living in the city and PANSS total scores were significantly associated with IA. In addition, correlation analysis showed significant correlations between IA total score and the following parameters: good socioeconomic status, living in the city, negative subscore, concrete subscore, depression subscore, excited subscore and PANSS total score (Bonferroni corrected all p <0.05). Conclusion: The results of this study indicate that the prevalence of IA in Chinese adolescents with schizophrenia is higher than that in the general population. Several demographic and clinical variables are risk factors for IA in adolescents with schizophrenia.