FBXO3 stabilizes USP4 and Twist1 to promote PI3K-mediated breast cancer metastasis.

Tumor metastasis is the major cause of breast cancer morbidity and mortality. It has been reported that the F-box protein FBXO3 functions as an E3 ubiquitin ligase in regulating various biological processes, including host autoimmune, antiviral innate immunity, and inflammatory response. However, the role of FBXO3 in tumor metastasis remains elusive. We have previously shown that ΔNp63α is a common inhibitory target in oncogene-induced cell motility and tumor metastasis. In this study, we show that FBXO3 plays a vital role in PI3K-mediated breast cancer metastasis independent of its E3 ligase activity and ΔNp63α in breast cancer cells and in mouse. FBXO3 can bind to and stabilize USP4, leading to Twist1 protein stabilization and increased breast cancer cell migration and tumor metastasis. Mechanistically, FBXO3 disrupts the interaction between USP4 and aspartyl aminopeptidase (DNPEP), thereby protecting USP4 from DNPEP-mediated degradation. Furthermore, p110αH1047R facilitates the phosphorylation and stabilization of FBXO3 in an ERK1-dependent manner. Knockdown of either FBXO3 or USP4 leads to significant inhibition of PI3K-induced breast cancer metastasis. Clinically, elevated expression of p110α/FBXO3/USP4/Twist1 is associated with poor overall survival (OS) and recurrence-free survival (RFS) of breast cancer patients. Taken together, this study reveals that the FBXO3-USP4-Twist1 axis is pivotal in PI3K-mediated breast tumor metastasis and that FBXO3/USP4 may be potential therapeutic targets for breast cancer treatment.

Mycn regulates intestinal development through ribosomal biogenesis in a zebrafish model of Feingold syndrome 1.

Feingold syndrome type 1, caused by loss-of-function of MYCN, is characterized by varied phenotypes including esophageal and duodenal atresia. However, no adequate model exists for studying the syndrome's pathological or molecular mechanisms, nor is there a treatment strategy. Here, we developed a zebrafish Feingold syndrome type 1 model with nonfunctional mycn, which had severe intestinal atresia. Single-cell RNA-seq identified a subcluster of intestinal cells that were highly sensitive to Mycn, and impaired cell proliferation decreased the overall number of intestinal cells in the mycn mutant fish. Bulk RNA-seq and metabolomic analysis showed that expression of ribosomal genes was down-regulated and that amino acid metabolism was abnormal. Northern blot and ribosomal profiling analysis showed abnormal rRNA processing and decreases in free 40S, 60S, and 80S ribosome particles, which led to impaired translation in the mutant. Besides, both Ribo-seq and western blot analysis showed that mTOR pathway was impaired in mycn mutant, and blocking mTOR pathway by rapamycin treatment can mimic the intestinal defect, and both L-leucine and Rheb, which can elevate translation via activating TOR pathway, could rescue the intestinal phenotype of mycn mutant. In summary, by this zebrafish Feingold syndrome type 1 model, we found that disturbance of ribosomal biogenesis and blockage of protein synthesis during development are primary causes of the intestinal defect in Feingold syndrome type 1. Importantly, our work suggests that leucine supplementation may be a feasible and easy treatment option for this disease.

Abalign: a comprehensive multiple sequence alignment platform for B-cell receptor immune repertoires.

The utilization of high-throughput sequencing (HTS) for B-cell receptor (BCR) immune repertoire analysis has become widespread in the fields of adaptive immunity and antibody drug development. However, the sheer volume of sequences generated by these experiments presents a challenge in data processing. Specifically, multiple sequence alignment (MSA), a critical aspect of BCR analysis, remains inadequate for handling massive BCR sequencing data and lacks the ability to provide immunoglobulin-specific information. To address this gap, we introduce Abalign, a standalone program specifically designed for ultrafast MSA of BCR/antibody sequences. Benchmark tests demonstrate that Abalign achieves comparable or even better accuracy than state-of-the-art MSA tools, and shows remarkable advantages in terms of speed and memory consumption, reducing the time required for high-throughput analysis from weeks to hours. In addition to its alignment capabilities, Abalign offers a broad range of BCR analysis features, including extracting BCRs, constructing lineage trees, assigning VJ genes, analyzing clonotypes, profiling mutations, and comparing BCR immune repertoires. With its user-friendly graphic interface, Abalign can be easily run on personal computers instead of computing clusters. Overall, Abalign is an easy-to-use and effective tool that enables researchers to analyze massive BCR/antibody sequences, leading to new discoveries in the field of immunoinformatics. The software is freely available at http://cao.labshare.cn/abalign/.

Prognostic value of baseline neutrophil/lymphocyte ratio in HER2-positive metastatic breast cancer: exploratory analysis of data from the CLEOPATRA trial.

PURPOSE: This study aimed to evaluate the prognostic role of the baseline neutrophil/lymphocyte ratio (NLR) in HER2-positive metastatic breast cancer (MBC) patients treated with trastuzumab/pertuzumab. EXPERIMENTAL DESIGN: Data from 780 patients from the CLEOPATRA trial and 248 local patients were collected. Patients were divided into the low and high NLR subgroups by the NLR cutoff value. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) methods were used to control bias. Associations between the NLR and progression-free survival (PFS) and overall survival (OS) were analyzed. RESULTS: The baseline characteristics of the subgroups were well balanced after PSM and IPTW. A low baseline NLR was associated with better PFS and OS in the trastuzumab and docetaxel (TH) group in the unadjusted, PSM and IPTW models. After IPTW, a low NLR, versus a high NLR, was associated with improved PFS (HR 1.35, 95% CI 1.07-1.70, P = 0.012) and OS (HR 1.47, 95% CI 1.12-1.94, P = 0.006) in the TH group. In patients undergoing treatment with trastuzumab and pertuzumab and docetaxel (THP), a low baseline NLR was also correlated with better PFS but not OS across the three models. After IPTW, a low NLR was associated with better PFS (HR 1.52, 95% CI 1.20-1.93, P = 0.001) than a high NLR in the THP group. Multivariate analyses showed that a low baseline NLR was a predictor for PFS and OS in the TH group and for PFS in the THP group in all three models. In the real-world setting, a low baseline NLR was a predictor of better PFS among patients treated with docetaxel plus trastuzumab without or with pertuzumab in the multivariate model (P = 0.015 and 0.008, respectively). CONCLUSIONS: A low baseline NLR is associated with better survival outcomes among HER2-positive MBC patients receiving docetaxel plus trastuzumab/pertuzumab as first-line therapy.

Serum dithiothreitol-oxidizing capacity (DOC) is a promising biomarker for excluding significant liver fibrosis: a proof-of-concept study.

BACKGROUND: APRI and FIB-4 scores are used to exclude clinically significant fibrosis (defined as stage ≥ F2) in patients with chronic viral hepatitis. However, the cut-offs for these scores (generated by Youden indices) vary between different patient cohorts. This study aimed to evaluate whether serum dithiothreitol-oxidizing capacity (DOC), i.e., a surrogate test of quiescin sulfhydryl oxidase-1, which is a matrix remodeling enzyme, could be used to non-invasively identify significant fibrosis in patients with various chronic liver diseases (CLDs). METHODS: Diagnostic performance of DOC was compared with APRI and FIB-4 for identifying significant fibrosis. ROC curve analyses were undertaken in: a) two chronic hepatitis B (CHB) cohorts, independently established from hospitals in Wenzhou (n = 208) and Hefei (n = 120); b) a MASLD cohort from Wenzhou hospital (n = 122); and c) a cohort with multiple CLD etiologies (except CHB and MASLD; n = 102), which was identified from patients in both hospitals. Cut-offs were calculated using the Youden index. All CLD patients (n = 552) were then stratified by age for ROC curve analyses and cut-off calculations. RESULTS: Stratified by CLD etiology or age, ROC curve analyses consistently showed that the DOC test was superior to APRI and FIB-4 for discriminating between clinically significant fibrosis and no fibrosis, when APRI and FIB-4 showed poor/modest diagnostic performance (P < 0.05, P < 0.01 and P < 0.001 in 3, 1 and 3 cohort comparisons, respectively). Conversely, the DOC test was equivalent to APRI and FIB-4 when all tests showed moderate/adequate diagnostic performances (P > 0.05 in 11 cohort comparisons). DOC had a significant advantage over APRI or FIB-4 scores for establishing a uniform cut-off independently of age and CLD etiology (coefficients of variation of DOC, APRI and FIB-4 cut-offs were 1.7%, 22.9% and 47.6% in cohorts stratified by CLD etiology, 2.0%, 26.7% and 29.5% in cohorts stratified by age, respectively). The uniform cut-off was 2.13, yielded from all patients examined. Surprisingly, the uniform cut-off was the same as the DOC upper limit of normal with a specificity of 99%, estimated from 275 healthy control individuals. Hence, the uniform cut-off should possess a high negative predictive value for excluding significant fibrosis in primary care settings. A high DOC cut-off with 97.5% specificity could be used for detecting significant fibrosis (≥ F2) with an acceptable positive predictive value (87.1%). CONCLUSIONS: This proof-of-concept study suggests that the DOC test may efficiently rule out and rule in significant liver fibrosis, thereby reducing the numbers of unnecessary liver biopsies. Moreover, the DOC test may be helpful for clinicians to exclude significant liver fibrosis in the general population.

Defective Tungsten Oxides with Stacking Faults for Proton Exchange Membrane Green-Hydrogen Generation.

Defects can introduce atomic structural modulation and tailor performance of materials. Herein, it demonstrates that semiconductor WO3 with inert electrocatalytic behavior can be activated through defect-induced tensile strains. Structural characterizations reveal that when simply treated in Ar/H2 atmosphere, oxygen vacancies will generate in WO3 and cause defective structures. Stacking faults are found in defects, thus modulating electronic structure and transforming electrocatalytic-inert WO3 into highly active electrocatalysts. Density functional theory (DFT) calculations are performed to calculate *H adsorption energies on various WOx surfaces, revealing the oxygen vacancy composition and strain predicted to optimize the catalytic activity of hydrogen evolution reaction (HER). Such defective tungsten oxides can be integrated into commercial proton exchange membrane (PEM) electrolyser with comparable performance toward Pt-based PEM. This work demonstrates defective metal oxides as promising non-noble metal catalysts for commercial PEM green-hydrogen generation.

Operando Spectroscopy Observation of Mo Clusters-Ti3 C2 TX Catalyst/Support Interface's Dynamic Evolution in Hydrogen Evolution Reaction.

The interaction between catalyst and support plays an important role in electrocatalytic hydrogen evolution (HER), which may explain the improvement in performance by phase transition or structural remodeling. However, the intrinsic behavior of these catalysts (dynamic evolution of the interface under bias, structural/morphological transformation, stability) has not been clearly monitored, while the operando technology does well in capturing the dynamic changes in the reaction process in real time to determine the actual active site. In this paper, nitrogen-doped molybdenum atom-clusters on Ti3 C2 TX (MoACs /N-Ti3 C2 TX ) is used as a model catalyst to reveal the dynamic evolution of MoAcs on Ti3 C2 TX during the HER process. Operando X-ray absorption structure (XAS) theoretical calculation and in situ Raman spectroscopy showed that the Mo cluster structure evolves to a 6-coordinated monatomic Mo structure under working conditions, exposing more active sites and thus improving the catalytic performance. It shows excellent HER performance comparable to that of commercial Pt/C, including an overpotential of 60 mV at 10 mA cm-2 , a small Tafel slope (56 mV dec-1 ), and high activity and durability. This study provides a unique perspective for investigating the evolution of species, interfacial migration mechanisms, and sources of activity-enhancing compounds in the process of electroreduction.

HMGB1-RAGE axis contributes to myocardial ischemia/reperfusion injury via regulation of cardiomyocyte autophagy and apoptosis in diabetic mice.

Patients with acute myocardial infarction complicated with diabetes are more likely to develop myocardial ischemia/reperfusion (I/R) injury (MI/RI) during reperfusion therapy. Both HMGB1 and RAGE play important roles in MI/RI. However, the specific mechanisms of HMGB1 associated with RAGE are not fully clarified in diabetic MI/RI. This study aimed to investigate whether the HMGB1-RAGE axis induces diabetic MI/RI via regulating autophagy and apoptosis. A db/db mouse model of MI/RI was established, where anti-HMGB1 antibody and RAGE inhibitor (FPS-ZM1) were respectively injected after 10 min of reperfusion. The results showed that treatment with anti-HMGB1 significantly reduced the infarct size, serum LDH, and CK-MB level. Similar situations also occurred in mice administrated with FPS-ZM1, though the HMGB1 level was unchanged. Then, we found that treatment with anti-HMGB1 or FPS-ZM1 performed the same effects in suppressing the autophagy and apoptosis, as reflected by the results of lower LAMP2 and LC3B levels, increased Bcl-2 level, reduced BAX and caspase-3 levels. Moreover, the Pink1/Parkin levels were also inhibited at the same time. Collectively, this study indicates that the HMGB1-RAGE axis aggravated diabetic MI/RI via apoptosis and Pink1/Parkin mediated autophagy pathways, and inhibition of HMGB1 or RAGE contributes to alleviating those adverse situations.

FitDock: protein-ligand docking by template fitting.

Protein-ligand docking is an essential method in computer-aided drug design and structural bioinformatics. It can be used to identify active compounds and reveal molecular mechanisms of biological processes. A successful docking usually requires thorough conformation sampling and scoring, which are computationally expensive and difficult. Recent studies demonstrated that it can be beneficial to docking with the guidance of existing similar co-crystal structures. In this work, we developed a protein-ligand docking method, named FitDock, which fits initial conformation to the given template using a hierarchical multi-feature alignment approach, subsequently explores the possible conformations and finally outputs refined docking poses. In our comprehensive benchmark tests, FitDock showed 40%-60% improvement in terms of docking success rate and an order of magnitude faster over popular docking methods, if template structures exist (> 0.5 ligand similarity). FitDock has been implemented in a user-friendly program, which could serve as a convenient tool for drug design and molecular mechanism exploration. It is now freely available for academic users at http://cao.labshare.cn/fitdock/.

Y4 RNA fragments from cardiosphere-derived cells ameliorate diabetic myocardial ischemia‒reperfusion injury by inhibiting protein kinase C ß-mediated macrophage polarization.

The specific pathophysiological pathways through which diabetes exacerbates myocardial ischemia/reperfusion (I/R) injury remain unclear; however, dysregulation of immune and inflammatory cells, potentially driven by abnormalities in their number and function due to diabetes, may play a significant role. In the present investigation, we simulated myocardial I/R injury by inducing ischemia through ligation of the left anterior descending coronary artery in mice for 40 min, followed by reperfusion for 24 h. Previous studies have indicated that protein kinase Cß (PKCß) is upregulated under hyperglycemic conditions and is implicated in the development of various diabetic complications. The Y4 RNA fragment is identified as the predominant small RNA component present in the extracellular vesicles of cardio sphere-derived cells (CDCs), exhibiting notable anti-inflammatory properties in the contexts of myocardial infarction and cardiac hypertrophy. Our investigation revealed that the administration of Y4 RNA into the ventricular cavity of db/db mice following myocardial I/R injury markedly enhanced cardiac function. Furthermore, Y4 RNA was observed to facilitate M2 macrophage polarization and interleukin-10 secretion through the suppression of PKCß activation. The mechanism by which Y4 RNA affects PKCß by regulating macrophage activation within the inflammatory environment involves the inhibition of ERK1/2 phosphorylation In our study, the role of PKCß in regulating macrophage polarization during myocardial I/R injury was investigated through the use of PKCß knockout mice. Our findings indicate that PKCß plays a crucial role in modulating the inflammatory response associated with macrophage activation in db/db mice experiencing myocardial I/R, with a notable exacerbation of this response observed upon significant upregulation of PKCß expression. In vitro studies further elucidated the protective mechanism by which Y4 RNA modulates the PKCß/ERK1/2 signaling pathway to induce M2 macrophage activation. Overall, our findings suggest that Y4 RNA plays an anti-inflammatory role in diabetic I/R injury, suggesting a novel therapeutic approach for managing myocardial I/R injury in diabetic individuals.

Noncanonical TGF-ß signaling leads to FBXO3-mediated degradation of ΔNp63α promoting breast cancer metastasis and poor clinical prognosis.

Transforming growth factor-ß (TGF-ß) signaling plays a critical role in promoting epithelial-to-mesenchymal transition (EMT), cell migration, invasion, and tumor metastasis. ΔNp63α, the major isoform of p63 protein expressed in epithelial cells, is a key transcriptional regulator of cell adhesion program and functions as a critical metastasis suppressor. It has been documented that the expression of ΔNp63α is tightly controlled by oncogenic signaling and is frequently reduced in advanced cancers. However, whether TGF-ß signaling regulates ΔNp63α expression in promoting metastasis is largely unclear. In this study, we demonstrate that activation of TGF-ß signaling leads to stabilization of E3 ubiquitin ligase FBXO3, which, in turn, targets ΔNp63α for proteasomal degradation in a Smad-independent but Erk-dependent manner. Knockdown of FBXO3 or restoration of ΔNp63α expression effectively rescues TGF-ß-induced EMT, cell motility, and tumor metastasis in vitro and in vivo. Furthermore, clinical analyses reveal a significant correlation among TGF-ß receptor I (TßRI), FBXO3, and p63 protein expression and that high expression of TßRI/FBXO3 and low expression of p63 are associated with poor recurrence-free survival (RFS). Together, these results demonstrate that FBXO3 facilitates ΔNp63α degradation to empower TGF-ß signaling in promoting tumor metastasis and that the TßRI-FBXO3-ΔNp63α axis is critically important in breast cancer development and clinical prognosis. This study suggests that FBXO3 may be a potential therapeutic target for advanced breast cancer treatment.

AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: An exploratory study.

BACKGROUND AND AIMS: Lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a pivotal role in the outcome of MASH clinical trials. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses can provide an automated quantitative assessment of fibrosis features on a continuous scale called qFibrosis. In this exploratory study, we used this approach to gain insight into the effect of lifestyle intervention-induced fibrosis changes in MASH. METHODS: We examined unstained sections from paired liver biopsies (baseline and end-of-intervention) from MASH individuals who had received either routine lifestyle intervention (RLI) (n = 35) or strengthened lifestyle intervention (SLI) (n = 17). We quantified liver fibrosis with qFibrosis in the portal tract, periportal, transitional, pericentral, and central vein regions. RESULTS: About 20% (7/35) and 65% (11/17) of patients had fibrosis regression in the RLI and SLI groups, respectively. Liver fibrosis tended towards no change or regression after each lifestyle intervention, and this phenomenon was more prominent in the SLI group. SLI-induced liver fibrosis regression was concentrated in the periportal region. CONCLUSION: Using digital pathology, we could detect a more pronounced fibrosis regression with SLI, mainly in the periportal region. With changes in fibrosis area in the periportal region, we could differentiate RLI and SLI patients in the placebo group in the MASH clinical trial. Digital pathology provides new insight into lifestyle-induced fibrosis regression and placebo responses, which is not captured by conventional histological staging.

Machine-learning model comprising five clinical indices and liver stiffness measurement can accurately identify MASLD-related liver fibrosis.

BACKGROUND & AIMS: aMAP score, as a hepatocellular carcinoma risk score, is proven to be associated with the degree of chronic hepatitis B-related liver fibrosis. We aimed to evaluate the ability of aMAP score for metabolic dysfunction-associated steatotic liver disease (MASLD; formerly NAFLD)-related fibrosis diagnosis and establish a machine-learning (ML) model to improve the diagnostic performance. METHODS: A total of 946 biopsy-proved MASLD patients from China and the United States were included in the analysis. The aMAP score, demographic/clinical indices and liver stiffness measurement (LSM) were included in seven ML algorithms to build fibrosis diagnostic models in the training set (N = 703). The performance of ML models was evaluated in the external validation set (N = 125). RESULTS: The AUROCs of aMAP versus fibrosis-4 index (FIB-4) and aspartate aminotransferase-platelet ratio (APRI) in cirrhosis and advanced fibrosis were (0.850 vs. 0.857 [P = 0.734], 0.735 [P = 0.001]) and (0.759 vs. 0.795 [P = 0.027], 0.709 [P = 0.049]). When using dual cut-off values, aMAP had a smaller uncertainty area and higher accuracy (26.9%, 86.6%) than FIB-4 (37.3%, 85.0%) and APRI (59.0%, 77.3%) in cirrhosis diagnosis. The seven ML models performed satisfactorily in most cases. In the validation set, the ML model comprising LSM and 5 indices (including age, sex, platelets, albumin and total bilirubin used in aMAP calculator), built by logistic regression algorithm (called LSM-plus model), exhibited excellent performance. In cirrhosis and advanced fibrosis detection, the LSM-plus model had higher accuracy (96.8%, 91.2%) than LSM alone (86.4%, 67.2%) and Agile score (76.0%, 83.2%), respectively. Additionally, the LSM-plus model also displayed high specificity (cirrhosis: 98.3%; advanced fibrosis: 92.6%) with satisfactory AUROC (0.932, 0.875, respectively) and sensitivity (88.9%, 82.4%, respectively). CONCLUSIONS: The aMAP score is capable of diagnosing MASLD-related fibrosis. The LSM-plus model could accurately identify MASLD-related cirrhosis and advanced fibrosis.

Prediction value of pericoronary fat attenuation index for coronary in-stent restenosis.

OBJECTIVES: As a novel imaging marker, pericoronary fat attenuation index (FAI) reflects the local coronary inflammation which is one of the major mechanisms for in-stent restenosis (ISR). We aimed to validate the ability of pericoronary FAI to predict ISR in patients undergoing percutaneous coronary intervention (PCI). MATERIALS AND METHODS: Patients who underwent coronary CT angiography (CCTA) before PCI within 1 week between January 2017 and December 2019 at our hospital and had follow-up invasive coronary angiography (ICA) or CCTA were enrolled. Pericoronary FAI was measured at the site where stents would be placed. ISR was defined as ≥ 50% diameter stenosis at follow-up ICA or CCTA in the in-stent area. Multivariable analysis using mixed effects logistic regression models was performed to test the association between pericoronary FAI and ISR at lesion level. RESULTS: A total of 126 patients with 180 target lesions were included in the study. During 22.5 months of mean interval time from index PCI to follow-up ICA or CCTA, ISR occurred in 40 (22.2%, 40/180) stents. Pericoronary FAI was associated with a higher risk of ISR (adjusted OR = 1.12, p = 0.028). The optimum cutoff was - 69.6 HU. Integrating the dichotomous pericoronary FAI into current state of the art prediction model for ISR improved the prediction ability of the model significantly (△area under the curve = + 0.064; p = 0.001). CONCLUSION: Pericoronary FAI around lesions with subsequent stent placement is independently associated with ISR and could improve the ability of current prediction model for ISR. CLINICAL RELEVANCE STATEMENT: Pericoronary fat attenuation index can be used to identify the lesions with high risk for in-stent restenosis. These lesions may benefit from extra anti-inflammation treatment to avoid in-stent restenosis. KEY POINTS: • Pericoronary fat attenuation index reflects the local coronary inflammation. • Pericoronary fat attenuation index around lesions with subsequent stents placement can predict in-stent restenosis. • Pericoronary fat attenuation index can be used as a marker for future in-stent restenosis.

Machine Learning-Assisted Optimization of Mixed Carbon Source Compositions for High-Performance Denitrification.

Appropriate mixed carbon sources have great potential to enhance denitrification efficiency and reduce operational costs in municipal wastewater treatment plants (WWTPs). However, traditional methods struggle to efficiently select the optimal mixture due to the variety of compositions. Herein, we developed a machine learning-assisted high-throughput method enabling WWTPs to rapidly identify and optimize mixed carbon sources. Taking a local WWTP as an example, a mixed carbon source denitrification data set was established via a high-throughput method and employed to train a machine learning model. The composition of carbon sources and the types of inoculated sludge served as input variables. The XGBoost algorithm was employed to predict the total nitrogen removal rate and microbial growth, thereby aiding in the assessment of the denitrification potential. The predicted carbon sources exhibited an enhanced denitrification potential over single carbon sources in both kinetic experiments and long-term reactor operations. Model feature analysis shows that the cumulative effect and interaction among individual carbon sources in a mixture significantly enhance the overall denitrification potential. Metagenomic analysis reveals that the mixed carbon sources increased the diversity and complexity of denitrifying bacterial ecological networks in WWTPs. This work offers an efficient method for WWTPs to optimize mixed carbon source compositions and provides new insights into the mechanism behind enhanced denitrification under a supply of multiple carbon sources.

CB-Dock2: improved protein-ligand blind docking by integrating cavity detection, docking and homologous template fitting.

Protein-ligand blind docking is a powerful method for exploring the binding sites of receptors and the corresponding binding poses of ligands. It has seen wide applications in pharmaceutical and biological researches. Previously, we proposed a blind docking server, CB-Dock, which has been under heavy use (over 200 submissions per day) by researchers worldwide since 2019. Here, we substantially improved the docking method by combining CB-Dock with our template-based docking engine to enhance the accuracy in binding site identification and binding pose prediction. In the benchmark tests, it yielded the success rate of ∼85% for binding pose prediction (RMSD < 2.0 Å), which outperformed original CB-Dock and most popular blind docking tools. This updated docking server, named CB-Dock2, reconfigured the input and output web interfaces, together with a highly automatic docking pipeline, making it a particularly efficient and easy-to-use tool for the bioinformatics and cheminformatics communities. The web server is freely available at https://cadd.labshare.cn/cb-dock2/.

New Phenol Derivatives from the Haima Cold Seep-Derived Fungus Aspergillus subversicolor CYH-17.

Seven new phenol derivatives, subversins A-E (1-5), subversic acid A (6) and epi-wortmannine G (7); one new natural product, 4-hydroxy-7-methoxyphthalide (8); and five known compounds (9-13) were isolated from the fungus Aspergillus subversicolor CYH-17 collected from the Haima cold seep. The structures and absolute configurations of these compounds were determined via NMR, MS, optical rotation, electronic circular dichroism (ECD) calculation, X-ray diffraction analysis and comparison with the literature. Compounds 2 and 5 were two pairs of enantiomers. All compounds were tested for their α-glucosidase and acetylcholinesterase (AChE) inhibitory activity, antioxidant activity and antibacterial activity, but no obvious activity was observed among these studied compounds.

[Application of process analysis technology in traditional Chinese medicine manufacturing industry].

In the traditional Chinese medicine(TCM) manufacturing industry, quality control determines the safety, effectiveness, and quality stability of the final product. The traditional quality control method generally carries out sampling off-line testing of drugs after the end of the batch production, which is incomprehensive, and it fails to find the problems in the production process in time. Process analysis technology(PAT) uses process testing, mathematical modeling, data analysis, and other technologies to collect, analyze, feedback, control, and continuously improve the critical quality attributes(CQA) in all aspects of the production of TCM preparations in real time. The application of PAT in the TCM manufacturing industry is one of the research hotspots in recent years, which has the advantages of real-time, systematic, non-destructive, green, and rapid detection for the production quality control of TCM preparations. It can effectively ensure the stability of the quality of TCM preparations, improve production efficiency, and play a key role in the study of the quantity and quality transfer law of TCM. Commonly used PAT includes near-infrared spectroscopy, Raman spectroscopy, online microwave, etc. In addition, the establishment of an online detection model by PAT is the key basic work to realize intelligent manufacturing in TCM production. Obtaining real-time online detection data through PAT and establishing a closed-loop control model on this basis are a key common technical difficulty in the industry. This paper adopted systematic literature analysis to summarize the relevant Chinese and foreign literature, policies and regulations, and production applications, and it introduced the development trend and practical application of PAT, so as to provide references for accelerating the application of PAT in the TCM manufacturing industry, the intelligent transformation and upgrading, and high-quality development of the TCM industry.

Unconventional hcp/fcc Nickel Heteronanocrystal with Asymmetric Convex Sites Boosts Hydrogen Oxidation.

Developing non-platinum group metal catalysts for the sluggish hydrogen oxidation reaction (HOR) is critical for alkaline fuel cells. To date, Ni-based materials are the most promising candidates but still suffer from insufficient performance. Herein, we report an unconventional hcp/fcc Ni (u-hcp/fcc Ni) heteronanocrystal with multiple epitaxial hcp/fcc heterointerfaces and coherent twin boundaries, generating rugged surfaces with plenty of asymmetric convex sites. Systematic analyses discover that such convex sites enable the adsorption of *H in unusual bridge positions with weakened binding energy, circumventing the over-strong *H adsorption on traditional hollow positions, and simultaneously stabilizing interfacial *H2O. It thus synergistically optimizes the HOR thermodynamic process as well as reduces the kinetic barrier of the rate-determining Volmer step. Consequently, the developed u-hcp/fcc Ni exhibits the top-rank alkaline HOR activity with a mass activity of 40.6 mA mgNi-1 (6.3 times higher than fcc Ni control) together with superior stability and high CO-tolerance. These results provide a paradigm for designing high-performance catalysts by shifting the adsorption state of intermediates through configuring surface sites.

The Hsp70-Bag3 complex modulates the phosphorylation and nuclear translocation of Hippo pathway protein Yap.

Protein abnormalities can accelerate aging causing protein misfolding diseases, and various adaptive responses have evolved to relieve proteotoxicity. To trigger these responses, cells must detect the buildup of aberrant proteins. Previously we demonstrated that the Hsp70-Bag3 (HB) complex senses the accumulation of defective ribosomal products, stimulating signaling pathway proteins, such as stress kinases or the Hippo pathway kinase LATS1. Here, we studied how Bag3 regulates the ability for LATS1 to regulate its key downstream target YAP (also known as YAP1). In naïve cells, Bag3 recruited a complex of LATS1, YAP and the scaffold AmotL2, which links LATS1 and YAP. Upon inhibition of the proteasome, AmotL2 dissociated from Bag3, which prevented phosphorylation of YAP by LATS1, and led to consequent nuclear YAP localization together with Bag3. Mutations in Bag3 that enhanced its translocation into nucleus also facilitated nuclear translocation of YAP. Interestingly, Bag3 also controlled YAP nuclear localization in response to cell density, indicating broader roles beyond proteotoxic signaling responses for Bag3 in the regulation of YAP. These data implicate Bag3 as a regulator of Hippo pathway signaling, and suggest mechanisms by which proteotoxic stress signals are propagated.