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Cryo-EM structures of E. coli F1Fo ATP synthase highlight the role of the inhibitory ε subunit in regulating the torsional movement of the central stalk within the Fo motor and central stalk flexibility in coupling the F1 and Fo motors.

BAFF, an activator of the noncanonical NFκB pathway, provides critical survival signals during B cell maturation and contributes to B cell proliferation. We found that the NFκB family member RelB is required ex vivo for B cell maturation, but cRel is required for proliferation. Combined molecular network modeling and experimentation revealed Nfkb2 p100 as a pathway switch; at moderate p100 synthesis rates in maturing B cells, BAFF fully utilizes p100 to generate the RelB:p52 dimer, whereas at high synthesis rates, p100 assembles into multimeric IκBsome complexes, which BAFF neutralizes in order to potentiate cRel activity and B cell expansion. Indeed, moderation of p100 expression or disruption of IκBsome assembly circumvented the BAFF requirement for full B cell expansion. Our studies emphasize the importance of p100 in determining distinct NFκB network states during B cell biology, which causes BAFF to have context-dependent functional consequences.

Abstract Third-generation EGFR tyrosine kinase inhibitors (TKIs), exemplified by osimertinib, have demonstrated promising clinical efficacy in the treatment of non-small cell lung cancer (NSCLC). Our previous work has identified ASK120067 as a novel third-generation EGFR TKI with remarkable antitumor effects that has undergone New Drug Application (NDA) submission in China. Despite substantial progress, acquired resistance to EGFR-TKIs remains a significant challenge, impeding the long-term effectiveness of therapeutic approaches. In this study, we conducted a comprehensive investigation utilizing high-throughput proteomics analysis on established TKI-resistant tumor models, and found a notable upregulation of branched-chain amino acid transaminase 1 (BCAT1) expression in both osimertinib- and ASK120067-resistant tumors compared with the parental TKI-sensitive NSCLC tumors. Genetic depletion or pharmacological inhibition of BCAT1 impaired the growth of resistant cells and partially re-sensitized tumor cells to EGFR TKIs. Mechanistically, upregulated BCAT1 in resistant cells reprogrammed branched-chain amino acid (BCAA) metabolism and promoted alpha ketoglutarate (α-KG)-dependent demethylation of lysine 27 on histone H3 (H3K27) and subsequent transcriptional derepression of glycolysis-related genes, thereby enhancing glycolysis and promoting tumor progression. Moreover, we identified WQQ-345 as a novel BCAT1 inhibitor exhibiting antitumor activity both in vitro and in vivo against TKI-resistant lung cancer with high BCAT1 expression. In summary, our study highlighted the crucial role of BCAT1 in mediating resistance to third-generation EGFR-TKIs through epigenetic activation of glycolysis in NSCLC, thereby supporting BCAT1 as a promising therapeutic target for the treatment of TKI-resistant NSCLC.

Abstract Wounding initiates intricate responses crucial for tissue repair and regeneration. Yet, the gene regulatory networks governing wound healing remain poorly understood. Here, employing single-worm RNA sequencing (swRNA-seq) across 12 time-points, we delineated a three-stage wound repair process in C. elegans: response, repair, and remodeling. Integrating diverse datasets, we constructed a dynamic regulatory network comprising 241 transcription regulators and their inferred targets. We identified potentially seven autoregulatory TFs and five cross-autoregulatory loops involving pqm-1 and jun-1. We revealed that TFs might interact with chromatin factors and form TF-TF combinatory modules via intrinsically disordered regions to enhance response robustness. We experimentally validated six regulators functioning in transcriptional and translocation-dependent manners. Notably, nhr-76, daf-16, nhr-84, and oef-1 are potentially required for efficient repair, while elt-2 may act as an inhibitor. These findings elucidate transcriptional responses and hierarchical regulatory networks during C. elegans wound repair, shedding light on mechanisms underlying tissue repair and regeneration.

Abstract Background Large bone defects pose a clinical treatment challenge; inhibiting transferrin receptor 2 (TfR2), which is involved in iron metabolism, can promote osteogenesis. Iron-based metal-organic frameworks (MOF-Fe) particles not only inhibit TfR2 but also serve as biomimetic catalysts to remove hydrogen peroxide in reactive oxygen species (ROS); excess ROS can disrupt the normal functions of osteoblasts, thereby hindering bone regeneration. This study explored the potential effects of MOF-Fe in increasing osteogenic activity and clearing ROS. Methods In vitro experiments were performed to investigate the osteogenic effects of MOF-Fe particles and assess their impact on cellular ROS levels. To further validate the role of MOF-Fe in promoting bone defect repair, we injected MOF-Fe suspensions into the femoral defects of SD rats and implanted MOF-Fe-containing hydrogel scaffolds in rabbit cranial defect models and observed their effects on bone healing. Results In vitro, the presence of MOF-Fe significantly increased the expression levels of osteogenesis-related genes and proteins compared to those in the control group. Additionally, compared to those in the untreated control group, the cells treated with MOF-Fe exhibited a significantly increased ability to remove hydrogen peroxide from ROS and generate oxygen and water within the physiological pH range. In vivo experiments further confirmed the positive effect of MOF-Fe in promoting bone defect repair. Conclusion This study supports the application of MOF-Fe as an agent for bone regeneration, particularly for mitigating ROS and activating the bone morphogenetic protein (BMP) pathway, demonstrating its potential value.

The transporter protein ABC subfamily G member 2 (ABCG2) is implicated in epilepsy; however, its specific role remains unclear. In this study, we assessed changes in ABCG2 expression and its role in epilepsy both in vitro and in vivo. We observed an instantaneous increase in ABCG2 expression in epileptic animals and cells. Further, ABCG2 overexpression significantly suppressed the oxidative stress and apoptosis induced by glutamate, kainic acid (KA), and lipopolysaccharide (LPS) in neuronal and microglia cells. Furthermore, inhibiting ABCG2 activity offset this protective effect. ABCG2-deficient mice (ABCG2−/−) showed shorter survival times and decreased survival rates when administered with pentylenetetrazole (PTZ). We also noticed the accumulation of signal transducer and activator of transcription 1 (STAT1) and decreased phosphorylation of mammalian target of rapamycin kinase (mTOR) along with increased ISGylation in ABCG2−/− mice. ABCG2 overexpression directly interacted with STAT1 and mTOR, leading to a decrease in their ISGylation. Our findings indicate the rapid increase in ABCG2 expression acts as a shield in epileptogenesis, indicating ABCG2 may serve as a potential therapeutic target for epilepsy treatment.

SARS-CoV-2 spike protein (SARS-2-S) induced cell-cell fusion in uninfected cells may occur in long COVID-19 syndrome, as circulating SARS-2-S or extracellular vesicles containing SARS-2-S (S-EVs) were found to be prevalent in post-acute sequelae of COVID-19 (PASC) for up to 12 months after diagnosis. Although isolated recombinant SARS-2-S protein has been shown to increase the SASP in senescent ACE2-expressing cells, the direct linkage of SARS-2-S syncytia with senescence in the absence of virus infection and the degree to which SARS-2-S syncytia affect pathology in the setting of cardiac dysfunction are unknown. Here, we found that the senescent outcome of SARS-2-S induced syncytia exacerbated heart failure progression. We first demonstrated that syncytium formation in cells expressing SARS-2-S delivered by DNA plasmid or LNP-mRNA exhibits a senescence-like phenotype. Extracellular vesicles containing SARS-2-S (S-EVs) also confer a potent ability to form senescent syncytia without de novo synthesis of SARS-2-S. However, it is important to note that currently approved COVID-19 mRNA vaccines do not induce syncytium formation or cellular senescence. Mechanistically, SARS-2-S syncytia provoke the formation of functional MAVS aggregates, which regulate the senescence fate of SARS-2-S syncytia by TNFα. We further demonstrate that senescent SARS-2-S syncytia exhibit shrinked morphology, leading to the activation of WNK1 and impaired cardiac metabolism. In pre-existing heart failure mice, the WNK1 inhibitor WNK463, anti-syncytial drug niclosamide, and senolytic dasatinib protect the heart from exacerbated heart failure triggered by SARS-2-S. Our findings thus suggest a potential mechanism for COVID-19-mediated cardiac pathology and recommend the application of WNK1 inhibitor for therapy especially in individuals with post-acute sequelae of COVID-19.

Significant advancements in our understanding and clinical treatment of cholangiocarcinoma (CCA) have been achieved over the past 5 years. Groundbreaking studies have illuminated the immune landscape and pathological characteristics of the tumor microenvironment in CCA. The development of immune- and metabolism-based classification systems has enabled a nuanced exploration of the tumor microenvironment and the origins of CCA, facilitating a detailed understanding of tumor progression modulation. Despite these insights, targeted therapies have not yet yielded satisfactory clinical results, highlighting the urgent need for innovative therapeutic strategies. This review delineates the complexity and heterogeneity of CCA, examines the current landscape of therapeutic strategies and clinical trials, and delves into the resistance mechanisms underlying targeted therapies. Finally, from a single-cell and spatial transcriptomic perspective, we address the challenge of therapy resistance, discussing emerging mechanisms and potential strategies to overcome this barrier and enhance treatment efficacy.

Background Global public health is seriously threatened by the escalating issue of antimicrobial resistance (AMR). Antimicrobial peptides (AMPs), pivotal components of the innate immune system, have emerged as a potent solution to AMR due to their therapeutic potential. Employing computational methodologies for the prompt recognition of these antimicrobial peptides indeed unlocks fresh perspectives, thereby potentially revolutionizing antimicrobial drug development. Methods In this study, we have developed a model named as deepAMPNet. This model, which leverages graph neural networks, excels at the swift identification of AMPs. It employs structures of antimicrobial peptides predicted by AlphaFold2, encodes residue-level features through a bi-directional long short-term memory (Bi-LSTM) protein language model, and constructs adjacency matrices anchored on amino acids’ contact maps. Results In a comparative study with other state-of-the-art AMP predictors on two external independent test datasets, deepAMPNet outperformed in accuracy. Furthermore, in terms of commonly accepted evaluation matrices such as AUC, Mcc, sensitivity, and specificity, deepAMPNet achieved the highest or highly comparable performances against other predictors. Conclusion deepAMPNet interweaves both structural and sequence information of AMPs, stands as a high-performance identification model that propels the evolution and design in antimicrobial peptide pharmaceuticals. The data and code utilized in this study can be accessed at https://github.com/Iseeu233/deepAMPNet.

Abstract DANCE is the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts, such as using only one command line. In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to facilitate their own model development. DANCE is an open-source Python package that welcomes all kinds of contributions.

Abstract Vaccines have proven effective in protecting populations against COVID-19, including the recombinant COVID-19 vaccine (Sf9 cells), the first approved recombinant protein vaccine in China. In this positive-controlled trial with 85 adult participants (Sf9 cells group: n = 44; CoronaVac group: n = 41), we evaluated the safety, immunogenicity, and protective effectiveness of a heterologous boost with the Sf9 cells vaccine in adults who had been vaccinated with the inactivated vaccine, and found a post-booster adverse events rate of 20.45% in the Sf9 cells group and 31.71% in the CoronaVac group (p = 0.279), within 28 days after booster injection. Neither group reported any severe adverse events. Following the Sf9 cells vaccine booster, the geometric mean titer (GMT) of binding antibodies to the receptor-binding domain of prototype SARS-CoV-2 on day 28 post-booster was significantly higher than that induced by the CoronaVac vaccine booster (100,683.37 vs. 9,451.69, p

Objectives: The study aimed to investigate the relationship between blood pressure (BP) levels and mortality among critically ill older adults in the intensive care unit (ICU), establish optimal BP target for this population, and assess the mediating effect of severe malnutrition on BP-related mortality. Methods: Data were extracted from the Medical Information Mart for Intensive Care IV version 2.2 database, focusing on critically ill patients aged 80 years and older. The analysis included various BP parameters, such as systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP). Results: The study cohort comprised 14,660 critically ill patients, of whom 1558 (10.6 %) experienced ICU mortality and 2493 (17.0 %) experienced in-hospital mortality. Lower BP levels (SBP ≤ 112 mmHg; DBP ≤ 53 mmHg; MAP ≤65 mmHg), were associated with an increased risk of both ICU and in-hospital mortality. Notably, only reduced SBP levels were linked to a higher risk of 1-year mortality, with an adjusted hazard ratio 1.13 (95 % confidence interval 1.05 to 1.23). Additionally, severe malnutrition was identified as a mediator in the relationship between low BP levels and ICU mortality, with BP levels positively correlated with prognostic nutritional indexes. Conclusion: Among critically ill older adults, lower BP levels are significantly associated with higher risks of ICU and in-hospital mortality, while reduced SBP levels are linked to 1-year mortality. These findings emphasize the importance of assessing nutritional status in older ICU patients with low BP levels to potentially mitigate mortality risk.

Aims: The relationship between sarcopenia and cognitive impairment in older adults remains contentious. This study investigates this association and examines the long-term prognosis for individuals with both conditions. Methods: Utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014, this study focuses on the correlation between sarcopenia and cognitive impairment, as well as the extended prognosis for individuals managing these conditions. Results: The study cohort comprised 2890 participants, with 648 (22.4 %) diagnosed with sarcopenia. Multivariable logistic regression analysis identified a significant association between sarcopenia and an increased risk of cognitive impairment (adjusted odds ratio [aOR]: 1.68, 95 % confidence interval [CI]: 1.30–2.17). Over a median follow-up period of 48 months, 200 individuals (6.9 %) succumbed to cardiovascular and cerebrovascular diseases (CCVDs), including hypertension, congestive heart failure, coronary artery disease, and stroke, as well as Alzheimer's disease (AD). Participants had comorbid conditions such as CCVDs and diabetes mellitus. Kaplan–Meier survival analysis and the Cox proportional hazards model indicated that individuals with both sarcopenia and cognitive impairment had the highest mortality risk from CCVDs and AD (adjusted hazard ratio [aHR]: 2.73, 95 % CI: 1.48–5.02). Individuals with sarcopenia and comorbidities exhibited a higher mortality risk from CCVDs or AD compared to those without sarcopenia but with comorbidities (aHR: 2.71, 95 % CI: 1.37–5.37). Conclusion: Sarcopenia is independently associated with cognitive impairment. Older adults with both sarcopenia and cognitive impairment or concurrent comorbidities face increased mortality risks from CCVDs or AD compared to their healthy counterparts. Clinical implication: • Sarcopenia is associated with cognitive impairment. • Cognitive impairment and comorbidities increased the risk of mortality from CCVDs and AD for sarcopenia patients.

BackgroundHepatocellular carcinoma (HCC) is the most common type of liver cancer. Small extracellular vesicles (sEVs) are bilayer lipid membrane vesicles containing RNA that exhibit promising diagnostic and prognostic potential as cancer biomarkers.AimsTo establish a miRNA panel from peripheral blood for use as a noninvasive biomarker for the diagnosis of HCC.MethodssEVs obtained from plasma were profiled using high-throughput sequencing. The identified differential miRNA expression patterns were subsequently validated using quantitative real-time polymerase chain reaction analysis.ResultsThe random forest method identified ten distinct miRNAs distinguishing HCC plasma from non-HCC plasma. During validation, miR-140-3p (p = 0.0001) and miR-3200-3p (p = 0.0017) exhibited significant downregulation. Enrichment analysis uncovered a notable correlation between the target genes of these miRNAs and cancer development. Utilizing logistic regression, we developed a diagnostic model incorporating these validated miRNAs. Receiver operating characteristic (ROC) curve analysis revealed an area under the curve (AUC) of 0.951, with a sensitivity of 90.1% and specificity of 87.8%.ConclusionThese aberrantly expressed miRNAs delivered by sEVs potentially contribute to HCC pathology and may serve as diagnostic biomarkers for HCC.

Background Contextual cueing refers to the phenomenon in which individuals utilize frequently encountered environmental contexts, comprised of distractors, as cues to expedite a target search. Due to the conflict between the widespread occurrence of contextual cue transfer and the observed impact of changing the identity of distractors on contextual cue learning, the content of contextual cue representations remains contentious. Considering the independent nature of contextual cue learning and expression, our proposition is twofold: (1) Contextual cue representations are stimulus-specific, and (2) their expression is highly flexible. Methods To validate the model, two experiments were conducted. Experiment 1 aimed to confirm the hypothesis that contextual cue representations are stimulus-specific. We manipulated the identity consistency of distractors within repeated scenes during contextual cue learning. Difficulty in contextual cue learning under the identity-changing condition would suggest the necessity of identity within contextual cue representation, indicating the stimulus-specific nature of these representations. Experiment 2 was designed to affirm the conclusion of Experiment 1 and explore the flexibility in the expression of contextual cue representations. This experiment comprised two phases: learning and testing. During the learning phase, participants were exposed to two sets of repeated scenes in different colors under two learning conditions: load and no-load. Working memory load was introduced to interfere with the expression to prevent it from becoming automatic. In the subsequent testing phase, the colors of the two scene sets were interchanged to impede retrieval based on identity. If both load and no-load conditions demonstrate similar levels of contextual cue effects during the testing phase, it implies the flexibility in the expression of contextual cue representations and confirms the conclusion of Experiment 1. Results In Experiment 1, a notable contextual cue learning effect was observed under the identity-consistent condition (p = 0.001). However, this effect was not evident under the identity-changing condition (p = 0.286). This finding strongly supports the stimulus-specific nature of contextual cue representation. In Experiment 2, the contextual cueing effect appeared but did not show a significant difference between the two conditions (t(23) = 0.02, p = 0.987, BF10 = 0.215), indicating the cognitive system’s ability to flexibly redefine retrieval cues. This adaptability aligns with our hypothesis and confirms the high flexibility in the expression process of contextual cue representations and confirms the conclusion of Experiment 1.

Objective Whether serum uric acid (SUA) at baseline could been identiûed as a risk factor for progression in IgA nephropathy (IgAN) patients remains unclear, therefore, long- term SUA control levels must be monitored. We aimed to investigate the relevant factors affecting time-averaged SUA (TA-SUA) and to assess the prognostic value of TA-SUA in IgAN. Methods This retrospective study included 152 patients with IgAN. The relationships between TA-SUA and clinicopathological features and renal outcomes (defined as the doubling of the baseline serum creatinine level or end-stage renal disease) were analyzed in groups divided by quartiles of TA-SUA levels, the presence of hyperuricemia, and sex. Results Patients with high TA-SUA levels had higher levels of baseline SUA, blood urea nitrogen (BUN), triglycerides, serum C3 and serum C4 and were more likely to be male and have hypertension, proteinuria, poor renal function, and pathological injuries including high grades of tubular atrophy/interstitial fibrosis (T1–T2). These patients had a poorer prognosis compared with patients with low TA-SUA levels. The TA-SUA level was positively correlated with baseline age and BUN, triglycerides, serum C3, and serum C4 levels, and negatively correlated with baseline eGFR. Survival curve analysis indicated that persistent hyperuricemia was associated with significantly poorer renal outcomes than normo-uricemia in both men and women. The TA-SUA level also was an independent predictor of renal outcome in patients with IgAN, with optimal cutoû values of 451.38 µmol/L (area under the curve (AUC) = 0.934) for men and 492.83 µmol/L (AUC = 0.768) for women. Conclusions The TA-SUA level is associated with triglyceride level, complement component levels, renal function, and pathological severity of IgAN, and it may be a prognostic indicator in male and female patients with IgAN.

Background Acute pulmonary embolism (APE) is classified as a subset of diseases that are characterized by lung obstruction due to various types of emboli. Current clinical APE treatment using anticoagulants is frequently accompanied by high risk of bleeding complications. Recombinant hirudin (R-hirudin) has been found to have antithrombotic properties. However, the specific impact of R-hirudin on APE remains unknown. Methods Sprague-Dawley (SD) rats were randomly assigned to five groups, with thrombi injections to establish APE models. Control and APE group rats were subcutaneously injected with equal amounts of dimethyl sulfoxide (DMSO). The APE+R-hirudin low-dose, middle-dose, and high-dose groups received subcutaneous injections of hirudin at doses of 0.25 mg/kg, 0.5 mg/kg, and 1.0 mg/kg, respectively. Each group was subdivided into time points of 2 h, 6 h, 1 d, and 4 d, with five animals per point. Subsequently, all rats were euthanized, and serum and lung tissues were collected. Following the assessment of right ventricular pressure (RVP) and mean pulmonary artery pressure (mPAP), blood gas analysis, enzyme-linked immunosorbnent assay (ELISA), pulmonary artery vascular testing, hematoxylin-eosin (HE) staining, Terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling (TUNEL) staining, immunohistochemistry, and Western blot experiments were conducted. Results R-hirudin treatment caused a significant reduction of mPAP, RVP, and Malondialdehyde (MDA) content, as well as H2O2 and myeloperoxidase (MPO) activity, while increasing pressure of oxygen (PaO2) and Superoxide Dismutase (SOD) activity. R-hirudin also decreased wall area ratio and wall thickness to diameter ratio in APE rat pulmonary arteries. Serum levels of endothelin-1 (ET-1) and thromboxaneB2 (TXB2) decreased, while prostaglandin (6-K-PGF1α) and NO levels increased. Moreover, R-hirudin ameliorated histopathological injuries and reduced apoptotic cells and Matrix metalloproteinase-9 (MMP9), vascular cell adhesion molecule-1 (VCAM-1), p-Extracellular signal-regulated kinase (ERK)1/2/ERK1/2, and p-P65/P65 expression in lung tissues. Conclusion R-hirudin attenuated pulmonary hypertension and thrombosis in APE rats, suggesting its potential as a novel treatment strategy for APE.

Blunting the tumor's stress-sensing ability is an effective strategy for controlling tumor adaptive survival and metastasis. Here, we have designed a cyclically amplified nano-energy interference device based on lipid nanoparticles (LNP), focused on altering cellular energy metabolism. This innovative nano device efficiently targets and monitors the tumor's status while simultaneously inhibiting mitochondrial respiration, biogenesis and ribosome production. To this end, we first identified azelaic acid (AA), a binary acid capable of disrupting the mitochondrial respiratory chain. Upon encapsulation in LNP and linkage to mitochondrial-targeting molecules, this disruptive effect is further augmented. Consequently, tumors exhibit a substantial upregulation of the glycolytic pathway, intensifying their glucose demand and worsening the tumor's energy-deprived microenvironment. Then, the glucose analog, 2-Deoxy-D-glucose (2-DG), linked to the LNP, efficiently targets tumors and competitively inhibits the tumor's normal glucose uptake. The synergetic results of combining AA with 2-DG induce comprehensive energy deficiency within tumors, blocking the generation of energy-sensitive ribosomes. Ultimately, the disruption of both mitochondria and ribosomes depletes energy supply and new protein-generating capacity, weakening tumor's ability to adapt to environmental stress and thereby inhibiting growth and metastasis. Comprehensively, this nano-energy interference device, by controlling the tumor's stress-sensing ability, provides a novel therapeutic strategy for refractory tumors.

Abstract Background Protein–protein interactions (PPIs) are crucial in various biological functions and cellular processes. Thus, many computational approaches have been proposed to predict PPI sites. Although significant progress has been made, these methods still have limitations in encoding the characteristics of each amino acid in sequences. Many feature extraction methods rely on the sliding window technique, which simply merges all the features of residues into a vector. The importance of some key residues may be weakened in the feature vector, leading to poor performance. Results We propose a novel sequence-based method for PPI sites prediction. The new network model, PPINet, contains multiple feature processing paths. For a residue, the PPINet extracts the features of the targeted residue and its context separately. These two types of features are processed by two paths in the network and combined to form a protein representation, where the two types of features are of relatively equal importance. The model ensembling technique is applied to make use of more features. The base models are trained with different features and then ensembled via stacking. In addition, a data balancing strategy is presented, by which our model can get significant improvement on highly unbalanced data. Conclusion The proposed method is evaluated on a fused dataset constructed from Dset186, Dset_72, and PDBset_164, as well as the public Dset_448 dataset. Compared with current state-of-the-art methods, the performance of our method is better than the others. In the most important metrics, such as AUPRC and recall, it surpasses the second-best programmer on the latter dataset by 6.9% and 4.7%, respectively. We also demonstrated that the improvement is essentially due to using the ensemble model, especially, the hybrid feature. We share our code for reproducibility and future research at https://github.com/CandiceCong/StackingPPINet .

In the complex clutter background, the clutter center frequency is not fixed, and the spectral width is wide, which leads to the performance degradation of the traditional adaptive clutter suppression method. Therefore, an adaptive clutter intelligent suppression method based on deep reinforcement learning (DRL) is proposed. Each range cell to be detected is regarded as an independent intelligence (agent) in the proposed method. The clutter environment is interactively learned using a deep learning (DL) process, and the filter parameter optimization is positively motivated by the reinforcement learning (RL) process to achieve the best clutter suppression effect. The suppression performance of the proposed method is tested on simulated and real data. The experimental results indicate that the filter notch designed by the proposed method is highly matched with the clutter compared with the existing adaptive clutter suppression methods. While suppressing the clutter, it has a higher amplitude-frequency response to signals at non-clutter frequencies, thus reducing the loss of the target signal and maximizing the output signal-to-clutter and noise rate (SCNR).

Tea plants are a perennial crop with significant economic value. Chlorophyll, a key factor in tea leaf color and photosynthetic efficiency, is affected by the photoperiod and usually exhibits diurnal and seasonal variations. In this study, high-throughput transcriptomic analysis was used to study the chlorophyll metabolism, under different photoperiods, of tea plants. We conducted a time-series sampling under a skeleton photoperiod (6L6D) and continuous light conditions (24 L), measuring the chlorophyll and carotenoid content at a photoperiod interval of 3 h (24 h). Transcriptome sequencing was performed at six time points across two light cycles, followed by bioinformatics analysis to identify and annotate the differentially expressed genes (DEGs) involved in chlorophyll metabolism. The results revealed distinct expression patterns of key genes in the chlorophyll biosynthetic pathway. The expression levels of CHLE (magnesium-protoporphyrin IX monomethyl ester cyclase gene), CHLP (geranylgeranyl reductase gene), CLH (chlorophyllase gene), and POR (cytochrome P450 oxidoreductase gene), encoding enzymes in chlorophyll synthesis, were increased under continuous light conditions (24 L). At 6L6D, the expression levels of CHLP1.1, POR1.1, and POR1.2 showed an oscillating trend. The expression levels of CHLP1.2 and CLH1.1 showed the same trend, they both decreased under light treatment and increased under dark treatment. Our findings provide potential insights into the molecular basis of how photoperiods regulate chlorophyll metabolism in tea plants.

Background: Platelets, a type of anucleated cell, play a crucial role in cardiovascular diseases (CVDs). Therefore, targeting platelet activation is essential for mitigating CVDs. Endogenous agonists, such as collagen, activate platelets by initiating signal transduction through specific platelet receptors, leading to platelet aggregation. Eugenol, primarily sourced from clove oil, is known for its antibacterial, anticancer, and anti-inflammatory properties, making it a valuable medicinal agent. In our previous study, eugenol was shown to inhibit platelet aggregation induced by collagen and arachidonic acid. We concluded that eugenol exerts a potent inhibitory effect on platelet activation by targeting the PLCγ2–PKC and cPLA2-TxA2 pathways, thereby suppressing platelet aggregation. In our current study, we found that eugenol significantly inhibits NF-κB activation. This led us to investigate the relationship between the NF-κB and cPLA2 pathways to elucidate how eugenol suppresses platelet activation. Methods: In this study, we prepared platelet suspensions from the blood of healthy human donors to evaluate the inhibitory mechanisms of eugenol on platelet activation. We utilized immunoblotting and confocal microscopy to analyze these mechanisms in detail. Additionally, we assessed the anti-thrombotic effect of eugenol by observing fluorescein-induced platelet plug formation in the mesenteric microvessels of mice. Results: For immunoblotting and confocal microscopy studies, eugenol significantly inhibited NF-κB-mediated signaling events stimulated by collagen in human platelets. Specifically, it reduced the phosphorylation of IKK and p65 and prevented the degradation of IκBα. Additionally, CAY10502, a cPLA2 inhibitor, significantly reduced NF-κB-mediated signaling events. In contrast, BAY11-7082, an IKK inhibitor, did not affect collagen-stimulated cPLA2 phosphorylation. These findings suggest that cPLA2 acts as an upstream regulator of NF-κB activation during platelet activation. Furthermore, both BAY11-7082 and CAY10502 significantly reduced the collagen-induced rise in intracellular calcium levels. In the animal study, eugenol demonstrated potential as an anti-thrombotic agent by significantly reducing platelet plug formation in fluorescein-irradiated mouse mesenteric microvessels. Conclusion: Our study uncovered a novel pathway in platelet activation involving the cPLA2-NF-κB axis, which plays a key role in the antiplatelet effects of eugenol. These findings suggest that eugenol could serve as a valuable and potent prophylactic or therapeutic option for arterial thrombosis.

Background Biochar amendments enhance crop productivity and improve agricultural quality. To date, studies on the correlation between different amounts of biochar in pakchoi (Brassica campestris L.) quality and rhizosphere soil microorganisms are limited, especially in weakly alkaline soils. The experiment was set up to explore the effect of different concentrations of biochar on vegetable quality and the correlation between the index of quality and soil bacterial community structure changes. Methods The soil was treated in the following ways via pot culture: the blank control (CK) without biochar added and with biochar at different concentrations of 1% (T1), 3% (T2), 5% (T3), and 7% (T4). Here, we investigatedthe synergistic effect of biochar on the growth and quality of pakchoi, soil enzymatic activities, and soil nutrients. Microbial communities from pakchoi rhizosphere soil were analyzed by Illumina MiSeq. Results The results revealed that adding 3% biochar significantly increased plant height, root length, and dry weight of pakchoi and increased the contents of soluble sugars, soluble proteins, Vitamin C (VC), cellulose, and reduced nitrate content in pakchoi leaves. Meanwhile, soil enzyme activities and available nutrient content in rhizosphere soil increased. This study demonstrated that the the microbial community structure of bacteria in pakchoi rhizosphere soil was changed by applying more than 3% biochar. Among the relatively abundant dominant phyla, Gemmatimonadetes, Anaerolineae, Deltaproteobacteria and Verrucomicrobiae were reduced, and Alphaproteobacteria, Gammaproteobacteria, Bacteroidia, and Acidimicrobiia relative abundance increased. Furthermore, adding 3% biochar reduced the relative abundance of Gemmatimonas and increased the relative abundances of Ilumatobacter, Luteolibacter, Lysobacter, Arthrobacter, and Mesorhizobium. The nitrate content was positively correlated with the abundance of Gemmatimonadetes, and the nitrate content was significantly negatively correlated with the relative abundance of Ilumatobacter. Carbohydrate transport and metabolism in the rhizosphere soil of pakchoi decreased, and lipid transport and metabolism increased after biochar application. Conclusion Overall, our results indicated that applying biochar improved soil physicochemical states and plant nutrient absorption, and affected the abundance of dominant bacterial groups (e.g., Gemmatimonadetes and Ilumatobacter), these were the main factors to increase pakchoi growth and promote quality of pakchoi. Therefore, considering the growth, quality of pakchoi, and soil environment, the effect of using 3% biochar is better.

Background: Sex differences in health status and life expectancy are widely accepted to exist. The mechanisms underlying it are still poorly understood. In this study, we aimed to clarify the influences and contributions of sex on the gut microbiome in healthy centenarians and to explore the different roles played by the gut microbiome in healthy aging between the sexes. Results: Taking covariates of different dimensions into account (social demographics, anthropometry, the activities of daily living, dietary structure, mental state, blood tests, lifestyle and disease history), our data showed that sex was one of the most significant covariates affecting the gut microbiome of healthy centenarians at both the species and Kyoto Encyclopedia of Genes and Genomes Orthology (KO) levels. The beta diversity between the sexes were significantly different (Adonis test: p = 0.011, R2 = 0.031), and the male centenarians had a greater alpha diversity than the females (Simpson and Shannon test: P

Background As a component of chromatin remodeling complex, chromatin accessibility complex subunit 1 (CHRAC1) is critical in transcription and DNA replication. However, the significance of CHRAC1 in cancer progression has not been investigated extensively. This research aimed to determine the function of CHRAC1 in breast and cervical cancer and elucidate the molecular mechanism. Methods The Bio-ID method was used to identify the interactome of transcriptional activator Yes-associated protein (YAP) and the binding between YAP and CHRAC1 was verified by immunofluorescence. CCK8, colony formation and subcutaneous xenograft assays were conducted to explore the function of CHRAC1 in cancer cell proliferation. RNA-seq analysis and RT-PCR were used to analyze the transcription program change after CHRAC1 ablation. The diagnostic value of CHRAC1 was analyzed by TCGA database and further validated by immunohistochemistry staining. Results In the current study, we found that the chromatin remodeler CHRAC1 was a potential YAP interactor. CHRAC1 depletion suppressed breast and cervical cancer cell proliferation and tumor growth. The potential mechanism may be that CHRAC1 interacts with YAP to facilitate oncogenic transcription of YAP target genes in Hippo pathway, thereby promoting tumorigenesis. CHRAC1 was elevated in cervical and breast cancer biopsies and the upregulation correlated with shorter survival, poor pathological stages and metastasis of cancer patients. Moreover, CHRAC1 expression was statistically associated with YAP in breast and cervical cancer biopsies. Conclusions These findings highlight that CHRAC1 contributes to cancer progression through regulating the oncogenic transcription of YAP, which makes it a potential therapeutic target for cancer treatment.

Objective The objective is to explore whether the flagellin-TLR5 complex signal can enhance the antigen presentation ability of myeloid DCs through the TRIF-ERK1/2 pathway, and the correlation between this pathway and intestinal mucosal inflammation response. Methods Mouse bone marrow-derived DC line DC2.4 was divided into four groups: control group (BC) was DC2.4 cells cultured normally; flagellin single signal stimulation group (DC2.4+CBLB502) was DC2.4 cells stimulated with flagellin derivative CBLB502 during culture; TLR5-flagellin complex signal stimulation group (ov-TLR5-DC2.4+CBLB502) was flagellin derivative CBLB502 stimulated ov-TLR5-DC2.4 cells with TLR5 gene overexpression; TRIF signal interference group (ov-TLR5-DC2.4+CBLB502+Pepinh-TRIFTFA) was ov-TLR5-DC2.4 cells with TLR5 gene overexpression stimulated with flagellin derivative CBLB502 and intervened with TRIF-specific inhibitor Pepinh-TRIFTFA. WB was used to detect the expression of TRIF and p-ERK1/2 proteins in each group of cells; CCK8 was used to detect cell proliferation in each group; flow cytometry was used to detect the expression of surface molecules MHCI, MHCII, CD80, 86 in each group of cells; ELISA was used to detect the levels of IL-12 and IL-4 cytokines in each group. Results Compared with the BC group, DC2.4+CBLB502 group, and ov-TLR5-DC2.4+CBLB502+Pepinh-TRIFTFA group, the expression of TRIF protein and p-ERK1/2 protein in ov-TLR5-DC2.4+CBLB502 group was significantly upregulated (TRIF: p = 0.02, = 0.007, = 0.048) (ERK1: p

Microbial natural products have been one of the most important sources for drug development. In the current postgenomic era, sequence-driven approaches for natural product discovery are becoming increasingly popular. Here, we develop an effective genome mining strategy for the targeted discovery of microbial metabolites with antitumor activities. Our method employs uvrA-like genes as genetic markers, which have been identified in the biosynthetic gene clusters (BGCs) of several chemotherapeutic drugs of microbial origin and confer self-resistance to the corresponding producers. Through systematic genomic analysis of gifted actinobacteria genera, identification of uvrA-like gene-containing BGCs, and targeted isolation of products from a BGC prioritized for metabolic analysis, we identified a new tetracycline-type DNA intercalator timmycins. Our results thus provide a new genome mining strategy for the efficient discovery of antitumor agents acting through DNA intercalation.

Abstract Background Single-cell RNA sequencing (scRNA-seq) enables the high-throughput profiling of gene expression at the single-cell level. However, overwhelming dropouts within data may obscure meaningful biological signals. Various imputation methods have recently been developed to address this problem. Therefore, it is important to perform a systematic evaluation of different imputation algorithms. Results In this study, we evaluated 11 of the most recent imputation methods on 12 real biological datasets from immunological studies and 4 simulated datasets. The performance of these methods was compared, based on numerical recovery, cell clustering and marker gene analysis. Most of the methods brought some benefits on numerical recovery. To some extent, the performance of imputation methods varied among protocols. In the cell clustering analysis, no method performed consistently well across all datasets. Some methods performed poorly on real datasets but excellent on simulated datasets. Surprisingly and importantly, some methods had a negative effect on cell clustering. In marker gene analysis, some methods identified potentially novel cell subsets. However, not all of the marker genes were successfully imputed in gene expression, suggesting that imputation challenges remain. Conclusions In summary, different imputation methods showed different effects on different datasets, suggesting that imputation may have dataset specificity. Our study reveals the benefits and limitations of various imputation methods and provides a data-driven guidance for scRNA-seq data analysis.

Accurate prediction of outgoing moisture content is the key to achieving energy-saving and efficient technological transformation of drying. This study relies on a grain drying simulation experiment system which combined counter and current drying sections to design corn kernel drying experiments. This study obtains 18 kinds of temperature and humidity variables during the drying process and uses Uninformative Variable Elimination (UVE) method to screen sensitive variables affecting the outgoing moisture content. Subsequently, six prediction models for the outgoing corn moisture content were developed, innovatively incorporating Multiple Linear Regression (MLR), Extreme Learning Machine (ELM), and Long Short-Term Memory (LSTM). The results show that eight sensitive variables have been screened to predict the moisture content of outgoing corn. The sensitive variables effectively reduced the redundancy and multicollinearity of data in the MLR model and improved the coefficient of determination (R2) of ELM and LSTM models by 0.02 and 0.05. The MLR prediction model established based on the full set of temperature and humidity data has an R2 of 0.910 and a root-mean-square error (RMSE) of 0.881%, while the UVE-ELM and UVE-LSTM prediction models achieve a better fitting effect and prediction accuracy. The UVE-LSTM model is set with a batch size of 30, a learning rate of 0.01, and 100 iterations. For the training set of UVE-LSTM, the R2 value is 0.931 and the RMSE value is 0.711%. The UVE-ELM model, with sigmoid as the activation function and 14 neurons configured, runs fast and has the best prediction accuracy. The R2 values of UVE-ELM training set and validation set are 0.943 and 0.946, respectively, and the RMSEs are 0.544% and 0.581%. The models proposed in this study provide data reference and technical support for process optimization and automation control of the corn drying process.

In the realm of quantitative proteomics, data-independent acquisition (DIA) has emerged as a promising approach, offering enhanced reproducibility and quantitative accuracy compared to traditional data-dependent acquisition (DDA) methods. However, the analysis of DIA data is currently hindered by its reliance on project-specific spectral libraries derived from DDA analyses, which not only limits proteome coverage but also proves to be a time-intensive process. To overcome these challenges, we propose ProPept-MT, a novel deep learning-based multi-task prediction model designed to accurately forecast key features such as retention time (RT), ion intensity, and ion mobility (IM). Leveraging advanced techniques such as multi-head attention and BiLSTM for feature extraction, coupled with Nash-MTL for gradient coordination, ProPept-MT demonstrates superior prediction performance. Integrating ion mobility alongside RT, mass-to-charge ratio (m/z), and ion intensity forms 4D proteomics. Then, we outline a comprehensive workflow tailored for 4D DIA proteomics research, integrating the use of 4D in silico libraries predicted by ProPept-MT. Evaluation on a benchmark dataset showcases ProPept-MT’s exceptional predictive capabilities, with impressive results including a 99.9% Pearson correlation coefficient (PCC) for RT prediction, a median dot product (DP) of 96.0% for fragment ion intensity prediction, and a 99.3% PCC for IM prediction on the test set. Notably, ProPept-MT manifests efficacy in predicting both unmodified and phosphorylated peptides, underscoring its potential as a valuable tool for constructing high-quality 4D DIA in silico libraries.

The booming growth of the internet of things has brought about widespread deployment of devices and massive amounts of sensing data to be processed. Federated learning (FL)-empowered mobile edge computing, known for pushing artificial intelligence to the network edge while preserving data privacy in learning cooperation, is a promising way to unleash the potential information of the data. However, FL’s multi-server collaborative operating architecture inevitably results in communication energy consumption between edge servers, which poses great challenges to servers with constrained energy budgets, especially wireless communication servers that rely on battery power. The device-to-device (D2D) communication mode developed for FL turns high-cost and long-distance server interactions into energy-efficient proximity delivery and multi-level aggregations, effectively alleviating the server energy constraints. A few studies have been devoted to D2D-enabled FL management, but most of them have neglected to investigate server computing power for FL operation, and they have all ignored the impact of dataset characteristics on model training, thus failing to fully exploit the data processing capabilities of energy-constrained edge servers. To fill this gap, in this paper we propose a D2D-assisted FL mechanism for energy-constrained edge computing, which jointly incorporates computing power allocation and dataset correlation into FL scheduling. In view of the variable impacts of computational power on model accuracy at different training stages, we design a partite graph-based FL scheme with adaptive D2D pairing and aperiodic variable local iterations of heterogeneous edge servers. Moreover, we leverage graph learning to exploit the performance gain of the dataset correlation between the edge servers in the model aggregation process, and we propose a graph-and-deep reinforcement learning-based D2D server pairing algorithm, which effectively reduces FL model error. The numerical results demonstrate that our designed FL schemes have great advantages in improving FL training accuracy under edge servers’ energy constraints.

Photoacoustic imaging integrates the strengths of optics and ultrasound, offering high resolution, depth penetration, and multimodal imaging capabilities. Practical considerations with instrumentation and geometry limit the number of available acoustic sensors and their “view” of the imaging target, which result in image reconstruction artifacts degrading image quality. To address this problem, YOLOv8-Pix2Pix is proposed as a hybrid artifact-removal algorithm, which is advantageous in comprehensively eliminating various types of artifacts and effectively restoring image details compared to existing algorithms. The proposed algorithm demonstrates superior performance in artifact removal and segmentation of photoacoustic images of brain tumors. For the purpose of further expanding its application fields and aligning with actual clinical needs, an experimental system for photoacoustic detection is designed in this paper to be verified. The experimental results show that the processed images are better than the pre-processed images in terms of reconstruction metrics PSNR and SSIM, and also the segmentation performance is significantly improved, which provides an effective solution for the further development of photoacoustic imaging technology.

A new imaging technique called photoacoustic imaging (PAI) combines the advantages of ultrasound imaging and optical absorption to provide structural and functional details of tissues. It has broad application prospects in the accurate diagnosis and treatment monitoring of brain tumours. However, the existing photoacoustic image classification algorithms cannot effectively distinguish benign tumours from malignant tumours. To address this problem, the YoLov8-MedSAM model is proposed in this research to provide precise and adaptable brain tumour identification and detection segmentation. Additionally, it employs convolutional neural networks (CNNs) to classify and identify tumours in order to distinguish between benign and malignant variations in PAI. The experimental results show that the method proposed in this study not only effectively detects and segments brain tumours of various shapes and sizes but also increases the accuracy of brain tumour classification to 97.02%. The method provides richer and more valuable diagnostic information to the clinic and effectively optimizes the diagnosis and treatment strategy of brain tumours.

Photoacoustic imaging (PAI) is an emerging imaging technique that offers real-time, non-invasive, and radiation-free measurements of optical tissue properties. However, image quality degradation due to factors such as non-ideal signal detection hampers its clinical applicability. To address this challenge, this paper proposes an algorithm for super-resolution reconstruction and segmentation based on deep learning. The proposed enhanced deep super-resolution minimalistic network (EDSR-M) not only mitigates the shortcomings of the original algorithm regarding computational complexity and parameter count but also employs residual learning and attention mechanisms to extract image features and enhance image details, thereby achieving high-quality reconstruction of PAI. DeepLabV3+ is used to segment the images before and after reconstruction to verify the network reconstruction performance. The experimental results demonstrate average improvements of 19.76% in peak-signal-to-noise ratio (PSNR) and 4.80% in structural similarity index (SSIM) for the reconstructed images compared to those of their pre-reconstructed counterparts. Additionally, mean accuracy, mean intersection and union ratio (IoU), and mean boundary F1 score (BFScore) for segmentation showed enhancements of 8.27%, 6.20%, and 6.28%, respectively. The proposed algorithm enhances the effect and texture features of PAI and makes the overall structure of the image restoration more complete.

The present study evaluated the antiseizure and neuroprotective effects of sodium houttuyfonate (SH), a derivative of Houttuynia cordata Thunb. (H. cordata), in a kainic acid (KA)- induced seizure rat model and its underlying mechanism. Sprague Dawley rats were administered normal saline, SH (50 or 100 mg/kg), or carbamazepine (300 mg/kg) by oral gavage for seven consecutive days before the intraperitoneal administration of KA (15 mg/kg). SH showed antiseizure effects at a dose of 100 mg/kg; it prolonged seizure latency and decreased seizure scores. SH also significantly decreased neuronal loss in the hippocampi of KA-treated rats, which was associated with the prevention of glutamate level increase, the upregulation of glutamate reuptake-associated proteins (excitatory amino acid transporters 1–3), glutamate metabolism enzyme glutamine synthetase, the downregulation of the glutamate synthesis enzyme glutaminase, and significant alterations in the expression of AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor) and NMDA (N-methyl-D-aspartic acid receptor) receptor subunits in the hippocampus. Furthermore, the effects of SH were similar to those of the antiseizure drug carbamazepine. Therefore, the results of the present study suggest that SH has antiseizure effects on KA-induced seizures, possibly through the prevention of glutamatergic alterations. Our findings suggest that SH is a potential alternative treatment that may prevent seizures by preserving the normal glutamatergic system.

The mechanical forces exerted by cells on their surrounding microenvironment are known as cellular traction forces. These forces play crucial roles in various biological processes, such as tissue development, wound healing and cell functions. However, it is hard for traditional techniques to measure cellular traction forces accurately because their magnitude (from pN to nN) and the length scales over which they occur (from nm to μm) are extremely small. In order to fully understand mechanotransduction, highly sensitive tools for measuring cellular forces are needed. Current powerful techniques for measuring traction forces include traction force microscopy (TFM) and fluorescent molecular force sensors (FMFS). In this review, we elucidate the force imaging principles of TFM and FMFS. Then we highlight the application of FMFS in a variety of biological processes and offer our perspectives and insights into the potential applications of FMFS.

Diabetic retinopathy (DR) is one of the most severe complications of diabetes mellitus and potentially leads to significant visual impairment and blindness. The complex mechanisms involved in the pathological changes in DR make it challenging to achieve satisfactory outcomes with existing treatments. Diets conducive to glycemic control have been shown to improve outcomes in diabetic patients, thus positioning dietary interventions as promising avenues for DR treatment. Investigations have demonstrated that natural products (NPs) may effectively manage DR. Many types of natural compounds, including saponins, phenols, terpenoids, flavonoids, saccharides, alkaloids, and vitamins, have been shown to exert anti-inflammatory, antioxidant, anti-neovascular, and antiapoptotic effects in vivo and in vitro. Nevertheless, the clinical application of NPs still faces challenges, such as suboptimal specificity, poor bioavailability, and a risk of toxicity. Prospective clinical studies are imperative to validate the therapeutic potential of NPs in delaying or preventing DR.

The study used whole-genome sequencing (WGS) and bioinformatics analysis for the genomic characterization of 60 isolates of Listeria monocytogenes obtained from the beef production chain (cattle farms, abattoirs, and retail outlets) in Gauteng province, South Africa. The sequence types (STs), clonal complexes (CCs), and the lineages of the isolates were determined using in silico multilocus sequence typing (MLST). We used BLAST-based analyses to identify virulence and antimicrobial genes, plasmids, proviruses/prophages, and the CRISPR-Cas system. The study investigated any association of the detected genes to the origin in the beef production chain of the L. monocytogenes isolates. Overall, in 60 isolates of Listeria monocytogenes, there were seven STs, six CCs, forty-four putative virulence factors, two resistance genes, one plasmid with AMR genes, and three with conjugative genes, one CRISPR gene, and all 60 isolates were positive for proviruses/prophages. Among the seven STs detected, ST204 (46.7%) and ST2 (21.7%) were the most prominent, with ST frequency varying significantly (p < 0.001). The predominant CC detected were CC2 (21.7%) and CC204 (46.7%) in lineages I and II, respectively. Of the 44 virulence factors detected, 26 (across Listeria Pathogenicity Islands, LIPIs) were present in all the isolates. The difference in the detection frequency varied significantly (p < 0.001). The two AMR genes (fosX and vga(G)) detected were present in all 60 (100%) isolates of L. monocytogenes. The only plasmid, NF033156, was present in three (5%) isolates. A CRISPR-Cas system was detected in six (10%), and all the isolates carried proviruses/prophages. The source and sample type significantly affected the frequencies of STs and virulence factors in the isolates of L. monocytogenes. The presence of fosX and vga(G) genes in all L. monocytogenes isolates obtained from the three industries of the beef production chain can potentially cause therapeutic implications. Our study, which characterized L. monocytogenes recovered from the three levels in the beef production chain, is the first time genomics was performed on this type of data set in the country, and this provides insights into the health implications of Listeria.

Blood loss by hemorrhaging wounds accounts for over one-third of ∼5 million trauma fatalities worldwide every year. If not controlled in a timely manner, exsanguination can take lives within a few minutes. Developing new biomaterials that are easy to use by non-expert patients and promote rapid blood coagulation is an unmet medical need. Here, biocompatible, and biodegradable microneedle arrays (MNAs) based on gelatin methacryloyl (GelMA) biomaterial hybridized with silicate nanoplatelets (SNs) are developed for hemorrhage control. The SNs render the MNAs hemostatic, while the needle-shaped structure increases the contact area with blood, synergistically accelerating the clotting time from 11.5 min to 1.3 min in vitro. The engineered MNAs reduce bleeding by ∼92% compared with the untreated injury group in a rat liver bleeding model. SN-containing MNAs outperform the hemostatic effect of needle-free patches and a commercial hemostat in vivo via combining micro- and nanoengineered features. Furthermore, the tissue adhesive properties and mechanical interlocking support the suitability of MNAs for wound closure applications. These hemostatic MNAs may enable rapid hemorrhage control, particularly for patients in developing countries or remote areas with limited or no immediate access to hospitals.

Abstract Phosphatidylinositol 3-kinase alpha (PI3Kα) inhibitors are currently evaluated for the therapy of esophageal squamous cell carcinoma (ESCC). It is of great importance to identify potential biomarkers to predict or monitor the efficacy of PI3Kα inhibitors in an aim to improve the clinical responsive rate in ESCC. Here, ESCC PDXs with CCND1 amplification were found to be more sensitive to CYH33, a novel PI3Kα-selective inhibitor currently in clinical trials for the treatment of advanced solid tumors including ESCC. Elevated level of cyclin D1, p21 and Rb was found in CYH33-sensitive ESCC cells compared to those in resistant cells. CYH33 significantly arrested sensitive cells but not resistant cells at G1 phase, which was associated with accumulation of p21 and suppression of Rb phosphorylation by CDK4/6 and CDK2. Hypo-phosphorylation of Rb attenuated the transcriptional activation of SKP2 by E2F1, which in turn hindered SKP2-mediated degradation of p21 and reinforced accumulation of p21. Moreover, CDK4/6 inhibitors sensitized resistant ESCC cells and PDXs to CYH33. These findings provided mechanistic rationale to evaluate PI3Kα inhibitors in ESCC patients harboring amplified CCND1 and the combined regimen with CDK4/6 inhibitors in ESCC with proficient Rb.

ABSTRACTObjectives To observe the protective effects of dexmedetomidine (Dex) postconditioning on myocardial ischemia/reperfusion injury (IRI) and to explore its potential molecular mechanisms.Methods One-hundred forty-seven male Sprague-Dawley rats were randomly divided into five groups receiving the different treatments: Sham, ischemia/reperfusion (I/R), Dex, Brusatol, Dex + Brusatol. By the in vivo rat model of myocardial IRI, cardioprotective effects of Dex postconditioning were evaluated by assessing serum CK-MB and cTnI levels, myocardial HE and Tunel staining and infarct size. Furthermore, the oxidative stress-related markers including intracellular ROS level, myocardial tissue MDA level, SOD and GSH-PX activities were determined.Results Dex postconditioning significantly alleviated myocardial IRI, decreased intracellular ROS and myocardial tissue MDA level, increased SOD and GSH-PX activities. Dex postconditioning significantly up-regulated myocardial expression of Bcl-2, down-regulated Bax and cleaved caspase-3 and decreased cardiomyocyte apoptosis rate. furthermores, Dex postconditioning promoted Nrf2 nuclear translocation, increased myocardial expression of Sirt3 and SOD2 and decreased Ac-SOD2. However, brusatol reversed cardioprotective benefits of Dex postconditioning, significantly decreased Dex-induced Nrf2 nuclear translocation and reduced myocardial expression of Sirt3 and SOD2.Conclusions Dex postconditioning can alleviate myocardial IRI by suppressing oxidative stress and apoptosis, and these beneficial effects are at least partly mediated by activating the Nrf2/Sirt3/SOD2 signaling pathway.

Background Lung cancer (LC) is the most prevalent cancer with a poor prognosis. Semaphorin4A (Sema4A) is important in many physiological and pathological processes. This study aimed to explore the role and mechanism of Sema4A in LC. Methods Firstly, Sema4A expression was analyzed by the available dataset and detected in human normal bronchial epithelial cell line (HBE) and LC cell line (NCI-H460). Then, LC cells were transfected with Sema4A siRNA, and the cells were stimulated by PlexinB1, PlexinB2, PlexinD1 blocking antibodies, IgG antibody, BAY 11-7082 (an inhibitor for NF-κB pathway) and Sema4A-Fc protein, alone or in combination. After transfection, PlexinB1 mRNA expression was analyzed. Next, the biological functions, including proliferative, migratory, invasive abilities and viability of the cells were detected by colony formation, scratch, Transwell and MTT assays, respectively. NF-κB, Stat3 and MAPK protein expressions were determined by western blot. Furthermore, the secretion of IL-6 in LC cells was tested by ELISA. Results Sema4A was highly expressed in LC tissues and cells, could activate the NF-κB pathway and upregulate PlexinB1 mRNA expression. Furthermore, we observed that Sema4A knockdown suppressed the biological functions of NCI-H460 cells, while Sema4A-Fc protein reversed the situation. However, Sema4A-induced biological functions and activation in the NF-κB pathway were inhibited by PlexinB1 blocking antibody. Consistently, Sema4A promoted IL-6 production, which was down-regulated by PlexinB1 blocking antibody and BAY 11-7082. Conclusions Sema4A may facilitate LC development via the activation of the NF-κB pathway mediated by PlexinB1, suggesting that Sema4A would be a novel therapeutic target for LC treatment.

Abstract Advanced intrahepatic cholangiocarcinoma (ICC) has a dismal prognosis. Here, we report the efficacy and safety of combining toripalimab, lenvatinib, and gemcitabine plus oxaliplatin (GEMOX) as first-line therapy for advanced ICC. Thirty patients with pathologically confirmed advanced ICC received intravenous gemcitabine (1 g/m2) on Days 1 and 8 and oxaliplatin (85 mg/m2) Q3W for six cycles along with intravenous toripalimab (240 mg) Q3W and oral lenvatinib (8 mg) once daily for one year. The expression of programmed death-ligand 1 (PD-L1) and genetic status was investigated in paraffin-embedded tissues using immunohistochemistry and whole-exome sequencing (WES) analysis. The primary endpoint was the objective response rate (ORR). Secondary outcomes included safety, overall survival (OS), progression-free survival (PFS), disease control rate (DCR) and duration of response (DoR). As of July 1, 2022, the median follow-up time was 23.5 months, and the ORR was 80%. Twenty-three patients achieved partial response, and one achieved complete response. Patients (21/30) with DNA damage response (DDR)-related gene mutations showed a higher ORR, while patients (14/30) with tumor area positivity ≥1 (PD-L1 staining) showed a trend of high ORR, but without significant difference. The median OS, PFS, and DoR were 22.5, 10.2, and 11.0 months, respectively. The DCR was 93.3%. Further, 56.7% of patients experienced manageable grade ≥3 adverse events (AEs), commonly neutropenia (40.0%) and leukocytopenia (23.3%). In conclusion, toripalimab plus lenvatinib and GEMOX are promising first-line regimens for the treatment of advanced ICC. A phase-III, multicenter, double-blinded, randomized study to validate our findings was approved by the National Medical Products Administration (NMPA, No. 2021LP01825). Trial registration Clinical trials: NCT03951597.

As an effective soil amendment, biochars require a comprehensive ecological evaluation before they can be widely used in agriculture because endogenous contaminants, such as environmentally persistent free radicals (EPFRs), certainly pose an ecological risk to soil invertebrates. In this study, Caenorhabditis elegans (C. elegans) was used as a model organism to investigate the neurotoxicity of two rice straw biochars pyrolyzed at 500 and 700 °C. After 24 h exposure to unwashed biochar, washed biochar, and leaching fluids (supernatants), the neurobehavioral parameters of C. elegans were determined in a liquid toxicity test. The results showed that the washed 700 °C biochar particles significantly impaired locomotion and prolonged the defecation interval at a biochar concentration of 4 g·well−1, while the unwashed biochar and supernatants caused no apparent impairment. Supporting this, electron paramagnetic resonance (EPR) results showed that the intensity of EPFRs in unwashed 700 °C biochar was stronger than that of the corresponding washed particles. This indicates that, in the liquid test, the EPR signal alone is not indicative of particle toxicity. The accessibility and activity of the EPFRs should be considered. Dissolved organic matter (DOM) was observed in the leaching fluids. The neurotoxic activity of the washed biochar was alleviated after the re-addition of leaching fluids to the washed biochar, suggesting that the dissolved organic materials modulate the reactivity of the EPFRs in the liquid phase. This study suggests that the leaching process may increase the risk of biochar when used in the field environment.

Abstract Alternative splicing (AS) is an important approach for pathogens and hosts to remodel transcriptome. However, tuberculosis (TB)-related AS has not been sufficiently explored. Here we presented the first landscape of TB-related AS by long-read sequencing, and screened four AS events (S100A8-intron1-retention intron, RPS20-exon1-alternaitve promoter, KIF13B-exon4-skipping exon (SE) and UBE2B-exon7-SE) as potential biomarkers in an in-house cohort-1. The validations in an in-house cohort-2 (2274 samples) and public datasets (1557 samples) indicated that the latter three AS events are potential promising biomarkers for TB diagnosis, but not for TB progression and prognosis. The excellent performance of classifiers further underscored the diagnostic value of these three biomarkers. Subgroup analyses indicated that UBE2B-exon7-SE splicing was not affected by confounding factors and thus had relatively stable performance. The splicing of UBE2B-exon7-SE can be changed by heat-killed mycobacterium tuberculosis through inhibiting SRSF1 expression. After heat-killed mycobacterium tuberculosis stimulation, 231 ubiquitination proteins in macrophages were differentially expressed, and most of them are apoptosis-related proteins. Taken together, we depicted a global TB-associated splicing profile, developed TB-related AS biomarkers, demonstrated an optimal application scope of target biomarkers and preliminarily elucidated mycobacterium tuberculosis-host interaction from the perspective of splicing, offering a novel insight into the pathophysiology of TB.

Abstract Histone deacetylase (HDAC) is a kind of protease that modifies histone to regulate gene expression, and is usually abnormally activated in tumors. The approved pan-HDAC inhibitors have demonstrated clinical benefits for patients in some hematologic malignancies. Only limited therapeutic success in breast cancer has been observed in clinical trials. In this study, we declare that pan-HDAC inhibitors targeting NEDD9-FAK pathway exacerbate breast cancer metastasis in preclinical models, which may severely impede their clinical success. NEDD9 is not an oncogene, however, it has been demonstrated recently that there are high level or activity changes of NEDD9 in a variety of cancer, including leukemia, colon cancer, and breast cancer. Mechanistically, pan-HDAC inhibitors enhance H3K9 acetylation at the nedd9 gene promoter via inhibition of HDAC4 activity, thus increase NEDD9 expression, and then activate FAK phosphorylation. The realization that pan-HDAC inhibitors can alter the natural history of breast cancer by increasing invasion warrants clinical attention. In addition, although NEDD9 has been reported to have a hand in breast cancer metastasis, it has not received much attention, and no therapeutic strategies have been developed. Notably, we demonstrate that FAK inhibitors can reverse breast cancer metastasis induced by upregulation of NEDD9 via pan-HDAC inhibitors, which may offer a potential combination therapy for breast cancer.

Load-bearing biological tissues, such as cartilage and muscles, exhibit several crucial properties, including high elasticity, strength, and recoverability. These characteristics enable these tissues to endure significant mechanical stresses and swiftly recover after deformation, contributing to their exceptional durability and functionality. In contrast, while hydrogels are highly biocompatible and hold promise as synthetic biomaterials, their inherent network structure often limits their ability to simultaneously possess a diverse range of superior mechanical properties. As a result, the applications of hydrogels are significantly constrained. This article delves into the design mechanisms and mechanical properties of various tough hydrogels and investigates their applications in tissue engineering, flexible electronics, and other fields. The objective is to provide insights into the fabrication and application of hydrogels with combined high strength, stretchability, toughness, and fast recovery as well as their future development directions and challenges.

The circadian clock refers to the formation of a certain rule in the long-term evolution of an organism, which is an invisible ‘clock’ in the body of an organism. As one of the largest TF families in higher plants, the MYB transcription factor is involved in plant growth and development. MYB is also inextricably correlated with the circadian rhythm. In this study, the transcriptome data of the tea plant ‘Baiyeyihao’ were measured at a photoperiod interval of 4 h (24 h). A total of 25,306 unigenes were obtained, including 14,615 unigenes that were annotated across 20 functional categories within the GO classification. Additionally, 10,443 single-gene clusters were annotated to 11 sublevels of metabolic pathways using KEGG. Based on the results of gene annotation and differential gene transcript analysis, 22 genes encoding MYB transcription factors were identified. The G10 group in the phylogenetic tree had 13 members, of which 5 were related to the circadian rhythm, accounting for 39%. The G1, G2, G8, G9, G15, G16, G18, G19, G20, G21 and G23 groups had no members associated with the circadian rhythm. Among the 22 differentially expressed MYB transcription factors, 3 members of LHY, RVE1 and RVE8 were core circadian rhythm genes belonging to the G10, G12 and G10 groups, respectively. Real-time fluorescence quantitative PCR was used to detect and validate the expression of the gene transcripts encoding MYB transcription factors associated with the circadian rhythm.