Crucial roles of the BRCA1-BARD1 E3 ubiquitin ligase activity in homology-directed DNA repair.

The tumor-suppressor breast cancer 1 (BRCA1) in complex with BRCA1-associated really interesting new gene (RING) domain 1 (BARD1) is a RING-type ubiquitin E3 ligase that modifies nucleosomal histone and other substrates. The importance of BRCA1-BARD1 E3 activity in tumor suppression remains highly controversial, mainly stemming from studying mutant ligase-deficient BRCA1-BARD1 species that we show here still retain significant ligase activity. Using full-length BRCA1-BARD1, we establish robust BRCA1-BARD1-mediated ubiquitylation with specificity, uncover multiple modes of activity modulation, and construct a truly ligase-null variant and a variant specifically impaired in targeting nucleosomal histones. Cells expressing either of these BRCA1-BARD1 separation-of-function alleles are hypersensitive to DNA-damaging agents. Furthermore, we demonstrate that BRCA1-BARD1 ligase is not only required for DNA resection during homology-directed repair (HDR) but also contributes to later stages for HDR completion. Altogether, our findings reveal crucial, previously unrecognized roles of BRCA1-BARD1 ligase activity in genome repair via HDR, settle prior controversies regarding BRCA1-BARD1 ligase functions, and catalyze new efforts to uncover substrates related to tumor suppression.

DNA polymerase delta governs parental histone transfer to DNA replication lagging strand.

Chromatin replication is intricately intertwined with the recycling of parental histones to the newly duplicated DNA strands for faithful genetic and epigenetic inheritance. The transfer of parental histones occurs through two distinct pathways: leading strand deposition, mediated by the DNA polymerase ε subunits Dpb3/Dpb4, and lagging strand deposition, facilitated by the MCM helicase subunit Mcm2. However, the mechanism of the facilitation of Mcm2 transferring parental histones to the lagging strand while moving along the leading strand remains unclear. Here, we show that the deletion of Pol32, a nonessential subunit of major lagging-strand DNA polymerase δ, results in a predominant transfer of parental histone H3-H4 to the leading strand during replication. Biochemical analyses further demonstrate that Pol32 can bind histone H3-H4 both in vivo and in vitro. The interaction of Pol32 with parental histone H3-H4 is disrupted through the mutation of the histone H3-H4 binding domain within Mcm2. Our findings identify the DNA polymerase δ subunit Pol32 as a critical histone chaperone downstream of Mcm2, mediating the transfer of parental histones to the lagging strand during DNA replication.

Defective transfer of parental histone decreases frequency of homologous recombination by increasing free histone pools in budding yeast.

Recycling of parental histones is an important step in epigenetic inheritance. During DNA replication, DNA polymerase epsilon subunit DPB3/DPB4 and DNA replication helicase subunit MCM2 are involved in the transfer of parental histones to the leading and lagging strands, respectively. Single Dpb3 deletion (dpb3Δ) or Mcm2 mutation (mcm2-3A), which each disrupts one parental histone transfer pathway, leads to the other's predominance. However, the biological impact of the two histone transfer pathways on chromatin structure and DNA repair remains elusive. In this study, we used budding yeast Saccharomyces cerevisiae to determine the genetic and epigenetic outcomes from disruption of parental histone H3-H4 tetramer transfer. We found that a dpb3Δ mcm2-3A double mutant did not exhibit the asymmetric parental histone patterns caused by a single dpb3Δ or mcm2-3A mutation, suggesting that the processes by which parental histones are transferred to the leading and lagging strands are independent. Surprisingly, the frequency of homologous recombination was significantly lower in dpb3Δ, mcm2-3A and dpb3Δ mcm2-3A mutants, likely due to the elevated levels of free histones detected in the mutant cells. Together, these findings indicate that proper transfer of parental histones during DNA replication is essential for maintaining chromatin structure and that lower homologous recombination activity due to parental histone transfer defects is detrimental to cells.

Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer.

BACKGROUND: This study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients. METHODS: A total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre­therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines. RESULTS: Twenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels. CONCLUSION: Serum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.

Psychological stress induces hair regenerative disorders through corticotropin-releasing hormone-mediated autophagy inhibition.

Psychosocial stress is increasing, causing a growing number of people to suffer from hair loss. Stress-related corticotropin-releasing hormone (CRH) is associated with hair loss, but the mechanism by which hair follicles respond to stress and CRH remain poorly understood. The aim of the study is to elucidate the association between CRH and stress-related hair regenerative disorders, and reveal the potential pathological mechanisms. A chronic unpredictable stress mouse model and a chronic social defeat stress mouse model were used to examine the role of CRH and stress-related hair regrowth. Chronic unpredictable stress and chronic social defeat stress increased the expression of CRH and CRH receptors (CRHRs), and contributed to the onset of hair-cycle abnormalities. Psychoemotional stress and stress-related CRH blocked hair follicle regrowth, which could be restored by astressin, a CRHR antagonist. Long-term exposure to either chronic unpredictable stress or CRH induced a decrease in autophagy, which could be partially rescued by astressin. Activating CRHR, by stress or CRH administration, decreased autophagy via the mTOR-ULK1 signaling pathway to mediate hair regenerative disorders, which could be partially reversed through enhancing autophagy by administration of brefeldin A. These findings indicate that CRH-mediated autophagy inhibition play an important role in stress-induced hair regenerative disorders. CRH regulates the local hypothalamic-pituitary-adrenal axis of hair follicles, but also plays an independent pathogenic role in stress-related hair regenerative disorders through CRH-mediated autophagy inhibition. This work contributes to the present understanding of hair loss and suggests that enhancing autophagy may have a therapeutic effect on stress-induced hair loss.

Simultaneous Efficient Photocatalytic Hydrogen Evolution and Degradation of Dye Wastewater without Cocatalysts and Sacrificial Agents Based on g-C3N5 and Hybridized Ni-MOF Derivative-CdS-DETA.

Inspired by energy conversion and waste reuse, hybridized Ni-MOF derivative-CdS-DETA/g-C3N5, a type-II heterojunction photocatalyst, is synthesized by a hydrothermal method for simultaneous and highly efficient photocatalytic degradation and hydrogen evolution in dye wastewater. Without the addition of cocatalysts and sacrificial agents, the optimal MOF-CD(2)/CN5 (i.e. Ni-MOF derivative-CdS-DETA (20 wt.%)/g-C3N5) exhibit good bifunctional catalytic activity, with a H2 evolution rate of 2974.4 µmol g-1 h-1 during the degradation of rhodamine B (RhB), and a removal rate of 99.97% for RhB. In the process of H2-evolution-only, triethanolamine is used as a sacrificial agent, exhibiting a high H2 evolution rate (19663.1 µmol g-1 h-1) in the absence of a cocatalyst, and outperforming most similar related materials (such as MOF/g-C3N5, MOF-CdS, CdS/g-C3N5). With the help of type-II heterojunction, holes are scavenged for the oxidative degradation of RhB, and electrons are used in the decomposition of water for H2 evolution during illumination. This work opens a new path for photocatalysts with dual functions of simultaneous efficient degradation and hydrogen evolution.

Non-invasive diagnosis of liver fibrosis via MRI using targeted gadolinium-based nanoparticles.

INTRODUCTION: Accurate diagnosis of liver fibrosis is crucial for preventing cirrhosis and liver tumors. Liver fibrosis is driven by activated hepatic stellate cells (HSCs) with elevated CD44 expression. We developed hyaluronic acid (HA)-coated gadolinium-based nanoprobes to specifically target CD44 for diagnosing liver fibrosis using T1-weighted magnetic resonance imaging (MRI). MATERIALS AND METHODS: NaGdF4 nanoparticles (NPs) were synthesized via thermal decomposition and modified with polyethylene glycol (PEG) to obtain non-targeting NaGdF4@PEG NPs. These were subsequently coated with HA to target HSCs, resulting in liver fibrosis-targeting NaGdF4@PEG@HA nanoprobes. Characterization includedd transmission electron microscopy and X-ray diffraction. Cell viability was assessed using the Cell Counting Kit-8 (CCK-8). Internalization of NaGdF4@PEG@HA nanoprobes by mouse HSCs JS1 cells via ligand-receptor interaction was observed using flow cytometry and confocal laser scanning microscopy (CLSM). Liver fibrosis was induced in C57BL/6 mice using a methionine-choline deficient (MCD) diet. MRI performance and nanoprobe distribution in fibrotic and normal livers were analyzed using a GE Discovery 3.0T MR 750 scanner. RESULTS: NaGdF4@PEG@HA nanoprobes exhibited homogeneous morphology, low toxicity, and a high T1 relaxation rate (7.645 mM⁻¹s⁻¹). CLSM and flow cytometry demonstrated effective phagocytosis of NaGdF4@PEG@HA nanoprobes by JS1 cells compared to NaGdF4@PEG. MRI scans revealed higher T1 signals in fibrotic livers compared to normal livers after injection of NaGdF4@PEG@HA. NaGdF4@PEG@HA demonstrated higher targeting ability in fibrotic mice. CONCLUSIONS: NaGdF4@PEG@HA nanoprobes effectively target HSCs with high T1 relaxation rate, facilitating efficient MRI diagnosis of liver fibrosis.

Design and Realization of Visual and Contact-Type Fast Charging Power Source.

Charging power supplies with both fast and visualization functions have a wide range of applications in the information and new energy industries. In this paper, the visualized and contact-type fast charging power supply based on WO3 film and Zn sheet is presented, and the prototype devices are fabricated. Different with the charging method of conventional batteries, charging is achieved by a Zn sheet contacting with a WO3 film moistened with water, resulting in a rapid discoloration of WO3. Theoretical investigation indicates that the interaction between Zn sheet and water molecules is the primary cause of the color change in the WO3 film. The WO3 film completes the colouring state within 10 s in the presence of Zn sheet and water, and the open-circuit voltage of the device is 0.7 V, which can be used to drive various electronics by series-parallel connection. This research introduces a novel method to induce colouring of WO3 films and proposes a fast charging mode different from traditional power sources. It provides valuable insights for the future development of fast charging in the field of electrical energy.

Self-amplified activatable nanoprodrugs for enhanced chemodynamic/chemo combination therapy.

Chemodynamic therapy (CDT) has gained increasing attention by virtue of its high tumor specificity and low side effect. However, the low concentration of hydrogen peroxide (H2O2) in the tumor site suppresses the therapeutic efficacy of CDT. To improve the efficacy, introducing other kind of therapeutic modality is a feasible choice. Herein, we develop a self-amplified activatable nanomedicine (PCPTH NP) for chemodynamic/chemo combination therapy. PCPTH NP is composed of a H2O2-activatable amphiphilic prodrug PEG-PCPT and hemin. Upon addition of H2O2, the oxalate linkers within PCPTH NP are cleaved, which makes the simultaneous release of CPT and hemin. The released CPT can not only kill cancer cells but also upregulate the intracellular reactive oxygen species (ROS) level. The elevated ROS level may accelerate the release of drugs and enhance the CDT efficacy. PCPTH NP shows a H2O2concentration dependent release profile, and can effectively catalyze H2O2into hydroxyl radical (·OH) under acidic condition. Compared with PCPT NP without hemin, PCPTH NP has better anticancer efficacy bothin vitroandin vivowith high biosafety. Thus, our study provides an effective approach to improve the CDT efficacy with high tumor specificity.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China.

BACKGROUND: The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces. METHODS: A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations. RESULTS: Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups. CONCLUSION: Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Research on the causal relationship between fine particulate matter and type 2 diabetes mellitus: A two-sample multivariable mendelian randomization study.

BACKGROUND AND AIMS: Previous research has suggested a correlation between fine particulate matter (PM2.5) and type 2 diabetes mellitus (T2DM). However, the causality was vulnerable to confounding variables. METHODS AND RESULTS: A two-sample multivariable mendelian randomization study was designed to examine the causal connection between PM2.5 and T2DM. PM2.5 trait was investigated as exposure while T2DM-related traits as outcomes. The summary data were obtained from the Finngen database and the open genome-wide association study database. The mendelian randomization estimates were obtained using the inverse-variance weighted approach, and multiple sensitivity analyses were conducted. There were potential causal relationships between PM2.5 and T2DM (OR = 2.418; P = 0.019), PM2.5 and glycated hemoglobin (HbA1c) (OR = 1.590; P = 0.041), and PM2.5 and insulin metabolism. PM2.5 was found to have no causal effect on fasting glucose and insulin, 2-h glucose, and insulin-like growth factor binding protein-1 (P > 0.05), while had a potential protective effect against some diabetes complications. CONCLUSIONS: Our findings indicated potential causal relationships among PM2.5 and T2DM, especially the causal relationship between PM2.5 and long-term glucose levels.

Desipramine ameliorates fine particulate matter-induced hepatic insulin resistance by modulating the ceramide metabolism in mice.

Recent research has highlighted a correlation between exposure to ambient fine particulate matter (PM2.5) and the development of systemic insulin resistance (IR) along with an elevated risk of diabetes. Ceramide has emerged as one of the pathogenic mechanisms contributing to IR. The inhibition of acid sphingomyelinase (ASMase) activity by desipramine (DES) has been shown to effectively reduce ceramide levels. In the present study, 24 female C57BL/6 N mice were randomized into one of the four groups: the filtered air exposure (FA) group, the concentrated PM2.5 exposure (PM) group, the concentrated PM2.5 treated with low-dose DES (DL) group, and the concentrated PM2.5 treated with high-dose DES (DH) group. The PM, DL and DH groups were exposed to PM2.5 for an 8-week period within a whole-body exposure system. The study encompassed extensive examinations of glucose homeostasis, liver lipid profile, ceramide pathway, and insulin signaling pathway. Our results demonstrated that PM2.5 exposure caused impaired glucose tolerance, elevated ceramide levels, increased phosphorylation PP2A, reduced Akt phosphorylation, and hindered GLUT2 expression. Remarkably, DES administration mitigated PM2.5-induced IR by effectively lowering ceramide levels. In conclusion, the reduction of ceramide levels by DES may be a promising therapeutic strategy for coping PM2.5-induced IR.

Maintenance treatment with oral anticancer agents after first-line chemotherapy in patients with recurrent or metastatic nasopharyngeal carcinoma: a systematic review and meta-analysis.

OBJECTIVE: Maintenance therapy following first-line chemotherapy is of particular significance in patients diagnosed with recurrent or metastatic nasopharyngeal carcinoma (NPC). We conducted a meta-analysis to investigate the impact of maintenance therapy (MT) on the survival prognosis of individuals with recurrent or metastatic NPC. METHODS: The databases Embase, PubMed, and the Cochrane Library were thoroughly searched in a comprehensive manner. Prospective studies of MT for recurrent or metastatic NPC are required. Study endpoints included progression-free survival (PFS) and overall survival (OS). RESULTS: Two randomized controlled clinical trials, with a total of 294 participants, were analyzed. The maintenance therapy group consisted of 140 participants, while the remaining participants were in the non-maintenance therapy (non-MT) group. The MT group showed a notable enhancement in PFS compared to the non-MT group, with a hazard ratio(HR) of 0.44 and a 95% Confidence interval [CI] of 0.34-0.58 (p < 0.0001). Overall survival was also significantly improved (HR0.42, 95% CI 0.30-0.58; p < 0.0001). The incidence of grade 3 or 4 side effects in the MT group was leukopenia (2.9%), thrombocytopenia (0.7%), and anemia (4.3%), hand-foot syndrome (5.8%), and thrombocytopenia (0.7%). oral mucositis (1.5%), and nausea and vomiting (2.2%). CONCLUSIONS: Maintenance therapy with S-1 (tegafur/gimeracil/oltiracetam) or capecitabine following first-line chemotherapy significantly enhanced OS and PFS in patients with recurrent or metastatic nasopharyngeal carcinoma, while exhibiting minimal incidence of grade 3-4 side effects.

An intelligent grasper to provide real-time force feedback to shorten the learning curve in laparoscopic training.

BACKGROUND: A lack of force feedback in laparoscopic surgery often leads to a steep learning curve to the novices and traditional training system equipped with force feedback need a high educational cost. This study aimed to use a laparoscopic grasper providing force feedback in laparoscopic training which can assist in controlling of gripping forces and improve the learning processing of the novices. METHODS: Firstly, we conducted a pre-experiment to verify the role of force feedback in gripping operations and establish the safe gripping force threshold for the tasks. Following this, we proceeded with a four-week training program. Unlike the novices without feedback (Group A2), the novices receiving feedback (Group B2) underwent training that included force feedback. Finally, we completed a follow-up period without providing force feedback to assess the training effect under different conditions. Real-time force parameters were recorded and compared. RESULTS: In the pre-experiment, we set the gripping force threshold for the tasks based on the experienced surgeons' performance. This is reasonable as the experienced surgeons have obtained adequate skill of handling grasper. The thresholds for task 1, 2, and 3 were set as 0.731 N, 1.203 N and 0.938 N, respectively. With force feedback, the gripping force applied by the novices with feedback (Group B1) was lower than that of the novices without feedback (Group A1) (p < 0.005). During the training period, the Group B2 takes 6 trails to achieve gripping force of 0.635 N, which is lower than the threshold line, whereas the Group A2 needs 11 trails, meaning that the learning curve of Group B2 was significantly shorter than that of Group A2. Additionally, during the follow-up period, there was no significant decline in force learning, and Group B2 demonstrated better control of gripping operations. The training with force feedback received positive evaluations. CONCLUSION: Our study shows that using a grasper providing force feedback in laparoscopic training can help to control the gripping force and shorten the learning curve. It is anticipated that the laparoscopic grasper equipped with FBG sensor is promising to provide force feedback during laparoscopic training, which ultimately shows great potential in laparoscopic surgery.

Time Series Prediction of Gas Emission in Coal Mining Face Based on Optimized Variational Mode Decomposition and SSA-LSTM.

The accurate prediction of gas emissions has important guiding significance for the prevention and control of gas disasters in order to further improve the prediction accuracy of gas emissions in the mining face. According to the absolute gas emission monitoring data of the 1417 working face in a coal mine in Shaanxi Province, a GA-VMD-SSA-LSTM gas emission prediction model (GVSL) based on genetic algorithm (GA)-optimized variational mode decomposition (VMD) and sparrow search algorithm (SSA)-optimized long short-term memory (LSTM) is proposed. Firstly, a VMD evaluation standard for evaluating the amount of decomposition loss is proposed. Under this standard, the GA is used to find the optimal parameters of the VMD. Then, the SSA is used to optimize the key parameters of the LSTM to establish a GVSL prediction model. The model predicts each component and finally superimposes the prediction results for each component to obtain the final gas emission result. The results show that the accuracy of the evaluation indexes of the GVSL model and VMD-LSTM model, as well as the SSA-LSTM model and Gaussian process regression (GPR) model, are compared and analyzed horizontally and vertically under three scenarios with prediction sets of 121,94 and 57 groups. The GVSL model has the best prediction effect, and its fitting degree R2 values are 0.95, 0.96, and 0.99, which confirms the effectiveness of the proposed GVSL model for the time series prediction of gas emission in the mining face.

Gas Outburst Warning Method in Driving Faces: Enhanced Methodology through Optuna Optimization, Adaptive Normalization, and Transformer Framework.

Addressing common challenges such as limited indicators, poor adaptability, and imprecise modeling in gas pre-warning systems for driving faces, this study proposes a hybrid predictive and pre-warning model grounded in time-series analysis. The aim is to tackle the effects of broad application across diverse mines and insufficient data on warning accuracy. Firstly, we introduce an adaptive normalization (AN) model for standardizing gas sequence data, prioritizing recent information to better capture the time-series characteristics of gas readings. Coupled with the Gated Recurrent Unit (GRU) model, AN demonstrates superior forecasting performance compared to other standardization techniques. Next, Ensemble Empirical Mode Decomposition (EEMD) is used for feature extraction, guiding the selection of the Variational Mode Decomposition (VMD) order. Minimal decomposition errors validate the efficacy of this approach. Furthermore, enhancements to the transformer framework are made to manage non-linearities, overcome gradient vanishing, and effectively analyze long time-series sequences. To boost versatility across different mining scenarios, the Optuna framework facilitates multiparameter optimization, with xgbRegressor employed for accurate error assessment. Predictive outputs are benchmarked against Recurrent Neural Networks (RNN), GRU, Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM), where the hybrid model achieves an R-squared value of 0.980975 and a Mean Absolute Error (MAE) of 0.000149, highlighting its top performance. To cope with data scarcity, bootstrapping is applied to estimate the confidence intervals of the hybrid model. Dimensional analysis aids in creating real-time, relative gas emission metrics, while persistent anomaly detection monitors sudden time-series spikes, enabling unsupervised early alerts for gas bursts. This model demonstrates strong predictive prowess and effective pre-warning capabilities, offering technological reinforcement for advancing intelligent coal mine operations.

Metabolic Profile and Lipid Metabolism Phenotype in Mice with Conditional Deletion of Hepatic BMAL1.

The disruption of circadian rhythms (CRs) has been linked to metabolic disorders, yet the role of hepatic BMAL1, a key circadian regulator, in the whole-body metabolism and the associated lipid metabolic phenotype in the liver remains unclear. Bmal1 floxed (Bmal1f/f) and hepatocyte-specific Bmal1 knockout (Bmal1hep-/-) C57BL/6J mice underwent a regular feeding regimen. Hepatic CR, lipid content, mitochondrial function, and systemic metabolism were assessed at zeitgeber time (ZT) 0 and ZT12. Relevant molecules were examined to elucidate the metabolic phenotype. Hepatocyte-specific knockout of Bmal1 disrupted the expression of rhythmic genes in the liver. Bmal1hep-/- mice exhibited decreased hepatic TG content at ZT0, primarily due to enhanced lipolysis, reduced lipogenesis, and diminished lipid uptake. The ß-oxidation function of liver mitochondria decreased at both ZT0 and ZT12. Our findings on the metabolic profile and associated hepatic lipid metabolism in the absence of Bmal1 in hepatocytes provides new insights into metabolic syndromes from the perspective of liver CR disturbances.

CRISPR Screen Identifies the RNA-Binding Protein Eef1a1 as a Key Regulator of Myogenesis.

Skeletal muscle myogenesis hinges on gene regulation, meticulously orchestrated by molecular mechanisms. While the roles of transcription factors and non-coding RNAs in myogenesis are widely known, the contribution of RNA-binding proteins (RBPs) has remained unclear until now. Therefore, to investigate the functions of post-transcriptional regulators in myogenesis and uncover new functional RBPs regulating myogenesis, we employed CRISPR high-throughput RBP-KO (RBP-wide knockout) library screening. Through this approach, we successfully identified Eef1a1 as a novel regulatory factor in myogenesis. Using CRISPR knockout (CRISPRko) and CRISPR interference (CRISPRi) technologies, we successfully established cellular models for both CRISPRko and CRISPRi. Our findings demonstrated that Eef1a1 plays a crucial role in promoting proliferation in C2C12 myoblasts. Through siRNA inhibition and overexpression methods, we further elucidated the involvement of Eef1a1 in promoting proliferation and suppressing differentiation processes. RIP (RNA immunoprecipitation), miRNA pull-down, and Dual-luciferase reporter assays confirmed that miR-133a-3p targets Eef1a1. Co-transfection experiments indicated that miR-133a-3p can rescue the effect of Eef1a1 on C2C12 myoblasts. In summary, our study utilized CRISPR library high-throughput screening to unveil a novel RBP, Eef1a1, involved in regulating myogenesis. Eef1a1 promotes the proliferation of myoblasts while inhibiting the differentiation process. Additionally, it acts as an antagonist to miR-133a-3p, thus modulating the process of myogenesis.