Inactivation of mitochondrial MUL1 E3 ubiquitin ligase deregulates mitophagy and prevents diet-induced obesity in mice.

Obesity is a growing epidemic affecting millions of people worldwide and a major risk factor for a multitude of chronic diseases and premature mortality. Accumulating evidence suggests that mitochondria have a profound role in diet-induced obesity and the associated metabolic changes, but the molecular mechanisms linking mitochondria to obesity remain poorly understood. Our studies have identified a new function for mitochondrial MUL1 E3 ubiquitin ligase, a protein known to regulate mitochondrial dynamics and mitophagy, in the control of energy metabolism and lipogenesis. Genetic deletion of Mul1 in mice impedes mitophagy and presents a metabolic phenotype that is resistant to high-fat diet (HFD)-induced obesity and metabolic syndrome. Several metabolic and lipidomic pathways are perturbed in the liver and white adipose tissue (WAT) of Mul1(-/-) animals on HFD, including the one driven by Stearoyl-CoA Desaturase 1 (SCD1), a pivotal regulator of lipid metabolism and obesity. In addition, key enzymes crucial for lipogenesis and fatty acid oxidation such as ACC1, FASN, AMPK, and CPT1 are also modulated in the absence of MUL1. The concerted action of these enzymes, in the absence of MUL1, results in diminished fat storage and heightened fatty acid oxidation. Our findings underscore the significance of MUL1-mediated mitophagy in regulating lipogenesis and adiposity, particularly in the context of HFD. Consequently, our data advocate the potential of MUL1 as a therapeutic target for drug development in the treatment of obesity, insulin resistance, NAFLD, and cardiometabolic diseases.

Identification of molecular subtypes based on chromatin regulator-related genes and experimental verification of the role of ASCL1 in conferring chemotherapy resistance to breast cancer.

Objective: The aim of this study was to identify the molecular subtypes of breast cancer based on chromatin regulator-related genes. Methods: The RNA sequencing data of The Cancer Genome Atlas-Breast Cancer cohort were obtained from the official website, while the single-cell data were downloaded from the Gene Expression Omnibus database (GSE176078). Validation was performed using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Furthermore, the immune characteristics, tumor stemness, heterogeneity, and clinical characteristics of these molecular subtypes were analyzed. The correlation between chromatin regulators and chemotherapy resistance was examined in vitro using the quantitative real-time polymerase chain reaction (qRT-PCR) and Cell Counting Kit-8 (CCK8) assays. Results: This study identified three stable molecular subtypes with different prognostic and pathological features. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses revealed that the differentially expressed genes were associated with disease processes, such as mitotic nuclear division, chromosome segregation, condensed chromosome, and specific chromosome region. The T stage and subtypes were correlated with the clinical features. Tumor heterogeneity (mutant-allele tumor heterogeneity, tumor mutational burden, purity, and homologous recombination deficiency) and tumor stemness (RNA expression-based stemness score, epigenetically regulated RNA expression-based stemness score, DNA methylation-based stemness score, and epigenetically regulated DNA methylation-based stemness score) significantly varied between the three subtypes. Furthermore, Western blotting, qRT-PCR, and CCK8 assays demonstrated that the expression of ASCL1 was positively correlated with chemotherapy resistance in breast cancer. Conclusion: This study identified the subtypes of breast cancer based on chromatin regulators and analyzed their clinical features, gene mutation status, immunophenotype, and drug sensitivity. The results of this study provide effective strategies for assessing clinical prognosis and developing personalized treatment strategies.

Zn promoted GaZrOx ternary solid solution oxide combined with SAPO-34 effectively converts CO2 to light olefins with low CO selectivity.

We proposed a new strategy for CO2 hydrogenation to prepare light olefins by introducing Zn into GaZrOx to construct ZnGaZrOx ternary oxides, which was combined with SAPO-34 to prepare a high-performance ZnGaZrOx/SAPO-34 tandem catalyst for CO2 hydrogenation to light olefins. By optimizing the Zn doping content, the ratio and mode of the two-phase composite, and the process conditions, the 3.5%ZnGaZrOx/SAPO-34 tandem catalyst showed excellent catalytic performance and good high-temperature inhibition of the reverse water-gas shift (RWGS) reaction. The catalyst achieved 26.6% CO2 conversion, 82.1% C2=-C4= selectivity and 11.8% light olefins yield. The ZnGaZrOx formed by introducing an appropriate amount of Zn into GaZrOx significantly enhanced the spillover H2 effect and also induced the generation of abundant oxygen vacancies to effectively promote the activation of CO2. Importantly, the RWGS reaction was also significantly suppressed at high temperatures, with the CO selectivity being only 46.1% at 390°C.

Efficacy and safety of CO2 fractional laser versus Er:YAG fractional laser in the treatment of atrophic acne scar: A meta-analysis and systematic review.

BACKGROUND: To date, a consensus on the relative efficacy and safety of CO2 fractional laser versus erbium-doped yttrium aluminum garnet (Er:YAG) fractional laser treatments for atrophic acne scars has not been reached. This meta-analysis aims to systematically assess and compare their effectiveness and safety in clinical practice. METHODS: For this meta-analysis, we conducted comprehensive searches in Pubmed, Embase, and Cochrane databases, covering publications from their inception up to August 2023. Our focus was on studies comparing fractional CO2 laser with Er:YAG fractional laser treatments for atrophic acne scars. We excluded duplicate publications, research lacking full-text access, incomplete data, or cases where data extraction was not feasible. Additionally, animal experiments, reviews, and systematic reviews were not considered. Data analysis was performed using STATA 15.1. RESULTS: Eight studies (seven randomized controlled trials (RCTs) and a retrospective study) were included in this meta-analysis. The sample size ranged from 28 to 106 with a total of 418 patients, including 210 in the CO2 fractional group and 208 in Er:YAG fractional group. The pooled results showed that the effective rate of CO2 fractional laser in treating atrophic acne scar was significantly higher than that of Er:YAG fractional laser (OR = 1.81, 95% CI: 1.08-3.01) and the downtime of CO2 fractional laser in treating atrophic acne scar was significantly shorter than that of Er:YAG fractional laser (Weighted Mean Difference (WMD) = -2.11, 95% CI: -3.11 to -1.10). In addition, VAS of CO2 fractional laser in treating atrophic acne scar was significantly higher than that of Er:YAG fractional laser (WMD = 1.77, 95% CI: 1.32-2.21) and the duration of erythema of CO2 fractional laser in treating atrophic acne scar was significantly longer than that of Er:YAG fractional laser (WMD = 1.85, 95% CI: 1.63-2.07). However, there was no significant difference in the duration of pain and incidence of PIHbetween CO2 fractional laser and of Er:YAG fractional laser. CONCLUSION: When it comes to treating atrophic acne scars, CO2 fractional laser demonstrates superior efficacy and leads to shorter downtime. However, it is important to note that CO2 fractional laser treatments tend to result in higher pain intensity and may carry a higher risk of post-treatment pigmentation compared to Er:YAG fractional laser procedures.

From Organelle Morphology to Whole-Plant Phenotyping: A Phenotypic Detection Method Based on Deep Learning.

The analysis of plant phenotype parameters is closely related to breeding, so plant phenotype research has strong practical significance. This paper used deep learning to classify Arabidopsis thaliana from the macro (plant) to the micro level (organelle). First, the multi-output model identifies Arabidopsis accession lines and regression to predict Arabidopsis's 22-day growth status. The experimental results showed that the model had excellent performance in identifying Arabidopsis lines, and the model's classification accuracy was 99.92%. The model also had good performance in predicting plant growth status, and the regression prediction of the model root mean square error (RMSE) was 1.536. Next, a new dataset was obtained by increasing the time interval of Arabidopsis images, and the model's performance was verified at different time intervals. Finally, the model was applied to classify Arabidopsis organelles to verify the model's generalizability. Research suggested that deep learning will broaden plant phenotype detection methods. Furthermore, this method will facilitate the design and development of a high-throughput information collection platform for plant phenotypes.

Morphological Changes of the Temporomandibular Joint and Masseter Muscle After Mandibular Angle Osteotomy.

Mandibular angle osteotomy with outer cortex grinding is an effective cosmetic procedure for correcting square faces. However, morphological changes in the mandible may also cause temporomandibular joint (TMJ) disorders. This retrospective study aimed to investigate the morphological stabilization of the TMJ and changes in masseter muscle thickness after mandibular angle osteotomy to evaluate the safety of the procedure. Data from patients who underwent mandibular angle osteotomy with outer cortex grinding between January 2016 and January 2019 were retrospectively reviewed. Preoperative and long-term follow-up (~1 y) computed tomography data were collected from these patients, and morphological changes in the TMJ and masseter muscle were analyzed. The results from the computed tomography data showed that the condylar length and condylar height were significantly reduced 1 year after the operation (P < 0.05). In addition, the morphology of the TMJ was stable, and the distance between the mandibular condyle and the glenoid fossa did not change significantly. No significant difference was observed in masseter muscle thickness before and after the operation. After mandibular angle osteotomy with outer cortex grinding, the length and height of the mandibular condyle were functionally restored without any disorders of the TMJ. Moreover, the masseter muscle exhibited stable function. In conclusion, the procedure is safe for occlusal function and suitable for popularization.

Response of microbial community composition and function to land use in mining soils of Xikuang Mountain in Hunan.

Nine land types in the northern mining area (BKQ) (mining land, smelting land, living area), the old mining area (LKQ) (whole-ore heap, wasteland, grassland), and southern mining area (NKQ) (grassland, shrubs, farmland) of Xikuang Mountain were chosen to explore the composition and functions of soil bacterial communities under different habitats around mining areas. The composition and functions of soil bacterial communities were compared among the sampling sites using 16S rRNA high-throughput sequencing and metagenomic sequencing. α diversity analysis showed the soil bacterial diversity and abundance in the old mining area were significantly higher than those in the northern mining area. ß diversity analysis demonstrated that the soil bacterial community composition was highly similar among different vegetation coverages in the southern mining area. Microbial community function analysis showed the annotated KEGG function pathways and eggNOG function composition were consistent between the grassland of the old mining area and the grassland of the southern mining area. This study uncovers the soil bacterial community composition and functions among different habitats in the mining areas of Xikuang Mountain and will underlie soil ecosystem restoration in different habitats under heavy metal pollution around the mining areas there.

Spectrum feature extraction method combining Allan variance, VMD, and PSD.

Spectrum feature extraction plays a crucial role in identifying seismic events and calculating structural response parameters. However, the criteria for identifying effective modal components in Variational Mode Decomposition (VMD) are not well-defined, resulting in inaccurate spectrum feature extraction. To address this issue, we propose a novel spectrum feature extraction method that combines Allan variance, VMD, and power spectral density (PSD). Firstly, VMD is applied to filter noise components from triaxial accelerometer observations and add effective signals. Secondly, PSD is utilized to extract three groups of seismic frequencies (tri-axial accelerometers). Finally, the Allan method is introduced to identify the group of accelerometer observations with the highest reliability as the vibration frequency caused by the seismic excitation. We validate the effectiveness of our method by analyzing a Mw 2.6 micro-seismic event that occurred in Huairou, Beijing in 2022. The result shows that our proposed method accurately extracts spectrum features of the Great Wall. Specifically, the seismic excitation vibration frequencies at four monitoring stations were found to be 26.95 Hz, 12.89 Hz, 12.89 Hz, and 12.5 Hz. These findings underscore our method's utility in evaluating the Great Wall's structural response to seismic loading, which has significant implications for the conservation and protection of heritage structures.

Unraveling the important role of comammox Nitrospira to nitrification in the coastal aquaculture system.

Increasing nitrogen (N) input to coastal ecosystems poses a serious environmental threat. It is important to understand the responses and feedback of N removal microbial communities, particularly nitrifiers including the newly recognized complete ammonia-oxidizers (comammox), to improve aquaculture sustainability. In this study, we conducted a holistic evaluation of the functional communities responsible for nitrification by quantifying and sequencing the key functional genes of comammox Nitrospira-amoA, AOA-amoA, AOB-amoA and Nitrospira-nxrB in fish ponds with different fish feeding levels and evaluated the contribution of nitrifiers in the nitrification process through experiments of mixing pure cultures. We found that higher fish feeding dramatically increased N-related concentration, affecting the nitrifying communities. Compared to AOA and AOB, comammox Nitrospira and NOB were more sensitive to environmental changes. Unexpectedly, we detected an equivalent abundance of comammox Nitrospira and AOB and observed an increase in the proportion of clade A in comammox Nitrospira with the increase in fish feeding. Furthermore, a simplified network and shift of keystone species from NOB to comammox Nitrospira were observed in higher fish-feeding ponds. Random forest analysis suggested that the comammox Nitrospira community played a critical role in the nitrification of eutrophic aquaculture ponds (40-70 µM). Through the additional experiment of mixing nitrifying pure cultures, we found that comammox Nitrospira is the primary contributor to the nitrification process at 200 µM ammonium. These results advance our understanding of nitrifying communities and highlight the importance of comammox Nitrospira in driving nitrification in eutrophic aquaculture systems.

Establishment of a real-time fluorescent quantitative PCR detection method and phylogenetic analysis of BoAHV-1.

BACKGROUND: Infectious bovine rhinotracheitis (IBR), caused by Bovine alphaherpesvirus-1 (BoAHV-1), is an acute, highly contagious disease primarily characterized by respiratory tract lesions in infected cattle. Due to its severe pathological damage and extensive transmission, it results in significant economic losses in the cattle industry. Accurate detection of BoAHV-1 is of paramount importance. In this study, we developed a real-time fluorescent quantitative PCR detection method for detecting BoAHV-1 infections. Utilizing this method, we tested clinical samples and successfully identified and isolated a strain of BoAHV-1.1 from positive samples. Subsequently, we conducted a genetic evolution analysis on the isolate strain's gC, TK, gG, gD, and gE genes. RESULTS: The study developed a real-time quantitative PCR detection method using SYBR Green II, achieving a detection limit of 7.8 × 101 DNA copies/µL. Specificity and repeatability analyses demonstrated no cross-reactivity with other related pathogens, highlighting excellent repeatability. Using this method, 15 out of 86 clinical nasal swab samples from cattle were found to be positive (17.44%), which was higher than the results obtained from conventional PCR detection (13.95%, 12/86). The homology analysis and phylogenetic tree analysis of the gC, TK, gG, gD, and gE genes of the isolated strain indicate that the JL5 strain shares high homology with the BoAHV-1.1 reference strains. Amino acid sequence analysis revealed that gC, gE, and gG each had two amino acid mutations, while the TK gene had one synonymous mutation and one H to Y mutation, with no amino acid mutations observed in the gD gene. Phylogenetic tree analysis indicated that the JL5 strain belongs to the BoAHV-1.1 genotype and is closely related to American strains such as C33, C14, and C28. CONCLUSIONS: The established real-time fluorescent quantitative PCR detection method exhibits good repeatability, specificity, and sensitivity. Furthermore, genetic evolution analysis of the isolated BoAHV-1 JL-5 strain indicates that it belongs to the BoAHV-1.1 subtype. These findings provide a foundation and data for the detection, prevention, and control Infectious Bovine Rhinotracheitis.

Hydrolyzed egg yolk peptide prevented osteoporosis by regulating Wnt/ß-catenin signaling pathway in ovariectomized rats.

Hydrolyzed egg yolk peptide (YPEP) was shown to increase bone mineral density in ovariectomized rats. However, the underlying mechanism of YPEP on osteoporosis has not been explored. Recent studies have shown that Wnt/ß-catenin signaling pathway and gut microbiota may be involved in the regulation of bone metabolism and the progression of osteoporosis. The present study aimed to explore the preventive effect of the YPEP supplementation on osteoporosis in ovariectomized (OVX) rats and to verify whether YPEP can improve osteoporosis by regulating Wnt/ß-catenin signaling pathway and gut microbiota. The experiment included five groups: sham surgery group (SHAM), ovariectomy group (OVX), 17-ß estradiol group (E2: 25 µg /kg/d 17ß-estradiol), OVX with low-dose YPEP group (LYPEP: 10 mg /kg/d YPEP) and OVX with high-dose YPEP group (HYPEP: 40 mg /kg/d YPEP). In this study, all the bone samples used were femurs. Micro-CT analysis revealed improvements in both bone mineral density (BMD) and microstructure by YPEP treatment. The three-point mechanical bending test indicated an enhancement in the biomechanical properties of the YPEP groups. The serum levels of bone alkaline phosphatase (BALP), bone gla protein (BGP), calcium (Ca), and phosphorus (P) were markedly higher in the YPEP groups than in the OVX group. The LYPEP group had markedly lower levels of alkaline phosphatase (ALP), tartrate-resistant acid phosphatase (TRAP) and C-terminal telopeptide of type I collagen (CTX-I) than the OVX group. The YPEP groups had significantly higher protein levels of the Wnt3a, ß-catenin, LRP5, RUNX2 and OPG of the Wnt/ß-catenin signaling pathway compared with the OVX group. Compared to the OVX group, the ratio of OPG/RANKL was markedly higher in the LYPEP group. At the genus level, there was a significantly increase in relative abundance of Lachnospiraceae_NK4A136_group and a decrease in Escherichia_Shigella in YPEP groups, compared with the OVX group. However, in the correlation analysis, there was no correlation between these two bacteria and bone metabolism and microstructure indexes. These findings demonstrate that YPEP has the potential to improve osteoporosis, and the mechanism may be associated with its modulating effect on Wnt/ß-catenin signaling pathway.

BERT-TFBS: a novel BERT-based model for predicting transcription factor binding sites by transfer learning.

Transcription factors (TFs) are proteins essential for regulating genetic transcriptions by binding to transcription factor binding sites (TFBSs) in DNA sequences. Accurate predictions of TFBSs can contribute to the design and construction of metabolic regulatory systems based on TFs. Although various deep-learning algorithms have been developed for predicting TFBSs, the prediction performance needs to be improved. This paper proposes a bidirectional encoder representations from transformers (BERT)-based model, called BERT-TFBS, to predict TFBSs solely based on DNA sequences. The model consists of a pre-trained BERT module (DNABERT-2), a convolutional neural network (CNN) module, a convolutional block attention module (CBAM) and an output module. The BERT-TFBS model utilizes the pre-trained DNABERT-2 module to acquire the complex long-term dependencies in DNA sequences through a transfer learning approach, and applies the CNN module and the CBAM to extract high-order local features. The proposed model is trained and tested based on 165 ENCODE ChIP-seq datasets. We conducted experiments with model variants, cross-cell-line validations and comparisons with other models. The experimental results demonstrate the effectiveness and generalization capability of BERT-TFBS in predicting TFBSs, and they show that the proposed model outperforms other deep-learning models. The source code for BERT-TFBS is available at https://github.com/ZX1998-12/BERT-TFBS.

Ent-eudesmane sesquiterpenoids with anti-neuroinflammatory activity from the marine-derived fungus Eutypella sp. F0219.

In this study, twenty-three ent-eudesmane sesquiterpenoids (1-23) including fifteen previously undescribed ones, named eutypelides A-O (1-15) were isolated from the marine-derived fungus Eutypella sp. F0219. Their planar structures and relative configurations were established by HR-ESIMS and extensive 1D and 2D NMR investigations. The absolute configurations of the previously undescribed compounds were determined by single-crystal X-ray diffraction analyses, modified Mosher's method, and ECD calculations. Structurally, eutypelide A (1) is a rare 1,10-seco-ent-eudesmane, whereas 2-15 are typically ent-eudesmanes with 6/6/-fused bicyclic carbon nucleus. The anti-neuroinflammatory activity of all isolated compounds (1-23) was accessed based on their ability to NO production in LPS-stimulated BV2 microglia cells. Compound 16 emerged as the most potent inhibitor. Further mechanistic investigation revealed that compound 16 modulated the inflammatory response by decreasing the protein levels of iNOS and increasing ARG 1 levels, thereby altering the iNOS/ARG 1 ratio and inhibiting macrophage polarization. qRT-PCR analysis showed that compound 16 reversed the LPS-induced upregulation of pro-inflammatory cytokines, including iNOS, TNF-α, IL-6, and IL-1ß, at both the transcriptional and translational levels. These effects were linked to the inhibition of the NF-κB pathway, a key regulator of inflammation. Our findings suggest that compound 16 may be a potential structure basis for developing neuroinflammation-related disease therapeutic agents.

Integrative analyses of bulk and single-cell transcriptomics reveals the infiltration and crosstalk of cancer-associated fibroblasts as a novel predictor for prognosis and microenvironment remodeling in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly malignant neoplasm and characterized by desmoplastic matrix. The heterogeneity and crosstalk of tumor microenvironment remain incompletely understood. METHODS: To address this gap, we performed Weighted Gene Co-expression Network Analysis (WGCNA) to identify and construct a cancer associated fibroblasts (CAFs) infiltration biomarker. We also depicted the intercellular communication network and important receptor-ligand complexes using the single-cell transcriptomics analysis of tumor and Adjacent normal tissue. RESULTS: Through the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained. After a series of regression analyses, the CAFs score was generated by integrating the expressions of EVA1A, APBA2, LRRTM4, GOLGA8M, BPIFB2, and their corresponding coefficients. In the TCGA-CHOL, GSE89748, and 107,943 cohorts, the high CAFs score group showed unfavorable survival prognosis (p < 0.001, p = 0.0074, p = 0.028, respectively). Additionally, a series of drugs have been predicted to be more sensitive to the high-risk group (p < 0.05). Subsequent to dimension reduction and clustering, thirteen clusters were identified to construct the single-cell atlas. Cell-cell interaction analysis unveiled significant enhancement of signal transduction in tumor tissues, particularly from fibroblasts to malignant cells via diverse pathways. Moreover, SCENIC analysis indicated that HOXA5, WT1, and LHX2 are fibroblast specific motifs. CONCLUSIONS: This study reveals the key role of fibroblasts - oncocytes interaction in the remodeling of the immunosuppressive microenvironment in intrahepatic cholangiocarcinoma. Subsequently, it may trigger cascade activation of downstream signaling pathways such as PI3K-AKT and Notch in tumor, thus initiating tumorigenesis. Targeted drugs aimed at disrupting fibroblasts-tumor cell interaction, along with associated enrichment pathways, show potential in mitigating the immunosuppressive microenvironment that facilitates tumor progression.

Impact of Health Education Based on Protective Motivation Theory on the Mood State, Cancer-Related Fatigue, and Hope Level of Gastric Cancer Patients.

Background: Gastric cancer patients often feel physically tired and weak, lacking confidence and enthusiasm for relevant treatments. We aimed to explore the impacts of health education based on the theory of protective motivation on the emotional state, cancer-related fatigue, and hope levels of gastric cancer patients. Methods: A total of 160 gastric cancer patients admitted to the Sanmenxia Central Hospital, Henan, China, from May 2019 to March 2022 were selected as subjects. The control group (n=80) received routine health education, while the observation group (n=80) received health education based on the theory of protective motivation. Intervention evaluations included the Morisky medication compliance score, Plain Mood State Scale (POMS), Cancer Fatigue Scale (CFS), Herth Hope Scale (HHI), and Simple Health Survey Scale (SF-36). Results: After intervention, both groups showed an improvement in Morisky's medication compliance score, HHI scale score, and SF-36 scale score (all P<0.05). Additionally, the observation group exhibited greater improvement than the control group (P<0.05). There were no significant differences in POMS scale score and CFS scale score between the two groups before and after intervention. However, after intervention, both groups experienced a decrease in POMS scale score and CFS scale score (both P<0.05), with the observation group showing a more significant decrease compared to the control group (P<0.05). Conclusion: Health education based on the theory of protective motivation effectively enhances the mood state, reduces cancer-related fatigue, and increases hope levels among gastric cancer patients, thereby improving their medication compliance and overall quality of life.

Metal Nanogap Memory: Performances and Switching Mechanism.

The nanogap memory (NGM) device, emerging as a promising nonvolatile memory candidate, has attracted increasing attention for its simple structure, nano/atomic scale size, elevated operating speed, and robustness to high temperatures. In this study, nanogap memories based on Pd, Au, and Pt were fabricated by combining nanofabrication with electromigration technology. Subsequent evaluations of the electrical characteristics were conducted under ambient air or vacuum conditions at room temperature. The investigation unveiled persistent challenges associated with metal NGM devices, including (1) prolonged SET operation time in comparison to RESET, (2) the potential generation of error bits when enhancing switching speeds, and (3) susceptibility to degradation during program/erase cycles. While these issues have been encountered by predecessors in NGM device development, the underlying causes have remained elusive. Employing molecular dynamics (MD) simulation, we have, for the first time, unveiled the dynamic processes of NGM devices during both SET and RESET operations. The MD simulation highlights that the adjustment of the tunneling gap spacing in nanogap memory primarily occurs through atomic migration or field evaporation. This dynamic process enables the device to transition between the high-resistance state (HRS) and the low-resistance state (LRS). The identified mechanism provides insight into the origins of the aforementioned challenges. Furthermore, the study proposes an effective method to enhance the endurance of NGM devices based on the elucidated mechanism.

Deciphering styrene oxide tolerance mechanisms in Gluconobacter oxydans mutant strain.

Chemical production wastewater contains large amounts of organic solvents (OSs), which pose a significant threat to the environment. In this study, a 10 g·L-1 styrene oxide tolerant strain with broad-spectrum OSs tolerance was obtained via adaptive laboratory evolution. The mechanisms underlying the high OS tolerance of tolerant strain were investigated by integrating physiological, multi-omics, and genetic engineering analyses. Physiological changes are one of the main factors responsible for the high OS tolerance in mutant strains. Moreover, the P-type ATPase GOX_RS04415 and the LysR family transcriptional regulator GOX_RS04700 were also verified as critical genes for styrene oxide tolerance. The tolerance mechanisms of OSs can be used in biocatalytic chassis cell factories to synthesize compounds and degrade environmental pollutants. This study provides new insights into the mechanisms underlying the toxicological response to OS stress and offers potential targets for enhancing the solvent tolerance of G. oxydans.

Effect of Prosocial Behaviors on e-Consultations in a Web-Based Health Care Community: Panel Data Analysis.

BACKGROUND: Patients using web-based health care communities for e-consultation services have the option to choose their service providers from an extensive digital market. To stand out in this crowded field, doctors in web-based health care communities often engage in prosocial behaviors, such as proactive and reactive actions, to attract more users. However, the effect of these behaviors on the volume of e-consultations remains unclear and warrants further exploration. OBJECTIVE: This study investigates the impact of various prosocial behaviors on doctors' e-consultation volume in web-based health care communities and the moderating effects of doctors' digital and offline reputations. METHODS: A panel data set containing information on 2880 doctors over a 22-month period was obtained from one of the largest web-based health care communities in China. Data analysis was conducted using a 2-way fixed effects model with robust clustered SEs. A series of robustness checks were also performed, including alternative measurements of independent variables and estimation methods. RESULTS: Results indicated that both types of doctors' prosocial behaviors, namely, proactive and reactive actions, positively impacted their e-consultation volume. In terms of the moderating effects of external reputation, doctors' offline professional titles were found to negatively moderate the relationship between their proactive behaviors and their e-consultation volume. However, these titles did not significantly affect the relationship between doctors' reactive behaviors and their e-consultation volume (P=.45). Additionally, doctors' digital recommendations from patients negatively moderated both the relationship between doctors' proactive behaviors and e-consultation volume and the relationship between doctors' reactive behaviors and e-consultation volume. CONCLUSIONS: Drawing upon functional motives theory and social exchange theory, this study categorizes doctors' prosocial behaviors into proactive and reactive actions. It provides empirical evidence that prosocial behaviors can lead to an increase in e-consultation volume. This study also illuminates the moderating roles doctors' digital and offline reputations play in the relationships between prosocial behaviors and e-consultation volume.

Effects of antibiotics on microbial nitrogen cycling and N2O emissions: A review.

Sulfonamides, quinolones, tetracyclines, and macrolides are the most prevalent classes of antibiotics used in both medical treatment and agriculture. The misuse of antibiotics leads to their extensive dissemination in the environment. These antibiotics can modify the structure and functionality of microbial communities, consequently impacting microbial-mediated nitrogen cycling processes including nitrification, denitrification, and anammox. They can change the relative abundance of nirK/norB contributing to the emission of nitrous oxide, a potent greenhouse gas. This review provides a comprehensive examination of the presence of these four antibiotic classes across different environmental matrices and synthesizes current knowledge of their effects on the nitrogen cycle, including the underlying mechanisms. Such an overview is crucial for understanding the ecological impacts of antibiotics and for guiding future research directions. The presence of antibiotics in the environment varies widely, with significant differences in concentration and type across various settings. We conducted a comprehensive review of over 70 research articles that compare various aspects including processes, antibiotics, concentration ranges, microbial sources, experimental methods, and mechanisms of influence. Antibiotics can either inhibit, have no effect, or even stimulate nitrification, denitrification, and anammox, depending on the experimental conditions. The influence of antibiotics on the nitrogen cycle is characterized by dose-dependent responses, primarily inhibiting nitrification, denitrification, and anammox. This is achieved through alterations in microbial community composition and diversity, carbon source utilization, enzyme activities, electron transfer chain function, and the abundance of specific functional enzymes and antibiotic resistance genes. These alterations can lead to diminished removal of reactive nitrogen and heightened nitrous oxide emissions, potentially exacerbating the greenhouse effect and related environmental issues. Future research should consider diverse reaction mechanisms and expand the scope to investigate the combined effects of multiple antibiotics, as well as their interactions with heavy metals and other chemicals or organisms.

Clinical phenotype of a Kallmann syndrome patient with IL17RD and CPEB4 variants.

Background: This study aimed to characterize the clinical phenotype and genetic variations in patients with Kallmann syndrome (KS). Methods: This study involved the collection and analysis of clinical data from an individual with sporadic KS. Following this, peripheral blood samples were obtained from the patient and his parents. Genomic deoxyribonucleic acid was extracted and subjected to whole-exome sequencing and genomic copy number variation (CNV) detection. Finally, Sanger sequencing was performed to validate the suspected pathogenic variants. Results: Whole-exome sequencing confirmed that the child carried both the IL17RD variant (c.2101G>A, p.Gly701Ser) inherited from the mother and the new CPEB4 variant (c.1414C>T, p.Arg472*). No pathogenic CNVs were identified in CNV testing. Conclusion: Bioinformatics analysis shows that the IL17RD protein undergoing Gly701Ser mutation and is speculated to be phosphorylated and modified, thereby disrupting fibroblast growth factor signaling. This study also suggested that the CPEB4 might play a crucial role in the key signaling process affecting olfactory bulb morphogenesis. Overall, the findings of this study broaden the gene expression profile of KS-related pathogenic genes. This offers a new avenue for exploring the pathogenic mechanism of KS and provides valuable insights for precise clinical diagnosis and treatment strategies for this condition.