Caffeic acid O-methyltransferase from Ligusticum chuanxiong alleviates drought stress, and improves lignin and melatonin biosynthesis.

Drought stress is a major constraint on plant growth and agricultural productivity. Caffeic acid O-methyltransferase (COMT), an enzyme involved in the methylation of various substrates, plays a pivotal role in plant responses to abiotic stress. The involvement of COMTs in drought response, particularly through the enhancement of lignin and melatonin biosynthesis, remains poorly understood. In this study, LcCOMT was firstly proposed to be associated with the biosynthesis of both lignin and melatonin, as demonstrated through sequence comparison, phylogenetic analysis, and conserved motif identification. In vitro enzymatic assays revealed that LcCOMT effectively methylates N-acetylserotonin to melatonin, albeit with a higher Km value compared to caffeic acid. Site-directed mutagenesis of residues Phe171 and Asp269 resulted in a significant reduction in catalytic activity for caffeic acid, with minimal impact on N-acetylserotonin, underscoring the specificity of these residues in substrate binding and catalysis. Under drought conditions, LcCOMT expression was significantly upregulated. Overexpression of LcCOMT gene in Arabidopsis plants conferred enhanced drought tolerance, characterized by elevated lignin and melatonin levels, increased chlorophyll and carotenoid content, heightened activities of antioxidant enzymes peroxidase (POD), catalase (CAT), and superoxide dismutase (SOD), and reduced malondialdehyde (MDA) and hydrogen peroxide (H2O2) accumulation. This study is among the few to demonstrate that COMT-mediated drought tolerance is achieved through the simultaneous promotion of lignin and melatonin biosynthesis. LcCOMT represents the first functionally characterized COMT in Apiaceae family, and it holds potential as a target for genetic enhancement of drought tolerance in future crop improvement strategies.

Imputing abundance of over 2,500 surface proteins from single-cell transcriptomes with context-agnostic zero-shot deep ensembles.

Cell surface proteins serve as primary drug targets and cell identity markers. Techniques such as CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) have enabled the simultaneous quantification of surface protein abundance and transcript expression within individual cells. The published data have been utilized to train machine learning models for predicting surface protein abundance solely from transcript expression. However, the small scale of proteins predicted and the poor generalization ability of these computational approaches across diverse contexts (e.g., different tissues/disease states) impede their widespread adoption. Here, we propose SPIDER (surface protein prediction using deep ensembles from single-cell RNA sequencing), a context-agnostic zero-shot deep ensemble model, which enables large-scale protein abundance prediction and generalizes better to various contexts. Comprehensive benchmarking shows that SPIDER outperforms other state-of-the-art methods. Using the predicted surface abundance of >2,500 proteins from single-cell transcriptomes, we demonstrate the broad applications of SPIDER, including cell type annotation, biomarker/target identification, and cell-cell interaction analysis in hepatocellular carcinoma and colorectal cancer. A record of this paper's transparent peer review process is included in the supplemental information.

Individual and joint exposure to air pollutants and patterns of multiple chronic conditions.

Existing research on the detrimental effects of air pollution and its mixture on multiple chronic conditions (MCC) is not yet fully recognized. Our objective was to examine if individual and joint exposure to air pollution is associated with the incidence and patterns of MCC. Totally 10,231 CHARLS 2015 participants aged over 45 years and 1,938 without MCC were followed up in 2018 and 2020. Residential-levelcumulative personal exposure concentrations of PM1, PM10, PM2.5, CO, O3, NO2, SO2, NO3-, Cl-, NH4+, and SO42- at the residential level were determined utilizing a spatio-temporal random forest model with a spatial resolution of 0.1° × 0.1°. In the cross-sectional and longitudinal research, logistic regression, cox regression analysis, and quantile g-computation were utilized to estimate the single and joint effect with MCC and its patterns, respectively. Interaction analyses and stratified analyses were also performed. A correlation was observed between the prevalence of cardiovascular illnesses and the presence of all 11 major air pollutants. PM2.5, PM10, NH4+, NO3-, CO, and SO42- are associated with an increased frequency of respiratory disorders. An increase of PM2.5, PM1, PM10, NO2, and SO2 (a 10 µg/m3 rise), CO (a 0.1 mg/m3 rise), and PMCs (Cl-, NH4+, NO3-, and SO42-) (a 1 µg/m3 rise) corresponded to the HRs (95% CI) for developing MCC of 1.194 (95% CI: 1.043, 1.367), 1.362 (95% CI: 1.073, 1.728), 1.115 (95% CI: 1.026, 1.212), 1.443 (95% CI: 1.151, 1.808), 3.175 (95% CI: 2.291, 4.401), 1.272 (95% CI: 1.149,1.410), 1.382 (95% CI: 1.011, 1.888), 1.107 (95% CI: 1.003, 1.222), 1.035 (95% CI: 0.984, 1.088), and 1.122 (95% CI: 1.086, 1.160), respectively. SO2 was the predominant contributor to the combined effect (HR: 2.083, 95% CI: 1.659-2.508). Gender, age, drinking, and health status could modify the effects of air pollutants on MCC patterns. Long-term exposure to air pollution is correlated to the incidence and patterns of MCC in middle-aged and elderly Chinese individuals. Preventive methods are essential to safeguarding those susceptible to MCC.

Prediction of feeding difficulties in neonates with hypoxic-ischemic encephalopathy using magnetic resonance imaging-derived radiomics features.

BACKGROUND: The mechanisms behind brain and spinal cord injuries in hypoxic-ischemic encephalopathy (HIE) and associated feeding difficulties are unclear, with previous magnetic resonance imaging (MRI) attempts yielding inconclusive results. OBJECTIVE: We aim to evaluate an MRI radiomics model for predicting feeding difficulties in HIE infants. Additionally, we investigate changes in predictive capability after incorporating the duration of mechanical ventilation and the timing of MRI examination. MATERIALS AND METHODS: Retrospective study with 151 HIE infants (January 2013 to December 2021), randomly divided into training and validation sets. Radiomics features extracted from basal ganglia-thalamus and brainstem in T1-weighted and T2-weighted MRI. Established single-modality, single-site, and multimodality/multisite models. Receiver operating characteristic analysis and area under the curve evaluated models. Decision curve analysis assessed changes in predictive capability. RESULTS: The combined radiomics model of the basal ganglia-thalamus and brainstem regions on the T2-weighted imaging demonstrated superior performance (area under the curve: 0.958 and 0.875 for training and validation, respectively). Combining scores with duration of mechanical ventilation and MRI examination time in a calibration plot model improved and stabilized performance, showing high fitting and clinical utility. Decision curve analysis favored the combined calibration plot model. CONCLUSION: The MRI-based radiomics model predicts feeding difficulties in HIE infants, with basal ganglia-thalamus and brainstem as relevant factors. The combined calibration plot model exhibits the highest clinical predictive efficacy.

TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning.

Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellular responses for a variety of cell lines, including those derived from underrepresented groups, is not trivial when resources are minimal. Using gene expression to predict other measurements has been actively explored; however, systematic investigation of its predictive power in various measurements has not been well studied. Here, we evaluated commonly used machine learning methods and presented TransCell, a two-step deep transfer learning framework that utilized the knowledge derived from pan-cancer tumor samples to predict molecular features and responses. Among these models, TransCell had the best performance in predicting metabolite, gene effect score (or genetic dependency), and drug sensitivity, and had comparable performance in predicting mutation, copy number variation, and protein expression. Notably, TransCell improved the performance by over 50% in drug sensitivity prediction and achieved a correlation of 0.7 in gene effect score prediction. Furthermore, predicted drug sensitivities revealed potential repurposing candidates for new 100 pediatric cancer cell lines, and predicted gene effect scores reflected BRAF resistance in melanoma cell lines. Together, we investigated the predictive power of gene expression in six molecular measurement types and developed a web portal (http://apps.octad.org/transcell/) that enables the prediction of 352,000 genomic and cellular response features solely from gene expression profiles.

Prediction of synergistic gemcitabine-based combination treatment through a novel tumor stemness biomarker NANOG in pancreatic cancer.

Gemcitabine remains a first-class chemotherapeutic drug for pancreatic cancer. However, due to the rapid development of gemcitabine resistance in pancreatic cancer, gemcitabine alone or in combination with other anti-cancer drugs only showed limited effect in the clinic. It is extremely challenging to effectively and efficiently determine the optimal drug regimens. Thus, identification of appropriate prediction biomarkers is critical for the rational design of gemcitabine-based therapeutic options. Herein, a pancreatic cancer stem cell (PCSC) model exhibiting chemoresistance to gemcitabine was used to test the activity of clinical cancer drugs in the presence or absence of gemcitabine. As determined by combinatorial treatment, several types of drugs resensitized gemcitabine-resistant PCSCs to gemcitabine, with sorafenib (EGFR inhibitor)/gemcitabine and sunitinib (TBK1 inhibitors)/gemcitabine drug combinations being the most preferred treatments for PCSCs. Following the validation of the PCSC model by an antibody array test of 15-gene expression of stemness biomarkers, NANOG showed markedly different expression in PCSCs compared to the parental cells. From comprehensive analysis of stem cell index versus combination index, a stemness-related correlation model was successfully constructed to demonstrate the correlation between NANOG expression and synergism. Cancer cell stemness was ascertained to be highly relevant to NANOG overexpression that can be abrogated by synergized gemcitabine-drug combinations. Therefore, NANOG works as a therapeutic biomarker for predicating efficient combinatorial treatment of gemcitabine in pancreatic cancer.

Notopterygium incisum roots extract (NRE) alleviates neuroinflammation pathology in Alzheimer's disease through TLR4-NF-κB pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Notopterygium incisum Ting ex H. T. Chang, also called 'Qianghuo', is a distinct umbelliferae plant in China. The rhizomes and roots of Notopterygium incisum have long been used to treat headaches, colds, analgesia and rheumatoid arthritis. It is a main traditional Chinese medicine in Qianghuo Yufeng Decoction, which was used to treat diseases such as liver and kidney insufficiency, mental paralysis and dementia. AIM OF THIS STUDY: As the most common dementia, Alzheimer's disease (AD) has a complicated pathogenesis. So far, there is no effective drug to prevent its pathological process. Previous research has shown that Notopterygium incisum root extract (NRE) may inhibit the release of Aß and the activation of tau in mice with AD. However, the effect of NRE on the pathological process of neuroinflammation is still unclear. MATERIALS AND METHODS: We determined the pro-inflammatory cytokines levels in BV2 cells exposed to LPS/Aß42 after treated with NRE. APP/PS1 and LPS-induced C57BL/6 neuroinflammatory mice were given NRE for 8 weeks and 5 days respectively to detect the pathological changes of neuroinflammation. RESULTS: The findings showed that NRE had a notable inhibitory effect on the levels of TNF-α and IL-1ß in BV2 cells induced by LPS/Aß42. The results of in vivo experiments show that following NRE treatment, there was a notable decrease in the number of activated microglia in the hippocampus of APP/PS1 mice as indicated by immunofluorescence results. Sholl analysis showed that microglia branches increased in NRE group, indicating that M1 microglia activation was inhibited. In the mice model injected with LPS in the tail vein, PCR and Western Blot results confirmed the anti-inflammatory effect of NRE, Nissl staining showed the protective effect of NRE on neurons, and immunofluorescence results also indicated that the activation of M1 microglia was inhibited. CONCLUSION: These results suggest that long term oral administration of NRE may inhibit neuroinflammation in the progression of AD.

Optimal therapeutic strategies for hepatic metachronous oligometastatic nasopharyngeal carcinoma: Insights from a retrospective study.

Hepatic metachronous oligometastatic nasopharyngeal carcinoma (hmoNPC) exhibits distinct clinical characteristics compared to other types of metastatic NPC. We investigated the optimal therapy for hmoNPC. 160 patients with hmoNPC treated in Sun Yat-sen University Cancer Center between 2010 and 2021 were retrospectively recruited. A total of 56 patients were classified into the local therapy (LT) cohort, 23 into the systemic therapy (ST) cohort and 81 into the combination therapy (LT + ST) cohort. The median PFS was 7.9 months (95% confidence interval [CI]: 4.1-11.9 months) in the LT cohort, 15.5 months (95% CI: 10.5-32.3 months) in the ST cohort, and 31.3 months (95% CI: 20.3 to NA months) in the LT + ST cohort. The median OS was 41.1 months (95% CI: 30.0-54.0 months) in the LT cohort, 50.4 months (95% CI: 41.5 to NA months) in the ST cohort and not reached (NR) (95% CI: 77.3 to NA months) in the LT + ST cohort. Cox analysis was used to construct nomograms to predict patient outcomes. Among patients with no evidence of disease status after LT, the prognosis was significantly better in the LT + ST cohort than LT cohort (median PFS: NR [95% CI: 29.0 to NA months] vs. 20.0 months [95% CI: 10.4 to NA months]). More survival benefits were achieved with platinum-based chemotherapy than oral monotherapy (median PFS: NR [95% CI: 21.7 to NA months] vs. 17.2 months [95% CI: 10.2 to NA months]). Fewer postoperative early progression events were observed in neoadjuvant chemotherapy cohort than in adjuvant chemotherapy cohort (2.78% vs. 18.81%, P = .013). In conclusion, combining neoadjuvant platinum-based chemotherapy and local therapy was the best strategy for patients with hmoNPC.

Imputing abundance of over 2500 surface proteins from single-cell transcriptomes with context-agnostic zero-shot deep ensembles.

Cell surface proteins serve as primary drug targets and cell identity markers. The emergence of techniques like CITE-seq has enabled simultaneous quantification of surface protein abundance and transcript expression for multimodal data analysis within individual cells. The published data have been utilized to train machine learning models for predicting surface protein abundance based solely from transcript expression. However, the small scale of proteins predicted and the poor generalization ability for these computational approaches across diverse contexts, such as different tissues or disease states, impede their widespread adoption. Here we propose SPIDER (surface protein prediction using deep ensembles from single-cell RNA-seq), a context-agnostic zero-shot deep ensemble model, which enables the large-scale prediction of cell surface protein abundance and generalizes better to various contexts. Comprehensive benchmarking shows that SPIDER outperforms other state-of-the-art methods. Using the predicted surface abundance of >2500 proteins from single-cell transcriptomes, we demonstrate the broad applications of SPIDER including cell type annotation, biomarker/target identification, and cell-cell interaction analysis in hepatocellular carcinoma and colorectal cancer.

Kalman filtering to reduce measurement noise of sample entropy: An electroencephalographic study.

In the analysis of electroencephalography (EEG), entropy can be used to quantify the rate of generation of new information. Entropy has long been known to suffer from variance that arises from its calculation. From a sensor's perspective, calculation of entropy from a period of EEG recording can be treated as physical measurement, which suffers from measurement noise. We showed the feasibility of using Kalman filtering to reduce the variance of entropy for simulated signals as well as real-world EEG recordings. In addition, we also manifested that Kalman filtering was less time-consuming than moving average, and had better performance than moving average and exponentially weighted moving average. In conclusion, we have treated entropy as a physical measure and successfully applied the conventional Kalman filtering with fixed hyperparameters. Kalman filtering is expected to be used to reduce measurement noise when continuous entropy estimation (for example anaesthesia monitoring) is essential with high accuracy and low time-consumption.

The mediating role of hostile attribution bias in social exclusion affecting aggressive behavior.

Aggression is one of the public social issues affecting campus harmony and stability, and social exclusion is an important interpersonal contextual factor among many factors affecting aggression. However, studies examining the influence of social exclusion on aggression and its mediating mechanism are not systematic enough. Based on the general aggression model (GAM), we intend to explore the role of hostile attribution bias (HAB) in both trait and state levels of social exclusion, which leads to aggression through a combination of questionnaire and experimental methods. Study 1 surveyed 388 current high school students (Mage = 16.09, SD = 1.01) and found that HAB mediates the relationship between long-term social exclusion (trait level) and aggression tendency. Study 2 experimented with 181 high school students (Mage = 16.95, SD = 1.13) to examine whether short-term social exclusion (state level) after initiating the Cyberball paradigm could still influence aggressive behavior through the mediating role of HAB. Results found that the mediating role of HAB still holds. The findings of the study further enrich the GAM and have important implications for a more targeted approach to aggression prevention and intervention.

ChemReco: automated recognition of hand-drawn carbon-hydrogen-oxygen structures using deep learning.

Chemical molecular structures are a direct and convenient means of expressing chemical knowledge, playing a vital role in academic communication. In chemistry, hand drawing is a common task for students and researchers. If we can convert hand-drawn chemical molecular structures into machine-readable formats, like SMILES encoding, computers can efficiently process and analyze these structures, significantly enhancing the efficiency of chemical research. Furthermore, with the progress of educational technology, automated grading is gaining popularity. When machines automatically recognize chemical molecular structures and assess the correctness of the drawings, it offers great convenience to teachers. We created ChemReco, a tool designed to identify chemical molecular structures involving three atoms: C, H, and O, providing convenience for chemical researchers. Currently, there are limited studies on hand-drawn chemical molecular structures. Therefore, the primary focus of this paper is constructing datasets. We propose a synthetic image method to rapidly generate images resembling hand-drawn chemical molecular structures, enhancing dataset acquisition efficiency. Regarding model selection, the hand-drawn chemical molecule structural recognition model developed in this article achieves a final recognition accuracy of 96.90%. This model employs the encoder-decoder architecture of EfficientNet + Transformer, demonstrating superior performance compared to other encoder-decoder combinations.

Pan-Cancer Analysis of ART1 and its Potential Value in Gastric Cancer.

Objective: To comprehensively explore the impact of Mono-ADP-ribosyltransferases-1 expression on both prognosis and the intricate landscape of the tumor immune microenvironment across diverse cancer types, our study seeks to delve into the multifaceted interplay between Mono-ADP-ribosyltransferases-1 expression levels and their implications for clinical outcomes and the dynamic milieu of immune responses within tumors. Methods: Genomic, transcriptomic, and clinical datasets spanning diverse cancer types were meticulously curated from The Cancer Genome Atlas and Genotypic Tissue Expression repositories. Initially, our inquiry focused on discerning the prognostic significance and immunological implications of Mono-ADP-ribosyltransferases-1 expression across this heterogeneous spectrum of malignancies. Subsequently, we scrutinized the relationships between Mono-ADP-ribosyltransferases-1 expression levels and a spectrum of factors including RNA modification genes, genetic mutations, and the emergent concept of tumor stemness. Employing functional enrichment analyses, we endeavored to unravel the underlying mechanistic pathways modulated by Mono-ADP-ribosyltransferases-1. Leveraging Bayesian co-localization analysis, we sought to discern the spatial convergence of Mono-ADP-ribosyltransferases-1 expression particularly within the context of digestive tract tumors. Lastly, to corroborate our findings, we conducted in vitro experiments, specifically focusing on Gastric Cancer, thus corroborating the putative oncogenic role attributed to Mono-ADP-ribosyltransferases-1 in this malignancy. Results: Across diverse tumor types, Mono-ADP-ribosyltransferases-1 expression exhibits distinctive patterns compared to normal and adjacent tissues, thereby intertwining with the prognostic outcomes of numerous cancer patients. Noteworthy findings from our immune role identification underscore the pivotal involvement of Mono-ADP-ribosyltransferases-1 in the landscape of tumor immunotherapy. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis elucidates the enrichment of Mono-ADP-ribosyltransferases-1-associated genes predominantly within the NF-kB, Foxo, and PI3K-Akt signaling cascades, shedding light on potential mechanistic pathways underlying its influence. Bayesian co-localization analysis unveils a compelling genetic correlation between Mono-ADP-ribosyltransferases-1 and digestive tract tumors, accentuating its relevance within this specific oncological domain. Importantly, experimental validation attests to the therapeutic promise of targeting Mono-ADP-ribosyltransferases-1 in the treatment paradigm of gastric cancer, thereby underscoring its potential as a viable therapeutic target deserving of further exploration and clinical translation. Conclusion: This comprehensive pan-cancer analysis unveils crucial insights into the intricate role played by Mono-ADP-ribosyltransferases-1 in the tumorigenesis of diverse malignancies, thereby establishing a robust theoretical framework for subsequent in-depth investigations. Leveraging these insights, targeting Mono-ADP-ribosyltransferases-1-related signaling pathways within the dynamic tumor microenvironment emerges as a promising avenue for novel therapeutic interventions in the realm of tumor immunotherapy. By delineating the interplay between Mono-ADP-ribosyltransferases-1 expression and tumorigenic processes across various cancer types, this study paves the way for innovative therapeutic strategies aimed at disrupting oncogenic signaling cascades and bolstering immune-mediated antitumor responses.

Distinct fungal communities affecting opposite galanthamine accumulation patterns in two Lycoris species.

Lycoris radiata is the main source of galanthamine, a clinical drug used in Alzheimer's disease; however, the galanthamine content in L. radiata is low. Lycoris aurea is another Lycoris species with high galanthamine content. Fungal endophytes can enhance plant secondary metabolite accumulation; thus, we compared the fungal communities in these two Lycoris species to identify certain fungal taxa in L. aurea capable of enhancing galanthamine accumulation. Several fungal endophytes, which were enriched in, exclusively isolated from L. aurea, or showed significant correlations with galanthamine, were demonstrated to enhance the accumulation of only galanthamine but no other Amaryllidaceae alkaloids (AAs) in L. radiata. These fungal endophytes mainly upregulated the downstream genes in the biosynthesis pathways of AAs in L. radiata, suggesting that they may allocate more precursors for galanthamine biosynthesis. This study demonstrated that fungal endophytes from L. aurea with higher galanthamine content can specifically enhance the accumulation of this medicinal alkaloid in other Lycoris species, thereby increasing the galanthamine source and reducing galanthamine separation and purification costs. This study broadens our understanding of the complex interactions between plant secondary metabolites and fungal endophytes.

Hypervirulent fowl adenovirus serotype 4 elicits early innate immune response and promotes virus-induced cellular autophagy in the spleen.

The recent emergence of hepatitis-hydropericardium syndrome caused by highly pathogenic fowl adenovirus serotype 4 (FAdV-4) has resulted in significant economic losses to the poultry industry. However, the early innate immune response of immune organs within 24 hpi and the induction of autophagy in vivo after FAdV-4 infection have not been fully elucidated. In this study, 35-day-old specific pathogen-free (SPF) chickens were artificially infected with hypervirulent FAdV-4, which resulted in a mortality rate of up to 90%. The results showed that FAdV-4 infection rapidly triggered the innate immune response in vivo of chickens, with the spleen eliciting a stronger innate immune response than the thymus and bursa. During the early stage of viral infection within 24 hpi, the main receptors TLR3/7/21, MDA5, and cGAS were activated via the NF-κB and TBK1/IRF7-dependent signaling pathways, which up-regulated production of inflammatory cytokines and type I interferons. Additionally, the expression levels of the autophagy-related molecules LC3B, Beclin1, and ATG5 were significantly up-regulated at 24 hpi, while degradation of SQSTM1/p62 was observed, suggesting that FAdV-4 infection elicits a complete autophagy response in the spleen. Besides, the colocalization of Fiber2 and LC3B suggested that FAdV-4 infection induced autophagy which benefits FAdV-4 replication in vivo. This study provides new insights into the immunoregulation signal pathways of the early innate immunity in response to hypervirulent FAdV-4 infection in vivo within 24 hpi and the close relationship between viral replication and autophagy.

Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes.

The emerging large language models (LLMs) are actively evaluated in various fields including healthcare. Most studies have focused on established benchmarks and standard parameters; however, the variation and impact of prompt engineering and fine-tuning strategies have not been fully explored. This study benchmarks GPT-3.5 Turbo, GPT-4, and Llama-7B against BERT models and medical fellows' annotations in identifying patients with metastatic cancer from discharge summaries. Results revealed that clear, concise prompts incorporating reasoning steps significantly enhanced performance. GPT-4 exhibited superior performance among all models. Notably, one-shot learning and fine-tuning provided no incremental benefit. The model's accuracy sustained even when keywords for metastatic cancer were removed or when half of the input tokens were randomly discarded. These findings underscore GPT-4's potential to substitute specialized models, such as PubMedBERT, through strategic prompt engineering, and suggest opportunities to improve open-source models, which are better suited to use in clinical settings.

Circular RNA circNIPBL regulates TP53-H179R mutations in NNK-induced bronchial epithelial carcinogenesis.

Exposure to environmental carcinogens is a significant contributor to cancer development, with genetic and epigenetic alterations playing pivotal roles in the carcinogenic process. However, the interplay between epigenetic regulation and genetic changes in carcinogenesis has yet to receive comprehensive attention. This study investigates the impact of continuous exposure to the tobacco-specific carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) on bronchial epithelial cells, leading to malignant transformation. Our findings reveal the down-regulation of the tumor suppressor-like circular RNA circNIPBL during oncogenic processes concomitant with the accumulation of the TP53-H179R, a single nucleotide variant. Diminished circNIPBL expression enhances the proliferative, distant metastatic, and tumor-forming capabilities of NNK-induced cancerous cells and lung cancer cell lines (A549, H1299), while also promoting the accumulation of TP53-H179R during NNK-induced carcinogenesis. Mechanistic investigations demonstrate that circNIPBL interacts with HSP90α to regulate the translocation of AHR into the nucleus, which may be a potential regulatory mechanism for NNK-induced carcinogenesis and TP53-H179R accumulation. This study introduces a novel perspective on the interplay between genetic alterations and epigenetic regulation in chemical carcinogenesis, which provides novel insight into the etiology of cancer.

Analysis of related factors and treatment effect of chylothorax after lung surgery.

Background: Chylothorax is a seldom encountered complication following lung surgery. However, due to the widespread practice of lung surgery, postoperative complications have inevitably arisen. Chylothorax significantly affects a patient's discharge and recovery. This study investigates the risk factors for postoperative chylothorax at our center and analyzes various treatment modalities and prognostic outcomes. Methods: A retrospective analysis was conducted on all postoperative lung resections performed between January 2018 to August 2021 that met the inclusion criteria. Inclusion criteria covered patients undergoing various thoracic surgeries for lung conditions, while exclusion criteria included postoperative referrals for surgeries unrelated to lung tumors. Results: Postoperative chylothorax occurred in 42 of 5,706 patients after lung surgery. General information and disease-related data of the chylothorax and control group were analyzed by univariate and multivariate analyses. Multivariate analysis showed that serum albumin before surgery [odds ratio (OR) =0.86, 95% confidence interval (CI): 0.81-0.91, P<0.001], γ-glutamyl transferase level before surgery (after logarithmic transformation, OR =1.01, 95% CI: 1.00-1.01, P=0.01), squamous cell carcinoma (OR =2.77, 95% CI: 1.37-5.6, P=0.008), right mediastinal lymph node dissection (OR =3.15, 95% CI: 1.62-6.14, P<0.001) were independent risk factors for postoperative chylothorax. Among the 42 cases of postoperative chylothorax, 26 patients were improved with conservative treatments, and 6 patients were improved with chemical pleurodesis. Eight patients with postoperative chylothorax underwent thoracoscopic thoracic duct ligation. Three patients experienced severe postoperative complications: one was discharged after prolonged treatment, while the remaining two either succumbed or were discharged against medical advice. Conclusions: The incidence of chylothorax after lung surgery closely correlates with the intraoperative trauma and nutritional status of patients during the perioperative period. The majority of patients with postoperative chylothorax experienced relief through conservative measures, somatostatin administration, and chemical pleurodesis. Nevertheless, substantial postoperative chylothorax necessitated surgical intervention, involving thoracic duct ligation or drug pleurodesis.

The TLR4/NF-κB/NLRP3 and Nrf2/HO-1 pathways mediate the neuroprotective effects of alkaloids extracted from Uncaria rhynchophylla in Parkinson's disease.

ETHNOPHARMACOLOGICAL RELEVANCE: Parkinson's disease (PD) is the second most common neurodegenerative disorder with limited therapeutic options available. Neuroinflammation plays an important role in the occurrence and development of PD. Alkaloids extracted from Uncaria rhynchophylla (URA), have emerged as a potential neuroprotective agent because of its anti-inflammatory and anti-oxidant properties. Nevertheless, the underlying mechanism by which URA exerts neuroprotective effects in PD remains obscure. AIM OF THE STUDY: The main aim of this study was to investigate the neuroprotective effects and underlying mechanism of URA in the treatment of PD through in vivo and in vitro models, focusing on the neuroinflammation and oxidative stress pathways. MATERIALS AND METHODS: The protective effects of URA against PD were evaluated by neurobehavioral tests, immunohistochemistry, serum biochemical assays, and real-time quantitative polymerase chain reaction in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mice. The role of the TLR4/NF-κB/NLRP3 pathway and the Nrf2/HO-1 pathway in URA-mediated effects was examined in lipopolysaccharide (LPS)-stimulated BV-2 microglial cells and a microglia-neuron coculture system. RESULTS: URA significantly alleviated motor deficits and dopaminergic neurotoxicity, and reversed the abnormal secretion of inflammatory and oxidative stress factors in the serum of MPTP-induced mice. URA suppressed the gene expression of Toll-like receptor 4 (TLR4), NOD-like receptor protein 3, and cyclooxygenase 2 (COX2) in the striatum of PD mice. Further studies indicated that URA inhibited activation of the TLR4/NF-κB/NLRP3 pathway and enhanced activation of the Nrf2/HO-1 pathway, reduced reactive oxygen species (ROS) production, and reversed the secretion of inflammatory mediators in LPS-stimulated BV-2 microglial cells, thereby alleviating neuroinflammatory damage to SH-SY5Y neuronal cells. CONCLUSION: URA exerted neuroprotective effects against PD mainly by the inhibition of the TLR4/NF-κB/NLRP3 pathway and activation of the Nrf2/HO-1 antioxidant pathway, highlighting URA as a promising candidate for PD treatment.

Gradient Doping Enables an Extraordinary Efficiency in Thermoelectric PbTe1-xIx.

The conversion efficiency of thermoelectric generators that have to be operated under a temperature difference (ΔT) is mainly determined by material's dimensionless figure of merit (zT). However, maximization of zT at each temperature requires an optimization of carrier concentration (nopt) which strongly depends on the temperature and band parameters. Commonly utilized strategy of chemical doping usually enables a homogeneous carrier concentration throughout the material, leading the maximal zT to be achievable only within a narrow temperature range. In this work, a gradiently doping is successfully realized in PbTe1-xIx using a vertical gradient solidification technique, enabling a spatial gradient in carrier concentration that correspondingly optimizes zT at each portion of the material under its operating temperature. Such a gradient doping results in an extraordinary device efficiency of ≈14% at a ΔT of ≈500 K, corresponding to a ≈40% improvement as compared to that of homogeneous doping. Since directional solidification technique commonly enables gradient dopant concentrations in semiconductors, the resultant gradient carrier concentration is illustrated here as an effective approach for advancing thermoelectrics.