VARIDT 3.0: the phenotypic and regulatory variability of drug transporter.

The phenotypic and regulatory variability of drug transporter (DT) are vital for the understanding of drug responses, drug-drug interactions, multidrug resistances, and so on. The ADME property of a drug is collectively determined by multiple types of variability, such as: microbiota influence (MBI), transcriptional regulation (TSR), epigenetics regulation (EGR), exogenous modulation (EGM) and post-translational modification (PTM). However, no database has yet been available to comprehensively describe these valuable variabilities of DTs. In this study, a major update of VARIDT was therefore conducted, which gave 2072 MBIs, 10 610 TSRs, 46 748 EGRs, 12 209 EGMs and 10 255 PTMs. These variability data were closely related to the transportation of 585 approved and 301 clinical trial drugs for treating 572 diseases. Moreover, the majority of the DTs in this database were found with multiple variabilities, which allowed a collective consideration in determining the ADME properties of a drug. All in all, VARIDT 3.0 is expected to be a popular data repository that could become an essential complement to existing pharmaceutical databases, and is freely accessible without any login requirement at: https://idrblab.org/varidt/.

DRESIS: the first comprehensive landscape of drug resistance information.

Widespread drug resistance has become the key issue in global healthcare. Extensive efforts have been made to reveal not only diverse diseases experiencing drug resistance, but also the six distinct types of molecular mechanisms underlying this resistance. A database that describes a comprehensive list of diseases with drug resistance (not just cancers/infections) and all types of resistance mechanisms is now urgently needed. However, no such database has been available to date. In this study, a comprehensive database describing drug resistance information named 'DRESIS' was therefore developed. It was introduced to (i) systematically provide, for the first time, all existing types of molecular mechanisms underlying drug resistance, (ii) extensively cover the widest range of diseases among all existing databases and (iii) explicitly describe the clinically/experimentally verified resistance data for the largest number of drugs. Since drug resistance has become an ever-increasing clinical issue, DRESIS is expected to have great implications for future new drug discovery and clinical treatment optimization. It is now publicly accessible without any login requirement at: https://idrblab.org/dresis/.

A task-specific encoding algorithm for RNAs and RNA-associated interactions based on convolutional autoencoder.

RNAs play essential roles in diverse physiological and pathological processes by interacting with other molecules (RNA/protein/compound), and various computational methods are available for identifying these interactions. However, the encoding features provided by existing methods are limited and the existing tools does not offer an effective way to integrate the interacting partners. In this study, a task-specific encoding algorithm for RNAs and RNA-associated interactions was therefore developed. This new algorithm was unique in (a) realizing comprehensive RNA feature encoding by introducing a great many of novel features and (b) enabling task-specific integration of interacting partners using convolutional autoencoder-directed feature embedding. Compared with existing methods/tools, this novel algorithm demonstrated superior performances in diverse benchmark testing studies. This algorithm together with its source code could be readily accessed by all user at: https://idrblab.org/corain/ and https://github.com/idrblab/corain/.

Tailoring Titanium Carbide Clusters for New Materials: from Met-Cars to Carbon-Doped Superatoms.

Tailoring materials with prescribed properties and regular structures is a critical and challenging research topic. Early transition metals were found to form supermagic M8C12 metallocarbohedrenes (Met-Cars); however, stable metal carbides are not limited to this common stoichiometry. Utilizing self-developed deep-ultraviolet laser ionization mass spectrometry, here, we report a strategy to generate new titanium carbides by reacting pure Tin clusters with acetylene. Interestingly, two products corresponding to Ti17C2 and Ti19C10 exhibit superior abundances in addition to the Ti8C12 Met-Cars. Using global-minimum search, the structures of Ti17C2 and Ti19C10 are determined to be an ellipsoidal D4d and a rod-shaped D5h geometry, respectively, both with carbon-capped Ti4C moieties and superatomic features. We illustrate the electronic structures and bonding nature in these carbon-doped superatoms concerning their enhanced stability and local aromaticity, shedding light on a new class of metal-carbide nanomaterials with atomic precision.

Large Language Model-Based Natural Language Encoding Could Be All You Need for Drug Biomedical Association Prediction.

Analyzing drug-related interactions in the field of biomedicine has been a critical aspect of drug discovery and development. While various artificial intelligence (AI)-based tools have been proposed to analyze drug biomedical associations (DBAs), their feature encoding did not adequately account for crucial biomedical functions and semantic concepts, thereby still hindering their progress. Since the advent of ChatGPT by OpenAI in 2022, large language models (LLMs) have demonstrated rapid growth and significant success across various applications. Herein, LEDAP was introduced, which uniquely leveraged LLM-based biotext feature encoding for predicting drug-disease associations, drug-drug interactions, and drug-side effect associations. Benefiting from the large-scale knowledgebase pre-training, LLMs had great potential in drug development analysis owing to their holistic understanding of natural language and human topics. LEDAP illustrated its notable competitiveness in comparison with other popular DBA analysis tools. Specifically, even in simple conjunction with classical machine learning methods, LLM-based feature representations consistently enabled satisfactory performance across diverse DBA tasks like binary classification, multiclass classification, and regression. Our findings underpinned the considerable potential of LLMs in drug development research, indicating a catalyst for further progress in related fields.

Overexpressing S100A9 ameliorates NK cell dysfunction in estrogen receptor-positive breast cancer.

BACKGROUND: Estrogen receptor (ER) positive human epidermal growth factor receptor 2 (HER2) negative breast cancer (ER+/HER2-BC) and triple-negative breast cancer (TNBC) are two distinct breast cancer molecular subtypes, especially in tumor immune microenvironment (TIME). The TIME of TNBC is considered to be more inflammatory than that of ER+/HER2-BC. Natural killer (NK) cells are innate lymphocytes that play an important role of tumor eradication in TME. However, studies focusing on the different cell states of NK cells in breast cancer subtypes are still inadequate. METHODS: In this study, single-cell mRNA sequencing (scRNA-seq) and bulk mRNA sequencing data from ER+/HER2-BC and TNBC were analyzed. Key regulator of NK cell suppression in ER+/HER2-BC, S100A9, was quantified by qPCR and ELISA in MCF-7, T47D, MDA-MB-468 and MDA-MB-231 cell lines. The prognosis predictability of S100A9 and NK activation markers was evaluated by Kaplan-Meier analyses using TCGA-BRAC data. The phenotype changes of NK cells in ER+/HER2-BC after overexpressing S100A9 in cancer cells were evaluated by the production levels of IFN-gamma, perforin and granzyme B and cytotoxicity assay. RESULTS: By analyzing scRNA-seq data, we found that multiple genes involved in cellular stress response were upregulated in ER+/HER2-BC compared with TNBC. Moreover, TLR regulation pathway was significantly enriched using differentially expressed genes (DEGs) from comparing the transcriptome data of ER+/HER2-BC and TNBC cancer cells, and NK cell infiltration high/low groups. Among the DEGs, S100A9 was identified as a key regulator. Patients with higher expression levels of S100A9 and NK cell activation markers had better overall survival. Furthermore, we proved that overexpression of S100A9 in ER+/HER2-cells could improve cocultured NK cell function. CONCLUSION: In conclusion, the study we presented demonstrated that NK cells in ER+/HER2-BC were hypofunctional, and S100A9 was an important regulator of NK cell function in ER+BC. Our work contributes to elucidate the regulatory networks between cancer cells and NK cells and may provide theoretical basis for novel drug development.

Genome-wide identification and investigation of monosaccharide transporter gene family based on their evolution and expression analysis under abiotic stress and hormone treatments in maize (Zea mays L.).

BACKGROUND: Monosaccharide transporter (MST) family, as a carrier for monosaccharide transport, plays an important role in carbon partitioning and widely involves in plant growth and development, stress response, and signaling transduction. However, little information on the MST family genes is reported in maize (Zea mays), especially in response to abiotic stresses. In this study, the genome-wide identification of MST family genes was performed in maize. RESULT: A total of sixty-six putative members of MST gene family were identified and divided into seven subfamilies (including SPT, PMT, VGT, INT, pGlcT, TMT, and ERD) using bioinformatics approaches, and gene information, phylogenetic tree, chromosomal location, gene structure, motif composition, and cis-acting elements were investigated. Eight tandem and twelve segmental duplication events were identified, which played an important role in the expansion of the ZmMST family. Synteny analysis revealed the evolutionary features of MST genes in three gramineous crop species. The expression analysis indicated that most of the PMT, VGT, and ERD subfamilies members responded to osmotic and cadmium stresses, and some of them were regulated by ABA signaling, while only a few members of other subfamilies responded to stresses. In addition, only five genes were induced by NaCl stress in MST family. CONCLUSION: These results serve to understand the evolutionary relationships of the ZmMST family genes and supply some insight into the processes of monosaccharide transport and carbon partitioning on the balance between plant growth and development and stress response in maize.

ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA.

In recent years, many studies have illustrated the significant role that non-coding RNA (ncRNA) plays in biological activities, in which lncRNA, miRNA and especially their interactions have been proved to affect many biological processes. Some in silico methods have been proposed and applied to identify novel lncRNA-miRNA interactions (LMIs), but there are still imperfections in their RNA representation and information extraction approaches, which imply there is still room for further improving their performances. Meanwhile, only a few of them are accessible at present, which limits their practical applications. The construction of a new tool for LMI prediction is thus imperative for the better understanding of their relevant biological mechanisms. This study proposed a novel method, ncRNAInter, for LMI prediction. A comprehensive strategy for RNA representation and an optimized deep learning algorithm of graph neural network were utilized in this study. ncRNAInter was robust and showed better performance of 26.7% higher Matthews correlation coefficient than existing reputable methods for human LMI prediction. In addition, ncRNAInter proved its universal applicability in dealing with LMIs from various species and successfully identified novel LMIs associated with various diseases, which further verified its effectiveness and usability. All source code and datasets are freely available at https://github.com/idrblab/ncRNAInter.

Targeted ablation of the left middle cervical ganglion prevents ventricular arrhythmias and cardiac injury induced by AMI.

Cardiac sympathetic overactivation is a critical driver in the progression of acute myocardial infarction (AMI). The left middle cervical ganglion (LMCG) is an important extracardiac sympathetic ganglion. However, the regulatory effects of LMCG on AMI have not yet been fully documented. In the present study, we detected that the LMCG was innervated by abundant sympathetic components and exerted an excitatory effect on the cardiac sympathetic nervous system in response to stimulation. In canine models of AMI, targeted ablation of LMCG reduced the sympathetic indexes of heart rate variability and serum norepinephrine, resulting in suppressed cardiac sympathetic activity. Moreover, LMCG ablation could improve ventricular electrophysiological stability, evidenced by the prolonged ventricular effective refractory period, elevated action potential duration, increased ventricular fibrillation threshold, and enhanced connexin43 expression, consequently showing antiarrhythmic effects. Additionally, compared with the control group, myocardial infarction size, circulating cardiac troponin I, and myocardial apoptosis were significantly reduced, accompanied by preserved cardiac function in canines subjected to LMCG ablation. Finally, we performed the left stellate ganglion (LSG) ablation and compared its effects with LMCG destruction. The results indicated that LMCG ablation prevented ventricular electrophysiological instability, cardiac sympathetic activation, and AMI-induced ventricular arrhythmias with similar efficiency as LSG denervation. In conclusion, this study demonstrated that LMCG ablation suppressed cardiac sympathetic activity, stabilized ventricular electrophysiological properties and mitigated cardiomyocyte death, resultantly preventing ischemia-induced ventricular arrhythmias, myocardial injury, and cardiac dysfunction. Neuromodulation therapy targeting LMCG represented a promising strategy for the treatment of AMI.

Combined modulation format identification and optical signal-to-noise ratio monitoring with high accuracy and generalizability based on a proposed fused module few-shot learning algorithm in dynamic coherent optical transmissions.

Modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) monitoring are important portions of optical performance monitoring (OPM) for future dynamic optical networks. In this paper, we proposed a fusion module few-shot learning (FMFSL) algorithm as an improvement upon the ordinary few-shot learning algorithms for image recognition with the specialty in adopting a combination of a dilated convolutional group and an asymmetric convolutional group to advance the feature extraction. FMFSL algorithm is applied in MFI and OSNR monitoring in coherent optical communication systems with its performance investigated in both back-to-back and fiber transmission scenarios using small-scale constellation diagrams. The results show that FMFSL algorithm can achieve 100% accuracy in MFI and higher OSNR monitoring accuracy compared to the few-shot learning algorithms Deep Nearest Neighbor Neural Network (DN4) and Prototypical Nets (PN) with 2.14% and 4.28% for 64QAM and 3.38% and 8.06% for 128QAM, respectively, without much increase in time consumption. Furthermore, the trained FMFSL algorithm remains excellent in MFI and OSNR monitoring without retraining while employed in back-to-back transmission scenarios with smaller OSNR intervals and fiber transmission scenarios with different amounts of Kerr nonlinearity, demonstrating its high capabilities in generalization and robustness. FMFSL algorithm provides a potential solution for OPM in future dynamic optical networks as a novel machine learning tool.

MOINER: A Novel Multiomics Early Integration Framework for Biomedical Classification and Biomarker Discovery.

In the context of precision medicine, multiomics data integration provides a comprehensive understanding of underlying biological processes and is critical for disease diagnosis and biomarker discovery. One commonly used integration method is early integration through concatenation of multiple dimensionally reduced omics matrices due to its simplicity and ease of implementation. However, this approach is seriously limited by information loss and lack of latent feature interaction. Herein, a novel multiomics early integration framework (MOINER) based on information enhancement and image representation learning is thus presented to address the challenges. MOINER employs the self-attention mechanism to capture the intrinsic correlations of omics-features, which make it significantly outperform the existing state-of-the-art methods for multiomics data integration. Moreover, visualizing the attention embedding and identifying potential biomarkers offer interpretable insights into the prediction results. All source codes and model for MOINER are freely available https://github.com/idrblab/MOINER.

Comparison of Different Endovascular Treatments of Femoropopliteal Artery In-Stent Restenosis: A Systematic Review and Bayesian Network Meta-Analysis.

BACKGROUND: This Bayesian network meta-analysis (NMA) sought to evaluate the efficacy of different endovascular treatments for femoropopliteal artery in-stent restenosis (FP-ISR). METHODS: PubMed, Embase, Cochrane Central Register of Controlled Trials, and Web of science for clinical trials from database inception to March 31, 2023, with no language restrictions to retrieve randomized controlled trials or cohort studies evaluating the impact of any kind of endovascular treatments for FP-ISR. Pair-wise meta-analysis and Bayesian NMA were performed to pool the outcome estimates different endovascular treatments. The primary end points under consideration were primary patency rates at both 6-month and 12-month follow-up. RESULTS: A total of 15 studies with 1,424 patients were ultimately enrolled to be analyzed, 7 types of endovascular treatment were identified for comparison. In terms of primary patency and freedom from target lesion revascularization (TLR) at 6-month and12-month follow-up, the direct meta-analysis findings showed that drug-coated balloons (DCB) and covered stent (CS) are considerably superior to plain old balloon angioplasty (POBA), Excimer laser atherectomy (ELA) + DCB is significantly better than DCB. According to the meta-analysis based on Bayesian theory, during the 6-month and 12-months follow-up, we could not find significant difference between the different treatments in terms of the primary patency and the freedom from TLR, based on the surface values under the cumulative ranking curve (SUCRA), CS was considered the best treatment in terms of primary patency (6 months SUCRA = 85.2; 12 months SUCRA = 78.9) and freedom from TLR (6 months SUCRA = 84.9; 12 months SUCRA = 70.9); directional atherectomy + POBA may lead to higher survival rate at 12 months (SUCRA = 89.1) than others treatments; in addition, both ELA + POBA and ELA + DCB have higher limb salvage than POBA. CONCLUSIONS: The findings of this NMA suggest that CS showed positive encouraging results in primary patency and TLR in FP-ISR at 6 and 12 months. However, due to the potential influence of certain confounding factors, the long-term results necessitate validation through numerous randomized controlled trials.

Degradation of tetracycline under a wide pH range in a heterogeneous photo bio-electro-fenton system using FeMn-LDH/g-C3N4 cathode: Performance and mechanism.

The widespread use of antibiotics and the inefficiency of traditional degradation treatments pose threats to the environment and human health. Previous studies have reported the potential of bio-electro-Fenton (BEF) processes for antibiotic removal. However, some drawbacks, such as a strict pH range of 2-3 and iron sludge generation, limit their large-scale application. Thus, to overcome the narrow pH range of traditional BEF processes, a photo-BEF (PBEF) system was established using a novel FeMn-layered double hydroxide (LDH)/graphitic carbon nitride (g-C3N4) (FM/CN) composite cathode. The performance of the PBEF system was investigated by degrading tetracycline (TC) under low-power LED lamp irradiation. The results indicated that the pH range of the PBEF system could be expanded to 3-11 using an FM/CN cathode, which exhibited a TC removal efficiency of 63.0%-75.9%. The highest TC removal efficiency was achieved at pH 7. The efficient mineralization of TC by the PBEF system can be high, up to 67.6%. In addition, the TC removal mechanism was discussed in terms of reactive oxygen species, TC degradation intermediate analyses, and density functional theory (DFT) calculations. Strong oxidative hydroxyl radicals (·OH) were the dominant reactive oxidizing species in the PBEF system, followed by ·O2- and h+. Three pathways of TC degradation were proposed based on the analysis of intermediates, and the reactive sites attacked by electrophilic reagents were explored using DFT modeling. In addition, the overall toxicity of TC degradation intermediates effectively decreased in the PBEF system. This work offers deep insights into the TC removal mechanisms and performance of the PBEF system over a wide pH range of 3-11.

[Gene-gene/gene-environment interaction of transforming growth factor-ß signaling pathway and the risk of non-syndromic oral clefts].

OBJECTIVE: To explore the association between polymorphisms of transforming growth factor-ß (TGF-ß) signaling pathway and non-syndromic cleft lip with or without cleft palate (NSCL/P) among Asian populations, while considering gene-gene interaction and gene-environment interaction. METHODS: A total of 1 038 Asian NSCL/P case-parent trios were ascertained from an international consortium, which conducted a genome-wide association study using a case-parent trio design to investigate the genes affec-ting risk to NSCL/P. After stringent quality control measures, 343 single nucleotide polymorphism (SNP) spanning across 10 pivotal genes in the TGF-ß signaling pathway were selected from the original genome-wide association study(GWAS) dataset for further analysis. The transmission disequilibrium test (TDT) was used to test for SNP effects. The conditional Logistic regression models were used to test for gene-gene interaction and gene-environment interaction. Environmental factors collected for the study included smoking during pregnancy, passive smoking during pregnancy, alcohol intake during pregnancy, and vitamin use during pregnancy. Due to the low rates of exposure to smoking during pregnancy and alcohol consumption during pregnancy (<3%), only the interaction between maternal smoking during pregnancy and multivitamin supplementation during pregnancy was analyzed. The threshold for statistical significance was rigorously set at P =1.46×10-4, applying Bonferroni correction to account for multiple testing. RESULTS: A total of 23 SNPs in 4 genes yielded nominal association with NSCL/P (P<0.05), but none of these associations was statistically significant after Bonferroni' s multiple test correction. However, there were 6 pairs of SNPs rs4939874 (SMAD2) and rs1864615 (TGFBR2), rs2796813 (TGFB2) and rs2132298 (TGFBR2), rs4147358 (SMAD3) and rs1346907 (TGFBR2), rs4939874 (SMAD2) and rs1019855 (TGFBR2), rs4939874 (SMAD2) and rs12490466 (TGFBR2), rs2009112 (TGFB2) and rs4075748 (TGFBR2) showed statistically significant SNP-SNP interaction (P<1.46×10-4). In contrast, the analysis of gene-environment interactions did not yield any significant results after being corrected by multiple testing. CONCLUSION: The comprehensive evaluation of SNP associations and interactions within the TGF-ß signaling pathway did not yield any direct associations with NSCL/P risk in Asian populations. However, the significant gene-gene interactions identified suggest that the genetic architecture influencing NSCL/P risk may involve interactions between genes within the TGF-ß signaling pathway. These findings underscore the necessity for further investigations to unravel these results and further explore the underlying biological mechanisms.

[A ssociations of short-term ambient particulate matter exposure and MTNR1B gene with triglyceride-glucose index: A family-based study].

OBJECTIVE: To explore the effects of short-term particulate matter (PM) exposure and the melatonin receptor 1B (MTNR1B) gene on triglyceride-glucose (TyG) index utilizing data from Fang-shan Family-based Ischemic Stroke Study in China (FISSIC). METHODS: Probands and their relatives from 9 rural areas in Fangshan District, Beijing, were included in the study. PM data were obtained from fixed monitoring stations of the National Air Pollution Monitoring System. TyG index was calculated by fasting triglyceride and glucose concentrations. The associations of short-term PM exposure and rs10830963 polymorphism of the MTNR1B gene with the TyG index were assessed using mixed linear models, in which covariates such as age, sex, and lifestyles were adjusted for. Gene-environment inter-action analysis was furtherly performed using the maximum likelihood methods to explore the potential effect modifier role of rs10830963 polymorphism in the association of PM with TyG index. RESULTS: A total of 4 395 participants from 2 084 families were included in the study, and the mean age of the study participants was (58.98±8.68) years, with 53. 90% females. The results of association analyses showed that for every 10 µg/m3 increase in PM2.5 concentration, TyG index increased by 0.017 (95%CI: 0.007-0.027), while for per 10 µg/m3 increment in PM10, TyG index increased by 0.010 (95%CI: 0.003-0.017). And the associations all had lagged effects. In addition, there was a positive association between the rs10830963 polymorphism and the TyG index. For per increase in risk allele G, TyG index was elevated by 0.040 (95%CI: 0.004-0.076). The TyG index was 0.079 (95%CI: 0.005-0.152) higher in carriers of the GG genotype compared with carriers of the CC genotype. The interaction of rs10830963 polymorphism with PM exposure had not been found to be statistically significant in the present study. CONCLUSION: Short-term exposure to PM2.5 and PM10 were associated with higher TyG index. The G allele of rs10830963 polymorphism in the MTNR1B gene was associated with the elevated TyG index.

Optical mapping of cardiac electromechanics in beating in vivo hearts.

Optical mapping has been widely used in the study of cardiac electrophysiology in motion-arrested, ex vivo heart preparations. Recent developments in motion artifact mitigation techniques have made it possible to optically map beating ex vivo hearts, enabling the study of cardiac electromechanics using optical mapping. However, the ex vivo setting imposes limitations on optical mapping such as altered metabolic states, oversimplified mechanical loads, and the absence of neurohormonal regulation. In this study, we demonstrate optical electromechanical mapping in an in vivo heart preparation. Swine hearts were exposed via median sternotomy. Voltage-sensitive dye, either di-4-ANEQ(F)PTEA or di-5-ANEQ(F)PTEA, was injected into the left anterior descending artery. Fluorescence was excited by alternating green and amber light for excitation ratiometry. Cardiac motion during sinus and paced rhythm was tracked using a marker-based method. Motion tracking and excitation ratiometry successfully corrected most motion artifact in the membrane potential signal. Marker-based motion tracking also allowed simultaneous measurement of epicardial deformation. Reconstructed membrane potential and mechanical deformation measurements were validated using monophasic action potentials and sonomicrometry, respectively. Di-5-ANEQ(F)PTEA produced longer working time and higher signal/noise ratio than di-4-ANEQ(F)PTEA. In addition, we demonstrate potential applications of the new optical mapping system including electromechanical mapping during vagal nerve stimulation, fibrillation/defibrillation. and acute regional ischemia. In conclusion, although some technical limitations remain, optical mapping experiments that simultaneously image electrical and mechanical function can be conducted in beating, in vivo hearts.

BPIFB1 promotes metastasis of hormone receptor-positive breast cancer via inducing macrophage M2-like polarization.

Metastasis is an important factor affecting the prognosis of hormone receptor-positive breast cancer (BC). However, the molecular basis for migration and invasion of tumor cells remains poorly understood. Here, we identify that bactericidal/permeability-increasing-fold-containing family B member 1 (BPIFB1), which plays an important role in innate immunity, is significantly elevated in breast cancer and associated with lymph node metastasis. High expression of BPIFB1 and its coding mRNA are significantly associated with poor prognosis of hormone receptor-positive BC. Using enrichment analysis and constructing immune infiltration evaluation, we predict the potential ability of BPIFB1 to promote macrophage M2 polarization. Finally, we demonstrate that BPIFB1 promotes the metastasis of hormone receptor-positive BC by stimulating the M2-like polarization of macrophages via the establishment of BC tumor cells/THP1 co-culture system, qPCR, Transwell assay, and animal experiments. To our knowledge, this is the first report on the role of BPIFB1 as a tumor promoter by activating the macrophage M2 polarization in hormone receptor-positive breast carcinoma. Together, these results provide novel insights into the mechanism of BPIFB1 in BC.

Real-World Emission Characteristics of Full-Volatility Organics Originating from Nonroad Agricultural Machinery during Agricultural Activities.

Nonroad agricultural machinery (NRAM) emissions constitute a significant source of air pollution in China. Full-volatility organics originating from 19 machines under 6 agricultural activities were measured synchronously. The diesel-based emission factors (EFs) for full-volatility organics were 4.71 ± 2.78 g/kg fuel (average ± standard deviation), including 91.58 ± 8.42% volatile organic compounds (VOCs), 7.94 ± 8.16% intermediate-volatility organic compounds (IVOCs), 0.28 ± 0.20% semivolatile organic compounds (SVOCs), and 0.20 ± 0.16% low-volatility organic compounds (LVOCs). Full-volatility organic EFs were significantly reduced by stricter emission standards and were the highest under pesticide spraying activity. Our results also demonstrated that combustion efficiency was a potential factor influencing full-volatility organic emissions. Gas-particle partitioning in full-volatility organics could be affected by multiple factors. Furthermore, the estimated secondary organic aerosol formation potential based on measured full-volatility organics was 143.79 ± 216.80 mg/kg fuel and could be primarily attributed to higher-volatility-interval IVOCs (bin12-bin16 contributed 52.81 ± 11.58%). Finally, the estimated emissions of full-volatility organics from NRAM in China (2021) were 94.23 Gg. This study provides first-hand data on full-volatility organic EFs originating from NRAM to facilitate the improvement of emission inventories and atmospheric chemistry models.

Alexithymia and related factors among patients with epilepsy.

OBJECTIVE: Alexithymia is a psychiatric symptom characterized by difficulties in emotion recognition, expression, and regulation. The purpose of our study was to investigate the prevalence of alexithymia among patients with epilepsy (PWE) and related factors. METHODS: By the means of a cross-sectional study, we consecutively recruited PWE who visited the First Hospital of Jilin University. The demographical information and clinical data were collected. Toronto Alexithymia Scale-20 (TAS-20), Emotion Regulation Questionnaire (ERQ), Kilifi Stigma Scale for Epilepsy (KSSE), Neurological Disorders Depression Inventory for Epilepsy (NDDI-E), Generalized Anxiety Disorder-7 (GAD-7), and Nurses' Global Assessment of Suicide Risk scale (NGASR) scales were applied to assess alexithymia, emotion regulation strategies, and the presence of comorbid psychiatric symptoms. RESULTS: A total of 203 PWE were included. The differences in education, monthly per capita income of the family, and the number of antiepileptic drugs were statistically significant among these three groups with alexithymia, possible alexithymia, and non-alexithymia (p < 0.05). Toronto Alexithymia Scale-20 scores were significantly and positively correlated with BMI (rho = 0.143, p = 0.042). Expression suppression, stigma, and generalized anxiety were independent risk factors for alexithymia (R2 = 0.471, F = 19.075, p < 0.001). CONCLUSIONS: A high prevalence of alexithymia (18.7%) was found in PWE. Alexithymia is primarily influenced by the emotional regulation strategies, anxiety, and stigma among PWE. It tends to be a mood symptom or personality trait rather than a direct result of epilepsy.

Identifying the preoperative factors predicting the surgical difficulty of robotic distal pancreatectomy.

BACKGROUND: Few studies have evaluated the preoperative factors predicting the surgical difficulty of robotic distal pancreatectomy (RDP). This study aims to explore such factors and provide guidance on the selection of suitable patients to aid surgeons lacking extensive experience in RDP. METHODS: A retrospective study was conducted on consecutive patients who underwent RDP to identify preoperative factors predicting surgical difficulty. High surgical difficulty was defined by both operation time and intraoperative estimated blood loss exceeding their median, or by conversion to laparotomy. RESULTS: A total of 161 patients were ultimately enrolled, including 51 patients with high levels of surgical difficulty. Multivariate analysis revealed that male sex [OR (95% CI): 4.07 (1.77,9.40), p = 0.001], body mass index (BMI) ≥ 25 kg/m2 OR (95% CI): 2.27 (1.03,5.00), p = 0.042], tumors located at the neck of the pancreas [OR (95% CI): 4.15 (1.49,11.56), p = 0.006] and splenic artery type B [OR (95% CI): 3.28 (1.09,9.91), p = 0.035] were independent risk factors for surgical difficulty. Regarding postoperative complications, high surgical difficulty was associated with the risk of overall complications and pancreatic fistula (grade B/C) (49.0% vs. 22.7%, p < 0.001; 39.2% vs. 19.1%, p = 0.006). CONCLUSION: Male sex, body mass index ≥ 25 kg/m2, tumor located at the neck of the pancreas and splenic artery type B are associated with a high RDP difficulty level. These factors can be used preoperatively to assess the difficulty level of surgery, to help surgeons choose patients suitable for them and ensure surgical safety.