MicroRNA-122 protects against interferon-α-induced hepatic inflammatory response via the Janus kinase-signal transducer and activator of transcription pathway.

Significant overlap in the epidemiology and coinfection of chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) has been identified, which accelerates the development of severe liver cirrhosis and hepatocellular carcinoma worldwide. Interferon-α (IFN-α), a cytokine with antiviral properties, exerts profound physiological effects on innate immunity by regulating interferon-stimulated genes (ISGs) within cells. However, the underlying mechanism of IFN-α in hepatic inflammation remains to be fully elucidated. Here, we utilized LO2 cells treated with the recombinant IFN-α protein and conducted microRNA (miR) sequencing. MiR-122-3p and miR-122-5p_R+1 were the most enriched miRNAs involved in the pathogenesis of IFN-α-induced inflammatory responses and were significantly downregulated by IFN-α treatment. Furthermore, we identified interferon induced protein with tetratricopeptide repeats 1 (IFIT1) as a potential target gene of miR-122. IFN-α markedly increased the expression of proinflammatory cytokines and fibrogenic genes but decreased the mRNA expression of ISGs. Additionally, IFN-α significantly activated the NF-κB p-p65, MAPK p-p38, and Jak/STAT pathways to trigger inflammation. Importantly, supplementation with a miR-122 mimic significantly alleviated IFN-α-induced inflammation and induced IFIT1 expression in LO2 cells. Conversely, the suppression of miR-122 markedly exacerbated the inflammatory response triggered by IFN-α. Furthermore, silencing IFIT1 via an siRNA elicited an inflammatory response, whereas IFIT1 overexpression ameliorated hepatic inflammation and fibrosis in a manner comparable to that induced by IFN-α treatment. Taken together, our findings suggest that miR-122 and its target, IFIT1, reciprocally regulate the inflammatory response associated with IFN through the Jak/STAT pathway.

The effects of Pseudomonas strains isolated from Achnatherum inebrians on plant growth: A genomic perspective.

Achnatherum inebrians is a perennial grass widely distributed in northwest China. Nearly all wild A. inebrians plants are infected by Epichloë endophytes. In this study, bacteria from the phyllosphere were isolated from leaves of both endophyte-free and endophyte-infected A. inebrians and sequenced for identification. Pseudomonas, comprising 48.12% of the culturable bacterial communities, was the most dominant bacterial genus. Thirty-four strains from 12 Pseudomonas species were used to inoculate A. inebrians seeds and plants. Results indicated that Epichloë significantly increased the diversity and richness index of the phyllosphere. Pseudomonas Sp1, Sp3, Sp5 and Sp7 had a significantly positive effect on plant growth and photosynthesis, whereas Sp10, Sp11 and Sp12 had a significantly negative effect. Whole-genome and pan-genome analysis suggested that the variability in the effects of Pseudomonas on A. inebrians was related to differences in genome composition and genomic islands.

In silico and in vivo verification of the mechanism of formononetin in treating hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a significant global medical challenge. Formononetin, an isoflavone derived from Astragalus membranaceus, has been shown to have various regulatory effects on HCC. However, the exact molecular mechanism by which formononetin acts against HCC is still unclear. PURPOSE: To elucidate the molecular mechanism of formononetin in treating HCC. METHODS: The potential targets of formononetin were retrieved from Swisstargets and SEA databases, while targets associated with HCC were sourced from GeneCards, NCBI and DisGeNET databases. The overlapping targets were visualized using protein-protein interaction (PPI) network analysis via String database, and subsequently subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking was employed to confirm the interaction between formononetin and key targets. Ultimately, the effectiveness of formononetin on HCC and the signalling pathway with the highest enrichment were confirmed in the HCC tumour-bearing mice. Histopathological changes in tumour tissues were observed using haematoxylin and eosin (HE) staining, while apoptosis of tumour cells in mice was assessed through TdT-mediated dUTP nick end labelling (TUNEL) and immunofluorescence staining. The most enriched signalling pathway was verified using Western blotting and immunohistochemical (IHC) staining. RESULTS: One hundred and ninety-three potential targets related to formononetin, 6980 targets associated with HCC and 156 overlapping targets were obtained from the online public databases. Molecular docking studies demonstrated formononetin's robust interaction with core targets. KEGG enrichment analysis identified 111 signalling pathways, including PI3K/AKT and apoptosis signalling pathways. In vivo experiments demonstrated that formononetin significantly promoted apoptosis of tumour cell in mice, as confirmed by HE, TUNEL and immunofluorescence staining (p < .05). Formononetin was found to decrease the phosphorylation levels of PI3K and AKT, reduce the expression of Bcl-2, and increase the expression of cleaved-Caspase-3 and Bax (p < .05). CONCLUSIONS: Formononetin demonstrates dose-dependent regulatory effects on multiple targets, biological processes and signalling pathways in HCC. The compound can mitigate HCC by enhancing PI3K/AKT-mediated apoptosis of tumour cells.

Research progress on cottonseed meal as a protein source in pig nutrition: An updated review.

At a global level, the supply of protein sources is insufficient to support the current magnitude of pig production. Moreover, given the exorbitant expense of conventional protein feed options like soybean meal and fish meal, it becomes imperative to promptly explore alternative sources of protein feed for the sustainable advancement of the pig industry. Cottonseed meal, a by-product from the extraction of cottonseed oil, exhibits significant potential as a protein source for pig feed owing to its high protein content, high yield, low cost, well-balanced amino acid composition, and sufficient accessibility. However, cottonseed meal possesses several anti-nutritional factors, especially gossypol, which adversely affect growth and reproductive performance, resulting in the limited utilization of cottonseed meal in pig feed. To maximize the benefits of cottonseed meal and promote its application in pig production, it is imperative to acquire comprehensive knowledge regarding its nutritional value and current utilization. In this review, we initially presented a summary of the nutritional values of cottonseed meal, primary anti-nutritional factors, and effective approaches for improving its utilization as a protein source feed. Subsequently, we comprehensively summarized the latest research progress of cottonseed meal application in pig nutrition over the past decade. The outcome of this review serves as a theoretical foundation and practical guidance for the research and application of cottonseed meal in pig nutrition and promotes the reduction of soybean meal utilization in the pig industry.

PAC1 constrains type II inflammation through promotion of CGRP signaling in ILC2s.

Dysfunction of group II innate lymphoid cells (ILC2s) plays an important role in the development of type II inflammation-related diseases such as asthma and pulmonary fibrosis. Notably, neural signals are increasingly recognized as pivotal regulators of ILC2s. However, how ILC2s intrinsically modulate their responsiveness to these neural signals is still largely unknown. Here, using single-cell RNA sequencing, we found that the immune regulatory molecule PAC1 (phosphatase of activated cells 1) selectively promotes the signaling of neuropeptide CGRP (calcitonin gene-related peptide) in ILC2s through a cell-intrinsic manner. Genetic ablation of PAC1 in ILC2s substantially impaired the inhibitory effect of CGRP on proliferation and IL-13 secretion. PAC1 deficiency significantly exacerbated allergic airway inflammation induced by Alternaria alternata or papain in mice. Moreover, in human circulating ILC2s, the expression level of PAC1 was also significantly negatively correlated with the cell amount and the expression level of IL13. Mechanistically, PAC1 was necessary for ensuring the expression of CGRP-response genes by influencing chromatin accessibility. In summary, our study demonstrated that PAC1 is an important regulator of ILC2 responses and we proposed that PAC1 is a potential target for therapeutic interventions of type II inflammation-related diseases.

The developmental and dynamic relationship between psychopathology and psychotic-like experiences trajectories in children and adolescents.

BACKGROUND: The previous cross-sectional and prospective studies have reported that psychopathology was associated with the occurrence of psychotic-like experiences (PLEs). However, few of these studies have examined this longitudinal association considering the different developmental trajectories of PLEs, as well as the growth or changes of psychopathology over time. METHODS: Four waves PLEs and psychopathology assessments from Adolescent Brain Cognitive Development (ABCD) study were used. The latent class growth modeling (LCGM) and latent growth curve modeling (LGCM) was used to assess latent PLEs class (group) and time-varying psychopathology, respectively. Lastly, the multinomial logistic regression model was used to examined the dynamic and developmental relationship between intercept/slope in psychopathology and different PLEs trajectories. RESULTS: Three PLEs trajectory classes were confirmed: low decreasing PLEs (84.7 %), persistent PLEs (7.01 %) and high decreasing PLEs trajectories (8.29 %). We also found that the intercept of anxious/depressed problems and total problems scales and the slope of social problems were associated with the persistent PLEs trajectory compared with the low decreasing PLEs trajectories, indicating both the early onset and the growth of psychopathology over time are needed to be clinical attention. LIMITATIONS: The CBCL as the sole outcome measure for psychopathology and a widely acknowledged definition for PLEs is lacking. We lacked the mechanisms underlying the current results. CONCLUSION: These longitudinal and dynamic results suggest that future intervention studies aimed at preventing the transition from persistent PLEs to psychotic disorders can focus on both the early onset and the growth of psychopathology over time.

Inactivation of JNK signalling results in polarity loss and cell senescence of Sertoli cell.

As major somatic cells in the testis, Sertoli cell development is precisely regulated by numerous factors, and aberrant development of these cells is associated with male reproductive diseases. JNK signalling is evolutionarily conserved and involved in multiple critical biological processes. Here, we found that the double knockout of Jnk1 and Jnk2 resulted in aberrant localisation of Sertoli cells at early developmental stages, with most Sertoli cells being lost at later stages. Further studies revealed that the inactivation of JNK signalling caused polarity loss in Sertoli cells. In vitro-cultured Jnk1/2-DKO Sertoli cells exhibited a senescence-associated phenotype. Mechanistic studies demonstrate that JNK signalling is likely involved in establishing Sertoli cell polarity by regulating the expression of TGF-ß2, mediated by c-Jun. The senescence of Sertoli cells in JNKs-deficient mice is caused by aberrant proteolysis of P27KIP1, mediated by c-Myc. This study demonstrates the role of JNK signalling in Sertoli cell development and functional maintenance, which may also represent an aetiology of male infertility in humans.

Pure rotational and rovibrational spectroscopy of cyclopropylamine in the far-infrared region: -NH2 torsion.

The pure rotational and rovibrational spectra of the ν27 -NH2 torsion of cyclopropylamine (CPA) in the far-infrared region were measured with a high-resolution Fourier transform infrared coupled to a synchrotron. The complex spectra reflect the presence of both trans and gauche conformers. Analysis of the pure rotational spectra (34-64 cm-1) yielded accurate rotational and centrifugal distortion constants of the ground and first two torsional excited states of trans-CPA. The fundamental, hot bands and weak overtones were identified and assigned in the 200-550 cm-1 range. Global analysis of over 19 000 transitions provides accurate energy levels of the torsional polyads up to vT = 3. The torsional levels and their rotational constants were in agreement with the theoretical results from quasiadiabatic channel reaction path Hamiltonian (RPH) calculations, emphasizing the need for molecular-specific theoretical treatments for large amplitude motions. Tunneling components of the torsional fundamental of gauche-CPA were assigned based on the RPH results and symmetry considerations, differing from previous experimental and theoretical work. This comprehensive spectroscopic characterization of CPA is crucial for its potential detection in the interstellar medium as a precursor to complex prebiotic molecules, providing essential data for future astronomical searches and advancing our understanding of nitrogen-containing organic molecules in space.

School Bullying, Bystander Behavior, and Mental Health among Adolescents: The Mediating Roles of Self-Efficacy and Coping Styles.

While numerous studies have revealed the impact of different bullying behaviors, such as victimization and perpetration, on the psychological development of adolescents, the exploration of the correlates of positive/negative bystander behaviors and their potential underlying mechanisms remains scarce in China. The present study aims to compare the relationships between mental health and positive versus negative bystander behavior and to clarify whether self-efficacy and coping styles mediate the relationships between mental health and bullying dynamics. The current study was conducted on 11,734 students from 18 secondary schools in Suzhou, China (Meanage = 15.00, SDage = 1.47; 53.8% boys). The information on bullying victimization, perpetration, positive/negative bystander behaviors, as well as self-efficacy, coping styles and mental health variables (including depression, anxiety, sleep disturbance, suicide risk), were collected. Negative bystander behavior was positively associated with mental health problems, while positive bystander behavior was negatively associated with these factors. Also, further analysis showed that coping styles and self-efficacy mediated the relationship between different bullying behaviors and mental health outcomes. The results highlighted the comparison of the correlates of positive and negative bystander behaviors, which were comparably crucial to those of victims and perpetrators for prevention and intervention efforts. Promoting adaptive coping styles and self-efficacy to buffer the deleterious psychological consequences of bullying behavior in adolescents was also important.

Roles of extracellular vesicles derived from healthy and obese adipose tissue in inter-organ crosstalk and potential clinical implication.

Extracellular vesicles (EVs) are nanovesicles containing bioactive molecules including proteins, nucleic acids and lipids that mediate intercellular and inter-organ communications, holding promise as potential therapeutics for multiple diseases. Adipose tissue (AT) serves as a dynamically distributed energy storage organ throughout the body, whose accumulation leads to obesity, a condition characterized by infiltration with abundant immune cells. Emerging evidence has illustrated that EVs secreted by AT are the novel class of adipokines that regulate the homeostasis between AT and peripheral organs. However, most of the studies focused on the investigations of EVs derived from adipocytes or adipose-derived stem cells (ADSCs), the summarization of functions in cellular and inter-organ crosstalk of EVs directly derived from adipose tissue (AT-EVs) are still limited. Here, we provide a systemic summary on the key components and functions of EVs derived from healthy adipose tissue, showing their significance on the tissue recovery and metabolic homeostasis regulation. Also, we discuss the harmful influences of EVs derived from obese adipose tissue on the distal organs. Furthermore, we elucidate the potential applications and constraints of EVs from healthy patients lipoaspirates as therapeutic agents, highlighting the potential of AT-EVs as a valuable biological material with broad prospects for future clinical use.

Comparison of Lung Tissue-Derived Extracellular Vesicles Using Multiple Dissociation Methods for Profiling Protein Biomarkers.

Extracellular vesicles (EVs) operate as chemical messengers that facilitate intercellular communication. Emerging evidence has demonstrated that lung tissue-derived EVs play pivotal roles in pulmonary physiological processes and have potential as biomarkers and therapeutics for lung diseases. Multiple methods have been proposed for the isolation of lung tissue-derived EVs. However, the effects of different tissue pre-treatments on lung EV isolation and subsequent disease biomarker discovery have not yet been comprehensively investigated. In this study, we compared the physical characteristics, recovery yields, and protein compositions of EVs isolated from lung tissues using three methods based on different tissue dissociation principles. Methodologically, the beneficial roles of blood perfusion and gentle meshing were emphasized based on their impact on EV yield and purity. These results demonstrate that different methods enrich distinct subpopulations of EVs that exhibit significant differences in their protein cargo and surface properties. These disparities directly affect the diagnostic detection of marker proteins related to lung diseases, including lung tumors, asthma, and pulmonary fibrosis. Collectively, these findings highlight the variations in EV characteristics resulting from the applied approaches and offer compelling suggestions for guiding researchers in selecting a suitable isolation method based on downstream functional studies and clinical applications.

Cross-View Representation Learning-Based Deep Multiview Clustering With Adaptive Graph Constraint.

Deep multiview clustering provides an efficient way to analyze the data consisting of multiple modalities and features. Recently, the autoencoder (AE)-based deep multiview clustering algorithms have attracted intensive attention by virtue of their rewarding capabilities of extracting inherent features. Nevertheless, most existing methods are still confronted by several problems. First, the multiview data usually contains abundant cross-view information, thus parallel performing an individual AE for each view and directly combining the extracted latent together can hardly construct an informative view-consensus feature space for clustering. Second, the intrinsic local structures of multiview data are complicated, hence simply embedding a preset graph constraint into multiview clustering models cannot guarantee expected performance. Third, current methods commonly utilize the Kullback-Leibler (KL) divergence as clustering loss and accordingly may yield appalling clusters that lack discriminate characters. To solve these issues, in this article we propose two new AE-based deep multiview clustering algorithms named AE-based deep multiview clustering model incorporating graph embedding (AG-DMC) and deep discriminative multiview clustering algorithm with adaptive graph constraint (ADG-DMC). In AG-DMC, a novel cross-view representation learning model is established delicately by performing decoding processes based on the cascaded view-specific latent to learn sound view-consensus features for inspiring clustering results. In addition, an entropy-regularized adaptive graph constraint is imposed on the obtained soft assignments of data to precisely preserve potential local structures. Furthermore, in the improved model ADG-DMC, the adversarial learning mechanism is adopted as clustering loss to strengthen the discrimination of different clusters for better performance. In the comprehensive experiments carried out on eight real-world datasets, the proposed algorithms have achieved superior performance in the comparison with other advanced multiview clustering algorithms.

Metabolic syndrome predictive modelling in Bangladesh applying machine learning approach.

Metabolic syndrome (MetS) is a cluster of interconnected metabolic risk factors, including abdominal obesity, high blood pressure, and elevated fasting blood glucose levels, that result in an increased risk of heart disease and stroke. In this research, we aim to identify the risk factors that have an impact on MetS in the Bangladeshi population. Subsequently, we intend to construct predictive machine learning (ML) models and ultimately, assess the accuracy and reliability of these models. In this particular study, we utilized the ATP III criteria as the basis for evaluating various health parameters from a dataset comprising 8185 participants in Bangladesh. After employing multiple ML algorithms, we identified that 27.8% of the population exhibited a prevalence of MetS. The prevalence of MetS was higher among females, accounting for 58.3% of the cases, compared to males with a prevalence of 41.7%. Initially, we identified the crucial variables using Chi-Square and Random Forest techniques. Subsequently, the obtained optimal variables are employed to train various models including Decision Trees, Random Forests, Support Vector Machines, Extreme Gradient Boosting, K-nearest neighbors, and Logistic Regression. Particularly we employed the ATP III criteria, which utilizes the Waist-to-Height Ratio (WHtR) as an anthropometric index for diagnosing abdominal obesity. Our analysis indicated that Age, SBP, WHtR, FBG, WC, DBP, marital status, HC, TGs, and smoking emerged as the most significant factors when using Chi-Square and Random Forest analyses. However, further investigation is necessary to evaluate its precision as a classification tool and to improve the accuracy of all classifiers for MetS prediction.

Regulatory mechanism of strigolactone in tall fescue to low-light stress.

Strigolactone (SL), a plant hormone derived from carotenoids, has been recognized for its pivotal role in regulating plant growth. Nevertheless, the influence of SL on tall fescue (Festuca arundinacea) under low-light conditions remains unclear. This study aimed to investigate the impact of SL on various aspects of tall fescue, including its morphological characteristics, photosynthesis, levels of antioxidant and concentrations of SL, under low light intensity (LI). The findings showed that GR24, an artificial analog of SL, positively influenced several parameters of tall fescue under LI. In particular, it enhanced the morphological features such as plant height, leaf width, and biomass, while reducing the number of tillers. Furthermore, it improved the efficiency of photosynthetic by enhancing chlorophyll fluorescence and the gas exchange parameters, mitigating cell damage and improving the contents of antioxidants by increasing the levels of antioxidant enzymes and non-enzymatic antioxidant compounds. Moreover, treatment with SL led to elevated concentrations of this hormone and the levels of gene expression in related pathways. Owing to the immaturity of the genetic transformation system in tall fescue, partial validation through transgenic and mutant materials was obtained using Arabidopsis (Arabidopsis thaliana). These findings demonstrate that SL alleviates the physiological indicators of tall fescue under LI stress and enhances its tolerance to shade. Additionally, it suggests that SL may regulate the shade tolerance of tall fescue through the involvement of FaD14.

The Effects of Daily-Living Risks on Breast Cancer-Related Lymphedema.

BACKGROUND: Conventional advice to reduce the risk of breast cancer-related lymphedema (BCLE) suggests avoidance of daily-living risks, and limited research has investigated these risks. OBJECTIVE: This study aimed to examine the occurrence, patterns, and effects of daily-living risks on BCLE. METHODS: A cross-sectional design was used to collect data from 567 patients at a metropolitan cancer center in the United States. The Lymphedema Risk-Reduction Behavior Checklist was used to assess the occurrence of 11 daily-living risks. Descriptive, regression, and factor analyses were performed. RESULTS: Significant odds of BCLE were associated with infection (odds ratio [OR] 2.58, 95% confidence interval [CI] 1.95-3.42), cuts/scratches (OR 2.65, 95% CI 1.97-3.56), sunburn (OR 1.89, 95% CI 1.39-3.56), oil splash or steam burns (OR 2.08, 95% CI 1.53-3.83), and insect bites (OR 1.59, 95% CI 1.18-2.13). The daily-living risks were clustered into factors related to skin trauma and carrying objects. Skin trauma risk was significantly associated with BCLE (B = 0.539, z = 3.926, OR 1.714, 95% CI 1.312-2.250; p < 0.001). Having three, four, or five skin trauma risks significantly increased the odds of BCLE to 4.31, 5.14, and 6.94 times, respectively. The risk of carrying objects had no significant or incremental effects on BCLE. CONCLUSION: Complete avoidance of daily-living risks is challenging given 52.73% of patients incurred more than five daily-living risks. Our study findings underscore the importance of 'what to do' strategies to minimize infection and skin trauma.

Bone age assessment by multi-granularity and multi-attention feature encoding.

Background: Bone age assessment (BAA) is crucial for the diagnosis of growth disorders and the optimization of treatments. However, the random error caused by different observers' experiences and the low consistency of repeated assessments harms the quality of such assessments. Thus, automated assessment methods are needed. Methods: Previous research has sought to design localization modules in a strongly or weakly supervised fashion to aggregate part regions to better recognize subtle differences. Conversely, we sought to efficiently deliver information between multi-granularity regions for fine-grained feature learning and to directly model long-distance relationships for global understanding. The proposed method has been named the "Multi-Granularity and Multi-Attention Net (2M-Net)". Specifically, we first applied the jigsaw method to generate related tasks emphasizing regions with different granularities, and we then trained the model on these tasks using a hierarchical sharing mechanism. In effect, the training signals from the extra tasks created as an inductive bias, enabling 2M-Net to discover task relatedness without the need for annotations. Next, the self-attention mechanism acted as a plug-and-play module to effectively enhance the feature representation capabilities. Finally, multi-scale features were applied for prediction. Results: A public data set of 14,236 hand radiographs, provided by the Radiological Society of North America (RSNA), was used to develop and validate 2M-Net. In the public benchmark testing, the mean absolute error (MAE) between the bone age estimates of the model and of the reviewer was 3.98 months (3.89 months for males and 4.07 months for females). Conclusions: By using the jigsaw method to construct a multi-task learning strategy and inserting the self-attention module for efficient global modeling, we established 2M-Net, which is comparable to the previous best method in terms of performance.

Efficacy and safety of second-line therapies for advanced hepatocellular carcinoma: a network meta-analysis of randomized controlled trials.

BACKGROUND: The selection of appropriate second-line therapy for liver cancer after first-line treatment failure poses a significant clinical challenge due to the lack of direct comparative studies and standard treatment protocols. A network meta-analysis (NMA) provides a robust method to systematically evaluate the clinical outcomes and adverse effects of various second-line treatments for hepatocellular carcinoma (HCC). METHODS: We systematically searched PubMed, Embase, Web of Science and the Cochrane Library to identify phase III/IV randomized controlled trials (RCTs) published up to March 11, 2024. The outcomes extracted were median overall survival (OS), median progression-free survival (PFS), time to disease progression (TTP), disease control rate (DCR), objective response rate (ORR), and adverse reactions. This study was registered in the Prospective Register of Systematic Reviews (CRD42023427843) to ensure transparency, novelty, and reliability. RESULTS: We included 16 RCTs involving 7,005 patients and 10 second-line treatments. For advanced HCC patients, regorafenib (HR = 0.62, 95%CI: 0.53-0.73) and cabozantinib (HR = 0.74, 95%CI: 0.63-0.85) provided the best OS benefits compared to placebo. Cabozantinib (HR = 0.42, 95%CI: 0.32-0.55) and regorafenib (HR = 0.46, 95% CI: 0.31-0.68) also offered the most significant PFS benefits. For TTP, apatinib (HR = 0.43, 95% CI: 0.33-0.57), ramucirumab (HR = 0.44, 95% CI: 0.34-0.57), and regorafenib (HR = 0.44, 95% CI: 0.38-0.51) showed significant benefits over placebo. Regarding ORR, ramucirumab (OR = 9.90, 95% CI: 3.40-42.98) and S-1 (OR = 8.68, 95% CI: 1.4-154.68) showed the most significant increases over placebo. Apatinib (OR = 3.88, 95% CI: 2.48-6.10) and cabozantinib (OR = 3.53, 95% CI: 2.54-4.90) provided the best DCR benefits compared to placebo. Tivantinib showed the most significant advantages in terms of three different safety outcome measures. CONCLUSIONS: Our findings suggest that, in terms of overall efficacy and safety, regorafenib and cabozantinib are the optimal second-line treatment options for patients with advanced HCC.

TF-EPI: an interpretable enhancer-promoter interaction detection method based on Transformer.

The detection of enhancer-promoter interactions (EPIs) is crucial for understanding gene expression regulation, disease mechanisms, and more. In this study, we developed TF-EPI, a deep learning model based on Transformer designed to detect these interactions solely from DNA sequences. The performance of TF-EPI surpassed that of other state-of-the-art methods on multiple benchmark datasets. Importantly, by utilizing the attention mechanism of the Transformer, we identified distinct cell type-specific motifs and sequences in enhancers and promoters, which were validated against databases such as JASPAR and UniBind, highlighting the potential of our method in discovering new biological insights. Moreover, our analysis of the transcription factors (TFs) corresponding to these motifs and short sequence pairs revealed the heterogeneity and commonality of gene regulatory mechanisms and demonstrated the ability to identify TFs relevant to the source information of the cell line. Finally, the introduction of transfer learning can mitigate the challenges posed by cell type-specific gene regulation, yielding enhanced accuracy in cross-cell line EPI detection. Overall, our work unveils important sequence information for the investigation of enhancer-promoter pairs based on the attention mechanism of the Transformer, providing an important milestone in the investigation of cis-regulatory grammar.

Optimizing treatment sequence for inoperable locally advanced breast cancer: Long-term outcomes of surgery first versus neoadjuvant chemotherapy in a real-world setting.

Locally advanced breast cancer (LABC) is challenging with limited treatment options. This study investigates the feasibility and long-term outcomes of upfront surgery compared to neoadjuvant chemotherapy (NAC) in a real-world cohort. This retrospective study analyzed 243 inoperable LABC patients (excluding T3N1M0) that underwent upfront surgery (n = 187) or NAC (n = 56) in matched groups. Disease-free survival (DFS) and overall survival (OS) are primary outcomes. Secondary outcomes included NAC response rate and subgroup analyses based on age, tumor stage, and treatment response. Survival was estimated using Kaplan-Meier methods with log-rank tests for comparisons. Cox proportional hazards models were used for subgroup analyses. With a median follow-up of 60.9 months, no significant difference emerged in 5-year OS (upfront surgery: 89.6%, NAC: 81.9%, p = .12) or 5-year DFS rates (73.0% vs. 67.1%, p = .24). Subgroup analyses revealed upfront surgery offered significantly better OS for patients under 60 (HR = 0.32; 95% CI: 0.10-0.96; p = .0429) and stage IIIA disease (HR = 0.22; CI: 0.06-0.86; p = .03). Upfront surgery showed a trend towards improved OS for tumors under 5 cm (HR = 0.37; 95% CI: 0.13-1.03; p = .056). Patients with progressive disease (PD) or stable disease (SD) after NAC had significantly worse DFS (HR = 0.27; 95% CI: 0.09-0.79; p = .017) and OS (HR = 0.09; 95% CI: 0.02-0.48; p = .004) compared to responders. Upfront surgery may be viable for LABC patients, particularly younger patients, those with stage IIIA disease, or smaller tumors. NAC response can inform treatment decisions. These findings highlight the need for personalized LABC treatment considering patient characteristics and NAC response.