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The increasing popularity of sharing platforms is raising concerns about a lack of information on the demand side: the cost of serving specific buyers is typically unknown to sellers. To mitigate this concern, some platforms, such as Airbnb, have adopted the bilateral review system (BRS), allowing buyers and sellers to rate each other. This differs from the traditional unilateral review system (URS), which allows only buyers to rate sellers. In this study, we examine how these two review systems impact the operation of a peer-to-peer (P2P) sharing platform, where sellers with different qualities are matched with buyers with different serving costs. Our analysis reveals that under URS, even with perfect seller information, high-quality sellers can still be driven out of the market due to unknown information about the buyer and the "coproduction" nature of the serving cost. This differs from the adverse selection problem often observed in the used car market, for example, where sellers of high-quality products withdraw due to generally unknown product quality. Additionally, we highlight the critical role of the expected buyer cost: When this cost is high, BRS can benefit the platform by alleviating the adverse selection problem; however, when this cost is low, BRS becomes detrimental to the platform. Our analysis also shows that BRS helps buyers but can hurt sellers. However, BRS has the potential to generate a favorable outcome for all parties involved, resulting in a win-win-win situation benefiting the platform, buyers, and sellers. Our results not only shed light on review system design but also provide a plausible explanation for the widespread use of BRS by sharing platforms such as Airbnb, Fiverr, and Turo. [ABSTRACT FROM AUTHOR]

The infusion of emerging technologies (e.g., IoT-enabled algorithmic customer service systems [IACSs]) often brings disruptive changes to customer service. In particular, the agentic nature of these technologies challenges prominent service theories. Among these challenges, recent scholarly calls have pushed for more research on the infusion of emerging technologies into the service-profit chain (SPC) framework, advocating for the importance of extended knowledge to develop a techno-infused version of the SPC. Thus, from an interdisciplinary perspective, we draw upon role theory and propose a technoservice-profit chain (TSPC). Specifically, we contextualize the SPC in the technoservice context with different approaches, including decomposing context-specific constructs and theorizing IACS implementation as a contextual factor that moderates TSPC relationships. Using a sequential mixed methods design combining quantitative and qualitative approaches, we tested our research model by conducting multiwave surveys and follow-up interviews in a large business-to-business service firm with data from employees, supervisors, and customers before and after IACS implementation. This interdisciplinary study contributes to the information systems, service marketing, and management literatures by enriching the compositions of core SPC constructs, theorizing interactions between human agents and technology agents, and scrutinizing the impacts of technology agents on the linkages between internal employee management and external customer service. Our results further reveal the emerging issues of competing bosses (i.e., supervisors and IACSs), competing employees (i.e., employees and IACSs), and the unintended dehumanization effects of IACSs on supervisors and employees. [ABSTRACT FROM AUTHOR]

The usability of voice interaction is critical for consumers to have a satisfactory experience when interacting with voice-controlled smart products. However, voice interaction from the user's perspective is underresearched and there are no existing scales to measure voice-interaction usability. This study uses a mixed methods approach to explore the construct of voice-interaction usability and establish a scale that can be used for measuring it. We first developed voice-interaction usability dimensions based on user reviews by using a coding technique that stems from grounded theory and then set up a classification of voice-interaction usability with five dimensions and 13 subdimensions based on cooperative principle theory. After developing the multilevel dimensions, we collected and examined multiple rounds of survey data to develop and validate a voice-interaction usability scale. This study enhances cooperative principle theory by extending the four-principle framework, developing the subdimensions of the framework in the human-machine voice-interaction context, and operationalizing the dimension concepts by developing the associated scales. The voice-interaction usability scale not only contributes to research on users' behavior and experience with voice-controlled smart products but also provides insights to improve the design of voice-interaction functions. [ABSTRACT FROM AUTHOR]

The rapid proliferation of complex information systems has been met by an ever-increasing quantity of exploits that can cause irreparable cyber breaches. To mitigate these cyber threats, academia and industry have placed a significant focus on proactively identifying and labeling exploits developed by the international hacker community. However, prevailing approaches for labeling exploits in hacker forums do not leverage metadata from exploit darknet markets or public exploit repositories to enhance labeling performance. In this study, we adopted the computational design science paradigm to develop a novel information technology artifact, the deep transfer learning exploit labeler (DTL-EL). DTL-EL incorporates a pre-initialization design, multi-layer deep transfer learning (DTL), and a self-attention mechanism to automatically label exploits in hacker forums. We rigorously evaluated the proposed DTL-EL against state-of-the-art non-DTL benchmark methods based in classical machine learning and deep learning. Results suggest that the proposed DTL-EL significantly outperforms benchmark methods based on accuracy, precision, recall, and F1-score. Our proposed DTL-EL framework provides important practical implications for key stakeholders such as cybersecurity managers, analysts, and educators. [ABSTRACT FROM AUTHOR]

Fructose is associated with colorectal cancer tumorigenesis and metastasis through ketohexokinase-mediated metabolism in the colorectal epithelium, yet its role in the tumor immune microenvironment remains largely unknown. Here, we show that a modest amount of fructose, without affecting obesity and associated complications, promotes colorectal cancer tumorigenesis and growth by suppressing the polarization of M1-like macrophages. Fructose inhibits M1-like macrophage polarization independently of fructose-mediated metabolism. Instead, it serves as a signal molecule to promote the interaction between hexokinase 2 and inositol 1,4,5-trisphophate receptor type 3, the predominant Ca2+ channel on the endoplasmic reticulum. The interaction reduces Ca2+ levels in cytosol and mitochondria, thereby suppressing the activation of mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription 1 (STAT1) as well as NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome activation. Consequently, this impedes M1-like macrophage polarization. Our study highlights the critical role of fructose as a signaling molecule that impairs the polarization of M1-like macrophages for tumor growth. [Display omitted] • Fructose suppresses M1-like tumor-associated macrophage polarization • Fructose enhances the interaction between HK2 and ITPR3 in BMDMs • Fructose restrains inflammasome formation by regulating calcium flux • Macrophage GLUT5 expression positively relates to human colorectal cancer progression Yan et al. report that fructose promotes the progression of colorectal cancer by inhibiting M1-like tumor-associated macrophage polarization. Specifically, fructose functions as a signaling molecule, enhancing the interaction between HK2 and ITPR3, which disrupts intracellular calcium signaling, thereby impeding M1-like macrophage polarization. [ABSTRACT FROM AUTHOR]

Nitrogen and genotype play vital roles in modulating plant disease resistance. Maize (Zea mays L.) rough dwarf disease (MRDD) is a global viral disease that has caused serious yield losses. However, it is not clear how nitrogen and genotype interact to affect MRDD. We conducted field experiments in 2011 and 2013 to investigate the MRDD incidence, yield, and yield loss rate of 59 maize hybrids under high nitrogen (HN) and low nitrogen (LN). Compared with HN, the MRDD incidence and yield loss rate of S‐sensitive hybrids (nitrogen significantly influenced MRDD incidence in susceptible genotypes) could be significantly reduced by 50.6% and 35.5%, respectively, in LN without compromising maize yield. In contrast, R‐insensitive types (resistant hybrids in which MRDD incidence was unresponsive to nitrogen treatment) could maintain high MRDD resistance and yield at HN. US hybrid 78599 and inbred line Dan340 were the main parental resources of the resistant genotypes, and inbred lines Huangzao4 and Ye478 were the main parental resources of the susceptible genotypes. The physiological mechanism leading to increased MRDD incidence was thought to be higher nitrogen concentrations in the stalks. This study provided theoretical support for using reasonable nitrogen management to control MRDD and breeding MRDD‐resistant maize hybrids. Core Ideas: Low nitrogen input can decrease maize rough dwarf disease (MRDD) incidence of susceptible genotypes that are responsive to N.Resistant hybrids could maintain high MRDD resistance and yield at high nitrogen.Higher stalk N concentration may be a potential physiological mechanism leading to increased MRDD incidence.US hybrid 78599 and inbred line Dan340 are the main parental resources of the resistant genotypes.Huangzao4 and Ye478 are the main parental resources of the susceptible genotypes. [ABSTRACT FROM AUTHOR]

EMR and endoscopic submucosal dissection (ESD) are minimally invasive endoscopic techniques, developed for the removal of benign and early malignant lesions throughout the GI tract. Submucosal injection of a marking agent can help to identify lesions during surgery. Endoscopic resection frequently involves "lifting" of the lesions by injection of a substance within the submucosal space to create a cushion for safe resection. This review summarizes the current techniques and agents available for endoscopic marking and lifting of GI tract lesions. The MEDLINE database was searched through April 2023 for relevant articles related to the lifting and marking aspect of EMR by using key words such as "endoscopy" or "endoscopic" combined with "marking," "tattoo," and "lifting." The report was drafted, reviewed, and edited by the American Society for Gastrointestinal Endoscopy Technology Committee and approved by the Governing Board of the American Society for Gastrointestinal Endoscopy. This technology review describes the techniques for endoscopic tattoo placement and submucosal lifting, along with currently available agents, safety, and costs. Endoscopists performing EMR and ESD have several choices in submucosal injection materials for lifting and marking agents for tattoos. These may be commercially prepared agents or off-the-shelf materials with or without additives to facilitate visualization. A thorough understanding of the indications, techniques, properties of various agents, costs, and adverse events is necessary in choosing the appropriate materials and technique to optimize lesion resection in EMR and ESD. [ABSTRACT FROM AUTHOR]

Loganin (LOG), a bioactive compound derived from Cornus officinalis Siebold & Zucc, has been understudied in the context of osteoarthritis (OA) treatment. In this study, we induced an inflammatory response in chondrocytes using lipopolysaccharide (LPS) and subsequently treated these cells with LOG. We employed fluorescence analysis to quantify reactive oxygen species (ROS) levels and measured the expression of NLRP3 and nuclear factor erythropoietin-2-related factor 2 (NRF2) using real-time quantitative polymerase chain reaction (qRT-PCR), Western blotting, and immunofluorescence (IF) techniques. Additionally, we developed an OA mouse model by performing medial meniscus destabilization (DMM) surgery and monitored disease progression through micro-computed tomography (micro-CT), hematoxylin and eosin (H&E) staining, safranin O and fast green (S&F) staining, and immunohistochemical (IHC) analysis. Our results indicate that LOG significantly reduced LPS-induced ROS levels in chondrocytes, inhibited the activation of the NLRP3 inflammasome, and enhanced NRF2/heme oxygenase 1 (HO-1) signaling. In vivo , LOG treatment mitigated cartilage degradation and osteophyte formation triggered by DMM surgery, decreased NLRP3 expression, and increased NRF2 expression. These findings suggest that LOG has a protective effect against OA, potentially delaying disease progression by inhibiting the ROS-NLRP3-IL-1β axis and activating the NRF2/HO-1 pathway. [ABSTRACT FROM AUTHOR]

In this study, using Taiwan's National Health Insurance (NHI) as an example of a single-payer system, we examined the extent of pharmaceutical procurement profits (PPP) and evaluated their impact on the financial performance of healthcare institutions. We extracted data from financial statements and healthcare service declarations of NHI-contracted hospitals from 2015 to 2021. Financial data concerning PPP, health service profits (HSP), and total operating profits (TOP) from each hospital were analyzed. The impact of PPP on hospitals with positive and negative HSP was further investigated. The total PPP across all hospitals studied gradually increased from NT$30.6 billion in 2015 to NT$47.0 billion in 2021. In 2021, 28.1% of all hospitals reported a deficit in HSP. PPP appeared to have a significantly positive impact on the financial performance of these hospitals. It not only enhanced positive profits, but also helped mitigate or completely offset the negative profits from HSP. The effect of PPP seems to be more pronounced for hospitals with larger HSP values, suggesting that larger hospitals benefit more from PPP in absolute terms. Average PPP increased during the study period, increasingly affecting hospitals' financial stability across all strata. The gap between TOP and HSP in medical centers has gradually widened, suggesting an increase in non-health service profits. In this study, we propose a payment policy reform that fosters sustainability of the healthcare and financing system under universal health coverage and corrects the potential distortions caused by PPP. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, Taiwan's pediatric healthcare system faced its most severe shortage of pediatric residents in history. This review investigates the causes, consequences, and potential solutions to this shortage. Between 2020 and 2023, the recruitment rate of pediatric residents dropped by 27.3%, increasing workloads for attending pediatricians and may worsening health outcomes for pediatric patients. Compared to South Korea and Japan, Taiwan has the highest neonatal mortality rates and lowest life expectancy at birth. Additionally, Taiwan's National Health Insurance (NHI) pays pediatricians in hospitals half of what it pays those in local clinics, hindering the attraction of pediatric hospitalists. To sustain the pediatric healthcare system, the government could consider directly compensating pediatricians at clinic rates and transitioning to a capitation payment system. Systemic recommendations include increasing health expenditure as a percentage of gross domestic production (GDP) and amending the NHI Act to eliminate the global budget payment system. Managing the resulting increase in financial responsibility could involve raising tax revenue as a percentage of GDP. Implementing these measures could strengthen the pediatric healthcare system and prevent a collapse of pediatric inpatient care. [ABSTRACT FROM AUTHOR]

This paper examines the resilience of Taiwan's oral healthcare system in response to COVID-19, focusing on pre-pandemic conditions, pandemic impacts, and policy recommendations for future resilience. In Taiwan, oral diseases were prevalent, with 80.48% of adults affected by periodontitis in 2016, and 65.43% of 5-year-old children experiencing dental caries. Taiwan's National Health Insurance (NHI) covers over 99% of the population, providing comprehensive dental care. The global budget (GB) payment system, implemented in 1998, ensured financial stability. During the pandemic, dental visits in Taiwan decreased by 5.1% in 2021 compared to 2019. Despite reduced visits, the GB system maintained financial stability, mitigating financial impacts on healthcare institutions. The pandemic generally negatively affected healthcare workers' well-being, increasing resignation intentions. However, the number of practicing dentists in Taiwan remained stable from 2016 to 2022, with slight increases. Urban-rural disparities persisted, and workplace transitions increased, indicating greater mobility among dental professionals. To enhance resilience, the following recommendations are proposed: 1. Strengthen hierarchy of oral healthcare system: Balance dental resources across regions, and improve referrals between hospital and clinics; 2. Provide integrated patient-centered care: Integrate oral health into disease prevention and offer comprehensive services across all stages of life; 3. Integrate digital technology: Promote teledentistry and leverage Taiwan's strengths in information and communication technology (ICT). [ABSTRACT FROM AUTHOR]

Global Nash equilibrium is an optimal solution for each player in a graphical game. This paper proposes an iterative adaptive dynamic programming-based algorithm to solve the global Nash equilibrium solution for optimal containment control problem with robustness analysis to the iterative error. The containment control problem is transferred into the graphical game formulation. Sufficient conditions are given to decouple the Hamilton–Jacobi equations, which guarantee the solvability of the global Nash equilibrium solution. The iterative algorithm is designed to obtain the solution without any knowledge of system dynamics. Conditions of iterative error for global stability are given with rigorous proof. Compared with existing works, the design procedures of control gain and coupling strength are separated, which avoids trivial cases in the design procedure. The robustness analysis exactly quantifies the effect of the iterative error caused by various sources in engineering practice. The theoretical results are validated by two numerical examples with marginally stable and unstable dynamics of the leader. [ABSTRACT FROM AUTHOR]

Extensive researches have been conducted on transfer learning based fault diagnosis. However, negative information transfer may arise due to significant differences in the subdomain distribution across multiple source domains (MSDs). Most existing methods focus solely on the impact of subdomains from a single source domain (SSD) on the target domain (TD). Therefore, this paper proposed a novel multi-stage alignment multi-source subdomain adaptation (MAMSA) method. The global feature extractor is designed to extract domain-invariant features. Three domain-specific feature extractors capture high-level fault features from different domains with a customized adaptation strategy, which combines adversarial learning and distribution alignment based on multiple pseudo-label-guided local maximum mean discrepancy (MP-LMMD) to learn subdomain-invariant features. MP-LMMD utilizes pseudo-labels generated from all classifiers in the TD to guide the alignment of subdomains, suppressing negative transfer from the source domains (SDs). The experimental results indicate that the MAMSA method has excellent capabilities to suppress negative transfer, and the diagnostic performance can be greatly promoted with MAMSA under cross-working conditions. • A novel multi-stage alignment multi-source subdomain adaptation (MAMSA) method is proposed. • A two-stage feature extractor based on specially designed attention mechanism is proposed. • A multiple pseudo-label-guided local maximum mean discrepancy metric is proposed. • The proposed method can suppress the negative transfer and achieve good diagnostic results. [ABSTRACT FROM AUTHOR]

to develop a deep learning radiomics graph network (DLRN) that integrates deep learning features extracted from gray scale ultrasonography, radiomics features and clinical features, for distinguishing parotid pleomorphic adenoma (PA) from adenolymphoma (AL) A total of 287 patients (162 in training cohort, 70 in internal validation cohort and 55 in external validation cohort) from two centers with histologically confirmed PA or AL were enrolled. Deep transfer learning features and radiomics features extracted from gray scale ultrasound images were input to machine learning classifiers including logistic regression (LR), support vector machines (SVM), KNN, RandomForest (RF), ExtraTrees, XGBoost, LightGBM, and MLP to construct deep transfer learning radiomics (DTL) models and Rad models respectively. Deep learning radiomics (DLR) models were constructed by integrating the two features and DLR signatures were generated. Clinical features were further combined with the signatures to develop a DLRN model. The performance of these models was evaluated using receiver operating characteristic (ROC) curve analysis, calibration, decision curve analysis (DCA), and the Hosmer-Lemeshow test. In the internal validation cohort and external validation cohort, comparing to Clinic (AUC=0.767 and 0.777), Rad (AUC=0.841 and 0.748), DTL (AUC=0.740 and 0.825) and DLR (AUC=0.863 and 0.859), the DLRN model showed greatest discriminatory ability (AUC=0.908 and 0.908) showed optimal discriminatory ability. The DLRN model built based on gray scale ultrasonography significantly improved the diagnostic performance for benign salivary gland tumors. It can provide clinicians with a non-invasive and accurate diagnostic approach, which holds important clinical significance and value. Ensemble of multiple models helped alleviate overfitting on the small dataset compared to using Resnet50 alone. [ABSTRACT FROM AUTHOR]

Low-grade glioma (LGG) is associated with increased mortality owing to recrudescence and the tendency for malignant transformation. Therefore, it is imperative to discover novel prognostic biomarkers as existing traditional prognostic biomarkers of glioma, including clinicopathological features and imaging examinations, are unable to meet the clinical demand for precision medicine. Accordingly, we aimed to evaluate the prognostic value of cyclin D1 (CCND1) expression levels and construct radiomic models to predict these levels in patients with LGG A total of 412 LGG cases from The Cancer Genome Atlas (TCGA) were used for gene-based prognostic analysis. Using magnetic resonance imaging (MRI) images stored in The Cancer Imaging Archive with genomic data from TCGA, 149 cases were selected for radiomics feature extraction and model construction. After feature extraction, the radiomic signature was constructed using logistic regression (LR) and support vector machine (SVM) analyses. CCND1 was identified as a prognosis-related gene with differential expression in tumor and normal samples and plays a role in regulating both the cell cycle and immune response. Landmark analysis revealed that high-expression levels of CCND1 were beneficial for survival (P < 0.05) in advanced LGG. Four optimal radiomics features were selected to construct radiomics models. The performance of LR and SVM achieved areas under the curve of 0.703 and 0.705, as well as 0.724 and 0.726 in the training and validation sets, respectively. Elevated levels of CCND1 expression could impact the prognosis of patients with LGG. MRI-based radiomics, especially the AUC values, can serve as a novel tool for predicting CCND1 expression and understanding the correlation between elevated CCND1 expression and prognosis. The datasets analyzed during the current study are available in the TCGA, TCIA, UCSC XENA and GTEx repository, https://portal.gdc.cancer.gov/ , https://www.cancerimagingarchive.net/ , https://xenabrowser.net/datapages/ , https://www.gtexportal.org/home/. [ABSTRACT FROM AUTHOR]

To investigate the accuracy and reliability of magnetic resonance imaging (MRI) in identifying and grading chondral lesions and explore the optimal imaging technique to image cartilage. A comprehensive search was conducted on Medline, Embase, and Cochrane Library. Eligible cohort studies published before August 2022 were included. The study reports used MRI to diagnose and grade cartilage lesions, with intraoperative findings as the reference standard. Summary estimates of diagnostic performance were obtained. The reliability of MRI interpretation was summarized. Subgroup analyses were performed based on assessed imaging techniques, field strength, and joint surface. Forty-three trials and 3,706 patients were included in the systematic review. The overall area under curve for hierarchical summarized receiver operating characteristics was 0.91 (95% confidence interval [CI] 0.88-0.93). The pooled sensitivity for quantitative MRI, 3-dimensional MRI, and 2-dimensional MRI was 0.82 (95% CI 0.64-0.92), 0.79 (95% CI 0.74-0.83), and 0.63 (95% CI 0.51-0.73), respectively. The pooled sensitivity of 3 Tesla (3T), 1.5 Tesla (1.5T), and <1.5 Tesla MRI was 0.79 (95% CI 0.72-0.85), 0.67 (95% CI 0.60-0.74), and 0.55 (95% CI 0.39-0.71), respectively. There were differences in interobserver consistency across different studies. In general, MRI had high specificity in discriminating normal cartilage, but its sensitivity for identifying chondral lesions is less optimal. Further analysis showed that quantitative MRI, 3D MRI, and 3T MRI demonstrate greater sensitivity compared with 2D MRI, 1.5T MRI, and <1.5 Tesla MRI. Level III, systematic review of Level II and III studies. [ABSTRACT FROM AUTHOR]

Dexmedetomidine (Dex) as a local anesthesia adjuvant for nerve block procedures can improve the quality of patient recovery. However, the impact of using Dex as a local anesthetic adjuvant for serratus anterior plane block (SAPB) procedures on recovery quality for children undergoing ear reconstruction remains unclear. Eighty-four patients who underwent ear reconstruction with autogenous costal cartilage (ACC) were randomized into two groups (n = 42/group) in which SAPB was performed with ropivacaine alone (R group) and with Dex and ropivacaine (DR group). Primary outcomes were patient 15-item quality of recovery (QoR-15) scale scores on days 1 and 2 post-surgery. Secondary outcomes included postoperative rest and coughing numerical rating scale (NRS) chest pain scores, duration of analgesia, oral rescue analgesic usage, and opioid-related side effects. Forty patients per group completed the study. QoR-15 scores on days 1 and 2 post-surgery in the DR group were significantly increased relative to the R group (126.35 ± 9.81 vs. 115.53 ± 8.58 and 131.78 ± 8.67 vs. 122.80 ± 8.59, all P < 0.001). Rest and coughing NRS chest pain scores at 2, 4, 8, 12, and 24 h postoperatively in the DR group were all significantly lower relative to the R group (all P < 0.05). The DR group also exhibited significantly longer analgesic duration (P < 0.001) and significantly reduced incidences of oral rescue analgesic usage and opioid-related side effect (all P < 0.05). Combining Dex and ropivacaine for SAPB in children undergoing ear reconstruction with ACC can significantly improve the quality of recovery, quality of analgesia, and analgesic duration. [ABSTRACT FROM AUTHOR]

Objective: Previously, we have successfully purified and synthesized viscolin, an agent derived from Viscum coloratum extract, which has shown significant potential in the treatment of stroke. Our study aimed to evaluate the neuroprotective effects of viscolin. Methods: We first assessed the cytotoxicity of viscolin on primary neuronal cultures and determined its antioxidant and radical scavenging properties. Subsequently, we identified the optimal dose-response of viscolin in protecting against glutamate-induced neurotoxicity. Results: Our results demonstrated that viscolin at a concentration of 10 μM effectively reduced neuronal cell death up to 6 hours after glutamate-induced neurotoxicity. Additionally, we investigated the therapeutic window of opportunity and the potential of viscolin in preventing necrotic and apoptotic damage in cultured neurons exposed to oxygen glucose deprivation-induced neurotoxicity. Our findings showed that viscolin treatment significantly reduced DNA breakage, prevented the release of cytochrome c from mitochondria to cytosol, increased the expression of anti-apoptotic protein Bcl-2, decreased the expression of pro-apoptotic protein Bax, and reduced the number of TUNEL-positive cells. Additionally, our in vivo investigation demonstrated a reduction in brain infarction following middle cerebral artery occlusion. Conclusion: Viscolin has potential utility as a therapeutic agent in the treatment of stroke. [ABSTRACT FROM AUTHOR]

The study aimed to develop a model to predict the risk of sarcopenia in gastrointestinal cancer patients. The goal was to identify these patients early and classify them into different risk categories based on their likelihood of developing sarcopenia. This study evaluated risk factors for sarcopenia in patients with gastrointestinal cancers through a systematic review and meta-analysis. The natural logarithm of the combined risk estimate for each factor was used as a coefficient to assign scores within the model for risk prediction. Data from 270 patients with gastrointestinal cancers, collected between October 2023 and April 2024, was used to assess the predictive performance of the scoring model. The analysis included 17 studies that included 9405 patients with gastrointestinal cancers, out of which 4361 had sarcopenia. The model identified several significant predictors of sarcopenia, including age (OR = 2.45), sex (OR = 1.15), combined diabetes (OR = 2.02), neutrophil-to-lymphocyte ratio (NLR) category (OR = 1.61), TNM stage (OR = 1.61), and weight change (OR = 1.60). Model validation was performed using an external cohort through logistic regression, resulting in an area under the curve (AUC) of 0.773. This model attained a sensitivity of 0.714 and a specificity of 0.688 and ultimately selected 16.5 as the ideal critical risk score. Furthermore, an AUC of 0.770 was obtained from Bayesian model validation; the optimal critical risk score was determined to be 19.0, which corresponds to a sensitivity of 0.658 and a specificity of 0.847. The model of risk prediction developed through systematic review and meta-analysis demonstrates substantial for sarcopenia in patients with gastrointestinal cancers. Its clinical usability facilitates the screening of patients at high risk for sarcopenia. [ABSTRACT FROM AUTHOR]

Risk stratification for patients with a higher risk of hepatocellular carcinoma (HCC) is crucial. We aimed to investigate the role of the Fibrosis-4 (FIB-4) index in predicting chronic hepatitis C (CHC)-related HCC. A retrospective cohort study consecutively included treatment-naive CHC patients receiving longitudinal follow-up at the National Taiwan University Hospital from 1986 to 2014. The clinical data were collected and traced for HCC development. Multivariable Cox proportional hazard regression analysis was used to investigate the predictors for HCC. A total of 1285 patients in the ERADICATE-C cohort were included. The median age was 54, 56% were females, and 933 had HCV viremia. There were 33%, 38%, and 29% of patients having FIB-4 index <1.45, 1.45–3.25, and ≥3.25, respectively. After a median of 9-year follow-up, 186 patients developed HCC. Multivariable analysis revealed that older age, AFP≥20 ng/mL, cirrhosis, and a higher FIB-4 index were independent predictors for HCC. Compared with patients with FIB-4 index <1.45, those with FIB-4 1.45–3.25 had a 5.51-fold risk (95% confidence interval [CI]: 2.65–11.46), and those with FIB-4 ≥ 3.25 had 7.45-fold risk (95% CI: 3.46–16.05) of HCC. In CHC patients without viremia, FIB-4 index 1.45–3.25 and FIB-4 ≥ 3.25 increased 6.78-fold and 16.77-fold risk of HCC, respectively, compared with those with FIB-4 < 1.45. The baseline FIB-4 index can stratify the risks of HCC in untreated CHC patients, even those without viremia. The FIB-4 index should thus be included in the management of CHC. [ABSTRACT FROM AUTHOR]

Pineapple has strong adaptability to acidic soil and has become a significant economic fruit crop in the tropics and subtropics. The multidrug and toxin compound extrusion (MATE) gene family plays crucial roles in plant growth, development and responses to adverse stresses, especially in acidic soils. In this study, forty-two AcMATE genes were identified and classified into six subfamilies based on phylogenetic analysis. The chromosomal distribution, physical characteristics, phylogenetic relationships, and gene and protein structures of pineapple MATE gene family members were systematically analysed. Our results showed that six AcMATE genes can be further clustered into subfamily III with similar conserved motifs and exon-intron patterns, and are unevenly distributed on four pineapple chromosomes. Citrate exuding motif (CEM) was present in all six AcMATE proteins of subfamily III. Finally, quantitative real-time PCR experiments indicated that subfamily III AcMATE genes were highly expressed in roots and distinctly upregulated under Al stresses. In conclusion, our study illustrated that the AcMATE genes of subfamily III may function as an Al-induced citrate transporter in alleviating Al toxicity to adapt acidic soil in pineapple. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ginsenoside fraction from Panax ginseng decreased the acetylated protein levels of spliceosome in cardiomyocytes. • Ginsenoside Rb2 inhibited SF3A2 acetylation at lysine 10 to promote mitochondrial function against myocardial ischemic/reperfusion injury. • Ginsenoside Rb2 promoted Fscn1 alternative splicing to enhance mitochondrial respiration. • The decreased acetylation of SF3A2 (K 10) by ginsenoside Rb2 was mediated by p300 inhibition. Ginsenosides (GS) derived from Panax ginseng can regulate protein acetylation to promote mitochondrial function for protecting cardiomyocytes. However, the potential mechanisms of GS for regulating acetylation modification are not yet clear. This study aimed to explore the potential mechanisms of GS in regulating protein acetylation and identify ginsenoside monomer for fighting myocardial ischemia-related diseases. The 4D-lable free acetylomic analysis was employed to gain the acetylated proteins regulated by GS pretreatment. The co-immunoprecipitation assay, immunofluorescent staining, and mitochondrial respiration measurement were performed to detect the effect of GS or ginsenoside monomer on acetylated protein level and mitochondrial function. RNA sequencing, site-specific mutation, and shRNA interference were used to explore the downstream targets of acetylation modificationby GS. Cellular thermal shift assay and surface plasmon resonance were used for identifying the binding of ginsenoside with target protein. In the cardiomyocytes of normal, oxygen glucose deprivation and/or reperfusion conditions, the acetylomic analysis identified that the acetylated levels of spliceosome proteins were inhibited by GS pretreatment and SF3A2 acetylation at lysine 10 (K 10) was significantly decreased as a potential target of GS. Ginsenoside Rb2 was identified as one of the active ginsenoside monomers for reducing the acetylation of SF3A2 (K 10), which enhanced mitochondrial respiration against myocardial ischemic injury in in vivo and in vitro experiments. RNA-seq analysis showed that ginsenoside Rb2 promoted alternative splicing of mitochondrial function-related genes and the level of fascin actin-bundling protein 1 (Fscn1) was obviously upregulated, which was dependent on SF3A2 acetylation. Critically, thermodynamic, kinetic and enzymatic experiments demonstrated that ginsenoside Rb2 directly interacted with p300 for inhibiting its activity. These findings provide a novel mechanism underlying cardiomyocyte protection of ginsenoside Rb2 by inhibiting p300-mediated SF3A2 acteylation for promoting Fscn1 expression, which might be a promising approach for the prevention and treatment of myocardial ischemic diseases. [ABSTRACT FROM AUTHOR]

[Display omitted] • This study achieved label-free visualization of PD-L1 expression at tissue level for the first time. • MLC-Raman histopathology achieved an accuracy of 0.99 in classifying distinct PD-L1 expression cells in GBM IME. • MLC-Raman histopathology could identify glioma, CD8+ T cells, macrophages and normal cells. • The imaging results exhibited strong concordance with MxIF and traditional pathologists' scoring. • The entire process from signal collection to visualization could be completed within 30 min. Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming. To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level. We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically. The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R 2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm−1 showed a positive linear correlation with PD-L1 expression level. This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy. [ABSTRACT FROM AUTHOR]