MGCNSS: miRNA-disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy.

Identifying disease-associated microRNAs (miRNAs) could help understand the deep mechanism of diseases, which promotes the development of new medicine. Recently, network-based approaches have been widely proposed for inferring the potential associations between miRNAs and diseases. However, these approaches ignore the importance of different relations in meta-paths when learning the embeddings of miRNAs and diseases. Besides, they pay little attention to screening out reliable negative samples which is crucial for improving the prediction accuracy. In this study, we propose a novel approach named MGCNSS with the multi-layer graph convolution and high-quality negative sample selection strategy. Specifically, MGCNSS first constructs a comprehensive heterogeneous network by integrating miRNA and disease similarity networks coupled with their known association relationships. Then, we employ the multi-layer graph convolution to automatically capture the meta-path relations with different lengths in the heterogeneous network and learn the discriminative representations of miRNAs and diseases. After that, MGCNSS establishes a highly reliable negative sample set from the unlabeled sample set with the negative distance-based sample selection strategy. Finally, we train MGCNSS under an unsupervised learning manner and predict the potential associations between miRNAs and diseases. The experimental results fully demonstrate that MGCNSS outperforms all baseline methods on both balanced and imbalanced datasets. More importantly, we conduct case studies on colon neoplasms and esophageal neoplasms, further confirming the ability of MGCNSS to detect potential candidate miRNAs. The source code is publicly available on GitHub https://github.com/15136943622/MGCNSS/tree/master.

Predicting microbe-drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy.

MOTIVATION: Predicting the associations between human microbes and drugs (MDAs) is one critical step in drug development and precision medicine areas. Since discovering these associations through wet experiments is time-consuming and labor-intensive, computational methods have already been an effective way to tackle this problem. Recently, graph contrastive learning (GCL) approaches have shown great advantages in learning the embeddings of nodes from heterogeneous biological graphs (HBGs). However, most GCL-based approaches don't fully capture the rich structure information in HBGs. Besides, fewer MDA prediction methods could screen out the most informative negative samples for effectively training the classifier. Therefore, it still needs to improve the accuracy of MDA predictions. RESULTS: In this study, we propose a novel approach that employs the Structure-enhanced Contrastive learning and Self-paced negative sampling strategy for Microbe-Drug Association predictions (SCSMDA). Firstly, SCSMDA constructs the similarity networks of microbes and drugs, as well as their different meta-path-induced networks. Then SCSMDA employs the representations of microbes and drugs learned from meta-path-induced networks to enhance their embeddings learned from the similarity networks by the contrastive learning strategy. After that, we adopt the self-paced negative sampling strategy to select the most informative negative samples to train the MLP classifier. Lastly, SCSMDA predicts the potential microbe-drug associations with the trained MLP classifier. The embeddings of microbes and drugs learning from the similarity networks are enhanced with the contrastive learning strategy, which could obtain their discriminative representations. Extensive results on three public datasets indicate that SCSMDA significantly outperforms other baseline methods on the MDA prediction task. Case studies for two common drugs could further demonstrate the effectiveness of SCSMDA in finding novel MDA associations. AVAILABILITY: The source code is publicly available on GitHub https://github.com/Yue-Yuu/SCSMDA-master.

Drug-target interaction predictions with multi-view similarity network fusion strategy and deep interactive attention mechanism.

MOTIVATION: Accurately identifying the drug-target interactions (DTIs) is one of the crucial steps in the drug discovery and drug repositioning process. Currently, many computational-based models have already been proposed for DTI prediction and achieved some significant improvement. However, these approaches pay little attention to fuse the multi-view similarity networks related to drugs and targets in an appropriate way. Besides, how to fully incorporate the known interaction relationships to accurately represent drugs and targets is not well investigated. Therefore, there is still a need to improve the accuracy of DTI prediction models. RESULTS: In this study, we propose a novel approach that employs Multi-view similarity network fusion strategy and deep Interactive attention mechanism to predict Drug-Target Interactions (MIDTI). First, MIDTI constructs multi-view similarity networks of drugs and targets with their diverse information and integrates these similarity networks effectively in an unsupervised manner. Then, MIDTI obtains the embeddings of drugs and targets from multi-type networks simultaneously. After that, MIDTI adopts the deep interactive attention mechanism to further learn their discriminative embeddings comprehensively with the known DTI relationships. Finally, we feed the learned representations of drugs and targets to the multilayer perceptron model and predict the underlying interactions. Extensive results indicate that MIDTI significantly outperforms other baseline methods on the DTI prediction task. The results of the ablation experiments also confirm the effectiveness of the attention mechanism in the multi-view similarity network fusion strategy and the deep interactive attention mechanism. AVAILABILITY AND IMPLEMENTATION: https://github.com/XuLew/MIDTI.

Increased gene dosage of RFWD2 causes autistic-like behaviors and aberrant synaptic formation and function in mice.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interactions, communication deficits and repetitive behaviors. A study of autistic human subjects has identified RFWD2 as a susceptibility gene for autism, and autistic patients have 3 copies of the RFWD2 gene. The role of RFWD2 as an E3 ligase in neuronal functions, and its contribution to the pathophysiology of ASD, remain unknown. We generated RFWD2 knockin mice to model the human autistic condition of high gene dosage of RFWD2. We found that heterozygous knockin (Rfwd2+/-) male mice exhibited the core symptoms of autism. Rfwd2+/- male mice showed deficits in social interaction and communication, increased repetitive and anxiety-like behavior, and spatial memory deficits, whereas Rfwd2+/- female mice showed subtle deficits in social communication and spatial memory but were normal in anxiety-like, repetitive, and social behaviors. These autistic-like behaviors in males were accompanied by a reduction in dendritic spine density and abnormal synaptic function on layer II/III pyramidal neurons in the prelimbic area of the medial prefrontal cortex (mPFC), as well as decreased expression of synaptic proteins. Impaired social behaviors in Rfwd2+/- male mice were rescued by the expression of ETV5, one of the major substrates of RFWD2, in the mPFC. These findings indicate an important role of RFWD2 in the pathogenesis of autism.

Endothelial Autophagy Promotes Atheroprotective Communication Between Endothelial and Smooth Muscle Cells via Exosome-Mediated Delivery of miR-204-5p.

BACKGROUND: Cellular communication among different types of vascular cells is indispensable for maintaining vascular homeostasis and preventing atherosclerosis. However, the biological mechanism involved in cellular communication among these cells and whether this biological mechanism can be used to treat atherosclerosis remain unknown. We hypothesized that endothelial autophagy mediates the cellular communication in vascular tissue through exosome-mediated delivery of atherosclerosis-related genes. METHODS: Rapamycin and adeno-associated virus carrying Atg7 short hairpin RNA under the Tie (TEK receptor tyrosine kinase) promoter were used to activate and inhibit vascular endothelial autophagy in high-fat diet-fed ApoE-/- mice, respectively. miRNA microarray, in vivo and in vitro experiments, and human vascular tissue were used to explore the effects of endothelial autophagy on endothelial function and atherosclerosis and its molecular mechanisms. Quantitative polymerase chain reaction and miRNA sequencing were performed to determine changes in miRNA expression in exosomes. Immunofluorescence and exosome coculture experiments were conducted to examine the role of endothelial autophagy in regulating the communication between endothelial cells and smooth muscle cells (SMCs) via exosomal miRNA. RESULTS: Endothelial autophagy was inhibited in thoracic aortas of high-fat diet-fed ApoE-/- mice. Furthermore, rapamycin alleviated high-fat diet-induced atherosclerotic burden and endothelial dysfunction, while endothelial-specific Atg7 depletion aggravated the atherosclerotic burden. miRNA microarray, in vivo and in vitro experiments, and human vascular tissue analysis revealed that miR-204-5p was significantly increased in endothelial cells after high-fat diet exposure, which directly targeted Bcl2 to regulate endothelial cell apoptosis. Importantly, endothelial autophagy activation decreased excess miR-204-5p by loading miR-204-5p into multivesicular bodies and secreting it through exosomes. Moreover, exosomal miR-204-5p can effectively transport to SMCs, alleviating SMC calcification by regulating target proteins such as RUNX2. CONCLUSIONS: Our study revealed the exosomal pathway by which endothelial autophagy protects atherosclerosis: endothelial autophagy activation transfers miR-204-5p from endothelial cells to SMCs via exosomes, both preventing endothelial apoptosis and alleviating SMC calcification. REGISTRATION: URL: https://www.chictr.org.cn/; Unique identifier: ChiCTR2200064155.

Klebsiella pneumoniae carbapenemase variants: the new threat to global public health.

Klebsiella pneumoniae carbapenemase (KPC) variants, which refer to the substitution, insertion, or deletion of amino acid sequence compared to wild blaKPC type, have reduced utility of ceftazidime-avibactam (CZA), a pioneer antimicrobial agent in treating carbapenem-resistant Enterobacterales infections. So far, more than 150 blaKPC variants have been reported worldwide, and most of the new variants were discovered in the past 3 years, which calls for public alarm. The KPC variant protein enhances the affinity to ceftazidime and weakens the affinity to avibactam by changing the KPC structure, thereby mediating bacterial resistance to CZA. At present, there are still no guidelines or expert consensus to make recommendations for the diagnosis and treatment of infections caused by KPC variants. In addition, meropenem-vaborbactam, imipenem-relebactam, and other new ß-lactam-ß-lactamase inhibitor combinations have little discussion on KPC variants. This review aims to discuss the clinical characteristics, risk factors, epidemiological characteristics, antimicrobial susceptibility profiles, methods for detecting blaKPC variants, treatment options, and future perspectives of blaKPC variants worldwide to alert this new great public health threat.

Photocatalytic Aptamer Chemiluminescent System for a Homogeneous, Reliable, Label-Free, Generic Assay of Small Molecules.

Chemiluminescence is a powerful analytical technique with many advantages, while aptamers are well-known as good molecular recognition units. However, many aptamer-based chemiluminescence assays employed interface sensing, which often needed several immobilization, separation, and washing steps. To minimize the risks of contamination and false-positive, we for the first time proposed a photocatalytic aptamer chemiluminescent system for a homogeneous, label-free, generic assay of small molecules. After binding to a DNA aptamer, thioflavin T has a unique photocatalytic oxidase activity to activate the system's luminol chemiluminescence. Then, the specific binding between the aptamer and target molecules will compete with the above process. Therefore, we can realize the efficient assay of different analytes including estradiol and adenosine. Such a homogeneous chemiluminescent system allowed a direct assay of small molecules with limits of detection in a nM level. Several control tests were carried out to avoid possible false-positive results, which were originated from the interactions between analytes and sensing interfaces previously. This homogeneous chemiluminescent system provides a useful strategy to reliably assay various analytes in the pharmacy or biology field.

Predicting miRNA-disease associations via learning multimodal networks and fusing mixed neighborhood information.

MOTIVATION: In recent years, a large number of biological experiments have strongly shown that miRNAs play an important role in understanding disease pathogenesis. The discovery of miRNA-disease associations is beneficial for disease diagnosis and treatment. Since inferring these associations through biological experiments is time-consuming and expensive, researchers have sought to identify the associations utilizing computational approaches. Graph Convolutional Networks (GCNs), which exhibit excellent performance in link prediction problems, have been successfully used in miRNA-disease association prediction. However, GCNs only consider 1st-order neighborhood information at one layer but fail to capture information from high-order neighbors to learn miRNA and disease representations through information propagation. Therefore, how to aggregate information from high-order neighborhood effectively in an explicit way is still challenging. RESULTS: To address such a challenge, we propose a novel method called mixed neighborhood information for miRNA-disease association (MINIMDA), which could fuse mixed high-order neighborhood information of miRNAs and diseases in multimodal networks. First, MINIMDA constructs the integrated miRNA similarity network and integrated disease similarity network respectively with their multisource information. Then, the embedding representations of miRNAs and diseases are obtained by fusing mixed high-order neighborhood information from multimodal network which are the integrated miRNA similarity network, integrated disease similarity network and the miRNA-disease association networks. Finally, we concentrate the multimodal embedding representations of miRNAs and diseases and feed them into the multilayer perceptron (MLP) to predict their underlying associations. Extensive experimental results show that MINIMDA is superior to other state-of-the-art methods overall. Moreover, the outstanding performance on case studies for esophageal cancer, colon tumor and lung cancer further demonstrates the effectiveness of MINIMDA. AVAILABILITY AND IMPLEMENTATION: https://github.com/chengxu123/MINIMDA and http://120.79.173.96/.

MHADTI: predicting drug-target interactions via multiview heterogeneous information network embedding with hierarchical attention mechanisms.

MOTIVATION: Discovering the drug-target interactions (DTIs) is a crucial step in drug development such as the identification of drug side effects and drug repositioning. Since identifying DTIs by web-biological experiments is time-consuming and costly, many computational-based approaches have been proposed and have become an efficient manner to infer the potential interactions. Although extensive effort is invested to solve this task, the prediction accuracy still needs to be improved. More especially, heterogeneous network-based approaches do not fully consider the complex structure and rich semantic information in these heterogeneous networks. Therefore, it is still a challenge to predict DTIs efficiently. RESULTS: In this study, we develop a novel method via Multiview heterogeneous information network embedding with Hierarchical Attention mechanisms to discover potential Drug-Target Interactions (MHADTI). Firstly, MHADTI constructs different similarity networks for drugs and targets by utilizing their multisource information. Combined with the known DTI network, three drug-target heterogeneous information networks (HINs) with different views are established. Secondly, MHADTI learns embeddings of drugs and targets from multiview HINs with hierarchical attention mechanisms, which include the node-level, semantic-level and graph-level attentions. Lastly, MHADTI employs the multilayer perceptron to predict DTIs with the learned deep feature representations. The hierarchical attention mechanisms could fully consider the importance of nodes, meta-paths and graphs in learning the feature representations of drugs and targets, which makes their embeddings more comprehensively. Extensive experimental results demonstrate that MHADTI performs better than other SOTA prediction models. Moreover, analysis of prediction results for some interested drugs and targets further indicates that MHADTI has advantages in discovering DTIs. AVAILABILITY AND IMPLEMENTATION: https://github.com/pxystudy/MHADTI.

A novel three-plasmid packaging system for chimeric SFV/SIN VRPs derived from Semliki Forest virus and Sindbis virus as a candidate gene delivery vector.

Semliki Forest virus (SFV) viral replicon particles (VRPs) have been frequently used in various animal models and clinical trials. Chimeric replicon particles offer different advantages because of their unique biological properties. We here constructed a novel three-plasmid packaging system for chimeric SFV/SIN VRPs. The capsid and envelope of SIN structural proteins were generated using two-helper plasmids separately, and the SFV replicon contained the SFV replicase gene, packaging signal of SIN, subgenomic promoter followed by the exogenous gene, and 3' UTR of SIN. The chimeric VRPs carried luciferase or eGFP as reporter genes. The fluorescence and electron microscopy results revealed that chimeric VRPs were successfully packaged. The yield of the purified chimeric VRPs was approximately 2.5 times that of the SFV VRPs (1.38 × 107 TU/ml vs. 5.41 × 106 TU/ml) (p < 0.01). Furthermore, chimeric VRPs could be stored stably at 4°C for at least 60 days. Animal experiments revealed that mice immunized with chimeric VRPs (luciferase) had stronger luciferase expression than those immunized with equivalent amount of SFV VRPs (luciferase) (p < 0.01), and successfully expressed luciferase for approximately 12 days. Additionally, the chimeric VRPs expressed the RBD of SARS-CoV-2 efficiently and induced robust RBD-specific antibody responses in mice. In conclusion, the chimeric VRPs constructed here met the requirements of a gene delivery tool for vaccine development and cancer therapy.

Three-dimensional laser micromachining system with integrated sub-100†nm resolution in-situ measurement.

In this study, a three-dimensional (3D) laser micromachining system with an integrated sub-100 nm resolution in-situ measurement system was proposed. The system used the same femtosecond laser source for in-situ measurement and machining, avoiding errors between the measurement and the machining positions. It could measure the profile of surfaces with an inclination angle of less than 10°, and the measurement resolution was greater than 100 nm. Consequently, the precise and stable movement of the laser focus could be controlled, enabling highly stable 3D micromachining. The results showed that needed patterns could be machined on continuous surfaces using the proposed system. The proposed machining system is of great significance for broadening the application scenarios of laser machining.

Frequency-domain terahertz optoacoustics for non-contact quantitative detection of gas, liquid, and solid samples.

Terahertz optoacoustics (THz-OA) combines the advantages of abundant molecular characteristic absorptions in a terahertz band and the low attenuation through ultrasonic detection. Frequency-domain THz-OA, benefiting from the compact and the low cost of a continuous-wave THz source, has been used in gas detection and sensing. However, liquid and solid detections are hard to achieve due to the sensitivity limitation of existing technologies. Here we present a high-sensitivity frequency-domain THz-OA system with customized optoacoustic cells to accomplish non-contact quantitative detection of gas, liquid, and solid samples. The relationships between signal amplitudes and sample concentration, volume and temperature are discussed separately, revealing a potential application of this technology.

Persistent increase of accumbens cocaine ensemble excitability induced by IRK downregulation after withdrawal mediates the incubation of cocaine craving.

The incubation phenomenon, cue-induced drug craving progressively increasing over prolonged withdrawal, accounts for persistent relapse, leading to a dilemma in the treatment of cocaine addiction. The role of neuronal ensembles activated by initial cocaine experience in the incubation phenomenon was unclear. In this study, with cocaine self-administration (SA) models, we found that neuronal ensembles in the nucleus accumbens shell (NAcSh) showed increasing activation induced by cue-induced drug-seeking after 30-day withdrawal. Inhibition or activation of NAcSh cocaine-ensembles suppressed or promoted craving for cocaine, demonstrating a critical role of NAcSh cocaine-ensembles in incubation for cocaine craving. NAcSh cocaine-ensembles showed a specific increase of membrane excitability and a decrease of inward rectifying channels Kir2.1 currents after 30-day withdrawal. Overexpression of Kir2.1 in NAcSh cocaine-ensembles restored neuronal membrane excitability and suppressed cue-induced drug-seeking after 30-day withdrawal. Expression of dominant-negative Kir2.1 in NAcSh cocaine-ensembles enhanced neuronal membrane excitability and accelerated incubation of cocaine craving. Our results provide a cellular mechanism that the downregulation of Kir2.1 functions in NAcSh cocaine-ensembles induced by prolonged withdrawal mediates the enhancement of ensemble membrane excitability, leading to incubation of cocaine craving.

Measuring functional similarity of lncRNAs based on variable K-mer profiles of nucleotide sequences.

Long non-coding RNAs are a class of essential non-coding RNAs with a length of more than 200 nts. Recent studies have indicated that lncRNAs have various complex regulatory functions, which play great impacts on many fundamental biological processes. However, measuring the functional similarity between lncRNAs by traditional wet-experiments is time-consuming and labor intensive, computational-based approaches have been an effective choice to tackle this problem. Meanwhile, most sequences-based computation methods measure the functional similarity of lncRNAs with their fixed length vector representations, which could not capture the features on larger k-mers. Therefore, it is urgent to improve the predict performance of the potential regulatory functions of lncRNAs. In this study, we propose a novel approach called MFSLNC to comprehensively measure functional similarity of lncRNAs based on variable k-mer profiles of nucleotide sequences. MFSLNC employs the dictionary tree storage, which could comprehensively represent lncRNAs with long k-mers. The functional similarity between lncRNAs is evaluated by the Jaccard similarity. MFSLNC verified the similarity between two lncRNAs with the same mechanism, detecting homologous sequence pairs between human and mouse. Besides, MFSLNC is also applied to lncRNA-disease associations, combined with the association prediction model WKNKN. Moreover, we also proved that our method can more effectively calculate the similarity of lncRNAs by comparing with the classical methods based on the lncRNA-mRNA association data. The detected AUC value of prediction is 0.867, which achieves good performance in the comparison of similar models.

Electroantennographic and Behavioral Responses of the Melon fly, Zeugodacus cucurbitae (Coquillett), to Volatile Compounds of Ridge Gourd, Luffa acutangular L.

The melon fly, Zeugodacus cucurbitae (Coquillett), is a major invasive pest, widely distributed in the Asia-Pacific region and some parts of Africa. Melon fly attractants could improve the effectiveness of current pest management measures. Previous studies have shown that some host fruits are attractive to melon flies but few have investigated the chemical compounds responsible for their attraction. In this study, we aimed to identify the volatile compounds from Luffa acutangula L that attract Z. cucurbitae. In headspace trapping, chemical profiling identified 19 compounds from ridge gourds, with 1-pentadecene being the major component. EAG results revealed that seven compounds elicited antennal responses in Z. cucurbitae, and significant differences in antennal responses between male and female Z. cucurbitae adults were recorded to p-xylene, alpha-pinene, and 1-octadecene. Behavioral experiments demonstrated that the EAG-active compounds methyl isovalerate and methyl myristate had either attractive or repellent effects on Z. cucurbitae at different concentrations, and 1-octadecene attracted Z. cucurbitae. Our findings provide a theoretical basis producing repellents or attractants for effective Integrated Pest Management of Z. cucurbitae.

A nomogram of anastomotic stricture after rectal cancer: a retrospective cohort analysis.

BACKGROUND: Anastomotic stricture significantly impacts patients' quality of life and long-term prognosis. However, current clinical practice lacks accurate tools for predicting anastomotic stricture. This study aimed to develop a nomogram to predict anastomotic stricture in patients with rectal cancer who have undergone anterior resection. METHODS: A total of 1542 eligible patients were recruited for the study. Least absolute shrinkage selection operator (Lasso) analysis was used to preliminarily select predictors. A prediction model was constructed using multivariate logistic regression and presented as a nomogram. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration diagrams, and decision curve analysis (DCA). Internal validation was conducted by assessing the model's performance on a validation cohort. RESULTS: 72 (4.7%) patients were diagnosed with anastomotic stricture. Participants were randomly divided into training (n = 1079) and validation (n = 463) sets. Predictors included in this nomogram were radiotherapy, diverting stoma, anastomotic leakage, and anastomotic distance. The area under the ROC curve (AUC) for the training set was 0.889 [95% confidence interval (CI) 0.840-0.937] and for the validation set, it was 0.930 (95%CI 0.879-0.981). The calibration curve demonstrated a strong correlation between predicted and observed outcomes. DCA results showed that the nomogram had clinical value in predicting anastomotic stricture in patients after anterior resection of rectal cancer. CONCLUSION: We developed a predictive model for anastomotic stricture following anterior resection of rectal cancer. This nomogram could assist clinicians in predicting the risk of anastomotic stricture, thus improving patients' quality of life and long-term prognosis.

Surgical options and survival prognosis in geriatric patients beyond average lifespan with locally advanced gastric cancer: a propensity score-matched analysis.

BACKGROUND: The appropriateness of laparoscopic gastrectomy (LG) for super-geriatric patients with locally advanced gastric cancer (LAGC) is inconclusive, and the prognostic factors are also yet to be elucidated. Herein, we aimed to investigate the surgical and oncological outcomes of LG versus open gastrectomy (OG) for geriatric patients with LAGC who have outlived the average lifespan of the Chinese population (≥ 78 years). METHODS: This is a monocentric, retrospective, comparative study. A 1:1 propensity score matching (PSM) was performed to minimize selection bias and ensure well-balanced characteristics. The primary endpoint of interest was 3-year overall survival, while secondary endpoints included procedure-related variables, postoperative recovery indices, and complications. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify unfavorable prognostic factors. RESULTS: Of 196 eligible individuals, 107 underwent LG and 89 underwent OG, with a median age (interquartile range [IQR]) of 82 [79, 84] years. PSM yielded 61 matched pairs, with comparable demographic and tumor characteristics. The LG group had a significantly lower overall complication rate than the OG group (31.1% vs. 49.2%, P = 0.042), as well as shorter duration of postoperative hospital stay [12 (11, 13) vs. 13 (12, 15.5) d, P < 0. 001], less intraoperative blood loss [95 (75, 150) vs. 230 (195, 290) mL, P < 0.001], but a longer operative time [228 (210, 255.5) vs. 196 (180, 219.5) min, P < 0.001]. The times to first aerofluxus, defecation, liquid diet, and half-liquid diet were comparable. Kaplan-Meier analyses revealed no significant difference in 3-year overall survival between the groups, either in the entire cohort or in subgroups with different TNM staging. Moreover, Age-adjusted Charlson Comorbidity Index scores of > 6 [hazard ratio (HR) 4.003; P = 0.021] and pathologic TNM stage III (HR 3.816, P = 0.023) were independent unfavorable prognostic factors for long-term survival. CONCLUSIONS: LG performed by experienced surgeons offers the benefits of comparable or better surgical and oncological safety profiles than OG for super-geriatric patients with LAGC.

Ultrasonographic evaluation of the gallbladder motor function in the diagnosis and prognosis of intrahepatic cholestasis of pregnancy.

BACKGROUND: Intrahepatic cholestasis of pregnancy (ICP) is characterized by skin pruritus, elevated liver enzymes, and increased serum total bile acids. Several previous studies have revealed that the fasting and ejection volumes of the gallbladder in cholestasis of pregnancy are greater than those in normal pregnancy. The goal of this study was to explore the gallbladder volume and evaluate the diagnostic and prognostic value of ultrasound in ICP. METHODS: We prospectively recruited a cohort of 60 ICP patients at the First Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, China from January 2020 to December 2021 and compared their data with those from healthy pregnant women (n = 60). The gallbladder volume was evaluated by real-time ultrasound examination after overnight fasting and at 30, 60, 120, and 180 min after a liquid test meal of 200 mL, and the ejection fraction was calculated. Continuous data between two groups were compared by Student's t test. Differences were considered significant for p < 0.05. The diagnostic and prognostic value of the volume and ejection function of the gallbladder was analyzed by the receiver operating characteristic (ROC) curve. RESULTS: The ICP group had significantly higher gallbladder basal volume (43.49 ± 1.34 cm3 vs. 26.66 ± 0.83 cm3, p < 0.01) and higher ejection fraction compared with the healthy group. The ejection fraction higher than 54.55% at 120 min might predict ICP diagnosis with 96.67% sensitivity and 88.33% specificity, and an AUC of 0.9739 (95% CI 0.9521-0.9956), while the gallbladder volume higher than 12.52 cm3 at 60 min might predict ICP severity with 59.18% sensitivity and 72.73% specificity, and an AUC of 0.7319 (95% CI 0.5787-0.8852). CONCLUSION: Our results indicate abnormal volume and ejection function of the gallbladder in patients with ICP. The ejection fraction at 120 min can assist in the diagnosis if ICP exists, and the gallbladder volume at 60 min may assess the degree of severity of ICP.

The genetic and immune features of salivary gland secretory carcinoma with high-grade transformation.

OBJECTIVES: To compare the clinicopathological, molecular, and immune features of conventional and high-grade transformation (HGT) secretory carcinoma (SC) in salivary glands. MATERIALS AND METHODS: The clinicopathological data of 88 cases including 74 conventional SCs and 14 SCs with HGT were reviewed. Targeted next-generation sequencing was performed in 11 SCs with HGT and 7 conventional SCs. The level of PD-L1 and CD8+ TILs was determined by immunohistochemistry. RESULTS: Compared with the conventional group, the rates of nodal metastasis, local recurrence, distant metastasis and mortality were significantly higher in the HGT cohort. Mutations of ARID1A/B, KMT2A, HOXD13, NRG1 and ETV6 genes were identified in HGT SCs. A recurrent E307G mutation in GATA6 gene was also observed in two cases. Two deceased HGT patients with distant metastasis harboured NOTCH3 mutations. ETV6-RET translocation was prone to occur in the HGT SCs. Additionally, PD-L1 expression was low, and CD8+ TILs were sparse in most HGT cases. CONCLUSION: Our findings reveal novel gene alterations involved in the progression of HGT in SCs. Most HGT SCs patients cannot benefit from PD-L1 blocking and may be approached with a distinct treatment strategy including the lymph node dissection and application of molecular target drugs in precision oncology.

Manganese drives ferroptosis of cancer cells via YAP/TAZ phase separation activated ACSL4 in OSCC.

OBJECTIVE: Ferroptosis has been defined as a novel form of regulated cell death characterized by iron-dependent lipid peroxidation. Manganese has been used to induce ferroptosis in cancer cells recently. This study aims to investigate whether manganese can induce ferroptosis in oral squamous cell carcinoma (OSCC) and the underlying biological mechanisms. MATERIALS AND METHODS: Cancer cells with or without manganese treatment were analyzed by RNA-sequencing to identify ferroptosis-related genes. Next, the activation of YAP/TAZ/ACSL4-ferroptosis signaling pathway was detected. Bioinformatic analysis and immunofluorescence assay were used to explore the phase separation of YAP/TAZ. Finally, specimens of OSCC patients were applied to analyze the clinical significance of YAP/TAZ/ACSL4. RESULTS: RNA-sequencing analysis showed the ferroptosis-related genes and YAP/TAZ were upregulated after manganese treatment. The results of immunofluorescence, ELISA, western blotting, etc. further confirmed that manganese-induced ferroptosis depends on YAP/TAZ/ACSL4 signaling pathway. Moreover, the activation of ACSL4 was achieved by YAP/TAZ phase separation. The survival analysis in OSCC specimen suggested that the higher level of YAP/TAZ-ACSL4 axis expression indicates longer survival. CONCLUSIONS: Manganese induces YAP/TAZ phase separation and subsequent ACSL4 activation via YAP/TAZ nuclear translocation, which facilitates ferroptosis of OSCC. Then YAP/TAZ-ACSL4 axis can be used as a potential prognostic predictor of OSCC patients.