A feature extraction method based on noise reduction for circRNA-miRNA interaction prediction combining multi-structure features in the association networks.

MOTIVATION: A large number of studies have shown that circular RNA (circRNA) affects biological processes by competitively binding miRNA, providing a new perspective for the diagnosis, and treatment of human diseases. Therefore, exploring the potential circRNA-miRNA interactions (CMIs) is an important and urgent task at present. Although some computational methods have been tried, their performance is limited by the incompleteness of feature extraction in sparse networks and the low computational efficiency of lengthy data. RESULTS: In this paper, we proposed JSNDCMI, which combines the multi-structure feature extraction framework and Denoising Autoencoder (DAE) to meet the challenge of CMI prediction in sparse networks. In detail, JSNDCMI integrates functional similarity and local topological structure similarity in the CMI network through the multi-structure feature extraction framework, then forces the neural network to learn the robust representation of features through DAE and finally uses the Gradient Boosting Decision Tree classifier to predict the potential CMIs. JSNDCMI produces the best performance in the 5-fold cross-validation of all data sets. In the case study, seven of the top 10 CMIs with the highest score were verified in PubMed. AVAILABILITY: The data and source code can be found at https://github.com/1axin/JSNDCMI.

GnRH-driven FTO-mediated RNA m6A modification promotes gonadotropin synthesis and secretion.

BACKGROUND: Gonadotropin precisely controls mammalian reproductive activities. Systematic analysis of the mechanisms by which epigenetic modifications regulate the synthesis and secretion of gonadotropin can be useful for more precise regulation of the animal reproductive process. Previous studies have identified many differential m6A modifications in the GnRH-treated adenohypophysis. However, the molecular mechanism by which m6A modification regulates gonadotropin synthesis and secretion remains unclear. RESULTS: Herein, it was found that GnRH can promote gonadotropin synthesis and secretion by promoting the expression of FTO. Highly expressed FTO binds to Foxp2 mRNA in the nucleus, exerting a demethylation function and reducing m6A modification. After Foxp2 mRNA exits the nucleus, the lack of m6A modification prevents YTHDF3 from binding to it, resulting in increased stability and upregulation of Foxp2 mRNA expression, which activates the cAMP/PKA signaling pathway to promote gonadotropin synthesis and secretion. CONCLUSIONS: Overall, the study reveals the molecular mechanism of GnRH regulating the gonadotropin synthesis and secretion through FTO-mediated m6A modification. The results of this study allow systematic interpretation of the regulatory mechanism of gonadotropin synthesis and secretion in the pituitary at the epigenetic level and provide a theoretical basis for the application of reproductive hormones in the regulation of animal artificial reproduction.

Membrane-Free Electrosynthesis of Epichlorohydrins Mediated by Bromine Radicals over Nanotips.

The industrial manufacture of epichlorohydrin (ECH) often suffers from excessive corrosive chlorine and multistep processes. Here, we report a one-pot membrane-free Br radical-mediated ECH electrosynthesis. Bromine radicals electro-oxidized from Br- ions initiate the reaction and then eliminate HBr from bromohydrin to give ECH and release Br- ions for reuse. A high energy barrier for *OH oxidation and isolated Br adsorption sites enables NiCo2O4 to suppress the competitive oxygen and bromine evolution reactions. The high-curvature nanotips with an increased electric field concentrate Br- and OH- ions to accelerate ECH electrosynthesis. This strategy delivers ECH with a Faradaic efficiency of 47% and a reaction rate of 1.4 mol h-1 gcat-1 at a high current density of 100 mA cm-2, exceeding the profitable target from the techno-economic analysis. Economically profitable electrosynthesis, methodological universality, and the extended synthesis of epoxide-drug blocks highlight their promising potential.

Two Cytochrome P450 Enzymes Form the Tricyclic Nested Skeleton of Meroterpenoids by Sequential Oxidative Reactions.

Meroterpenoid clavilactones feature a unique benzo-fused ten-membered carbocyclic ring unit with an α,ß-epoxy-γ-lactone moiety, forming an intriguing 10/5/3 tricyclic nested skeleton. These compounds are good inhibitors of the tyrosine kinase, attracting a lot of chemical synthesis studies. However, the natural enzymes involved in the formation of the 10/5/3 tricyclic nested skeleton remain unexplored. Here, we identified a gene cluster responsible for the biosynthesis of clavilactone A in the basidiomycetous fungus Clitocybe clavipes. We showed that a key cytochrome P450 monooxygenase ClaR catalyzes the diradical coupling reaction between the intramolecular hydroquinone and allyl moieties to form the benzo-fused ten-membered carbocyclic ring unit, followed by the P450 ClaT that exquisitely and stereoselectively assembles the α,ß-epoxy-γ-lactone moiety in clavilactone biosynthesis. ClaR unprecedentedly acts as a macrocyclase to catalyze the oxidative cyclization of the isopentenyl to the nonterpenoid moieties to form the benzo-fused macrocycle, and a multifunctional P450 ClaT catalyzes a ten-electron oxidation to accomplish the biosynthesis of the 10/5/3 tricyclic nested skeleton in clavilactones. Our findings establish the foundation for the efficient production of clavilactones using synthetic biology approaches and provide the mechanistic insights into the macrocycle formation in the biosynthesis of fungal meroterpenoids.

Assessment of SWI/SNF chromatin remodeling complex related genes as potential biomarkers and therapeutic targets in pan-cancer.

Recent research has uncovered a surprisingly high occurrence of aberrant expression and mutations in the genes that encode subunits of the SWI/SNF chromatin-remodeling complexes (SCRC). Nevertheless, the carcinogenic effects of aberrant expression and mutations in SWI/SNF genes have only been acknowledged in recent times, resulting in a comparatively limited understanding of these modifications. In this study, we comprehensively analyzed the expression difference, somatic mutation, potential biological pathways, stromal or immune cell infiltration, and drug sensitivity of SCRC-related genes (SCRGs) in pan-cancer. Furthermore, the evolutionary trend, prognostic signature, and immunotherapy response of SCRGs in kidney renal clear cell carcinoma (KIRC) were also evaluated. The expression of SCRGs was changed in 13 out of 14 tumor types, strongly linked to prognosis, and mutated in 30.9% of tumor patients. SCRGs were also closely associated with immune-related pathways and tumor metastasis pathways. The expression of SCRGs was positively associated with the immune score or stromal score but negatively correlated with Tumor purity. Three potential drugs (FK866, Ispinesib mesylate, and WZ3105) were identified to target the SCRGs. In KIRC, scRNA-seq analysis showed that the enrichment of SCRC and the communication frequency with immune cells were significantly declined during tumor cell progression. A prognostic signature was constructed in KIRC and was effective in predicting the prognosis for KIRC. Aberrant expression of eleven prognostic genes identified from the KIRC prognostic signature and the cytotoxicity of FK866 and Ispinesib mesylate to KIRC were verified by qRT-PCR and CCK-8 assay, respectively. Our study identified SCRGs as potential biomarker and therapeutic targets, providing new insights into SCRC for tumor-targeted therapy.

A biomedical knowledge graph-based method for drug-drug interactions prediction through combining local and global features with deep neural networks.

Drug-drug interactions (DDIs) prediction is a challenging task in drug development and clinical application. Due to the extremely large complete set of all possible DDIs, computer-aided DDIs prediction methods are getting lots of attention in the pharmaceutical industry and academia. However, most existing computational methods only use single perspective information and few of them conduct the task based on the biomedical knowledge graph (BKG), which can provide more detailed and comprehensive drug lateral side information flow. To this end, a deep learning framework, namely DeepLGF, is proposed to fully exploit BKG fusing local-global information to improve the performance of DDIs prediction. More specifically, DeepLGF first obtains chemical local information on drug sequence semantics through a natural language processing algorithm. Then a model of BFGNN based on graph neural network is proposed to extract biological local information on drug through learning embedding vector from different biological functional spaces. The global feature information is extracted from the BKG by our knowledge graph embedding method. In DeepLGF, for fusing local-global features well, we designed four aggregating methods to explore the most suitable ones. Finally, the advanced fusing feature vectors are fed into deep neural network to train and predict. To evaluate the prediction performance of DeepLGF, we tested our method in three prediction tasks and compared it with state-of-the-art models. In addition, case studies of three cancer-related and COVID-19-related drugs further demonstrated DeepLGF's superior ability for potential DDIs prediction. The webserver of the DeepLGF predictor is freely available at http://120.77.11.78/DeepLGF/.

A novel circRNA-miRNA association prediction model based on structural deep neural network embedding.

A large amount of clinical evidence began to mount, showing that circular ribonucleic acids (RNAs; circRNAs) perform a very important function in complex diseases by participating in transcription and translation regulation of microRNA (miRNA) target genes. However, with strict high-throughput techniques based on traditional biological experiments and the conditions and environment, the association between circRNA and miRNA can be discovered to be labor-intensive, expensive, time-consuming, and inefficient. In this paper, we proposed a novel computational model based on Word2vec, Structural Deep Network Embedding (SDNE), Convolutional Neural Network and Deep Neural Network, which predicts the potential circRNA-miRNA associations, called Word2vec, SDNE, Convolutional Neural Network and Deep Neural Network (WSCD). Specifically, the WSCD model extracts attribute feature and behaviour feature by word embedding and graph embedding algorithm, respectively, and ultimately feed them into a feature fusion model constructed by combining Convolutional Neural Network and Deep Neural Network to deduce potential circRNA-miRNA interactions. The proposed method is proved on dataset and obtained a prediction accuracy and an area under the receiver operating characteristic curve of 81.61% and 0.8898, respectively, which is shown to have much higher accuracy than the state-of-the-art models and classifier models in prediction. In addition, 23 miRNA-related circular RNAs (circRNAs) from the top 30 were confirmed in relevant experiences. In these works, all results represent that WSCD would be a helpful supplementary reliable method for predicting potential miRNA-circRNA associations compared to wet laboratory experiments.

Metformin enhances endogenous neural stem cells proliferation, neuronal differentiation, and inhibits ferroptosis through activating AMPK pathway after spinal cord injury.

BACKGROUND: Inadequate nerve regeneration and an inhibitory local microenvironment are major obstacles to the repair of spinal cord injury (SCI). The activation and differentiation fate regulation of endogenous neural stem cells (NSCs) represent one of the most promising repair approaches. Metformin has been extensively studied for its antioxidative, anti-inflammatory, anti-aging, and autophagy-regulating properties in central nervous system diseases. However, the effects of metformin on endogenous NSCs remains to be elucidated. METHODS: The proliferation and differentiation abilities of NSCs were evaluated using CCK-8 assay, EdU/Ki67 staining and immunofluorescence staining. Changes in the expression of key proteins related to ferroptosis in NSCs were detected using Western Blot and immunofluorescence staining. The levels of reactive oxygen species, glutathione and tissue iron were measured using corresponding assay kits. Changes in mitochondrial morphology and membrane potential were observed using transmission electron microscopy and JC-1 fluorescence probe. Locomotor function recovery after SCI in rats was assessed through BBB score, LSS score, CatWalk gait analysis, and electrophysiological testing. The expression of the AMPK pathway was examined using Western Blot. RESULTS: Metformin promoted the proliferation and neuronal differentiation of NSCs both in vitro and in vivo. Furthermore, a ferroptosis model of NSCs using erastin treatment was established in vitro, and metformin treatment could reverse the changes in the expression of key ferroptosis-related proteins, increase glutathione synthesis, reduce reactive oxygen species production and improve mitochondrial membrane potential and morphology. Moreover, metformin administration improved locomotor function recovery and histological outcomes following SCI in rats. Notably, all the above beneficial effects of metformin were completely abolished upon addition of compound C, a specific inhibitor of AMP-activated protein kinase (AMPK). CONCLUSION: Metformin, driven by canonical AMPK-dependent regulation, promotes proliferation and neuronal differentiation of endogenous NSCs while inhibiting ferroptosis, thereby facilitating recovery of locomotor function following SCI. Our study further elucidates the protective mechanism of metformin in SCI, providing new mechanistic insights for its candidacy as a therapeutic agent for SCI.

Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.

BACKGROUND: We aimed to construct and validate a deep learning (DL) radiomics nomogram using baseline and restage enhanced computed tomography (CT) images and clinical characteristics to predict the response of metastatic lymph nodes to neoadjuvant chemotherapy (NACT) in locally advanced gastric cancer (LAGC). METHODS: We prospectively enrolled 112 patients with LAGC who received NACT from January 2021 to August 2022. After applying the inclusion and exclusion criteria, 98 patients were randomized 7:3 to the training cohort (n = 68) and validation cohort (n = 30). We established and compared three radiomics signatures based on three phases of CT images before and after NACT, namely radiomics-baseline, radiomics-delta, and radiomics-restage. Then, we developed a clinical model, DL model, and a nomogram to predict the response of LAGC after NACT. We evaluated the predictive accuracy and clinical validity of each model using the receiver operating characteristic curve and decision curve analysis, respectively. RESULTS: The radiomics-delta signature was the best predictor among the three radiomics signatures. So, we developed and validated a DL delta radiomics nomogram (DLDRN). In the validation cohort, the DLDRN produced an area under the receiver operating curve of 0.94 (95% confidence interval, 0.82-0.96) and demonstrated adequate differentiation of good response to NACT. Furthermore, the DLDRN significantly outperformed the clinical model and DL model (p < 0.001). The clinical utility of the DLDRN was confirmed through decision curve analysis. CONCLUSIONS: In patients with LAGC, the DLDRN effectively predicted a therapeutic response in metastatic lymph nodes, which could provide valuable information for individualized treatment.

Prevalence, characteristics, evaluation, and management of carotid body tumors: Systematic analysis based on available evidence.

OBJECTIVE: Although carotid body tumors (CBTs) are rare, they attract particular attention because of their propensity for malignant transformation and the high surgical risk. Because data are scarce and as it is difficult to achieve a large sample size, no study has yet comprehensively analyzed the characteristics, management, or operative complications of CBTs. Therefore, we collected and analyzed all currently available information on CBTs and used the pooled data to derive quantitative information on disease characteristics and management. METHODS: We systematically searched PubMed, Embase, the Cochrane Library, and the Web of Science up to December 1, 2022, for studies that investigated the characteristics and management of CBTs. The primary objective was to identify the prevalence of the various characteristics and the incidence of complications. The secondary objective was to compare patients who underwent preoperative embolization (PE) and those who did not (non-PE), as well as to compare patients with different Shamblin grades and those with and without succinate dehydrogenase (SDH) mutations in terms of CBT characteristics and complications. Two reviewers selected studies for inclusion and independently extracted data. All statistical analyses were performed using the standard statistical procedures of Review Manager 5.2 and Stata 12.0. RESULTS: A total of 155 studies with 9291 patients and 9862 tumors were identified. The pooled results indicated that the median age of patients with CBT was 45.72 years, and 65% were female. The proportion of patients with bilateral lesions was 13%. In addition, 16% of patients had relevant family histories, and the proportion of those with SDH gene mutations was 36%. Sixteen percent of patients experienced multiple paragangliomas, and 12% of CBTs had catecholamine function. The incidence of cranial nerve injury (CNI) was 27%, and 14% of patients suffered from permanent CNI. The incidence rates of operative mortality and stroke were both 1%, and 4% of patients developed transient ischemic attacks. Of all CBTs, 6% were malignant or associated with metastases or recurrences. The most common metastatic locations were the lymph nodes (3%) and bone (3%), followed by the lungs (2%). Compared with non-PE, PE reduced the estimated blood loss (standardized mean difference, -0.95; 95% confidence interval [CI], -1.70 to -0.20) and the operation time (standardized mean difference, -0.56; 95% CI, -1.03 to -0.09), but it increased the incidence of stroke (odds ratio, 2.44; 95% CI, 1.04-5.73). Higher Shamblin grade tumors were associated with more operative complications. Patients who were SDH gene mutation-positive were more likely to have a relevant family history and had more symptoms. CONCLUSIONS: CBT was most common in middle-aged females, and early surgical resection was feasible; there was a low incidence of serious operative complications. Routine PE is not recommended because this may increase the incidence of stroke, although PE somewhat reduced the estimated blood loss and operation time. Higher Shamblin grade tumors increased the incidence of operative complications. Patients who were SDH gene mutation-positive had the most relevant family histories and symptoms.

Exploring the impact of gut microbiota on liver health in mice and patients with Wilson disease.

BACKGROUND AND AIMS: Distinctive gut microbial profiles have been observed between patients with Wilson disease (WD) and healthy individuals. Despite this, the exact relationship and influence of gut microbiota on the advancement of WD-related liver damage remain ambiguous. This research seeks to clarify the gut microbiota characteristics in both human patients and mouse models of WD, as well as their impact on liver injury. METHODS: Gut microbial features in healthy individuals, patients with WD, healthy mice and mice with early- and late-stage WD were analysed using 16S rRNA gene sequencing. Additionally, WD-afflicted mice underwent treatment with either an antibiotic cocktail (with normal saline as a control) or healthy microbiota (using disease microbiota as a control). The study assessed gut microbiota composition, hepatic transcriptome profiles, liver copper concentrations and hepatic pathological injuries. RESULTS: Patients with hepatic WD and mice with WD-related liver injury displayed altered gut microbiota composition, notably with a significant reduction in Lactobacillus abundance. Additionally, the abundances of several gut genera, including Lactobacillus, Veillonella and Eubacterium coprostanoligenes, showed significant correlations with the severity of liver injury in patients with WD. In WD mice, antibiotic treatment or transplantation of healthy microbiota altered the gut microbial structure, increased Lactobacillus abundance and modified the hepatic transcriptional profile. These interventions resulted in reduced hepatic copper concentration and alleviation of WD-related liver injury. CONCLUSIONS: Individuals and mice with pronounced WD-related liver injury exhibited shifts in gut microbial composition. Regulating gut microbiota through healthy microbiota transplantation emerges as a promising therapeutic approach for treating WD-related liver injury.

Nanoliposomes a future based delivery vehicle of cyanidin-3-O-glucoside against major chronic disease.

BACKGROUND: Cyanidin-3-O-glucoside (C3G), is an anthocyanin mainly found in berries, and can also be produced by microorganisms. It has been traditionally used as a natural coloring agent for decades. Recently, it has been investigated for its high antioxidant activity and anti-cancer attributes. C3G has low bioavailability and is sensitive to oxidation and gastric pH; therefore, it is encapsulated in nanoliposomes to enhance its bio-availability, targeted delivery- and efficacy against chronic disease. SCOPE AND APPROACH: In this review, the role of C3G nanoliposomes against major chronic diseases has been discussed. The focus was on research findings and the mechanism of action to affect the proliferation of cancer, neuro disease and cardiovascular problems. It also discussed the formulation of nanoliposomes, their role in nutraceutical delivery and enhancement in C3G bioavailability. KEY FINDINGS AND CONCLUSIONS: Data suggested that nanoliposomes safeguard C3G, enhance bioavailability, and ensure safe, adequate and targeted delivery. It can reduce the impact of cancer and inflammation by inhibiting the ß-catenin/O6-methylguanine-DNA methyltransferase (MGMT) pathway and upregulating miR-214-5p. Formation of C3G nanoliposomes significantly enhances the nutraceutical efficacy of C3G against major chronic disease therefore, C3G nanoliposomes might be a future-based nutraceutical to treat major chronic diseases, including cancer, neuro problems and CVD, but challenges remain in finding correct dose and techniques to maximize its efficacy.

A comprehensive review of medium chain monoglycerides on metabolic pathways, nutritional and functional properties, nanotechnology formulations and applications in food system.

A large and growing body of literature has investigated the broad antibacterial spectrum and strong synergistic antimicrobial activity of medium chain monoglycerides (MCMs) have been widely investigated. Recently, more and more researches have focused on the regulation of MCMs on metabolic health and gut microbiota both in vivo and in vitro. The current review summarizes the digestion, absorption and metabolism of MCMs. Subsequently, it focuses on the functional and nutritional properties of MCMs, including the antibacterial and antiviral characteristics, the modulation of metabolic balance, the regulation of gut microbiota, and the improvement in intestinal health. Additionally, we discuss the most recent developments and application of MCMs using nanotechnologies in food industry, poultry and pharmaceutical industry. Additionally, we analyze recent application examples of MCMs and their nanotechnology formation used in food. The development of nanotechnology platforms facilitating molecular encapsulation and functional presentation contribute to the application of hydrophobic fatty acids and monoglycerides in food preservation and their antibacterial effectiveness. This study emphasizes the metabolic mechanisms and biological activity of MCMs by summarizing the prevailing state of knowledge on this topic, as well as providing insights into prospective techniques for developing the beneficial applications of MCMs to realize the industrialized production.

RBNE-CMI: An Efficient Method for Predicting circRNA-miRNA Interactions via Multiattribute Incomplete Heterogeneous Network Embedding.

Circular RNA (circRNA)-microRNA (miRNA) interaction (CMI) plays crucial roles in cellular regulation, offering promising perspectives for disease diagnosis and therapy. Therefore, it is necessary to employ computational methods for the rapid and cost-effective prediction of potential circRNA-miRNA interactions. However, the existing methods are limited by incomplete data; therefore, it is difficult to model molecules with different attributes on a large scale, which greatly hinders the efficiency and performance of prediction. In this study, we propose an effective method for predicting circRNA-miRNA interactions, called RBNE-CMI, and introduce a framework that can embed incomplete multiattribute CMI heterogeneous networks. By combining the proposed method, we integrate different data sets in the CMI prediction field into one incomplete network for modeling, achieving superior performance in 5-fold cross-validation. Moreover, in the prediction task based on complete data, the proposed method still achieves better performance than the known model. In addition, in the case study, we successfully predicted 18 of the 20 potential cancer biomarkers. The data and source code can be found at https://github.com/1axin/RBNE-CMI.

SiSGC: A Drug Repositioning Prediction Model Based on Heterogeneous Simplifying Graph Convolution.

Drug repositioning plays a key role in disease treatment. With the large-scale chemical data increasing, many computational methods are utilized for drug-disease association prediction. However, most of the existing models neglect the positive influence of non-Euclidean data and multisource information, and there is still a critical issue for graph neural networks regarding how to set the feature diffuse distance. To solve the problems, we proposed SiSGC, which makes full use of the biological knowledge information as initial features and learns the structure information from the constructed heterogeneous graph with the adaptive selection of the information diffuse distance. Then, the structural features are fused with the denoised similarity information and fed to the advanced classifier of CatBoost to make predictions. Three different data sets are used to confirm the robustness and generalization of SiSGC under two splitting strategies. Experiment results demonstrate that the proposed model achieves superior performance compared with the six leading methods and four variants. Our case study on breast neoplasms further indicates that SiSGC is trustworthy and robust yet simple. We also present four drugs for breast cancer treatment with high confidence and further give an explanation for demonstrating the rationality. There is no doubt that SiSGC can be used as a beneficial supplement for drug repositioning.

Neutrophil extracellular traps promote acetaminophen-induced acute liver injury in mice via AIM2.

Excessive acetaminophen (APAP) can induce neutrophil activation and hepatocyte death. Along with hepatocyte dysfunction and death, NETosis (a form of neutrophil-associated inflammation) plays a vital role in the progression of acute liver injury (ALI) induced by APAP overdose. It has been shown that activated neutrophils tend to migrate towards the site of injury and participate in inflammatory processes via formation of neutrophil extracellular traps (NETs). In this study we investigated whether NETs were involved in hepatocyte injury and contributed to APAP-induced ALI progression. ALI mouse model was established by injecting overdose (350 mg/kg) of APAP. After 24 h, blood and livers were harvested for analyses. We showed that excessive APAP induced multiple programmed cell deaths of hepatocytes including pyroptosis, apoptosis and necroptosis, accompanied by significantly increased NETs markers (MPO, citH3) in the liver tissue and serum. Preinjection of DNase1 (10 U, i.p.) for two consecutive days significantly inhibited NETs formation, reduced PANoptosis and consequently alleviated excessive APAP-induced ALI. In order to clarify the communication between hepatocytes and neutrophils, we induced NETs formation in isolated neutrophils, and treated HepaRG cells with NETs. We found that NETs treatment markedly increased the activation of GSDMD, caspase-3 and MLKL, while pre-treatment with DNase1 down-regulated the expression of these proteins. Knockdown of AIM2 (a cytosolic innate immune receptor) abolished NETs-induced PANoptosis in HepaRG cells. Furthermore, excessive APAP-associated ALI was significantly attenuated in AIM2KO mice, and PANoptosis occurred less frequently. Upon restoring AIM2 expression in AIM2KO mice using AAV9 virus, both hepatic injury and PANoptosis was aggravated. In addition, we demonstrated that excessive APAP stimulated mtROS production and mitochondrial DNA (mtDNA) leakage, and mtDNA activated the TLR9 pathway to promote NETs formation. Our results uncover a novel mechanism of NETs and PANoptosis in APAP-associated ALI, which might serve as a therapeutic target.

Efficacy of hepatectomy for hepatolithiasis using 3D visualization combined with ICG fluorescence imaging: A retrospective cohort study.

BACKGROUND: Hepatolithiasis is a complex condition that poses challenges and difficulties in surgical treatment. Three-dimensional visualization technology combined with fluorescence imaging (3DVT-FI) enables accurate preoperative assessment and real-time intraoperative navigation. However, the perioperative outcomes of 3DVT-FI in hepatolithiasis have not been reported. We aim to evaluate the efficacy of 3DVT-FI in the treatment of hepatolithiasis. METHODS: A retrospective analysis was performed on 128 patients who underwent hepatectomy for hepatolithiasis at the Department of Hepatobiliary Surgery, Zhujiang Hospital, between January 2017 and December 2022. Among them, 50 patients underwent hepatectomy using 3DVT-FI (3DVT-FI group), while 78 patients underwent conventional hepatectomy without 3DVT-FI (CH group). The operative data, postoperative liver function indices, complication rates and stone residue were compared between the two groups. RESULTS: There were no significant differences in preoperative baseline data between the two groups (p > 0.05). Compared with the CH group, the 3DVT-FI group exhibited lower intraoperative blood loss (140.00 ± 112.12 vs. 225.99 ± 186.50 mL, p = 0.001), and a lower intraoperative transfusion rate (8.0% vs. 23.1%, p = 0.027). The overall incidence of postoperative complications did not differ significantly (22.0% vs. 35.9%, p = 0.096). The 3DVT-FI group was associated with a lower immediate residual stone rate (16.0% vs. 34.6%, p = 0.021). There were no perioperative deaths in the 3DVT-FI group, while one perioperative death occurred in the CH group. CONCLUSIONS: The 3DVT-FI may offer significant benefits in terms of surgical safety, reduced intraoperative bleeding and decreased stone residue during hepatectomy for hepatolithiasis.

Long term survival outcomes of surgery combined with hyperthermic intraperitoneal chemotherapy for perforated low-grade appendiceal mucinous neoplasms: A multicenter retrospective study.

BACKGROUND: Low-grade appendiceal mucinous neoplasms (LAMN) are very rare, accounting for approximately 0.2%-0.5% of gastrointestinal tumors. We conducted a multicenter retrospective study to explore the impact of different surgical procedures combined with HIPEC on the short-term outcomes and long-term survival of patients. METHODS: We retrospectively analyzed the clinicopathological data of 91 LAMN perforation patients from 9 teaching hospitals over a 10-year period, and divided them into HIPEC group and non-HIPEC group based on whether or not underwent HIPEC. RESULTS: Of the 91 patients with LAMN, 52 were in the HIPEC group and 39 in the non-HIPEC group. The Kaplan-Meier method predicted that 52 patients in the HIPEC group had 5- and 10-year overall survival rates of 82.7% and 76.9%, respectively, compared with predicted survival rates of 51.3% and 46.2% for the 39 patients in the non-HIPEC group, with a statistically significant difference between the two groups (χ2 = 10.622, p = 0.001; χ2 = 10.995, p = 0.001). Compared to the 5-year and 10-year relapse-free survival rates of 75.0% and 65.4% in the HIPEC group, respectively, the 5-year and 10-year relapse-free survival rates of 48.7% and 46.2% in the non-HIPEC group were significant different between the two outcomes (χ2 = 8.063, p = 0.005; χ2 = 6.775, p = 0.009). The incidence of postoperative electrolyte disturbances and hypoalbuminemia was significantly higher in the HIPEC group than in the non-HIPEC group (p = 0.023; p = 0.044). CONCLUSIONS: This study shows that surgery combined with HIPEC can significantly improve 5-year and 10-year overall survival rates and relapse-free survival rates of LAMN perforation patients, without affecting their short-term clinical outcomes.

Recent advances in the application of gasotransmitters in spinal cord injury.

Spinal Cord Injury (SCI) is a condition characterized by complete or incomplete motor and sensory impairment, as well as dysfunction of the autonomic nervous system, caused by factors such as trauma, tumors, or inflammation. Current treatment methods primarily include traditional approaches like spinal canal decompression and internal fixation surgery, steroid pulse therapy, as well as newer techniques such as stem cell transplantation and brain-spinal cord interfaces. However, the above methods have limited efficacy in promoting axonal and neuronal regeneration. The challenge in medical research today lies in promoting spinal cord neuron regeneration and regulating the disrupted microenvironment of the spinal cord. Studies have shown that gas molecular therapy is increasingly used in medical research, with gasotransmitters such as hydrogen sulfide, nitric oxide, carbon monoxide, oxygen, and hydrogen exhibiting neuroprotective effects in central nervous system diseases. The gas molecular protect against neuronal death and reshape the microenvironment of spinal cord injuries by regulating oxidative, inflammatory and apoptotic processes. At present, gas therapy mainly relies on inhalation for systemic administration, which cannot effectively enrich and release gas in the spinal cord injury area, making it difficult to achieve the expected effects. With the rapid development of nanotechnology, the use of nanocarriers to achieve targeted enrichment and precise control release of gas at Sites of injury has become one of the emerging research directions in SCI. It has shown promising therapeutic effects in preclinical studies and is expected to bring new hope and opportunities for the treatment of SCI. In this review, we will briefly outline the therapeutic effects and research progress of gasotransmitters and nanogas in the treatment of SCI.

The association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio with type 2 diabetes mellitus: recent findings from NHANES 2007-2018.

OBJECTIVE: This study aims to assess the relationship between NHHR (non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio) and Type 2 diabetes mellitus (T2DM) in US adults, using National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2018. METHODS: This study explored the connection between NHHR and T2DM by analyzing a sample reflecting the adult population of the United States (n = 10,420; NHANES 2007-2018). NHHR was characterized as the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol. T2DM was defined based on clinical guidelines. This research used multivariable logistic models to examine the connection between NHHR and T2DM. Additionally, it included subgroup and interaction analyses to assess variations among different groups. Generalized additive models, smooth curve fitting, and threshold effect analysis were also employed to analyze the data further. RESULTS: The study included 10,420 subjects, with 2160 diagnosed with T2DM and 8260 without. The weighted multivariate logistic regression model indicated an 8% higher probability of T2DM for each unit increase in NHHR (OR: 1.08, 95% CI: 1.01-1.15) after accounting for all covariates. Subgroup analysis outcomes were uniform across various categories, demonstrating a significant positive relationship between NHHR and T2DM. Interaction tests showed that the positive link between NHHR and T2DM remained consistent regardless of age, body mass index, smoking status, moderate recreational activities, hypertension, or stroke history, with all interaction P-values exceeding 0.05. However, participants' sex appeared to affect the magnitude of the connection between NHHR and T2DM (interaction P-value < 0.05). Also, a nonlinear association between NHHR and T2DM was discovered, featuring an inflection point at 1.50. CONCLUSIONS: Our study suggests that an increase in NHHR may be correlated with a heightened likelihood of developing T2DM. Consequently, NHHR could potentially serve as a marker for estimating the probability of T2DM development.