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To achieve precise Couinaud liver segmentation in preoperative planning for hepatic surgery, accommodating the complex anatomy and significant variations, optimizing surgical approaches, reducing postoperative complications, and preserving liver function.This research presents a novel approach to automating liver segmentation by identifying seven key anatomical landmarks using portal venous phase images from contrast-enhanced magnetic resonance imaging (CE-MRI). By employing a multi-task learning framework, we synchronized the detection of these landmarks with the segmentation process, resulting in accurate and robust delineation of the Couinaud segments.To comprehensively validate our model, we included multiple patient types in our test set—those with normal livers, diffuse liver diseases, and localized liver lesions—under varied imaging conditions, including two field strengths, two devices, and two contrast agents. Our model achieved an average Dice Similarity Coefficient (DSC) of 85.29%, surpassing the next best-performing models by 3.12%.Our research presents a pioneering automated approach for segmenting Couinaud segments using CE-MRI. By correlating landmark detection with segmentation, we enhance surgical planning precision. This method promises improved clinical outcomes by accurately adapting to anatomical variability and reducing potential postoperative complications.Clinical impact: The application of this technique in clinical settings is poised to enhance the precision of liver surgical planning. This could lead to more tailored surgical interventions, minimization of operative risks, and preservation of healthy liver tissue, culminating in improved patient outcomes and potentially lowering the incidence of postoperative complications.Clinical and Translational Impact Statement: This research offers a novel automated liver segmentation technique, enhancing preoperative planning and potentially reducing complications, which may translate into better postoperative outcomes in hepatic surgery.

Introduction: Both innate and adaptive immune system undergo evolution from low to high vertebrates. Due to the limitation of conventional approaches in identifying broader spectrum of immune cells and molecules from various vertebrates, it remains unclear how immune molecules evolve among vertebrates. Objectives: Here, we utilized carry out comparative transcriptome analysis in various immune cells across seven vertebrate species. Methods: Single-cell RNA sequencing (scRNA-seq). Results: We uncovered both conserved and species-specific profiling of gene expression in innate and adaptive immunity. Macrophages exhibited highly-diversified genes and developed sophisticated molecular signaling networks along with evolution, indicating effective and versatile functions in higher species. In contrast, B cells conservatively evolved with less differentially-expressed genes in analyzed species. Interestingly, T cells represented a dominant immune cell populations in all species and unique T cell populations were identified in zebrafish and pig. We also revealed compensatory TCR cascade components utilized by different species. Inter-species comparison of core gene programs demonstrated mouse species has the highest similarity in immune transcriptomes to human. Conclusions: Therefore, our comparative study reveals gene transcription characteristics across multiple vertebrate species during the evolution of immune system, providing insights for species-specific immunity as well as the translation of animal studies to human physiology and disease.

Background: Recent genetic evidence supports that circulating biochemical and metabolic traits (BMTs) play a causal role in Alzheimer's disease (AD), which might be mediated by changes in brain structure. Here, we leveraged publicly available genome-wide association study data to investigate the intrinsic causal relationship between blood BMTs, brain image-derived phenotypes (IDPs) and AD. Methods: Utilizing the genetic variants associated with 760 blood BMTs and 172 brain IDPs as the exposure and the latest AD summary statistics as the outcome, we analyzed the causal relationship between blood BMTs and brain IDPs and AD by using a two-sample Mendelian randomization (MR) method. Additionally, we used two-step/mediation MR to study the mediating effect of brain IDPs between blood BMTs and AD. Results: Twenty-five traits for genetic evidence supporting a causal association with AD were identified, including 12 blood BMTs and 13 brain IDPs. For BMTs, glutamine consistently reduced the risk of AD in 3 datasets. For IDPs, specific alterations of cortical thickness (atrophy in frontal pole and insular lobe, and incrassation in superior parietal lobe) and subcortical volume (atrophy in hippocampus and its subgroups, left accumbens and left choroid plexus, and expansion in cerebral white matter) are vulnerable to AD. In the two-step/mediation MR analysis, superior parietal lobe, right hippocampal fissure and left accumbens were identified to play a potential mediating role among three blood BMTs and AD. Conclusions: The results obtained in our study suggest that 12 circulating BMTs and 13 brain IDPs play a causal role in AD. Importantly, a subset of BMTs exhibit shared genetic architecture and potentially causal relationships with brain structure, which may contribute to the alteration of brain IDPs in AD.

Abstract Genome‑wide association studies (GWASs) have revealed numerous loci associated with Parkinson’s disease (PD). However, some potential causal/risk genes were still not revealed and no etiological therapies are available. To find potential causal genes and explore genetically supported drug targets for PD is urgent. By integrating the expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) datasets from multiple tissues (blood, cerebrospinal fluid (CSF) and brain) and PD GWAS summary statistics, a pipeline combing Mendelian randomization (MR), Steiger filtering analysis, Bayesian colocalization, fine mapping, Protein-protein network and enrichment analysis were applied to identify potential causal genes for PD. As a result, GPNMB displayed a robust causal role for PD at the protein level in the blood, CSF and brain, and transcriptional level in the brain, while the protective role of CD38 (in brain pQTL and eQTL) was also identified. We also found inconsistent roles of DGKQ on PD between protein and mRNA levels. Another 9 proteins (CTSB, ARSA, SEC23IP, CD84, ENTPD1, FCGR2B, BAG3, SNCA, FCGR2A) were associated with the risk for PD based on only a single pQTL after multiple corrections. We also identified some proteins’ interactions with known PD causative genes and therapeutic targets. In conclusion, this study suggested GPNMB, CD38, and DGKQ may act in the pathogenesis of PD, but whether the other proteins involved in PD needs more evidence. These findings would help to uncover the genes underlying PD and prioritize targets for future therapeutic interventions.

Background and aimsObesity and insulin resistance are well-known important risk factors for hypertension. This study aimed to investigate the mediating effect of the triglyceride-glucose index (TyG) in the association between Chinese visceral obesity index (CVAI) and hypertension among Chinese middle-aged and older adults.MethodsA total of 10,322 participants aged 45 years and older from CHARLS (2011–2018) were included. Baseline data were collected in 2011 and hypertension incidence data were gathered during follow-up in 2013, 2015 and 2018. Multivariate logistic regression models were constructed to investigate the association of CVAI and TyG with the incidence of hypertension. Additionally, mediation analyses were conducted to evaluate the mediating role of the TyG index in the relationship between CVAI and hypertension. Subgroup analysis was also performed.ResultsA total of 2,802 participants developed hypertension during the follow-up period. CVAI and TyG index were independently and significantly associated with hypertension incidence. Increasing quartiles of CVAI and TyG index were associated with high hypertension incidence in middle-aged and older adults. The TyG index was identified as a mediator in the relationship between CVAI and hypertension incidence, with a mediation effect (95% confidence interval) was 12.38% (6.75, 31.81%).ConclusionOur study found that CVAI and TyG were independently associated with hypertension incidence. TyG played a partial mediating effect in the positive association between CVAI and hypertension incidence.

Abstract Background Prostate cancer (PCa), the second most prevalent solid tumor among men worldwide, has caused greatly increasing mortality in PCa patients. The effects of lipid metabolism on tumor growth have been explored, but the mechanistic details of the association of lipid metabolism disorders with PCa remain largely elusive. Methods The RNA sequencing data of the GSE45604 and The Cancer Genome Atlas-Prostate Adenocarcinoma (TCGA-PRAD) datasets were extracted from the Gene Expression Omnibus (GEO) and UCSC Xena databases, respectively. The Molecular Signatures Database (MSigDB) was utilized to identify lipid metabolism-related genes. The limma R package was used to identify differentially expressed lipid metabolism-related genes (DE-LMRGs) and differentially expressed microRNAs (DEMs). Moreover, least absolute shrinkage and selection operator (LASSO), extreme gradient boosting (XGBoost), and support vector machine-recursive feature elimination (SVM-RFE) were applied to select signature miRNAs and construct a lipid metabolism-related diagnostic model. The expression levels of selected differentially expressed lipid metabolism-related miRNAs (DE-LMRMs) in PCa and benign prostate hyperplasia (BPH) specimens were verified using quantitative real-time polymerase chain reaction (qRT‒PCR). Furthermore, a transcription factor (TF)-miRNA‒mRNA network was constructed. Eventually, Kaplan‒Meier (KM) curves were plotted to illustrate the associations between signature miRNA-related mRNAs and TFs and overall survival (OS) along with biochemical recurrence-free survival (BCR). Results Forty-seven LMRMs were screened based on the correlation analysis of 29 DE-LMRGs and 56 DEMs, in which 27 LMRMs were stably expressed in the GSE45604 dataset. Subsequently, receiver operating characteristic (ROC) curves and machine learning methods were employed to develop a lipid metabolism-related diagnostic signature, which may be of diagnostic value for PCa patients. qRT‒PCR results showed that all seven key DE-LMRMs were differentially expressed between PCa and BPH tissues. Eventually, a TF-miRNA‒mRNA network was constructed. Conclusions These results suggested that 7 key diagnostic miRNAs were closely related to PCa pathological processes and provided new targets for the diagnosis and treatment of PCa. Moreover, CLIC6 and SCNN1A linked to miR-200c-3p had good prognostic potential and provided valuable insights into the pathogenesis of PCa.

Abstract Background Schizophrenia (SCZ) is a chronic and severe mental illness with no cure so far. Mendelian randomization (MR) is a genetic method widely used to explore etiologies of complex traits. In the current study, we aimed to identify novel proteins underlying SCZ with a systematic analytical approach. Methods We integrated protein quantitative trait loci (pQTLs) of the brain, cerebrospinal fluid (CSF), and plasma with the latest and largest SCZ genome-wide association study (GWAS) via a systematic analytical framework, including two-sample MR analysis, Steiger filtering analysis, and Bayesian colocalization analysis. Results The genetically determined protein level of C4A/C4B (OR = 0.70, p = 1.66E−07) in the brain and ACP5 (OR = 0.42, p = 3.73E−05), CNTN2 (OR = 0.62, p = 2.57E−04), and PLA2G7 (OR = 0.71, p = 1.48E−04) in the CSF was associated with a lower risk of SCZ, while the genetically determined protein level of TIE1 (OR = 3.46, p = 4.76E−05), BCL6 (OR = 3.63, p = 1.59E−07), and MICB (OR = 4.49, p = 2.31E−11) in the CSF were associated with an increased risk for SCZ. Pathway enrichment analysis indicated that genetically determined proteins suggestively associated with SCZ were enriched in the biological process of the immune response. Conclusion In conclusion, we identified one protein in the brain and six proteins in the CSF that showed supporting evidence of being potentially associated with SCZ, which could provide insights into future mechanistic studies to find new treatments for the disease. Our results also supported the important role of neuroinflammation in the pathogenesis of SCZ.

Abstract Increased expression of CD33 in the brain has been suggested to be associated with increased amyloid plaque burden, while the peripheral level of CD33 in Alzheimer’s disease (AD) patients and its role in AD remain unclear. The current study aimed to systematically explore the bidirectional relationship between peripheral CD33 and AD. Genome-wide association study (GWAS) datasets of AD (Ncases: 21982; Ncontrols: 41944), blood CD33 mRNA level, the plasma CD33 protein level, and CD33 expression on immune-cell subtypes were obtained from GWASs conducted in the European population. Eligible IVs were extracted from the GWASs. MR estimates were calculated by inverse-variance weighting (IVW) and other sensitivity analyses. The main statistical analyses were conducted using TwoSampleMR (v.0.5.5) in R package (V.4.1.2).In the forward MR analysis (CD33 as exposure and AD as outcome), the IVW results indicated that elevated blood CD33 mRNA level (OR [95% CI] = 1.156[1.080, 1.238], p = 3.25e-05), elevated serum CD33 protein level (OR [95% CI] = 1.08 [1.031, 1.139], p = 1.6e-03) and increased CD33's expression on immune cell subtypes (p 0.05). In conclusion, our results indicated that elevated peripheral expression of CD33 was causal to the development of AD. Future studies are needed to work on developing CD33 as a biomarker and therapeutic target in AD.

Purpose To develop a model for predicting response to total neoadjuvant treatment (TNT) for patients with locally advanced rectal cancer (LARC) based on baseline magnetic resonance imaging (MRI) and clinical data using artificial intelligence methods. Methods Baseline MRI and clinical data were curated from patients with LARC and analyzed using logistic regression (LR) and deep learning (DL) methods to predict TNT response retrospectively. We defined two groups of response to TNT as pathological complete response (pCR) versus non-pCR (Group 1), and high sensitivity [tumor regression grade (TRG) 0 and TRG 1] versus moderate sensitivity (TRG 2 or patients with TRG 3 and a reduction in tumor volume of at least 20% compared to baseline) versus low sensitivity (TRG 3 and a reduction in tumor volume

ObjectiveWe aimed to identify feature immune-related genes that correlated with graft rejection and to develop a prognostic model based on immune-related genes in kidney transplantation.MethodsGene expression profiles were obtained from the GEO database. The GSE36059 dataset was used as a discovery cohort. Then, differential expression analysis and a machine learning method were performed to select feature immune-related genes. After that, univariate and multivariate Cox regression analyses were used to identify prognosis-related genes. A novel Riskscore model was built based on the results of multivariate regression. The levels of these feature genes were also confirmed in an independent single-cell dataset and other GEO datasets.Results15 immune-related genes were expressed differently between non-rejection and rejection kidney allografts. Those differentially expressed immune-related genes (DE-IRGs) were mainly associated with immune-related biological processes and pathways. Subsequently, a 5-immune-gene signature was constructed and showed favorable predictive results in the GSE21374 dataset. Recipients were divided into the high-risk and low-risk groups according to the median value of RiskScore. The GO and KEGG analysis indicated that the differentially expressed genes (DEGs) between high-risk and low-risk groups were mainly involved in inflammatory pathways, chemokine-related pathways, and rejection-related pathways. Immune infiltration analysis demonstrated that RiskScore was potentially related to immune infiltration. Kaplan-Meier survival analysis suggested that recipients in the high-risk group had poor graft survival. AUC values of 1- and 3-year graft survival were 0.804 and 0.793, respectively.ConclusionOur data suggest that this immune-related prognostic model had good sensitivity and specificity in predicting the 1- and 3-year kidney graft survival and might act as a useful tool for predicting kidney graft loss.

Tubular epithelial cells (TECs) represent the primary site of renal ischemia/reperfusion injury (RIRI). However, whether the damage of TECs could drive the initiation of inflammation was unclear. Here we investigated the role of the TECs and macrophages during RIRI. Increased expression of inflammation response and activated M1 macrophage were determined in the mice model of RIRI. Moreover, we demonstrated global miRNA expression profiling of renal exosomes, and miR-374b-5p was most upregulated in these exosomes in vivo. Inhibition of miR-374b-5p in the mice upon RIR operation would alleviate the kidney injury via decreasing the production of proinflammatory cytokines and suppressing the macrophage activation. Similar results were also identified in the hypoxia-induced cell model where exosomal miR-374b-5p was dramatically upregulated. Uptake of exosomes derived from the hypoxic TECs by macrophages would trigger M1 polarization via transferring miR-374b-5p. Besides, we confirmed that miR-374b-5p could directly bind to Socs1 using a dual-luciferase reporter assay. Notably, when we injected the miR-374b-5p-enriched exosomes into mice, a high-level inflammatory response and M1 macrophage activation were performed. Our studies demonstrated that exosomal miR-374b-5p played an essential role in the communication between injured TECs and macrophages, resulting in the M1 macrophage activation during RIRI. The blockage of the release of such exosomes may serve as a new therapeutic strategy for RIRI.

Renal ischemia/reperfusion (I/R) injury is a particular threat faced by clinicians in kidney transplantation. Previous studies have confirmed the importance of oxidative stress and inflammation in the pathogenesis of I/R injury. Angiopoietin-like protein 2 (ANGPTL2) belongs to the angiopoietin-like family and has been found to be involved in the regulation of kidney function as well as oxidative and inflammatory response. In the present study, we aimed to evaluate the role of ANGPTL2 in renal I/R injury in vitro . The human proximal tubular epithelial cell line (HK-2 cells) was subjected to hypoxia/ reoxygenation (H/R) to mimic I/R injury in vitro . We found that the expression level of ANGPTL2 was markedly increased in H/R-induced HK-2 cells. Knockdown of ANGPTL2 improved the decreased cell viability of HK-2 cells in response to H/R stimulation. Knockdown of ANGPTL2 significantly inhibited the H/R-caused increase in levels of reactive oxygen species, malondialdehyde, and proinflammatory cytokines, including interleukin (IL)-6, IL-1β, and tumor necrosis factor-alpha, as well as a decrease in superoxide dismutase activity in the HK-2 cells. Besides, the increased bax expression and caspase-3 activity and decreased bcl-2 expression in H/R-induced HK-2 cells were also attenuated by knockdown of ANGPTL2. Moreover, ANGPTL2 overexpression showed the opposite effects. Further mechanism investigations proved that the activation of Nrf2/HO-1 signaling pathway and the inhibition of toll-like receptor 4/nuclear factor kappa-light-chain-enhancer of activated B cells signaling pathway were both implicated in the renal-protective effects of ANGPTL2 knockdown on H/R-induced HK-2 cells. Collectively, these findings suggested that ANGPTL2 might be a new possible target for the treatment and prevention of renal I/R injury.

Thermocouple thermometers are widely used in laboratories and industry, the ice-water mixture is usually used as cold end compensation for thermocouple thermometer measurement. However, the ice-water mixture has disadvantages, such as complex manufacturing process, short use time, and unstable internal temperature field. The zero-temperature thermostat can replace the traditional ice water mixture to provide a stable temperature field environment. However, there is no suitable measurement method that can evaluate the zero-degree thermostat to meet the measurement requirements of thermocouple thermometer. Therefore, comparative experiments on temperature deviation, volatility, axial temperature field uniformity, radial temperature field uniformity, and load characteristics of the ice-water mixture and the zero-temperature thermostat are evaluated. In addition, the uncertainty of the zero-temperature thermostat and the ice water mixture is also proposed. The results reveal that the measurement results of temperature deviation, volatility, axial temperature field uniformity and load characteristic of the zero-temperature thermostat is smaller than that of the ice water mixture. Meanwhile, the uncertainty results also reveal that the zero-temperature thermostat is more stable than the ice water mixture. This study provides a comprehensive method for evaluating the performance of zero temperature thermostats, which can be used to verify the accuracy of the instrument and ensures the reliability of the thermocouple thermometers measurement, and promotes the development of zero temperature thermostat in temperature measurement field. [ABSTRACT FROM AUTHOR]

Phosphorylated mammalian target of rapamycin (p-mTOR) is a promising prognostic marker in many types of cancer. However, its survival benefit in patients with breast carcinoma remains unknown. The aim of the present study was to assess the relationship between p-mTOR expression and prognosis in breast carcinoma based on a systematic review and meta-analysis.Electronic databases (including Pubmed, Embase, ISI web of science, and Cochrane Library) were searched up to November 24, 2015. The outcome measures were hazard ratios (HRs) with 95% confidence interval (CI) for the association between the prognosis of breast carcinoma patients and p-mTOR expression. Primary end points were disease-free survival (DFS), overall survival (OS), and recurrence-free survival (RFS). Statistical analysis was performed with STATA 12.0.Nine cohort studies including 3051 patients met full eligibility criteria. The pooled HRs (95% CI) for OS, DFS, and RFS were 0.84 (0.27-2.63), 0.71 (0.40-1.23), and 0.48 (0.20-1.18), respectively.Our findings suggested that p-mTOR overexpression was not significantly related to prognosis in breast carcinoma regarding OS and disease recurrence. Prospective studies are warranted to examine the association between p-mTOR expression and survival outcomes in breast carcinoma.

Cellular processes such as cell cycle progression, mitosis, apoptosis, and cell migration are characterized by well-defined events that are modulated as a function of time. Measuring these events in the context of time and its perturbation by small molecule compounds and RNAi can provide mechanistic information about cellular pathways being affected. We have used impedance-based time-dependent cell response profiling (TCRP) to measure and characterize cellular responses to antimitotic compounds or siRNAs. Our findings indicate that small molecule perturbation of mitosis leads to unique TCRP. We have further used this unique TCRP signature to screen 119 595 compound library and identified novel antimitotic compounds based on clustering analysis of the TCRPs. Importantly, 113 of the 117 hit compounds in the TCRP antimitotic cluster were confirmed as antimitotic based on independent assays, thus establishing the robust predictive nature of this profiling approach. In addition, potent and novel agents that induce mitotic arrest either by directly interfering with tubulin polymerization or by other mechanisms were identified. The TCRP approach allows for a practical and unbiased phenotypic profiling and screening tool for small molecule and RNAi perturbation of specific cellular pathways and time resolution of the TCRP approach can serve as a complement for other existing multidimensional profiling approaches. 10.1021/ac1007877