An ensemble deep learning model for predicting minimum inhibitory concentrations of antimicrobial peptides against pathogenic bacteria.

The rise of antibiotic resistance necessitates effective alternative therapies. Antimicrobial peptides (AMPs) are promising due to their broad inhibitory effects. This study focuses on predicting the minimum inhibitory concentration (MIC) of AMPs against whom-priority pathogens: Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922, and Pseudomonas aeruginosa ATCC 27853. We developed a comprehensive regression model integrating AMP sequence-based and genomic features. Using eight AI-based architectures, including deep learning with protein language model embeddings, we created an ensemble model combining bi-directional long short-term memory (BiLSTM), convolutional neural network (CNN), and multi-branch model (MBM). The ensemble model showed superior performance with Pearson correlation coefficients of 0.756, 0.781, and 0.802 for the bacterial strains, demonstrating its accuracy in predicting MIC values. This work sets a foundation for future studies to enhance model performance and advance AMP applications in combating antibiotic resistance.

Comparative analysis of readmission rates and outcomes: Sleeve gastrectomy with versus without Nissen fundoplication using a National Database.

Laparoscopic sleeve gastrectomy (LSG) is the most frequently performed bariatric procedure. To study the safety of LSG done with Nissen Fundoplication (NF) in patients affected by obesity and GERD and assess the complication rate. A retrospective cohort study using the Nationwide Readmissions Database from 2016 to 2019. A total of 236111 patients underwent LSG with and without NF. A matched cohort of 1096 without NF and 548 with NF was obtained. The median age of patients was 47 years old. Median length of hospital stay was higher in the LSG with NF group. Median total charge was higher in the LSG with NF group. There was no statistically significant difference in 30-day readmission rates in patients with obesity and GERD who received LSG with NF compared to those who received LSG alone. Complications after both procedures were low, which highlights the safety of both procedures.

A Study of Disease Prognosis in Lung Adenocarcinoma Using Single-Cell Decomposition and Immune Signature Analysis.

Background: The development of tumors is a highly complex process that entails numerous interactions and intricate relationships between the host immune system and cancer cells. It has been demonstrated in studies that the treatment response of patients can be correlated with the tumor microenvironment (TME). Consequently, the examination of diverse immune profiles within the TME can facilitate the elucidation of tumor development and the development of advantageous models for diagnoses and prognoses. Methods: In this study, we utilized a single-cell decomposition method to analyze the relationships between cell proportions and immune signatures in lung adenocarcinoma (LUAD) patients. Results: Our findings indicate that specific immune cell populations and immune signatures are significantly associated with patient prognosis. By identifying poor prognosis signatures (PPS), we reveal the critical role of immune profiles and cellular composition in disease outcomes, emphasizing their diagnostic potential for predicting patient prognosis. Conclusions: This study highlights the importance of immune signatures and cellular composition, which may serve as valuable biomarkers for disease prognosis in LUAD patients.

Bariatric surgery: trends in utilization, complications, conversions and revisions.

BACKGROUND: Sleeve gastrectomy (SG) increased in popularity after 2010 but recent data suggest it has concerning rates of gastroesophageal reflux and need for conversions. This study aims to evaluate recent trends in the utilization of bariatric procedures, associated complications, and conversions using an administrative claims database in the United States. METHODS: We included adults who had bariatric procedures from 2000 to 2020 with continuous enrollment for at least 6 months in the MarketScan Commercial Claims and Encounters database. Index bariatric procedures and subsequent revisions or conversions were identified using CPT codes. Baseline comorbidities and postoperative complications were identified with ICD-9-CM and ICD-10 codes. Cumulative incidences of complications were estimated at 30-days, 6-months, and 1-year and compared with stabilized inverse probability of treatment weighted Kaplan-Meier analysis. RESULTS: We identified 349,411 bariatric procedures and 5521 conversions or revisions. The sampled SG volume appeared to begin declining in 2018 while Roux-en-Y gastric bypass (RYGB) remained steady. Compared to RYGB, SG was associated with lower 1-year incidence [aHR, (95% CIs)] for 30-days readmission [0.65, (0.64-0.68)], dehydration [0.75, (0.73-0.78)], nausea or vomiting [0.70, (0.69-0.72)], dysphagia [0.55, (0.53-0.57)], and gastrointestinal hemorrhage [0.43, (0.40-0.46)]. Compared to RYGB, SG was associated with higher 1-year incidence [aHR, (95% CIs)] of esophagogastroduodenoscopy [1.13, (1.11-1.15)], heartburn [1.38, (1.28-1.49)], gastritis [4.28, (4.14-4.44)], portal vein thrombosis [3.93, (2.82-5.48)], and hernias of all types [1.36, (1.34-1.39)]. There were more conversions from SG to RYGB than re-sleeving procedures. SG had a significantly lower 1-year incidence of other non-revisional surgical interventions when compared to RYGB. CONCLUSIONS: The overall volume of bariatric procedures within the claims database appeared to be declining over the last 10 years. The decreasing proportion of SG and the increasing proportion of RYGB suggest the specific complications of SG may be driving this trend. Clearly, RYGB should remain an important tool in the bariatric surgeon's armamentarium.

Evaluation of 30-day outcomes for open ventral hernia repair using self-gripping versus nonself-gripping mesh.

BACKGROUND: The use of mesh is standard of care for large ventral hernias repaired on an elective basis. The most used type of mesh includes synthetic polypropylene mesh; however, there has been an increase in the usage of a new polyester self-gripping mesh, and there are limited data regarding its efficacy for ventral hernia. The purpose of the study is to determine whether there is a difference in surgical site occurrence (SSO), surgical site infection (SSI), surgical site occurrence requiring procedural intervention (SSOPI), and recurrence at 30 days after ventral hernia repair (VHR) using self-gripping (SGM) versus non-self-gripping mesh (NSGM). METHODS: We performed a retrospective study from January 2014 to April 2022 using the Abdominal Core Health Quality Collaborative (ACHQC). We collected data on patients over 18 years of age who underwent elective open VHR using SGM or NSGM and whom had 30-day follow-up. Propensity matching was utilized to control for variables including hernia width, body mass index, age, ASA, and mesh location. Data were analyzed to identify differences in SSO, SSI, SSOPI, and recurrence at 30 days. RESULTS: 9038 patients were identified. After propensity matching, 1766 patients were included in the study population. Patients with SGM had similar demographic and clinical characteristics compared to NSGM. The mean hernia width to mesh width ratio was 8 cm:18 cm with NSGM and 7 cm:15 cm with SGM (p = 0.63). There was no difference in 30-day rates of recurrence, SSI or SSO. The rate of SSOPI was also found to be 5.4% in the nonself-gripping group compared to 3.1% in the self-gripping mesh group (p < .005). There was no difference in patient-reported outcomes at 30 days. CONCLUSIONS: In patients undergoing ventral hernia repair with mesh, self-gripping mesh is a safe type of mesh to use. Use of self-gripping mesh may be associated with lower rates of SSOPI when compared to nonself-gripping mesh.

Updates in Bariatric Surgery.

Bariatric surgery is currently the most effective long-term treatment for morbid obesity as well as type-2 diabetes mellitus. The field of metabolic and bariatric surgery has seen tremendous growth over the past decade with dramatically reduced risks. This article aims to provide an update on bariatric surgery, highlighting the latest outcomes, improvements, and challenges in the field. Recently, the American Society of Metabolic and Bariatric Surgery (ASMBS) and the International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) released a major update to the indications for bariatric surgery at BMI ≥35 kg/m2 regardless of co-morbidities and 30-34.9 kg/m2 with obesity-related comorbidities. Sleeve gastrectomy has emerged as the most popular bariatric procedure in the last 10 years with its remarkable efficacy and safety profile. The implementation of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) and Enhanced Recovery After Surgery (ERAS) protocols have significantly improved the quality of care for all bariatric patients. The recent introduction and FDA approval of Glucagon-Like Peptide-1 (GLP-1) agonists for chronic obesity has garnered significant media coverage and popularity, but no guidelines exist regarding its use in relation to bariatric surgery. This update underscores the need for tailored approaches, ongoing research, and the integration of evidence-based medicine and innovations to enhance patient care.

Assessing Non-Specific Neck Pain through Pose Estimation from Images Based on Ensemble Learning.

BACKGROUND: Mobile phones, laptops, and computers have become an indispensable part of our lives in recent years. Workers may have an incorrect posture when using a computer for a prolonged period of time. Using these products with an incorrect posture can lead to neck pain. However, there are limited data on postures in real-life situations. METHODS: In this study, we used a common camera to record images of subjects carrying out three different tasks (a typing task, a gaming task, and a video-watching task) on a computer. Different artificial intelligence (AI)-based pose estimation approaches were applied to analyze the head's yaw, pitch, and roll and coordinate information of the eyes, nose, neck, and shoulders in the images. We used machine learning models such as random forest, XGBoost, logistic regression, and ensemble learning to build a model to predict whether a subject had neck pain by analyzing their posture when using the computer. RESULTS: After feature selection and adjustment of the predictive models, nested cross-validation was applied to evaluate the models and fine-tune the hyperparameters. Finally, the ensemble learning approach was utilized to construct a model via bagging, which achieved a performance with 87% accuracy, 92% precision, 80.3% recall, 95.5% specificity, and an AUROC of 0.878. CONCLUSIONS: We developed a predictive model for the identification of non-specific neck pain using 2D video images without the need for costly devices, advanced environment settings, or extra sensors. This method could provide an effective way for clinically evaluating poor posture during real-world computer usage scenarios.

Predicting readmission after bariatric surgery using machine learning.

BACKGROUND: While bariatric surgery is an effective method for achieving long-term weight loss, postoperative readmissions are associated with negative clinical outcomes and significant costs. OBJECTIVES: We aimed to use machine learning (ML) algorithms to predict readmissions and compare results to logistic regression. SETTING: Hospitals participating in the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program, United States. METHODS: Patients who underwent sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB), and biliopancreatic diversion with duodenal switch between 2016 and 2020 were selected from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) database. Patient variables reported by the MBSAQIP database were analyzed by ML algorithms random forest (RF), gradient boosting (XGB), and deep neural networks (NN), and the results of the predictive models were compared to logistic regression using area under the receiver operating characteristic curve (AUROC). RESULTS: Our study included 863,348 patients, of which 39,068 (4.52%) were readmitted. AUROC scores were XGB .785 (95% CI .784-.786), RF .785 (95% CI .784-.785), and NN .754 (95% CI .753-.754), compared with .62 (95% CI .62-.621) for logistic regression (LR) (P < .001). The sensitivity and specificity for XGB, the best performing model, were 73.81% and 70%, compared with 52.94% and 70% for logistic regression. The most important variables were intervention or reoperation prior to discharge, unplanned ICU admission, initial procedure, and the intraoperative transfusion. CONCLUSIONS: ML demonstrates significant advantages over logistic regression when predicting 30-day readmission following bariatric surgery. With external validation, models could identify the best candidates for early discharge or targeted postdischarge resources.

Application of machine learning to predict postoperative gastrointestinal bleed in bariatric surgery.

BACKGROUND: Postoperative gastrointestinal bleeding (GIB) is a rare but serious complication of bariatric surgery. The recent rise in extended venous thromboembolism regimens as well as outpatient bariatric surgery may increase the risk of postoperative GIB or lead to delay in diagnosis. This study seeks to use machine learning (ML) to create a model that predicts postoperative GIB to aid surgeon decision-making and improve patient counseling for postoperative bleeds. METHODS: The Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) database was used to train and validate three types of ML methods: random forest (RF), gradient boosting (XGB), and deep neural networks (NN), and compare them with logistic regression (LR) regarding postoperative GIB. The dataset was split using fivefold cross-validation into training and validation sets, in an 80/20 ratio. The performance of the models was assessed using area under the receiver operating characteristic curve (AUROC) and compared with the DeLong test. Variables with the strongest effect were identified using Shapley additive explanations (SHAP). RESULTS: The study included 159,959 patients. Postoperative GIB was identified in 632 (0.4%) patients. The three ML methods, RF (AUROC 0.764), XGB (AUROC 0.746), and NN (AUROC 0.741) all outperformed LR (AUROC 0.709). The best ML method, RF, was able to predict postoperative GIB with a specificity and sensitivity of 70.0% and 75.4%, respectively. Using DeLong testing, the difference between RF and LR was determined to be significant with p < 0.01. Type of bariatric surgery, pre-op hematocrit, age, duration of procedure, and pre-op creatinine were the 5 most important features identified by ML retrospectively. CONCLUSIONS: We have developed a ML model that outperformed LR in predicting postoperative GIB. Using ML models for risk prediction can be a helpful tool for both surgeons and patients undergoing bariatric procedures but more interpretable models are needed.

Corrigendum: Systolic blood pressure as the mediator of the effect of early menarche on the risk of coronary artery disease: A Mendelian randomization study.

[This corrects the article DOI: 10.3389/fcvm.2022.1023355.].

Hypertension as a Novel Link for Shared Heritability in Age at Menarche and Cardiometabolic Traits.

CONTEXT: Extremely early age at menarche, also called precocious puberty, has been associated with various cardiometabolic traits, but their shared heritability remains unclear. OBJECTIVES: This work aimed to identify new shared genetic variants and their pathways for age at menarche and cardiometabolic traits and to investigate the influence of central precocious puberty on childhood cardiometabolic traits. METHODS: Using the conjunction false discovery rate method, this study analyzed genome-wide association study data from the menarche-cardiometabolic traits among 59 655 females of Taiwanese ancestry and systemically investigated pleiotropy between age at menarche and cardiometabolic traits. To support the novel hypertension link, we used the Taiwan Puberty Longitudinal Study (TPLS) to investigate the influence of precocious puberty on childhood cardiometabolic traits. RESULTS: We discovered 27 novel loci, with an overlap between age at menarche and cardiometabolic traits, including body fat and blood pressure. Among the novel genes discovered, SEC16B, CSK, CYP1A1, FTO, and USB1 are within a protein interaction network with known cardiometabolic genes, including traits for obesity and hypertension. These loci were confirmed through demonstration of significant changes in the methylation or expression levels of neighboring genes. Moreover, the TPLS provided evidence regarding a 2-fold higher risk of early-onset hypertension that occurred in girls with central precocious puberty. CONCLUSION: Our study highlights the usefulness of cross-trait analyses for identifying shared etiology between age at menarche and cardiometabolic traits, especially early-onset hypertension. The menarche-related loci may contribute to early-onset hypertension through endocrinological pathways.

Comparison of Robotic, Laparoscopic, and Open Unilateral Repair of Non-recurrent Inguinal Hernia.

BACKGROUND: There is a paucity of data comparing open, robotic, and laparoscopic approaches on unilateral, non-recurrent inguinal hernias. Our study presents a large, retrospective triple-arm outcome analysis between robotic, laparoscopic, and open unilateral, non-recurrent inguinal hernia repairs at a single institution. METHODS: 706 patients who underwent elective, non-recurrent inguinal hernia repair performed by 8 general surgeons at a single institution from 2016 to 2019 were reviewed retrospectively. Patient baseline characteristics, operative times, resident involvement, and postoperative outcomes were analyzed for all repair types. A cost analysis of the different procedures was performed. RESULTS: There were 305 laparoscopic repairs, 207 robotic repairs, and 194 open repairs. Open and laparoscopic repairs were performed on patients who were older (p =< .001) and with a higher Charlson Comorbidity Index (p =< .001). Patient BMI was higher in minimally invasive repair than open repair (P = .021). There were no significant differences in complication rates on pairwise analysis. Robotic and open repairs had significantly longer operative times than laparoscopic repairs (P < .001). There was less resident involvement in robotic repair than with the other approaches (P < .001). Resident involvement was associated with shorter OR times (P = .001) and no significant difference in postoperative complications. There was a trend over the study period toward faster operative times and more robotic repair. Robotic repair is the most expensive repair, followed by laparoscopic and open repairs. CONCLUSION: All 3 repair techniques can be performed without significant differences in outcomes. The technique utilized should be based on surgeon preference and patient characteristics.

Anti-Angiogenetic and Anti-Lymphangiogenic Effects of a Novel 2-Aminobenzimidazole Derivative, MFB.

Background and Purpose: Benzimidazoles have attracted much attention over the last few decades due to their broad-spectrum pharmacological properties. Increasing evidence is showing the potential use of benzimidazoles as anti-angiogenic agents, although the mechanisms that impact angiogenesis remain to be fully defined. In this study, we aim to investigate the anti-angiogenic mechanisms of MFB, a novel 2-aminobenzimidazole derivative, to develop a novel angiogenesis inhibitor. Experimental Approach: MTT, BrdU, migration and invasion assays, and immunoblotting were employed to examine MFB's effects on vascular endothelial growth factor (VEGF)-induced endothelial cell proliferation, migration, invasion, as well as signaling molecules activation. The anti-angiogenic effects of MFB were analyzed by tube formation, aorta ring sprouting, and matrigel plug assays. We also used a mouse model of lung metastasis to determine the MFB's anti-metastatic effects. Key Results: MFB suppressed cell proliferation, migration, invasion, and endothelial tube formation of VEGF-A-stimulated human umbilical vascular endothelial cells (HUVECs) or VEGF-C-stimulated lymphatic endothelial cells (LECs). MFB suppressed VEGF-A and VEGF-C signaling in HUVECs or LECs. In addition, MFB reduced VEGF-A- or tumor cells-induced neovascularization in vivo. MFB also diminished B16F10 melanoma lung metastasis. The molecular docking results further showed that MFB may bind to VEGFR-2 rather than VEGF-A with high affinity. Conclusions and Implications: These observations indicated that MFB may target VEGF/VEGFR signaling to suppress angiogenesis and lymphangiogenesis. It also supports the role of MFB as a potential lead in developing novel agents for the treatment of angiogenesis- or lymphangiogenesis-associated diseases and cancer.

Systolic blood pressure as the mediator of the effect of early menarche on the risk of coronary artery disease: A Mendelian randomization study.

Background: Menarche timing may not be directly associated with the risk of coronary artery disease (CAD). Therefore, we investigated the roles of metabolic factors in explaining the effect of age at menarche on CAD risk. Methods: We identified women with age at menarche and CAD by using three analytical methods: Mendelian randomization (MR), logistic regression analysis, and Cox proportional hazard regression. The first two analyses were performed in the Taiwan Biobank (N = 71,923) study, and the last analysis was performed in the Chin-Shan Community Cardiovascular Cohort study (N = 1,598). We further investigated the role of metabolic factors in mediating the effect of age at menarche on CAD risk by using three complementary methods with mediation analyses. Results: One standard deviation of earlier age at menarche was associated with a 2% higher CAD risk [odds ratio = 1.02, 95% confidence interval (CI) = 1.001-1.03] in the MR analysis, an 11% higher risk (odds ratio = 1.11, 95% CI = 1.02-1.21) in the logistic regression analysis, and a 57% higher risk (hazard ratio = 1.57, 95% CI = 1.12-2.19) in the Cox proportional hazard regression. All the analyses consistently supported the role of systolic blood pressure in mediating this effect. The MR results indicated that 29% (95% CI = 26%-32%) of the effect of genetically predicted earlier age at menarche on CAD risk was mediated by genetically predicted systolic blood pressure. Conclusion: The results obtained using different analytical methods suggest that interventions aimed at lowering systolic blood pressure can reduce the cases of CAD attributable to earlier age at menarche.

Targeted next-generation sequencing for genetic variants of left ventricular mass status among community-based adults in Taiwan.

Background: Left ventricular mass is a highly heritable disease. Previous studies have suggested common genetic variants to be associated with left ventricular mass; however, the roles of rare variants are still unknown. We performed targeted next-generation sequencing using the TruSight Cardio panel, which provides comprehensive coverage of 175 genes with known associations to 17 inherited cardiac conditions. Methods: We conducted next-generation sequencing using the Illumina TruSight Cardiomyopathy Target Genes platform using the 5% and 95% extreme values of left ventricular mass from community-based participants. After removing poor-quality next-generation sequencing subjects, including call rate <98% and Mendelian errors, 144 participants were used for the analysis. We performed downstream analysis, including quality control, alignment, coverage length, and annotation; after setting filtering criteria for depths more than 60, we found a total of 144 samples and 165 target genes for further analysis. Results: Of the 12,287 autosomal variants, most had minor allele frequencies of <1% (rare frequency), and variants had minor allele frequencies ranging from 1% to 5%. In the multi-allele variant analyses, 16 loci in 15 genes were significant using the false discovery rate of less than .1. In addition, gene-based analyses using continuous and binary outcomes showed that three genes (CASQ2, COL5A1, and FXN) remained to be associated with left ventricular mass status. One single-nucleotide polymorphism (rs7538337) was enriched for the CASQ2 gene expressed in aorta artery (p = 4.6 × 10-18), as was another single-nucleotide polymorphism (rs11103536) for the COL5A1 gene expressed in aorta artery (p = 2.0 × 10-9). Among the novel genes discovered, CASQ2, COL5A1, and FXN are within a protein-protein interaction network with known cardiovascular genes. Conclusion: We clearly demonstrated candidate genes to be associated with left ventricular mass. Further studies to characterize the target genes and variants for their functional mechanisms are warranted.

dbPTM in 2022: an updated database for exploring regulatory networks and functional associations of protein post-translational modifications.

Protein post-translational modifications (PTMs) play an important role in different cellular processes. In view of the importance of PTMs in cellular functions and the massive data accumulated by the rapid development of mass spectrometry (MS)-based proteomics, this paper presents an update of dbPTM with over 2 777 000 PTM substrate sites obtained from existing databases and manual curation of literature, of which more than 2 235 000 entries are experimentally verified. This update has manually curated over 42 new modification types that were not included in the previous version. Due to the increasing number of studies on the mechanism of PTMs in the past few years, a great deal of upstream regulatory proteins of PTM substrate sites have been revealed. The updated dbPTM thus collates regulatory information from databases and literature, and merges them into a protein-protein interaction network. To enhance the understanding of the association between PTMs and molecular functions/cellular processes, the functional annotations of PTMs are curated and integrated into the database. In addition, the existing PTM-related resources, including annotation databases and prediction tools are also renewed. Overall, in this update, we would like to provide users with the most abundant data and comprehensive annotations on PTMs of proteins. The updated dbPTM is now freely accessible at https://awi.cuhk.edu.cn/dbPTM/.

Identification of Differentially Expressed Genes in Different Glioblastoma Regions and Their Association with Cancer Stem Cell Development and Temozolomide Response.

The molecular heterogeneity of gene expression profiles of glioblastoma multiforme (GBM) are the most important prognostic factors for tumor recurrence and drug resistance. Thus, the aim of this study was to identify potential target genes related to temozolomide (TMZ) resistance and GBM recurrence. The genomic data of patients with GBM from The Cancer Genome Atlas (TCGA; 154 primary and 13 recurrent tumors) and a local cohort (29 primary and 4 recurrent tumors), samples from different tumor regions from a local cohort (29 tumor and 25 peritumoral regions), and Gene Expression Omnibus data (GSE84465, single-cell RNA sequencing; 3589 cells) were included in this study. Critical gene signatures were identified based an analysis of differentially expressed genes (DEGs). DEGs were further used to evaluate gene enrichment levels among primary and recurrent GBMs and different tumor regions through gene set enrichment analysis. Protein-protein interactions (PPIs) were incorporated into gene regulatory networks to identify the affected metabolic pathways. The enrichment levels of 135 genes were identified in the peritumoral regions as being risk signatures for tumor recurrence. Fourteen genes (DVL1, PRKACB, ARRB1, APC, MAPK9, CAMK2A, PRKCB, CACNA1A, ERBB4, RASGRF1, NF1, RPS6KA2, MAPK8IP2, and PPM1A) derived from the PPI network of 135 genes were upregulated and involved in the regulation of cancer stem cell (CSC) development and relevant signaling pathways (Notch, Hedgehog, Wnt, and MAPK). The single-cell data analysis results indicated that 14 key genes were mainly expressed in oligodendrocyte progenitor cells, which could produce a CSC niche in the peritumoral region. The enrichment levels of 336 genes were identified as biomarkers for evaluating TMZ resistance in the solid tumor region. Eleven genes (ARID5A, CDC42EP3, CDKN1A, FLT3, JUNB, MAP2K3, MYBPC2, RGS14, RNASEK, TBC1D30, and TXNDC11) derived from the PPI network of 336 genes were upregulated and may be associated with a high risk of TMZ resistance; these genes were identified in both the TCGA and local cohorts. Furthermore, the expression patterns of ARID5A, CDKN1A, and MAP2K3 were identical to the gene signatures of TMZ-resistant cell lines. The identified enrichment levels of the two gene sets expressed in tumor and peritumoral regions are potentially helpful for evaluating TMZ resistance in GBM. Moreover, these key genes could be used as biomarkers, potentially providing new molecular strategies for GBM treatment.

Detection of PD-L1 Expression in Temozolomide-Resistant Glioblastoma by Using PD-L1 Antibodies Conjugated with Lipid­Coated Superparamagnetic Iron Oxide.

PURPOSE: Targeted superparamagnetic iron oxide (SPIO) nanoparticles are a promising tool for molecular magnetic resonance imaging (MRI) diagnosis. Lipid-coated SPIO nanoparticles have a nonfouling property that can reduce nonspecific binding to off-target cells and prevent agglomeration, making them suitable contrast agents for molecular MRI diagnosis. PD-L1 is a poor prognostic factor for patients with glioblastoma. Most recurrent glioblastomas are temozolomide resistant. Diagnostic probes targeting PD-L1 could facilitate early diagnosis and be used to predict responses to targeted PD-L1 immunotherapy in patients with primary or recurrent glioblastoma. We conjugated lipid-coated SPIO nanoparticles with PD-L1 antibodies to identify PD-L1 expression in glioblastoma or temozolomide-resistant glioblastoma by using MRI. METHODS: The synthesized PD-L1 antibody-conjugated SPIO (PDL1-SPIO) nanoparticles were characterized using dynamic light scattering, zeta potential assays, transmission electron microscopy images, Prussian blue assay, in vitro cell affinity assay, and animal MRI analysis. RESULTS: PDL1-SPIO exhibited a specific binding capacity to PD-L1 of the mouse glioblastoma cell line (GL261). The presence and quantity of PDL1-SPIO in temozolomide-resistant glioblastoma cells and tumor tissue were confirmed through Prussian blue staining and in vivo T2* map MRI, respectively. CONCLUSION: This is the first study to demonstrate that PDL1-SPIO can specifically target temozolomide-resistant glioblastoma with PD-L1 expression in the brain and can be quantified through MRI analysis, thus making it suitable for the diagnosis of PD-L1 expression in temozolomide-resistant glioblastoma in vivo.

Maternal Vegetable and Fruit Consumption during Pregnancy and Its Effects on Infant Gut Microbiome.

Maternal nutrition intake during pregnancy may affect the mother-to-child transmission of bacteria, resulting in gut microflora changes in the offspring, with long-term health consequences in later life. Longitudinal human studies are lacking, as only a small amount of studies showing the effect of nutrition intake during pregnancy on the gut microbiome of infants have been performed, and these studies have been mainly conducted on animals. This pilot study explores the effects of high or low fruit and vegetable gestational intake on the infant microbiome. We enrolled pregnant women with a complete 3-day dietary record and received postpartum follow-up. The 16S rRNA gene sequence was used to characterize the infant gut microbiome at 2 months (n = 39). Principal coordinate analysis ordination revealed that the infant gut microbiome clustered differently for high and low maternal fruit and vegetable consumption (p < 0.001). The linear discriminant analysis effect size and feature selection identified 6 and 17 taxa from both the high and low fruit and vegetable consumption groups. Among the 23 abundant taxa, we observed that six maternal intake nutrients were associated with nine taxa (e.g., Erysipelatoclostridium, Isobaculum, Lachnospiraceae, Betaproteobacteria, Burkholderiaceae, Sutterella, Clostridia, Clostridiales, and Lachnoclostridium). The amount of gestational fruit and vegetable consumption is associated with distinct changes in the infant gut microbiome at 2 months of age. Therefore, strategies involving increased fruit and vegetable consumption during pregnancy should be employed for modifying the gut microbiome early in life.

Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion.

This study is to identify potential multiomics biomarkers for the early detection of the prognostic recurrence of PC patients. A total of 494 prostate adenocarcinoma (PRAD) patients (60-recurrent included) from the Cancer Genome Atlas (TCGA) portal were analyzed using the autoencoder model and similarity network fusion. Then, multiomics panels were constructed according to the intersected omics biomarkers identified from the two models. Six intersected omics biomarkers, TELO2, ZMYND19, miR-143, miR-378a, cg00687383 (MED4), and cg02318866 (JMJD6; METTL23), were collected for multiomics panel construction. The difference between the Kaplan-Meier curves of high and low recurrence-risk groups generated from the multiomics panel achieved p-value = 5.33 × 10-9, which is better than the former study (p-value = 5 × 10-7). Additionally, when evaluating the selected multiomics biomarkers with clinical information (Gleason score, age, and cancer stage), a high-performance prediction model was generated with C-index = 0.713, p-value = 2.97 × 10-15, and AUC = 0.789. The risk score generated from the selected multiomics biomarkers worked as an effective indicator for the prediction of PRAD recurrence. This study helps us to understand the etiology and pathways of PRAD and further benefits both patients and physicians with potential prognostic biomarkers when making clinical decisions after surgical treatment.