Scalp acupuncture guidance for identifying the optimal site for transcranial electrical stimulation of the hand.

Transcranial electrical stimulation (tES) often targets the EEG-guided C3/C4 area that may not accurately represent M1 for hand muscles. This study aimed to determine if the neuroanatomy-based scalp acupuncture-guided site (AC) was a more effective spot than the C3 site for neuromodulation. Fifteen healthy subjects received one 20-minute session of high-definition transcranial alternating current stimulation (HD-tACS) intervention (20 Hz at 2 mA) at the AC or C3 sites randomly with a 1-week washout period. Subjects performed ball-squeezing exercises with the dominant hand during the HD-tACS intervention. The AC site was indiscernible from the finger flexor hotspot detected by TMS. At the baseline, the MEP amplitude from finger flexors was greater with less variability at the AC site than at the C3 site. HD-tACS intervention at the AC site significantly increased the MEP amplitude. However, no significant changes were observed after tACS was applied to the C3 site. Our results provide evidence that HD-tACS at the AC site produces better neuromodulation effects on the flexor digitorum superficialis (FDS) muscle compared to the C3 site. The AC localization approach can be used for future tES studies.

Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer.

BACKGROUND: Synchronous liver metastasis (SLM) is a significant contributor to morbidity in colorectal cancer (CRC). There are no effective predictive device integration algorithms to predict adverse SLM events during the diagnosis of CRC. AIM: To explore the risk factors for SLM in CRC and construct a visual prediction model based on gray-level co-occurrence matrix (GLCM) features collected from magnetic resonance imaging (MRI). METHODS: Our study retrospectively enrolled 392 patients with CRC from Yichang Central People's Hospital from January 2015 to May 2023. Patients were randomly divided into a training and validation group (3:7). The clinical parameters and GLCM features extracted from MRI were included as candidate variables. The prediction model was constructed using a generalized linear regression model, random forest model (RFM), and artificial neural network model. Receiver operating characteristic curves and decision curves were used to evaluate the prediction model. RESULTS: Among the 392 patients, 48 had SLM (12.24%). We obtained fourteen GLCM imaging data for variable screening of SLM prediction models. Inverse difference, mean sum, sum entropy, sum variance, sum of squares, energy, and difference variance were listed as candidate variables, and the prediction efficiency (area under the curve) of the subsequent RFM in the training set and internal validation set was 0.917 [95% confidence interval (95%CI): 0.866-0.968] and 0.09 (95%CI: 0.858-0.960), respectively. CONCLUSION: A predictive model combining GLCM image features with machine learning can predict SLM in CRC. This model can assist clinicians in making timely and personalized clinical decisions.

FAK inhibitors in cancer, a patent review - an update on progress.

INTRODUCTION: Focal adhesion kinase (FAK) is a cytoplasmic non-receptor tyrosine kinase over-expressed in various malignancies which is related to various cellular functions such as adhesion, metastasis and proliferation. AREAS COVERED: There is growing evidence that FAK is a promising therapeutic target for designing inhibitors by regulating the downstream pathways of FAK. Some potential FAK inhibitors have entered clinical phase research. EXPERT OPINION: FAK could be an effective target in medicinal chemistry research and there were a variety of FAKIs have been patented recently. Here, we updated an overview of design, synthesis and structure-activity relationship of chemotherapeutic FAK inhibitors (FAKIs) from 2017 until now based on our previous work. We hope our efforts can broaden the understanding of FAKIs and provide new ideas and insights for future cancer treatment from medicinal chemistry point of view.

Physiology, Biochemistry, and Transcriptomics Jointly Reveal the Phytotoxicity Mechanism of Acetochlor on Pisum sativum L.

Acetochlor, as a commonly used pre-emergent herbicide, can be toxic to crops and affect production if used improperly. However, the toxic mechanism of acetochlor on plants is not fully understood. The present study used a combination of transcriptomic analysis and physiological measurements to investigate the effects of short-term (15-day) exposure to different concentrations of acetochlor (1, 10, 20 mg/kg) on the morphology, physiology, and transcriptional levels of pea seedlings, aiming to elucidate the toxic response and resistance mechanisms in pea seedlings under herbicide stress. The results showed that the toxicity of acetochlor to pea seedlings was dose-dependent, manifested as dwarfing and stem base browning with increasing concentrations, especially at 10 mg/kg and above. Analysis of the antioxidant system showed that from the 1 mg/kg treatment, malondialdehyde, superoxide dismutase, peroxidase, and glutathione peroxidase in peas increased with increasing concentrations of acetochlor, indicating oxidative damage. Analysis of the glutathione (GSH) metabolism system showed that under 10 mg/kg treatment, the GSH content of pea plants significantly increased, and GSH transferase activity and gene expression were significantly induced, indicating a detoxification response in plants. Transcriptomic analysis showed that after acetochlor treatment, differentially expressed genes in peas were significantly enriched in the phenylpropane metabolic pathway, and the levels of key metabolites (flavonoids and lignin) were increased. In addition, we found that acetochlor-induced dwarfing of pea seedlings may be related to gibberellin signal transduction. Environ Toxicol Chem 2024;00:1-15. © 2024 SETAC.

SENP1-Mediated HSP90ab1 DeSUMOylation in Cardiomyocytes Prevents Myocardial Fibrosis by Paracrine Signaling.

Myocardial infarction (MI) triggers a poor ventricular remodeling response, but the underlying mechanisms remain unclear. Here, the authors show that sentrin-specific protease 1 (SENP1) is downregulated in post-MI mice and in patients with severe heart failure. By generating cardiomyocyte-specific SENP1 knockout and overexpression mice to assess cardiac function and ventricular remodeling responses under physiological and pathological conditions. Increased cardiac fibrosis in the cardiomyocyte-specific SENP1 deletion mice, associated with increased fibronectin (Fn) expression and secretion in cardiomyocytes, promotes fibroblast activation in response to myocardial injury. Mechanistically, SENP1 deletion in mouse cardiomyocytes increases heat shock protein 90 alpha family class B member 1 (HSP90ab1) SUMOylation with (STAT3) activation and Fn secretion after ventricular remodeling initiated. Overexpression of SENP1 or mutation of the HSP90ab1 Lys72 ameliorates adverse ventricular remodeling and dysfunction after MI. Taken together, this study identifies SENP1 as a positive regulator of cardiac repair and a potential drug target for the treatment of MI. Inhibition of HSP90ab1 SUMOylation stabilizes STAT3 to inhibit the adverse ventricular remodeling response.

Significance and Possible Biological Mechanism for CLDN8 Downregulation in Kidney Renal Clear Cell Carcinoma Tissues.

Background: The clinical role of claudin 8 (CLDN8) in kidney renal clear cell carcinoma (KIRC) remains unclarified. Herein, the expression level and potential molecular mechanisms of CLDN8 underlying KIRC were determined. Methods: High-throughput datasets of KIRC were collected from GEO, ArrayExpress, SRA, and TCGA databases to determine the mRNA expression level of the CLDN8. In-house tissue microarrays and immunochemistry were performed to examine CLDN8 protein expression. A summary receiver operating characteristic curve (SROC) and standardized mean difference (SMD) forest plot were generated using Stata v16.0. Single-cell analysis was conducted to further prove the expression level of CLDN8. A clustered regularly interspaced short palindromic repeats knockout screen analysis was executed to assess the growth impact of CLDN8. Functional enrichment analysis was conducted using the Metascape database. Additionally, single-sample gene set enrichment analysis was implied to explore immune cell infiltration in KIRC. Results: A total of 17 mRNA datasets comprising 1,060 KIRC samples and 452 non-cancerous control samples were included in this study. Additionally, 105 KIRC and 16 non-KIRC tissues were analyzed using in-house immunohistochemistry. The combined SMD was -5.25 (95% confidence interval (CI): -6.13 to -4.37), and CLDN8 downregulation yielded an SROC area under the curve (AUC) close to 1.00 (95% CI: 0.99 - 1.00). CLDN8 downregulation was also confirmed at the single-cell level. Knocking out CLDN8 stimulated KIRC cell proliferation. Lower CLDN8 expression was correlated with worse overall survival of KIRC patients (hazard ratio of CLDN8 downregulation = 1.69, 95% CI: 1.2 - 2.4). Functional pathways associated with CLDN8 co-expressed genes were centered on carbon metabolism obstruction, with key hub genes ACADM, ACO2, NDUFS1, PDHB, SDHD, SUCLA2, SUCLG1, and SUCLG2. Conclusions: CLDN8 is downregulated in KIRC and is considered a potential tumor suppressor. CLDN8 deficiency may promote the initiation and progression of KIRC, potentially in conjunction with metabolic dysfunction.

Corrigendum: High-definition transcranial direct current stimulation for upper extremity rehabilitation in moderate-to-severe ischemic stroke: a pilot study.

[This corrects the article DOI: 10.3389/fnhum.2023.1286238.].

New options for endoscopic treatment of gastric varices.

BACKGROUND: Gastric venous bleeding is one of the most common adverse events in liver cirrhosis. The therapeutic effect of isolated gastric varices is relatively clear. However, there is no appropriate clinical and endoscopic treatment for extensive variceal bleeding in the gastric fundus and body. METHODS: In this patient with non-isolated gastric varices, we decided to perform endoscopic multi-point ligation of the obvious varices in the gastric fundus and body. RESULTS: In this patient, endoscopic treatment of gastric varices with bleeding after surgery achieved a significant therapeutic effect. Reexamination of gastroscopy at 3 months after operation showed that multiple scars were formed in the gastric fundus and fundus, and no obvious varices were found. CONCLUSIONS: For patients with non-isolated gastric varices, endoscopic multi-point ligation is a safe and effective treatment option for the varices with obvious gastric fundus and body.

Machine learning-based CT radiomics enhances bladder cancer staging predictions: A comparative study of clinical, radiomics, and combined models.

BACKGROUND: Predicting the accurate preoperative staging of bladder cancer (BLCA), which markedly affects treatment decisions and patient outcomes, using traditional clinical parameters is challenging. Nevertheless, emerging studies in radiomics, especially machine learning-based computed tomography (CT) image-based radiomics, hold promise in improving stage prediction accuracy in various tumors. However, the comparative performance and clinical utility of models for BLCA are under investigation. PURPOSE: We aimed to investigate the application value of machine learning-based CT radiomics in preoperative staging prediction by comparing the performance of clinical, radiomics, and clinical-radiomics combined models. METHODS: A retrospective cohort of 105 patients with initial BLCA was randomized into training (70%) and testing (30%) cohorts. Radiomics features were extracted from CT images using the optimal feature filter, followed by the application of the least absolute shrinkage and selection operator algorithm for optimum feature selection. Furthermore, machine learning algorithms were used to establish a radiomics model within the training cohort. Independent risk factors for muscle-invasive BLCA (MIBC) obtained by multivariate logistic regression (LR) analysis were separately used to construct a clinical model. For a clinical-radiomics fusion model, radiomics features were combined with clinical parameters. Performance was evaluated based on receiver operating characteristic curves, calibration curves, decision curve analysis (DCA), and standard performance metrics. RESULTS: Patients exhibited a significantly higher age (p = 0.029), larger tumor size (p = 0.01), and an increased neutrophil-to-lymphocyte ratio (NLR; p = 0.045) in the MIBC group than in the NMIBC group. LR analysis revealed age (p = 0.026), tumor size (p = 0.007), and NLR (p = 0.019) as significant predictors for constructing the clinical model. In the testing cohort, the radiomics model, which used an Support Vector Machine classifier, achieved the highest area under the curve (AUC) value of 0.857. The clinical-radiomics model outperformed the remaining two models, with AUC values of 0.958 and 0.893 in the training and testing cohorts, respectively. DeLong's test indicated significant differences between the three models. Calibration curves showed good agreement, and DCA confirmed the superior clinical utility of the clinical-radiomics model. CONCLUSIONS: Machine learning-based CT radiomics combined with clinical parameters was a promising approach in staging BLCA accurately, which outperformed the individual models. Integrating radiomics features with clinical information holds the potential to improve personalized treatment planning and patient outcomes in BLCA.

Early detection of pancreatic cancer in patients with recurrent pancreatitis: A case report.

BACKGROUND: Pancreatic cancer presents a challenge with its low early diagnosis and treatment rates, leading to high metastasis and mortality rates. The median survival time for advanced pancreatic cancer is a mere 3 months. However, there's hope: small pancreatic cancers diagnosed at an early stage (T1) or those less than or equal to 1 cm in diameter boast an impressive 5-year survival rate of nearly 100%. This underscores the critical importance of early pancreatic cancer detection for significantly improving prognosis. CASE SUMMARY: Pancreatic cancer, a malignant tumor of the digestive tract, poses challenges in both diagnosis and treatment due to its occult and atypical clinical symptoms. Clinically, patients with recurrent pancreatitis should be vigilant, as it may be indicative of pancreatic cancer, particularly in middle-aged and elderly patients. Here, we presented the case of a patient who experienced recurrent acute pancreatitis within a span of 2 months. During the initial episode of pancreatitis, routine imaging failed to identify the cause of pancreatic cancer. However, upon recurrence of acute pancreatitis, endoscopic ultrasonography (EUS) revealed a space-occupying lesion approximately 1 cm in size in the pancreatic body. Subsequent EUS coupled with fine-needle aspiration examination demonstrated atypical pancreatic gland epithelium. Ultimately, the patient underwent surgery and was diagnosed with an intraductal papillary mucinous tumor of the pancreas (severe epithelial dysplasia, focal cancer). CONCLUSION: We recommend EUS for patients with recurrent pancreatitis of unknown etiology to exclude early pancreatic cancer.

Tailoring aberration-free photonic nanojets through the illumination of dielectric cylinders using cylindrical vector beams.

This study explores the manipulation of photonic nanojets (PNJs) via axial illumination of cylindrical dielectric particles with cylindrical vector beams (CVBs). The edge diffraction effect of cylindrical particles is harnessed to achieve the near-field focusing of CVBs, minimizing the spherical aberration's impact on the quality of the PNJ. By discussing how beam width, refractive index, and particle length affect PNJs under radially polarized incidence, a simple and effective approach is demonstrated to generate rod-like PNJs with uniform transmission distances and super-diffraction-limited PNJs with pure longitudinal polarization. Azimuthal polarization, on the other hand, generates tube-like PNJs. These PNJs maintain their performance across scale. Combining edge diffraction with CVBs offers innovative PNJ modulation schemes, paving the way for potential applications in particle trapping, super-resolution imaging, photo-lithography, and advancing mesotronics and related fields.

Potential diagnostic biomarkers for immunogenic cell death in elderly female patients with ischemic stroke: identification and analysis.

Ischemic stroke (IS) is of increasing concern given the aging population and prevalence of unhealthy lifestyles, with older females exhibiting higher susceptibility. This study aimed to identify practical diagnostic markers, develop a diagnostic model for immunogenic cell death (ICD)-associated IS, and investigate alterations in the immune environment caused by hub genes. Differentially expressed genes associated with ICD in IS were identified based on weighted gene co-expression network analysis and the identification of significant modules. Subsequently, machine learning algorithms were employed to screened hub genes, which were further assessed using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis. A nomogram mode lwas then constructed for IS diagnosis, and its diagnostic value was assessed using a receiver operating characteristic curve. Finally, alterations in immune cell infiltration were assessed within patients with IS, and the pan-cancer expression patterns of hub genes were evaluated. Three hub genes associated with ICD (PDK4, CCL20, and FBL) were identified. The corresponding nomogram model for IS diagnosis could effectively identify older female patients with IS (area under the curve (AUC) = 0.9555). Overall, the three hub genes exhibit good diagnostic value (AUC > 0.8). CCL20 and FBL are significantly associated with the extent of immune cells infiltration. Moreover, a strong link exists between hub gene expression and pan-cancer prognosis. Cumulatively, these results indicate that ICD-related hub genes critically influence IS progression in older females, presenting novel diagnostic and therapeutic targets for personalized treatment.

Compact, low-loss, and high-polarized-extinction ratio terahertz TM-pass polarizer based on a hybrid plasmonic waveguide with a graphene ridge.

A compact, low-loss, and high-polarized-extinction ratio TM-pass polarizer based on a graphene hybrid plasmonic waveguide (GHPW) has been demonstrated for the terahertz band. A ridge coated by a graphene layer and the hollow HPW with a semiround arch (SRA) Si core is introduced to improve structural compactness and suppress the loss. Based on this, a TM-pass polarizer has been designed that can effectively cut off the unwanted TE mode, and the TM mode passes with negligible loss. By optimizing the angle of the ridge, the height of the ridge, air gap height, and the length of the tapered mode converter, an optimum performance with a high polarization extinction ratio of 30.28 dB and a low insert loss of 0.4 dB is achieved in the 3 THz band. This work provides a scheme for the design and optimization of polarizers in the THz band, which has potential application value in integrated terahertz systems.

Causal network perturbation analysis identifies known and novel type-2 diabetes driver genes.

The molecular pathogenesis of diabetes is multifactorial, involving genetic predisposition and environmental factors that are not yet fully understood. However, pancreatic ß-cell failure remains among the primary reasons underlying the progression of type-2 diabetes (T2D) making targeting ß-cell dysfunction an attractive pathway for diabetes treatment. To identify genetic contributors to ß-cell dysfunction, we investigated single-cell gene expression changes in ß-cells from healthy (C57BL/6J) and diabetic (NZO/HlLtJ) mice fed with normal or high-fat, high-sugar diet (HFHS). Our study presents an innovative integration of the causal network perturbation assessment (ssNPA) framework with meta-cell transcriptome analysis to explore the genetic underpinnings of type-2 diabetes (T2D). By generating a reference causal network and in silico perturbation, we identified novel genes implicated in T2D and validated our candidates using the Knockout Mouse Phenotyping (KOMP) Project database.

CBioProfiler: A Web and Standalone Pipeline for Cancer Biomarker and Subtype Characterization.

Cancer is a leading cause of death worldwide, and the identification of biomarkers and subtypes that can predict the long-term survival of cancer patients is essential for their risk stratification, treatment, and prognosis. However, there are currently no standardized tools for exploring cancer biomarkers or subtypes. In this study, we introduced Cancer Biomarker and Subtype Profiler (CBioProfiler), a web server and standalone application that includes two pipelines for analyzing cancer biomarkers and subtypes. The cancer biomarker pipeline consists of five modules for identifying and annotating cancer survival-related biomarkers using multiple survival-related machine learning algorithms. The cancer subtype pipeline includes three modules for data preprocessing, subtype identification using multiple unsupervised machine learning methods, as well as subtype evaluation and validation. CBioProfiler also includes CuratedCancerPrognosisData, a novel R package that integrates reviewed and curated gene expression and clinical data from 268 studies. These studies cover 43 common blood and solid tumors and draw upon 47,686 clinical samples. The web server is available at https://www.cbioprofiler.com/ and https://cbioprofiler.znhospital.cn/CBioProfiler/, and the standalone app and source code can be found at https://github.com/liuxiaoping2020/CBioProfiler.

Lipocalin-2-mediated intestinal epithelial cells pyroptosis via NF-κB/NLRP3/GSDMD signaling axis adversely affects inflammation in colitis.

Ulcerative colitis (UC) is a major inflammatory bowel disease (IBD) characterized by intestinal epithelium damage. Recently, Lipocalin-2 (LCN2) has been identified as a potential fecal biomarker for patients with UC. However, further investigation is required to explore its pro-inflammatory role in UC and the underlying mechanism. The biological analysis revealed that Lcn2 serves as a putative signature gene in the colon mucosa of patients with UC and its association with the capsase/pyroptosis signaling pathway in UC. In wild-type mice with DSS-induced colitis, LCN2 overexpression in colon mucosa via in vivo administration of Lcn2 overexpression plasmid resulted in exacerbation of colitis symptoms and epithelium damage, as well as increased expression levels of pyroptosis markers (cleaved caspase1, GSDMD, IL-1ß, HMGB1 and IL-18). Additionally, we observed downregulation in the expression levels of pyroptosis markers following in vivo silencing of LCN2. However, the pro-inflammatory effect of LCN2 overexpression was effectively restrained in GSDMD-KO mice. Moreover, single-cell RNA-sequencing analysis revealed that Lcn2 was predominantly expressed in the intestinal epithelial cells (IECs) within the colon mucosa of patients with UC. We found that LCN2 effectively regulated pyroptosis events by modulating the NF-κB/NLRP3/GSDMD signaling axis in NCM460 cells stimulated by LPS and ATP. These findings demonstrate the pro-inflammatory role of LCN2 in colon epithelium and provide a potential target for inhibiting pyroptosis in UC.

Distinct characteristics of the gut virome in patients with osteoarthritis and gouty arthritis.

BACKGROUND/PURPOSE(S): The gut microbiota and its metabolites play crucial roles in pathogenesis of arthritis, highlighting gut microbiota as a promising avenue for modulating autoimmunity. However, the characterization of the gut virome in arthritis patients, including osteoarthritis (OA) and gouty arthritis (GA), requires further investigation. METHODS: We employed virus-like particle (VLP)-based metagenomic sequencing to analyze gut viral community in 20 OA patients, 26 GA patients, and 31 healthy controls, encompassing a total of 77 fecal samples. RESULTS: Our analysis generated 6819 vOTUs, with a considerable proportion of viral genomes differing from existing catalogs. The gut virome in OA and GA patients differed significantly from healthy controls, showing variations in diversity and viral family abundances. We identified 157 OA-associated and 94 GA-associated vOTUs, achieving high accuracy in patient-control discrimination with random forest models. OA-associated viruses were predicted to infect pro-inflammatory bacteria or bacteria associated with immunoglobulin A production, while GA-associated viruses were linked to Bacteroidaceae or Lachnospiraceae phages. Furthermore, several viral functional orthologs displayed significant differences in frequency between OA-enriched and GA-enriched vOTUs, suggesting potential functional roles of these viruses. Additionally, we trained classification models based on gut viral signatures to effectively discriminate OA or GA patients from healthy controls, yielding AUC values up to 0.97, indicating the clinical utility of the gut virome in diagnosing OA or GA. CONCLUSION: Our study highlights distinctive alterations in viral diversity and taxonomy within gut virome of OA and GA patients, offering insights into arthritis etiology and potential treatment and prevention strategies.