Explore the vast range of titles available.

CD4+CD25+Foxp3+ regulatory T cells (Tregs) can inhibit cytotoxic responses. Though several studies have analyzed Treg frequency in the peripheral blood mononuclear cells (PBMCs) of pancreatic ductal adenocarcinoma (PDA) patients using flow cytometry (FCM), few studies have examined how intratumoral Tregs might contribute to immunosuppression in the tumor microenvironment. Thus, the potential role of intratumoral Tregs in PDA patients remains to be elucidated. In this study, we found that the percentages of Tregs, CD4+ T cells and CD8+ T cells were all increased significantly in tumor tissue compared to control pancreatic tissue, as assessed via FCM, whereas the percentages of these cell types in PBMCs did not differ between PDA patients and healthy volunteers. The percentages of CD8+ T cells in tumors were significantly lower than in PDA patient PBMCs. In addition, the relative numbers of CD4+CD25+Foxp3+ Tregs and CD8+ T cells were negatively correlated in the tissue of PDA patients, and the abundance of Tregs was significantly correlated with tumor differentiation. Additionally, Foxp3+ T cells were observed more frequently in juxtatumoral stroma (immediately adjacent to the tumor epithelial cells). Patients showing an increased prevalence of Foxp3+ T cells had a poorer prognosis, which was an independent factor for patient survival. These results suggest that Tregs may promote PDA progression by inhibiting the antitumor immunity of CD8+ T cells at local intratumoral sites. Moreover, a high proportion of Tregs in tumor tissues may reflect suppressed antitumor immunity.

Background Recent studies have drawn attention to the association between preserved ratio impaired spirometry (PRISm) and cognitive function decline. High systolic blood pressure (SBP) is a known risk factor for both PRISm and dementia. This study aimed to investigate whether elevated SBP may mediate the relationship between PRISm and cognitive function in older adults. Methods This study analyzed 732 participants aged ≥ 60 years who had completed spirometry and cognitive function tests in the National Health and Nutrition Examination Survey (NHANES) 2011–2012. Multivariable linear regression was employed to assess the relationship between PRISm and cognitive function, as measured through the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) Word Learning sub-test, the Animal Fluency test (AFT), the Digit Symbol Substitution test (DSST), and global cognition tests. All cognitive tests were modeled as z-scores, and global cognition was calculated as the sum of the z-scores of the CERAD, AFT, and DSST. Mediation analyses were conducted to test the mediating effect of SBP on the association between PRISm and cognitive function. Results Participants with PRISm had lower AFT (β = -0.300; 95% confidence interval [CI] = -0.479 to -0.122; p  = 0.001), DSST (β = -0.157; 95% CI = -0.309 to -0.004; p  = 0.044), and global cognition scores (β = -0.211; 95% CI = -0.369 to -0.053; p  = 0.009) than those with normal spirometry, after adjusting for all potential confounders. SBP was considerably associated with AFT (β = -0.084; 95% CI = -0.162 to -0.005; p  = 0.038) and DSST (β = -0.132; 95% CI = -0.207 to -0.057; p  < 0.001), mediating 7.9% and 18.0% of the association of PRISm with cognitive function, respectively. Furthermore, SBP mediated 17.1% of the association of PRISm with global cognition. Conclusions The findings suggested the potential role of SBP as a mediator of associations between PRISm and cognitive decline in older adults.

Cutaneous squamous cell carcinoma (cSCC) is the second most common nonmelanoma skin cancer characterized by high invasiveness, heterogeneity, and mainly occurs in the ultraviolet (UV)-exposed regions of the skin, but its pathogenesis is still unclear. Here, we generated single-cell transcriptome profiles for 350 cells from six primary UV-induced cSCCs, together with matched adjacent skin samples, and three healthy control skin tissues by single-cell RNA-sequencing technology based on Smart-seq2 strategy. A series of bioinformatics analyses and in vitro experiments were used to decipher and validate the critical molecular pattern of cSCC. Results showed that cSCC cells and normal keratinocytes were significantly distinct in gene expression and chromosomal copy number variation. Furthermore, cSCC cells exhibited 18 hallmark pathways of cancer by gene set enrichment analysis. Differential expression analysis demonstrated that many members belonging to S100 gene family, SPRR gene family, and FABP5 were significantly upregulated in cSCC cells. Further experiments confirmed their upregulation and showed that S100A9 or FABP5 knockdown in cSCC cells inhibited their proliferation and migration through NF-κB pathway. Taken together, our data provide a valuable resource for deciphering the molecular pattern in UV-induced cSCC at a single-cell level and suggest that S100A9 and FABP5 may provide novel targets for therapeutic intervention of cSCC in the future.

Background: Pancreatic ductal adenocarcinoma (PDAC) accounts for about 90% of pancreatic cancers, which represents one of the most lethal malignancies with a 5-year overall survival less than 10%. Identifying molecular biomarkers is invaluable in helping to predict clinical outcomes and developing targeted chemotherapies. Actin gamma 1 (ACTG1) is a kind of actin isoform that exists in almost all cell types as a component of the cytoskeleton, thus mediating cell viability. Although there have been studies revealing the prognostic significance of ACTG1 in several malignancies such as glioblastoma and hepatocellular carcinoma, its involvement and function in pancreatic cancer needs to be elucidated. Methods: We retrospectively enrolled a cohort of PDAC patients after surgical resection (n = 149) and conducted immunohistochemistry experiments to explore the expression profile of ACTG1. Univariate and multivariate analyses were performed to investigate the clinical relevance of ACTG1. The functional role of ACTG1 in PDAC progression was further validated via both in vitro and in vivo studies. Results: ACTG1 presented a higher expression in PDAC tissues than in nontumorous pancreatic tissues. ACTG1 level positively correlated with tumor stage, implying its potential role as a tumor promoter. Univariate and multivariate analyses identified that patients with lower ACTG1 showed a better overall survival compared to those with higher ACTG1 expression. Cellular and xenograft experiments confirmed the role of ACTG1 on facilitating tumor proliferation both in vitro and in vivo. Conclusions: Our study revealed a pro-oncogenic role of ACTG1 in PDAC, which may help predict prognosis and serve as a novel therapeutic target.

Split Hopkinson pressure bar (SHPB) tests are usually used to determine the dynamic mechanical strength of basalt-fiber-reinforced concrete (BFRC), but this test method is time-consuming and expensive. This paper makes predictions about the dynamic mechanical strength of BFRC by employing machine learning (ML) algorithms and feature sets drawn from experimental data from prior works. However, there is still the problem of improving the accuracy of the dynamic mechanical strength prediction by the BFRC, which remains a challenge. Using stacking ensemble learning and genetic algorithms (GA) to optimize parameters, this study proposes a prediction method that combines these two techniques for obtaining accurate predictions. This method is composed of three parts: (1) the training uses multiple base learners, and the algorithms employed by the learners include extreme gradient boosting (XGBoost), gradient boosting (GB), random forest (RF), and support vector regression (SVR); (2) multi-base learners are combined using a stacking strategy to obtain the final prediction; and (3) using GA, the parameters are optimized in the prediction model. An experiment was conducted to compare the proposed approach with popular techniques for machine learning. In the study, the stacking ensemble algorithm integrated the base learner prediction results to improve the model’s performance and the GA further improved prediction accuracy. As a result of the application of the method, the dynamic mechanical strength of BFRC can be predicted with high accuracy. A SHAP analysis was also conducted using the stacking model to determine how important the contributing properties are and the sensitivity of the stacking model. Based on the results of this study, it was found that in the SHPB test, the strain rate had the most significant influence on the DIF, followed by the specimen diameter and the compressive strength.

To solve the problems of measurement errors led by mismatches of dense feature matching in machine vision structural deflection measurement, this paper proposes a dense feature extraction, matching, and dual-step mismatch-removal-based full-field structural dynamic deflection measurement method. First, the of dense feature detection and matching theory is introduced to extract the SIFT feature points on a structural surface in an image sequence and matched by FLANN to trace the structure movement, and the mechanisms and causes of mismatches are analyzed. Then, a dual-step mismatch removal method combining RANSAC and Structural Displacement Continuity Restriction (SDCR) is introduced to achieve full-field dynamic beam deflection measurement. The proposed method is validated through indoor cantilever beam experiments, and results show that the method can effectively eliminate a large number of SIFT feature mismatches (accounting for approximately 55% of the total matched feature points). The full-field dynamic displacement field of the beam can be measured with the correctly matched dense feature points by converting dense feature point displacements into continuous and uniform spatiotemporal deflections of the structure. A comparison with the GOM Correlate Professional DIC measurement system was conducted, and the maximum measurement error of the cantilever beam dynamic displacement of the proposed method is between 0.024 and 0.053 mm, the root mean squared error of displacement is approximately 0.01 mm, and the correlation coefficient between two deflection–time curves reaches 0.9964. The proposed algorithm is proven to be effective in full-field displacement measurement and has great potential in future structural health monitoring of bridges.

IntroductionThis meta-analysis aims to evaluate the agreement and correlation between phase-resolved functional lung MRI (PREFUL MRI) and dynamic contrast-enhanced (DCE) MRI in evaluating perfusion defect percentage (QDP), as well as the agreement between PREFUL MRI and 129Xe MRI in assessing ventilation defect percentage (VDP).MethodA systematic search was conducted in the Medline, Embase and Cochrane Library databases to identify relevant studies comparing QDP and VDP measured by DCE MRI and 129Xe MRI compared with PREFUL MRI. Meta-analytical techniques were applied to calculate the pooled weighted bias, limits of agreement (LOA) and correlation coefficient. The publication bias was assessed using Egger’s regression test, while heterogeneity was assessed using Cochran’s Q test and Higgins I2 statistic.ResultsA total of 399 subjects from 10 studies were enrolled. The mean difference and LOA were −2.31% (−8.01% to 3.40%) for QDP and 0.34% (−4.94% to 5.62%) for VDP. The pooled correlations (95% CI) were 0.65 (0.55 to 0.73) for QDP and 0.72 (0.61 to 0.80) for VDP. Furthermore, both QDP and VDP showed a negative correlation with forced expiratory volume in 1 s (FEV1). The pooled correlation between QDP and FEV1 was −0.51 (−0.74 to −0.18), as well as between VDP and FEV1 was −0.60 (−0.73 to −0.44).ConclusionsPREFUL MRI is a promising imaging for the assessment of lung function, as it demonstrates satisfactory deviations and LOA when compared with DEC MRI and 129Xe MRI.PROSPERO registration numberCRD42023430847.

Mammary and extramammary Paget’s Diseases (PD) are a malignant skin cancer characterized by the appearance of Paget cells. Although easily diagnosed, its pathogenesis remains unknown. Here, single-cell RNA-sequencing identified distinct cellular states, novel biomarkers, and signaling pathways — including mTOR, associated with extramammary PD. Interestingly, we identified MSI1 ectopic overexpression in basal epithelial cells of human PD skin, and show that Msi1 overexpression in the epidermal basal layer of mice phenocopies human PD at histopathological, single-cell and molecular levels. Using this mouse model, we identified novel biomarkers of Paget-like cells that translated to human Paget cells. Furthermore, single-cell trajectory, RNA velocity and lineage-tracing analyses revealed a putative keratinocyte-to-Paget-like cell conversion, supporting the in situ transformation theory of disease pathogenesis. Mechanistically, the Msi1-mTOR pathway drives keratinocyte-Paget-like cell conversion, and suppression of mTOR signaling with Rapamycin significantly rescued the Paget-like phenotype in Msi1-overexpressing transgenic mice. Topical Rapamycin treatment improved extramammary PD-associated symptoms in humans, suggesting mTOR inhibition as a novel therapeutic treatment in PD.

In this case study, we are extending feature engineering approaches for short text samples by integrating techniques which have been introduced in the context of time series classification and signal processing. The general idea of the presented feature engineering approach is to tokenize the text samples under consideration and map each token to a number, which measures a specific property of the token. Consequently, each text sample becomes a language time series, which is generated from consecutively emitted tokens, and time is represented by the position of the respective token within the text sample. The resulting language time series can be characterised by collections of established time series feature extraction algorithms from time series analysis and signal processing. This approach maps each text sample (irrespective of its original length) to 3970 stylometric features, which can be analysed with standard statistical learning methodologies. The proposed feature engineering technique for short text data is applied to two different corpora: the Federalist Papers data set and the Spooky Books data set. We demonstrate that the extracted language time series features can be successfully combined with standard machine learning approaches for natural language processing and have the potential to improve the classification performance. Furthermore, the suggested feature engineering approach can be used for visualizing differences and commonalities of stylometric features. The presented framework models the systematic feature engineering based on approaches from time series classification and develops a statistical testing methodology for multi-classification problems.

Background Vitiligo is an acquired depigmented disorder that causes great damage to patient's appearance and mental health. Surgical treatment plays a vital role in patients with refractory vitiligo. Recipient‐site preparation (such as liquid nitrogen, mechanical dermabrasion, chemical peeling and laser) is a key step in surgical treatment. Among them, mechanical dermabrasion and CO2 laser can achieve accurate ablation in different parts and depths. Objectives To compare the advantages and disadvantages of mechanical dermabrasion and CO2 laser and their preference for different parts in cultured epithelial sheets transplantation for the treatment of vitiligo. Methods We used a self‐controlled study to compare the efficacy of mechanical dermabrasion and CO2 laser in 120 stable vitiligo patients of different parts at different time points after cultured epithelial sheets transplantation. Results No overall difference between the mechanical dermabrasion group and the CO2 laser group. While the recovery rate of different parts of the mechanical dermabrasion group was significantly different (p < 0.05). Two methods have distinct efficacy for different parts, and CO2 laser is better at treating uneven parts. Conclusions Both mechanical dermabrasion and CO2 laser have good results in cultured epithelial sheets transplantation for the treatment of vitiligo.