UNASSIGNED: 1) To develop a deep learning (DL) pipeline allowing quantification of COVID-19 pulmonary lesions on low-dose computed tomography (LDCT). 2) To assess the prognostic value of DL-driven lesion quantification.
UNASSIGNED: This monocentric retrospective study included training and test datasets taken from 144 and 30 patients, respectively. The reference was the manual segmentation of 3 labels: normal lung, ground-glass opacity(GGO) and consolidation(Cons). Model performance was evaluated with technical metrics, disease volume and extent. Intra- and interobserver agreement were recorded. The prognostic value of DL-driven disease extent was assessed in 1621 distinct patients using C-statistics. The end point was a combined outcome defined as death, hospitalization>10 days, intensive care unit hospitalization or oxygen therapy.
UNASSIGNED: The Dice coefficients for lesion (GGO+Cons) segmentations were 0.75±0.08, exceeding the values for human interobserver (0.70±0.08; 0.70±0.10) and intraobserver measures (0.72±0.09). DL-driven lesion quantification had a stronger correlation with the reference than inter- or intraobserver measures. After stepwise selection and adjustment for clinical characteristics, quantification significantly increased the prognostic accuracy of the model (0.82 vs. 0.90; p<0.0001).
UNASSIGNED: A DL-driven model can provide reproducible and accurate segmentation of COVID-19 lesions on LDCT. Automatic lesion quantification has independent prognostic value for the identification of high-risk patients.

UNASSIGNED: Patients with pulmonary tuberculosis (PTB) disease and positive sputum cultures are the main source of infection. Culture conversion time is inconsistent and defining the length of respiratory isolation is challenging. The objective of this study is to develop a score to predict the length of isolation period.
UNASSIGNED: A retrospective study was carried out to evaluated risk factors associated with persistent positive sputum cultures after 4 weeks of treatment in 229 patients with PTB. A multivariable logistic regression model was used to determinate predictors for positive culture and a scoring system was created based on the coefficients of the final model.
UNASSIGNED: Sputum culture was persistently positive in 40.6%. Fever at consultation (1.87, 95% CI:1.02-3.41), smoking (2.44, 95% CI:1.36-4.37), >2 affected lung lobes (1.95, 95% CI:1.08-3.54), and neutrophil-to-lymphocyte ratio > 3.5 (2.22, 95% CI:1.24-3.99), were significantly associated with delayed culture conversion. Therefore, we assembled a severity score that achieved an area under the curve of 0.71 (95% CI:0.64-0.78).
UNASSIGNED: In patients with smear positive PTB, a score with clinical, radiological and analytical parameters can be used as a supplemental tool to assist clinical decisions in isolation period.

UNASSIGNED: Global liquid chromatography mass spectrometry (LC-MS) profiling in a Thai population has previously identified a urinary metabolic signature in Opisthorchis viverrini-induced cholangiocarcinoma (CCA), primarily characterised by disturbance in acylcarnitine, bile acid, steroid, and purine metabolism. However, the detection of thousands of analytes by LC-MS in a biological sample in a single experiment potentially introduces false discovery errors. To verify these observed metabolic perturbations, a second validation dataset from the same population was profiled in a similar fashion.
UNASSIGNED: Reverse-phase ultra-performance liquid-chromatography mass spectrometry was utilised to acquire the global spectral profile of 98 spot urine samples (from 46 healthy volunteers and 52 CCA patients) recruited from Khon Kaen, northeast Thailand (the highest incidence of CCA globally).
UNASSIGNED: Metabolites were differentially expressed in the urinary profiles from CCA patients. High urinary elimination of bile acids was affected by the presence of obstructive jaundice. The urine metabolome associated with non-jaundiced CCA patients showed a distinctive pattern, similar but not identical to published studies. A panel of 10 metabolites achieved a diagnostic accuracy of 93.4% and area under the curve value of 98.8% (CI = 96.3%-100%) for the presence of CCA.
UNASSIGNED: Global characterisation of the CCA urinary metabolome identified several metabolites of biological interest in this validation study. Analyses of the diagnostic utility of the discriminant metabolites showed excellent diagnostic potential. Further larger scale studies are required to confirm these findings internationally, particularly in comparison to sporadic CCA, not associated with liver fluke infestation.

The vital cellular functions in Gram-positive bacteria are controlled by signaling molecules known as quorum sensing peptides (QSPs), considered promising therapeutic interventions for bacterial infections. In the bacterial system QSPs bind to membrane-coupled receptors, which then auto-phosphorylate and activate intracellular response regulators. These response regulators induce target gene expression in bacteria. One of the most reliable trends in drug discovery research for virulence-associated molecular targets is the use of peptide drugs or new functionalities. In this perspective, computational methods act as auxiliary aids for biologists, where methodologies based on machine learning and in silico analysis are developed as suitable tools for target peptide identification. Therefore, the development of quick and reliable computational resources to identify or predict these QSPs along with their receptors and inhibitors is receiving considerable attention. The databases such as Quorumpeps and Quorum Sensing of Human Gut Microbes (QSHGM) provide a detailed overview of the structures and functions of QSPs. The tools and algorithms such as QSPpred, QSPred-FL, iQSP, EnsembleQS and PEPred-Suite have been used for the generic prediction of QSPs and feature representation. The availability of compiled key resources for utilizing peptide features based on amino acid composition, positional preferences, and motifs as well as structural and physicochemical properties, including biofilm inhibitory peptides, can aid in elucidating the QSP and membrane receptor interactions in infectious Gram-positive pathogens. Herein, we present a comprehensive survey of diverse computational approaches that are suitable for detecting QSPs and QS interference molecules. This review highlights the utility of these methods for developing potential biomarkers against infectious Gram-positive pathogens.

UNASSIGNED: Finding a non-invasive and repeatable tool has been recommended to make an accurate diagnosis of Alzheimer\'s disease (AD) and Parkinson\'s disease (PD).
UNASSIGNED: 70 volunteers participated in three groups: 24 with mild dementia of AD, 24 in the first and second stages of PD, and 22 healthy controls. After valuing the scores of cognitive tests, the salivary levels of phosphorylated tau (p-tau), total alpha-synuclein (α-syn), and beta-amyloid 1-42 (Aβ)‏‎ proteins have been evaluated. Finally, the cutoff points, receiver operating characteristic (ROC), sensitivity, and specificity have been calculated to find accurate and detectable biomarkers.
UNASSIGNED: Findings showed that the salivary level of Aβ was higher in both PD (p < 0.01) and AD (p < 0.001) patients than in controls. Moreover, the level of α-syn in both PD and AD patients was similarly lower than in controls (p < 0.05). However, the level of p-tau was only ‎higher in the AD group than in the control (p < 0.01). Salivary Aβ 1-42 level at a 60.3 pg/ml cutoff point revealed an excellent performance for diagnosing AD (AUC: 0.81).
UNASSIGNED: Evaluation of p-tau, α-syn, and Aβ 1-42 levels in the saliva of AD and PD patients could help the early diagnosis. The p-tau level might be valuable for differentiation between AD and PD. Therefore, these hopeful investigations could be done to reduce the usage of invasive diagnostic methods, which alone is a success in alleviating the suffering of AD and PD patients. Moreover, introducing accurate salivary biomarkers according to the pathophysiology of AD and PD should be encouraged.

Cancer-associated fibroblasts (CAFs) can exert their immunosuppressive effects by secreting various effectors that are involved in the regulation of tumor-infiltrating immune cells as well as other immune components in the tumor immune microenvironment (TIME), thereby promoting tumorigenesis, progression, metastasis, and drug resistance. Although a large number of studies suggest that CAFs play a key regulatory role in the development of head and neck squamous cell carcinoma (HNSCC), there are limited studies on the relevance of CAFs to the prognosis of HNSCC. In this study, we identified a prognostic signature containing eight CAF-related genes for HNSCC by univariate Cox analysis, lasso regression, stepwise regression, and multivariate Cox analysis. Our validation in primary cultures of CAFs from human HNSCC and four human HNSCC cell lines confirmed that these eight genes are indeed characteristic markers of CAFs. Immune cell infiltration differences analysis between high-risk and low-risk groups according to the eight CAF-related genes signature hinted at CAFs regulatory roles in the TIME, further revealing its potential role on prognosis. The signature of the eight CAF-related genes was validated in different independent validation cohorts and all showed that it was a valid marker for prognosis. The significantly higher overall survival (OS) in the low-risk group compared to the high-risk group was confirmed by Kaplan-Meier (K-M) analysis, suggesting that the signature of CAF-related genes can be used as a non-invasive predictive tool for HNSCC prognosis. The low-risk group had significantly higher levels of tumor-killing immune cell infiltration, as confirmed by CIBERSORT analysis, such as CD8+ T cells, follicular helper T cells, and Dendritic cells (DCs) in the low-risk group. In contrast, the level of infiltration of pro-tumor cells such as M0 macrophages and activated Mast cells (MCs) was lower. It is crucial to delve into the complex mechanisms between CAFs and immune cells to find potential regulatory targets and may provide new evidence for subsequently targeted immunotherapy. These results suggest that the signature of the eight CAF-related genes is a powerful indicator for the assessment of the TIME of HNSCC. It may provide a new and reliable potential indicator for clinicians to predict the prognosis of HNSCC, which may be used to guide treatment and clinical decision-making in HNSCC patients. Meanwhile, CAF-related genes are expected to become tumor biomarkers and effective targets for HNSCC.

暂无摘要。

Tripterygium glycosides tablets (TGT) are the commonly used preparation for rheumatoid arthritis (RA). However, the changes in TGT on RA are still unclear at the metabolic level. This study aimed to reveal the biological processes of TGT in collagen-induced arthritis (CIA) rats through integrated metabolomics and network analysis. First, the CIA model in rats was established, and the CIA rats were given three doses of TGT. Then, the endogenous metabolites in the serum from normal rats, CIA rats, and CIA rats treated with varying doses of TGT were detected by UHPLC-QTOF-MS/MS. Next, univariate and multivariate statistical analyses were performed to find the differential metabolites. Finally, differential metabolites, metabolic pathways, and hub genes were analyzed integrally to reveal the biological processes of TGT in CIA rats. The paw diameter, arthritis score, immunoglobulin G (IgG) concentration, CT image, and histological assay showed that TGT had evident therapeutic effects on CIA rats. Untargeted metabolomics revealed that TGT could ameliorate the down-regulation of lipid levels in CIA rats. Four key differential metabolites were found including LysoP(18:0), LysoPA(20:4), LysoPA(18:2), and PS(O-20:0/17:1). The glycerophospholipid metabolic pathway was perturbed in treating CIA with TGT. A total of 24 genes, including PLD1, LPCAT4, AGPAT1, and PLA2G4A, were found to be the hub genes of TGT in CIA rats. In conclusion, the integrated analysis provided a novel and holistic perspective on the biological processes of TGT in CIA rats, which could give helpful guidance for further TGT on RA. Future studies based on human samples are necessary.

UNASSIGNED: Blood biomarkers facilitating the diagnosis of covert hepatic encephalopathy (CHE) in patients with cirrhosis are lacking. Astrocyte swelling is a major component of hepatic encephalopathy. Thus, we hypothesised that glial fibrillary acidic protein (GFAP), the major intermediate filament of astrocytes, might facilitate early diagnosis and management. This study aimed to investigate the utility of serum GFAP (sGFAP) levels as a biomarker of CHE.
UNASSIGNED: In this bicentric study, 135 patients with cirrhosis, 21 patients with ongoing harmful alcohol use and cirrhosis, and 15 healthy controls were recruited. CHE was diagnosed using psychometric hepatic encephalopathy score. sGFAP levels were measured using a highly sensitive single-molecule array (SiMoA) immunoassay.
UNASSIGNED: In total, 50 (37%) people presented with CHE at study inclusion. Participants with CHE displayed significantly higher sGFAP levels than those without CHE (median sGFAP, 163 pg/ml [IQR 136; 268] vs. 106 pg/ml [IQR 75; 153]; p <0.001) or healthy controls (p <0.001). sGFAP correlated with results in psychometric hepatic encephalopathy score (Spearman\'s ρ = -0.326, p <0.001), model for end-stage liver disease score (Spearman\'s ρ = 0.253, p = 0.003), ammonia (Spearman\'s ρ = 0.453, p = 0.002), and IL-6 serum levels (Spearman\'s ρ = 0.323, p = 0.006). Additionally, sGFAP levels were independently associated with the presence of CHE in multivariable logistic regression analysis (odds ratio 1.009; 95% CI 1.004-1.015; p <0.001). sGFAP levels did not differ between patients with alcohol-related cirrhosis vs. patients with non-alcohol-related cirrhosis or between patients with ongoing alcohol use vs. patients with discontinued alcohol use.Conclusions: sGFAP levels are associated with CHE in patients with cirrhosis. These results suggest that astrocyte injury may already occur in patients with cirrhosis and subclinical cognitive deficits and that sGFAP could be explored as a novel biomarker.
UNASSIGNED: Blood biomarkers facilitating the diagnosis of covert hepatic encephalopathy (CHE) in patients with cirrhosis are lacking. In this study, we were able to demonstrate that sGFAP levels are associated with CHE in patients with cirrhosis. These results suggest that astrocyte injury may already occur in patients with cirrhosis and subclinical cognitive deficits and that sGFAP could be explored as a novel biomarker.

UNASSIGNED: To evaluate diagnostic precision and prove equivalence of 2 devices, Advanced vision analyzer (AVA, Elisar Vision Technology) and Humphrey field analyzer (HFA, Zeiss) for the detection of glaucoma on 10-2 program.
UNASSIGNED: Prospective, cross-sectional, observational study.
UNASSIGNED: Threshold estimates of 1 eye each of 66 patients with glaucoma, 36 control participants, and 10 glaucoma suspects were analyzed on 10-2 test with AVA and HFA.
UNASSIGNED: Mean sensitivity (MS) values of 68 points and central 16 test points were calculated and compared. Intraclass correlation (ICC), Bland-Altman (BA) plots, linear regression of MS, mean deviation (MD), and pattern standard deviation (PSD) were computed to assess the 10-2 threshold estimate of the devices. Receiver operating characteristic curves were generated for MS and MD values, and the area under the curve (AUC) was compared with assessing diagnostic precision.
UNASSIGNED: Mean sensitivity values of 68 points and central 16 points, AUC for MS and MD values, ICC values, BA plots, and linear-regression analysis.
UNASSIGNED: Bland-Altman plot showed significant correlation for MS, MD, and PSD values for both devices. For MS, the overall ICC value was 0.96 (P < 0.001) with a mean bias of 0.0 dB and limits of agreement range of 7.59. The difference in MS values between both devices was -0.4760 ± 1.95 (P > 0.05). The AUC for MS values for AVA was 0.89 and for HFA was 0.92 (P = 0.188); whereas it was similar at 0.88 for MD values (P = 0.799). Advanced vision analyzer and HFA identically discriminated between healthy and patients with glaucoma (P < 0.001), although HFA denoted marginally greater ability (P > 0.05).
UNASSIGNED: Statistical results denote adequate equivalence between AVA and HFA because threshold estimates of AVA strongly correlate with HFA for 10-2 program.
UNASSIGNED: Proprietary or commercial disclosure may be found after the references.