A detection and classification machine-learning model to inspect Thin Film Transistor Liquid Crystal Display (TFT-LCD) Mura is proposed in this study. To improve the capability of the ...machine-learning model to inspect panels' low-contrast grayscale images, piecewise gamma correction and a Selective Search algorithm are applied to detect and optimize the feature regions based on the Semiconductor Equipment and Materials International Mura (SEMU) specifications. In this process, matching the segment proportions to gamma values of piecewise gamma is a task that involves derivative-free optimization which is trained by adaptive particle swarm optimization. The detection accuracy rate (DAR) is approximately 93.75%. An enhanced convolutional neural network model is then applied to classify the Mura type through using the Taguchi experimental design method that identifies the optimal combination of the convolution kernel and the maximum pooling kernel sizes. A remarkable defect classification accuracy rate (CAR) of approximately 96.67% is ultimately achieved. The entire defect detection and classification process can be completed in about 3 milliseconds.
Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a triage system, such as the 5-level emergency severity index, ...somewhat improves the process of ED treatment, it still heavily relies on the nurse's subjective judgment and triages too many patients to emergency severity index level 3 in current practice. Hence, a system that can help clinicians accurately triage a patient's condition is imperative.
This study aims to develop a deep learning-based triage system using patients' ED electronic medical records to predict clinical outcomes after ED treatments.
We conducted a retrospective study using data from an open data set from the National Hospital Ambulatory Medical Care Survey from 2012 to 2016 and data from a local data set from the National Taiwan University Hospital from 2009 to 2015. In this study, we transformed structured data into text form and used convolutional neural networks combined with recurrent neural networks and attention mechanisms to accomplish the classification task. We evaluated our performance using area under the receiver operating characteristic curve (AUROC).
A total of 118,602 patients from the National Hospital Ambulatory Medical Care Survey were included in this study for predicting hospitalization, and the accuracy and AUROC were 0.83 and 0.87, respectively. On the other hand, an external experiment was to use our own data set from the National Taiwan University Hospital that included 745,441 patients, where the accuracy and AUROC were similar, that is, 0.83 and 0.88, respectively. Moreover, to effectively evaluate the prediction quality of our proposed system, we also applied the model to other clinical outcomes, including mortality and admission to the intensive care unit, and the results showed that our proposed method was approximately 3% to 5% higher in accuracy than other conventional methods.
Our proposed method achieved better performance than the traditional method, and its implementation is relatively easy, it includes commonly used variables, and it is better suited for real-world clinical settings. It is our future work to validate our novel deep learning-based triage algorithm with prospective clinical trials, and we hope to use it to guide resource allocation in a busy ED once the validation succeeds.
Introduction
Carina breakthrough (CB) at the right pulmonary vein (RPV) can occur after circumferential pulmonary vein isolation (PVI) due to epicardial bridging or transient tissue edema. High‐power ...short‐duration (HPSD) ablation may increase the incidence of RPV CB. Currently, the surrogate of ablation parameters to predict RPV CB is not well established. This study investigated predictors of RPV CB in patients undergoing ablation index (AI)‐guided PVI with HPSD.
Methods
The study included 62 patients with symptomatic atrial fibrillation (AF) who underwent AI‐guided PVI using HPSD. Patients were categorized into two groups based on the presence or absence of RPV CB. Lesions adjacent to the RPV carina were assessed, and CB was confirmed through residual voltage, low voltage along the ablation lesions, and activation wavefront propagation.
Results
Out of the 62 patients, 21 (33.87%) experienced RPV CB (Group 1), while 41 (66.13%) achieved first‐pass RPV isolation (Group 2). Despite similar AI and HPSD, patients with RPV CB had lower contact force (CF) at lesions adjacent to the RPV carina. Receiver operating characteristic (ROC) curve analysis identified CF < 10.5 g as a predictor of RPV CB, with 75.7% sensitivity and 56.2% specificity (area under the curve: 0.714).
Conclusion
In patients undergoing AI‐guided PVI with HPSD, lower CF adjacent to the carina was associated with a higher risk of RPV CB. These findings suggest that maintaining higher CF during ablation in this region may reduce the occurrence of RPV CB.
Whether retroperitoneal fat should be included in the measurement of visceral fat remains controversial. We compared the relationships of fat areas in peritoneal, retroperitoneal, and subcutaneous ...compartments to metabolic syndrome, adipokines, and incident hypertension and diabetes.
We enrolled 432 adult participants (153 men and 279 women) in a community-based cohort study. Computed tomography at the umbilicus level was used to measure the fat areas.
Retroperitoneal fat correlated significantly with metabolic syndrome (adjusted odds ratio (OR), 5.651, p<0.05) and the number of metabolic abnormalities (p<0.05). Retroperitoneal fat area was significantly associated with blood pressure, plasma glycemic indices, lipid profile, C-reactive protein, adiponectin (r = -0.244, P<0.05), and leptin (r = 0.323, p<0.05), but not plasma renin or aldosterone concentrations. During the 2.94 ± 0.84 years of follow-up, 32 participants developed incident hypertension. Retroperitoneal fat area (hazard ration (HR) 1.62, p = 0.003) and peritoneal fat area (HR 1.62, p = 0.009), but not subcutaneous fat area (p = 0.14) were associated with incident hypertension. Neither retroperitoneal fat area, peritoneal fat area, nor subcutaneous fat areas was associated with incident diabetes after adjustment.
Retroperitoneal fat is similar to peritoneal fat, but differs from subcutaneous fat, in terms of its relationship with metabolic syndrome and incident hypertension. Retroperitoneal fat area should be included in the measurement of visceral fat for cardio-metabolic studies in human.
Studies on resveratrol in a wide range of concentrations on obese mice and adipose cells are necessary to comprehend its range of diverse and contradictory effects. In this study, we examined the ...anti-obesity effects of resveratrol on high-fat diet (HFD)-induced obese mice at dosages ranging from 1 to 30 mg/kg treatment for 10 wk. We also evaluated the effects of resveratrol on cytotoxicity, proliferation, adipogenic differentiation, and lipolysis of 3T3-L1 cells at concentrations ranging from 0.03 to 100 μM. In HFD obese mice, resveratrol treatment for 10 wk without decreased calories intake significantly attenuated HFD-induced weight gain in a dose-dependent manner. Resveratrol treatment also protected against HFD-induced lipid deposition in adipose tissues and liver. In cultured 3T3-L1 preadipocytes, high dosage (10 to 100 μM) resveratrol treatment produced cytotoxicity in both preadipocytes and mature adipocytes. In contrast, low concentration resveratrol treatment (1 to 10 μM) significantly inhibited the capacity of 3T3-L1 cells differentiated into mature adipocytes. Low dose resveratrol treatment also downregulated peroxisome proliferator-activated receptor gamma (PPARγ) and perilipin protein expressions in differentiated adipocytes. Additionally, tumor necrosis factor alpha (TNFα)-induced lipolysis was inhibited by low concentration resveratrol treatment in mature adipocytes. At concentrations of 10-100 μM, resveratrol exerted cytotoxicity. In contrast, at concentrations of 1-10 μM resveratrol inhibited adipogenic differentiation in preadipocytes and suppressed lipolysis in mature adipocytes. Our results suggest that resveratrol possessed anti-obesity effects by induction of cytotoxicity at high dosage and that it influences preadipocyte differentiation and mature adipocyte lipolysis at low concentration.
Diabetes is an independent predictor of poor outcomes in patients with COVID-19. We compared the effects of the preadmission use of antidiabetic medications on the in-hospital mortality of patients ...with COVID-19 having type 2 diabetes.
A systematic search of PubMed, EMBASE, Scopus and Web of Science databases was performed to include studies (except case reports and review articles) published until November 30, 2021. We excluded papers regarding in-hospital use of antidiabetic medications. We used a random-effects meta-analysis to calculate the pooled OR (95% CI) and performed a sensitivity analysis to confirm the robustness of the meta-analyses.
We included 61 studies (3,061,584 individuals), which were rated as having low risk of bias. The OR (95% CI) indicated some medications protective against COVID-related death, including metformin 0.54 (0.47–0.62), I2 86%, glucagon-like peptide-1 receptor agonist (GLP-1RA) 0.51 (0.37–0.69), I2 85%, and sodium–glucose transporter-2 inhibitor (SGLT-2i) 0.60 (0.40–0.88), I2 91%. Dipeptidyl peptidase-4 inhibitor (DPP-4i) 1.23 (1.07–1.42), I2 82% and insulin 1.70 (1.33–2.19), I2 97% users were more likely to die during hospitalization. Sulfonylurea, thiazolidinedione, and alpha-glucosidase inhibitor were mortality neutral 0.92 (95% CI 0.83–1.01, I2 44%), 0.90 (95% CI 0.71–1.14, I2 46%), and 0.61 (95% CI 0.26–1.45, I2 77%), respectively. The sensitivity analysis indicated that our findings were robust.
Metformin, GLP-1RA, and SGLT-2i were associated with lower mortality rate in patients with COVID-19 having type 2 diabetes. DPP-4i and insulin were linked to increased mortality. Sulfonylurea, thiazolidinedione, and alpha-glucosidase inhibitors were mortality neutral. These findings can have a large impact on the clinicians' decisions amid the COVID-19 pandemic.
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•Metformin, GLP-1RA, and SGLT-2i were associated with lower mortality rate.•Metformin use was associated with better outcomes in a dose-response manner.•Dipeptidyl peptidase-4 inhibitor and insulin were linked to increased mortality.•Sulfonylurea, thiazolidinedione, and AGI were mortality neutral.
Rationale
Breast cancer is one of the most common cancers among women and its associated mortality is on the rise. Metabolomics is a potential strategy for breast cancer detection. The post‐column ...infused internal standard (PCI‐IS)‐assisted liquid chromatography/tandem mass spectrometry (LC/MS/MS) method has been demonstrated as an effective strategy for quantitative metabolomics. In this study, we evaluated the performance of targeted metabolomics with the PCI‐IS quantification method to identify women with breast cancer.
Methods
We used metabolite profiling to identify 17 dysregulated metabolites in breast cancer patients. Two LC/MS/MS methods in combination with the PCI‐IS strategy were developed to quantify these metabolites in plasma samples. Detection models were built through the analysis of plasma samples from 176 subjects consisting of healthy volunteers and breast cancer patients.
Results
Three isotope standards were selected as the PCI‐ISs for the metabolites. The accuracy was within 82.8–114.16%, except for citric acid and lactic acid at high concentration levels. The repeatability and intermediate precision were all lower than 15% relative standard deviation. We have identified several metabolites that indicate the presence of breast cancer. The area under the receiver operating characteristics (AUROC) curve, sensitivity and specificity of the linear combinations of metabolite concentrations and age with the highest AUROC were 0.940 (0.889–0.992), 88.4% and 94.2% for pre‐menopausal woman, respectively, and 0.828 (0.734–0.922), 73.5% and 85.1% for post‐menopausal women, respectively.
Conclusions
The targeted metabolomics with PCI‐IS quantification method successfully established prediction models for breast cancer detection. Further study is essential to validate these proposed markers.
Abstract Objectives This study sought to determine predictors for successful endovascular treatment in patients with chronic carotid artery occlusion (CAO). Background Endovascular recanalization in ...patients with chronic CAO has been reported to be feasible, but technically challenging. Methods Endovascular attempts in 138 consecutive chronic CAO patients with impaired ipsilateral hemisphere perfusion were reviewed. We analyzed potential variables including epidemiology, symptomatology, angiographic morphology, and interventional techniques in relation to the technical success. Results The technical success rate was 61.6%. Multivariate analysis showed absence of prior neurologic event (odds ratio OR: 0.27; 95% confidence interval CI: 0.10 to 0.76), nontapered stump (OR: 0.18; 95% CI: 0.05 to 0.67), distal internal carotid artery (ICA) reconstitution via contralateral injection (OR: 0.19; 95% CI: 0.05 to 0.75), and distal ICA reconstitution at communicating or ophthalmic segments (OR:0.12; 95% CI: 0.04 to 0.36) to be independent factors associated with lower technical success. Point scores were assigned proportional to model coefficients, and technical success rates were >80% and <40% in patients with scores of ≤1 and ≥4, respectively. The c-indexes for this score system in predicting technical success was 0.820 (95% CI: 0.748 to 0.892; p < 0.001) with a sensitivity of 84.7% and a specificity of 67.9%. Conclusions Absence of prior neurologic event, nontapered stump, distal ICA reconstitution via contralateral injection, and distal ICA reconstitution at communicating or ophthalmic segments were identified as independent negative predictors for technical success in endovascular recanalization for CAO.
Prostate-specific antigen (PSA) is an intercellular glycoprotein produced primarily by the prostate gland, which is commonly chosen as the initial target for the early diagnosis of prostate cancer. ...In this work, we demonstrate a simple yet sensitive sandwich-type single-particle enumeration (SPE) immunoassay for the quantitative detection of PSA in a flow chamber. The design is based on the luminescence resonance energy transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (GNPs). The carboxyl group-functionalized UCNPs are conjugated with anti-PSA detection antibodies (Ab1) and serve as the luminescence energy donor, while GNPs are modified with anti-PSA capture antibodies (Ab2) and act as the energy acceptor. In the presence of target antigen (i.e., PSA), the specific immnuoreaction brings the donor and acceptor into close proximity, resulting in quenched luminescence. Through statistical counting of the target-dependent fluorescent particles on the glass slide surface, the quantity of antigens in the solution is accurately determined. The dynamic range for PSA detection in Tris-buffered saline (TBS) is 0–500 pM and the limit-of-detection (LOD) is 1.0 pM, which is much lower than the cutoff level in patients’ serum samples. In the serum sample assay, comparable LOD was also achieved (i.e., 2.3 pM). As a consequence, this method will find promising applications for the selective detection of cancer biomarkers in clinical diagnosis.
PARK14 patients with homozygous (D331Y) PLA2G6 mutation display motor deficits of pure early-onset Parkinson’s disease (PD). The aim of this study is to investigate the pathogenic mechanism of mutant ...(D331Y) PLA2G6-induced PD. We generated knockin (KI) mouse model of PARK14 harboring homozygous (D331Y) PLA2G6 mutation. Then, we investigated neuropathological and neurological phenotypes of PLA2G6
D331Y/D331Y
KI mice and molecular pathogenic mechanisms of (D331Y) PLA2G6-induced degeneration of substantia nigra (SN) dopaminergic neurons. Six-or nine-month-old PLA2G6
D331Y/D331
Y KI mice displayed early-onset cell death of SNpc dopaminergic neurons. Lewy body pathology was found in the SN of PLA2G6
D331Y/D331Y
mice. Six-or nine-month-old PLA2G6
D331Y/D331Y
KI mice exhibited early-onset parkinsonism phenotypes. Disrupted cristae of mitochondria were found in SNpc dopaminergic neurons of PLA2G6
D331Y/D331Y
mice. PLA2G6
D331Y/D331Y
mice displayed mitochondrial dysfunction and upregulated ROS production, which may lead to activation of apoptotic cascade. Upregulated protein levels of Grp78, IRE1, PERK, and CHOP, which are involved in activation of ER stress, were found in the SN of PLA2G6
D331Y/D331Y
mice. Protein expression of mitophagic proteins, including parkin and BNIP3, was downregulated in the SN of PLA2G6
D331Y/D331Y
mice, suggesting that (D331Y) PLA2G6 mutation causes mitophagy dysfunction. In the SN of PLA2G6
D331Y/D331Y
mice, mRNA levels of eight genes that are involved in neuroprotection/neurogenesis were decreased, while mRNA levels of two genes that promote apoptotic death were increased. Our results suggest that PARK14 (D331Y) PLA2G6 mutation causes degeneration of SNpc dopaminergic neurons by causing mitochondrial dysfunction, elevated ER stress, mitophagy impairment, and transcriptional abnormality.
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