A comparison of various insulin resistance indices and the possibility of hypertension in military adults: CHIEF study.

BACKGROUND: Insulin resistance is associated with the development of hypertension, whereas there were rare studies comparing various non-insulin based insulin resistance (NI-IR) indices for the possibility of hypertension among young and middle-aged adults. METHODS: This cross-sectional study included a total of 4,080 military personnel, aged 18-50 years, without antihypertensive medications therapy in 2014. All subjects received annual health examinations for blood pressure (BP) measurements. Stage I isolated diastolic hypertension (IDH) and isolated systolic hypertension (ISH) and combined hypertension were respectively defined as systolic BP (SBP) < 130 mmHg/diastolic BP (DBP) 80-89 mmHg, SBP 130-139 mmHg/DBP < 80 mmHg, and SBP 130-139 mmHg/DBP 80-89 mmHg. The cut-off values of stage II hypertension for SBP and DBP were 140-159 mmHg and 90-99 mmHg, respectively. Four NI-IR indices included the serum triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) ratio, TyG index, Metabolic Score for IR (METS-IR) and ZJU index which were defined according to their specific formula. Multiple logistic regression analysis with adjustments for age, sex, anthropometrics, substance use, kidney function, serum uric acid, atherogenic cholesterols and physical activity was performed to determine the associations. RESULTS: There were 1,024 subjects with hypertension (25.1%) in which 739 were stage I hypertension, and 285 were stage II hypertension. For total hypertension, there were an association with TyG and METS-IR indices [odds ratios (ORs) and 95% confidence intervals: 1.432 (1.215-1.688) and 1.553 (1.040-2.321), respectively]. For hypertension subtypes, TyG index was positively associated with overall, stage I, and stage II ISH [ORs: 1.447 (1.149-1.823), 1.317 (1.029-1.687), and 2.011 (1.351-2.994), respectively], while TG/HDL-C, METS-IR and ZJU indices were merely associated with stage II ISH [ORs: 1.053 (1.006-1.103), 3.001 (1.171-7.696) and 1.009 (1.000-1.017), respectively]. In addition, TyG and METS-IR indices were positively associated with stage II IDH [ORs: 1.813 (1.207-2.721) and 2.85 (1.080-7.520), respectively], and TyG index was also associated with combined hypertension [OR: 1.425 (1.007-1.833)]. CONCLUSION: Among young and middle-aged adults, insulin resistance assessed by the four NI-IR indices was positively associated with stage II ISH, while only TyG index had a significant association for both stage II IDH and combined hypertension.

Evaluation of deep learning computer vision for water level measurements in rivers.

Image-based gauging stations offer the potential for substantial enhancement in the monitoring networks of river water levels. Nonetheless, the majority of camera gauges fall short in delivering reliable and precise measurements because of the fluctuating appearance of water in the rivers over the course of the year. In this study, we introduce a method for measuring water levels in rivers using both the traditional continuous image subtraction (CIS) approach and a SegNet neural network based on deep learning computer vision. The historical images collected from on-site investigations were employed to train three neural networks (SegNet, U-Net, and FCN) in order to evaluate their effectiveness, overall performance, and reliability. The research findings demonstrated that the SegNet neural network outperformed the CIS method in accurately measuring water levels. The root mean square error (RMSE) between the water level measurements obtained by the SegNet neural network and the gauge station's readings ranged from 0.013 m to 0.066 m, with a high correlation coefficient of 0.998. Furthermore, the study revealed that the performance of the SegNet neural network in analyzing water levels in rivers improved with the inclusion of a larger number of images, diverse image categories, and higher image resolutions in the training dataset. These promising results emphasize the potential of deep learning computer vision technology, particularly the SegNet neural network, to enhance water level measurement in rivers. Notably, the quality and diversity of the training dataset play a crucial role in optimizing the network's performance. Overall, the application of this advanced technology holds great promise for advancing water level monitoring and management in river systems.

Pathologic liver tumor detection using feature aligned multi-scale convolutional network.

The detection of the most common type of liver tumor, that is, hepatocellular carcinoma (HCC), is one essential step to liver pathology image analysis. In liver tissue, common cell change phenomena such as apoptosis, necrosis, and steatosis are similar in tumor and benign tissue. Hence, the detection of HCC may fail when the patches covered only limited tissue region without enough neighboring cell structure information. To address this problem, a Feature Aligned Multi-Scale Convolutional Network (FA-MSCN) architecture is proposed in this paper for automatic liver tumor detection based on whole slide images (WSI). The proposed network integrates the features obtained at different magnification levels to improve the detection performance by referencing more neighboring information. The FA-MSCN consists of two parallel convolutional networks in which one would extract high-resolution features and the other would extract low-resolution features by atrous convolution. The low-resolution features then go through central cropping, upsampling, and concatenation with high-resolution features for final classification. The experimental results demonstrated that Multi-Scale Convolutional Network (MSCN) improves the detection performance compared to Single-Scale Convolutional Network (SSCN), and that the FA-MSCN is superior to both SSCN and MSCN, demonstrating on HCC detection.

piRTarBase: a database of piRNA targeting sites and their roles in gene regulation.

PIWI-interacting RNAs (piRNAs) are a class of small noncoding RNAs that guard animal genomes against mutation by silencing transposons. In addition, recent studies have reported that piRNAs silence various endogenous genes. Tens of thousands of distinct piRNAs made in animals do not pair well to transposons and currently the functions and targets of piRNAs are largely unexplored. piRTarBase provides a user-friendly interface to access both predicted and experimentally identified piRNA targeting sites in Caenorhabditis elegans. The user can input genes of interest and retrieve a list of piRNA targeting sites on the input genes. Alternatively, the user can input a piRNA and retrieve a list of its mRNA targets. Additionally, piRTarBase integrates published mRNA and small RNA sequencing data, which will help users identify biologically relevant targeting events. Importantly, our analyses suggest that the piRNA sites found by both predictive and experimental approaches are more likely to exhibit silencing effects on their targets than each method alone. Taken together, piRTarBase offers an integrative platform that will help users to identify functional piRNA target sites by evaluating various information. piRTarBase is freely available for academic use at http://cosbi6.ee.ncku.edu.tw/piRTarBase/.

pirScan: a webserver to predict piRNA targeting sites and to avoid transgene silencing in C. elegans.

pirScan is a web-based tool for identifying C. elegans piRNA-targeting sites within a given mRNA or spliced DNA sequence. The purpose of our tool is to allow C. elegans researchers to predict piRNA targeting sites and to avoid the persistent germline silencing of transgenes that has rendered many constructs unusable. pirScan fulfills this purpose by first enumerating the predicted piRNA-targeting sites present in an input sequence. This prediction can be exported in a tabular or graphical format. Subsequently, pirScan suggests silent mutations that can be introduced to the input sequence that would allow the modified transgene to avoid piRNA targeting. The user can customize the piRNA targeting stringency and the silent mutations that he/she wants to introduce into the sequence. The modified sequences can be re-submitted to be certain that any previously present piRNA-targeting sites are now absent and no new piRNA-targeting sites are accidentally generated. This revised sequence can finally be downloaded as a text file and/or visualized in a graphical format. pirScan is freely available for academic use at http://cosbi4.ee.ncku.edu.tw/pirScan/.

Effect of (Ti, Al)N Nanostructured Arc-Coatings on Wear and Corrosion Properties of 4340 Alloy Steel.

This study utilized cathodic arc deposition technology to coat Ti-Al-N hard films on AISI 4340 alloy steel. Composition, morphology, and structure of the coatings were analyzed using EPMA, FESEM, XRD, and TEM. Both wear tests and polarization tests were conducted to determine the abrasion and corrosion properties of the steel before and after coating. The results showed that a specific (Ti, Al)N nanostructured multilayer was synthesized smoothly. The multilayer consisted of 10 nm-TiN and 15 nm-TiAlN interaction layers. The coating not only greatly reduced the friction coefficient of AISI 4340 alloy steel from 0.81 to 0.45, but also provided an effective improvement in corrosion resistance.

The piRNA targeting rules and the resistance to piRNA silencing in endogenous genes.

Piwi-interacting RNAs (piRNAs) silence transposons to safeguard genome integrity in animals. However, the functions of the many piRNAs that do not map to transposons remain unknown. Here, we show that piRNA targeting in Caenorhabditis elegans can tolerate a few mismatches but prefer perfect pairing at the seed region. The broad targeting capacity of piRNAs underlies the germline silencing of transgenes in C. elegans Transgenes engineered to avoid piRNA recognition are stably expressed. Many endogenous germline-expressed genes also contain predicted piRNA targeting sites, and periodic An/Tn clusters (PATCs) are an intrinsic signal that provides resistance to piRNA silencing. Together, our study revealed the piRNA targeting rules and highlights a distinct strategy that C. elegans uses to distinguish endogenous from foreign nucleic acids.

Association among depressive disorder, adjustment disorder, sleep disturbance, and suicidal ideation in Taiwanese adolescent.

INTRODUCTION: The aim of this study is to investigate the association among depressive disorder, adjustment disorder, sleep disturbance, and suicidal ideation in Taiwanese adolescent. METHODS: We recruited 607 students (grades 5-9) to fill out the investigation of basic data and sleep disturbance. Psychiatrists then used the Mini International Neuropsychiatric Interview-Kid to interview these students to assess their suicidal ideation and psychiatric diagnosis. Multiple logistic regression with forward conditionals was used to find the risk factors for multivariate analysis. RESULTS: Female, age, depressive disorder, adjustment disorder, and poor sleep all contributed to adolescent suicidal ideation in univariate analysis. However, poor sleep became non-significant under the control of depressive disorder and adjustment disorder. DISCUSSION: We found that both depressive disorder and adjustment disorder play important roles in sleep and adolescent suicidal ideation. After controlling both depressive disorder and adjustment disorder, sleep disturbance was no longer a risk of adolescent suicidal ideation. We also confirm the indirect influence of sleep on suicidal ideation in adolescent.

A rapid screening test for depression in junior high school children.

BACKGROUND: Depression generates a remarkable disease burden. Early onset of depression in young people is associated with a poor prognosis. This has precipitated developing a screening instrument for early detection of depression in Taiwan adolescents. METHODS: We recruited 662 junior high school students who completed the Screening Test for Depression (STD) designed using diagnostic and statistical manual-IV diagnostic criteria of major depressive disorder for assessing depressive symptoms. The students were then interviewed by psychiatrists who used the Mini International Neuropsychiatric Interview-Kid to verify the validity of the soon-to-be-developed Rapid STD (RSTD). Multiple logistic regression analysis of the STD results was used to extract items for the RSTD. RESULTS: We extracted four items for the RSTD: "insomnia or hypersomnia", "recurrent thoughts of death or recurrent suicidal ideation", "feelings of worthlessness or excessive or inappropriate guilt", and "psychomotor agitation or retardation". Any two of the first three yielded the best-balanced algorithm for major depressive disorder, which had a sensitivity of 75.0%, specificity of 92.9%, positive predictive value of 28.6%, and negative predictive value of 99.0%. Any two of the four yielded the best-balanced algorithm for depressive disorders, which had a sensitivity of 71.4%, specificity of 92.0%, the positive predictive value of 33.3%, and the negative predictive value of 98.3%. CONCLUSION: The RSTD, a 4-item tool for junior high school children, can be easily used to assess fluctuating risks of major depressive disorder and depressive disorders at any time.

Factor analysis of the Schizophrenia Quality of Life Scale Revision 4 (SQLS-R4) Chinese version and related factors.

Objectives. To validate the Schizophrenia Quality of Life Scale Revision 4 (SQLS-R4) Chinese version with factor analysis. We also investigated factors influencing quality of life results. Method. One hundred patients with schizophrenia participated in this study. Experienced psychiatrists evaluated each patient's current psychological condition to assure intact judgment. Participants then filled out the quality of life questionnaire, SQLS-R4. We used principal component analysis to analyze SQLS-R4 with oblique rotation. We also collected demographic data, another subjective and objective quality of life questionnaire, and information about the functional status of the participants at the same time. Multiple linear regression was used to analyze collected factors which may influence the quality of life of schizophrenic patients. Results. We extracted seven factors that explained a 68.1% variance in the patients' quality of life. The factors were relationships with others, loneliness, exhaustion, depressed thinking, somatic concerns, vitality, and worry. Conclusion. We found that the SQLS-R4 factor analysis provided insights into the structure of the quality of life of patients with schizophrenia. We also found that subjective social participation, subjective health, and depression were quality-of-life-related factors. Whether other factors influence the quality of life in patients with schizophrenia requires further investigation.

Validation of the Chinese version of the Schizophrenia Quality of Life Scale Revision 4 (SQLS-R4) in Taiwanese patients with schizophrenia.

We tested the reliability, sensitivity, and validity of a Chinese translation of the Schizophrenia Quality of Life Scale Revision 4 (SQLS-R4). One hundred Taiwanese individuals with schizophrenia were recruited. The internal consistency reliability was satisfactory for both the psychosocial and vitality domains (Cronbach's alpha = 0.92, 0.84). The test-retest reliability was also high (psychosocial: ICC = 0.84, vitality: ICC = 0.84) for those individuals whose psychological conditions remained stable between the two-week interval. However, the responsiveness coefficient for those with considerable changes in psychological conditions ranged from very small to moderate, suggesting either low responsiveness for the vitality domain or a complex relationship between the change of psychological conditions and quality of life, and the need to estimate responsiveness more conclusively in a future intervention study. The convergent validity was supported by moderate-to-large correlations between domains measuring related constructs of the SQLS-R4 and SF-36 (r = -0.65 to -0.67). Overall, the results of this study provide preliminary evidence for the reliability and validity of the SQLS-R4 used in Taiwanese individuals with schizophrenia. This study provides a common ground for international researchers to understand quality of life in Taiwanese patients with schizophrenia.