On-Call Duty Effects on Sleep-State Physiological Stability in Male Medical Interns

Background: On-call duty among medical interns is characterized by sleep deprivation and stressful working conditions, both of which alter cardiac autonomic modulation. We hypothesized that sleep stability decreased in medical interns during on-call duty. We used cardiopulmonary-coupling (CPC) analysis to test our hypothesis. Methods: We used electrocardiogram (ECG)-based CPC analysis to quantify physiological parameters of sleep stability in 13 medical interns during on-call and on-call duty-free periods. There were ten 33.5-h on-call duty shifts per month for interns, each followed by 2 on-call duty-free days, over 3 months. Measurements during sleep were collected before, during, and after an on-call shift. Measurements were repeated 3 months later during an on-call duty-free period. Results: The medical interns had significantly reduced stable sleep, and displayed increased latency to the first epoch of stable sleep during the on-call night shift, compared to the pre-call and on-call duty-free nights. Interns also had significantly increased rapid-eye-movement (REM) sleep during the on-call night shift, compared to the pre-call and on-call duty-free nights. Conclusion: Medical interns suffer disrupted sleep stability and continuity during on-call night shifts. The ECG-based CPC analysis provides a straightforward means to quantify sleep quality and stability in medical staff performing shift work under stressful conditions

Oncologic impact of delay between diagnosis and radical nephroureterectomy

PurposeThis study aimed to evaluate the oncological outcome of delayed surgical wait time from the diagnosis of upper tract urothelial carcinoma (UTUC) to radical nephroureterectomy (RNU).MethodsIn this multicenter retrospective study, medical records were collected between 1988 and 2021 from 18 participating Taiwanese hospitals under the Taiwan UTUC Collaboration Group. Patients were dichotomized into the early (≤90 days) and late (>90 days) surgical wait-time groups. Overall survival, disease-free survival, and bladder recurrence-free survival were calculated using the Kaplan–Meier method and multivariate Cox regression analysis. Multivariate analysis was performed using stepwise linear regression.ResultsOf the 1251 patients, 1181 (94.4%) were classifed into the early surgical wait-time group and 70 (5.6%) into the late surgical wait-time group. The median surgical wait time was 21 days, and the median follow-up was 59.5 months. Our study showed delay-time more than 90 days appeared to be associated with worse overall survival (hazard ratio [HR] 1.974, 95% confidence interval [CI] 1.166−3.343, p = 0.011), and disease-free survival (HR 1.997, 95% CI 1.137−3.507, p = 0.016). This remained as an independent prognostic factor after other confounding factors were adjusted. Age, ECOG performance status, Charlson Comorbidity Index (CCI), surgical margin, tumor location and adjuvant systemic therapy were independent prognostic factors for overall survival. Tumor location and adjuvant systemic therapy were also independent prognostic factors for disease-free survival.ConclusionsFor patients with UTUC undergoing RNU, the surgical wait time should be minimized to less than 90 days. Prolonged delay times may be associated with poor overall and disease-free survival

Correction: Tsai et al. The Efficacy of Transvaginal Ultrasound-Guided BoNT-A External Sphincter Injection in Female Patients with Underactive Bladder. <i>Toxins</i> 2023, <i>15</i>, 199

In the original publication [...

Design and Control of Reactive Distillation Process for the Production of Methyl Valerate

Methyl valerate (VAME), also known as methyl pentanoate, is a methyl ester of pentanoic acid (valeric acid). VAME is usually used as a fragrance in the production of beauty care, soap, and laundry detergents. High purity VAME can also be used as a kind of plasticizer. This study presents design details of the process for the manufacture of VAME. A reactive distillation column (RDC) is used in the production process to overcome equilibrium limitation of the esterification reaction. There is no bottom outlet of this RDC. Both products, VAME and water, are withdrawn from the distillate of RDC and then can be separated by two strippers and a decanter. A thermally coupled design is then developed to reduce the remixing effect in the rectifying section of the RDC. The simulation results show that 30% energy saving can be achieved by using the proposed thermally coupled configuration, but only 17% of total annual costs can be saved due to the use of a compressor. Control strategies of both conventional and thermally coupled configurations in neat design are investigated. The simulation results show that a thermally coupled configuration can reject disturbances faster with smaller steady state deviations from the specifications of the VAME product

Leveraging the Niche of Open Data for Disease Surveillance and Health Education

ObjectiveTo visualize the incidence of notifiable infectious diseasesspatially and interactively, we aimed to provide a friendly interfaceto access local epidemic information based on open data for healthprofessionals and the public.IntroductionTransparency of information on infectious disease epidemicsis crucial for not only public health workers but also the residentsin the communities. Traditionally, disease control departmentscreated official websites for displaying disease maps or epi-curveswith the confirmed case counts. The websites were usually veryformal and static, without interaction, animation, or even the aid ofspatial statistics. Therefore, we tried to take advantage of open dataand use a lightweight programming language, JavaScript, to createan interactive website, named “Taiwan Infectious Disease Map(http://ide.geohealth.tw/)“. With the website, we expect to providereal-time incidence information and related epidemiological featuresusing interactive maps and charts.MethodsThis study used infectious-disease-related open data from Taiwan’sopen data platform (http://data.gov.tw) maintained by the TaiwanCDC. It covers 70 types of infectious diseases starting from 2004, andthe latest status is updated every day. We then automatically bridgethis data into our database and calculate the age-adjusted incidencerate by annual census data and 2000 WH0 standard population.The spatial resolution is mostly at the township level, except thatresolution for sexually-transmitted infectious diseases is at the citylevel. The temporal resolution is month and year, except for denguefever, which is by week.We used R software to automatically compute incidence everyday, and also used its package named “spdep” to compute the spatialclusters of the selected infectious diseases online. In addition, weused JavaScript language, PHP, OpenLayers 3 and Highcharts toimplement interactive maps and charts. All the data and graphicalfigures from the charts viewed in this website can be downloadedfreely. The temporal animation slider can be played and paused atany time point. The health education button can directly link to anintroduction to the selected infectious disease maintained by theTaiwan CDC.ResultsThe website of the Taiwan Infectious Disease Map is displayedin Figure 1. The users can select the temporal precision, types ofinfectious diseases, spatial precision and the gender at the beginning.In this case, the left map is the spatial distribution of the cumulativeincidence of tuberculosis (TB) in 2016. The darker red color representshigher incidence. The right top panel is the ranking of TB incidenceamong 368 townships. The right middle panel is the ranking of TBincidence among 22 cities or counties. The right bottom panel is theannual TB incidence from 2004 to the current date. The highest TBincidence was 67.47 per 100,000 in 2004, and this declined sharply to15.92 per 100,000 in 2015.ConclusionsWith this user-friendly web application, the public and localpublic health workers can easily understand the current risk for theirtownships. The application can provide relevant health education forthe public to understand diseases and how to protect themselves. Thespatial clusters, gender distribution, age distribution, epi-curve andtop ten infectious diseases are all practical and important informationprovided from this website to assist in preventing and mitigating nextepidemic

Leveraging the Niche of Open Data for Disease Surveillance and Health Education

ObjectiveTo visualize the incidence of notifiable infectious diseasesspatially and interactively, we aimed to provide a friendly interfaceto access local epidemic information based on open data for healthprofessionals and the public.IntroductionTransparency of information on infectious disease epidemicsis crucial for not only public health workers but also the residentsin the communities. Traditionally, disease control departmentscreated official websites for displaying disease maps or epi-curveswith the confirmed case counts. The websites were usually veryformal and static, without interaction, animation, or even the aid ofspatial statistics. Therefore, we tried to take advantage of open dataand use a lightweight programming language, JavaScript, to createan interactive website, named “Taiwan Infectious Disease Map(http://ide.geohealth.tw/)“. With the website, we expect to providereal-time incidence information and related epidemiological featuresusing interactive maps and charts.MethodsThis study used infectious-disease-related open data from Taiwan’sopen data platform (http://data.gov.tw) maintained by the TaiwanCDC. It covers 70 types of infectious diseases starting from 2004, andthe latest status is updated every day. We then automatically bridgethis data into our database and calculate the age-adjusted incidencerate by annual census data and 2000 WH0 standard population.The spatial resolution is mostly at the township level, except thatresolution for sexually-transmitted infectious diseases is at the citylevel. The temporal resolution is month and year, except for denguefever, which is by week.We used R software to automatically compute incidence everyday, and also used its package named “spdep” to compute the spatialclusters of the selected infectious diseases online. In addition, weused JavaScript language, PHP, OpenLayers 3 and Highcharts toimplement interactive maps and charts. All the data and graphicalfigures from the charts viewed in this website can be downloadedfreely. The temporal animation slider can be played and paused atany time point. The health education button can directly link to anintroduction to the selected infectious disease maintained by theTaiwan CDC.ResultsThe website of the Taiwan Infectious Disease Map is displayedin Figure 1. The users can select the temporal precision, types ofinfectious diseases, spatial precision and the gender at the beginning.In this case, the left map is the spatial distribution of the cumulativeincidence of tuberculosis (TB) in 2016. The darker red color representshigher incidence. The right top panel is the ranking of TB incidenceamong 368 townships. The right middle panel is the ranking of TBincidence among 22 cities or counties. The right bottom panel is theannual TB incidence from 2004 to the current date. The highest TBincidence was 67.47 per 100,000 in 2004, and this declined sharply to15.92 per 100,000 in 2015.ConclusionsWith this user-friendly web application, the public and localpublic health workers can easily understand the current risk for theirtownships. The application can provide relevant health education forthe public to understand diseases and how to protect themselves. Thespatial clusters, gender distribution, age distribution, epi-curve andtop ten infectious diseases are all practical and important informationprovided from this website to assist in preventing and mitigating nextepidemic

Transcription Factor 7-Like 2 (TCF7L2) rs7903146 Polymorphism as a Risk Factor for Gestational Diabetes Mellitus: A Meta-Analysis

<div><p>Background</p><p>There are racial and ethnic differences in the prevalence of gestational diabetes mellitus (GDM). Prior meta-analyses included small samples and very limited non-Caucasian populations. Studies to determine the relationship between transcription factor 7 like-2 (<i>TCF7L2)</i> rs7903146 polymorphism and risk of GDM in Hispanics/Latinos are recently available. The present meta-analysis was to estimate the impact of allele variants of <i>TCF7L2</i> rs7903146 polymorphism on GDM susceptibility in overall population and racial/ethnic subgroups.</p><p>Methods</p><p>Literature was searched in multiple databases including PubMed, Web of Science, EMBASE (Ovid SP), Airiti Library, Medline Complete, and ProQuest up to July 2015. Allelic frequency for <i>TCF7L2</i> rs7903146 polymorphism in GDM and control subjects was extracted and statistical analysis was performed using Comprehensive Meta-Analysis (CMA) 2.0 statistical software. The association between <i>TCF7L2</i> rs7903146 polymorphism and GDM risk was assessed by pooled odd ratios (ORs) using five gene models (dominant, recessive, homozygote, heterozygote, and allele). Stratified analysis based on race/ethnicity was also conducted. The between-study heterogeneity and contribution of each single study to the final result was tested by Cochran Q test and sensitivity analyses, respectively. Publication bias was evaluated using Egger’s linear regression test.</p><p>Results</p><p>A total of 16 studies involving 4,853 cases and 10,631 controls were included in this meta-analysis. Significant association between the T-allele of rs7903146 and GDM risk was observed under all genetic models, dominant model (OR = 1.44, 95% CI = 1.19–1.74), recessive model (OR = 1.35, 95% CI = 1.08–1.70), heterozygous model (OR = 1.31, 95% CI = 1.12–1.53), homozygous model (OR = 1.67, 95% CI = 1.31–2.12), and allele model (OR = 1.31, 95% CI = 1.12–1.53). Stratified analysis by race/ethnicity showed a statistically significant association between rs7903146 polymorphism and susceptibility to GDM under homozygous genetic model (TT versus CC) among whites, Hispanics/Latinos and Asians. Sensitivity analysis showed that the overall findings were robust to potentially influential decisions of the 16 studies included. No significant evidence for publication bias was observed in this meta-analysis for overall studies and subgroup studies.</p><p>Conclusions</p><p>This meta-analysis showed that the T allele of <i>TCF7L2</i> rs7903146 polymorphism was associated with susceptibility of GDM in overall population in white, Hispanic/Latino and Asian sub-groups. Asians with homozygous TT allele of rs7903146 polymorphism have highest risk of GDM (OR = 2.08) followed by Hispanics/Latinos (OR = 1.80) and whites (OR = 1.51). The highest and lowest frequency of T allele of rs7903146 was found in Malaysia and South Korea, respectively. Future studies are needed to profile genetic risk for GDM among high risk Asian and Pacific Islander subgroups.</p></div