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Abstract Using a self‐administered questionnaire (the five‐item Brief Symptom Rating Scale, BSRS‐5), determine the prevalence of suicide ideation (SI), psychiatric morbidity (PM), and the factors associated with these conditions in a general hospital in Taiwan. All individuals aged 12 years or older, who were admitted to a Medical University Hospital between August 2014 and December 2016, were asked to fill out the BSRS‐5 at admission. The study was conducted in a medical inpatient setting, excluding Intensive Care Units and the Emergency Service Department. The 93,129 participants were recruited for analysis. Pearson's correlation, regression analysis and path analysis were performed to test the association between SI and each item of psychopathology and to determine the discrimination validity of individual BSRS‐5 items for predicting SI. The prevalence rate was 2.3% for SI and 2.0% for PM among all participants. PM was more prevalent in females and those aged 25–54 years. Individuals with PM had a significantly higher rate of SI (44.6%) than did others (1.4%). The prevalence of PM was varied by department, e.g., Psychiatry (44.3%), Rehabilitation Medicine (7.9%), and Nephrology (5.2%). The regression analysis and path analysis with structural equation model indicated that depression, hostility, anxiety, and inferiority were significant independent predictors of SI. The BSRS‐5 is an efficient and useful screening tool to identify psychological distress and SI among inpatients in a general hospital. Its integration into the electronic medical chart facilitates identifying patients at risk.

Large-scale forest inventory at the individual tree level is critical for natural resource management decision making. Terrestrial Laser Scanning (TLS) has been used for individual tree level inventory at plot scale However, due to the inflexibility of TLS and the complex scene of natural forests, it is still challenging to localize and measure every tree at large scale. In this paper, we present a framework to conduct large-scale natural forest inventory at the individual tree level by taking advantage of deep learning models and Mobile Laser Scanning (MLS) systems. First, a deep learning model, ForestSPG, was developed to perform large-scale semantic segmentation on MLS LiDAR data in natural forests. Then, the forest segmentation results were used for individual stem mapping. Finally, Diameter at Breast Height (DBH) was measured for each individual stem. Two natural forests mapped with backpack and Unmanned Aerial Vehicle (UAV) LiDAR systems were tested. The results showed that the proposed ForestSPG is able to segment large-scale forest LiDAR data into multiple ecologically meaningful classes. The proposed framework was able to localize and measure all 5838 stems at individual tree level in a 20 ha natural forest in less than 20 min using UAV LiDAR. DBH measurement results on trees’ DBH larger than 38.1 cm (15 in) showed that backpack LiDAR was able to achieve 1.82 cm of Root Mean Square Error (RMSE) and UAV LiDAR was able to achieve 3.13 cm of RMSE. The proposed framework can not only segment complex forest components with LiDAR data from different platforms but also demonstrate good performance on stem mapping and DBH measurement. Our research provides and automatic and scalable solution for large-scale natural forest inventory at individual tree level, which can be the basis for large-scale estimation of wood volume and biomass.

Abstract Introduction Ropeginterferon alfa-2b is a novel mono-pegylated proline-interferon. This clinical study aimed to evaluate its antiviral efficacy of ropeginterferon alfa-2b against SARS-CoV-2 infection. Methods This is a multicenter, randomized, open-label study. Adult patients with confirmed SARS-CoV-2 infection with initial cycle threshold (Ct) value

Background: Recent studies have demonstrated a global decline in the age at menarche. Our study aimed to determine the age at menarche of Taiwanese women born between 1943 and 1989. Methods: Data were obtained from the Taiwan Biobank. To view the trends in age at menarche, we analyzed data from 74,799 women. The mean, standard deviation, and annual percentage change in age at menarche were calculated for birth-year cohorts. Results: The mean age at menarche of Taiwanese women born in 1943 was 14.85 years. The age at menarche decreased to 12.20 years for those born in 1989. The mean age at menarche declined by 2.65 years across the 47-year study period; hence, the reduction rate was 0.56 years per decade. This study demonstrated a downward secular trend in the age at menarche of Taiwanese women born between 1943 and 1989. This trend occurred in three stages of decline: fast (1943–1953), slow (1953–1965), and moderate (1965–1989). Conclusion: The age at menarche decreased by 2.65 years among Taiwanese women born in 1943 compared with those born in 1989. This decline occurred in three stages: fast (1943–1953), slow (1953–1965), and moderate (1965–1989). This significant downward secular trend in age at menarche reflects Taiwan's socioeconomic development.

Abstract Objective Early diagnosis and treatment of nasopharyngeal carcinoma (NPC) are vital for a better prognosis. Still, because of obscure anatomical sites and insidious symptoms, nearly 80% of patients with NPC are diagnosed at a late stage. This study aimed to validate a machine learning (ML) model utilizing symptom‐related diagnoses and procedures in medical records to predict nasopharyngeal carcinoma (NPC) occurrence and reduce the prediagnostic period. Materials and Methods Data from a population‐based health insurance database (2001–2008) were analyzed, comparing adults with and without newly diagnosed NPC. Medical records from 90 to 360 days before diagnosis were examined. Five ML algorithms (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting [XGB], Multivariate Adaptive Regression Splines [MARS], Random Forest [RF], and Logistics Regression [LG]) were evaluated for optimal early NPC detection. We further use a real‐world data of 1 million individuals randomly selected for testing the final model. Model performance was assessed using AUROC. Shapley values identified significant contributing variables. Results LGB showed maximum predictive power using 14 features and 90 days before diagnosis. The LGB models achieved AUROC, specificity, and sensitivity were 0.83, 0.81, and 0.64 for the test dataset, respectively. The LGB‐driven NPC predictive tool effectively differentiated patients into high‐risk and low‐risk groups (hazard ratio: 5.85; 95% CI: 4.75–7.21). The model‐layering effect is valid. Conclusions ML approaches using electronic medical records accurately predicted NPC occurrence. The risk prediction model serves as a low‐cost digital screening tool, offering rapid medical decision support to shorten prediagnostic periods. Timely referral is crucial for high‐risk patients identified by the model.

Background: Understanding the neutralizing antibody (NAb) titer against COVID-19 over time is important to provide information for vaccine implementation. The longitudinal NAb titer over one year after SARS-CoV-2 infection is still unclear. The purposes of this study are to evaluate the duration of the neutralizing NAb titers in COVID-19 convalescents and factors associated with the titer positive duration. Methods: A cohort study followed COVID-19 individuals diagnosed between 2020 and 2021 May 15th from the COVID-19 database from the Taiwan Centers for Disease Control. We analyzed NAb titers from convalescent SARS-CoV-2 individuals. We used generalized estimating equations (GEE) and a Cox regression model to summarize the factors associated with NAb titers against COVID-19 decaying in the vaccine-free population. Results: A total of 203 convalescent subjects with 297 analytic samples were followed for a period of up to 588 days. Our study suggests that convalescent COVID-19 in individuals after more than a year and four months pertains to only 25% of positive titers. The GEE model indicates that longer follow-up duration was associated with a significantly lower NAb titer. The Cox regression model indicated the disease severity with advanced condition was associated with maintaining NAb titers (adjusted hazard ratio: 2.01, 95% CI: 1.11–3.63) and that smoking was also associated with higher risk of negative NAb titers (adjusted hazard ratio: 0.55, 95% CI: 0.33–0.92). Conclusions: Neutralizing antibody titers diminished after more than a year. The antibody titer response against SARS-CoV-2 in naturally convalescent individuals provides a reference for vaccinations.

Abstract Human mitochondrial NAD(P)+-dependent malic enzyme (ME2) is well-known for its role in cell metabolism, which may be involved in cancer or epilepsy. We present potent ME2 inhibitors based on cyro-EM structures that target ME2 enzyme activity. Two structures of ME2-inhibitor complexes demonstrate that 5,5’-Methylenedisalicylic acid (MDSA) and embonic acid (EA) bind allosterically to ME2’s fumarate-binding site. Mutagenesis studies demonstrate that Asn35 and the Gln64-Tyr562 network are required for both inhibitors’ binding. ME2 overexpression increases pyruvate and NADH production while decreasing the cell’s NAD+/NADH ratio; however, ME2 knockdown has the opposite effect. MDSA and EA inhibit pyruvate synthesis and thus increase the NAD+/NADH ratio, implying that these two inhibitors interfere with metabolic changes by inhibiting cellular ME2 activity. ME2 silence or inhibiting ME2 activity with MDSA or EA decreases cellular respiration and ATP synthesis. Our findings suggest that ME2 is crucial for mitochondrial pyruvate and energy metabolism, as well as cellular respiration, and that ME2 inhibitors could be useful in the treatment of cancer or other diseases that involve these processes.

Abstract After ovulation, the mitochondrial enzyme CYP11A1 cleavage the cholesterol into pregnenolone for progesterone synthesis, suggesting that mitochondrial dynamics play a vital role in the female reproductive system. The changes in the mitochondria dynamics throughout the ovarian cycle have been reported in literature, but the correlation to its role in the ovarian cycle remains unclear. In this study, mitochondrial fusion promotor, M1, was used to study the impact of mitochondria dynamics in the female reproductive system. Our results showed that M1 treatment in mice can lead to the disruptions of estrous cycles in vagina smears. The decrease in serum LH was recorded in the animal. And the inhibitions of progesterone secretion and ovulations were observed in ovarian culture. Although no significant changes in mitochondrial networks were observed in the ovaries, significant up-regulation of mitochondrial respiratory complexes was revealed in M1 treatments through transcriptomic analysis. In contrast to the estrogen and steroid biosynthesis up-regulated in M1, the molecules of extracellular matrix, remodeling enzymes, and adhesion signalings were decreased. Collectively, our study provides novel targets to regulate the ovarian cycles through the mitochondria. However, more studies are still necessary to provide the functional connections between mitochondria and the female reproductive systems.

Abstract We have previously applied ultrasound (US) with microbubbles (MBs) to enhance inner ear drug delivery, with most experiments conducted using single‐frequency, high‐power density US, and multiple treatments. In the present study, the treatment efficacy was enhanced and safety concerns were addressed using a combination of low‐power‐density, single‐transducer, dual‐frequency US (ISPTA = 213 mW/cm2) and MBs of different sizes coated with insulin‐like growth factor 1 (IGF‐1). This study is the first to investigate the drug‐coating capacity of human serum albumin (HSA) MBs of different particle sizes and their drug delivery efficiency. The concentration of HSA was adjusted to produce different MB sizes. The drug‐coating efficiency was significantly higher for large‐sized MBs than for smaller MBs. In vitro Franz diffusion experiments showed that the combination of dual‐frequency US and large MB size delivered the most IGF‐1 (24.3 ± 0.47 ng/cm2) to the receptor side at the second hour of treatment. In an in vivo guinea pig experiment, the efficiency of IGF‐1 delivery into the inner ear was 15.9 times greater in animals treated with the combination of dual‐frequency US and large MBs (D‐USMB) than in control animals treated with round window soaking (RWS). The IGF‐1 delivery efficiency was 10.15 times greater with the combination of single‐frequency US and large size MBs (S‐USMB) than with RWS. Confocal microscopy of the cochlea showed a stronger distribution of IGF‐1 in the basal turn in the D‐USMB and S‐USMB groups than in the RWS group. In the second and third turns, the D‐USMB group showed the greatest IGF‐1 distribution. Hearing assessments revealed no significant differences among the D‐USMB, S‐USMB, and RWS groups. In conclusion, the combination of single‐transducer dual‐frequency US and suitably sized MBs can significantly reduce US power density while enhancing the delivery of large molecular weight drugs, such as IGF‐1, to the inner ear.

Although real-time reverse transcriptase polymerase chain reaction (real-time RT-PCR) remains as a golden standard for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, it can not be easily expanded to large-scaled screening during outbreaks, and the positive results do not necessarily correlate with infectious status of the identified subjects. In this study, the performance of Vstrip® RV2 COVID-19 Antigen Rapid Test (RAT) and its correlation with virus infectivity was examined by virus culture using 163 sequential respiratory specimens collected from 26 SARS-CoV-2 infected patients. When the presence of cytopathic effects (CPE) in cell culture was used as a reference method for virus infectivity, the sensitivity, specificity and accuracy of Vstrip® RV2 COVID-19 Antigen Rapid Test was 96.43%, 89.63%, and 90.8%, respectively. The highest Ct value was 27.7 for RdRp gene and 25.79 for E gene within CPE-positive samples, and the highest Ct value was 31.9 for RdRp gene and 29.1 for E gene within RAT positive samples. When the Ct values of specimens were below 25, the CPE and RAT results had high degree of consistency. We concluded that the RAT could be a great alternative method for determining the infectious potential of individuals with high viral load.

Emerging mobile LiDAR mapping systems exhibit great potential as an alternative for mapping urban environments. Such systems can acquire high-quality, dense point clouds that capture detailed information over an area of interest through efficient field surveys. However, automatically recognizing and semantically segmenting different components from the point clouds with efficiency and high accuracy remains a challenge. Towards this end, this study proposes a semantic segmentation framework to simultaneously classify bridge components and road infrastructure using mobile LiDAR point clouds while providing the following contributions: 1) a deep learning approach exploiting graph convolutions is adopted for point cloud semantic segmentation; 2) cross-labeling and transfer learning techniques are developed to reduce the need for manual annotation; and 3) geometric quality control strategies are proposed to refine the semantic segmentation results. The proposed framework is evaluated using data from two mobile mapping systems along an interstate highway with 27 highway bridges. With the help of the proposed cross-labeling and transfer learning strategies, the deep learning model achieves an overall accuracy of 84% using limited training data. Moreover, the effectiveness of the proposed framework is verified through test covering approximately 42 miles along the interstate highway, where substantial improvement after quality control can be observed.

This study proposes a single-ended operational trans-conductance amplifier (SEOTA)-based triple inputs and single output high-input impedance voltage-mode (VM) universal second-order filter. The proposed universal VM SEOTA-based second-order filter can be realized for the non-inverting low-pass, non-inverting high-pass, non-inverting band-reject, non-inverting all-pass and inverting band-pass filtering functions by appropriately using different triple-input voltage signals. The high-input impedances of the proposed universal VM SEOTA-based configuration enable the second-order filter to be cascaded without additional buffers. The proposed configuration does not employ external resistors and accordingly is an active SEOTAs and capacitors (SEOTA-C) universal second-order filter. The proposed circuit using two grounded capacitors which is more apposite to further develop into an integrated circuit implementation. The resonance angular frequency and quality factor are orthogonal electronically adjustable. By slightly modifying the proposed universal VM SEOTA-based second-order filter configuration, the VM SEOTA-C quadrature sinusoidal oscillator is achieved. The oscillation frequency and the oscillation condition of the quadrature sinusoidal oscillator can be independently and electronically tuned by adjusting the bias currents of two SEOTAs. PSpice simulation results confirmed theoretic anticipation. The result of the experiment of the commercially available SEOTAs, LT1228s, are also used to verify the characteristics of the proposed universal VM SEOTA-based second-order filter and VM SEOTA-based quadrature sinusoidal oscillator.

Recently, light detection and ranging (LiDAR)-based mobile mapping systems (MMS) have been utilized for extracting lane markings using deep learning frameworks. However, huge datasets are required for training neural networks. Furthermore, with accurate lane markings being detected utilizing LiDAR data, an algorithm for automatically reporting their intensity information is beneficial for identifying worn-out or missing lane markings. In this paper, a transfer learning approach based on fine-tuning of a pretrained U-net model for lane marking extraction and a strategy for generating intensity profiles using the extracted results are presented. Starting from a pretrained model, a new model can be trained better and faster to make predictions on a target domain dataset with only a few training examples. An original U-net model trained on two-lane highways (source domain dataset) was fine-tuned to make accurate predictions on datasets with one-lane highway patterns (target domain dataset). Specifically, encoder- and decoder-trained U-net models are presented wherein, during retraining of the former, only weights in the encoder path of U-net were allowed to change with decoder weights frozen and vice versa for the latter. On the test data (target domain), the encoder-trained model (F1-score: 86.9%) outperformed the decoder-trained (F1-score: 82.1%). Additionally, on an independent dataset, the encoder-trained one (F1-score: 90.1%) performed better than the decoder-trained one (F1-score: 83.2%). Lastly, on the basis of lane marking results obtained from the encoder-trained U-net, intensity profiles were generated. Such profiles can be used to identify lane marking gaps and investigate their cause through RGB imagery visualization.

Abstract Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aim to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We present a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/ ). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality has been extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses include patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine is 1.11 (95% CI: 1.02, 1.20; I² = 0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I² = 0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine is associated with increased mortality in COVID-19 patients, and there is no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.

ABSTRACT The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has substantially affected human health globally. Spike-specific antibody response plays a major role in protection against SARS-CoV-2 infection. Here, we examined serological anti-spike antibody and memory B cell responses in adults with acute SARS-CoV-2 infection. Twenty-five adult patients were enrolled between January and September 2020, and 21 (84%) had a detectable spike-binding antibody response in serum on day 21 ± 8 (6 to 33) after the onset of illness. Among those with positive spike-binding antibody response, 19 (90%) had a positive hemagglutination titer and 15 (71%) had angiotensin-converting enzyme 2 (ACE2)-blocking serological activities. Follow-up serum samples collected 11 ± 1 (7 to 15) months after infection exhibited an average of 2.6 ± 1.0 (1.0 to 3.5)-fold reduction in the spike-binding antibody response. Moreover, convalescent and follow-up serum samples showed 83 ± 82 (15 to 306)- and 165 ± 167 (12 to 456)-fold reductions in the neutralization activity against the Omicron variant, respectively. Upon acute infection, spike-specific memory B cell responses were elicited, with an average frequency of 1.3% ± 1.2% of peripheral B cells on day 19 ± 7 (6 to 33) after the onset of illness. IgM memory B cells were predominantly induced. Patients with fever and pneumonia showed significantly stronger spike-binding, ACE2-blocking antibody, and memory B cell responses. In conclusion, spike-specific antibody response elicited upon acute SARS-CoV-2 infection may wane over time and be compromised by the emergence of viral variants. IMPORTANCE As spike protein-specific antibody responses play a major role in protection against SARS-CoV-2, we examined spike-binding and ACE2-blocking antibody responses in SARS-CoV-2 infection at different time points. We found robust responses following acute infection, which waned approximately 11 months after infection. Patients with fever and pneumonia showed significantly stronger spike-binding, ACE2-blocking antibody, and memory B cell responses. In particular, spike-specific antibody response in the convalescent and follow-up serum samples was substantially affected by emerging variants, especially Beta and Omicron variants. These results warrant continued surveillance of spike-specific antibody responses to natural infections and highlight the importance of maintaining functional anti-spike antibodies through immunization.

Aims Studies have observed changes in autophagic flux in the adipose tissue of type 2 diabetes patients with obesity. However, the role of autophagy in obesity-induced insulin resistance is unclear. We propose to confirm the effect of a high-fat diet (HFD) on autophagy and insulin signaling transduction from adipose tissue to clarify whether altered autophagy-mediated HFD induces insulin resistance, and to elucidate the possible mechanisms in autophagy-regulated adipose insulin sensitivity. Methods Eight-week-old male C57BL/6 mice were fed with HFD to confirm the effect of HFD on autophagy and insulin signaling transduction from adipose tissue. Differentiated 3T3-L1 adipocytes were treated with 1.2 mM fatty acids (FAs) and 50 nM Bafilomycin A1 to determine the autophagic flux. 2.5 mg/kg body weight dose of Chloroquine (CQ) in PBS was locally injected into mouse epididymal adipose (10 and 24 h) and 40 µM of CQ to 3T3-L1 adipocytes for 24 h to evaluate the role of autophagy in insulin signaling transduction. Results The HFD treatment resulted in a significant increase in SQSTM1/p62, Rubicon expression, and C/EBP homologous protein (CHOP) expression, yet the insulin capability to induce Akt (Ser473) and GSK3β (Ser9) phosphorylation were reduced. PHLPP1 and PTEN remain unchanged after CQ injection. In differentiated 3T3-L1 adipocytes treated with CQ, although the amount of phospho-Akt stimulated by insulin in the CQ-treated group was significantly lower, CHOP expressions and cleaved caspase-3 were increased and bafilomycin A1 induced less accumulation of LC3-II protein. Conclusion Long-term high-fat diet promotes insulin resistance, late-stage autophagy inhibition, ER stress, and apoptosis in adipose tissue. Autophagy suppression may not affect insulin signaling transduction via phosphatase expression but indirectly causes insulin resistance through ER stress or apoptosis.

Abstract The risk of bisphosphonate-related osteonecrosis of the jaw (BRONJ) in primary Sjogren syndrome (pSS) has rarely been explored. To explore the association between BRONJ and pSS, we conducted a population-based propensity-score-matched cohort study using Taiwan’s National Health Insurance Research Database, including pSS patients receiving antiosteoporotic therapy and patients without pSS receiving antiosteoporotic therapy. A 1:4 matched-pair cohort based on propensity score was created. The stratified Cox proportional hazards model compared the risk of BRONJ in the pSS and non-pSS groups. In the study, 23,280 pSS patients and 28,712,152 controls were enrolled. After matching, 348 patients with pSS receiving antiosteoporotic drugs and 50,145 without pSS receiving antiosteoporotic drugs were included for analysis. The risk of developing BRONJ was 1.96 times higher in pSS patients compared with non-pSS patients after adjustment for age, sex, and comorbidities. No dose–response effect was observed in the bisphosphonate-treated pSS cohorts, documented as the cumulative defined daily doses of either

By the request of the Minister of Health and Welfare, NHRI Biobank was assigned to establish a COVID-19 biobank in early Feb, 2020 to collect COVID-19 patients’ blood samples for Taiwan researchers and industries in an emergent way. It was set up in less than 3 weeks and quickly opened for application. By August 5, 2020, this COVID-19 biobank has collected 165 blood samples of 110 patients from more than 10 hospitals across north, middle and south part of Taiwan, including both COVID-19 (+) and (-) pneumonia patients. This biobank can provide applicants with biosamples, such as serum, DNA and RNA, and also the clinical and genomic data, so as to accelerate the COVID-19 treatment and prevention research in Taiwan. This COID-19 biobank already received 15 applications. It has become the most important research resource for the COVID-19 pandemic in Taiwan, including new screening reagents, disease mechanism, the variable human responses and epidemic preventions. Since it is publicly available for both academic and industrial applicants.

Abstract Objectives The data concerning the association between Tx and ADs remain unclear and are scarce. This study was undertaken to investigate whether people with Tx are more likely to develop ADs, compared to those without Tx. Methods Individuals who received Tx between 2002 and 2015 were identified and matched on age and sex with individuals without Tx. We performed multivariate and stratified analysis using the Kaplan–Meier method and Cox proportional hazards models in order to estimate the association between Tx and the risk of developing ADs. Results A total of 2550 thymectomized (Txd) patients and 24,664.941 non‐Txd comparison subjects were selected from NHIRD. Tx‐MG (myasthenia gravis) as compared with general population (nonTx‐nonMG), adjusted hazard ratio (aHR) were higher for incident Addison disease (aHR = 10.40, 95% CI 1.01–107), autoimmune hemolytic anemia (aHR = 21.54, 95% CI 2.06–14.8), Hashmoto thyroiditis (aHR = 5.52, 95% CI 1.34–34.7), ankylosing spondylitis (aHR = 2.73, 95% CI 1.09–6.84), rheumatoid arthritis (aHR = 5.25, 95% CI 1.79–15.47), primary Sjogren syndrome (pSS) (aHR = 3.77, 95% CI 1.30–11.0), and systemic lupus erythemtoasus (aHR = 10.40). Tx‐nonMG as compared with general population, aHR were higher for incident autoimmune hemolytic anemia (aHR = 25.50), Hashmoto thyroiditis (aHR = 6.75) and systemic lupus erythematosus (SLE) (aHR = 13.38). NonTx‐MG as compared with general population, aHR were higher for incident Hashmoto thyroiditis (aHR = 6.57), pSS (aHR = 4.50), SLE (aHR = 17.29), and systemic vasculitis (aHR = 25.86). Interpretation In conclusion, based on a retrospective cohort study throughout Taiwan, patients with Tx have a higher risk of new onset ADs than patients without Tx.

Various all-atom molecular dynamics (MD) simulation methods have been developed to compute free energies and crossing rates of ions and small molecules through ion channels. However, a systemic comparison across different methods is scarce. Using a carbon nanotube as a model of small conductance ion channel, we computed the single-channel permeability for potassium ion using umbrella sampling, Markovian milestoning, and steady-state flux under applied voltage. We show that a slightly modified inhomogeneous solubility-diffusion equation yields a single-channel permeability consistent with the mean first passage time (MFPT) based method. For milestoning, applying cylindrical and spherical bulk boundary conditions yield consistent MFPT if factoring in the effective bulk concentration. The sensitivity of the MFPT to the output frequency of collective variables is highlighted using the convergence and symmetricity of the inward and outward MFPT profiles. The consistent transport kinetic results from all three methods demonstrated the robustness of MD-based methods in computing ion channel permeation. The advantages and disadvantages of each technique are discussed, focusing on the future applications of milestoning in more complex systems.

Forest inventory has been relying on labor-intensive manual measurements. Using remote sensing modalities for forest inventory has gained increasing attention in the last few decades. However, tools for deriving accurate tree-level metrics are limited. This paper investigates the feasibility of using LiDAR units onboard uncrewed aerial vehicle (UAV) and Backpack mobile mapping systems (MMSs) equipped with an integrated Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) to provide high-quality point clouds for accurate, fine-resolution forest inventory. To improve the quality of the acquired point clouds, a system-driven strategy for mounting parameters estimation and trajectory enhancement using terrain patches and tree trunks is proposed. By minimizing observed discrepancies among conjugate features captured at different timestamps from multiple tracks by single/multiple systems, while considering the absolute and relative positional/rotational information provided by the GNSS/INS trajectory, system calibration parameters and trajectory information can be refined. Furthermore, some forest inventory metrics, such as tree trunk radius and orientation, are derived in the process. To evaluate the performance of the proposed strategy, three UAV and two Backpack datasets covering young and mature plantations were used in this study. Through sequential system calibration and trajectory enhancement, the spatial accuracy of the UAV point clouds improved from 20 cm to 5 cm. For the Backpack datasets, when the initial trajectory was of reasonable quality, conducting trajectory enhancement significantly improved the relative alignment of the point cloud from 30 cm to 3 cm, and an absolute accuracy at the 10 cm level can be achieved. For a lower-quality trajectory, the initial 1 m misalignment of the Backpack point cloud was reduced to 6 cm through trajectory enhancement. However, to derive products with accurate absolute accuracy, UAV point cloud is required as a reference in the trajectory enhancement process of the Backpack dataset.

ABSTRACTThis multicenter, retrospective study included 346 serum samples from 74 patients with coronavirus disease 2019 (COVID-19) and 194 serum samples from non-COVID-19 patients to evaluate the performance of five anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests, i.e. two chemiluminescence immunoassays (CLIAs): Roche Elecsys® Anti-SARS-CoV-2 Test (Roche Test) and Abbott SARS-CoV-2 IgG (Abbott Test), and three lateral flow immunoassays (LFIAs): Wondfo SARS-CoV-2 Antibody Test (Wondfo Test), ASK COVID-19 IgG/IgM Rapid Test (ASK Test), and Dynamiker 2019-nCoV IgG/IgM Rapid Test (Dynamiker Test). We found high diagnostic sensitivities (%, 95% confidence interval [CI]) for the Roche Test (97.4%, 93.4–99.0%), Abbott Test (94.0%, 89.1–96.8%), Wondfo Test (91.4%, 85.8–94.9%), ASK Test (97.4%, 93.4–99.0%), and Dynamiker Test (90.1%, 84.3–94.0%) after >21 days of symptom onset. Meanwhile, the diagnostic specificity was 99.0% (95% CI, 96.3–99.7%) for the Roche Test, 97.9% (95% CI, 94.8–99.2%) for the Abbott Test, and 100.0% (95% CI, 98.1–100.0%) for the three LFIAs. Cross-reactivity was observed in sera containing anti-cytomegalovirus (CMV) IgG/IgM antibodies and autoantibodies. No difference was observed in the time to seroconversion detection of the five serological tests. Specimens from patients with COVID-19 pneumonia demonstrated a shorter seroconversion time and higher chemiluminescent signal than those without pneumonia. Our data suggested that understanding the dynamic antibody response after COVID-19 infection and performance characteristics of different serological test are crucial for the appropriate interpretation of serological test result for the diagnosis and risk assessment of patient with COVID-19 infection.

Connexin hemichannels were identified as the first members of the eukaryotic large-pore channel family that mediate permeation of both atomic ions and small molecules between the intracellular and extracellular environments. The conventional view is that their pore is a large passive conduit through which both ions and molecules diffuse in a similar manner. In stark contrast to this notion, we demonstrate that the permeation of ions and of molecules in connexin hemichannels can be uncoupled and differentially regulated. We find that human connexin mutations that produce pathologies and were previously thought to be loss-of-function mutations due to the lack of ionic currents are still capable of mediating the passive transport of molecules with kinetics close to those of wild-type channels. This molecular transport displays saturability in the micromolar range, selectivity, and competitive inhibition, properties that are tuned by specific interactions between the permeating molecules and the N-terminal domain that lies within the pore--a general feature of large-pore channels. We propose that connexin hemichannels and, likely, other large-pore channels, are hybrid channel/transporter-like proteins that might switch between these two modes to promote selective ion conduction or autocrine/paracrine molecular signaling in health and disease processes. [ABSTRACT FROM AUTHOR]

Abstract Background Weight‐reduction therapies, including bariatric surgery (BS), are standard treatments for severely obese patients with type 2 diabetes; however, the outcomes of these therapies are inconclusive for obese patients with chronic kidney disease (CKD). This study aimed to investigate the effects of BS or non‐surgical interventions on the estimated glomerular filtration rate (eGFR) and to determine whether BS can be recommended for renal function preservation based on body mass index (BMI) and eGFR changes in obese patients with CKD. Methods This study used data from the weight Reduction Intervention on GFR in Obese Patients with Renal Impairment‐Taipei Medical University (TMU) study, which was a large, long‐term, propensity score‐matched cohort study based on clinical data from patients who registered at weight‐reduction centres at TMU and its affiliated hospitals from 2008 to 2016. The patients were stratified according to whether they had undergone BS and into the mild, moderate, and high CKD risk groups using the Kidney Disease: Improving Global Outcomes guidelines. The primary outcome was the eGFR calculated using the Taiwan Chronic Kidney Disease‐Epidemiology Collaboration equation. Cox regression models were used to determine hazard ratios (HRs) for eGFR decreases ≥25%. Results A total of 4332 obese patients were enrolled in this study. After propensity score matching, 1620 patients, including 60.2% women, with a mean age of 36.5 (9.9) years were divided into BS or non‐surgery groups (n = 810 per group). The overall mean eGFRs increased by 4.4 (14) mL/min·1.73 m2 and decreased by 6.4 (16.0) mL/min·1.73 m2 in the BS and non‐surgery groups, respectively. The decrease in BMI in the BS and non‐surgery groups were 2.5 and 1.3 kg/m2, respectively. In the moderate/high CKD risk BS group, a significant correlation was evident between an increased eGFR and a reduced BMI (Spearman's correlation −0.229, P < 0.001). The Cox regression analysis showed that the BS group had a significantly lower risk of an eGFR decline ≥25% at 12 months [adjusted HR (aHR) 0.47, P = 0.03). After BS, obese patients with hypertension or albuminuria had significantly lower risks of eGFR declines ≥25% (aHR 0.37, P = 0.02 and aHR 0.13, P = 0.0018, respectively). Conclusions Bariatric surgery was associated with eGFR preservation in all obese patients and, particularly, in those with moderate‐to‐high CKD risks. A longer term outcome study is warranted to determine the benefits of BS for CKD patients.

We report the safety and immunogenicity results in participants administrated with a booster dose of protein subunit vaccine MVC-COV1901 at 12 (Group A) or 24 (Group B) weeks after two doses of AZD1222 (ChAdOx1 nCoV-19). The administration of the MVC-COV1901 vaccine as a booster dose in both groups was generally safe. There were no serious adverse events related to the intervention as adverse events reported were “mild” or “moderate” in nature. In subjects fully vaccinated with two doses of AZD1222, waning antibody immunity was apparent within six months of the second dose of AZD1222. At one month after the MVC-COV1901 booster dose, those who were vaccinated within 12 weeks after the last AZD1222 dose (Group A) had anti-SARS-CoV-2 spike IgG antibody titers and neutralizing antibody titers which were 14- and 6.5-fold increased, respectively, when compared to the titer levels on the day of the booster dose. On the other hand, fold-increase a month post-booster in people who had a booster 24 weeks after the last AZD1222 dose (Group B) were 19.5 and 14.0 times for anti-SARS-CoV-2 spike IgG antibody titers and neutralizing antibody titers, respectively. Among those who were vaccinated within 12 weeks after the last AZD1222 dose, we also observed 5.2- and 5.6-fold increases in neutralizing titer levels against ancestral strain and Omicron variant pseudovirus after the booster dose, respectively. These results support the use of MVC-COV1901 as a heterologous booster for individuals vaccinated with AZD1222. Furthermore, regardless of the dosing schedule, the combination of AZD1222 primary series and MVC-COV1901 booster can be cost-effective and suitably applied to low- and middle-income countries (LMIC).

Light Detection and Ranging (LiDAR) data collected by mobile mapping systems (MMS) have been utilized to detect lane markings through intensity-based approaches. As LiDAR data continue to be used for lane marking extraction, greater emphasis is being placed on enhancing the utility of the intensity values. Typically, intensity correction/normalization approaches are conducted prior to lane marking extraction. The goal of intensity correction is to adjust the intensity values of a LiDAR unit using geometric scanning parameters (i.e., range or incidence angle). Intensity normalization aims at adjusting the intensity readings of a LiDAR unit based on the assumption that intensity values across laser beams/LiDAR units/MMS should be similar for the same object. As MMS technology develops, correcting/normalizing intensity values across different LiDAR units on the same system and/or different MMS is necessary for lane marking extraction. This study proposes a generalized correction/normalization approach for handling single-beam/multi-beam LiDAR scanners onboard single or multiple MMS. The generalized approach is developed while considering the intensity values of asphalt and concrete pavement. For a performance evaluation of the proposed approach, geometric/morphological and deep/transfer-learning-based lane marking extraction with and without intensity correction/normalization is conducted. The evaluation shows that the proposed approach improves the performance of lane marking extraction (e.g., the F1-score of a U-net model can change from 0.1% to 86.2%).

LiDAR data acquired by various platforms provide unprecedented data for forest inventory and management. Among its applications, individual tree detection and segmentation are critical and prerequisite steps for deriving forest structural metrics, especially at the stand level. Although there are various tree detection and localization approaches, a comparative analysis of their performance on LiDAR data with different characteristics remains to be explored. In this study, a new trunk-based tree detection and localization approach (namely, height-difference-based) is proposed and compared to two state-of-the-art strategies—DBSCAN-based and height/density-based approaches. Leaf-off LiDAR data from two unmanned aerial vehicles (UAVs) and Geiger mode system with different point densities, geometric accuracies, and environmental complexities were used to evaluate the performance of these approaches in a forest plantation. The results from the UAV datasets suggest that DBSCAN-based and height/density-based approaches perform well in tree detection (F1 score > 0.99) and localization (with an accuracy of 0.1 m for point clouds with high geometric accuracy) after fine-tuning the model thresholds; however, the processing time of the latter is much shorter. Even though our new height-difference-based approach introduces more false positives, it obtains a high tree detection rate from UAV datasets without fine-tuning model thresholds. However, due to the limitations of the algorithm, the tree localization accuracy is worse than that of the other two approaches. On the other hand, the results from the Geiger mode dataset with low point density show that the performance of all approaches dramatically deteriorates. Among them, the proposed height-difference-based approach results in the greatest number of true positives and highest F1 score, making it the most suitable approach for low-density point clouds without the need for parameter/threshold fine-tuning.

Rapid development and deployment of vaccines is crucial to control the continuously evolving COVID-19 pandemic. The placebo-controlled phase 3 efficacy trial is still the standard for authorizing vaccines in the majority of the world. However, due to a lack of eligible participants in parts of the world, this has not always been feasible. Recently, the Taiwan Food and Drug Administration, following the consensus of the International Coalition of Medicines Regulatory Authorities (ICMRA), adopted the use of immunobridging studies as acceptable for authorizing COVID-19 vaccines in lieu of efficacy data. Here, we describe a study in which our candidate vaccine, MVC-COV1901, an adjuvanted protein subunit vaccine, has been granted emergency use authorization (EUA) in Taiwan based on a noninferiority immunobridging study. Immunogenicity results from the per protocol immunogenicity (PPI) subset (n = 903) from the MVC-COV1901 phase 2 trial were compared with results from 200 subjects who had received an adenovirus vector vaccine, AstraZeneca ChAdOx nCOV-19 (AZD1222), in a separate study. The lower bound of the 95% confidence interval (CI) of the geometric mean titer (GMT) ratio comparing MVC-COV1901 to AZD1222 was 3.4. The lower bound of the 95% CI of the sero-response rate was 95.5%. Both the GMT ratio and sero-response rate exceeded the criteria established by the Taiwan regulatory authority, leading to EUA approval of MVC-COV1901 in Taiwan.

Abstract Background Several studies examined headaches as a symptom of brain neoplasms. Nevertheless, very few studies attempted to specifically evaluate the role of headaches as a risk factor. This study aimed to investigate the risk of migraine occurrence in the preceding years among patients diagnosed with brain tumors and unaffected controls. Methods Data were obtained from the Taiwan National Health Insurance Research Database. In total, 11,325 adults with a first-time brain tumor diagnosis were included as cases, together with 11,325 unaffected matched controls. Each individual was traced in the healthcare claims dataset for a prior diagnosis of migraines. Conditional logistic regressions were performed to calculate the odds ratio (OR) and the corresponding 95% confidence interval (CI) to present the association between brain tumors and having previously been diagnosed with migraines. Results We found that among patients with and those without brain tumors, 554 (4.89%) and 235 (2.08%) individuals, respectively, were identified as having a prior migraine diagnosis. Compared to unaffected controls, patients with brain tumors experienced an independent 2.45-fold increased risk of having a prior migraine diagnosis. The risks were even higher among men (odds ratio (OR) = 3.04, 95% confidence interval (CI) = 2.29~ 4.04) and after patients who had received a prior migraine diagnosis within 3 years were excluded (OR = 1.91, 95% CI = 1.59~ 2.29). Conclusions This is the first report demonstrating the occurrence of brain tumors to be associated with a prior migraine history, for both men and women, in a population-based study.