Benefits of Hepatitis C Viral Eradication: A Real-World Nationwide Cohort Study in Taiwan.

BACKGROUND: Chronic hepatitis C (CHC) increases the risk of liver cirrhosis (LC) and hepatocellular carcinoma (HCC). This nationwide cohort study assessed the effectiveness of viral eradication of CHC. METHODS: The Taiwanese chronic hepatitis C cohort and Taiwan hepatitis C virus (HCV) registry are nationwide HCV registry cohorts incorporating data from 23 and 53 hospitals in Taiwan, respectively. This study included 27,577 individuals from these cohorts that were given a diagnosis of CHC and with data linked to the Taiwan National Health Insurance Research Database. Patients received either pegylated interferon and ribavirin or direct-acting antiviral agent therapy for > 4 weeks for new-onset LC and liver-related events. RESULTS: Among the 27,577 analyzed patients, 25,461 (92.3%) achieved sustained virologic response (SVR). The mean follow-up duration was 51.2 ± 48.4 months, totaling 118,567 person-years. In the multivariable Cox proportional hazard analysis, the hazard ratio (HR) for incident HCC was 1.39 (95% confidence interval [CI]: 1.00-1.95, p = 0.052) among noncirrhotic patients without SVR compared with those with SVR and 1.82 (95% CI 1.34-2.48) among cirrhotic patients without SVR. The HR for liver-related events, including HCC and decompensated LC, was 1.70 (95% CI 1.30-2.24) among cirrhotic patients without SVR. Patients with SVR had a lower 10-year cumulative incidence of new-onset HCC than those without SVR did (21.7 vs. 38.7% in patients with LC, p < 0.001; 6.0 vs. 18.4% in patients without LC, p < 0.001). CONCLUSION: HCV eradication reduced the incidence of HCC in patients with and without LC and reduced the incidence of liver-related events in patients with LC.

Evaluation of Spectrum-Aided Visual Enhancer (SAVE) in Esophageal Cancer Detection Using YOLO Frameworks.

The early detection of esophageal cancer presents a substantial difficulty, which contributes to its status as a primary cause of cancer-related fatalities. This study used You Only Look Once (YOLO) frameworks, specifically YOLOv5 and YOLOv8, to predict and detect early-stage EC by using a dataset sourced from the Division of Gastroenterology and Hepatology, Ditmanson Medical Foundation, Chia-Yi Christian Hospital. The dataset comprised 2741 white-light images (WLI) and 2741 hyperspectral narrowband images (HSI-NBI). They were divided into 60% training, 20% validation, and 20% test sets to facilitate robust detection. The images were produced using a conversion method called the spectrum-aided vision enhancer (SAVE). This algorithm can transform a WLI into an NBI without requiring a spectrometer or spectral head. The main goal was to identify dysplasia and squamous cell carcinoma (SCC). The model's performance was evaluated using five essential metrics: precision, recall, F1-score, mAP, and the confusion matrix. The experimental results demonstrated that the HSI model exhibited improved learning capabilities for SCC characteristics compared with the original RGB images. Within the YOLO framework, YOLOv5 outperformed YOLOv8, indicating that YOLOv5's design possessed superior feature-learning skills. The YOLOv5 model, when used in conjunction with HSI-NBI, demonstrated the best performance. It achieved a precision rate of 85.1% (CI95: 83.2-87.0%, p < 0.01) in diagnosing SCC and an F1-score of 52.5% (CI95: 50.1-54.9%, p < 0.01) in detecting dysplasia. The results of these figures were much better than those of YOLOv8. YOLOv8 achieved a precision rate of 81.7% (CI95: 79.6-83.8%, p < 0.01) and an F1-score of 49.4% (CI95: 47.0-51.8%, p < 0.05). The YOLOv5 model with HSI demonstrated greater performance than other models in multiple scenarios. This difference was statistically significant, suggesting that the YOLOv5 model with HSI significantly improved detection capabilities.

Association between maternal antidepressant use during pregnancy and the risk of autism spectrum disorder and attention deficit hyperactivity disorder in offspring.

Prenatal antidepressant exposure has been reported to be associated with adverse neurodevelopmental outcomes, yet studies considering confounding factors in Asian populations are lacking. This study utilized a nationwide data base in Taiwan, enrolling all liveborn children registered in the National Health Insurance system between 2004 and 2016. Subjects were divided into two groups: antidepressant-exposed (n = 55,707)) and antidepressant-unexposed group (n = 2,245,689). The effect of antidepressant exposure during different trimesters on autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) was examined. Sibling controls and parallel comparisons by paternal exposure status were treated as negative controls. Additional sensitivity analyses were conducted to examine the effects of antidepressant exposure before and after pregnancy. Prenatal antidepressant exposure was associated with increased risks of ASD and ADHD in population-wide and adjusted analysis. However when comparing antidepressant-exposed children with their unexposed siblings, no differences were found for ASD (Hazard ratio [HR]: 1.04, 95% confidence interval [CI] 0.76-1.42 in first trimester; HR: 0.96, 95% CI 0.62-1.50 in second trimester; HR: 0.69, 95% CI 0.32-1.48 in third trimester) and ADHD (HR: 0.98, 95%CI 0.84-1.15 in first trimester; HR: 0.91, 95% CI 0.73-1.14 in second trimester; HR: 0.79, 95% CI 0.54-1.16 in third trimester). Increased risks for ASD and ADHD were also noted in paternal control, before and after pregnancy analyses. These results imply that the association between prenatal antidepressant exposure and ASD and ADHD is not contributed to by an intrauterine medication effect but more likely to be accounted for by maternal depression, genetic, and potential environmental factors.

Real-World Efficacy and Safety of Universal 8-Week Glecaprevir/Pibrentasvir for Treatment-Naïve Patients from a Nationwide HCV Registry in Taiwan.

INTRODUCTION: Eight-week glecaprevir/pibrentasvir (GLE/PIB) is indicated for treatment-naïve (TN) patients with chronic hepatitis C (CHC), with or without compensated cirrhosis. Given that the Taiwanese government is committed to eliminating hepatitis C virus (HCV) by 2025, this study aimed to measure real-world evidence for TN patients using 8-week GLE/PIB in the Taiwan HCV Registry (TACR). METHODS: The data of patients with CHC treated with 8-week GLE/PIB were retrieved from TACR, a nationwide registry program organized by the Taiwan Association for the Study of the Liver (TASL). Treatment efficacy, defined as a sustained virologic response at posttreatment week 12 (SVR12), was assessed in the modified intention-to-treat (mITT) population, which excluded patients who were lost to follow-up or lacked SVR12 data. The safety profile of the ITT population was assessed. RESULTS: A total of 7246 (6897 without cirrhosis; 349 with cirrhosis) patients received at least one dose of GLE/PIB (ITT), 7204 of whom had SVR12 data available (mITT). The overall SVR12 rate was 98.9% (7122/7204) among all patients, 98.9% (6780/6856) and 98.3% (342/348) among patients without and with cirrhosis, respectively. For the selected subgroups, which included patients with genotype 3 infection, diabetes, chronic kidney disease, people who injected drugs, and those with human immunodeficiency virus coinfection, the SVR12 rates were 95.1% (272/286), 98.9% (1084/1096), 99.0% (1171/1183), 97.4% (566/581), and 96.1% (248/258), respectively. Overall, 14.1% (1021/7246) of the patients experienced adverse events (AEs). Twenty-two patients (0.3%) experienced serious AEs, and 15 events (0.2%) resulted in permanent drug discontinuation. Only one event was considered treatment drug related. CONCLUSION: Eight-week GLE/PIB therapy was effective and well tolerated in all TN patients, regardless of cirrhosis status.

New Scheme of MEMS-Based LiDAR by Synchronized Dual-Laser Beams for Detection Range Enhancement.

A new scheme presents MEMS-based LiDAR with synchronized dual-laser beams for detection range enhancement and precise point-cloud data without using higher laser power. The novel MEMS-based LiDAR module uses the principal laser light to build point-cloud data. In addition, an auxiliary laser light amplifies the single-noise ratio to enhance the detection range. This LiDAR module exhibits the field of view (FOV), angular resolution, and maximum detection distance of 45° (H) × 25° (V), 0.11° (H) × 0.11° (V), and 124 m, respectively. The maximum detection distance is enhanced by 16% from 107 m to 124 m with a laser power of 1 W and an additional auxiliary laser power of 0.355 W. Furthermore, the simulation results show that the maximum detection distance can be up to 300 m with laser power of 8 W and only 6 W if the auxiliary laser light of 2.84 W is used, which is 35.5% of the laser power. This result indicates that the synchronized dual-laser beams can achieve long detection distance and reduce laser power 30%, hence saving on the overall laser system costs. Therefore, the proposed LiDAR module can be applied for a long detection range in autonomous vehicles without requiring higher laser power if it utilizes an auxiliary laser light.

Assessment of Narrow-Band Imaging Algorithm for Video Capsule Endoscopy Based on Decorrelated Color Space for Esophageal Cancer: Part II, Detection and Classification of Esophageal Cancer.

Esophageal carcinoma (EC) is a prominent contributor to cancer-related mortality since it lacks discernible features in its first phases. Multiple studies have shown that narrow-band imaging (NBI) has superior accuracy, sensitivity, and specificity in detecting EC compared to white light imaging (WLI). Thus, this study innovatively employs a color space linked to décor to transform WLIs into NBIs, offering a novel approach to enhance the detection capabilities of EC in its early stages. In this study a total of 3415 WLI along with the corresponding 3415 simulated NBI images were used for analysis combined with the YOLOv5 algorithm to train the WLI images and the NBI images individually showcasing the adaptability of advanced object detection techniques in the context of medical image analysis. The evaluation of the model's performance was based on the produced confusion matrix and five key metrics: precision, recall, specificity, accuracy, and F1-score of the trained model. The model underwent training to accurately identify three specific manifestations of EC, namely dysplasia, squamous cell carcinoma (SCC), and polyps demonstrates a nuanced and targeted analysis, addressing diverse aspects of EC pathology for a more comprehensive understanding. The NBI model effectively enhanced both its recall and accuracy rates in detecting dysplasia cancer, a pre-cancerous stage that might improve the overall five-year survival rate. Conversely, the SCC category decreased its accuracy and recall rate, although the NBI and WLI models performed similarly in recognizing the polyp. The NBI model demonstrated an accuracy of 0.60, 0.81, and 0.66 in the dysplasia, SCC, and polyp categories, respectively. Additionally, it attained a recall rate of 0.40, 0.73, and 0.76 in the same categories. The WLI model demonstrated an accuracy of 0.56, 0.99, and 0.65 in the dysplasia, SCC, and polyp categories, respectively. Additionally, it obtained a recall rate of 0.39, 0.86, and 0.78 in the same categories, respectively. The limited number of training photos is the reason for the suboptimal performance of the NBI model which can be improved by increasing the dataset.

An algorithm for simplified hepatitis C virus treatment with non-specialist care based on nation-wide data from Taiwan.

BACKGROUND: Both European Association for the Study of the Liver (EASL) and American Association for the Study of Liver Diseases and the Infectious Diseases Society of America (AASLD-IDSA) guidelines recommend simplified hepatitis C virus (HCV) treatment with pan-genotypic sofosbuvir/velpatasvir or glecaprevir/pibrentasvir for eligible patients. This observational study used real-world data to assess these regimens' safety in eligible patients and develop an algorithm to identify patients suitable for simplified treatment by non-specialists. METHODS: 7,677 HCV-infected patients from Taiwan Hepatitis C Registry (TACR) who received at least one dose of sofosbuvir/velpatasvir or glecaprevir/pibrentasvir, and fulfilled the EASL/AASLD-IDSA criteria for simplified treatment were analyzed. Multivariate analysis was conducted on patient characteristics and safety data. RESULTS: Overall, 92.8% (7,128/7,677) of patients achieved sustained virological response and only 1.9% (146/7,677) experienced Grades 2-4 laboratory abnormalities in key liver function parameters (alanine aminotransferase, aspartate aminotransferase, and total bilirubin), with only 18 patients (0.23%) experiencing Grades 3-4 abnormalities. Age > 70 years old, presence of hepatocellular carcinoma, total bilirubin > 1.2 mg/dL, estimated glomerular filtration rate < 60 mL/min/1.73 m2, and Fibrosis-4 > 3.25 were associated with higher risks of Grades 2-4 abnormalities. Patients with any of these had an odds of 4.53 times than that of those without in developing Grades 2-4 abnormalities (p < 0.01). CONCLUSIONS: Real-world data from Taiwan confirmed that simplified HCV treatment for eligible patients with pan-genotypic regimens is effective and well tolerated. The TACR algorithm, developed based on this study's results, can further identify patients who can be safely managed by non-specialist care.

Recent progress in unraveling cardiovascular complications associated with primary aldosteronism: a succinct review.

This comprehensive review offers a thorough exploration of recent advancements in our understanding of the intricate cardiovascular complications associated with Primary Aldosteronism (PA). PA encompasses a spectrum of conditions characterized by hypertension and excessive production of aldosterone operating independently of the renin-angiotensin system. Given its association with an elevated risk of cardiovascular and cerebrovascular complications, as well as a higher incidence of metabolic syndrome in comparison to individuals with essential hypertension (EH), an accurate diagnosis of PA is of paramount importance. This review delves into the intricate interplay between PA and cardiovascular health and focuses on the key pathophysiological mechanisms contributing to adverse cardiac outcomes. The impact of different treatment modalities on cardiovascular health is also examined, offering insights into potential therapeutic approaches. By highlighting the significance of recognizing PA as a significant contributor to cardiovascular morbidity, this review emphasizes the need for improved screening, early diagnosis, and tailored management strategies to both enhance patient care and mitigate the burden of cardiovascular diseases. The findings presented herein underscore the growing importance of PA in the context of cardiovascular medicine and emphasize the potential for translating these insights into targeted interventions to improve patient outcomes.

Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program.

BACKGROUND/AIMS: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1-3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. METHODS: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. RESULTS: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. CONCLUSION: Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

The role of confirmatory tests in the diagnosis of primary aldosteronism.

Confirmatory tests for diagnosis of primary aldosteronism (PA) play an important role in sparing patients with a false-positive aldosterone-to-renin ratio (ARR) screening test from undergoing invasive subtyping procedures. We recommend that patients with a positive ARR test should undergo at least one confirmatory test to confirm or exclude the diagnosis of PA before directly proceeding to subtype studies, except for patients with significant PA phenotypes, including spontaneous hypokalemia, plasma aldosterone concentration >20 ng/dL plus plasma renin activity below a detectable level. Although a gold standard confirmatory test has not been identified, we recommend that saline infusion test and captopril challenge test, which were widely used in Taiwan. Patients with PA have been reported to have a higher prevalence of concurrent autonomous cortisol secretion (ACS). ACS is a biochemical condition of mild cortisol overproduction from adrenal lesions, but without the typical clinical features of overt Cushing's syndrome. Concurrent ACS may result in incorrect interpretation of adrenal venous sampling (AVS) and may lead to adrenal insufficiency after adrenalectomy. We recommend screening for ACS in patients with PA scheduled for AVS examinations as well as for adrenalectomy. We recommend the 1-mg overnight dexamethasone suppression test as screening method to detect ACS.

Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer.

The clinical signs and symptoms of esophageal cancer (EC) are often not discernible until the intermediate or advanced phases. The detection of EC in advanced stages significantly decreases the survival rate to below 20%. This study conducts a comparative analysis of the efficacy of several imaging techniques, including white light image (WLI), narrowband imaging (NBI), cycle-consistent adversarial network simulated narrowband image (CNBI), and hyperspectral imaging simulated narrowband image (HNBI), in the early detection of esophageal cancer (EC). In conjunction with Kaohsiung Armed Forces General Hospital, a dataset consisting of 1000 EC pictures was used, including 500 images captured using WLI and 500 images captured using NBI. The CycleGAN model was used to generate the CNBI dataset. Additionally, a novel method for HSI imaging was created with the objective of generating HNBI pictures. The evaluation of the efficacy of these four picture types in early detection of EC was conducted using three indicators: CIEDE2000, entropy, and the structural similarity index measure (SSIM). Results of the CIEDE2000, entropy, and SSIM analyses suggest that using CycleGAN to generate CNBI images and HSI model for creating HNBI images is superior in detecting early esophageal cancer compared to the use of conventional WLI and NBI techniques.

Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imaging.

One of the leading causes of cancer deaths is esophageal cancer (EC) because identifying it in early stage is challenging. Computer-aided diagnosis (CAD) could detect the early stages of EC have been developed in recent years. Therefore, in this study, complete meta-analysis of selected studies that only uses hyperspectral imaging to detect EC is evaluated in terms of their diagnostic test accuracy (DTA). Eight studies are chosen based on the Quadas-2 tool results for systematic DTA analysis, and each of the methods developed in these studies is classified based on the nationality of the data, artificial intelligence, the type of image, the type of cancer detected, and the year of publishing. Deeks' funnel plot, forest plot, and accuracy charts were made. The methods studied in these articles show the automatic diagnosis of EC has a high accuracy, but external validation, which is a prerequisite for real-time clinical applications, is lacking.

Assessment of Narrow Band Imaging Algorithm for Video Capsule Endoscopy Based on Decorrelated Color Space for Esophageal Cancer.

Video capsule endoscopy (VCE) is increasingly used to decrease discomfort among patients owing to its small size. However, VCE has a major drawback of not having narrow band imaging (NBI) functionality. The current VCE has the traditional white light imaging (WLI) only, which has poor performance in the computer-aided detection (CAD) of different types of cancer compared to NBI. Specific cancers, such as esophageal cancer (EC), do not exhibit any early biomarkers, making their early detection difficult. In most cases, the symptoms are unnoticeable, and EC is diagnosed only in later stages, making its 5-year survival rate below 20% on average. NBI filters provide particular wavelengths that increase the contrast and enhance certain features of the mucosa, thereby enabling early identification of EC. However, VCE does not have a slot for NBI functionality because its size cannot be increased. Hence, NBI image conversion from WLI can presently only be achieved in post-processing. In this study, a complete arithmetic assessment of the decorrelated color space was conducted to generate NBI images from WLI images for VCE of the esophagus. Three parameters, structural similarity index metric (SSIM), entropy, and peak-signal-to-noise ratio (PSNR), were used to assess the simulated NBI images. Results show the good performance of the NBI image reproduction method with SSIM, entropy difference, and PSNR values of 93.215%, 4.360, and 28.064 dB, respectively.

Preparing Well for Esophageal Endoscopic Detection Using a Hybrid Model and Transfer Learning.

Early detection of esophageal cancer through endoscopic imaging is pivotal for effective treatment. However, the intricacies of endoscopic diagnosis, contingent on the physician's expertise, pose challenges. Esophageal cancer features often manifest ambiguously, leading to potential confusions with other inflammatory esophageal conditions, thereby complicating diagnostic accuracy. In recent times, computer-aided diagnosis has emerged as a promising solution in medical imaging, particularly within the domain of endoscopy. Nonetheless, contemporary AI-based diagnostic models heavily rely on voluminous data sources, limiting their applicability, especially in scenarios with scarce datasets. To address this limitation, our study introduces novel data training strategies based on transfer learning, tailored to optimize performance with limited data. Additionally, we propose a hybrid model integrating EfficientNet and Vision Transformer networks to enhance prediction accuracy. Conducting rigorous evaluations on a carefully curated dataset comprising 1002 endoscopic images (comprising 650 white-light images and 352 narrow-band images), our model achieved exceptional outcomes. Our combined model achieved an accuracy of 96.32%, precision of 96.44%, recall of 95.70%, and f1-score of 96.04%, surpassing state-of-the-art models and individual components, substantiating its potential for precise medical image classification. The AI-based medical image prediction platform presents several advantageous characteristics, encompassing superior prediction accuracy, a compact model size, and adaptability to low-data scenarios. This research heralds a significant stride in the advancement of computer-aided endoscopic imaging for improved esophageal cancer diagnosis.

IgG4-Related Disease Mimicking Unilateral Urothelial Carcinoma: A Rare Case Report and Literature Review.

Immunoglobulin G4-related disease (IgG4-RD) is an autoimmune-mediated disorder with heterogeneous multiorgan manifestations. Early identification and treatment of IgG4-RD are crucial for organ function recovery. Rarely, IgG4-RD manifests as a unilateral renal pelvic soft tissue mass that may be misdiagnosed as urothelial malignancy, resulting in invasive surgical intervention and organ damage. Here we present a 73-year-old man who had a right ureteropelvic mass with hydronephrosis detected by enhanced computed tomography. Right upper tract urothelial carcinoma and lymph node metastasis was highly suggested based on the image findings. However, IgG4-RD was suspected due to his past history of bilateral submandibular lymphadenopathy, nasolacrimal duct obstruction, as well as a high serum IgG4 level of 861 mg/dL. The ureteroscopy with tissue biopsy showed no evidence of urothelial malignancy. His lesions and symptoms improved after glucocorticoid treatment. Hence, a diagnosis of IgG4-RD was made, with the phenotype of classic Mikulicz syndrome with systemic involvement. The manifestation of IgG4-RD as a unilateral renal pelvic mass is rare and should be kept in mind. A ureteroscopic biopsy and serum IgG4 level measurement can help in the diagnosis of IgG4-RD in patients with a unilateral renal pelvic lesion.

Tensins in Kidney Function and Diseases.

Tensins are focal adhesion proteins that regulate various biological processes, such as mechanical sensing, cell adhesion, migration, invasion, and proliferation, through their multiple binding activities that transduce critical signals across the plasma membrane. When these molecular interactions and/or mediated signaling are disrupted, cellular activities and tissue functions are compromised, leading to disease development. Here, we focus on the significance of the tensin family in renal function and diseases. The expression pattern of each tensin in the kidney, their roles in chronic kidney diseases, renal cell carcinoma, and their potentials as prognostic markers and/or therapeutic targets are discussed in this review.

Treatment effectiveness and side effects of patients with hepatitis C in the prisons of Southern Taiwan: a real-life retrospective analysis.

OBJECTIVE: Hepatitis C is an important risk factor for cirrhosis and liver cancer in the Taiwanese population. Domestic prisons reported a higher rate of hepatitis C infection than the national average. Efficient and effective treatment of patients with hepatitis C in prisons is required to decrease the number of infections. This study analysed the effectiveness of hepatitis C treatment and its side effects in prison patients. DESIGN: This retrospective analysis included adult patients with hepatitis C who received direct-acting antiviral agents between 2018 and 2021. SETTING: The special hepatitis C clinics in the two prisons were run by a medium-sized hepatitis C treatment hospital in Southern Taiwan. Three direct-acting antiviral agents, sofosbuvir/ledipasvir for 12 weeks, glecaprevir/pibrentasvir for 8 or 12 weeks and sofosbuvir/velpatasvir for 12 weeks, were adopted based on patient characteristics. PARTICIPANTS: 470 patients were included. OUTCOME MEASURE: The sustained virological response at 12 weeks after the end of treatment was compared between the different groups. RESULTS: Most of the patients were men (70.0%) with a median age of 44 years. The most prevalent hepatitis C virus genotype was genotype 1 (44.26%). A total of 240 patients (51.06%) had a history of injectable drug use; 44 (9.36%) and 71 (15.11%) patients were coinfected with hepatitis B virus and HIV, respectively. Only 51 patients (10.85%) had liver cirrhosis. Most patients (98.30%) had normal renal function or no history of kidney disease. The patients had a sustained virological response achievement rate of 99.2%. The average incidence of adverse reactions during treatment was approximately 10%. Many of the adverse reactions were mild and resolved spontaneously. CONCLUSION: Direct-acting antiviral agents are effective for treating hepatitis C in Taiwanese prisoners. These therapeutics were well-tolerated by the patient population.

Large area MoS2 thin film growth by direct sulfurization.

In this study, we present the growth of monolayer MoS2 (molybdenum disulfide) film. Mo (molybdenum) film was formed on a sapphire substrate through e-beam evaporation, and triangular MoS2 film was grown by direct sulfurization. First, the growth of MoS2 was observed under an optical microscope. The number of MoS2 layers was analyzed by Raman spectrum, atomic force microscope (AFM), and photoluminescence spectroscopy (PL) measurement. Different sapphire substrate regions have different growth conditions of MoS2. The growth of MoS2 is optimized by controlling the amount and location of precursors, adjusting the appropriate growing temperature and time, and establishing proper ventilation. Experimental results show the successful growth of a large-area single-layer MoS2 on a sapphire substrate through direct sulfurization under a suitable environment. The thickness of the MoS2 film determined by AFM measurement is about 0.73 nm. The peak difference between the Raman measurement shift of 386 and 405 cm-1 is 19.1 cm-1, and the peak of PL measurement is about 677 nm, which is converted into energy of 1.83 eV, which is the size of the direct energy gap of the MoS2 thin film. The results verify the distribution of the number of grown layers. Based on the observation of the optical microscope (OM) images, MoS2 continuously grows from a single layer of discretely distributed triangular single-crystal grains into a single-layer large-area MoS2 film. This work provides a reference for growing MoS2 in a large area. We expect to apply this structure to various heterojunctions, sensors, solar cells, and thin-film transistors.