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Magnetic resonance cholangiopancreatography (MRCP) is a useful and non-invasive method to diagnose biliary atresia (BA) in term infants, however few studies have investigated its use in preterm infants. This study aimed to evaluate the accuracy of MRCP in the diagnosis of BA in preterm infants with cholestasis.Infants aged less than 6 months who received MRCP for cholestasis at a tertiary medical center were enrolled from 2011 to 2020. Demographic and laboratory data were retrospectively obtained. One pediatric radiologist reviewed the MRCP images. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of MRCP to diagnose BA based on surgical proof or at least 6 months of follow-up were assessed.A total of 80 infants (36 preterm and 44 term) were analyzed. The mean post-chronological age was 1.8 months, and the female-to-male ratio was 0.78. Six (16.7%) preterm and 16 (36.4%) term infants were confirmed to have BA. BA was obscured by a choledochal cyst preoperatively in two term infants. In the preterm infants, the sensitivity, specificity, PPV, NPV, and accuracy of MRCP to diagnose BA were 100%, 77%, 46%, 100%, and 81%, respectively, compared to 81%, 86%, 76%, 89%, and 84% in the term infants. Using MRCP to differentiate BA from other cholestasis in the preterm infants had superior sensitivity (100% vs. 81%) and NPV (100% vs. 89%), and lower specificity (77% vs. 86%) and PPV (46% vs. 76%) than in the term infants.Negative MRCP findings can be used to exclude BA in preterm infants with cholestasis based on a favorable NPV.

BACKGROUND Atherosclerosis and vascular inflammatory response have been considered as risk factors for non-typhoidal Salmonella (NTS) vascular infection. The study aims to assess the risk of vascular infection by measuring atherosclerosis severity, NTS vascular infection (NTSVI) score, and serum levels of inflammatory markers in people with NTS bacteremia. METHODS A prospective observational study was conducted in two medical centers and two regional hospitals. Adults aged ≥50 years with NTS bacteremia who underwent computed tomography (CT) scan for revealing vascular infections were enrolled. The degree of atherosclerosis was scaled by a calcium score determined by a CT scan. Serum concentrations of inflammatory biomarkers were determined in the patients enrolled in a medical center. RESULTS Fourteen (20.3%) of 69 patients with NTS bacteremia had vascular infections. Calcium scores over the thoracic (12,540 vs. 3,261, P = 0.0005) and abdominal (9755 vs. 3,461, P = 0.0006) aorta of those with vascular infections were higher than those without vascular infection. All vascular infections were present in the high-risk group (NTSVI score ≥1), yielding a sensitivity of 100% and specificity of 30.9%. Among 17 low-risk patients (NTSVI score

Background Cancer-specific adoptive T cell therapy has achieved successful milestones in multiple clinical treatments. However, the commercial production of cancer-specific T cells is often hampered by laborious cell culture procedures, the concern of retrovirus-based gene transfection, or insufficient T cell purity. Methods In this study, we developed a non-genetic engineering technology for rapidly manufacturing a large amount of cancer-specific T cells by utilizing a unique anti-cancer/anti-CD3 bispecific antibody (BsAb) to directly culture human peripheral blood mononuclear cells (PBMCs). The anti-CD3 moiety of the BsAb bound to the T cell surface and stimulated the differentiation and proliferation of T cells in PBMCs. The anti-cancer moiety of the BsAb provided these BsAb-armed T cells with the cancer-targeting ability, which transformed the naïve T cells into cancer-specific BsAb-armed T cells. Results With this technology, a large amount of cancer-specific BsAb-armed T cells can be rapidly generated with a purity of over 90% in 7 days. These BsAb-armed T cells efficiently accumulated at the tumor site both in vitro and in vivo. Cytotoxins (perforin and granzyme) and cytokines (TNF-α and IFN-γ) were dramatically released from the BsAb-armed T cells after engaging cancer cells, resulting in a remarkable anti-cancer efficacy. Notably, the BsAb-armed T cells did not cause obvious cytokine release syndrome or tissue toxicity in SCID mice bearing human tumors. Conclusions Collectively, the BsAb-armed T cell technology represents a simple, time-saving, and highly safe method to generate highly pure cancer-specific effector T cells, thereby providing an affordable T cell immunotherapy to patients.

Learning analytics (LA) has gained increasing attention for its potential to improve different educational aspects (e.g., students’ performance and teaching practice). The existing literature identified some factors that are associated with the adoption of LA in higher education, such as stakeholder engagement and transparency in data use. The broad literature on information systems also emphasizes the importance of trust as a critical predictor of technology adoption. However, the extent to which trust plays a role in the adoption of LA in higher education has not been examined in detail in previous research. To fill this literature gap, we conducted a mixed method (survey and interviews) study aimed to explore how much teaching staff trust LA stakeholders (e.g., higher education institutions or third-parties) and LA technology, as well as the trust factors that could hinder or enable adoption of LA. The findings show that the teaching staff had a high level of trust in the competence of higher education institutions and the usefulness of LA; however, the teaching staff had a low level of trust in third parties that are involved in LA (e.g., external technology vendors) in terms of handling privacy and ethics-related issues. They also had a low level of trust in data accuracy due to issues such as outdated data and lack of data governance. The findings have strategic implications for institutional leaders and third parties in the adoption of LA by providing recommendations to increase trust, such as, improving data accuracy, developing policies for data sharing and ownership, enhancing the consent-seeking process, and establishing data governance guidelines. Therefore, this study contributes to the literature on the adoption of LA in HEIs by integrating trust factors.

Educational feedback has been widely acknowledged as an effective approach to improving student learning. However, scaling effective practices can be laborious and costly, which motivated researchers to work on automated feedback systems (AFS). Inspired by the recent advancements in the pre-trained language models (e.g., ChatGPT), we posit that such models might advance the existing knowledge of textual feedback generation in AFS because of their capability to offer natural-sounding and detailed responses. Therefore, we aimed to investigate the feasibility of using ChatGPT to provide students with feedback to help them learn better. Specifically, we first examined the readability of ChatGPT-generated feedback. Then, we measured the agreement between ChatGPT and the instructor when assessing students' assignments according to the marking rubric. Finally, we used a well-known theoretical feedback framework to further investigate the effectiveness of the feedback generated by ChatGPT. Our results show that i) ChatGPT is capable of generating more detailed feedback that fluently and coherently summarizes students' performance than human instructors; ii) ChatGPT achieved high agreement with the instructor when assessing the topic of students' assignments; and iii) ChatGPT could provide feedback on the process of students completing the task, which benefits students developing learning skills.

Learning Analytics (LA) is an emerging field concerned with measuring, collecting, and analysing data about learners and their contexts to gain insights into learning processes. As the technology of Learning Analytics is evolving, many systems are being implemented. In this context, it is essential to understand stakeholders' expectations of LA across Higher Education Institutions (HEIs) for large-scale implementations that take their needs into account. This study aims to contribute to knowledge about individual LA expectations of European higher education students. It may facilitate the strategy of stakeholder buy-in, the transfer of LA insights across HEIs, and the development of international best practices and guidelines. To this end, the study employs a ‘Student Expectations of Learning Analytics Questionnaire’ (SELAQ) survey of 417 students at the Goethe University Frankfurt (Germany) Based on this data, Multiple Linear Regressions are applied to determine how these students position themselves compared to students from Madrid (Spain), Edinburgh (United Kingdom) and the Netherlands, where SELAQ had already been implemented at HEIs. The results show that students' expectations at Goethe University Frankfurt are rather homogeneous regarding ‘LA Ethics and Privacy’ and ‘LA Service Features’. Furthermore, we found that European students generally show a consistent pattern of expectations of LA with a high degree of similarity across the HEIs examined. European HEIs face challenges more similar than anticipated. The HEI experience with implementing LA can be more easily transferred to other HEIs, suggesting standardized LA rather than tailor-made solutions designed from scratch. (DIPF/Orig.) Learning Analytics (LA) ist ein junger Forschungsbereich, der sich mit dem Messen, Sammeln und Analysieren von Daten über Lernende und ihr Umfeld befasst, um Erkenntnisse über Lernprozesse zu gewinnen. Da sich die Learning-Analytics-Technologie weiterentwickelt, werden derzeit viele Systeme implementiert. In diesem Zusammenhang ist es von entscheidender Bedeutung, die Erwartungen von Stakeholdern an LA in den Hochschulen zu verstehen, um groß angelegte Implementierungen zu ermöglichen, die ihren Bedürfnissen Rechnung tragen. Diese Studie soll einen Beitrag zum Wissen über die individuellen Erwartungen der europäischen Hochschulstudenten an LA leisten. Sie kann die Strategie der Einbindung von Interessengruppen, den Transfer von LA-Erkenntnissen zwischen Hochschulen und die Entwicklung von internationalen Best Practices und Richtlinien erleichtern. Zu diesem Zweck wird in der Studie der "Student Expectations of Learning Analytics Questionnaire" (SELAQ) eingesetzt, mit dem 417 Studierende der Goethe-Universität Frankfurt (Deutschland) befragt wurden. Auf Grundlage dieser Daten werden Multiple Lineare Regressionen erstellt, um zu vergleichen, wie sich diese Studierenden zu Studierenden aus Madrid (Spanien), Edinburgh (Vereinigtes Königreich) und den Niederlanden positionieren, wo SELAQ-Umfragen bereits an Hochschulen durchgeführt wurden. Die Ergebnisse zeigen, dass die Erwartungen der Studierenden an der Goethe-Universität Frankfurt in Bezug auf die Themen "Ethik und Datenschutz" und "LA-Servicemerkmale" recht homogen sind. Darüber hinaus haben wir festgestellt, dass die europäischen Studierenden im Allgemeinen ein konsistentes Muster von Erwartungen an LA zeigen, das sich über die untersuchten Hochschulen hinweg stark ähnelt. Die Herausforderungen für europäische Hochschulen sind ähnlicher als erwartet. Die Erfahrungen der Hochschulen mit der Implementierung von LA lassen sich leichter auf andere Hochschulen übertragen, was eher für standardisierte LA spricht als für maßgeschneiderte Lösungen, die von Grund auf neu entwickelt werden. (Autor*innen)

Background The metabolome is the best representation of cancer phenotypes. Gene expression can be considered a confounding covariate affecting metabolite levels. Data integration across metabolomics and genomics to establish the biological relevance of cancer metabolism is challenging. This study aimed to eliminate the confounding effect of metabolic gene expression to reflect actual metabolite levels in microsatellite instability (MSI) cancers. Methods In this study, we propose a new strategy using covariate-adjusted tensor classification in high dimensions (CATCH) models to integrate metabolite and metabolic gene expression data to classify MSI and microsatellite stability (MSS) cancers. We used datasets from the Cancer Cell Line Encyclopedia (CCLE) phase II project and treated metabolomic data as tensor predictors and data on gene expression of metabolic enzymes as confounding covariates. Results The CATCH model performed well, with high accuracy (0.82), sensitivity (0.66), specificity (0.88), precision (0.65), and F1 score (0.65). Seven metabolite features adjusted for metabolic gene expression, namely, 3-phosphoglycerate, 6-phosphogluconate, cholesterol ester, lysophosphatidylethanolamine (LPE), phosphatidylcholine, reduced glutathione, and sarcosine, were found in MSI cancers. Only one metabolite, Hippurate, was present in MSS cancers. The gene expression of phosphofructokinase 1 (PFKP), which is involved in the glycolytic pathway, was related to 3-phosphoglycerate. ALDH4A1 and GPT2 were associated with sarcosine. LPE was associated with the expression of CHPT1, which is involved in lipid metabolism. The glycolysis, nucleotide, glutamate, and lipid metabolic pathways were enriched in MSI cancers. Conclusions We propose an effective CATCH model for predicting MSI cancer status. By controlling the confounding effect of metabolic gene expression, we identified cancer metabolic biomarkers and therapeutic targets. In addition, we provided the possible biology and genetics of MSI cancer metabolism.

Sarcopenia is defined as the loss of skeletal muscle mass and muscle function. It is common in patients with malignancies and often associated with adverse clinical outcomes. The presence of sarcopenia in patients with cancer is determined by body composition, and recently, radiologic technology for the accurate estimation of body composition is under development. Artificial intelligence- (AI-) assisted image measurement facilitates the detection of sarcopenia in clinical practice. Sarcopenia is a prognostic factor for patients with cancer, and confirming its presence helps to recognize those patients at the greatest risk, which provides a guide for designing individualized cancer treatments. In this review, we examine the recent literature (2017-2021) on AI-assisted image assessment of body composition and sarcopenia, seeking to synthesize current information on the mechanism and the importance of sarcopenia, its diagnostic image markers, and the interventions for sarcopenia in the medical care of patients with cancer. We concluded that AI-assisted image analysis is a reliable automatic technique for segmentation of abdominal adipose tissue. It has the potential to improve diagnosis of sarcopenia and facilitates identification of oncology patients at the greatest risk, supporting individualized prevention planning and treatment evaluation. The capability of AI approaches in analyzing series of big data and extracting features beyond manual skills would no doubt progressively provide impactful information and greatly refine the standard for assessing sarcopenia risk in patients with cancer.

Feedback is an effective way to assist students in achieving learning goals. The conceptualisation of feedback is gradually moving from feedback as information to feedback as a learner-centred process. To demonstrate feedback effectiveness, feedback as a learner-centred process should be designed to provide quality feedback content and promote student learning outcomes on the subsequent task. However, it remains unclear how instructors adopt the learner-centred feedback framework for feedback provision in the teaching practice. Thus, our study made use of a comprehensive learner-centred feedback framework to analyse feedback content and identify the characteristics of feedback content among student groups with different performance changes. Specifically, we collected the instructors' feedback on two consecutive assignments offered by an introductory to data science course at the postgraduate level. On the basis of the first assignment, we used the status of student grade changes (i.e., students whose performance increased and those whose performance did not increase on the second assignment) as the proxy of the student learning outcomes. Then, we engineered and extracted features from the feedback content on the first assignment using a learner-centred feedback framework and further examined the differences of these features between different groups of student learning outcomes. Lastly, we used the features to predict student learning outcomes by using widely-used machine learning models and provided the interpretation of predicted results by using the SHapley Additive exPlanations (SHAP) framework. We found that 1) most features from the feedback content presented significant differences between the groups of student learning outcomes, 2) the gradient boost tree model could effectively predict student learning outcomes, and 3) SHAP could transparently interpret the feature importance on predictions.

The adoption of learning analytics (LA) in complex educational systems is woven into sociocultural and technical challenges that have induced distrust in data and difficulties in scaling LA. This paper presents a study that investigated areas of distrust and threats to trustworthy LA through a series of consultations with teaching staff and students at a large UK university. Surveys and focus groups were conducted to explore participant expectations of LA. The observed distrust is broadly attributed to three areas: the subjective nature of numbers, the fear of power diminution, and approaches to design and implementation of LA. The paper highlights areas to maintain existing trust with policy procedures and areas to cultivate trust by engaging with tensions arising from the social process of LA.

Background. Radiation using conventional X-ray is associated with exposure of radiosensitive organs and typically requires the use of protection. This study is aimed at evaluating the use of bismuth shielding for radiation protection in pediatric pelvic radiography. The effects of the anteroposterior and lateral bismuth shielding were verified by direct measurements at the anatomical position of the gonads. Methods. Radiation doses were measured using optically stimulated luminescence dosimeters (OSLD) and CIRS ATOM Dosimetry Verification Phantoms. Gonad radiographs were acquired using different shields of varying material (lead, bismuth) and thickness and were compared with radiographs obtained without shielding to examine the effects on image quality and optimal reduction of radiation dose. All images were evaluated separately by three pediatric orthopedic practitioners. Results. Results showed that conventional lead gonadal shielding reduces radiation doses by 67.45%, whereas dose reduction using one layer of bismuth shielding is 76.38%. The use of two layers of bismuth shielding reduces the dose by 84.01%. Using three and four layers of bismuth shielding reduces dose by 97.33% and 99.34%, respectively. Progressively lower radiation doses can be achieved by increasing the number of bismuth layers. Images obtained using both one and two layers of bismuth shielding provided adequate diagnostic information, but those obtained using three or four layers of bismuth shielding were inadequate for diagnosis. Conclusions. Bismuth shielding reduces radiation dose exposure providing appropriate protection for children undergoing pelvic radiography. The bismuth shielding material is lighter than lead, making pediatric patients more comfortable and less apt to move, thereby avoiding repeat radiography.

The high accessibility to healthcare and increasing awareness of hepatocellular carcinoma (HCC) surveillance after sustained virologic response (SVR) to HCV treatment allow early detection of operable HCC in Taiwan. However, the effects of achieving SVR on patient characteristics and surgical outcomes after curative resection remain elusive. We aimed to compare the clinical presentation and postoperative prognosis among patients with early-stage HCV-related HCC and different viral status. We retrospectively analyzed 208 patients with BCLC stage 0 or A-HCC, including 44 patients who remained HCV viremic, 90 patients who developed HCC after achieving SVR (post-SVR HCC), and 74 patients who subsequently achieved SVR after resection. Patients with post-SVR HCC had a lower degree of hepatitis and better liver function than those who achieved SVR or remained viremic after resection. Notably, 75.6% of patients with post-SVR HCC did not have cirrhosis. Patients with post-SVR HCC and those achieving SVR after resection exhibited comparable recurrence rates and recurrence-free survival, while patients with persistent viremia had the worst surgical outcomes. We concluded that patients with post-SVR HCC had a better liver function but similar surgical outcomes compared with patients who achieved SVR after resection. The low prevalence of cirrhosis in patients with post-SVR HCC highlights the importance of regular surveillance after SVR.

Type I Chiari malformation (CM-I) consists of downward herniation of the cerebellar tonsils below the foramen magnum and often requires surgical decompression if symptomatic. Spontaneous resolution of CM-I is rare. We present a case of resolved CM-I without surgery in a 6-year-old boy with B-cell lymphoma who was diagnosed with CM-I during lymphoma staging. Cerebrospinal fluid cytology and brain MRI revealed negative CNS involvement but showed CM-I with tonsillar ectopia 19 mm below the foramen magnum. The patient underwent induction chemotherapy including 5 doses of intrathecal chemotherapy. Follow-up MRI demonstrated marked regression of CM-I to less than 6 mm in 3 months, and complete resolution of CM-I was observed in 2 years. To the best of our knowledge, this is the first case of resolved CM-I and syringomyelia following chemotherapy. In this case report, the authors summarize all of the clinical characteristics, the radiological appearance, and the potential causes of resolution based on a review of the literature and propose the mechanisms through which intrathecal chemotherapy contributed to the CM-I and syringomyelia resolution in the present case.

Coronavirus Disease-19 (COVID-19) has been in a global pandemic currently and relating symptoms were reported variously around the world. We reported a previously healthy man of COVID-19 presenting with anosmia as the obvious symptom with relevant radiological findings on brain magnetic resonance imaging.

To evaluate whether adjusted computed tomography (CT) scan image-based radiomics combined with immune genomic expression can achieve accurate stratification of cancer recurrence and identify potential therapeutic targets in stage III colorectal cancer (CRC), this cohort study enrolled 71 patients with postoperative stage III CRC. Based on preoperative CT scans, radiomic features were extracted and selected to build pixel image data using covariate-adjusted tensor classification in the high-dimension (CATCH) model. The differentially expressed RNA genes, as radiomic covariates, were identified by cancer recurrence. Predictive models were built using the pixel image and immune genomic expression factors, and the area under the curve (AUC) and F1 score were used to evaluate their performance. Significantly adjusted radiomic features were selected to predict recurrence. The association between the significantly adjusted radiomic features and immune gene expression was also investigated. Overall, 1037 radiomic features were converted into 33 × 32-pixel image data. Thirty differentially expressed genes were identified. We performed 100 iterations of 3-fold cross-validation to evaluate the performance of the CATCH model, which showed a high sensitivity of 0.66 and an F1 score of 0.69. The area under the curve (AUC) was 0.56. Overall, ten adjusted radiomic features were significantly associated with cancer recurrence in the CATCH model. All of these methods are texture-associated radiomics. Compared with non-adjusted radiomics, 7 out of 10 adjusted radiomic features influenced recurrence-free survival. The adjusted radiomic features were positively associated with PECAM1, PRDM1, AIF1, IL10, ISG20, and TLR8 expression. We provide individualized cancer therapeutic strategies based on adjusted radiomic features in recurrent stage III CRC. Adjusted CT scan image-based radiomics with immune genomic expression covariates using the CATCH model can efficiently predict cancer recurrence. The correlation between adjusted radiomic features and immune genomic expression can provide biological relevance and individualized therapeutic targets.

Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning analytics method proposed for detecting learning tactics and strategies from trace data. The method was applied to the datasets collected in three different course designs and delivery modalities, including flipped classroom, blended learning, and massive open online course. The proposed method combines process mining and sequence analysis. The detected learning strategies are explored in terms of their association with academic performance. The results indicate the applicability of the proposed method across different learning contexts. Moreover, the findings contribute to the understanding of the learning tactics and strategies identified in the trace data: learning tactics proved to be responsive to the course design, whereas learning strategies were found to be more sensitive to the delivery modalities than to the course design. These findings, well aligned with self-regulated learning theory, highlight the association of learning contexts with the choice of learning tactics and strategies.

BACKGROUND AND AIM The serial serologic changes of hepatitis D virus (HDV) infection among chronic hepatitis B virus (HBV) infected patients who received oral nucleotide/nucleoside analogues are elusive. METHODS Serum anti-HDV and HDV RNA among chronic hepatitis B (CHB) patients were tested at the time of initiating anti-HBV therapy and subsequently during the follow-up period. RESULTS The seropositive rate of anti-HDV and HDV RNA among 2850 CHB patients, was 2.7% and 0.9%, respectively. Factors associated with anti-HDV seropositivity were platelet counts (odds ratio [OR]/95% confidence intervals [CI]: 0.995/0.992-0.999; P = 0.006), HBV DNA levels (OR/CI: 0.81/0.70-0.94; P = 0.005), and hepatitis B e-antigen (HBeAg) seropositivity (OR/CI: 0.22/0.05-0.95; P = 0.04). The only factor associated with HDV RNA positivity among anti-HDV seropositive patients was age (OR/CI: 0.95/0.90-1.00; P = 0.03). The spontaneous clearance rate of serum anti-HDV antibody was 3.0 per 100 person-years with a median follow-up period of 3.5 years (range 2-12 years), whereas the seroclearance rate of HDV RNA was 4.3 per 100 person-years among anti-HDV seropositive patients after a median follow-up period of 6.0 years (range 2-11 years). A baseline anti-HDV titer

Background Primary cardiac angiosarcoma is a rare primary cardiac malignancy. Biopsy of such vascular-rich tumours may result in serious complications. Case summary This is a case of a 43-year-old woman who presented with syncope. According to clinical history, she initially had massive pericardial effusion, with an uncertain aetiology. Multimodality imaging at our hospital revealed a cauliflower-like tumour in the right atrium. Coronary angiography results confirmed multiple feeding vessels from the right coronary artery to the tumour. Thoracoscopic biopsy resulted in a massive bleeding requiring haemostasis via thoracotomy. Histopathological examination of the specimen showed an angiosarcoma with atypical cells and spindle cells in a myxomatous background. Treatment with systemic targeted therapy and chemotherapy was initiated, and the patient is still under active treatment. Discussion Cardiac angiosarcomas most commonly arise from the right atrium and may be hard to detect with transthoracic echocardiography. Biopsy of primary cardiac angiosarcomas requires careful planning because they are highly vascularized. Currently, no guidelines regarding the treatment of such tumours exist, and a multidisciplinary treatment is needed.

Feedback plays a crucial role in learning. Yet, higher education continues to face challenges regarding facilitating effective feedback processes. One of the challenges is the difficulty to track how students interact with feedback and the impact of feedback on learning outcomes. Learning analytics (LA) has opened up opportunities to enhance feedback practice with a wide array of data. However, most research seeks to deliver data-driven feedback rather than understanding how students make use of feedback and how educators can use learning analytics to support students in this process. As a first step to address this gap, our study investigated educators’ views of challenges and elements of effective feedback processes in addition to their perceptions of data-driven feedback. The study found that feedback design (e.g., feedback purpose, content, and structure), educator-related factors (e.g., time constraints and resource limitations), and student-related factors (e.g., disposition, self-regulation, and sense-making) can have positive or negative impacts on the feedback process. It also highlights the need for the development of student feedback literacy. Based on the findings, we proposed ideas for an LA-based feedback tool that can be used to facilitate a dialogic feedback process and address challenges with feedback.

Background: The aim of this study was to evaluate the impact of adverse lifestyle factors on outcomes in patients with human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (OPSCC). Methods: From 2010 to 2019, 150 consecutive non-metastatic OPSCC patients receiving curative treatment in our institution were retrospectively enrolled. HPV positivity was defined as p16 expression ≥75%. The effects of adverse lifestyle factors on overall survival (OS) and disease-free survival (DFS) on OPSCC patients were determined. Results: The median follow-up duration was 3.6 years. Of the 150 OPSCCs, 51 (34%) patients were HPV-positive and 99 (66%) were HPV-negative. The adverse lifestyle exposure rates were 74.7% (n = 112) alcohol use, 57.3% (n = 86) betel grid chewing, and 78% (n = 117) cigarette smoking. Alcohol use strongly interacted with HPV positivity (HR, 6.00; 95% CI, 1.03–35.01), leading to an average 26.1% increased risk of disease relapse in patients with HPV-positive OPSCC. Heavy smoking age ≥30 pack-years was associated with increased risk of death (HR, 2.05; 95% CI, 1.05–4.00) and disease relapse (HR, 1.99; 95% CI, 1.06–3.75) in OPSCC patients. In stratified analyses, the 3-year absolute risk of disease relapse in HPV-positive OPSCC patients reached up to 50% when alcohol use and heavy smoking for ≥30 pack-years were combined. Conclusions: Alcohol acted as a significant treatment-effect modifier for DFS in HPV-positive OPSCC patients, diluting the favorable prognostic effect of HPV positivity. Heavy smoking age ≥30 pack-years was an independent adverse prognostic factor of OS and DFS in OPSCC patients. De-intensification treatment for HPV-related OPSCC may be avoided when these adverse lifestyle factors are present.

Background One-handed backhand (OB) and two-handed backhand (TB) styles are commonly used in tennis, but only TB generates loadings on the non-dominant arm and a greater extension torque on the rear leg, leading to a greater axial torque involving rotation of the hip and trunk. The current study investigated whether those effects can further affect bone area (BA), bone mineral content (BMC) and density (BMD) in postmenopausal recreational tennis players. Methods BA, BMC and BMD of the lumbar spine, hip and distal radius were assessed using dual-energy X-ray absorptiometry in TB, OB, and swimmers’ group as a control (SG) (all participants self-reported for at least 5 years of exercise history, n = 14 per group). Muscular strength was assessed with a hand dynamometer. Among these three groups, the BA, BMC and BMD of distal radius and muscle strength were assessed using one-way ANOVA, and those of the lumbar region and the hip joint were tested by one-way ANCOVA. Results TB showed higher BMC and BMD for both lumbar spine and femoral neck than SG (all, p p p p Conclusion For postmenopausal women, performing two-handed backhand strokes, leads to higher BMC and BMD in the non-dominant arm, the lumbar region, and hips, indicating potential benefit to maintain bone health and strength. Whether this result leads to reducing the risk of osteoporosis needs to be investigated in further research.

OBJECTIVES This study aimed to evaluate the feasibility of automatic Stanford classification of classic aortic dissection (AD) using a 2-step hierarchical neural network. METHODS Between 2015 and 2019, 130 arterial phase series (57 type A, 43 type B, and 30 negative cases) in aortic CTA were collected for the training and validation. A 2-step hierarchical model was built including the first step detecting AD and the second step predicting the probability (0-1) of Stanford types. The model's performance was evaluated with an off-line prospective test in 2020. The sensitivity and specificity for Stanford type A, type B, and no AD (Sens A, B, N and Spec A, B, N, respectively) and Cohen's kappa were reported. RESULTS Of 298 cases (22 with type A, 29 with type B, and 247 without AD) in the off-line prospective test, the Sens A, Sens B, and Sens N were 95.45% (95% confidence interval [CI], 77.16-99.88%), 79.31% (95% CI, 60.28-92.01%), and 93.52% (95% CI, 89.69-96.25%), respectively. The Spec A, Spec B, and Spec N were 98.55% (95% CI, 96.33-99.60%), 94.05% (95% CI, 90.52-96.56%), and 94.12% (95% CI, 83.76-98.77%), respectively. The classification rate achieved 92.28% (95% CI, 88.64-95.04%). The Cohen's kappa was 0.766 (95% CI, 0.68-0.85; p

The emergence of personalised data technologies, such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related decisions and ‘datafying’ students in the process of collecting, analysing and interpreting data. This paper presents a study that explores staff and student experience of agency, equity, and transparency in existing data practices and expectations towards learning analytics in a UK university. The results show a number of intertwined factors that have contributed to the tensions between enhancing a learner’s control of their studies and, at the same time, diminishing their autonomy as an active agent in the process of learning analytics. This paper argues that learner empowerment should not be automatically assumed to have taken place as part of the adoption of learning analytics. Instead, the interwoven power relationships in a complex educational system and the interactions between humans and machines need to be taken into consideration when presenting learning analytics as an equitable process to enhance student agency and educational equity.

HfO2-based ferroelectric field-effect transistors (FeFET) on Si were employed as the platform to investigate the impact of 60Co $\gamma $ -rays radiation on memory characteristics. For pristine state, the memory window by ±4 V sweeping for non-irradiated devices is 1.48 V which does not degrade with 300-krad and 10-Mrad radiation dose even though the remnant polarization ( $\text{P}_{\textsf {r}}$ ) decreases due to radiation-induced oxygen vacancies (Vo) and lattice distortion in the ferroelectric material HfZrOx (HZO). With the radiation dose level, the devices still hold the current ratio between “1” and “0” state of $2.2\times 10^{\textsf {3}}$ by extrapolating to 10 years at 25 °C, which is comparable to that of non-irradiated devices. The most adverse effect of radiation is the deteriorated endurance caused by the increased number of Vo during cycling test (+5.5 V, −5 V/ $10~\mu \text{s}$ ) as evidenced by memory window of 0.52 V at 106 cycles for devices with 300-krad radiation dose. Furthermore, robust HZO and SiOx interacial layer against radiation is required to suppress the bond break so that the reliability can be improved.

Sorafenib is currently the first‐line therapy for advanced hepatocellular carcinoma (aHCC) patients. However, the outcomes and prognostic factors of sorafenib therapy have not been well investigated. We aimed to investigate the pretreatment factors and outcomes among Taiwanese aHCC patients receiving sorafenib treatment. A total of 347 patients with aHCC and well‐compensated liver cirrhosis (Child‐Pugh A) status receiving sorafenib were consecutively enrolled from March 2013 through December 2016. Pre‐treatment clinical data and viral hepatitis markers were collected and analyzed with their outcomes. The primary endpoint of the study was overall survival. The factors associated with overall survival were also investigated. The median overall survival of all the patients was 238 days (range, 9‐1504 days) with a 1‐year overall survival of 43.2%. Positive hepatitis B surface antigen and absence of portal vein thrombosis (PVT) were independent factors associated with better overall survival. The median duration of sorafenib therapy was 93.0 days (range, 4‐1504 days). After stopping sorafenib, the median survival was 93.0 days (range, 1‐1254 days). The 1‐year survival after stopping sorafenib was 21.2%. In chronic hepatitis B patients, total bilirubin level was the only factor associated with overall survival. Hepatitis C antibody RNA negativity, tumor size, PVT, and white blood cell count were the independent factors associated with survival among those chronic hepatitis C patients. There were different prognostic factors stratified by viral etiologies in aHCC patients receiving sorafenib. Viral eradication increased survival in chronic hepatitis C patients.

Student engagement within the development of learning analytics services in Higher Education is an important challenge for the researchers and practitioners to address. Despite calls for greater inclusion of stakeholders, there still remains only a small number of investigations into students’ beliefs and expectations towards learning analytics services. To meet the challenge of greater participation from the student population in the implementation of learning analytics services, this paper presents a descriptive instrument to measure student expectations (ideal and predicted) of learning analytics services. The scales used in the instrument have been grounded in theoretical framework of expectations, with a specific focus on ideal (hopes) and predicted (realistic beliefs) expectations. Items were then generated on the basis of four identified themes (Ethical and Privacy Expectations, Agency Expectations, Intervention Expectations, and Meaningfulness Expectations), which emerged through the undertaking of a review of the learning analytics literature. The developed instrument was then subject to peer review, pilot testing, and a full roll-out across students at two universities. The results of an exploratory factor analysis and the results from both an exploratory structural equation model and confirmatory factor analysis supported a two-factor structure best accounted for the data pertaining to ideal and predicted expectations. Factor one refers to Ethical and Privacy Expectations, whilst factor two covers Service Feature Expectations. In addition, both scales (ideal and predicted) were found to have good internal reliability. The 12-item Student Expectations of Learning Analytics Questionnaire (SELAQ) provides researchers and practitioners with a reliable and valid instrument to collect quantitative measures of students’ expectations of learning analytics services.

To provide precision medicine for better cancer care, researchers must work on clinical patient data, such as electronic medical records, physiological measurements, biochemistry, computerized tomography scans, digital pathology, and the genetic landscape of cancer tissue. To interpret big biodata in cancer genomics, an operational flow based on artificial intelligence (AI) models and medical management platforms with high-performance computing must be set up for precision cancer genomics in clinical practice. To work in the fast-evolving fields of patient care, clinical diagnostics, and therapeutic services, clinicians must understand the fundamentals of the AI tool approach. Therefore, the present article covers the following four themes: (i) computational prediction of pathogenic variants of cancer susceptibility genes; (ii) AI model for mutational analysis; (iii) single-cell genomics and computational biology; (iv) text mining for identifying gene targets in cancer; and (v) the NVIDIA graphics processing units, DRAGEN field programmable gate arrays systems and AI medical cloud platforms in clinical next-generation sequencing laboratories. Based on AI medical platforms and visualization, large amounts of clinical biodata can be rapidly copied and understood using an AI pipeline. The use of innovative AI technologies can deliver more accurate and rapid cancer therapy targets.

Feedback plays a crucial role in student learning. Learning analytics (LA) has demonstrated potential in addressing prominent challenges with feedback practice, such as enabling timely feedback based on insights obtained from large data sets. However, there is insufficient research looking into relations between student expectations of feedback and their experience with LA-based feedback. This paper presents a pilot study that examined students’ experience of LA-based feedback, offered with the OnTask system, taking into consideration the factors of students’self-efficacy and self-regulation skills. Two surveys were carried out at a Brazilian university, and the results highlighted important implications for LA-based feedback practice, including leveraging the ‘partnership’ between the human teacher and the computer, and developing feedback literacy among learners.

Manga (comic books originating in Japan) are among those texts that children in Taiwan actively seek out to enjoy the pleasure of reading. However, the social stigma of manga as inferior literature has resulted in fear of its potential harm to child development and an insufficient understanding of its complexity and literary values. While the global popularity of manga has had some positive impact on its social status and the recognition of its cultural and entertainment values, the role of manga and comics in general continues to be ambiguous and awkward in literacy education in Taiwan. In this chapter, the author reflects on this guilty pleasure in her childhood and traces its historical influence in Taiwanese society from the creation of comic arts to the formation of a reading culture. Drawing on an example of the texts recommended by a governmental reading campaign, the author provides a critical analysis and practical suggestions for the use of comic books in the classroom.

HCC, a leading cause of cancer-related mortality, is diagnosed at advanced stages. Although antiviral therapy has reduced the risk of HCC among chronic hepatitis C (CHC) patients, the risk of HCC remains, thus, highlighting the unmet need for continuous surveillance. Therefore, stable and cost-effective biomarkers, such as circulating microRNAs, must be identified. We aimed to clarify whether serum levels of the Let-7 family can predict HCC risk in patients with CHC using univariate and multivariate Cox’s proportional hazards model. We analyzed the sera of 54 patients with CHC who developed HCC after antiviral therapy and compared the data with those of 173 patients without HCC development. The Let-7 family (except for let-7c) exhibited significant negative correlations with the fibrosis score (r = −0.2736 to −0.34, p = 0.0002 to

Chapter 4 focuses on the impact of manga on children. Visual media such as manga, anime, and games are very popular among children not only in Japan, but also in other countries. Although such pop cultures have achieved widespread popularity worldwide, little is known about their impact on children. In particular, positive aspects are not well discussed. Therefore, it is necessary to investigate the significance of their popularity and possible impact on children. This chapter discusses the following three points: 1) the reason children are devoted to manga, 2) impact of manga on children, and 3) positive use of manga to prevent traditional/cyber bullying and other Internet-related problems. Although the most popular view of manga tends to be negative regarding the impact on child readers, we challenge this view by investigating the potential of using manga to positively influence children’s well-being. This chapter discusses the recent history of manga, its current situation, and the possibility of introducing a new usage of manga to positively impact children.

Background Cardiac insufficiency is a major cause of mortality in eosinophilic granulomatosis with polyangiitis (EGPA). Despite the dosages-related cardiotoxicity, cyclophosphamide is usually prescribed to induce disease remission in the presence of myocarditis with heart involvement. There is an imperative need of novel medications to efficiently control disease activity and spare the use of cyclophosphamide. Methods A retrospective study was carried out in hospitalized EGPA patients from January 1, 2008 to December 31, 2019, focusing on the use of biologics including benralizumab (BEN, anti-IL-5 receptor), mepolizumab (MEP, anti-IL-5), omalizumab (OMA, anti-IgE) and rituximab (RTX, anti-CD20). Results Sixteen admitted patients, 8 females aged 10 to 70 years (40.4 ± 15.5), had higher disease activities (Birmingham Vasculitis Activity Score 16 to 39, 26.8 ± 6.9), poorer prognostic factors (five-factor score 1 or 2, 1.4 ± 0.5) and elevated eosinophil counts (2,314 to 26,781/µL, 11,108 ± 7,060). BEN, MEP, OMA and RTX were prescribed in one, 2, one and 6 patients, respectively. Ten patients (63%) had myocarditis with impaired left ventricle ejection fraction and cardiac arrhythmia, and 7 received biological therapy without a combined use of cyclophosphamide. One patient obtained MEP with a 100 mg quadri-weekly × 13 regimen at induction for disease relapse. Six patients acquired RTX with a 375 mg/m2 weekly × 4 regimen at induction for refractory activity or relapsing disease, or plus a yearly maintenance schedule in 5. All patients received serial cardiac magnetic resonance imaging, transthoracic echocardiography and 24-hour Holter monitor to evaluate the therapeutic responses in heart involvement. After biological therapy, there were improved cardiac dysfunction, lower eosinophil counts and clinical remission (4 complete, 3 partial) with a relapse-free follow-up (13 to 61 months, 39.1 ± 16.0) after induction. Conclusions In this single-center retrospective study, we observed improved cardiac dysfunction and disease activity after biological therapy in EGPA patients with myocarditis.

BACKGROUND As the COVID-19 epidemic increases in severity, the burden of quarantine stations outside emergency departments (EDs) at hospitals is increasing daily. To address the high screening workload at quarantine stations, all staff members with medical licenses are required to work shifts in these stations. Therefore, it is necessary to simplify the workflow and decision-making process for physicians and surgeons from all subspecialties. OBJECTIVE The aim of this paper is to demonstrate how the National Cheng Kung University Hospital artificial intelligence (AI) trilogy of diversion to a smart quarantine station, AI-assisted image interpretation, and a built-in clinical decision-making algorithm improves medical care and reduces quarantine processing times. METHODS This observational study on the emerging COVID-19 pandemic included 643 patients. An “AI trilogy” of diversion to a smart quarantine station, AI-assisted image interpretation, and a built-in clinical decision-making algorithm on a tablet computer was applied to shorten the quarantine survey process and reduce processing time during the COVID-19 pandemic. RESULTS The use of the AI trilogy facilitated the processing of suspected cases of COVID-19 with or without symptoms; also, travel, occupation, contact, and clustering histories were obtained with the tablet computer device. A separate AI-mode function that could quickly recognize pulmonary infiltrates on chest x-rays was merged into the smart clinical assisting system (SCAS), and this model was subsequently trained with COVID-19 pneumonia cases from the GitHub open source data set. The detection rates for posteroanterior and anteroposterior chest x-rays were 55/59 (93%) and 5/11 (45%), respectively. The SCAS algorithm was continuously adjusted based on updates to the Taiwan Centers for Disease Control public safety guidelines for faster clinical decision making. Our ex vivo study demonstrated the efficiency of disinfecting the tablet computer surface by wiping it twice with 75% alcohol sanitizer. To further analyze the impact of the AI application in the quarantine station, we subdivided the station group into groups with or without AI. Compared with the conventional ED (n=281), the survey time at the quarantine station (n=1520) was significantly shortened; the median survey time at the ED was 153 minutes (95% CI 108.5-205.0), vs 35 minutes at the quarantine station (95% CI 24-56; PP CONCLUSIONS The AI trilogy improved our medical care workflow by shortening the quarantine survey process and reducing the processing time, which is especially important during an emerging infectious disease epidemic.

Background: The biochemical response is a crucial indicator of prognosis in chronic hepatitis B (CHB) patients treated with nucleotide/nucleoside analogues (NAs). The impact of hepatitis D virus (HDV) infection on alanine aminotransferase normalization is elusive. Methods: The longitudinal study recruited 1185 CHB patients who received NAs. These patients were tested for anti-HDV antibody and HDV RNA at the initiation of anti-hepatitis B virus (HBV) therapy and annually for patients who were HDV-seropositive. ALT levels were examined at the first and second year of anti-HBV therapy. ALT abnormality was defined as ALT levels above 40 IU/mL in both male and female, and the risk factors associated with ALT abnormality were analysed. Results: Rates of seropositivity for anti-HDV and HDV RNA were 2.0% and 0.8% among 1185 NA-treated CHB patients, respectively. The strongest factor associated with ALT abnormality (>40 IU/mL) after first year treatment with NAs was HDV RNA seropositivity at year 1 (odds ratio [OR]/95% confidence interval [CI]: 31.44/3.49–283.56, P = 0.002), followed by liver cirrhosis (2.18/1.51–3.15, P

Learning analytics promises to support adaptive learning in higher education. However, the associated issues around privacy protection, especially their implications for students as data subjects, has been a hurdle to wide-scale adoption. In light of this, we set out to understand student expectations of privacy issues related to learn-ing analytics and to identify gaps between what students desire and what they expect to happen or choose to do in reality when it comes to privacy protection. To this end, an investigation was carried out in a UK higher education institution using a survey (N=674) and six focus groups (26 students). The study highlight a number of key implications for learning analytics research and practice: (1) purpose, access, and anonymity are key benchmarks of ethics and privacy integrity; (2) transparency and communication are key levers for learning analytics adoption; and (3) information asymmetry can impede active participation of students in learning analytics.

Several tools to support learning processes based on educational data have emerged from research on Learning Analytics (LA) in the last few years. These tools aim to support students and instructors in daily activities, and academic managers in making institutional decisions. Although the adoption of LA tools is spreading, the field still needs to deepen the understanding of the contexts where learning takes place, and of the views of the stakeholders involved in implementing and using these tools. In this sense, the SHEILA framework proposes a set of instruments to perform a detailed analysis of the expectations and needs of different stakeholders in higher education institutions, regarding the adoption of LA. Moreover, there is a lacuna in research on stakeholders' expectations from LA outside the Global North. Therefore, this paper reports on the findings of the application of interviews and focus groups, based on the SHEILA framework, with students and teaching staff from a Brazilian public university, to investigate their perceptions of the potential benefits and risks of using LA in higher education in the country. Findings indicate that there is a high interest in using LA for improving the learning experience, in particular, being able to provide personalized feedback, to adapt teaching practices to students' needs, and to make evidence-based pedagogical decisions. From the analysis of these perspectives, we point to opportunities for using LA in Brazilian higher education.

Prospective electrocardiography (ECG)-gated cardiac computed tomography angiography (CTA) is widely used for pediatric patients with congenital heart disease (CHD) due to the lower radiation dose compared with the ECG-gated technique. However, functional parameters acquired using ECG-gated cardiac CT to predict pulmonary hypertension (PH) in children with CHD have not yet been reported. This study aimed to investigate the potential of diastolic and systolic right ventricular diameters (RVD) on prospective ECG-gated cardiac CTA to predict PH in children with CHD. A total of 44 children with CHD were divided into two groups: CHD with PH (n = 22) and CHD without PH (n = 22). The association between ECG-gated CTA parameters and PH was evaluated by logistic regression. The receiver operating characteristic curve (ROC) was used to find the best cut-off point for the parameters measured by Youden's index. Patients with higher RVD-BSA [aOR (95% CI) diastolic: 2.76 (1.23–6.23); systolic: 6.15 (1.72–22.06)] had higher risk of PH after adjusting for age and patent ductus arteriosus. The area under the curve (AUC) of D-RVD-BSA was 0.907 and the AUC of S-RVD-BSA was 0.917. Logistic regression showed that patients with D-RVD-BSA over 6.86 or S-RVD-BSA over 5.87 had significantly higher risk of PH after adjustments (aOR = 23.52, 95% CI = 2.89–191.03; aOR = 31.14, 95% CI = 2.75–352.85). In conclusion, in children with CHD, measurements of diastolic or systolic BSA-modified RVDs on prospective ECG-gated CTA are non-invasive markers of PH. BSA-modified D-RVD of 6.86 or BSA-modified S-RVD of 5.87 may be used to identify PH in children with CHD.

Learning analytics (LA) can provide useful information for addressing the educational needs in Latin American universities, such as reducing program quality disparities and student dropout rates. Some researchers have suggested to build capacity in this region for institutional adoption of LA tools. Yet, there is still a long way to move from experimentation to actual integration of LA tools into institutional processes. With the objective of understanding how we could facilitate LA adoption in Latin American contexts, we present the cases of four Latin American universities adapting LA tools to meet institutional needs. Two questionnaires with open-ended questions were used to identify similarities and differences among the four cases in terms of two dimensions: (1) leadership processes to involve diverse stakeholders in the adoption of LA tools and (2) organizational maturity to analyze and act upon educational data. Findings indicate that leadership processes for LA adoption that engage middle managers, such as deans and directors of undergraduate studies, facilitated the involvement of intended users to receive feedback on the design and of senior managers to allocate resources for scaling up the LA initiative. Besides, a greater organizational maturity facilitated the incorporation of the LA tool into an existing academic process at a department or institutional level. Future work might explore how leadership processes and organizational maturity evolve in other Latin American universities, in order to provide guidelines and recommendations for scaling LA adoption in different contexts.

// Chia-Yen Dai 1, 2, 3, 4, 5, 6, * , Yi-Shan Tsai 1, * , Wen-Wen Chou 1 , Tawei Liu 1 , Chung-Feng Huang 1, 2, 4 , Shu-Chi Wang 3 , Pei-Chien Tsai 1 , Ming-Lun Yeh 1, 4, 5 , Ming-Yen Hsieh 1 , Ching-I Huang 1, 5 , Shang-Yin Vanson Liu 7 , Jee-Fu Huang 1, 4 , Wan-Long Chuang 1, 4, 6 and Ming-Lung Yu 1, 2, 3, 4, 5, 6, 8 1 Hepatobiliary Division, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan 2 Department of Occupational and Environmental Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan 3 Health Management Center, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan 4 Faculty of Internal Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan 5 Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan 6 Center for Infectious Disease and Cancer Research, Kaohsiung Medical University, Kaohsiung, Taiwan 7 Department of Marine Biotechnology and Resources, National Sun Yat-Sen University, Kaohsiung, Taiwan 8 Institute of Biomedical Sciences, National Sun Yat-Sen University, Kaohsiung, Taiwan * These authors contributed equally to this work Correspondence to: Ming-Lung Yu, email: fish6069@gmail.com Keywords: miR-125b; HCV; IL-6; STAT3; HCV Received: July 28, 2017 Accepted: December 01, 2017 Published: January 10, 2018 ABSTRACT Background/Aims: MicroRNA-125b (miR-125b) has been found to regulate inflammation and acts as an oncogene in many cancers. The mechanisms of miR-125b expression during hepatitis C virus (HCV) infection remain to be clarified. The present study aims to identify the factors that might regulate miR-125b expression in HCV infection. Results: High expression of miR-125b was found to correlate with HCV infection in replicon cells and in sera from HCV-infected patients, whereas the miR-125b inhibitor reduced HCV gene expression. The interleukin 6 (IL-6)/signal transducer and activator of transcription 3 (STAT3) pathway plays an inducible effect on miR-125b gene expression. STAT3 siRNA or inhibitor could reduce HCV replication. Materials and Methods: HCV replicon cells Con1 (type 1b) and Huh7/Ava5 (type 1b) were treated with 17-hydroxy-jolkinolide B (HJB) or STAT3 siRNA. Cell viability assay and Renilla Luciferase Assay were used. Fragments of the miR-125b-1 promoter were constructed for the luciferase reporter assay. PSMB8, PSMB9, miR-125b-1, and miR-125b-2 expression was determined using TaqMan ® Gene Expression Assays. Western blot analysis was performed to assess protein abundance. Conclusions: This study elucidates a novel pathway for miR-125b in the pathogenesis of chronic HCV infection and suggests it as a possible target for treating HCV infection.

Background/Purpose Pegylated interferon (PegIFN) plus ribavirin (RBV) combination therapy has been the standard of care since 2002. Although a better viral response has been achieved among chronic hepatitis C (CHC) patients in Taiwan, approximately 25% of hepatitis C virus (HCV) genotype 1 (G1) patients and 15% of G2 patients failed to achieve a sustained virological response (SVR) at the first therapy. The actual cost-effectiveness of the retreatment remains elusive. The present study conducted a real-world cost-effectiveness analysis of a large cohort among different pre-specified subgroups of treatment-experienced CHC patients. Methods A total of 117 patients with CHC who failed to achieve SVR at the first IFN-based therapy and received a second IFN-based therapy were enrolled. The inpatient and outpatient costs were acquired from National Health Insurance Research Database of Taiwan. The related medical care costs per treatment and per SVR were calculated. Results We demonstrated that the average cost per SVR achieved was $13,722 in treatment-experienced CHC patients. Especially, patients with HCV G1 infection, baseline viral loads > 400,000 IU/mL, advanced hepatic fibrosis, not achieving a rapid viral response at week 4 or complete early viral response at week 12, had poorer cost-effectiveness for PegIFN/RBV retherapy, ranging from around $15,520 to as high as $72,546 per SVR achieved. Conclusion In the current study, we explored the real-world cost-effectiveness data of PegIFN/RBV for different subgroups of treatment-experienced HCV patients. These findings provide information for policy-makers for making decisions on treatment strategies of costly direct-acting antiviral agents for retreating CHC patients.

Objectives To investigate the diagnostic value of first-pass myocardial perfusion defects visualised in non-gated high-pitch computed tomography angiography (CTA) in patients admitted to the emergency department (ED) for suspected aortic dissection. Methods We recruited 174 ED patients who underwent high-pitch CTA of the aorta because of suspected aortic dissection. We divided these patients into two groups (diseased and control groups) based on whether their clinical data fulfilled the third universal definition of acute myocardial infarction (AMI), specifically an increase in cardiac troponin (cTn) with at least one of the following: (a) symptoms of ischemia; (b) new ST-segment-T wave (ST-T) changes or new left bundle branch block (LBBB); (c) development of pathological Q wave; (d) new loss of viable myocardium or new regional wall motion abnormality; or (e) identification of an intracoronary thrombus by angiography or autopsy. Twenty-two patients with a clinical diagnosis of AMI were placed in the diseased group. Myocardial perfusion defects were evaluated qualitatively and quantitatively on the late arterial phase obtained 50 s post-threshold. Results Of the 22 patients with a final diagnosis of AMI, visually identifiable perfusion defects were observed in 12 patients. The sensitivity, specificity, negative predictive value, and positive predictive value of any perfusion defect for predicting AMI were 54.6%, 94.7%, 93.5%, and 60.0%, respectively. Quantitative analysis indicated that CT attenuation was significantly lower within perfusion defects than within the normal myocardium (67.6 ± 29.5 HU vs. 92.2 ± 19.7 HU; p Conclusions In patients with acute chest pain, the presence of myocardial perfusion defect observed on nongated high-pitch CTA of the aorta can be used to identify individuals with AMI with high specificity, but low sensitivity.