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Many challenges remain in diagnosing monoclonal immunoglobulin-associated renal disease, despite widespread application of immunofluorescence (IF) and immunohistochemistry. Here, we report a newly diagnosed case of multiple myeloma with clinical suspicion of renal amyloidosis, which had negative IF staining for kappa and lambda light chains in the glomeruli. Although laser microdissection and mass spectrometry-based proteomic analysis have emerged as important tools for amyloid typing in the literature, such facilities are still not widely available in Asia. We propose that a clinicopathological algorithm for the evaluation of organized monoclonal renal deposits, together with a combined nephrological-haematological approach, will still be adequate to generate an unequivocal diagnosis in the majority of cases.

Abstract Background Sorafenib has been shown to improve survival in patients with advanced hepatocellular carcinoma (HCC), however, full dose can be difficult to tolerate. The aim of this study was to determine whether sorafenib starting dose and mean dose intensity affect survival. Methods Patients treated with sorafenib for HCC from January 2008 to July 2016 in several Canadian provinces were included and retrospectively analyzed. The primary end point was overall survival (OS) of patients starting on sorafenib full dose compared to reduced dose. Secondary analysis compared OS with different mean dose‐intensity groups. Survival outcomes were assessed with Kaplan‐Meier curves and Cox proportional hazards models. A propensity score analysis was performed to account for treatment bias and confounding. Results Of 681 patients included, sorafenib was started at full dose in 289 patients (42%). Median survival for starting full and reduced dose was 9.4 months and 8.9 months (P = .15) respectively. After propensity score matching and adjusting for potential confounders there was still no difference in survival (HR 0.8, 95% CI, 0.61‐1.06, P = .12). Almost half of the patients (45%) received a dose intensity 75%, 50%‐75%, and

Abstract Background The CELESTIAL, RESORCE, and REACH‐2 trials showed survival benefit of cabozantinib, regorafenib, and ramucirumab, respectively, in hepatocellular carcinoma (HCC) patients treated with sorafenib who had good performance status (ECOG 0‐1) and liver function (Child‐Pugh‐A). This study characterizes subsequent treatments received by HCC patients after sorafenib, and determines the proportion of patients eligible for novel therapies if strict eligibility criteria (SEC) were utilized compared to more liberal modified eligibility criteria (MEC, including ECOG 2, Child‐Pugh‐B7). Methods HCC patients who received sorafenib between 2008 and 2017 were included from the Canadian HCC CHORD Database. Patients were classified as eligible or ineligible based on available CELESTIAL, RESORCE, and REACH‐2 trial SEC or MEC. Median overall survival (mOS) was assessed using the Kaplan‐Meier method. Results A total of 730 patients were identified; and 172 (23.6%) received subsequent treatment. Patients who received subsequent treatment had longer mOS than those who did not (12.1 vs 3.3 months; P

The coronavirus disease 2019 (COVID-19) pandemic has caused a catastrophic global health crisis. There is a lack of mitigation and clinical management strategies for COVID-19 in specific patient cohorts such as hemodialysis (HD) patients. We report our experience in treating the first case of COVID-19 in a HD patient in Singapore who had a severe clinical course including acute respiratory distress syndrome and propose a clinical management strategy. We propose a clinical workflow in managing such patients based on available evidence from literature review. We also highlight the importance of early recognition and intervention for disease control, dialysis support in an acute hospital isolation facility, deisolation protocol, and discharge planning due to prolonged viral shedding. The case highlights important points specific to a HD patient with a COVID-19 diagnosis, tailored interventions for each stage of the disease, and deisolation considerations in the recovery phase.

Baricitinib is known to reduce mortality and disease progression in COVID-19 patients; however, the data are inconsistent. Therefore, it needs to be explored to further understand the clinical benefits of this drug in the management of COVID-19 patients. Does baricitinib statistically significantly reduce mortality and disease progression in COVID-19 patients? To answer these questions, three databases known as ScienceDirect, PubMed/MEDLINE, and Scopus and other sources, such as preprint (medRxiv) and reference lists, were thoroughly searched. Four randomised controlled trials (RCTs) were included. Based on the meta-analysis, baricitinib statistically significantly reduced mortality with the risk ratio (RR) of RR = 0.74 [95% CI: 0.58 to 0.94; p=0.01] and moderately high heterogeneity, where I2 = 62% and p=0.05. On the other hand, RR = 0.84 [95% CI: 0.75 to 0.95; p=0.005] with insignificant heterogeneity of I2 = 20% and p=0.28 was found for disease progression. Cochrane risk of bias (RoB) analysis revealed that three out of four articles were ranked as high-quality articles with low RoB. Based on the evidence grading, the overall certainty of evidences was moderate. In conclusion, baricitinib statistically significantly reduced mortality and disease progression in COVID-19 patients when the patients were treated with baricitinib at a dosage of 2 mg or 4 mg for a maximum duration of 14 days.

Background: The Covid-19 pandemic has forced businesses in the direction of technology development. In particular, financial institutions have started the digital transformation, embracing the usage of artificial intelligence. In this respect, consumers’ willingness to adopt artificial intelligence in finance, appears to have relevance to current efforts to enhance the efficiency and effectiveness of the financial system. This study aims to better comprehend the antecedents towards the intention to adopt artificial intelligence in financial services among Generation Z, with the use of the Technology Acceptance Model. Methods: In this study, questionnaires were used to collect data from 150 male and female Malaysian undergraduates. Partial Least Squares-Structural Equation Modelling was employed to analyse the data. Results: Perceived ease of use and attitude, positively influenced the adoption of artificial intelligence in financial services. Conclusion: The results have suggested the improvement in user interface, information and activities to encourage generation Z to adopt artificial intelligence in financial services.

Indigenous peoples in Taiwan belong to the Austronesian racial group. Confined to their oral language tradition, knowledge about Taiwan aborigines based on written documents reflected the positionality of dominant ethnic groups. This qualitative study employed participatory research approach to explore the process of producing their own knowledge through collective investigation of problems and issues among Taiwan aborigine tribal members in the Nantou region. Nantou is located in the central mountain range of Taiwan. The data were collected through participatory observation and interviewing 6 key research participants about their experiences of participating in this project. Two main findings are revealed from the analysis of these data. The first finding is the participants' expectation of adult educators' role as an information provider. They also expect adult educator as a facilitator for promoting the project to move towards a more empowering praxis and as a mediator for attracting external attention on indigenous voices. The second finding is that minority's experiences are always a site of struggle and central to this struggle is the reconfiguration of 'ethnicity' which is rooted in socio-cultural context. Taking account of context, experience might be distorted while experiential learning can be stigmatizing, in that learners can become un-reflective prisoners of their experience. However, experience certainly has the potential of liberating marginalized learners. The findings implied the importance of the socio-cultural context of situated "experience". This insight suggests that "power" can be renegotiated to challenge and eventually change the structure of the socio-cultural context.

Aim: The quality of life in people with psychosis has been consistently demonstrated to be lower than those without, with self‐stigma contributing greatly to this impairment. Hence, it is imperative to address this gap in order to facilitate recovery‐oriented and other outcomes. This study investigates the potential of religiosity in moderating the effects of self‐stigma on quality of life among those with psychosis. Methods: Adults with psychosis (n = 99) were recruited from the Early Psychosis Intervention Programme in Singapore from 2018 to 2021, and administered the self‐report Religious Commitment Index, Internalized Stigma of Mental Illness scale, and Abbreviated World Health Organization Quality of Life instrument. Linear regression analyses were conducted and the interaction between self‐stigma and religious commitment scores calculated to investigate the moderation effects of religiosity on the relationship between stigma and quality of life. Results: Preliminary regression analyses revealed a significant association between sex and psychological quality of life. After controlling for sex, religiosity was found to moderate the relationship between self‐stigma and psychological quality of life. Conclusions: The results of the study demonstrate the potential of religiosity in buffering the effects of self‐stigma on quality of life. This reveals an area that can be easily targeted and addressed in treatment programs to improve outcomes beyond the clinical setting among people living with psychosis, to facilitate their recovery journey and beyond. [ABSTRACT FROM AUTHOR]

Face recognition is the dominant biometrics system used to authenticate an individual's identity in various applications. Most commercial face recognition systems rely on 2D face images, but the changes in the environment lighting and a person's posture affect the accuracy of the 2D face recognition systems. Hence, the 2.5D face recognition system arises as the solution to eliminate the drawbacks of the 2D face recognition system. The depth feature in the 2.5D data (depth image) provides additional information that can help to improve the accuracy and robustness of 2.5D face recognition systems, particularly in challenging scenarios. This paper proposes a fusion-based approach for the 2.5D face recognition system to enhance the system's performance, where feature fusion involves the combination of features extracted from the depth image. Gabor-based Region Covariance Matrices (GRCMs) that serve as face identifiers combine the depth and texture images in the structure of a covariance matrix. Several experiments on different fusions have been conducted in the Face Recognition Grand Challenge version 2 (FRGC v2.0) database. This paper shows that the max-min fusion applied to the surface normal (y-direction) and the mean curvature has achieved the best accuracy rate of 93.66% among the other fusion approaches used. [ABSTRACT FROM AUTHOR]