Adaptation and psychometric evaluation of the Chinese version of the functional assessment of chronic illness therapy spiritual well-being scale among Chinese childhood cancer patients in China

BackgroundSpiritual well-being is a strength for childhood cancer patients to cope with cancer. The availability of a valid and reliable instrument for assessing spiritual well-being is crucial. This study translated and adapted the Functional Assessment of Chronic Illness Therapy Spiritual Well-being scale (FACIT-Sp) for Chinese childhood cancer patients and examined the psychometric properties and factor structure in this population.MethodsThis was a methodological study. The FACIT-Sp was translated into Chinese. Adaptation was based on our qualitative study. For psychometric evaluation, a convenience sample of 412 were recruited based on the suggested sample size for the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Childhood cancer patients were included if they aged 8–17 years, with parental consent to participate, able to communicate that they were being treated for cancer, and able to communicate and read Chinese. Participants answered the Chinese version of the adapted FACIT-Sp, the Center for Epidemiology Studies Depression Scale for Children (CES-DC), and the Pediatric Quality of Life Inventory 3.0 Cancer Module (PedsQL). Content validity, convergent validity, internal consistency and test–retest reliability were examined. Both EFA and CFA assessed the structural validity of the adapted FACIT-Sp.ResultsThe content validity index values for items ranged 0.8–1.0 and that for the scale was 0.84, indicating appropriate content validity. The scale had good internal consistency, with a Cronbach’s alpha of 0.815. The FACIT-Sp scores positively correlated with the CES-DC scores, and negatively correlated with PedsQL scores, suggesting that the Chinese version of the adapted FACIT-Sp had reasonable convergent validity. EFA yielded a four-factor (meaning, peace, faith, and connection with others) model. The CFA results revealed that the four-factor model achieved a better fit than the original three-factor model (Chi-Square Mean/Degree of Freedom = 2.240 vs. 3.557, Comparative Fit Index = 0.953 vs. 0.916, Goodness of Fit Index = 0.909 vs. 0.884, Root Mean Square Error of Approximation = 0.078 vs. 0.112).ConclusionThe Chinese version of the adapted FACIT-Sp is a reliable and valid instrument for assessing spiritual well-being among Chinese childhood cancer patients. This instrument can be applied in clinical settings for routine assessment

Association of Genetic Variants Related to Combined Exposure to Higher Body Mass Index and Waist-to-Hip Ratio on Lifelong Cardiovascular Risk in UK Biobank

OBJECTIVE: This study examines the individual and combined association of body mass index (BMI) and 7 waist-to-hip ratio (WHR) with cardiovascular diseases (CVD) risk using genetic scores of the 8 obesity measurements as proxies. DESIGN: A 2×2 factorial analysis approach was applied, with participants divided into four groups of lifetime exposure to low BMI and WHR, high BMI, high WHR, and high BMI and WHR based on weighted genetic risk scores. The difference in CVD risk across groups was evaluated using multivariable logistic regression. SETTING: Cohort study. PARTICIPANTS: A total of 408,003 participants were included from the prospective observational UK Biobank study. RESULTS: A total of 58,429 of CVD events were recorded. Compared to the low BMI and WHR genetic scores group, higher BMI or higher WHR genetic scores were associated with an increase in CVD risk (high BMI: odds ratio (OR), 1.07; 95%CI, 1.04-1.10; high WHR: OR, 1.12; 95%CI, 1.09-1.16). A weak additive effect on CVD risk was found between BMI and WHR (high BMI and WHR: OR, 1.16; 95%CI, 1.12-1.19). Subgroup analysis showed similar patterns between different sex, age (<65, ≥65 years old), smoking status, Townsend deprivation index, fasting glucose level and medication uses, but lower systolic blood pressure was associated with higher CVD risk in obese participants. CONCLUSIONS: High BMI or WHR were associated with increased CVD risk, and their effects are weakly additive. Even though there were overlapping of effect, both BMI and WHR are important in assessing the CVD risk in the general population

Milk Consumption Across Life Periods in Relation to Lower Risk of Nasopharyngeal Carcinoma: A Multicentre Case-Control Study

Background: The much higher incidence of nasopharyngeal carcinoma (NPC) in men suggests sex hormones as a risk factor, and dairy products contain measurable amounts of steroid hormones. Milk consumption has greatly increased in endemic regions of NPC. We investigated the association between NPC and milk consumption across life periods in Hong Kong.Methods: A multicentre case-control study included 815 histologically confirmed NPC incident cases and 1,502 controls who were frequency-matched on age and sex at five major hospitals in Hong Kong in 2014–2017. Odds ratios (ORs) of NPC (cases vs. controls) for milk consumption at different life periods were estimated by unconditional logistic regression, adjusting for sex, age, socioeconomic status score, smoking and alcohol drinking status, exposure to occupational hazards, family history of cancer, IgA against Epstein-Barr virus viral capsid antigen, and total energy intake.Results: Compared with abstainers, lower risks of NPC were consistently observed in regular users (consuming ≥5 glasses of milk [fresh and powdered combined] per month) across four life periods of age 6–12 (adjusted OR 0.74, 95% CI 0.54–0.86), 13–18 (0.68, 0.55–0.84), 19–30 (0.68, 0.55–0.84), and 10 years before recruitment (0.72, 0.59–0.87). Long-term average milk consumption of ≤2.5, &gt;2.5, and ≤12.5, &gt;12.5 glasses per month yielded adjusted OR (95% CI) of 1.00 (0.80–1.26), 0.98 (0.81–1.18), 0.95 (0.76–1.18), and 0.55 (0.43–0.70), respectively (all P-values for trend &lt; 0.05).Conclusion: Consumption of milk across life periods was associated with lower risks of NPC. If confirmed to be causal, this has important implications for dairy product consumption and prevention of NPC

「回首．動情．傳承」長者生命故事計劃

嶺南大學亞太老年學研究中心獲華人永遠墳場管理委員會（「華永會」）資助為期一年的「回首．動情．傳承」長者生命故事計劃(「計劃」)。此計劃旨在讓青年人認識長者生命經驗，學習克服困難與挫折以提升抗逆力，建立正向人生觀。 近年，主流媒體經常批評年輕人的負面人生觀，例如：「躺平主義」、「享樂主義」、「犬儒心態」等，亦不時看到青年人輕生的新聞。我們曾在大學內處理過不少受情緒困擾及企圖自殺的個案，與學生深入交流後，發現他們面對着沉重的學業壓力、財政困難或複雜的家庭關係，內心充滿掙扎不安。 此計劃讓嶺大學生與長者導師進行深度的對談，透過了解長者走過的路、他們經歷過的挫折和教訓，給予年輕人生命的啟示。如果我們以旅遊比喻人生，長者就像環遊世界的資深背包客，即使大家遊覽不同的地點、觀賞過不同的風景，他們總能夠分享一些旅遊的心得，讓新手遊客走少一點冤枉路，或領悟到旅遊的樂趣和意義。長者亦可以藉由敍述人生片段回顧他們生命中的故事，學習接納過去，增加自我認同感。青年人創作生命教育書冊，將長者積極的人生觀傳給年輕一代，並藉此鼓勵其他長者豁達地度過餘年。 我們於2022年初招募嶺南大學學生接受「生命故事敍述」培訓，內容包括：本港的人口老化現象、敍述治療理論、與長者溝通的技巧及模擬實踐練習等，以裝備同學的知識和技巧。本中心再向屯門、元朗區的長者機構發邀請信，誠邀長者擔任生命導師接受訪問。 嶺大安排同學以兩人一組的小隊形式，於2022年6至7月期間前往長者中心、日間護理中心、嶺南大學或長者家中，與十二位長者進行深入訪談。訪談結束後，同學根據訪談的內容，為長者書寫他們獨特的生命故事。例如在人離鄉賤的異國環境下，努力打拼事業的Alfred；堅持不懈持續進修的淑芹和馮春林；即使沒機會求學，仍憑一雙巧手闖出一片天的譚惠；在文化大革命的漩渦中，憑着熱忱而改變命運的蘭英；還有為家人無私奉獻的鳳群、歐婆婆、雅芳及細女；離鄉別井勇闖異地的阿美和阿水；即使被家人賣去做「妹仔」，仍能以「阿Q精神」面對的諒餘。 為保障長者的私隱權益，本書內所有刊登之故事皆經過受訪者或社工審閱，部份受訪者選擇以化名的形式來分享自己的故事，我們亦移除了部份敏感的個人資料。https://commons.ln.edu.hk/apias_guide/1008/thumbnail.jp

Vascular proteomics in metabolic and cardiovascular diseases.

The vasculature is essential for proper organ function. Many pathologies are directly and indirectly related to vascular dysfunction, which causes significant morbidity and mortality. A common pathophysiological feature of diseased vessels is extracellular matrix (ECM) remodelling. Analysing the protein composition of the ECM by conventional antibody-based techniques is challenging; alternative splicing or post-translational modifications, such as glycosylation, can mask epitopes required for antibody recognition. By contrast, proteomic analysis by mass spectrometry enables the study of proteins without the constraints of antibodies. Recent advances in proteomic techniques make it feasible to characterize the composition of the vascular ECM and its remodelling in disease. These developments may lead to the discovery of novel prognostic and diagnostic markers. Thus, proteomics holds potential for identifying ECM signatures to monitor vascular disease processes. Furthermore, a better understanding of the ECM remodelling processes in the vasculature might make ECM-associated proteins more attractive targets for drug discovery efforts. In this review, we will summarize the role of the ECM in the vasculature. Then, we will describe the challenges associated with studying the intricate network of ECM proteins and the current proteomic strategies to analyse the vascular ECM in metabolic and cardiovascular diseases

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Dijet Resonance Search with Weak Supervision Using root S=13 TeV pp Collisions in the ATLAS Detector

This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on signal simulations for developing the analysis selection. Weakly supervised learning is used to train classifiers directly on data to enhance potential signals. The targeted topology is dijet events and the features used for machine learning are the masses of the two jets. The resulting analysis is essentially a three-dimensional search A → BC, for mA ∼ OðTeVÞ, mB; mC ∼ Oð100 GeVÞ and B, C are reconstructed as large-radius jets, without paying a penalty associated with a large trials factor in the scan of the masses of the two jets. The full run 2 ffiffi s p ¼ 13 TeV pp collision dataset of 139 fb−1 recorded by the ATLAS detector at the Large Hadron Collider is used for the search. There is no significant evidence of a localized excess in the dijet invariant mass spectrum between 1.8 and 8.2 TeV. Cross-section limits for narrow-width A, B, and C particles vary with mA, mB, and mC. For example, when mA ¼ 3 TeV and mB ≳ 200 GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on mC. For certain masses, these limits are up to 10 times more sensitive than those obtained by the inclusive dijet search. These results are complementary to the dedicated searches for the case that B and C are standard model boson

A Pervasive Promotion Model for Personalized Promotion Systems on Using WLAN Localization and NFC Techniques

In this paper, we propose a novel pervasive business model for sales promotion in retail chain stores utilizing WLAN localization and near field communication (NFC) technologies. The objectives of the model are to increase the customers’ flow of the stores and their incentives in purchasing. In the proposed model, the NFC technology is used as the first mean to motivate customers to come to the stores. Then, with the use of WLAN, the movements of the customers, who are carrying smartphones, within the stores are captured and maintained in the movement database. By interpreting the movements of customers as indicators of their interests to the displayed items, personalized promotion strategies can be formulated to increase their incentives for purchasing future items. Various issues in the application of the adopted localization scheme for locating customers in a store are discussed. To facilitate the item management and space utilization in displaying the items, we propose an enhanced R-tree for indexing the data items maintained in the movement database. Experimental results have demonstrated the effectiveness of the adopted localization scheme in supporting the proposed model

Public Trust in Artificial Intelligence Applications in Mental Health Care: Topic Modeling Analysis

BackgroundMental disorders (MDs) impose heavy burdens on health care (HC) systems and affect a growing number of people worldwide. The use of mobile health (mHealth) apps empowered by artificial intelligence (AI) is increasingly being resorted to as a possible solution. ObjectiveThis study adopted a topic modeling (TM) approach to investigate the public trust in AI apps in mental health care (MHC) by identifying the dominant topics and themes in user reviews of the 8 most relevant mental health (MH) apps with the largest numbers of reviewers. MethodsWe searched Google Play for the top MH apps with the largest numbers of reviewers, from which we selected the most relevant apps. Subsequently, we extracted data from user reviews posted from January 1, 2020, to April 2, 2022. After cleaning the extracted data using the Python text processing tool spaCy, we ascertained the optimal number of topics, drawing on the coherence scores and used latent Dirichlet allocation (LDA) TM to generate the most salient topics and related terms. We then classified the ascertained topics into different theme categories by plotting them onto a 2D plane via multidimensional scaling using the pyLDAvis visualization tool. Finally, we analyzed these topics and themes qualitatively to better understand the status of public trust in AI apps in MHC. ResultsFrom the top 20 MH apps with the largest numbers of reviewers retrieved, we chose the 8 (40%) most relevant apps: (1) Wysa: Anxiety Therapy Chatbot; (2) Youper Therapy; (3) MindDoc: Your Companion; (4) TalkLife for Anxiety, Depression & Stress; (5) 7 Cups: Online Therapy for Mental Health & Anxiety; (6) BetterHelp-Therapy; (7) Sanvello; and (8) InnerHour. These apps provided 14.2% (n=559), 11.0% (n=431), 13.7% (n=538), 8.8% (n=356), 14.1% (n=554), 11.9% (n=468), 9.2% (n=362), and 16.9% (n=663) of the collected 3931 reviews, respectively. The 4 dominant topics were topic 4 (cheering people up; n=1069, 27%), topic 3 (calming people down; n=1029, 26%), topic 2 (helping figure out the inner world; n=963, 25%), and topic 1 (being an alternative or complement to a therapist; n=870, 22%). Based on topic coherence and intertopic distance, topics 3 and 4 were combined into theme 3 (dispelling negative emotions), while topics 2 and 1 remained 2 separate themes: theme 2 (helping figure out the inner world) and theme 1 (being an alternative or complement to a therapist), respectively. These themes and topics, though involving some dissenting voices, reflected an overall high status of trust in AI apps. ConclusionsThis is the first study to investigate the public trust in AI apps in MHC from the perspective of user reviews using the TM technique. The automatic text analysis and complementary manual interpretation of the collected data allowed us to discover the dominant topics hidden in a data set and categorize these topics into different themes to reveal an overall high degree of public trust. The dissenting voices from users, though only a few, can serve as indicators for health providers and app developers to jointly improve these apps, which will ultimately facilitate the treatment of prevalent MDs and alleviate the overburdened HC systems worldwide