A blended face-to-face and eHealth lifestyle intervention on physical activity, diet, and health outcomes in Hong Kong community-dwelling older adults: a study protocol for a randomized controlled trial

BackgroundAging individuals are vulnerable to various Noncommunicable Diseases (NCDs). Different behaviors are closely related to a decreased risk of suffering from NCDs: sufficient Physical Activity (PA) (e.g., at least 150 mins Moderate-to-vigorous Physical Activity (MVPA) per week) and a healthy daily diet (e.g., at least five portions of Fruit and Vegetable Intake (FVI), 5–6 taels (189.0–226.8 g) Meat, Fish, Egg and Alternatives (MFEA)). Traditional face-to-face interventions were effective in behavior change. However, it was revealed to be resource-intensive and limited transfer due to poor self-regulation skills outside of face-to-face sessions. Thus, eHealth could be a supplement for older adults outside traditional face-to-face settings. The blended approach combining these two interventions might optimize the intervention effects on lifestyle behavior initiation and maintenance, but little research can be found among Hong Kong older adults. Therefore, the study aims to test a blended intervention to promote PA, diet, and health outcomes among Hong Kong community-dwelling older adults.MethodsThis study will adopt a 10-week three-arm randomized controlled trial. The blended group will receive weekly (1) two 60-min face-to-face sessions with one for PA and one for diet, and (2) two web-based sessions with one for PA and one for diet. The face-to-face group will receive the same intervention content as the face-to-face sessions in the blended group. The control condition will receive a biweekly telephone call. The outcomes will include MVPA (minutes/week), FVI (portions/day), MFEA consumption (taels/day), social-cognitive factors (self-efficacy, planning, social support, action control), physical health outcomes (clinical indicators, senior physical fitness), mental health outcomes (depression, loneliness) and health-related quality of life. Data collection will be implemented at the pre-test, post-test, and 3-month follow-up test.DiscussionThis is the first study evaluating a blended intervention promoting multiple health behaviors among Hong Kong community-dwelling older adults. If the effect of the blended intervention is superior to the traditional face-to-face group and the control group, it will enrich lifestyle intervention approaches and can be applied to older adults, helping them obtain health benefits. Furthermore, a better understanding of mechanisms will also have implications for theory-building.Clinical trial registrationhttps://www.isrctn.com/ISRCTN32329348, ISRCTN32329348

Characterization of the transcripts of human cytomegalovirus UL144

<p>Abstract</p> <p>Background</p> <p>The genome of human cytomegalovirus (HCMV) has been studied extensively, particularly in the UL/b' region. In this study, transcripts of one of the UL/b' genes, UL144, were identified in 3 HCMV isolates obtained from urine samples of congenitally infected infants.</p> <p>Methods</p> <p>Northern blot hybridization, cDNA library screening, and RACE-PCR were used.</p> <p>Results</p> <p>We identified at least 4 differentially regulated 3'-coterminal transcripts of UL144 in infected cells of 1,300, 1,600, 1,700, and 3,500 nucleotides (nt). The 1600 nt transcript was the major form of UL144 mRNA. The largest transcript initiated from the region within the UL141 open reading frame (ORF) and included UL141, UL142, UL143, UL144, and UL145 ORFs.</p> <p>Conclusions</p> <p>These findings reveal the complex nature of the transcription of the UL144 gene in clinical isolates.</p

Genome-wide association study for intramuscular fat content in Chinese Lulai black pigs

Objective Intramuscular fat (IMF) content plays an important role in meat quality. Identification of single nucleotide polymorphisms (SNPs) and genes related to pig IMF, especially using pig populations with high IMF content variation, can help to establish novel molecular breeding tools for optimizing IMF in pork and unveil the mechanisms that underlie fat metabolism. Methods We collected muscle samples of 453 Chinese Lulai black pigs, measured IMF content by Soxhlet petroleum-ether extraction method, and genotyped genome-wide SNPs using GeneSeek Genomic Profiler Porcine HD BeadChip. Then a genome-wide association study was performed using a linear mixed model implemented in the GEMMA software. Results A total of 43 SNPs were identified to be significantly associated with IMF content by the cutoff p<0.001. Among these significant SNPs, the greatest number of SNPs (n = 19) were detected on Chr.9, and two linkage disequilibrium blocks were formed among them. Additionally, 17 significant SNPs are mapped to previously reported quantitative trait loci (QTLs) of IMF and confirmed previous QTLs studies. Forty-two annotated genes centering these significant SNPs were obtained from Ensembl database. Overrepresentation test of pathways and gene ontology (GO) terms revealed some enriched reactome pathways and GO terms, which mainly involved regulation of basic material transport, energy metabolic process and signaling pathway. Conclusion These findings improve our understanding of the genetic architecture of IMF content in pork and facilitate the follow-up study of fine-mapping genes that influence fat deposition in muscle

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing

Education and urbanization improves cognitive function affected by altitude of adolescents: a cross-section study in Tibet, China

BackgroundThe aim of the study was to examine the cognitive function of Tibetan adolescents at different altitudes and evaluate the influence of education and urbanization on child’s cognition at high altitudes.MethodsA cross-sectional study was conducted between October 2015 and September 2016 in four counties in Tibet. The study population included 324 adolescents living at an altitude of 2,800 m, including 227 who grew up at altitudes of 4,300 m, and 732 adolescents attending three high-altitude boarding schools (one at 4,300 m and two at 4,500 m), including 119 who grew up at an altitude of 2,800 m. Fluid reasoning was assessed using Standard Progressive Matrices (SPMs). The background information was collected using self-administered questionnaires.ResultsA multilevel linear regression model was used to determine the effects of altitude, education, and urbanization on fluid reasoning. In the fixed-effects model, the average SPM score of adolescents from low altitudes who attended kindergarten was 40.41. Scores of students who moved from high to low altitudes, came from high altitudes, and moved from low to high altitudes were 2.66, 4.71, and 6.70 points lower, respectively, than those of students from low altitudes, and 2.50 points lower in students who had not attended kindergarten than those who had. In the random-effects model, the scores of those who only went to first grade were 2.93 points lower. Students from County 3 had average scores of 1.89 higher than did students from the other three counties.ConclusionHigh altitudes may negatively affect the cognition of Tibetan adolescents. This effect was reduced by moving to a lower altitude, increasing the number of years of formal education, attending kindergarten, and living in a more urbanized location. Even at high altitude, moving to higher altitudes should be avoided

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Application of machine learning in predicting aggressive behaviors from hospitalized patients with schizophrenia

ObjectiveTo establish a predictive model of aggressive behaviors from hospitalized patients with schizophrenia through applying multiple machine learning algorithms, to provide a reference for accurately predicting and preventing of the occurrence of aggressive behaviors.MethodsThe cluster sampling method was used to select patients with schizophrenia who were hospitalized in our hospital from July 2019 to August 2021 as the survey objects, and they were divided into an aggressive behavior group (611 cases) and a non-aggressive behavior group (1,426 cases) according to whether they experienced obvious aggressive behaviors during hospitalization. Self-administered General Condition Questionnaire, Insight and Treatment Attitude Questionnaire (ITAQ), Family APGAR (Adaptation, Partnership, Growth, Affection, Resolve) Questionnaire (APGAR), Social Support Rating Scale Questionnaire (SSRS) and Family Burden Scale of Disease Questionnaire (FBS) were used for the survey. The Multi-layer Perceptron, Lasso, Support Vector Machine and Random Forest algorithms were used to build a predictive model for the occurrence of aggressive behaviors from hospitalized patients with schizophrenia and to evaluate its predictive effect. Nomogram was used to build a clinical application tool.ResultsThe area under the receiver operating characteristic curve (AUC) values of the Multi-Layer Perceptron, Lasso, Support Vector Machine, and Random Forest were 0.904 (95% CI: 0.877–0.926), 0.901 (95% CI: 0.874–0.923), 0.902 (95% CI: 0.876–0.924), and 0.955 (95% CI: 0.935–0.970), where the AUCs of the Random Forest and the remaining three models were statistically different (p &lt; 0.0001), and the remaining three models were not statistically different in pair comparisons (p &gt; 0.5).ConclusionMachine learning models can fairly predict aggressive behaviors in hospitalized patients with schizophrenia, among which Random Forest has the best predictive effect and has some value in clinical application

Assessing malnutrition in patients with nasopharyngeal carcinoma: Diagnostic protocol for the development and validation of a new nutritional assessment tool

Introduction There is currently no gold standard or specific nutritional assessment tool to assess malnutrition in patients with nasopharyngeal carcinoma (NPC). Our study aims to develop a new nutritional assessment tool for NPC patients. Methods and analysis NPC patients will be required to complete a risk factor questionnaire after obtaining their informed consent. The risk factor questionnaire will be used to collect potential risk factors for malnutrition. Univariate and multivariate logistic regression analyses will be used to identify risk factors for malnutrition. A new nutritional assessment tool will be developed based on risk factors. The new tool's performance will be assessed by calibration and discrimination. The bootstrapping will be used for internal validation of the new tool. In addition, external validation will be performed by recruiting NPC patients from another hospital. Discussion If the new tool is validated to be effective, it will potentially save medical staff time in assessing malnutrition and improve their work efficiency. Additionally, it may reduce the incidence of malnutrition and its adverse consequences. Strengths and limitations of this study The study will comprehensively analyze demographic data, disease status, physical examination, and blood sampling to identify risk factors for malnutrition. Furthermore, the new tool will be systematically evaluated, and validated to determine their effectiveness. However, the restricted geographical range may limit the generalizability of the results to other ethnicities. Additionally, the study does not analyze subjective indicators such as psychology. Ethics and dissemination The ethical approval was granted by the Ethical Committee of the First Affiliated Hospital of Guangxi Medical University (NO. 2022-KT-GUI WEI-005) and the Second Affiliated Hospital of Guangxi Medical University (NO. 2022-KY-0752). © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Serial Monitoring of Circulating Tumor DNA in Patients With Metastatic Colorectal Cancer to Predict the Therapeutic Response

Early biomarkers of therapeutic responses can help optimize the treatment of metastatic colorectal cancers (mCRC). In this prospective exploratory study, we examined serial changes of plasma-circulating tumor DNA (ctDNA) in 41 mCRC patients receiving first-line chemotherapies and tested its association with treatment outcomes according to radiological assessments. Using next-generation sequencing technologies, we profiled somatic mutations in 50 cancer-related genes in ctDNA before each of the first four treatment cycles. We observed mutations in 95.7% of pre-treatment ctDNA samples. Using mutations of the maximal frequency in each pre-treatment plasma ctDNA sample as the candidate targets, we computed log2 fold changes of ctDNA levels between adjacent treatment cycles. We found that ctDNA reductions as early as prior to cycle 2 predicted responses after cycle 4. Log2 fold changes of ctDNA after cycle 1 (ctDNA log2 (C1/C0)) &gt; −0.126 predicted progressive disease, with an accuracy of 94.6%. These patients also showed significantly worse progression-free survival than those with ctDNA log2 (C1/C0) ≤ −0.126 (median 2.0 vs. 9.0 months; P = 0.007). Together, the present exploratory study suggests that early changes in ctDNA levels detected via targeted sequencing are potential biomarkers of future treatment responses in mCRCs