METHODS: In this work, we performed a systematic review and meta-analysis to precisely examine the association between circulating levels of leptin and adiponectin and CRC risk. A systematic literature search was performed in PubMed/MEDLINE, Scopus, Web of Science, and EMBASE databases from inception until October 2020. The pooled effect size was then estimated by calculating the odds ratio (OR).
RESULTS: A total of 23 records (comprising 26 studies) were included in the meta-analysis. The overall analysis found that circulating levels of leptin and adiponectin were not significantly associated with CRC risk (P > 0.05). Interestingly, subgroup analysis revealed that a higher level of adiponectin was significantly associated with an increased CRC risk among overweight individuals (OR = 1.16; 95 % CI: 1.02, 1.32), and a decreased CRC risk among normal weight individuals (OR = 0.76; 95 % CI: 0.62, 0.92). Besides, a higher level of adiponectin was also significantly associated with a decreased risk of CRC in men (OR = 0.76; 95 % CI: 0.59, 0.98).
CONCLUSIONS: In conclusion, circulating leptin level was not associated with CRC risk, but that of adiponectin was associated with CRC risk only in specific subgroups.
AIM: Systems approaches can help characterise local causal systems, identify useful leverage points, and foster participation needed to localise and catalyse development action. Critically, such efforts must be deeply rooted in place, involving local actors in mapping decision-processes and causation within local physical, social and policy environments. Given that each place has a unique geographical or spatial extent and therein lies its unique characters and problems, we term these activities "placially explicit." We describe and reflect on a process used to develop placially explicit, systems-based (PESB) case studies on issues that intersect with and impact urban health and wellbeing, addressing the perspectives of various actors to produce place-based models and insights that are useful for SDG localisation.
METHODS: Seven case studies were co-produced by one or more Partners with place-based knowledge of the case study issue and a Systems Thinker. In each case, joint delineation of an appropriate framing was followed by iterative dialogue cycles to uncover key contextual factors, with attention to institutional and societal structures and paradigms and the motivations and constraints of other actors. Casual loop diagrams (CLDs) were iteratively developed to capture complex narratives in a simple visual way.
RESULTS: Case study development facilitated transfer of local knowledge and development of systems thinking capacity. Partners reported new insights, including a shifting of problem frames and corresponding solution spaces to higher systems levels. Such changes led partners to re-evaluate their roles and goals, and thence to new actions and strategies. CLD-based narratives also proved useful in ongoing communications.
CONCLUSION: Co-production of PESB case studies are a useful component of transdisciplinary toolsets for local SDG implementation, building the capacity of local actors to explore complex problems, identify new solutions and indicators, and understand the systemic linkages inherent in SDG actions across sectors and scales.
METHODS: A comparative cross-sectional study was conducted over a period of 1 year (June 1st, 2018-May 31st, 2019) in two tertiary referral centers in Kuala Lumpur, Malaysia. Thirty-eight survivors of childhood brain tumors aged 6 to 18 years old who had been off-treatment for at least 1 year and were in remission, 38 age- and gender-matched survivors of childhood leukemia who had been off-treatment for at least 1 year and were in remission, and 38 age- and gender-matched unrelated healthy children were recruited. The Child Behaviour Checklist (CBCL) parent report and Youth Self-Report (YSR) questionnaires were used to assess behavioral outcomes.
RESULTS: Survivors of childhood brain tumors showed statistically significantly worse behavioral outcomes than healthy children for social problems and attention problems (p
METHODS: A gender-matched case-control study was conducted in the largest public sector cardiac hospital of Pakistan, and the data of 460 subjects were collected. The dataset comprised of eight nonclinical features. Four supervised ML algorithms were used to train and test the models to predict the CVDs status by considering traditional logistic regression (LR) as the baseline model. The models were validated through the train-test split (70:30) and tenfold cross-validation approaches.
RESULTS: Random forest (RF), a nonlinear ML algorithm, performed better than other ML algorithms and LR. The area under the curve (AUC) of RF was 0.851 and 0.853 in the train-test split and tenfold cross-validation approach, respectively. The nonclinical features yielded an admissible accuracy (minimum 71%) through the LR and ML models, exhibiting its predictive capability in risk estimation.
CONCLUSION: The satisfactory performance of nonclinical features reveals that these features and flexible computational methodologies can reinforce the existing risk prediction models for better healthcare services.
MATERIALS AND METHOD: A panel of 768 single-nucleotide polymorphisms (SNPs) previously associated with various cancers and known non-genetic risk factors for NPC were selected and analyzed for their associations with NPC in a case-control study.
RESULTS: Statistical analysis identified 40 SNPs associated with NPC risk in our population, including 5 documented previously by genome-wide association studies (GWAS) and other case-control studies; the associations of the remaining 35 SNPs with NPC were novel. In addition, consistent with previous studies, exposure to occupational hazards, overconsumption of salt-cured foods, red meat, as well as low intake of fruits and vegetables were also associated with NPC risk.
CONCLUSIONS: In short, this study confirmed and/or identified genetic, environmental and dietary risk factors associated with NPC susceptibility in a Southeast Asian population.