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Iodine deficiency has multiple adverse effects on growth and development. Diets in many countries cannot provide adequate iodine without iodine fortification of salt. In 2020, 124 countries have legislation for mandatory salt iodization and 21 have legislation allowing voluntary iodization. As a result, 88% of the global population uses iodized salt. For population surveys, the urinary iodine concentration (UIC) should be measured and expressed as the median, in μg/L. The quality of available survey data is high UIC surveys have been done in 152 out of 194 countries in the past 15 years; in 132 countries, the studies were nationally representative. The number of countries with adequate iodine intake has nearly doubled from 67 in 2003 to 118 in 2020. However, 21 countries remain deficient, while 13 countries have excessive intakes, either due to excess groundwater iodine, or over-iodized salt. Iodine programs are reaching the poorest of the poor of the 15 poorest countries in the world, 10 are iodine sufficient and only 3 (Burundi, Mozambique and Madagascar) remain mild-to-moderately deficient. Nigeria and India have unstable food systems and millions of malnourished children, but both are iodine-sufficient and population coverage with iodized salt is a remarkable 93% in both. Once entrenched, iodine programs are often surprisingly durable even during national crises, for example, war-torn Afghanistan and Yemen are iodine-sufficient. However, the equity of iodized salt programs within countries remains an important issue. In summary, continued support of iodine programs is needed to sustain these remarkable global achievements, and to reach the remaining iodine-deficient countries.Emerging evidence has demonstrated that melatonin (MT) plays a crucial role in regulating mammalian reproductive functions. It has been reported that MT has a protective effect on polycystic ovary syndrome (PCOS). However, the protective mechanisms of MT remain poorly understood. This study aims to explore the effect of MT on ovarian function in PCOS and to elucidate the relevant molecular mechanisms in vivo and in vitro. We first analysed MT expression levels in the follicular fluid of PCOS patients. A significant reduction in MT expression levels was noted in PCOS patients. BzATP triethylammonium Intriguingly, reduced MT levels correlated with serum testosterone and inflammatory cytokine levels in follicular fluid. Moreover, we confirmed the protective function of MT through regulating autophagy in a DHEA-induced PCOS rat model. Autophagy was activated in the ovarian tissue of the PCOS rat model, whereas additional MT inhibited autophagy by increasing PI3K–Akt pathway expression. In addition, serum-free testosterone, inflammatory and apoptosis indexes were reduced after MT supplementation. Furthermore, we also found that MT suppressed autophagy and apoptosis by activating the PI3K-Akt pathway in the DHEA-exposed human granulosa cell line KGN. Our study showed that MT ameliorated ovarian dysfunction by regulating autophagy in DHEA-induced PCOS via the PI3K-Akt pathway, revealing a potential therapeutic drug target for PCOS.Cambodia has made impressive progress in reducing malaria trends and, in 2018, reported no malaria-related deaths for the first time. However, the coronavirus disease (COVID-19) pandemic presents a potential challenge to the country’s goal for malaria elimination by 2025. The path toward malaria elimination depends on sustained interventions to prevent rapid resurgence, which can quickly set back any gains achieved.Malaria Consortium supported mobile malaria workers (MMWs) to engage with target communities to build acceptance, trust, and resilience. At the start of the pandemic, Malaria Consortium conducted a COVID-19 risk assessment and quickly developed and implemented a mitigation plan to ensure MMWs were able to continue providing malaria services without putting themselves or their patients at risk. Changes in malaria intervention coverage and community uptake have been monitored to gauge the indirect effects of COVID-19. Comparisons have been made between output indicators reported in 2020 and from the same month-period of the previous year.In general, malaria service intervention coverage and utilization rates did not decline in 2020. Rather, the reported figures show there was a substantial increase in service utilization. Preliminary internal reviews and community meetings show that despite a heightened public risk perception toward COVID-19, malaria testing motivation has been well sustained throughout the pandemic. This may be attributable to proactive program planning and data monitoring and active engagement with the communities and the national authorities to circumvent the indirect effect of COVID-19 on intervention coverage in Cambodia during the pandemic.For gait analysis, especially for the detection of subtle gait abnormalities, the collected datasets involve high variability across subjects due to inherent biometric traits and movement behaviors, leading to limited detection accuracy and poor generalizability. To address this, we propose a novel deep multi-source Unsupervised Domain Adaptation (UDA) approach, namely Maximum Cross-Domain Classifier Discrepancy (MCDCD), which aims to improve the classification performance on the test subject (target domain) by leveraging the information from multiple labelled training subjects (source domains). Specifically, the proposed model consists of a feature extractor and a domain-specific category classifier per source domain. The former feature extractor learns to generate discriminative gait features. For the latter classifiers, we minimize the cross-entropy loss to accurately classify source samples, and simultaneously maximize a novel cross-domain discrepancy loss between any two category classifiers to minimize domain shift between multiple sources and the target domain. To validate the proposed MCDCD for detecting gait abnormalities on novel subjects, we collected both high-quality Motion capture (Mocap) and noisy Electromyography (EMG) data from eighteen subjects with both normal and imitated abnormal gaits. Experiment results using both data modalities demonstrate that the proposed approach can achieve superior performance in abnormal gait classification compared to baseline deep models and state-of-the-art UDA methods.