An in vitro mechanism study on the proliferation and pluripotency of human embryonic stems cells in response to magnesium degradation.

Magnesium (Mg) is a promising biodegradable metallic material for applications in cellular/tissue engineering and biomedical implants/devices. To advance clinical translation of Mg-based biomaterials, we investigated the effects and mechanisms of Mg degradation on the proliferation and pluripotency of human embryonic stem cells (hESCs). We used hESCs as the in vitro model system to study cellular responses to Mg degradation because they are sensitive to toxicants and capable of differentiating into any cell types of interest for regenerative medicine. In a previous study when hESCs were cultured in vitro with either polished metallic Mg (99.9% purity) or pre-degraded Mg, cell death was observed within the first 30 hours of culture. Excess Mg ions and hydroxide ions induced by Mg degradation may have been the causes for the observed cell death; hence, their respective effects on hESCs were investigated for the first time to reveal the potential mechanisms. For this purpose, the mTeSR®1 hESC culture media was either modified to an alkaline pH of 8.1 or supplemented with 0.4-40 mM of Mg ions. We showed that the initial increase of media pH to 8.1 had no adverse effect on hESC proliferation. At all tested Mg ion dosages, the hESCs grew to confluency and retained pluripotency as indicated by the expression of OCT4, SSEA3, and SOX2. When the supplemental Mg ion dosages increased to greater than 10 mM, however, hESC colony morphology changed and cell counts decreased. These results suggest that Mg-based implants or scaffolds are promising in combination with hESCs for regenerative medicine applications, providing their degradation rate is moderate. Additionally, the hESC culture system could serve as a standard model for cytocompatibility studies of Mg in vitro, and an identified 10 mM critical dosage of Mg ions could serve as a design guideline for safe degradation of Mg-based implants/scaffolds

Variation of household electricity consumption and potential impact of outdoor PM2.5 concentration: a comparison between Singapore and Shanghai

The auto-regressive distributed lag (ARDL) bound testing approach was used to study the relationships between the monthly household electricity consumption and outdoor PM2.5 concentration with the consideration of ambient temperature and the number of rainy days for Singapore and Shanghai. It is shown that there are significant long-run relationships between the household electricity consumption and the regressors for both Singapore and Shanghai. For Singapore, a 20% increase in the PM2.5 concentration of a single month is in the long-run significantly related to a 0.8% increase in the household electricity consumption. This corresponds to an electricity overconsumption of 5.0 GWh, a total of 0.7–1.0 million USD in electricity cost, and 2.1 kilotons of CO2 emission associated with electricity generation. For Shanghai, a 20% decrease in the PM2.5 concentration of a single month is in the long-run significantly related to a 2.2% decrease in the household electricity consumption. This corresponds to a 35.0 GWh decrease in the overall household electricity consumption, 1.6–5.1 million USD decrease in electricity cost, and 17.5 kilotons of CO2 emission. The results suggest that the cost of electricity consumption should be included in the economic cost analysis of PM2.5 pollution in the future. A 1 °C increase in the monthly temperature is in the long-run significantly related to a 13.6% increase in the monthly electricity consumption for Singapore, while a 30 degree days increase in heating & cooling days (HCDD) is in the long-run significantly related to a 24.9% increase in the monthly electricity consumption for Shanghai. A 5-day increase in the number of rainy days per month is in the long-run significantly related to a 3.0% and 5.8% increase in the monthly electricity consumption for Singapore and Shanghai, respectively

On the association between outdoor PM 2.5 concentration and the seasonality of tuberculosis for Beijing and Hong Kong

Tuberculosis (TB) is still a serious public health problem in various countries. One of the long-elusive but critical questions about TB is what the risk factors are and how they contribute for its seasonality. An ecologic study was conducted to examine the association between the variation of outdoor PM2.5 concentration and the TB seasonality based on the monthly TB notification and PM2.5 concentration data of Hong Kong and Beijing. Both descriptive analysis and Poisson regression analysis suggested that the outdoor PM2.5 concentration could be a potential risk factor for the seasonality of TB disease. The significant relationship between the number of TB cases and PM2.5 concentration was not changed when regression models were adjusted by sunshine duration, a potential confounder. The regression analysis showed that a 10 μg/m3 increase in PM2.5 concentrations during winter is significantly associated with a 3% (i.e. 18 and 14 cases for Beijing and Hong Kong, respectively) increase in the number of TB cases notified during the coming spring or summer for both Beijing and Hong Kong. Three potential mechanisms were proposed to explain the significant relationship: (1) increased PM2.5 exposure increases host's susceptibility to TB disease by impairing or modifying the immunology of the human respiratory system; (2) increased indoor activities during high outdoor PM2.5 episodes leads to an increase in human contact and thus the risk of TB transmission; (3) the seasonal change of PM2.5 concentration is correlated with the variation of other potential risk factors of TB seasonality. Preliminary evidence from the analysis of this work favors the first mechanism about the PM2.5 exposure-induced immunity impairment. This work adds new horizons to the explanation of the TB seasonality and improves our understanding of the potential mechanisms affecting TB incidence, which benefits the prevention and control of TB disease

Full HD JPEG XR Encoder Design for Digital Photography Applications

Non

A Chip Architecture for Compressive Sensing Based Detection of IC Trojans

We present a chip architecture for a compressive sensing based method that can be used in conjunction with the JTAG standard to detect IC Trojans. The proposed architecture compresses chip output resulting from a large number of test vectors applied to a circuit under test (CUT). We describe our designs in sensing leakage power, computing random linear combinations under compressive sensing, and piggybacking these new functionalities on JTAG. Our architecture achieves approximately a 10× speedup and 1000× reduction in output bandwidth while incurring a small area overhead.Engineering and Applied Science

Fault Orientation Determination for the 4 March 2008 Taoyuan Earthquake from Dense Near-Source Seismic Observations

On 4 March 2008, a moderate earthquake (ML = 5.2) occurred in southern Taiwan and named as the Taoyuan earthquake, preceded by foreshocks and followed by numerous aftershocks. This earthquake sequence occurred during the TAIGER (TAiwan Integrated GEodynamics Research) controlled-source seismic experiment. Consequently, several seismic networks were deployed in the Taiwan area at this time and many stations recorded this earthquake sequence in the near-source region. We archived and processed near-source observations to determine the fault orientation. To locate the events more accurately, station corrections, waveform cross-correlation to pick seismic phases, and a double-difference earthquake location algorithm were used to compute earthquake hypocenters. Over a 50-hour recording period, beginning half an hour before the start of the main shock, 2340 events were identified within the earthquake sequence. The identified aftershocks reveal a clear fault plane with a strike of N37°E and a dip of 45°SE. This plane corresponds to one of the focal mechanism nodal planes determined by the Broadband Array in Taiwan for Seismology (BATS) (strike = 37°, dip = 48°, and rake = 96°). Based on the main shock focal mechanism, the aftershock distribution, and the regional geological reports, we suggest that faulting on the northern extension of the major regional active fault, the Chishan Fault, caused the Taoyuan earthquake sequence

Spatiotemporal droplet dispersion measurements demonstrate face masks reduce risks from singing

COVID-19 has restricted singing in communal worship. We sought to understand variations in droplet transmission and the impact of wearing face masks. Using rapid laser planar imaging, we measured droplets while participants exhaled, said ‘hello’ or ‘snake’, sang a note or ‘Happy Birthday’, with and without surgical face masks. We measured mean velocity magnitude (MVM), time averaged droplet number (TADN) and maximum droplet number (MDN). Multilevel regression models were used. In 20 participants, sound intensity was 71 dB for speaking and 85 dB for singing (p  85% reduction wearing face masks. Droplet transmission varied widely, particularly for singing. Masks decreased TADN by 99% (p < 0.001) and MDN by 98% (p < 0.001) for singing and 86–97% for other tasks. Masks reduced variance by up to 48%. When wearing a mask, neither singing task transmitted more droplets than exhaling. In conclusion, wide variation exists for droplet production. This significantly reduced when wearing face masks. Singing during religious worship wearing a face mask appears as safe as exhaling or talking. This has implications for UK public health guidance during the COVID-19 pandemic

Environmental Health Disparities: A Framework Integrating Psychosocial and Environmental Concepts

Although it is often acknowledged that social and environmental factors interact to produce racial and ethnic environmental health disparities, it is still unclear how this occurs. Despite continued controversy, the environmental justice movement has provided some insight by suggesting that disadvantaged communities face greater likelihood of exposure to ambient hazards. The exposure–disease paradigm has long suggested that differential “vulnerability” may modify the effects of toxicants on biological systems. However, relatively little work has been done to specify whether racial and ethnic minorities may have greater vulnerability than do majority populations and, further, what these vulnerabilities may be. We suggest that psychosocial stress may be the vulnerability factor that links social conditions with environmental hazards. Psychosocial stress can lead to acute and chronic changes in the functioning of body systems (e.g., immune) and also lead directly to illness. In this article we present a multidisciplinary framework integrating these ideas. We also argue that residential segregation leads to differential experiences of community stress, exposure to pollutants, and access to community resources. When not counterbalanced by resources, stressors may lead to heightened vulnerability to environmental hazards

Prevalence of coronavirus disease 2019 (COVID-19) in different clinical stages before the national COVID-19 vaccination programme in Malaysia: A systematic review and meta-analysis

More than 1.75 million COVID-19 infections and 16 thousand associated deaths have been reported in Malaysia. A meta-analysis on the prevalence of COVID-19 in different clinical stages before the National COVID-19 Vaccination Program in Malaysia is still lacking. To address this, the disease severity of a total of 215 admitted COVID-19 patients was initially recorded in the early phase of this study, and the data were later pooled into a meta-analysis with the aim of providing insight into the prevalence of COVID-19 in 5 different clinical stages during the outset of the COVID-19 pandemic in Malaysia. We have conducted a systematic literature search using PubMed, Web of Science, Scopus, ScienceDirect, and two preprint databases (bioRxiv and medRxiv) for relevant studies with specified inclusion and exclusion criteria. The quality assessment for the included studies was performed using the Newcastle–Ottawa Scale. The heterogeneity was examined with an I2 index and a Q-test. Funnel plots and Egger’s tests were performed to determine publication bias in this meta-analysis. Overall, 5 studies with 6375 patients were included, and the pooled prevalence rates in this meta-analysis were calculated using a random-effect model. The highest prevalence of COVID-19 in Malaysia was observed in Stage 2 cases (32.0%), followed by Stage 1 (27.8%), Stage 3 (17.1%), Stage 4 (7.6%), and Stage 5 (3.4%). About two-thirds of the number of cases have at least one morbidity, with the highest percentage of hypertension (66.7%), obesity (55.5%), or diabetes mellitus (33.3%) in Stage 5 patients. In conclusion, this meta-analysis suggested a high prevalence of COVID-19 occurred in Stage 2. The prevalence rate in Stage 5 appeared to be the lowest among COVID-19 patients before implementing the vaccination program in Malaysia. These meta-analysis data are critically useful for designing screening and vaccination programs and improving disease management in the country