Rapid elimination of Plasmodium falciparum malaria in Cambodia is a goal with both national and international significance. Transmission of malaria in Cambodia is limited to forest environments, and the main population at risk consists of forest-goers who rely on forest products for income or sustenance. The ideal interventions to eliminate malaria from this population are unknown.

In two forested regions of Cambodia, forest-goers were trained to become forest malaria workers (FMWs). In one region, FMWs performed mass screening and treatment, focal screening and treatment, and passive case detection inside the forest. In the other region, FMWs played an observational role for the first year, to inform the choice of intervention for the second year. In both forests, FMWs collected blood samples and questionnaire data from all forest-goers they encountered. Mosquito collections were performed in each forest.

Malaria prevalence by PCR was high in the forest, with 2.3-5.0% positive for P. falciparum and 14.6-25.0% positive for Plasmodium vivax among forest-goers in each study site. In vectors, malaria prevalence ranged from 2.1% to 9.6%, but no P. falciparum was observed. Results showed poor performance of mass screening and treatment, with sensitivity of rapid diagnostic tests equal to 9.1% (95% CI 1.1%, 29.2%) for P. falciparum and 4.4% (95% CI 1.6%, 9.2%) for P. vivax. Malaria infections were observed in all demographics and throughout the studied forests, with no clear risk factors emerging.

Malaria prevalence remains high among Cambodian forest-goers, but performance of rapid diagnostic tests is poor. More adapted strategies to this population, such as intermittent preventive treatment of forest goers, should be considered.

Malaria prevalence remains high among Cambodian forest-goers, but performance of rapid diagnostic tests is poor. More adapted strategies to this population, such as intermittent preventive treatment of forest goers, should be considered.

A novel goose-origin astrovirus (GoAstV) has broken out across China in recent years, causing gout in goslings with a mortality rate of around 50%. However, our understanding of the dynamic distribution, tissue tropism and pathogenesis of GoAstV is incomplete. In order to assess its pathogenicity, one-day-old goslings were inoculated separately with GoAstV via oral and subcutaneous injection routes.

Clinical symptoms, gross and microscopic lesions, blood biochemical parameters and viral loads were detected and recorded for 20 days after infection. Typical gout was observed in experimental goslings. GoAstV can be replicated in tissues and cause pathological damage, especially in the kidney, liver, heart and spleen. Elenestinib Virus-specific genomic RNA was detected in blood, cloacal swabs and all representative tissues, and virus shedding was detected up to 20 days after inoculation, suggesting that GoAstV has a wide tissue tropism and spread systematically after inoculation. The viral copy numbers examined in kidney were the highest, followed by spleen and liver.

This experiment determined the accurate value of viral loads and biochemical indicators of GoAstV-induced goslings. These findings increase our understanding of the pathogenicity of GoAstV in goslings and provide more reference for future research.

This experiment determined the accurate value of viral loads and biochemical indicators of GoAstV-induced goslings. These findings increase our understanding of the pathogenicity of GoAstV in goslings and provide more reference for future research.Hypoxia is a common feature of solid tumors, and develops because of the rapid growth of the tumor that outstrips the oxygen supply, and impaired blood flow due to the formation of abnormal blood vessels supplying the tumor. It has been reported that tumor hypoxia can activate angiogenesis, thereby enhancing invasiveness and risk of metastasis; increase survival of tumor, as well as suppress anti-tumor immunity and hamper the therapeutic response. Hypoxia mediates these effects by several potential mechanisms altering gene expression, the activation of oncogenes, inactivation of suppressor genes, reducing genomic stability and clonal selection. We have reviewed the effects of hypoxia on tumor biology and the possible strategiesto manage the hypoxic tumor microenvironment (TME), highlighting the potential use of cancer stem cells in tumor treatment.

Emergency situations, including epidemics, increase incidence of violence against women, especially intimate partner violence (IPV). This paper describes specific scenarios of IPV reported by women during the COVID-19 pandemic in Nigeria to provide insight for policy and programmatic efforts.

This paper draws on seven de-identified case reports from organisations serving women experiencing IPV as well as media coverage of IPV cases in Nigeria, between April and May, 2020.

In most cases, reports identified IPV that was occurring prior to the lockdown, but increased in severity or involved new types of violence during the lockdown. The case scenarios included descriptions of many forms of IPV commonly reported, including physical, economic, psychological and sexual violence, often concurrently. Several women also reported threats of being thrown out of their homes by perpetrators, which threatens women’s ability to protect themselves from exposure to COVID-19, but could also leave women stranded with no artently placed women already experiencing partner violence at risk for experiencing more severe violence, new challenges to cope with violent experiences, and other forms of violence, including violence that used the lockdown as a way to threaten women’s security and ability to protect themselves from the virus. Hence, there is need for innovative approaches to support victims, with emphasis on ways in which perpetrators of IPV may be using the threat of COVID-19 to further gain power and control over partners.

In biomedical applications, valuable data is often split between owners who cannot openly share the data because of privacy regulations and concerns. Training machine learning models on the joint data without violating privacy is a major technology challenge that can be addressed by combining techniques from machine learning and cryptography. When collaboratively training machine learning models with the cryptographic technique named secure multi-party computation, the price paid for keeping the data of the owners private is an increase in computational cost and runtime. A careful choice of machine learning techniques, algorithmic and implementation optimizations are a necessity to enable practical secure machine learning over distributed data sets. Such optimizations can be tailored to the kind of data and Machine Learning problem at hand.

Our setup involves secure two-party computation protocols, along with a trusted initializer that distributes correlated randomness to the two computing parties. We use a gradient descent based algorithm for training a logistic regression like model with a clipped ReLu activation function, and we break down the algorithm into corresponding cryptographic protocols.