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In Cambodia, goat production and meat consumption are customary among Muslim communities. Recently, goat meat has gained popularity among Cambodians. Goat farmers use a traditional management system, including grazing, requiring minimal labour. The close proximity between humans and animals could increase the risk of zoonotic disease transmission. A serological survey was undertaken to estimate the prevalence of some priority zoonoses and high-impact animal diseases in the Cambodian goat population. A total of 540 samples were collected from goats in six provinces and analysed with commercially available enzyme-linked immunosorbent assays for Brucella species, Q fever (Coxiella burnetii), Foot and Mouth Disease virus non-structural protein (FMDV NSP) and Peste des Petits Ruminants virus (PPRV). True seroprevalences with a 95% Confidence Interval (CI), taking into account imperfect tests, risk factors and odds ratios (ORs), were calculated to better understand the disease distribution and epidemiology. Independent variables used in statistical modellings included sex, body condition score, age, vaccination history, province and commune, while dependent variables were ELISA test results. The overall true prevalence of antibodies to Brucella spp., C. burnetii, FMDV and PPRV, were 0.1% (95% CI 0.0, 1.0), 7.2% (95% CI 5.3, 9.7), 57.7% (95% CI 53.1, 62.3) and 0.0% (95% CI 0.0, 0.0), respectively. There was no identified risk factor for brucellosis and PPR. The two risk factors for C. burnetii seropositivity were sex (p-value = 0.0005) and commune (p-value

In December 2019, cases of atypical pneumonia were diagnosed in hospital patients in Wuhan, Hubei province, China. The disease, now known as COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As case numbers increased and spread across the planet many companies scrambled to develop vaccines to control the infection and disease. Prior research on SARS-CoV-1, new vaccine technologies and unprecedented funding have allowed vaccines to be developed and approved in record time, without the usual pauses and bypassing any of the requirements of the vaccine approval process. This paper is a review of the current literature on some of the vaccines targeting SARS-CoV-2 and of the new technologies used to produce them.

Heparan sulfate modified proteins or proteoglycans (HSPGs) are an abundant class of cell surface and extracellular matrix molecules. They serve important co-receptor functions in the regulation of signaling as well as membrane trafficking. Many of these activities directly affect processes associated with neurodegeneration including uptake and export of Tau protein, disposition of Amyloid Precursor Protein-derived peptides, and regulation of autophagy. In this review we focus on the impact of HSPGs on autophagy, membrane trafficking, mitochondrial quality control and biogenesis, and lipid metabolism. Disruption of these processes are a hallmark of Alzheimer’s disease (AD) and there is evidence that altering heparan sulfate structure and function could counter AD-associated pathological processes. Compromising presenilin function in several systems has provided instructive models for understanding the molecular and cellular underpinnings of AD. Disrupting presenilin function produces a constellation of cellular deficits including accumulation of lipid, disruption of autophagosome to lysosome traffic and reduction in mitochondrial size and number. Inhibition of heparan sulfate biosynthesis has opposing effects on all these cellular phenotypes, increasing mitochondrial size, stimulating autophagy flux to lysosomes, and reducing the level of intracellular lipid. These findings suggest a potential mechanism for countering pathology found in AD and related disorders by altering heparan sulfate structure and influencing cellular processes disrupted broadly in neurodegenerative disease. Vertebrate and invertebrate model systems, where the cellular machinery of autophagy and lipid metabolism are conserved, continue to provide important translational guideposts for designing interventions that address the root cause of neurodegenerative pathology.

The article presents abstracts on topics related to factor analysis which include the application of factor analysis to developed and developing countries and the use of factor analysis in the study of the Civil War.

NK cell exhaustion is caused by chronic exposure to activating stimuli during viral infection, tumorigenesis, and prolonged cytokine treatment. Evidence suggests that exhaustion may play a role in disease progression. However, relative to T cell exhaustion, the mechanisms underlying NK cell exhaustion and methods of reversing it are poorly understood. Here, we describe a potentially novel in vitro model of exhaustion that uses plate-bound agonists of the NK cell activating receptors NKp46 and NKG2D to induce canonical exhaustion phenotypes. In this model, prolonged activation resulted in downregulation of activating receptors, upregulation of checkpoint markers, decreased cytokine production and cytotoxicity in vitro, weakened glycolytic capacity, and decreased persistence, function, and tumor control in vivo. Furthermore, we discovered a beneficial effect of NK cell inhibitory receptor signaling during exhaustion. By simultaneously engaging the inhibitory receptor NKG2A during activation in our model, cytokine production and cytotoxicity defects were mitigated, suggesting that balancing positive and negative signals integrated by effector NK cells can be beneficial for antitumor immunity. Together, these data uncover some of the mechanisms underlying NK cell exhaustion in humans and establish our in vitro model as a valuable tool for studying the processes regulating exhaustion.

While MRI contrast agents such as those based on Gadolinium are needed for high-resolution mapping of brain metabolism, these contrast agents require intravenous administration, and there are rising concerns over their safety and invasiveness. Furthermore, non-contrast MRI scans are more commonly performed than those with contrast agents and are readily available for analysis in public databases such as the Alzheimer's Disease Neuroimaging Initiative (ADNI). In this article, we hypothesize that a deep learning model, trained using quantitative steady-state contrast-enhanced structural MRI datasets, in mice and humans, can generate contrast-equivalent information from a single non-contrast MRI scan. The model was first trained, optimized, and validated in mice, and was then transferred and adapted to humans. We observe that the model can substitute for Gadolinium-based contrast agents in approximating cerebral blood volume, a quantitative representation of brain activity, at sub-millimeter granularity. Furthermore, we validate the use of our deep-learned prediction maps to identify functional abnormalities in the aging brain using locally obtained MRI scans, and in the brain of patients with Alzheimer's disease using publicly available MRI scans from ADNI. Since it is derived from a commonly-acquired MRI protocol, this framework has the potential for broad clinical utility and can also be applied retrospectively to research scans across a host of neurological/functional diseases.