A systematic literature review of milk consumption and associated bacterial zoonoses in East Africa

Consumption of unsafe animal-source foods is the major cause of foodborne disease outbreaks in low-income countries. Despite current knowledge of the threat posed by raw milk consumption to human health, people in many countries in East Africa still consume unboiled milk. This literature review explored the association between milk consumption and the occurrence of five milk-borne bacterial zoonoses: brucellosis, salmonellosis, campylobacteriosis, Escherichia coli infections, and tuberculosis. A search for literature published up to 1 October 2021 was conducted through the Web of Science, PubMed, and Scopus databases, using Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. The selection process yielded 65 articles describing studies conducted in East Africa 2010-2021, which were carefully scrutinized. The most investigated pathogen was Brucella spp. (54.5%), followed by E. coli (18.2%), Salmonella spp. (12.1%), Mycobacterium spp. (6.1%), and E. coli O157: H7 (6.1%). The most common predisposing factors for potential milk-borne disease outbreaks were consumption of contaminated raw milk, inadequate cold storage along the milk value chain, poor milk handling practices, and lack of awareness of the health risks of consuming unpasteurized milk. Thus, a tailor-made training program is needed for all milk value chain actors to enhance the safety of milk sold in informal markets, and a One Health approach should be applied. Future studies should employ more advanced diagnostic techniques and countries in East Africa should invest in modern diagnostic tools and equipment, both in hospitals and in local rural settings where most cases occur

MILK Symposium review: Microbiological quality and safety of milk from farm to milk collection centers in Rwanda

The aim of this study was to generate knowledge on the most important milk quality and safety attributes, including somatic cell count (SCC), total bacterial count (TBC), Escherichia coli, Salmonella, and Brucella spp. antibodies and antibiotic residues in milk in the chain from farm to milk collection center (MCC) in Rwanda. In addition, we investigated farm and management factors associated with high TBC, SCC, and Salmonella counts. Raw milk was sampled at the farm and MCC levels. Milk samples were taken from dairy farms linked to 2 selected MCC in each of the 4 provinces in Rwanda. In total, 406 bulk milk samples from 406 farms and 32 bulk milk samples from 8 MCC were collected and analyzed. Farm milk average SCC varied between 180 × 103 and 920 × 103 cells/mL, whereas average SCC in milk samples at MCC varied between 170 × 103 and 1,700 × 103 cells/mL. The mean milk TBC of different farms per MCC varied between 1.1 × 106 and 1.6 × 107 cfu/mL, whereas in milk samples from different MCC, the mean TBC ranged between 5.3 × 105 and 2.4 × 108 cfu/mL. The high TBC in milk from MCC suggests proliferation or recontamination of milk by bacteria during transportation. Escherichia coli was detected in 35 of 385 farm milk samples and ranged between 5 cfu/mL and 1.1 × 104 cfu/mL, whereas in milk samples from the MCC, it was detected in 20 out 32 samples varying between 5 cfu/mL and 2.9 × 103 cfu/mL. Overall farm prevalence of Salmonella in milk samples was 14%, but no milk samples from MCC were positive for Salmonella. Five out of 22 bulk milk samples from different MCC were positive for Brucella spp. antibodies, but no Brucella antibodies were detected in milk samples from farms. The prevalence of antibiotic residues as detected by the Delvotest SP NT (DSM, Delft, the Netherlands) was low: 1.3% in farm milk samples and undetected in MCC milk samples. Lack of a separate milking area was associated with high TBC, whereas offering of supplemental feeds, keeping data of past diseases, and an unhygienic milking area were associated with high SCC. Lack of teat washing before milking was the only factor associated with Salmonella contamination of milk at the farm level. This study indicated high TBC and SCC of milk samples at the farm and MCC levels, which indicates both microbial contamination of milk and poor udder health in dairy cows. Presence of E. coli, Salmonella, and Brucella antibodies in milk was common, but finding antibiotic residues in milk was uncommon

Wellbeing indicators affecting female entrepreneurship in OECD countries

[EN] The objective of this research is to know which wellbeing indicators, such as work-life balance, educational level, income or job security, are related to the rate of female entrepreneurship in 29 OECD countries. In addition, these countries have been classified according to the motivation of the entrepreneur either by necessity or by opportunity. The empiric study is focused on 29 OECD countries covering the different geographic areas (Western Europe, Central and Eastern Europe, Middle East, etc.) Due to the fact that the sample is relatively small, it is essential to use a selective approach when selecting the causal conditions. To this end, fsQCA is the most appropriate methodology for such a small data set. A total of 5 variables have been used: an independent variable (female TEA ratio), and four dependent variables (work life balance, educational level, sustainable household income and job security). Data measuring female TEA ratio have been obtained from Global Entrepreneur Monitor (GEM in Global report, 2015) data base, while data measuring wellbeing dimensions were taken from the Better Life Index (OECD in How¿s life? Measuring wellbeing, 2015. http://www.oecdbetterlifeindex.org). The results of this piece of research show that countries with high sustainable household income together with high level of education achieves high female entrepreneurship ratio with both, a good work-life balance (despite of a high unemployment probability), or a high labour-personal imbalance (in this latter, with a low probability of unemployment).This work has been funded by the R + D project for emerging research groups with reference (GVA) GV/2016/078.Ribes-Giner, G.; Moya Clemente, I.; Cervelló Royo, RE.; Perelló Marín, MR. (2019). Wellbeing indicators affecting female entrepreneurship in OECD countries. 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The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Influencing subjective well-being for business and sustainable development using big data and predictive regression analysis

YesBusiness leaders and policymakers within service economies are placing greater emphasis on well-being, given the role of workers in such settings. Whilst people’s well-being can lead to economic growth, it can also have the opposite effect if overlooked. Therefore, enhancing subjective well-being (SWB) is pertinent for all organisations for the sustainable development of an economy. While health conditions were previously deemed the most reliable predictors, the availability of data on people’s personal lifestyles now offers a new dimension into well-being for organisations. Using open data available from the national Annual Population Survey in the UK, which measures SWB, this research uncovered that among several independent variables to predict varying levels of people's perceived well-being, long-term health conditions, one's marital status, and age played a key role in SWB. The proposed model provides the key indicators of measuring SWB for organisations using big data

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Aetiology and prevalence of subclinical mastitis in dairy herds in peri-urban areas of Kigali in Rwanda

The aim of this cross-sectional study was to evaluate the prevalence of subclinical mastitis (SCM) and associated risk factors in dairy cows in peri-urban areas of Kigali, Rwanda, and identify causative udder pathogens. A sample of 256 cows from 25 herds was screened with the California Mastitis Test (CMT), and udder quarters with CMT score >= 3 (scale 1-5) were milk sampled for culture and final bacteriological identification with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). All resultant staphylococci species were tested for beta-lactamase production with the clover leaf method. In parallel, herd bulk milk somatic cell count (SCC) of each herd was analysed using a portable device, the DeLaval cell counter. The prevalence of SCM was 43.1% at quarter level and 76.2% at cow level based on CMT test. Multiparous, Holstein cows were 2.50 (C.I = 1.32-4.71) and 10.08 (C.I = 1.54-66.13) times more likely to contract SCM infection than primiparous animals or cows of other breeds, respectively. The median and mean SCC of all herds were 1108 x 10(3) cells/mL and 1179 x 10(3) cells/mL, respectively. The most prevalent pathogens were non-aureus staphylococci (NAS; 40.2%) followed by Staphylococcus aureus (22%) and less prevalent pathogens (6%). Samples with no growth or contamination constituted 30.4% and 1.4% of the diagnoses, respectively. The most prevalent species within NAS were S. epidermidis (38.2%) followed by S. sciuri (19.5%), S. chromogenes (9.8%), and nine less prevalent NAS species (32.5%). Out of 209 staphylococci isolates, 77% exhibited beta-lactamase production. The study shows that there is high prevalence of SCM and high herd bulk milk SCC in herds in Kigali, indicating udder health problems in dairy cows. Additionally, beta-lactamase production among staphylococci species was common. Improved milking hygiene and application of biosecurity measures, or a complete mastitis control plan, is required to lower the prevalence of SCM and minimize the spread of pathogens among dairy cows