Single-cell RNA transcriptome landscape of hepatocytes and non-parenchymal cells in healthy and NAFLD mouse liver

Nonalcoholic fatty liver disease (NAFLD) is a global health-care problem with limited therapeutic options. To obtain a cellular resolution of pathogenesis, 82,168 single-cell transcriptomes (scRNA-seq) across different NAFLD stages were profiled, identifying hepatocytes and 12 other non-parenchymal cell (NPC) types. scRNA-seq revealed insights into the cellular and molecular mechanisms of the disease. We discovered a dual role for hepatic stellate cells in gene expression regulation and in the potential to trans-differentiate into myofibroblasts. We uncovered distinct expression profiles of Kupffer cells versus monocyte-derived macrophages during NAFLD progression. Kupffer cells showed stronger immune responses, while monocyte-derived macrophages demonstrated a capability for differentiation. Three chimeric NPCs were identified including endothelial-chimeric stellate cells, hepatocyte-chimeric endothelial cells, and endothelial-chimeric Kupffer cells. Our work identified unanticipated aspects of mouse with NAFLD at the single-cell level and advanced the understanding of cellular heterogeneity in NAFLD livers

Geographical information system and predictive risk maps of urinary schistosomiasis in Ogun State, Nigeria

<p>Abstract</p> <p>Background</p> <p>The control of urinary schistosomiasis in Ogun State, Nigeria remains inert due to lack of reliable data on the geographical distribution of the disease and the population at risk. To help in developing a control programme, delineating areas of risk, geographical information system and remotely sensed environmental images were used to developed predictive risk maps of the probability of occurrence of the disease and quantify the risk for infection in Ogun State, Nigeria.</p> <p>Methods</p> <p>Infection data used were derived from carefully validated morbidity questionnaires among primary school children in 2001–2002, in which school children were asked among other questions if they have experienced "blood in urine" or urinary schistosomiasis. The infection data from 1,092 schools together with remotely sensed environmental data such as rainfall, vegetation, temperature, soil-types, altitude and land cover were analysis using binary logistic regression models to identify environmental features that influence the spatial distribution of the disease. The final regression equations were then used in Arc View 3.2a GIS software to generate predictive risk maps of the distribution of the disease and population at risk in the state.</p> <p>Results</p> <p>Logistic regression analysis shows that the only significant environmental variable in predicting the presence and absence of urinary schistosomiasis in any area of the State was Land Surface Temperature (LST) (B = 0.308, p = 0.013). While LST (B = -0.478, p = 0.035), rainfall (B = -0.006, p = 0.0005), ferric luvisols (B = 0.539, p = 0.274), dystric nitosols (B = 0.133, p = 0.769) and pellic vertisols (B = 1.386, p = 0.008) soils types were the final variables in the model for predicting the probability of an area having an infection prevalence equivalent to or more than 50%. The two predictive risk maps suggest that urinary schistosomiasis is widely distributed and occurring in all the Local Government Areas (LGAs) in State. The high-risk areas (≥ 50% prevalence) however, are confined to scatter foci in the north western part of the State. The model also estimated that 98.99% of schools aged children (5–14 years) are living in areas suitable for urinary schistosomiasis transmission and are at risk of infection.</p> <p>Conclusion</p> <p>The risk maps developed will hopefully be useful to the state health officials, by providing them with detailed distribution of urinary schistosomiasis, help to delineate areas for intervention, assesses population at risk thereby helping in optimizing scarce resources.</p

Onchocerciasis transmission in Ghana: biting and parous rates of host-seeking sibling species of the Simulium damnosum complex

Background: Ghana is renowned for its sibling species diversity of the Simulium damnosum complex, vectors of Onchocerca volvulus. Detailed entomological knowledge becomes a priority as onchocerciasis control policy has shifted from morbidity reduction to elimination of infection. To date, understanding of transmission dynamics of O. volvulus has been mainly based on S. damnosum sensu stricto (s.s.) data. We aim to elucidate bionomic features of vector species of importance for onchocerciasis elimination efforts. Methods: We collected S. damnosum sensu lato from seven villages in four Ghanaian regions between 2009 and 2011, using standard vector collection, and human- and cattle-baited tents. Taxa were identified using morphological and molecular techniques. Monthly biting rates (MBR), parous rates and monthly parous biting rates (MPBR) are reported by locality, season, trapping method and hour of collection for each species. Results: S. damnosum s.s./S. sirbanum were collected at Asubende and Agborlekame, both savannah villages. A range of species was caught in the Volta region (forest-savannah mosaic) and Gyankobaa (forest), with S. squamosum or S. sanctipauli being the predominant species, respectively. In Bosomase (southern forest region) only S. sanctipauli was collected in the 2009 wet season, but in the 2010 dry season S. yahense was also caught. MBRs ranged from 714 bites/person/month at Agborlekame (100% S. damnosum s.s./S. sirbanum) to 8,586 bites/person/month at Pillar 83/Djodji (98.5% S. squamosum). MBRs were higher in the wet season. In contrast, parous rates were higher in the dry season (41.8% vs. 18.4%), resulting in higher MPBRs in the dry season. Daily host-seeking activity of S. damnosum s.s./S. sirbanum was bimodal, whilst S. squamosum and S. sanctipauli had unimodal afternoon peaks. Conclusions: The bionomic differences between sibling species of the S. damnosum complex need to be taken into account when designing entomological monitoring protocols for interventions and parameterising mathematical models for onchocerciasis control and elimination

Augmented acquisition of cocaine self-administration and altered brain glucose metabolism in adult female but not male rats exposed to a cannabinoid agonist during adolescence

Marijuana consumption during adolescence has been proposed to be a stepping stone for adult cocaine addiction. However, experimental evidence for this hypothesis is missing. In this work we chronically injected male and female Wistar rats with either the cannabinoid agonist CP 55,940 (CP; 0.4 mg/kg) or its corresponding vehicle. Adult acquisition (seven 30 min daily sessions) and maintenance (fourteen 2 h daily sessions) of cocaine self administration (1 mg/kg), food reinforced operant learning under conditions of normal (ad libitum access to food), and high motivation (food restriction schedule) were measured. Additionally, brain metabolic activity was analyzed by means of [18F] fluorodeoxyglucose positron emission tomography. During the acquisition phase, female CP treated rats showed a higher rate of cocaine self administration as compared to vehicle treated females and males; no differences were found between both male groups. This effect disappeared in the maintenance phase. Moreover, no differences among groups were evident in the food reinforced operant task, pointing to the cocaine specific nature of the effect seen in self administration rather than a general change in reward processing. Basal brain metabolic activity also changed in CP treated females when compared to their vehicle treated counterparts with no differences being found in the males; more specifically we observed a hyper activation of the frontal cortex and a hypo activation of the amygdalo entorhinal cortex. Our results suggest that a chronic exposure to cannabinoids during adolescence alters the susceptibility to acquire cocaine self administration, in a sex specific fashion. This increased susceptibility could be related to thechanges in brain metabolic activity induced by cannabinoids during adolescenceThis work was supported by Grants FIS G03/05 (Red de Trastornos Adictivos), BSO2001-1099, FIS 01-05-01, Plan Nacional sobre Drogas (PNSD) 2001–2003, PNSD 2004–2007, GR-SAL/0260/2004 to EA and Grants INT/2012/ 2002, CB06/01/0079, and CENIT (2006–2009) to MDPublicad

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Prevalence of antibiotic-resistant Escherichia coli isolated from urban and agricultural streams in Canterbury, New Zealand

Baseline studies are needed to identify environmental reservoirs of non-pathogenic but associating microbiota or pathogenic bacteria that are resistant to antibiotics and to inform safe use of freshwater ecosystems in urban and agricultural settings. Mesophilic bacteria and Escherichia coli were quantified and isolated from water and sediments of two rivers, one in an urban and one in an agricultural area near Christchurch, New Zealand. Resistance of E. coli to one or more of nine different antibiotics was determined. Additionally, selected strains were tested for conjugative transfer of resistances. Despite having similar concentrations of mesophilic bacteria and E. coli, the rivers differed in numbers of antibiotic-resistant E. coli isolates. Fully antibiotic-susceptible and -resistant strains coexist in the two freshwater ecosystems. This study was the first phase of antibiotic resistance profiling in an urban setting and an intensifying dairy agroecosystem. Antibiotic-resistant E. coli may pose different ingestion and contact risks than do susceptible E. coli. This difference cannot be seen in population counts alone. This is an important finding for human health assessments of freshwater systems, particularly where recreational uses occur downstream