Cephalometric Assessment of the Fourth Ventricles Using Computerized Tomography: A Five Year Study in Usmanu Danfodiyo University Teaching Hospital (UDUTH), Sokoto, North-Western Nigeria

The fourth ventricle is usually affected in posterior cranial fossa tumours and other intracranial and ventricular disorders. Therefore, accurate measurement of the fourth ventricle will go a long way in evaluating braindisorders and decision making prior to neurosurgical procedures. This, therefore, places high premium on the accuracy in the technique and equipment used in obtaining a good Computerised Tomography (CT) Scan of the brain. To provide baseline data for measurements of normal fourth ventricle using computed tomographic Scan. Measurement was made with Dragon V3.1.1. A total of 652 scan examinations of subjects were analyzed in this study. 434 (65.79%) of the subjects were males while 217 (34.21%) were females. (M: F ratio = 2:1).The mean length of the fourth ventricles was 9.55mm and mean width was 12.86mm. Maximum length was 13.95mm and minimum length was 5.1mm. Least width was 2.65mm and greatest width was 17.28mm. Thus, the difference between the lengths of the fourth ventricles was not statistically significant (p.0.05), so also there was no statistically significant difference (p> 0.05) between the width of the fourth ventricles in males and females. In conclusion, this study has provided reference ranges for the normal values of the length and width of the fourth ventricle in male and female Nigerians.Keywords: Cephalometry, assessment, fourth ventricles, CT, Nigeria

Bioenergy generation from co-digestion of food waste and rumen fluid: impact of varying quantities of rumen fluid on biogas yields

This paper examines the effect of mixing varying quantities of rumen fluid with food waste (FW) to generate biogas energy at ambient temperature (37oC) in a batch anaerobic digestion process. The researchers adopted an anaerobic digestion process for the study. Food waste was obtained from selected fast food establishments at Auchi, Edo State, South-South, Nigeria. The rumen fluid was obtained from an abattoir located at Auchi, Nigeria. Anaerobic digestion of food waste without rumen fluid served as control experiment while 4 other digesters contained 20, 40, 60 and 80ml of rumen fluid for co-digestion experiment. The digesters were labelled FW1-FW5 based on their compositions. The laboratory experiment lasted for a retention time of 17 days without pH control and mixing. Cumulative biogas yield was measured daily by water displacement technique. The values were 2220, 2280, 1860, 1600 and 1420ml respectively. The results obtained showed that addition of rumen fluid did not have any positive impact on biogas yields in digesters FW3-FW5 when compared with the control. Digester FW2 was only 2.70% higher than FW1 which was not a significant increase. Generally, there were antagonistic effects in the codigestion of food waste with rumen fluid as the quantity added increased. This implied that monodigestion of food waste could produce significant quantity of biogas with impressive production rate. Co-digestion should be carried out at a lower quantity of rumen fluid to improve biogas yield and the performance of the process. This article contributed to the body of knowledge by bridging the gap of limited literature in the domain of food waste management techniques in Auchi and Nigeria in general

Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension

In this paper we introduce a novel and accurate optimisation method for segmentation of cardiac MR (CMR) images in patients with pulmonary hypertension (PH). The proposed method explicitly takes into account the image features learned from a deep neural network. To this end, we estimate simultaneous probability maps over region and edge locations in CMR images using a fully convolutional network. Due to the distinct morphology of the heart in patients with PH, these probability maps can then be incorporated in a single nested level set optimisation framework to achieve multi-region segmentation with high efficiency. The proposed method uses an automatic way for level set initialisation and thus the whole optimisation is fully automated. We demonstrate that the proposed deep nested level set (DNLS) method outperforms existing state-of-the-art methods for CMR segmentation in PH patients

Smart waste bin monitoring using IoT for sustainable biomedical waste management.

Suboptimal management of healthcare waste poses a significant concern that can be effectively tackled by implementing Internet of Things (IoT) solutions to enhance trash monitoring and disposal processes. The potential utilisation of the Internet of Things (IoT) in addressing the requirements associated with biomedical waste management within the Kaduna area was examined. The study included a selection of ten hospitals, chosen based on the criterion of having access to wireless Internet connectivity. The issue of biomedical waste is significant within the healthcare sector since it accounts for a considerable amount of overall waste generation, with estimates ranging from 43.62 to 52.47% across various facilities. Utilisation of (IoT) sensors resulted in the activation of alarms and messages to facilitate the prompt collection of waste. Data collected from these sensors was subjected to analysis to discover patterns and enhance the overall efficiency of waste management practices. The study revealed a positive correlation between the quantity of hospital beds and the daily garbage generated. Notably, hospitals with a higher number of beds were observed to generate a much greater amount of waste per bed. Hazardous waste generated varies by hospital, with one hospital leading in sharps waste (10.98 kgd-1) and chemical waste (21.06 kgd-1). Other hospitals generate considerable amounts of radioactive waste (0.60 kgd-1 and 0.50 kgd-1), pharmaceuticals, and genotoxic waste (16.19 kgd-1), indicating the need for specialised waste management approaches. The study sheds light on the significance of IoT in efficient waste collection and the need for tailored management of hazardous waste

Evaluation of traditional and machine learning approaches for modeling volatile fatty acid concentrations in anaerobic digestion of sludge: potential and challenges

This study evaluates models for predicting volatile fatty acid (VFA) concentrations in sludge processing, ranging from classical statistical methods (Gaussian and Surge) to diverse machine learning algorithms (MLAs) such as Decision Tree, XGBoost, CatBoost, LightGBM, Multiple linear regression (MLR), Support vector regression (SVR), AdaBoost, and GradientBoosting. Anaerobic bio-methane potential tests were carried out using domestic wastewater treatment primary and secondary sludge. The tests were monitored over 40 days for variations in pH and VFA concentrations under different experimental conditions. The data observed was compared to predictions from the Gaussian and Surge models, and the MLAs. Based on correlation analysis using basic statistics and regression, the Gaussian model appears to be a consistent performer, with high R2 values and low RMSE, favoring precision in forecasting VFA concentrations. The Surge model, on the other hand, albeit having a high R2, has high prediction errors, especially in dynamic VFA concentration settings. Among the MLAs, Decision Tree and XGBoost excel at predicting complicated patterns, albeit with overfitting issues. This study provides insights underlining the need for context-specific considerations when selecting models for accurate VFA forecasts. Real-time data monitoring and collaborative data sharing are required to improve the reliability of VFA prediction models in AD processes, opening the way for breakthroughs in environmental sustainability and bioprocessing applications

Monocytes regulate the mechanism of T-cell death by inducing Fas-mediated apoptosis during bacterial infection.

Monocytes and T-cells are critical to the host response to acute bacterial infection but monocytes are primarily viewed as amplifying the inflammatory signal. The mechanisms of cell death regulating T-cell numbers at sites of infection are incompletely characterized. T-cell death in cultures of peripheral blood mononuclear cells (PBMC) showed 'classic' features of apoptosis following exposure to pneumococci. Conversely, purified CD3(+) T-cells cultured with pneumococci demonstrated necrosis with membrane permeabilization. The death of purified CD3(+) T-cells was not inhibited by necrostatin, but required the bacterial toxin pneumolysin. Apoptosis of CD3(+) T-cells in PBMC cultures required 'classical' CD14(+) monocytes, which enhanced T-cell activation. CD3(+) T-cell death was enhanced in HIV-seropositive individuals. Monocyte-mediated CD3(+) T-cell apoptotic death was Fas-dependent both in vitro and in vivo. In the early stages of the T-cell dependent host response to pneumococci reduced Fas ligand mediated T-cell apoptosis was associated with decreased bacterial clearance in the lung and increased bacteremia. In summary monocytes converted pathogen-associated necrosis into Fas-dependent apoptosis and regulated levels of activated T-cells at sites of acute bacterial infection. These changes were associated with enhanced bacterial clearance in the lung and reduced levels of invasive pneumococcal disease

Seasonal variations of EPG levels in gastro-intestinal parasitic infection in a southeast asian controlled locale:a statistical analysis

We present a data based statistical study on the effects of seasonal variations in the growth rates of the gastro-intestinal (GI) parasitic infection in livestock. The alluded growth rate is estimated through the variation in the number of eggs per gram (EPG) of faeces in animals. In accordance with earlier studies, our analysis too shows that rainfall is the dominant variable in determining EPG infection rates compared to other macro-parameters like temperature and humidity. Our statistical analysis clearly indicates an oscillatory dependence of EPG levels on rainfall fluctuations. Monsoon recorded the highest infection with a comparative increase of at least 2.5 times compared to the next most infected period (summer). A least square fit of the EPG versus rainfall data indicates an approach towards a super diffusive (i. e. root mean square displacement growing faster than the square root of the elapsed time as obtained for simple diffusion) infection growth pattern regime for low rainfall regimes (technically defined as zeroth level dependence) that gets remarkably augmented for large rainfall zones. Our analysis further indicates that for low fluctuations in temperature (true on the bulk data), EPG level saturates beyond a critical value of the rainfall, a threshold that is expected to indicate the onset of the nonlinear regime. The probability density functions (PDFs) of the EPG data show oscillatory behavior in the large rainfall regime (greater than 500 mm), the frequency of oscillation, once again, being determined by the ambient wetness (rainfall, and humidity). Data recorded over three pilot projects spanning three measures of rainfall and humidity bear testimony to the universality of this statistical argument. © 2013 Chattopadhyay and Bandyopadhyay

Age and sex-associated variation in the multi-site microbiome of an entire social group of free-ranging rhesus macaques

Background: An individual’s microbiome changes over the course of its lifetime, especially during infancy, and again in old age. Confounding factors such as diet and healthcare make it difficult to disentangle the interactions between age, health, and microbial changes in humans. Animal models present an excellent opportunity to study age- and sex-linked variation in the microbiome, but captivity is known to influence animal microbial abundance and composition, while studies of free-ranging animals are typically limited to studies of the fecal microbiome using samples collected non-invasively. Here, we analyze a large dataset of oral, rectal, and genital swabs collected from 105 free-ranging rhesus macaques (Macaca mulatta, aged 1 month-26 years), comprising one entire social group, from the island of Cayo Santiago, Puerto Rico. We sequenced 16S V4 rRNA amplicons for all samples. Results: Infant gut microbial communities had significantly higher relative abundances of Bifidobacterium and Bacteroides and lower abundances of Ruminococcus, Fibrobacter, and Treponema compared to older age groups, consistent with a diet high in milk rather than solid foods. The genital microbiome varied widely between males and females in beta-diversity, taxonomic composition, and predicted functional profiles. Interestingly, only penile, but not vaginal, microbiomes exhibited distinct age-related changes in microbial beta-diversity, taxonomic composition, and predicted functions. Oral microbiome composition was associated with age, and was most distinctive between infants and other age classes. Conclusions: Across all three body regions, with notable exceptions in the penile microbiome, while infants were distinctly different from other age groups, microbiomes of adults were relatively invariant, even in advanced age. While vaginal microbiomes were exceptionally stable, penile microbiomes were quite variable, especially at the onset of reproductive age. Relative invariance among adults, including elderly individuals, is contrary to findings in humans and mice. We discuss potential explanations for this observation, including that age-related microbiome variation seen in humans may be related to changes in diet and lifestyle. 4_dARqKdohA9mAZyu7q9YNVideo abstrac

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation