Evaluation of the performance of lecturers in general surgery by 4th- and 6th-year MB ChB students at the University of Limpopo, Polokwane, South Africa

Background. Students’ evaluation of teaching performance is one of the important means of measuring the quality of higher education worldwide. Students are valuable contributors to improvement of the teaching performance of lecturers. For any academic institution, it is very important to receive feedback on teaching quality from students. Objectives. To determine lecturers’ performance as evaluated by undergraduate students in general surgery, with the aim of identifying the lecturers’ strengths and planning tactics for any necessary improvement measures. Methods. This study followed a descriptive research design to evaluate seven lecturers in general surgery by 4th- and 6th-year MB ChB students at the University of Limpopo, Polokwane, South Africa. Results. Seven lecturers were evaluated by the students. From the study results, there is strong evidence that the majority of the participants were satisfied with 5/7 lecturers’ interpersonal skills and communication and presentation style, including an overall rating (p<0.0001). Two lecturers were considered by the students to require some level of improvement in performance (p<0.0001). Conclusion. General surgery students expressed satisfaction with the teaching performance of most members of the academic staff. However, some lecturers need to improve with regard to audibility and preparation for slide presentations

Morphological, Biochemical and Genetic Variation of Rice (Oryza sativa L.) Genotypes to Vegetative Stage Salinity Stress

Salinity is one of the most serious issues in rice cultivation and production. Salt stress significantly reduced seedling growth performance of rice. This research was conducted to study the effects of vegetative stage salinity stress on morphological, biochemical, molecular and genetic variation of 12 rice genotypes as well as 2 check varieties, MR297 (susceptible) and Pokkali (tolerant). The experiment was arranged in a split-plot design with 3 replications. Normal freshwater at 0 dS m-1 (L1), saline water at 6 dS m-1 (L2) and saline water at 12 dS m-1 (L3) were the main plot and rice genotypes were the sub-plot. In general, morphological and biochemical traits of all genotypes showed an overall reduction of about 47.41% in L3 as compared to L1 except for the tolerant check, Pokkali. The genetics and correlation analysis indicated that plant height, leaf size and standard evaluation system (SES) score might be used as a selection criterion in developing salt tolerant rice. The multivariate analysis revealed that a Malaysian landraces, Jarom Mas was clustered together with Pokkali as tolerant genotype. Screening using tightly linked Simple Sequence Repeat (SSR) markers (RM1287, RM10748, RM493) of salinity tolerant QTL, Saltol indicated that this QTL was absence in Jarom Mas. This finding might indicate the presence of other QTL associated with salinity tolerance in Jarom Mas. Further study on identifying the speculated QTL may be conducted to confirm this postulation

COVID-19 fake news detection model on social media data using machine learning techniques

Social media sites like Instagram, Twitter, and Facebook have become indispensable parts of the daily routine. These social media sites are powerful instruments for spreading the news, photographs, and other sorts of information. However, since the emergence of the COVID-19 pandemic in December 2019, many articles and headlines concerning the COVID-19 epidemic have surfaced on social media. Social media is frequently used to disseminate fraudulent material or information. This disinformation may confuse consumers, perhaps causing worry. It is hard to counter the widespread dissemination of disinformation. As a result, it is critical to develop a model for recognizing fake news in the news stream. The dataset, which would be a synthesis of COVID-19-related news from numerous social media and news sources, is utilized for categorization in this work. Markers are retrieved from unstructured textual data gathered from a variety of sources. Then, to eliminate the computational burden of analyzing all of the features in the dataset, feature selection is done. Finally, to categorize the COVID -19 related dataset, multiple cutting-edge machine-learning algorithms were trained. Support Vector Machine (SVM), Naïve Bayes (NB), and Decision Tree (DT) are the machine learning models presented. Finally, numerous measures are used to evaluate these algorithms such as accuracy, precision, recall, and F1 score. The Decision Tress algorithm reported the highest accuracy of 100% compared to the Support Vector Machine 98.7% and Naïve Bayes 96.3%

Morpho-Physiological Response of Rice (Oryza Sativa L.) Genotypes to Salinity Stress at Seedling Stage

Salinity stress would significantly reduce seedling growth performance of rice. In addition, salinity also affects physiological and metabolic process mainly the osmotic and ionic balance of the cells. Hence, the present study was conducted to evaluate morpho-physiological and biochemical response of selected rice genotypes to salinity stress at seedling stage. Twelve rice genotypes were used in the pot-trial experiment including two checks namely Pokkali (tolerant) and MR297 (susceptible). The experiment was conducted in a split plot design with three replications. Three salinity levels involved were L1 (normal fresh water), L2 (saline water at 12 dSm-1), and L3 (saline water at 24 dSm-1) as the main plot while rice genotypes as the sub-plot. Salinity stress was imposed for 14 days starting from 21 days after sowing. In overall, L3 salinity stress significantly reduced 47.41% of all seedling growth attributes for all genotypes except for Pokkali (V11) as compared to control condition. Meanwhile, Haiboq (V9) and Basmati 370 (V3) recorded significantly similar response as the MR297 (V10). The trend of chlorophyll content reduction could be seen in all genotypes under L2 and L3 salinity stress with average 77.72% reduced over control condition. In contrast, proline content was increased over 7 folds in all genotypes as level of salinity increases except for V11. Proline may function as a signal metabolites thus higher proline content indicates that the plant is under stress. In conclusion, chlorophyll and proline content may be used as indicators of sensitivity to salinity stress in rice cultivars along with the morphological growth responses

The FUN30 Chromatin Remodeler, Fft3, Protects Centromeric and Subtelomeric Domains from Euchromatin Formation

The chromosomes of eukaryotes are organized into structurally and functionally discrete domains. This implies the presence of insulator elements that separate adjacent domains, allowing them to maintain different chromatin structures. We show that the Fun30 chromatin remodeler, Fft3, is essential for maintaining a proper chromatin structure at centromeres and subtelomeres. Fft3 is localized to insulator elements and inhibits euchromatin assembly in silent chromatin domains. In its absence, euchromatic histone modifications and histone variants invade centromeres and subtelomeres, causing a mis-regulation of gene expression and severe chromosome segregation defects. Our data strongly suggest that Fft3 controls the identity of chromatin domains by protecting these regions from euchromatin assembly

Endothelial Progenitor Cells (EPCs) as Gene Carrier System for Rat Model of Human Glioma

Due to their unique property to migrate to pathological lesions, stem cells are used as a delivery vehicle for therapeutic genes to tumors, especially for glioma. It is critically important to track the movement, localization, engraftment efficiency and functional capability or expression of transgenes of selected cell populations following transplantation. The purposes of this study were to investigate whether 1) intravenously administered, genetically transformed cord blood derived EPCs can carry human sodium iodide symporter (hNIS) to the sites of tumors in rat orthotopic model of human glioma and express transgene products, and 2) whether accumulation of these administered EPCs can be tracked by different in vivo imaging modalities.Collected EPCs were cultured and transduced to carry hNIS. Cellular viability, differential capacity and Tc-99m uptake were determined. Five to ten million EPCs were intravenously administered and Tc-99-SPECT images were acquired on day 8, to determine the accumulation of EPCs and expression of transgenes (increase activity of Tc-99m) in the tumors. Immunohistochemistry was performed to determine endothelial cell markers and hNIS positive cells in the tumors. Transduced EPCs were also magnetically labeled and accumulation of cells was confirmed by MRI and histochemistry. SPECT analysis showed increased activity of Tc-99m in the tumors that received transduced EPCs, indicative of the expression of transgene (hNIS). Activity of Tc-99m in the tumors was also dependent on the number of administered transduced EPCs. MRI showed the accumulation of magnetically labeled EPCs. Immunohistochemical analysis showed iron and hNIS positive and, human CD31 and vWF positive cells in the tumors.EPC was able to carry and express hNIS in glioma following IV administration. SPECT detected migration of EPCs and expression of the hNIS gene. EPCs can be used as gene carrier/delivery system for glioma therapy as well as imaging probes

Disrupted autophagy undermines skeletal muscle adaptation and integrity

This review assesses the importance of proteostasis in skeletal muscle maintenance with a specific emphasis on autophagy. Skeletal muscle appears to be particularly vulnerable to genetic defects in basal and induced autophagy, indicating that autophagy is co-substantial to skeletal muscle maintenance and adaptation. We discuss emerging evidence that tension-induced protein unfolding may act as a direct link between mechanical stress and autophagic pathways. Mechanistic links between protein damage, autophagy and muscle hypertrophy, which is also induced by mechanical stress, are still poorly understood. However, some mouse models of muscle disease show ameliorated symptoms upon effective targeting of basal autophagy. These findings highlight the importance of autophagy as therapeutic target and suggest that elucidating connections between protein unfolding and mTOR-dependent or mTOR-independent hypertrophic responses is likely to reveal specific therapeutic windows for the treatment of muscle wasting disorders

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions