Perspectives of nonmajor undergraduate students on the impact of group discussions in learning physiology

A 3-year study (2017-2019) was conducted to obtain the views of nonmajor undergraduate students about discussions in learning physiology. The teaching methods used were lecture only (lecture), group discussion alone (discussion), and a combination of lecture and discussion (lecture + discussion). Students were assigned homework in a textbook, and they did not have access to textbook/notes during discussions. Under these conditions, 58% of students indicated that they learned best with lecture + discussion strategy, compared with 49% for lecture and 18% for discussion approaches. Remarkably, 61% of students said the discussion did not enhance learning; by comparison, 35% and 14% had the same views about lecture and lecture + discussion, respectively. Furthermore, if given the opportunity to choose a teaching/learning environment, 66% of students would select lecture + discussion, 33% would pick lecture, and only 6% would choose discussion setting. As many as 77% of students would reject the discussion setting if given the choice. The opinions of students were similar irrespective of their expected grades (whether A, B, or C); however, greater proportions of B or C students disliked discussion than A students. Thus, whereas 63% of A students disliked discussion, 81% of B students and 83% of C students disliked it. Also, 64% of students indicated that they would have been poorly prepared for classes without assigned homework. Essential outcomes of this study include undergraduates viewed the lecture + discussion setting as a supportive/desirable environment for learning physiology, and they consistently rated the lecture method higher than the discussion-only approach. Students did not relish learning physiology in a discussion-only setting. These findings may help in establishing teaching/learning environments from the student's perspective.NEW & NOTEWORTHY This article reports perspectives of nonmajor undergraduates about group discussions in learning physiology. Three teaching methods were used: traditional lecture alone (lecture), discussion alone (discussion), and combined lecture and discussion (lecture + discussion). Students rated lecture + discussion setting as the most conducive for learning. The rank order of student preference for learning environment was, first, lecture + discussion; second, lecture; and third, discussion. These opinions were similar irrespective of expected grades in the course. Enjoyment of the teaching/learning process and environment is important to students.

Connection between two historical tuberculosis outbreak sites in Japan, Honshu, by a new ancestral Mycobacterium tuberculosis L2 sublineage

By gathering 680 publicly available Sequence Read Archives from isolates of Mycobacterium tuberculosis complex (MTBC) including 190 belonging to the lineage 2 Beijing , and using an in-house bioinformatical pipeline, the TB-Annotator , that analyses more than 50 000 characters, we describe herein a new L2 sublineage from 20 isolates found in the Tochigi province, (Japan), that we designate as asia ancestral 5 (AAnc5). These isolates harbour a number of specific criteria (42 SNPs) and their intra-cluster pairwise distance suggests historical and not epidemiological transmission. These isolates harbour a mutation in rpoC , and do not fulfil, any of the modern Beijing lineage criteria, nor any of the other ancestral Beijing lineages described so far. Asia ancestral 5 isolates do not possess mutT2 58 and ogt 12 characteristics of modern Beijing , but possess ancestral Beijing SNPs characteristics. By looking into the literature, we found a reference isolate ID381, described in Kobe and Osaka belonging to the ‘G3’ group, sharing 36 out of the 42 specific SNPs found in AAnc5. We also assessed the intermediate position of the asia ancestral 4 (AAnc4) sublineage recently described in Thailand and propose an improved classification of the L2 that now includes AAnc4 and AAnc5. By increasing the recruitment into TB-Annotator to around 3000 genomes (including 642 belonging to L2), we confirmed our results and discovered additional historical ancestral L2 branches that remain to be investigated in more detail. We also present, in addition, some anthropological and historical data from Chinese and Japan history of tuberculosis, as well as from Korea, that could support our results on L2 evolution. This study shows that the reconstruction of the early history of tuberculosis in Asia is likely to reveal complex patterns since its emergence.

COVID-19 detection and disease progression visualization: Deep learning on chest X-rays for classification and coarse localization

Chest X-rays are playing an important role in the testing and diagnosis of COVID-19 disease in the recent pandemic. However, due to the limited amount of labelled medical images, automated classification of these images for positive and negative cases remains the biggest challenge in their reliable use in diagnosis and disease progression. We implemented a transfer learning pipeline for classifying COVID-19 chest X-ray images from two publicly available chest X-ray datasets1,2. The classifier effectively distinguishes inflammation in lungs due to COVID-19 and Pneumonia from the ones with no infection (normal). We have used multiple pre-trained convolutional backbones as the feature extractor and achieved an overall detection accuracy of 90%, 94.3%, and 96.8% for the VGG16, ResNet50, and EfficientNetB0 backbones respectively. Additionally, we trained a generative adversarial framework (a CycleGAN) to generate and augment the minority COVID-19 class in our approach. For visual explanations and interpretation purposes, we implemented a gradient class activation mapping technique to highlight the regions of the input image that are important for predictions. Additionally, these visualizations can be used to monitor the affected lung regions during disease progression and severity stages.

Maternal and infant predictors of infant mortality in California, 2007-2015

Objective

To identify current maternal and infant predictors of infant mortality, including maternal sociodemographic and economic status, maternal perinatal smoking and obesity, mode of delivery, and infant birthweight and gestational age.

Methods

This retrospective study analyzed data from the linked birth and infant death files (birth cohort) and live births from the Birth Statistical Master files (BSMF) in California compiled by the California Department of Public Health for 2007–2015. The birth cohort study comprised 4,503,197 singleton births including 19,301 infant deaths during the nine-year study period. A subpopulation to study fetal growth consisted of 4,448,300 birth cohort records including 13,891 infant deaths.

Results

The infant mortality rate (IMR) for singleton births decreased linearly (p <0.001) from 4.68 in 2007 to 3.90 (per 1,000 live births) in 2015. However, significant disparities in IMR were uncovered in different population groups depending upon maternal sociodemographic and economic characteristics and maternal characteristics during pregnancy. Children of African American women had almost twice the risk of infant mortality when compared with children of White women (AOR 2.12; 95% CI, 1.98–2.27; p<0.001). Infants of women with Bachelor’s degrees or higher were 89% less likely to die (AOR 1.89; 95% CI, 1.76–2.04; p<0.001) when compared to infants of women with education less than high school. Infants of maternal smokers were 75% more likely to die (AOR 1.75; 95% CI, 1.58–1.93; p<0.001) than infants of nonsmokers. Infants of women who were overweight and obese during pregnancy accounted for 55% of IMR over all women in the study. More than half of the infant deaths were to children of women with lower socioeconomic status; infants of WIC participants were 59% more likely to die (AOR 1.59; 95% CI, 1.52–1.67; p<0.001) than infants of non-WIC participants. With respect to infant predictors, infants born with LBW or PTB were more than six times (AOR 6.29; 95% CI, 5.90–6.70; p<0.001) and almost four times (AOR 3.95; 95% CI, 3.73–4.19; p<0.001) more likely to die than infants who had normal births, respectively. SGA and LGA infants were more than two times (AOR 2.03; 95% CI, 1.92–2.15; p<0.001) and 41% (AOR 1.41; 95% CI, 1.32–1.52; p<0.001) more likely to die than AGA infants, respectively.

Conclusions

While the overall IMR in California is declining, wide disparities in death rates persist in different groups, and these disparities are increasing. Our data indicate that maternal sociodemographic and economic factors, as well as maternal prepregnancy obesity and smoking during pregnancy, have a prominent effect on IMR though no causality can be inferred with the current data. These predictors are not typically addressed by direct medical care. Infant factors with a major effect on IMR are birthweight and gestational age—predictors that are addressed by active medical services. The highest value interventions to reduce IMR may be social and public health initiatives that mitigate disparities in sociodemographic, economic and behavioral risks for mothers.

Harmonizing technological advances in phenomics and genomics for enhanced salt tolerance in rice from a practical perspective

Half of the global human population is dependent on rice as a staple food crop and more than 25% increase in rice productivity is required to feed the global population by 2030. With increase in irrigation, global warming and rising sea level, rising salinity has become one of the major challenges to enhance the rice productivity. Since the loss on this account is to the tune of US$12 billion per annum, it necessitates the global attention. In the era of technological advancement, substantial progress has been made on phenomics and genomics data generation but reaping benefit of this in rice salinity variety development in terms of cost, time and precision requires their harmonization. There is hardly any comprehensive holistic review for such combined approach. Present review describes classical salinity phenotyping approaches having morphological, physiological and biochemical components. It also gives a detailed account of invasive and non-invasive approaches of phenomic data generation and utilization. Classical work of rice salinity QLTs mapping in the form of chromosomal atlas has been updated. This review describes how QTLs can be further dissected into QTN by GWAS and transcriptomic approaches. Opportunities and progress made by transgenic, genome editing, metagenomics approaches in combating rice salinity problems are discussed. Major aim of this review is to provide a comprehensive over-view of hitherto progress made in rice salinity tolerance research which is required to understand bridging of phenotype based breeding with molecular breeding. This review is expected to assist rice breeders in their endeavours by fetching greater harmonization of technological advances in phenomics and genomics for better pragmatic approach having practical perspective.

An MTF1 binding site disrupted by a homozygous variant in the promoter of ATP7B likely causes Wilson Disease

Approximately 2% of the human genome accounts for protein-coding genes, yet most known Mendelian disease-causing variants lie in exons or splice sites. Individuals who symptomatically present with monogenic disorders but do not possess function-altering variants in the protein-coding regions of causative genes may harbor variants in the surrounding gene regulatory domains. We present such a case: a male of Afghani descent was clinically diagnosed with Wilson Disease-a disorder of systemic copper buildup-but was found to have no function-altering coding variants in ATP7B (ENST00000242839.4), the typically causative gene. Our analysis revealed the homozygous variant chr13:g.52,586,149T>C (NC_000013.10, hg19) 676 bp into the ATP7B promoter, which disrupts a metal regulatory transcription factor 1 (MTF1) binding site and diminishes expression of ATP7B in response to copper intake, likely resulting in Wilson Disease. Our approach to identify the causative variant can be generalized to systematically discover function-altering non-coding variants underlying disease and motivates evaluation of gene regulatory variants.

Hunger influenced life expectancy in war-torn Sub-Saharan African countries

BACKGROUND

Malnutrition is a global public health problem especially in developing countries experiencing war/conflicts. War might be one of the socio-political factors influencing malnutrition in Sub-Saharan African (SSA) countries. This study aims at determining the influence of war on corruption, population (POP), number of population malnourished (NPU), food security and life expectancy (LE) in war-torn SSA countries (WTSSA) by comparing their malnutrition indicators.

METHODS

Fourteen countries in WTSSA were stratified into zones according to war incidences. Countries' secondary data on population (POP), NPU, Food Security Index (FSI), corruption perceptions index (CPI), Global Hunger Index (GHI) and LE were obtained from global published data. T test, multivariate and Pearson correlation analyses were performed to determine the relationship between CPI, POP, GHI, FSI, NPU, male LE (MLE) and female LE (FLE) in WTSSA at p < .05. Data were presented in tables, means, standard deviation and percentages.

RESULTS

Mean NPU, CPI, GHI, POP, FSI, MLE and FLE in WTSSA were 5.0 million, 28.3%, 18.2%, 33.8 million, 30.8%, 54.7 years and 57.1 years, respectively. GHI significantly influenced LE in both male and female POP in WTSSA. NPU, CPI, FSI, GHI and FLE were not significantly different according to zones except in MLE.

CONCLUSIONS

Malnutrition indicators were similarly affected in WTSSA. Hunger influenced life expectancy. Policies promoting good governance, equity, peaceful co-existence, respect for human right and adequate food supply will aid malnutrition eradication and prevent war occurrences in Sub-Saharan African countries.