Explore the vast range of titles available.

First year is a delicate time for students. Many have little idea what to expect of university, and their sense of identity as tertiary students is fragile. A diagnostic assessment early in first semester may reassure students that they have chosen the right path. However, some academics, particularly in engineering, argue that this early assessment should be very demanding - so tough, in fact, that some students fail - in order to alert students to the hard work required to pass the course. This study uses a mixed methods design (weekly surveys and in-depth interviews) to explore the effects of a purposefully tough early assessment on first year engineering students at an Australian university. We find that, across the cohort, the high failure rate was not associated with a significant slump or spike in motivation. Although some students were initially dismayed by their results, most went on to address their study with resilience, and appreciated the \"kick up the bum\", as they described it.

HIV/AIDS is a leading cause of disease burden in sub-Saharan Africa. Existing evidence has demonstrated that there is substantial local variation in the prevalence of HIV; however, subnational variation has not been investigated at a high spatial resolution across the continent. Here we explore within-country variation at a 5 × 5-km resolution in sub-Saharan Africa by estimating the prevalence of HIV among adults (aged 15–49 years) and the corresponding number of people living with HIV from 2000 to 2017. Our analysis reveals substantial within-country variation in the prevalence of HIV throughout sub-Saharan Africa and local differences in both the direction and rate of change in HIV prevalence between 2000 and 2017, highlighting the degree to which important local differences are masked when examining trends at the country level. These fine-scale estimates of HIV prevalence across space and time provide an important tool for precisely targeting the interventions that are necessary to bringing HIV infections under control in sub-Saharan Africa. Fine-scale estimates of the prevalence of HIV in adults across sub-Saharan Africa reveal substantial within-country variation and local differences in both the direction and rate of change in the prevalence of HIV between 2000 and 2017.

Background HIV remains the largest cause of disease burden among men and women of reproductive age in sub-Saharan Africa. Voluntary medical male circumcision (VMMC) reduces the risk of female-to-male transmission of HIV by 50–60%. The World Health Organization (WHO) and Joint United Nations Programme on HIV/AIDS (UNAIDS) identified 14 priority countries for VMMC campaigns and set a coverage goal of 80% for men ages 15–49. From 2008 to 2017, over 18 million VMMCs were reported in priority countries. Nonetheless, relatively little is known about local variation in male circumcision (MC) prevalence. Methods We analyzed geo-located MC prevalence data from 109 household surveys using a Bayesian geostatistical modeling framework to estimate adult MC prevalence and the number of circumcised and uncircumcised men aged 15–49 in 38 countries in sub-Saharan Africa at a 5 × 5-km resolution and among first administrative level (typically provinces or states) and second administrative level (typically districts or counties) units. Results We found striking within-country and between-country variation in MC prevalence; most (12 of 14) priority countries had more than a twofold difference between their first administrative level units with the highest and lowest estimated prevalence in 2017. Although estimated national MC prevalence increased in all priority countries with the onset of VMMC campaigns, seven priority countries contained both subnational areas where estimated MC prevalence increased and areas where estimated MC prevalence decreased after the initiation of VMMC campaigns. In 2017, only three priority countries (Ethiopia, Kenya, and Tanzania) were likely to have reached the MC coverage target of 80% at the national level, and no priority country was likely to have reached this goal in all subnational areas. Conclusions Despite MC prevalence increases in all priority countries since the onset of VMMC campaigns in 2008, MC prevalence remains below the 80% coverage target in most subnational areas and is highly variable. These mapped results provide an actionable tool for understanding local needs and informing VMMC interventions for maximum impact in the continued effort towards ending the HIV epidemic in sub-Saharan Africa.

Laboratory learning plays a distinctive role in science education. This study focuses on the laboratory report writing of students to investigate to what extent laboratory experience mimics the process of 'doing science'. A quantitative analysis was performed to identify the different Moves in students' report introductions according to the Swales' (2004) CARS model which is a tool used to analyse research articles. This model is well suited to analysing student writing since they also follow the IMRD structure when writing laboratory reports. The results revealed that students generally use Moves 1 (topic generalization with increasing specificity) and 3 (presenting the present work) but Move 2 (establishing the niche) is absent in physics and biology laboratory reports and physics project reports. Move 2 is central to doing science. In contrast to the laboratory and project reports, Move 2 was present in science research placement project reports. This paper suggests that it is better, where possible, to incorporate this aspect of doing science into laboratory programs since it gives novices a better understanding of genuine research processes. This study also highlights the importance of interaction between discipline specific academics and academic language units to give students a consistent message. [Author abstract]

First year is a delicate time for students. Many have little idea what to expect of university, and their sense of identity as tertiary students is fragile. A diagnostic assessment early in first semester may reassure students that they have chosen the right path. However, some academics, particularly in engineering, argue that this early assessment should be very demanding - so tough, in fact, that some students fail - in order to alert students to the hard work required to pass the course. This study uses a mixed methods design (weekly surveys and in-depth interviews) to explore the effects of a purposefully tough early assessment on first year engineering students at an Australian university. We find that, across the cohort, the high failure rate was not associated with a significant slump or spike in motivation. Although some students were initially dismayed by their results, most went on to address their study with resilience, and appreciated the \"kick up the bum\", as they described it.

Animal studies show aging varies between individuals as well as between organs within an individual 1 – 4 , but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20–50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer’s disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. 5 ), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects. Blood plasma protein data was combined with machine learning models for a simple method to determine differences in organ-specific aging; the study provides a basis for the prediction of diseases and aging effects using plasma proteomics.

Diabetic kidney disease (DKD) is the leading cause of end stage kidney failure worldwide, of which cellular insulin resistance is a major driver. Here, we study key human kidney cell types implicated in DKD (podocytes, glomerular endothelial, mesangial and proximal tubular cells) in insulin sensitive and resistant conditions, and perform simultaneous transcriptomics and proteomics for integrated analysis. Our data is further compared with bulk- and single-cell transcriptomic kidney biopsy data from early- and advanced-stage DKD patient cohorts. We identify several consistent changes (individual genes, proteins, and molecular pathways) occurring across all insulin-resistant kidney cell types, together with cell-line-specific changes occurring in response to insulin resistance, which are replicated in DKD biopsies. This study provides a rich data resource to direct future studies in elucidating underlying kidney signalling pathways and potential therapeutic targets in DKD. Diabetic kidney disease is the leading cause of kidney failure in the world and cellular insulin resistance is an important driver of this disease. Here, Lay et al identify multiple insulin-resistance driven “common” and “cell-specific” kidney cell pathways and molecules that may be good therapeutic and biomarker targets.

Induced pluripotent stem cells (iPSC) are an attractive progenitor source for the generation of in vitro blood products. However, before iPSC-derived erythroid cells can be considered for therapeutic use their similarity to adult erythroid cells must be confirmed. We have analysed the proteome of erythroid cells differentiated from the iPSC fibroblast derived line (C19) and showed they express hallmark RBC proteins, including all those of the ankyrin and 4.1R complex. We next compared the proteome of erythroid cells differentiated from three iPSC lines (C19, OCE1, OPM2) with that of adult and cord blood progenitors. Of the 1989 proteins quantified <3% differed in level by 2-fold or more between the different iPSC-derived erythroid cells. When compared to adult cells, 11% of proteins differed in level by 2-fold or more, falling to 1.9% if a 5-fold threshold was imposed to accommodate slight inter-cell line erythropoietic developmental variation. Notably, the level of >30 hallmark erythroid proteins was consistent between the iPSC lines and adult cells. In addition, a sub-population (10-15%) of iPSC erythroid cells in each of the iPSC lines completed enucleation. Aberrant expression of some cytoskeleton proteins may contribute to the failure of the majority of the cells to enucleate since we detected some alterations in cytoskeletal protein abundance. In conclusion, the proteome of erythroid cells differentiated from iPSC lines is very similar to that of normal adult erythroid cells, but further work to improve the induction of erythroid cells in existing iPSC lines or to generate novel erythroid cell lines is required before iPSC-derived red cells can be considered suitable for transfusion therapy.

Non-homologous chromosomal contacts (NHCCs) between different chromosomes participate considerably in gene and genome regulation. Due to analytical challenges, NHCCs are currently considered as singular, stochastic events, and their extent and fundamental principles across cell types remain controversial. We develop a supervised and unsupervised learning algorithm, termed Signature , to call NHCCs in Hi-C datasets to advance our understanding of genome topology. Signature reveals 40,282 NHCCs and their properties across 62 Hi-C datasets of 53 diploid human cell types. Genomic regions of NHCCs are gene-dense, highly expressed, and harbor genes for cell-specific and sex-specific functions. Extensive inter- telomeric and inter- centromeric clustering occurs across cell types [Rabl’s configuration] and 61 NHCCs are consistently found at the nuclear speckles. These constitutive ‘anchor loci’ facilitate an axis of genome activity whilst cell-type-specific NHCCs act in discrete hubs. Our results suggest that non-random chromosome positioning is supported by constitutive NHCCs that shape genome topology along an off-centered spatial gradient of genome activity. The authors develop a supervised and unsupervised learning algorithm Signature. Machine learning and network model analysis of Hi-C datasets across 62 2n genomes suggest that inter-chromosomal contacts demarcate genome topology along a spatial gradient of genome activity.