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In settings with high tuberculosis (TB) endemicity, distinct genotypes of the Mycobacterium tuberculosis complex (MTBC) often differ in prevalence. However, the factors leading to these differences remain poorly understood. Here we studied the MTBC population in Dar es Salaam, Tanzania over a six-year period, using 1,082 unique patient-derived MTBC whole-genome sequences (WGS) and associated clinical data. We show that the TB epidemic in Dar es Salaam is dominated by multiple MTBC genotypes introduced to Tanzania from different parts of the world during the last 300 years. The most common MTBC genotypes deriving from these introductions exhibited differences in transmission rates and in the duration of the infectious period, but little differences in overall fitness, as measured by the effective reproductive number. Moreover, measures of disease severity and bacterial load indicated no differences in virulence between these genotypes during active TB. Instead, the combination of an early introduction and a high transmission rate accounted for the high prevalence of L3.1.1, the most dominant MTBC genotype in this setting. Yet, a longer co-existence with the host population did not always result in a higher transmission rate, suggesting that distinct life-history traits have evolved in the different MTBC genotypes. Taken together, our results point to bacterial factors as important determinants of the TB epidemic in Dar es Salaam.

Physics teachers need diagnostic competence to effectively identify students' misconceptions, but studies have yet to sufficiently investigate how this competence can be advanced through various instructional strategies. In this study, we compared a problem-solving strategy against an example-based strategy in advancing diagnostic competence in science teacher education. For both instructional strategies, we used tasks from Diagnoser.com and controlled for preservice teachers' prior diagnostic knowledge. A total of 81 preservice teachers teaching physics took part in the controlled field experiment. A between-subjects experimental design was used to assess preservice teachers' diagnostic competence. We used a standardized test to measure their diagnostic competence before and after the intervention. To measure diagnostic competence, we focused on conceptual diagnostic knowledge and knowledge about strategic routines (procedural knowledge). The results showed that the problem-solving strategy enhanced preservice teachers' conceptual diagnostic knowledge significantly more than the example-based strategy did, t(77) = 2.96, p = 0.011, d = 0.812. We also found that problem-solving was better than example-based learning in enhancing diagnostic competence in the form of conceptual knowledge in comparison with a control group, t(77) = 4.97, p < 0.001, d = 1.382. We conclude that, even though both instructional strategies can be used to advance preservice teachers' diagnostic competence with respect to knowledge about concepts, problem-solving is better for enhancing diagnostic competence in identifying students' misconceptions than example-based learning is. It is possible that a problem-solving instructional strategy has a stronger positive effect on the acquisition of knowledge about concepts than on knowledge about procedures because this strategy provides scaffolding during the learning process.

Thin silicon oxide films deposited on a polypropylene substrate by plasma-enhanced chemical vapor deposition were investigated using atomic force microscopy-based infrared (AFM-IR) nanospectroscopy in contact and surface-sensitive mode. The focus of this work is the comparison of the different measurement methods (i.e., contact mode and surface-sensitive mode) with respect to the chemical surface sensitivity. The use of the surface-sensitive mode in AFM-IR shows an enormous improvement for the analysis of thin films on the IR-active substrate. As a result, in this mode, the signal of the substrate material could be significantly reduced. Even layers that are so thin that they could hardly be measured in the contact mode can be analyzed with the surface-sensitive mode.

Abstract Since the ingestion of both natural and anthropogenic microfibers produces a deleterious effect on aquatic organisms, it is crucial to explore the emission of these pollutants by WWTPs into the receiving water bodies, such as rivers. Cellulose- and petroleum-based microfibers, as well as microplastic particles, were collected from the effluent of a municipal WWTP operating with activated sludge technology in Budapest, Hungary. During two sampling campaigns organized in February and April of 2023 on different working days and at different times of the day, 123–145 L of effluent was sieved and filtered. The organic matter was removed by hydrogen-peroxide treatment. All fibers and particles larger than 10 µm were counted, and using a fluorescence microscope, the fibers were geometrically characterized in terms of length and diameter. Each fiber was individually identified by transflection-FT-IR method. The fiber concentration varied in the range of 1.88–2.84 and 4.25–6.79 items/L during the 7th and the 16th week of 2023, respectively. In February and April, the proportion of microfibers in the solid particles was 78.3 and 94.7%, respectively. In the effluent the cellulose-based microfibers were dominant (53–91%), while among the petroleum-based microfibers, polyester occurred most often. The median length of cellulose-based fibers was considerably higher in April than in February (650 vs. 1250 µm), and simultaneously the median diameter also increased from 21 to 29 µm. This behaviour was also seen, albeit to a lesser extent, in connection to microfibers derived from petroleum. The treated wastewater’s daily microfiber transport to the Danube River varied between 0.44 − 0.69 and 0.94–1.53 billion in February and April 2023, respectively.

Abstract Wastewater surveillance for SARS-CoV-2 provides early warnings of emerging variants of concerns and can be used to screen for novel cryptic linked-read mutations, which are co-occurring single nucleotide mutations that are rare, or entirely missing, in existing SARS-CoV-2 databases. While previous approaches have focused on specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and investigating their potential origin. We present Crykey, a tool for rapidly identifying rare linked-read mutations across the genome of SARS-CoV-2. We evaluated the utility of Crykey on over 3,000 wastewater and over 22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations in wastewater that represent potential circulating cryptic lineages, serving as a new computational tool for wastewater surveillance of SARS-CoV-2.

Abstract Background Adolescents and young adults in residential care and correctional institutions face various challenges, leading to negative life outcomes. Implementation barriers within these institutions, such as limited financial and spatial resources, pose significant hurdles to providing necessary support. Web-based approaches address these challenges by offering cost-effective, accessible solutions. This study aims to assess the efficacy of a newly developed web-based version of the existing evidence-based START NOW skills training in fostering emotion regulation and resilience among institutionalized adolescents and young adults. We present the study protocol (Version 5, August 2023) of the trial titled “Implementation of an e-version of the skills training START NOW for promoting emotion regulation and resilience in residential youth care and correctional institutions”. Methods The study is a monocentric, prospective, confirmatory randomized controlled trial with 150 institutionalized adolescents and young adults with a need to improve resilience (predefined cut-offs). Participating institutions will be randomized to one of three conditions: (i) 9-week web-based group training guided by a facilitator, (ii) 9-week web-based self-help training, (iii) and treatment as usual. The primary endpoint is the change in psychological flexibility, assessed by the Avoidance and Fusion Questionnaire for Youth score, from baseline to follow-up 12 weeks post skills training. Secondary objectives encompass assessing pre-post changes in psychological flexibility and other psychological health-related outcome measures in participating adolescents, young adults, and caretakers from baseline, to post training, and to 12- and 24-week follow-ups. Discussion This study evaluates the efficacy of START NOW as web-based training for institutionalized adolescents and young adults, providing valuable insights into web-based interventions and aiming to optimize support levels. Trial registration {2a and 2b} ClinicalTrials.gov NCT05313581. Registered on 6 April 2022.

Abstract Background Monitoring of infectious diseases on swine farms requires a high diagnostic sensitivity and specificity of the test system. Moreover, particularly in cases of swine influenza A virus (swIAV) it is desirable to include characterization of the virus as precisely as possible. This is indispensable for strategies concerning prophylaxis of swIAV and furthermore, to meet the requirements of a purposeful monitoring of newly emerging swIAV strains in terms of vaccine design and public health. Within the present cross-sectional study, we compared the diagnostic value of group samples (wipes of surfaces with direct contact to mouth/nose, dust wipes, udder skin wipes, oral fluids) to individual samples (nasal swabs, tracheobronchial swabs) for both swIAV identification and characterization. Sampling included different stages of pig production on 25 sow farms with attached nursery considered as enzootically infected with swIAV. Firstly, samples were analyzed for IAV genome and subsequently samples with Ct-values

Abstract Consumption-based carbon assessments are essential for evaluating climate change responsibility. However, the results vary greatly depending on the boundary chosen, making them hard to understand for non-expert readers and hindering their uptake by policy makers. Sankey diagrams are a type of flow diagram where the thickness of a flow is proportional to its value. They allow to shed light on the various ways to calculate carbon footprints and on the implications of choosing one method over another. Although several multi-regional input-output databases allow for the calculation of footprints, none of them has been systematically represented as Sankey diagrams. To fill this gap, we build an open access web application to represent carbon footprints for 49 world regions between 1995 and 2019 based on EXIOBASE 3 data. We include production-based, consumption-based and consumption-based with capital endogenized accounts. We then provide examples of the insights gained with such diagrams.

Abstract According to the World Health Organization, Chagas disease (CD) is the most prevalent poverty-promoting neglected tropical disease. Alarmingly, climate change is accelerating the geographical spreading of CD causative parasite, Trypanosoma cruzi, which additionally increases infection rates. Still, CD treatment remains challenging due to a lack of safe and efficient drugs. In this work, we analyze the viability of T. cruzi Akt-like kinase (TcAkt) as drug target against CD including primary structural and functional information about a parasitic Akt protein. Nuclear Magnetic Resonance derived information in combination with Molecular Dynamics simulations offer detailed insights into structural properties of the pleckstrin homology (PH) domain of TcAkt and its binding to phosphatidylinositol phosphate ligands (PIP). Experimental data combined with Alpha Fold proposes a model for the mechanism of action of TcAkt involving a PIP-induced disruption of the intramolecular interface between the kinase and the PH domain resulting in an open conformation enabling TcAkt kinase activity. Further docking experiments reveal that TcAkt is recognized by human inhibitors PIT-1 and capivasertib, and TcAkt inhibition by UBMC-4 and UBMC-6 is achieved via binding to TcAkt kinase domain. Our in-depth structural analysis of TcAkt reveals potential sites for drug development against CD, located at activity essential regions.

Abstract Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

Abstract Background Nail involvement is frequent in patients with psoriasis (Pso) and psoriatic arthritis (PsA) and there is a relationship between nail involvement and inflammation of the enthesis. The main objective of the present study is to describe the ultrasound findings and clinical characteristics of nails from patients with psoriasis and psoriatic arthritis with and without nail dystrophy. Methods A cross-sectional study including consecutive patients with PsO and PsA was carried out. The study patients were divided into 4 groups, totaling 120 participants. Group 1: patients with psoriasis vulgaris and clinically normal nails; Group 2: patients with psoriasis vulgaris and onychodystrophy; Group 3: patients with psoriatic arthritis and clinically normal nails; Group 4: patients with psoriatic arthritis and onychodystrophy; All patients were submitted to dermatological and rheumatological clinical analysis. Ultrasound examinations was performed by a single examiner, blinded to all clinical data, with ultrasound high resolution, in B-mode or gray-scale (GS), Power Doppler (PD) and Spectral Doppler. Results A significant difference was found between the groups regarding the variable Psoriasis Area and Severity Index (PASI) (p = 0.008) and body surface area (BSA) (p = 0.005), with patients with psoriatic arthritis having lower PASI and BSA compared to patients with only cutaneous psoriasis. A positive relationship was found with the average ultrasound thickness of the nail bed and the Nail Psoriasis Severity Index (NAPSI) in correlation analysis (rho = 0.344). When we grouped patients with psoriasis and psoriatic arthritis, there was no significant difference between the cutaneous psoriasis groups and the psoriatic arthritis groups in terms of nail plate GS (p = 0.442), nail bed PD (p = 0.124). Conclusion Greater nail bed thickness indicates early psoriatic nail disease, as confirmed in our study correlating NAPSI with nail bed thickness. Ultrasonography is a low-cost exam, promising in the evaluation, showing that the ultrasound grayscale is consistent with those who have dystrophic nails, but it can’t distinguish psoriasis from psoriatic arthritis, even in those with nail dystrophy.

Abstract Objectives The objective of this data note is to provide a reliable, comprehensive dataset focusing on work-related injuries and fatalities, broken down by year, country, gender, and economic sector. We aim to fill a significant gap in sustainability models, specifically in metrics concerning occupational health. Although the data is compatible with any Multi-Regional Input–Output (MRIO) model, it is primarily designed for integration with the EXIOBASE model. The dataset seeks to broaden MRIO models’ capabilities in social impact assessments and national social footprint evaluations. Ultimately, this resource aims to offer a holistic tool for researchers and policymakers, enabling more thorough assessments of international trade flows, Global Value Chains (GVC), and national policies across both environmental and social dimensions. Data description Our dataset enriches the EXIOBASE model with updated fatality statistics from World Health Organization (WHO) and Eurostat databases, covering the years 2008 to 2019. It provides detailed data on work-related fatal injuries by country, gender, and economic sector. With its broad applicability, this dataset stands to influence research and policy across multiple disciplines. It offers valuable insights for studies on global social impacts, policy economics, and the real effects of global value chains, among other research areas.

Abstract Wastewater surveillance has proven a cost-effective key public health tool to understand a wide range of community health diseases and has been a strong source of information on community levels and spread for health departments throughout the SARS- CoV-2 pandemic. Studies spanning the globe demonstrate the strong association between virus levels observed in wastewater and quality clinical case information of the population served by the sewershed. Few of these studies incorporate the temporal dependence present in sampling over time, which can lead to estimation issues which in turn impact conclusions. We contribute to the literature for this important public health science by putting forward time series methods coupled with statistical process control that (1) capture the evolving trend of a disease in the population; (2) separate the uncertainty in the population disease trend from the uncertainty due to sampling and measurement; and (3) support comparison of sub-sewershed population disease dynamics with those of the population represented by the larger downstream treatment plant. Our statistical methods incorporate the fact that measurements are over time, ensuring correct statistical conclusions. We provide a retrospective example of how sub-sewersheds virus levels compare to the upstream wastewater treatment plant virus levels. An on-line algorithm supports real-time statistical assessment of deviations of virus level in a population represented by a sub-sewershed to the virus level in the corresponding larger downstream wastewater treatment plant. This information supports public health decisions by spotlighting segments of the population where outbreaks may be occurring.