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Background: There is variance in the incidence of lower extremity amputation across and within countries including within the UK. National data shows up to a fourfold variance in the amputation rate throughout the regions of England and differences in amputation incidence have been reported in Scotland and Ireland. Lower extremity amputation rate has yet to be documented within Wales. The aim of this cohort study was to examine trends in diabetes and non-diabetes related lower extremity amputation incidence within the Welsh population and to examine the influence of diabetes on the relative risk of amputation. Materials and Methods: All first-time amputations between 2008-2018 were extracted from SAIL, a repository of all routine medical data of residents of Wales. People with diabetes were identified using an algorithm utilising data from several clinical and non-clinical sources. Crude and direct age and sex adjusted incidences were estimated over time. Results: Over the period 3505 major amputations and 4335 minor amputations occurred. The diabetes population greater than 17 years of age increased by 29.4% from 143,595 in 2008 to 206,818 in 2018. There was a statistically significant rate reduction in major amputation in both populations. In the diabetes population the number of major amputations reduced from 6.9 [5.5–8.5]/10 000 person years (PY) in 2008 to 4.9 [5.4–6.2]/10 000 PY in 2018. However, for major amputation, the risk of incident amputation in people with diabetes was 7.3 fold higher [7.1–7.5] than those without diabetes. The relative risk of minor amputation for those with diabetes was higher at 11.9 [11.8 –1.01]. There was no reduction in this risk over the period. Conclusion: This study found that rates of major amputation decreased over the study period but the risk of amputation for persons with diabetes remained substantial. As the population with diabetes increases so do crude rates of amputation, providing a substantial financial and societal cost to the Welsh Population.

Abstract Tissue biofabrication mimicking organ-specific architecture and function requires physiologically-relevant cell densities. Bioprinting using spheroids can achieve this, but is limited due to the lack of practical, scalable techniques. This study presents HITS-Bio (High-throughput Integrated Tissue Fabrication System for Bioprinting), a multiarray bioprinting technique for rapidly positioning multiple spheroids simultaneously using a digitally-controlled nozzle array (DCNA). HITS-Bio achieves an unprecedented speed, ten times faster compared to existing techniques while maintaining high cell viability ( > 90%). The utility of HITS-Bio was exemplified in multiple applications, including intraoperative bioprinting with microRNA transfected human adipose-derived stem cell spheroids for calvarial bone regeneration ( ~ 30 mm3) in a rat model achieving a near-complete defect closure (bone coverage area of ~ 91% in 3 weeks and ~96% in 6 weeks). Additionally, the successful fabrication of scalable cartilage constructs (1 cm3) containing ~600 chondrogenic spheroids highlights its high-throughput efficiency (under 40 min per construct) and potential for repairing volumetric defects.

Abstract Background Genotype by environment interactions (GxE) affect a range of production traits in beef cattle. Quantifying the effect of GxE in commercial and multi-breed herds is challenging due to unknown genetic linkage between animals across environment levels. The primary aim of this study was to use multi-trait models to investigate GxE for three heifer fertility traits, corpus luteum (CL) presence, first pregnancy and second pregnancy, in a large tropical beef multibreed dataset (n = 21,037). Environmental levels were defined by two different descriptors, burden of heat load (temperature humidity index, THI) and nutritional availability (based on mean average daily gain for the herd, ADWG). To separate the effects of genetic linkage and real GxE across the environments, 1000 replicates of a simulated phenotype were generated by simulating QTL effects with no GxE onto real marker genotypes from the population, to determine the genetic correlations that could be expected across environments due to the existing genetic linkage only. Correlations from the real phenotypes were then compared to the empirical distribution under the null hypothesis from the simulated data. By adopting this approach, this study attempted to establish if low genetic correlations between environmental levels were due to GxE or insufficient genetic linkage between animals in each environmental level. Results The correlations (being less than

Gluconacetobacter diazotrophicus is a nitrogen fixing bacterium able to colonise a wide range of host plants and is marketed as a biofertiliser due to its ability to promote plant growth. This study aims to investigate how biological nitrogen fixation (BNF) competency affects the growth promotion of inoculated tomato plants and to describe the colonisation mechanism of this bacterium in dicot systems. A nitrogen fixation impaired mutant (Gd nifD-) was produced by disrupting the nifD gene, which encodes the nitrogenase Mo-Fe subunit, in order to assess its plant growth promotion (PGP) capability in comparison to G. diazotrophicus wild type strain (Gd WT). Furthermore, tagged strains were employed to monitor the colonisation process through qPCR analyses and fluorescence microscopy. Following a preliminary glass house trial, Gd WT or Gd nifD- were applied to hydroponically grown tomato plants under nitrogen-replete and nitrogen-limiting conditions. Bacteria reisolation data and plant growth parameters including height, fresh weight, and chlorophyll content were assessed 15 days post inoculation (dpi). Gd WT significantly enhanced plant height, fresh weight, and chlorophyll content in both nitrogen conditions, while Gd nifD- showed a reduced PGP effect, particularly in terms of chlorophyll content. Both strains colonised plants at similar levels, suggesting that the growth advantages were linked to BNF capacity rather than colonisation differences. These findings indicate that a functional nifD gene is a fundamental requirement for optimal plant growth promotion by G. diazotrophicus.

Abstract Background In the high disease burden and resource-constrained contexts of sub-Saharan Africa (SSA), health workers experience a range of psychosocial stressors that leave them vulnerable to developing burnout, which can reduce service quality and negatively impact their own health and wellbeing. As universal testing and treatment (UTT) for HIV scales up across SSA, we sought to understand the implications of this human resource-intensive approach to HIV prevention to inform decision-making about health workforce staffing and support needs. Methods Using the Maslach Burnout Inventory-Human Services Survey (MBI-HSS), we assessed the prevalence of three domains of burnout—emotional exhaustion, depersonalization, and personal accomplishment—among three cadres of health workers delivering health services in areas receiving a UTT intervention in Zambia and South Africa. These cadres included health facility workers (n = 478), community health workers (n = 159), and a study-specific cadre of community HIV care providers (n = 529). We used linear regression to assess risk factors associated with emotional exhaustion, the only domain with sufficient variation in our sample. Results The MBI-HSS was completed by 1499/2153 eligible participants (69.6% response rate). Less than 1% of health workers met Maslach’s definition for burnout. All groups of health workers reported lower levels of emotional exhaustion than found in previous studies of this type (mean score scores ranged from 10.7 to 15.4 out of 54 across health cadres). Higher emotional exhaustion was associated with higher educational attainment (βadj = 2.24, 95% CI 0.76 to 3.72), greater years providing HIV services (βadj = 0.20, 95% CI 0.03 to 0.36), and testing negative for HIV at last HIV test (βadj = − 3.88 − 95% CI 5.69 to − 2.07). Working as a CHW was significantly associated with lower emotional exhaustion (βadj = − 2.52, 95% CI − 4.69 to − 0.35). Among all health workers, irrespective of HIV status, witnessing stigmatizing behaviors towards people living with HIV among their co-workers was associated with significantly increased emotional exhaustion (βadj = 3.38, 95% CI 1.99 to 4.76). Conclusions The low level of burnout detected among health workers is reassuring. However, it remains important to assess how UTT may affect levels of emotional exhaustion among health workers over time, particularly in the context of emerging global pandemics, as burnout may impact the quality of HIV services they provide and their own mental health and wellbeing. Interventions to reduce HIV stigma in health facilities may protect against emotional exhaustion among health workers, as well as interventions to increase mindfulness and resilience among health workers at risk of burnout. Trial registration ClinicalTrials.gov number: NCT01900977.

Abstract Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we use genome-wide association summary statistics for Heifer puberty (pubertal or not at 600 days) from 27,707 Bos indicus, Bos taurus and crossbred cattle; multi-trait GWAS signals from 2119 indicine cattle for four fertility traits, including days to calving, age at first calving, pregnancy status, and foetus age in weeks (assessed by rectal palpation of the foetus); and expression quantitative trait locus for whole blood from 489 indicine cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis reveals a significant overlap between the set of cattle and previously reported human fertility-related genes, impling the existence of a shared pool of genes that regulate fertility in mammals. These findings are crucial for developing approaches to improve fertility in cattle and potentially other mammals.

Abstract The causes of temporal fluctuations in adult traits are poorly understood. Here, we investigate the genetic determinants of within-person trait variability of 8 repeatedly measured anthropometric traits in 50,117 individuals from the UK Biobank. We found that within-person (non-directional) variability had a SNP-based heritability of 2–5% for height, sitting height, body mass index (BMI) and weight (P $$\le$$ ≤ 2.4 × 10− 3). We also analysed longitudinal trait change and show a loss of both average height and weight beyond about 70 years of age. A variant tracking the Alzheimer’s risk APOE- $${{{{{\mathcal{E}}}}}}4$$ E 4 allele (rs429358) was significantly associated with weight loss ( $$\beta$$ β = −0.047 kg per yr, s.e. 0.007, P = 2.2 × 10−11), and using 2-sample Mendelian Randomisation we detected a relationship consistent with causality between decreased lumbar spine bone mineral density and height loss (b xy = 0.011, s.e. 0.003, P = 3.5 × 10−4). Finally, population-level variance quantitative trait loci (vQTL) were consistent with within-person variability for several traits, indicating an overlap between trait variability assessed at the population or individual level. Our findings help elucidate the genetic influence on trait-change within an individual and highlight disease risks associated with these changes.

BackgroundThe COVID-19 pandemic triggered policy changes in 2020 that allowed insurance companies to reimburse telehealth services, leading to increased telehealth use, especially in rural and underserved areas. However, with many emergency rules ending in 2022, patients and health care providers face potential challenges in accessing these services. ObjectiveThis study analyzed telehealth use across specialties in Arkansas before and after the pandemic (2017-2022) using data from electronic medical records from the University of Arkansas for Medical Sciences Medical Center. We explored trends in insurance coverage for telehealth visits and developed metrics to compare the performance of telehealth versus in-person visits across various specialties. The results inform insurance coverage decisions for telehealth services. MethodsWe used pre- and postpandemic data to determine the impacts of the COVID-19 pandemic and changes in reimbursement policies on telehealth visits. We proposed a framework to calculate 3 appointment metrics: indirect waiting time, direct waiting time, and appointment length. Statistical analysis tools were used to compare the performance of telehealth and in-person visits across the following specialties: obstetrics and gynecology, psychiatry, family medicine, gerontology, internal medicine, neurology, and neurosurgery. We used data from approximately 4 million in-person visits and 300,000 telehealth visits collected from 2017 to 2022. ResultsOur analysis revealed a statistically significant increase in telehealth visits across all specialties (P

IntroductionBovine Genital Campylobacteriosis (BGC), caused by Campylobacter fetus subsp. venerealis, is a sexually transmitted bacterium that significantly impacts cattle reproductive performance. However, current detection methods lack consistency and reliability due to the close genetic similarity between C. fetus subsp. venerealis and C. fetus subsp. fetus. Therefore, this study aimed to utilize complete genome analysis to distinguish genetic features between C. fetus subsp. venerealis and other subspecies, thereby enhancing BGC detection for routine screening and epidemiological studies.Methods and resultsThis study reported the complete genomes of four C. fetus subsp. fetus and five C. fetus subsp. venerealis, sequenced using long-read sequencing technologies. Comparative whole-genome analyses (n = 25) were conducted, incorporating an additional 16 complete C. fetus genomes from the NCBI database, to investigate the genomic differences between these two closely related C. fetus subspecies. Pan-genomic analyses revealed a core genome consisting of 1,561 genes and an accessory pangenome of 1,064 genes between the two C. fetus subspecies. However, no unique predicted genes were identified in either subspecies. Nonetheless, whole-genome single nucleotide polymorphisms (SNPs) analysis identified 289 SNPs unique to one or the C. fetus subspecies. After the removal of SNPs located on putative genomic islands, recombination sites, and those causing synonymous amino acid changes, the remaining 184 SNPs were functionally annotated. Candidate SNPs that were annotated with the KEGG “Peptidoglycan Biosynthesis” pathway were recruited for further analysis due to their potential association with the glycine intolerance characteristic of C. fetus subsp. venerealis and its biovar variant. Verification with 58 annotated C. fetus genomes, both complete and incomplete, from RefSeq, successfully classified these seven SNPs into two groups, aligning with their phenotypic identification as CFF (Campylobacter fetus subsp. fetus) or CFV/CFVi (Campylobacter fetus subsp. venerealis and its biovar variant). Furthermore, we demonstrated the application of mraY SNPs for detecting C. fetus subspecies using a quantitative PCR assay.DiscussionOur results highlighted the high genetic stability of C. fetus subspecies. Nevertheless, Campylobacter fetus subsp. venerealis and its biovar variants encoded common SNPs in genes related to glycine intolerance, which differentiates them from C. fetus subsp. fetus. This discovery highlights the potential of employing a multiple-SNP assay for the precise differentiation of C. fetus subspecies.

ABSTRACT Bacterial species often consist of strains with variable gene content, collectively referred to as the pangenome. Variations in the genetic makeup of strains can alter bacterial physiology and fitness. To define biologically relevant genes of a genome, genome-wide transposon mutant libraries have been used to identify genes essential for survival or virulence in a given strain. Such phenotypic studies have been conducted in four different genotypes of the human pathogen Streptococcus pyogenes, yet challenges exist in comparing results across studies conducted in different genetic backgrounds and conditions. To advance genotype to phenotype inferences across different S. pyogenes strains, we built a pangenome database of 249 S. pyogenes reference genomes. We systematically re-analyzed publicly available transposon sequencing datasets from S. pyogenes using a transposon sequencing-specific analysis pipeline, Transit. Across four genetic backgrounds and nine phenotypic conditions, 355 genes were essential for survival, corresponding to ~24% of the core genome. Clusters of Orthologous Genes (COG) categories related to coenzyme and lipid transport and growth functions were overrepresented as essential. Finally, essential operons across S. pyogenes genotypes were defined, with an increased number of essential operons detected under in vivo conditions. This study provides an extendible database to which new studies can be added, and a searchable html-based resource to direct future investigations into S. pyogenes biology.IMPORTANCEStreptococcus pyogenes is a human-adapted pathogen occupying restricted ecological niches. Understanding the essentiality of genes across different strains and experimental conditions is important to direct research questions and efforts to prevent the large burden of disease caused by S. pyogenes. To this end we systematically reanalyzed transposon sequencing studies in S. pyogenes using transposon sequencing-specific methods, integrating them into an extendible meta-analysis framework. This provides a repository of gene essentiality in S. pyogenes which was used to highlight specific genes of interest and for the community to guide future phenotypic studies.

Abstract Streptococcus dysgalactiae subsp. equisimilis (SDSE) is an emerging cause of human infection with invasive disease incidence and clinical manifestations comparable to the closely related species, Streptococcus pyogenes. Through systematic genomic analyses of 501 disseminated SDSE strains, we demonstrate extensive overlap between the genomes of SDSE and S. pyogenes. More than 75% of core genes are shared between the two species with one third demonstrating evidence of cross-species recombination. Twenty-five percent of mobile genetic element (MGE) clusters and 16 of 55 SDSE MGE insertion regions were shared across species. Assessing potential cross-protection from leading S. pyogenes vaccine candidates on SDSE, 12/34 preclinical vaccine antigen genes were shown to be present in >99% of isolates of both species. Relevant to possible vaccine evasion, six vaccine candidate genes demonstrated evidence of inter-species recombination. These findings demonstrate previously unappreciated levels of genomic overlap between these closely related pathogens with implications for streptococcal pathobiology, disease surveillance and prevention.

This review is a synopsis of selected articles from neuroscience, neuroanesthesia, and neurocritical care from 2023 (January–November 2023). The journals reviewed include anesthesia journals, critical care medicine journals, neurosurgical journals as well as high-impact medical journals such as the Lancet, Journal of American Medical Association, New England Journal of Medicine, and Stroke. The summary of important articles will serve to update the knowledge of neuroanesthesiologists and other perioperative physicians who provide care to neurosurgical and neurocritical patients.

Abstract The skin is the primary feeding site of ticks that infest livestock animals such as cattle. The highly specialised functions of skin at the molecular level may be a factor contributing to variation in susceptibility to tick infestation; but these remain to be well defined. The aim of this study was to investigate the bovine skin transcriptomic profiles of tick-naïve and tick-infested cattle and to uncover the gene expression networks that influence contrasting phenotypes of host resistance to ticks. RNA-Seq data was obtained from skin of Brangus cattle with high (n = 5) and low (n = 6) host resistance at 0 and 12 weeks following artificial tick challenge with Rhipicephalus australis larvae. No differentially expressed genes were detected pre-infestation between high and low resistance groups, but at 12-weeks there were 229 differentially expressed genes (DEGs; FDR

Streptococcus pyogenes (Group A Streptococcus, GAS) is a human-restricted pathogen that causes a wide range of diseases from pharyngitis and scarlet fever to more severe, invasive infections such as necrotising fasciitis and streptococcal toxic shock syndrome. There has been a global increase in both scarlet fever and invasive infections during the COVID-19 post-pandemic period. The aim of this study was the molecular characterisation of 17 invasive and non-invasive clinical non-emm1 GAS isolates from an Australian tertiary hospital collected between 2021 and 2022. Whole genome sequencing revealed a total of nine different GAS emm types with the most prevalent being emm22, emm12 and emm3 (each 3/17, 18%). Most isolates (14/17, 82%) carried at least one superantigen gene associated with contemporary scarlet fever outbreaks, and the carriage of these toxin genes was non-emm type specific. Several mutations within key regulatory genes were identified across the different GAS isolates, which may be linked to an increased expression of several virulence factors. This study from a single Australian centre provides a snapshot of non-emm1 GAS clinical isolates that are multiclonal and linked with distinct epidemiological markers commonly observed in high-income settings. These findings highlight the need for continual surveillance to monitor genetic markers that may drive future outbreaks.

Abstract Loss of genetic diversity in elite crop breeding pools can severely limit long‐term genetic gains and limit ability to make gains in new traits, like heat tolerance, that are becoming important as the climate changes. Here, we investigate and propose potential breeding program applications of optimal haplotype stacking (OHS), a selection method that retains useful diversity in the population. OHS selects sets of candidates containing, between them, haplotype segments with very high segment breeding values for the target trait. We compared the performance of OHS, a similar method called optimal population value (OPV), truncation selection on genomic estimated breeding values (GEBVs), and optimal contribution selection (OCS) in stochastic simulations of recurrent selection on founder wheat genotypes. After 100 generations of intercrossing and selection, OCS and truncation selection had exhausted the genetic diversity, while considerable diversity remained in the OHS population. Gain under OHS in these simulations ultimately exceeded that from truncation selection or OCS. OHS achieved faster gains when the population size was small, with many progeny per cross. A promising hybrid strategy, involving a single cycle of OHS in the first generation followed by recurrent truncation selection, substantially improved long‐term gain compared with truncation selection and performed similarly to OCS. The results of this study provide initial insights into where OHS could be incorporated into breeding programs.

Abstract Advancements in comprehending myelodysplastic neoplasms (MDS) have unfolded significantly in recent years, elucidating a myriad of cellular and molecular underpinnings integral to disease progression. While molecular inclusions into prognostic models have substantively advanced risk stratification, recent revelations have emphasized the pivotal role of immune dysregulation within the bone marrow milieu during MDS evolution. Nonetheless, immunotherapy for MDS has not experienced breakthroughs seen in other malignancies, partly attributable to the absence of an immune classification that could stratify patients toward optimally targeted immunotherapeutic approaches. A pivotal obstacle to establishing “immune classes” among MDS patients is the absence of validated accepted immune panels suitable for routine application in clinical laboratories. In response, we formed International Integrative Innovative Immunology for MDS (i4MDS), a consortium of multidisciplinary experts, and created the following recommendations for standardized methodologies to monitor immune responses in MDS. A central goal of i4MDS is the development of an immune score that could be incorporated into current clinical risk stratification models. This position paper first consolidates current knowledge on MDS immunology. Subsequently, in collaboration with clinical and laboratory specialists, we introduce flow cytometry panels and cytokine assays, meticulously devised for clinical laboratories, aiming to monitor the immune status of MDS patients, evaluating both immune fitness and identifying potential immune “risk factors.” By amalgamating this immunological characterization data and molecular data, we aim to enhance patient stratification, identify predictive markers for treatment responsiveness, and accelerate the development of systems immunology tools and innovative immunotherapies.

Abstract Background Genomic prediction describes the use of SNP genotypes to predict complex traits and has been widely applied in humans and agricultural species. Genotyping-by-sequencing, a method which uses low-coverage sequence data paired with genotype imputation, is becoming an increasingly popular SNP genotyping method for genomic prediction. The development of Oxford Nanopore Technologies’ (ONT) MinION sequencer has now made genotyping-by-sequencing portable and rapid. Here we evaluate the speed and accuracy of genomic predictions using low-coverage ONT sequence data in a population of cattle using four imputation approaches. We also investigate the effect of SNP reference panel size on imputation performance. Results SNP array genotypes and ONT sequence data for 62 beef heifers were used to calculate genomic estimated breeding values (GEBVs) from 641 k SNP for four traits. GEBV accuracy was much higher when genome-wide flanking SNP from sequence data were used to help impute the 641 k panel used for genomic predictions. Using the imputation package QUILT, correlations between ONT and low-density SNP array genomic breeding values were greater than 0.91 and up to 0.97 for sequencing coverages as low as 0.1 × using a reference panel of 48 million SNP. Imputation time was significantly reduced by decreasing the number of flanking sequence SNP used in imputation for all methods. When compared to high-density SNP arrays, genotyping accuracy and genomic breeding value correlations at 0.5 × coverage were also found to be higher than those imputed from low-density arrays. Conclusions Here we demonstrated accurate genomic prediction is possible with ONT sequence data from sequencing coverages as low as 0.1 × , and imputation time can be as short as 10 min per sample. We also demonstrate that in this population, genotyping-by-sequencing at 0.1 × coverage can be more accurate than imputation from low-density SNP arrays.

Abstract Background It has been challenging to implement genomic selection in multi-breed tropical beef cattle populations. If commercial (often crossbred) animals could be used in the reference population for these genomic evaluations, this could allow for very large reference populations. In tropical beef systems, such animals often have no pedigree information. Here we investigate potential models for such data, using marker heterozygosity (to model heterosis) and breed composition derived from genetic markers, as covariates in the model. Models treated breed effects as either fixed or random, and included genomic best linear unbiased prediction (GBLUP) and BayesR. A tropically-adapted beef cattle dataset of 29,391 purebred, crossbred and composite commercial animals was used to evaluate the models. Results Treating breed effects as random, in an approach analogous to genetic groups allowed partitioning of the genetic variance into within-breed and across breed-components (even with a large number of breeds), and estimation of within-breed and across-breed genomic estimated breeding values (GEBV). We demonstrate that moderately-accurate (0.30–0.43) GEBV can be calculated using these models. Treating breed effects as random gave more accurate GEBV than treating breed as fixed. A simple GBLUP model where no breed effects were fitted gave the same accuracy (and correlations of GEBV very close to 1) as a model where GEBV for within-breed and the GEBV for (random) across-breed effects were included. When GEBV were predicted for herds with no data in the reference population, BayesR resulted in the highest accuracy, with 3% accuracy improvement averaged across traits, especially when the validation population was less related to the reference population. Estimates of heterosis from our models were in line with previous estimates from beef cattle. A method for estimating the number of effective breed comparisons for each breed combination accumulated across contemporary groups is presented. Conclusions When no pedigree is available, breed composition and heterosis for inclusion in multi-breed genomic evaluation can be estimated from genotypes. When GEBV were predicted for herds with no data in the reference population, BayesR resulted in the highest accuracy.

Summary: Background: The World Health Organization seeks to eliminate viral hepatitis as a public health threat by 2030. This review and meta-analysis aims to evaluate the effectiveness of programs for hepatitis B and C testing and treatment in community pharmacies. Methods: Medline, Embase, Cochrane CENTRAL, and Global Health were searched from database inception until 12 November 2023. Comparative and single arm intervention studies were eligible for inclusion if they assessed delivery of any of the following interventions for hepatitis B or C in pharmacies: (1) pre-testing risk assessment, (2) testing, (3) pre-treatment assessment or (4) treatment. Primary outcomes were proportions testing positive and reaching each stage in the cascade. Random effects meta-analysis was used to estimate pooled proportions stratified by recruitment strategy and setting where possible; other results were synthesised narratively. This study was pre-registered (PROSPERO: CRD42022324218). Findings: Twenty-seven studies (4 comparative, 23 single arm) were included, of which 26 reported hepatitis C outcomes and four reported hepatitis B outcomes. History of injecting drug use was the most identified risk factor from pre-testing risk assessments. The pooled proportion hepatitis C antibody positive from of 19 studies testing 5096 participants was 16.6% (95% CI 11.0%–23.0%; heterogeneity I2 = 96.6%). The pooled proportion antibody positive was significantly higher when testing targeted people with specified risk factors (32.5%, 95% CI 24.8%–40.6%; heterogeneity I2 = 82.4%) compared with non-targeted or other recruitment methods 4.0% (95% CI 2.1%–6.5%; heterogeneity I2 = 83.5%). Meta-analysis of 14 studies with 813 participants eligible for pre-treatment assessment showed pooled attendance rates were significantly higher in pharmacies (92.7%, 95% CI 79.1%–99.9%; heterogeneity I2 = 72.4%) compared with referral to non-pharmacy settings (53.5%, 95% CI 36.5%–70.1%; heterogeneity I2 = 92.3%). The pooled proportion initiating treatment was 85.6% (95% CI 74.8%–94.3%; heterogeneity I2 = 75.1%). This did not differ significantly between pharmacy and non-pharmacy settings. Interpretation: These findings add pharmacies to the growing evidence supporting community-based testing and treatment for hepatitis C. Few comparative studies and high degrees of statistical heterogeneity were important limitations. Hepatitis B care in pharmacies presents an opportunity for future research. Funding: None.

Abstract Genomic selection in sugarcane faces challenges due to limited genomic tools and high genomic complexity, particularly because of its high and variable ploidy. The classification of genotypes for single nucleotide polymorphisms (SNPs) becomes difficult due to the wide range of possible allele dosages. Previous genomic studies in sugarcane used pseudo‐diploid genotyping, grouping all heterozygotes into a single class. In this study, we investigate the use of continuous genotypes as a proxy for allele‐dosage in genomic prediction models. The hypothesis is that continuous genotypes could better reflect allele dosage at SNPs linked to mutations affecting target traits, resulting in phenotypic variation. The dataset included genotypes of 1318 clones at 58K SNP markers, with about 26K markers filtered using standard quality controls. Predictions for tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and fiber content (Fiber) were made using parametric, non‐parametric, and Bayesian methods. Continuous genotypes increased accuracy by 5%–7% for CCS and Fiber. The pseudo‐diploid parametrization performed better for TCH. Reproducing kernel Hilbert spaces model with Gaussian kernel and AK4 (arc‐cosine kernel with hidden layer 4) kernel outperformed other methods for TCH and CCS, suggesting that non‐additive effects might influence these traits. The prevalence of low‐dosage markers in the study may have limited the benefits of approximating allele‐dosage information with continuous genotypes in genomic prediction models. Continuous genotypes simplify genomic prediction in polyploid crops, allowing additional markers to be used without adhering to pseudo‐diploid inheritance. The approach can particularly benefit high ploidy species or emerging crops with unknown ploidy.

Rapid increase in body surface area of growing zebrafish larvae ( Danio rario ) is partially accomplished by asynthetic fission of superficial epithelial cells (SECs) of the skin. There are two cycles of this atypical form of cell division which is unaccompanied by DNA replication; resulting in cells with a variable DNA content. Here, electron microscopy of basal epithelium cells that give rise to these SECs in zebrafish larvae shows aggregation of mitochondria around the nucleus and the formation of nucleus–mitochondria membrane contact sites. Membrane aggregates appear in the lumen of the nuclear envelope at these sites of membrane contact in some cells, suggesting lipid turnover in this vicinity. As the epithelial cells mature and stratify, the mitochondria are engulfed by extensions arising from the nuclear envelope. The mitochondrial outer membrane fragments and mitochondria fuse with the nuclear envelope and parts of the endoplasmic reticulum. Other organelles, including the Golgi apparatus, progressively localize to a central region of the cell and lose their integrity. Thus, asynthetic fission is accompanied by an atypical pattern of organelle destruction and a prelude to this is the formation of nucleus–mitochondria membrane contact sites.

Climate zones play a significant role in shaping the forest ecosystems located within them by influencing multiple ecological processes, including growth, disturbances, and species interactions. Therefore, delineation of current and future climate zones is essential to establish a framework for understanding and predicting shifts in forest ecosystems. In this study, we developed and applied an efficient approach to delineate regional climate zones in the northeastern United States and maritime Canada, aiming to characterize potential shifts in climate zones and discuss associated changes in forest ecosystems. The approach comprised five steps: climate data dimensionality reduction, sampling scenario design, cluster generation, climate zone delineation, and zone shift prediction. The climate zones in the study area were delineated into four different orders, with increasing subzone resolutions of 3, 9, 15, and 21. Furthermore, projected climate normals under Shared Socioeconomic Pathways 4.5 and 8.5 scenarios were used to predict the shifts in climate zones until 2100. Our findings indicate that climate zones characterized by higher temperatures and lower precipitation are expected to become more prevalent, potentially becoming the dominant climate condition across the entire region. Thes changes are likely to alter regional forest composition, structure, and productivity. In short, such shifts in climate underscore the significant impact of environmental change on forest ecosystem dynamics and carbon sequestration potential.

We report the first results from a deep near-infrared campaign with the Hubble Space Telescope to obtain late-epoch images of the Hubble Ultra Deep Field, 10–15 yr after the first epoch data were obtained. The main objectives are to search for faint active galactic nuclei (AGN) at high redshifts by virtue of their photometric variability and measure (or constrain) the comoving number density of supermassive black holes (SMBHs), n _SMBH , at early times. In this Letter, we present an overview of the program and preliminary results concerning eight objects. Three variables are supernovae, two of which are apparently hostless with indeterminable redshifts, although one has previously been recorded as a z ≈ 6 object precisely because of its transient nature. Two further objects are clear AGN at z = 2.0 and 3.2, based on morphology and/or infrared spectroscopy from JWST. Three variable targets are identified at z = 6–7 that are also likely AGN candidates. These sources provide a first measure of n _SMBH in the reionization epoch by photometric variability, which places a firm lower limit of 3 × 10 ^−4 cMpc ^−3 . After accounting for variability and luminosity incompleteness, we estimate n _SMBH ≳ 8 × 10 ^−3 cMpc ^−3 , which is the largest value so far reported at these redshifts. This SMBH abundance is also strikingly similar to estimates of n _SMBH in the local Universe. We discuss how these results test various theories for SMBH formation.

Abstract Sugarcane has a complex, highly polyploid genome with multi‐species ancestry. Additive models for genomic prediction of clonal performance might not capture interactions between genes and alleles from different ploidies and ancestral species. As such, genomic prediction in sugarcane presents an interesting case for machine learning (ML) methods, which are purportedly able to deal with high levels of complexity in prediction. Here, we investigated deep learning (DL) neural networks, including multilayer networks (MLP) and convolution neural networks (CNN), and an ensemble machine learning approach, random forest (RF), for genomic prediction in sugarcane. The data set used was 2912 sugarcane clones, scored for 26,086 genome wide single nucleotide polymorphism markers, with final assessment trial data for total cane harvested (TCH), commercial cane sugar (CCS), and fiber content (Fiber). The clones in the latest trial (2017) were used as a validation set. We compared prediction accuracy of these methods to genomic best linear unbiased prediction (GBLUP) extended to include dominance and epistatic effects. The prediction accuracies from GBLUP models were up to 0.37 for TCH, 0.43 for CCS, and 0.48 for Fiber, while the optimized ML models had prediction accuracies of 0.35 for TCH, 0.38 for CCS, and 0.48 for Fiber. Both RF and DL neural network models have comparable predictive ability with the additive GBLUP model but are less accurate than the extended GBLUP model.

Mate-allocation strategies in breeding programs can improve progeny performance by harnessing non-additive genetic effects. These approaches prioritise predicted progeny merit over parental breeding value, making them particularly appealing for clonally propagated crops such as sugarcane. We conducted a comparative analysis of mate-allocation strategies, exploring utilising non-additive and heterozygosity effects to maximise clonal performance with schemes that solely consider additive effects to optimise breeding value. Using phenotypic and genotypic data from a population of 2,909 clones evaluated in final assessment trials of Australian sugarcane breeding programs, we focused on three important traits: tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and Fibre. By simulating families from all possible crosses (1,225) with 50 progenies each, we predicted the breeding and clonal values of progeny using two models: GBLUP (considering additive effects only) and extended-GBLUP (incorporating additive, non-additive, and heterozygosity effects). Integer linear programming was used to identify the optimal mate-allocation among selected parents. Compared to breeding value-based approaches, mate-allocation strategies based on clonal performance yielded substantial improvements, with predicted progeny values increasing by 57% for TCH, 12% for CCS, and 16% for fibre. Our simulation study highlights the effectiveness of mate-allocation approaches that exploit non-additive and heterozygosity effects, resulting in superior clonal performance. However, there was a notable decline in additive gain, particularly for TCH, likely due to significant epistatic effects. When selecting crosses based on clonal performance for TCH, the inbreeding coefficient of progeny was significantly lower compared to random mating, underscoring the advantages of leveraging non-additive and heterozygosity effects in mitigating inbreeding depression. Thus, mate-allocation strategies are recommended in clonally propagated crops to enhance clonal performance and reduce the negative impacts of inbreeding.

This research explores the concept of placemaking in the context of sports events tourism, using the case study of the 2019 Rugby World Cup hosted in Japan. The study investigates how host cities used liminoid spaces between transport hubs and stadiums to create a festive atmosphere and articulate the identity of the place itself. Employing a novel ethnographic methodology centred around walking and participatory methods, the researcher occupied a dual tourist-researcher role, immersing himself in the liminoid space. Findings suggest that the use of such spaces was innovative and successful in creating a sense of place and developing a festive atmosphere through which visitors moved. However, the study acknowledges that these strategies may not be applicable to all sports events and that the direct experiences of visitors through ethnographic methods do not allow for empirical claims about the success of strategies or their longitudinal effects. Nevertheless, the study highlights the potential of placemaking in the periphery of sports events to enhance the visitor experience and promote the identity of the host destination.

Abstract Mercury’s southern inner magnetosphere is an unexplored region as it was not observed by earlier space missions. In October 2021, BepiColombo mission has passed through this region during its first Mercury flyby. Here, we describe the observations of SERENA ion sensors nearby and inside Mercury’s magnetosphere. An intermittent high-energy signal, possibly due to an interplanetary magnetic flux rope, has been observed downstream Mercury, together with low energy solar wind. Low energy ions, possibly due to satellite outgassing, were detected outside the magnetosphere. The dayside magnetopause and bow-shock crossing were much closer to the planet than expected, signature of a highly eroded magnetosphere. Different ion populations have been observed inside the magnetosphere, like low latitude boundary layer at magnetopause inbound and partial ring current at dawn close to the planet. These observations are important for understanding the weak magnetosphere behavior so close to the Sun, revealing details never reached before.