bluuebunny/crossref_metadata_2025 huggingface dataset:
UNDERSTANDING THE DETERMINANTS OF FLOURISHING AMONG ADOLESCENTS OF MAYUGE AND MPIGI DISTRICTS IN UGANDA: LINKING PHYSICAL, MENTAL, CULTURAL, ECONOMIC, AND SOCIAL DIMENSIONS THROUGH A GENDER-TRANSFORMATIVE LENS
Authors: Muthama Benson Mutuku , Henry Carol , White Judy , Lieffers Jessica , Fowler-Kerry Susan , Kikulwe Daniel , Tiessen Rebecca , Kibiri Lydia , Lough Benjamin , Musoke David , Tolossa Asrat Dibaba
Published: January 2024

The study sought to engage adolescents in Uganda to learn about their perspectives on the factors that enable or hinder their flourishing. This cross-sectional study was conducted in Mpigi and Mayuge districts in Uganda, using a survey with adolescent boys and girls aged 14-19 years. The survey examined seven aspects of human flourishing including: knowledge/education, emotional health, physical health, physical safety, financial security, social connectedness, and spiritual practices. The interpretation of scores and correlations was based on established classifications. Findings indicated that education, family, and community support were highly valued among participants. Among the respondents, eighty-five percent reported awareness of their right to education, and 79% expressed satisfaction with their access to primary or secondary education. Most respondents felt good about their emotional health (84%). Participants felt confidence in their decision-making abilities. Though the majority of respondents recognized the importance of a balanced diet to their own physical health, less than half reported being able to make decisions about what they eat. Most respondents reported feeling safe at home, with no significant differences by gender or region. Spiritual connectedness was also strong. Many reported that spirituality brought a sense of purpose, gratitude to their lives, and inner peace and harmony. Strong spiritual values within the communities were identified as important to their wellbeing; approximately seventy-seven percent expressed comfort in speaking to their faith leaders about their problems. Financial insecurity emerged as a significant obstacle (60%), however, eighty-four (84%) expressed confidence in finding work they liked, and most (88%) believed their future work would support them financially. Findings represent a first step in gaining a cross-cultural perspective of adolescent views on human flourishing. Findings may have implications for policymakers and decision-makers seeking to understand human flourishing among adolescents, and strategies to enable their flourishing.
Antiphospholipid antibodies exacerbate damage following oxygen deprivation-reperfusion injury in anin vivomodel for stroke and inex vivoblood derived endothelial cells
Authors: Pericleous Charis , Stuckey Daniel J. , Maughan Robert T. , Paschalaki Koralia , Kabir Lida , Bourke Lauren T. , Willis Rohan , Rahman Anisur , Randi Anna M. , Arachchillage Deepa J. , Lythgoe Mark , Giles Ian P. , Mason Justin C. , Ioannou Yiannis
Published: January 2024

Background

Prothrombotic antiphospholipid antibodies (aPL) found in patients with antiphospholipid syndrome (APS) are a recognised risk factor for ischemic stroke. However, it is unclear if aPL cause injury post thrombolysis leading to worse outcomes. We investigated whether aPL exacerbate reperfusion injury and sought to translate our findings in endothelial colony forming cells (ECFC) isolated from patients with APS.

Methods

Transient ischemic stroke was induced in adult rats injected with serum-derived IgG from patients with APS (APS-IgG, containing aPL) or healthy controls (HC-IgG). Infarct size and intracellular signalling processes involved in ischemia-reperfusion injury were determined post reperfusion.In vitro, human umbilical vein endothelial cells (HUVEC) treated with IgG, as well as APS and HC ECFC, were exposed to hypoxia (0.1% O2). Cell death and relevant signalling mechanisms were assessed following reperfusion and compared to matched normoxic cultures.

Results

In vivo, APS-IgG induced >2-fold larger infarcts and lower levels of active phosphorylated Akt, a key pro-survival kinase, compared to HC-IgG.In vitro, aPL-mediated cell death and suppression of Akt phosphorylation was confirmed in HUVEC exposed to IgG and hypoxia-reperfusion. Consistent with these findings, higher rates of cell death and reduced Akt phosphorylation following reperfusion were observed inex vivoAPS ECFC compared to HC ECFC. Treatment with the immunomodulating agent hydroxychloroquine ameliorated ECFC death and this effect was more pronounced in APS-derived cells.

Conclusion

Patient-derived IgG aPL exacerbate cell death following reperfusion in a novelin vivostroke model for APS, as well asin vitroHUVEC cultures. These observations are mimicked inex vivoAPS ECFC. Our findings describe a novel pathogenic role for aPL in mediating tissue injury in addition to their known thrombogenic properties and indicate potential for pharmacological intervention.
In major depression, complex intersections between adverse childhood experiences and negative life events impact neuroticism, brooding, suicidal tendencies, insomnia, and cognitive interference
Authors: Vasupanrajit Asara , Maes Michael , Jirakran Ketsupar , Tunvirachaisakul Chavit
Published: January 2024

Background

There is evidence that adverse childhood experiences (ACEs) and negative life events (NLEs) are associated with major depression (MDD).

Purpose

To determine whether ACEs affect all features of mild MDD, including suicidal tendencies, brooding, neuroticism, insomnia, cognitive deficits, severity of depression and anxiety, and cognitive deficits, and whether NLEs mediate these effects.

Patients and methods

This study examines a cohort of 118 academic students, namely 74 students who satisfied the DSM-5-TR criteria for MDD and 44 normal control students. We assessed brooding, neuroticism, suicidal ideation and attempts, and the severity of depression, anxiety, insomnia, and the Stroop tests.

Results

One validated factor could be extracted from brooding, neuroticism, current suicidal behaviors, and the severity of depression, anxiety, and insomnia, labeled the phenome of depression. A large part of the variance in the phenome of depression (55.0%) was explained by the combined effects of self-, relationships, and academic-related NLEs in conjunction with ACEs, including family dysfunction and abuse and neglect (both physical and emotional). The latter ACEs significantly interacted (moderating effect) with NLEs to impact the depression phenome. Although sexual abuse did not have direct effects on the phenome, its effects were mediated by NLEs. We discovered that increased sexual abuse, physical and emotional abuse and neglect, and ACEs related to family dysfunction predicted 22.5% of the variance in NLEs. Up to 18.5% of the variance in the Stroop test scores was explained by sexual abuse and the phenome of depression. The latter mediated the effects of NLEs and abuse, neglect, and family dysfunction on the Stroop test scores.

Conclusion

Complex intersections between ACEs and NLEs impact the phenome of depression, which comprises neuroticism, brooding, suicidal tendencies, and the severity of insomnia, anxiety, and depression, while sexual abuse together with other ACEs and NLEs may impact cognitive interference inhibition.
Understanding the Preferences of Young Women in Self-Sampling Interventions for STI Diagnosis: A Discrete Choice Experiment Protocol
Authors: Jaya Ziningi N. , Mapanga Witness , Mashamba-Thompson Tivani P
Published: January 2024

Introduction

Sexually transmitted infections (STIs) are a significant public health concern globally, particularly affecting young women. Early diagnosis and treatment are essential to reducing or stopping the continuous spread of infections and the development of the associated complications. Syndromic management, which is commonly used for STIs, presents several barriers, particularly for young women. This protocol is for a study that aims to understand young women’s preferences for a self-sampling intervention for STI diagnosis by using a Discrete Choice Experiment (DCE).

Methods and analysis

The following attributes of a self-sampling intervention were identified through a Nominal Group Technique: accessibility, education, confidentiality, self-sampling method, youth-friendliness, and cost. A pilot study involving 20 participants was conducted to refine the DCE questionnaire. A total of 196 young women from underserved communities will be recruited. The participants will be sampled from communities, stratified by settlement type and socioeconomic status. Data will be analysed using the multinomial logit model and mixed logit model to assess preferences and heterogeneity.

Ethics and dissemination

The study findings have the potential to inform policies for STI treatment and management to align healthcare services with user preferences. This can improve STI healthcare access for young women in underserved communities. Ethical approval was obtained, and results will be disseminated through peer-reviewed journals and health conferences.

Strengths and limitations of this study

DCEs provide a platform for users or consumers to express their preference for particular goods or services based on their attribute selection.

Previously STI healthcare service provision has not been aligned with the preferences of young women. Therefore, this will reveal their preferences for a self-sampling intervention for STI healthcare and management.

In instances where user preferences do not align with current practices for STI healthcare, this will provide an opportunity for policies to be reviewed and amended accordingly.

This type of impact on STI healthcare aligns with goal 3.1 of South Africa’s National Strategic Plan which seeks to improve access to healthcare services for STIs and other diseases (1). It also aligns with goal three of the United Nations which seeks to improve access to healthcare for all and thus achieve universal healthcare coverage (2, 3).

Since our study will be conducted on young women residing in underserved urban populations, our findings may not be a true reflection of young women from diverse communities.
Survival Prediction Landscape: An In-Depth Systematic Literature Review on Activities, Methods, Tools, Diseases, and Databases
Authors: Abbasi Ahtisham Fazeel , Asim Muhammad Nabeel , Ahmed Sheraz , Vollmer Sebastian , Dengel Andreas
Published: January 2024

Survival prediction integrates patient-specific molecular information and clinical signatures to forecast the anticipated time of an event, such as recurrence, death, or disease progression. Survival prediction proves valuable in guiding treatment decisions, optimizing resource allocation, and interventions of precision medicine. The wide range of diseases, the existence of various variants within the same disease, and the reliance on available data necessitate disease-specific computational survival predictors. The widespread adoption of artificial intelligence (AI) methods in crafting survival predictors has undoubtedly revolutionized this field. However, the ever-increasing demand for more sophisticated and effective prediction models necessitates the continued creation of innovative advancements. To catalyze these advancements, the need of the hour is to bring existing survival predictors knowledge and insights into a centralized platform. The paper in hand thoroughly examines 22 existing review studies and provides a concise overview of their scope and limitations. Focusing on a comprehensive set of 74 most recent survival predictors across 44 diverse diseases, it delves into insights of diverse types of methods that are used in the development of disease-specific predictors. This exhaustive analysis encompasses the utilized data modalities along with a detailed analysis of subsets of clinical features, feature engineering methods, and the specific statistical, machine or deep learning approaches that have been employed. It also provides insights about survival prediction data sources, open-source predictors, and survival prediction frameworks.
Symptom propagation in respiratory pathogens of public health concern: a review of the evidence
Authors: Asplin Phoebe , Mancy Rebecca , Finnie Thomas , Cumming Fergus , Keeling Matt J. , Hill Edward M.
Published: January 2024

Symptom propagation occurs when the symptom set an individual experiences is correlated with the symptom set of the individual who infected them. Symptom propagation may dramatically affect epidemiological outcomes, potentially causing clusters of severe disease. Conversely, it could result in chains of mild infection, generating widespread immunity with minimal cost to public health.

Despite accumulating evidence that symptom propagation occurs for many respiratory pathogens, the underlying mechanisms are not well understood. Here we conducted a scoping literature review for 14 respiratory pathogens to ascertain the extent of evidence for symptom propagation by two mechanisms: dose-severity relationships and route-severity relationships.

We identify considerable heterogeneity between pathogens in the relative importance of the two mechanisms, highlighting the importance of pathogen-specific investigations. For almost all pathogens, including influenza and SARS-CoV-2, we found support for at least one of the two mechanisms. For some pathogens, including influenza, we found convincing evidence that both mechanisms contribute to symptom propagation.

Furthermore, infectious disease models traditionally do not include symptom propagation. We summarise the present state of modelling advancements to address the methodological gap. We then investigate a simplified disease outbreak scenario, finding that under strong symptom propagation, quarantining mildly infected individuals can have negative epidemiological implications.
The Asia-Pacific body mass index classification and new-onset chronic kidney disease in non-diabetic Japanese adults: A community-based longitudinal study from 1998 to 2023
Authors: Okawa Yukari , Mitsuhashi Toshiharu , Tsuda Toshihide
Published: January 2024

Background/Objectives

Obesity is a risk factor for chronic kidney disease (CKD) in Asians. The Asia-Pacific body mass index (BMI) classification sets lower obesity cutoffs than the conventional BMI classification for all races, generally reflecting the lower BMIs in Asians. This longitudinal study evaluated the association between BMI, as classified by the Asia-Pacific BMI system, and CKD development in non-diabetic Asian adults.

Methods

A population-based longitudinal study (1998–2023) was conducted in non-diabetic Japanese adults (hemoglobin A1c < 6.5%) in Zentsuji City (Kagawa Prefecture, Japan). The generalized gamma model was used to assess the relationship between time-varying BMI categories and CKD development, stratified by sex. CKD was defined as an estimated glomerular filtration rate of <60 mL/min/1.73 m2. BMI was calculated as weight (kg) divided by the square of height (m2) and categorized per the Asia-Pacific classification as overweight (23.0–24.9 kg/m2), obesity class I (25.0–29.9 kg/m2), and obesity class II (≥30.0 kg/m2).

Results

CKD developed in 34.2% of 3,098 men and 34.8% of 4,391 women. The mean follow-up times were 7.41 years for men and 8.25 years for women. During follow-up, the BMI distributions for men were 5.0% underweight, 43.3% normal weight, 25.6% overweight, 24.1% obesity class I, and 2.0% obesity class II; those for women were 7.7%, 50.5%, 20.5%, 18.3%, and 2.9%, respectively. Compared with normal weight, obesity class I was associated with a 6% (95% confidence interval [CI]: 2%–10%) shorter time to CKD onset in men and 5% (95% CI: 2%–7%) in women. In both sexes, obesity class II showed shorter survival times than normal weight by point estimates, although all 95% CIs crossed the null value.

Conclusions

Obesity, as classified by the Asia-Pacific BMI system, shortened the time to CKD onset in non-diabetic Asians. The conventional BMI cutoff for obesity (≥30.0 kg/m2) may be too high to identify CKD risk in this population. The findings of this study may be useful for public health professionals in designing interventions to prevent CKD.
Machine learning across multiple imaging and biomarker modalities in the UK Biobank improves genetic discovery for liver fat accumulation
Authors: Somineni Hari , Mukherjee Sumit , Amar David , Pei Jingwen , Guo Karl , Light David , Flynn Kaitlin ,   insitro Research Team, Probert Chris , Soare Thomas , Satapati Santhosh , Koller Daphne , Lloyd David J. , O’Dushlaine Colm
Published: January 2024

Metabolic dysfunction-associated steatotic liver disease (MASLD), liver with more than 5.5% fat content, is a leading risk factor for chronic liver disease with an estimated worldwide prevalence of 30%. Though MASLD is widely recognized to be polygenic, genetic discovery has been lacking primarily due to the need for accurate and scalable phenotyping, which proves to be costly, time-intensive and variable in quality. Here, we used machine learning (ML) to predict liver fat content using three different data modalities available in the UK Biobank: dual-energy X-ray absorptiometry (DXA; n = 46,461 participants), plasma metabolites (n = 82,138), and anthropometric and blood-based biochemical measures (biomarkers; n = 262,927). Based on our estimates, up to 29% of participants in UKB met the criteria for MASLD. Genome-wide association studies (GWASs) of these estimates identified 15, 55, and 314 loci associated with liver fat predicted from DXA, metabolites and biomarkers, respectively, totalling 321 unique independent loci. In addition to replicating 9 of the 14 known loci at genome-wide significance, our GWASs identified 312 novel loci, significantly expanding our understanding of the genetic contributions to liver fat accumulation. Genetic correlation analysis indicated a strong correlation between ML-derived liver fat across modalities (rgranging from 0.85 to 0.96) and with clinically diagnosed MASLD (rgranging from 0.74 to 0.88), suggesting that a majority of the newly identified loci are likely to be relevant for clinical MASLD. DXA exhibited the highest precision, while biomarkers demonstrated the highest recall, respectively. Overall, these findings demonstrate the value of leveraging ML-based trait predictions across orthogonal data sources to improve our understanding of the genetic architecture of complex diseases.
Approach and Method for Bayesian Network Modelling: A Case Study in Pregnancy Outcomes for England and Wales
Authors: McLachlan Scott , Daley Bridget J , Saidi Sam , Kyrimi Evangelia , Dube Kudakwashe , Grosan Crina , Neil Martin , Rose Louise , Fenton Norman E
Published: January 2024

Efforts to fully exploit the rich potential of Bayesian Networks (BNs) have hitherto not seen a practical approach for development of domain-specific models using large-scale public statistics which have the potential to reduce the time required to develop probability tables and train the model. As a result, the duration of projects seeking to develop health BNs tend to be measured in years due to their reliance on obtaining ethics approval and collecting, normalising, and discretising collections of patient EHRs. This work addresses this challenge by investigating a new approach to developing health BNs that combines expert elicitation with knowledge from literature and national health statistics. The approach presented here is evaluated through the development of a BN for pregnancy complications and outcomes using national health statistics for all births in England and Wales during 2021. The result is a BN that when validated using vignettes against other common types of predictive models including multivariable logistic regression and nomograms produces comparable predictions. The BN using our approach and large-scale public statistics was also developed in a project with a duration measured in months rather than years. The unique contributions of this paper are a new efficient approach to BN development and a working BN capable of reasoning over a broad range of pregnancy-related conditions and outcomes.
Metformin use is associated with lower risks of dementia, anxiety and depression: The Hong Kong Diabetes Study
Authors: Hui Jeremy Man Ho , Zhou Jiandong , Lee Teddy Tai Loy , Hui Kyle , Chou Oscar Hou In , Lee Yan Hiu Athena , Lee Sharen , Wong Wing Tak , Wai Abraham Ka Chung , Chang Carlin , Jeevaratnam Kamalan , Liu Tong , Tse Gary
Published: January 2024

Aims

To compare the effects of metformin and sulphonylurea on new-onset dementia, anxiety disorder and depression, and all-cause mortality in patients with type 2 diabetes mellitus.

Methods

This is a retrospective population-based cohort study of type 2 diabetes mellitus patients exposed to either metformin or sulphonylureas attending the Hospital Authority of Hong Kong between 1stand 31stDecember 2009. The follow-up was until 31stDecember 2019. The primary outcome was a new diagnosis of dementia, and anxiety disorder/depression. Propensity score matching (1:1 ratio) between metformin and sulphonylurea users based on demographics, CAIDE score, CHA-DS-VASc score, Charlson comorbidity index, past comorbidities, medications, and total cholesterol was performed. Cox regression was used to identify significant risk predictors. Cause-specific and subdistribution hazard models were also used.

Results

A total of 89,711 patients (46% men, mean age: 67 years old [SD: 12]) followed-up for 1,579 days (SD: 650). Metformin users were at a lower risk of dementia (before: 0.78 [0.72, 0.84], P-value < 0.0001; after: 0.88 [0.80, 0.97], P-value = 0.0074), anxiety disorder and depression (before: 0.77 [0.69, 0.86], P-value < 0.0001; after: 0.71 [0.61, 0.82], P-value < 0.0001), and all-cause mortality (before: 0.69 [0.68, 0.71], P-value < 0.0001; after: 0.83 [0.80, 0.85], P-value < 0.0001). These associations remained significant in the competing risk models.

Conclusion

Metformin use is associated with lower risks of dementia, new-onset anxiety disorder and depression, and all-cause mortality, compared to sulphonylurea use. The protective effects of metformin and possible use in drug repurposing for indications beyond diabetes warrant further investigation.

Highlights

Patients with type 2 diabetes have an increased risk of cognitive, anxiety or depressive problems

Metformin use was associated with lower risks of new diagnosis of dementia, anxiety disorder and depression

Patients who developed dementia had lower levels of albumin, alanine transaminase and HbA1c compared to those who developed anxiety disorder and depression

Appropriate glycemic control and maintenance of normal liver function are important in slowing cognitive decline in type 2 diabetes mellitus
Designing multimedia patient education materials for adolescent idiopathic scoliosis: a protocol for a feasibility randomized controlled trial of patient education videos
Authors: Oirschot Garett Van , Doherty Cailbhe
Published: January 2024

Triple-masked three-armed feasibility parallel randomized controlled trial Multimedia patient education materials are increasingly used in healthcare. While much research focuses on optimising their scientific content, research is equally needed to optimise design and implementation. This study aims to determine the feasibility of a study examining how the implementation of scientific advice on design affects patient outcomes. Participants aged 10-18 with radiographically confirmed adolescent idiopathic scoliosis will be recruited from community settings in Ireland and randomized into usual care or receiving multimedia educational videos with or without evidence-informed design principles. Participants will be masked in the two video intervention arms, as will the therapist sending the educational videos. Outcomes will include the number of participants recruited and randomized, the number analysed post-intervention and at week eight, and the outcomes for baseline, post-intervention, and week 8. Adverse events will also be reported. This feasibility randomized controlled trial will offer insight into the feasibility of implementing advice from the literature in designing a trial of multimedia patient education materials for a population with adolescent idiopathic scoliosis.

Trial is registered onClinicalTrials.govasNCT06090344.
Predicting dimensions of depression from smartphone data
Authors: Holstein Vincent L. , Akre Samir , Leenings Ramona , Chung Yoonho , Hahn Tim , Baker Justin T.
Published: January 2024

Depressive disorders are highly prevalent but demand nuanced personalized treatment that traditional approaches in psychiatry cannot address. This gap has prompted a surge of interest in leveraging digital technology, particularly smartphones, for remote monitoring to enhance outpatient care. This study utilizes the BRIGHTEN dataset to construct interpretable prediction models for overall depression severity, measured by PHQ-9, and various depression dimensions using a factor modelling approach.

Our factor model unveils a three-factor solution encompassing mood, somatic, and concentration/psychomotor-related factors. Machine learning models effectively predict both the PHQ-9 scores and individual factors, with feature importance methods analyses underscoring the influence of the PHQ-2 scale and communication-related features. These findings are corroborated by models trained on data subsets.

Through nested multi-level models, we identify between-subject effects for the PHQ-2 and select communication-related features, along with within-subject effects for these features. In summary, this study underscores the robust predictive capacity of ecological momentary assessments and highlights features of potential relevance for future investigations, such as communication-related features. We advocate for future studies to assess the cost-effectiveness and intervention potential of these models.
Estimation of SARS-CoV-2 fitness gains from genomic surveillance data without prior lineage classification
Authors: Donker Tjibbe , Papathanassopoulos Alexis , Ghosh Hiren , Kociurzynski Raisa , Felder Marius , Grundmann Hajo , Reuter Sandra
Published: January 2024

The emergence of SARS-CoV-2 variants with increased fitness has had a strong impact on the epidemiology of COVID-19, with the higher effective reproduction number of the viral variants leading to new epidemic waves. Tracking such variants and their genetic signatures, using data collected through genomic surveillance, is therefore crucial for forecasting likely surges in incidence. Current methods of estimating fitness advantages of variants rely on tracking the changing proportion of a particular lineage over time, but describing successful lineages in a rapidly evolving viral population is a difficult task. We propose a new method of estimating fitness gains directly from nucleotide information generated by genomic surveillance, without a-priori assigning isolates to lineages from phylogenies, based solely on the abundance of Single Nucleotide Polymorphisms (SNPs). The method is based on mapping changes in the genetic population structure over time. Changes in the abundance of SNPs associated with periods of increasing fitness allow for the unbiased discovery of new variants, and thereby obviating a deliberate lineage assignment and phylogenetic inference. We conclude that the method provides a fast and reliable way to estimate fitness advantages of variants without the need for a-priori assigning isolates to lineages.
How executive control and emotional reactivity influence coping strategies in psychiatric patients during the COVID-19 pandemic
Authors: Kist Josina D. , Schlüter Linda , Duyser Fleur , Mulders Peter C.R. , Vrijsen Janna N. , Collard Rose M. , van Eijndhoven Philip F.P. , Tendolkar Indira
Published: January 2024

Background

During times of environmental challenges, adaptive coping strategies are essential to maintain mental health. Coping relies on executive control, which is often impaired in individuals with psychiatric disorders. Furthermore, emotional reactivity may interfere with executive control. Studying the association between cognitive skills and adaptive coping strategies, as well as the potential impact of emotional reactivity, could inform how we can provide mental support during large-scale adversity. In this study we examined coping strategies in a thoroughly phenotyped psychiatric cohort, the MIND-Set cohort, during the early COVID-19 pandemic stage.

Methods

We studied 1) the association between coping and both subjective and objective executive control before the pandemic, and three different coping strategies used during the pandemic, 2) the mediating role of emotional reactivity, indexed by amygdala reactivity, and 3) the moderating role of the presence of a psychiatric diagnosis in these associations. After finding no specific impact of patient or control status in this association, we decided to post-hoc study the transdiagnostic impact of depression severity in these associations.

Results

showed 1) only a significant association between subjective executive control and a self-reported positive reappraisal style and corona-related reappraisal. However, after controlling for depression severity, this association was no longer significant. Additionally, objective executive control was only directly associated with right amygdala reactivity, while amygdala reactivity in neither of the hemispheres mediated the association between executive control and any of the coping styles. Furthermore, the type of diagnosis did not moderate the association between executive control and coping.

Conclusion

Our findings firstly underline the difference between self-reported and performance based executive control. While both deficits in subjective and performance based EC may play a role in the persistence of psychiatric symptomatology, this finding emphasizes how depressive symptoms or negative affect can impact reappraisal ability. As this ability is fundamental to staying resilient, treatments focused on reducing negative affect and thereby training reappraisal are pivotal in the maintenance of mental health in the entire population during environmental challenges.

Competing Interest Statement

The authors have declared no competing interest.
Understanding diagnostic delay for endometriosis: a scoping review
Authors: Fryer Jodie , Mason-Jones Amanda J. , Woodward Amie
Published: January 2024

Introduction

Diagnostic delay for endometriosis is a well-established phenomenon. Despite this, little is known about where in the health care system these delays occur or why they occur. Our review is the first attempt to synthesise and analyse this evidence.

Methods

A systematic scoping review with a pre-specified protocol was used to incorporate the global mixed methods literature on diagnostic delay for endometriosis. Four databases (PubMed, MEDLINE, EMBASE, PsychINFO) were searched from inception to September 2023 with a search strategy designed specifically for each.

Results

The search yielded 367 studies, 22 of which met the inclusion criteria. A third of studies has been published since 2020 and 65% were from high income countries. Six were qualitative and 16 were quantitative studies. The average age of onset of endometriosis was 14 years for adolescents and 20 for adults. On average, the diagnostic delay reported for endometriosis across the included studies was 6.6 years (range 1.5 to 11.3 years) but this masked the very wide differences reported between countries such as a 0.5-year delay in Brazil to a 27-year delay in the UK.

Discussion

Health system barriers included access to private healthcare for those with limited finance, physical access for those using public health systems and a general lack of knowledge amongst patients and health care professionals. Women often reported feeling unheard by health professionals. Considering the impact on individuals and the health system, addressing diagnostic delay for endometriosis must remain a priority for researchers, health care providers and policy makers.

What is already known on this topic

Endometriosis is currently difficult to diagnose. This results in delays in diagnosis which negatively impacts those suffering and increases the severity of pain and extent of the disease with increased costs to health systems.

What this study adds

The scoping review methodology included studies using a range of methods. The longest average delay occurs in secondary care. Those seeking public health care experienced longer average delay in diagnosis compared to those seeking private health care. Improved clinical guidelines may reduce diagnostic delay.

How this study might affect research, practice or policy

This is the first known review to explore diagnostic delay for endometriosis and provides an overview of the current literature. Clearer definitions of diagnostic delay for endometriosis are needed to aid in comparisons across countries. Improving education, tracking outcomes through medical records and developing non-invasive diagnostic tools will be crucial to improve women’s health.
Evaluating topography of mutational signatures with SigProfilerTopography
Authors: Otlu Burçak , Alexandrov Ludmil B.
Published: January 2024

The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome’s architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.
Deficiency in ribosome biogenesis causes streptomycin resistance and impairs motility inSalmonella
Authors: Lyu Zhihui , Ling Yunyi , van Hoof Ambro , Ling Jiqiang
Published: January 2024

The ribosome is the central hub for protein synthesis and the target of many antibiotics. Whereas the majority of ribosome-targeting antibiotics inhibit protein synthesis and are bacteriostatic, aminoglycosides promote protein mistranslation and are bactericidal. Understanding the resistance mechanisms of bacteria against aminoglycosides is not only vital for improving the efficacy of this critically important group of antibiotics but also crucial for studying the molecular basis of translational fidelity. In this work, we analyzedSalmonellamutants evolved in the presence of the aminoglycoside streptomycin (Str) and identified a novel generimPto be involved in Str resistance. RimP is a ribosome assembly factor critical for the maturation of the 30S small subunit that binds Str. Deficiency in RimP increases resistance against Str and facilitates the development of even higher resistance. DeletingrimPdecreases mistranslation and cellular uptake of Str, and further impairs flagellar motility. Our work thus highlights a previously unknown mechanism of aminoglycoside resistance via defective ribosome assembly.
GLDADec: marker-gene guided LDA modelling for bulk gene expression deconvolution
Authors: Azuma Iori , Mizuno Tadahaya , Kusuhara Hiroyuki
Published: January 2024

Inferring cell type proportions from bulk transcriptome data is crucial in immunology and oncology. Here, we introduce GLDADec (Guided LDA Deconvolution), a bulk deconvolution method that guides topics using cell type-specific marker gene names to estimate topic distributions for each sample. Through benchmarking using blood-derived datasets, we demonstrate its high estimation performance and robustness. Moreover, we apply GLDADec to heterogeneous tissue bulk data and perform comprehensive cell type analysis in a data-driven manner. We show that GLDADec outperforms existing methods in estimation performance and evaluate its biological interpretability by examining enrichment of biological processes for topics. Finally, we apply GLDADec to TCGA tumor samples, enabling subtype stratification and survival analysis based on estimated cell type proportions, thus proving its practical utility in clinical settings. This approach, utilizing marker gene names as partial prior information, can be applied to various scenarios for bulk data deconvolution. GLDADec is available as an open-source Python package athttps://github.com/mizuno-group/GLDADec.
Quantifying the advantage of multimodal data fusion for survival prediction in cancer patients
Authors: Nikolaou Nikolaos , Salazar Domingo , RaviPrakash Harish , Gonçalves Miguel , Mulla Rob , Burlutskiy Nikolay , Markuzon Natasha , Jacob Etai
Published: January 2024

The last decade has seen an unprecedented advance in technologies at the level of high-throughput molecular assays and image capturing and analysis, as well as clinical phenotyping and digitization of patient data. For decades, genotyping (identification of genomic alterations), the casual anchor in biological processes, has been an essential component in interrogating disease progression and a guiding step in clinical decision making. Indeed, survival rates in patients tested with next-generation sequencing have been found to be significantly higher in those who received a genome-guided therapy than in those who did not. Nevertheless, DNA is only a small part of the complex pathophysiology of cancer development and progression. To assess a more complete picture, researchers have been using data taken from multiple modalities, such as transcripts, proteins, metabolites, and epigenetic factors, that are routinely captured for many patients. Multimodal machine learning offers the potential to leverage information across different bioinformatics modalities to improve predictions of patient outcome. Identifying a multiomics data fusion strategy that clearly demonstrates an improved performance over unimodal approaches is challenging, primarily due to increased dimensionality and other factors, such as small sample sizes and the sparsity and heterogeneity of data. Here we present a flexible pipeline for systematically exploring and comparing multiple multimodal fusion strategies. Using multiple independent data sets from The Cancer Genome Atlas, we developed a late fusion strategy that consistently outperformed unimodal models, clearly demonstrating the advantage of a multimodal fusion model.
Characterization and genomic analysis of the Lyme disease spirochete bacteriophage ϕBB-1
Authors: Faith Dominick R. , Kinnersley Margie , Brooks Diane M. , Drecktrah Dan , Hall Laura S. , Luo Eric , Santiago-Frangos Andrew , Wachter Jenny , Samuels D. Scott , Secor Patrick R.
Published: January 2024

Lyme disease is a tick-borne infection caused by the spirocheteBorrelia(Borreliella)burgdorferi.Borreliaspecies have highly fragmented genomes composed of a linear chromosome and a constellation of linear and circular plasmids some of which are required throughout the enzootic cycle. Included in this plasmid repertoire by almost all Lyme disease spirochetes are the 32-kb circular plasmid cp32 prophages that are capable of lytic replication to produce infectious virions called ϕBB-1. While theB. burgdorferigenome contains evidence of horizontal transfer, the mechanisms of gene transfer between strains remain unclear. While we know that ϕBB-1 transduces cp32 and shuttle vector DNA duringin vitrocultivation, the extent of ϕBB-1 DNA transfer is not clear. Herein, we use proteomics and long-read sequencing to further characterize ϕBB-1 virions. Our studies identified the cp32pacregion and revealed that ϕBB-1 packages linear cp32s via a headful mechanism with preferentially packaging of plasmids containing the cp32pacregion. Additionally, we find ϕBB-1 packages fragments of the linear chromosome and full-length plasmids including lp54, cp26, and others. Furthermore, sequencing of ϕBB-1 packaged DNA allowed us to resolve the covalently closed hairpin telomeres for the linearB. burgdorferichromosome and most linear plasmids in strain CA-11.2A. Collectively, our results shed light on the biology of the ubiquitous ϕBB-1 phage and further implicates ϕBB-1 in the generalized transduction of diverse genes and the maintenance of genetic diversity in Lyme disease spirochetes.
Carbapenemase-producing Enterobacterales colonisation status does not lead to more frequent admissions: a linked patient study
Authors: Lydeamore Michael J , Donker Tjibbe , Wu David , Gorrie Claire , Turner Annabelle , Easton Marion , Hennessey Daneeta , Geard Nic , Howden Ben P. , Cooper Ben S. , Wilson Andrew , Peleg Anton Y , Stewardson Andrew J
Published: January 2024

Background

Hospitals in any given region can be considered as part of a network, where facilities are connected to one another – and hospital pathogens potentially spread – through the movement of patients between them. We sought to describe the hospital admission patterns of patients known to be colonised with carbapenemase-producing Enterobacterales (CPE), and compare them with CPE-negative patients.

Methods

We performed a linkage study in Victoria, Australia, including datasets with notifiable diseases (CPE notifications) and hospital admissions (admission dates and diagnostic codes) for the period 2011 to 2020. Where the CPE notification date occurred during a hospital admission for the same patient, we identified this as the ‘index admission’. We determined the number of distinct health services each patient was admitted to, and time to first admission to a different health service. We compared CPE-positive patients with four cohorts of CPE-negative patients, sampled based on different matching criteria.

Results

Of 528 unique patients who had CPE detected during a hospital admission, 222 (42%) were subsequently admitted to a different health service during the study period. Among these patients, CPE diagnosis tended to occur during admission to a metropolitan public hospital (86%, 190/222), whereas there was a greater number of metropolitan private (23%, 52/222) and regional public (18%, 39/222) hospitals for the subsequent admission. Median time to next admission was 4 days (IQR, 0-75 days). Admission patterns for CPE-positive patients was similar to the cohort of CPE-negative patients matched on index admission, time period, and age-adjusted Charlson comorbidity index.

Conclusions

Movement of CPE-positive patients between health services is not a rare event. While the most common movement is from one public metropolitan health service to another, there is also a trend for movement from metropolitan public hospitals into private and regional hospitals. CPE-positivity does not appear to impact on hospital admission frequency and timing. These findings support the potential utility of a centralised notification and outbreak management system for CPE positive patients.
ScGOclust: leveraging gene ontology to compare cell types across distant species using scRNA-seq data
Authors: Song Yuyao , Hu Yanhui , Dow Julian , Perrimon Norbert , Papatheodorou Irene
Published: January 2024

Basic biological processes are shared among animal species, yet their cellular mechanisms are profoundly diverse. Comparing cell type expression profiles across species reveals the conservation and divergence of cellular functions. With the increase of phylogenetic distance between species of interest, a gene-based comparison becomes limited. The Gene Ontology (GO) knowledgebase is the most comprehensive resource of gene functions, providing a bridge for comparing cell types between remote species. Here, we present scGOclust, a computational tool to construct cellular functional profiles using GO terms and facilitates systematic, robust comparisons within and across species. We use scGOclust to analyse and compare the heart, gut and kidney between mouse and fly. We show that scGOclust recapitulates the function spectrum of different cell types, characterises functional similarities between homologous cell types, and reveals functional convergence between unrelated cell types. Furthermore, we identify subpopulations in the fly crop by cross-species comparison of GO profiles. Finally, scGOclust resolved the analogy between Malpighian tubule and kidney segments.
Differences in Alu vs L1-rich chromosome bands underpin architectural reorganization of the inactive-X chromosome and SAHFs
Authors: Hall Lisa L. , Creamer Kevin M. , Byron Meg , Lawrence Jeanne B.
Published: January 2024

The linear DNA sequence of mammalian chromosomes is organized in large blocks of DNA with similar sequence properties, producing a pattern of dark and light staining bands on mitotic chromosomes. Cytogenetic banding is essentially invariant between people and cell-types and thus may be assumed unrelated to genome regulation. We investigate whether large blocks of Alu-rich R-bands and L1-rich G-bands provide a framework upon which functional genome architecture is built. We examine two models of large-scale chromatin condensation: X-chromosome inactivation and formation of senescence-associated heterochromatin foci (SAHFs). XIST RNA triggers gene silencing but also formation of the condensed Barr Body (BB), thought to reflect cumulative gene silencing. However, we find Alu-rich regions are depleted from the L1-rich BB, supporting it is a dense core but not the entire chromosome. Alu-rich bands are also gene-rich, affirming our earlier findings that genes localize at the outer periphery of the BB. SAHFs similarly form within each territory by coalescence of syntenic L1 regions depleted for highly Alu-rich DNA. Analysis of senescent cell Hi-C data also shows large contiguous blocks of G-band and R-band DNA remodel as a segmental unit. Entire dark-bands gain distal intrachromosomal interactions as L1-rich regions form the SAHF. Most striking is that sharp Alu peaks within R-bands resist these changes in condensation. We further show that Chr19, which is exceptionally Alu rich, fails to form a SAHF. Collective results show regulation of genome architecture corresponding to large blocks of DNA and demonstrate resistance of segments with high Alu to chromosome condensation.

Graphical Abstract