bluuebunny/crossref_metadata_2025 huggingface dataset:
A Bayesian Noisy Logic Model for Inference of Transcription Factor Activity from Single Cell and Bulk Transcriptomic Data
Authors: Arriojas Argenis , Patalano Susan , Macoska Jill , Zarringhalam Kourosh
Published: May 2023

The advent of high-throughput sequencing has made it possible to measure the expression of genes at relatively low cost. However, direct measurement of regulatory mechanisms, such as Transcription Factor (TF) activity is still not readily feasible in a high-throughput manner. Consequently, there is a need for computational approaches that can reliably estimate regulator activity from observable gene expression data. In this work, we present a noisy Boolean logic Bayesian model for TF activity inference from differential gene expression data and causal graphs. Our approach provides a flexible framework to incorporate biologically motivated TF-gene regulation logic models. Using simulations and controlled over-expression experiments in cell cultures, we demonstrate that our method can accurately identify TF activity. Moreover, we apply our method to bulk and single cell transcriptomics measurements to investigate transcriptional regulation of fibroblast phenotypic plasticity. Finally, to facilitate usage, we provide user-friendly software packages and a web-interface to query TF activity from user input differential gene expression data:https://umbibio.math.umb.edu/nlbayes/.

Author Summary

NextGen RNA sequencing (RNA-Seq) has enabled simultaneous measurement of the expression level of all genes. Measurements can be done at the population level or single-cell resolution. However, direct measurement of regulatory mechanisms, such as Transcription Factor (TF) activity, is still not possible in a high-throughput manner. As such, there is a need for computational models to infer regulator activity from gene expression data. In this work, we introduce a Bayesian methodology that utilizes prior biological knowledge on bio-molecular interactions in conjunction with readily available gene expression measurements to estimate TF activity. The Bayesian model naturally incorporates biologically motivated combinatorial TF-gene interaction logic models and accounts for noise in gene expression data as well as prior knowledge. The method is accompanied by efficiently implemented R and Python software packages as well as a user-friendly web-based interface that allows users to upload their gene expression data and run queries on a TF-gene interaction network to identify and rank putative transcriptional regulators. This tool can be used for a wide range of applications, such as identification of TFs downstream of signaling events and environmental or molecular perturbations, the aberration in TF activity in diseases, and other studies with ‘case-control’ gene expression data.
Pulmonary Matrix Derived Hydrogels from Patients with Idiopathic Pulmonary Fibrosis Induce a Proinflammatory State in Lung FibroblastsIn Vitro
Authors: Fernandez Davila JG , Moore DW , Kim J , Khan JA , Singh AK , Lemma M , King CS , Nathan SD , Rodriguez LR , Grant GM , Moran JL
Published: May 2023

Idiopathic pulmonary fibrosis (IPF), one of the most common forms of interstitial lung disease, is a poorly understood, chronic, and often fatal fibroproliferative condition with only two FDA-approved medications. Understanding the pathobiology of the fibroblast in IPF is critical to evaluating and discovering novel therapeutics. Unfortunately, our ability to interrogate this biologyin vitrois greatly limited by the well-documented effects of tissue culture plastic on the fibroblast phenotype. Using a decellularized lung matrix derived from IPF patients, we generate three-dimensional (3D) hydrogels asin vitromodels of lung physiology and characterize the phenotype of fibroblasts seeded into the hydrogels. When cultured in our hydrogels, IPF fibroblasts display differential contractility compared to their normal counterparts, lose the classical myofibroblast marker α-smooth muscle actin, and increase expression of proinflammatory cytokines compared to fibroblasts seeded two-dimensionally (2D) on tissue culture dishes. We validate this proinflammatory state in fibroblast conditioned media studies with monocytes and monocyte-derived macrophages. These findings add to a growing understanding of the lung microenvironment effect on fibroblast phenotypes, shed light on the potential role of fibroblasts as immune signaling hubs during lung fibrosis, and suggest intervention in fibroblast-immune cell crosstalk as a possible novel therapeutic avenue.
Worth the weight: Sub-Pocket EXplorer (SubPEx), a weighted-ensemble method to enhance binding-pocket conformational sampling
Authors: Hellemann Erich , Durrant Jacob D.
Published: May 2023

1.

Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license:http://durrantlab.com/subpex/
Neural responses to reconstructed target pursuits
Authors: Ogawa Yuri , Nicholas Sarah , Thyselius Malin , Leibbrandt Richard , Nowotny Thomas , Knight James C. , Nordström Karin
Published: May 2023

Many animals use motion vision information to control dynamic behaviors. Predatory animals, for example, show an exquisite ability to detect rapidly moving prey followed by pursuit and capture. Such target detection is not only used by predators but can also play an important role in conspecific interactions. Male hoverflies (Eristalis tenax), for example, vigorously defend their territories against conspecific intruders. Visual target detection is believed to be subserved by specialized target tuned neurons that are found in a range of species, including cats, zebrafish, and insects. However, how these target-tuned neurons respond to actual pursuit trajectories is currently not well understood. To redress his, we recorded extracellularly from target selective descending neurons (TSDNs) in maleEristalis tenaxhoverflies. We show that the neurons have dorso-frontal receptive fields, with a preferred direction up and away from the visual midline. We next reconstructed visual flow-fields as experienced during pursuits of artificial targets (black beads). We recorded TSDN responses to six reconstructed pursuits and found that each neuron responded consistently at remarkably specific time points, but that these time points differed between neurons. We compared the observed spike probability with the spike probability predicted from each neuron’s receptive field and size tuning, and found a correlation coefficient of 0.35. Interestingly, however, the overall response rate was low, with individual neurons responding to only a small part of each reconstructed pursuit. In contrast, the TSDN population responded to a substantially larger proportion of the pursuits (up to a median of 23%). This large variation between neurons could be useful if different neurons control different parts of the behavioral output.

Significance statement

Descending neurons constitute less than 1% of the nervous system, yet have to convey all requisite information from the brain to the body. They are therefore a crucial bottleneck in sensorimotor transformation. Descending target tuned neurons in male hoverflies (Eristalis tenax), for example, are believed to play a key role in territory defense and pursuit of conspecifics. However, this has not been tested using visual stimuli resembling reconstructed target pursuits. We here found that the observed neural responses to reconstructed pursuits are stronger than those predicted from responses to simpler stimuli. In addition, while the responses to simple stimuli suggested a homogenous population of neurons, the reconstructed pursuits showed important differences between individual neurons. Our data thus highlight the need for using more naturalistic stimuli when deciphering neural function.
Spatially-resolved single-cell atlas of ascidian endostyle provides insights into the origin of vertebrate pharyngeal organs
Authors: Jiang An , Han Kai , Wei Jiankai , Su Xiaoshan , Wang Rui , Zhang Wei , Liu Xiawei , Qiao Jinghan , Liu Penghui , Liu Qun , Zhang Jin , Zhang Nannan , Ge Yonghang , Zhuang Yuan , Yu Haiyan , Wang Shi , Chen Kai , Xu Xun , Yang Huanming , Fan Guangyi , Dong Bo
Published: May 2023

The pharynx is an endoderm innovation in deuterostome ancestors, the vertebrate descendent structure of which is a pharyngeal developmental organizer involving multi-germ layer and organ derivatives. However, the evolutionary origination of complicated pharynx organs in vertebrates is still largely unknown. Endostyle, a transitional pharyngeal organ exclusively in basal chordates provides an opportunity to reveal the origin of pharyngeal organs. Here, utilizing cutting-edged Stereo-seq and single-cell RNA-seq, we constructed the first spatially-resolved single-cell atlas in the endostyle of urochordate ascidianStyela clava, where the spatial location of Stereo-seq and high capture efficiency of single-cell RNA-seq complement each other and identified 23 highly differentiated cell types. We identified a previously overlooked hemolymphoid region (HLR), which harbors immune and blood cell clusters with enriched stemness capacities, illuminating a mixed rudiment and stem-cell niches for the blood and lymphoid system. More excitingly, we discovered a mechanical-sensitive hair cell candidate in zone 3 homologous to vertebrate acoustico-lateralis system, which was supported by the expression ofin situhybridization-verified inner ear-specific markers, includingPTPRQ,USH2A,WHRN, andADGRV1, ultracellular structure evidence and cross-species comparison. These results thoroughly renewed the comprehension of the basal-chordate pharynx and provides expressional evidence for multiplexed pharyngeal organ evolution.
Probing Conformational Landscapes of Binding and Allostery in the SARS-CoV-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations and Perturbation-Based Profiling Approaches: Hidden Role of Omicron Mutations as Modulators of Allosteric Signaling and Epistatic Relationships
Authors: Verkhivker Gennady , Alshahrani Mohammed , Gupta Grace , Xiao Sian , Tao Peng
Published: May 2023

In this study, we systematically examine the conformational dynamics, binding and allosteric communications in the Omicron BA.1, BA.2, BA.3 and BA.4/BA.5 complexes with the ACE2 host receptor using molecular dynamics simulations and perturbation-based network profiling approaches. Microsecond atomistic simulations provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the BA.2 variant which is contrasted with the BA.4/BA.5 variants inducing a significant mobility of the complexes. Using ensemble-based mutational scanning of binding interactions, we identified binding affinity and structural stability hotspots in the Omicron complexes. Perturbation response scanning and network-based mutational profiling approaches probed the effect of the Omicron variants on allosteric communications. The results of this analysis revealed specific roles of Omicron mutations as “plastic and evolutionary adaptable” modulators of binding and allostery which are coupled to the major regulatory positions through interaction networks. Through perturbation network scanning of allosteric residue potentials in the Omicron variant complexes, which is performed in the background of the original strain, we identified that the key Omicron binding affinity hotspots N501Y and Q498R could mediate allosteric interactions and epistatic couplings. Our results suggested that the synergistic role of these hotspots in controlling stability, binding and allostery can enable for compensatory balance of fitness tradeoffs with conformationally and evolutionary adaptable immune-escape Omicron mutations. Through integrative computational approaches, this study provides a systematic analysis of the effects of Omicron mutations on thermodynamics, binding and allosteric signaling in the complexes with ACE2 receptor. The findings support a mechanism in which Omicron mutations can evolve to balance thermodynamic stability and conformational adaptability in order to ensure proper tradeoff between stability, binding and immune escape.
Opportunities and limitations of genomics for diagnosing bedaquiline-resistant tuberculosis: an individual isolate meta-analysis
Authors: Nimmo Camus , Bionghi Neda , Cummings Matthew J. , Perumal Rubeshan , Hopson Madeleine , Al Jubaer Shamim , Wolf Allison , Mathema Barun , Larsen Michelle H. , O’Donnell Max
Published: May 2023

Background

Clinical bedaquiline resistance predominantly involves mutations inmmpR5(Rv0678). However,mmpR5resistance-associated variants (RAVs) have a variable relationship with phenotypicM. tuberculosisresistance. We performed a systematic review to (1) assess the maximal sensitivity of sequencing bedaquiline resistance-associated genes and (2) evaluate the association between RAVs and phenotypic resistance, using traditional and machine-based learning techniques.

Methods

We screened public databases for articles published until October 2022. Eligible studies performed sequencing of at leastmmpR5andatpEon clinically-sourcedM. tuberculosisisolates and measured bedaquiline minimum inhibitory concentrations (MICs). We performed genetic analysis for identification of phenotypic resistance and determined the association of RAVs with resistance. Machine-based learning methods were employed to define test characteristics of optimised sets of RAVs, andmmpR5mutations were mapped to the protein structure to highlight mechanisms of resistance.

Results

Eighteen eligible studies were identified, comprising 975M. tuberculosisisolates containing ≥1 potential RAV (mutation inmmpR5, atpE, atpBorpepQ), with 201 (20.6%) demonstrating phenotypic bedaquiline resistance. 84/285 (29.5%) resistant isolates had no candidate gene mutation. Sensitivity and positive predictive value of taking an ‘any mutation’ approach was 69% and 14% respectively. Thirteen mutations, all inmmpR5, had a significant association with a resistant MIC (adjusted p<0.05). Gradient-boosted machine classifier models for predicting intermediate/resistant and resistant phenotypes both had receiver operator characteristic c-statistics of 0.73. Frameshift mutations clustered in the alpha 1 helix DNA binding domain, and substitutions in the alpha 2 and 3 helix hinge region and in the alpha 4 helix binding domain.

Discussion

Sequencing candidate genes is insufficiently sensitive to diagnose clinical bedaquiline resistance, but where identified a limited number of mutations should be assumed to be associated with resistance. Genomic tools are most likely to be effective in combination with rapid phenotypic diagnostics.
GPT-4 outperforms ChatGPT in answering non-English questions related to cirrhosis
Authors: Yeo Yee Hui , Samaan Jamil S. , Ng Wee Han , Ma Xiaoyan , Ting Peng-Sheng , Kwak Min-Sun , Panduro Arturo , Lizaola-Mayo Blanca , Trivedi Hirsh , Vipani Aarshi , Ayoub Walid , Yang Ju Dong , Liran Omer , Spiegel Brennan , Kuo Alexander
Published: May 2023

Background and Objectives

Artificial intelligence is increasingly being employed in healthcare, raising concerns about the exacerbation of disparities. This study evaluates ChatGPT and GPT-4’s ability to comprehend and respond to cirrhosis-related questions in English, Korean, Mandarin, and Spanish, addressing language barriers that may impact patient care.

Methods

A set of 36 cirrhosis-related questions were translated into Korean, Mandarin, and Spanish and prompted to both ChatGPT and GPT-4 models. Non-English responses were graded by native-speaking hepatologists on accuracy and similarity to English responses. Chi-square tests were used to compare the proportions of grading between ChatGPT and GPT-4.

Results

GPT-4 showed a marked improvement in the proportion of comprehensive and correct answers compared to ChatGPT across all four languages (p<0.05). GPT-4 demonstrated enhanced accuracy and avoided erroneous responses evident in ChatGPT’s output. Significant improvement was observed in Mandarin and Korean subgroups, with a smaller quality gap between English and non-English responses in GPT-4 compared to ChatGPT.

Conclusions

GPT-4 exhibited significantly higher accuracy in English and non-English cirrhosis-related questions, highlighting its potential for more accurate and reliable language model applications in diverse linguistic contexts. These advancements have important implications for patients with language discordance, contributing to equalizing health literacy on a global scale.
Evaluating GPT-4-based ChatGPT’s Clinical Potential on the NEJM Quiz
Authors: Ueda Daiju , Walston Shannon L , Matsumoto Toshimasa , Deguchi Ryo , Tatekawa Hiroyuki , Miki Yukio
Published: May 2023

Background

GPT-4-based ChatGPT demonstrates significant potential in various industries; however, its potential clinical applications remain largely unexplored.

Methods

We employed the New England Journal of Medicine (NEJM) quiz “Image Challenge” from October 2021 to March 2023 to assess ChatGPT’s clinical capabilities. The quiz, designed for healthcare professionals, tests the ability to analyze clinical scenarios and make appropriate decisions. We evaluated ChatGPT’s performance on the NEJM quiz, analyzing its accuracy rate by questioning type and specialty after excluding quizzes which were impossible to answer without images. The NEJM quiz has five multiple-choice options, but ChatGPT was first asked to answer without choices, and then given the choices to answer afterwards, in order to evaluate the accuracy in both scenarios.

Results

ChatGPT achieved an 87% accuracy without choices and a 97% accuracy with choices, after excluding 16 image-based quizzes. Upon analyzing performance by quiz type, ChatGPT excelled in the Diagnosis category, attaining 89% accuracy without choices and 98% with choices. Although other categories featured fewer cases, ChatGPT’s performance remained consistent. It demonstrated strong performance across the majority of medical specialties; however, Genetics had the lowest accuracy at 67%.

Conclusion

ChatGPT demonstrates potential for clinical application, suggesting its usefulness in supporting healthcare professionals and enhancing AI-driven healthcare.
Excess Mortality Resulting from COVID-19 in Turkey during 2020-2021: Regional and Time-Based Analysis
Authors: Keskin Salih , Ergör Gül
Published: May 2023

Turkey experienced substantial excess mortality in 2020 and 2021 related to the COVID-19 pandemic. Methods used to estimate excess mortality vary, making comparisons difficult. This study assessed the impact of the COVID-19 pandemic in Turkey, using the TURKSTAT data which became available on February 23, 2023. We applied a quasi-Poisson model to estimate excess mortality during 2020–2021, comparing excess mortality by time periods and socioeconomic factors. During 2020–2021, Turkey experienced 72,886 excess deaths in 2020 (P-score 16.8%) and 125,540 in 2021 (P-score 28.5%). An additional 80 excess deaths per 100,000 people were recorded in 2020 and 143 in 2021. Excess all-cause mortality varied across socioeconomic levels, with notable social disparities in pandemic deaths as the highest rates were observed in the lowest socioeconomic group. This study highlights the importance of a comprehensive approach to address the diverse impacts of the pandemic on health and well-being while considering socioeconomic disparities, and potential areas for improvement in data collection and reporting.
A blended learning approach for capacity strengthening to improve the quality of integrated HIV, TB, and Malaria services during antenatal and postnatal care in LMICs: A feasibility study
Authors: Ladur Alice Norah , Kumah Elizabeth Adjoa , Egere Uzochukwu , Mgawadere Florence , Murray Christopher , Ravit Marion , White Sarah Ann , Mohammed Hauwa , Mutai Rael , Nyaga Lucy , Shikuku Duncan , Bashir Issak , Ayinde Olubunmi Olufunmilola , Bakar Rukia , Katalambula Leonard , Federici Carlo , Torbica Aleksandra , Furtado Nicholas , Ameh Charles
Published: May 2023

The blended learning (BL) approach to training health care professionals is increasingly adopted in many countries because of high costs and disruption to service delivery in the light of severe human resource shortage in low resource settings. The Covid-19 pandemic increased the urgency to identify alternatives to traditional face-to-face (f2f) education approach. A four-day f2f antenatal care (ANC) and postnatal care (PNC) continuous professional development course (CPD) was repackaged into a 3-part BL course; 1) self-directed learning (16 hours) 2) facilitated virtual sessions (2.5 hours over 3 days) and 3) 2-day f2f sessions. This study assessed the feasibility, change in healthcare providers’ knowledge and costs of the BL package in Nigeria, Tanzania, and Kenya. A mixed methods design was used. A total of 89 healthcare professionals, were purposively selected. Quantitative data was collected through an online questionnaire and skills assessments, analyzed using STATA 12 software. Qualitative data was collected through key informant interviews and focus group discussions, analysed using thematic analysis.

Majority of participants (86%) accessed the online sessions using a mobile phone from home and health facilities. The median (IQR) time of completing the self-directed component was 16 hours, IQR (8, 30). A multi-disciplinary team comprising of 42% nurse-midwives, 28% doctors, 20% clinical officers and 10% other healthcare professionals completed the BL course. Participants liked the BL approach due to its flexibility in learning, highly educative/relevant content, mixing of health worker cadres and CPD points. Aspects that were noted as challenging were related to personal log-in details and network connectivity issues during the self-directed learning and facilitated virtual sessions respectively. The blended learning approach to ANC-PNC in-service training was found to be feasible, cost saving compared to the face-to-face approach and acceptable to health care professionals in LMICs.
Understanding the social inclusion needs of people living in mental health supported accommodation
Authors: Eager Sharon , Killaspy Helen , Joanna C , Mezey Gillian , Downey Megan , Lloyd-Evans Brynmor
Published: May 2023

Objectives

To identify the social inclusion needs that were i) most commonly identified and ii) most and least commonly prioritised as support planning goals for mental health service users living in supported accommodation, using the online Social Inclusion Questionnaire User Experience (SInQUE). We qualitatively examined mental health supported accommodation staff and servicer users’ views on barriers to offering support with two less commonly prioritised areas: help finding a partner and feeling less lonely.

Methods

Anonymous SInQUE data were collected during a completed study in which we developed and tested the online SInQUE. Four focus groups were conducted with mental health supported accommodation staff (N=2) and service users (N=2).

Results

The most common social inclusion needs identified by service users (n=31) were leisure activities, finding transport options, and feeling less lonely. Of the needs identified, those that service users and staff least frequently prioritised as support planning goals were having company at mealtimes, getting one’s own furniture, feeling less lonely, help with finances, and help finding a partner. In the focus groups, staff and service users identified barriers to helping with loneliness and finding a partner which related to staff and service users themselves, supported accommodation services, and wider societal factors.
Using Random Forest feature importance results to predict zoonosis
Authors: Gonzalez Roger Geertz
Published: May 2023

This study fills a gap in the literature regarding using machine learning techniques within the field of zoonoses. Instead of using linear and logistic inference modeling like in previous (Knowledge, Attitudes, and Practices (KAP) studies, this study incorporates Random Forest (RF) to identify important features that predict zoonotic diseases using survey and blood serology data. Using RF, we found that the most important features related to zoonoses were villages where households were 46 or larger and where participants owned many animals such as ducks, cats, and pigs. Compared to previous KAP studies in other countries where ethnicity, age, and education background were important features regarding knowledge, awareness, and practices relating to zoonoses, the KAP Cambodia case was different because these features were not found to be important.
Prevalence of cardiometabolic risk factors according to urbanization level, gender and age, in apparently healthy adults living in Gabon, Central Africa
Authors: Ada Mengome Mérédith Flore , Kono Héléna Néoline , Ayo Bivigou Elsa , M’Bondoukwe Noé Patrick , Ndong Ngomo Jacques-Mari , Moutombi Ditombi Bridy , Pongui Ngondza Bedrich , Bisseye Cyrille , Mawili-Mboumba Denise Patricia , Bouyou Akotet Marielle Karine
Published: May 2023

The prevalence of cardiometabolic risk factors (CMRFs) is increasing in sub-Saharan Africa and represents a serious health issue. Specific and accurate data are required to implement prevention programs and healthcare strategies. Thus, the aim of this study was to estimate the prevalence rates of CMRFs according to the level of urbanization, age and gender in Gabon.

A cross-sectional study was conducted using the World Health Organization’s (WHO) stepwise approach for the surveillance of chronic disease risk factors. Participants over 18 years of age, without known underlying disease, from rural and urban areas of Gabon were included. Biological and behavioral data were collected using an adapted version of the standardized WHO survey questionnaire.

The median age was 38[28–50] years. Tobacco consumption was more frequent in rural areas than in urban areas (26.1% vs 6.2%;p< 0.01). Men were more likely to be smokers than women, in both settings (aOR: 8.0[4.9-13.5],p< 0.01). Excessive alcohol consumption (19.4% vs 9.6%;p< 0.01) predominated in rural than in urban areas. Urban dwellers were less physically active than rural people (29.5% vs 16.3%;p< 0.01). In total, 79.9% of participants aged under 54 years had a high blood pressure (HBP) while 10.6% of the younger participants had pre-hypertension. Metabolic syndrome was higher in women (21.7% vs 10.0%;p< 0.01) than in men. Furthermore, 6.4% of men and 2.5% of women had a high risk of developing coronary heart diseases in the next 10 years (p= 0.03). Finally, 54.0% of the study population had three or four risk factors.

The prevalence rates of CMRFs were high in the study population. Disparities were observed according to urban and rural areas, gender and age groups. National prevention and healthcare strategies for cardiometabolic diseases in Gabon should take into account these observed differences.
Using comprehensive disease modeling to assess the burden of substandard and falsified oxytocin in Kenya
Authors: Zaraa Sabra , Carlson Josh J , Vodicka Elisabeth , Stergachis Andy
Published: May 2023

BACKGROUND

Substandard and falsified (SF) oxytocin threatens the health of pregnant patients, resulting in prolonged illness and severe avertable disease outcomes. Additionally, SF oxytocin leads to an economic burden on the healthcare system and society due to increased treatment costs and productivity losses from sickness and premature death. While oxytocin is widely accessible, there are concerns about its quality and the burden of SF oxytocin remains understudied.

OBJECTIVE

To develop an impact model to estimate the health and economic burden of SF oxytocin in Kenya. This paper presents the methodology and the findings of assessing SF oxytocin in Kenya.

METHODS

A decision tree model was developed to compare health outcomes and costs with and without SF oxytocin from a healthcare sector and societal perspective. This model incorporates healthcare seeking behavior, epidemiological parameters, medicine quality, health outcomes and costs. The main assumption of the model is that lower active pharmaceutical ingredient (API) percentage results in lower medicine efficacy. Sensitivity analyses were performed to evaluate parameter uncertainty.

FINDINGS

For 1.1 million pregnant patients delivering in a healthcare facility in Kenya and a 7% prevalence of oxytocin with 75%-90% API, the model estimates that the presence of SF oxytocin in Kenya is associated with 1,484 additional cases of mild PPH, 583 additional cases of severe PPH, 15 hysterectomies, 32 deaths, 633 DALYs accrued, 560 QALYs lost, and 594 years of life lost yearly. The economic burden of SF oxytocin was $1,970,013 USD from a societal perspective, including $1,219,895 from the healthcare sector perspective. Productivity losses included $12,069 due to missed days of work and $725,979 due to premature death.

CONCLUSIONS

By providing local estimates on the burden of SF medicines, the model can inform key policy makers on the magnitude of their impact and support initiatives that facilitate greater access to quality medicines.
COMMON ADOLESCENT MENTAL HEALTH DISORDERS SEEN IN FAMILY MEDICINE CLINICS IN GHANA AND NIGERIA
Authors: Kumbet JS , Oseni TIA , Mensah-Bonsu M , Damagum FM , Opare-Lokko EA , Namisango E , Olawumi AL , Ephraim OC , Aweh B
Published: May 2023

Background

Mental health disorders among adolescents is on the rise globally. For fear of stigmatization, patients seldom present to mental health physicians. They are mostly picked during consultations with Family Physicians. This study seeks to evaluate the common mental health disorders seen by family Physicians in Family Medicine Clinics in Nigeria and Ghana.

Methodology

A descriptive cross-sectional study involving 302 Physicians practicing in Family Medicine Clinics in Nigeria and Ghana who were randomly selected for the study. Data were collected using self-administered semi-structured questionnaire, and were entered into excel spreadsheet before analysing with IBM-SPSS version 22. Descriptive statistics using frequencies and percentages was used to describe variables. Ethical approval was obtained prior to commencement of the study.

Results

Of the 302 Physicians recruited for the study, only 233 completed the study, in which 168 (72.1%) practiced in Nigeria and 65 (27.9%) in Ghana. They were mostly in urban communities (77.3%) and tertiary health facilities (65.2%). Over 90% of Family Medicine practitioners attended to adolescents with mental health issues with over 70% of them seeing at least 2 adolescents with mental health issues every year. The burden of mental health disorder was 16% and the common mental health disorders seen were depression (59.2%), Bipolar Affective Disorder (55.8%), Epilepsy (51.9%) and Substance Abuse Disorder (44.2%).

Conclusion

Family Physicians in Nigeria and Ghana attend to a good number of adolescents with mental health disorders in their Family Medicine clinics. There is the need for Family Physicians to have specialized training and retraining to be able to recognize and treat adolescent mental health disorders. This will help reduce stigmatization and improve the management of the disease thus reducing the burden.
Real-time heart rate variability according to ambulatory glucose profile in patients with diabetes mellitus
Authors: Im Sung Il , Bae Su Hyun , Kim Soo Jin , Kim Bong Joon , Heo Jung Ho , Kwon Su kyoung , Cho Sung Pil , Shim Hun , Park Jung Hwan , Kim Hyun Su , Oak Chul Ho
Published: May 2023

Background

Autonomic neuropathy commonly occurs as a long-term complication of diabetes mellitus (DM) and can be diagnosed based on heart rate variability (HRV), calculated from electrocardiogram (ECG) recordings. There are limited data on HRV using real-time ECG and ambulatory glucose monitoring in patients with DM.

Methods and Results

A total of 43 patients (66.3±7.5 years) with DM underwent continuous real-time ECG monitoring (225.7±107.3 hours) for HRV and ambulatory glucose monitoring using a remote monitoring system. We compared the HRV according to the ambulatory glucose profile. Data were analyzed according to the target in glucose range (TIR). There were no significant differences in the baseline characteristics of the patients according to the TIR. During monitoring, we checked ECG and ambulatory glucose levels (a total of 15,090 times) simultaneously for all patients. Both time- and frequency-domain HRVs were lower when the patients had poorly controlled glucose levels (>200 mg/dL) and TIR<70% compared with normally controlled glucose levels (<200 mg/dL) and TIR>70%. In addition, heart and respiratory rates increased with real-time glucose levels (P<0.001).

Conclusions

Poorly controlled glucose levels were independently associated with lower HRV in patients with DM. This was further substantiated by the independent continuous association between real-time measurements of hyperglycemia and lower HRV. These data strongly suggest that cardiac autonomic dysfunction is caused by elevated blood sugar levels.
Behavioral Paradigm for the Evaluation of Stimulation-Evoked Somatosensory Perception Thresholds in Rats
Authors: Smith Thomas J. , Wu Yupeng , Cheon Claire , Khan Arlin A. , Srinivasan Hari , Capadona Jeffrey R. , Cogan Stuart F. , Pancrazio Joseph J. , Engineer Crystal T. , Hernandez-Reynoso Ana G.
Published: May 2023

Intracortical microstimulation (ICMS) of the somatosensory cortex via penetrating microelectrode arrays (MEAs) can evoke cutaneous and proprioceptive sensations for restoration of perception in individuals with spinal cord injuries. However, ICMS current amplitudes needed to evoke these sensory percepts tend to change over time following implantation. Animal models have been used to investigate the mechanisms by which these changes occur and aid in the development of new engineering strategies to mitigate such changes. Non-human primates are commonly the animal of choice for investigating ICMS, but ethical concerns exist regarding their use. Rodents are a preferred animal model due to their availability, affordability, and ease of handling, but there are limited choices of behavioral tasks for investigating ICMS. In this study, we investigated the application of an innovative behavioral go/no-go paradigm capable of estimating ICMS-evoked sensory perception thresholds in freely moving rats. We divided animals into two groups, one receiving ICMS and a control group receiving auditory tones. Then, we trained the animals to nose-poke – a well-established behavioral task for rats – following either a suprathreshold ICMS current-controlled pulse train or frequency-controlled auditory tone. Animals received a sugar pellet reward when nose-poking correctly. When nose-poking incorrectly, animals received a mild air puff. After animals became proficient in this task, as defined by accuracy, precision, and other performance metrics, they continued to the next phase for perception threshold detection, where we varied the ICMS amplitude using a modified staircase method. Finally, we used non-linear regression to estimate perception thresholds.

Results indicated that our behavioral protocol could estimate ICMS perception thresholds based on ∼95% accuracy of rat nose-poke responses to the conditioned stimulus. This behavioral paradigm provides a robust methodology for evaluating stimulation-evoked somatosensory percepts in rats comparable to the evaluation of auditory percepts. In future studies, this validated methodology can be used to study the performance of novel MEA device technologies on ICMS-evoked perception threshold stability using freely moving rats or to investigate information processing principles in neural circuits related to sensory perception discrimination.
Regulatory network structure and environmental signals constrain transcription factor innovation
Authors: Shepherd Matthew J. , Reynolds Mitchell , Pierce Aidan P. , Rice Alan M. , Taylor Tiffany B.
Published: May 2023

Evolutionary innovation of transcription factors frequently drives phenotypic diversification and adaptation to environmental change. Rewiring – that is gaining or losing connections to transcriptional target genes – is a key mechanism by which transcription factors evolve and innovate. However the frequency of functional adaptation varies between different regulators, even when they are closely related. To identify factors influencing propensity for rewiring, we utilise aPseudomonas fluorescensSBW25 strain rendered incapable of flagellar mediated motility in soft-agar plates via deletion of the flagellar master regulator (fleQ). This bacterium can evolve to rescue flagellar motility via gene regulatory network rewiring of an alternative transcription factor to rescue activity of FleQ. Previously, we have identified two members (out of 22) of the RpoN-dependent enhancer binding protein (RpoN-EBP) family of transcription factors (NtrC and PFLU1132) that are capable of innovating in this way. These two transcription factors rewire repeatably and reliably in a strict hierarchy – with NtrC the only evolved rewiring route in a ΔfleQbackground, and PFLU1132 the only evolved rewiring route in a ΔfleQΔntrCbackground. However, why other members in the same transcription factor family have not been observed to rescue flagellar activity is unclear. Previous work shows that protein homology cannot fully explain this pattern, and mutations in rewired strains suggested high levels of transcription factor expression and activation drive rewiring. We predict that mutations that increase expression of the rewired transcription factor are vital to unlock rewiring potential. Here, we construct titratable expression mutant lines for 11 of the RpoN-EBPs inP. fluorescens. We show that in 5 additional RpoN-EBPs (HbcR, GcsR, DctD, AauR and PFLU2209), high expression levels result in different mutations conferring motility rescue, suggesting alternative rewiring pathways. Our results indicate that expression levels (and not protein homology) of RpoN-EBPs are a key constraining factor in determining rewiring potential. This suggests that transcription factors that can achieve high expression through few mutational changes, or transcription factors that are active in the selective environment, are more likely to innovate and contribute to adaptive gene regulatory network rewiring.
A bivalent ChAd nasal vaccine protects against SARS-CoV-2 BQ.1.1 and XBB.1.5 infection and disease in mice and hamsters
Authors: Ying Baoling , Darling Tamarand L. , Desai Pritesh , Liang Chieh-Yu , Dmitriev Igor P. , Soudani Nadia , Bricker Traci , Kashentseva Elena A. , Harastani Houda , Schmidt Aaron G. , Curiel David T. , Boon Adrianus C.M. , Diamond Michael S.
Published: May 2023

We previously described a nasally delivered monovalent adenoviral-vectored SARS- CoV-2 vaccine (ChAd-SARS-CoV-2-S, targeting Wuhan-1 spike [S]; iNCOVACC®) that is currently used in India as a primary or booster immunization. Here, we updated the mucosal vaccine for Omicron variants by creating ChAd-SARS-CoV-2-BA.5-S, which encodes for a pre- fusion and surface-stabilized S protein of the BA.5 strain, and then tested monovalent and bivalent vaccines for efficacy against circulating variants including BQ.1.1 and XBB.1.5. Whereas monovalent ChAd-vectored vaccines effectively induced systemic and mucosal antibody responses against matched strains, the bivalent ChAd-vectored vaccine elicited greater breadth. However, serum neutralizing antibody responses induced by both monovalent and bivalent vaccines were poor against the antigenically distant XBB.1.5 Omicron strain and did not protect in passive transfer experiments. Nonetheless, nasally delivered bivalent ChAd- vectored vaccines induced robust antibody and spike-specific memory T cell responses in the respiratory mucosa, and conferred protection against WA1/2020 D614G and Omicron variants BQ.1.1 and XBB.1.5 in the upper and lower respiratory tracts of both mice and hamsters. Our data suggest that a nasally delivered bivalent adenoviral-vectored vaccine induces protective mucosal and systemic immunity against historical and emerging SARS-CoV-2 strains without requiring high levels of serum neutralizing antibody.
ImSpiRE: Image feature-aided spatial resolution enhancement method
Authors: Hua Yuwei , Zhang Yizhi , Guo Zhenming , Bian Shan , Zhang Yong
Published: May 2023

The resolution of most spatially resolved transcriptomic technologies usually cannot attain the single-cell level, limiting their applications in biological discoveries. Here, we introduce ImSpiRE, an image feature-aided spatial resolution enhancement method forin situcapturing spatial transcriptome. Taking the information stored in histological images, ImSpiRE solves an optimal transport problem to redistribute the expression profiles of spots to construct new transcriptional profiles with enhanced resolution, together with imputing the gene expression profiles in unmeasured regions. Applications to multiple datasets confirm that ImSpiRE can enhance spatial resolution to the subspot level while contributing to the discovery of tissue domains, signaling communication patterns, and spatiotemporal characterization.
Resolving the paradox of local warning signal diversity with predator learning
Authors: Kuo Chi-Yun
Published: May 2023

Coexistence of distinct warning signals at local scales has long stood as a paradox, as selection is expected to preserve only the most common signal. So far, there has not been an explanation that is both broadly applicable and testable. This study presents a novel and generalizable resolution to this paradox (the Unforgetful Predator Hypothesis) by showing that prey displaying a rarer warning signal can persist if predators have low enough forgetting rates relative to prey generation time. In addition, inducing a high level of predator avoidance facilitates warning signal diversity when prey do not compete. In the presence of prey competition, however, warning signal diversity is more likely to occur if prey elicit intermediate levels of avoidance, such that the competitive disadvantage for individuals displaying the rare signal can be offset by predation. This hypothesis can be tested by quantifying predator avoidance and forgetting rate in laboratory and field experiments. As the level of predator avoidance is also crucial in determining the fate of rare signal in communities, I performed a meta-analysis to examine the determinants of its variation and found that higher predator avoidance can be observed in the following situations – when prey unprofitability is due to toxicity rather than mere unpalatability, when predators search widely for prey and/or prey aggregate, and when predators could differentiate between unprofitable and profitable prey using only color or pattern. In addition to resolving the paradox, these findings help inform the types of communities in which distinct warning signals can stably coexist.

Significance

Coexistence of distinct warning signals within a community represents an evolutionary paradox that still awaits a resolution that is both general and testable. I used ecologically realistic simulations to show that warning signal diversity can occur if predators have long enough memory and if prey elicit either low or moderate levels of avoidance, depending on whether they compete. A meta-analysis further shows that higher levels of predator avoidance tend to occur when unprofitable prey are highly unprofitable, when predators search widely for prey, when prey aggregate, and when prey profitability could be discerned by only color or pattern. These findings offer a testable resolution to the paradox and inform the types of communities where warning signal diversity may occur.
netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity
Authors: Li Zuqi , Melograna Federico , Hoskens Hanne , Duroux Diane , Marazita Mary L. , Walsh Susan , Weinberg Seth M. , Shriver Mark D. , Müller-Myhsok Bertram , Claes Peter , Van Steen Kristel
Published: May 2023

Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these classes. NetMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.

Author summary

In recent years, we see the increasing possibility of collecting data from multiple modalities in various fields, requesting novel methods to exploit the consensus among different data types. As exemplified in systems biology or epistasis analyses, the interactions between features may contain more information than the features themselves, thereby necessitating the use of feature networks. Furthermore, in real-life scenarios, subjects, such as patients or individuals, may originate from diverse populations, which underscores the importance of subtyping or clustering these subjects to account for their heterogeneity. In this study, we present a novel pipeline for selecting the most relevant features from multiple data types, constructing a feature network for each subject, and obtaining a subgrouping of samples informed by a phenotype of interest. We validated our method on synthetic data and demonstrated its superiority over several state-of-the-art multi-view clustering approaches. Additionally, we applied our method to a real-life, large-scale dataset of genomic data and facial images, where it effectively identified a meaningful BMI subtyping that complemented existing BMI categories and offered new biological insights. Our proposed method has wide applicability to complex multi-view or multi-omics datasets for tasks such as disease subtyping or personalized medicine.