bluuebunny/crossref_metadata_2025 huggingface dataset:
Untargeted Pixel-by-Pixel Imaging of Metabolite Ratio Pairs as a Novel Tool for Biomedical Discovery in Mass Spectrometry Imaging
Authors: Cheng Huiyong , Miller Dawson , Southwell Nneka , Porcari Paola , Fischer Joshua L. , Taylor Isobel , Michael Salbaum J. , Kappen Claudia , Hu Fenghua , Yang Cha , Keshari Kayvan R. , Gross Steven S. , D’Aurelio Marilena , Chen Qiuying
Published: January 2024

Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of metabolites across tissue cryosections. While software packages exist for pixel-by-pixel individual metabolite and limited target pairs of ratio imaging, the research community lacks an easy computing and application tool that images any metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs may contribute to the discovery of unanticipated molecules in shared metabolic pathways. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling, markedly enhances spatial image contrast, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent hypothesis generation tool to enhance knowledge obtained from current spatial metabolite profiling technologies.
A Scoping Review on Influence of Socioeconomic Status on Antenatal Care Utilization and Pregnancy Outcomes in Sub-Saharan Africa
Authors: Esther Adeyemo Queen , Yahaya Haphsheitu , Esther Ajayi O. , Aboagye-Mensah Priscilla , Blessing Adeyemo J. , Ikome Theckla E.
Published: January 2024

Maternal and perinatal mortality are the most adverse pregnancy outcomes of public health concerns. Although, slowly declining, Sub-Saharan Africa (SSA), has been reported as one of the regions with the highest incidence globally. Regions in SSA where these problems are prominent have been reported to have poor access to antenatal care services. Since socioeconomic factors are major factors influencing the use of antenatal care services and pregnancy outcomes. This study, therefore, aimed to explore the socioeconomic determinants of antenatal care utilization and pregnancy outcomes in Sub-Saharan countries. Studies were systematically searched using credible search engines, whereby 82 studies based on the selection criteria from eight countries with reported maximum burden of study were found. Consistently across all reviewed studies, poor socioeconomic status was a significant determinant of Antenatal care utilization thus leading to poor pregnancy outcomes, particularly, low income, and education. The impact of occupation on the other hand has been poorly studied. Poor socioeconomic factors also limit the use of antenatal care services, increasing the burden of the deaths. The study therefore submits that, interventions, and policies to reduce maternal and perinatal mortality should focus on improving pregnant women’s’ lives by improving access to antenatal care services pre- and postnatal period.
Picturing plant biodiversity from airborne environmental DNA
Authors: Thuillet Anne-Céline , Morisot Didier , Renno Jean-François , Scarcelli Nora , Serret Julien , Mariac Cédric
Published: January 2024

While eDNA approaches have gained interest over the past decades all types of organisms have not been addressed evenly. In particular terrestrial plants have been the subject of less attention. Here we address the possibility to represent plant biodiversity from airborne environmental DNA (eDNA) sampling and metabarcoding. We collected air using a biological air sampler in the Botanical Garden of Montpellier (France) and compared the list of revealed plant species to the botanical inventory of the Garden. Ninety-two plant species could be detected from three sampling points across the 4,6 ha of the Garden, after one hour sampling allowing to filter 9 m3of air. We recorded the plants carrying flowers at the time of the experiment, which allowed us to estimate that plants flowering at the time of the sampling could be detected 10 times more easily than plants that were not, given the number of plants carrying flowers. However, flowering is far from being required as a vast majority of plants still was detected without flowering. We also show that not all species orders are detected with the same probability, tree species being better represented in the sample than herbal plants, given the number of trees present in the garden. Finally using diagnostic species, present only once in the garden, we estimate that the maximum sampling distance allowed by the biological air sampler is at least 110 m. Our study underlines that air sampling is a promising method for monitoring terrestrial plant biodiversity and highlights the parameters that should be adjusted to optimize the approach.
Mapping planktonic communities: a network approach to assess the role of scale and centrality on their diversity and composition
Authors: Cunillera-Montcusí David , Bengtsson Mia , Matthews Blake , Preiler Christian , Horváth Zsófia , Vad Csaba F. , Ptacnik Robert
Published: January 2024

The distribution of habitats across a landscape and their centrality gradient are key elements defining the effective pathways of dispersal, and thus of metacommunity assembly. Understanding how centrality shapes diversity patterns is essential for predicting the impact of future landscape changes on diversity. While alpine lakes have been extensively studied, often considering the fluvial network as a potential landscape, small planktonic communities have frequently been overlooked as potential dispersers due to their assumed ubiquity. In this study, we investigate the diversity patterns of alpine lake planktonic communities along lake networks constructed at different scales, ranging from 6.5 to 650 km and the fluvial network. We sampled 55 lakes in the northern Alps (16S, 18S, phytoplankton and zooplankton) and calculated several diversity metrics (alpha, beta diversity and LCBD) and multivariate analysis. We then constructed several networks responding to different scales, determined their centrality gradients, and finally explored their relationship with the diversity of each planktonic group. We expected that a groups’ diversity would relate differently across scales based on body size, but the outcomes were varied. Bacterioplankton and zooplankton diversity were both affected across scales higher than 100 km, whereas phytoplankton appeared completely unrelated to centrality. Nonetheless, we could observe that when significant, the relationships between diversity and centrality were shared among organisms. These findings not only underscore that planktonic organisms are influenced by landscape configurations larger than the fluvial system but also emphasise the critical role of dispersal for these groups and the scales at which it impacts metacommunity assembly.

Significance statement

While dispersal is widely recognized as a key driver of assembly, some groups and systems remain insufficiently explored to fully grasp the impact of landscape and dispersal on their assembly. Planktonic communities have traditionally been considered ubiquitous and detached from regional-level structure, primarily due to their small size, leading to the notion that “everything is everywhere”. Additionally, alpine lake communities have traditionally been perceived as solely connected through fluvial systems. In this study, we challenge these notions by demonstrating how planktonic communities are indeed influenced by the relative positioning of lakes in the landscape, with significant impacts occurring at larger scales, spanning hundreds of kilometres. However, not all planktonic groups responded uniformly to the analysed factors, emphasizing the marked differences among groups and the diverging drivers shaping planktonic metacommunities.
Integrative analysis in head and neck cancer reveals distinct role of miRNome and methylome as tumour epigenetic drivers
Authors: Mandić Katarina , Milutin Gašperov Nina , Božinović Ksenija , Dediol Emil , Krasić Jure , Sinčić Nino , Grce Magdalena , Sabol Ivan , Barešić Anja
Published: January 2024

Background

Head and neck cancer is the sixth most common malignancy worldwide, with the relatively low 5-year survival rate, mainly because it is diagnosed at a late stage. Infection with HPV is well known etiology, which affects nature of these cancers and patients’ survival. Besides, it is considered that the main driving force for this type of cancer could be epigenetics. In this study we aimed to find potential epigenetic biomarkers, by integrating miRNome, methylome, and transcriptome analyses.

Methods

From the fresh head and neck cancer tissue samples, we chose a group for miRNome, methylome and transcriptome profiling, in comparison to adequate control samples. Bioinformatics analyses are performed in R v4.2.2. Count normalization and group differential expression for mRNA and the previously obtained miRNA count data was performed with DESeq2 v1.36. Gene set enrichment analysis was performed and visualized using gProfiler2 v0.2.1 Identification of miRNA targets was performed by querying in miRTarBase using multiMiR v1.18.0. Annotation of CpG sites merging into islands was obtained from RnBeads.hg19 v1.28.0. package. For the integrative analysis we performed kmeans clustering using stats v4.2.2 package, using 8-12 clusters and nstart 100.

Results

We found that transcriptome analysis divides samples into cancers and controls clusters, with no relation to HPV status or cancer anatomical location. Differently expressed genes (n=2781) were predominantly associated with signaling pathways of tumour progression. We identified a cluster of genes under control of the transcription factor E2F, that are significantly underexpressed in cancer tissue, as well as T cell immunity genes and genes related to regulation of transcription. Among overexpressed genes in tumours we found those that belong to cell cycle regulation and vasculature. A small number of genes were found significantly differently expressed in HPV positive versus HPV negative tumours (for example NEFH, ZFR2, TAF7L, ZNF541, and TYMS).

Conclusions

In this comprehensive study on an overlapping set of samples where the integration of miRNome, methylome and transcriptome analysis were performed for head and neck cancer, we demonstrated that the majority of genes were associated exclusively with miRNome or methylome and, to a lesser extent, under control of both epigenetic mechanisms.
A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data
Authors: Zingaro Alberto , Ahmad Zan , Kholmovski Eugene , Sakata Kensuke , Dede’ Luca , Morris Alan K. , Quarteroni Alfio , Trayanova Natalia A.
Published: January 2024

Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the CHA2DS2-VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments.
Obesity Facilitates Sex-Specific Improvement In Cognition And Neuronal Function In A Rat Model Of Alzheimer’s Disease
Authors: Lai Aaron Y. , Almanza Dustin Loren V. , Ribeiro Jessica A. , Hill Mary E. , Mandrozos Matthew , Koletar Margaret M. , Stefanovic Bojana , McLaurin JoAnne
Published: January 2024

Obesity reduces or increases the risk of developing Alzheimer’s disease (AD) depending on whether it is assessed in mid-life or late-life. There is currently no consensus on the relationship between obesity and AD or the mechanism or their interaction. Here, we aim to differentiate the cause-and-effect relationship between obesity and AD in a controlled rat model of AD. We induced obesity in 9-month-old TgF344-AD rats, that is pathology-load wise similar to early symptomatic phase of human AD. To more accurately model human obesity, we fed both TgF344-AD and non-transgenic littermates a varied high-carbohydrate-high-fat diet consisting of human food for 3 months. Obesity increased overall glucose metabolism and slowed cognitive decline in TgF344-AD rats, specifically executive function, without affecting non-transgenic rats. Pathological analyses of prefrontal cortex and hippocampus showed that obesity in TgF344-AD rats produced varied effects, with increased density of myelin and oligodendrocytes, lowered density and activation of microglia that we propose contributes to the cognitive improvement. However, obesity also decreased neuronal density, and promoted deposition of amyloid-beta plaques and tau inclusions. After 6 months on the high-carbohydrate-high-fat diet, detrimental effects on density of neurons, amyloid-beta plaques, and tau inclusions persisted while the beneficial effects on myelin, microglia, and cognitive functions remained albeit with a lower effect size. By examining the effect of sex, we found that both beneficial and detrimental effects of obesity were stronger in female TgF344-AD rats indicating that obesity during early symptomatic phase of AD is protective in females.
Intense storms affect sinking particle fluxes after the North Atlantic diatom spring bloom
Authors: Romanelli Elisa , Giering Sarah Lou Carolin , Estapa Margaret , Siegel David A. , Passow Uta
Published: January 2024

The sinking of large particles (i.e., marine snow) has long been recognized as a key pathway for efficient particulate organic carbon (POC) export to the ocean interior during the decline of spring diatom blooms. Recent work has suggested that particles smaller than marine snow can also substantially contribute to POC export. However, a detailed characterization of small and large sinking particles at the end of blooms is missing. Here, we separately collected suspended and small and large sinking particles using Marine Snow Catchers and assessed their biogeochemical composition after the North Atlantic spring bloom in May 2021. During the three weeks of sampling, when four intense storms (maximum wind speeds 37 – 50 kts) created high turbulent energy dissipation rates and deepened the mixed layer, we observed two distinct sedimentation episodes. During the storm periods, sinking particles were dominated by small (diameter < 0.1 mm), slow-sinking (~18 m d−1), silica-rich particles that carried a moderate POC flux (< 6 mmol C m−2d−1) to 500 m depth. Once the storms ceased, the volume of large (diameter > 0.1 mm), fast-sinking (> 75 m d−1), carbon-rich marine snow aggregates (not fecal pellets) increased exponentially and POC fluxes at 100 m depth were more than fourfold greater (30±12 mmol C m−2d−1) than those during the previous event. The aggregates consisted of a mixed post-bloom plankton community. Our data suggest that the intense storms determined the timing, type, and magnitude of POC flux at the end of a spring phytoplankton bloom.
Existence and Stability Criteria for Global Synchrony and for Synchrony in two Alternating Clusters of Pulse-Coupled Oscillators Updated to Include Conduction Delays
Authors: Vedururu Srinivas Ananth , Canavier Carmen C.
Published: January 2024

Phase Response Curves (PRCs) have been useful in determining and analyzing various phase-locking modes in networks of oscillators under pulse-coupling assumptions, as reviewed in Mathematical Biosciences, 226:77-96, 2010. Here, we update that review to include progress since 2010 on pulse coupled oscillators with conduction delays. We then present original results that extend the derivation of the criteria for stability of global synchrony in networks of pulse-coupled oscillators to include conduction delays. We also incorporate conduction delays to extend previous studies that showed how an alternating firing pattern between two synchronized clusters could enforce within cluster synchrony, even for clusters unable to synchronize themselves in isolation. To obtain these results, we used self-connected neurons to represent clusters. These results greatly extend the applicability of the stability analyses to networks of pulse-coupled oscillators since conduction delays are ubiquitous and strongly impact the stability of synchrony. Although these analyses only strictly apply to identical oscillators with identical connections to other oscillators, the principles are general and suggest how to promote or impede synchrony in physiological networks of neurons, for example. Heterogeneity can be interpreted as a form of frozen noise, and approximate synchrony can be sustained despite heterogeneity. The pulse-coupled oscillator model can not only be used to describe biological neuronal networks but also cardiac pacemakers, lasers, fireflies, artificial neural networks, social self-organization, and wireless sensor networks.

AMS Subject Classification

37N25, 39A06, 39A30, 92B25, 92C20
Klebsiella pneumoniaeexhibiting a phenotypic hyper-splitting phenomenon including the formation of small colony variants
Authors: Doğan Eyüp , Sydow Katharina , Heiden Stefan E. , Eger Elias , Wassilew Georgi , Proctor Richard A. , Bohnert Jürgen A. , Idelevich Evgeny A. , Schaufler Katharina , Becker Karsten
Published: January 2024

In this study, we characterized aKlebsiella pneumoniaestrain in a patient with shrapnel hip injury, which resulted in multiple phenotypic changes, including the formation of a small colony variant (SCV) phenotype. Although already described since the 1960s, there is little knowledge about SCV phenotypes inEnterobacteriaceae. The formation of SCVs has been recognized as a bacterial strategy to evade host immune responses and compromise the efficacy of antimicrobial therapies, leading to persistent and recurrent courses of infections. In this case, 14 different, clonally identical resisto- and morpho-types were distinguished from the patient’s urine and tissue samples. Whole genome sequencing revealed theK. pneumoniaehigh-risk clonal lineage belonging to sequence type 147. Subculturing the SCV colonies consistently resulted in the reappearance of the initial SCV phenotype and three stable normal-sized phenotypes with distinct morphological characteristics. Additionally, an increase in resistance was observed over time in isolates that shared the same colony appearance. Our findings highlight the complexity of bacterial behavior by revealing a case of phenotypic “hyper-splitting” in aK. pneumoniaeSCV and its potential clinical significance.
Neuronal subtypes and connectivity of the adult mouse paralaminar amygdala
Authors: Saxon David , Alderman Pia J , Sorrells Shawn F , Vicini Stefano , Corbin Joshua G
Published: January 2024

The paralaminar nucleus of the amygdala (PL) is comprised of neurons which exhibit delayed maturation. PL neurons are born during gestation but mature during adolescent ages, differentiating into excitatory neurons. The PL is prominent in the adult amygdala, contributing to its increased neuron number and relative size compared to childhood. However, the function of the PL is unknown, as the region has only recently begun to be characterized in detail. In this study, we investigated key defining features of the adult PL; the intrinsic morpho-electric properties of its neurons, and its input and output connectivity. We identify two subtypes of excitatory neurons in the PL based on unsupervised clustering of electrophysiological properties. These subtypes are defined by differential action potential firing properties and dendritic architecture, suggesting divergent functional roles. We further uncover major axonal inputs to the adult PL from the main olfactory network and basolateral amygdala. We also find that axonal outputs from the PL project reciprocally to major inputs, and to diverse targets including the amygdala, frontal cortex, hippocampus, hypothalamus, and brainstem. Thus, the adult PL is centrally placed to play a major role in the integration of olfactory sensory information, likely coordinating affective and autonomic behavioral responses to salient odor stimuli.

Significance Statement

Mammalian amygdala development includes a growth period from childhood to adulthood, believed to support emotional and social learning. This amygdala growth is partly due to the maturation of neurons during adolescence in the paralaminar amygdala. However, the functional properties of these neurons are unknown. In our recent studies, we characterized the paralaminar amygdala in the mouse. Here, we investigate the properties of the adult PL in the mouse, revealing the existence of two neuronal subtypes that may play distinct functional roles in the adult brain. We further reveal the brain-wide input and output connectivity of the PL, indicating that the PL combines olfactory cues for emotional processing and delivers information to regions associated with reward and autonomic states.
The novel linkage betweenFuzandGpr161genes regulates sonic hedgehog signaling during mouse embryonic development
Authors: Kim Sung-Eun , Kim Hyun Yi , Wlodarczyk Bogdan J. , Finnell Richard H.
Published: January 2024

Sonic hedgehog (Shh) signaling regulates embryonic morphogenesis utilizing primary cilia, the cell antenna acting as a signaling hub. Fuz, an effector of planar cell polarity (PCP) signaling, involves Shh signaling via cilia formation, while the G protein-coupled receptor 161 (Gpr161) is a negative regulator of Shh signaling. The range of phenotypic malformations observed in mice bearing mutations in either of these two genes is similar; however, their functional relations have not been previously explored. This study identified the genetic and biochemical link between Fuz and Gpr161 in mouse embryonic development.Fuzwas genetically epistatic toGpr161via Shh signaling during mouse embryonic development. The FUZ biochemically interacted with GPR161, and Fuz regulated Gpr161 ciliary trafficking via β-arrestin2. Our study suggested the novel Gpr161-Fuz axis that regulates Shh signaling during mouse embryonic development.

Summary statement

This study illuminates the novel genetic and biochemical linkages between Fuz and Gpr161 to regulate sonic hedgehog signaling during mouse embryonic development.
Cell-type-specific origins of locomotor rhythmicity at different speeds in larval zebrafish
Authors: Agha Moneeza A. , Kishore Sandeep , McLean David L.
Published: January 2024

Different speeds of locomotion require heterogeneous spinal populations, but a common mode of rhythm generation is presumed to exist. Here, we explore the cellular versus synaptic origins of spinal rhythmicity at different speeds by performing electrophysiological recordings from premotor excitatory interneurons in larval zebrafish. Chx10-labeled V2a neurons are divided into at least two morphological subtypes proposed to play distinct roles in timing and intensity control. Consistent with distinct rhythm generating and output patterning functions within the spinal V2a population, we find that descending subtypes are recruited exclusively at slow or fast speeds and exhibit intrinsic cellular properties suitable for rhythmogenesis at those speeds, while bifurcating subtypes are recruited more reliably at all speeds and lack appropriate rhythmogenic cellular properties. Unexpectedly, however, phasic firing patterns during locomotion in rhythmogenic and non-rhythmogenic V2a neurons alike are best explained by distinct modes of synaptic inhibition linked to cell-type and speed. At fast speeds reciprocal inhibition in descending V2a neurons supports phasic firing, while recurrent inhibition in bifurcating V2a neurons helps pattern motor output. In contrast, at slow speeds recurrent inhibition in descending V2a neurons supports phasic firing, while bifurcating V2a neurons rely on reciprocal inhibition alone to pattern output. Our findings suggest cell-type-specific, not common, modes of rhythmogenesis generate and coordinate different speeds of locomotion.
Mathematical Modeling of Drug Delivery from Bi-Layered Core-Shell Polymeric Microspheres
Authors: Ruiz Eduardo A. Chacin , Carpenter Samantha L. , Swindle-Reilly Katelyn E. , Versypt Ashlee N. Ford
Published: January 2024

Chronic diseases usually require repetitive dosing. Depending on factors such as dosing frequency, mode of administration, and associated costs this can result in poor patient compliance. A better alternative involves using drug delivery systems to reduce the frequency of dosing and extend drug release. However, reaching the market stage is a time-consuming process. In this study, we used two numerical approaches for estimating the values of the critical parameters that govern the diffusion-controlled drug release within bilayered core-shell microspheres. Specifically, the estimated parameters include burst release, drug diffusion coefficient in two polymers, and the drug partition coefficient. Estimating these parameters provides insight for optimizing device design, guiding experimental efforts, and improving the device’s effectiveness. We obtained good agreement between the models and the experimental data. The methods explored in this work apply not only to bi-layered spherical systems but can also be extended to multi-layered spherical systems.
Sonic restoration: Acoustic stimulation enhances soil fungal biomass and activity of plant growth-promoting fungi
Authors: Robinson Jake M. , Cando-Dumancela Christian , Breed Martin F.
Published: January 2024

Ecosystem restoration interventions often utilise visible elements to restore an ecosystem (e.g., replanting native plant communities and reintroducing lost species). However, using acoustic stimulation to restore ecosystems has received little attention. Our study aimed to (a) investigate the potential effects of acoustic stimulation on fungal biomass and organic matter decomposition, which are both crucial components of ecosystem functioning and (b) assess the effect of acoustic stimulation on the growth rate and sporulation of the plant growth-promoting fungusTrichoderma harzianum. We played 70 dB and 90 dB soundscape treatments (@ 8 kHz) to green and rooibos teabags in compost in experimental mesocosms for 8 hours per day for 14 days to test whether acoustic stimulation affected fungal biomass and organic matter decomposition (a control mesocosm received only ambient sound stimulation <30 dB). We played a monotone soundscape (80 dB @ 8 kHz) over five days toTrichoderma harzianumto assess whether this stimulation affected the growth rate and sporulation of this fungus (control samples received only ambient sound stimulation <30 dB). We show that the acoustic stimulation treatments resulted in increased fungal biomass, greater decomposition, and enhancedT. harzianumconidia (spore) activity compared to controls. These results indicate that acoustic stimulation influences soil fungal growth and potentially facilitates their functioning. A piezoelectric effect and/or fungal mechanoreceptor stimulation are possible mechanisms. Our study highlights the potential of acoustic stimulation to alter important functional soil components, which could, with further development, be harnessed to aid ecosystem restoration.
Do People Reduce Attempts At Lifestyle Change After Initiating Weight Loss Medication? A Review Of Trial Evidence
Authors: Macfarlane Megan , Cooper David , Avenell Alison
Published: January 2024

Anti-obesity medications (AOMs) are used with lifestyle change support for weight management for adults with obesity. We investigated whether initiation of AOMs appeared to reduce attempted lifestyle changes. We searched for orlistat, liraglutide, semaglutide, and low-fat reducing diet (LFRD) trials in a trial register, Medline, Embase and systematic reviews from 1990 to June 2023. Weight changes in placebo groups of AOM trials with lifestyle interventions were compared to weight changes in LFRD trials. 16 orlistat, 7 liraglutide, 5 semaglutide, and 7 LFRD trials were included. Weight loss in orlistat placebo groups was 1.1kg less than LFRDs, a statistically non-significant difference, where last observation carried forward values were used for missing data in trials. Adjustment with baseline observation carried forward found 2.6kg less weight lost, a significant difference. Last observation carried forward data for orlistat trials providing completer data found a 0.2kg difference.

Liraglutide placebo groups had 2.1kg less weight lost than predicted from LFRD trials. Semaglutide placebo groups had 2.0kg less weight loss.

Compensatory reductions in changes to lifestyle behaviours may result following AOM initiation, but this needs to be explored further. Variability in trial design and study populations may contribute to the differences in weight change found.
Lethal phenotypes in Mendelian disorders
Authors: Cacheiro Pilar , Lawson Samantha , Van den Veyver Ignatia B. , Marengo Gabriel , Zocche David , Murray Stephen A. , Duyzend Michael , Robinson Peter N. , Smedley Damian
Published: January 2024

Essential genes are those whose function is required for cell proliferation and/or organism survival. A gene’s intolerance to loss-of-function can be allocated within a spectrum, as opposed to being considered a binary feature, since this function might be essential at different stages of development, genetic backgrounds or other contexts. Existing resources that collect and characterise the essentiality status of genes are based on either proliferation assessment in human cell lines, embryonic and postnatal viability evaluation in different model organisms, and gene metrics such as intolerance to variation scores derived from human population sequencing studies. There are also several repositories available that document phenotypic annotations for rare disorders in humans such as the Online Mendelian Inheritance in Man (OMIM) and the Human Phenotype Ontology (HPO) knowledgebases. This raises the prospect of being able to use clinical data, including lethality as the most severe phenotypic manifestation, to further our characterisation of gene essentiality. Here we queried OMIM for terms related to lethality and classified all Mendelian genes into categories, according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. To showcase this curated catalogue of human essential genes, we developed the Lethal Phenotypes Portal (https://lethalphenotypes.research.its.qmul.ac.uk), where we also explore the relationships between these lethality categories, constraint metrics and viability in cell lines and mouse. Further analysis of the genes in these categories reveals differences in the mode of inheritance of the associated disorders, physiological systems affected and disease class. We highlight how the phenotypic similarity between genes in the same lethality category combined with gene family/group information can be used for novel disease gene discovery. Finally, we explore the overlaps and discrepancies between the lethal phenotypes observed in mouse and human and discuss potential explanations that include differences in transcriptional regulation, functional compensation and molecular disease mechanisms. We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.
Artificial intelligence-based automated left ventricular mass quantification from non-contrast cardiac CT scans: correlation with contrast CT and cardiac MRI
Authors: Han Donghee , Shanbhag Aakash , Miller Robert JH , Kwok Nicholas , Waechter Parker , Builoff Valerie , Newby David E , Dey Damini , Berman Daniel S , Slomka Piotr
Published: January 2024

Background

Non-contrast CT scans are not used for evaluating left ventricle myocardial mass (LV mass), which is typically evaluated with contrast CT or cardiovascular magnetic resonance imaging (MRI). We assessed the feasibility of LV mass estimation from standard, ECG-gated, non-contrast CT using an artificial intelligence (AI) approach and compare it with coronary CT angiography (CTA) and cardiac MRI.

Methods

We enrolled consecutive patients who underwent coronary CTA, which included non-contrast CT calcium scanning and contrast CTA, and cardiac MRI. The median interval between coronary CTA and MRI was 22 days (IQR: 3-76). We utilized an nn-Unet AI model that automatically segmented non-contrast CT structures. AI measurement of LV mass was compared to contrast CTA and MRI.

Results

A total of 316 patients (Age: 57.1±16.7, 56% male) were included. The AI segmentation took on average 22 seconds per case. An excellent correlation was observed between AI and contrast CTA LV mass measures (r=0.84, p<0.001), with no significant differences (136.5±55.3 vs. 139.6±56.9 g, p=0.133). Bland-Altman analysis showed minimal bias of 2.9. When compared to MRI, measured LV mass was higher with AI (136.5±55.3 vs. 127.1±53.1 g, p<0.001). There was an excellent correlation between AI and MRI (r=0.85, p<0.001), with a small bias (−9.4). There were no statistical differences between the correlations of LV mass between contrast CTA and MRI, or AI and MRI.

Conclusions

The AI-based automated estimation of LV mass from non-contrast CT demonstrated excellent correlations and minimal biases when compared to contrast CTA and MRI.
Methylation profiles at birth linked to early childhood obesity
Authors: Lariviere Delphine , Craig Sarah J.C. , Paul Ian M. , Hohman Emily E. , Savage Jennifer S. , Wright Robert O. , Chiaromonte Francesca , Makova Kateryna D. , Reimherr Matthew L.
Published: January 2024

Childhood obesity represents a significant global health concern and identifying risk factors is crucial for developing intervention programs. Many ‘omics’ factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months. We characterized genome-wide DNA methylation profiles using the Illumina Infinium MethylationEpic chip, and incorporated information on child and maternal health, and various environmental factors into the analysis. We used regression analysis to identify genes with methylation profiles most predictive of infant weight outcomes, finding a total of 23 relevant genes in cord blood and 10 in placenta. Notably, in cord blood, the methylation profiles of three genes (PLIN4, UBE2F,andPPP1R16B) were associated with all three weight outcomes, which are also associated with weight outcomes in an independent cohort suggesting a strong relationship with weight trajectories in the first six months after birth. Additionally, we developed a Methylation Risk Score (MRS) that could be used to identify children most at risk for developing childhood obesity. While many of the genes identified by our analysis have been associated with weight-related traits (e.g., glucose metabolism, BMI, or hip-to-waist ratio) in previous genome-wide association and variant studies, our analysis implicated several others, whose involvement in the obesity phenotype should be evaluated in future functional investigations.
PrimateAI-3D outperforms AlphaMissense in real-world cohorts
Authors: Parry David A. , Bosc Tom , Hamp Tobias , Fiziev Petko P. , Sharma Abhishek , Kassam Irfahan , McRae Jeremy , Farh Kyle Kai-How
Published: January 2024

Accurately predicting the impact of genetic variants is essential for interpreting genomic data, yet no consensus exists on how to measure classifier performance. We prepared the most comprehensive set of benchmarks to date and applied them to the recently published models PrimateAI-3D and AlphaMissense. PrimateAI-3D outperforms AlphaMissense on rare-disease cohort and biobank benchmarks, indicating that performance on clinical databases orin vitroassays does not reliably generalize to real-world cohorts.
Brain morphology mediating the effect of genetic risk variants on Alzheimer’s disease
Authors: Breddels Esmee M. , Snihirova Yelyzaveta , Pishva Ehsan , Gülöksüz Sinan , Blokland Gabriëlla A.M. , Luykx Jurjen , Andreassen Ole A. , Linden David E.J. , van der Meer Dennis ,   Alzheimer’s Disease Neuroimaging Initiative
Published: January 2024

INTRODUCTION

Late-onset Alzheimer’s disease (LOAD) has been associated with alterations in the morphology of multiple brain structures and it is likely that disease mechanisms differ between brain regions. Coupling genetic determinants of LOAD with measures of brain morphology could localize and identify primary causal neurobiological pathways.

METHODS

Mediation and Mendelian randomization (MR) analysis were performed using common genetic variation, T1 MRI and clinical data collected by UK Biobank and Alzheimer’s Disease Neuroimaging Initiative.

RESULTS

Thickness of the entorhinal cortex and the volumes of the hippocampus, amygdala, choroid plexus and inferior lateral ventricle mediated the effect ofAPOEε4 on LOAD. MR showed that a thinner entorhinal cortex, a smaller hippocampus and amygdala, and a larger volume of the choroid plexus and inferior lateral ventricles, increased the risk of LOAD as well as vice versa.

DISCUSSION

Combining neuroimaging and genetic data can give insight into the causal neuropathological pathways of LOAD.
Interpretable Machine Learning Leverages Proteomics to Improve Cardiovascular Disease Risk Prediction and Biomarker Identification
Authors: Climente-González Héctor , Oh Min , Chajewska Urszula , Hosseini Roya , Mukherjee Sudipto , Gan Wei , Traylor Matthew , Hu Sile , Fatemifar Ghazaleh , Del Villar Paul Pangilinan , Vernet Erik , Koelling Nils , Du Liang , Abraham Robin , Li Chuan , Howson Joanna M. M.
Published: January 2024

Cardiovascular diseases (CVD), primarily coronary heart disease and stroke, rank amongst the leading causes of long-term disability and mortality. Providing accurate disease risk predictions and identifying genes associated with CVD are crucial for prevention, early intervention, and the development of novel medications.

The recent availability of UK Biobank Proteomics data enables the investigation of the blood proteome and its association with a wide variety of diseases. We employed the Explainable Boosting Machine (EBM), an interpretable machine learning model, for CVD risk prediction. The EBM model using proteomics outperforms traditional clinical models with an AUROC of 0.767 and an AUPRC of 0.2405. Adding clinical features further improves the AUROC to 0.785 and the AUPRC to 0.2835. Our models demonstrate consistent performance across sexes and ethnicities.

While most prior studies using proteomics data for disease prediction have primarily focused on maximizing the accuracy at the population level, our model provides additional enriched insights into individualized disease risk predictions and in-depth biological insights into biomarkers. Our analysis also uncovers nonlinear risks linked to varying feature values. We further corroborate our findings using statistical approaches and evidence from the literature.

In conclusion, we present a highly accurate and explanatory framework for proteomics data analysis, offering comprehensive and in-depth molecular and clinical insights. Our findings support future approaches that prioritize individualized disease risk prediction and the identification of target genes for drug development.
Interstitial Fibrosis and Arrhythmic Mitral Valve Prolapse: Unravelling Sex-Based Differences
Authors: Tastet Lionel , Dixit Shalini , Nguyen Thuy , Lim Lisa J. , Al-Akchar Mohammad , Bibby Dwight , Arya Farzin , Cristin Luca , Anwar Shafkat , Higuchi Satoshi , Hsia Henry , Lee Yoo Jin , Delling Francesca N.
Published: January 2024

Background

Interstitial fibrosis as quantified by cardiac magnetic resonance (CMR) has been demonstrated in arrhythmic mitral valve prolapse (MVP), a condition with known female predominance. However, prior studies included only MVP cases with significant mitral regurgitation (MR) or mitral annular disjunction (MAD). We sought to evaluate the association between interstitial fibrosis and complex ventricular ectopy (ComVE) in MVPs unselected for MAD or severe MR, and to investigate the contribution of sex to this association.

Methods

We performed contrast CMR in consecutive individuals with MVP between 2020 and 2022. Extracellular volume fraction (ECV%), a surrogate marker for interstitial fibrosis, was quantified using T1mapping. Replacement fibrosis was assessed using late gadolinium enhancement (LGE). ComVE, defined as frequent premature ventricular contractions and/or non-sustained/sustained ventricular tachycardia (VT), was detected using ambulatory ECG monitoring.

Results

We identified 59 MVP cases without severe MR (49% women, 80% with mild or less MR) and available ECV% measurement. Among these, 23 (39%) had ComVE, including a case of aborted ventricular fibrillation (VF) and one with sudden arrhythmic death, both females. Global ECV% was significantly greater in ComVE versus non-ComVE (31%[27-33] vs 27%[23-30], p=0.002). In MVP-ComVE, higher segmental ECV% was not limited to the inferolateral/inferior LV wall, but was also demonstrated in atypical segments including the anterior/anterolateral wall (p<0.05). The association between ComVE and ECV% was driven by female sex (32%[30-33] vs 28%[26-30], p=0.003 in females; 31%[25-33] vs 26%[23-30], p=0.22 in males). ECV% remained independently associated with an increased risk of ComVE, including VT/VF, after adjustment for cardiovascular risk factors, MAD, and LGE (p<0.01).

Conclusion

In MVP without significant MR, interstitial fibrosis by CMR is associated with an increased risk of ComVE, suggesting a primary myopathic process. The stronger association between interstitial fibrosis and ComVE in females may explain why severe arrhythmic complications are more prevalent among women.

Abstract Figure

GRAPHICAL ABSTRACT:

Expansion of Interstitial Myocardial Fibrosis in Mitral Valve Prolapse with Complex Ventricular Ectopy. Illustrative MVP case with ComVE and greater interstitial fibrosis as demonstrated by T1mapping on CMR (Top). The violin plot shows significantly greater ECV% in MVPs with ComVE compared to non-ComVE (Top). The association between greater interstitial fibrosis (i.e. ECV%) and ComVE was stronger in women than men (Bottom). MR = mitral regurgitation
A high throughput blood-based assay for the early detection of pancreatic cancer
Authors: Montoya Mira Jose L. , Quentel Arnaud , Patel Ranish K. , Keith Dove , Minnier Jessica , David Larry , Esener Sadik C. , Sears Rosalie C. , Lopez Charles D. , Sheppard Brett C. , Demirci Utkan , Wong Melissa H. , Fischer Jared M.
Published: January 2024

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers due in part to the cancer being diagnosed is at a late stage when effective treatment options are limited. Early detection of PDAC via liquid biopsy would revolutionize survival from the disease. To address the lack of effective non-invasive detection assays for PDAC, we developed aproteaseactivity-based assay using amagneticnanosensor (PAC•MANN). The PAC•MANN assay leverages protease activity in blood to amplify the signal of the target-probe based sensor. An initial screening revealed that the PAC•MANN assay could reliably differentiate patients with PDAC from healthy subjects and patients at high risk of PDAC. Finally, in two cohorts: training (n=145) and blinded validation (n=72), we demonstrated that the PAC•MANN assay had high specificity (86%) and sensitivity (78%) for detection of PDAC compared to healthy subjects. This performance was enhanced when combined with the current standard of care assay, CA19-9 (100% specificity, 84% sensitivity). Our results demonstrate a novel assay that is rapid, high-throughput, and requires low specimen volume, which may not only improve cancer detection but could be useful for monitoring of at-risk patients and could be deployed in low resource settings.

One sentence summary

A high-throughput, non-invasive, rapid protease-activated nanosensor identifies pancreatic cancer from a small volume of blood
Trajectory of the body mass index of children and adolescents attending a reference mental health center
Authors: Echeveste-Navarrete Juliana , Zavaleta-Ramírez Patricia , Castilla-Peon Maria Fernanda
Published: January 2024

Objectives

To describe the standardized body mass index (z-BMI) trajectory of children and adolescents admitted to a psychiatric reference center in Mexico City according to their diagnosis and medication use. A secondary objective was to compare z-BMI between antipsychotic users and non-users.

Methods

Diagnosis, prescribed medications, serial heights, and weights were collected from the medical records.

Results

The median baseline z-BMI of the 129 analyzed cases was 0.88 (IQR: 0 -1.92), and the overweight/obesity prevalence was 46.8%. At the end of follow-up (median, 50.3 weeks), they had a median change in z-BMI of -0.09 (IQR: - 0.68 -0.42). New long-term users of antipsychotics (n = 29) had an increase in their z-BMI, in contrast to never-users (median difference 0.73, p = 0.01) and to previous users (median difference 0.92, p = 0.047). The 59 subjects with excessive weight at admission had a median change in z -BMI of -0.39 (IQR: - 0.81--0.04). Among patients with excessive weight and depression, a greater decrease in z-BMI was observed in sertraline users (n = 13) compared with fluoxetine users (n = 15) (median -0.65 vs. 0.21, p<0.001).

Conclusions

New long-term users of antipsychotics increased their z-BMI significantly. Patients with depressive disorders and obesity on sertraline therapy tend to decrease their z-BMI.