bluuebunny/crossref_metadata_2025 huggingface dataset:
Forces directing the systemic correlations of cell migration
Authors: De la Fuente Ildefonso M. , Carrasco-Pujante Jose , Camino-Pontes Borja , Fedetz Maria , Bringas Carlos , Pérez-Samartín Alberto , Pérez-Yarza Gorka , López José I. , Malaina Iker , Cortes Jesus M
Published: April 2024

Directional motility is an essential property of cells. Despite its enormous relevance in many fundamental physiological and pathological processes, how cells control their locomotion movements remains an unresolved question. Here we have addressed the systemic processes driving the directed locomotion of cells. Specifically, we have performed an exhaustive study analyzing the trajectories of 700 individual cells belonging to three different species (Amoeba proteus,Metamoeba leningradensisandAmoeba borokensis) in four different scenarios: in absence of stimuli, under an electric field (galvanotaxis), in a chemotactic gradient (chemotaxis), and under simultaneous galvanotactic and chemotactic stimuli. All movements were analyzed using advanced quantitative tools. The results show that the trajectories are mainly characterized by coherent integrative responses that operate at the global cellular scale. These systemic migratory movements depend on the cooperative non-linear interaction of most, if not all, molecular components of cells.

Significance

Cellular migration is a cornerstone issue in many human physiological and pathological processes. For years, the scientific attention has been focused on the individualized study of the diverse molecular parts involved in directional motility; however, locomotion movements have never been regarded as a systemic process that operates at a global cellular scale. In our quantitative experimental analysis essentialsystemicproperties underlying locomotion movements were detected. Such emergent systemic properties are not found specifically in any of the molecular parts, partial mechanisms, or individual processes of the cell. Cellular displacements seem to be regulated by integrative processes operating atsystemiclevel.
Mutant TP53 switches therapeutic vulnerability during gastric cancer progression within Interleukin-6 family cytokines
Authors: Huber Anne , Allam Amr H. , Dijkstra Christine , Thiem Stefan , Huynh Jennifer , Poh Ashleigh R. , Konecnik Joshua , Jacob Saumya P. , Busuttil Rita , Liao Yang , Chisanga David , Shi Wei , Alorro Mariah G. , Forrow Stephen , Tauriello Daniele V.F. , Batlle Eduard , Boussioutas Alex , Williams David S. , Buchert Michael , Ernst Matthias , Eissmann Moritz F.
Published: April 2024

Although aberrant activation of the KRAS and PI3K pathway alongside TP53 mutations account for frequent aberrations in human gastric cancers, neither the sequence nor the individual contributions of these mutations have been clarified. Here, we establish an allelic series of mice to afford conditional expression in glandular epithelium ofKrasG12D;Pik3caH1047RorTrp53R172Hand/or ablation ofPtenorTrp53. We find thatKrasG12D;Pik3caH1047Ris sufficient to induce adenomas, and that lesions progress to carcinoma when also harboringPten-deletions. Additional challenge with eitherTrp53loss- or gain-of-function alleles further accelerated tumor progression and triggered metastatic disease. While tumor-intrinsic STAT3 signaling in response to gp130 family cytokines remained as a gatekeeper for all stages of tumor development, metastatic progression required a mutantTrp53-induced interleukin (IL)-11 to IL-6 dependency switch. Consistent with poorer survival of patients with high IL6 expression, we identify IL6/STAT3 signaling as a therapeutic vulnerability for TP53-mutant gastric cancer.
Figeno: multi-region genomic figures with long-read support
Authors: Sollier Etienne , Heilmann Jessica , Gerhäuser Clarissa , Scherer Michael , Plass Christoph , Lutsik Pavlo
Published: April 2024

The vast amount of publicly available genomic data requires analysis and visualization tools. Here, we present figeno, an application for generating publication-quality FIgures for GENOmics. Figeno particularly focuses on multi-region views across genomic breakpoints and on long reads with base modifications. Additionally, we support epigenomic data including ATAC-seq, ChIP-seq or HiC, as well as whole genome sequencing data with copy numbers and structural variants.

Availability and Implementation

Figeno is available as a python package with both a command line and graphical user interface. It can be installed via PyPI and the source code is available athttps://github.com/CompEpigen/figeno.

Supplementary information

Supplementary data is provided.
Inbreeding and gallbladder cancer risk: Homozygosity associations adjusted for indigenous American ancestry, BMI and genetic risk of gallstone disease
Authors: Ceballos Francisco , Boekstegers Felix , Scherer Dominique , Ponce Carol Barahona , Marcelain Katherine , Gárate-Calderón Valentina , Waldenberger Melanie , Morales Erik , Rojas Armando , Munoz César , Retamales Javier , de Toro Gonzalo , Kortmann Allan Vera , Barajas Olga , Teresa Rivera María , Cortés Analía , Loader Denisse , Saavedra Javiera , Gutiérrez Lorena , Ortega Alejandro , Bertrán Maria Enriqueta , Bartolotti Leonardo , Gabler Fernando , Campos Mónica , Alvarado Juan , Moisán Fabricio , Spencer Loreto , Nervi Bruno , Carvajal-Hausdorf Daniel , Losada Héctor , Almau Mauricio , Fernández Plinio , Olloquequi Jordi , Rothhammer Francisco , Bermejo Justo Lorenzo
Published: April 2024

Latin Americans have a rich genetic make-up that translates into heterogeneous fractions of the autosomal genome in runs of homozygosity (FROH), and heterogeneous types and proportions of indigenous American ancestry. While autozygosity has been linked to several human diseases, very little is known about the relationship between inbreeding, genetic ancestry and cancer risk in Latin Americans.

Chile has one of the highest incidences of gallbladder cancer (GBC) in the world, and here we investigated the association between inbreeding, GBC, gallstone disease (GSD) and body mass index (BMI) in 4029 genetically admixed Chileans. We calculated individual FROHabove 1.5 Mb and weighted polygenic risk scores for GSD, and applied multiple logistic regression to assess the association between homozygosity and GBC risk.

We found that homozygosity was due to a heterogeneous mixture of genetic drift and consanguinity in the study population. Although we found no association between homozygosity and overall GBC risk, we detected interactions between FROHand sex, age, and genetic risk of GSD on GBC risk. Specifically, the increase in GBC risk per 1% FROHwas 19% in men (P-value = 0.002), 30% in those under 60 years of age (P-value = 0.001), and 12% in those with a genetic risk of GSD above the median (P-value = 0.01).

The present study highlights the complex interplay between inbreeding, genetic ancestry and genetic risk of GSD in the development of GBC. The applied methodology and our findings underscore the importance of considering the population-specific genetic architecture, along with sex- and age specific-effects, when investigating the genetic basis of complex traits in Latin Americans.
Large-scale Deep Proteomic Analysis in Alzheimer’s Disease Brain Regions Across Race and Ethnicity
Authors: Seifar Fatemeh , Fox Edward J. , Shantaraman Anantharaman , Liu Yue , Dammer Eric B. , Modeste Erica , Duong Duc M. , Yin Luming , Trautwig Adam N. , Guo Qi , Xu Kaiming , Ping Lingyan , Reddy Joseph S. , Allen Mariet , Quicksall Zachary , Heath Laura , Scanlan Jo , Wang Erming , Wang Minghui , Linden Abby Vander , Poehlman William , Chen Xianfeng , Baheti Saurabh , Ho Charlotte , Nguyen Thuy , Yepez Geovanna , Mitchell Adriana O. , Oatman Stephanie R. , Wang Xue , Carrasquillo Minerva M. , Runnels Alexi , Beach Thomas , Serrano Geidy E. , Dickson Dennis W. , Lee Edward B. , Golde Todd E. , Prokop Stefan , Barnes Lisa L. , Zhang Bin , Haroutunian Varham , Gearing Marla , Lah James J. , De Jager Philip , Bennett David A , Greenwood Anna , Ertekin-Taner Nilüfer , Levey Allan I. , Wingo Aliza , Wingo Thomas , Seyfried Nicholas T.
Published: April 2024

Abstract

Introduction

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups.

Methods

Dorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS).

Results

As a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant withAPOEgenotype of the individuals.

Discussion

This comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.
The Discovery of Small Molecule Inhibitors of cFLIP that Sensitise Tumour Cells to TRAIL
Authors: Giancotti Gilda , French Rhiannon , Hayward Olivia , Lee Kok Yung , Robinson Timothy , Ribeiro da Silva Andreia M. , Varnava Athina , MacFarlane Marion , Clarkson Richard W.E. , Westwell Andrew D. , Brancale Andrea
Published: April 2024

The TNF-related apoptosis-inducing ligand (TRAIL) has potential as a therapeutic agent as it has previously been shown to induce apoptosis in triple-negative breast cancer. Recombinant human TRAIL has shown promise in pre-clinical studies of breast cancer. TRAIL exhibits specificity for triple-negative and treatment-resistant disease subsets. However, several studies have demonstrated that patient tumours exhibit resistance to TRAIL and TRAIL-receptor agonists. We have previously demonstrated that suppression of the TRAIL-receptor inhibitor cFLIP can sensitise breast cancer stem cells to apoptosis inducers, but development of pharmacological inhibitors of cFLIP have been impeded by concerns over structural similarities between cFLIP and the pro-apoptotic procaspase-8.

We used molecular dynamics to model the interactions between cFLIP, procaspase-8 and the TRAIL-receptor Death Inducing Signalling Complex (TRAIL-DISC), followed by virtual pharmacophore screening and in-cell viability assays to identify a small-molecule (OH14,3) that selectively inhibited cFLIP binding to the DISC and promoted TRAIL-mediated apoptosis in breast cancer cell lines. When used in combination with TRAIL, OH14 significantly impaired breast cancer cell viability in primary derived and established cell culture.

Given the relatively low (micromolar) potency of the initial hit compound inhibitor OH14 (3), limiting its utility as a preclinical development candidate, we carried out structure-activity relationship studies to find a cFLIP inhibitor with more potent cellular activity. Our findings confirm the proof-of-principle that selective pharmacological inhibition of cFLIP can be used to target a vulnerability in breast cancer cells.
Transcriptomic characterization of human lateral septum neurons reveals conserved and divergent marker genes across species
Authors: Phillips Robert A. , Oh Seyun , Bach Svitlana V. , Du Yufeng , Miller Ryan A. , Kleinman Joel E. , Hyde Thomas M. , Hicks Stephanie C. , Page Stephanie C. , Martinowich Keri
Published: April 2024

The lateral septum (LS) is a midline, subcortical structure, which regulates social behaviors that are frequently impaired in neurodevelopmental disorders including schizophrenia and autism spectrum disorder. Mouse studies have identified neuronal populations within the LS that express a variety of molecular markers, including vasopressin receptor, oxytocin receptor, and corticotropin releasing hormone receptor, which control specific facets of social behavior. Despite its critical role in regulating social behavior and notable gene expression patterns, comprehensive molecular profiling of the human LS has not been performed. Here, we conducted single nucleus RNA-sequencing (snRNA-seq) to generate the first transcriptomic profiles of the human LS using postmortem human brain tissue samples from 3 neurotypical donors. Our analysis identified 5 transcriptionally distinct neuronal cell types within the human LS that are enriched forTRPC4, the gene encoding Trp-related protein 4. Differential expression analysis revealed a distinct LS neuronal cell type that is enriched forOPRM1, the gene encoding the µ-opioid receptor. Leveraging recently generated mouse LS snRNA-seq datasets, we conducted a cross-species analysis. Our results demonstrate thatTRPC4enrichment in the LS is highly conserved between human and mouse, whileFREM2, which encodes FRAS1 related extracellular matrix protein 2, is enriched only in the human LS. Together, these results highlight transcriptional heterogeneity of the human LS, and identify robust marker genes for the human LS.
Neto proteins differentially modulate the gating properties ofDrosophilaNMJ glutamate receptors
Authors: Han Tae Hee , Vicidomini Rosario , Ramos Cathy Isaura , Mayer Mark , Serpe Mihaela
Published: April 2024

The formation of functional synapses requires co-assembly of ion channels with their accessory proteins which controls where, when, and how neurotransmitter receptors function. The auxiliary protein Neto modulates the function of kainate-type glutamate receptors in vertebrates as well as at theDrosophilaneuromuscular junction (NMJ), a glutamatergic synapse widely used for genetic studies on synapse development. We previously reported that Neto is essential for the synaptic recruitment and function of glutamate receptors. Here, using outside-out patch-clamp recordings and fast ligand application, we examine for the first time the biophysical properties of recombinantDrosophilaNMJ receptors expressed in HEK293T cells and compare them with native receptor complexes of genetically controlled composition. The two Neto isoforms, Neto-α and Neto-β, differentially modulate the gating properties of NMJ receptors. Surprisingly, we found that deactivation is extremely fast and that the decay of synaptic currents resembles the rate of iGluR desensitization. The functional analyses of recombinant iGluRs that we report here should greatly facilitate the interpretation of compoundin vivophenotypes of mutant animals.
Quantum Chemistry in a Pocket: A Multifaceted Tool to Link Structure and Activity
Authors: Menezes Filipe , Napolitano Valeria , Fröhlich Tony , Rioton Sarah , Olmos Julian D. Janna , Dubin Grzegorz , Popowicz Grzegorz M.
Published: April 2024

We introduce In-Pocket Analysis, a simple and efficient protein-ligand complex structure optimization algorithm. It provides structural biology and structure-based drug discovery with a much-needed tool for data curation and quantification analysis. In-pocket analysis removes unphysical tension from experimental structures, yielding high-quality atomic models. This includes deformed bonds, structural clashes, proton refinement, and solvent envelope. The algorithm is compatible with quantum methods or force fields, delivering precise calculations of binding energies and QSAR. Its applications include refinement of experimental structures, calculation of inter- and intramolecular energetics, scoring of docked poses, scaffold decoration/hopping, or building of explainable QSAR.

For validation and benchmarking we used high-resolution crystal structures of the N-terminal domain of PEX14 with small-molecule inhibitors. PEX14 is a target candidate against Trypanosomiasis and Leishmaniasis. The application of our algorithm allowed for an explanation of unexpected binding poses, rationalization of binding energies, and affinities as well as precise quantification of solvent-mediated interactions.

TABLE OF CONTENTS
Detecting color differences in lentil flour samples using an inexpensive, hand-held colorimeter
Authors: Viscarra Sarahi , Vargas Ana , Jardine Laura , Tulbek Mehmet , Bett Kirstin E.
Published: April 2024

Premise

The Nix Spectro 2 was developed to obtain CIEL*a*b* values from small samples and is an affordable alternative to the more expensive spectrophotometers typically used to assess food color.

Methods

To validate the use of the Nix for lentil seed quality research, eight genotypes in three different field trials, were evaluated for flour color using HunterLab (illuminant C) and Nix (illuminants D50 and C) instruments and results compared for consistency.

Results

The a* and b* Nix scores were comparable to those obtained with the HunterLab (r2= 0.9-0.95). L* scores had lower correlation values: 0.61 and 0.58 when comparing HunterLab (C) with Nix (D50) and Nix (C), respectively.

Discussion

Lower L* correlations could be a result of the influence of direct light exposure during HunterLab scans. In contrast, the Nix uses more technical repetitions per scan and avoids direct light exposure with the use of an adaptor, suggesting the L* Nix values are more reliable than those from the HunterLab. We observed that the Nix procedures are more repeatable and rigorous, validating its use for assessing color, especially for small samples, a common limitation within breeding programs.
Development of Germline Progenitors in Larval Queen Honeybee ovaries
Authors: Cullen Georgia , Delargy Erin , Dearden Peter K.
Published: April 2024

Honeybees (Apis mellifera) are a keystone species for managed pollination and the production of hive products. Eusociality in honeybees leads to much of the reproduction in a hive driven by the queen. Queen bees have two large active ovaries that can produce large numbers of eggs if conditions are appropriate. These ovaries are also active throughout the long lives of these insects, up to 5 years in some cases.

Recent studies have indicated that the germline precursors of the adult honeybee queen ovary are organized into 8 cell clusters, joined together by a polyfusome; a cytoplasmic bridge. To understand the origin of these clusters, and trace the development of the honeybee queen ovary, we examined the cell types and regionalization of the developing larval and pupal queen ovaries.

We used established (nanosandcastor), and novel (odd skipped) gene expression markers to determine regions of the developing ovary. Primordial germline cells develop in the honeybee embryo and are organized into ovary structures before the embryo hatches. The ovary is regionalized by Larval Stage 3 into terminal filaments and germaria. At this stage clusters of germline cells in the germaria are joined by fusomes and are dividing synchronously. The origin of the 8-cell clusters in the adult germarium is therefore during larval stages.

On emergence, the queen ovary has terminal filaments and germaria but has not yet developed any vitellaria, which are produced after the queen embarks on a nuptial flight. The lack of germaria, and the storing of germline progenitors as clusters, may be adaptions for queen bees to endure the metabolic demands of a nuptial flight, as well as rapidly lay large numbers of eggs to establish a hive.
scMUSCL: Multi-Source Transfer Learning for Clustering scRNA-seq Data
Authors: Khoeini Arash , Sar Funda , Lin Yen-Yi , Collins Colin , Ester Martin
Published: April 2024

Motivation

scRNA-seq analysis relies heavily on single-cell clustering to perform many downstream functions. Several machine learning methods have been proposed to improve the clustering of single cells, yet most of these methods are fully unsupervised and ignore the wealth of publicly available annotated datasets from single-cell experiments. Cells are high-dimensional entities, and unsupervised clustering might find clusters without biological meaning. Exploiting relevant annotated scRNA-seq dataset as the learning reference can provide an algorithm with the knowledge that guides it to better estimate the number of clusters and find meaningful clusters in the target dataset.

Results

In this paper, we propose Single Cell MUlti-Source CLustering, scMUSCL, a novel transfer learning method for finding clusters of cells in a target dataset by transferring knowledge from multiple annotated source (reference) datasets. scMUSCL relies on a deep neural network to extract domain and batch invariant cell representations, and it effectively addresses discrepancies across multiple source datasets and between source and target datasets in the new representation space. Unlike existing methods, scMUSCL does not need to know the number of clusters in the target dataset in advance and it does not require batch correction between source and target datasets. We conduct extensive experiments using 20 real-life datasets and show that scMUSCL outperforms the existing unsupervised and transfer-learning-based methods in almost all experiments. In particular, we show that scMUSCL outperforms the state-of-the-art transfer-learning-based scRNA-seq clustering method, MARS, by a large margin.

Availability

The Python implementation of scMUSCL is available athttps://github.com/arashkhoeini/scMUSCL
More than the sum of its parts: investigating episodic memory as a multidimensional cognitive process
Authors: Mirjalili Soroush , Duarte Audrey
Published: April 2024

Why do we remember some events but forget others? Previous studies attempting to decode successful vs. unsuccessful brain states to investigate this question have met with limited success, potentially due, in part, to assessing episodic memory as a unidimensional process, despite evidence that multiple domains contribute to episodic encoding. Using a novel machine learning algorithm known as “transfer learning”, we leveraged visual perception, sustained attention, and selective attention brain states to better predict episodic memory performance from trial-to-trial encoding electroencephalography (EEG) activity. We found that this multidimensional treatment of memory decoding improved prediction performance compared to traditional, unidimensional, methods, with each cognitive domain explaining unique variance in decoding of successful encoding-related neural activity. Importantly, this approach could be applied to cognitive domains outside of memory. Overall, this study provides critical insight into the underlying reasons why some events are remembered while others are not.
Paralog-dependent Specialization of Paf1C subunit, Ctr9, for Sex Chromosome Gene Regulation and Male Germline Differentiation in Drosophila
Authors: Kai Toshie , Zheng Jinglan , Iki Taichiro
Published: April 2024

Testis-specific gene regulatory mechanisms govern the differentiation of germ cells into mature sperms. However, the molecular underpinnings are not fully elucidated. Here, we show the subunits forming Polymerase Associated Factor 1 Complex (Paf1C), a transcription regulator conserved across eukaryotes, have their individual paralogs predominantly expressed inDrosophilatestes. One of these, namely, Ctr9 paralog enriched in testes (Ctr9t) was found to play a critical and nonredundant role in post-meiotic spermatid differentiation and male fertility inD. melanogaster. A proximity proteome analysis provides evidence that Ctr9t forms complexes with other paralog members. We show endogenous Ctr9t is expressed in germ cells at spermatocyte stages, accumulating in a distinct compartment within the nucleolus. There, Ctr9t co-localizes with Spermatocyte arrest (Sa), a testis-specific paralog of TATA-binding protein (TBP)-associated factor 8 (TAF8). We further demonstrate thatctr9tfunction is crucial for maintaining Sa in the nucleolus, but notvice versa. Transcriptome profiling reveals that Ctr9t acts as an activator for the set of male fertility genes on Y chromosome, but it also acts as a global repressor of X chromosome genes. Collectively, our results shed light on the nucleolus-associated, paralog-dependent regulation of gene expression from sex chromosomes, which ensures the terminal differentiation of male germ cells.

Author summary

A wide repertoire of genes takes a coordinated action during sperm formation. However, gene expression during spermatogenesis is controlled by heretofore unelucidated mechanisms. In this study, we showDrosophilaexpresses testis-specific paralogs of the individual subunits forming a conserved transcription regulator called Paf1C. We generated a loss of function allele of one of the paralog members which we named Ctr9t, and demonstrate that Ctr9t function is crucial for post-meiotic spermatid differentiation and male fertility. Therefore, the paralog has established a nonredundant role for spermatogenesis. Using newly generated antibodies, we show Ctr9t protein is expressed in germ cells at spermatocyte stages and, intriguingly, enriched in the nucleolus. There, Ctr9t interacts with Spermatocyte arrest (Sa), a key transcription factor essential for meiotic and post-meiotic differentiation processes. By further performing whole testis transcriptome analyses, we reveal that Ctr9t acts as a regulator of gene expression from sex chromosomes. Importantly, the activation of male fertility genes located on Y chromosome relies on Ctr9t function, which can explain the defects observed inctr9tmutant germ cells. Altogether, we propose that Ctr9t acts as a key player in the spermatocyte nucleolus where it controls the expression of sex chromosome genes and ensures functional sperm formation.
Brain age prediction and deviations from normative trajectories in the neonatal connectome
Authors: Sun Huili , Mehta Saloni , Khaitova Milana , Cheng Bin , Hao Xuejun , Spann Marisa , Scheinost Dustin
Published: April 2024

Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brain’s maturity relative to normative data. The difference between the individual’s predicted and chronological age—or brain age gap (BAG)—represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We used resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based predictive modeling to predict postmenstrual age (PMA). Structural and functional connectomes accurately predicted PMA for term and preterm infants. Predicted ages from each modality were correlated. At the network level, nearly all canonical brain networks—even putatively later developing ones—generated accurate PMA prediction. Additionally, BAGs were associated with perinatal exposures and toddler behavioral outcomes. Overall, our results underscore the importance of normative modeling and deviations from these models during the perinatal period.
Automated Thyroid Ultrasound Analysis: Hashimoto’s Thyroiditis
Authors: de Oliveira Andrade Luís Jesuíno , de Oliveira Gabriela Correia Matos , de Oliveira Luísa Correia Matos , de Oliveira Luís Matos
Published: April 2024

Introduction

Thyroid ultrasound provides valuable insights for thyroid disorders but is hampered by subjectivity. Automated analysis utilizing large datasets holds immense promise for objective and standardized assessment in screening, thyroid nodule classification, and treatment monitoring. However, there remains a significant gap in the development of applications for the automated analysis of Hashimoto’s thyroiditis (HT) using ultrasound.

Objective

To develop an automated thyroid ultrasound analysis (ATUS) algorithm using the C# programming language to detect and quantify ultrasonographic characteristics associated with HT.

Materials and Methods

This study describes the development and evaluation of an ATUS algorithm using C#. The algorithm extracte relevant features (texture, vascularization, echogenicity) from preprocessed ultrasound images and utilizes machine learning techniques to classify them as “normal” or indicative of HT. The model is trained and validated on a comprehensive dataset, with performance assessed through metrics like accuracy, sensitivity, and specificity. The findings highlight the potential for this C#-based ATUS algorithm to offer objective and standardized assessment for HT diagnosis.

Results

The program preprocesses images (grayscale conversion, normalization, etc.), segments the thyroid region, extracts features (texture, echogenicity), and utilizes a pre-trained model for classification (“normal” or “suspected Hashimoto’s thyroiditis”). Using a sample image, the program successfully preprocessed, segmented, and extracted features. The predicted classification (“suspected HT”) with high probability (0.92) aligns with the pre-established diagnosis, suggesting potential for objective HT assessment.

Conclusion

C#-based ATUS algorithm successfully detects and quantifies Hashimoto’s thyroiditis features, showcasing the potential of advanced programming in medical image analysis.
Prevalence ofMycoplasma genitaliuminfection and macrolide and fluoroquinolone resistance mutations among U.S. Air Force service members living with HIV, 2016-2020
Authors: Hakre Shilpa , Sanders-Buell Eric , Casimier Rosemary O. , O’Sullivan Anne Marie , Peel Sheila A. , Tovanabutra Sodsai , Scott Paul T. , Okulicz Jason F.
Published: April 2024

Background

Mycoplasma genitalium(MG) infection is of public health concern due to antimicrobial resistance (AMR). Data are limited on repeat MG infection and AMR among United States Air Force (USAF) service members (SMs) living with human immunodeficiency virus (HIV).

Methods

USAF SMs seeking HIV care were screened for MG infection during the surveillance period (May 16, 2016-March 16, 2020). Baseline and repeat MG prevalence were estimated. An extended Cox proportional hazards regression model evaluated characteristics associated with repeat MG infection. MG-positive rectal samples were tested for macrolide or fluoroquinolone resistance.

Results

Among 299 male patients of a total 308 patients followed during the surveillance period, baseline prevalence of MG infection was 19.7% (59/299) and repeat MG was 35% (36/101) among patients who screened positive for MG at any time during the surveillance period. Characteristics independently associated with increased risk of repeat infection were reported prior sexually-transmitted infection (STI) history vs none (adjusted hazards ratio (aHR) 2.21, 95% confidence interval (CI) 1.13-4.35), presence of STI coinfection vs not indicated (aHR 5.13, 95% CI 2.78-9.49), new HIV diagnosis (<1 year vs 1 year or more, aHR 2.63, 95% CI 1.62-4.27). AMR in MG-positive rectal specimens was 88% (43/49) indicating macrolide resistance, 18% (10/56) with quinolone resistance, and 18% (10/56) with both macrolides and fluoroquinolone resistance.

Conclusions

Macrolide and fluoroquinolone resistance mutations were common. Testing for co-occurring MG infection and AMR mutations may be warranted in guiding treatment for STIs such as chlamydia or gonorrhea detected at HIV diagnosis.
The potential role of cultural and religious healing practices in shaping community vulnerability to highly infectious diseases in western Kenya
Authors: Nga’ng’a Naomi , Momanyi Reuben Onkoba , Chemirmir Caleb , Biwott Hazael , Ayodo George , Orero Monica , Ochanda Damaris , Ngere Sarah , Ogola Winnie , Murundu Tutus , Munene Geoffrey , Misiani Zachary , Ayaibei Michael , Kiaka Richard Dimba
Published: April 2024

We draw from empirical research conducted in communities in three border counties in western Kenya – Homa Bay, Bungoma and West Pokot - to examine how cultural and religious beliefs and healing practices can potentially shape the vulnerability of those communities to highly infectious diseases. Fieldwork consisting of mixed methods namely, key informant interviews with traditional and religious healers as well as their patients, focus group discussions with community members knowledgeable on cultural customs and practices, and participatory inquiry workshops with health professionals and administrators were used to collect the data.

We find that traditional and religious beliefs and healing practices potentially shape community vulnerability to highly infectious diseases in two major ways. First, is a dualistic illness etiology involving a biomedical and socio-cultural etiology. Unexplained illnesses and illnesses that did not respond to conventional medicine were treated using traditional medicine. Making traditional and religious healers the first mile treatment preference could potentially delay appropriate treatment and compromise safe handling in case the disease is highly infectious. Second aspect pertains to the risks in the traditional and spiritual healing practices. Shared consecrated water often fetched from a large water body, laying of hands, use of herbs and rituals involving slaughtering of animals enhanced contacts. The use of protective gears during healing was inconsistent among the healers, but largely lacking as many healers could not afford them or were considered to reduce patient’s faith in the healing powers. These practices potentially predispose people to highly infectious diseases and can hasten the spread and symptom severity. To reduce the vulnerability of border communities to highly infectious diseases, we argue for a need for comprehensive strategies that consider the intersecting factors of vulnerability to outbreaks, healing beliefs and practices. This may involve policy initiatives aimed at integrating traditional medicine practice and the mainstream health system.
Automated detection of large vessel occlusion using deep learning: a pivotal multicenter clinical trial and reader assessment study
Authors: Kim Jae Guk , Ha Sue Young , Kang You-Ri , Hong Hotak , Kim Dongmin , Lee Myungjae , Sunwoo Leonard , Ryu Wi-Sun , Kim Joon-Tae
Published: April 2024

Background

This multicenter clinical trial evaluated the stand-alone efficacy and the improvements in diagnostic accuracy of early-career physicians using a deep learning-based software to detect large vessel occlusion (LVO) in CT angiography (CTA).

Methods

This multicenter pivotal clinical trial included 595 ischemic stroke patients from January 2018 to September 2023. Standard reference and LVO locations (intracranial internal carotid artery [ICA], M1, or M2) were determined by consensus among three expert vascular neurologists after reviewing CTA, MR imaging, and symptom data. The performance of the JLK-LVO software was evaluated against a standard reference, and its impact on the diagnostic accuracy of four residents involved in stroke care was assessed. Performance metrics included the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Results

Among the 595 patients (mean age 68.5 ± 13.4 years, 56% male), 275 (46.2%) had LVO. The median time interval from the last known well moment to the CTA was 46 hours (IQR 11.8 to 64.4). For LVO detection, the software demonstrated a sensitivity of 86% and a specificity of 97%. For isolated M2 occlusions, it achieved a sensitivity of 69% and a specificity of 96%. The reader assessment study showed that reading with software assistance improved the sensitivity by 4.0% and AUROC by 2.4% (all p < 0.001) compared to readings without AI assistance.

Conclusion

The software demonstrated a high detection rate for proximal LVO and moderate sensitivity for isolated MCA-M2 occlusion. In addition, the software improved diagnostic accuracy of early-career physicians in detecting LVO.
Ca2+-dependent phosphodiesterase 1 regulates the plasticity of striatal spiny projection neuron glutamatergic synapses
Authors: Zhai Shenyu , Otsuka Shintaro , Xu Jian , Clarke Vernon R. J. , Tkatch Tatiana , Wokosin David , Xie Zhong , Tanimura Asami , Agarwal Hitesh K. , Ellis-Davies Graham C. R. , Contractor Anis , Surmeier D. James
Published: April 2024

Long-term synaptic plasticity at glutamatergic synapses on striatal spiny projection neurons (SPNs) is central to learning goal-directed behaviors and habits. Although considerable attention has been paid to the mechanisms underlying synaptic strengthening and new learning, little scrutiny has been given to those involved in the attenuation of synaptic strength that attends suppression of a previously learned association. Our studies revealed a novel, non-Hebbian, long-term, postsynaptic depression of glutamatergic SPN synapses induced by interneuronal nitric oxide (NO) signaling (NO-LTD) that was preferentially engaged at quiescent synapses. This form of plasticity was gated by local Ca2+influx through CaV1.3 Ca2+channels and stimulation of phosphodiesterase 1 (PDE1), which degraded cyclic guanosine monophosphate (cGMP) and blunted NO signaling. Consistent with this model, mice harboring a gain-of-function mutation in the gene coding for the pore-forming subunit of CaV1.3 channels had elevated depolarization-induced dendritic Ca2+entry and impaired NO-LTD. Extracellular uncaging of glutamate and intracellular uncaging of cGMP suggested that this Ca2+-dependent regulation of PDE1 activity allowed for local regulation of dendritic NO signaling. This inference was supported by simulation of SPN dendritic integration, which revealed that dendritic spikes engaged PDE1 in a branch-specific manner. In a mouse model of Parkinson’s disease (PD), NO-LTD was absent not because of a postsynaptic deficit in NO signaling machinery, but rather due to impaired interneuronal NO release. Re-balancing intrastriatal neuromodulatory signaling in the PD model restored NO release and NO-LTD. Taken together, these studies provide novel insights into the mechanisms governing NO-LTD in SPN and its role in psychomotor disorders, like PD.
The gut microbiome associated with LGI1- and CASPR2-antibody encephalitis
Authors: Gilbert Edmund , Binks Sophie , Damato Valentina , Uy Christopher , Colmenero Paula , Khalil Mohamed Ibrahim , O’Brien Marcus , Claesson Marcus , Cryan John F , Delanty Norman , Irani Sarosh R , Cavalleri Gianpiero L
Published: April 2024

Autoimmune encephalitis is a cause of brain inflammation characterised by auto-antibodies which target cell surface neuronal proteins, and lead to neuronal dysfunction. In older people, common forms are encephalitis with autoantibodies to leucine-rich glioma inactivated protein 1 (LGI1) and contactin associated protein like 2 (CASPR2), whose presentation includes frequent focal seizures. The exact cause of these autoantibodies remain unknown, but established predispositions include overrepresented human leukocyte antigen (HLA) alleles. Yet, these alleles are themselves common in the healthy ancestry-matched population. One potential aetiological hypothesis is that an environmental trigger, such as the gut microbiome, interacts with a genetically predisposed individual. To investigate this, we studied 47 patients with leucine-rich glioma-inactivated 1 (LGI1)- or contactin-associated protein 2 (CAPSR2)-antibody encephalitis (LGI1/CASPR2-Ab-E) and 37 familial/environmentally matched controls, and performed metagenomic shotgun sequencing, to describe compositional and functional differences in the gut microbiome. We observed that LGI1/CASPR2-Ab-E gut microbiomes exhibited a significant reduction in the ratio ofFirmicutesandBacteroidetesphyla, which associated with dosage of HLA susceptibility alleles in LGI1-Ab-E patients. Furthermore, we identified differences in functional gene profiles in the gut microbiome that led to a reduction of neuroinflammatory protective short-chain-fatty-acids (SCFA) in LGI1-Ab-E patients. Taken together, our results suggest that a compositional shift in the gut microbiome of LGI1/CASPR2-Ab-E associates with a neuroinflammatory state, possibly through the reduction of SCFA production. Our study highlights the potential of the gut microbiome to explain some of the complex condition and unravel aetiological questions. Validation studies with greater sample sizes are recommended.
Climate-Sensitive Health Outcomes in Kenya: A Scoping Review of Environmental Exposures and Health Outcomes Research, 2000 – 2023
Authors: Gerard Jessica , Kibaara Titus , Blom Iris Martine , Falconer Jane , Mohammed Shamsudeen , Kadri-Alabi Zaharat , Taylor Roz , Abdullahi Leila , Hughes Robert C , Onyango Bernard , Brunn Ariel A
Published: April 2024

Climate change threatens health and social development gains in Kenya, necessitating health policy planning for risk reduction and mitigation. To understand the baseline state of knowledge of environmental determinants of health in Kenya relevant to climate change, a comprehensive scoping review was undertaken. Compliant with a pre-registered protocol, nine bibliographic databases and grey literature sources were searched for articles published from 2000-2023. Two-stage screening was conducted on 17,394 articles; 635 full-texts were screened in duplicate. A final 353 articles underwent data extraction for topic categorisation, bibliometric analysis, and narrative summary. This was comprised of 344 (97%) journal articles, 59% of which were published after 2014 (n=207). Main study designs included observational (n=211) and modelling studies (n=64). Health topics centred on vector-borne diseases (41%, n=147), primarily vector abundance (n=102) and malaria (n=60), while injury or death (n=10), mental health conditions (n=7) and heat exposure (n=7) studies were less frequent. Environmental health research in Kenya is largely conducted in the Lake Victoria Basin, Rift Valley and Coastal regions, with fewer studies from the northern arid and semi-arid regions. Findings of this review suggest a growing and diverse field of predominantly observational research with an increasing focus on social determinants and policy-relevant themes, however research on vector-borne disease dwarfs other health outcomes and sparsely populated but climatically fragile regions are less represented in published literature. Addressing existing gaps in baseline evidence underpinning associations between the environment and health outcomes will benefit climate change attribution research and support future development of evidence-informed climate change and health policy in Kenya.
Multi-ancestry meta-analyses of lung cancer in the Million Veteran Program reveal novel risk loci and elucidate smoking-independent genetic risk
Authors: Gorman Bryan R. , Ji Sun-Gou , Francis Michael , Sendamarai Anoop K. , Shi Yunling , Devineni Poornima , Saxena Uma , Partan Elizabeth , DeVito Andrea K. , Byun Jinyoung , Han Younghun , Xiao Xiangjun , Sin Don D. , Timens Wim , Moser Jennifer , Muralidhar Sumitra , Ramoni Rachel , Hung Rayjean J. , McKay James D. , Bossé Yohan , Sun Ryan , Amos Christopher I. ,   VA Million Veteran Program, Pyarajan Saiju
Published: April 2024

Lung cancer remains the leading cause of cancer mortality, despite declines in smoking rates. Previous lung cancer genome-wide association studies (GWAS) have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. We performed multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program (MVP) cohort and a previous study of European-ancestry individuals, comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We further performed conditional meta-analyses on cigarettes per day and identified two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in LUSC. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma (LUAD), and squamous cell lung carcinoma (LUSC), nine of which were externally replicated. Finally, we performed phenome-wide association studies (PheWAS) on polygenic risk scores (PRS) for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer PRS was associated with smoking status in controls, illustrating reduced predictive utility in non-smokers. Additionally, our PRS demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.
Plasma endostatin is an early creatinine independent predictor of acute kidney injury and need for renal replacement therapy in critical care
Authors: Koozi Hazem , Engström Jonas , Spångfors Martin , Friberg Hans , Frigyesi Attila
Published: April 2024

Purpose

Endostatin is a promising biomarker for predicting acute kidney injury (AKI) and mortality in the intensive care unit (ICU). We investigated plasma endostatin upon ICU admission as a predictor of AKI, renal replacement therapy (RRT), and 30-day mortality.

Methods

A retrospective multicenter study was performed with admissions (ICU length of stay ≥24 hours) to four ICUs. KDIGO criteria defined AKI. Endostatin on ICU admission was compared to creatinine, cystatin C, and the Simplified Acute Physiology Score 3 (SAPS-3). Admissions with sepsis and creatinine <100 μmol/L on ICU admission underwent subgroup analyses. Regression models and the area under the receiver operating characteristic curve (AUC) were assessed.

Results

In total, 4449 admissions were included (43% sepsis and 61% AKI). Endostatin was associated with AKI (odds ratio [OR] 1.6, 95% confidence interval [CI] 1.4-1.7), future AKI (OR 1.5, 95% CI 1.4-1.7), future AKI stage 3 (OR 1.4, 95% CI 1.2-1.6), and RRT (OR 1.2, 95% CI 1.1-1.4) independently of creatinine and cystatin C, with similar results in sepsis. Endostatin was also associated with time to AKI (hazard ratio 1.2, 95% CI 1.1-1.2). For admissions with creatinine <100 μmol/L, endostatin (AUC 0.62, 95% CI 0.59-0.65) outperformed creatinine (AUC 0.51, 95% CI 0.49-0.54) and cystatin C (AUC 0.53, 95% CI 0.50-0.56) in predicting future AKI (p<0.001). Endostatin was not associated with 30-day mortality after adjusting for SAPS-3.

Conclusion

Endostatin is an early and potentially clinically useful biomarker for predicting AKI and RRT needs at ICU admission, especially in patients with low to mildly elevated creatinine.