bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractIntroductionAlzheimer’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.MethodsDorsolateral 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).ResultsAs 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.DiscussionThis 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

AbstractThe 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

ABSTRACTThe 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

AbstractThe 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

ABSTRACTWe 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

ABSTRACTPremiseThe 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.MethodsTo 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.ResultsThe 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.DiscussionLower 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

AbstractHoneybees (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

AbstractMotivationscRNA-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.ResultsIn 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.AvailabilityThe Python implementation of scMUSCL is available athttps://github.com/arashkhoeini/scMUSCL
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

AbstractTestis-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 summaryA 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

AbstractStructural 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

ABSTRACTIntroductionThyroid 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.ObjectiveTo develop an automated thyroid ultrasound analysis (ATUS) algorithm using the C# programming language to detect and quantify ultrasonographic characteristics associated with HT.Materials and MethodsThis 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.ResultsThe 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.ConclusionC#-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

ABSTRACTBackgroundMycoplasma 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).MethodsUSAF 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.ResultsAmong 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.ConclusionsMacrolide 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.