bluuebunny/crossref_metadata_2025 huggingface dataset:
Digital profiling of cancer transcriptomes from histology images with grouped vision attention
Authors: Zheng Yuanning , Pizurica Marija , Carrillo-Perez Francisco , Noor Humaira , Yao Wei , Wohlfart Christian , Marchal Kathleen , Vladimirova Antoaneta , Gevaert Olivier
Published: October 2023

Cancer is a heterogeneous disease that demands precise molecular profiling for better understanding and management. Recently, deep learning has demonstrated potentials for cost-efficient prediction of molecular alterations from histology images. While transformer-based deep learning architectures have enabled significant progress in non-medical domains, their application to histology images remains limited due to small dataset sizes coupled with the explosion of trainable parameters. Here, we developSEQUOIA, a transformer model to predict cancer transcriptomes from whole-slide histology images. To enable the full potential of transformers, we first pre-train the model using data from 1,802 normal tissues. Then, we fine-tune and evaluate the model in 4,331 tumor samples across nine cancer types. The prediction performance is assessed at individual gene levels and pathway levels through Pearson correlation analysis and root mean square error. The generalization capacity is validated across two independent cohorts comprising 1,305 tumors. In predicting the expression levels of 25,749 genes, the highest performance is observed in cancers from breast, kidney and lung, whereSEQUOIAaccurately predicts the expression of 11,069, 10,086 and 8,759 genes, respectively. The accurately predicted genes are associated with the regulation of inflammatory response, cell cycles and metabolisms. While the model is trained at the tissue level, we showcase its potential in predicting spatial gene expression patterns using spatial transcriptomics datasets. Leveraging the prediction performance, we develop a digital gene expression signature that predicts the risk of recurrence in breast cancer.SEQUOIAdeciphers clinically relevant gene expression patterns from histology images, opening avenues for improved cancer management and personalized therapies.
Deep Learning-enabled Detection of Aortic Stenosis from Noisy Single Lead Electrocardiograms
Authors: Aminorroaya Arya , Dhingra Lovedeep S , Sangha Veer , Oikonomou Evangelos K , Khunte Akshay , Shankar Sumukh Vasisht , Camargos Aline Pedroso , Haynes Norrisa A , Hofer Ira , Ouyang David , Nadkarni Girish N. , Khera Rohan
Published: October 2023

Background

Due to the lack of a feasible screening strategy, aortic stenosis (AS) is often diagnosed after the development of clinical symptoms, representing advanced stages of disease. Portable and wearable devices capable of recording electrocardiograms (ECGs) can be used for scalable screening for AS, if the diagnosis can be made with a single-lead ECG, despite potentially noisy acquisition.

Methods

Using electronic health records and imaging data from a large, diverse hospital system (2015-2022), we developed a deep learning-based approach to detect moderate/severe AS using a single-lead ECG. We used ECGs paired with echocardiograms obtained within 30 days of each other to develop the model. We extracted lead I signal data from clinical ECG and augmented it with random Gaussian noise. We trained a convolutional neural network (CNN) to identify TTE-confirmed AS using noisy single-lead ECGs. Finally, we used the CNN model probabilities, along with patient age and sex, as predictive inputs to train an extreme gradient boosting (XGBoost) model to detect moderate/severe AS.

Results

The model was developed in 75,901 ECGs/35,992 patients (median age 61 [interquartile range (IQR) 47-72] years, 54.3% women, 9.5% Black) and validated in 3,733 patients (median age 61 [IQR 47-72] years, 53.4% women, 9.7% Black). In the held-out validation set, the ensemble XGBoost model achieved an AUROC of 0.829 (95% CI: 0.800-0.855), with a sensitivity of 90.4% and specificity of 58.7% for detecting moderate/severe AS. For detecting severe AS, the model’s AUROC was 0.846 (95% CI, 0.778-0.899), with a sensitivity of 94.3% and specificity of 57.0%. In the test set with a 4.5% prevalence of moderate/severe AS, the model had a PPV of 9.3% and an NPV of 99.2%. In simulated cohorts with 1% and 20% prevalence of moderate/severe AS, the model’s NPVs varied from 99.8% to 96.1%, and PPV from 2.2% to 35.4%, respectively.

Conclusion

We developed a novel portable– and wearable-adapted deep learning approach for the detection of moderate/severe AS from noisy single-lead ECGs. Our approach represents a highly sensitive, feasible, and scalable strategy for community-based AS screening.
HyperPRI: A Dataset of Hyperspectral Images for Underground Plant Root Study
Authors: Chang Spencer J. , Chowdhry Ritesh , Song Yangyang , Mejia Tomas , Hampton Anna , Kucharski Shelby , Sazzad TM , Zhang Yuxuan , Koppal Sanjeev J. , Wilson Chris H. , Gerber Stefan , Tillman Barry , Resende Marcio F. R. , Hammond William M. , Zare Alina
Published: October 2023

Collecting and analyzing hyperspectral imagery (HSI) of plant roots over time can enhance our understanding of their function, responses to environmental factors, turnover, and relationship with the rhizosphere. Current belowground red-green-blue (RGB) root imaging studies infer such functions from physical properties like root length, volume, and surface area. HSI provides a more complete spectral perspective of plants by capturing a high-resolution spectral signature of plant parts, which have extended studies beyond physical properties to include physiological properties, chemical composition, and phytopathology. Understanding crop plants’ physical, physiological, and chemical properties enables researchers to determine high-yielding, drought-resilient genotypes that can withstand climate changes and sustain future population needs. However, most HSI plant studies use cameras positioned above ground, and thus, similar belowground advances are urgently needed. One reason for the sparsity of belowground HSI studies is that root features often have limited distinguishing reflectance intensities compared to surrounding soil, potentially rendering conventional image analysis methods ineffective. Here we present HyperPRI, a novel dataset containing RGB and HSI data for in situ, non-destructive, underground plant root analysis using ML tools. HyperPRI contains images of plant roots grown in rhizoboxes for two annual crop species – peanut (Arachis hypogaea) and sweet corn (Zea mays). Drought conditions are simulated once, and the boxes are imaged and weighed on select days across two months. Along with the images, we provide hand-labeled semantic masks and imaging environment metadata. Additionally, we present baselines for root segmentation on this dataset and draw comparisons between methods that focus on spatial, spectral, and spatialspectral features to predict the pixel-wise labels. Results demonstrate that combining HyperPRI’s hyperspectral and spatial information improves semantic segmentation of target objects.
Elasticity of the HIV-1 Core Facilitates Nuclear Entry and Infection
Authors: Deshpande Akshay , Bryer Alexander J. , Andino Jonathan , Shi Jiong , Hong Jun , Torres Cameron , Harel Shimon , Francis Ashwanth C. , Perilla Juan R. , Aiken Christopher , Rousso Itay
Published: October 2023

HIV-1 infection requires passage of the viral core through the nuclear pore of the cell, a process that depends on functions of the viral capsid1,2. Recent studies have shown that HIV- 1 cores enter the nucleus prior to capsid disassembly3–5. Interactions with the nuclear pore complex are necessary but not sufficient for nuclear entry, and the mechanism by which the viral core traverses the comparably sized nuclear pore is unknown. Here we show that the HIV-1 core is highly elastic and that this property is linked to nuclear entry and infectivity. Using atomic force microscopy-based approaches, we found that purified wild type cores rapidly returned to their normal conical morphology following a severe compression. Results from independently performed molecular dynamic simulations of the mature HIV-1 capsid also revealed its elastic property. Analysis of four HIV-1 capsid mutants that exhibit impaired nuclear entry revealed that the mutant viral cores are brittle. Suppressors of the mutants restored elasticity and rescued infectivity and nuclear entry. Elasticity was also reduced by treatment of cores with the capsid-targeting compound PF74 and the antiviral drug lenacapavir. Our results indicate that capsid elasticity is a fundamental property of the HIV-1 core that enables its passage through the nuclear pore complex, thereby facilitating infection. These results provide new insights into the mechanisms of HIV-1 nuclear entry and the antiviral mechanisms of HIV-1 capsid inhibitors.
Genome analysis of the Jomon dogs reveals the oldest domestic dog lineage in Eastern Eurasia
Authors: Terai Yohey , Xiaokaiti Xiayire , Gojobori Jun , Arakawa Nami , Sato Takao , Kasai Kenji , Machida Kenichi , Yamazaki Kyomi , Yamaji Naomitsu , Hongo Hitomi , Gakuhari Takashi
Published: October 2023

Dog is the oldest domesticated animal that established close relationships with humans. Due to its ancient origin, when, where, and whether a single or dual domestication event occurred is still under debate. The dogs in the Jomon period (Jomon dogs) in the Japanese archipelago had little change in morphology from 10,000 to 3,000 years ago. Therefore, we expected that the ancient genome of the Jomon dogs would provide a clue to reveal the characteristics of the ancient East Asian dogs. Here, we have sequenced the genomes of three 6000-year-old Jomon dogs, one 3000-4000-year-old Jomon dog, and four late 8th century dogs excavated in Japan. Our analyses suggest that the Jomon dogs are a distinct lineage from the previously known ancient dogs and are one of the oldest among the dogs in East Eurasian lineages. In addition, the genome of the Jomon dogs contained 9.5% of the genome of Japanese wolf ancestry due to a single introgression event. We estimated the proportion of the Jomon dog lineage genome in the genomes of dogs, which indicates that the genomic composition derived from the Jomon dog lineage is one of the major sources of modern dog genomes. Furthermore, we estimated the early admixture events of dogs in East Eurasia by analyzing the ancient genomes of the Jomon dogs. Due to the admixture events, the Jomon dog-derived genome has been one of the genomic sources of a wide range of modern dogs.
Benchmarking enrichment analysis methods with the disease pathway network
Authors: Buzzao Davide , Castresana-Aguirre Miguel , Guala Dimitri , Sonnhammer Erik L.L.
Published: October 2023

Enrichment analysis (EA) is a common approach to gain functional insights from genome-scale experiments. As a consequence, a large number of EA methods have been developed, yet it is unclear from previous studies which method is the best for a given dataset. The main issues with previous benchmarks include the complexity of correctly assigning true pathways to a test dataset, and lack of generality of the evaluation metrics, for which the rank of a single target pathway is commonly used.

We here provide a generalized EA benchmark and apply it to the most widely used EA methods, representing all four categories of current approaches. The benchmark employs a new set of 82 curated gene expression datasets from DNA microarray and RNA-Seq experiments for 26 diseases, of which only 13 are cancers. In order to address the shortcomings of the single target pathway approach and to enhance the sensitivity evaluation, we present the Disease Pathway Network, in which related KEGG pathways are linked. We introduce a novel approach to evaluate pathway EA by combining sensitivity and specificity to provide a balanced evaluation of EA methods. This approach identifies Network Enrichment Analysis methods as the overall top performers compared to overlap-based methods. By using randomized gene expression datasets, we explore the null hypothesis bias of each method, revealing that most of them produce skewedp-values.
Clostridioides difficileutilizes siderophores as an iron source and FhuDBGC contributes to ferrichrome uptake
Authors: Hastie Jessica L. , Carmichael Hannah L. , Werner Bailey M. , Dunbar Kristin E. , Carlson Paul E.
Published: October 2023

Clostridioides difficileremains a public health threat commonly observed following antibiotic use. Due to the importance of iron in many cell processes, most bacteria, includingC. difficile, have multiple mechanisms of acquiring iron. Previous studies have examined ferrous iron uptake inC. difficile, here we focus on the role of siderophores. In a growth assay, we show thatC. difficilecan use a variety of siderophores as the sole iron source. InC. difficile,two ABC transporters induced under low iron conditions are predicted siderophore importers: FhuDBGC and YclNOPQ. We hypothesized that these transporters are responsible for the uptake of the siderophores we tested. To investigate the specificity of these transporters, we purified the substrate binding proteins and examined siderophore binding using thermal shift. We demonstrate increased stability between one siderophore binding protein, FhuD, and the siderophore ferrichrome, suggesting a binding interaction. This specificity correlates with the inability of anΔfhuDBGCmutant to grow efficiently under iron limiting conditions in the presence of ferrichrome. WhileC. difficileused additional siderophores in our growth experiments, we did not observe increased thermal stability between the receptor proteins and any of the other siderophores tested, suggesting these siderophores do not bind these receptors and other siderophore import mechanisms remain to be elucidated. Redundancy in iron acquisition is a microbial survival adaptation to cope with the constant battle for iron within a host. Greater knowledge about howC. difficileacquires iron will provide insight about howC. difficilecolonizes and persists in the colon.

IMPORTANCE

This study is the first example ofC. difficilegrowing with siderophores as the sole iron source and describes the characterization of the ferric hydroxamate uptake ABC transporter (FhuDBGC). This transporter shows specificity to the siderophore ferrichrome. While not required for pathogenesis, this transporter highlights the redundancy in iron acquisition mechanisms whichC. difficileuses to compete for iron during an infection.
Mycobacterium tuberculosisKu stimulates multi-round DNA unwinding by UvrD1 monomers
Authors: Chadda Ankita , Kozlov Alexander G. , Nguyen Binh , Lohman Timothy M. , Galburt Eric A.
Published: October 2023

Mycobacterium tuberculosisis the causative agent of Tuberculosis. During the host response to infection, the bacterium is exposed to both reactive oxygen species and nitrogen intermediates that can cause DNA damage. It is becoming clear that the DNA damage response inMtband related actinobacteria function via distinct pathways as compared to well-studied model bacteria. For example, we have previously shown that the DNA repair helicase UvrD1 is activated for processive unwinding via redox-dependent dimerization. In addition, mycobacteria contain a homo-dimeric Ku protein, homologous to the eukaryotic Ku70/Ku80 dimer, that plays roles in double-stranded break repair via non-homologous end-joining. Ku has been shown to stimulate the helicase activity of UvrD1, but the molecular mechanism, as well as which redox form of UvrD1 is activated, is unknown. We show here that Ku specifically stimulates multi-round unwinding by UvrD1 monomers which are able to slowly unwind DNA, but at rates 100-fold slower than the dimer. We also demonstrate that the UvrD1 C-terminal Tudor domain is required for the formation of a Ku-UvrD1 protein complex and activation. We show thatMtbKu dimers bind with high nearest neighbor cooperativity to duplex DNA and that UvrD1 activation is observed when the DNA substrate is bound with two or three Ku dimers. Our observations reveal aspects of the interactions between DNA,MtbKu, and UvrD1 and highlight the potential role of UvrD1 in multiple DNA repair pathways through different mechanisms of activation.

Declaration of Interests

None
A redundant chloroplast protein is co-opted by potyvirids as the scaffold protein to mediate viral intercellular movement complex assembly
Authors: Qin Li , Liu Hongjun , Liu Peilan , Jiang Lu , Cheng Xiaofei , Li Fangfang , Shen Wentao , Dai Zhaoji , Cui Hongguang
Published: October 2023

For viruses in the familyPotyviridae(potyvirids), three virus-encoded proteins (P3N-PIPO, CI and CP) and several host components are known to coordinately regulate viral cell-to-cell movement. Here, we found that HCPro2 encoded by areca palm necrotic ring spot virus is involved in the intercellular movement, which could be functionally complemented by its counterpart HCPro from a potyvirus. The affinity purification and mass spectrum analysis identified several viral factors (including CI and CP) and a variety of host proteins that physically associate with HCPro2. We demonstrated that HCPro2 interacts with either CI or CPin planta, and the three form plasmodesmata (PD)-localized interactive complex in viral infection. Further, we screened HCPro2-associating host proteins, and identified a common host protein RbCS that mediates the interactions of HCPro2-CI, HCPro2-CP and CI-CP among the complex. Knockdown ofNbRbCSsimultaneously impairs the interactions of HCPro2-CI, HCPro2-CP and CI-CP, and significantly attenuates the intercellular movement and systemic infection for ANRSV and other three tested potyvirids. This study highlights that a nucleus-encoded chloroplast-targeted protein is hijacked by potyvirids as the scaffold protein to mediate the assembly of viral intercellular movement complex to promote viral infection.
The prion-like domain of the chloroplast RNA binding protein CP29A is required for cold-induced phase separation next to nucleoids and supports RNA splicing and translation during cold acclimation
Authors: Legen Julia , Lenzen Benjamin , Kachariya Nitin , Feltgen Stephanie , Gao Yang , Mergenthal Simon , Weber Willi , Klotzsch Enrico , Zoschke Reimo , Sattler Michael , Schmitz-Linneweber Christian
Published: October 2023

Arabidopsis thalianais capable of producing photosynthetic tissue with active chloroplasts at temperatures as low as 4°C, and this process depends on the presence of the nuclear-encoded, chloroplast-localized RNA-binding protein CP29A. In this study, we demonstrate that CP29A undergoes phase separation in vitro and in vivo in a temperature-dependent manner, which is mediated by a prion-like domain (PLD) located between the two RNA recognition motif (RRM) domains of CP29A. The resulting droplets display liquid-like properties and are found in close proximity to chloroplast nucleoids. The PLD is required to support chloroplast RNA splicing and translation in cold-treated tissue. Together, our findings suggest that plant chloroplast gene expression is compartmentalized by inducible condensation of CP29A at low temperatures, a mechanism that could play a crucial role for plant cold resistance.
Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration
Authors: Bramer Lisa M. , Dixon Holly M. , Degnan David J. , Rohlman Diana , Herbstman Julie B. , Anderson Kim A. , Waters Katrina M.
Published: October 2023

Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.
HOIL-1L deficiency induces cell cycle alteration which causes immaturity of myocyte and fibrogenesis
Authors: Akagi Kentaro , Baba Shiro , Fujita Hiroaki , Fuseya Yasuhiro , Yoshinaga Daisuke , Kubota Hirohito , Kume Eitaro , Fukumura Fumiaki , Matsuda Koichi , Tanaka Takayuki , Hirata Takuya , Iwai Kazuhiro , Takita Junko
Published: October 2023

HOIL-1L deficiency was recently reported to be one of the causes of myopathy and dilated cardiomyopathy (DCM). However, the mechanisms by which myopathy and DCM develop have not been clearly elucidated. Here, we sought to elucidate these mechanisms using the murine myoblast cell line C2C12 and disease-specific human induced pluripotent stem cells (hiPSCs). Myotubes were differentiated from control and HOIL-1L-KO C2C12 cells. Cardiomyocytes (CMs) were differentiated from control and patient-derived hiPSCs. We investigated the impact of HOIL-1L on differentiation of myotubes and CMs. Myotubes differentiated from HOIL-1L-KO C2C12 cells exhibited deteriorated differentiation and mitotic cell accumulation. CMs differentiaed from patient-derived hiPSCs had an abnormal morphology with a larger size and were excessively multinucleated compared with CMs differentiaed from control hiPSCs. Further analysis of hiPSC- derived CMs showed that HOIL-1L deficiency caused cell cycle alteration and mitotic cell accumulation. These results were supported by RNA sequencing of C2C12 cell-derived myotubes. In addition,SerpinE2, a cardiac fibrogenesis gene, was significantly upregulated in CMs differentiaed from patient-derived hiPSCs. These results demonstrate that abnormal cell maturation and fibrosis possibly contribute to the development of DCM and myopathy. In conclusion, HOIL-1L is an important intrinsic regulator of cell cycle-related myotube and CM maturation and cell proliferation.
Depressed Proximal Glycolysis in Myocardium Of Human Heart Failure with Preserved Ejection Fraction
Authors: Koleini Navid , Meddeb Mariam , Keykhaei Mohammad , Kwon Seoyoung , Zhao Liang , Hahn Virginia , Sharma Kavita , Pearce Erika L , Kass David A
Published: October 2023

Heart failure with preserved ejection fraction (HFpEF) accounts for >50% of all heart failure world-wide and remains a major unmet medical need. The most effective recently approved treatments were first developed for diabetes, suggesting metabolic defects are paramount. Myocardial metabolomics in human HFpEF has identified reduced fatty acid and branched chain amino acid catabolism, but the status of glycolysis is unknown. Here we performed targeted metabolomics and protein analysis of glycolytic pathway enzymes in myocardial biopsies of patients with HFpEF versus HF with reduced ejection fraction (HFrEF0 or non-failing controls. Glucose was increased in HFpEF myocardium, but immediate downstream glycolytic metabolites (glucose-6 phosphate, fructose 1,6 diphosphate), were more reduced in HFpEF than the other groups, as were their associated synthetic enzymes hexokinase and phosphofructokinase. Pyruvate was also reduced in HFpEF versus controls. These changes were either not present or substantially less so in HFrEF. Suppression of proximal glycolysis was also coupled to lower metabolites and proteins in the pentose phosphate pathway but was independent of diabetes or obesity. These findings support marked metabolic inflexibility in HFpEF and identifies very proximal blockade in glucose metabolism. Efforts to improve metabolic use of carbohydrates in HFpEF will likely need to target these proximal glycolytic enzymes.
Identification of watermelon genes involved in the ZYMV interaction through a miRNA bioinformatics analysis and characterization ofATRIPandRBOHB
Authors: Berbati Margarita , Bousali Maria , Kaldis Athanasios , Moravec Tomas , Karamitros Timokratis , Voloudakis Andreas
Published: October 2023

Small RNA sequencing of healthy and ZYMV-infected watermelon (21 dpi) was performed and bioinformatics analysis identified 353 miRNAs from which 22 known and 331 new miRNAs. Important information about their precursors, their length, the loci of which they originated on watermelon genome are provided. The ZYMV genome could be a target for mir396a-3p, miR8706a, and miR1886i-5p from the miRbase, but none of them was identified in the watermelon miRNAome. Furthermore, watermelon miRNAome does not contain a miRNA targeting ZYMV genome with an expectation score ≤ 3.5. There were 34 resistance genes (CC-NBS-LRR, TIR-NBS-LRR, TIR-NBS) predicted as targets of 32 miRNAs in healthy watermelon. For nine differentially expressed miRNAs the respective target genes (10 in total) were bioinformatically predicted. For cla-new_miR307 (upregulated upon ZYMV infection) and cla-miR166h-3p (downregulated upon ZYMV infection) the targets were predicted to beClaATRIPandClaRBOHB, respectively, withClaATRIPdownregulated andClaRBOHBupregulated upon ZYMV infection. ALSV-mediated VIGS ofClaATRIPrendered watermelon plants more resistant to ZYMV, whereas VIGS ofClaRBOHBresulted in higher levels of ZYMV titer in watermelon. These data suggest thatClaATRIPandClaRBOHBare a susceptibility and resistant gene, respectively. Our results provide new insights in watermelon miRNAome and could propose new strategies for generating resistant watermelon to ZYMV.

Highlights

Bioinformatics analysis in healthy and ZYMV-infected watermelon plants gave 353 miRNAs, 22 known and 331 new.

The watermelon miRNAome identified in the present study does not appear to target the ZYMV genome (sense and reverse complement).

The differential expression of ten genes of watermelon in relation to ZYMV infection was validated.

The silencing of the two genes,ATRIPandRBOHB, through VIGS strongly suggested thatATRIPis a gene of susceptibility andRBOHBis a gene of resistance.
A Web Service for Automated Design of Multiple Types of Ribozymes Targeting RNA: from minimal hammerhead to aptazymes
Authors: Najeh Sabrine , Kharma Nawwaf , Vaudry-Read Thomas , Haurie Anita , Paslawski Christopher , Adams Daniel , Ferreira Steve , Perreault Jonathan
Published: October 2023

Ribosoft 2.0 is the second version of a web service to design different types oftrans-acting conventional and allosteric ribozymes. The web service is publicly available athttps://ribosoft2.fungalgenomics.ca/. Ribosoft 2.0 uses template secondary structures that can be submitted by users to design ribozymes in accordance with parameters provided by the user. The generated designs specifically target a transcript (or, generally, an RNA sequence) given by the user. Herein, sixty ribozymes of different types were tested on two different mRNAs, with a majority shown to be active. We have also generated and proved the activity of the firsttrans-acting aptazyme designedin silico.
Positive Transfer of the Whisper Speech Transformer to Human and Animal Voice Activity Detection
Authors: Gu Nianlong , Lee Kanghwi , Basha Maris , Ram Sumit Kumar , You Guanghao , Hahnloser Richard H. R.
Published: October 2023

This paper introduces WhisperSeg, utilizing the Whisper Transformer pre-trained for Automatic Speech Recognition (ASR) for human and animal Voice Activity Detection (VAD). Contrary to traditional methods that detect human voice or animal vocalizations from a short audio frame and rely on careful threshold selection, WhisperSeg processes entire spectrograms of long audio and generates plain text representations of onset, offset, and type of voice activity. Processing a longer audio context with a larger network greatly improves detection accuracy from few labeled examples. We further demonstrate a positive transfer of detection performance to new animal species, making our approach viable in the data-scarce multi-species setting.1
Localization of Cadherins in the postnatal cochlear epithelium and their relation to space formation
Authors: Beaulac Holly J. , Munnamalai Vidhya
Published: October 2023

The sensory epithelium of the cochlea, the organ of Corti, has complex cytoarchitecture consisting of mechanosensory hair cells intercalated by epithelial support cells. The support cells provide important trophic and structural support to the hair cells. Thus, the support cells must be stiff yet compliant enough to withstand and modulate vibrations to the hair cells. Once the sensory cells are properly patterned, the support cells undergo significant remodeling from a simple epithelium into a structurally rigid epithelium with fluid-filled spaces in the murine cochlea. Cell adhesion molecules such as cadherins are necessary for sorting and connecting cells in an intact epithelium. To create the fluid-filled spaces, cell adhesion properties of adjoining cell membranes between cells must change to allow the formation of spaces within an epithelium. However, the dynamic localization of cadherins has not been properly analyzed as these spaces are formed. There are three cadherins that are reported to be expressed during the first postnatal week of development when the tunnel of Corti forms in the cochlea. In this study, we characterize the dynamic localization of cadherins that are associated with cytoskeletal remodeling at the contacting membranes of the inner and outer pillar cells flanking the tunnel of Corti.

Key findings

F-actin remodeling occurs between E18.5 to P7 in the cochlear sensory epithelium.

Transient changes of F-actin cytoskeleton drives epithelial morphogenesis.

Fluid-filled spaces in epithelium is driven by changes in cell adhesion.
Mfsd7b facilitates choline uptake and missense mutations affect choline transport function
Authors: Thuy Ha Hoa Thi , Sukumar Viresh Krishnan , Bao Chua Jonathan Wei , Nguyen Dat T. , Nguyen Toan Q. , Kim Lim Lina Hsiu , Cazenave-Gassiot Amaury , Nguyen Long N.
Published: October 2023

MFSD7b belongs to the Major Facilitator Superfamily of transporters that transport small molecules. Two isoforms of MFSD7b have been identified and they are reported to be heme exporters that play a crucial role in maintaining the cytosolic and mitochondrial heme levels, respectively. Mutations of MFSD7b (also known as FLVCR1) have been linked to retinitis pigmentosa, posterior column ataxia, and hereditary sensory and autonomic neuropathy. Although MFSD7b functions have been linked to heme detoxification by exporting excess heme from erythroid cells, it is ubiquitously expressed with a high level in the kidney, gastrointestinal tract, lungs, liver, and brain. Here, we showed that MFSD7b functions as a facilitative choline transporter. Expression of MFSD7b slightly but significantly increased choline import, while its knockdown reduced choline influx in mammalian cells. The influx of choline transported by MFSD7b is dependent on the expression of choline metabolizing enzymes such as choline kinase (CHKA), but it is independent from gradient of cations. Additionally, we showed that choline transport function of Mfsd7b is conserved from fly to man. Employing our transport assays, we showed that missense mutations of MFSD7b caused reduced choline transport functions. Our results show that MFSD7b functions as a facilitative choline transporter in mammalian cells.
A mobile intron facilitates interference competition between co-infecting viruses
Authors: Birkholz Erica A. , Morgan Chase J. , Laughlin Thomas G. , Lau Rebecca K. , Prichard Amy , Rangarajan Sahana , Meza Gabrielle N. , Lee Jina , Armbruster Emily G. , Suslov Sergey , Pogliano Kit , Meyer Justin R. , Villa Elizabeth , Corbett Kevin D. , Pogliano Joe
Published: October 2023

Mobile introns containing homing endonucleases are widespread in nature and have long been assumed to be selfish elements that provide no benefit to the host organism. These genetic elements are common in viruses, but whether they confer a selective advantage is unclear. Here we studied a mobile intron in bacteriophage ΦPA3 and found its homing endonuclease gp210 contributes to viral competition by interfering with the virogenesis of co-infecting phage ΦKZ. We show that gp210 targets a specific sequence in its competitor ΦKZ, preventing the assembly of progeny viruses. This work reports the first demonstration of how a mobile intron can be deployed to engage in interference competition and provide a reproductive advantage. Given the ubiquity of introns, this selective advantage likely has widespread evolutionary implications in nature.
Demographic profile, risk stratification, clinical characteristics, and treatment outcome of patients with multiple myeloma: A five-year retrospective study at a tertiary hospital in Ethiopia
Authors: Haile Ephrem , Tasew Adugna , Gebremedhin Amha , Sherif Abdulaziz , Tadesse Fissehatsion
Published: October 2023

Background

Patients with multiple myeloma are being seen at an increasing frequency in different indigenous African population. However, local data regarding the demographic profile, clinical characteristics, risk stratification, and treatment outcome of these patients is lacking. This study was designed to fill this existing gap in our setup. Hence, it will aid in the revision of treatment guidelines based on local data on the efficacy of existing treatment regimens and risk stratification of patients with a newly diagnosed multiple myeloma.

Methods

A single centered Hospital-based retrospective Cohort study was conducted from January 2015 to December 2019. Eighty patients with newly diagnosed MM who received non-proteasome inhibitor-based therapy at TASH, Addis Ababa, Ethiopia were analyzed in the study.

Results

Out of the 80 patients in this cohort, 51(63.8%) of the patients were males (M: F ratio 1.76:1)and the median age at diagnosis was 52 years. The commonest complications identified were anemia (56.3%) and pathologic fracture (55%). The commonest comorbid conditions were; systemic hypertension (24%), CKD (6.3%), and diabetes (5%). The median Progression-Free Survival (PFS) and Overall Survival (OS) of patients were found to be 17.5 and 20 months respectively. This study also identified factors like advanced DS stage, presence of plasmacytoma, renal dysfunction, elevated serum LDH, high levels of serum protein, and monoclonal M-protein to have adverse implication on the OS and PFS of patients.

Conclusion

Multiple Myeloma is more common in the male population group and our patients are younger than the western population. Myeloma treatment regimens like CP and CPT are found to be less effective in our patients than in patients elsewhere. This is likely to be due to the advanced stage at presentation. In resource-limited setups, where determination of cytogenetic features of myeloma is difficult, different clinical and laboratory parameters can still serve as prognostic markers of treatment outcome & patient survival.

Competing Interests

The authors declare that they have no competing interests
Knowledge, Attitude and Utilisation of Modern Contraceptives among Female Senior High School Students in the Kpando Municipality, Ghana
Authors: Debuo Der Amanda , Tarkang Elvis Enowbeyang
Published: October 2023

Background

Adolescent fertility regulation and pregnancy prevention is one of the most important healthcare issues of the twenty-first century. Contraceptive can potentially improve the quality of the lives of adolescents and their economic welfare by preventing unwanted pregnancies. Volta Region records one of the highest prevalence of teenage pregnancy and adolescents aged 15-19 years are the least acceptors of contraceptives in the Region. This study determined the knowledge, attitude and utilisation of modern contraceptives among female senior high school students in the Kpando Municipality.

Methods

A descriptive cross-sectional design was employed in this study with a stratified sample of 270 participants. Data were collected using a self-administered questionnaire and analysed using Stata Version 16. Descriptive statistics such as frequencies and percentages were used to summarise the data. Logistic regression analyses were used to test the association between the dependent and independent variables at the 0.05 significance level at a 95% confidence interval.

Results

The participants had adequate knowledge of modern contraceptives (78.5%) and their major source of information was the school (59.7%) with the most commonly known contraceptive being the condom (86.3%). School of attendance (AOR= 0.29), religion (AOR= 0.25), marital status (AOR= 0.47) and programme of study were significantly associated with knowledge of modern contraceptives. The attitude of respondents was also favourable (63%) but the majority reported that modern contraceptives could lead to bareness in the future (59.3%). Only school of attendance was significantly associated with attitude (AOR= 2.04). However, current utilisation of modern contraceptives was low (24.2%) and the majority revealed their source of modern contraceptives to be the pharmacy (63.1%). Also, school of attendance (AOR= 2.36), age (AOR= 2.45), marital status (AOR= 41.81) and grade level (AOR= 2.13) were significantly associated with the utilisation of modern contraceptives.

Conclusion

There was adequate knowledge and favourable attitude regarding contraceptives. However, utilisation was low. Health promotion campaigns to improve contraceptive use among SHS students in Kpando Municipality should target those in the lower grade levels, those between the ages of 12 and 17, those who are currently not in any relationship and include all students regardless of their programme of study.
Inferring plasticity rules from single-neuron spike trains using deep learning methods
Authors: Wang Xingyun , Béïque Jean-Claude , Naud Richard
Published: October 2023

Synaptic plasticity is a core basis for learning and adaptation. Determining how synapses are altered by local signals – the learning rules – is the hinge about which brain activity pivots. A large number of in vitro characterizations have focused on restricted sets of core properties, but it remains to be established which if any of the known learning rules is most consistent with changes in activity patterns in behaving animals. To address this question, we hypothesize that the correlation between features of the activity of a single post-synaptic neuron and subsequent changes of the representations could be used to detect the underlying learning rule. Because this correlation is expected to be diluted in the notoriously large variability of brain activity, we test here learning rule inference based on passive observations of single neurons using deep artificial neural networks. Using simulated data, we found that both transformers, temporal convolutional networks, and SVM could classify learning rules far above the chance level, with transformers achieving the best overall accuracy. This performance can be achieved despite the presence of noise and representational drift. We further investigated the features used by the algorithms to perform the classification and found the deep net used inner temporal differences of distinct learning rules to separate learning trajectories. We also find, however, that the classification accuracy is sensitive to alterations in network properties. Our work illustrates that distinct learning rules’ generate distinguishable trajectories of responses, but warns against using simulation-trained classifiers to infer learning rules from real data.
RECLUSIVE CHANDELIERS: FUNCTIONAL ISOLATION OF DENTATE AXO-AXONIC CELLS AFTER EXPERIMENTAL STATUS EPILEPTICUS
Authors: Proddutur Archana , Nguyen Susan , Yeh Chia-Wei , Gupta Akshay , Santhakumar Vijayalakshmi
Published: October 2023

Axo-axonic cells (AACs) provide specialized inhibition to the axon initial segment (AIS) of excitatory neurons and can regulate network output and synchrony. Although hippocampal dentate AACs are structurally altered in epilepsy, physiological analyses of dentate AACs are lacking. We demonstrate that parvalbumin neurons in the dentate molecular layer express PTHLH, an AAC marker, and exhibit morphology characteristic of AACs. Dentate AACs show high-frequency, non-adapting firing but lack persistent firing in the absence of input and have higher rheobase than basket cells suggesting that AACs can respond reliably to network activity. Early after pilocarpine-induced status epilepticus (SE), dentate AACs receive fewer spontaneous excitatory and inhibitory synaptic inputs and have significantly lower maximum firing frequency. Paired recordings and spatially localized optogenetic stimulation revealed that SE reduced the amplitude of unitary synaptic inputs from AACs to granule cells without altering reliability, short-term plasticity, or AIS GABA reversal potential. These changes compromised AAC-dependent shunting of granule cell firing in a multicompartmental model. These early post-SE changes in AAC physiology would limit their ability to receive and respond to input, undermining a critical brake on the dentate throughput during epileptogenesis.
Disrupted Ecology andH. parainfluenzaeDistinguish the Gut Microbiota of an Ethnic Minority Predisposed to Type 2 Diabetes Mellitus
Authors: Nayman Eric I. , Schwartz Brooke A. , Polmann Michaela , Gumabong Alayna C. , Nieuwdorp Max , Cickovski Trevor , Mathee Kalai
Published: October 2023

Purpose

Decreased gut microbiota production of short-chain fatty acids (SCFAs) has been implicated in type 2 diabetes mellitus (T2DM) disease progression. Most microbiome studies focus on ethnic majorities. This study aims to understand microbiome differences between an ethnic majority (the Dutch) and minority (the South-Asian Surinamese (SAS)) group with a lower and higher prevalence of T2DM, respectively.

Methods

Microbiome data from the Healthy Life in an Urban Setting (HELIUS) cohort were used. The 16S rRNA V4 region was sequenced. Two age– and gender-matched groups were compared: the Dutch (n = 41) and SAS (n = 43). Microbial compositions were generated via DADA2. Alpha and beta-diversity and Principal Coordinate Analysis (PCoA) were computed. DESeq2 differential bacterial abundance and LEfSe biomarker analyses were performed to determine discriminating features. Co-occurrence networks were constructed to examine gut ecology.

Results

A tight cluster of bacterial abundances was observed in the Dutch women, which overlapped with some of the SAS microbiomes. The Dutch gut contained a more interconnected microbial ecology, whereas the SAS network was dispersed.Bacteroides caccae, Butyricicoccus, Alistipes putredinis, Coprococcus comes,Odoribacter splanchnicus,andLachnospiracharacterized the Dutch gut.Haemophilus,Bifidobacterium,andAnaerostipes hadruscharacterized the SAS gut. All butLachnospiraand certain strains ofHaemophilusare known SCFA producers.

Conclusion

The Dutch gut microbiome was distinguished from the SAS by diverse, differentially abundant SCFA-producing taxa with significant cooperation. The dynamic ecology observed in the Dutch was lost in the SAS. The higher prevalence of T2DM in the SAS may be associated with the dysbiosis observed.
PhyGCN: Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning
Authors: Deng Yihe , Zhang Ruochi , Xu Pan , Ma Jian , Gu Quanquan
Published: October 2023

Hypergraphs are powerful tools for modeling complex interactions across various domains, including biomedicine. However, learning meaningful node representations from hypergraphs remains a challenge. Existing supervised methods often lack generalizability, thereby limiting their real-world applications. We propose a new method, Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning (PhyGCN), which leverages hypergraph structure for self-supervision to enhance node representations. PhyGCN introduces a unique training strategy that integrates variable hyperedge sizes with self-supervised learning, enabling improved generalization to unseen data. Applications on multi-way chromatin interactions and polypharmacy side-effects demonstrate the effectiveness of PhyGCN. As a generic framework for high-order interaction datasets with abundant unlabeled data, PhyGCN holds strong potential for enhancing hypergraph node representations across various domains.
An exploratory review of resiliency assessments after brain injury
Authors: Griffioen Janna , Gingrich Nicole , Pollock Courtney , Schmidt Julia
Published: October 2023

Objective

To identify resiliency measures which have been established for use with people after acquired brain injury, using the process-based Traumatic Brain Injury Resiliency Model as the guiding conceptual framework.

Method

Databases CINAHL, EMBASE, Medline, and PsychINFO were searched. Using COnsensus based Standards for the selection of Health guidelines of health status Measurement INstruments (COSMIN) guidelines for reporting, articles providing data on psychometric properties for measures of resilience for people with brain injury were retrieved. Psychometric properties and clinical utility (number of items, scoring details) were summarized.

Results

Nine articles were retrieved, including 9 measures of resiliency.

Conclusion

There are established measures of resiliency in brain injury rehabilitation. Future work may explore use of these measures in a clinical context and implementation of rehabilitation goals for improving resiliency after brain injury.
CarDS-Plus ECG Platform: Development and Feasibility Evaluation of a Multiplatform Artificial Intelligence Toolkit for Portable and Wearable Device Electrocardiograms
Authors: Shankar Sumukh Vasisht , Oikonomou Evangelos K , Khera Rohan
Published: October 2023

In the rapidly evolving landscape of modern healthcare, the integration of wearable and portable technology provides a unique opportunity for personalized health monitoring in the community. Devices like the Apple Watch, FitBit, and AliveCor KardiaMobile have revolutionized the acquisition and processing of intricate health data streams that were previously accessible only through devices only available to healthcare providers. Amidst the variety of data collected by these gadgets, single-lead electrocardiogram (ECG) recordings have emerged as a crucial source of information for monitoring cardiovascular health. Notably, there has been significant advances in artificial intelligence capable of interpreting these 1-lead ECGs, facilitating clinical diagnosis as well as the detection of rare cardiac disorders. This design study describes the development of an innovative multi-platform system aimed at the rapid deployment of AI-based ECG solutions for clinical investigation and care delivery. The study examines various design considerations, aligning them with specific applications, and develops data flows to maximize efficiency for research and clinical use. This process encompasses the reception of single-lead ECGs from diverse wearable devices, channeling this data into a centralized data lake, and facilitating real-time inference through AI models for ECG interpretation. An evaluation of the platform demonstrates a mean duration from acquisition to reporting of results of 33.0 to 35.7 seconds, after a standard 30 second acquisition, allowing the complete process to be completed in 63.0 to 65.7 seconds. There were no substantial differences in acquisition to reporting across two commercially available devices (Apple Watch and KardiaMobile). These results demonstrate the succcessful translation of design principles into a fully integrated and efficient strategy for leveraging 1-lead ECGs across platforms and interpretation by AI-ECG algorithms. Such a platform is critical to translating AI discoveries for wearable and portable ECG devices to clinical impact through rapid deployment.