bluuebunny/crossref_metadata_2025 huggingface dataset:
Surprising connections between DNA binding and function for the near-complete set of yeast transcription factors
Authors: Mahendrawada Lakshmi , Warfield Linda , Donczew Rafal , Hahn Steven
Published: July 2023

DNA sequence-specific transcription factors (TFs) modulate transcription and chromatin architecture, acting from regulatory sites in enhancers and promoters of eukaryotic genes. How TFs locate their DNA targets and how multiple TFs cooperate to regulate individual genes is still unclear. Most yeast TFs are thought to regulate transcription via binding to upstream activating sequences, situated within a few hundred base pairs upstream of the regulated gene. While this model has been validated for individual TFs and specific genes, it has not been tested in a systematic way with the large set of yeast TFs. Here, we have integrated information on the binding and expression targets for the near-complete set of yeast TFs. While we found many instances of functional TF binding sites in upstream regulatory regions, we found many more instances that do not fit this model. In many cases, rapid TF depletion affects gene expression where there is no detectable binding of that TF to the upstream region of the affected gene. In addition, for most TFs, only a small fraction of bound TFs regulates the nearby gene, showing that TF binding does not automatically correspond to regulation of the linked gene. Finally, we found that only a small percentage of TFs are exclusively strong activators or repressors with most TFs having dual function. Overall, our comprehensive mapping of TF binding and regulatory targets have both confirmed known TF relationships and revealed surprising properties of TF function.
Atypical Biological Motion Perception in Children with Attention Deficit Hyperactivity Disorder: Local Motion and Global Configuration Processing
Authors: Tian Junbin , Yang Fang , Wang Ying , Wang Li , Wang Ning , Jiang Yi , Yang Li
Published: July 2023

Perceiving biological motion (BM) is crucial for human survival and social interaction. Many studies have reported impaired BM perception in autism spectrum disorder, which is characterised by deficits in social interaction. Children with attention deficit hyperactivity disorder (ADHD) often exhibit similar difficulties in social interaction. However, few studies have investigated BM perception in children with ADHD. Here, we compared differences in the ability to process local kinematic and global configurational cues, two fundamental abilities of BM perception, between typically developing and ADHD children. We further investigated the relationship between BM perception and social interaction skills measured using the Social Responsiveness Scale and examined the contributions of latent factors (e.g., sex, age, attention, and intelligence) to BM perception. The results revealed that children with ADHD exhibited atypical BM perception. Local and global BM processing showed distinct features. Local BM processing ability was related to social interaction skills, whereas global BM processing ability significantly improved with age. Critically, general BM perception (i.e., both local and global BM processing) may be affected by sustained attentional ability in children with ADHD. This relationship was primarily mediated by reasoning intelligence. These findings elucidate atypical BM perception in ADHD and the latent factors related to BM perception. Moreover, this study provides new evidence that BM perception is a hallmark of social cognition and advances our understanding of the potential roles of local and global processing in BM perception and social cognitive disorders.
Overcoming the nutritional immunity by engineering iron scavenging bacteria for cancer therapy
Authors: Huang Sin-Wei , Lim See-Khai , Yu Yao-An , Pan Yi-Chung , Lien Wan-Ju , Mou Chung-Yuan , Hu Che-Ming Jack , Mou Kurt Yun
Published: July 2023

Certain bacteria demonstrate the ability to target and colonize the tumor microenvironment, a characteristic that positions them as innovative carriers for delivering various therapeutic agents in cancer therapy. Nevertheless, our understanding of how bacteria adapt their physiological condition to the tumor microenvironment remains elusive. In this work, we employed liquid chromatography-tandem mass spectrometry to examine the proteome ofE. colicolonized in murine tumors. Comparing toE. colicultivated in the rich medium, we found thatE. colicolonized in tumors notably upregulated the processes related to ferric ions, including the enterobactin biosynthesis and iron homeostasis. This finding indicated that the tumor is an iron-deficient environment toE. coli. We also found that the colonization ofE. coliin the tumor led to an increased expression of lipocalin 2 (LCN2), a host’s protein that can sequester the enterobactin. We therefore engineeredE. coliin order to evade the nutritional immunity provided by LCN2. By introducing the IroA cluster, theE. colisynthesizes the glycosylated enterobactin, which creates steric hindrance to avoid the LCN2 sequestration. The IroA-E. colishowed enhanced resistance to LCN2 and significantly improved the anti-tumor activity in mice. Moreover, the mice cured by the IroA-E. colitreatment became resistant to the tumor re-challenge, indicating the establishment of immunological memory. Overall, our study underscores the crucial role of bacteria’s ability to acquire ferric ions within the tumor microenvironment for effective cancer therapy.
Proteomic analysis of human serum Extracellular Vesicles reveals early diagnostic markers for Amyotrophic Lateral Sclerosis
Authors: Vassileff Natasha , Leblanc Pascal , Bernard Emilien , Fourier Anthony , Quadrio Isabelle , Lowe Rohan G. T. , Spiers Jereme G. , Hill Andrew F. , Cheng Lesley
Published: July 2023

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by the deposition of misfolded proteins leading to the death of motor neurons. Several ALS-associated proteins, including TAR DNA-binding protein 43 (TDP-43) and Superoxide dismutase-1 (SOD-1), have been linked to small extracellular vesicles (EVs). However, the role of these EVs and their cargo in ALS patients, prior to treatment intervention, has not been investigated. This study aims to identify the earliest protein changes facilitated by EVs in ALS by examining the serum of recently diagnosed ALS patients. EVs were isolated from the serum of ALS (n = 25) and healthy control (HC, n = 9) patients before undergoing proteomics analysis. This resulted in the identification of a panel of 9 significantly up-regulated proteins and included haptoglobin and hemoglobin subunits, complement, and afamin, which are involved in pathways including heme homeostasis and autophagy. The identification of haptoglobin in ALS serum EVs suggests it has potential as an early diagnostic biomarker whilst activation of autophagy pathways suggests early recruitment of clearance pathways in ALS. This study uncovers the processes and proteins facilitated through small EVs in the initial stages of ALS. Proteomics data are available via ProteomeXchange with identifier PXD036652.

Statement of significance of the study

The role of small EVs, which are involved in cell-to-cell communication, and their cargo in the initiation of ALS has not been investigated. This study is the first to identify the earliest protein changes occurring in ALS through small EV facilitation. This study examined serum from newly diagnosed ALS patients, prior to treatment intervention. Therefore, the EVs, isolated from ALS and healthy control patients, captured novel ALS associated changes without confoundment from medication, which could mask early changes. A panel of 9 statistically up-regulated proteins was identified after mass spectrometry analysis. These included: haptoglobin and hemoglobin subunits, complement, and afamin. The identification of up-regulated levels of these proteins in the ALS serum EVs suggests they have potential as diagnostic biomarkers whilst identifying pathways including chaperone mediated autophagy (CMA) and microautophagy suggests early recruitment of clearance pathways in ALS. Therefore, this study uncovered the proteins being facilitated through small EVs in the initial stages of ALS.
Machine-learning approach for Type 2 Diabetes diagnosis and prognosis models over heterogeneous feature spaces
Authors: Navarro-Cerdán J.Ramón , Pons-Suñer Pedro , Arnal Laura , Arlandis Joaquim , Llobet Rafael , Pérez-Cortés Juan-Carlos , Lara-Hernández Francisco , Alvarez Luis , García-García Ana-Bárbara , Chaves Felipe Javier
Published: July 2023

This research aims to evaluate the Type 2 Diabetes (T2D) diagnosis and prognosis power from heterogeneous environmental, lifestyle and biochemistry data. Model estimation has previously addressed three main actions as: 1) Missingvalue imputation using specific univariant and multivariant imputers accommodated to each particular feature; 2) Quasi-constancy detection in variables; 3) Constructing geographical pollution and rent data from municipality information. Next, different T2D diagnosis and prognosis models are fitted and evaluated, showing increasing performance as more specific features become available while the prediction cost rises as a consequence of requiring more specific data. Finally, four models are obtained: two of them for T2D diagnosis and the other two for T2D prognosis respectively, with performances ranging from 73.3 to 95.41 AUC-ROC. One pair of diagnosis and prognosis models were thought for a global testing that can be done in general locations by only asking general lifestyle-related questions. On the other hand, the other pair, which achieves higher performances, is thought to be applied in a clinical environment where it is easy to obtain more specific biochemistry measures.
Routine surveillance of kidney allograft rejection using a fully automated urinary CXCL9 and CXCL10 immunoassay
Authors: Tinel Claire , Sauvaget Virginia , Aouni Laïla , Lamarthée Baptiste , Leclaire Charlotte , Legendre Christophe , Marquet Pierre , Normand Corinne , Rabant Marion , Terzi Fabiola , Anglicheau Dany
Published: July 2023

Background

For kidney transplant recipients, assessing non-invasively the individualized risk of acute rejection is one of the most unmet need. Urinary chemokines are one of the short-term most promising biomarkers, because of their simple and low-cost analytical method in easily accessible samples, and their high diagnostic performance consistently assessed over the last decade. In this study, we aimed at confronting all practical issues of routine implementation of kidney allograft rejection monitoring using urine CXCL9 and CXCL10.

Methods

The next-generation immunoassay Ella® was investigated as feasible quantification platform, from sample collection to render of the results. Urine CXCL9/10 levels were measured using Ella® microfluidic cartridges, across preanalytical (sample preparation, storage conditions, freeze-thaw cycles) and analytical (linearity, ranges, intra/inter-assay variability) performances studies, and diagnostic accuracy was assessed in comparison to the ELISA reference method, in urine samples from previously published cohorts.

Results

Upon assay preparation, Ella® appeared very efficient with a minimal workflow (urine sample thaw> centrifugation>1:2 dilution>loading) and a time to result of 90 minutes. Preanalytical studies showed high stability of urine CXCL9/10 levels across various temperatures (4° vs 25°C) and time (24/48/72H) before storage and over 5 freeze-thaw cycles. How complex urine matrix, analytical studies confirmed excellent linearity of dosage, as well as intra-assay (≤5%) and inter-assay precision. Across 1024 samples, Ella® results were highly correlated to those quantified by ELISA (P<0.0001), and further entered into our previously validated urine chemokine model. 268 out of the 1024 samples were collected at time of acute rejection (26.2%). In this cohort, accuracy was 0.85 for acute rejection diagnosis.

Conclusion

Ella® fulfils all prerequisites for clinical implementation of urinary chemokines monitoring. It has proven a robust, easy-to-use platform with unprecedented validation to quantify urine chemokines.
Human and computer attention in assessing genetic conditions
Authors: Duong Dat , Johny Anna Rose , Hanchard Suzanna Ledgister , Fortney Chris , Hellmann Fabio , Hu Ping , Javanmardi Behnam , Moosa Shahida , Patel Tanviben , Persky Susan , Sümer Ömer , Tekendo-Ngongang Cedrik , Hsieh Tzung-Chien , Waikel Rebekah L. , André Elisabeth , Krawitz Peter , Solomon Benjamin D.
Published: July 2023

Deep learning (DL) and other types of artificial intelligence (AI) are increasingly used in many biomedical areas, including genetics. One frequent use in medical genetics involves evaluating images of people with potential genetic conditions to help with diagnosis. A central question involves better understanding how AI classifiers assess images compared to humans. To explore this, we performed eye-tracking analyses of geneticist clinicians and non-clinicians. We compared results to DL-based saliency maps. We found that human visual attention when assessing images differs greatly from the parts of images weighted by the DL model. Further, individuals tend to have a specific pattern of image inspection, and clinicians demonstrate different visual attention patterns than non-clinicians.
Impact of Community Masking on SARS-CoV-2 Transmission in Ontario after Adjustment for Differential Testing by Age and Sex
Authors: Peng Amy , Bosco Savana , Simmons Alison , Tuite Ashleigh R. , Fisman David N.
Published: July 2023

Background

Use of masks and respirators for prevention of respiratory infectious disease transmission is not new, but has proven controversial, and even politically polarizing during the SARS-CoV-2 pandemic. In the Canadian province of Ontario, mask mandates were introduced by the 34 regional health authorities in an irregular fashion from June to September 2020, creating a quasi-experiment that can be used to evaluate impact of community mask mandates. Ontario SARS-CoV-2 case counts were strongly biased by testing focussed on long-term care facilities and healthcare workers. We developed a simple regression-based test-adjustment method that allowed us to adjust cases for undertesting by age and gender. We used this test- adjusted time series to evaluate mask mandate effectiveness.

Methods

We evaluated the effect of masking using count-based regression models that allowed adjustment for age, sex, public health region and time trends with either reported (unadjusted) cases, or testing-adjusted case counts, as dependent variables. Mask mandates were assumed to take effect in the week after their introduction. Model based estimates of effectiveness were used to estimate the fraction of SARS- CoV-2 cases, severe outcomes, and costs, averted by mask mandates.

Results

Models that used unadjusted cases as dependent variable identified protective effects of masking (effectiveness 15-42%), though effectiveness was variably statistically significant, depending on model choice. Mask effectiveness in models predicting test-adjusted case counts was substantially higher, ranging from 49% (44- 53%) to 73% (48-86%) depending on model choice. Effectiveness was greater in women than men (P = 0.016), and in urban health units as compared to rural units (P < 0.001). The prevented fraction associated with mask mandates was 46% (41-51%), averting approximately 290,000 clinical cases, averting 3008 deaths and loss of 29,038 QALY. Costs averted represented $CDN 610 million in economic wealth.

Conclusions

Lack of adjustment for SARS-CoV-2 undertesting in younger individuals and males generated biased estimates of infection risk and obscures the impact of public health preventive measures. After adjustment for under-testing, the effectiveness of mask mandates emerges as substantial, and robust regardless of model choice. Mask mandates saved substantial numbers of lives, and prevented economic costs, during the SARS-CoV-2 pandemic in Ontario, Canada.
Drivers of bias in diagnostic test accuracy estimates when using expert panels as a reference standard
Authors: Kellerhuis BE , Jenniskens K , Schuit E , Hooft L , Moons KGM , Reitsma JB
Published: July 2023

Objectives

To assess the impact of study and expert panel characteristics on index test diagnostic accuracy estimates.

Study Design and Setting

Simulations were performed in which an expert panel was used as reference standard to estimate the sensitivity and specificity of an index diagnostic test. Diagnostic accuracy was determined by combining probability estimates of target condition presence, as provided by experts using four component reference tests, through a predefined threshold. Study and panel characteristics were varied in several scenarios: target condition prevalence (20%, 40%, 50%), accuracy of component reference tests (70%, 80%, mixed), expert panel size (2, 3, 10), study population size (360, 1000), and random or systematic differences between expert’s probability estimates. Bias in accuracy estimates across all possible true index test values was quantified for all scenarios. The total bias in each scenario was quantified using the mean squared error (MSE).

Results

When estimating an index test with 80% sensitivity and 70% specificity, bias in these estimates was hardly affected by the study population size or the number of experts. When one expert was systematically biased, bias in sensitivity and specificity estimates increased, but this effect lessened when the number of experts in the panel was higher. Prevalence had a large effect on bias, scenarios with a prevalence of 0.5 estimated sensitivity between 63.3% and 76.7% and specificity between 56.1% and 68.7%, whereas scenarios with a prevalence of 0.2 estimated sensitivity between 48.5% and 73.3% and specificity between 65.5% and 68.7%. Random and systematic differences between experts also increased bias, with estimated sensitivity between 48.6% and 77.4% and specificity between 59.1% and 69.1% as opposed to scenarios without random or systematic differences, which estimated sensitivity between 58.0% and 77.4% and specificity between 56.1% and 69.1%. More accurate component reference tests also reduced bias. Scenarios with four component tests of 80% sensitivity and specificity estimated index test sensitivity between 60.1% and 77.4% and specificity between 62.9% and 69.1%, whereas scenarios with four component tests of 70% sensitivity and specificity estimated index test sensitivity between 48.5% and 73.4% and specificity between 56.1% and 67.0%.

Conclusion

Bias in accuracy estimates when using an expert panel will increase if the component reference tests (combined) are less accurate. Prevalence, the true value of the index test accuracy, and random or systematic differences between experts can also impact the amount of bias, but the amount and even direction will vary between scenarios.
Functionalizing face masks with natural clays: preliminary results
Authors: Hernández D. , Rodríguez-de-Torner L. A. , Altshuler E. , Rivera A.
Published: July 2023

The materials used in the fabrication of standard, three-layered surgical masks are functionalized by the incorporation of Cuban natural clay with potential microbicidal properties. Different treatments involving aqueous solutions of bentonite (Bent) clay and small amounts of a cationic surfactant are studied. Optical microscopy indicates that the clay particles are effectively adhered to the fibers forming the mask layers. The capacity of the materials to block ballistic droplets showed to be very high for the external and medium layers of a surgical mask both before and after functionalization. However, functionalization demonstrated to increase the blocking capacity of the material in the inner layer, i.e., that closer to the user’s face.
Unveiling the Genetic Landscape of Basal Ganglia: Implications for Common Brain Disorders
Authors: Bahrami Shahram , Nordengen Kaja , Rokicki Jaroslav , Shadrin Alexey A. , Rahman Zillur , Smeland Olav B. , Jaholkowski Piotr Pawel , Parker Nadine , Parekh Pravesh , O’Connell Kevin S. , Elvsåshagen Torbjørn , Toft Mathias , Djurovic Srdjan , Dale Anders M. , Westlye Lars T. , Kaufmann Tobias , Andreassen Ole A.
Published: July 2023

The basal ganglia are subcortical brain structures involved in motor control, cognition, and emotion regulation. We conducted a multivariate genome-wide association analysis (GWAS) to explore the genetic architecture of basal ganglia volumes using brain scans obtained from 34,794 European individuals with replication in 5,236 non-Europeans. We identified 72 genetic loci associated with basal ganglia volumes with a replication rate of 87.5%, revealing a distributed genetic architecture across basal ganglia structures. Of the 72 loci, 51 are novel. Of these,APOE,NBR1andHLAA, are all exonic and among the novel loci. Furthermore, we examined the genetic overlap between basal ganglia volumes and several neurological and psychiatric disorders. The most prominent overlap was seen with Parkinson’s disease, schizophrenia and migraine.HPandTMEM161Bshowed overlap between basal ganglia and Parkinson’s disease, but also three different psyciatric or nevrodevelopmental disorder(s), demonstrating important shared biology between brain disorders. Functional analyses implicated neurogenesis, neuron differentiation and development in basal ganglia volumes. These results enhance our understanding of the genetic architecture and molecular associations of basal ganglia structure and their role in brain disorders.
Attitudes and Perceptions of Medical Researchers Towards the Use of Artificial Intelligence Chatbots in the Scientific Process: A Protocol for a Cross-Sectional Survey
Authors: Ng Jeremy Y. , Maduranayagam Sharleen G. , Lokker Cynthia , Iorio Alfonso , Haynes R. Brian , Moher David
Published: July 2023

Artificial intelligence (AI) refers to computer systems or robots that can perform tasks associated with human intelligence, such as reasoning, problem-solving, and learning. While AI programs have not matched human versatility, they are increasingly used in various domains like self-driving cars, speech transcription, medical diagnosis, and smart assistants. AI has benefited fields like medicine, healthcare, and scientific research by improving productivity, reducing errors, and lowering costs. AI chatbots are conversational programs used for customer service, mental health support, and education. In scientific research, chatbots have the potential to automate tasks like literature searches, data analysis, and manuscript writing, improving efficiency and addressing the reproducibility crisis. However, there are challenges to overcome, including accuracy, reliability, ethical concerns, and limitations of current chatbot models. Scholarly publishing faces debates about authorship and guidelines have been established by journals and publishing organizations regarding the use of AI chatbots. To understand researchers’ attitudes towards AI chatbots, an international survey is proposed to explore their familiarity, perceived benefits, limitations, and factors influencing adoption. Findings can guide policy development and implementation of AI chatbots in scientific research.
Interaction of Post-Traumatic Stress Disorder and Race on Readmissions after Stroke
Authors: Lin Chen , King Peter H. , Richman Joshua , Davis Lori L.
Published: July 2023

Background

There is limited research on outcomes of patients with post-traumatic stress disorder (PTSD) who also develop stroke, particularly regarding racial disparities. Our goal was to determine whether PTSD is associated with the risk of hospital readmission after stroke and if racial disparities existed.

Methods

The analytical sample consisted of all veterans receiving care in the Veterans Health Administration (VHA) who were identified as having a new stroke requiring inpatient treatment based on International Classification of Diseases codes. The retrospective cohort data was obtained from the VA Corporate Data Warehouse. The main outcome was any readmission to VHA. The hypothesis that PTSD is associated with readmission after stroke was tested using Cox regression adjusted for patient characteristics with PTSD as a time-varying covariate.

Results

Our final cohort consisted of 93,652 patients with inpatient stroke diagnosis and no prior VHA codes for stroke starting from 1999 with follow-up through 6-August-2022. Of these patients, 12,916 (13.8%) had comorbid PTSD. Of the final cohort, 16,896 patients (18.0%) with stroke were readmitted. Our fully-adjusted model for readmission found an interaction between African Americans (AA) and PTSD with a hazard ratio of 1.09 (95% CI 1.00-1.20; p<0.05). In stratified models, PTSD has a significant HR of 1.10 (1.02-1.18, p=0.01) for AA but not White veterans 1.05 (0.99-1.11, p=0.10).

Conclusion

Among AA Veterans who suffered stroke, pre-existing PTSD was associated with increased risk of readmission, which was not significant among White veterans. This study highlights the need to focus on high-risk groups to reduce readmissions after stroke.
Interventions to reduce peripheral blood culture contamination in acute care settings: A systematic review and meta-analysis
Authors: Hughes James A. , Cabilan C.J. , Williams Julian , Ray Mercedes , Coyer Fiona
Published: July 2023

Background

Blood culture contamination is a significant problem in acute care settings. Contamination of a blood sample with pathogens not present in the patient’s blood leads to increases in length of stay, overuse of antimicrobials, and increases in healthcare cost. Several interventions have been reported in different settings within the literature to decrease the contamination. However, their overall effectiveness is currently unknown.

Objective

This systematic review aimed to identify interventions to reduce contamination from peripherally collected blood cultures and to evaluate the effectiveness of these interventions.

Design

Systematic review and meta-analysis

Methods

In March 2019 we performed a systematic search of English language literature from academic databases, registers of clinical trials and grey literature for interventions aimed at reducing blood culture contamination in adult acute care settings. Studies meeting inclusion criteria were reviewed and data were extracted by two independent reviewers.

Results

A total of 6,302 articles were retrieved from searches. After removal of duplicates and screening against inclusion criteria 57 studies were included. The majority of the 57 studies had a medium to high risk of bias. These studies identified eight specific interventions (collection packs, dedicated collection teams, education, staff feedback, intervention bundle, sterile procedure, Initial Specimen Diversion Devices, or change of asepsis solution) used in acute care. Thirty-four studies were included in the meta-analysis. There was a wide variation in the definition of contamination which precluded many studies from being included in the meta-analysis. Dedicated collection teams (RR 0.40, 95%CI 0.21 – 0.76, I287%, p<0.001) and initial specimen diversion devices (RR 0.43, 95%CI0.31 – 0.58, I284%, p<0.001) were the most successful at reducing blood culture contamination. Heterogeneity was high across all studies and interventions.

Conclusions

The use of dedicated collection teams or initial specimen diversion devices showed the most significant reduction in blood culture contamination; however, other interventions such as intervention bundles, education or feedback, may have benefits in terms of ease of implementation, and have still been shown to lower blood culture contamination.
Multi-region spatial transcriptome analysis reveals cellular networks and pathways associated with hepatocellular carcinoma recurrence
Authors: Aiderus Aziz , Seshachalam Pratap Veerabrahma , Idzham Khaireen , Caldez Matias , Shanmugam Raghuvaran , Sari Ita Novita , Ying Dorcas Hei Hui , Chong Shay Lee , Sekar Karthik , Chew Sin Chi , Chen Gao Bin , Chung Alexander Yaw-Fui , Cheow Peng Chung , Kam Juinn Huar , Kow Alfred Wei-Chieh , Ganpathi Iyer Shridhar , Loong Shihleone , Leow Wei-Qiang , Chen Kaina , Chanwat Rawisak , de Villa Vanessa H. , Koh Peng Soon , Bonney Glenn K , Goh Brian K. P. , Tam Wai Leong , Tergaonkar Vinay , Chow Pierce Kah Hoe
Published: July 2023

Hepatocellular carcinomas (HCC) are driven by various etiologies and molecular diversity at presentation. Patient prognosis post-surgery is generally dismal, and the majority respond poorly to adjuvant targeted and/or immuno-therapies. Tumours are an ecosystem comprised of organization and interaction between different cell types that may contribute to clinically significant outcomes, such as disease recurrence. To better understand this phenomenon, we leveraged on a local cohort of patients with or without recurrence to generate spatial transcriptome profiles from multiple sectors from each tumour. We identified widespread gene expression intra- and inter tumour heterogeneity observed across the tumour sectors. Our analysis also revealed the cell type enrichment and localization, and ligand-receptor interactions identify a specific subset of endothelial cell enriched in primary tumours of patients with recurrence. Altogether, this study describes the spatial gene expression landscape in HCC patients associated with disease recurrence.
Exploring the Relation Between Stiffness Perception and Action Using Models and Artificial Neural Networks
Authors: Lev Hanna Kossowsky , Nisky Ilana
Published: July 2023

Applying artificial skin stretch with force feedback increases perceived stiffness and affects grip force. We explored if participants’ perceptual responses in a stiffness discrimination task could be predicted solely from their action signals using models and artificial neural networks. Successful prediction could indicate a relation between participants’ perception and action. We found that the skin stretch perceptual augmentation could be predicted to an extent from action signals alone. We predicted the general trend of increased predicted augmentation for increased real augmentation, and average augmentation effect across participants, but not the precise effect sizes of individual participants. This indicates some relation between participants’ perceptual reports and action signals, enabling the partial prediction. Furthermore, of the action signals examined, grip force was necessary for predicting the augmentation effect, and a motion signal (e.g., position) was needed for predicting human-like perception, shedding light on what information may be present in the different signals.
Survey of commercial antibodies targeting Y chromosome-encoded genes
Authors: Gelfand Bradley D. , Argyle Dionne A. , Olivieri Joseph J. , Ambati Jayakrishna
Published: July 2023

Commercial antibodies are both a mainstay of biomedical research and subject to increasingly widespread scrutiny for their specificity. We evaluated the specificity of commercially available research grade antibodies by investigating those whose antigen targets are encoded by the Y chromosome. We assessed vendor-provided validation data such as immunoblotting and identified 65 commercial research grade antibodies that exhibited positive reactivity in female-derived tissues and/or cell lines. A thorough analysis of 30 commercial antibodies marketed as targeting the Y chromosome-encoded protein DDX3Y found that 16 (53%) provided no marketing data on specificity, 9 (30%) provided positive data in female or likely female materials, 4 (13%) provided only positive data in male materials, and 1 (3%) provided positive data in male materials and negative data in female materials. Together, these findings suggest that many commercial antibodies may be unsuitable to distinguish between related X and Y chromosome-encoded gene pairs and should instill caution in researchers using these tools to investigate sex chromosome-encoded proteins.
A dynamic generative model can extract interpretable oscillatory components from multichannel neurophysiological recordings
Authors: Das Proloy , He Mingjian , Purdon Patrick L.
Published: July 2023

Modern neurophysiological recordings are performed using multichannel sensor arrays that are able to record activity in an increasingly high number of channels numbering in the 100’s to 1000’s. Often, underlying lower-dimensional patterns of activity are responsible for the observed dynamics, but these representations are difficult to reliably identify using existing methods that attempt to summarize multivariate relationships in a post-hoc manner from univariate analyses, or using current blind source separation methods. While such methods can reveal appealing patterns of activity, determining the number of components to include, assessing their statistical significance, and interpreting them requires extensive manual intervention and subjective judgement in practice. These difficulties with component selection and interpretation occur in large part because these methods lack a generative model for the underlying spatio-temporal dynamics. Here we describe a novel component analysis method anchored by a generative model where each source is described by a bio-physically inspired state space representation. The parameters governing this representation readily capture the oscillatory temporal dynamics of the components, so we refer to it as Oscillation Component Analysis (OCA). These parameters – the oscillatory properties, the component mixing weights at the sensors, and the number of oscillations – all are inferred in a data-driven fashion within a Bayesian framework employing an instance of the expectation maximization algorithm. We analyze high-dimensional electroencephalography and magnetoencephalography recordings from human studies to illustrate the potential utility of this method for neuroscience data.

Significance Statement

Neuroscience studies often involve simultaneous recordings in a large number of sensors in which a smaller number of dynamic components generate the complex spatio-temporal patterns observed in the data. Current blind source separation techniques produce sub-optimal results and are difficult to interpret because these methods lack an appropriate generative model that can guide both statistical inference and interpretation. Here we describe a novel component analysis method employing a dynamic generative model that can decompose high-dimensional multivariate data into a smaller set of oscillatory components are learned in a data-driven way, with parameters that are immediately interpretable. We show how this method can be applied to neurophysiological recordings with millisecond precision that exhibit oscillatory activity such as electroencephalography and magnetoencephalography.
CAVE: Connectome Annotation Versioning Engine
Authors: Dorkenwald Sven , Schneider-Mizell Casey M. , Brittain Derrick , Halageri Akhilesh , Jordan Chris , Kemnitz Nico , Castro Manual A. , Silversmith William , Maitin-Shephard Jeremy , Troidl Jakob , Pfister Hanspeter , Gillet Valentin , Xenes Daniel , Bae J. Alexander , Bodor Agnes L. , Buchanan JoAnn , Bumbarger Daniel J. , Elabbady Leila , Jia Zhen , Kapner Daniel , Kinn Sam , Lee Kisuk , Li Kai , Lu Ran , Macrina Thomas , Mahalingam Gayathri , Mitchell Eric , Mondal Shanka Subhra , Mu Shang , Nehoran Barak , Popovych Sergiy , Takeno Marc , Torres Russel , Turner Nicholas L. , Wong William , Wu Jingpeng , Yin Wenjing , Yu Szi-chieh , Reid R. Clay , da Costa Nuno Maçarico , Seung H. Sebastian , Collman Forrest
Published: July 2023

Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this constantly changing and expanding data landscape. Here, we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure for immediate and reproducible connectome analysis in up-to petascale datasets (∼1mm3) while proofreading and annotating is ongoing. For segmentation, CAVE provides a distributed proofreading infrastructure for continuous versioning of large reconstructions. Annotations in CAVE are defined by locations such that they can be quickly assigned to the underlying segment which enables fast analysis queries of CAVE’s data for arbitrary time points. CAVE supports schematized, extensible annotations, so that researchers can readily design novel annotation types. CAVE is already used for many connectomics datasets, including the largest datasets available to date.
KCNQ5 controls perivascular adipose tissue-mediated vasodilation
Authors: Tsvetkov Dmitry , Schleifenbaum Johanna , Wang Yibin , Kassmann Mario , Polovitskaya Maya M , Schütze Sebastian , Rothe Michael , Luft Friedrich C , Jentsch Thomas J , Gollasch Maik
Published: July 2023

Background

Small arteries exhibit resting tone, a partially contracted state that maintains arterial blood pressure. In arterial smooth muscle cells (SMCs), potassium channels control contraction and relaxation. Perivascular adipose tissue (PVAT) has been shown to exert anticontractile effects on the blood vessels. However, the mechanisms by which PVAT signals small arteries, and their relevance, remain largely unknown. We aimed to uncover key molecular components in adipose-vascular coupling.

Methods

A wide-spectrum of genetic mouse models targetingKcnq3, Kcnq4andKcnq5genes (Kcnq3−/−,Kcnq4−/−,Kcnq5−/−,Kcnq5dn/dn,Kcnq4−/−/Kcnq5dn/dn,Kcnq4−/−/Kcnq5−/−), telemetry blood pressure measurements, targeted lipidomics, and RNA-Seq profiling, wire-myography, patch-clamp, and sharp-electrode membrane potential measurements were used.

Results

We show that PVAT causes SMC KCNQ5 (KV7.5) channels to hyperpolarize the membrane potential. This effect relaxes small arteries and regulates blood pressure. Oxygenation of polyunsaturated fats generates oxylipins, a superclass of lipid mediators. We identified numerous oxylipins released by PVAT that potentiate vasodilatory action in small arteries by opening SMC KCNQ5 channels.

Conclusions

Our results reveal a key molecular function of KCNQ5 channels in adipose-vascular coupling, translating PVAT signals, particularly oxylipins, to the central physiological function of vasoregulation. This novel pathway opens new therapeutic perspectives.
Artificial Intelligence Enables the Label-Free Identification of Chronic Myeloid Leukemia Cells with Mitochondrial Morphological Alterations
Authors: Suzuki Kohjin , Watanabe Naoki , Torii Satoru , Arakawa Satoko , Ochi Kiyosumi , Tsuchiya Shun , Yamada Kazuhiro , Kawamura Yoko , Ota Sadao , Komatsu Norio , Shimizu Shigeomi , Ando Miki , Takaku Tomoiku
Published: July 2023

Long-term tyrosine kinase inhibitor (TKI) treatment for patients with chronic myeloid leukemia (CML) causes various adverse events. Achieving a deep molecular response (DMR) is necessary for discontinuing TKIs and attaining treatment-free remission. Thus, early diagnosis is crucial as a lower DMR achievement rate has been reported in high-risk patients. Therefore, we attempted to identify CML cells using a novel technology that combines artificial intelligence (AI) with flow cytometry and investigated the basis for AI- mediated identification. Our findings indicate thatBCR-ABL1-transduced cells and leukocytes from patients with CML showed significantly fragmented mitochondria and decreased mitochondrial membrane potential. Additionally,BCR-ABL1enhanced the phosphorylation of Drp1 via the mitogen-activated protein kinase pathway, inducing mitochondrial fragmentation. Finally, the AI identified cell line models and patient leukocytes that showed mitochondrial morphological changes. Our study suggested that this AI- based technology enables the highly sensitive detection ofBCR-ABL1-positive cells and early diagnosis of CML.
When Maturation is Not Linear: Brain Oscillatory Activity in the Process of Aging as Measured by Electrophysiology
Authors: Doval Sandra , López-Sanz David , Bruña Ricardo , Cuesta Pablo , Antón-Toro Luis , Taguas Ignacio , Torres-Simón Lucía , Chino Brenda , Maestú Fernando
Published: July 2023

Changes in brain oscillatory activity are commonly used as biomarkers both in cognitive neuroscience and in neuropsychiatric conditions. However, little is known about how its profile changes across maturation. Here we use regression models to characterize magnetoencephalography power changes within classical frequency bands in a sample of 792 healthy participants, covering the range 13 to 80 years old.

Our results reveal complex, non-linear trajectories of power changes that challenge the linear model traditionally reported. Moreover, these trajectories also exhibit variations across cortical regions. Remarkably, we observed that increases in slow wave activity are associated with a better cognitive performance across the lifespan, as well as with larger gray matter volume for elderlies, while fast wave activity decreases with adulthood.

These results suggest that elevated power in low-frequency resting-state activity during aging may reflect a proxy for deterioration, rather than serving as a compensatory mechanism, as usually interpreted. In addition, it enhances our comprehension of both neurodevelopment and the aging process by highlighting the complexity and regional specificity of changes in brain rhythms. Furthermore, our findings have potential implications for understanding cognitive performance and structural integrity.
Enforcing local DNA kinks by sequence-selective trisintercalating oligopeptides of a tricationic porphyrin. A polarizable Molecular Dynamics study
Authors: Gresh Nohad , Hage Krystel El , Lagardère Louis , Brégier Frédérique , Godard Jérémy , Piquemal Jean-Philip , Perrée-Fauvet Martine , Sol Vincent
Published: July 2023

Bisacridinyl-bisarginyl porphyrin (BABAP) is a trisintercalating derivative of a tricationic porphyrin, formerly designed and synthesized in order to selectively target and photosensitize the ten-base pair palindromic sequence d(CGGGCGCCCG)2. We resorted to the previously derived (Far et al., 2004) lowest energy-minimized (EM) structure of the BABAP complex with this sequence as a starting point. We performed polarizable molecular dynamics (MD) on this complex. It showed, over a 150 ns duration, the persistent binding of the Arg side-chain on each BABAP arm to the two G bases upstream from the central porphyrin intercalation site. We subsequently performed progressive shortenings of the connector chain linking the Arg-Gly backbone to the acridine, from n=6 methylenes to 4, followed by removal of the Gly backbone and further connector shortenings, from n=4 to n=1. These resulted into progressive deformations (‘kinks’) of the DNA backbone. In its most accented kinked structure, the DNA backbone was found to have a close overlap with that of DNA bound toCrerecombinase, with, at the level of one acridine intercalation site, negative roll and positive tilt values consistent with those experimentally found for this DNA at its own kinked dinucleotide sequence. Thus, in addition to their photosensitizing properties, some BABAP derivatives could induce sequence-selective, controlled DNA deformations, which are targets for cleavage by endonucleases or for repair enzymes.
Unravelling vulture avoidance tactic of wind turbines combining empirical and simulation data
Authors: Yohan Sassi , Noémie Ziletti , Olivier Duriez , Benjamin Robira
Published: July 2023

The increase of wind turbine installations to limit climate change may affect bird populations because of collisions with rotor blades. Birds may respond to wind turbine presence along a gradient of behavioural changes: avoiding the wind farm (macro-scale) or only the wind turbines either by anticipating wind turbine locations (meso-scale) or engaging into last-minute flee attempts after late perception (micro-scale). We investigated the flight response at these three spatial scales of 25 adult griffon vultures (Gyps fulvus) equipped with GPS tags over three years when flying in an area including ten wind farms in the Causses, France. At macro-scale, the population foraging range and habitat use revealed that vultures did not avoid wind farms. To investigate avoidance at meso- and micro-scales we focused on the four mostly visited wind farms. We compared vulture flights to null movement models, based on a method allowing us to keep the correlation between flights and topography while creating movement independent of wind turbine locations. At most sites, vultures did not show avoidance behaviour. Yet, simulations from our agent-based model highlighted that the avoidance pattern detected at one wind farm matched with an anticipated avoidance of turbines, probably linked to the presence of a ridge nearby. Overall, our results suggest wind farm-specific responses by soaring birds as a function of the landscape topography. Thus, stakeholders should carefully consider the wind farm location for siting and designing preventive measures (e.g. improve detection of species not able to avoid turbines in switching off on-demand technologies) to reduce collision risk of soaring birds.
Interaction of SCoV-2NSP7orNSP8alone withNSP12causes constriction of the RNA entry channel: Implications for novel RdRp inhibitor drug discovery
Authors: Singh Deepa , Kushwaha Tushar , Kulandaisamy Rajkumar , Kumar Vikas , Baswal Kamal , Tiwari Saras H , Ghorai Arkadyuti , Kumar Manoj , Kumar Saroj , Polamarasetty Aparoy , Sehgal Deepak , Katika Madhumohan R , Gadde Suresh , Côté Marceline , Kayampeta Sarala R , Appaiahgari Mohan B , Inampudi Krishna K
Published: July 2023

RNA-dependent RNA polymerase (RdRP) is a critical component of the RNA virus life cycle, including SCoV-2. Among the Coronavirus-encoded proteins, non-structural protein 12 (NSP12) exhibits polymerase activity in collaboration with one unit ofNSP7and two units ofNSP8, constituting the RdRp holoenzyme. While there is abundant information on SCoV-2 RdRp-mediated RNA replication, the influence of interplay amongNSP12, NSP7, andNSP8on template RNA binding and primer extension activity remains relatively unexplored and poorly understood. Here, we recreated a functional RdRp holoenzymein vitrousing recombinant SCoV-2NSP12, NSP7, andNSP8, and established its functional activity. Subsequently, molecular interactions among theNSPs in the presence of a variety of templates and their effects on polymerase activity were studied, wherein we found thatNSP12alone exhibited notable polymerase activity that increased significantly in the presence ofNSP7andNSP8. However, this activity was completely shut down, and the template RNA-primer complex was detached fromNSP12when one of the two cofactors was present. Through computational analysis, we found that the template RNA entry channel was more constricted in the presence of one of the two cofactors, which was relatively more constricted in the presence ofNSP8compared to that in the presence ofNSP7. In conclusion, we report thatNSP7andNSP8together synergise to enhance the activity ofNSP12, but antagonise when present alone. Our findings have implications for novel drug development, and compounds that obstruct the binding ofNSP7orNSP8toNSP12can have lethal effects on viral RNA replication.