bluuebunny/crossref_metadata_2025_split huggingface dataset:
ASSESSING TARGET SPECIFICITY OF THE SMALL MOLECULE INHIBITOR MARIMASTAT TO SNAKE VENOM TOXINS: A NOVEL APPLICATION OF THERMAL PROTEOME PROFILING
Authors: Smith Cara F. , Modahl Cassandra M. , Ceja-Galindo David , Larson Keira Y. , Maroney Sean P. , Bahrabadi Lilyrose , Brandehoff Nicklaus P. , Perry Blair W. , McCabe Maxwell C. , Petras Daniel , Lomonte Bruno , Calvete Juan J. , Castoe Todd A. , Mackessy Stephen P. , Hansen Kirk C. , Saviola Anthony J. 
Published: October 2023

AbstractNew treatments that circumvent the pitfalls of traditional antivenom therapies are critical to address the problem of snakebite globally. Numerous snake venom toxin inhibitors have shown promising cross-species neutralization of medically significant venom toxinsin vivoandin vitro. The development of high-throughput approaches for the screening of such inhibitors could accelerate their identification, testing, and implementation, and thus holds exciting potential for improving the treatments and outcomes of snakebite envenomation worldwide. Energetics-based proteomic approaches, including Thermal Proteome Profiling (TPP) and Proteome Integral Solubility Alteration (PISA), assays represent “deep proteomics” methods for high throughput, proteome-wide identification of drug targets and ligands. In the following study, we apply TPP and PISA methods to characterize the interactions between venom toxin proteoforms inCrotalus atrox(Western Diamondback Rattlesnake) and the snake venom metalloprotease (SVMP) inhibitor marimastat. We investigate its venom proteome-wide effects and characterize its interactions with specific SVMP proteoforms, as well as its potential targeting of non-SVMP venom toxin families. We also compare the performance of PISA thermal window and soluble supernatant with insoluble precipitate using two inhibitor concentrations, providing the first demonstration of the utility of a sensitive high-throughput PISA-based approach to assess the direct targets of small molecule inhibitors for snake venom.
Cost-effectiveness analysis of COVID-19 booster doses and oral antivirals in the Indo-Pacific
Authors: Bilgin Gizem Mayis , Munira Syarifah Liza , Lokuge Kamalini , Glass Kathryn 
Published: October 2023

AbstractBackgroundDecision-makers in middle-income countries need evidence on the cost-effectiveness of COVID-19 booster doses and oral antivirals to appropriately prioritise these healthcare interventions.MethodsWe used a dynamic transmission model to assess the cost-effectiveness of COVID-19 booster doses and oral antivirals in Fiji, Indonesia, Papua New Guinea, and Timor-Leste. We conducted cost-effectiveness analysis from both healthcare and societal perspectives using 3% discounting for ongoing costs and health benefits. We developed an interactive R Shiny which allows the user to vary key model assumptions, such as the choice of discounting rate, and view how these assumptions affect model results.FindingsBooster doses were cost saving and therefore cost-effective in all four middle-income settings from both healthcare and societal perspectives using 3% discounting. Providing oral antivirals was cost-effective from a healthcare perspective if procured at a low generic ($25 United States Dollars) or middle-income reference price ($250 United States Dollars); however, their cost-effectiveness was strongly influenced by rates of wastage or misuse, and the ongoing costs of care for patients hospitalised with COVID-19. Interestingly, the cost or wastage of rapid antigen tests did not appear strongly influential over the cost-effectiveness of oral antivirals in any of the four study settings.ConclusionsOur results support that government funded COVID-19 booster programs continue to be cost-effective in middle-income settings. Oral antivirals demonstrate the potential to be cost-effective if procured at or below a middle-income reference price of $250 USD per schedule. Further research should quantify the rates of wastage or misuse of oral COVID-19 antivirals in middle-income settings.
Is Gauchian genotyping ofGBA1variants reliable?
Authors: Tayebi Nahid , Lichtenberg Jens , Hertz Ellen , Sidransky Ellen 
Published: October 2023

AbstractBiallelic mutations inGBA1result in Gaucher disease (GD), the inherited deficiency of glucocerebrosidase. Variants inGBA1are also a common genetic risk factor for Parkinson disease (PD). Currently, some PD centers screen for mutantGBA1alleles to stratify patients who may ultimately benefit fromGBA1-targeted therapeutics. However, accurately detecting variants, especially recombinant alleles resulting from a crossover betweenGBA1and its pseudogene, is challenging, impacting studies of both GD andGBA1-associated parkinsonism. Recently, the software tool Gauchian was introduced to identifyGBA1variants from whole genome sequencing. We evaluated Gauchian in 90 Sanger-sequenced patients with GD and fiveGBA1heterozygotes. While Gauchian genotyped most patients correctly, it missed some rare orde novomutations due to its limited internal database and over-reliance on intergenic structural variants. This resulted in misreported homozygosity, incomplete genotypes, and undetected recombination events, limiting Gauchian’s utility in variant screening and precluding its use in diagnostics.
Genetic Analysis and Natural History of Parkinson’s Disease Due to the LRRK2 G2019S Variant
Authors: Kmiecik Matthew J. , Micheletti Steven , Coker Daniella , Heilbron Karl , Shi Jingchunzi , Stagaman Keaton , Filshtein Sonmez Teresa , Fontanillas Pierre , Shringarpure Suyash , Schloetter Madeleine , Rowbotham Helen M. , Cannon Paul , Shelton Janie F. , Hinds David A. , Tung Joyce Y. ,   23andMe Research Team, Holmes Michael V. , Aslibekyan Stella , Norcliffe-Kaufmann Lucy 
Published: October 2023

AbstractTheLRRK2 G2019Svariant is the most common cause of monogenic Parkinson’s Disease (PD); however, questions remain regarding the penetrance, clinical phenotype, and natural history of carriers.We performed a 3.5 year prospective longitudinal online study in a large number of 1,286 genotypedLRRK2 G2019Scarriers and 109,154 controls, with and without Parkinson’s disease (PD) recruited from the 23andMe Research Cohort. We collected self-reported motor and non-motor symptoms every six months, as well as demographics, family histories, and environmental risk factors. Incident cases of PD (phenoconverters) were identified at follow-up. We determined lifetime risk of PD using accelerated failure time modeling and explored the impact of polygenic risk on penetrance. We also computed the genetic ancestry of allLRRK2 G2019Scarriers in the 23andMe database and identified regions of the world where carrier frequencies are highest.We observed that despite a one year longer disease duration (p=0.016),LRRK2 G2019Scarriers with PD had similar burden of motor symptoms, yet significantly fewer non-motor symptoms including cognitive difficulties, REM sleep behavior disorder (RBD), and hyposmia (allp-values<0.0002). The cumulative incidence of PD inG2019Scarriers by age 60 was 8.66%.G2019Scarriers had a 10-fold risk of developing PD versus non-carriers. This rose to a 27-fold risk inG2019Scarriers with a PD polygenic risk score in the top 25% versus non-carriers in the bottom 25%. In addition to identifying ancient founding events in people of North African and Ashkenazi descent, our genetic ancestry analyses infer that theG2019Svariant was later introduced to Spanish colonial territories in the Americas.Our results suggestLRRK2 G2019SPD appears to be a slowly progressive predominantly motor subtype of PD with a lower prevalence of hyposmia, RBD, and cognitive impairment. This suggests that the current prodromal criteria, which are based on idiopathic PD, may lack sensitivity to detect the early phases ofLRRK2PD inG2019Scarriers. We show that polygenic burden may contribute to the development of PD in theLRRK2 G2019Scarrier population. Collectively, the results should help support screening programs and candidate enrichment strategies for upcoming trials ofLRRK2inhibitors in early-stage disease.
Assessing mechanical agency during apical apoptotic cell extrusion
Authors: Anjum Sommer , Turner Llaran , Atieh Youmna , Eisenhoffer George T. , Davidson Lance 
Published: October 2023

ABSTRACTEpithelial tissues maintain homeostasis through the continual addition and removal of cells. Homeostasis is necessary for epithelia to maintain barrier function and prevent the accumulation of defective cells. Unfit, excess, and dying cells can be removed from epithelia by the process of extrusion. Controlled cell death and extrusion in the epithelium of the larval zebrafish tail fin coincides with oscillation of cell area, both in the extruding cell and its neighbors. Both cell-autonomous and non-autonomous factors have been proposed to contribute to extrusion but have been challenging to test by experimental approaches. Here we develop a dynamic cell-based biophysical model that recapitulates the process of oscillatory cell extrusion to test and compare the relative contributions of these factors. Our model incorporates the mechanical properties of individual epithelial cells in a two-dimensional simulation as repelling active particles. The area of cells destined to extrude oscillates with varying durations or amplitudes, decreasing their mechanical contribution to the epithelium and surrendering their space to surrounding cells. Quantitative variations in cell shape and size during extrusion are visualized by a hybrid weighted Voronoi tessellation technique that renders individual cell mechanical properties directly into an epithelial sheet. To explore the role of autonomous and non-autonomous mechanics, we vary the biophysical properties and behaviors of extruding cells and neighbors such as the period and amplitude of repulsive forces, cell density, and tissue viscosity. Our data suggest that cell autonomous processes are major contributors to the dynamics of extrusion, with the mechanical microenvironment providing a less pronounced contribution. Our computational model based onin vivodata serves as a tool to provide insights into the cellular dynamics and localized changes in mechanics that promote elimination of unwanted cells from epithelia during homeostatic tissue maintenance.
Chromokinesin Klp-19 regulates microtubule overlap and dynamics during anaphase inC. elegans
Authors: Zimyanin Vitaly , Magaj Magdalena , Manzi Nadia Ingabire , Yu Che-Hang , Gibney Theresa , Chen Yu-Zen , Basaran Mustafa , Horton Xavier , Siller Karsten , Pani Ariel , Needleman Daniel , Dickinson Daniel J. , Redemann Stefanie 
Published: October 2023

AbstractRecent studies have highlighted the significance of the spindle midzone, the region between the segregating chromosomes, in ensuring proper chromosome segregation. By combining 3D electron tomography, cutting-edge light microscopy and a novel single cellin vitroessay allowing single molecule tracking, we have discovered a previously unknown role of the regulation of microtubule dynamics within the spindle midzone ofC. elegansby the chromokinesin KLP-19, and its relevance for proper spindle function. Using Fluorescence recovery after photobleaching and a combination of second harmonic generation and two-photon fluorescence microscopy, we found that the length of the antiparallel microtubule overlap zone in the spindle midzone is constant throughout anaphase, and independent of cortical pulling forces as well as the presence of the microtubule bundling protein SPD-1. Further investigations of SPD-1 and KLP-19 inC. elegans, the homologs of PRC1 and KIF4a, suggest that KLP-19 regulates the overlap length and functions independently of SPD-1. Our data shows that KLP-19 plays an active role in regulating the length of microtubules within the midzone as well as the size of the antiparallel overlap region throughout mitosis. Depletion of KLP-19 in mitosis leads to an increase in microtubule length and thus microtubule-based interactions in the spindle midzone, which affects spindle dynamics and force transmission. Our data shows that by localizing KLP-19 to the spindle midzone in anaphase microtubule dynamics can be locally controlled allowing the formation of a functional midzone.SummaryKLP-19 controls microtubule length in the spindle midzone ofC. elegans, affecting spindle dynamics and force transmission during mitosis.
Dictyostelium discoideum-assisted pharmacognosy of plant resources for discovering antivirulence molecules targetingKlebsiella pneumoniae
Authors: Hernández Marcos , Areche Carlos , Castañeta Grover , Rojas Diego , Varas Macarena A. , Marcoleta Andrés E. , Chávez Francisco P. 
Published: October 2023

ABSTRACTThe rise of antibiotic-resistant bacterial strains poses a significant global health challenge, underscoring the critical need for innovative strategies to address this threat. Natural products and their derivatives have emerged as a promising reservoir for drug discovery. The social amoebaDictyostelium discoideumis an advantageous model organism in this effort. Using this invertebrate model, we introduce a novel perspective to screen natural plant extracts for molecules with potential antivirulence activity. As a proof of concept, we established a simple high-throughput assay to screen for antivirulence molecules targetingKlebsiella pneumoniaeamong extracts ofHelenium aromaticum. Thus, we aimed to identify compounds attenuatingK. pneumoniaevirulence without inducing cytotoxic effects on amoeba cells. Notably, the methanolic root extract ofH. aromaticumbut not other extracts fulfilled these prerequisites. Further analysis via UHPLC-ESI-MS/MS led to the identification of 24 chemical compounds boasting potential antivirulence attributes. This research underscores the potential of employingD. discoideum-assisted pharmacognosy for unearthing novel antivirulence agents against multidrug-resistant pathogens.Table of Content Graphic
NMN Works in HFD-Induced T2DM by Interesting Effects in Adipose Tissue, and Not by Mitochondrial Biogenesis
Authors: Popescu Roua Gabriela , Dinischiotu Anca , Soare Teodoru , Vlase Ene , Marinescu George Cătălin 
Published: October 2023

AbstractNicotinamide mononucleotide (NMN) has emerged as a promising therapeutic intervention for age-related disorders, including Type 2 Diabetes.In this study, we investigated the effects of NMN treatment on glucose uptake and its underlying mechanisms in various tissue and cell lines. Through a comprehensive proteomic analysis, we uncovered a series of distinct organ-specific effects that contribute to the observed improvements in glucose metabolism.Notably, we observed the upregulation of thermogenic UCP1, promoting enhanced glucose utilization in muscle tissue. Additionally, liver and muscle cells displayed a unique response, characterized by spliceosome down-regulation and concurrent upregulation of chaperones, proteasomes, and ribosomes, leading to a mildly impaired and energy-inefficient protein synthesis machinery. Adipose tissue exhibited increased protein synthesis and degradation, fatty acid degradation, Lysosome and mTOR cell proliferation signalling up-regulation, while showing a surprising repressive effect on mitochondrial biogenesis.Furthermore, our findings revealed a remarkable metabolic rewiring in the brain, involving increased production of ketone bodies, down-regulation of mitochondrial OXPHOS components and the TCA cycle, and the induction of known fasting-associated effects.Collectively, our data elucidate the multifaceted nature of NMN action, highlighting its organ-specific effects and their role in modulating glucose metabolism. These findings deepen our understanding of NMN’s therapeutic potential and pave the way for novel strategies in managing metabolic disorders.
The genetic architecture of protein stability
Authors: Faure Andre J. , Martí-Aranda Aina , Hidalgo-Carcedo Cristina , Schmiedel Jörn M. , Lehner Ben 
Published: October 2023

AbstractThere are more ways to synthesize a 100 amino acid protein (20100) than atoms in the universe. Only a miniscule fraction of such a vast sequence space can ever be experimentally or computationally surveyed. Deep neural networks are increasingly being used to navigate high-dimensional sequence spaces. However, these models are extremely complicated and provide little insight into the fundamental genetic architecture of proteins. Here, by experimentally exploring sequence spaces >1010, we show that the genetic architecture of at least some proteins is remarkably simple, allowing accurate genetic prediction in high-dimensional sequence spaces with fully interpretable biophysical models. These models capture the non-linear relationships between free energies and phenotypes but otherwise consist of additive free energy changes with a small contribution from pairwise energetic couplings. These energetic couplings are sparse and caused by structural contacts and backbone propagations. Our results suggest that artificial intelligence models may be vastly more complicated than the proteins that they are modeling and that protein genetics is actually both simple and intelligible.
Ocular dominance-dependent binocular combination of monocular neuronal responses in macaque V1
Authors: Zhang Sheng-Hui , Zhao Xing-Nan , Tang Shi-Ming , Yu Cong 
Published: October 2023

AbstractPrimates rely on two eyes to see depth, while keeping a stable vision when one eye is closed. Although psychophysical and modeling studies have investigated how monocular signals are combined to form binocular vision, the corresponding neuronal mechanisms, especially in V1 where most neurons become binocular but with different eye preferences, are not well understood. Here we used two-photon calcium imaging to compare monocular and binocular responses of thousands of V1 superficial-layer neurons in three awake macaques. Under monocular stimulation, neurons preferring the stimulated eye responded substantially stronger than those preferring both eyes. However, under binocular stimulation, the responses of neurons preferring either eye were suppressed, and those preferring both eyes were enhanced, so that neuronal responses became similar regardless of eye preferences. A neuronally realistic model of binocular combination, which includes ocular dominance-dependent divisive interocular inhibition, and binocular summation, is proposed to account for these observations.
Reviewing the affordability and adequacy of affordable housing in urban India: impact of the covid-19 pandemic
Authors: Agarwal Shagun , Singh Tribhuvan Pratap , Bajaj Deepak 
Published: October 2023

Purpose
Housing policies in India (last modified in 2017) define “affordable housing” on three main parameters – income of the target group, dwelling unit size and house price to income ratio. The Covid-19 pandemic has questioned the robustness of the defining parameters of affordable housing. This paper aims to study the impact of Covid-19 pandemic on housing affordability and adequacy for the urban poor and highlights how one pandemic has directly challenged the practicality of the affordable housing criteria in urban India.

Design/methodology/approach
The study is based on a pilot test conducted through interviews with the consumer group. Furthermore, the affordable housing policies of urban India were studied in conjunction with the pandemic guidelines laid down by the World Health Organization. The consumer responses were analyzed in relation to the policies and guidelines to arrive at the inferences. The secondary case examples of the Dharavi slums in Mumbai and the Savda Ghevra slum resettlement colony in Delhi, along with the findings of the primary survey in the economically weaker section category, are used to formulate the conclusions.

Findings
The pilot test conducted for the target consumer group clearly indicates that (i) the pandemic has severely affected the housing purchase capacity of the target consumer, thereby questioning the “affordability” of housing; (ii) proposed housing solutions are inadequate to enable livability, thereby questioning the “adequacy” of housing; and (iii) proposed housing solutions are inept to accommodate pandemic protocols. The Covid-19 pandemic and the conditions it imposed on the built environment clearly highlight the inadequacy of affordable housing parameters being followed in urban India.

Research limitations/implications
Further research may be conducted on global best practices in housing, which may advise the housing policies in India.

Practical implications
The study suggests key areas that need intervention and modification to make the housing policies more robust and effective.

Social implications
The study explores the social sustainability aspects of housing, which are often considered secondary in policies.

Originality/value
Because housing has a direct bearing on the physical, social and mental well-being of society, it is imperative to find housing solutions that are safe and resilient for a sustainable future. This paper is an original attempt by the author to question and highlight how the current affordable housing solutions adopted in urban India will continue to fail under any external adverse conditions unless modifications are considered in the existing housing parameters.
Deep learning architectures in dental diagnostics: a systematic comparison of techniques for accurate prediction of dental disease through x-ray imaging
Authors: Hasnain Muhammad Adnan , Malik Hassaan , Asad Muhammad Mujtaba , Sherwani Fahad 
Published: October 2023

PurposeThe purpose of the study is to classify the radiographic images into three categories such as fillings, cavity and implant to identify dental diseases because dental disease is a very common dental health problem for all people. The detection of dental issues and the selection of the most suitable method of treatment are both determined by the results of a radiological examination. Dental x-rays provide important information about the insides of teeth and their surrounding cells, which helps dentists detect dental issues that are not immediately visible. The analysis of dental x-rays, which is typically done by dentists, is a time-consuming process that can become an error-prone technique due to the wide variations in the structure of teeth and the dentist's lack of expertise. The workload of a dental professional and the chance of misinterpretation can be decreased by the availability of such a system, which can interpret the result of an x-ray automatically.Design/methodology/approachThis study uses deep learning (DL) models to identify dental diseases in order to tackle this issue. Four different DL models, such as ResNet-101, Xception, DenseNet-201 and EfficientNet-B0, were evaluated in order to determine which one would be the most useful for the detection of dental diseases (such as fillings, cavity and implant).FindingsLoss and accuracy curves have been used to analyze the model. However, the EfficientNet-B0 model performed better compared to Xception, DenseNet-201 and ResNet-101. The accuracy, recall, F1-score and AUC values for this model were 98.91, 98.91, 98.74 and 99.98%, respectively. The accuracy rates for the Xception, ResNet-101 and DenseNet-201 are 96.74, 93.48 and 95.65%, respectively.Practical implicationsThe present study can benefit dentists from using the DL model to more accurately diagnose dental problems.Originality/valueThis study is conducted to evaluate dental diseases using Convolutional neural network (CNN) techniques to assist dentists in selecting the most effective technique for a particular clinical condition.