bluuebunny/crossref_metadata_2025_split huggingface dataset:
WORKING MEMORY FILTERING AT ENCODING AND MAINTENANCE IN HEALTHY AGEING, ALZHEIMER’S AND PARKINSON’S DISEASE
Authors: Toniolo Sofia , Udale Robert , Klar Verena Svenja , Maio Maria Raquel , Attaallah Bahaaeddin , Tofaris George , Hu Michele Tao-Ming , Manohar Sanjay George , Husain Masud 
Published: June 2024

AbstractThe differential impact on working memory (WM) performance of distractors presented either at encoding or during maintenance was investigated in Alzheimer’s (AD), Parkinson’s Disease (PD) and healthy ageing. Across three studies, 28 AD and 28 PD patients, 28 elderly (EHC) and 28 young healthy controls (YHC) were enrolled. All participants performed a delayed reproduction task, where they reported the orientation of an arrow from a study set of either two or three items, with a distractor present either at encoding or at maintenance. Mean absolute error (the difference between probed and reported orientation) was calculated as an analogue measure of WM. Additionally, mixture model metrics i.e., memory precision, target detection, misbinding (swapping the features of an object with another probed item) and guessing were computed. MRI data was also acquired in AD, PD and EHC participants, and whole hippocampal volumes were extracted to test whether WM filtering and overall performance were related to hippocampal integrity.EHC and PD patients showed good filtering abilities both at encoding and during maintenance. However, AD patients exhibited significant filtering deficits specifically when the distractor appearedduring maintenance.Healthy ageing and AD were associated with higher rates of both misbinding and guessing, as well as lower target detection, and memory precision. However, in healthy ageing there was a prominent decline in WM memory precision, whilst in AD lower target detection and higher guessing were the main sources of error. Conversely, PD was associated only with higher guessing rates. Hippocampal volume was significantly correlated with filtering during maintenance – but not at encoding – as well as with overall mean absolute error, target detection, guessing and misbinding. These findings demonstrate how healthy ageing and neurodegenerative diseases exhibit distinct patterns of WM impairment, including differential effects on filtering irrelevant material presented at encoding and maintenance.
Associations between prenatal caffeine exposure and child development: Longitudinal results from the Adolescent Brain Cognitive Development (ABCD) Study
Authors: Modi Hailey , Baranger David AA , Paul Sarah E , Gorelik Aaron J , Hornstein Alana , Balbona Jared V , Agrawal Arpana , Bijsterbosch Janine D , Bogdan Ryan 
Published: June 2024

AbstractObjectiveThough caffeine use during pregnancy is common, its longitudinal associations with child behavioral and physical health outcomes remain poorly understood. Here, we estimated associations between prenatal caffeine exposure, body mass index (BMI), and behavior as children enter adolescence.MethodLongitudinal data and caregiver-reported prenatal caffeine exposure were obtained from the ongoing Adolescent Brain and Cognitive Development (ABCD)SMStudy, which recruited 11,875 children aged 9-11 years at baseline from 21 sites across the United States starting June 1, 2016. Prenatal caffeine exposure was analyzed as a 4-level categorical variable, and further group contrasts were used to characterize “any exposure” and “daily exposure” groups. Outcomes included psychopathology characteristics in children, sleep problems, and BMI. Potentially confounding covariates included familial (e.g., income, familial psychopathology), pregnancy (e.g., prenatal substance exposure), and child (e.g., caffeine use) variables.ResultsAmong 10,873 children (5,686 boys [52.3%]; mean [SD] age, 9.9 [0.6] years) with nonmissing prenatal caffeine exposure data, 6,560 (60%) were exposed to caffeine prenatally. Relative to no exposure, daily caffeine exposure was associated with higher child BMI (β=0.08; FDR-correctedp=0.02), but was not associated with child behavior. Those exposed to two or more cups of caffeine daily (n=1,028) had greater sleep problems than those with lower/no exposure (β>0.92; FDR-correctedp<0.04).ConclusionDaily prenatal caffeine exposure is associated with heightened childhood BMI, and when used multiple times a day greater sleep problems even after accounting for potential confounds. Whether this relationship is a consequence of prenatal caffeine exposure or its correlated factors remains unknown.
Statistical Coupling Analysis Predicts Correlated Motions in Dihydrofolate Reductase
Authors: Kalmer Thomas L. , Ancajas Christine Mae F. , Cohen Cameron I. , McDaniel Jade M. , Oyedele Abiodun S. , Thirman Hannah L. , Walker Allison S. 
Published: June 2024

AbstractThe role of dynamics in enzymatic function is a highly debated topic. Dihydrofolate reductase (DHFR), due to its universality and the depth with which it has been studied, is a model system in this debate. Myriad previous works have identified networks of residues in positions near to and remote from the active site that are involved in dynamics and others that are important for catalysis. For example, specific mutations on the Met20 loop inE. coliDHFR (N23PP/S148A) are known to disrupt millisecond-timescale motions and reduce catalytic activity. However, how and if networks of dynamically coupled residues influence the evolution of DHFR is still an unanswered question. In this study, we first identify, by statistical coupling analysis and molecular dynamic simulations, a network of coevolving residues, which possess increased correlated motions. We then go on to show that allosteric communication in this network is selectively knocked down in N23PP/S148A mutantE. coliDHFR. Finally, we identify two sites in the human DHFR sector which may accommodate the Met20 loop double proline mutation while preserving dynamics. These findings strongly implicate protein dynamics as a driving force for evolution.
Gliflozins, sucrose and flavonoids are allosteric activators of lecithin:cholesterol acyltransferase
Authors: Niemelä Akseli , Giorgi Laura , Nouri Sirine , Yurttaş Betül , Rauniyar Khushbu , Jeltsch Michael , Koivuniemi Artturi 
Published: June 2024

ABSTRACTLecithin:cholesterol acyltransferase (LCAT) serves as a pivotal enzyme in preserving cholesterol homeostasis via reverse cholesterol transport, a process closely associated with the onset of atherosclerosis. Impaired LCAT function can lead to severe LCAT deficiency disorders for which no pharmacological treatment exists. LCAT-based therapies, such as small molecule positive allosteric modulators (PAMs), against LCAT deficiencies and atherosclerosis hold promise, although their efficacy against atherosclerosis remains challenging. Herein we utilized a quantitative in silico metric to predict the activity of novel PAMs and tested their potencies with in vitro enzymatic assays. As predicted, sodium-glucose cotransporter 2 (SGLT2) inhibitors (gliflozins), sucrose and flavonoids activate LCAT. This has intriguing implications for the mechanism of action of gliflozins, which are commonly used in the treatment of type 2 diabetes, and for the endogenous activation of LCAT. Our results underscore the potential of molecular dynamics simulations in rational drug design.
What makesCandida aurispan-drug resistant? Integrative insights from genomic, transcriptomic, and phenomic analysis of clinical strains resistant to all four major classes of antifungal drugs
Authors: Rhodes Johanna , Jacobs Jonathan , Dennis Emily K. , Manjari Swati R. , Banavali Nilesh , Marlow Robert , Rokebul Mohammed Anower , Chaturvedi Sudha , Chaturvedi Vishnu 
Published: June 2024

AbstractThe global epidemic of drug-resistantCandida auriscontinues unabated. We do not know what caused the unprecedented appearance of pan-drug resistant (PDR)Candida aurisstrains in a hospitalized patient in New York; the initial report highlighted both known and unique mutations in the prominent gene targets of azoles, amphotericin B, echinocandins, and flucytosine antifungal drugs. However, the factors that allowC. auristo acquire multi-drug resistance and pan-drug resistance are not known. Therefore, we conducted a comprehensive genomic, transcriptomic, and phenomic analysis to better understand PDRC. auris. Among 1,570 genetic variants in drug-resistantC. auris, 299 were unique to PDR strains. The whole genome sequencing results suggested perturbations in genes associated with nucleotide biosynthesis, mRNA processing, and nuclear export of mRNA. Whole transcriptome sequencing of PDRC. aurisrevealed two genes to be significantly differentially expressed - a DNA repair protein and DNA replication-dependent chromatin assembly factor 1. Of 59 novel transcripts, 12 candidate transcripts had no known homology among expressed transcripts found in other organisms. We observed no fitness defects among multi-drug resistant (MDR) and PDRC. aurisstrains grown in nutrient-deficient or - enriched media at different temperatures. Phenotypic profiling revealed wider adaptability to nitrogenous nutrients with an uptick in the utilization of substrates critical in upper glycolysis and tricarboxylic acid cycle. Structural modelling of 33-amino acid deletion in the gene for uracil phosphoribosyl transferase suggested an alternate route inC. auristo generate uracil monophosphate that does not accommodate 5-fluorouracil as a substrate. Overall, we find evidence of metabolic adaptations in MDR and PDRC. aurisin response to antifungal drug lethality without deleterious fitness costs.
Endosomolytic Peptides Enable the Cellular Delivery of Peptide Nucleic Acids
Authors: Giancola JoLynn B. , Raines Ronald T. 
Published: June 2024

ABSTRACTPrecision genetic medicine enlists antisense oligonucleotides (ASOs) to bind to nucleic acid targets important for human disease. Peptide nucleic acids (PNAs) have many desirable attributes as ASOs but lack cellular permeability. Here, we use an assay based on the corrective splicing of an mRNA to assess the ability of synthetic peptides to deliver a functional PNA into a human cell. We find that the endosomolytic peptides L17E and L17ER4are highly efficacious delivery vehicles. Co-treatment of a PNA with low micromolar L17E or L17ER4enables robust corrective splicing in nearly all treated cells. Peptide–PNA conjugates are even more effective. These results enhance the utility of PNAs as research tools and potential therapeutic agents.
Nanopore Decoding with Speed and Versatility for Data Storage
Authors: Volkel Kevin D. , Hook Paul W. , Keung Albert , Timp Winston , Tuck James M. 
Published: June 2024

AbstractMotivationAs nanopore technology reaches ever higher throughput and accuracy, it becomes an increasingly viable candidate for reading out DNA data storage. Nanopore sequencing offers considerable flexibility by allowing long reads, real-time signal analysis, and the ability to read both DNA and RNA. We need flexible and efficient designs that match nanopore’s capabilities, but relatively few designs have been explored and many have significant inefficiency in read density, error rate, or compute time. To address these problems, we designed a new single-read per-strand decoder that achieves low byte error rates, offers high throughput, scales to long reads, and works well for both DNA and RNA molecules. We achieve these results through a novel soft decoding algorithm that can be effectively parallelized on a GPU. Our faster decoder allows us to study a wider range of system designs.ResultsWe demonstrate our approach on HEDGES, a state-of-the-art DNA-constrained convolutional code. We implement one hard decoder that runs serially and two soft decoders that run on GPUs. Our evaluation for each decoder is applied to the same population of nanopore reads collected from a synthesized library of strands. These same strands are synthesized with a T7 promoter to enable RNA transcription and decoding. Our results show that the hard decoder has a byte error rate over 25%, while the prior state of the art soft decoder can achieve error rates of 2.25%. However, that design also suffers a low throughput of 183 seconds/read. Our new Alignment Matrix Trellis soft decoder improves throughput by 257x with the trade off of a higher byte error rate of 3.52% compared to the state-of-the-art. Furthermore, we use the faster speed of our algorithm to explore more design options. We show that read densities of 0.33 bits/base can be achieved, which is 4x larger than prior MSA-based decoders. We also compare RNA to DNA, and find that RNA has 85% as many error free reads as compared to DNA.Availability and implementationSource code for our soft decoder and data used to generate figures is available publicly in the Github repositoryhttps://github.com/dna-storage/hedges-soft-decoder(10.5281/zenodo.11454877). All raw FAST5/FASTQ data is available at 10.5281/zenodo.11985454 and 10.5281/zenodo.12014515.Contackvolkel@ncsu.eduorjtuck@ncsu.edu
Digital libraries for minor languages in India: frameworks for addressing absences in policy and governance
Authors: Wadhwa Soni 
Published: June 2024

Purpose
Given that Indian languages in general are under-represented on the internet and that languages of minority linguistic groups find very little space on digital platforms, it is imperative for institutions such as libraries to cater to smaller communities and their educational needs while also reaching out to them in their own languages. This study aims to deliberate on strategies for enlisting community support for gathering diverse learning resources in different languages and for enlisting participation in activities such as crowdsourcing in initiatives such as annotations and transliteration.

Design/methodology/approach
This paper calls for interventions that imagine and create infrastructure for the flourishing of smaller libraries that can draw from and feed into large-scale national and international libraries. Offering a conceptual framework to rethink the country’s approach toward minor languages, it first offers an overview of policies and initiatives relevant to the concerns of minor languages in digital libraries in India. Based on the policy analysis, it then goes on to suggest starting points for policy designers and custodians of libraries to help them work toward better representation of languages in their resources.

Findings
The existing frameworks analyzed here for the greater or representation of minor Indian languages reveal a culture of silence toward the issue of language. With some advocacy, these frameworks can be mined to craft different ways that are critical not just for enriching libraries but also for preservation of cultural heritage of the communities concerned, thus adding a larger social dimension to the question of access.

Originality/value
While a lot of socio-political discourse on minority languages in India exists, this study pushes for their bearing on digital libraries, educational frameworks and cultural heritage.
Exploring job satisfaction’s impact on turnover tendency among employees in Kosova’s microfinance institutions
Authors: Aliu Flokart , Kutllovci Enver 
Published: June 2024

Purpose
The purpose of this paper is to delve into the intricate link between job satisfaction and employees’ turnover intentions. To accomplish this, a detailed structural model was constructed, incorporating five essential constructs: job satisfaction, turnover intention, satisfaction with financial factors, satisfaction with non-financial factors and external factors.

Design/methodology/approach
The research used a questionnaire with 28 items based on established tools, focusing on five different constructs. The model’s validation involved applying structural equation modelling to 147 non-managerial employees in microfinance institutions.

Findings
The findings reveal a significant negative correlation between job satisfaction and turnover intention. Satisfaction with financial factors significantly outweighs satisfaction with non-financial factors in shaping job satisfaction. In addition, the impact of external factors on turnover intention was observed to be minimal and inconsequential.

Research limitations/implications
This review highlights the importance of investigating the moderating factors in the job satisfaction–turnover relationship, distinguishing between types of satisfaction and conducting longitudinal studies across diverse contexts. It notably presents a diverse range of recent findings in this field, emphasising the breadth of the results that have emerged in this area of research.

Practical implications
Understanding job satisfaction and turnover intention is crucial for microfinance institutions. By prioritising efforts to enhance job satisfaction through improved financial offerings and non-financial factors like a supportive work environment and opportunities for growth, organisations can effectively mitigate turnover rates and foster success.

Social implications
The study underscores the societal value of supportive work environments beyond just benefits and career opportunities. By understanding the external influences on employee satisfaction, organisations can contribute to building more decent workplaces and promote social well-being, while advocating for social considerations in organisational practices.

Originality/value
This paper uses a novel integrated model comprising five distinct constructs not previously used together. It stands among the pioneering works that not only elucidate the correlation between job satisfaction and turnover intention but also delineate the constituents of job satisfaction itself.
IPO conditional conservatism, underpricing and post-issue stock market survival
Authors: Kim Sujin , Kent Pamela Fae , Richardson Grant , Yawson Alfred 
Published: June 2024

PurposeWe examine the association between conditional conservatism in initial public offering (IPO) underpricing and post-issue stock market survival in the U.S.Design/methodology/approachWe adopt an archival approach by collecting data for 1,761 U.S. IPO issuers for the period 1990–2017. Regression analyses are conducted to evaluate the association between conditional conservatism in initial public offerings with underpricing and post-issue stock market survival. We identify firms that went public in the period 1990–2012. These firms are then followed for five years after the IPO to assess their stock market survival.FindingsWe find that pre-issue conditional conservatism is significantly associated with less IPO underpricing. We also detect that IPO firms with higher levels of conditional conservative reporting are more likely to survive in the post-IPO stock market in the three-, four-, and five-year periods after the IPO. Our main findings are robust after controlling for other factors in our models, such as IPO cycles, venture capitalists, research and development investment, and pre-IPO accounting performance.Originality/valueWe extend research by demonstrating that conditional conservative reporting practices help firms reduce their indirect costs of raising their initial public capital. Additionally, our research introduces new evidence on the association between pre-IPO conditional conservatism and after-issue stock market survival. Our findings empirically support the International Accounting Standards Board’s (IASB) decision to reintroduce the concept of prudence into the conceptual framework, by showing how conservative reporting can reduce information asymmetry in IPO firms.
Impact of COVID-19 on market efficiency
Authors: Bhattacharya Rajeev R. 
Published: June 2024

PurposeCOVID-19 and its accompanying lockdowns were arguably the most traumatic events of our times. This paper investigates the impact of COVID-19 on market efficiency.Design/methodology/approachI analyze all publicly traded U.S. equities for 2014–September 2021, using intraday data from TAQ, TRACE, I/B/E/S and Capital IQ and daily data from CRSP, Thomson Reuters, Compustat, CRSP-Compustat Merged Database and FRED, using a controlled contrast between absolute abnormal returns for relevant halfhours versus absolute abnormal returns in control halfhours, measured by the negative of the coefficient of the fixed effect of the interaction between the indicator variable, and as the case may be, ticker and/or time period of interest, in the regression of halfhour-level absolute abnormal returns on tickers, months and interactions.FindingsUsing two separate objective, systematic, independent and ordinal per se measures of market efficiency based upon market reactions separately to key developments and earnings announcements, I find that U.S. equities markets were statistically and economically significantly less efficient during the first two-three months of the COVID-19 lockdowns.Practical implicationsEfficient capital markets provide substantial social benefits and are a sine qua non for the democratization of markets and the protection of investors, and constitute a critical mission of regulatory bodies such as the U.S. Securities and Exchange Commission (SEC) and the U.S. Financial Industry Regulatory Authority (FINRA).Social implicationsThe impact on market efficiency provides one critical input into the social cost-benefit analysis of public health policy and that of government interventions in general.Originality/valueThere has been no previous work done on the systematic and objective characterization of the impact of COVID-19 and associated lockdowns on market efficiency.
Examining AI competence, chatbot use and perceived autonomy as drivers of students' engagement in informal digital learning
Authors: Hidayat-ur-Rehman Imdadullah 
Published: June 2024

PurposeDigital technology's integration into education has transformed learning frameworks, necessitating the exploration of factors influencing students’ engagement in digital informal settings. This study, grounded in self-determination theory (SDT), proposes a model comprising artificial intelligence (AI) competence, chatbot usage, perceived autonomy (PA), digital informal learning (DIL) and students’ engagement.Design/methodology/approachThe study collected survey data from 409 participants at Saudi Arabian universities, ultimately using 387 valid responses for analysis. This dataset was subjected to a thorough examination to confirm the validity of our proposed model. To decipher the complex interactions within our model, we utilized partial least squares structural equation modeling (PLS-SEM). The study adopted a disjoint two-stage method to formulate a reflective-formative higher-order construct (HOC).FindingsThe study's findings showed that cognitive learning (CL), metacognitive learning (MCL) and social and motivational learning (SML) are the essential components of DIL. Significantly, the study determined that AI competence, chatbot usage, PA and DIL markedly affect students’ engagement. Moreover, the R2 value of 0.592 for student engagement indicates the model's robustness in explaining 59.2% of the variance, highlighting its effectiveness in identifying key drivers of student engagement in DIL contexts.Originality/valueThis research enhances understanding by detailing the intricate relationships among AI competence, chatbot usage, and students’ engagement in informal digital learning. It extends SDT to emphasize intrinsic motivations and AI capabilities, introducing reflective-formative HOCs for comprehending educational intricacies. It provides practical strategies for enhancing AI abilities and chatbot use in education, promoting personalized, engaging and autonomous digital learning spaces, thereby advancing educational theory and practice.