bluuebunny/crossref_metadata_2025_split huggingface dataset:
Atypical action updating in a dynamic environment associated with adolescent obsessive-compulsive disorder
Authors: Marzuki Aleya A. , Vaghi Matilde M. , Conway-Morris Anna , Kaser Muzaffer , Sule Akeem , Apergis-Schoute Annemieke , Sahakian Barbara J. , Robbins Trevor W. 
Published: November 2021

AbstractBackgroundComputational research had determined that adults with obsessive-compulsive disorder (OCD) display heightened action updating in response to noise in the environment and neglect meta-cognitive information (such as confidence) when making decisions. These features are proposed to underlie patients’ compulsions despite knowledge they are irrational. Nonetheless, it is unclear whether this extends to adolescents with OCD as research in this population is lacking. Thus, this study aimed to investigate the interplay between action and confidence in adolescents with OCD.MethodsTwenty-seven adolescents with OCD and 46 controls completed a predictive-inference task, designed to probe how subjects’ actions and confidence ratings fluctuate in response to unexpected outcomes. We investigated how subjects update actions in response to prediction errors (indexing mismatches between expectations and outcomes) and used parameters from a Bayesian model to predict how confidence and action evolve over time. Confidence-action association strength was assessed using a regression model. We also investigated the effects of serotonergic medication.ResultsAdolescents with OCD showed significantly increased learning rates, particularly following small prediction errors. Results were driven primarily by unmedicated patients. Confidence ratings appeared equivalent between groups, although model-based analysis revealed that patients’ confidence was less affected by prediction errors compared to controls. Patients and controls did not differ in the extent to which they updated actions and confidence in tandem.ConclusionsAdolescents with OCD showed enhanced action adjustments, especially in the face of small prediction errors, consistent with previous research establishing ‘just-right’ compulsions, enhanced error-related negativity, and greater decision-uncertainty in paediatric-OCD. These tendencies were ameliorated in patients receiving serotonergic medication, emphasising the importance of early intervention in preventing disorder-related cognitive deficits. Confidence ratings were equivalent between young patients and controls, mirroring findings in adults OCD research.
Signal from the Noise: A Mixed Methods Process Mining Approach to Evaluate Care Pathways
Authors: Noshad Morteza , Rose Christian C. , Chen Jonathan H. 
Published: November 2021

ABSTRACTObjectiveMapping real-world practice patterns vs. deviations from intended guidelines and protocols is necessary to identify and improve the quality of care for emergent medical conditions like stroke. We propose a process mining algorithm applied to Electronic Health Record (EHR) event log data as a unique opportunity to more easily identify and compare real-world care processes.MaterialsData was obtained from the event log of a major EHR vendor (Epic) for Stanford Health Care Hospital patients aged 18 years and older presenting to the ED from January 1, 2010 through December 31, 2018 and receiving tPA within 4.5 hours of presentation. Our algorithm was built using the Python programming language.MethodsAn unsupervised process-mining algorithm was developed and used to create a process map for our cohort. This map was then used to identify the most common path as well as individual and average conformity to this path across all encounters.ResultsOur automatically generated process mining graph, specifically its most common path, mimicked our institution’s recommended “code stroke” clinical pathway. The average conformity score for our cohort was 0.36 with a range from high of 0.64 and low of 0.20.DiscussionThis method allows for greater detail into common process measures to be more easily illustrated to evaluate the quality of care at a given institution. It may be extended to other, similarly well-defined processes or those which currently lack standardized clinical pathways.ConclusionOur mixed methods approach represents an essential data analysis step to improve complex care processes by automatically generating a qualitative and quantitative process measures from existing event log data which can then be used to target quality improvement initiatives.
De novo emergence of a remdesivir resistance mutation during treatment of persistent SARS-CoV-2 infection in an immunocompromised patient: A case report
Authors: Gandhi Shiv , Klein Jonathan , Robertson Alexander , Peña-Hernández Mario A. , Lin Michelle J , Roychoudhury Pavitra , Lu Peiwen , Fournier John , Ferguson David , Mohamed Bakhash Shah A. , Catherine Muenker M. , Srivathsan Ariktha , Wunder Elsio A. , Kerantzas Nicholas , Wang Wenshuai , Lindenbach Brett , Pyle Anna , Wilen Craig B. , Ogbuagu Onyema , Greninger Alexander L. , Iwasaki Akiko , Schulz Wade L. , Ko Albert I. 
Published: November 2021

AbstractSARS-CoV-2 remdesivir resistance mutations have been generated in vitro but have not been reported in patients receiving treatment with the antiviral agent. We present a case of an immunocompromised patient with acquired B-cell deficiency who developed an indolent, protracted course of SARS-CoV-2 infection. Remdesivir therapy alleviated symptoms and produced a transient virologic response, but her course was complicated by recrudescence of high-grade viral shedding. Whole genome sequencing identified a mutation, E802D, in the nsp12 RNA-dependent RNA polymerase, which was not present in pre-treatment specimens. In vitro experiments demonstrated that the mutation conferred a ∼6-fold increase in remdesivir IC50 but resulted in a fitness cost in the absence of remdesivir. Sustained clinical and virologic response was achieved after treatment with casirivimab-imdevimab. Although the fitness cost observed in vitro may limit the risk posed by E802D, this case illustrates the importance of monitoring for remdesivir resistance and the potential benefit of combinatorial therapies in immunocompromised patients with SARS-CoV-2 infection.
Data-driven prognosis for COVID-19 patients based on symptoms and age
Authors: Paul Subhendu , Lorin Emmanuel 
Published: November 2021

ABSTRACTIn this article, we develop an algorithm and a computational code to extract, analyze and compress the relevant information from the publicly available database of Canadian COVID-19 patients. We digitize the symptoms, that is, we assign a label/code as an integer variable for all possible combinations of various symptoms. We introduce a digital code for individual patient and divide all patients into a myriad of groups based on symptoms and age. In addition, we develop an electronic application (app) that allows for a rapid digital prognosis of COVID-19 patients, and provides individual patient prognosis on chance of recovery, average recovery period, etc. using the information, extracted from the database. This tool is aimed to assist health specialists in their decision regarding COVID-19 patients, based on symptoms and age of the patient. This novel approach can be used to develop similar applications for other diseases.
Block aligner: fast and flexible pairwise sequence alignment with SIMD-accelerated adaptive blocks
Authors: Liu Daniel , Steinegger Martin 
Published: November 2021

AbstractBackgroundThe Smith-Waterman-Gotoh alignment algorithm is the most popular method for comparing biological sequences. Recently, Single Instruction Multiple Data methods have been used to speed up alignment. However, these algorithms have limitations like being optimized for specific scoring schemes, cannot handle large gaps, or require quadratic time computation.ResultsWe propose a new algorithm called block aligner for aligning nucleotide and protein sequences. It greedily shifts and grows a block of computed scores to span large gaps within the aligned sequences. This greedy approach is able to only compute a fraction of the DP matrix. In exchange for these features, there is no guarantee that the computed scores are accurate compared to full DP. However, in our experiments, we show that block aligner performs accurately on various realistic datasets, and it is up to 9 times faster than the popular Farrar’s algorithm for protein global alignments.ConclusionsOur algorithm has applications in computing global alignments and X-drop alignments on proteins and long reads. It is available as a Rust library at https://github.com/Daniel-Liu-c0deb0t/block-aligner.
Molecular signature of postmortem lung tissue from COVID-19 patients suggests distinct trajectories driving mortality
Authors: Budhraja Anshul , Basu Anubhav , Gheware Atish , Abhilash Dasari , Rajagopala Seesandra , Pakala Suman , Sumit Madhuresh , Ray Animesh , Arulselvi S , Mathur Purva , Nambirajan Aruna , Kumar Sachin , Gupta Ritu , Wig Naveet , Trikha Anjan , Guleria Randeep , Sarkar Chitra , Gupta Ishaan , Jain Deepali 
Published: November 2021

AbstractThe precise molecular mechanisms behind life-threatening lung abnormalities during severe SARS-CoV-2 infections are still unclear. To address this challenge, we performed whole transcriptome sequencing of lung autopsies from 31 patients suffering from severe COVID-19 related complications and 10 uninfected controls. Using a metatranscriptome analysis of lung tissue samples we identified the existence of two distinct molecular signatures of lethal COVID-19. The dominant “classical” signature (n=23) showed upregulation of unfolded protein response, steroid biosynthesis and complement activation supported by massive metabolic reprogramming leading to characteristic lung damage. The rarer signature (n=8) potentially representing “Cytokine Release Syndrome” (CRS) showed upregulation of cytokines such IL1 and CCL19 but absence of complement activation and muted inflammation. Further, dissecting expression of individual genes within enriched pathways for patient signature suggests heterogeneity in host response to the primary infection. We found that the majority of patients cleared the SARS-CoV-2 infection, but all suffered from acute dysbiosis with characteristic enrichment of opportunistic pathogens such asStaphylococcus cohniiin “classical” patients andPasteurella multocidain CRS patients. Our results suggest two distinct models of lung pathology in severe COVID-19 patients that can be identified through the status of the complement activation, presence of specific cytokines and characteristic microbiome. This information can be used to design personalized therapy to treat COVID-19 related complications corresponding to patient signature such as using the identified drug molecules or mitigating specific secondary infections.
Nuclear Progestin Receptor Mediated Linkage of Blood Coagulation and Ovulation
Authors: Huang Jing , Sun Chao , Liu Dong Teng , Zhao Nan Nan , Shavit Jordan A. , Zhu Yong , Chen Shi Xi 
Published: November 2021

AbstractOvulation is a dramatic remodeling process that includes rupture of blood capillaries and clotting, but coagulation is not thought to directly regulate this process. Herein, we report remarkable increases of coagulation factors V (f5, ∼3145-fold) and tissue factor (f3a, ∼120-fold) in zebrafish ovarian follicle cells during ovulation. This increase was mediated through the nuclear progestin receptor (Pgr), which is essential for ovulation in zebrafish, and was totally abolished in ovarian follicular cells from pgr-/- mutants. In addition, promoter activities of f5 and f3a were significantly enhanced by progestin (DHP) via Pgr. Similar regulation of human F5 promoter activity was induced via human PGRB, suggesting a conserved mechanism. Site-directed mutagenesis of the zebrafish f5 promoter further demonstrated a direct regulation of coagulation factors via progestin response elements. Moreover, a stark increase of erythrocytes occurred in capillaries meshed in wildtype preovulatory follicles but was absent in pgr-/- mutants. Interestingly, anticoagulants significantly inhibited ovulation both in vitro and in vivo, respectively. Furthermore, reduced fecundity was observed in f5+/- female zebrafish. Taken together, our study provides plausible evidence for steroid regulation of coagulation factors, and a new hypothesis for blood clotting triggered ovulation in vertebrates.
An active learning framework improves tumor variant interpretation
Authors: Blee Alexandra M. , Li Bian , Pecen Turner , Meiler Jens , Nagel Zachary D. , Capra John A. , Chazin Walter J. 
Published: November 2021

AbstractFor precision medicine to reach its full potential for treatment of cancer and other diseases, protein variant effect prediction tools are needed that characterize variants of unknown significance (VUS) in a patient’s genome with respect to their likelihood to influence treatment response and outcomes. However, the performance of most variant prediction tools is limited by the difficulty of acquiring sufficient training and validation data. To overcome these limitations, we applied an iterative active learning approach starting from available biochemical, evolutionary, and functional annotations. The potential of active learning to improve variant interpretation was first demonstrated by applying it to synthetic and deep mutational scanning (DMS) datasets for four cancer-relevant proteins. We then probed its utility to guide interpretation and functional validation of tumor VUS in a potential biomarker for cancer therapy sensitivity, the nucleotide excision repair (NER) protein Xeroderma Pigmentosum Complementation Group A (XPA). A quantitative high-throughput cell-based NER activity assay, fluorescence-based multiplex flow-cytometric host cell reactivation (FM-HCR), was used to validate XPA VUS selected by the active learning strategy. In all cases, selecting VUS for validation by active learning yielded an improvement in performance over traditional learning. These analyses suggest that active learning is well-suited to significantly improve interpretation of VUS and cancer patient genomes.
The tongue biofilm metatranscriptome identifies metabolic pathways associated with halitosis and its prevention
Authors: Carda-Diéguez M. , Rosier B.T. , Lloret S. , Llena C. , Mira A. 
Published: November 2021

AbstractHalitosis is an oral condition caused by an increase in the concentration of volatile sulfur compounds (VSCs), such as methyl mercaptan and hydrogen sulfide, generated as a consequence of bacterial metabolism on the tongue biofilm. Microbial communities on the tongue of halitosis patients have been studied by bacterial culture, 16S rRNA taxonomic studies and metagenomics. However, there are currently no reports on the microbial gene-expression profiles. In this study, we performed RNAseq of tongue coating samples from control individuals and halitosis patients with different levels and composition of VSCs, as determined by gas chromatography. In this metatranscriptomic study, the activity of Streptococcus, Veillonella and Rothia species was associated with halitosis-free individuals while Prevotella, Fusobacterium and Leptotrichia species were associated with halitosis. Although methyl mercaptan is considered an indicator of halitosis, the metatranscriptome of patients in which only this VSC was present in elevated levels was similar to that of halitosis-free individuals. Veillonella dispar, Streptococcus parasanguinis and Rothia mucilaginosa were over-represented in halitosis-free communities in comparison to the rest of the groups, suggesting that these species could be used as a halitosis-free biomarkers. In contrast, the abundance of Prevotella shahi and Fusobacterium nucleatum were significantly higher when hydrogen sulfide concentration was over the established halitosis-threshold, making these species putative halitosis biomarkers. Finally, gene expression profiles showed a significant over-expression of genes involved in L-cysteine and L-homocysteine synthesis in halitosis-free individuals and an over-expression of genes responsible for cysteine degradation into hydrogen sulfide in halitosis patients. In addition, nitrate reduction into nitrite was also over-expressed in halitosis-free patients. In conclusion, halitosis was associated with communities that degrade amino acids and reduce sulfide, whereas tongue communities that produce L-cysteine from hydrogen sulfide and that reduce nitrate were associated with the absence of halitosis. The latter could provide new strategies to treat this condition.
Islamic finance and economic growth: the Turkish experiment
Authors: Ledhem Mohammed Ayoub , Mekidiche Mohammed 
Published: November 2021

PurposeThis study aims to empirically investigate the connection between Islamic finance and economic growth in Turkey using the endogenous growth model.Design/methodology/approachIt applies quantile regression with the Markov chain marginal bootstrap resampling technique by adopting total Islamic financing as the main exogenous explanatory factor in the endogenous growth model, while the gross domestic product (GDP) is employed as a measure of economic growth. The sample consists of all full-fledged participation (Islamic) banks operating in Turkey spanning from 2013Q4 until 2019Q4. The study uses academic literature, official financial reports from the Participation Banks Association of Turkey, REDmoney Group, Islamic Financial Services Board (IFSB) and the International Monetary Fund (IMF) database.FindingsThe results show that Islamic finance is promoting economic growth in Turkey, which mirrors the success of the New Turkish Economy Program (2019–2021) which aims at boosting economic growth by enhancing the Islamic finance share in the Turkish banking sector and the global market.Research limitations/implicationsTurkey has a dual banking system (conventional and participation (Islamic)) and both can influence the country's real economy. This study is limited to the influence of Islamic banking on Turkish economic growth. The study also restricts its size and coverage from 2013Q4 to 2019Q4, to cover the years over which data for all variables included in the research are available.Practical implicationsThis paper suggests the adoption of the Turkish successful experiment as a path to reach economic growth by increasing the Islamic finance share in the banking industry for countries that seek to promote economic growth by Islamic finance, as the findings of this paper support.Originality/valueThis study is the first that examines the influence of Islamic finance on economic growth under a new theoretical framework of the endogenous growth model in Turkey using a robust non-parametric approach.
Green market orientation and organizational performance in Taiwan’s electric and electronic industry: the mediating role of green supply chain management capability
Authors: Borazon Elaine Quintana , Huang Yi-Chun , Liu Jen-Ming 
Published: November 2021

PurposeGreen sustainability has become a critical challenge for businesses to execute green supply chain management (GSCM). Most of the literature on GSCM emphasizes regulations as drivers and few pieces of research are conducted from an internal organizational culture view. This study aims to use the cultural perspective of market orientation (MO) and draws on both the natural resource-based view (NRBV) and dynamic capability view (DCV) to explore the relationships among green market orientation (GMO), GSCM capability and organizational performance.Design/methodology/approachA total of 1,000 survey questionnaires were distributed to the Taiwanese electronics industry and 207 valid questionnaires were collected. Data was analyzed using structural equation modeling.FindingsThe results show that GMOs have a significant positive impact on GSCM capability, environmental performance and economic performance. Moreover, GSCM capability is positively related to environmental and economic performance. The results also show that GMOs have a significant indirect influence on environmental performance and economic performance through GSCM capability.Practical implicationsThe findings of this study suggest how Taiwan’s electrical and electronic manufacturers, while faced with pressure from competitors, customers and regulations (i.e. waste electrical and electronic equipment directive, Restriction of Hazardous Substances Directive and energy-using products directives), should efficiently and effectively implement GMO and enhance GSCM capability to improve organizational performance.Originality/valueThis study fills up the gap between MO and performance indistinct relationships. It has also integrated two perspectives, namely, NRBV and DCV, to explain GSCM capability as a mediator between GMO and organizational performance relationship and to examine the relationships among GMO, GSCM capability and organizational performance.
Service recovery performance and repurchase intentions: the mediation effect of service quality at KFC
Authors: Amoako George Kofi , Caesar Livingstone Divine , Dzogbenuku Robert Kwame , Bonsu Gifty Agyeiwah 
Published: November 2021

PurposeThis paper investigates the effects of service quality on customer satisfaction and repurchase intentions among customers of the KFC Fast Food Restaurant Chains.Design/methodology/approachIn total, 500 randomly sampled KFC restaurant customers were surveyed using a quantitative research design. The partial least square technique was used for data analysis.FindingsThis paper shows that service quality and recovery directly impact customers' repurchase intention. The results further showed that a positive and significant connection exists between customer satisfaction and repurchase intentions.Practical implicationsThe study recommends that KFC utilizes service quality dimensions to meet their customers' expectations and elicit repurchase intentions necessary to remain competitive in the fast-food industry.Originality/valueThis paper highlights the impact of service quality in developing loyal customers in the fast-food sector. It offers managers insight into understanding the factors positively impacting repurchase intentions and the nexus between service recovery performance and repurchase intentions from an emerging market perspective.
Implications of green HRM on the firm's green competitive advantage: the mediating role of enablers of green culture
Authors: Muisyo Paul , Su Qin , Ho Thu Hau , Julius Mercy Muthoni , Usmani Muhammad Shahjahan 
Published: November 2021

PurposeThe available literature demonstrates that green human resource management (GHRM) practices enhance the firm's green performance. However, the studies fail to show how GHRM practices give rise to green culture and how such green culture influences the green competitiveness of a firm. Anchored on the Ability Motivation Opportunity (AMO) theory, this study investigates how firms can build green competitive advantage from GHRM. The study focuses on four enablers of green culture (EGC): leadership emphasis, message credibility, peer involvement and employee empowerment. The study tests the mediating role of each EGC in the relationship between GHRM and green competitive advantage (GCA). The study findings provide managers with a deeper understanding of how GHRM supports the development of the EGC and how they explain the firm's GCA.Design/methodology/approachData was collected from a large-scale survey of Malaysia's manufacturing firm. We managed to collect 96 valid and useable questionnaires.FindingsWe find that GHRM practices give rise to EGC and the EGC mediate the relationship between GHRM and GCA.Originality/valueThe study presents the EGC in the green competitiveness context and goes further to test its mediating role in the GHRM–GCA relationship. We also develop a novel conceptual framework that manufacturing firms can deploy to attain green competitive advantage.