bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experiences of the physicians in the largest COVID-19 dedicated hospital of Bangladesh about COVID-19 and its aftermath
Authors: Mahmud Reaz , Banu Sultana Shahana , Sultana Nusrat , Monayem Farhana Binte , Datta Ponkaj Kanti , Hoque Mohammad Mahfuzul , Rahman Habib S.M. Habibur , Abedin Joynal , Islam Md. Fakhrul , Arifuzzaman Md. , Islam Md Khairul , Deb Sudip Ranjan , Chowdhury Ahmed Hossain , Uddin Ahmed Kazi Gias , Miah Md. Titu , Rahman Md. Mujibur 
Published: February 2022

AbstractBackgroundThe doctors and the other health care workers are the first-line fighters against COVID-19. This study aims to identify the prevalence, risk factors, clinical severity of COVID-19 infection among the doctors working in the COVID unit. We also analyzed the hospital data for admission and RT-PCR positivity among the physicians.MethodsIt was a cross-sectional survey and review of the hospital database. We surveyed from September 2021 to October 2021 and explored the hospital data from march 2020 to September 2021.We included 342 physicians for analysis in the survey. We reviewed hospital data of 1578 total admitted patients and 336 RT-PCR test positive physicians for analyzing the hospital admission rate, the positivity rate for COVID-19 among the physicians and the other patients in the different COVID-19 surges.FindingsIn this study, we demonstrated the physicians’ sufferings during the pandemic era. We have observed four surges in the hospital admission and RT-PCR for COVID-19 positivity rate among the physicians and the general population. The physicians experienced a similar surge in the hospital admission and positivity rate to the general population. The hospital admission was lower in the fourth surge among the physicians than the general population. The positivity rate was higher in the first, second and third surge among the physicians. In the survey, a total of 146(42%) respondents had COVID-19 infection, and among them, 50(34.2%) had re-detectable positive SARS-CoV-2 infection. Most of them experienced mild (77[52.7%]) to moderate (41[28.1%]) symptoms. Increasing age (OR, 95%CI, p-value; 1.15, 1.05-1.25, 0.002), male sex (OR, 95%CI, p-value; 5.8, 3.2-9.8, <0.001), and diabetes (OR, 95%CI, p-value; 25.6, 2-327.2, 0.01) were the risk factor of having COVID-19. Female sex and diabetes were the risk factors for re-detectable positive SARS-CoV-2 infection. (OR, 95%CI, p-value; 0.24, 0.09-0.67, 0.006; 44, 8.9-218.7, <0.001 respectively). Most respondents suffered for 7-14 days. Total 98(67%) suffered from post-COVID fatigue.ConclusionsThe physicians observed four surges in hospital admission and COVID-19 positivity rate. A significant number of the COVID-warrior became positive for SARS-CoV-2, had re-detectable positive SARS-CoV-2 infection, and suffered in the post-COVID-19 state.
Directed differentiation of EA/TEF patient-derived induced pluripotent stem cells into esophageal epithelial organoids reveal SOX2 dysregulation at the anterior foregut stage
Authors: Raad Suleen , David Anu , Sagniez Melanie , Orfi Zakaria , Dumont Nicolas A. , Smith Martin , Faure Christophe 
Published: February 2022

SummaryA series of well-regulated cellular and molecular events result in the compartmentalization of the anterior foregut into the esophagus and trachea. Disruption of the compartmentalization process leads to esophageal atresia/tracheoesophageal fistula (EA/TEF). Therefore, the objective is to differentiate pluripotent stem cells (PSCs), namely, embryonic stem cells and iPSCs from healthy individuals and iPSCs from EA/TEF type C patients, into mature 3-dimensional esophageal organoids expressing Involucrin, Keratin-4, -13, and p63. CXCR4, SOX17, and GATA4 expression was similar in both patient and healthy endodermal cells. Key transcription factor SOX2 was significantly lower in patient-derived anterior foregut. RNA sequencing revealed critical genes GSTM1 and RAB37 to be significantly lower in patient-derived anterior foregut. Furthermore, we observed an abnormal expression of NKX2.1 in the patient-derived mature esophageal organoids. We therefore hypothesize that a transient dysregulation of SOX2 and the abnormal expression of NKX2.1 in patient-derived cells could be responsible for the abnormal foregut compartmentalization.
Artificial intelligence: a strategy to harness its power through organizational learning
Authors: Jarrahi Mohammad Hossein , Kenyon Sarah , Brown Ashley , Donahue Chelsea , Wicher Chris 
Published: February 2022

Purpose
The purpose of this paper is to present a framework that captures the strategic value of artificial intelligence (AI) systems. Although AI has become a crucial component of digital transformation efforts tied to organizational strategy, many firms struggle to derive strategic value from emerging AI systems.

Design/methodology/approach
The analytical framework in this paper is based on a learning-centered approach. Specifically, by building on the knowledge-based perspective, this paper elaborates on how AI can contribute to organizational learning to create a competitive advantage in knowledge-intensive contexts.

Findings
This paper argues that the power of AI as a strategic resource lies in its self-learning capacities. Such learning capacities are only realized in partnership with humans through mutual learning. This paper formulates the concept of artificial capital and the ways artificial and human capital can together drive routinization and strategic learning processes that connect internal and external environments of the organization.

Originality/value
This is a timely contribution as many organizations are considering adopting AI technologies for strategic purposes. This paper translates the proposed framework into several practical implications for managing and developing AI to meet strategic business goals.
Offline to online shopping: shift in volition or escape from violation
Authors: Duggal Ekta , Verma Harsh Vardhan 
Published: February 2022

Purpose
Research studies have attributed customer shift from offline to online retail to primarily functional reasons. Indian retailing differs from western counterparts in terms of structure and socio-cultural-historical-economic context. The purpose of this paper is to find whether this shift is instigated by positive or negative drive.

Design/methodology/approach
The data were collected through group discussions and reflective experiential accounts in the form of text. The textual material was thematically analyzed to develop thematic networks. By this method, the text’s patent structures were explored, and underlying hidden patterns were identified.

Findings
Two global themes of “volition” and “violation” were discovered. At the patent level, customers are attracted to online in volition as it allows them to move to higher or desired value space. However, at the deeper level, customer shifted to online as a means to escape from violations involved in human-to-human dealings with offline retailers.

Practical implications
The way forward for offline retailers is to build their advantage based on human interactions. The salvation of offline retailing does not lie in trying to beat online retailers on their position of strength but in leveraging interactions to build social capital.

Originality/value
This study sought to explore and apprehend the meaning of customer shift from offline to online retail at deeper psycho-socio-cultural level.
Application of classification models on maintenance records through text mining approach in industrial environment
Authors: Rahman Umama , Mahbub Miraj Uddin 
Published: February 2022

PurposeThe data created from regular maintenance activities of equipment are stored as text in industrial plants. The size of these data is increasing rapidly nowadays. Text mining provides a chance to handle this huge amount of text data and extract meaningful information to improve various processes of an industrial environment. This paper represents the application of classification models on maintenance text records to classify failure for improving maintenance programs in the industry.Design/methodology/approachThis paper is presented as an implementation study, where text mining approaches are used for binary classification of text data. Naive Bayes and Support Vector Machine (SVM), two classification algorithms are applied for training and testing of the models as per the labeled data. The reason behind this is, these algorithms perform better on text data for classifying failure and they are easy to handle. A methodology is proposed for the development of maintenance programs, including classification of potential failure in advance by analyzing the regular maintenance data as well as comparing the performance of both models on the data.FindingsThe accuracy of both models falls within the acceptable limit, and performance evaluation of the models concludes the validation of the results. Other performance measures exhibit excellent values for both of the models.Practical implicationsThe proposed approach provides the maintenance team an opportunity to know about the upcoming breakdown in advance so that necessary measures can be taken to prevent failure in an industrial environment. As predictive maintenance incurs a high expense, it could be a better replacement for small and medium industrial plants.Originality/valueNowadays, maintenance is preventive-based rather than a corrective approach. The proposed technique is facilitating the concept of a proactive approach by minimizing the cost of additional maintenance steps. As predictive maintenance is efficient but incurs high expenses, this proposed method can minimize unnecessary maintenance operations and keep control over the budget. This is a significant way of developing maintenance programs and will make maintenance personnel ready for the machine breakdown.
Impact of visit‐to‐visit fasting plasma glucose variability on the development of diabetes: The mediation by insulin resistance
Authors: Xu Jiji , Li Ling , Huang Shuangqing , Song Haihong , Gao Jinli , Ni Hengru , Lin Hong , Wang Shuangyuan , Li Mian , Wang Tiange , Zhao Zhiyun , Xu Min , Lu Jieli , Bi Yufang , Xu Yu , Qian Xiaozhong 
Published: February 2022

AbstractBackgroundLittle is known about the risk of diabetes due to higher glycemic variability and the underlying mechanisms. We aimed to examine the association of visit‐to‐visit variability (VVV) in fasting plasma glucose (FPG) with incident diabetes in Chinese adults and whether the association was mediated by changes in insulin resistance (IR).MethodsWe included 1856 community residents without a history of diabetes and having attended 3 examinations in 2008, 2009, and 2013 respectively. The SD, the average successive variability (ASV), the coefficient of variation (CV), and the variability independent of the mean (VIM) of three recorded FPG measurements were calculated for each participant, and SD, ASV, CV, and VIM were used as a measure of VVV in FPG. Incident diabetes was defined according to the 1999 World Health Organization criteria. IR was evaluated using the homeostatic model assessment (HOMA).ResultsA total of 153 (8.2%) participants developed incident diabetes at the third visit. Compared with the lowest tertile (0–5.83 mg/dl) of FPG‐SD, the highest tertile (9.55–74.17 mg/dl) was associated with a 148% increased risk of diabetes (odds ratio [OR], 2.48; 95% confidence interval [CI], 1.36–4.49), after adjustment for covariates including mean FPG at 3 visits. Mediation analyses suggested that changes in IR (ΔHOMA‐IR) might mediate 17.3% of the association between increased FPG‐SD and elevated diabetes risk. Similar results were found for FPG‐CV, FPG‐ASV, and FPG‐VIM.ConclusionsThe VVV in FPG was significantly associated with risks of diabetes in Chinese adults, which was partially mediated by changes in IR.
Long‐term consequences of alcohol use in early adolescent mice: Focus on neuroadaptations in GR, CRF and BDNF
Authors: Sampedro‐Piquero Patricia , Moreno‐Fernández Román D. , Begega Azucena , López Matías , Santín Luis J. 
Published: February 2022

AbstractOur aim was to assess the cognitive and emotional state, as well as related‐changes in the glucocorticoid receptor (GR), the corticotropin‐releasing factor (CRF) and the brain‐derived neurotrophic factor (BDNF) expression of adolescent C57BL/6J male mice after a 5‐week two‐bottle choice protocol (postnatal day [pd]21 to pd52). Additionally, we wanted to analyse whether the behavioural and neurobiological effects observed in late adolescence (pd62) lasted until adulthood (pd84). Behavioural testing revealed that alcohol during early adolescence increased anxiety‐like and compulsive‐related behaviours, which was maintained in adulthood. Concerning cognition, working memory was only altered in late adolescent mice, whereas object location test performance was impaired in both ages. In contrast, novel object recognition remained unaltered. Immunohistochemical analysis showed that alcohol during adolescence diminished BDNF+ cells in the cingulate cortex, the hippocampal CA1 layer and the central amygdala. Regarding hypothalamic‐pituitary‐adrenal axis (HPA) functioning, alcohol abuse increased the GR and CRF expression in the hypothalamic paraventricular nucleus and the central amygdala. Besides this, GR density was also higher in the prelimbic cortex and the basolateral amygdala, regardless of the animals' age. Our findings suggest that adolescent alcohol exposure led to long‐term behavioural alterations, along with changes in BDNF, GR and CRF expression in limbic brain areas involved in stress response, emotional regulation and cognition.
Perinatal antidepressant use and breastfeeding outcomes: Findings from the Norwegian Mother, Father and Child Cohort Study
Authors: Grzeskowiak Luke E. , Saha Moni R. , Nordeng Hedvig , Ystrom Eivind , Amir Lisa H. 
Published: February 2022

AbstractIntroductionAntidepressant use is common in the perinatal period, but there are concerns that it can negatively impact on breastfeeding outcomes. The aim of this study was to examine the effects of perinatal antidepressant use on breastfeeding initiation and duration.Material and methodsThis was a retrospective analysis of 80 882 mother–infant dyads in the Norwegian Mother, Father and Child Cohort Study (MoBa). Women were first classified according to self‐reported mental disorders and timing of antidepressant use before and/or after gestational week 28 (i.e., early‐mid–gestation and/or late‐gestation use). We subsequently classified women according to self‐reported mental disorders and antidepressant use postpartum and whether antidepressants were continued from late gestation or were new/restarted. Breastfeeding outcomes included breastfeeding initiation as well as predominant or any breastfeeding and abrupt breastfeeding discontinuation until 6 months.ResultsLate‐gestation antidepressant use was associated with a reduced likelihood of breastfeeding initiation (adjusted relative risk [aRR] 0.93; 95% confidence interval [CI] 0.90–0.97) but not predominant (aRR 0.96; 95% CI 0.67–1.39) or any (aRR 1.00; 95% CI 0.93–1.07) breastfeeding at 6 months compared with unexposed women with mental disorders. When examined according to postnatal antidepressant use, no differences in predominant (aRR 0.94; 95% CI 0.60–1.48) or any breastfeeding (aRR 0.99; 95% CI 0.91–1.07) at 6 months were evident among women who continued antidepressant use from late gestation into the postpartum period compared with unexposed women with mental disorders. In contrast, new/restarted antidepressant use postpartum was associated with a reduced likelihood of predominant (aRR 0.37; 95% CI 0.22–0.61) and any (aRR 0.49; 95% CI 0.42–0.56) breastfeeding at 6 months, as well as increased risk of abrupt breastfeeding discontinuation (aRR 2.64; 95% CI 2.07–3.37) compared with the unexposed women with mental disorders.ConclusionsA complex relation exists between depression, antidepressant use, and breastfeeding outcomes. Antidepressant use in late pregnancy was associated with a reduced likelihood of breastfeeding initiation but not breastfeeding duration or exclusivity. In contrast, initiating or restarting antidepressants postpartum was associated with poorer breastfeeding outcomes. Overall, women taking antidepressants and women with a mental disorder may benefit from additional education and support to improve breastfeeding rates and promote maternal and infant health and wellbeing.
Review highlights the importance of donor human milk being available for very low birth weight infants
Authors: Picaud Jean‐Charles 
Published: February 2022

AbstractAimThe aim of this paper was to review the role that donor human milk plays in caring for very low birth weight (VLBW) infants.MethodsThis review focussed on academic papers and background information published in English and French up to 8 August 2021.ResultsDonor human milk provides a useful bridge to successful breastfeeding in hospitalised neonates and does not have a negative impact on the use of mother's own milk and breastfeeding rates at discharge. It helps to prevent key complications of prematurity, particularly necrotising enterocolitis up to 36 weeks of postmenstrual age, which is more common in infants fed formulas based on cows' milk. When it is carefully fortified, it supports the postnatal growth of the majority of very preterm infants. Well‐organised, accessible human milk banks are required to cover the needs of hospitalised infants, and donor human milk must be prioritised for patients who derive the greatest health benefit from it. These include very preterm infants and those born at term, or near term, with surgical digestive malformations or congenital heart disease.ConclusionSafe, high‐quality donor human milk, which is distributed by well‐organised human milk banks, is essential for the most vulnerable hospitalised neonates.
An interpretative phenomenological analysis of the development and maintenance of gluten‐related distress and unhelpful eating and lifestyle patterns in coeliac disease
Authors: Satherley Rose‐Marie , Lerigo Fiona , Higgs Suzanne , Howard Ruth 
Published: February 2022

ObjectiveEstimates indicate that individuals with coeliac disease are more likely to experience disordered eating and impaired well‐being than healthy controls, but less is known about the mechanisms by which these factors are related. The aim of this study was to understand experiences of coeliac disease and influence on subsequent unhelpful eating and lifestyle patterns.MethodsAn online focus group discussion, hosted through a synchronous chat log, with adults living with coeliac disease was conducted. Seven individuals discussed their condition, lifestyle, and dietary changes post‐diagnosis. Discussions were analysed using an interpretative phenomenological approach, a technique that enables new practical or research insight into health conditions based upon participants’ experiences of their condition.ResultsThree themes were identified: (i) Nobody knew what was happening to my body; (ii) I am so afraid of being ‘glutened’ that it is central to my thoughts and anxieties; and (iii) I am frightened but I can keep myself safe by being a ‘good’ coeliac. These appeared to contribute to participant distress or unhelpful eating or lifestyle behaviours. Participants appeared to develop severe anxiety around gluten, and implausible beliefs around diet and lifestyle management that appear to initiate and maintain unhelpful eating behaviours and maladaptive lifestyles changes, that contribute to distress.ConclusionsExtending current knowledge, we propose a novel cognitive perspective on the development and maintenance of disordered eating in coeliac disease. Implications for how health providers can better support individuals with coeliac disease, and the role of dietary management, anxiety, and gastrointestinal symptoms in the development of disordered eating are discussed.
Adrenal androgens versus cortisol for primary aldosteronism subtype determination in adrenal venous sampling
Authors: Viukari Marianna , Kokko Eeva , Pörsti Ilkka , Leijon Helena , Vesterinen Tiina , Hinkka Tero , Soinio Minna , Schalin‐Jäntti Camilla , Matikainen Niina , Nevalainen Pasi I. 
Published: February 2022

AbstractObjectiveWe examined if measurement of adrenal androgens adds to subtype diagnostics of primary aldosteronism (PA) under cosyntropin‐stimulated adrenal venous sampling (AVS).DesignA prospective pre‐specified secondary endpoint analysis of 49 patients with confirmed PA, of whom 29 underwent unilateral adrenalectomy with long‐term follow‐up.MethodsConcentrations of androstenedione, dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulphate (DHEAS) were measured during AVS in addition to aldosterone and cortisol. Subjects with lateralisation index (LI) of ≥4 were treated with unilateral adrenalectomy, and the immunohistochemical subtype was determined with CYP11B2 and CYP11B1 stains. The performance of adrenal androgens was evaluated by receiver operating characteristics (ROC) curve analyses in adrenalectomy and medical therapy groups.ResultsDuring AVS, the correlations between cortisol and androstenedione, DHEA and DHEAS for LI and selectivity index (SI) were highly significant. The right and left side SIs for androstenedione and DHEA were higher (p < .001) than for cortisol. In ROC analysis, the optimal LI cut‐off values for androstenedione, DHEA and DHEAS were 4.2, 4.5 and 4.6, respectively. The performance of these LIs for adrenal androgens did not differ from that of cortisol.ConclusionsUnder cosyntropin‐stimulated AVS, the measurement of androstenedione and DHEA did not improve the cannulation selectivity. The performance of cortisol and adrenal androgens are confirmatory but not superior to cortisol‐based results in lateralisation diagnostics of PA.
Machine learning algorithms are comparable to conventional regression models in predicting distant metastasis of follicular thyroid carcinoma
Authors: Mao Yaqian , Lan Huiyu , Lin Wei , Liang Jixing , Huang Huibin , Li Liantao , Wen Junping , Chen Gang 
Published: February 2022

AbstractObjectiveDistant metastasis often indicates a poor prognosis, so early screening and diagnosis play a significant role. Our study aims to construct and verify a predictive model based on machine learning (ML) algorithms that can estimate the risk of distant metastasis of newly diagnosed follicular thyroid carcinoma (FTC).DesignThis was a retrospective study based on the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015.PatientsA total of 5809 FTC patients were included in the data analysis. Among them, there were 214 (3.68%) cases with distant metastasis.MethodUnivariate and multivariate logistic regression (LR) analyses were used to determine independent risk factors. Seven commonly used ML algorithms were applied for predictive model construction. We used the area under the receiver‐operating characteristic (AUROC) curve to select the best ML algorithm. The optimal model was trained through 10‐fold cross‐validation and visualized by SHapley Additive exPlanations (SHAP). Finally, we compared it with the traditional LR method.ResultsIn terms of predicting distant metastasis, the AUROCs of the seven ML algorithms were 0.746–0.836 in the test set. Among them, the Extreme Gradient Boosting (XGBoost) had the best prediction performance, with an AUROC of 0.836 (95% confidence interval [CI]: 0.775–0.897). After 10‐fold cross‐validation, its predictive power could reach the best [AUROC: 0.855 (95% CI: 0.803–0.906)], which was slightly higher than the classic binary LR model [AUROC: 0.845 (95% CI: 0.818–0.873)].ConclusionsThe XGBoost approach was comparable to the conventional LR method for predicting the risk of distant metastasis for FTC.