bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of interval between oocyte retrieval and resuscitation embryo transfer on pregnancy outcomes
Authors: Wan Qi , Chen Ming-Xing , Wang Xue-Jiao , Tan Li , Yu Hui-Jun , LV Xing-Yu , Zhong Zhao-Hui , Tang Xiao-Jun , Ding Yu-Bin , Xia Min , Li Yuan 
Published: August 2022

Abstract
Resuscitation transfer of embryos after elective cryopreservation is gaining popularity worldwide owing to higher implantation rates. This method separates oocyte retrieval from embryo transfer. The optimal time for frozen embryo transfer (FET) remains unknown. This retrospective cohort study aimed to determine the difference in pregnancy outcomes between patients who underwent immediate FET and those who underwent delayed FET. We analyzed real-world data of patients who underwent resuscitation transplantation between October 2019 and July 2021 at the Reproductive Center of Chengdu Jinjiang Hospital for Women’s and Children’s Health. Propensity score matching was applied to control for potential confounding factors. A total of 5549 patients who received at least one FET were analyzed. Patients undergoing transplantation within 60 days of oocyte retrieval were included in the immediate FET group (n = 1265) and those undergoing transplantation > 60 days after retrieval were included in the delayed FET group (n = 4284). Live birth rates between the two groups were comparable (45.25% vs. 45.76%, p = 0.757). Moreover, no difference was observed in the rates of biochemical pregnancy (64.50% vs. 66.80%), clinical pregnancy (55.24% vs. 56.83%), ectopic pregnancy (1.47% vs. 1.39%), early miscarriage (14.41% vs. 16.20%), late miscarriage (2.21% vs. 2.09%), singleton premature delivery (16.67% vs. 18.29%), and neonatal deformity (1.97% vs. 1.80%). After stratifying the patients based on the type of embryo transferred, number of embryos transferred, FET protocol, and good prognosis criteria, live birth rates remained comparable between the two groups (p > 0.05). In conclusion, pregnancy outcomes were comparable between the immediate and delayed FET groups.
Photocatalytic degradation of tetracycline antibiotic and organic dyes using biogenic synthesized CuO/Fe2O3 nanocomposite: Pathways and mechanism insights
Authors: Kaushal Sandeep , Kumar Avdhesh , Bains Himani , Singh Prit Pal 
Published: August 2022

Abstract
Tetracycline (TC) is a frequently administered antibiotic in many countries, due to its low price and excellent potency. However, certain antibiotics can be hazardous to living creatures due to their accumulation by complexation with metal ions which can contribute to teratogenicity and carcinogenicity. In this investigation, ferrous oxide-copper oxide nanocomposite (CuO/Fe2O3 nanocomposite) were synthesised employing Psidium guajava (P. guajava) leaf extract as a reductant and a capping agent in an environment friendly and economical green synthesis method. The as-synthesized CuO/Fe2O3 nanocomposite were comprehensively characterized using various sophisticated techniques and their efficiency as photocatalyst for degradation of TC antibiotic and toxic dyes i.e. rhodamine B (RhB) and methylene blue (MB) was investigated. The CuO/Fe2O3 nanocomposite exhibited exceptional efficiency for degradation of TC antibiotic (88% removal in 80 min), RhB (96% removal in 40 min) and MB (93% elimination in 40 min) with apparent rate constant of 0.048, 0.068 and 0.032 min− 1. In the degradation experiments, photocatalytic activities of CuO/Fe2O3 nanocomposite were studied by varying different factors such as time of contact, catalyst dose and solution pH. The role of reactive species in antibiotics and dye degradation was validated by radical scavenging studies which indicated that .OH radical has a critical role in photocatalytic decomposition. Furthermore, liquid chromatography-mass spectrometry (LC-MS) investigations were employed to anticipate a plausible mechanism for TC degradation.
The CASPer Preparation Program Innovation: Increasing Self-Perceived Competence and Confidence of Underrepresented Applicants on the Novel CASPer Snapshot and CanMEDS Roles
Authors: Mahmood Farhan , Oguntala Julianah , Henoud Claudine , Pierre-Louis Libny Lahelle , Fuad Asli , Okafor Ike 
Published: August 2022

Abstract
Background: Underrepresented Minorities in Medicine (URMMs) may face financial and social limitations when matriculating into medical schools. Performance on situational judgment tests such as Computer-based Assessment for Sampling Personal Characteristics (CASPer) can be enhanced by coaching and mentorship. The CASPer Preparation Program (CPP) coaches URMMs to prepare for the CASPer test. During the coronavirus 2019 pandemic (COVID-19), CPP implemented novel curricula on the CASPer Snapshot and CanMEDS roles.Methods: Pre and post-program questionnaires were completed by the students, which assessed their: 1) confidence in understanding the CanMEDS roles, and 2) perceived confidence in performing well and their familiarity and preparedness with the CASPer Snapshot.Results: Participants reported a significant increase in the URMMs’ knowledge, self-perceived competency to complete the CASPer Snapshot, and their anxiety significantly decreased. The level of confidence in understanding CanMEDS roles for a career in healthcare increased as well. The majority (91%) agreed that the feedback received from tutors was adequate and the virtual component of the program was beneficial during COVID-19.Conclusion: Pathway coaching programs have the potential to increase confidence and familiarity amongst URMMs for the CASPer tests and CanMEDS roles. Similar programs should be developed with the aim to increase the chances of URMMs matriculating into medical schools.
Cellular and humoral SARS-CoV2 vaccination responses in 192 adult recipients of allogeneic hematopoietic cell transplantation
Authors: Wehr Claudia , Meyer Thomas , Ihorst Gabriele , Bartsch Ingrid , Zeiser Robert , Wäsch Ralph , Bertz Hartmut , Finke Jürgen , Huzly Daniela 
Published: August 2022

Abstract
To determine factors influencing the vaccination response against SARS-CoV2 is of importance in recipients of allogeneic hematopoietic cell transplantation (allo-HCT) as they display an increased mortality after SARS-CoV2 infection, an increased risk of extended viral persistence and reduced vaccination response. Real-life data on anti-SARS-CoV2-S1-IgG titres (n = 192) and IFN-γ release (n = 110) of allo-HCT recipients were obtained using commercially available, validated assays after vaccination with either mRNA (BNT™, Moderna™) or vector based vaccines (AstraZeneca™, Johnson/Johnson™) or after a heterologous protocol (vector/mRNA). Humoral response (78% response rate) was influenced by age, time after transplantation, the usage of ATG and ongoing immunosuppression, specifically corticosteroids. High counts of B cells during the vaccination period correlated with a humoral response. Only half (55%) of participants showed a cellular vaccination response. It depended on age, time after transplantation, ongoing immunosuppression with ciclosporin A, cGvHD and vaccination type with vector based protocols favoring response. Cellular response failure correlated with higher CD8 + count and activated/HLA-DR + T cells one year after transplantation. Our data provide the basis to assess both humoral and cellular responses after SARS-CoV2 vaccination in daily practice, thereby opening the possibility to identify patients at risk.
Development of Python Application for Automated Geomatics Data Processing, Analysis, and Visualisation
Authors: Ugwuanyi Ifeanyi A. , Anejionu Obinna C.D. 
Published: August 2022

Abstract
Emerging technologies have led to the rapid generation of vast quantities of field data by geomatics professionals. However, these raw field data cannot be directly utilised unless they undergo rigorous processing (using complex mathematical models e.g. - reductions, adjustments, and computations) to convert them to meaningful information. These operations are often repetitive. Despite global advancement in automated data processing, most surveyors in developing countries such as Nigeria still deploy manual surveying computation techniques for their day-to-day data processing and analysis needs. Hence, the development of cost effective and easy-to-use automated applications based on the existing models is highly relevant, to ease operations requiring repeated processes. This study developed a Python-based geomatics application “Survey Companion” that can streamline the processing of survey field data into meaningful spatial information. To achieve these, python codes were written for the processing of data from key geomatics operations such as traverse and levelling networks, resection, intersection, and bathymetric operations as well as area computation. It is expected that this application will greatly improve survey operations in developing countries as well as increase the speed of data processing, thereby reducing overall project costs.
Prediction of estimated risk for bipolar disorder using machine learning and structural MRI features
Authors: Mikolas Pavol , Marxen Michael , Riedel Philipp , Bröckel Kyra , Martini Julia , Huth Fabian , Berndt Christina , Vogelbacher Christoph , Jansesn Andreas , Kircher Tilo , Falkenberg Irina , Lambert Martin , Kraft Vivien , Leicht Gregor , Mulert Christoph , Fallgatter Andreas , Ethofer Thomas , Rau Anne , Leopold Karolina , Bechdolf Andreas , Reif Andreas , Matura Silke , Bermpohl Felix , Fiebig Jana , Stamm Thomas , Correll Christoph , Juckel Georg , Flasbeck Vera , ritter philipp , Bauer Michael , Pfennig Andrea 
Published: August 2022

Abstract

Individuals with bipolar disorder are commonly correctly diagnosed a decade after the onset of first symptoms. Machine learning techniques may aid in early recognition and reduce the disease burden. As both individuals at risk and those with a manifest disease display structural brain markers, structural magnetic resonance imaging (MRI) may provide relevant classification features. Following a pre-registered protocol, we trained linear support vector machine (SVM) to classify individuals according to their estimated risk for bipolar disorder using regional cortical thickness values of help-seeking individuals from 7 study sites (N = 276). We estimated the risk using three state-of-the-art assessment instruments (BPSS-P, BARS and EPIbipolar). For BPSS-P, SVM achieved a fair performance of Cohen's kappa of 0.235 (95% CI 0.11–0.361) and a balanced accuracy of 63.1% (95% CI 55.9–70.3) in the 10-fold crossvalidation. In the leave-one-site-out crossvalidation, the model performed with a Cohen's kappa of 0.128 (95% CI -0.069-0.325) and a balanced accuracy of 56.2% (95% CI 44.6–67.8). BARS and EPIbipolar could not be predicted. In post hoc analyses, regional surface area, subcortical volumes as well as hyperparameter optimization did not improve the performance. Individuals at risk for bipolar disorder, as assessed by BPSS-P, display brain structural alterations that can be detected using machine learning. The achieved performance is comparable to previous studies which attempted to classify patients with manifest disease and healthy controls. Unlike previous studies of bipolar risk, our multicenter design permitted a leave-one-site-out crossvalidation. Whole brain cortical thickness seem to be superior to other structural brain features.
Psychotropic Consumption Before and During Covid-19 in Asturias, Spain
Authors: García Dra. María Luisa Nicieza , Martínez Dra. Paula Fernández , Bretón Dra. Eva Fernández , Dra Marta María Martínez Alfonso , Gil Patricio Suárez 
Published: August 2022

Abstract
BACKGROUND: Spain as multiple other countries, has been experiencing an increasing and sustained trend in the use of psychotropic medications since the mid 90s. Recent studies show public health measures implemented to control SARS-Cov2, such as mobility restrictions and the shutdown of nonessential activities increased mental suffering, even contributing to a higher number of anxiety, depression and insomnia disorders that could lead to an increase in the consumption of psychotropics. The aims were: 1) Evaluate the temporal trend in psychotropic consumption by therapeutic subgroup, sex, and age group 2) Estimate the effect of the COVID-19 pandemic in the use of psychotropic drugs.METHODS: We conducted a retrospective observational study, retrieving all prescriptions of anxiolytics, hypnotics/sedatives, and antidepressants dispensed in pharmacies of Asturias (Northern Spain) for Primary Care patients for the period 2018-2021.We presented the data expressed in Daily Defined Doses (DDDs) for 1000 persons/day (DHD). To estimate changes in DHDs by year and age group we conducted 2 multiple linear regressions (one for males and one for females) for every therapeutic subgroup studied. Changes were considered statistically significant when the regression coefficient was p<0.05. We used the Software R 4.1.0.RESULTS:For the studied period, the highest DHDs are for antidepressants, although all of the subgroups experienced an increase in consumption rates.Women consumed more psychotropic drugs than men. In 2021, 372 out of every 1,000 women were taking daily 1 DDD of these drugs versus 184 out of every 1,000 men. Consumption rates for all psychotropic drugs progressively increases with age. Conversely, the biggest increases in consumption were among the youngest age groups (0-14 years, 43.2% increase and 15-29 years, 35.1% increase).The regression models suggest an upward trend in psychotropic consumption during all the period, especially remarkable from 2020, for both genders and all age groups. CONCLUSIONS:-The growing and sustained trend in consumption of psychotropic drugs for the recent years has increased since the start of the SARS-COV2 pandemic for both sexes, especially from 2020 onwards. This trend is consistent with the observed national one.-The increase observed on children and adolescents is a matter of concern.
The impact of cyclin-dependent kinases 4 and 6 inhibitors in the immune response to mRNA SARS-CoV-2 vaccine in women with breast cancer.
Authors: Saavedra Cristina , Vallejo Alejandro , Longo Federico , Serrano Juan José , Fernández-Abad María , Gion María , López-Miranda Elena , Martínez-Jáñez Noelia , Guerra Eva , Chamorro Jesús , Rosero Diana , Velasco Héctor , Martín Adrián , Carrato Alfredo , Casado Jose Luis , Cortés Alfonso 
Published: August 2022

Abstract
Introduction:
Patients with cancer have a higher risk of complications and death from coronavirus disease 2019 (COVID19), thus vaccination is crucial in this population. Oncologic therapies can affect vaccination response, but few data are available about the immune response to mRNA SARS-CoV-2 vaccines in patients with breast cancer receiving cyclin-dependent kinases 4/6 inhibitors (CDK4/6i). Our study aimed to assess the immunogenicity and safety of the mRNA-1273 vaccine in patients treated with CDK4/6i in comparison with a group of volunteer health workers.
Methods:
We conducted a prospective, single-center study including patients with breast cancer treated with CDK4/6i and a comparative group of health care workers (HCW). Blood samples were collected before and after first dose administration, and after second dose. The primary endpoint was to compare the rate and magnitude of humoral and T-cell responses after full vaccination. Neutralizing antibodies titers, the correlation between neutralizing and anti-S antibodies, the incidence of COVID-19 after vaccination, and safety were defined as secondary objectives.
Results:
No differences were observed in the rate of either anti-S or neutralizing antibodies after full vaccination, being 100% in both groups. A positive correlation was found between neutralizing and anti-S antibodies. However, the rate of anti-S CD4 and CD8 T-cell response after complete vaccination was a 15% lower in the CDK4/6i group, although differences were not statistically significant (CD4 T-cell response 69.2% vs 84.6%; p 0.324; anti-S T-cell CD8 response 69.2% vs 84.6%; p 0.324). No differences in the incidence of COVID-19 after vaccination were found (19.2% vs 11.5%, p 0.703). Patients with vaccine breakthrough showed lower levels of anti-S antibody after the first dose (492.29 vs 157.96; p 0.029) and lower titers of neutralizing antibodies after full vaccination (p 0.068). The rate of adverse events was higher in patients treated with CDK4/6i. No serious adverse events were reported in any of the two groups.
Conclusion:
While a robust humoral response was observed in the CDK4/6i group, a limited T cell response was found, without differences in the rate of subsequent COVID-19. Further insight into the underlying mechanisms is crucial to improve breast cancer patients’ protection and to adjust vaccination strategies in this specific population.
Pattern Discovery and Disentanglement: A New Interpretable Machine Learning Paradigm for Relational Datasets
Authors: Zhou Pei-Yuan , Wong Andrew , Lee Annie 
Published: August 2022

Abstract
In machine learning (ML) on relational datasets, association patterns in the data, paths in decision trees, and weights between layers of the neural network coming from multiple underlying sources are often entangled, masking the pattern-to-source relation, weakening prediction and defying explanation. This paper presents a revolutionary ML paradigm: Pattern Discovery and Disentanglement (PDD), which disentangles associations and provides an All-in-One knowledge framework and computational platform, capable of a) disentangling patterns to associate with distinct sources/classes; b) discovering rare/imbalanced groups, detecting anomalies and rectifying discrepancies to improve class association, pattern/entity clustering; c) organizing knowledge for interpretability/traceability for causal exploration with statistical support. Results from base studies validate such capabilities. The explainable knowledge reveals pattern-source relations, entity characteristics and underlying factors for causal inference, clinical study, and practice, addressing the major concern of interpretability, trust and reliability when applying ML to healthcare --- a step towards closing the AI chasm.
Effects of an Attenuated Coxsackievirus B3 Strain to Cells With Different Expression Levels of Coxsackievirus-Adenovirus Receptor
Authors: Cai Ligang , Li Junxiong , Liu Zhiyi , Tian You 
Published: August 2022

Abstract
Oncolytic therapy has emerged as a new method of cancer treatment next to surgery, chemotherapy, and radiotherapy. RNA viruses can become oncolytic viruses as their replication occurs in the cytoplasm and they do not integrate into the host DNA. Coxsackievirus can potentially become a type of oncolytic virus because of its ability to cause disease (mainly in children) and its simple genome structure which makes genetic manipulation easy. Coxsackievirus B3 (CVB3) has a good cytotoxic effect on non-small cell lung cancer in vitro. At present, some locally injectable oncolytic viruses approved for clinical studies include Rigvir and CAVATAK. Nevertheless, not enough studies are available on whether CVB3 has different cytotoxic effects on Coxsackievirus-Adenovirus Receptor (CAR) cells and whether the inhibition rate of tumor tissues show variations with different CAR expression levels in vivo. In the current research, the recombinant CVB3 strain constructed and preserved in our laboratory was used as an oncolytic virus to investigate if its cytotoxic effect on lung cancer cells was related to CAR receptor expression. Because the recombinant CVB3 strain was targeted for oncolytic treatment of lung cancer, an intravenous injection was proposed. The results indicated that the expression level of CAR on the cell surface was not the only factor affecting CVB3 infection, but the sensitivity of NSCLC cell lines to CVB3 was associated with CAR expression level on the cell surface. According to in vivo studies, the CVB3 showed a better inhibitory effect on tumor tissues that have a high level of CAR expression. These findings support the intravenous administration of CVB3 for oncolytic therapy.
Household food waste and theory of planned behavior: A systematic review and meta-analysis
Authors: Srivast Saurabh Kumar , Mishra Aviral , Singh Saumya , Jaiswal Deepak 
Published: August 2022

Abstract
The darker side of food behavior is that millions of tons of food have been shown the doors of garbage. Therefore, food waste behavior needs an eye to look upon. The purpose of this research is to inculcate the concept of systematic literature review along with meta-analysis in order to examine the Theory of Planned Behavior (TPB) with respect to food waste behavior. The methodology includes Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) that is conducted for identification, screening and inclusion of studies. In all, twenty-six independent studies with (N = 13373) met the inclusion criteria. For validating the related literature, Random-effects meta-analysis has been applied for ascertaining average correlation among the variables. More specifically, the present study also examines the sub-group analysis effect among TPB variables. The findings reveal that the strongest association was observed between attitude and intention followed by subjective norms and intention, perceived behavioral control and intention, and intention and behavior. Furthermore, the subgroup analysis using multi-cultural groups explores the highest composite correlation in case other cultural groups that included country like Canada. In addition, the sample size subgroup analysis supports that the increase in sample size lead towards more strengthening of association among TPB variables. The outcomes of the present study seek to serve in the best interest of households, event management stakeholders and food policy makers.