bluuebunny/crossref_metadata_2025_split huggingface dataset:
Treatments and whole exon sequencing of a case with multiple primary lung cancer
Authors: Bai Guangyu , Li Yuan , Ji Ying , Peng Yue , Yang Zhenlin , Zhao Liang 
Published: November 2022

Abstract
Background: The number of patients with synchronous multiple primary lung cancer (sMPLC) has increased recently. However, diagnosing and selecting the appropriate therapeutic strategy for this type of disease is not simple.
Case presentation: This report presented a case of sMPLC with lymph node metastasis. With no smoking and cancer history, this patient had seven nodules in the right lung and underwent single-portal video-assisted thoracoscopic surgery (VATS). In addition, she received four cycles of chemotherapy after the operation. Whole exon sequencing (WES) was performed in five resected tissue samples (four tumors and one lymph node). We conducted genomic profiling and clone evolution analysis of the five samples. Gene detection helped to confirm that the metastasis lymph node was transferred from one nodule. There was apparent heterogeneity of gene mutations among the five samples of the patient, with only one shared “neurofilament heavy polypeptide” (NEFH) mutation. A dominant substitution of C>T/G>A was found in all the samples. Pyclone model was used to calculate all tissues' cellular prevalence (CP) values, and NEFH mutations were thought to be the ancestral clones. During the follow-up period, residual lesions showed no apparent changes and limited response to chemotherapy.
Conclusions: This report showed an essential role in genomic detection and selecting the appropriate treatment of sMPLC. Surgery remains the primary treatment strategy for this type of disease, and the occurrence and development of sMPLC need more in-depth research.
Challenges, rewards and lessons learned from family and community caregivers of individuals with serious mental illness and cancer
Authors: Murphy Kerri A. , Corveleyn Amy E. , Park Elyse R. , Irwin Kelly E. 
Published: November 2022

Abstract
Purpose: The caregiving experience for individuals with serious mental illness (SMI) and cancer has not been explored in previous cancer caregiver research. This study assessed the challenges, rewards, and lessons learned from this unique population of caregivers.
Methods: We conducted qualitative interviews with 13 caregivers: (9 family caregivers, 4 community caregivers) of patients recently diagnosed with head and neck, breast, lung or gastrointestinal cancer and SMI who participated in a single-arm pilot of person-centered collaborative care. Interviews were transcribed and analyzed using inductive and deductive approaches. Investigators developed a coding scheme based on the interview guide. Interviews were double-coded and themes were identified via an iterative consensus process consistent with a Content Analysis framework. Comparisons between community and family caregiver experiences were explored.
Results: Caregiving challenges included the impact of mental health symptoms on timely diagnosis, treatment and coordination of care and lack of resources specific to SMI and cancer caregiving. Family caregivers valued increased closeness and meaningfulness in their relationships. Family and community caregivers found it rewarding to be part of a person-centered care model that was effective for the patient. Lessons learned included tending to their own needs too, and the importance of advocacy and a team approach to decrease mental health stigma and coordinate care.
Conclusions: This study highlights the complex challenges and rewards experienced by family and community caregivers for individuals with cancer and SMI. Tailored approaches to support caregivers as individuals are needed. Additional research on community caregiver-patient dyads and non-spousal family caregiver-patient dyads are needed to inform intervention development.
Enhancing the parameters of ZnO/CdZnS thin film photodetector by thermal annealing
Authors: Mohammed Kahtan A. , Alshamarti Hussein. A. , Jameel Hadeel. A. 
Published: November 2022

Abstract
This work aims to manufacture photodetectors from semiconducting bilayer materials of zinc oxide Nanorods (ZnO NRs) and coated with a thin layer of CdZnS by chemical bath deposition method (CBD). The effect of annealing time on the optical and electrical properties of the prepared devices and on the parameters of the devices was also studied. The prepared films were thermally treated by annealing at a temperature of 200 ° C for several times for the purpose of comparison. The annealing times were 15 30 35 60 minutes, respectively, by means of a vacuum furnace. The effect of the annealing time was noticeable and obvious on the optical and electrical properties of the manufactured photodetectors.
Formation and Degradability of Per- and Polyfluoroalkyl Substances in River Soils around a Fluoropolymer Manufacturing Plant in Osaka, Japan
Authors: Thepaksorn Phayong , Lee Pureum , Shiwaku Yoko , Zheng Bo , Koizumi Akio , Harada Kouji 
Published: November 2022

Abstract
Our previous studies reported that perfluorooctanoic acid (PFOA) contamination has decreased in well, tap and surface water around a fluoropolymer plant in Osaka, Japan between 2003 and 2016. In this study, we evaluated the degradability of PFOA and perfluorohexanoic acid in river soils to identify the influence of the degradation on the perfluorocarboxylic acids (PFCAs) in the Yodo River Basin. We also investigated the influence of abiotic oxidation on the formation of PFCAs in soils and measured the fluorotelomer alcohols (FTOHs) as precursors of PFCAs in the soil and air samples collected at Osaka and Kyoto, respectively. No major changes were observed in soils contaminated with PFCA during the 24-week experimental period, while the PFOA levels increased only in the control group. The PFCA levels significantly increased after oxidation in this group. The dominant FTOH in soils was 10:2 FTOH, whereas 6:2 FTOH was dominant in the air samples. These findings suggest that PFOA was rapidly removed from water system but persist in soils. Moreover, the results indicate the need to evaluate not only the PFCAs, but also the FTOHs and other precursors for the accurate prediction of PFCA accumulation and fates in the environment.
Chronicity of high and low level Mupirocin resistance in Staphylococcus aureus from 30 Indian hospitals
Authors: Prakash Rajni , Garg Amar , Arya Riteshkumar 
Published: November 2022

Abstract
Mupirocin is one of the most effective topically used antibiotic for the treatment of dermatitis, nasal carriage, decolonization of methicillin susceptible Staphylococcus aureus and eradication of methicillin resistant Staphylococcus aureus. Extensive use of this antibiotic has resulted in mupirocin resistance in Staphylococcus aureus which is a matter of concern. This study was conducted to evaluate the high and low level of mupirocin resistance in Staphylococcus aureus collected from various Indian hospitals. A total of 600 samples, of which 436 were pus specimens and 164 wound site swabs were collected from 30 Indian hospitals. Disc diffusion and agar dilution methods were used to test mupirocin susceptibility in methicillin resistant staphylococcus aureus. Out of 600 non-duplicate Staphylococcus aureus isolates, 176 isolates (29.33%) were found to be methicillin resistant Staphylococcus aureus (MRSA). Out of 176 non-duplicate MRSA strains,138 isolates were found to be mupirocin sensitive, 21 isolates had high level resistance whereas 17 isolates had low level resistance to mupirocin, which contributed 78.41%, 11.93 % and 9.66% respectively. Overall, high rate of mupirocin resistance was found in the studied samples which might be a result of in discriminated use of mupirocin in the population of studied region. This data emphasizes the urgent need for formulation of a well-defined and regulated guidelines for mupirocin use. Moreover, continuous surveillance is needed for the use of mupirocin and routine test should be performed to detect MRSA in patients and health care personnel to prevent MRSA infections.
Development of machine learning models for predicting unfavorable functional outcomes in patients with chronic subdural hematomas
Authors: Fuse Yutaro , Nagashima Yoshitaka , Nishiwaki Hiroshi , Ohka Fumiharu , Muramatsu Yusuke , Araki Yoshio , Nishimura Yusuke , Ienaga Junpei , Nagatani Tetsuya , Seki Yukio , Watanabe Kazuhiko , Ohno Kinji , Saito Ryuta 
Published: November 2022

Abstract
Chronic subdural hematoma (CSDH) often causes neurological deterioration and is treated with hematoma evacuation. This study aimed to assess the feasibility of various machine learning models to preoperatively predict the functional outcome of patients with CSDH. Data were retrospectively collected from patients who underwent CSDH surgery at two institutions: one for internal validation and the other for external validation. The poor functional outcome was defined as a modified Rankin scale score of 3–6 upon hospital discharge. The unfavorable outcome was predicted using four machine learning algorithms on an internal held-out cohort (n = 188): logistic regression, support vector machine (SVM), random forest, and light gradient boosting machine. The prediction performance of these models was also validated in an external cohort (n = 99). The area under the curve of the receiver operating characteristic curve (ROC-AUC) of each machine learning-based model was found to be high in both validations (internal: 0.906–0.925, external: 0.833–0.860). In external validation, the SVM model demonstrated the highest ROC-AUC of 0.860 and accuracy of 0.919. This study revealed the potential of machine learning algorithms in predicting unfavorable outcomes at discharge among patients with CSDH undergoing burr hole surgery.
Designing, Implementing, and Evaluating of Teaching Scholarship in Virtual Multidisciplinary Tumor Board
Authors: Khoshgoftar Zohreh , Sodeifian Fatemeh , Allameh Farzad 
Published: November 2022

Abstract
Background
Cancer management has become increasingly challenging due to the emergence of personalized approach which requires careful assessment, multidisciplinary efforts, and experienced physicians.
Because of the COVID-19 pandemic’s effect on executing all medical meetings as well as multidisciplinary tumor boards (MTB) we decided to design, perform and evaluate a teaching scholarship in virtual MTB for urologic cancer patients.
Methods
In this prospective study from December 2020 to July 2022, the authors evaluated designing, implementation, and learning efficacy of a virtual tumor board in the urology department of Shahid Beheshti University of Medical Sciences (SBMU). All the faculty members (N=25) and urology residents (N=35) were included in this investigation. To make the sessions, multidisciplinary, other related departments including pathology, radio-oncology, medical oncology, radiology, and nuclear medicine were also included. Virtual tumor boards were implanted monthly in twenty sessions.
Results
A short interview was conducted for the needs assessment. The faculty members and residents’ statements were divided of high, intermediate, and low importance. After implementation satisfaction questionnaire based on the first level of Kirkpatrick model was recorded and the means were 76% and 71% in faculty members and residents respectively for virtual execution. Results of evaluating the intervention according to the second level of Kirkpatrick model and through the tests before and after tumor boards were recorded and the mean differences evaluated by paired t-test were statistically significant. In the last step for external evaluation, the satisfaction rate of 5 arbitrators was 75% for executing a proper virtual MTB.
Conclusion
A virtual board is an effective learning method for medical education of urology residents. It could help practitioner to coordinate and discuss with different specialties and leads to the best decision for urologic cancer patients.
Methionine mitigates protein deficiency by regulating the expression of translation initiation factors, even with sufficient sulfur, in rats fed a protein-deprived diet
Authors: Yamada Fumiyo , Mori Erika , Yamaoka Ippei 
Published: November 2022

Abstract
Dietary supplementation with methionine and threonine mitigates protein deficiency in rats fed a protein-deprived diet, an effect that is not observed for other essential amino acids. However, the precise mechanisms are not fully understood. The aim of this study was to explore whether the activation of translation initiation factors in the mammalian target of rapamycin pathway in skeletal muscle contributes to protein retention by supplementation with methionine and/or threonine. Male Sprague-Dawley rats were freely fed 0% protein diets for 2 weeks, and furthermore fed for 12 days 14.5 g of a restricted diet containing 12% soy protein supplemented with methionine and threonine (MT), methionine (M), threonine (T), or neither (NA) (n = 8), while two additional groups were fed 0% protein or 20% casein protein diets as controls (n = 6). Body weight and gastrocnemius muscle weight were higher, and blood urea nitrogen and urinary nitrogen excretion were lower, in the M and MT groups than in the T and NA groups, respectively. p70 S6 kinase 1 abundance and protein expression levels were higher, and eukaryotic translation initiation factor 4E-binding protein 1 abundance and mRNA levels were lower, in the skeletal muscles of rats fed with methionine (M and MT groups). These results suggest that methionine regulates the mass of protein via translation initiation machinery in the skeletal muscle, retaining whole-body protein in protein-deprived rats.
Optimization of experimental design techniques for modeling volumetric shrinkage in injection molding experiment using artificial intelligence
Authors: Raimi Oluwole Abiodun 
Published: November 2022

Abstract
The study examined two types of design of experiments (DoE) methods for injection molding of a molded part. It evaluated them using an artificial neural network (ANN) and a support vector machine (SVM) via cross-validation and holdout validation. The innovative goal is to identify the most efficient and successful ways for modeling varied DoE. The influence of four processing parameters on the volumetric shrinkage of a thin polystyrene plate sample is simulated using factorial design and orthogonal Taguchi arrays design. As measured by root mean square error (RMSE), the prediction performance revealed that DoE with eight experimental points as in \({2}^{4-1}\) for fractional factorial design and L8 for orthogonal Taguchi design is particularly efficient for this modeling simulation problem. Both design methods are beneficial and efficient because orthogonal Taguchi arrays play an essential role when the accuracy of fractional factorial designs is insufficient.
COVID-19 progression and convalescence in common variable immunodeficiency patients shows incomplete adaptive responses and persistent inflammasome activation
Authors: Rodríguez-Ubreva Javier , Handfield Louis-Francois , Keller Baerbel , Ciudad Laura , Calle-Fabregat Carlos de la , Godoy-Tena Gerard , Calafell-Segura Josep , Andrés-León Eduardo , Hoo Regina , Porter Tarryn , Prigmore Elena , Hofmann Maike , Decker Annegrit , Martín Javier , Warnatz Klaus , Vento-Tormo Roser , Ballestar Esteban 
Published: November 2022

Abstract

Patients with common variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, are characterized by hypogammaglobulinemia, poorly protective vaccine titers and increased susceptibility to infections. New pathogens such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), might constitute a particular threat to these immunocompromised patients since many of them experience a slower recovery and do not achieve full response to SARS-CoV-2 vaccines. To define the molecular basis of the altered immune responses caused by SARS-CoV-2 infection in CVID patients, we generated longitudinal single-cell datasets of peripheral blood immune cells along viral infection and recovery. We sampled the same individuals before, during and after SARS-CoV-2 infection to model their specific immune response dynamics while removing donor variability. We observed that COVID-19 CVID patients show defective canonical NF-κB pathway activation and dysregulated expression of BCR-related genes in naïve B cells, as well as enhanced cytotoxic activity but incomplete cytokine response in NK and T cells. Moreover, monocytes from COVID-19 CVID patients show persistent activation of several inflammasome-related genes, including the pyrin and NLRC4 inflammasomes. Our results shed light on the molecular basis of the prolonged clinical manifestations observed in these immunodeficient patients upon SARS-CoV-2 infection, which might illuminate the development of tailored treatments for COVID-19 CVID patients.
Impact of dysautonomic symptom burden on the quality of life in Neuromyelitis optica spectrum disorder patients
Authors: Yang Lili , Li Wenjing , Xie Yan , Ma Shuai , Zhou Xiaobo , Huang Xinyue , Tan Song 
Published: November 2022

Abstract
Background
The aim of this study was to investigate the clinical risk factors of dysautonomic symptom burden in neuromyelitis optica spectrum disorder (NMOSD), and its impact on patients’ quality of life.
Methods
A total of 63 NMOSD patients and healthy controls were enrolled. All participants completed the Composite Autonomic Symptom Score 31 (COMPASS-31) to screen for symptoms of autonomic dysfunction. A comprehensive clinical evaluation was performed in NMOSD patients, including disease characteristics and composite evaluations of life status, including quality of life, anxiety/depression, sleep, and fatigue. Correlated factors of dysautonomic symptoms and quality of life were analyzed.
Results
The score of COMPASS-31 in the NMOSD group was 17.2 ± 10.3, significantly higher than that in healthy controls (P = 0.002). In NMOSD patients, the higher COMPASS-31 score was correlated with more attacks (r = 0.49, P < 0.001), longer disease duration (r = 0.52, P < 0.001), severer disability (r = 0.50, P < 0.001), more thoracic cord lesions (r = 0.29, P = 0.02), more total spinal cord lesions (r = 0.35, P = 0.005), severer anxiety (r = 0.55, P < 0.001), severer depression (r = 0.48, P < 0.001), severer sleep disturbances (r = 0.59, P < 0.001), and severer fatigue (r = 0.56, P < 0.001). The disability, total spinal cord lesions and fatigue were revealed to be independently associated factors. Further analysis revealed that the COMPASS-31 score was the independently correlated with score of all the domains of patients’ quality of life scale (P < 0.05).
Conclusions
Dysautonomic symptom burden is correlated with decreased quality of life and certain clinical characteristics such as disability, spinal cord lesions and fatigue in NMOSD patients. Investigation and proper management of autonomic dysfunction may help to improve the quality of life in patients with NMOSD.
An Adaptive k-nearest neighbor Classifier using Differential Evolution with Auto-Enhanced Population Diversity for Intrusion Detection
Authors: Karimi Zohre , Torabi Zeinab 
Published: November 2022

Abstract
Machine learning methods have attracted increasing interest in recent studies on intrusion detection. A classifier is applied to discriminate attacks from normal connections in these methods. 𝒌-nearest neighbor (𝒌NN) has been widely used in intrusion detection due to its simplicity and effectiveness. The classical 𝒌NN exploits Euclidean distance for identifying nearest neighbors, whereas how to compute the distance of data points is highly application-specific and plays a crucial role in the effectiveness of this classifier. In this paper, a novel 𝒌NN classifier is proposed that employs p-norm distance metric, the generalization of Euclidean distance, by learning p from data. The value of p in the proposed data-dependent metric is learned by the differential evolution algorithm exploiting auto-enhanced population diversity. The experimental results showed significant improvements in terms of F1 score and error rate compared to conventional kNN and Naive Bayesian classifiers on Kyoto2006+ and NSL-KDD. Furthermore, they verify the superiority of kNN classifier using the proposed data-dependent metric in terms of receiver operating characteristic curve and the corresponding area under the curve.
Longitudinal telomere dynamics within natural lifespans of a wild bird
Authors: Pepke Michael Le , Kvalnes Thomas , Wright Jonathan , Araya-Ajoy Yimen G. , Ranke Peter Sjolte , Boner Winnie , Monaghan Pat , Sæther Bernt-Erik , Jensen Henrik , Ringsby Thor Harald 
Published: November 2022

Abstract
Telomeres, the nucleotide sequences that protect the ends of eukaryotic chromosomes, shorten with each cell division and telomere loss may be increased by factors such as oxidative stress. Telomere length (TL) decreases with age in several species, and TL or the change in TL (∆TL) have emerged as biomarkers reflecting experienced stress. In this study, we tracked changes in TL throughout the natural lifespan (from a few months to almost 9 years) of free-living house sparrows (Passer domesticus) in two different island populations. TL was measured in nestlings and subsequently up to 4 times during their lifetime. TL generally decreased with age (senescence), but we also observed instances of telomere lengthening within individuals. We found some evidence for selective disappearance of individuals with shorter telomeres through life. Early-life TL positively predicted later-life TL, but the within-individual repeatability in TL was low (9.2%). Using genetic pedigrees, we found a moderate heritability of ∆TL (h2 = 0.21), which was higher than the heritabilities of early-life TL (h2 = 0.14) and later-life TL measurements (h2 = 0.15). Cohort effects explained considerable proportions of variation in early-life TL (60%), later-life TL (53%), and ∆TL (37%), which suggests persistent impacts of the early-life environment on lifelong telomere dynamics. Individual changes in TL were independent of early-life TL. Finally, there was weak evidence for population differences in ∆TL that may be linked to ecological differences in habitat types. Combined, our results show that individual telomere biology is highly dynamic and influenced by both genetic and environmental variation in natural conditions.