bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlation analysis of hysterectomy and ovarian preservation with depression
Authors: Yang Yunhong , Zhang Xiangqi , Fan Yinuo , Zhang Jiahao , Chen Bingchun , Sun Xiaofeng , Zhao Xiaofeng 
Published: June 2023

AbstractThe relationship between hysterectomy and ovarian preservation and depression is controversial. This study aimed to determine the association of hysterectomy and ovarian preservation with depression using National Health and Nutrition Examination Survey. To assess the association between hysterectomy with or without ovariectomy and depression, we used 3 methods. Method 1: propensity score model (PSM) was established. Method 2 was logistics regression analysis of hysterectomy and depression before and after PSM. Method 3 was a logistics regression analysis of the relationship between hysterectomy and different depressive symptoms. At the same time, in order to evaluate the association between hysterectomy with or without oophorectomy and depression, we explored the effect of four different surgical procedures on depression using logistic regression equations. We enrolled 12,097 women, of whom 2763 underwent hysterectomy, 34.455% were positive for depression. After weighting, 33.825% of the total sample had a PHQ ≥ 5. Finally, a total of 2778 women were successfully matched by propensity score, and 35.537% of them were positive for depression. The OR for PHQ ≥ 5 was 1.236 after crude adjustment of covariates and 1.234 after exact adjustment. This suggests that Hysterectomy is strongly associated with positive depression. Positive depression (PHQ ≥ 5) was associated with little interest, feeling down and trouble concentrating. It was not associated with trouble sleeping, feeling tired, poor appetite, feeling bad, slow moving or speaking, and suicidal thoughts. Oophorectomy-alone is not associated with depression. Hysterectomy-alone is a risk factor for depression, but Hysterectomy combined with Oophorectomy has a stronger correlation with depression than Hysterectomy-alone. Women who have had a Hysterectomy are at higher risk of depression than women who have not had a Hysterectomy, and this risk may be exacerbated if the uterus and ovaries are removed. When clinically appropriate, surgeons should try to preserve the patient's ovaries.
The prevalence of masked hypertension in patients with lone atrial fibrillation: a cross sectional analytical study
Authors: Ayalon-Dangur Irit , Ofer-Shiber Shachaf , Shochat Tzippy , Genin Irina , Arlyuk Maya , Grossman Alon 
Published: June 2023

AbstractAtrial fibrillation (AF) is prevalent in individuals with essential hypertension (HTN). Masked hypertension occurs in up to 15% of the general population and is associated with adverse clinical outcome. The aim of the current study was to evaluate the prevalence of masked hypertension in apparently normotensive individuals with lone AF. A cross sectional analytical study performed at the Rabin Medical Center included all patients > 18 years who visited the emergency department (ED) in the years 2018–2021 with idiopathic AF, had normal blood pressure (BP) values during their ED visit and did not have a history of hypertension or current use of anti-hypertensives. Ambulatory blood pressure monitoring (ABPM) was performed in all eligible patients within 30 days from ED visit. Data collected included information from the ED visit and data extracted from the monitoring device. A total of 1258 patients were screened for eligibility, of which 40 were included in the analysis. The average age was 53.4 ± 16 years, 28 patients (70%) were males. Overall, 18 individuals (46%) had abnormal BP values according to the 2017 ACC/AHA guidelines for the diagnosis of hypertension. Of these, 12 had abnormal 24-h BP average (≥ 125/75 mmHg), one had isolated daytime abnormal average (≥ 130/80 mmHg) and 11 had isolated night time abnormal average (≥ 110/65 mmHg). Masked hypertension is prevalent in patients with lone AF without a diagnosis of HTN and performing ABPM in such individuals should be strongly considered.
Global contextual attention augmented YOLO with ConvMixer prediction heads for PCB surface defect detection
Authors: Xia Kewen , Lv Zhongliang , Liu Kang , Lu Zhenyu , Zhou Chuande , Zhu Hong , Chen Xuanlin 
Published: June 2023

AbstractTo solve the problem of missed and false detection caused by the large number of tiny targets and complex background textures in a printed circuit board (PCB), we propose a global contextual attention augmented YOLO model with ConvMixer prediction heads (GCC-YOLO). In this study, we apply a high-resolution feature layer (P2) to gain more details and positional information of small targets. Moreover, in order to suppress the background noisy information and further enhance the feature extraction capability, a global contextual attention module (GC) is introduced in the backbone network and combined with a C3 module. Furthermore, in order to reduce the loss of shallow feature information due to the deepening of network layers, a bi-directional weighted feature pyramid (BiFPN) feature fusion structure is introduced. Finally, a ConvMixer module is introduced and combined with the C3 module to create a new prediction head, which improves the small target detection capability of the model while reducing the parameters. Test results on the PCB dataset show that GCC-YOLO improved the Precision, Recall, mAP@0.5, and mAP@0.5:0.95 by 0.2%, 1.8%, 0.5%, and 8.3%, respectively, compared to YOLOv5s; moreover, it has a smaller model volume and faster reasoning speed compared to other algorithms.
Adaptive parameter estimation for the expanded sandwich model
Authors: Yang Guanglu , Zhang Huanlong , Liu Yubao , Sun Qingling , Qiao Jianwei 
Published: June 2023

AbstractAn expanded-sandwich system is a nonlinear extended block-oriented system in which memoryless elements in conventional block-oriented systems are displaced by memory submodels. Expanded-sandwich system identification has received extensive attention in recent years due to the powerful ability of these systems to describe actual industrial systems. This study proposes a novel recursive identification algorithm for an expanded-sandwich system, in which an estimator is developed on the basis of parameter identification error data rather than the traditional prediction error output information. In this scheme, a filter is introduced to extract the available system information based on miserly structure layout, and some intermediate variables are designed using filtered vectors. According to the developed intermediate variables, the parameter identification error data can be obtained. Thereafter, an adaptive estimator is established by integrating the identification error data compared with the classic adaptive estimator based on the prediction error output information. Thus, the design framework introduced in this research provides a new perspective for the design of identification algorithms. Under a general continuous excitation condition, the parameter estimation values can converge to the true values. Finally, experimental results and illustrative examples indicate the availability and usefulness of the proposed method.
Applying in-situ visible photopolymerization for fabrication of electrospun nanofibrous carrier for meloxicam delivery
Authors: Ahmadipour Z. , Seyed Dorraji M. S. , Ashjari H. R. , Dodangeh F. , Rasoulifard M. H. 
Published: June 2023

AbstractDespite meloxicam’s many benefits, it will cause many drawbacks if the meloxicam release rate is not controlled. Accordingly, we introduced a technique based on the electrospinning process to control the release rate and also to reduce side effects. For this purpose, different nanofibers were used as drug couriers. Nanofibers were prepared using polyurethane, polyethylene glycol, and light curable poly (ethylene glycol) diacrylate (PEGDA) by electrospinning. In fact, light curable poly (ethylene glycol) diacrylate (PEGDA) was synthesized as a hydrophilic functional group. Next, PEGDA and polyurethane were used simultaneously to fabricate the drug carrier nanofiber in a single processing step, and the electrospinning apparatus was equipped with a blue light source for in-situ photopolymerization during the electrospinning process. The molecular structures of nanofibers and PEGDA were investigated by FT-IR, 1H NMR, 13C NMR, SEM, TEM, XRD, and DSC analyses. Finally, we reduced in vitro drug release to 44% within ten hours, while the minimum release of meloxicam from the tablet was 98%.
Order scheduling optimization in manufacturing enterprises based on MDP and dynamic programming
Authors: Wulan Qiqige 
Published: June 2023

AbstractIn the era of Industry 4.0, order scheduling is a crucial link in the production of manufacturing enterprises. In view of order scheduling in manufacturing enterprises, a finite horizon Markov decision process model is proposed in this work based on two sets of equipment and three types of orders with different production lead times to maximize the revenue in manufacturing production systems. Then, the dynamic programming model is incorporated into the optimal order scheduling strategy. Python is employed to simulate the order scheduling in manufacturing enterprises. Based on survey data, the superiority of the proposed model compared to traditional first come, first served order scheduling is verified by experimental cases. Finally, sensitivity analysis is conducted on the longest service hours of the devices and the order completion rate to explore the applicability of the proposed order scheduling strategy.
Integrative transcriptome and proteome analyses of clear cell renal cell carcinoma develop a prognostic classifier associated with thrombus
Authors: Shi Xiaolei , Pang Qingyang , Nian Xinwen , Jiang Aimin , Shi Haoqing , Liu Wenqiang , Gan Xinxin , Gao Yisha , Yang Yiren , Ji Jin , Tan Xiaojie , Xiao Chengwu , Zhang Wei 
Published: June 2023

AbstractClear cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) is associated with poor prognosis. Our integrative analyses of transcriptome and proteome reveal distinctive molecular features of ccRCC with VTT, and yield the development of a prognostic classifier to facilitate ccRCC molecular subtyping and treatment. The RNA sequencing and mass spectrometry were performed in normal-tumor-thrombus tissue triples of five ccRCC patients. Statistical analysis, GO and KEGG enrichment analysis, and protein–protein interaction network construction were used to interpret the transcriptomic and proteomic data. A six-gene-based classifier was developed to predict patients’ survival using Cox regression, which was validated in an independent cohort. Transcriptomic analysis identified 1131 tumorigenesis-associated differentially expressed genes (DEGs) and 856 invasion-associated DEGs. Overexpression of transcription factor EGR2 in VTT indicated its important role in tumor invasion. Furthermore, proteomic analysis showed 597 tumorigenesis-associated differentially expressed proteins (DEPs) and 452 invasion-associated DEPs. The invasion-associated DEPs showed unique enrichment in DNA replication, lysine degradation, and PPAR signaling pathway. Integration of transcriptome and proteome reveals 142 tumorigenesis-associated proteins and 84 invasion-associated proteins displaying changes consistent with corresponding genes in transcriptomic profiling. Based on their different expression patterns among normal-tumor-thrombus triples, RAB25 and GGT5 were supposed to play a consistent role in both tumorigenesis and invasion processes, while SHMT2 and CADM4 might play the opposite roles in tumorigenesis and thrombus invasion. A prognostic classifier consisting of six DEGs (DEPTOR, DPEP1, NAT8, PLOD2, SLC7A5, SUSD2) performed satisfactorily in predicting survival of ccRCC patients (HR = 4.41, P < 0.001), which was further validated in an independent cohort of 40 cases (HR = 5.52, P = 0.026). Our study revealed the transcriptomic and proteomic profiles of ccRCC patients with VTT, and identified the distinctive molecular features associated with VTT. The six-gene-based prognostic classifier developed by integrative analyses may facilitate ccRCC molecular subtyping and treatment.
A novel prognostic model for hepatocellular carcinoma based on pyruvate metabolism-related genes
Authors: Shi Qingmiao , Xue Chen , Zeng Yifan , Gu Xinyu , Wang Jinzhi , Li Lanjuan 
Published: June 2023

AbstractHepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer, accounting for over 90% of cases. As pyruvate metabolic pathways are often dysregulated in cancer cells, investigating pyruvate metabolism-related genes may help identify prognostic gene signature and develop potential strategies for the management of patients with HCC. The mRNA expression profile, gene mutation data, and clinical information of HCC were obtained from open-source databases. A list of pyruvate metabolism-related genes was downloaded from the MSigDB dataset. Our findings revealed that certain pyruvate metabolism-related genes had copy number variations and single nucleotide variations in patients with liver cancer. Based on pyruvate metabolism-related genes, we stratified patients with HCC into three subtypes with different prognoses, clinical features, mutation profiles, functional annotation, and immune infiltration status. Next, we identified 13 key pyruvate metabolism-related genes significantly correlated with the prognosis of HCC using six machine learning algorithms and constructed a risk model. We also observed that the risk score was positively associated with a worse prognosis and increased immune infiltration. In summary, our study established a prognostic risk model for HCC based on pyruvate metabolism-related genes, which may contribute to the identification of potential prognostic targets and the development of new clinical management strategies for HCC.
Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data
Authors: Wegmann Martin , Jaume-Santero Fernando 
Published: June 2023

AbstractUnderstanding monthly-to-annual climate variability is essential for adapting to future climate extremes. Key ways to do this are through analysing climate field reconstructions and reanalyses. However, producing such reconstructions can be limited by high production costs, unrealistic linearity assumptions, or uneven distribution of local climate records. Here, we present a machine learning-based non-linear climate variability reconstruction method using a Recurrent Neural Network that is able to learn from existing model outputs and reanalysis data. As a proof-of-concept, we reconstructed more than 400 years of global, monthly temperature anomalies based on sparse, realistically distributed pseudo-station data and show the impact of different training data sets. Our reconstructions show realistic temperature patterns and magnitude reproduction costing about 1 hour on a middle-class laptop. We highlight the method’s capability in terms of mean statistics compared to more established methods and find that it is also suited to reconstruct specific climate events. This approach can easily be adapted for a wide range of regions, periods and variables.
Hybrid immunity in older adults is associated with reduced SARS-CoV-2 infections following BNT162b2 COVID-19 immunisation
Authors: Pallett Scott J. C. , Heskin Joseph , Keating Fergus , Mazzella Andrea , Taylor Hannah , Patel Aatish , Lamb Georgia , Sturdy Deborah , Eisler Natalie , Denny Sarah , Charani Esmita , Randell Paul , Mughal Nabeela , Parker Eleanor , de Oliveira Carolina Rosadas , Rayment Michael , Jones Rachael , Tedder Richard , McClure Myra , Groppelli Elisabetta , Davies Gary W. , O’Shea Matthew K. , Moore Luke S. P. 
Published: June 2023

Abstract
Background
Older adults, particularly in long-term care facilities (LTCF), remain at considerable risk from SARS-CoV-2. Data on the protective effect and mechanisms of hybrid immunity are skewed towards young adults precluding targeted vaccination strategies.

Methods
A single-centre longitudinal seroprevalence vaccine response study was conducted with 280 LCTF participants (median 82 yrs, IQR 76-88 yrs; 95.4% male). Screening by SARS-CoV-2 polymerase chain reaction with weekly asymptomatic/symptomatic testing (March 2020-October 2021) and serology pre-/post-two-dose Pfizer-BioNTech BNT162b2 vaccination for (i) anti-nucleocapsid, (ii) quantified anti-receptor binding domain (RBD) antibodies at three time-intervals, (iii) pseudovirus neutralisation, and (iv) inhibition by anti-RBD competitive ELISA were conducted. Neutralisation activity: antibody titre relationship was assessed via beta linear-log regression and RBD antibody-binding inhibition: post-vaccine infection relationship by Wilcoxon rank sum test.

Results
Here we show neutralising antibody titres are 9.2-fold (95% CI 5.8–14.5) higher associated with hybrid immunity (p < 0.00001); +7.5-fold (95% CI 4.6-12.1) with asymptomatic infection; +20.3-fold, 95% (CI 9.7-42.5) with symptomatic infection. A strong association is observed between antibody titre: neutralising activity (p < 0.00001) and rising anti-RBD antibody titre: RBD antibody-binding inhibition (p < 0.001), although 18/169 (10.7%) participants with high anti-RBD titre (>100BAU/ml), show inhibition <75%. Higher RBD antibody-binding inhibition values are associated with hybrid immunity and reduced likelihood of infection (p = 0.003).

Conclusions
Hybrid immunity in older adults was associated with considerably higher antibody titres, neutralisation and inhibition capacity. Instances of high anti-RBD titre with lower inhibition suggests antibody quantity and quality as independent potential correlates of protection, highlighting added value of measuring inhibition over antibody titre alone to inform vaccine strategy.
Sleep quality and temperament in association with autism spectrum disorder among infants in Japan
Authors: Kikuchi Kimiyo , Michikawa Takehiro , Morokuma Seiichi , Hamada Norio , Suetsugu Yoshiko , Ikeda Subaru , Nakahara Kazushige , Kato Kiyoko , Ochiai Masayuki , Shibata Eiji , Tsuji Mayumi , Shimono Masayuki , Kawamoto Toshihiro , Ohga Shouichi , Kusuhara Koichi ,   The Japan Environment and Children’s Study Group, Kamijima Michihiro , Yamazaki Shin , Ohya Yukihiro , Kishi Reiko , Yaegashi Nobuo , Hashimoto Koichi , Mori Chisato , Ito Shuichi , Yamagata Zentaro , Inadera Hidekuni , Nakayama Takeo , Iso Hiroyasu , Shima Masayuki , Kurozawa Youichi , Suganuma Narufumi , Katoh Takahiko 
Published: June 2023

Abstract
Background
Sleep problems and irritable temperaments are common among infants with autism spectrum disorder (ASD). The prospective association between such sleep problems and irritable temperaments and ASDs needs to be determined for elucidating the mechanism and exploring the future intervention study. Thus, in this study, we investigated whether sleep quality and temperament in 1-month-old infants are associated with the onset of ASD in 3-year-old children. We also assessed its sex-stratified associations.

Methods
We conducted a longitudinal study using data from 69,751 mothers and infants from a large-cohort study, the Japan Environment and Children’s Study. We examined the prospective association between infant sleep quality and temperament at 1 month of age and ASD diagnosis by 3 years of age.

Results
Here we show infants with longer daytime sleep have a higher risk of later ASD than those with shorter daytime sleep (risk ratio [RR]: 1.33, 95% confidence interval [CI]: 1.01–1.75). Infants who experienced intense crying have a higher risk of ASD than those who did not (RR: 1.31, 95% CI: 1.00–1.72). There is a difference in sex in the association between a bad mood and later ASD. In particular, female infants experiencing bad moods have a higher risk of ASD than others (RR: 3.59, 95% CI: 1.91–6.75).

Conclusions
The study findings provide important information for future intervention to reduce the risk of future ASD.
Multimodal MRI improves diagnostic accuracy and sensitivity to longitudinal change in amyotrophic lateral sclerosis
Authors: Pisharady Pramod Kumar , Eberly Lynn E. , Adanyeguh Isaac M. , Manousakis Georgios , Guliani Gaurav , Walk David , Lenglet Christophe 
Published: June 2023

Abstract
Background
Recent advances in MRI acquisitions and image analysis have increased the utility of neuroimaging in understanding disease-related changes. In this work, we aim to demonstrate increased sensitivity to disease progression as well as improved diagnostic accuracy in Amyotrophic lateral sclerosis (ALS) with multimodal MRI of the brain and cervical spinal cord.

Methods
We acquired diffusion MRI data from the brain and cervical cord, and T1 data from the brain, of 20 participants with ALS and 20 healthy control participants. Ten ALS and 14 control participants, and 11 ALS and 13 control participants were re-scanned at 6-month and 12-month follow-ups respectively. We estimated cross-sectional differences and longitudinal changes in diffusion metrics, cortical thickness, and fixel-based microstructure measures, i.e. fiber density and fiber cross-section.

Results
We demonstrate improved disease diagnostic accuracy and sensitivity through multimodal analysis of brain and spinal cord metrics. The brain metrics also distinguished lower motor neuron-predominant ALS participants from control participants. Fiber density and cross-section provided the greatest sensitivity to longitudinal change. We demonstrate evidence of progression in a cohort of 11 participants with slowly progressive ALS, including in participants with very slow change in ALSFRS-R. More importantly, we demonstrate that longitudinal change is detectable at a six-month follow-up visit. We also report correlations between ALSFRS-R and the fiber density and cross-section metrics.

Conclusions
Our findings suggest that multimodal MRI is useful in improving disease diagnosis, and fixel-based measures may serve as potential biomarkers of disease progression in ALS clinical trials.
Highly drug resistant clone of Salmonella Kentucky ST198 in clinical infections and poultry in Zimbabwe
Authors: Mashe Tapfumanei , Thilliez Gaetan , Chaibva Blessmore V. , Leekitcharoenphon Pimlapas , Bawn Matt , Nyanzunda Moses , Robertson Valerie , Tarupiwa Andrew , Al-Khanaq Haider , Baker Dave , Gosa Moishe , Kock Marleen M. , Midzi Stanley , Witson Mwamakamba Lusubilo , Jorge Matheu , Jensen Jacob Dyring , Aarestrup Frank M. , Weill François-Xavier , Hendriksen Rene S. , Ehlers Marthie M. , Kingsley Robert A. 
Published: June 2023

AbstractA highly multidrug-resistant strain of Salmonella enterica serotype Kentucky (S. Kentucky) of sequence type (ST)198 emerged in North Africa and has since spread widely. To investigate the genetic diversity and phylogenetic relationship of S. Kentucky in Zimbabwe and identify potential sources of infection, the whole-genome sequence of 37 S. Kentucky strains isolated from human clinical infections and from poultry farms between 2017 and 2020 was determined. Of 37 S. Kentucky isolates, 36 were ST198 and one was ST152. All ST198 isolates had between six and fifteen antimicrobial resistance (AMR) genes, and 92% carried at least ten AMRs. All ST198 isolates harbored the Salmonella genomic island K-Israel variant (SGI1-KIV) integrated into the chromosome with aac(3)-ld, aac(6)-laa, aadA7, blaTEM-1, sul1, and tetA genes, with occasional sporadic loss of one or more genes noted from five isolates. All ST198 isolates also had mutations in the quinolone resistance-determining region of the gyrA and parC genes. The blaCTX-M-14.1 and fosA3 genes were present in 92% of the ST198 isolates, conferring resistance to extended-spectrum cephalosporins and fosfomycin, respectively, were present on an IncHI2 plasmid with the aadA2b, aadA1, aph(3’)-Ib, aph(6’)-Id, cmlA1 and sul3 AMR genes. S. Kentucky ST198 isolates from Zimbabwe formed a closely related phylogenetic clade that emerged from a previously reported global epidemic population. The close genetic relationship and population structure of the human clinical and poultry isolates of ST198 in Zimbabwe are consistent with poultry being an important source of highly resistant strains of S. Kentucky in Zimbabwe.