bluuebunny/crossref_metadata_2025_split huggingface dataset:
Work engagement of healthcare workers in maternal and child health institutions in the post-COVID-19 era: an online cross-sectional study.
Authors: Zhu Hongjin , Long Xin , Cao Limei , Chen Yanqiu 
Published: May 2023

Abstract
In the first wave of infection peak after China officially entered the normalization phase of the COVID-19 pandemic, healthcare workers are facing enormous challenges. This study aims to explore the work engagement and its influencing factors of healthcare workers in maternal and child health institutions in the post-COVID-19 era, as well as possible personal and organizational consequences. In January 2023, an online cross-sectional survey was conducted at maternal and child health institutions in Chongqing, China. Data were collected using the Utrecht Work Engagement Scale (UWES), the Perceived social support scale (PSSS), the Pittsburgh Sleep Quality Index (PSQI), and the Depression Anxiety Stress Scale-21 (DASS-21). Descriptive statistics, t-tests, one-way analyses of variance (ANOVAs), Pearson’s correlation analysis, multiple linear regression analysis and chi-square tests were used to analyze the relationship between variables. Among the 411 healthcare workers, most participants reported moderate and high levels of work engagement. Low and moderate work engagement are more prone to anxiety/depression than high work engagement. The higher the level of work engagement, the higher job satisfaction and the lower turnover intention. Gender was associated with absorption. Employment form was associated with work engagement and its two dimensions (vigor and absorption). Preparedness and perceived social support were positively associated with work engagement and its three dimensions. The results call on hospital management to formulate strategies and measures to increase work engagement by providing a supportive work environment for employees in a high-pressure environment such as the pandemics, thereby ensuring their physical and mental health, retaining and attracting qualified employees, and maintaining the stability of the medical team.
Assessment of the Impact of Climate Change on Soil Moisture Using Remote Sensing and Geographic Information Systems
Authors: MEGHRAOUI Maamar , Mohamed Regagba 
Published: May 2023

Abstract

Studying the relationship between the Soil Moisture Index (SMI) and climate change is crucial, as it provides insights into the impacts of changing climatic conditions on soil moisture dynamics and hydrological processes. Our main objective in this study is to evaluate soil moisture variations in the El Mefrouche watershed in northwestern Algeria, based on changes in climatic parameters such as precipitation and temperature over a period of five years. To achieve this objective, we will use Landsat 8 satellite.images for each year of the study period. The study uses a Soil Moisture Index (SMI) to analyze satellite images taken on five different dates. The results show that on 02/01/2019, the soil moisture was very high (SMI from 0.8 to 1) covering an area of 309.67 hectares, whereas on 12/30/2017, the soil moisture was very low (SMI from 0.8 to 1) covering only an area of 65.46 hectares. The driest SMI values (0 to 0.2) were recorded on 12/30/2017, covering the largest area of 1809.37 hectares, indicating that the soil was very dry in a large part of the watershed. What is really confirmed after analyzing the climatic data for the cited period.
Development of an early mortality risk prediction model for pediatric hemophagocytic lymphohistiocytosis
Authors: Tang Zhexuan , Li Xun , Yan Haipeng , Luo Ting , Xie Longlong , Yang Yufan , Tang Minghui , Jiang Xuedan , Huang Jiaotian , Zhang Xinping , Xiao Zhenghui , Lu Xiulan 
Published: May 2023

Abstract

Background Hemophagocytic lymphohistiocytosis (HLH) is a rare but life-threatening disease with rapid progressing and high mortality, which is more commonly seen in children. Objective Our goal was to develop a novel model for predicting early mortality risk in pediatric HLH patients using readily accessible parameters and build a nomogram. Methods We conducted a retrospective analysis of 170 pediatric HLH patients diagnosed at Hunan Children's Hospital between March 1, 2017, and March 1, 2022. These patients were split into a training cohort and a validation cohort. Early mortality was defined as 28-day mortality post-diagnosis. A prediction model with nomogram was developed using binary logistic regression analysis in the training cohort. The model underwent internal and external validation using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). Results The final prediction model included 11 predictor variables: glutamic-pyruvic transaminase, albumin, globulin, myohemoglobin, creatine kinase, serum potassium, procalcitonin, serum ferritin, the interval between onset and diagnosis, and the interval between admission and diagnosis. The 28-day mortality prediction AUC was 0.957 in the training cohort and 0.929 in the validation cohort. Utilizing the 28-day mortality prediction for estimating 7-day and 14-day mortality, the AUC values were 0.930 and 0.938, respectively. The calibration plot revealed an adequate fit with 1000 bootstrap resampling and the DCA exhibited great net benefit. Conclusion The study constructed a novel prediction model with nomogram in pediatric HLH, which could contribute to rapid assessment early mortality risk after diagnosis with readily available parameters, providing clinical support to identify patients with a poor prognosis and enhancing their prognostic outcomes.
LncRNA GAS5 restrains ISO-induced cardiac fibrosis by targeting miR-217 through regulating SIRT1
Authors: Zhang Yan-hong , Sun Ting-ting , Liu Zhen-huan , LI Xu , Fan Xiao-Fang , Han Liping 
Published: May 2023

Abstract
Aims: Considering the SIRT1 has the effect of improving myocardial fibrosis and GAS5 can inhibit the occurrence and development of myocardial fibrosis at the cellular level, the aim of the present study was to investigate whether LncRNA GAS5 could attenuate cardiac fibrosis through regulating miR-217/SIRT1, and whether the NLRP3 inflammasome activation was involved in this process.
Methods and Results: Isoprenaline (ISO) was given subcutaneously to the male C57BL/6 mice to induce myocardial fibrosis and the AAV9 vectors were randomly injected into the left ventricle of each mouse to overexpress long-chain non-coding RNA GAS5. Primary myocardial fibroblasts (MCFs) derived from neonatal C57BL/6 mice and TGF-β1 was used to induce fibrosis. And the GAS5 overexpressed MCFs were treated with miR-217 mimics and miR-217 inhibitor respectively. Then the assays of expression levels of NLRP3, Caspase-1, IL-1βand SIRT1 were conducted. The Results showed that the overexpression of GAS5 reduced the expression levels of collagen, NLRP3, Capase-1, IL-1β and SIRT1 in ISO treated mice and TGF-β1 treated MCFs. However, this effect was significantly weakened after miR-217 overexpression, but was further enhanced after knockdown of miR-217.
Conclusion: miR-217 down-regulats the expression of SIRT1, then aggravates NLRP3 inflammasome activation-mediated pyroptosis. LncRNA GAS5 alleviates cardiac fibrosis induced by NLRP3 inflammasome activation-mediated pyroptosis via regulating miR-217/SIRT1 pathway. This study provides significant experimental evidence suggesting LncRNA GAS5 to be a potential therapeutic target for cardiac fibrosis and other fibrotic diseases.
Risk factors for hypoactive delirium in patients with non-traumatic ARDS：a prospective, observational study
Authors: Lian Fuyan , li Fei , Tang Xuemei , Yuan Yuan 
Published: May 2023

Abstract
Aims and Objective: To investigate the incidence, characteristics and risk factors for hypoactive delirium in patients with non-traumatic ARDS.Background Hypoactive delirium is a known serious complication in ARDS patients and currently there are no effective early detection models and clinical prediction tools, lack of clinical treatment.Methods The study was conducted with non-traumatic ARDS patients who stayed in the ICU for more than 24 hours and were older than 18 years. 205 ARDS patients admitted to ICU in Gansu Provincial People's Hospital from December 2021 to February 2023 were selected. Demographic, clinical characteristics and laboratory test indicators were collected within 24 h after the patient entered the ICU. A multivariate logistic regression analysis was used to investigate risk factors, at the same times evaluate the clinical prediction effect of the model and draw a Nomogram for visual display.Results The incidence of hypoactive delirium among patients included in the study was 41%. Patients with hypoactive delirium were hypertension, diabetes mellitus, APACHE II score ≥ 15, higher procalcitonin, higher CRP, higher lactic dehydrogenase and higher IL-6 than those without hypoactive delirium. The logistic regression analysis results revealed that diabetes mellitus (OR 3.305, 95% CI: 1.866–12.616; p = 0.047), CRP (OR 1.002, 95% CI: 1.001–1.023; p = 0.044), IL-6 (OR 1.045, 95% CI: 1.017–1.063; p = 0.001) were independent risk factors of hypoactive delirium. After ROC, Calibration plot and Decision Curve Analysis (DCA) confirmed that the clinical prediction of this study model was satisfactory, and a nomogram were drawn for visual display.Conclusions Hypoactive delirium is a common serious complication in non-traumatic ARDS patients. Our logistic regression model not only effectively predicts hypoactive delirium early, but also excavates potential clinical therapeutic targets.
New records of Nanipora aff. kamurai from Akajima and Okinawajima Islands, Okinawa, southern Japan, and a review of the distribution of the genus
Authors: Mironenko Guillermo , Reimer James Davis 
Published: May 2023

Abstract
Nanipora Miyazaki and Reimer, 2015 is a recently described monotypic octocoral genus belonging to the family Helioporidae (class Octocorallia). Nanipora kamurai Miyazaki & Reimer, 2015 was formally described from shallow coral reefs around Zamami Island, within Kerama-shoto National Park, in Okinawa, southern Japan. To date, Nanipora has been reported from two other locations in Japan: N. aff. kamurai from a shallow inner lagoon at Iriomote Island, and N. cf. kamurai from the coral reef surrounding a shallow CO2 vent at Iotorishima Island, both in Okinawa. Additionally, N. cf. kamurai has been reported from two locations outside Japan; in shallow seagrass meadows at Dongsha Atoll in the South China Sea, and on coral reefs at Kho Tao in Thailand. Finally, N. kamurai has been detected in environmental DNA samples from the Rowley Shoals off north western Australia. As a ‘living fossil’ and also apparently common in the low pH environment of Iotorishima I., a clearer understanding of the distribution of the genus should aid in better understanding its ecology. Here, we report three new additional records from the Ryukyu Archipelago where Nanipora colonies were found, resulting in nine total records of Nanipora. However, as Nanipora has been reported as N. kamurai (= azooxanthellate), and as zooxanthellate N. aff. kamurai and N. cf. kamurai across different environments, these findings suggest that the genus Nanipora contains more than one species, and might be a more common and widespread genus across the western Pacific than has been believed until now.
Comparison of equations for eGFR and their predictive ability on postoperative AKI in patients undergoing CABG
Authors: Yin Qi , Shan Lingtong , Zhao Naishi , Sun Yangyang , Pan Yilin , Sun Lin , Dai Huangdong , Han Lixiang , Zhang Yangyang , Liu Xiaoxin , Li Zhi , Xu Tingting 
Published: May 2023

Abstract
Background
Estimated glomerular filtration rate (eGFR) is a recognized and available method for assessing renal functions. Owing to different design purposes and applicable objects, there are different eGFR equations in clinical practice. The aim of this study was to assess the predictive ability of different methods of eGFR for postoperative acute renal injury (AKI) in patients undergoing coronary artery bypass grafting (CABG).
Methods
Totally 2557 patients undergoing CABG were included. Their perioperative clinical data were collected retrospectively through the hospital information system. The predictive power of the Cockcroft-Gault equation (CG), the Berlin Initiative Study equation (BIS), the chronic kidney disease epidemiology collaboration equation (CKD-EPI), and the full age spectrum equation (FAS) was validated both in the total cohort and in the elderly (≥ 70 years) according to the applicability of each equation. The predictive power of these equations for postoperative AKI was assessed and compared using the receiver’s operating characteristic curve, the Bland-Altman plot, decision curve analysis, the net reclassification index (NRI) and integrated discrimination improvement (IDI).
Results
Totally 418 (16.35%) patients were diagnosed with post-operative AKI during the hospital stay, but this percentage reached 25.61% in the elderly population. The CG and CKD-EPI equations were suitable for predicting the occurrence of postoperative AKI in the total cohort, and the FAS equation performed the best (area under the curve = 0.757). The BIS, CKD-EPI, and FAS equations performed generally in the elderly population, but were more consistent and again approximately equal in terms of clinical benefit. NRI and IDI showed the FAS equation continued to perform the best in the total cohort.
Conclusions
The FAS equation can predict the occurrence of postoperative AKI after CABG both in the total cohort and in the elderly population. All of these equations have available predictive power in the elderly population.
Clinical trial registration number: ChiCTR2200061191
On the use of tsunami-source data for high-resolution fault imaging of offshore earthquakes
Authors: Kubo Hisahiko , Kubota Tatsuya , Suzuki Wataru , Nakamura Takeshi 
Published: May 2023

AbstractThe source imaging for offshore earthquakes using terrestrial geodetic data has a limited estimation performance due to the low data resolution. One approach to overcome this limitation is the use of seafloor geodetic data. In this study, we focus on tsunami-source data, which is the spatial distribution of vertical crustal displacements above the source area and can be derived from tsunami waveform records. We evaluate how the use of this spatial seafloor geodetic data improves the estimation of a rectangular fault model. Here, the fault model of the 2016 off-Fukushima, Japan, earthquake, which was a shallow intraplate earthquake (Mw7.0), was estimated by three inversions: terrestrial Global Navigation Satellite System (GNSS) data only, tsunami-source data only, and a combination of the GNSS data and tsunami-source data. A Bayesian inversion approach was used to understand the distribution of the estimated fault parameters and their relationship. The results indicated that the terrestrial GNSS data has a low resolution for the analysis of the offshore earthquake, which resulted in a biased solution with large uncertainty. Conversely, the use of tsunami-source data significantly improved the resolution and reliability of source imaging and reduced the dependency among fault parameters. These results suggested that the high-spatial-resolution information of tsunami source is a powerful tool in source imaging of offshore shallow earthquakes. Moreover, the combined use of the two different geodetic data leads to a more robust estimation of fault parameters. We believe that the use of tsunami-source data is useful, not only for the post-hoc source analysis, but also for estimating an earthquake rupture area just after a large earthquake, where GNSS data are currently used.
Application of density functional theory to study the electronic structure and magnetic behavior of clusters MnPS3 (M=Fe, Co, Ni; n=0~3)
Authors: SONG Jing li , FANG Zhi gang , LIU Li e , WEI Dai xia , YUAN Lin 
Published: May 2023

Abstract
In order to expand the comparative analysis of electronic and magnetic properties of transition metal phosphate materials MPS3, the article selected iron-based transition elements Fe, Co, and Ni as metal atoms M. The configuration design and optimization of cluster MnPS3 were carried out at the calculation level of B3LYP/def2-tzvp using density functional theory, and the optimized configurations were obtained. Analysis of the electronic properties of the optimized configuration reveals thatthe electrons inside the cluster MnPS3 flow from the metal atom M and the non-metal atom P to the non-metal atom S; the S atom is the main site of the electrophilic reaction within the cluster; the electrons inside the metal atom are the main site of the nucleophilic reaction within the cluster; the configurations 2a(2), 2b(2), 3a(4), 3b(3) and 3c(2) have larger mobility of electrons and optimal electronic properties.The analysis of the magnetic properties of the optimized configurations shows that, the magnetic properties of cluster MnPS3 are also determined by the spin motion of α electrons in the p orbital, and the contribution of metal atoms to the magnetic properties of cluster MnPS3 is relatively large; the magnetic properties of configurations 1b(3), 2c(4) and 3a(4) are relatively larger than those of other configurations of the same size.
Investigation of process parameters effects on porosity in SLM process of AlSi10Mg alloys
Authors: MemaranBabakan Ahmad , Davoodi Mohammad , Shafaie Majid , Sarparast Mohsen , Zhang hongyan 
Published: May 2023

Abstract
The laser selective melting (SLM) process is commonly used in additive manufacturing (AM) to produce integrated parts from metallic powder. However, this process can result in porosity in the fabricated components due to gas bubbles or lack of fusion. In a recent study, four different methods (response surface methodology (RSM), artificial neural network (ANN), fuzzy logic (FL), and adaptive-network-based fuzzy inference system (ANFIS)) were employed to predict the correlation between process parameters and porosity levels in AlSi10Mg alloy produced by the SLM process. The ANFIS method was used in this study, which utilizes fuzzy rules and artificial neural networks to predict the impact of process parameters, such as island size, hatch space, scan speed, and laser power on porosity levels. The results showed that the laser power and scan speed had a significant effect on the volume of porosity, while the influence of island size and hatch space was slighter in the SLM process of AlSi10Mg alloy. Furthermore, the ANFIS model demonstrated an excellent fitting parameter with an R2 value of more than 0.99 for the total data and an RMSE of about 0.67 for the output. This result indicates that the ANFIS method is the best model among all the methods tested in accurately predicting the process target. The success of the ANFIS method in this study suggests that it is a robust and reliable technique for predicting porosity levels in the SLM process.
Atypical localization of eczema discriminates DOCK8 or STAT3 deficiencies from atopic dermatitis
Authors: Kasap Nurhan , Kara Altan , Celik Velat , Eltan Sevgi Bilgic , Haci Idil Akay , Kose Hulya , Aygun Ayse , Akkelle Emre , Yakici Nalan , Guner Sukru Nail , Reisli Ismail , Keles Sevgi , Cekic Sukru , Kilic Sara Sebnem , Karaca Neslihan Edeer , Gulez Nesrin , Genel Ferah , Ozen Ahmet , Yucelten Ayse Deniz , Aydiner Elif Karakoc , Schmitz-Abe Klaus , Baris Safa 
Published: May 2023

Abstract
Purpose: Autosomal recessive dedicator of cytokinesis 8 (DOCK8-/-) and autosomal dominant signal transducer and activator of transcription 3 (STAT3+/-) deficiencies are inborn errors of immunity (IEI) disorders present with the classic features of eczema and create a dilemma during differentiation from atopic dermatitis (AD). Therefore, an appropriate approach is required for eczema to diagnose DOCK8-/- and STAT3+/- early. Here, we described a set of clinical and immunological variables, including atypical AD localizations and lymphocyte subsets, to differentiate DOCK8-/- or STAT3+/- from AD.
Methods: This multicenter study involved 100 patients with DOCK8-/- and STAT3+/- and moderate/severe AD. We recruited disease manifestations, including detailed localizations of eczema, infections, and allergy. Principle Component analysis (PCA) was used to discriminate DOCK8-/- or STAT3+/- from AD.
Results: There were 43 patients with DOCK8-/-, 23 with STAT3+/-, and 34 with AD. Pneumonia, severe infections, mucocutaneous candidiasis, and skin abscesses were commonly observed in DOCK8 and STAT3 deficiencies. Atypical skin involvement with neonatal rash, retro auricular, axillary, sacral, and genital eczema discriminate DOCK8-/- and STAT3+/- from AD with high specificity ranges between 73.5 and 94.1% and positive predictive index ranges between 55 and 93.1%. Together with using absolute numbers of CD3+, CD4+, and CD8+ T cells, the combined clinical and laboratory features showed perfect differentiation between DOCK8-/- or STAT3+/- and AD via PCA.
Conclusions: The described features can be easily implemented by physicians providing early diagnosis of DOCK8 and STAT3 deficiencies.
Reducing artifactual somatic variant calls from formalin-fixed paraffin-embedded specimens by using DEEPOMICS® FFPE, a bioinformatic approach based on deep neural networks
Authors: Heo Dong-hyuk , Kim Inyoung , Seo Heejae , Kim Seong-Gwang , Kim Minji , Park Jiin , Park Hongsil , Kang Seungmo , Paik Soonmyung , Hong Seong-Eui 
Published: May 2023

Abstract
Formalin-fixed, paraffin-embedded (FFPE) tissue specimens are routinely used in pathological diagnosis, but their large number of artifactual mutations complicate the evaluation of companion diagnostics and analysis of next-generation sequencing data. Identification of variants with low allele frequencies is challenging because existing FFPE filtering tools label all low-frequency variants as artifacts. To address this problem, we aimed to develop DEEPOMICS® FFPE, an AI model that can classify a true variant from an artifact. Paired exome genome sequencing data from fresh frozen and FFPE samples from 24 tumors were obtained from public sources and used as training and validation sets at a ratio of 7:3. A deep neural network model with three hidden layers was trained with input features using outputs of the MuTect2 caller. Contributing features were identified using the SHapley Additive exPlanations algorithm and optimized based on training results. The performance of the final model (DEEPOMICS® FFPE) was compared with those of existing models (MuTect filter, FFPolish, and SOBDetector) by using well-defined test datasets. We found 43 discriminating properties for FFPE artifacts. Optimization of property quantification improved the model performance. DEEPOMICS® FFPE removed 99.6% of artifacts while maintaining 85.2% of true variants, with an F1-score of 87.8 in the dataset not used for training, which is significantly higher than those of existing tools. Its performance was maintained even for low-allele-fraction variants with an specificity of 0.998, suggesting that it can be used to identify subclonal variants. Different from existing methods, DEEPOMICS® FFPE identified most of the sequencing artifacts in the FFPE samples while retaining more of true variants, including those of low allele frequencies. The newly developed tool DEEPOMICS® FFPE may be useful in designing capture panels for personalized circulating tumor DNA assay and identifying candidate neoepitopes for personalized vaccine design. DEEPOMICS® FFPE is freely available on the web for academic use ().