bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis and Prediction of Elderly Sports Participation using Artificial Neural Networks and Logistic Regression Models
Authors: Byun Hyun , Jeon Sang-Wan , Yi Eun Surk 
Published: December 2022

Abstract
Background
Korea's aging population and the lack of participation in sports by the elderly are increasing medical expenses. This study aimed to segment elderly sports participants based on their demographic characteristics and exercise practice behavior and applies artificial neural network and logistic regression models to these segments in order to best predict the effect of medical cost reduction. It presents strategies for elderly sports participation.
Methods
A sample comprising data on 1,770 elderly people aged 50 years and above, drawn from the 2019 National Sports Survey were used. The data were analyzed through frequency analysis, hierarchical and K-means clustering, artificial neural network, logistic regression, and cross-tabulation analyses, as well as one-way ANOVA using SPSS 23 and Modeler 14.2. The participants were divided into five clusters.
Results
The artificial neural network and logistic analysis models showed that the cluster comprising married women in their 60s who participated in active exercise had the highest possibility of reducing medical expenses.
Conclusions
Targeting women in their 60s who actively participate in sports The government should expand the supply of local gymnasiums, community centers, and sports programs. Thus, if local gymnasiums and community centers run sports programs and appoint appropriate sports instructors, the most effective medical cost reduction effect can be obtained.
A novel predictive model for phthisis bulbi following facial hyaluronic acid cosmetic injection
Authors: Si Shancheng , Su Wei , Wang Lei , Ji Yicong , Chen Anming , Hu Yuntao 
Published: December 2022

Abstract
Purpose:To observe long-term prognosis of anterior segment ischemia (ASI) following hyaluronic acid (HA) injection, propose a severity grading system for ASI and a predictive model for phthisis bulbi (PB) based on long-term secretion dysfunction of ciliary process.
Methods: This is a retrospective case-control study. All enrolled 20 patients were divided into two groups and followed for at least 6 months to observe the formation and transformation characteristics of ASI and long-term prognosis based on the degrees of ciliary function damage.
Results:The severity of ASI following HA injection could be subdivided into 4 grades according to the degrees of ciliary function damage, comprising ASI grades 0, 1, 2 and 3. In 20 patients, PB at the 2-year follow-up, ophthalmoplegia at 1-month follow-up, ASI within 1 month, ASI at 1-month follow-up, hypotony within 6 months were all significantly more common in study group than in control group (50% vs. 0%, P=0.033; 60% vs. 0%, P=0.011; 100% vs. 20%, P=0.001; 100% vs. 0%, P＜0.001; 80% vs. 0%, P=0.001, respectively). Sensitivity, specificity and the area under the receiver operating characteristic curve (AUC) for predicting subsequent PB at 2-year follow-up through the co-occurrence of ophthalmoplegia at 1-month follow-up and hypotony within 6 months was 100%, 100% and 1.00, respectively.
Conclusions: The new grading system for ASI and novel predictive model for PB we proposed could predict the long-term prognosis and probability of subsequent PB due to ASI following HA injection through several dynamic assessments within 6 months.
Level of Evidence:Level IV, observational prognostic study
Development and application of hepatocellular carcinoma risk prediction model based on clinical characteristics and liver related indexes
Authors: Liu Zhijie , Xu Yue , Wang Wenxuan , Guo Bin , Guo Xiaolan , Zhang Guoyuan , Luo Guangcheng , Wang Qiang 
Published: December 2022

Abstract
Background and aims:

Hepatocellular carcinoma (HCC) is difficult to diagnose and has a low survival rate. The survival of patients with HCC is closely related to the stage of diagnosis. Using logistic regression model, this study aimed to identify risk factors associated with HCC and establish a risk prediction model based on clinical characteristics and liver-related indicators to predict the presence of HCC.

Methods

The clinical data of patients in Affiliate Hospital of North Sichuan Medical College from 2016 to 2020 were collected. Based on the time of admission, the cases were divided into training cohort (n = 1739) and validation cohort (n = 467). Using HCC as a dependent variable, the research indicators were incorporated into logistic univariate and multivariate analysis. An HCC risk prediction model, which was called NSMC-HCC model, was then established in training cohort and verified in validation cohort.

Results

The area under receiver operating characteristic curve (AUC) of NSMC-HCC model in HCC diagnosis was 0.960, with sensitivity 94.40% and specificity 95.35% in training cohort, and AUC was 0.966, with sensitivity 90.00% and specificity 94.20% in validation cohort. In early-stage HCC diagnosis, the AUC of NSMC-HCC model was 0.946, with sensitivity 85.93% and specificity 93.62% in training cohort, and AUC was 0.947, with sensitivity 89.10% and specificity 98.49% in validation cohort.

Conclusions

NSMC-HCC model was an effective risk prediction model in HCC and early-stage HCC diagnosis.
Seroprevalence against SARS-CoV-2 in health workers: evaluation 6 months after the complete scheme and reinfections
Authors: Cureño-Díaz Mónica Alethia , Vargas-De-León Cruz , Salaza Ma. Isabel , Cruz-Cruz Clemente , Loyola-Cruz Miguel Ángel , Durán-Manuel Emilio Mariano , Zamora-Pacheco Edwin Rodrigo , Bravata-Alcántara Juan Carlos , Fernández-Sánchez Verónica , Bello-López Juan Manuel , Gabriela Ibáñez-Cervantes 
Published: December 2022

Abstract
Background: One of the priority lines for the containment of the SARS-CoV-2 virus pandemic is the vaccination programs for health personnel. However, with the emergence of highly contagious strains such as the Omicron variant, it is necessary to know the serological status of health personnel to make decisions for the application of reinforcements.
Objectives: To determine the seroprevalence against SARS-CoV-2 in health workers in a Mexican hospital, after six months of the administration of the Pfizer BioNTech vaccine and the association between comorbidities, response to the vaccine and reinfections.
Methods: Antibodies against SARS-CoV-2 were determined by ELISA assays in 262 employees of the Hospital Juárez de México with and without a history of COVID-19. A beta regression analysis was performed to study the associated comorbidities and their relationship with the levels of antibodies against SARS-CoV-2. Finally, epidemiological follow-up was carried out to detect reinfections in this population.
Results: A significant difference in SARS-CoV-2 seroprevalence was observed in workers with a history of COVID-19 prior to vaccination, compared to those without a history of the disease. Beta regression showed that workers with a history of COVID-19 have greater protection, compared to those without a history of the infection. Neutralizing antibodies were found to be decreased in alcoholic and diabetic subjects. Eight cases with omicron reinfections were identified, and gender and obesity are associated with the presence of reinfections.
Conclusion: The response to the vaccine was influenced by the history of SARS-CoV-2 infection and associated comorbidities. The above highlights the importance of prioritizing this segment of the population for reinforcements in periods of less than one year to guarantee their effectiveness against new variants.
Experimental Approach for Development of a Powder Spreading Metric in Additive Manufacturing
Authors: Sehhat M. Hossein , Sutton Austin T. , Yates Zane , Leu Ming C. 
Published: December 2022

Abstract
The powder spreading is a vital step of powder-based Additive Manufacturing (AM) processes. The quality of spread powder can considerably influence the properties of fabricated parts. Poorly-packed powder beds with high surface roughness result in printed part layers with large porosity and low dimensional accuracy, leading to poor mechanical properties. Therefore, the powder spreadability and its dependence on process parameters and powder characteristics should be quantified to improve the efficiency of powder-based AM methods. This study proposes a novel dimensionless powder spreadability metric that can be commonly used in different powder-based AM processes. The quality of spread powder in terms of powder bed density and surface roughness was evaluated by adjusting the process parameters, including recoating velocity and layer thickness, and powder characteristics, including particle size distribution. In addition, the dynamic repose angle was proposed and examined as another powder spreadability metric. The results showed that these two proposed metrics were strongly correlated, and lower recoating velocity and larger layer thickness led to higher spreadability and lower dynamic repose angle.
Mediators and Moderators of the Effect of the Game Changers for Cervical Cancer Prevention Intervention on Cervical Cancer Screening Among Previously Unscreened Social Network Members in Uganda
Authors: Matovu Joseph KB , Wagner Glenn J. , Juncker Margrethe , Namisango Eve , Bouskill Kathryn , Nakami Sylvia , Beyeza-Kashesya Jolly , Luyirika Emmanuel , Wanyenze Rhoda K. 
Published: December 2022

Abstract
Introduction: Cervical cancer (CC) rates are high in Uganda, yet CC screening rates are very low. Our peer advocacy group intervention, Game Changers for Cervical Cancer Prevention (GC-CCP), was shown to increase CC screening uptake among social network members. In this secondary analysis, we examined mediators and moderators of this effect to better understand how and for whom the intervention was most successful in promoting CC screening.
Methods: We conducted a pilot randomized controlled trial of GC-CCP in Namayingo district, Eastern Uganda between September 2021 and April 2022. Forty adult women who had screened for CC in the past year (index participants) enrolled at baseline: 20 were randomized to receive the 7-session intervention to empower women to engage in CC prevention advocacy, and 20 were assigned to the waitlist control; from these index participants, 103 unscreened social network members (alters) also enrolled. All participants were assessed at baseline and month 6 follow-up. Change in cognitive and behavioral CC-related constructs from baseline to month 6 were examined as mediators, using multivariate linear regression analysis. Index and alter demographics and index CC treatment status were examined as moderators.
Results: Increased alter engagement in CC prevention advocacy fully mediated the intervention effect on alter uptake of CC screening, and was associated with an increased likelihood of alter CC screening. CC treatment status of the index participant was the sole moderator of the intervention effect, as those in the intervention group who had screened positive and received treatment for pre-cancerous lesions were more likely to have alters who got screened for CC by month 6.
Conclusion: The effect of GC-CCP on alter CC screening is enhanced when the alter has been spurned on to increase her own advocacy for CC prevention. The intervention effects on increased engagement in CC prevention advocacy among both index and alter participants suggest a diffusion of advocacy, which bodes well for dissemination of knowledge and screening activation throughout a network and the larger community.
Kai-Xin-San protects against mitochondrial dysfunction in Alzheimer's disease through SIRT3/NLRP3 pathway
Authors: Su Shi-Jie , Chen GongCan , Gao Minghuang , Zhong Guangcheng , Zhang Zerong , Wei Dongyun , Luo Xue , Wang Qi 
Published: December 2022

Abstract
Background
Kai-Xin-San (KXS) has been reported to have a good curative impact on dementia. The purpose of the study was to determine whether KXS might ameliorate cognitive deficits in APP/PS1 mice and to evaluate its neuroprotective mechanism.
Methods
APP/PS1 mice were employed as an AD animal model; Aβ1–42 and KXS-containing serum were used in HT22 cells. Four different behavioral tests were used to determine the cognitive ability of mice. Nissl staining was utilized to detect hippocampal neuron changes. ROS, SOD, and MDA were used to detect oxidative stress levels. Transmission electron microscopy and Western blot were used to evaluate mitochondrial morphology, mitochondrial division, and fusion state. Western blotting and immunofluorescence identified PSD95, BDNF, NGF, SYN, SIRT3, and NLRP3 inflammasome levels.
Results
The results indicated that KXS protected APP/PS1 mice against cognitive impairments. KXS suppressed neuronal apoptosis and oxidative stress among APP/PS1 mice. KXS and KXS-containing serum improved mitochondrial dysfunction and synaptic and neurotrophic factors regarding APP/PS1 mice. In addition, KXS and KXS-containing serum enhanced mitochondrial SIRT3 expression and reduced NLRP3 inflammasome expression in APP/PS1 mice.
Conclusion
KXS improves cognitive dysfunction among APP/PS1 mice via regulating SIRT3-mediated neuronal cell apoptosis. These results suggested that KXS was proposed as a neuroprotective agent for AD progression.
Siamese Neural Networks for Regression: Similarity-Based Pairing and Uncertainty Quantification
Authors: Zhang Yumeng , Menke Janosch , He Jiazhen , Nittinger Eva , Tyrchan Christian , Koch Oliver , Zhao Hongtao 
Published: December 2022

Abstract
Here we present a similarity-based pairing method for generating compound pairs to train Siamese neural networks. In comparison with the conventional exhaustive pairing, it reduces the algorithm complexity from O(n2) to O(n). It also results in a better prediction performance consistently on the three physicochemical datasets, using a multilayer perceptron with the circular fingerprint as a proof of concept. We further include into a Siamese neural network the transformer-based Chemformer which extracts task-specific features from the simplified molecular-input line-entry system representation of compounds. Additionally, we propose a means to measure the prediction uncertainty by utilizing the n-shot ensemble learning. Our results demonstrate that the high prediction accuracy correlates with the high confidence. Finally, we investigate implications of the similarity property principle in machine learning.
Vogesella urethralis-induced aspiration pneumonia and bacteremia in an elderly man: a first case report
Authors: Matsuda Hironari , Katayama Isana , Watanabe Takayasu , Komatsu Arisa , Iwakami Naoko , Goto Yukiko , Suzuki Misako , Iwakami Shin-ichiro , Takahashi Kazuhisa 
Published: December 2022

Abstract
Background: Vogesella species are common aquatic Gram-negative rods first reported in 1997. Vogesella urethralis bacterium was first isolated from human urine in 2020. Only one case of Vogesella species-caused disease has been reported; however, no case of Vogesella urethralis-caused disease has been reported. Here, we report a case of aspiration pneumonia and bacteremia caused by Vogesella urethralis.
Case presentation: An 82-year-old male patient was admitted with dyspnea, increased sputum production, and hypoxia. Gram-negative rods were isolated from blood and sputum cultures from the patient. He was diagnosed with aspiration pneumonia and bacteremia. Initially, Vogesella urethralis was wrongly identified as Comamonas testosteroni using fully automated susceptibility testing; however, additional 16S rRNA gene sequencing identified it as Vogesella urethralis. The patient was treated with piperacillin and tazobactam. Unfortunately, he developed aspiration pneumonia again and passed away during hospitalization.
Conclusion: Since no database exists for rare bacteria in traditional clinical microbiology laboratories, 16S rRNA gene sequence analysis was considered useful. We report the first case of Vogesella urethralis-induced aspiration pneumonia and bacteremia.
GVC: Efficient Random Access Compression for Gene Sequence Variations
Authors: Adhisantoso Yeremia Gunawan , Voges Jan , Rohlfing Christian , Tunev Viktor , Ohm Jens-Rainer , Ostermann Jörn 
Published: December 2022

Abstract
Background: In recent years, the advances in high-throughput sequencing technologies enabled the use of genomic information in many fields, such as precision medicine, oncology, and food quality control. The amount of genomic data being generated is growing rapidly and expected to soon surpass the amount of video data. The majority of sequencing experiments, such as genome-wide association studies, have the goal to identify gene sequence variations to better understand phenotypic variations.
We present a novel approach for the compression of gene sequence variations with random access capability: the Genomic Variant Codec (GVC). We use techniques such as binarization, joint row-and column-wise sorting of blocks of variations, as well as the image compression standard JBIG for efficient entropy coding.
Results: Our results show that GVC provides the best trade-off in an evaluation of compression and random access compared to the state-of-the-art: it reduces the genotype information size from 758 GiB down to 890 MiB on the publicly available 1000 Genomes Project (phase 3) data, which is 21% less than the state of the art in random-access capable methods.
Conclusions: By providing the best results in terms of combined random access and compression, GVC facilitates the efficient storage of large collections of gene sequence variations. In particular, the random access capability of GVC enables seamless remote data access and application integration. The software is open source and available at https://github.com/sXperfect/gvc/.
Robotic Versus Laparoscopic Partial Nephrectomy: A Prospective, Randomised Trial Comparing Two Surgical Techniques
Authors: Oberhammer Lukas , Lusuardi Lukas , Kunit Thomas , Griessner Hubert , Colleselli Daniela , Pallauf Maximilian , Eiben Christian , Oswald David , Mitterberger Michael Josef 
Published: December 2022

Abstract
Purpose:
To compare oncological, peri-, and postoperative outcomes of robot-assisted with those of laparoscopic partial nephrectomy.
Patients and Methods:
Thirty patients with low- or moderate-complexity renal tumors (R.E.N.A.L. nephrometry scoring) were randomized in a single-blind manner and operated on by the robot-assisted (n = 13) or laparoscopic (n = 17) approach. The primary outcome was oncological safety, based on the residual tumor (R) classification. Secondary outcome parameters were perioperative and postoperative results. The open-source R statistical software was used for statistical analysis.
Results:
Oncological outcomes did not differ significantly between the two surgical methods (p = 0.58). Operating time (p = 0.105), ischemia time (p = 0.884), overall length of hospital stay (p = 0.664), postoperative pain, and preoperative and in-hospital renal function scores were similar. Creatinine levels differed significantly six months postoperatively (robotic: 0.9 mg/dl versus laparoscopic: 1.1 mg/dl; p= 0.014). Intraoperative blood loss was significantly greater in the laparoscopic group (400 ml versus 168 ml; p = 0.028), which was also reflected in postoperative hemoglobin levels (13.8 mg/dl versus 12.5 mg/dl; p = 0.012). Peri- or postoperative complications did not differ significantly (p = 0.355). Subgroup analysis revealed significantly more frequent complications in patients with moderate-complexity tumors treated by laparoscopic surgery (p = 0.021).
Conclusions:
The oncological outcome in regard to the R status was similar in both groups. Intraoperative blood loss, postoperative renal function, and complications all benefited from robot-assisted surgery.
Trial registration:
The study was registered on ClinicalTrials.gov (NCT03900364; 03/04/2019).
S-ketamine promotes postoperative recovery of gastrointestinal function and reduces postoperative pain in gynecological abdominal surgery patients: a randomized controlled trial
Authors: Zhang Tianzhuo , Yue Zhijie , Yu Ling , Li Shuo , Xie Yining , Wei Jin , Wu Mengge , Liu Honglei , Tan Hongyu 
Published: December 2022

Abstract
Background: This prospective randomized controlled study was designed to evaluate the effect of S-ketamine with sufentanil given intraoperatively and postoperatively on recovery of gastrointestinal (GI) function and postoperative pain in gynecological patients undergoing open abdomen surgery.
Methods: One hundred gynecological patients undergoing open abdomen surgery were randomized into an S-ketamine group (group S) or placebo group (0.9% saline; group C). Anesthesia was maintained with S-ketamine, sevoflurane, and remifentanil-propofol target-controlled infusion in group S and with sevoflurane and remifentanil-propofol target-controlled infusion in group C. All patients were connected to patient-controlled intravenous analgesia (PCIA) pump at the end of the surgery with sufentanil, ketorolac tromethamine, and tropisetron in group C and additional S-ketamine in group S. The primary outcome was the time of first postoperative flatus, and the secondary outcome was postoperative pain score of patients. Postoperative sufentanil consumption within the first postoperative 24 h and adverse events such as nausea and vomiting were recorded.
Results: The time of first postoperative flatus in group S was significantly shorter (mean ± SD, 50.3±13.5 h) than that in group C (mean ± SD, 56.5±14.3 h, p=0.042). The patient’s visual analog scale (VAS) pain score 24 h after surgery at rest was significantly lower in group S than in group C (p=0.032). There were no differences in sufentanil consumption within the first postoperative 24 h, postoperative complications related to PCIA between the two groups.
Conclusions: S-ketamine accelerated postoperative GI recovery and reduced 24 h postoperative pain in patients undergoing open gynecological surgery.
Trial registration
ChiCTR2200055180. Registered on 02/01/2022.
Application of GIS-based hydrological modelling to assess ecohydrology of blanket bogs
Authors: Mackin Francis , Flynn Raymond , Fernandez-Valverde Fernando 
Published: December 2022

Abstract

A GIS-based hydrological model, developed to assess restoration potential of Irish raised bogs, was applied to four blanket bogs located across the island of Ireland. The model utilised high-resolution topographic data to predict surface/near-surface hydrological processes, based on climatic conditions, contributing catchment and local surface slope; these provided a prediction of relative surface wetness across each blanket bog catchment. Modifications to the raised bog modelling approach aimed to account for differences in hydrological processes. Application of a climatic correction factor, accounted for climatic variations between the four study sites, while monitoring of water table levels indicated a log-linear relationship between model outputs and summer water tables (median and D90 levels (i.e., water levels equalled or exceeded for 90% of the time)). Higher model outputs were associated with areas where the water table remains closer to the ground surface and a lower range of fluctuations during summer months. Deviations from model outputs were associated with hydrological pressures, such as artificial drainage or the occurrence of peat pipes, which lowered summer water tables. Model outputs also showed significant correlation with peat thickness. Despite being effective as a predictor of hydrological conditions, correlation with ecological variables such as Sphagnum spp. cover proved poor. This reflected the variation in vegetation within and between sites, pointing to the impact of past activities and damage caused by anthropogenic pressures. Findings demonstrate the model as an effective tool in simulating hydrological conditions within blanket bog-covered landscapes, thus proving useful to peatland practitioners in planning and prioritising restoration.