bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using artificial intelligence algorithms to predict the overall survival of hemodialysis patients during the COVID-19 pandemic: A prospective cohort study
Authors: Tang Shao-Yu , Chen Tz-Heng , Kuo Ko-Lin , Huang Jue-Ni , Kuo Chen-Tsung , Chu Yuan-Chia 
Published: September 2023

Background:
Hemodialysis (HD) patients are a vulnerable population at high risk for severe complications from COVID-19. The impact of partial COVID-19 vaccination on the survival of HD patients remains uncertain. This prospective cohort study was designed to use artificial intelligence algorithms to predict the survival impact of partial COVID-19 vaccination in HD patients.

Methods:
A cohort of 433 HD patients was used to develop machine-learning models based on a subset of clinical features assessed between July 1, 2021, and April 29, 2022. The patient cohort was randomly split into training (80%) and testing (20%) sets for model development and evaluation. Machine-learning models, including categorical boosting (CatBoost), light gradient boosting machines (LightGBM), RandomForest, and extreme gradient boosting models (XGBoost), were applied to evaluate their discriminative performance using the patient cohorts.

Results:
Among these models, LightGBM achieved the highest F1 score of 0.95, followed by CatBoost, RandomForest, and XGBoost, with area under the receiver operating characteristic curve values of 0.94 on the testing dataset. The SHapley Additive explanation summary plot derived from the XGBoost model indicated that key features such as age, albumin, and vaccination details had a significant impact on survival. Furthermore, the fully vaccinated group exhibited higher levels of anti-spike (S) receptor-binding domain antibodies.

Conclusion:
This prospective cohort study involved using artificial intelligence algorithms to predict overall survival in HD patients during the COVID-19 pandemic. These predictive models assisted in identifying high-risk individuals and guiding vaccination strategies for HD patients, ultimately improving overall prognosis. Further research is warranted to validate and refine these predictive models in larger and more diverse populations of HD patients.
Prediction of in-hospital Mortality of Intensive Care Unit Patients with Acute Pancreatitis Based on an Explainable Machine Learning Algorithm
Authors: Ren Wensen , Zou Kang , Huang Shu , Xu Huan , Zhang Wei , Shi Xiaomin , Shi Lei , Zhong Xiaolin , Peng Yan , Tang Xiaowei , Lü Muhan 
Published: September 2023

Background and Aim:
Acute pancreatitis (AP) is potentially fatal. Therefore, early identification of patients at a high mortality risk and timely intervention are essential. This study aimed to establish an explainable machine-learning model for predicting in-hospital mortality of intensive care unit (ICU) patients with AP.

Methods:
Data on patients with AP, including demographics, vital signs, laboratory tests, comorbidities, treatment, complication, and severity scores, were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the eICU collaborative research database (eICU-CRD). Based on the data from MIMIC-IV, we used the least absolute shrinkage and selection operator algorithm to select variables and then established 9 machine-learning models and screened the optimal model. Data from the eICU-CRD were used for external validation. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, decision curve, and calibration plots were used to assess the models’ efficacy. Shapley’s additive explanation values were used to explain the model.

Results:
Gaussian naive Bayes (GNB) model had the best performance on the data from MIMIC-IV, with an AUC, accuracy, sensitivity, and specificity of 0.840, 0.787, 0.839, and 0.792, respectively. The GNB model also performed well on the data from the eICU-CRD, with an AUC, accuracy, sensitivity, and specificity of 0.862, 0.833, 0.848, and 0.763, respectively. According to Shapley’s additive explanation values, the top 4 predictive factors were maximum red cell distribution width, minimum saturation of blood oxygen, maximum blood urea nitrogen, and the Sequential Organ Failure Assessment score.

Conclusion:
The GNB model demonstrated excellent performance and generalizability in predicting mortality in ICU patients with AP. Therefore, it can identify patients at a high mortality risk.
Changes in pain catastrophizing, fear-avoidance beliefs, and pain self-efficacy mediate changes in pain intensity on disability in the treatment of chronic low back pain
Authors: Ryum Truls , Stiles Tore C. 
Published: September 2023

Abstract

Introduction:
Treatment of chronic low back pain (CLBP) based on the fear-avoidance model (FAM) has received support in randomized controlled trials, but few studies have examined treatment processes associated with treatment outcome. This study examined changes in pain catastrophizing, fear-avoidance beliefs, and pain self-efficacy as mediators of the relation between changes in pain intensity and disability in exposure-based treatment of CLBP.

Methods:
Data from a randomized controlled trial with 2 treatment arms (exposure treatment based on the FAM with/without in-session exposure) was pooled, including only participants with complete data (N = 69). Change scores (pre to booster session) were computed for all variables, and the indirect effect of change in pain intensity on change in 3 measures of disability, through change in the proposed mediators, was tested in parallel mediation analyses.

Results:
Decreases in pain catastrophizing and fear-avoidance beliefs, as well as increases in pain self-efficacy, mediated a unique proportion of the relation between changes in pain intensity and disability, depending on the outcome measure. The direct relation between changes in pain intensity and disability was absent when indirect effects were controlled.

Conclusions:
The results suggest that the way pain is interpreted (pain catastrophizing, fear-avoidance beliefs), as well as pain self-efficacy, are all more critical for reducing disability in exposure-based treatment of CLBP than symptom relief per se.
Outcomes of Immediate Multistaged Abdominal Wall Reconstruction of Infected Mesh
Authors: Alimi Yewande , Deldar Romina , Sosin Michael , Lofthus Alexander , Nijhar Kieranjeet , Bartholomew Alex J. , Fan Kenneth L. , Bhanot Parag 
Published: September 2023

Background
Mesh infection is one of the most devastating complications after ventral hernia repair. To date, no clear consensus exists on the optimal timing of definitive abdominal wall reconstruction (AWR) after excision of infected mesh. We evaluated outcomes of immediate multistaged AWR in patients with mesh infection.

Methods
We performed a retrospective review of patients with mesh infection who underwent immediate, multistaged AWR, which consisted of exploratory laparotomy with debridement and mesh explantation, followed by definitive AWR during the same admission. Primary outcomes included hernia recurrence and surgical site occurrences, defined as wound dehiscence, surgical site infection, hematoma, and seroma.

Results
Forty-seven patients with infected mesh were identified. At mean follow-up of 9.5 months, 5 patients (10.6%) experienced hernia recurrence. Higher body mass index (P = 0.006), bridge repair (P = 0.035), and postoperative surgical site infection (P = 0.005) were associated with hernia recurrence.

Conclusion
Immediate multistaged AWR is an effective surgical approach in patients with infected mesh.
A Comparative Study of Titanium Cranioplasty for Extensive Calvarial Bone Defects
Authors: Kim Young Chul , Lee Seok Joon , Woo Soo Hyun , Yang Sook , Choi Jong Woo 
Published: September 2023

Objective
This study compared the complications and symmetry outcomes between 3-dimensionally printed titanium implants and premolded titanium mesh in patients with extensive calvarial bone defects.

Methods
This retrospective analysis included patients with calvarial defects >50 cm2 undergoing cranioplasty who received either a 3-dimensionally printed titanium implant manufactured by selective laser melting techniques (N = 12) or a premolded titanium mesh customized onto a 3-dimensionally printed skull template (N = 23). Complications including intracranial infection, hardware extrusion, wound dehiscence, and cerebrospinal fluid leaks were investigated. Predictive factors affecting complications were investigated to identify the odds ratios in univariate and multivariate analyses. The symmetry was assessed by calculating the root mean square deviation, which showed the morphological deviation of the selected area compared with the mirrored image of the contralateral region.

Results
The overall complication rate was 26.1% (6/23 patients) in the premolded titanium group and 16.7% (2/12 patients) in the 3-dimensionally printed group. The reoperation rates did not differ significantly between the 2 groups (3-dimensionally printed group, 16.7%, versus premolded group, 21.7%). In multivariate analysis, only the number of previous cranial operation was significantly associated with the complication rate (odds ratio, 2.42; 95% confidence interval, 1.037–5.649; P = 0.041). The mean ± SD of the root mean square deviation was significantly smaller in the 3-dimensionally printed group (2.58 ± 0.93 versus 4.82 ± 1.31 mm, P < 0.001).

Conclusions
The 3-dimensionally printed titanium implant manufactured by the selective laser melting technique showed comparable stability and improved symmetry outcomes compared with the conventional titanium mesh in the reconstruction of extensive calvarial defects.
Implications of the COVID-19 Pandemic on Immediate Breast Reconstruction Access
Authors: Raman Karanvir S. , Ninomiya Maya Morton , Bovill Esta S. , Doherty Christopher , Macadam Sheina A. , Van Laeken Nancy , Isaac Kathryn V. 
Published: September 2023

Aims
As a result of COVID-19, there have been restrictions on surgical interventions across Canada. Immediate breast reconstruction (IBR), while an essential component of cancer care, is classified as elective surgery and therefore has been restricted in access over the course of the pandemic. The purpose of this study was to compare wait times for breast cancer patients undergoing surgical intervention for IBR before and since the COVID-19 pandemic.

Methods
This was a retrospective cross-sectional study of consecutive patients who underwent IBR between July 2018 and October 2021 by 5 plastic surgeons at a single Canadian health center. Wait times to consultation and surgical intervention between pre- and post-COVID cohorts were analyzed.

Results
A total of 161 patients met inclusion criteria. For ablative surgery, there was no difference in wait times to surgical oncology consultation (14.0 ± 12.3 vs 14.0 ± 11.0 days, P = 0.991) and surgical intervention with IBR (41.0 ± 49.8 vs 35.0 ± 58.0 days, P = 0.621) between the pre- and post-COVID cohorts. For breast reconstruction, while time to consultation with plastic surgery (12.5 ± 14.8 vs 11.0 ± 12.8 days, P = 0.775) remained unchanged, usage of autologous techniques was reduced [n = 13 (16%) vs n = 2 (2%), P = 0.006], and time to second-stage alloplastic reconstruction increased (230 ± 102 vs 325 ± 224 days, P = 0.044) post-COVID.

Conclusions
Swift adoption of evidence driven protocols has resulted in comparable wait times for breast cancer ablative procedures. However, utilization of autologous techniques and wait times to second-stage reconstructions have increased.
Topologically associating domains can arise from stochastic folding of heterogeneous fluidlike chromatin
Authors: Meng Luming , Sheong Fu Kit , Luo Qiong 
Published: September 2023

SUMMARYTopologically associating domains (TADs) are critical for gene regulation. Current views attribute TAD formation to cohesin-mediated extrusion and ignore the role of physical properties ofin vivochromatin. Here, we demonstrate that the two universal properties: chromatin fluidlike behavior and heterogeneity in DNA-packing density along chromatin, can drive TAD formation. We use DNA-accessibility data to parameterize DNA-packing density along chromatin and simulate stochastic folding of the heterogeneous chromatin in nucleus to yield a conformation ensemble. Such an ensemble can be cross-validated by Hi-C and FISH data. Furthermore, the stochastic folding model allowsde novoprediction of the establishment and disappearance of key TADs during early T cell differentiation. Together, our work demonstrates that the intrinsic stochastic folding of fluidlike chromatin leads to the prevalence of TAD-like domains in single cells and their cell-to-cell variation, while the heterogeneity in DNA-packing density along chromatin mediates the emergence of TADs at ensemble-averaged level.In briefA study based on polymer simulation reveals that the two universal physical properties ofin vivochromatin fiber: chromatin fluidlike behavior and heterogeneity in DNA-packing density along chromatin play a vital role in TAD formation.HighlightsIntrinsic stochastic folding of fluidlike chromatin in nuclear space underlies the prevalence of TAD-like domains in single cells and their cell-to-cell variationHeterogeneity in DNA-packing density along chromatin causes the emergence of TADs at ensemble-averaged levelThe disappearance and establishment of key TADs during early T cell differentiation can occur through a stochastic folding process alone, without the need of any cohesin-mediated chromatin extrusionThe stochastic folding model applies to diverse cell types and is thus able tode novopredict the dynamics of genome organization over time
Evolutionary prediction for new echolocators
Authors: Liu Qi , Hua Qin-Yang , Sun Rui , He Shui-Wang , Li Meng-Cheng , Shi Lu-Ye , Chen Peng , Ma Yuan-Shuo , Zhang Qin , Jiang Xue-Long , Wang Yong , Shi Peng 
Published: September 2023

AbstractIt was suggested over 60 years ago that echolocation is widespread in animals. Although echolocation has been found to evolve independently in several mammalian lineages, this hypothesis remains largely untested due to the difficulty of determining the presence of echolocation. To address this issue, we combined molecular convergence analyses from 190 high-quality mammalian genomes with machine learning to predict potential new mammalian echolocators. Our model predicted three promising lineages of echolocating mammals. Behavioral experiments confirmed that the gracile shrew mole (Uropsilus gracilis), the highest- ranking species among predicted echolocators, as well as almost all shrew moles (Uropsilinae), are capable of echolocation through the use of ultrasonic pulses. In contrast to most bats that use laryngeal echolocation, the characteristics of calls, the morphology of the stylohyal bone, and the results of tongue ligation experiments all suggest that shrew moles produce ultrasonic clicks with their tongues for echolocation. Finally, we estimated at least 20% of all living mammalian orders with echolocation ability, thus empirically supporting Griffin’s hypothesis that echolocation is widespread among animals. Our findings not only provide evidence that three novel lineages of echolocating mammals, but also demonstrate that phylogenetically replicated phenotypes can be predicted through genetic convergence.One sentence summaryShrew moles are capable of echolocation.
Visual Artificial Grammar Learning Across One Year in 7-Year-Olds and Adults
Authors: Schönberger Daniela K. , Bruns Patrick , Röder Brigitte 
Published: September 2023

AbstractAcquiring sequential information is of utmost importance, e.g., for language acquisition in children. Yet, the long-term storage of statistical learning in children is poorly understood. To address this question, 27 seven-year-olds and 28 young adults completed four sessions of visual sequence learning (Year 1). From this sample, 16 seven-year-olds and 20 young adults participated in another four equivalent sessions after a 12-month-delay (Year 2). The first three sessions of each year used stimulus set-1, while the last session used stimulus set-2 to investigate transfer effects. Each session consisted of alternating learning and test phases in a modified artificial grammar learning task. In Year 1, seven-year-olds and adults learned the regularities and showed transfer to stimulus set-2. Both groups retained their final performance level over the one-year-period. In Year 2, children and adults continued to improve with stimulus set-1, but did not show additional transfer gains. Adults overall outperformed children, but transfer effects were indistinguishable between both groups. The present results suggest that long-term memory traces are formed from repeated sequence learning which can be used to generalize sequence rules to new visual input. However, the present study did not provide evidence for a childhood advantage in learning and remembering sequence rules.
Clinical outcomes and survival of individuals with methylmalonic acidemia, propionic acidemia, classic homocystinuria, and remethylation disorders identified through newborn screening
Authors: Reischl-Hajiabadi Anna T. , Schnabel Elena , Gleich Florian , Mengler Katharina , Lindner Martin , Burgard Peter , Posset Roland , Lommer-Steinhoff Svenja , Grünert Sarah C. , Thimm Eva , Freisinger Peter , Hennermann Julia B. , Krämer Johannes , Gramer Gwendolyn , Lenz Dominic , Christ Stine , Hörster Friederike , Hoffmann Georg F. , Garbade Sven F. , Kölker Stefan , Mütze Ulrike 
Published: September 2023

SummaryThe current German newborn screening (NBS) panel includes 13 inherited metabolic diseases (IMDs). In addition, the NBS pilot study in Southwest Germany identifies individuals with methylmalonic acidemia (MMA), propionic acidemia (PA), cystathionine β-synthase (CBS) deficiency, remethylation disorders [e.g. cobalamin (cbl) C and methylenetetrahydrofolate reductase (MTHFR) deficiency], and neonatal cbl deficiency through a combined second-tier algorithm. The long-term health benefits of screened individuals are evaluated in a prospective multicenter observational study.Twenty-seven individuals with IMDs [MMA (N=6), PA (N=13), cblC deficiency (N=5), MTHFR deficiency (N=2) and CBS deficiency (N=1)] and 42 with neonatal cbl deficiency were identified by the NBS pilot study and followed for a median of 3.6 years. Seventeen IMD patients (63%) experienced at least one metabolic decompensation, 14 of them neonatally and six even before the NBS report (cbl-nonresponsive MMA, PA). Three PA patients died despite NBS and immediate treatment. Fifteen individuals (79%) with MMA or PA and all with cblC deficiency presented with permanent, mostly neurological symptoms, while individuals with CBS, MTHFR and neonatal cbl deficiency had a favorable outcome.Utilizing a combined second-tier algorithm we demonstrate that NBS and specialized metabolic care result in substantial benefits for individuals with CBS deficiency, MTHFR deficiency, neonatal cbl deficiency, and to some extent, cblC deficiency and cbl-responsive MMA. However, its advantage is less evident for individuals with cbl-nonresponsive MMA and PA.
Stakeholder collaboration in the forecast-informed reservoir operations (FIRO) pilot project at Lake Mendocino, California
Authors: Galaitsi S.E. , Rand Krista , Yeates Elissa , Talbot Cary , O'Donnell Arleen , Pinigina Elizaveta , Linkov Igor 
Published: September 2023

PurposeWater is a critical and contentious resource in California, hence any changes in reservoir management requires coordination among many basin stakeholders. The Forecast-Informed Reservoir Operations (FIRO) pilot project at Lake Mendocino, California explored the viability of using weather forecasts to alter the operations of a United States Army Corps of Engineers (USACE) reservoir. The pilot project demonstrated FIRO's ability to improve water supply reliability, but also revealed the key role of a collaborative Steering Committee. Because Lake Mendocino's Viability Assessment did not explore the features of the Steering Committee, this study aims to examine the relationships and interactions between Steering Committee members that supported FIRO's implementation at Lake Mendocino.Design/methodology/approachThe project identified 17 key project participants who spoke at a FIRO workshop or emerged through chain-referrals. Using semi-structured interviews with these participants, the project examined the dynamics of human interactions that enabled the successful multi-institutional and multi-criteria innovation as analyzed through text-coding.FindingsThe results reveal the importance for FIRO Steering Committee members to understand the limitations and constraints of stakeholder counterparts at other organizations, the importance of building and safeguarding relationships, and the role of trust and belonging between members. The lessons learned suggest several interventions to support successful group collaboration dynamics for future FIRO projects.Originality/valueThis study identifies features of the Steering Committee that contributed to FIRO's success by supporting collaborative negotiations of infrastructure operations within a multi-institutional and multi-criteria context.
Exploring the potential of blockchain adoption for promoting value innovation: a case of the halal industry
Authors: Purusottama Ambara , Sunitiyoso Yos , Simatupang Togar Mangihut 
Published: September 2023

PurposeBlockchain technology has encouraged more transparent transactions process through decentralized protocols and has identified multi-dimensional benefits. However, value innovation–based blockchain for the particular industry requires further elaboration since there appears to be a vague understanding. Therefore, this study aims to provide a profound perspective of value innovation based blockchain, which has the potential to be applied in the halal industry.Design/methodology/approachThis study developed a typology model that describes a profound understanding of blockchain adoption for value innovation. Empirical research was conducted using multiple case studies to justify the model. The case selection in this study was based on the halal industry in Indonesia. This study employed few sources to derive sufficient data through in-depth interviews, direct observations, and archival records. In particular, this study drew upon specific theories to elaborate on the blockchain-enable value innovation.FindingsA blockchain is identified as having the opportunity to promote value innovation in the halal industry through its features. This study defines a typology model of value innovation-based blockchain for the halal industry that takes place on a particular spectrum. The model built in this study classifies blockchain adoption for the halal industry from specific dimensions: the degree of blockchain-based system complexity and the intensity of value innovation. Then, this study finds that these cases have different classifications and are evenly distributed in the quadrants of the model.Originality/valueThe typology model in this study can be a reference for decision-making when considering blockchain to leverage a value innovation in particular systems. Although blockchain technology can potentially be applied in vast areas, the decision-makers should understand that technology adoption should provide distinct values to its stakeholders, notably in multi-dimensional areas such as the halal industry. Thus, this study contributes significantly to blockchain technology usage for the halal industry.