bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seasonality and Spatial Dependence of Mesoscale and Submesoscale Ocean Currents from Along-Track Satellite Altimetry
Authors: Lawrence Albion , Callies Jörn 
Published: May 2022

Abstract
Along-track wavenumber spectral densities of sea surface height (SSH) are estimated from Jason-2 altimetry data as a function of spatial location and calendar month to understand the seasonality of meso- and submesoscale balanced dynamics across the global ocean. Regions with significant mode-1 and mode-2 baroclinic tides are rejected, restricting the analysis to the extratropics. Where balanced motion dominates, the SSH spectral density is averaged over all pass segments in a region for each calendar month and is fit to a four-parameter model consisting of a flat plateau at low wavenumbers, a transition at wavenumber k0 to a red power law spectrum k−s, and a white spectrum at high wavenumbers that models the altimeter noise. The monthly time series of the model parameters are compared to the evolution of the mixed layer. The annual mode of the spectral slope s reaches a minimum after the mixed layer deepens, and the annual mode of the bandpassed kinetic energy in the ranges [2k0, 4k0] and [k0, 2k0] peak ∼2 and ∼4 months, respectively, after the maximum of the annual mode of the mixed layer depth. This analysis is consistent with an energization of the submesoscale by a winter mixed layer instability followed by an inverse cascade of kinetic energy to the mesoscale, in agreement with prior modeling studies and in situ measurements. These results are compared to prior modeling, in situ, and satellite investigations of specific regions and are broadly consistent with them within measurement uncertainties.

Significance Statement
This paper uses satellite observations to understand the source of ocean dynamics at the 1–100-km scales at which vertical motion becomes important and which are thus relevant for biology and for the exchange of heat and carbon with the atmosphere. The observations are consistent with a seasonal variation of dynamics at these scales, predicted by a specific theory of upper-ocean turbulence and confirmed by modeling studies and regional observations. We update prior satellite-based studies by excluding regions with competing effects, by our treatment of the noise, and by our characterization of the seasonality. This work provides a template for analyzing data from the upcoming Surface Water and Ocean Topography (SWOT) satellite.
In Situ Calibration of Underwater Glider Flight Model Using Acoustic Doppler Current Profilers
Authors: Tanaka T. , Hasegawa D. , Okunishi T. , Yasuda I. , Welch T. P. 
Published: May 2022

Abstract
The angle of attack (AOA) is the difference between the underwater glider’s path and pitch angle and is necessary to accurately estimate dead-reckoned position and depth-averaged velocity. The AOA is also important for any sensor measurements that are affected by the glider’s velocity through water, such as ocean turbulence measurement. A glider flight model is generally used to accurately estimate AOA and glider’s actual velocity based on the knowledge of lift and drag coefficients optimized for each glider. This paper examines the AOA of a Slocum glider using an acoustic Doppler current profiler (ADCP) to demonstrate a regression method to estimate these coefficients. Since the current shear was sufficiently small on average, it was reasonable to assume that the ADCP velocity at the nearest bin could capture the glider’s motion during flight and was used to calculate AOA. The lift and drag coefficients were optimized so the flight model estimated the observed pitch–AOA relationship derived from the ADCP and the glider’s pitch observations. The resultant coefficients also satisfied the vertical and horizontal constraints of glider motion and gave unbiased estimates of turbulence intensity derived from the flight model and ADCP. Our method was also applied to a SeaExplorer glider to derive the lift and drag coefficients for the first time. The observed pitch–AOA relationship was reasonably captured by the flight model with the resultant coefficients, suggesting that our method to estimate the lift and drag coefficient of underwater gliders can be applied to any type of underwater glider equipped with an ADCP.
Paper 24: The Natural Course of Recovery for Health-Related Quality of Life Following Hip Arthroscopy for Femoroacetabular Impingement Syndrome
Authors: Malloy Phil , Alter Thomas , Chahla Jorge , Nho Shane , Clapp Ian , Bodendorfer Blake 
Published: May 2022

Objectives: To determine if subgroups of patients exist based on the recovery trajectory of health-related quality of life following hip arthroscopy for femoroacetabular impingement syndrome (FAIS), and to determine clinical data predictors for these subgroups of patients. Methods: A clinical hip data repository was queried for patients who underwent primary hip arthroscopy for the treatment of FAIS between January 2012 and May 2018. Patients who completed pre-operative, 1-year, and 2-year International Hip Outcome Tool-12 (iHOT-12) were included in the study. Latent class growth analysis (LCGA) and growth mixture models (GMM) were used to identify subgroups of patients based on trajectories of recovery for iHOT-12 utilizing 3 clinical time points (pre-operative [within 1 week of surgery], one-year postoperative, and two-year postoperative). LCGA and GMM models using 1 – 6 classes were assessed for best model fit according to AIC, BIC, bootstrapped likelihood ratio test, and log-likelihood ratios. Following the final model selection, a multivariable multinomial logistic regression on the final model was performed with the largest class as the reference group to determine clinical predictors of subgroup membership. Results: A total of 443 patients with an average age of 34.25 ± 12.65 and BMI of 25.02 ± 5.11met inclusion criteria. The 3-class GMM was the best fit model, and the resulting subgroups were named based on trajectories of iHOT-12 scores: early progressors, late regressors, and late progressors (Figure 1A). The early progressors comprised 70.0% of the study group and had substantial early improvement between preoperative and 1-year follow-up with further improved 2-year outcomes (Figure 1B). The late regressors comprised 22.3% of the study sample and demonstrated improvement between preoperative and 1-year follow-up with decreasing function between 1-year and 2-years postoperatively (Figure 1C). The late progressors represented the smallest group at 7.7% and only demonstrated improved outcomes after 1-year postoperatively (Figure 1D). Predictors of the late regressor membership were worker’s compensation status, psychiatric history, preoperative chronic pain, and lower preoperative iHOT-12 scores. Patients in the late progressor subgroup were less likely to participate in physical hobbies/exercise. Conclusions: Using growth mixture models, three natural courses of health-related quality of life recovery following hip arthroscopy for the treatment of FAIS were identified: early progressors, late regressors, and late progressors. Worker’s compensation status, psychiatric history, preoperative chronic pain, and lower preoperative iHOT-12 scores were predictive of less than favorable trajectories of recovery. [Figure: see text]
Gallbladder microbiota composition is associated with pancreaticobiliary and gallbladder cancer prognosis
Authors: Kirishima Mari , Yokoyama Seiya , Matsuo Kei , Hamada Taiji , Shimokawa Michiko , Akahane Toshiaki , Sugimoto Tomoyuki , Tsurumaru Hirohito , Ishibashi Matsujiro , Mataki Yuko , Ootsuka Takao , Nomoto Mitsuharu , Hayashi Chihiro , Horiguchi Akihiko , Higashi Michiyo , Tanimoto Akihide 
Published: May 2022

Abstract
Background
The microbial population of the intestinal tract and its relationship to specific diseases has been extensively studied during the past decade. However, reports characterizing the bile microbiota are rare. This study aims to investigate the microbiota composition in patients with pancreaticobiliary cancers and benign diseases by 16S rRNA gene amplicon sequencing and to evaluate its potential value as a biomarker for the cancer of the bile duct, pancreas, and gallbladder.

Results
We enrolled patients who were diagnosed with cancer, cystic lesions, and inflammation of the pancreaticobiliary tract. The study cohort comprised 244 patients. We extracted microbiome-derived DNA from the bile juice in surgically resected gallbladders. The microbiome composition was not significantly different according to lesion position and cancer type in terms of alpha and beta diversity. We found a significant difference in the relative abundance of Campylobacter, Citrobacter, Leptotrichia, Enterobacter, Hungatella, Mycolicibacterium, Phyllobacterium and Sphingomonas between patients without and with lymph node metastasis.

Conclusions
There was a significant association between the relative abundance of certain microbes and overall survival prognosis. These microbes showed association with good prognosis in cholangiocarcinoma, but with poor prognosis in pancreatic adenocarcinoma, and vice versa. Our findings suggest that pancreaticobiliary tract cancer patients have an altered microbiome composition, which might be a biomarker for distinguishing malignancy.
Determinants of implementing pet robots in nursing homes for dementia care
Authors: Koh Wei Qi , Toomey Elaine , Flynn Aisling , Casey Dympna 
Published: May 2022

AbstractBackgroundPet robots have been employed as viable substitutes to pet therapy in nursing homes. Despite their potential to enhance the psychosocial health of residents with dementia, there is a lack of studies that have investigated determinants of implementing pet robots in real-world practice. This study aims to explore the determinants of implementing pet robots for dementia care in nursing homes, from the perspectives of healthcare professionals and organisational leaders.MethodsA descriptive qualitative study, conceptualised and guided using the Consolidated Framework of Implementation Research (CFIR), was conducted. We conducted semi-structured interviews with healthcare professionals and organisational leaders from nursing homes. Data was transcribed and analysed using Framework Analysis, based on the CFIR as an a priori framework.ResultsA total of 22 participants from eight nursing homes were included. Determinants were mapped to constructs from all five CFIR domains. Determinants relating to the characteristics of pet robots include their design, realisticness and interactivity, affordability, cleanability, perceived evidence strength and comparative advantages to live pets. Determinants relating to external influences (outer setting) include national regulatory guidelines, funding and networks with other organisations. With regards to characteristics of nursing homes (inner setting), determinants include the relevance of pet robots in relation to the needs of residents with dementia, alignment with care processes, infection control mandates and their relative priority. In the domain ‘characteristics of individuals’, determinants were associated with individuals’ beliefs on the role of technology, desires to enhance residents’ quality of life, and differential attitudes on the use of robots. Finally, in the domain ‘implementation process’, assessments and care planning were identified as determinants.ConclusionsOverall, while sentiments around determinants within CFIR domains of pet robots’ characteristics, outer setting and implementation process were similar, participants’ opinions on the determinants within the ‘inner setting’ and ‘characteristics of individuals’ were more varied. This could be due to different organisational structures, disciplinary differences and personal experiences of using pet robots. Many determinants in different domains were interrelated. Findings provide a springboard for identifying and designing implementation strategies to guide the translation of pet robots from research into real-world practice.
Long-term effect of chronic hepatitis B on mortality in HIV-infected persons in a differential HBV transmission setting
Authors: Umutesi Justine , Nsanzimana Sabin , Yingkai Liu Carol , Vanella Patrizio , Ott Jördis J. , Krause Gérard 
Published: May 2022

Abstract
Background
There remain gaps in quantifying mortality risk among individuals co-infected with chronic hepatitis B (HBV) and human immunodeficiency virus (HIV) in sub-Saharan African contexts. Among a cohort of HIV-positive individuals in Rwanda, we estimate the difference in time-to mortality between HBV-positive (HIV/HBV co-infected) and HBV-negative (HIV mono-infected) individuals.

Methods
Using a dataset of HIV-infected adults screened for hepatitis B surface antigen (HBsAg) from January to June 2016 in Rwanda, we performed time-to-event analysis from the date of HBsAg results until death or end of study (31 December 2019). We used the Kaplan–Meier method to estimate probability of survival over time and Cox proportional hazard models to adjust for other factors associated with mortality.

Results
Of 21,105 available entries, 18,459 (87.5%) met the inclusion criteria. Mean age was 42.3 years (SD = 11.4) and 394 (2.1%) died during follow-up (mortality rate = 45.7 per 100,000 person-months, 95% confidence interval (CI) 41.4–50.4) Mortality rate ratio for co-infection was 1.7, 95% CI 1.1–2.6, however, Cox regression analysis did not show any association with mortality between compared groups. The adjusted analysis of covariates stratified by co-infection status showed that males, residing outside of the capital Kigali, drinking alcohol, WHO-HIV-clinical stage 3 and 4 were associated with increased mortality in this HIV cohort.

Conclusions
HBV infection does not significantly influence mortality among HIV-infected individuals in Rwanda. The current cohort is likely to have survived a period of high-risk exposure to HBV and HIV mortality and limited health care until their diagnosis.
Deep transfer learning to quantify pleural effusion severity in chest X-rays
Authors: Huang Tao , Yang Rui , Shen Longbin , Feng Aozi , Li Li , He Ningxia , Li Shuna , Huang Liying , Lyu Jun 
Published: May 2022

Abstract
Purpose
The detection of pleural effusion in chest radiography is crucial for doctors to make timely treatment decisions for patients with chronic obstructive pulmonary disease. We used the MIMIC-CXR database to develop a deep learning model to quantify pleural effusion severity in chest radiographs.

Methods
The Medical Information Mart for Intensive Care Chest X-ray (MIMIC-CXR) dataset was divided into patients ‘with’ or ‘without’ chronic obstructive pulmonary disease (COPD). The label of pleural effusion severity was obtained from the extracted COPD radiology reports and classified into four categories: no effusion, small effusion, moderate effusion, and large effusion. A total of 200 datasets were randomly sampled to manually check each item and determine whether the tags are correct. A professional doctor re-tagged these items as a verification cohort without knowing their previous tags. The learning models include eight common network structures including Resnet, DenseNet, and GoogleNET. Three data processing methods (no sampling, downsampling, and upsampling) and two loss algorithms (focal loss and cross-entropy loss) were used for unbalanced data. The Neural Network Intelligence tool was applied to train the model. Receiver operating characteristic curves, Area under the curve, and confusion matrix were employed to evaluate the model results. Grad-CAM was used for model interpretation.

Results
Among the 8533 patients, 15,620 chest X-rays with clearly marked pleural effusion severity were obtained (no effusion, 5685; small effusion, 4877; moderate effusion, 3657; and large effusion, 1401). The error rate of the manual check label was 6.5%, and the error rate of the doctor’s relabeling was 11.0%. The highest accuracy rate of the optimized model was 73.07. The micro-average AUCs of the testing and validation cohorts was 0.89 and 0.90, respectively, and their macro-average AUCs were 0.86 and 0.89, respectively. The AUC of the distinguishing results of each class and the other three classes were 0.95 and 0.94, 0.76 and 0.83, 0.85 and 0.83, and 0.87 and 0.93.

Conclusion
The deep transfer learning model can grade the severity of pleural effusion.
Enhancement of the International prognostic index with β2-microglobulin, platelet count and red blood cell distribution width: a new prognostic model for diffuse large B-cell lymphoma in the rituximab era
Authors: Chen Haizhu , Zhong Qiaofeng , Zhou Yu , Qin Yan , Yang Jianliang , Liu Peng , He Xiaohui , Zhou Shengyu , Zhang Changgong , Gui Lin , Yang Sheng , Zhou Liqiang , Shi Yuankai 
Published: May 2022

AbstractBackgroundThis study aimed to propose a new user-friendly, cost effective and robust risk model to facilitate risk stratification for diffuse large B-cell lymphoma (DLBCL) treated with frontline R-CHOP regimens.MethodsData on 998 patients with de novo DLBCL diagnosed between Jan 1st, 2005 and Dec 31st, 2018 at our center, who received frontline R-CHOP or R-CHOP-like regimens, were retrospectively collected. Patients were randomly divided into the training cohort (n = 701) and the validation cohort (n = 297). A new prognostic model for overall survival (OS) was built based on the training cohort. The performance of the new model was compared with International prognostic index (IPI), revised IPI (R-IPI) and National Comprehensive Cancer Network (NCCN)-IPI (NCCN-IPI). The new model was validated in the validation cohort.ResultsThe multivariate analysis of the training cohort showed that the IPI, β2-microglobulin, platelet count and red blood cell distribution width were independent factors for OS, which were incorporated into the new prognostic model. Patients were stratified into low risk, low-intermediate risk, high-intermediate risk, high risk and very high risk groups, with distinct survival outcomes. The new model achieved good C-indexes for 5-year OS prediction of 0.750 (95%CI 0.719–0.781) and 0.733 (95%CI 0.682–0.784) in the training and validation cohorts, respectively, and displayed well-fitted calibration curves. The C-index and the time-dependent ROC analysis demonstrated better performance of the new model than the IPI, R-IPI and NCCN-IPI in both training and validation cohorts. The integrated Brier score for predicting 5-year OS of the new model was lower than that of the IPI, R-IPI and NCCN-IPI in both cohorts, and decision curve analysis also showed a higher net benefit, indicating the superiority of the new model over the conventional models.ConclusionThe new prognostic model might be a useful predictive tool for DLBCL treated with R-CHOP regimens. Further external validation is warranted.
Prevalence and risk factors of functional gastrointestinal disorders in Vietnamese infants and young children
Authors: Chia Loo Wee , Nguyen Thi Viet Ha , Phan Van Nha , Luu Thi Thao Nguyen , Nguyen Gia Khanh , Tan Serene Yaling , Rajindrajith Shaman , Benninga Marc Alexander 
Published: May 2022

Abstract
Background
Functional gastrointestinal disorders (FGIDs) are common early in life. The prevalence of FGIDs varies among countries but is unknown in Vietnam. The aim of this study is to assess the prevalence of FGIDs in healthy Vietnamese infants and young children.

Methods
This was a cross-sectional, observational study involving healthy infants and young children between 0 – 48 months old in Hanoi, Vietnam. A representative total of 1511 subjects completed the validated questionnaire on paediatric FGIDs. Rome IV criteria were used to define FGIDs.

Results
For Vietnamese infants (0–6 months) and young children (7–48 months), the prevalence of having at least one FGID was 10.0% and only 0.6% was having more than one FGID. Infantile regurgitation (9.3%) was the most prevalent FGID among infants 0—6 months of age while all other FGIDs had a low prevalence between 0—2.5%. For young children between 7 – 48 months old, functional constipation was the most common disorder at the rate of 5.6%. Association analysis revealed that the risk of infant regurgitation was significantly lower among infants with exclusively breastfeeding at 2 – 3 months and 3 – 4 months, formula initiation at 0 – 1 months, and higher paternal education level. The prevalence of functional constipation was significantly higher in male subjects, children in families with annual household income between 273,000,000 – 546,999,999 VND (or estimate around 11,800 – 23,800 USD), families with one child only, and formula feeding initiation at 1 – 2 months.

Conclusions
The prevalence of FGIDs in Vietnamese infants and young children is relatively low compared to the published literature using Rome IV diagnostic criteria. Infantile regurgitation was the most common FGID in Vietnamese infants while functional constipation was most prevalent among Vietnamese young children.

Trial registration
Netherlands Trial Registry Identifier: NL7286/NTR7495.
The effect of talus osteochondral defects of different area size on ankle joint stability: a finite element analysis
Authors: Li Jia , Wang Yezhou , Wei Yu , Kong Dan , Lin Yuan , Wang Duanyang , Cheng Shi , Yin Pengbin , Wei Min 
Published: May 2022

Abstract
Background
Osteochondral lesion of the talus (OLT) is one of the most common ankle injuries, which will lead to biomechanical changes in the ankle joint and ultimately affect ankle function. Finite element analysis (FEA) is used to clarify the effect of talus osteochondral defects on the stability of the ankle joint at different depths. However, no research has been conducted on talus osteochondral defect areas that require prompt intervention. In this research, FEA was used to simulate the effect of the area size of talus osteochondral defect on the stress and stability of the ankle joint under a specific depth defect.

Methods
Different area sizes (normal, 2 mm* 2 mm, 4 mm* 4 mm, 6 mm* 6 mm, 8 mm* 8 mm, 10 mm* 10 mm, and 12 mm* 12 mm) of the three-dimensional finite element model of osteochondral defects were established. The model was used to simulate and calculate joint stress and displacement of the articular surface of the distal tibia and the proximal talus when the ankle joint was in the heel-strike, midstance, and push-off phases.

Results
When OLT occurred, the contact pressure of the articular surface, the equivalent stress of the proximal talus, the tibial cartilage, and the talus cartilage did not change significantly with an increase in the size of the osteochondral defect area when the heel-strike phase was below 6 mm * 6 mm. Gradual increases started at 6 mm * 6 mm in the midstance and push-off phases. Maximum changes were reached when the defect area size was 12 mm * 12 mm. The same patterns were observed in the talus displacement.

Conclusions
The effect of the defect area of the ankle talus cartilage on the ankle biomechanics is evident in the midstance and push-off phases. When the size of the defect reaches 6 mm * 6 mm, the most apparent change in the stability of the ankle joint occurs, and the effect does not increase linearly with the increase in the size of the defect.