bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel shockwave-driven nanomotor composite microneedle transdermal delivery system for the localized treatment of osteoporosis: a basic science study
Authors: Hu Fan , Liang Haojun , Xie Jing , Yuan Meng , Huang Wanxia , Lei Yinze , Li Hao , Lv Linwen , Liu Qiuyang , Zhang Junhui , Su Wenxi , Chen Ranran , Wang Zhe , Chang Ya-nan , Li Juan , Wei Cunfeng , Xing Gengyan , Xing Gengmei , Chen Kui 
Published: August 2024

Background:
Clinical protocols in osteoporosis treatment could not meet the requirement of increasing local bone mineral density. A local delivery system was brought in to fix this dilemma. The high-energy extracorporeal shock wave (ESW) can travel into the deep tissues with little heat loss. Hence, ESW-driven nanoparticles could be used for local treatment of osteoporosis.

Materials and methods:
An ESW-actuated nanomotor (NM) sealed into microneedles (MNs) (ESW-NM-MN) was constructed for localized osteoporosis protection. The NM was made of calcium phosphate nanoparticles with a high Young’s modulus, which allows it to absorb ESW energy efficiently and convert it into kinetic energy for solid tissue penetration. Zoledronic (ZOL), as an alternative phosphorus source, forms the backbone of the NM (ZOL-NM), leading to bone targeting and ESW-mediated drug release.

Results:
After the ZOL-NM is sealed into hyaluronic acid (HA)-made microneedles, the soluble MN tips could break through the stratum corneum, injecting the ZOL-NM into the skin. As soon as the ESW was applied, the ZOL-NM would absorb the ESW energy to move from the outer layer of skin into the deep tissue and be fragmented to release ZOL and Ca2+ for anti-osteoclastogenesis and pro-osteogenesis. In vivo, the ZOL-NM increases localized bone parameters and reduces fracture risk, indicating its potential value in osteoporotic healing and other biomedical fields.

Conclusion:
The ESW-mediated transdermal delivery platform (ESW-NM-MN) could be used as a new strategy to improve local bone mineral density and protect local prone-fracture areas.
Computed tomography-based fully automated artificial intelligence model to predict extrapancreatic perineural invasion in pancreatic ductal adenocarcinoma
Authors: Yu Jieyu , Chen Chengwei , Lu Mingzhi , Fang Xu , Li Jing , Zhu Mengmeng , Li Na , Yuan Xiaohan , Han Yaxing , Wang Li , Lu Jianping , Shao Chengwei , Bian Yun 
Published: August 2024

Background:
Extrapancreatic perineural invasion (EPNI) increases the risk of postoperative recurrence in pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop and validate a computed tomography (CT)-based, fully automated preoperative artificial intelligence (AI) model to predict EPNI in patients with PDAC.

Methods:
The authors retrospectively enrolled 1065 patients from two Shanghai hospitals between June 2014 and April 2023. Patients were split into training (n=497), internal validation (n=212), internal test (n=180), and external test (n=176) sets. The AI model used perivascular space and tumor contact for EPNI detection. The authors evaluated the AI model’s performance based on its discrimination. Kaplan–Meier curves, log-rank tests, and Cox regression were used for survival analysis.

Results:
The AI model demonstrated superior diagnostic performance for EPNI with 1-pixel expansion. The area under the curve in the training, validation, internal test, and external test sets were 0.87, 0.88, 0.82, and 0.83, respectively. The log-rank test revealed a significantly longer survival in the AI-predicted EPNI-negative group than the AI-predicted EPNI-positive group in the training, validation, and internal test sets (P<0.05). Moreover, the AI model exhibited exceptional prognostic stratification in early PDAC and improved assessment of neoadjuvant therapy’s effectiveness.

Conclusion:
The AI model presents a robust modality for EPNI diagnosis, risk stratification, and neoadjuvant treatment guidance in PDAC, and can be applied to guide personalized precision therapy.
Pediatric Failure Rates and Speech Outcomes in the HiRes Ultra and Ultra 3D Series Recall
Authors: Siddiqui Taimur , Lovin Benjamin D. , Nguyen Michelle T. , Marsh Megan , Spiro Jessica B. , Wickesberg-Summers Jennifer , Cantu Amy , Vilela Ronald J. , Sweeney Alex D. , Lindquist Nathan R. 
Published: August 2024

Objective
The recent Field Corrective Action (FCA) for the HiRes Ultra and Ultra 3D (V1) cochlear implants (CIs) triggered much research investigating clinical identification, failure rates, and postrevision outcomes. Pediatric data remain limited, especially with regards to speech outcomes. We aim to characterize the trajectory of children implanted with these devices with specific attention to speech outcomes.

Patients
Retrospective cohort study of pediatric patients with FCA-affected CIs from March 2017 to January 2020 at a tertiary children’s hospital.

Interventions
CI placement, device monitoring, audiologic evaluation, revision surgery.

Main Outcome Measures
CI failure rates, revision surgery rate, speech recognition outcomes.

Results
Forty-one devices were implanted in 27 pediatric patients. Average age at implantation was 4.01 years (range, 0.87–12.75). To date, 30 devices (73%) are known failures with 90% of these having undergone revision surgery. No statically significant difference was noted on open-set speech testing across best prerevision, immediate prerevision, and best postrevision time points. Best postrevision CNC scores had a mean score of 71% ± 26%, n = 16.

Conclusions
Pediatric patients implanted with FCA-affected CI devices have a high risk of device failure. Open-set speech recognition was not significantly different from prerevision to postrevision testing, suggesting preserved speech outcomes. This may be partially attributable to limitations of cohort size and the pediatric population with open-set speech testing. However, we suspect that close follow-up with standardized testing and a low threshold for revision surgery provided by our multidisciplinary team may have mitigated these changes. Postrevision open-set speech testing remains positive for these patients.
Seeking Precision Healthcare in Rural Patients With Cancer: Learning Self-advocacy
Authors: Curtin Martha S. , Somayaji Darryl , Dickerson Suzanne S. 
Published: August 2024

BackgroundPrecision medicine initiatives are offering superior treatments for cancer, and equitable distribution of these care measures is desired. Gaining insight into the meanings and shared practices of individuals navigating a cancer diagnosis and treatment in a rural setting will help efforts to mitigate inequities in this domain.ObjectivesTo (1) interpret individuals’ common meanings of a cancer diagnosis including what contributes to that meaning; (2) explicate the shared practices of individuals with cancer regarding accessing oncology care, including provider visits, testing, and treatments; and (3) interpret common understanding of testing and treatment options in individuals with cancer.MethodsUsing hermeneutic phenomenology, interviews with individuals who have cancer who may benefit from precision medicine initiatives and who live in a rural area were recorded, transcribed, and analyzed by the research team until common meanings arose from the narratives.ResultsFifteen participants provided in-depth interviews. Three main themes and a constitutive pattern emerged: (1) “Slipping through the cracks,” (2) Traveling this distance: “Gee, is there something closer?” and (3) Evoking some resilience: “Hope is a powerful word.” The constitutive pattern was: “The necessity of practicing and developing advocacy.”ConclusionsAccess to care in the rural setting is a complex concept and includes challenges with receiving care at a distance, travel to larger cities for adequate care, and coordination of care from multiple providers.Implications for PracticeEfforts toward providing advocacy in the healthcare setting, as well as developing ways to make access to specialized cancer care more readily available, are important steps toward mitigation of inequities in rural areas.
Baduanjin Exercise Improves Cognitive Function in Older Adults With Mild Cognitive Impairment
Authors: Li Liang , Li Wenlong , Fan Tonggang 
Published: August 2024

Abstract
As a nonpharmacological method for cognitive rehabilitation, older adults with mild cognitive impairment (MCI) may benefit from Baduanjin exercise (BE), a moderate-intensity aerobic exercise. This meta-analysis was conducted to determine if BE is effective in enhancing cognitive performance in older adults with MCI. Using a combination of topic phrases and free words, systematic searches were executed in nine databases. Review Manager 5.4 was used to retrieve and statistically evaluate the data. Fourteen randomized controlled studies comprising 994 individuals aged ≥60 years were included in the meta-analysis. BE enhanced the general cognitive performance in individuals with MCI as measured by the Montreal Cognitive Assessment (standardized mean difference [SMD] = 2.56; 95% confidence interval [CI], 2.17, 2.96; p < 0.001). The level of memory decline (Wechsler Memory Scale; SMD = 12.46; 95% CI, 8.36, 16.57; p < 0.001), executive function (Trail Making Test; SMD = −7.08; 95% CI, −11.21, −2.94; p < 0.001), and frailty (Edmonton Frailty Scale; SMD = −0.97; 95% CI, −1.30, −0.64; p < 0.001) were all improved with BE for older adults with MCI. This study presented a therapeutic practice guide for using BE for cognitive rehabilitation in older adults. BE notably improves cognitive function in older adults with MCI and can be an excellent nonpharmaceutical therapy option.
A Comparative Analysis of Recruitment Methods to Reach Emerging Adults Outside the Clinical Setting
Authors: Walsh Alli , Pathak Dola , Schlegel Emma C. 
Published: August 2024

Abstract

Background
Emerging adults are a hard-to-recruit population for health researchers, as many do not routinely access health care services and are best recruited outside clinical settings. Social media and research volunteer registries (e.g., ResearchMatch) offer great potential among this population, yet a comparison of these two recruitment methods has not been done.

Objectives
To compare participant enrollment and completion rates, participant demographics, and recruitment costs between recruitment methods (social media advertisements compared to ResearchMatch) deployed with a sample of female-bodied emerging adults.

Methods
Female-bodied emerging adults were recruited from October to November 2022 via ResearchMatch and social media (Instagram and Snapchat) advertisements. This analysis involves a subset of recruitment data from a larger institutional review board-approved study. Enrollment and survey completion rates were calculated using the number of individuals contacted and survey completion data from Qualtrics. Chi-square and independent t-test analyses were used to compare demographic data. Advertisement data collected included total cost, cost per click, link clicks, and paid impressions.

Results
Two hundred and forty-five emerging adults completed the survey, and 24 completed follow-up interviews. ResearchMatch and social media enrollment rates differed (58% and 39%, respectively). Survey completion rates for both methods were the same (~93%). Participants’ ages and levels of education were significantly different. Social media resulted in recruitment of younger participants (18–21 years), and ResearchMatch garnered participants with a higher level of education. Differences in race were also significant, as social media recruited higher numbers of White participants. Lastly, the researcher-incurred cost per survey was $0 for ResearchMatch versus $13 for social media.

Discussion
While social media and ResearchMatch are both successful tools for research recruitment, each provides distinct benefits for recruiting specific populations. ResearchMatch offers a lower-cost option and access to an older emerging adult population with higher education, while social media provides access to a younger emerging adult population. This knowledge can be imperative for deciding which recruitment methods best fit research study needs. Future research should explore differences in race by recruitment method to highlight potential sampling biases or recruitment opportunities.
Gerrymandering and the Packing and Cracking of Medical Uninsurance Rates in the United States
Authors: Rushovich Tamara , Nethery Rachel C. , White Ariel , Krieger Nancy 
Published: August 2024

Context:
Technological innovation and access to big data have allowed partisan gerrymandering to increase dramatically in recent redistricting cycles.

Objective:
To understand whether and how partisan gerrymandering, including “packing” and “cracking” (ie, respectively concentrating within or dividing specified social groups across political boundaries), distorts understanding of public health need when health statistics are calculated for congressional districts (CDs).

Design:
Cross-sectional study using 2020 CDs and nonpartisan simulated districts.

Setting:
United States, 2017-2021.

Participants:
United States residents.

Main Outcome Measure:
Percent with no medical insurance (uninsured), within-district variance of percent uninsured, and between-district variance of percent uninsured.

Results:
At the state level, states where partisan redistricting plans showed greater evidence of partisan gerrymandering were more likely to contain CDs with more extreme values of uninsurance rates than districts in states with less evidence for gerrymandering (association between z-scores for gerrymandering and between-district variation in uninsurance = 0.25 (−0.04, 0.53), P = .10). Comparing variation in uninsurance rates for observed CDs vs nonpartisan simulated districts across all states with more than 1 CD, in analyses stratified by state gerrymander status (no gerrymander, Democratic gerrymander, and Republican gerrymander), we found evidence of particularly extreme distortion of rates in Republican gerrymandered states, whereby Republican-leaning districts tended to have lower uninsurance rates (the percentage of Republican-leaning districts that were significantly lower than nonpartisan simulated districts was 5.1 times that of Democratic-leaning districts) and Democrat-leaning districts had higher uninsurance rates (the percentage of Democrat-leaning districts that were significantly higher than nonpartisan simulated districts was 3.0 times that of Republican-leaning districts).

Conclusions:
Partisan gerrymandering can affect determination of CD-level uninsurance rates and distort understanding of public health burdens.
Care Home Safety Incidents and Safeguarding Reports Relating to Hospital to Care Home Transitions: A Retrospective Content Analysis
Authors: Newman Craig , Mulrine Stephanie , Brittain Katie , Dawson Pamela , Mason Celia , Spencer Michele , Sykes Kate , Young-Murphy Lesley , Waring Justin , Scott Jason 
Published: August 2024

Objective
The purpose of this study was to further the understanding of reported patient safety events at the interface between hospital and care home including what active failings and latent conditions were present and how reporting helped learning.

Methods
Two care home organizations, one in the North East and one in the South West of England, participated in the study. Reports relating to a transition and where a patient safety event had occurred were sought during the COVID-19 (SARS-CoV-2) virus prepandemic and intrapandemic periods. All reports were screened for eligibility and analyzed using content analysis.

Results
Seventeen South West England care homes and 15 North East England care homes sent 114 safety incident reports and after screening 91 were eligible for review. A hospital discharge transition (n = 78, 86%) was most common. Pressure damage (n = 29, 32%), medication errors (n = 26, 29%) and premature discharge (n = 21, 23%) contributed to 84% of the total reporting. Many ‘active failings’ (n = 340) were identified with fewer latent conditions (failings) (n = 14, 15%) being reported. No examples of individual learning were identified. Organization and systems learning were identified in 12 reports (n = 12, 13%).

Conclusions
The findings highlight potentially high levels of underreporting. The most common safety incidents reported were pressure damage, medication errors, and premature discharge. Many active failings causing numerous staff actions were identified emphasizing the cost to patients and services. Additionally, latent conditions (failings) were not emphasized; similarly, evidence of learning from safety incidents was not addressed.
Guidance for Triangulating Data and Estimates of HIV Prevalence Among Pregnant Women and Coverage of PMTCT Using the Spectrum AIDS Impact Module
Authors: Walters Magdalene K. , Korenromp Eline L. , Yakusik Anna , Wanyeki Ian , Kaboré André , Poimouribou Arthur , Ki Célestine , Dao Coumbo , Bambara Paul , Derme Salam , Ouedraogo Théophile , Tang Kai Hon , Boily Marie-Claude , Mahy Mary , Imai-Eaton Jeffrey W. 
Published: August 2024

Background:
Most countries use the Spectrum AIDS Impact Module (Spectrum-AIM), antenatal care routine HIV testing, and antiretroviral treatment data to estimate HIV prevalence among pregnant women. Nonrepresentative program data may lead to inaccurate estimates of HIV prevalence and treatment coverage for pregnant women.

Setting:
One hundred fifty-four countries and subnational locations across 126 countries.

Methods:
Using 2023 UNAIDS HIV estimates, we calculated 3 ratios: (1) HIV prevalence among pregnant women to all women 15–49 yrs (prevalence), (2) ART coverage before pregnancy to women 15–49 yrs ART coverage (ART prepregnancy), and (3) ART coverage at delivery to women 15–49 yrs ART coverage (PMTCT coverage). We developed an algorithm to identify and adjust inconsistent results within regional ranges in Spectrum-AIM, illustrated using Burkina Faso estimates.

Results:
In 2022, the mean regional ratio of prevalence among pregnant women to all women ranged from 0.68 to 0.95. ART coverage prepregnancy ranged by region from 0.40 to 1.22 times ART coverage among all women. Mean regional PMTCT coverage ratios ranged from 0.85 to 1.51. The prevalence ratio in Burkina Faso was 1.59, above the typical range 0.62–1.04 in western and central Africa. Antenatal clinics reported more PMTCT recipients than estimated HIV-positive pregnant women from 2015 to 2019. We adjusted inputted PMTCT program data to enable consistency of HIV prevalence among pregnant women from programmatic routine HIV testing at antenatal clinics with values typical for western and central Africa.

Conclusions:
These ratios offer Spectrum-AIM users a tool to gauge the consistency of their HIV prevalence and treatment coverage estimates among pregnant women with other countries in the region.
Application of U-Net Network Utilizing Multiattention Gate for MRI Segmentation of Brain Tumors
Authors: Zhang Qiong , Hang Yiliu , Qiu Jianlin , Chen Hao 
Published: August 2024

Background
Studies have shown that the type of low-grade glioma is associated with its shape. The traditional diagnostic method involves extraction of the tumor shape from MRIs and diagnosing the type of glioma based on corresponding relationship between the glioma shape and type. This method is affected by the MRI background, tumor pixel size, and doctors' professional level, leading to misdiagnoses and missed diagnoses. With the help of deep learning algorithms, the shape of a glioma can be automatically segmented, thereby assisting doctors to focus more on the diagnosis of glioma and improving diagnostic efficiency. The segmentation of glioma MRIs using traditional deep learning algorithms exhibits limited accuracy, thereby impeding the effectiveness of assisting doctors in the diagnosis. The primary objective of our research is to facilitate the segmentation of low-grade glioma MRIs for medical practitioners through the utilization of deep learning algorithms.

Methods
In this study, a UNet glioma segmentation network that incorporates multiattention gates was proposed to address this limitation. The UNet-based algorithm in the coding part integrated the attention gate into the hierarchical structure of the network to suppress the features of irrelevant regions and reduce the feature redundancy. In the decoding part, by adding attention gates in the fusion process of low- and high-level features, important feature information was highlighted, model parameters were reduced, and model sensitivity and accuracy were improved.

Results
The network model performed image segmentation on the glioma MRI dataset, and the accuracy and average intersection ratio (mIoU) of the algorithm segmentation reached 99.7%, 87.3%, 99.7%, and 87.6%.

Conclusions
Compared with the UNet, PSPNet, and Attention UNet network models, this network model has obvious advantages in accuracy, mIoU, and loss convergence. It can serve as a standard for assisting doctors in diagnosis.
Predictors of Long-Term Protraction Headgear Success in Patients With Cleft Lip and Palate: A 5-Year Follow-Up
Authors: Schechter Jill , Alcon Andre , Verzella Alexandra , Diaz Allison , Staffenberg David , Flores Roberto , Shetye Pradip R. 
Published: August 2024

Patients with cleft lip and palate (CLP) characteristically present with maxillary hypoplasia and class III malocclusion. Protraction headgear (PHG) is a commonly used treatment for this type of malocclusion, with the goal of reducing future surgical needs. The purpose of this study was to evaluate the long-term effects of PHG treatment and determine the pretreatment predictors of long-term PHG success in patients with CLP. Twenty-nine patients with CLP who had undergone PHG treatment from 2012 to 2017 at a single institution were retrospectively analyzed. Patients were included if they had a lateral cephalogram or CBCT before, immediately after, and at least 5 years after their PHG treatment. Patients were divided into surgery and nonsurgery groups based on their 5-year follow-up clinical presentation. Student t tests, Wilcoxon signed-rank test, and a multivariate logistic regression model were used to compare pretreatment and post-treatment changes in both groups. Immediately post-treatment, the maxilla advanced 2.6 mm, the maxillary dentition advanced 4.7 mm, and the mandible rotated downward 5.0 mm and backward 2.6 mm. At long-term follow up the maxilla advanced 0.0 mm while the mandible advanced an additional 7.5 mm. Thus, PHG treatment is effective at improving class III malocclusion in the short term, but may not prevent future surgical need for patients with more severe skeletal discrepancies. Variables predictive of future surgical need include ANB, anterior facial height, overjet, and starting age of treatment, with ANB as the most reliable early predictor.
Photoproduction of
γp→f0(980)p
in an effective Lagrangian approach
Authors: Wei Neng-Chang , Wang Ai-Chao , Huang Fei 
Published: August 2024

The most recent data on differential cross sections and photon beam asymmetries Σ from the LEPS2/BGOegg Collaboration for the γp→f0(980)p reaction are analyzed within a tree-level effective Lagrangian approach. The t-channel ρ and ω exchanges, the u- and s-channel N exchanges, the interaction current, and the possible s-channel N* exchanges are taken into account in constructing the reaction amplitudes to reproduce the data. The results show that the contributions from either the N(2040)3/2+ or the N(2100)1/2+ resonance exchange in the s channel are necessarily required to describe the LEPS2/BGOegg data and they dominate the differential cross sections of γp→f0(980)p. Further analysis shows that the contributions from the t-channel ρ and ω exchanges and the interaction current are rather small to both differential cross sections and photo beam asymmetries, and the contributions from u-channel N exchange are considerable in the case of including N(2040)3/2+ in the model while negligible in the case of including N(2100)1/2+ in the model. Predictions of target asymmetries T for γp→f0(980)p are given, which can be examined by future experiments.

Published by the American Physical Society
2024