bluuebunny/crossref_metadata_2025_split huggingface dataset:
Equine-assisted services for individuals with substance use disorders: a scoping review
Authors: Diaz Liam , Gormley Mirinda Ann , Coleman Ashley , Sepanski Abby , Corley Heather , Perez Angelica , Litwin Alain H. 
Published: December 2022

AbstractThe implementation of equine-assisted services (EAS) during treatment for psychological disorders has been frequently documented; however, little is known about the effect of EAS on outcomes for populations with substance use disorder (SUD). The purpose of this scoping review was to synthesize existing literature reporting the effects of EAS when incorporated into SUD treatment. This review followed guidelines in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist for scoping reviews. A search of four databases (MEDLINE/PubMed, PsycINFO, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Academic OneFile) identified studies reporting quantitative and/or qualitative data for an EAS intervention that was implemented among a population receiving treatment for and/or diagnosed with SUD. Of 188 titles, 71 underwent full-text assessment and six met inclusion criteria. Three additional articles were identified through other sources. Quantitative data suggested a potential positive effect of EAS on SUD treatment retention and completion as well as participants’ mental health; however, studies were limited by small sample sizes. Qualitative data indicated that in addition to participants developing bonds with the horses and perceiving EAS as welcomed breaks from traditional treatment, they experienced increased self-efficacy, positive emotional affect, and SUD treatment motivation. Due to methodological limitations and an overall dearth of available studies, the effectiveness of EAS as adjuncts to SUD treatment is inconclusive. Additional research is necessary before supporting broad implementation of EAS as adjuncts to SUD treatment.
Dosimetric evaluation of bone marrow sparing in proton radiotherapy for cervical cancer guided by MR functional imaging
Authors: Qin Xiaohang , Gong Guanzhong , Wang Lizhen , Su Ya , Yin Yong 
Published: December 2022

Abstract
Background
To segment the pelvic active bone marrow (PABM) using magnetic resonance (MR) functional imaging and investigate the feasibility and dosimetric characteristics of cervical cancer proton radiotherapy for active bone marrow (ABM) sparing.

Methods
We collected CT and MR simulation images of 33 patients with cervical cancer retrospectively. The PBM was contoured on the MRI FatFrac images; the PBM was divided into high-active bone marrow (ABM-high) and low-active bone marrow based on the fat content of the PBM. Four radiotherapy plans were created for each patient, which included intensity-modulated photon therapy (IMRT), bone marrow sparing IMRT (IMRT-BMS), intensity-modulated proton therapy (IMPT), and bone marrow sparing IMPT (IMPT-BMS). The dosimetric differences among the four plans were compared.

Results
The ABM-high volume in the enrolled patients accounted for 45.2% of the total ABM volume. The target coverage was similar among the four radiotherapy plans. IMRT-BMS, IMPT, and IMPT-BMS reduced the Dmean of ABM-high by 16.6%, 14.2%, and 44.5%, respectively, compared to the Dmean of IMRT (p < 0.05). IMPT-BMS had the best protective effect on the bone marrow. Compared to IMRT, the volume of ABM-high receiving an irradiation dose of 5–40 Gy decreased by 10.2%, 36.8%, 58.8%, 67.4%, 64.9%, and 44.5%, respectively (p < 0.001).

Conclusions
The MR functional imaging technique helped in the grading and segmentation of PABM. MR functional image-guided proton radiotherapy for cervical cancer can achieve optimal BMS.
Automatic assessment of knee osteoarthritis severity in portable devices based on deep learning
Authors: Yang Jianfeng , Ji Quanbo , Ni Ming , Zhang Guoqiang , Wang Yan 
Published: December 2022

Abstract
Background
For knee osteoarthritis, the commonly used radiology severity criteria Kellgren–Lawrence lead to variability among surgeons. Most existing diagnosis models require preprocessed radiographs and specific equipment.

Methods
All enrolled patients diagnosed with KOA who met the criteria were obtained from **** Hospital. This study included 2579 images shot from posterior–anterior X-rays of 2,378 patients. We used RefineDet to train and validate this deep learning-based diagnostic model. After developing the model, 823 images of 697 patients were enrolled as the test set. The whole test set was assessed by up to 5 surgeons and this diagnostic model. To evaluate the model’s performance we compared the results of the model with the KOA severity diagnoses of surgeons based on K-L scales.

Results
Compared to the diagnoses of surgeons, the model achieved an overall accuracy of 0.977. Its sensitivity (recall) for K-L 0 to 4 was 1.0, 0.972, 0.979, 0.983 and 0.989, respectively; for these diagnoses, the specificity of this model was 0.992, 0.997, 0.994, 0.991 and 0.995. The precision and F1-score were 0.5 and 0.667 for K-L 0, 0.914 and 0.930 for K-L 1, 0.978 and 0.971 for K-L 2, 0.981 and 0.974 for K-L 3, and 0.988 and 0.985 for K-L 4, respectively. All K-L scales perform AUC > 0.90. The quadratic weighted Kappa coefficient between the diagnostic model and surgeons was 0.815 (P < 0.01, 95% CI 0.727–0.903). The performance of the model is comparable to the clinical diagnosis of KOA. This model improved the efficiency and avoided cumbersome image preprocessing.

Conclusion
The deep learning-based diagnostic model can be used to assess the severity of KOA in portable devices according to the Kellgren–Lawrence scale. On the premise of improving diagnostic efficiency, the results are highly reliable and reproducible.
Identifying adult hypophosphatasia in the rheumatology unit
Authors: Feurstein Julia , Behanova Martina , Haschka Judith , Roetzer Katharina , Uyanik Gökhan , Hadzimuratovic Benjamin , Witsch-Baumgartner Martina , Schett Georg , Zwerina Jochen , Kocijan Roland 
Published: December 2022

Abstract
Background
The most frequent manifestation in adult hypophosphatasia (HPP) is musculoskeletal pain. The unspecific nature of its clinical presentation may prevent correct diagnosis. The aim of the study was to assess the prevalence of ALPL mutations in adult patients treated in rheumatological outpatient facilities with evident musculoskeletal symptoms typical for HPP.

Methods
Over a period of 10 years 9,522 patients were screened in the rheumatology outpatient clinic of the Hanusch hospital Vienna. Serum ALP levels ≤ 40 U/L were found in 524 patients. After screening for secondary causes, 73 patients were invited for clinical evaluation. Genetic testing was performed in 23 patients with suspected HPP. Logistic regression models with Firth penalisation were used to estimate the unadjusted and BMI-adjusted association of each clinical factor with HPP.

Results
Mutations in the ALPL gene were observed in 57% of genetically screened patients. Arthralgia, fractures, and pain were the leading symptoms in individuals with ALPL mutation. Chondrocalcinosis (OR 29.12; 95% CI 2.02–1593.52) and dental disease (OR 8.33; 95% CI 0.93–143.40) were associated with ALPL mutation, independent of BMI. Onset of symptoms in patients with ALPL mutation was at 35.1 (14.3) years, with a mean duration from symptoms to diagnosis of 14.4 (8.1) years. Bone mineral density (BMD) and trabecular bone score (TBS) as well as bone turnover markers were not indicative for HPP or ALPL mutation.

Conclusion
HPP can mimic rheumatologic diseases. Thus, HPP should be considered as a possible diagnosis in adult patients presenting with musculoskeletal pain of unknown origin in rheumatology outpatient clinics. In patients with persistently low ALP serum levels and unclear musculoskeletal pain, HPP as the underlying cause has to be considered.
RETRACTED ARTICLE: ANGPTL4 functions as an oncogene through regulation of the ETV5/CDH5/AKT/MMP9 axis to promote angiogenesis in ovarian cancer
Authors: Liu Yinping , Yang Rui , Zhang Yan , Zhu Yaping , Bao Wei 
Published: December 2022

AbstractBackgroundAngiopoietin-like 4 (ANGPTL4) is highly expressed in a variety of neoplasms and promotes cancer progression. Nevertheless, the mechanism of ANGPTL4 in ovarian cancer (OC) metastasis remains unclear. This study aimeds to explore whether ANGPTL4 regulates OC progression and elucidate the underlying mechanism.MethodsANGPTL4 expression in clinical patient tumor samples was determined by immunohistochemistry (IHC) and high-throughput sequencing. ANGPTL4 knockdown (KD) and the addition of exogeneous cANGPTL4 protein were used to investigate its function. An in vivo xenograft tumor experiment was performed by intraperitoneal injection of SKOV3 cells transfected with short hairpin RNAs (shRNAs) targeting ANGPTL4 in nude mice. Western blotting and qRT-PCR were used to detect the levels of ANGPTL4, CDH5, p-AKT, AKT, ETV5, MMP2 and MMP9 in SKOV3 and HO8910 cells transfected with sh-ANGPTL4 or shRNAs targeting ETV5.ResultsIncreased levels of ANGPTL4 were associated with poor prognosis and metastasis in OC and induced the angiogenesis and metastasis of OC cells both in vivo and in vitro. This tumorigenic effect was dependent on CDH5, and the expression levels of ANGPTL4 and CDH5 in human OC werepositively correlated. In addition, CDH5 activated p-AKT, and upregulated the expression of MMP2 and MMP9. We also found that the expression of ETV5 was upregulated by ANGPTL4, which could bind the promoter region of CDH5, leading to increased CDH5 expression.ConclusionOur data indicated that an increase in the ANGPTL4 level results in increased ETV5 expression in OC, leading to metastasis via activation of the CDH5/AKT/MMP9 signaling pathway.
Machine learning for the real-time assessment of left ventricular ejection fraction in critically ill patients: a bedside evaluation by novices and experts in echocardiography
Authors: Varudo Rita , Gonzalez Filipe A. , Leote João , Martins Cristina , Bacariza Jacobo , Fernandes Antero , Michard Frederic 
Published: December 2022

Abstract
Background
Machine learning algorithms have recently been developed to enable the automatic and real-time echocardiographic assessment of left ventricular ejection fraction (LVEF) and have not been evaluated in critically ill patients.

Methods
Real-time LVEF was prospectively measured in 95 ICU patients with a machine learning algorithm installed on a cart-based ultrasound system. Real-time measurements taken by novices (LVEFNov) and by experts (LVEFExp) were compared with LVEF reference measurements (LVEFRef) taken manually by echo experts.

Results
LVEFRef ranged from 26 to 80% (mean 54 ± 12%), and the reproducibility of measurements was 9 ± 6%. Thirty patients (32%) had a LVEFRef < 50% (left ventricular systolic dysfunction). Real-time LVEFExp and LVEFNov measurements ranged from 31 to 68% (mean 54 ± 10%) and from 28 to 70% (mean 54 ± 9%), respectively. The reproducibility of measurements was comparable for LVEFExp (5 ± 4%) and for LVEFNov (6 ± 5%) and significantly better than for reference measurements (p < 0.001). We observed a strong relationship between LVEFRef and both real-time LVEFExp (r = 0.86, p < 0.001) and LVEFNov (r = 0.81, p < 0.001). The average difference (bias) between real time and reference measurements was 0 ± 6% for LVEFExp and 0 ± 7% for LVEFNov. The sensitivity to detect systolic dysfunction was 70% for real-time LVEFExp and 73% for LVEFNov. The specificity to detect systolic dysfunction was 98% both for LVEFExp and LVEFNov.

Conclusion
Machine learning-enabled real-time measurements of LVEF were strongly correlated with manual measurements obtained by experts. The accuracy of real-time LVEF measurements was excellent, and the precision was fair. The reproducibility of LVEF measurements was better with the machine learning system. The specificity to detect left ventricular dysfunction was excellent both for experts and for novices, whereas the sensitivity could be improved.
Trial registration: NCT05336448. Retrospectively registered on April 19, 2022.
circ-Iqsec1 induces bone marrow-derived mesenchymal stem cell (BMSC) osteogenic differentiation through the miR-187-3p/Satb2 signaling pathway
Authors: Fan Lixia , Yang Kaiyun , Yu Ruixuan , Hui Houde , Wu Wenliang 
Published: December 2022

Abstract
Background
Bone marrow-derived mesenchymal stem cells (BMSCs) are general progenitor cells of osteoblasts and adipocytes and they are characterized as a fundamental mediator for bone formation. The current research studied the molecular mechanisms underlying circRNA-regulated BMSC osteogenic differentiation.

Methods
Next-generation sequencing (NGS) was employed to study abnormal circRNA and mRNA expression in BMSCs before and after osteogenic differentiation induction. Bioinformatics analysis and luciferase reporting analysis were employed to confirm correlations among miRNA, circRNA, and mRNA. RT-qPCR, ALP staining, and alizarin red staining illustrated the osteogenic differentiation ability of BMSCs.

Results
Data showed that circ-Iqsec1 expression increased during BMSC osteogenic differentiation. circ-Iqsec1 downregulation reduced BMSC osteogenic differentiation ability. The present investigation discovered that Satb2 played a role during BMSC osteogenic differentiation. Satb2 downregulation decreased BMSC osteogenic differentiation ability. Bioinformatics and luciferase data showed that miR-187-3p linked circ-Iqsec1 and Satb2. miR-187-3p downregulation or Satb2 overexpression restored the osteogenic differentiation capability of BMSCs post silencing circ-Iqsec1 in in vivo and in vitro experiments. Satb2 upregulation restored osteogenic differentiation capability of BMSCs post miR-187-3p overexpression.

Conclusion
Taken together, our study found that circ-Iqsec1 induced BMSC osteogenic differentiation through the miR-187-3p/Satb2 signaling pathway.
The impact of hospital price and quality transparency tools on healthcare spending: a systematic review
Authors: Chen Jinyang , Miraldo Marisa 
Published: December 2022

Abstract
Background

Global spending on health was continuing to rise over the past 20 years. To reduce the growth rates, alleviate information asymmetry, and improve the efficiency of healthcare markets, global health systems have initiated price and quality transparency tools in the hospital industry in the last two decades.

Objective
The objective of this review is to synthesize whether, to what extent, and how hospital price and quality transparency tools affected 1) the price of healthcare procedures and services, 2) the payments of consumers, and 3) the premium of health insurance plans bonding with hospital networks.

Methods
A literature search of EMBASE, Web of Science, Econlit, Scopus, Pubmed, CINAHL, and PsychINFO was conducted, from inception to Oct 31, 2021. Reference lists and tracked citations of retrieved articles were hand-searched. Study characteristics were extracted, and included studies were scored through a risk of bias assessment framework. This systematic review was reported according to the PRISMA guidelines and registered in PROSPERO with registration No. CRD42022319070.

Results
Of 2157 records identified, 18 studies met the inclusion criteria. Near 40
percent of studies focused on hospital quality transparency tools, and more than 90 percent of studies were from the US. Hospital price transparency reduced the price of laboratory and imaging tests except for office-visit services. Hospital quality transparency declined the level or growth rates of healthcare spending, while it adversely and significantly raised the price of healthcare services and consumers’ payment in higher-ranked or rated facilities, which was referred to as the reputation premium in the healthcare industry. Hospital quality transparency not only leveraged private insurers bonding with a higher-rated hospital network to increase premiums, but also induced their anticipated pricing behaviors.

Conclusion
Hospital price and quality transparency was not effective as expected. Future research should explore the understudied consequences of hospital quality transparency programs, such as the reputation/rating premium and its policy intervention.
Transcriptomic analysis of spleen B cell revealed the molecular basis of bursopentin on B cell differentiation
Authors: Zhang Ze , Cai Jiaxi , Hao Shanshan , Li Chenfei , Chen Jiajing , Li Tongtong , Feng Xiuli 
Published: December 2022

AbstractThe bursa of Fabricius, the acknowledged humoral immune organ unique to birds, plays a vital role in B cell development. Bursopentin (BP5) derived from the bursa is reported to induce the development and formation of B cells. However, the mechanism of BP5 on B cell differentiation is still unclear. In this paper, total B lymphocytes from mice immunized with H9N2 subtype AIV vaccine were stimulated with BP5. The results show that BP5 at the experimental dosages promoted B cell differentiation, including the total B cells, activated B cells, differentiated B cells, mature B cells and plasma cells. Then, the in vivo immune experiment proved that the percentages of activated and differentiated B cells from mice immunized with AIV vaccine and 0.25 mg/mL BP5 were increased. To investigate the molecular mechanism of BP5 on B cell differentiation, the gene expression profiles of B cells purified from the spleen cells of mice immunized with AIV vaccine and BP5 were detected following RNA sequencing technology. The results show that BP5 at 0.05 and 0.25 mg/mL induced the enrichment of various biological functions, and stimulated five common significant enrichment pathways in B cells from the immunized mice. Additionally, 120 and 59 differentially expressed genes (DEG) represented transcriptional factors in B cells following 0.05 and 0.25 mg/mL BP5 immunization, respectively. In summary, these results suggest that BP5 regulates various gene expression involved in regulation of B cell development, which provides the knowledge required for additional studies on B cell differentiation in response to bursal-derived peptides and also provides an important experimental basis for improving vaccine immunity.
Pathogenicity of highly pathogenic avian influenza H5N8 subtype for herring gulls (Larus argentatus): impact of homo- and heterosubtypic immunity on the outcome of infection
Authors: Tarasiuk Karolina , Kycko Anna , Knitter Małgorzata , Świętoń Edyta , Wyrostek Krzysztof , Domańska-Blicharz Katarzyna , Bocian Łukasz , Meissner Włodzimierz , Śmietanka Krzysztof 
Published: December 2022

AbstractTo improve understanding of the pathobiology of highly pathogenic avian influenza virus (HPAIV) infections in wild birds, pathogenicity and transmissibility of HPAIV H5N8 subtype clade 2.3.4.4b was evaluated in ~ 8-week-old herring gulls (Larus argentatus) divided into 3 groups: naïve birds (group A), birds previously exposed to low pathogenic avian influenza virus (LPAIV) H5N1 (group B) and LPAIV H13N6 (group C). The HPAIV H5N8 virus was highly virulent for naïve gulls, that showed early morbidity, high mortality, a broad spectrum of clinical signs, including violent neurological disorders, systemic distribution of the virus in organs accompanied by high level of shedding and transmission to contact birds. Pre-exposure to homologous and heterologous LPAIV subtypes conferred only partial protection: we observed increased survival rate (statistically significant only in group B), nervous signs, pantropic distribution of virus in organs, shedding (significantly reduced in gulls of group C in the early phase of disease and asymptomatic shedding in the late phase), transmission to contact gulls (more pronounced in group B) and near-complete seroconversion in survivors. Histopathological and immunohistochemical results indicate virus tropism for the neural, respiratory and myocardial tissues. In conclusion, we demonstrate that HPAIV H5N8 clade 2.3.4.4b is highly virulent and lethal for fully susceptible herring gulls and that pre-exposure to homo- and heterosubtypic LPAIV only partially modulates the disease outcome.
An artificial intelligence-enabled ECG algorithm for identifying ventricular premature contraction during sinus rhythm
Authors: Chang Sheng-Nan , Tseng Yu-Heng , Chen Jien-Jiun , Chiu Fu-Chun , Tsai Chin-Feng , Hwang Juey-Jen , Wang Yi-Chih , Tsai Chia-Ti 
Published: December 2022

Abstract
Background
Ventricular premature complex (VPC) is a common arrhythmia in clinical practice. VPC could trigger ventricular tachycardia/fibrillation or VPC-induced cardiomyopathy in susceptible patients. Existing screening methods require prolonged monitoring and are limited by cost and low yield when the frequency of VPC is low. Twelve-lead electrocardiogram (ECG) is low cost and widely used. We aimed to identify patients with VPC during normal sinus rhythm (NSR) using artificial intelligence (AI) and machine learning-based ECG reading.

Methods
We developed AI-enabled ECG algorithm using a convolutional neural network (CNN) to detect the ECG signature of VPC presented during NSR using standard 12-lead ECGs. A total of 2515 ECG records from 398 patients with VPC were collected. Among them, only ECG records of NSR without VPC (1617 ECG records) were parsed.

Results
A total of 753 normal ECG records from 387 patients under NSR were used for comparison. Both image and time-series datasets were parsed for the training process by the CNN models. The computer architectures were optimized to select the best model for the training process. Both the single-input image model (InceptionV3, accuracy: 0.895, 95% confidence interval [CI] 0.683–0.937) and multi-input time-series model (ResNet50V2, accuracy: 0.880, 95% CI 0.646–0.943) yielded satisfactory results for VPC prediction, both of which were better than the single-input time-series model (ResNet50V2, accuracy: 0.840, 95% CI 0.629–0.952).

Conclusions
AI-enabled ECG acquired during NSR permits rapid identification at point of care of individuals with VPC and has the potential to predict VPC episodes automatically rather than traditional long-time monitoring.