bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emergency and successful management for a case of inferior vena cava perforation caused by cannulation of venovenous extracorporeal membrane oxygenation: A case report
Authors: Cen Xiangying , Chen Yanzhu , Chen Yi 
Published: February 2024

Rationale:
Vascular complications associated with extracorporeal membrane oxygenation (ECMO) increase the in-hospital mortality. Perforation of the inferior vena cava (IVC) during venovenous extracorporeal membrane oxygenation (V-V ECMO) cannulation and subsequent emergency management prior to vascular surgery has rarely been reported.

Patient concerns:
A 72-year-old female was diagnosed with IVC perforation caused by venovenous extracorporeal membrane oxygenation cannulation.

Diagnoses:
Abdominal computed tomography venography with 3D reconstruction confirmed that the cannula tip had perforated the abdominal cavity from the conjunction of the iliac vein and IVC. As a result, the patient was diagnosed with inferior vena cava perforation.

Interventions:
Attempts to reposition the dislocated cannula using digital subtraction angiography were unsuccessful. However, we found that ECMO could maintain a stable blood flow; therefore, we decided to keep ECMO running, and to minimize blood loss from the puncture site, we ensured adequate blood transfusion while operating V-V ECMO. Subsequently, emergency laparotomy was performed to fix the vascular lesion, and we established a new V-V ECMO circuit through cannulation of the bilateral internal jugular veins.

Outcomes:
In the case of confirmed V-V ECMO-related vascular perforation of the IVC, it is crucial to continue ECMO device operation to maintain negative pressure in the IVC and position the dislocated catheter to block the perforation site, effectively controlling bleeding. Therefore, emergency laparotomy should be promptly performed for vascular repair. Fortunately, the patient recovered successfully and was subsequently discharged.

Lessons:
This case highlights several important lessons: When advancing a cannula, in this case, it is essential to first identify the guidewire placement to ensure proper guidance; In the event of a confirmed V-V ECMO-related vascular perforation of the IVC, maintaining negative pressure in the IVC through continued ECMO device operation and positioning the dislocated catheter to block the perforation site are crucial steps to control bleeding prior to emergency open vascular repair; After undergoing vascular repair, if ECMO support is still necessary, it is advisable to opt for a catheterization strategy that avoids previously repaired blood vessels.
Bibliometric analysis of extracorporeal shock wave therapy for tendinopathy
Authors: Ji Haoyuan , Liu Haitao , Han Wenxiu , Xia Yingjian , Liu Feiyue 
Published: February 2024

Background:
Extracorporeal shock wave therapy (ESWT) is a mature, conservative treatment modality for tendinopathy. Although many relevant studies have been conducted, systematic bibliometric studies are lacking. This study aimed to identify trends and hotspots in the treatment of tendinopathy using ESWT.

Methods:
A literature search was conducted on ESWT for tendinopathy using the Web of Science Core Collection with a search period of 2002 to 2022. Of 559 identified studies, 276 met the inclusion criteria and were analyzed using CiteSpace software.

Results:
The results showed that from 2002 to 2022, the publication rate of literature on ESWT for tendinopathy was generally increasing. Research hotspots, such as tendinopathy and calcific rotator cuff deposits, began earlier but continued to receive scholarly attention. Research on animal models and molecular mechanisms has progressed slowly in this field. The combined or comparative effectiveness of injectable and supplement-based treatments with ESWT is a popular research topic.

Conclusion:
Pain management in patients with tendinopathy has received considerable attention. Simultaneously, more clinical indicators of energy levels and pulse parameters during ESWT are needed to provide more scientific and accurate treatment for patients.
Association between physical activity levels and anxiety or depression among college students in China during the COVID-19 pandemic: A meta-analysis
Authors: Yang Hongchang , Fu Chengjie , Zhang Xiaoxia , Li Wenchao 
Published: February 2024

Background:
This meta-analysis aimed to investigate the links between the level of physical activity and the risk of anxiety or depression among college students in China during the Coronavirus Disease 2019 pandemic.

Methods:
Eligible studies were searched from the PubMed, Embase, and Web of Science databases. The associations between them were assessed with odd ratio (OR) and 95% confidence interval (CI). The heterogeneity of the included studies was evaluated and subgroup analysis was performed. Sensitivity analysis was executed using leave-one-out method. Publication bias of included studies was evaluated. Ten studies with moderate quality were included.

Results:
Physical activity levels of college students were associated with reduced risk of depression (OR [95%CI] = 0.69 [0.58, 0.82], P < .001) and anxiety (OR [95%CI] = 0.71 [0.62, 0.80], P < .001). The measurement scale of depression or anxiety and whether multi-factor correction was performed or not did not influence the pooled results. The pooled results of depression and anxiety were stable and were not significantly influenced by a single study. No publication bias was observed in the included studies reporting depression and anxiety.

Conclusion:
The physical activity level of college students is negatively correlated with anxiety and depression in China during the pandemic. During the Coronavirus Disease 2019 pandemic, it is necessary to strengthen the construction of university physical education courses. As an organized form of physical activity, physical education classes are a necessary and effective way to increase physical activity among college students.
Lack of associations between thyroid dysfunction and obstructive sleep apnea-hypopnea syndrome: A meta-analysis
Authors: Xiong Juan , Hu Hongxia , Huang Yuanyuan , Zhang Jiexi , He Jie 
Published: February 2024

Background:
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a comprehensive syndrome with endocrine and metabolic complications. This review aims to explore the correlation between thyroid hormone levels and the severity of OSAHS in patients.

Methods:
The protocol for this meta-analysis has been registered on PROSPERO. Searches were carried out from the inception of the databases to July 18, 2023, utilizing 6 databases (PubMed, CNKI, EMBASE, Web of Science, Cochrane Library, China Biology Medicine, and Wanfang). Standardized mean difference (SMD) and correlation coefficients were used as the effect size measures. Additionally, random effects or fixed effects models were used for pooled analysis. Moreover, data were statistically evaluated with the help of STATA 11.0 and R 4.1.3.

Results:
This study included 23 articles that satisfied the pre-defined criteria. The prevalence of hypothyroidism and subclinical hypothyroidism in OSAHS patients was 6% and 8%, whereas hyperthyroidism had a prevalence of 2%. Moreover, thyroid hormone levels in OSAHS individuals exhibited no significant difference relative to healthy subjects. Subgroup analysis based on disease severity also established no significant changes in thyroid hormone levels between OSAHS individuals and controls. There was no significant correlation between the Apnea-Hypopnea Index (AHI) and free triiodothyronine (FT3), serum thyroid stimulating hormone (TSH), and free thyroxine (FT4) levels.

Conclusion:
The prevalence of thyroid dysfunction is relatively low in OSAHS individuals. Thyroid hormone levels show no significant difference between OSAHS patients and healthy subjects. Furthermore, there is no significant correlation between AHI and serum TSH, FT3, and FT4 levels. Based on existing data, the relationship between OSAHS and thyroid function remains controversial, and further in-depth research is warranted to validate the connection and elucidate the underlying mechanisms.
Mimicking descending necrotizing mediastinitis as acute myocardial infarction in a patient with severe coronary artery disease: A case report
Authors: Jung Yu Jung , Park Jong-Il 
Published: February 2024

Rationale:
It is a crucial disease that descending necrotizing mediastinitis need to be treated promptly with proper antibiotics and drainage. The characteristics of its symptoms such as chest pain are difficult to distinguish from acute myocardial infarction.

Patient concerns:
An 80-year-old female presented with severe squeezing chest pain. The cardiac marker was elevated. And coronary angiography showed the significant coronary stenosis. Although the revascularization through percutaneous coronary intervention was completed successfully, the patient still presented chest pain. Computed tomography of neck revealed that hypodense heterogeneous lesions with clear and distinguishable margin extended from the deep neck to mediastinum diffusely.

Diagnoses:
The patient was diagnosed with descending necrotizing mediastinitis.

Interventions:
Percutaneous catheter insertion to patient’s abscess lesion at was performed.

Outcomes:
Catheter drainage of descending necrotizing mediastinitis led to an improvement in the patient’s condition.

Lesson:
Descending necrotizing mediastinitis made chest paint with elevated cardiac enzyme mimicked myocardial infarction.
Prediction of molecular mechanism of processed ginseng in the treatment of heart failure based on network pharmacology and molecular docking technology
Authors: Dai Tingting , Gong Jiyu , Liu Shuying 
Published: February 2024

Background:
Heart failure (HF) is the most common cardiovascular disease in clinics. Processed Panax ginseng C.A. Mey. Products have significant therapeutic effects on HF. Therefore, it is of great significance to explore the mechanism of action of Processed Panax ginseng C.A. Mey. Products in the treatment of HF.

Methods:
The saponin-like constituents of 3 different ginseng preparations were characterized by UPLC/QE-MS and the identified saponin constituents were subjected to network pharmacological analysis. Protein–protein interaction analyses of the targets of different ginseng preparations for the treatment of heart failure (HF) were performed using the STRING database, Gene Ontology enrichment analyses and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the DAVID database, and the results of the network pharmacological analyses were validated using the Autodock software. Finally, the relative quantitative content of 5 major ginsenosides in 3 processed ginseng products was evaluated.

Results:
A total of 40 saponin compounds were identified based on mass spectrometry data. Network pharmacology and molecular docking analyses were used to predict the major targets of these sapions compounds and the key pathways mediating their anti-HF effects. After conducting a thorough screening, the study identified 5 primary ingredients of ginseng products ginsenoside Rh4, ginsenoside Rk3, ginsenoside Rk1, ginsenoside Rg5, and ginsenoside CK that can potentially target 22 essential proteins: EGFR, AKT1, ERBB2, STAT3, TNF, ESR1, MTOR, HRAS, MMP9, and PIK3CA, etc. Additionally, the Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that ginseng products can be beneficial in treating HF by interacting with pathways such as the PI3K-Akt signaling pathway, the TNF signaling pathway, the mTOR signaling pathway, and others.

Conclusion:
The present study revealed that the treatment of HF with different processed ginseng products may be related to the regulation of the PI3K-Akt signaling pathway, TNF signaling pathway, apoptosis pathway, mTOR signaling pathway, etc, and that the key active ingredients may be concentrated in black ginseng, which provides a theoretical basis and direction for the further study of the mechanism of action of ginseng. This provides a theoretical basis and research direction for further in-depth study of its mechanism of action.
Nonperturbative photon
qq¯
light front wave functions from a contact interaction model
Authors: Shi Chao , Yang Zhongtian , Chen Xurong , Jia Wenbao , Luo Cuibai , Xiang Wenchang 
Published: February 2024

We propose a method to calculate the qq¯ light front wave functions (LFWFs) of photons at low virtuality, i.e., the light front amplitude of γ*→qq¯ at low Q2, based on a light front projection approach. We exemplify this method using a contact interaction model within Dyson-Schwinger equations formalism and obtain the nonperturbative photon qq¯ LFWFs. In this case, we find the nonperturbative effects are encoded in the enhanced quark mass and a dressing function of covariant quark-photon vertex, as compared to the leading order quantum electrodynamics photon qq¯ LFWFs. We then use nonperturbative-effect modified photon qq¯ LFWFs to study the inclusive deep inelastic scattering HERA data in the framework of the color dipole model. The results demonstrate that the theoretical description of data at low Q2 can be significantly improved once the nonperturbative corrections are included in the photon LFWFs.

Published by the American Physical Society
2024
Search for decaying dark matter in the Virgo cluster of galaxies with HAWC
Authors: Albert A. , Alfaro R. , Alvarez C. , Arteaga-Velázquez J. C. , Ayala Solares H. A. , Babu R. , Belmont-Moreno E. , Caballero-Mora K. S. , Capistrán T. , Carramiñana A. , Casanova S. , Cotzomi J. , Coutiño de León S. , Depaoli D. , Diaz Hernandez R. , DuVernois M. A. , Durocher M. , Fraija N. , García-González J. A. , González M. M. , Goodman J. A. , Harding J. P. , Hernández-Cadena S. , Herzog I. , Huang D. , Hueyotl-Zahuantitla F. , Joshi V. , Kaufmann S. , León Vargas H. , Linnemann J. T. , Longinotti A. L. , Luis-Raya G. , Malone K. , Martínez-Castro J. , Matthews J. A. , Miranda-Romagnoli P. , Morales-Soto J. A. , Mostafá M. , Nayerhoda A. , Nellen L. , Nisa M. U. , Noriega-Papaqui R. , Omodei N. , Pérez-Pérez E. G. , Rho C. D. , Rosa-González D. , Schneider M. , Son Y. , Springer R. W. , Tibolla O. , Tollefson K. , Torres I. , Torres-Escobedo R. , Turner R. , Ureña-Mena F. , Villaseñor L. , Wang X. , Watson I. J. , Yun-Cárcamo S. ,   HAWC Collaboration
Published: February 2024

The decay or annihilation of dark matter particles may produce a steady flux of very-high-energy gamma rays detectable above the diffuse background. Nearby clusters of galaxies provide excellent targets to search for the signatures of particle dark matter interactions. In particular, the Virgo cluster spans several degrees across the sky and can be efficiently probed with a wide field-of-view instrument. The High Altitude Water Cherenkov (HAWC) observatory, due to its wide field of view and sensitivity to gamma rays at an energy scale of 300 GeV–100 TeV is well-suited for this search. Using 2141 days of data, we search for γ-ray emission from the Virgo cluster, assuming well-motivated dark matter substructure models. Our results provide some of the strongest constraints on the decay lifetime of dark matter for masses above 10 TeV.

Published by the American Physical Society
2024
Exploring academic influence of algorithms by co-occurrence network based on full-text of academic papers
Authors: Wang Yuzhuo , Zhang Chengzhi , Song Min , Kim Seongdeok , Ko Youngsoo , Lee Juhee 
Published: February 2024

PurposeIn the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.Design/methodology/approachWe use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.FindingsThe results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.Originality/valueTo the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.
R&D team network configurations, knowledge diversity and breakthrough innovation: a combined effect framework
Authors: Zhou Wenhao , Li Hailin 
Published: February 2024

PurposeThis study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.Design/methodology/approachBased on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.FindingsIt has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.Originality/valuePrevious studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.
Importance of AI attributes in Indian retail stores: a conjoint analysis approach
Authors: Srivastava Kavita , Pal Divyanshi 
Published: February 2024

PurposeThe study’s objective is to measure the importance consumers attach to AI-based attributes, namely, chatbots, face recognition, virtual fitting room, smart parking and cashier-free station in retail stores. The study also examines the specific purpose of using these attributes for shopping.Design/methodology/approachA conjoint experiment was conducted using fractional factorial design. Consumers were given 14 profiles (AI attributes and its levels) to rank according to their visiting preferences.FindingsThe results revealed that the retail chatbot was considered the most important attribute, followed by face recognition, virtual fitting room, smart parking system and cashier-free station. Moreover, consumers prefer to use chatbots for in-store shopping assistance over alerts and updates, customer support and feedback. Similarly, consumers wish a face recognition facility for greetings while entering the store over other services. In addition, cluster analyses revealed that customer groups significantly differ in their preferences for AI-based attributes.Practical implicationsThe study guides retail managers to invest in AI technologies to provide consumers with a technology-oriented shopping experience.Originality/valueOur results provide an insight into the receptivity of AI technologies that consumers would like to experience in their favorite retail stores. The present study contributes to the literature by investigating consumer preferences for various AI technologies and their specific uses for shopping.
Construction of a sustainability reporting score index integrating sustainable development goals (SDGs). The case of Sri Lankan listed firms
Authors: Soysa R.N.K. , Pallegedara Asankha , Kumara A.S. , Jayasena D.M. , Samaranayake M.K.S.M. 
Published: February 2024

PurposeAlthough publicly listed firms in Sri Lanka have been increasingly adapting sustainability reporting into their annual reporting practices, a limited number of firms prepare sustainability reports by integrating sustainable development goals (SDGs) into reporting mechanisms. This study attempts to develop an index to monitor firms' sustainability reporting practices based on Global Reporting Institute (GRI) guidelines integrating SDGs.Design/methodology/approachThis paper develops a sustainability score index using the 17 SDGs utilising the results of content analysis of corporate annual reports of a selected sample of 100 firms listed on the Colombo Stock Exchange (CSE). Principal component analysis was employed to examine the reliability of data in the developed index.FindingsFindings show that the developed scoring index is efficient for evaluating the contents of the sustainability reports of Sri Lankan firms. Sustainability reporting practises with regard to the SDGs were observed to have a turbulent period from 2015 to 2019 and the SDGs 12 and 15 were identified to be mostly reported in Sri Lankan corporate sustainability reports.Research limitations/implicationsThe results of the study add to knowledge on the monitoring of sustainability reporting practises with reference to SDGs. The study outcomes are useful for the investors, stakeholders, and statutory bodies to measure the sustainable performance of business firms and assess the firm’s commitment towards the global sustainability agenda.Originality/valueTo the best of our knowledge, this is the first study that constructs a sustainability reporting score index integrating SDGs.