bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical Characteristics and Outcomes of Endophthalmitis Before and During the COVID-19 Pandemic
Authors: H Fortes Blake , D Tailor Prashant , T Xu Timothy , A Churchill Robert , R Starr Matthew 
Published: July 2023

Purpose: To evaluate the clinical characteristics and visual acuity outcomes of patients who presented with endophthalmitis prior to and during the coronavirus disease 2019 (COVID-19) pandemic.
Methods: This multicenter retrospective case series with historical controls included consecutive patients presenting with any form of endophthalmitis from March 1, 2019 to September 1, 2019 (pre-COVID-19) and from March 1, 2020 to September 1, 2020 (COVID-19) at Mayo Clinic Rochester (MCR), Health System (MCHS), Arizona (MCA), and Florida (MCF) sites. Cases were divided into “pre-COVID-19” versus “COVID-19” groups depending on when they first presented with endophthalmitis.
Results: Twenty-eight cases of endophthalmitis presented to all Mayo Clinic sites during the study period. Of these, 10 patients presented during the first six months of the COVID-19 pandemic. During the same six-month period the year prior, 18 patients presented with endophthalmitis. Endophthalmitis etiology (post-injection, post-cataract extraction, post[1]glaucoma filtering surgery, post-pars plana vitrectomy, endogenous, and others) was similar between both groups (P = 0.34), as was post-injection endophthalmitis rate (P = 0.69), days to presentation (P = 0.07), initial management (P = 0.11), culture-positivity rate (P = 0.70), and need for subsequent pars plana vitrectomy (P = 1). Visual acuity outcomes were similar between both groups at six months, however, the mean LogMAR visual acuity at presentation was worse in the COVID-19 group compared to the pre-COVID-19 group (2.44 vs 1.82; P = 0.026).

Conclusion: Clinical characteristics and the post-injection endophthalmitis rate were similar during both periods, however, patients presented with worse vision during the pandemic suggesting that the pandemic may have contributed to delayed presentation, regardless, outcomes are still poor.
Counterpoint: Power in the Dining Hall
Authors: Collins Sophie G. 
Published: July 2023

Counterpoint: Power in the Dining Hall is a poem by Sophie Collins. Written as an echo and response to Al Zolynas' emotive poem Love in the Classroom, the poet describes the sudden, bodily intrusion of material smells in the atmosphere of a training session. This poem evokes school day memories , the physicality of learning, and the overwhelming frustration of teaching within neo-liberal educational constraints.
The Unheard Voices, the Unheard Struggle: Una fuerza poderosa que lucha por expresarse
Authors: Mendoza Reis Noni , Quintanar-Sarellana Rosalinda , Lee Enid , DePass Cecille 
Published: July 2023

Call for Submissions for the Winter 2025 (Volume 16, No. 2) Special Issue of Cultural and Pedagogical Inquiry entitled The Unheard Voices, the Unheard Struggle: Una fuerza poderosa que lucha por expresarse with Guest Co-Editors Noni Mendoza Reis, Rosalina Quintanar-Sarellana, Enid Lee and Cecille DePass.
The International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) at three years: an analysis of 4658 registered protocols on inplasy.com, platform features, and website statistics
Authors: Canellas João Vitor dos Santos , Ritto Fabio Gamboa , Rodolico Alessandro , Aguglia Eugenio , Fernandes Gustavo Vicentis de Oliveira , Figueredo Carlos Marcelo da Silva , Vettore Mario Vianna 
Published: July 2023

Abstract
Background: INPLASY® is an international platform for registering systematic reviews and meta-analysis protocols that was launched in March 2020. INPLASY® provides an online database in which the protocols are maintained as permanent public records and can be accessed on its website (www.inplasy.com).
Methods: We described the database features and registered information of all records published since the launch of the registry on March 31, 2023. Additionally, the website statistics dataset was analyzed to explore the user experience and promote data transparency.
Results: Four thousand six hundred fifty-eight records were registered in INPLASY®, and more than 94% of the protocols were published within 24 h. Most of the submissions were from China, followed by Portugal, Taiwan, Malaysia, and Brazil. The INPLASY® website received 386,395 page views from 64,568 visitors during the first three years. The accesses were obtained from 170 countries. Most of the accesses were from China, followed by the US, the UK, and Portugal. The review status ‘‘completed and published’’ was observed in 898 protocols, and these studies were published in 372 different scientific peer-reviewed journals. The INPLASY® features include: (i) INPLASY® identifier, a unique protocol number; (ii) the digital object identifier (DOI) number, the URL of the protocol linked to a specific DOI; (iii) ORCID update, INPLASY® updates the authors' ORCID page including their protocol automatically; (iv) search tools, the protocols are freely accessible on www.inplasy.com.
Conclusions: INPLASY® has several practical and useful features that should be considered when planning the registration of a systematic review protocol. Furthermore, the sharp increase in the number of protocols registered in INPLASY® in the first three years and the database statistics demonstrate that INPLASY® has become an important source of systematic review protocols. Therefore, authors should access INPLASY® before planning a future review study to avoid unintended duplication of efforts or obtain timely registration.
A Multimodal Large Language Modelling Deep Learning Framework for the Future Pandemic
Authors: Liu Fenglin , Zhu Tingting , Wu Xian , Yang Bang , You Chenyu , Wang Chenyang , Lu Lei , Liu Zhangdaihong , Zheng Yefeng , Sun Xu , Yang Yang , Clifton David 
Published: July 2023

Abstract
Deep neural networks have been integrated into the whole clinical decision procedure which can improve the efficiency of diagnosis and alleviate the heavy workload of physicians. Typical applications include 1) medical report generation, 2) disease classification, and 3) survival prediction. Since most neural networks are supervised, their quality heavily depends on the volume and quality of available labels. However, for rare diseases, e.g., new pandemics, there are few existing labels. In addition, collecting sufficient labels for training is time-consuming and is typically unavailable at the early stage. In this paper, we propose a multimodal large language model - Unsupervised Learning from Unlabelled Medical Images and Text (ULUMIT) framework for radiograph representation learning, which can learn broad medical knowledge (e.g., image understanding, text semantics, and clinical phenotypes) from unlabelled data. As a result, when encountering a rare disease, our framework can be rapidly deployed and easily adapted to them with limited labels. Furthermore, ULUMIT supports medical data across visual modality (e.g., chest X-ray and CT) and textual modality (e.g., medical report and free-text clinical note); therefore, it can be used for clinical tasks that involve both visual and textual medical data. We demonstrate the effectiveness of our ULUMIT by showing how it would perform using the COVID-19 pandemic ``in replay''. In particular, in the retrospective setting, we test the model on the early COVID-19 datasets; and in the prospective setting, we test the model on the new variant COVID-19-Omicron. The experiments are conducted on 1) three kinds of input medical data, image-only, text-only, and image-text; 2) three kinds of downstream tasks, medical reporting, diagnosis, and prognosis; 3) five public COVID-19 datasets; and 4) three different languages, i.e., English, Chinese, and Spanish. All experiments consistently show that our framework can make accurate and robust COVID-19 decision-support tasks with little labelled data. Besides COVID-19, our framework can be applied to identify 14 common thorax diseases and tuberculosis across five additional public datasets, demonstrating its robustness in generalization and transferability. In brief, our framework achieves state-of-the-art performances on ten datasets.
Physical exercise behavior characteristics and influencing factors of police officers
Authors: Feng Yuliang , Wang Dexin 
Published: July 2023

Abstract

Purpose
The present study was to explore the physical exercise behavior characteristics, motivation and influencing factors of police officers. To analyse the police's exercise behavior and influencing factors. In order to better promote the physical exercise behavior and health status of the police.
Methods
Stratified cluster sampling was adopted to investigate 3682 policemen from 16 district public security substations in a city in eastern China, in terms of physical exercise participation and influencing factors, and logistic regression analysis was utilized to investigate the three aspects of exercise behavior, health cognition and influencing factors.
Results
The physical exercise behavior of police showed long range of time, but less frequency and low intensity. The exercise programs were diverse but mainly was running. The exercise motivation was mainly to keep fit and stress relief. Logistic regression analysis indicates that source of police entry (OR = 1.467, 95%CI: 1.338 ~ 1.609), exercise conditions of workplace (OR = 1.069, 95%CI: 1.051 ~ 1.088), exercise conditions near home(OR = 1.123, 95%CI: 1.047 ~ 1.205), high volume physical labor required little exersise(OR = 1.372,95%CI: 1.038 ~ 1.813), lack of organization(OR = 1.415,95%CI: 1.164 ~ 1.720), economic conditions constraints(OR = 1.439, 95%CI: 1.114 ~ 1.858), weather restrictions(OR = 2.292, 95%CI: 2.418 ~ 3.548), were the main factors influencing police physical exercise behavior.
Conclusion
In view of all kinds of influencing factors and combining with the actual police work, the participation and effect of physical exercise of police officers should be improved, so as to better promote the physical health of police officers and serve the development of public security cause.
Evaluation of quality of life and associated factors in patients with intertrochanteric femoral fracture
Authors: Afzal Sina , Esmaeilnejad-Ganji Seyyed Mokhtar , Ghasemi Fatemeh , baroutkoub Mojtaba , Barati Hasan , Tavassoli Mehdi 
Published: July 2023

Abstract
Background: Intertrochanteric fracture is a common injury among the elderly population causing fundamental lifestyle derangements, which influences the patients’ social and psychological functioning. We aimed to study the quality of life (QoL) and its different parameters in patients with this type of injury.
Materials and methods: In this cohort study, all patients hospitalized with intertrochanteric fracture and aged above 50 from 2020 to the 2022 at the Shahid Beheshti Hospital in Babol, Iran, were included. Patients were managed mostly surgically and in exceptional cases non-surgically, were followed up for at least 12 months after receiving treatment. During the follow-up period, patients were dialed and completed a questionnaire to assess the patients' QoL by the 36-item Short Form Health Survey (SF-36). QoL parameters were analyzed based on patients’ sex, age, type of treatment, and height of fall causing fracture.
Result: A total number of 200 patients including 101 (50.5%) males and 99 (49.5%) females with mean age of patients was 74.76 ± 11.36 years (range: 50-99) were included. Regarding the received treatment, 192 (96.0%) patients underwent surgery, and 8 (4.0%) underwent non-surgical treatment. In the study of SF-36 scores, the mean score of male patients was 42.31±14.58 and females scored 37.83±15.35, and the difference was statistically significant (P=0.04). The mean score of QoL and its subscales among the patients of the 50-75 group was significantly higher than the 76-99 group (P<0.001). The average score of QoL was considerably higher in patients who had surgery (40.75±14.57) compared to those who has non-surgical treatment (24.30±19.85) (P=0.01). Patients having a fall from a higher height had higher QoL after treatment.
Conclusion: This study revealed that patients with an intertrochanteric femoral fracture had a poor QoL in all aspects. The overall QoL was significantly higher among male patients, younger patients, those who underwent surgical treatment, and the falls from higher heights. These findings highlight the necessity of long-term follow-up and support in patients with intertrochanteric fractures.
InflANNet: A neural network predictor for Influenza A CTL &amp; HTL epitopes to aid robust vaccine design
Authors: Karthika R , Muthusamy Sathya , Prabhu Prince R 
Published: July 2023

Abstract
Background
An efficient and reliable data-driven method is essential to aid robust vaccine design, particularly in the case of an epidemic like Influenza A. Although various prediction tools are existing, most of them focus on the MHC-peptide binding affinity predictions. A tool which can incorporate more features other than binding affinity which characterizes the T-cell epitopes as vaccine candidates would be of much value in this scenario. The objective of this study is to develop two separate neural network models for the predictions of CTLs (cytotoxic T lymphocyte) and HTLs (helper T lymphocyte) with the manually curated datasets as a part of this study from the raw viral sequences of Influenza A.
Results
The epitope datasets curated from the raw sequences of the broadly protective Neuraminidase protein was utilized for building and training the models for CTLs and HTLs. Each set consisted of nearly a balanced mix of vaccine candidates and non-vaccine candidates for both CTLs and HTLs. These were fed to neural networks as they are proven to be powerful for the predictions when compared with the other machine/deep learning algorithms. A set of epitopes experimentally proved were chosen to validate the model which was also tested through mutational analysis and cross-reactivity. The prepared dataset gave some valuable insights into the epitope distribution statistics and their conservancy in various outbreaks. An idea about the most probable range of peptide-MHC binding affinities were also obtained. Both the models performed well giving high accuracies when validated. These epitopes were checked for cross-reactivity with other antigens upon which it proved to be highly conservative and ideal for vaccine formulation.
Conclusions
The combination of various features and the resulting model efficiencies in turn proved that the collected features are valuable in the easy identification of the vaccine candidates. This suggests that our proposed models have more potential for conserved epitope prediction compared to other existing models trained on similar data and features. The possibility of refining the model with more set threshold values based on more parameters is an added feature that makes it more user driven. Furthermore, the uniqueness of the model due to exclusive set of Neuraminidase epitopes paves a robust way for rapid vaccine design.
Preoperative deep vein thrombosis in elderly hip fracture patients: a retrospective observational study
Authors: Tian Miao , Song Bixuan , Zhu Yanbin , Tian Yunxu , Zhang Kexin , Li Xiuting , Zhang Yahui 
Published: July 2023

Abstract
Objective: Deep vein thrombosis (DVT) is a frequent and life-threatening complication in elderly patients with hip fractures. The purpose of this study was to identify the incidence, predilection site, and associated risk factors of preoperative DVT.
Methods: This was a retrospective study of elderly patients who presented with hip fractures at our institution between January 2020 and December 2021. All patients received antithrombotic chemoprophylaxis during hospitalization. Patients were categorized into the non-DVT group and the DVT group based on ultrasonography results. The demographic data and laboratory findings at the admission of the two groups were extracted from electronic medical records. Univariate analysis and multivariate logistic regression analyses were conducted to obtain the associated risk factors for DVT.
Results: A total of 516 elderly hip fracture patients were included in the study, of whom 64 (12.4%) developed preoperative DVT. Of the 64 patients, 41 (64.1%) patients developed DVT in the injured limb, 11 (17.2%) patients had DVT in the uninjured limb, and 12 (18.8%) cases of DVT occurred on both sides. Multivariate analysis revealed that hypertension (OR, 2.5, 95%CI, 1.4 to 4.7; P=0.003), aged-adjusted Charlson comorbidity index (ACCI) ≥ 6 (OR, 1.4, 95%CI, 1.1 to 1.8; P=0.009), D-dimer at admission ≥ 2.5mg/L (OR, 3.1, 95%CI, 1.7 to 5.9; P=0.001), the time interval between injury and admission (OR, 1.1, 95%CI, 1.0 to 1.2; P=0.003), and the time interval between injury and operation (OR, 1.1, 95%CI, 1.0 to 1.1; P=0.002) were independent risk factors for preoperative DVT.
Conclusions: Elderly patients with hip fractures should be evaluated for the risk of DVT as soon as possible after admission. Providing effectively preventive measures to patients at high risk of DVT can avoid the occurrence of DVT to some extent.
Revealing Hidden Diversity and Community Dynamics of Land Snails through DNA Barcoding: Implications for Conservation and Ecological Studies
Authors: Mohammadi Sima , Ahmadzadeh Faraham 
Published: July 2023

Abstract
Land snails play a crucial role in maintaining ecosystem sustainability within their habitats. Therefore, understanding the characteristics of their communities is vital for ecological studies and the development of effective conservation strategies. In this study, we employed DNA barcoding (COI gene) to identify land snails inhabiting the Hyrcanian Forest. Furthermore, we examined the variations in their community composition along elevational gradients. Snail samples were collected from three distinct elevations in three different forest locations within the Hyrcanian area of Iran. Through our comprehensive analysis, we identified a total of 10 OTUs, which were further classified into seven families and nine genera. Remarkably, five of these genera had never been reported in the study region before. By employing statistical analyses such as ANOVA and PERMANOVA, we determined significant differences in the features of snail communities across different elevations. Interestingly, we observed a decline in OTU richness with increasing elevation; however, the maximum abundance of snails was found at higher elevations. The unique climatic conditions and spatial distribution of precipitation from lowlands to highlands, as well as from west to east, make the Hyrcanian forests an ideal case study area for understanding the dynamics of land snail communities. In summary, this study provides novel insights into the land snail communities thriving in the Hyrcanian forests. The findings from our research can contribute significantly to the development of effective conservation management strategies for forest ecosystems. By understanding the factors influencing the distribution and composition of land snail communities, we can make informed decisions to protect and preserve these valuable organisms and the balance they maintain within their habitats.
Isolation, Characterization, and Identification of Multiple Heavy Metal and Antibiotic-Resistant Bacteria From Wastewater
Authors: Hussain Muhammad Bakir , Abbas Saba , Raza Muhammad , Mehmood Noshaba , Amin Zeemal Seemab , Fatima Noor , Hamza Muhammad 
Published: July 2023

Abstract
Heavy metals are the most persistent pollutant in wastewater and cause several health and environmental hazards, contaminate soil, and reduced plant growth and productivity. Novel biotechnological approaches through inoculating bacterial strains might be adopted for the remediation of wastewater containing heavy metals. The study was conducted to reduce the toxicity of heavy metals in wastewater through inoculation of bacterial strains. The wastewater samples were collected under aseptic conditions from wastewater canals in Lahore. Bacterial strains were isolated by using nutrient agar media amended with 50 µg mL− 1 of heavy metals e.g. Zn, Cd, Co, and Hg. The multiple heavy metal-resistant bacterial strains were screened for different biochemical and morphological characteristics. Furthermore, selected multiple-heavy metals tolerant strains were evaluated resistance for multiple antibiotics resistance under in vitro conditions. A total of eighty multiple heavy tolerant bacterial strains were isolated from industrial effluents. The biomass of these multiple heavy metals-resistant bacterial strains was recorded in terms of optical density (OD). The strains with heavy maximum OD in 50 µg mL− 1 were selected for antibiotics resistance and revealed five bacterial strains were most resistant against antibiotics. The best-performing strains were identified as Klebsiella sp. strain BH49 and Salmonella sp. BH67 heaving accession numbers of MT074326 and MT074327, respectively, through 16S rRNA partial gene sequencing. Those identified strains might be used as a bioremediation agent for the efficient removal of heavy metals in contaminated wastewater.
Vibration analysis of 2D-functionally graded multiple nanobeam system by meshless method
Authors: Ahmadi Isa , Davarpanah Mahdi , Sladek Jan , Sladek Vladimir , Moradi Mohammad Naeim 
Published: July 2023

Abstract
In this study, the free vibration of two-directional functionally graded (2D-FG) multiple nanobeam system are studied by considering Winkler elastic medium between each nanobeam. Effects of small-scale are considered using the theory of nonlocal elasticity. The material properties of the FG nanobeams are considered to vary over the length and thickness of the nanobeams. The equations of motion are derived using Hamilton's principle and the first order shear deformation beam theory (FSDBT), and a meshless formulation is developed to discreteze the governing equations. Numerical results are obtained for both cases of free-chain and clamped-chain multiple nanobeam system (MNBS). In order to validate the accuracy of the meshless formulation, numerical results for free vibration of 1D-FG single nanobeam are compared with the predictions of various beam theories and solution approaches. Also, free vibration of homogeneous double nanobeam system is analyzed and good agreement is observed while comparing these results with analytical solutions. In the numerical results, the effects of nonlocal parameter, slenderness ratio, power FG indices, elastic medium stiffness, number of nanobeams, boundary conditions and concentrated mass on the free vibration of 1D- and 2D-FG single and multiple nanobeam system are investigated.