bluuebunny/crossref_metadata_2025_split huggingface dataset:
LCK and its related molecules as potential biomarkers in rheumatoid arthritis
Authors: Chen Xuemeng , Xie Li , Jiang Yi , Zhang Ronghua , Wu Wei 
Published: March 2022

Abstract
Background
Rheumatoid arthritis (RA) is a type of systemic immune disease characterized by chronic inflammatory disease of the joints. However, the etiology and underlying molecular events of RA are unclear. Here, we applied bioinformatics analysis to identify the potential biomarkers involved in RA.
Methods
The three microarray datasets (GSE1919、GSE10500 and GSE55457) were downloaded from the Gene Expression Omnibus (GEO) database. We used the R software screen the differentially expressed genes (DEGs). These DEGs shared by the three microarray datasets were further identified. Next, we carried out functional enrichment analysis using the Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG). Then, the hub genes with a relatively high number of connections to other DEGs, were identified by Cytoscape. Other bioinformatics methods are also performed, including protein–protein interaction (PPI) network analysis and construction of miRNA–hub gene networks and transcription factors (TF)–hub gene networks.
Results
A total of 115 overlapping DEGs were identified in this study. Subsequently, we constructed a PPI network encoded by these DEGs and identified 10 genes closely associated with RA – LCK, GZMA, GZMB, CD2, LAG3, IL-15, TNFRSF4, CD247, CCR5, and CCR7. Furthermore, in the miRNA–hub gene networks, we screened out has-miR-146a-5p, which is the miRNA controlling the largest number of hub genes. Finally, we found some transcription factors that closely interact with hub genes, such as FOXC1, GATA2, YY1, RUNX2, SREBF1, CEBPB, and NFIC.
Conclusions
In summary, bioinformatics analyses were used to identify DEGs to find potential biomarkers that may be associated with RA. This study successfully predicted that LCK, FOXC1 and has-mir-146a-5p can be used as potential biomarkers of RA. Our study may have potential implications for future prediction of disease progression in symptomatic RA patients, and has important significance for the pathogenesis and targeted therapy of RA.
Transcriptome and SARS-CoV-2 biological network directed analysis for better therapeutic development
Authors: Sharma Om Prakash , Sharma Ruchika , Chandil Vinay 
Published: March 2022

Abstract
Background
It has been almost 2 years since the first SARS-CoV-2 virus was first reported in the city of Wuhan. So far, 8 drugs are approved against Covid-19 by FDA, however, an active drug against multi-mutational Covid-19 is still missing. In this present study, we aim to identify the most crucial and highly correlated protein targets from the publicly available transcriptomics datasets.
Methods
Transcriptomics datasets were retrieved from Geo Omnibus (GEO). We use relevant datasets to identify the most significant and differentially expressed genes and integrated them into a Research graph called CovInt (a network of Covid-19) that includes all biological molecules associated in the network with their directionalities collected from publicly available and patient-derived multi-omics datasets from millions of unstructured and structured datasets such as publications, patents, grants, preclinical and clinical reports. CovInt utilizes powerful traversal, clustering and centrality algorithms to identify key connections in the pathophysiology of the disease and its treatments.
Results
Leveraging 3M + connections, important interactions among key 42 drugs, 962 biological processes and molecular functions, 926 pathways, 897 phenotypes, 7103 proteins, 61 tissues were identified. This narrowed interactome was explored further using PageRank, lovain detection & strongly connected components (SSC) algorithms. In our analysis 63, strongly connected communities were identified which gives us an understanding of hidden underlying mechanisms. We further explored this network to identify and triangulate the key proteins, metabolic pathways and associated risk factors that can regulate moderate to severe Covid-19 infections.
Conclusions
Our study suggests that CREB3L1, SOX2, UBR4, FLNC, ITPA, DLG3, ING4, TECR, NADH, SMAD, HUWE1, DDX17, CREBBP, RELA, HPSE, TRIM33, TNFSF13B are the key regulator proteins and involved in ER-stress, cytokine signaling, T-Cell activation, Activation of NLRP3 Inflammation by SARS-CoV-2, JAK-STAT, IL-4, IL-13 pathways, MAPK signaling pathways, Activation of NMDA receptor & postsynaptic events and TGF-β signaling pathways.
Comparison of Aurolab Aqueous Drainage Implant with Ahmed Glaucoma Valve for refractory glaucoma: a meta-analysis
Authors: Hong Mingsheng , Peng Yaling , Lai Yuan , Hong Chaoyang 
Published: March 2022

Abstract
Background: The purpose of this study was to compare the efficacy and safety of the Aurolab aqueous drainage implant（AADI）and the Ahmed glaucoma valve(AGV) for the treatment of refractory glaucoma. Methods: We comprehensively searched four databases, including PubMed, EMBASE, Web of Science, and the Cochrane Library databases, selecting the relevant studies. The continuous variables, namely, intraocular pressure reduction (IOPR) and a reduction in antiglaucoma medication (AGMR), were pooled by the weighted mean differences (WMDs), and the dichotomous outcomes, including success rates and complications were pooled by the odds ratio (ORs). Results: A total of 825 eyes from 820 patients from six studies were included. The WMDs of the IOPR between the AADI and the AGV implant were 0.58 (95 % CI:0.07 to 1.09) at 3 months, 0.44 (95 % CI: 0.11 to 0.77) at 6 months, 2.20 (95 % CI: 0.63 to 3.77) at 12 months, and 3.24 (95 % CI: 1.73 to 4.75) at follow-up endpoint. Significant difference was detected between the two groups at any point in time. The WMDs of the AGMR between the AADI and the AGV implant were 0.87(95 % CI: 0.61 to 1.13) at 6 months, 1.04(95 % CI: 0.66 to 1.42) at 12 months, and 0.93 (95 % CI: 0.52 to 1.34) at the follow-up endpoint , the differences reached statistical significance at any point in time. The pooled ORs comparing the AADI with the AGV were 3.68(95 % CI: 2.58 to 5.25) for the complete success rate and 1.72(95 % CI: 1.24 to 2.39) for qualified success rate, significant difference was detected between the two groups. There were no significant differences between the AADI the AGV implant on the rates of adverse events. Conclusions: The AADI is more effective in both its surgical success rate and reducing IOP and AGM. And the two implants may have comparable incidences of adverse events.
Influence of receptor status and proliferation index in skeletal metastases of breast carcinoma on pathological fracture occurrence
Authors: Rajkovic Stanislav , Simic Ljubica , Djuricic Goran , Dundjerovic Dusko , Miceta Lazar , Milicic Biljana , Sopta Jelena 
Published: March 2022

Abstract
Purpose. Bones affected with metastatic breast carcinoma are prone to pathological fracture, impairing quality of life and survival rate. This study examined estrogen, progesterone, and HER2 receptors status, and Ki-67 index in skeletal metastases of breast carcinoma and their potential influence on pathological fracture occurrence.Methods. The study included 152 samples of skeletal metastasis of breast carcinoma, each obtained from an individual patient. Allred’s score was used for immunohistochemical interpretation. Clinical and radiological data were gathered from each patient`s history of the disease.Results. Femur stood out as an independent risk factor – it had a nine times higher chance for pathological fracture than other bones. Estrogen receptors, HER2, and Ki-67 status had no statistical significance for pathological fracture occurrence. Progesterone receptors showed significance for fracture development. The probability of fracture in progesterone receptor positive metastases was 68,1%, risk increasing with the rise of positive cells percentage, regardless of the expression intensity.Conclusion. Receptor status is important for skeletal metastases of breast carcinoma and can be used in clinical decision-making for systemic therapy and surgical treatment in fracture prevention.
The role of irradiance in controlling coralline algal calcification
Authors: Krieger Erik C. , Nelson Wendy A. , Grand Johan , Ru Eric Le , Bury Sarah J. , Cossais Amelie , Davy Simon K. , Cornwall Christopher E. 
Published: March 2022

Abstract
Coralline algae are an essential element of benthic ecosystems throughout the ocean’s photic zone. Yet, the role of light in shaping the physiology of coralline algae from cold-water, low-light habitats is poorly understood. Here, we assess the calcification physiology of five cool-temperate coralline algae in response to different irradiances over three months. We show that in contrast to current models focused on warmer water species, previously observed enhancement of calcification rates by photosynthesis is largely limited to lower irradiances, and that the removal of CO2 from the calcifying fluid (CF) is not the underlying mechanism of this enhancement. Instead, this likely occurs via two processes: 1) increased ion pumping rates to elevate the calcium carbonate saturation state in the CF; and 2) a higher daytime pH in the diffusion boundary layer that raises pHCF. However, as irradiance increases, ion pumping becomes increasingly saturated limiting further enhancements. Our results also suggest the existence of two calcification strategies in coralline algae and indicate that magnesium incorporation is determined by the internal magnesium to calcium ratio [Mg]CF/[Ca]CF. This study adds to our mechanistic understanding of calcification in coralline and fills in much needed knowledge about the role of light in controlling their physiology.
Regional Brain Oxygen Saturation: There is also Life Beyond the Brain
Authors: J.L. Guerrero Orriach , A. Ramirez Fernandez 
Published: March 2022

Abstract:
Some procedures, such as cardiovascular surgery, may compromise brain perfusion and require careful
management to preserve the integrity of the central nervous system. In this setting, regional cerebral oxygen
saturation [rSO2] emerges as an alternative, minimally invasive, monitoring system. The mechanism by which
regional oxygen is measured is based on the refraction and absorption of a signal with a specific wavelength.
Diagnostic and therapeutic algorithms for these settings would allow for a more rational use of goal-directed
therapies that reduce morbidity and mortality in these patients.
An Arduino System for Collecting the Garbage in A Segregated Manner
Authors: Mathur Sandeep 
Published: March 2022

Abstract:
Garbage collection and segregation are among the biggest problems in today's world
across the globe. This work proposed a System that helps clean waste and eases people in daily life.
This system, proposed by Swachh Bharat Abhiyan, is an intelligent waste segregator bin embedded
with many applications. The system relies on an "Ultrasonic sensor, Calorimetric sensor, LED, Arduino,
programming language and some hardware used." The invention is quite innovative and advantageous.
A gist of the system mainly uses two divided sections for the segregation of bio and
non-biodegradable wastes. Arduino has been used to save the coding of the system. Hence, the system
helps us maintain and reduce garbage levels and can be proven a blessing in the waste management.
The patent office of India has patented the proposed innovation, application number
202111006039, 12th Feb 2021, and copyright has been granted from the copyright office, India, on
the design of the proposal having registration number L-104358/2021 dated 10th June 2021.
Virtual Prehabilitation in Patients With Cancer Undergoing Surgery During the COVID-19 Pandemic: Protocol for a Prospective Feasibility Study
Authors: Lambert Genevieve , Drummond Kenneth , Tahasildar Bhagya , Carli Francesco 
Published: March 2022

Background
Since the beginning of the COVID-19 pandemic, preoperative care, also termed prehabilitation, has become increasingly relevant due to the decreasing functional and psychosocial health of patients with cancer, which is a result of the pandemic restrictions. Concurrently, access to telehealth has improved; telehealth comprises all remote care delivery facilitated by information technologies (ie, virtually).

Objective
The aim of this protocol is to describe the rationale and methodology for a major trial investigating the feasibility and safety of multimodal virtual prehabilitation services (ie, teleprehabilitation).

Methods
This single-arm feasibility trial aims to recruit 100 patients with cancer to receive teleprehabilitation throughout their preoperative period. The inclusion criteria are as follows: (1) 18 years of age or older, (2) scheduled for elective cancer surgery and referred by a surgeon, (3) medically cleared by the referring physician to engage in physical activity, and (4) have a good comprehension of the English or French language. Feasibility will be assessed by documenting recruitment, adherence, and retention rates, in addition to patients’ motives for not participating in the trial, low participation, or discontinuation. The secondary outcome of safety will be assessed by reporting program-related adverse events.

Results
The Montreal General Hospital Foundation funded the project in August 2020. The protocol was then approved by the Research Ethics Board of the McGill University Health Centre in January 2021 (ID No. 2021-6730). The first patient was recruited in March 2021, and recruitment is expected to end in September 2022. As of March 2022, 36 patients have been recruited, including 24 who have completed their participation. No adverse events have been reported. Data collection is expected to conclude in November 2022. Data analysis will be performed, and the results will be published by the beginning of 2023.

Conclusions
This trial will provide guidance on the use of telehealth in the administration of prehabilitation services. The trial will provide a large amount of information that will respond to gaps in the literature, as there are minimal reports on the use of telehealth rehabilitation and prehabilitation services among elderly populations and in acute contexts, such as the preoperative period.

Trial Registration
ClinicalTrials.gov NCT0479956; https://clinicaltrials.gov/ct2/show/NCT04799561

International Registered Report Identifier (IRRID)
DERR1-10.2196/29936
Exploring Human-Data Interaction in Clinical Decision-making Using Scenarios: Co-design Study
Authors: Tendedez Helena , Ferrario Maria-Angela , McNaney Roisin , Gradinar Adrian 
Published: March 2022

Background
When caring for patients with chronic conditions such as chronic obstructive pulmonary disease (COPD), health care professionals (HCPs) rely on multiple data sources to make decisions. Collating and visualizing these data, for example, on clinical dashboards, holds the potential to support timely and informed decision-making. Most studies on data-supported decision-making (DSDM) technologies for health care have focused on their technical feasibility or quantitative effectiveness. Although these studies are an important contribution to the literature, they do not further our limited understanding of how HCPs engage with these technologies and how they can be designed to support specific contexts of use. To advance our knowledge in this area, we must work with HCPs to explore this space and the real-world complexities of health care work and service structures.

Objective
This study aimed to qualitatively explore how DSDM technologies could support HCPs in their decision-making regarding COPD care. We created a scenario-based research tool called Respire, which visualizes HCPs’ data needs about their patients with COPD and services. We used Respire with HCPs to uncover rich and nuanced findings about human-data interaction in this context, focusing on the real-world challenges that HCPs face when carrying out their work and making decisions.

Methods
We engaged 9 respiratory HCPs from 2 collaborating health care organizations to design Respire. We then used Respire as a tool to investigate human-data interaction in the context of decision-making about COPD care. The study followed a co-design approach that had 3 stages and spanned 2 years. The first stage involved 5 workshops with HCPs to identify data interaction scenarios that would support their work. The second stage involved creating Respire, an interactive scenario-based web app that visualizes HCPs’ data needs, incorporating feedback from HCPs. The final stage involved 11 one-to-one sessions with HCPs to use Respire, focusing on how they envisaged that it could support their work and decisions about care.

Results
We found that HCPs trust data differently depending on where it came from and who recorded it, sporadic and subjective data generated by patients have value but create challenges for decision-making, and HCPs require support in interpreting and responding to new data and its use cases.

Conclusions
Our study uncovered important lessons for the design of DSDM technologies to support health care contexts. We show that although DSDM technologies have the potential to support patient care and health care delivery, important sociotechnical and human-data interaction challenges influence the design and deployment of these technologies. Exploring these considerations during the design process can ensure that DSDM technologies are designed with a holistic view of how decision-making and engagement with data occur in health care contexts.
Locating Youth Exposed to Parental Justice Involvement in the Electronic Health Record: Development of a Natural Language Processing Model
Authors: Boch Samantha , Hussain Syed-Amad , Bambach Sven , DeShetler Cameron , Chisolm Deena , Linwood Simon 
Published: March 2022

Background
Parental justice involvement (eg, prison, jail, parole, or probation) is an unfortunately common and disruptive household adversity for many US youths, disproportionately affecting families of color and rural families. Data on this adversity has not been captured routinely in pediatric health care settings, and if it is, it is not discrete nor able to be readily analyzed for purposes of research.

Objective
In this study, we outline our process training a state-of-the-art natural language processing model using unstructured clinician notes of one large pediatric health system to identify patients who have experienced a justice-involved parent.

Methods
Using the electronic health record database of a large Midwestern pediatric hospital-based institution from 2011-2019, we located clinician notes (of any type and written by any type of provider) that were likely to contain such evidence of family justice involvement via a justice-keyword search (eg, prison and jail). To train and validate the model, we used a labeled data set of 7500 clinician notes identifying whether the patient was ever exposed to parental justice involvement. We calculated the precision and recall of the model and compared those rates to the keyword search.

Results
The development of the machine learning model increased the precision (positive predictive value) of locating children affected by parental justice involvement in the electronic health record from 61% (a simple keyword search) to 92%.

Conclusions
The use of machine learning may be a feasible approach to addressing the gaps in our understanding of the health and health services of underrepresented youth who encounter childhood adversities not routinely captured—particularly for children of justice-involved parents.
Multifaceted Intervention to Increase the Use of Home Dialysis
Authors: Manns Braden J. , Garg Amit X. , Sood Manish M. , Ferguson Thomas , Kim S. Joseph , Naimark David , Nesrallah Gihad E. , Soroka Steven D. , Beaulieu Monica , Dixon Stephanie N. , Alam Ahsan , Allu Selina , Tangri Navdeep 
Published: March 2022

Background and objectives
Home dialysis therapies (peritoneal and home hemodialysis) are less expensive and provide similar outcomes to in-center hemodialysis, but they are underutilized in most health systems. Given this, we designed a multifaceted intervention to increase the use of home dialysis. In this study, our objective was to evaluate the effect of this intervention on home dialysis use in CKD clinics across Canada.

Design, setting, participants, & measurements
We conducted a cluster randomized controlled trial in 55 CKD clinic clusters in nine provinces in Canada between October 2014 and November 2015. Participants included all adult patients who initiated dialysis in the year following the intervention. We evaluated the implementation of a four-component intervention, which included phone surveys from a knowledge translation broker, a 1-year center-specific audit/feedback on home dialysis use, delivery of an educational package (including tools aimed at both providers and patients), and an academic detailing visit. The primary outcome was the proportion of patients using home dialysis at 180 days after dialysis initiation.

Results
A total of 55 clinics were randomized (27 in the intervention and 28 in the control), with 5312 patients initiating dialysis in the 1-year follow-up period. In the primary analysis, there was no difference in the use of home dialysis at 180 days in the intervention and control clusters (absolute risk difference, 4%; 95% confidence interval, −2% to 10%). Using a difference-in-difference comparison, the use of home dialysis at 180 days was similar before and after implementation of the intervention (difference of 0% in intervention clinics; 95% confidence interval, −2% to 3%; difference of 0.8% in control clinics; 95% confidence interval, −1% to 3%; P=0.84).

Conclusions
A multifaceted intervention did not increase the use of home dialysis in adults initiating dialysis.

Clinical Trial registry name and registration number:
A Cluster Randomized Trial to Assess the Impact of Patient and Provider Education on Use of Home Dialysis, NCT02202018
An Overview Of Phytochemical Identification Of Secondary Metabolites Ofmedicinal Plant Dactylorhiza Hatagirea
Authors: Vishwakarma Shivani , Karole Dr. Sarita 
Published: March 2022

Plants are a valuable source of new natural products. Despite the availability of different approaches for the discovery of therapeutically, natural products still remain as one of the best reservoirs of new structural types. The standardized extracts of plants, provide unlimited opportunities for new drug discoveries because of the unmatched availability of chemical diversity. According to the World Health Organization (WHO), more than 80% of the world’s population relies on traditional medicine for their primary healthcare needs.HPLC is a versatile, robust, and widely used technique for the isolation of natural products, HPLC is a chromatographic technique that can separate a mixture of compounds and is used in phytochemical and analytical chemistry to identify, quantify and purify the individual components of the mixture. Currently, this technique is gaining popularity among various analytical techniques as the main choice for fingerprinting study for the quality control of herbal plants. Natural products are frequently isolated following the evaluation of a relatively crude extract in a biological assay in order to fully characterize its properties. Early studies showed that Dactylorhizahatagirea root are rich source of phytochemicals including flavonoids, phenolics, alkaloids. Therefore this study was conducted with the aim to investigate phytoconstituents present in Dactylorhizahatagirea root and assessment of their antioxidant characteristics.