bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteomics for heart failure risk stratification: a systematic review
Authors: Kuku Kayode O. , Oyetoro Rebecca , Hashemian Maryam , Livinski Alicia A. , Shearer Joseph J. , Joo Jungnam , Psaty Bruce M. , Levy Daniel , Ganz Peter , Roger Véronique L. 
Published: January 2024

Abstract
Background
Heart failure (HF) is a complex clinical syndrome with persistently high mortality. High-throughput proteomic technologies offer new opportunities to improve HF risk stratification, but their contribution remains to be clearly defined. We aimed to systematically review prognostic studies using high-throughput proteomics to identify protein signatures associated with HF mortality.

Methods
We searched four databases and two clinical trial registries for articles published from 2012 to 2023. HF proteomics studies measuring high numbers of proteins using aptamer or antibody-based affinity platforms on human plasma or serum with outcomes of all-cause or cardiovascular death were included. Two reviewers independently screened articles, extracted data, and assessed the risk of bias. A third reviewer resolved conflicts. We assessed the risk of bias using the Risk Of Bias In Non-randomized Studies—of Exposure tool.

Results
Out of 5131 unique articles identified, nine articles were included in the review. The nine studies were observational; three used the aptamer platform, and six used the antibody platform. We found considerable heterogeneity across studies in measurement panels, HF definitions, ejection fraction categorization, follow-up duration, and outcome definitions, and a lack of risk estimates for most protein associations. Hence, we proceeded with a systematic review rather than a meta-analysis. In two comparable aptamer studies in patients with HF with reduced ejection fraction, 21 proteins were identified in common for the association with all-cause death. Among these, one protein, WAP four-disulfide core domain protein 2 was also reported in an antibody study on HFrEF and for the association with CV death. We proposed standardized reporting criteria to facilitate the interpretation of future studies.

Conclusions
In this systematic review of nine studies evaluating the association of proteomics with mortality in HF, we identified a limited number of proteins common across several studies. Heterogeneity across studies compromised drawing broad inferences, underscoring the importance of standardized approaches to reporting.
The role of moesin in diagnosing and assessing severity of lymphangioleiomyomatosis
Authors: Song Xixi , Cai Hui , Peng Wenjun , Chen Ke , Abuduxukuer Zilinuer , Zeng Yingying , Zhu Guiping , Lu Chong , Chen Yu , Wang Jian , Ye Ling , Jin Meiling 
Published: January 2024

Abstract
Background
Lymphangioleiomyomatosis (LAM) is a rare disease which is easily misdiagnosed. Vascular endothelial growth factor D (VEGF-D), as the most common biomarker, however, is not so perfect for the diagnosis and severity assessment of LAM.

Materials and methods
The isobaric tags for relative and absolute quantitation (iTRAQ)-based method was used to identify a cytoskeleton protein, moesin. 84 patients with LAM, 44 patients with other cystic lung diseases (OCLDs), and 37 healthy control subjects were recruited for collecting blood samples and clinical data. The levels of moesin in serum were evaluated by ELISA. The relationships of moesin with lymphatic involvement, lung function, and treatment decision were explored in patients with LAM.

Results
The candidate protein moesin was identified by the proteomics-based bioinformatic analysis. The serum levels of moesin were higher in patients with LAM [219.0 (118.7–260.5) pg/mL] than in patients with OCLDs (125.8 ± 59.9 pg/mL, P < 0.0001) and healthy women [49.6 (35.5–78.9) ng/mL, P < 0.0001]. Moesin had an area under the receiver operator characteristic curve (AUC) of 0.929 for predicting LAM diagnosis compared to healthy women (sensitivity 81.0%, specificity 94.6%). The combination of moesin and VEGF-D made a better prediction in differentiating LAM from OCLDs than moesin or VEGF-D alone. Moreover, elevated levels of moesin were related to lymphatic involvement in patients with LAM. Moesin was found negatively correlated with FEV1%pred, FEV1/FVC, and DLCO%pred (P = 0.0181, r = − 0.3398; P = 0.0067, r = − 0.3863; P = 0.0010, r = − 0.4744). A composite score combining moesin and VEGF-D improved prediction for sirolimus treatment, compared with each biomarker alone.

Conclusion
Higher levels of moesin in serum may indicate impaired lung function and lymphatic involvement in patients with LAM, suggest a more serious condition, and provide clinical guidance for sirolimus treatment.
Impacts for health and care workers of Covid-19 and other public health emergencies of international concern: living systematic review, meta-analysis and policy recommendations
Authors: Fronteira Inês , Mathews Verona , dos Santos Ranailla Lima Bandeira , Matsumoto Karen , Amde Woldekidan , Pereira Alessandra , de Oliveira Ana Paula Cavalcante , Craveiro Isabel , Chança Raphael , Boniol Mathieu , Ferrinho Paulo , Poz Mario Roberto Dal 
Published: January 2024

Abstract
Background
Health and care workers (HCW) faced the double burden of the SARS-CoV-2 pandemic: as members of a society affected by a public health emergency and as HWC who experienced fear of becoming infected and of infecting others, stigma, violence, increased workloads, changes in scope of practice, among others. To understand the short and long-term impacts in terms of the COVID-19 pandemic and other public health emergencies of international concern (PHEICs) on HCW and relevant interventions to address them, we designed and conducted a living systematic review (LSR).

Methods
We reviewed literature retrieved from MEDLINE—PubMed, Embase, SCOPUS, LILACS, the World Health Organization COVID-19 database, the ClinicalTrials.org and the ILO database, published from January 2000 until December 2021. We included quantitative observational studies, experimental studies, quasi-experimental, mixed methods or qualitative studies; addressing mental, physical health and well-being and quality of life. The review targeted HCW; and interventions and exposures, implemented during the COVID-19 pandemic or other PHEICs. To assess the risk of bias of included studies, we used the Johanna Briggs Institute (JBI) Critical Appraisal Tools. Data were qualitatively synthetized using meta-aggregation and meta-analysis was performed to estimate pooled prevalence of some of the outcomes.

Results
The 1013 studies included in the review were mainly quantitative research, cross-sectional, with medium risk of bias/quality, addressing at least one of the following: mental health issue, violence, physical health and well-being, and quality of life. Additionally, interventions to address short- and long-term impact of PHEICs on HCW included in the review, although scarce, were mainly behavioral and individual oriented, aimed at improving mental health through the development of individual interventions. A lack of interventions addressing organizational or systemic bottlenecks was noted.

Discussion
PHEICs impacted the mental and physical health of HCW with the greatest toll on mental health. The impact PHEICs are intricate and complex. The review revealed the consequences for health and care service delivery, with increased unplanned absenteeism, service disruption and occupation turnover that subvert the capacity to answer to the PHEICs, specifically challenging the resilience of health systems.
Association of the pathomics-collagen signature with lymph node metastasis in colorectal cancer: a retrospective multicenter study
Authors: Jiang Wei , Wang Huaiming , Dong Xiaoyu , Zhao Yandong , Long Chenyan , Chen Dexin , Yan Botao , Cheng Jiaxin , Lin Zexi , Zhuo Shuangmu , Wang Hui , Yan Jun 
Published: January 2024

Abstract
Background
Lymph node metastasis (LNM) is a prognostic biomarker and affects therapeutic selection in colorectal cancer (CRC). Current evaluation methods are not adequate for estimating LNM in CRC. H&E images contain much pathological information, and collagen also affects the biological behavior of tumor cells. Hence, the objective of the study is to investigate whether a fully quantitative pathomics-collagen signature (PCS) in the tumor microenvironment can be used to predict LNM.

Methods
Patients with histologically confirmed stage I-III CRC who underwent radical surgery were included in the training cohort (n = 329), the internal validation cohort (n = 329), and the external validation cohort (n = 315). Fully quantitative pathomics features and collagen features were extracted from digital H&E images and multiphoton images of specimens, respectively. LASSO regression was utilized to develop the PCS. Then, a PCS-nomogram was constructed incorporating the PCS and clinicopathological predictors for estimating LNM in the training cohort. The performance of the PCS-nomogram was evaluated via calibration, discrimination, and clinical usefulness. Furthermore, the PCS-nomogram was tested in internal and external validation cohorts.

Results
By LASSO regression, the PCS was developed based on 11 pathomics and 9 collagen features. A significant association was found between the PCS and LNM in the three cohorts (P < 0.001). Then, the PCS-nomogram based on PCS, preoperative CEA level, lymphadenectasis on CT, venous emboli and/or lymphatic invasion and/or perineural invasion (VELIPI), and pT stage achieved AUROCs of 0.939, 0.895, and 0.893 in the three cohorts. The calibration curves identified good agreement between the nomogram-predicted and actual outcomes. Decision curve analysis indicated that the PCS-nomogram was clinically useful. Moreover, the PCS was still an independent predictor of LNM at station Nos. 1, 2, and 3. The PCS nomogram displayed AUROCs of 0.849–0.939 for the training cohort, 0.837–0.902 for the internal validation cohort, and 0.851–0.895 for the external validation cohorts in the three nodal stations.

Conclusions
This study proposed that PCS integrating pathomics and collagen features was significantly associated with LNM, and the PCS-nomogram has the potential to be a useful tool for predicting individual LNM in CRC patients.
New insights into mesoderm and endoderm development, and the nature of the onychophoran blastopore
Authors: Janssen Ralf , Budd Graham E. 
Published: January 2024

AbstractBackgroundEarly during onychophoran development and prior to the formation of the germ band, a posterior tissue thickening forms the posterior pit. Anterior to this thickening forms a groove, the embryonic slit, that marks the anterior–posterior orientation of the developing embryo. This slit is by some authors considered the blastopore, and thus the origin of the endoderm, while others argue that the posterior pit represents the blastopore. This controversy is of evolutionary significance because if the slit represents the blastopore, then this would support the amphistomy hypothesis that suggests that a slit-like blastopore in the bilaterian ancestor evolved into protostomy and deuterostomy.ResultsIn this paper, we summarize our current knowledge about endoderm and mesoderm development in onychophorans and provide additional data on early endoderm- and mesoderm-determining marker genes such asBlimp,Mox, and the T-box genes.ConclusionWe come to the conclusion that the endoderm of onychophorans forms prior to the development of the embryonic slit, and thus that the slit is not the primary origin of the endoderm. It is thus unlikely that the embryonic slit represents the blastopore. We suggest instead that the posterior pit indeed represents the lips of the blastopore, and that the embryonic slit (and surrounding tissue) represents a morphologically superficial archenteron-like structure. We conclude further that both endoderm and mesoderm development are under control of conserved gene regulatory networks, and that many of the features found in arthropods including the modelDrosophila melanogasterare likely derived.
Quercetin inhibits SARS-CoV-2 infection and prevents syncytium formation by cells co-expressing the viral spike protein and human ACE2
Authors: Roy Annie V. , Chan Michael , Banadyga Logan , He Shihua , Zhu Wenjun , Chrétien Michel , Mbikay Majambu 
Published: January 2024

Abstract
Background
Several in silico studies have determined that quercetin, a plant flavonol, could bind with strong affinity and low free energy to SARS-CoV-2 proteins involved in viral entry and replication, suggesting it could block infection of human cells by the virus. In the present study, we examined the ex vivo ability of quercetin to inhibit of SARS-CoV-2 replication and explored the mechanisms of this inhibition.

Methods
Green monkey kidney Vero E6 cells and in human colon carcinoma Caco-2 cells were infected with SARS-CoV-2 and incubated in presence of quercetin; the amount of replicated viral RNA was measured in spent media by RT-qPCR. Since the formation of syncytia is a mechanism of SARS-CoV-2 propagation, a syncytialization model was set up using human embryonic kidney HEK293 co-expressing SARS-CoV-2 Spike (S) protein and human angiotensin converting enzyme 2 (ACE2), [HEK293(S + ACE2) cells], to assess the effect of quercetin on this cytopathic event by microscopic imaging and protein immunoblotting.

Results
Quercetin inhibited SARS-CoV-2 replication in Vero E6 cells and Caco-2 cells in a concentration-dependent manner with a half inhibitory concentration (IC50) of 166.6 and 145.2 µM, respectively. It also inhibited syncytialization of HEK293(S + ACE2) cells with an IC50 of 156.7 µM. Spike and ACE2 co-expression was associated with decreased expression, increased proteolytic processing of the S protein, and diminished production of the fusogenic S2’ fragment of S. Furin, a proposed protease for this processing, was inhibited by quercetin in vitro with an IC50 of 116 µM.

Conclusion
These findings suggest that at low 3-digit micromolar concentrations of quercetin could impair SARS-CoV-2 infection of human cells partly by blocking the fusion process that promotes its propagation.
Collagen in the central nervous system: contributions to neurodegeneration and promise as a therapeutic target
Authors: Wareham Lauren K. , Baratta Robert O. , Del Buono Brian J. , Schlumpf Eric , Calkins David J. 
Published: January 2024

AbstractThe extracellular matrix is a richly bioactive composition of substrates that provides biophysical stability, facilitates intercellular signaling, and both reflects and governs the physiological status of the local microenvironment. The matrix in the central nervous system (CNS) is far from simply an inert scaffold for mechanical support, instead conducting an active role in homeostasis and providing broad capacity for adaptation and remodeling in response to stress that otherwise would challenge equilibrium between neuronal, glial, and vascular elements. A major constituent is collagen, whose characteristic triple helical structure renders mechanical and biochemical stability to enable bidirectional crosstalk between matrix and resident cells. Multiple members of the collagen superfamily are critical to neuronal maturation and circuit formation, axon guidance, and synaptogenesis in the brain. In mature tissue, collagen interacts with other fibrous proteins and glycoproteins to sustain a three-dimensional medium through which complex networks of cells can communicate. While critical for matrix scaffolding, collagen in the CNS is also highly dynamic, with multiple binding sites for partnering matrix proteins, cell-surface receptors, and other ligands. These interactions are emerging as critical mediators of CNS disease and injury, particularly regarding changes in matrix stiffness, astrocyte recruitment and reactivity, and pro-inflammatory signaling in local microenvironments. Changes in the structure and/or deposition of collagen impact cellular signaling and tissue biomechanics in the brain, which in turn can alter cellular responses including antigenicity, angiogenesis, gliosis, and recruitment of immune-related cells. These factors, each involving matrix collagen, contribute to the limited capacity for regeneration of CNS tissue. Emerging therapeutics that attempt to rebuild the matrix using peptide fragments, including collagen-enriched scaffolds and mimetics, hold great potential to promote neural repair and regeneration. Recent evidence from our group and others indicates that repairing protease-degraded collagen helices with mimetic peptides helps restore CNS tissue and promote neuronal survival in a broad spectrum of degenerative conditions. Restoration likely involves bolstering matrix stiffness to reduce the potential for astrocyte reactivity and local inflammation as well as repairing inhibitory binding sites for immune-signaling ligands. Facilitating repair rather than endogenous replacement of collagen degraded by disease or injury may represent the next frontier in developing therapies based on protection, repair, and regeneration of neurons in the central nervous system.
Visual and auditory attention defects in children with intermittent exotropia
Authors: Wei Cong , Yang Ding-Ping , Yang Yan , Yang Wen-Han , Lu Ya-Mei , Yu Xin-Ping , Chang Shuai 
Published: January 2024

Abstract
Background
Previous studies have shown that children with intermittent exotropia (IXT) have a higher rate of psychiatric abnormalities as they grow up, such as attention deficit. This study explored visual and hearing attention among children with IXT, and evaluated its association with clinical characteristics and cognitive development.

Methods
Forty-nine children with a diagnosis of IXT and 29 children with traditional development were recruited. The Integrated Visual and Auditory Continuous Performance Test (IVA-CPT) was used to measure the subjects’ full-scale response control quotient (FSRCQ), full-scale attention quotient (FSAQ), auditory response control quotient (ARCQ), auditory attention quotient (AAQ), visual response control quotient (VRCQ), and visual attention quotient (VAQ). The Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) was used to assess their cognitive function. The differences between the scores of children with IXT and normal controls were analyzed.

Results
The results showed that the FSRCQ, FSAQ, ARCQ, AAQ, VRCQ, and VAQ of children with IXT were all lower than those of normal controls with the same age (P < 0.05). The level of attention was significantly correlated with the age of strabismus onset (P < 0.05), but not with the degree of strabismus, stereopsis, or fusion control score. In addition, audiovisual attention was correlated significantly with their cognitive development level. The random forest classifier prediction model showed that age of strabismus onset was an important predictor of attention.

Conclusion
Children with IXT have lower visual and auditory attention and control than their peers, and the age of onset of strabismus may be a major factor.
The impact of obesity on different glucose tolerance status with incident cardiovascular disease and mortality events over 15 years of follow-up: a pooled cohort analysis
Authors: Asgari Samaneh , Molavizadeh Danial , soltani Kiarash , Khalili Davood , Azizi Fereidoun , Hadaegh Farzad 
Published: January 2024

Abstract
Background
The effect of obesity in different glucose tolerance statuses i.e. normoglycemia (NGT), pre-diabetes, and type 2 diabetes (T2DM) on cardiovascular disease (CVD) and mortality has been an area of ongoing debate and uncertainty. In the present study, we aimed to examine the impact of being obese, whether general or central separately, in comparison with non-obese in different glucose tolerance statuses on the above outcomes.

Methods
The study population included 18,184 participants aged 30–60 years (9927 women) from three longitudinal studies, including Atherosclerosis Risk in Communities, Multi-Ethnic Study of Atherosclerosis, and Tehran Lipid and Glucose Study. Glucose tolerance status was defined as NGT (fasting plasma glucose < 5.55 mmol/L), pre-diabetes (5.55–7.00 mmol/L), and T2DM (≥ 7 mmol/L or taking any medication for diabetes). Moreover, general and central obesity were defined based on body mass index and waist circumference (WC), respectively. Multivariable stratified Cox regression analysis was used to estimate hazard ratios (HRs (95% CI)) for CVD and mortality events.

Results
During a 16-year follow-up, 2733 CVD events, 1101 CV mortality, and 3678 all-cause mortality events were recorded. We observed that being generally obese in comparison with non-obese increased the risk of CV and all-cause mortality in all glucose tolerance statuses; while considering CVD events, only among individuals with T2DM, the presence of general obesity was associated with marginally significant higher risk [1.19 (0.98–1.43); p-value = 0.07]. Regarding central adiposity, multivariate analysis revealed that elevated WC in NGT participants is associated with incident CVD [1.27(1.12–1.46)] and all-cause mortality [1.13(1.00–1.28)]. Moreover, central adiposity increased the risk of CV mortality in pre-diabetes individuals [1.47 (1.11–1.95)].

Conclusion
Findings from this pooled prospective cohort studies provide evidence that general obesity shows an unfavorable association with CV and all-cause mortality among the general population irrespective of their glucose tolerance statusThe findings imply that it's important to take into account the requirement and magnitude of weight reduction in people who are obese when offering guidance.
A novel comparative study of NNAR approach with linear stochastic time series models in predicting tennis player's performance
Authors: Almarashi Abdullah M. , Daniyal Muhammad , Jamal Farrukh 
Published: January 2024

Abstract
Background
Prediction models have gained immense importance in various fields for decision-making purposes. In the context of tennis, relying solely on the probability of winning a single match may not be sufficient for predicting a player's future performance or ranking. The performance of a tennis player is influenced by the timing of their matches throughout the year, necessitating the incorporation of time as a crucial factor. This study aims to focus on prediction models for performance indicators that can assist both tennis players and sports analysts in forecasting player standings in future matches.

Methodology
To predict player performance, this study employs a dynamic technique that analyzes the structure of performance using both linear and nonlinear time series models. A novel approach has been taken, comparing the performance of the non-linear Neural Network Auto-Regressive (NNAR) model with conventional stochastic linear and nonlinear models such as Auto-Regressive Integrated Moving Average (ARIMA), Exponential Smoothing (ETS), and TBATS (Trigonometric Seasonal Decomposition Time Series).

Results
The study finds that the NNAR model outperforms all other competing models based on lower values of Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). This superiority in performance metrics suggests that the NNAR model is the most appropriate approach for predicting player performance in tennis. Additionally, the prediction results obtained from the NNAR model demonstrate narrow 95% Confidence Intervals, indicating higher accuracy and reliability in the forecasts.

Conclusion
In conclusion, this study highlights the significance of incorporating time as a factor when predicting player performance in tennis. It emphasizes the potential benefits of using the NNAR model for forecasting future player standings in matches. The findings suggest that the NNAR model is a recommended approach compared to conventional models like ARIMA, ETS, and TBATS. By considering time as a crucial factor and employing the NNAR model, both tennis players and sports analysts can make more accurate predictions about player performance.