bluuebunny/crossref_metadata_2025_split huggingface dataset:
A revision of the family Cucurbitariaceae with additional new taxa from forest trees in Iran
Authors: Eisvand Payam , Mehrabi-Koushki Mehdi , Crous Pedro 
Published: December 2023

Abstract
The family Cucurbitariaceae is rich in species diversity, and has a wide host range and geographic distribution. In this study, we identified 12 Cucurbitariaceae isolates which were obtained from disease symptoms in two forest trees in Khuzestan province, Iran. In addition, this family is reassessed using phylogenetic analyses based on DNA sequences from five nuclear regions (ITS, LSU, tub2, tef1a and rpb2). The phylogenetic analyses showed that the present isolates represent one new genus, Nothocucurbitaria, and two new species, Nothocucurbitaria izehica and Parafenestella quercicola which are described and illustrated. Furthermore, the genus Allocucurbitaria is emended to accommodate species of Seltsamia, that grouped with the type species of Allocucurbitaria. Parafenestella pittospori and A. prunicola are recombined into the genera Neocucurbitaria and Nothocucurbitaria, respectively. Comparative analysis of single-locus trees revealed that the tub2 and tef1a can distinguish most genera and species in Cucurbitariaceae, while the ITS and LSU phylogenies show low resolution at both generic and species level. The best single locus marker, rpb2, was able to distinguish all generic and most species lineages in Cucurbitariaceae.
Therapeutic effect of tranexamic acid on traumatic brain injury: a systematic review and meta-analysis
Authors: Wu Jianxiang , Zhong Hai , Chen Wei , Zheng Jianchun 
Published: December 2023

Abstract
Objective
Tranexamic acid exhibits certain therapeutic efficacy in the treatment of traumatic brain injury. The purpose of this systematic review and meta-analysis was to assess the safety and efficacy of TXA in patients with TBI.
Methods
The databases, namely PubMed, Embase, Web of Science, and Cochrane Library databases, were systematically searched to collect randomized controlled trials (RCTs) investigating the efficacy of tranexamic acid for traumatic brain injury from January 2000 to November 2023.
Results
The present meta-analysis encompasses six RCTs. Compared with placebo group in patients with traumatic brain injury, tranexamic acid results in remarkably reduced mortality (P < 0.001), hemorrhage growth (P = 0.03), the volume of hemorrhage growth (P = 0.003), but has no important impact on neurosurgery (P = 0.86), seizures (P = 0.19) and pulmonary embolism (P = 0.63).
Conclusion
The administration of tranexamic acid is significantly associated with reduced mortality and hemorrhage growth in patients suffering from traumatic brain injury, while the incidence of neurosurgery requirement, seizures, and pulmonary embolism remains comparable to that observed with placebo.
The role of fines in espresso extraction dynamics
Authors: Smrke Samo , Eiermann André , Yeretzian Chahan 
Published: December 2023

Abstract
The impact of particle size distribution of coffee grounds on espresso extraction was explored. Finely ground coffee for espresso has a characteristically bimodal particle size distribution. For a given median grind size, different grinding technologies can yield a different share of fines (particles < 100 µm). We performed espresso extractions for a range of median particle sizes and by systematically varying the share of fines in the ground coffee by adding sieved fines to the coffee grounds. Dynamic beverage weights, extraction percentage, extraction time and dynamic headspace PTR-MS (proton-transfer mass spectrometer) analysis and sensory evaluation of the resulting brews were measured. We show that the share of fines plays an important role in the espresso extraction flow rate. An increase of share of fines decreases coffee bed permeability and leads to reduced flow rates and longer extraction times. Statistical model using partial least squares regression of the particle size distributions of coffee grounds confirms that previously an arbitrary choice of fines at below 100 µm is an appropriate one for characterizing coffee grounds. The PTR-MS analysis shows a non-linear increase of aroma compounds content in the final cup with increasing extraction yield. Our hypothesis is that both extraction efficiency and post-extraction evaporative losses of aroma compounds influence the final aroma compound concentrations in the cup.
Moderate ethanol exposure reduces astrocyte-induced neuroinflammatorysignaling and cognitive decline in presymptomatic APP/PS1 mice
Authors: Kang Shinwoo , Lee Jeyeon , Choi Sun , Nesbitt Jarred , Min Paul H , Trushina Eugenia , Choi Doo-Sup 
Published: December 2023

Abstract
Background Alcohol use disorder (AUD) has been associated with the development of neurodegenerative diseases, including Alzheimer's disease (AD). However, recent studies demonstrate that moderate alcohol consumption may be protective against dementia and cognitive decline.
Methods We examined astrocyte function, low-density lipoprotein (LDL) receptor-related protein 1 (LRP1), and the NF-κB p65 and IKK-α/β signaling pathways in modulating neuroinflammation and amyloid beta (Aβ) deposition. We assessed apolipoprotein E (ApoE) in the mouse brain using IHC and ELISA in response to moderate ethanol exposure (MEE). First, to confirm the intracerebral distribution of ApoE, we co-stained with GFAP, a marker for astrocytes that biosynthesize ApoE. We sought to investigate whether the ethanol-induced upregulation of LRP1 could potentially inhibit the activity of IL-1β and TNF-α induced IKK-α/β towards NF-κB p65, resulting in a reduction of pro-inflammatory cytokines. To evaluate the actual Aβ load in the brains of APP/PS1 mice, we performed with a specific antibody Aβ (Thioflavin S) on both air- and ethanol-exposed groups, subsequently analyzing Aβ levels. We also measured glucose uptake activity using 18F-FDG in APP/PS1 mice. Finally, we investigated whether MEE induced cognitive and memory changes using the Y maze, noble objective recognition (NOR) test, and Morris water maze (MWM).
Results Our findings demonstrate that MEE reduced astrocytic glial fibrillary acidic protein (GFAP) and ApoE levels in the cortex and hippocampus in presymptomatic APP/PS1 mice. Interestingly, increased LRP1 protein expression is accompanied by dampening the IKK-α/β-NF-κB p65 pathway, resulting in decreased IL-1β and TNF-α levels in male mice. Notably, female mice show reduced anti-inflammatory cytokines, IL-4, and IL-10 levels without altering IL-1β and TNF-α concentrations. In both males and females, Aβ plaques, a hallmark of AD, were reduced in the cortex and hippocampus of ethanol-exposed presymptomatic APP/PS1 mice. Consistently, MEE increased fluorodeoxyglucose (FDG)-positron emission tomography (PET)-based brain activities and normalized cognitive and memory deficits in the APP/PS1 mice.
Conclusions Our findings suggest that MEE may benefit AD pathology via modulating LRP1 expression, potentially reducing neuroinflammation and attenuating Aβ deposition. Our study implies that reduced astrocyte derived ApoE and LDL cholesterol levels are critical for attenuating AD pathology.
Development and validation of a machine learning model to predict the risk of liver fibrosis
Authors: zhou weihan , Liu Dekun , Wei Ke , Yu Nanhui 
Published: December 2023

Abstract
Background: Liver fibrosis has become a major chronic disease affecting global health and safety. It is a sustained wound healing response that can cause excessive deposition of extracellular matrix (ECM) and lead to cirrhosis and hepatocellular carcinoma (HCC). Developing and validating a machine learning model to predict the risk of liver fibrosis is crucial for developing personalized prevention and treatment plans.
Objective: Our aim is to establish an interpretable model to predict the risk of liver fibrosis, and use the SHapley Additive exPlanations (SHAP) method to explain the RandomForest model and explore prognostic factors of liver fibrosis.
Method:In this retrospective cohort study, Health and Nutrition Examination Survey (NHANES). transient elastography (TE)-accessed liver stiffness was taken as independent and dependent variables, respectively. Liver steatosis and fibrosis were detected by controlling attenuation parameter (CAP) and TE. Th e median
liver stiffness of 8.2 kPa was used to identify significant fibrosis ( F2) among patients. We calculated the adjusted odds ratio (OR) and 95% confidential intervals (CIs) for associations with significant NAFLD fibrosis using multivariable logistic regression models.we conducted model development and performance comparison on NHANES. We extracted data for each case of liver fibrosis and randomly divided the dataset into training set (70%) and validation set (30%). The predictive performance was compared between the Random Forest model and eight other machine learning models based on the area under the curve. We used the SHAP method to explain the Random Forest model model.
Results: Overall, 5948 individuals with were included in the analysis and768 subjects met thedefinition of liver fibrosi .Among the nine models, the Random Forest model had the best predictive performance, with a training set area under the curve (AUC) of 0.993 (95% CI 0.880-0.985) and a validation set AUC of 0.609 (95% CI 0.443-0.775). The SVM model had the worst generalization ability (AUC=0.272, 95% CI 0.140-0.404). The decision curve showed that at threshold probabilities ranging from 10% to 28%, the net benefit of the Random Forest model exceeded that of other machine learning models. The SHAP method revealed the top seven predictive factors for liver fibrosis based on their importance ranking, with smoking status being considered as the most important predictor variable based on its mean value.
Conclusions:
Interpretable predictive models can help doctors predict the risk of liver fibrosis more accurately, thereby providing better early warning and treatment options for their patients. In addition, interpretable frameworks can increase the transparency of the model and promote understanding of the reliability of the predictive model for doctors.
Influence of melatonin supplementation on tissue response of endodontic sealers in Wistar rats
Authors: de Oliveira Pedro Henrique Chaves , Rodrigues Michael Júnio da Silva , Silva Cristiane Cantiga da , Cardoso Carolina de Barros Morais , Faria Flávio Duarte , Silva Leopoldo Cosme da , Ervolino Edilson , Cintra Luciano Tavares Angelo 
Published: December 2023

Abstract
Objectives: Evaluate the influence of melatonin supplementation on tissue’s response to endodontic sealers in Wistar rats.
Material and methods: Forty-eight Wistar rats had four polyethylene tubes implanted in their subcutaneous tissue, one empty (control) and three filled with endodontic sealers (AH Plus, Endofill and Sealapex). Half of the animals were supplemented with melatonin (TM) and the remaining with water (TW) for 15 days before the implantation until euthanasia. After 5, 15 and 30 days (n=8/group/period) tubes were removed and analyzed in H&E, immunohistochemistry, PSR, VK and POL. The results were statistically analyzed (p<0.05).
Results: In TW, Endofill evoked a more intense inflammatory infiltrate compared to AH Plus and control in 30-day (p<0.05). In TM tubes, there was any difference in both periods (p>0.05), differences for Endofill (p=0.05) and Sealapex (p<0.05) was observed in TM animals in 30-day, presenting lower inflammatory infiltrate. For IL-6 and TNF-α it was observed that the immunolabeling was lower in TM animals in all periods, despite of the sealer. In addition, there was a higher percentage of mature fibers in TM groups at 5 days (p<0.05). Structures positive for von Kossa staining and birefringent to polarized light were observed only for Sealapex in all periods, regardless of melatonin supplementation.
Conclusion: Melatonin influences inflammatory response of endodontic sealers, by modulating the inflammatory process and pre-inflammatory mediators, and stimulating tissue repair, without interfering on calcium deposition.
Clinical Relevance: Evidence that melatonin can regulate inflammatory responses after the contact of tissues with biomaterials.
Socio-demographic predictors of not having private dental insurance coverage: Machine-learning algorithms may help identify the disadvantaged
Authors: Duvvuri Venkata , Abdelrehim Mona , Singhal Sonica 
Published: December 2023

Abstract
Background
Unlike universal health care coverage, dental care in Canada is almost wholly privately financed, with approximately 62% having employment-based insurance, 32% having no insurance, and only 6% of Canadians have some form of dental care coverage through public purse. Consequently, the ability of people with no insurance or public coverage to access dental care is limited compared to those with private insurance. For governments to assess eligible target populations for future dental programs, it is important to understand the socio-demographic attributes of those who do not have insurance coverage or are currently on public programs.
Methods
Our study is a secondary data analysis of the latest available cycle of the Canadian Community Health Survey (2017-18), a cross-sectional survey that collects information on health status, health care utilization, and health determinants for the Canadian population. We started with bivariate analysis to determine the characteristics of Ontarians who lack dental insurance. Afterwards, we employed machine learning (ML) to analyze data and identify risk indicators for not having private dental insurance. Specifically, we trained seven supervised ML models and utilized Shapley additive explanations (SHAP) to determine the relative feature importance for not having private dental insurance from the best ML model [the gradient boosting (GBDT)].
Results
Approximately one-third of Canadians do not have private insurance coverage for dental care. Individuals with an income below $20,000, those unemployed or working part-time, seniors aged above 70, and those unable to afford to have their own housing are more at risk of not having dental insurance, leading to financial barriers in accessing dental care.
Conclusion
In the future, government-funded programs should incorporate these identified risk indicators when determining eligible populations for publicly funded dental programs. Understanding these attributes is critical for developing targeted and effective interventions, ensuring equitable access to dental care for Canadians.
No gender differences in the 24 month decline of non-invasive liver fibrosis markers in HCV-mono and HCV/HIV coinfection after direct-acting antiviral therapy
Authors: Collazos Julio , Perez-Is Laura , Fuente Belen De la , Morano Luis , Rivas-Carmenado Maria , Rodriguez Manuel , Romero-Favela Adolfo , gonzalez Galilea de Jesus Fonseca- , Melon Santiago , Diaz-arias Javier , Valle-Garay Eulalia , Asensi Victor 
Published: December 2023

Abstract
Purpose
Untreated HCV mono and HCV/HIV coinfected women have lower degrees of liver fibrosis (LF) compared to men. Direct acting antiviral (DAA) therapy attains viral eradication in > 90% of patients with progressive LF decline in parallel. Gender-related differences in LF regression in the long term assessed by non-invasive liver fibrosis markers (NILFM) in HCV mono and HCV/HIV coinfected after DAA treatment have not been explored so far
Patients and Methods
374 HCV-infected adult patients, of them 214 HCV-HIV coinfected, were followed-up for 24 months after starting DAA therapy. LF was assessed by NILFM: transient elastometry (TE) and several biochemical indexes (APRI, Forns, FIB-4).
Results
Men had significantly more advanced LF at baseline than women assessed by NILFM. No LF differences at baseline in age, HIV coinfection course (CD4, HIV viral load), and HCV features (HCV viral load, genotype) were detected. No significant gender differences in LF decline after comparing 24-month and baseline LF values were observed. LF changes after DAA therapy were similar in HCV mono and HCV/HIV coinfected patients and in both sexes. Gender did not influence the course of LF decline after DAA assessed by NILFM: TE (p = 0.8), APRI (P = 0.9)), Forns (P = 0.4) and FIB-4 (P = 0. 7) by multivariate analysis.
Conclusions
No gender differences in the 24 month LF decline after DAA with independence of having HCV mono or HCV/HIV coinfection were found.
Long-term Patterns of Stream Macroinvertebrates in an Alpine Cirque Landscape
Authors: Robinson Christopher T. , Jolidon Christa , Lods-Crozet Brigitte 
Published: December 2023

Abstract

Alpine landscapes are notable regarding their sensitivity to environmental change. Surface waters are especially sensitive as many are influenced by glacial meltwaters that are diminishing with the retreat of glaciers worldwide. The Macun Lakes region is an alpine cirque landscape housing a number of lakes interconnected by streams. Surface waters, 10 stream sites in the present study, have been monitored in mid-summer since the year 2001 for physico-chemistry, periphyton and macroinvertebrates (including 74 species of chironomids). Water physico-chemistry revealed that the two main basins in the catchment differed, reflecting the inputs of rock glacier waters in the south basin. However, trends suggest that waters are becoming more similar as rock glacier inputs diminish over time along with a general decrease in nitrogen levels in all waters. Periphyton biomass showed some spatial differences among sites and with a general decrease following 2010. Macroinvertebrate assemblages, including chironomids, clearly differed among basins and longitudinally along the stream network in each basin. Notably, no significant temporal trend was observed in the long-term data for macroinvertebrates, as well as chironomids, at the monitored sites. The results suggest that lotic macroinvertebrates may be buffered by the interconnectedness of streams with lakes in the landscape that mitigate major response patterns of running waters to environmental change.
Deletion of a GA-repeat in human GPM6B disrupts differentiation of NT2 cells to neural cells
Authors: Bayat Hadi , Mirahmadi Maryam , Azarshin Zohreh , Ohadi Hamid , Delbari Ahmad , Ohadi Mina 
Published: December 2023

Abstract
Across multiple primates and tissues, GPM6B (Glycoprotein membrane 6B) reaches maximum levels of expression in the human brain. This gene contains a strictly monomorphic short tandem repeat (STR) of (GA)9. We used a CRISPR-based tool to delete this GA-repeat in NT2 cells, and analyzed the consequence of this deletion on GPM6B expression, using qRT-PCR and western blot. Subsequently, the edited cells were induced to differentiate into neural cells, using retinoic acid (RA) treatment, and sorted by flowcytometry. Deletion of the GA-repeat significantly decreased the expression of GPM6B at the RNA level (p < 0.05) and 40% at the protein level. Compared to the control cells, the edited cells showed a dramatic decrease of the astrocyte and neural cell markers at the protein level, including GFAP (0.77-fold), TUBB3 (0.57-fold), and MAP2 (0.2-fold). Subsequent sorting of the edited cells, using the cell surface markers showed an increased number of NES (p < 0.01), but decreased number of GFAP (p < 0.001), TUBB3 (p < 0.05), and MAP2 (p < 0.01), compared to the control cells. In conclusion, we provide prime evidence of the biological role of a STR, exemplified in the regulation of GPM6B expression and optimal differentiation of human neural cell lineages.
qPCR as a decision-making tool for Plasmodiophora brassicae forecast in the field
Authors: Arias Francy Liliana García , Rodríguez Edwin , Dávila Lorena , Riascos Donald , Revelo Eliana , Gelvez Alejandro Villabona , Moreno-Velandia Carlos Andrés , Zuluaga Paola 
Published: December 2023

Abstract
Clubroot caused by Plasmodiophora brassicae is a very destructive soilborne disease of brassica plants worldwide. The pathogen survives in soil with resting spores, that are produced in large numbers inside infected roots and can persist in the soil for up to 17 years. These resting spores can build up in the soil when brassicas are repeatedly grown, increasing the inoculum potential, leading to increased disease incidence and severity in subsequent crops. Infection by this pathogen can result in considerable yield and quality losses in susceptible crops, accounting for a 20–90% yield loss of broccoli, cauliflower, and cabbage crops in Colombia. A national survey to determine the extent of clubroot in Colombia was done in 2017, and it was found that 53.7% of the visited fields had clubroot disease on the crops, but the pathogen DNA was detected by PCR methods on 91.3% of the surveyed fields in all the departments where crucifers are grown. At the time of the survey, no symptoms of clubroot disease were observed in Nariño department, despite finding the pathogen DNA at concentrations varying from 2x103 to 2x104 resting spores per gram of soil. However, during the year 2020, Nariño farmers reported the presence of a disease, causing wilting and plant death of their cruciferous crops. Here we report that P. brassicae is the causal agent of the newly appeared disease in brassica crops in Nariño. The aims of this study were to determine the inoculum threshold needed to cause disease and the inoculum concentration that can be detected in both artificially and naturally infected soils to use them as tools for P. brassicae management and control. We propose the use of qPCR as a decision-making tool for cruciferous growers.
Deep Learning for Microsatellite Instability Prediction in Colorectal Cancer: Impact of Clinicopathologic Variables on Model Performance
Authors: Kim Meejeong , Chikontwe Philip , Go Heounjeong , Jeong Jae Hoon , Shin Su-Jin , Park Sang Hyun , Nam Soo Jeong 
Published: December 2023

Abstract
Microsatellite instability (MSI) is a clinically significant subtype in colorectal cancer. Despite the promising performance of deep learning techniques in digital pathology for clinical diagnosis, the impact of clinicopathologic factors on the performance of these models has been largely overlooked. Using a total of 931 colorectal cancer whole-slide images (WSIs), we developed and verified a deep learning algorithm and analyzed the WSI-level MSI probability and clinicopathologic variables. In both internal and external cohorts, our deep learning model achieved an area under the receiver operating curve (AUROC) of 0.901 and 0.908, respectively. The presence of a mucinous or a signet ring cell carcinoma component enhanced the model’s ability to predict MSI (HR = 19.73, P = 0.026). Conversely, tumors subjected to neoadjuvant chemoradiation therapy (HR = 0.03, P = 0.002) and those with metastasis (HR = 0.01, P = 0.016) demonstrated an increased probability of being associated with microsatellite stability (MSS). To ensure the clinical applicability of the model, it is imperative to meticulously validate deep learning-based approaches for MSI prediction, accounting for diverse practical clinicopathologic backgrounds that may impact the model’s performance.