bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial Distribution and Growth Potential of Economically Important Rattan Species in Cameroon Seen Through the Lens of Indigenous Populations
Authors: Nfornkah Barnabas Neba , Kevin Enongene , Rene Kaam , Djomo Chimi Cedric , Forje Gadinga Walter , Awazi Nyong Princely , Delanor Tanougong Armand 
Published: October 2021

Abstract
Background: Rattan is an important Non-Timber Forest Product (NTFP) with huge potentials to boost socio-economic development in indigenous communities of Cameroon in particular and the entire country in general. Exploitation is from the wild, with no implication of stakeholders in renewing the resource, thus leading to resources scarcity. Insufficient knowledge on rattan’s growth potentials in Cameroon jeopardize resource regeneration and renewal. It was in this context that this study was initiated to (i) determine economically important rattan species distribution; (ii) identify their habitats and conservation status; (iii) examine harvester’s perceptions/observations on annual growth rate and age to maturity. Results: It was found that Eremospatha macrocarpa exist in all AEZs, Calamus deerratus was found in AEZ 2 & 5, Laccosperma Secundiflorum, L. Robustum, was found in AEZ 3, 4 and 5 and Eremospatha wendlandiana was found only in AEZ4. They grow in diverse habitat/environments with some habitats/environments specifically suitable for some rattan species. The current conservation status of commercial rattan species identified shows Least Concern (LC); but resource scarcity in high. Most harvesters observed that rattan takes either 2 – 3 years (51%) or 4 – 5 years (35%) to attain maturity. The harvesters’ observation on annual growth rate of economic rattan species varied in relation to the species and AEZs, nevertheless, globally 25% and 23% of the respondents observed a growth rate of 2-3 m and 3-4 m respectively. Kruskal-Wallis test shows a significant variation in harvesters’ perception in the different AEZs for all growth and maturity parameters of different rattan species (p<0.05) except for the number of years it takes for rattan to attain maturity (p>0.05)”.Conclusions: All five economically important rattan species are highly distributed in the Southern zone of Cameroon. The availability of E. macrocarpa in all zones indicates its great adaption. Renewing (plantations) rattan resource implies appropriate planting in the Southern and Coastal regions of Cameroon, since the all the species inhabit and grow rapidly. This is important to policymakers and development planners for policy reformulation towards the sustainable development of rattan in Cameroon.
Novel interferon-gamma-related 2-gene signature predicts outcome and responsiveness to immune checkpoint blockade in glioma
Authors: Li Yongzhe , Ji Hang 
Published: October 2021

Abstract
Background

Glioma represents the most common and aggressive brain malignancy. Interferon-gamma (IFNG)-related gene signatures have been shown of clinical significance in multiple cancers, while its role in glioma remains less addressed.
Methods

A total of 2933 glioma samples ranging from WHO grade II to IV with corresponding demographics were included. Multiple bioinformatics and machine learning algorithms were employed to establish an IFNG-related biomarker to classify survival differences and to elucidate the potential of glioma to respond to immune checkpoint blockade (ICB) therapy.
Results

The ssGSEA score of IFNGR1 and IFNGR2 was defined as the IFNGR score, which well-characterized the IFNG response in the glioma microenvironment. Increased IFNGR score was associated with clinicopathological parameters characterizing glioma malignancy, including WHO grade IV, mesenchymal subtype, and molecular biomarkers, including IDH1 wildtype, 1p19q non-codeletion, and unmethylated MGMT promoter. Consequently, K-M and Cox regression analysis found that the IFNGR score was a robust prognostic biomarker that was associated with tumor relapse for patients in certain subgroups. Moreover, the IFNGR-based group had the potential to predict ICB responsiveness, as effectively as previously validated IFNG-related gene signatures.
Conclusion

Together, we have developed a concise biomarker of clinical significance that may improve the current diagnosis and treatment of glioma.
Optimizing Stand Spatial Structure by Using Neighborhood-Based Quantitative Indicators: A Case of Boreal Forests
Authors: Dong Lingbo , Bettinger Pete , Liu Zhaogang 
Published: October 2021

Abstract
Background: Over the past fifty years, societies have placed increasing demands on forests, and their use has shifted gradually from wood production to the diversified benefits and functions of ecosystem services. The effects of neighborhood-based structural characteristics on regulating growth and promoting sustainability have therefore drawn much attention. However, direction for managing natural mixed forests using neighborhood-based indicators are still not clear.Methods: In this study, a tree-level harvest planning tool that considers four neighborhood-based structural parameters (species mingling, diametric differentiation, horizontal spatial pattern and crowdedness of trees) while concurrently recognizing other operational constraints, was developed using simulated annealing algorithm. The approach was applied to four 1-ha mapped stands in northeast China, namely a natural larch forest (NLF), a natural birch forest (NBF), a natural secondary forest (SEF), and a Korean pine broad-leaved forest (KBF). Results: The tree-level harvest optimization improved the objective function values by approximately 78.33% of NLF, and 134.96% of NBF, and 156.70% of SEF and 252.95%, respectively. The optimal harvest intensities for partial cutting activities varied from 22.16% (SEF) to 26.07% (NBF) of the standing volume. In evaluating the four neighborhood-based structural parameters, both species mingling and crowdedness have the highest priority to be used in structure-based forest management.Conclusions: Our results demonstrated that that the commonly used neighborhood-based structural parameters could be used to control the spatial layout of potential harvest trees, in turn may be conducive to regulate the growth and stability of forests.
Development and Validation of a Nomogram for the Early Prediction of Iga Nephropathy in Primary Glomerulonephritis
Authors: Luo Hou-Long , Cui Lixia , Li Mingyang , Huang Chencui , Liu Wei , Xia Yong , Ji Ling 
Published: October 2021

Abstract
Background: To make early prediction of immunoglobulin A nephropathy (IgAN) before renal biopsy, we developed and validated a new non-invasive nomogram for the early prediction of IgAN in primary glomerulonephritis (GN) in south China. Methods: A total of 431 patients were included in this study and additional 113 patients were included as the independent test cohorts to validate our results. A stepwise regression model was used for features selection. Multivariate logistic regression analysis with 5-fold cross validation was used to validate the result of the stepwise selection. Performance of the logistic regression model was assessed with respect to its calibration, discrimination, and clinical usefulness. Independent test was assessed. Results: We developed a model incorporating age of patients and four clinical chemistry signatures, including serum IgA, serum albumin (ALB), serum phosphorus (P) and 24-hour urinary protein (24hUpro) and presented with a nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) reached 0.89 (95% CI: 0.86–0.92) and 0.88 (95%: 0.85-0.92) in the training set and validation set, respectively. The model also had good performance in independent test cohorts (AUC of 0.82, 95% CI: 0.75–0.90). The DCA and calibration plot of the model also shows good performance. Conclusions: The logistic regression model presented in this study incorporates age of patients, IgA, ALB, P and 24hUpro and can be conveniently used to facilitate the individualized prediction of IgAN.
Functional Orderly Topography of Brain Networks Associated with Gene Expression Heterogeneity
Authors: Liu Wei , Zeng Lingli , Shen Hui , Zhou Zongtan , hu dewen 
Published: October 2021

Abstract
The human cerebral cortex expanded much more relative to non-human primates and rodent in evolution, leading to a functional orderly topography of the brain networks. Here, we show that functional topography may be associated with gene expression heterogeneity in various brain structures. The neocortex exhibits greater gene expression heterogeneity, with lower housekeeping gene proportion, a longer mean path length, less clusters, and a lower degree of ordering of networks, compared to archicortical and subcortical area in human, rhesus macaque, and mouse brains consistently. In particular, the cerebellar cortex displays greater gene expression heterogeneity than cerebellar deep nuclei in the human brain, but not in the mouse brain, corresponding to the emergence of novel functions in the human cerebellar cortex. Moreover, the cortical areas with greater gene expression heterogeneity, primarily located in multimodal association cortex, tend to express genes with higher evolutionary rates and exhibit higher functional connectivity degree measured by resting-state fMRI, implying that such spatial pattern of cortical gene expression may be shaped by evolution and favorable for the specialization of higher cognitive functions. Together, the cross-species imaging genetic findings may provide convergent evidence to support the association between the orderly topography of brain function networks and gene expression.
BNIP3 attenuates hepatocellular carcinoma by promoting lipid droplet turnover at the lysosome.
Authors: Berardi Damian , Bock-Hughes Althea , Drake Lauren , Terry Alexander , Bozek Grazyna , Macleod Kay 
Published: October 2021

Abstract
Hepatic steatosis is a major etiological factor in hepatocellular carcinoma (HCC). Work reported here identifies BNIP3 as a suppressor of HCC that mitigates against lipid accumulation.
Loss of BNIP3 decreased tumor latency and increased tumor burden in a mouse model of HCC. This was associated with increased lipid accumulation and elevated HCC tumor cell growth. Conversely, exogenous BNIP3 decreased lipid levels and reduced HCC tumor cell growth. Mutant BNIP3W18A that is unable to promote mitophagy did not decrease HCC cell growth and was defective at reducing lipid levels. Growth suppression by BNIP3 was not mediated by effects on fatty acid oxidation (FAO) or de novo lipogenesis (DNL). Rather, BNIP3 suppressed HCC cell growth by promoting lipid droplet turnover at the lysosome through a process we have termed “mitolipophagy” in which lipid droplets and mitochondria are turned over together at the lysosome. Low BNIP3 expression in human HCC also correlated with increased lipid content and worse prognosis than HCC expressing high levels of BNIP3. This work reveals a role for BNIP3 and lipid droplet turnover at the lysosome in attenuating HCC.
The Association between Homocysteinemia and Mortality in Pre-dialysis CKD patients: A Propensity-Score Matched Analysis Using NHANES-National Death Index Link
Authors: Song Je Hun , Huh Hyuk , Bae Eunjin , Lee Jeonghwan , Lee Jung Pyo , Lee Jong Soo , Yoo Kyung Don , Kim Gwang Sil 
Published: October 2021

Abstract
Background: Hyperhomocysteinemia (HHcy) is considered a risk factor for cardiovascular disease (CVD) including chronic kidney disease (CKD). In this study, we investigated the association between serum homocysteine (Hcy) level and mortality according to the presence of CKD.Methods: Our study included data of 9,895 participants from the 1996–2016 National Health and Nutrition Examination Surveys (NHANES). Moreover, linked mortality data were included and classified into four groups according to the Hcy level. Multivariable-adjusted Cox proportional hazards models using propensity-score were used to examine dose-response associations between Hcy level and mortality.Results: Of 9,895 participants, 1032 (21.2%) participants were diagnosed with CKD. In a multivariate Cox regression analysis including all participants, Hcy level was associated with all-cause mortality, compared with the 1st quartile in Model 3 (2nd quartile: hazard ratio (HR) 1.751, 95% confidence interval (CI) 1.348-2.274, p<0.001; 3rd quartile: HR 2.220, 95% CI 1.726-2.855, p<0.001; 4th quartile: HR 3.776, 95% CI 2.952-4.830, p<0.001). In the non-CKD group, there was a significant association with all-cause mortality; however, this finding was not observed in the CKD group. The observed pattern was similar after propensity score matching. In the non-CKD group, overall mortality increased in proportion to Hcy concentration (2nd quartile: HR 2.195, 95% CI 1.299-3.709, p = 0.003; 3rd quartile: HR 2.607, 95% CI 1.570-4.332, p<0.001; 4th quartile: HR 3.720, 95% CI 2.254-6.139, p<0.001). However, the risk of all-cause mortality according to the quartile of Hcy level did not increase in the CKD groupConclusion: This study found a correlation between the Hcy level and mortality rate only in the non-CKD group. This altered risk factor patterns may be attributed to protein-energy wasting or chronic inflammation status that is accompanied by CKD.
Automated Pancreas Segmentation And Volumetry Using Deep Neural Network On Computed Tomography
Authors: Lim Sang-Heon , Kim Young Jae , Park Yeon-Ho , Kim Doojin , Kim Kwang Gi , Lee Doo-Ho 
Published: October 2021

Abstract
Pancreas segmentation is necessary for observing lesions, analyzing anatomical structures, and predicting patient prognosis. Therefore, various studies have designed segmentation models based on convolutional neural networks for pancreas segmentation. However, the deep learning approach is limited by a lack of data, and studies conducted on a large computed tomography dataset are scarce. Therefore, this study aims to perform deep-learning-based semantic segmentation on 1,006 participants and evaluate the automatic segmentation performance of the pancreas via four individual three-dimensional segmentation networks. In this study, we performed internal validation with 1,006 patients and external validation using the Cancer Imaging Archive (TCIA) pancreas dataset. We obtained mean precision, recall, and dice similarity coefficients of 0.869, 0.842, and 0.842, respectively, for internal validation via a relevant approach among the four deep learning networks. Using the external dataset, the deep learning network achieved mean precision, recall, and dice similarity coefficients of 0.779, 0.749, and 0.735, respectively. We expect that generalized deep-learning-based systems can assist clinical decisions by providing accurate pancreatic segmentation and quantitative information of the pancreas for abdominal computed tomography.
Happi Kneecaps! A Double-Blind, Randomised, Parallel Group Superiority Trial Investigating the Effects of Shoe Inserts for Adolescents with Patellofemoral Pain: Phase II Feasibility Study
Authors: O'Sullivan Isobel C , Crossley Kay M , Kamper Steven J , Middelkoop Marienke van , Vicenzino Bill , Smith Melinda M Franettovich , Menz Hylton B , Smith Anne J , Tucker Kylie , O'Leary Karina T , Costa Nathalia Cordeiro da , Collins Natalie J 
Published: October 2021

Abstract
Background: Patellofemoral pain (PFP) affects one-third of adolescents and can persist into adulthood, negatively impacting health and quality of life. Foot orthoses are a recommended treatment for adults with PFP, but have not been evaluated in adolescents. The primary objective was to determine the feasibility of conducting a full-scale randomised controlled trial (RCT) evaluating effects of contoured, prefabricated foot orthoses on knee pain severity and patient-perceived global change, compared to flat insoles. The secondary objective was to describe outcomes on a range of patient-reported outcome measures. Methods: We recruited adolescents aged 12-18 years with PFP of ³2 months duration into a double-blind, randomised, parallel-group feasibility trial. Participants were randomised to receive prefabricated contoured foot orthoses or flat shoe insoles, and followed for 3 months. Participants and outcome assessors were blinded to group allocation. Primary outcomes were feasibility of a full-scale RCT (number of eligible/enrolled volunteers; recruitment rate; adherence with the intervention and logbook completion; adverse effects; success of blinding; drop-out rate), and credibility and expectancy of interventions. Secondary outcomes were patient-reported measures of pain, symptoms, function, quality of life, global rating of change, patient acceptable symptom state, and use of co-interventions.Results: 36 out of 279 (12.9%) volunteers (27 female, mean (SD) age 15 (2) years, body mass 60 (13) kg) were eligible and enrolled, at a recruitment rate of 1.2 participants/week. 17 participants were randomised to receive foot orthoses, and 19 to flat insoles. 15 participants returned logbooks; 7/15 (47%) adhered to the intervention. No serious adverse events were reported. 28% (10/36, 4 pandemic-related) of participants dropped out before 3 months. Blinding was successful. Both groups found the inserts to be credible. Conclusions: Based on a priori criteria for feasibility, findings suggest that a full-scale RCT comparing contoured foot orthoses to flat insoles in adolescents with PFP would not be feasible using the current protocol. Prior to conducting a full-scale RCT, further feasibility studies are needed, with protocol modifications to facilitate participant retention, logbook completion and shoe insert wear. Trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12619000957190. Date registered: 8/07/2019.
Mitigation of the Impact of the Covid 19 Pandemic on Poverty and Income Distribution: A Case Study in Wonogiri Regency
Authors: Rahayu Endang Siti , Astirin Okid Parama , Suryanto Suryanto 
Published: October 2021

Abstract
The Covid pandemic had a significant impact on the economy because almost all sectors are affected. Food and Agriculture Organization (FAO) warned countries to be alert to the potential food crisis due to the COVID-19 pandemic. The research objectives are to (1) identify the income of the people affected by Covid 19, (2) analyze the changes in income, (3) formulate a mitigation model. The research method used is a survey with 240 respondents from rural communities affected by Covid 19, especially farmers and Micro, Small and Medium Enterprises (MSMEs). The analytical method used is cost and income analysis, SWOT analysis, poverty analysis and income distribution with the Gini Index approach. Covid 19 has impacted decreasing income and increasing poverty by 48.44% and the GI value of 0.604. The income distribution is increasingly widening and low/poor. Based on the SWOT analysis, the people affected by Covid 19 are in quadrant II, the point of growth and development. Mitigation model to prevent poverty and increase equity level with intensive strategy and integrative strategy. The strategy is to maintain product quality and continuity and optimization and development of marketing by utilizing government support and institutional strengthening.
Extremophile at a Glance: Ostracod Crustacean From a Chemoautotrophic Sulphidic Cave Ecosystem
Authors: Iepure Sanda , Wysocka Anna , Sarbu Serban M. , Kijowska Michalina , Namiotko Tadeusz 
Published: October 2021

Abstract
Sulphidic cave ecosystems are remarkable evolutionary hotspots that have witnessed adaptive radiation of their fauna represented by extremophile species having particular traits. Ostracods, a very old group of crustaceans, exhibit specific morphological and ecophysiological features that enable them to thrive in groundwater sulphidic environments. Herein, we report a peculiar new ostracod species Pseudocandona movilaensis sp. nov. thriving in the chemoautotrophic sulphidic groundwater ecosystem of Movile Cave (Romania). The new species displays a set of homoplastic features specific for unrelated stygobitic species, for e.g., triangular carapace in lateral view with reduced postero–dorsal part and simplification of limb chaetotaxy (i.e., loss of some claws and reduction of secondary male sex characteristics), driven by a convergent or parallel evolution during or after colonization of the groundwater realm. P. movilaensis sp. nov. thrives exclusively in sulphidic meso-thermal waters (21°C) with high concentrations of sulphides, methane, and ammonium. Based on the geometric morphometrics-based study of the carapace shape and molecular phylogenetic analyses based on the COI marker (mtDNA), we discuss the phylogenetic relationship and evolutionary implication for the new species to thrive in groundwater sulphidic groundwater environments.
Complex Correlations between Microstructure and Magnetic Behavior in SrFe12O19 Hexaferrite Nanoparticles
Authors: Maltoni Pierfrancesco , Ivanov Sergey Alexander , Barucca Gianni , Varvaro Gaspare , Peddis Davide , Mathieu Roland 
Published: October 2021

Abstract
The magnetic properties of SrFe12O19 (SFO) hard hexaferrites are governed by the complex relation to its microstructure, determining their relevance for permanent magnets´ applications. A set of SFO nanoparticles obtained by sol-gel self-combustion synthesis was selected for an in-depth structural X-Rays powder diffraction (XRPD) characterization by means of G(L) line-profile analysis. The obtained crystallites´ size distribution reveal a clear dependence of the size along the [001] direction on the synthesis approach, resulting in the formation of platelet-like crystallites. In addition, the size of the SFO nanoparticles was determined by transmission electron microscopy (TEM) analysis and the average number of crystallites within a particle was estimated. These results have been evaluated to illustrate the formation of single-domain state below a critical value, and the activation volume was derived from time dependent magnetization measurements, aiming to clarify the reversal magnetization process of hard magnetic materials.