bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing ecosystem resilience: effects of different environments on native flora, lichens and bee pollen in a mid-sized Brazilian city
Authors: Bonatti-Chaves Mariane , Macalossi Jenifer , Cabral Rodrigo Dümes Chaves , Dias dos Santos Murylu , Pfundner Pamela , Bonatti Michelle , Sieber Stefan , Medeiros Sandra Helena Westrupp , Mouga Denise Monique Dubet da Silva , Gumboski Emerson Luiz , Melo Junior João Carlos Ferreira de 
Published: September 2024

Abstract
The alteration of the natural environment by human activities has increased in recent decades, with a significant impact on the organisms that inhabit it. One of the most apparent consequences of environmental alterations is the occurrence of climatic changes. The city of Joinville is situated in the southern region of Brazil. It has achieved a notable position at the national level, largely due to the significant presence of large-scale industrial operations in the metal-mechanical, plastic, and textile sectors. This study aimed to assess the effects of urban environments on Nectandra oppositifolia plants and lichen communities using a passive biomonitoring approach, and on Tetragonisca angustula stingless bees using an active biomonitoring approach. This study demonstrated a pronounced effect of anthropogenic activities on plant anatomy and morphology (higher leaf area, fresh mass, dry mass, and water content in the urban-industrial site), with higher metal concentrations in leaf particulate matter (3.14 ± 0.4 μg cm−2). The diversity of lichens was the lowest, whereas that of crustose lichens was the highest in industrial-urban and residential-rural sites (industrial-urban site = 13 species, residential-rural site = 29 species, control site = 33 species, p < 0.05). The distribution of species within the lichen communities was inversely correlated with the degree of anthropogenic influence. Some lichen species were found exclusively in the control areas, suggesting that they may indicate good environmental quality (Arthonia sp., Astrothelium sp., Phyllopsora pyxinoides, Phyllopsis sp., and others). Beehive pollen analysis revealed the presence of Zn, Cr, Ni, Cu, and Pb, and industrial-urban site exhibited higher metal concentrations (particularly, Ni, 12.59 ± 0.9, and Cr, 3.76 ± 1.00, mg kg−1). This approach highlights the environmental repercussions that affect the Plantae, Fungi, and Animalia kingdoms. The use of biomonitoring as a robust tool in good environmental quality assessment provides insight into policy decisions and underscores the importance of pollution studies.
A machine-learned kinetic energy model for light weight metals and compounds of group III-V elements
Authors: Lüder Johann , Ihara Manabu , Manzhos Sergei 
Published: September 2024

Abstract
We present a machine-learned (ML) model of kinetic energy for orbital-free density functional theory (OF-DFT) suitable for bulk light weight metals and compounds made of group III–V elements. The functional is machine-learned with Gaussian process regression (GPR) from data computed with Kohn-Sham DFT with plane wave bases and local pseudopotentials. The dataset includes multiple phases of unary, binary, and ternary compounds containing Li, Al, Mg, Si, As, Ga, Sb, Na, Sn, P, and In. A total of 433 materials were used for training, and 18 strained structures were used for each material. Averaged (over the unit cell) kinetic energy density is fitted as a function of averaged terms of the 4th order gradient expansion and the product of the density and effective potential. The kinetic energy predicted by the model allows reproducing energy-volume curves around equilibrium geometry with good accuracy. We show that the GPR model beats linear and polynomial regressions. We also find that unary compounds sample a wider region of the descriptor space than binary and ternary compounds, and it is therefore important to include them in the training set; a GPR model trained on a small number of unary compounds is able to extrapolate relatively well to binary and ternary compounds but not vice versa.
Process parameter interaction study for mechanical strength of r-HDPE filled calcium carbonate composites
Authors: Narayanan Thinakaran , Abd Razak Jeefferie 
Published: September 2024

Abstract
The increasing issue of plastic waste disposal has drawn attention to the urgent requirement for sustainable solutions. At the heart of this problem is polyethylene, a crucial industrial resin that has significant implications for recycling. This study aims to explore the feasibility of using recycled high-density polyethylene (rHDPE) derived from waste carpet as a sustainable alternative material for structural applications that undergo mechanical loads. The primary focus of this research is to incorporate calcium carbonate an easily obtainable and cost-effective inorganic mineral filler into the rHDPE. This will enhance mechanical strength. Calcium carbonate (CaCO3) is widely recognized for their reinforcing properties in various polymer composites, and in addition not only improves the mechanical strength of the blend but also reduces the environmental impact associated with plastic and waste carpet disposal. Our experimental approach involves preparing samples with varying compositions of rHDPE and calcium carbonate. This includes carefully considering extrusion process parameters such as screw speed and melting temperature. Mechanical testing was performed using a universal testing machine following the ASTM standard. The findings of this research are expected to open up new avenues for innovative strategies in reducing plastic waste and promoting the sustainable utilization of waste carpets thereby contributing to the broader field of environmental sustainability.
Experimental investigation on in-situ laser-assisted machining of single crystal silicon based on response surface methodology
Authors: Yao Dong , Shi Guangfeng , Meng Siwei 
Published: September 2024

Abstract
In this paper, Response Surface Methodology (RSM) was utilized as a robust and convenient predictive tool to establish the correlation between process parameters in in situ laser-assisted machining and the surface roughness of single-crystal silicon. An optimized design of the diamond tool, a novel temperature field analysis method, and Response Surface Methodology (RSM) were utilized. The contribution rate of each process parameter on surface roughness was laser power > rotation speed > cutting depth > feed rate. The optimal process parameter combination is: rotation speed as 1001 r min−1, feed rate as 4.9 μm/r, cutting depth as 7.55 μm, and laser power as 28.81 W. Experimental validation of these optimal parameters compared surface roughness values obtained experimentally with those predicted. The surface roughness model showed a maximum relative error of 5.2%, with an average error of 4.8% across three experimental sets. These errors are within acceptable limits, indicating an alignment between predicted and experimental results.
Causally interpretable meta-analysis combining aggregate and individual participant data
Authors: Rott Kollin W , Clark Justin M , Murad M Hassan , Hodges James S , Huling Jared 
Published: September 2024

Abstract
Recent work in causally-interpretable meta-analysis (CIMA) has bridged the gap between traditional meta-analysis and causal inference. While traditional meta-analysis results generally do not apply to any well-defined population, CIMA approaches specify a target population to which meta-analytic treatment effect estimates are transported. While theoretically attractive, these approaches currently have some practical limitations. Most assume that all studies in the meta-analysis have individual participant data (IPD), which is rare in practice because most trials share only aggregate data. We propose a method to perform CIMA using a combination of aggregate data and IPD. This method borrows information from studies with IPD to augment the aggregate data and create aggregate-matched synthetic IPD (AMSIPD), which can be used readily in the existing CIMA framework. By allowing use of both aggregate data and IPD, the method opens CIMA to more applications and can avoid biases arising from using only studies with IPD. We present a case study and simulations showing the AMSIPD approach is promising and merits further investigation as an advancement of CIMA.
Causal enhanced drug–target interaction prediction based on graph generation and multi-source information fusion
Authors: Qiao Guanyu , Wang Guohua , Li Yang 
Published: September 2024

Abstract

Motivation
The prediction of drug–target interaction is a vital task in the biomedical field, aiding in the discovery of potential molecular targets of drugs and the development of targeted therapy methods with higher efficacy and fewer side effects. Although there are various methods for drug–target interaction (DTI) prediction based on heterogeneous information networks, these methods face challenges in capturing the fundamental interaction between drugs and targets and ensuring the interpretability of the model. Moreover, they need to construct meta-paths artificially or a lot of feature engineering (prior knowledge), and graph generation can fuse information more flexibly without meta-path selection.

Results
We propose a causal enhanced method for drug–target interaction (CE-DTI) prediction that integrates graph generation and multi-source information fusion. First, we represent drugs and targets by modeling the fusion of their multi-source information through automatic graph generation. Once drugs and targets are combined, a network of drug–target pairs is constructed, transforming the prediction of drug–target interactions into a node classification problem. Specifically, the influence of surrounding nodes on the central node is separated into two groups: causal and non-causal variable nodes. Causal variable nodes significantly impact the central node’s classification, while non-causal variable nodes do not. Causal invariance is then used to enhance the contrastive learning of the drug–target pairs network. Our method demonstrates excellent performance compared with other competitive benchmark methods across multiple datasets. At the same time, the experimental results also show that the causal enhancement strategy can explore the potential causal effects between DTPs, and discover new potential targets. Additionally, case studies demonstrate that this method can identify potential drug targets.

Availability and implementation
The source code of AdaDR is available at: https://github.com/catly/CE-DTI.
A Bayesian nonparametric approach for causal mediation with a post-treatment confounder
Authors: Bae Woojung , Daniels Michael J , Perri Michael G 
Published: September 2024

ABSTRACT
We propose a new Bayesian nonparametric method for estimating the causal effects of mediation in the presence of a post-treatment confounder. The methodology is motivated by the Rural Lifestyle Intervention Treatment Effectiveness Trial (Rural LITE) for which there is interest in estimating causal mediation effects but is complicated by the presence of a post-treatment confounder. We specify an enriched Dirichlet process mixture (EDPM) to model the joint distribution of the observed data (outcome, mediator, post-treatment confounder, treatment, and baseline confounders). For identifiability, we use the extended version of the standard sequential ignorability (SI) as introduced in Hong et al. along with a Gaussian copula model assumption. The observed data model and causal identification assumptions enable us to estimate and identify the causal effects of mediation, that is, the natural direct effects (NDE) and natural indirect effects (NIE). Our method enables easy computation of NIE and NDE for a subset of confounding variables and addresses missing data through data augmentation under the assumption of ignorable missingness. We conduct simulation studies to assess the performance of our proposed method. Furthermore, we apply this approach to evaluate the causal mediation effect in the Rural LITE trial, finding that there was not strong evidence for the potential mediator.
Investigating the prevalence of MFN2 mutations in amyotrophic lateral sclerosis: insights from an Italian cohort
Authors: Abati Elena , Gagliardi Delia , Manini Arianna , Del Bo Roberto , Ronchi Dario , Meneri Megi , Beretta Francesca , Sarno Annalisa , Rizzo Federica , Monfrini Edoardo , Di Fonzo Alessio , Pellecchia Maria Teresa , Brusati Alberto , Silani Vincenzo , Comi Giacomo Pietro , Ratti Antonia , Verde Federico , Ticozzi Nicola , Corti Stefania 
Published: September 2024

Abstract
The MFN2 gene encodes mitofusin 2, a key protein for mitochondrial fusion, transport, maintenance and cell communication. MFN2 mutations are primarily linked to Charcot–Marie–Tooth disease type 2A. However, a few cases of amyotrophic lateral sclerosis and amyotrophic lateral sclerosis/frontotemporal dementia phenotypes with concomitant MFN2 mutations have been previously reported. This study examines the clinical and genetic characteristics of an Italian cohort of amyotrophic lateral sclerosis patients with rare, non-synonymous MFN2 mutations. A group of patients (n = 385) diagnosed with amyotrophic lateral sclerosis at our Neurology Units between 2008 and 2023 underwent comprehensive molecular testing, including MFN2. After excluding pathogenic mutations in the main amyotrophic lateral sclerosis–related genes (i.e. C9orf72, SOD1, FUS and TARDBP), MFN2 variants were classified based on the American College of Medical Genetics and Genomics guidelines, and demographic and clinical data of MFN2-mutated patients were retrieved. We identified 12 rare, heterozygous, non-synonymous MFN2 variants in 19 individuals (4.9%). Eight of these variants, carried by nine patients (2.3%), were either pathogenic, likely pathogenic or variants of unknown significance according to the American College of Medical Genetics and Genomics guidelines. Among these patients, four exhibited a familial pattern of inheritance. The observed phenotypes included classic and bulbar amyotrophic lateral sclerosis, amyotrophic lateral sclerosis/frontotemporal dementia, flail arm, flail leg and progressive muscular atrophy. Median survival after disease onset was extremely variable, ranging from less than 1 to 13 years. This study investigates the prevalence of rare, non-synonymous MFN2 variants within an Italian cohort of amyotrophic lateral sclerosis patients, who have been extensively investigated, enhancing our knowledge of the underlying phenotypic spectrum. Further research is needed to understand whether MFN2 mutations contribute to motor neuron disease and to what extent. Improving our knowledge regarding the genetic basis of amyotrophic lateral sclerosis is crucial both in a diagnostic and therapeutic perspective.
Rehabilitating homonymous visual field deficits: white matter markers of recovery—stage 2 registered report
Authors: Willis Hanna E , Caron Bradley , Cavanaugh Matthew R , Starling Lucy , Ajina Sara , Pestilli Franco , Tamietto Marco , Huxlin Krystel R , Watkins Kate E , Bridge Holly 
Published: September 2024

Abstract
Damage to the primary visual cortex or its afferent white matter tracts results in loss of vision in the contralateral visual field that can present as homonymous visual field deficits. Evidence suggests that visual training in the blind field can partially reverse blindness at trained locations. However, the efficacy of visual training is highly variable across participants, and the reasons for this are poorly understood. It is likely that variance in residual neural circuitry following the insult may underlie the variation among patients. Many stroke survivors with visual field deficits retain residual visual processing in their blind field despite a lack of awareness. Previous research indicates that intact structural and functional connections between the dorsal lateral geniculate nucleus and the human extrastriate visual motion-processing area hMT+ are necessary for blindsight to occur. We therefore hypothesized that changes in this white matter pathway may underlie improvements resulting from motion discrimination training.
Eighteen stroke survivors with long-standing, unilateral, homonymous field defects from retro-geniculate brain lesions completed 6 months of visual training at home. This involved performing daily sessions of a motion discrimination task, at two non-overlapping locations in the blind field, at least 5 days per week. Motion discrimination and integration thresholds, Humphrey perimetry and structural and diffusion-weighted MRI were collected pre- and post-training. Changes in fractional anisotropy (FA) were analysed in visual tracts connecting the ipsilesional dorsal lateral geniculate nucleus and hMT+, and the ipsilesional dorsal lateral geniculate nucleus and primary visual cortex. The (non-visual) tract connecting the ventral posterior lateral nucleus of the thalamus and the primary somatosensory cortex was analysed as a control. Changes in white matter integrity were correlated with improvements in motion discrimination and Humphrey perimetry. We found that the magnitude of behavioural improvement was not directly related to changes in FA in the pathway between the dorsal lateral geniculate nucleus and hMT+ or dorsal lateral geniculate nucleus and primary visual cortex. Baseline FA in either tract also failed to predict improvements in training. However, an exploratory analysis showed a significant increase in FA in the distal part of the tract connecting the dorsal lateral geniculate nucleus and hMT+, suggesting that 6 months of visual training in chronic, retro-geniculate strokes may enhance white matter microstructural integrity of residual geniculo-extrastriate pathways.
Consistent social odor representation across 7 languages: the Social Odor Scale translation and validation
Authors: Cecchetto Cinzia , Leleu Arnaud , Calce Roberta P , Arnhardt Sally , Parma Valentina , de Groot Jasper H B , Freiherr Jessica , Gentili Claudio , Zou Laiquan , Thunell Evelina , Fischmeister Florian Ph S , Rekow Diane , Dal Bò Elisa 
Published: September 2024

Abstract
The Social Odor Scale (SOS) is a 12-item questionnaire initially developed and validated in Italian and German to investigate self-reported awareness of social odors, which are odors emanating from the human body that convey diverse information and evoke various emotional responses. The scale includes a total score and 3 subscales representing social odors in the respective categories: romantic partner, familiar, and strangers. Here, we aimed to (i) replicate the validation of the Italian and German versions of the SOS, (ii) translate and validate the SOS into multiple additional languages (French, English, Dutch, Swedish, Chinese), and (iii) explore whether the factor structure of each translated version aligns with the original versions. Confirmatory Factor Analysis (CFA) supported the scale’s structure, yielding a good fit across all languages. Notable differences in SOS mean scores were observed among the different languages: Swedish participants exhibited lower social odor awareness compared to the other groups, whereas Chinese participants reported higher social odor awareness compared to Dutch and Swedish participants. Furthermore, SOS scores correlated with respondents’ geographical location, with higher (i.e. northern) latitudes linked to lower social odor awareness. These results corroborate the SOS as a valid and reliable instrument, especially for the SOS total score and the Familiar and Partner factors, emphasizing the influence of individual and geographic factors on social odor awareness.
GDF15 antagonism limits severe heart failure and prevents cardiac cachexia
Authors: Takaoka Minoru , Tadross John A , Al-Hadithi Ali B A K , Zhao Xiaohui , Villena-Gutiérrez Rocío , Tromp Jasper , Absar Shazia , Au Marcus , Harrison James , Coll Anthony P , Marciniak Stefan J , Rimmington Debra , Oliver Eduardo , Ibáñez Borja , Voors Adriaan A , O’Rahilly Stephen , Mallat Ziad , Goodall Jane C 
Published: September 2024

Abstract

Aims
Heart failure and associated cachexia is an unresolved and important problem. This study aimed to determine the factors that contribute to cardiac cachexia in a new model of heart failure in mice that lack the integrated stress response (ISR) induced eIF2α phosphatase, PPP1R15A.

Methods and results
Mice were irradiated and reconstituted with bone marrow cells. Mice lacking functional PPP1R15A, exhibited dilated cardiomyopathy and severe weight loss following irradiation, whilst wild-type mice were unaffected. This was associated with increased expression of Gdf15 in the heart and increased levels of GDF15 in circulation. We provide evidence that the blockade of GDF15 activity prevents cachexia and slows the progression of heart failure. We also show the relevance of GDF15 to lean mass and protein intake in patients with heart failure.

Conclusion
Our data suggest that cardiac stress mediates a GDF15-dependent pathway that drives weight loss and worsens cardiac function. Blockade of GDF15 could constitute a novel therapeutic option to limit cardiac cachexia and improve clinical outcomes in patients with severe systolic heart failure.
PeptiHub: a curated repository of precisely annotated cancer-related peptides with advanced utilities for peptide exploration and discovery
Authors: Zareei Sara , Khorsand Babak , Dantism Alireza , Zareei Neda , Asgharzadeh Fereshteh , Zahraee Shadi Shams , Mashreghi Kashan Samane , Hekmatirad Shirin , Amini Shila , Ghasemi Fatemeh , Moradnia Maryam , Vaghf Atena , Hemmatpour Anahid , Hourfar Hamdam , Niknia Soudabeh , Johari Ali , Salimi Fatemeh , Fariborzi Neda , Shojaei Zohreh , Asiaei Elaheh , Shabani Hossein 
Published: September 2024

Abstract
Peptihub (https://bioinformaticscollege.ir/peptihub/) is a meticulously curated repository of cancer-related peptides (CRPs) that have been documented in scientific literature. A diverse collection of CRPs is included in the PeptiHub, showcasing a spectrum of effects and activities. While some peptides demonstrated significant anticancer efficacy, others exhibited no discernible impact, and some even possessed alternative non-drug functionalities, including drug carrier or carcinogenic attributes. Presently, Peptihub houses 874 CRPs, subjected to evaluation across 10 distinct organism categories, 26 organs, and 438 cell lines. Each entry in the database is accompanied by easily accessible 3D conformations, obtained either experimentally or through predictive methodology. Users are provided with three search frameworks offering basic, advanced, and BLAST sequence search options. Furthermore, precise annotations of peptides enable users to explore CRPs based on their specific activities (anticancer, no effect, insignificant effect, carcinogen, and others) and their effectiveness (rate and IC50) under cancer conditions, specifically within individual organs. This unique property facilitates the construction of robust training and testing datasets. Additionally, PeptiHub offers 1141 features with the convenience of selecting the most pertinent features to address their specific research questions. Features include aaindex1 (in six main subcategories: alpha propensities, beta propensity, composition indices, hydrophobicity, physicochemical properties, and other properties), amino acid composition (Amino acid Composition and Dipeptide Composition), and Grouped Amino Acid Composition (Grouped amino acid composition, Grouped dipeptide composition, and Conjoint triad) categories. These utilities not only speed up machine learning-based peptide design but also facilitate peptide classification.
Database URL: https://bioinformaticscollege.ir/peptihub/