bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neurogenesis inhibition restores cocaine withdrawal-induced depression via Rac1 mediation
Authors: Zhang Lu , Qin sifei , Liu Yutong , Xue Tao , Tian Yuguang , Zhu Hangfei , Ye Qing , Tan Yi , Mo Jiading , Zhou Kaini , Li Qihao , Zhang Yilin , Xie Yutong , Li Juan , Jiang Yong , Zhu Yingjie , Guo Fukun , Zhang Lin 
Published: November 2024

Abstract

Mood disorders, such as depression, are strongly associated with cocaine withdrawal, which increases the risk of relapse1. Unlike many other addictive substances, cocaine is associated with chronic withdrawal symptoms, which often manifest as negative emotional states, including anxiety and depression2–4. However, the efficacy of antidepressant drugs in treating cocaine-induced depression is limited and controversial. Here we show that the distinct neural mechanisms underlying depressive-like behaviors induced by cocaine withdrawal. In contrast to earlier research protocols, we precisely classified cocaine withdrawal mice into several distinct phenotypes using receiver operating characteristic (ROC) curves and discovered enhanced neurogenesis in the dorsal dentate gyrus in anxiety- and depressive-like (AD) mice. Suppressing neurogenesis through the inactivation of Rac1-GTPase in D1R-expressing neurons specifically reversed depressive-like behaviors rather than anxiety-like behavior. Additionally, the neurogenesis-enhancing drug fluoxetine exacerbated depressive-like behaviors in AD mice, while neurogenesis-independent drugs alleviated depressive-like behaviors in AD mice. This study unravels a unique neurobiological mechanism for depression symptoms induced by cocaine withdrawal, providing a new perspective for future clinical treatment of cocaine withdrawal-induced depressive symptoms, and suggests Rac1 as a potential target for antidepressant therapeutic interventions.
Altered gut microbiome and metabolism in synucleinopathies and iRBD using multimodal differential abundance analyses
Authors: Du Juanjuan , Huang Pei , Zhang Pingchen , Gao Chao , Liu Jin , Huang Maoxin , Li Hongxia , Shen Xin , Tan Yuyan , Chen Shengdi 
Published: November 2024

Abstract

Background and Objectives:
The microbiota-gut-brain axis has been suggested to play an important role in synucleinopathy. Microbiota dysbiosis may occur in synucleinopathies including multiple system atrophy (MSA) and Parkinson’s disease (PD), however, the results of the microbiota were heterogeneous. Here we performed a cross-sectional study to profile gut microbiota across Idiopathic rapid-eye-movement sleep behavior disorder (iRBD), MSA, PD, and healthy controls (HCs) using multimodal differential abundance analyses based on DADA2 denoising algorithm and operational taxonomic unit (OTU) clustering method.
Methods
Gut microbiota and fecal Short-chain fatty acids (SCFAs) levels were measured in 37 iRBD, 70 MSA, 104 PD, and 61 HCs matched by age, gender and BMI, using 16S rRNA sequencing and gas chromatography-mass spectrometry respectively. Additionally, the samples were divided into training set and testing set to ensure robustness in our findings.
Results
Gut microbiota compositions were significantly altered in iRBD, MSA, and PD. The increase in the abundance of pro-inflammatory bacteria and decrease in the abundance of SCFA-Producing bacteria were observed in iRBD, MSA, and PD. Butyricicoccus remained distinctive among the overlapping gut microbiota genera of iRBD, MSA, and PD compared to HCs as revealed by random forest analysis. The fecal SCFAs levels (acetic acid, butyric acid, and isovaleric acid) were also altered in iRBD, MSA, and PD. The combination of differential microbiota and SCFAs could improve the accuracy of predictive models in the diagnosis and differential diagnosis of synucleinopathies.
Conclusions
Microbiota dysbiosis was observed in iRBD, sharing overlapping gut microbiota changes with synucleinopathies, indicating microbiota dysbiosis might be an early change in the disease process of synucleinopathies. Consequent functional alterations, such as SCFA changes, may provide microbiological explanations for pathogenesis of synucleinopathy. We identified Butyricicoccus as a biomarker for synucleinopathy, sharing by iRBD, MSA and PD, which may be a potential hallmark of phenoconversion of RBD to synucleinopathy. The combination of microbiota and SCFAs may be potential biomarkers in the diagnosis and differential diagnosis of synucleinopathies.
Naive weighting of Earth system models overestimates future carbon losses from tropical ecosystems
Authors: Meunier Felicien , Bauters Marijn , Boeckx Pascal , De Hertog Steven , Verbeeck Hans 
Published: November 2024

Abstract

Tropical ecosystems are critical carbon reservoirs and sinks, holding more than 200 Pg of aboveground carbon. However, global changes threaten those carbon stocks by altering precipitation and evapotranspiration patterns. This study leverages Earth system model (ESM) simulations from the latest phase of the Coupled Model Intercomparison Project (CMIP6) to assess future tropical carbon storage potential by linking the current tropical climate and state of the art tropical vegetation biomass maps. We find that weighting ESM - according to their ability to reproduce spatial patterns of water deficit observed in the tropics - reduces the estimated carbon losses compared with a naive average. Yet, our results indicate that tropical ecosystems could still experience substantial carbon losses, particularly under high-emission scenarios (SSP5-8.5), with predictions ranging from 23 (weighted average) to 37 (naive average) PgC by 2100, principally driven by the Amazon transition towards drier ecosystems. These findings underscore the need for accurate model representations of present-day climates to refine predictions of future sink-source balances of carbon in tropical ecosystems.
Sperm DNA methylation landscape and its links to male fertility in a non-model teleost using EM-seq
Authors: Pappas Fotis , Johnsson Martin , Andersson Göran , Debes Paul V. , Palaiokostas Christos 
Published: November 2024

Abstract

Male fertility in fish is often overlooked despite its critical importance to reproductive success in nature and captivity. Differential DNA methylation due to epigenetic phenomena plays a crucial role in regulating gene expression, and understanding such patterns in sperm may provide insights into male fertility. This study investigated the DNA methylation landscape in spermatozoa of domesticated Arctic charr (Salvelinus alpinus) and its associations with sperm quality parameters. Computer assisted-semen analysis (CASA) was performed in 48 sperm samples of farmed Arctic charr, followed by enzymatic methylation sequencing (EM-seq). Our results showed that the DNA of Arctic charr sperm is highly methylated (mean value of ~86%), though variations were observed in genomic features involved in gene regulation. Methylation at variable CpG sites exhibited regional correlation decaying by physical distance, while methylation similarities among individuals were strongly coupled with genetic variation and mirrored pedigree structure. Comethylation network analyses for promoters, CpG islands and first introns revealed genomic modules significantly correlated with sperm quality traits (P < 0.05; Bonferroni adjusted), with distinct patterns suggesting a resource trade-off between sperm concentration and kinematics. Furthermore, annotation and gene-set enrichment analysis highlighted biological mechanisms related to spermatogenesis, cytoskeletal regulation, and mitochondrial function, all vital to sperm physiology. These findings suggest that DNA methylation is a critical and fundamental factor influencing male fertility in Arctic charr, providing insights into the underlying mechanisms of male reproductive success.
Flatbands from Bound States in the Continuum for Orbital Angular Momentum Localization
Authors: Zhang Baile , zhu Weiwei , Zou Hong-yu , Ge Yong , Wang Yin , Cheng Zheyu , Wang Bing-bing , Yuan Shouqi , Sun Hong-xiang , Xue Haoran 
Published: November 2024

Abstract

A flatband material is a system characterized by energy bands with zero dispersion, allowing for the compact localization of wavefunctions in real space. This compact localization significantly enhances inter-particle correlations and light-matter interactions, leading to notable advancements such as fractional Chern insulators in condensed matter systems and flat-band lasers in photonics. Previous flatband platforms, including twisted bilayer graphene and artificial kagome/Lieb lattices, typically focused on nondegenerate flatbands, lacking access to the high degeneracy that can facilitate the localization of orbital angular momentum (OAM). Here, we propose a general framework to construct highly degenerate flatbands from bound states in the continuum (BICs)--a concept originating from quantum theory but significantly developed in photonics and acoustics in recent years. The degeneracy of flatbands is determined by the number of BICs within each unit cell in a lattice. We experimentally validate this approach in two-dimensional (2D) and three-dimensional (3D) acoustic crystals, demonstrating flatbands with 4-fold and 12-fold degeneracies, respectively. The high degeneracy provides sufficient internal degrees of freedom, enabling the selective excitation of localized OAM at any position in any direction. Our results pave the way for exploring BIC-constructed flatbands and their localization properties.
Comparing the Effectiveness of Gratitude Intervention and Behavioral Activation Technique in Breast Cancer Patients: A Randomized Trial
Authors: Shariatmadari Haniyeh , Taheri-Kharameh Zahra , Kamaliuon Noora , Abadi Bahram Ali Ghanbari Hasem , Shokouhi-Tabar Mahmoud 
Published: November 2024

Abstract

Background: Breast cancer diagnosis and treatment can lead to significant psychological distress, including anxiety and depression. Positive psychology interventions, such as Gratitude Intervention (GI) and Behavioral Activation (BA), have shown promise in managing mental health issues. This study aims to evaluate and compare the effects of GI and BA on anxiety and depression levels among women with breast cancer.
Method: This study randomly assigned 45 breast cancer patients from a hospital in Mashhad, Iran, into two groups: the gratitude group (n=22) and the BA group (n=23). The participants underwent six weekly 45-minute sessions of their respective interventions. The Hospital Anxiety and Depression Scale (HADS) was employed to assess anxiety and depression levels prior to and following the intervention. Statistical analyses were conducted to ascertain the relative effectiveness of the two methods.
Results: Following the intervention, both the GI and BA groups exhibited a statistically significant reduction in anxiety scores. However, the depression score changes were not statistically significant. The mean anxiety scores in the GI group decreased from 19.54 ± 3.63 to 17.00 ± 1.79, while in the BA group, anxiety scores decreased from 21.43 ± 3.65 to 18.73 ± 2.94. The BA group demonstrated a greater reduction in anxiety scores compared to the GI group, with a mean change of 2.70 ± 0.71 versus 2.54 ± 1.84, respectively. This difference was statistically significant (p=0.022).
Conclusion: The study suggests that both gratitude exercises and BA may be beneficial in mitigating anxiety among breast cancer patients, with BA demonstrating potentially greater efficacy. Further research with larger samples and longer follow-up periods is needed to confirm these preliminary findings.
AdditiveGDL: Generative deep learning for predicting local thermal distributions in metal 3D-printed layers
Authors: Guirguis David , Tucker Conrad , Beuth Jack 
Published: November 2024

Abstract

In metal additive manufacturing, comprehending the intricate thermal dynamics during the printing process is paramount. These dynamics have far-reaching effects on various critical aspects including microstructure and mechanical properties, fatigue life, residual stresses, dimensional accuracy, shape integrity, and surface quality. Additionally, the scan strategy significantly impacts heat accumulation, especially at geometric features with sharp corners, overhangs, and thin walls. Thus, predicting heat distribution given the scan strategy becomes crucial. While numerical simulations using finite element methods are common, they can be computationally prohibitive for complex parts. In this paper, we propose a method that leverages constrained generative neural networks to predict the local thermal distribution given the laser toolpath. By identifying critical regions of heat accumulation, we can optimize geometry, and scan paths, ultimately enhancing the quality and reliability of 3D-printed metal components. Results show that generative deep learning offers an alternative approach to predicting the thermal field of printed layers efficiently.
Characterizing changes in cranberry phenology from 1958 to 2022: Implications for spring frost protection in Massachusetts, United States
Authors: Bhatti Sandeep , Jeranyama Peter , Kennedy Casey D. , Buda Anthony R. , Ghantous Katherene , Millar David J. , DeMoranville Carolyn J. 
Published: November 2024

Abstract

Warmer temperatures associated with climate change have affected the phenology of most plants, but limited information exists for the American cranberry (Vaccinium macrocarpon Ait.). We examined long-term spatiotemporal trends in cranberry bud development during spring using detailed field observations of cranberry bud stages over a 65-yr period, spanning from 1958–2022. A growing degree day (GDD) model was further used to interpret the observed trends in bud development over the study period. To assess spatial variability in cranberry bud development, the GDDs were computed using gridded weather data for four counties of Massachusetts, representing 85% of the state’s cranberry acreage. A Theil-Sen linear regression model was implemented to determine trends in the occurrence of the cabbage head stage. We found significant temporal trends (p-value < 0.01) in the annual timing of white bud and cabbage head stages using the field observations, which were occurring 18 to 20 days earlier than was observed 65 years ago in the spring. GDDs accumulated at a faster rate in spring towards the end of the study period due to rising mean air temperature. Analysis of 65 years of gridded data revealed a significant trend (p-value < 0.01) of earlier phenological development across the four counties. The rate of advancement in cabbage head stage ranged from -0.15 to -0.25 d yr -1 across the study area. These findings highlight the need to update frost forecasting models that account for changes in growth schedule of cranberry.
Technical assessment of 3D-printed spur gears produced from recycled PLA
Authors: Hasan Mohammad Raquibul , Davies Ian J. , Pramanik Alokesh , John Michele , Biswas Wahidul K. 
Published: November 2024

Abstract

Plastic gears are primarily utilised in manufacturing and automotive industries due to their quiet operation, resistance to corrosion, and lightweight characteristics. Traditionally, injection moulding (IM) has been the preferred method for producing gears. However, the high cost associated with IM has made additive manufacturing (otherwise known as “3D printing”) an increasingly attractive alternative. This study investigated the potential benefits of 3D-printed spur gears made from three distinct types of polylactic acid (PLA) materials: recycled PLA (rPLA), blended PLA, and virgin PLA (vPLA). Gears with varying tooth counts were designed based on commercially available models and printed using optimised printing parameters, including layer height, infill density and nozzle temperature. The performance of polymer gears depends on several engineering characteristics, including wear resistance, running load, speed, and operating temperature. To assess these factors, sound, temperature, wear loss, wear rate, and service life were measured using a custom-built testing machine at rotational speeds of 500, 1000, and 1500 rpm under a torque of 1.5 Nm. The results were compared with those of injection-moulded PLA and nylon gears under the same testing conditions. The experimental findings revealed that the rPLA gears exhibited the poorest performance across all measured metrics. In contrast, the blended PLA gears demonstrated wear characteristics similar to those of the vPLA gears, although they still fell short of the performance of the injection-moulded gears.
Mapping and Functional Characterization of the Golden Fruit 1 (gf1) in Melon (Cucumis melo L.)
Authors: Li Shuai , Wang Huihui , Li Yang , Jing Feng , Xu Yuanchao , Deng Shijun , Wang Naonao , Zhang Zhonghua , Chai Sen 
Published: November 2024

Abstract

Melon (Cucumis melo L.) is a globally cultivated vegetable crop with substantial economic importance. Fruit color is an important factor that affect the appearance quality and economic value of crops, which is determined mainly by the type and concentration of pigments such as chlorophyll, carotenoids, anthocyanins, and flavonoids. Identifying and utilizing the genetic loci that govern melon fruit color is crucial for guiding breeding efforts aimed at enhancing melon rind coloration. In this study, we identified an EMS-induced mutant that produces golden-colored fruit which named gf1. Through MUTmap and map-based cloning, we narrowed the gf1 locus to an 862 kb region containing 28 SNPs, consistent with typical alkylation-induced mutations. Of these SNPs, only one was located in a coding region, resulting in a stop-gained mutation in the gene MELO3C008847, which exhibits the highest sequence similarity to AtEGY1 in Arabidopsis. Genome editing of CsEGY1, the homolog of CmEGY1 in cucumber, led to the golden fruit. Transcriptome and metabolome analysis reveal that flavonoid and carotenoid biosynthesis pathways were changed, which may affect the appearance quality and flavor of gf1 fruit. The identification and characterization of egy1 offer new insights into modifying fruit color in melons, providing valuable implications for future breeding programs.
Clinical Indications for Dialysis: A study of patient Demographics and Outcomes at Hargeisa Group Hospital
Authors: Ibrahim Naema , Abdikadir Abdikani , Ali Abdirahman Omer 
Published: November 2024

Abstract

Background: Chronic kidney disease (CKD) is a significant global health concern, with end-stage renal disease (ESRD) requiring dialysis or transplantation for survival. Data on clinical indications for dialysis initiation in resource-limited settings like Somaliland are scarce. This study aimed to identify the primary clinical indications for dialysis at Hargeisa Group Hospital in Somaliland.
Methods: A retrospective cross-sectional study was conducted using medical records of 123 patients undergoing hemodialysis from May 2022 to August 2024. Demographic and clinical data, including indications for dialysis initiation, were analyzed using descriptive statistics.
Results: Uremic syndromes, particularly uremic gastritis and uremic encephalopathy, were the most prevalent reasons for dialysis initiation. These findings differed from previous studies in developed countries, highlighting potential regional variations in CKD presentation and access to care. Significant disparities in dialysis indications across regions were observed, with Maroodijeex accounting for the majority of cases.
Discussion: The study highlights the significant burden of CKD in Somaliland and the need for improved early detection and management. The findings have important implications for strengthening primary care services, investing in infrastructure and personnel, promoting equitable access to dialysis, and fostering collaborative partnerships to address the growing burden of CKD.
Conclusion: This study provides valuable insights into the clinical indications for dialysis in Somaliland, emphasizing the need for a multifaceted approach to address the growing burden of CKD in the region. Strengthening primary care, investing in infrastructure, promoting equitable access, and fostering partnerships are crucial for improving kidney care and achieving better health outcomes for patients.
Causal relationships between smoking, alcohol consumption frequency, coffee intake and osteomyelitis: a univariable and multivariable Mendelian randomization study
Authors: Feng Tianxuan , Chen Peisheng , Lin Dongze , Zheng Ke , Liu Jiajie , Lin Fengfei 
Published: November 2024

Abstract

Background
This study aimed to evaluate the causal relationships between smoking, alcohol consumption and coffee intake with osteomyelitis through Mendelian randomization (MR) analysis.
Methods
Data on smoking, alcohol consumption, coffee intake, and osteomyelitis-related single nucleotide polymorphisms (SNPs) were obtained from the open Genome-Wide Association Study (GWAS) database of the Integrated Epidemiology Unit. We employed univariable Mendelian randomization (MR) methods, including MR‒Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode, to investigate the causal relationships between the three exposures (smoking initiation, alcohol consumption frequency, and coffee intake) and osteomyelitis. Sensitivity analyses, including heterogeneity tests, horizontal pleiotropy tests, and leave-one-out (LOO) analyses, were subsequently conducted. Furthermore, multivariable MR (MVMR) analyses were performed to simultaneously consider the effects of the three exposure factors on osteomyelitis.
Results
On the basis of the results of the univariable Mendelian randomization analysis via the inverse variance weighted method, a significant causal relationship was found between smoking initiation and alcohol consumption frequency with osteomyelitis, whereas no significant association was detected for coffee intake. Specifically, smoking initiation (p ≤ 0.001, odds ratio (OR) = 1.642, 95% confidence interval (CI): 1.321–2.041) and alcohol consumption frequency (p = 0.003, OR = 1.384, 95% CI: 1.116–1.716) were identified as risk factors for osteomyelitis. With respect to the sensitivity analysis for MR results, there was no heterogeneity or horizontal pleiotropy. Leave-one-out (LOO) analysis confirmed the robustness of the univariable MR results. Additionally, multivariable MR analysis revealed that smoking (p ≤ 0.001, OR = 1.573, 95% CI: 1.259–1.965) and alcohol consumption (p = 0.011, OR = 1.312, 95% CI: 1.064–1.618) remained significant risk factors for osteomyelitis when all three factors were considered simultaneously, whereas coffee intake was not statistically significant (p = 0.528).
Conclusion
This Mendelian randomization study revealed that smoking and alcohol consumption are significant risk factors for osteomyelitis, whereas coffee intake is not significantly associated with osteomyelitis. These findings provide important insights for osteomyelitis prevention and public health strategies.