bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing friction stir welding efficiency through rotational speed adjustment: a microstructural and mechanical analysis of Al-Cu alloy
Authors: Sasikala P , Madhusudhan R 
Published: January 2024

Abstract
Friction stir welding (FSW) has gained prominence in the aerospace and automotive industries due to its ability to produce high-strength and defect-free welds in aluminum alloys. The present investigation focuses on the impact of different tool rotational speeds (such as 700 rpm, 900 rpm, 1100 rpm and 1300 rpm), on the microstructure and mechanical characteristics of friction stir welded Al-Cu alloys. With the use of optical microscopy, scanning electron microscopy (SEM), x-ray diffraction (XRD), and evaluations of hardness, tensile characteristics, and fracture behavior, a thorough analysis was carried out. The weld nugget zone contained significant changes in grain size and shape as a function of rotational speed, as shown by microstructural analysis. The grain structure gradually became more refined when the rotating speed was raised from 900 to 1500 rpm. According to SEM observations, at faster speeds, the weld zone showed fewer defects per unit area and better bonding properties, which might be attributed to better material flow and plastic deformation. The effect was further clarified by XRD analysis, which showed differences in phase composition with varying rotating speeds. Evaluations of the mechanical properties showed a significant relationship between rotating speed and the mechanical performance of the welds. Hardness measurements showed that as rotating speed increased, hardness levels gradually increased. Welds made at faster rotational speeds had better elongation and tensile qualities, according to tensile tests. Additionally, fracture behavior study revealed that higher rotational speed welds displayed a more ductile fracture mode, indicating increased toughness.
Phase transitions in the mini-batch size for sparse and dense two-layer neural networks
Authors: Marino Raffaele , Ricci-Tersenghi Federico 
Published: January 2024

Abstract
The use of mini-batches of data in training artificial neural networks is nowadays very common. Despite its broad usage, theories explaining quantitatively how large or small the optimal mini-batch size should be are missing. This work presents a systematic attempt at understanding the role of the mini-batch size in training two-layer neural networks. Working in the teacher-student scenario, with a sparse teacher, and focusing on tasks of different complexity, we quantify the effects of changing the mini-batch size m. We find that often the generalization performances of the student strongly depend on m and may undergo sharp phase transitions at a critical value

m

c

, such that for

m
<

m

c

the training process fails, while for

m
>

m

c

the student learns perfectly or generalizes very well the teacher. Phase transitions are induced by collective phenomena firstly discovered in statistical mechanics and later observed in many fields of science. Observing a phase transition by varying the mini-batch size across different architectures raises several questions about the role of this hyperparameter in the neural network learning process.
Engineering zeolitic imidazolate framework-8 nanoparticles for smart drug delivery systems
Authors: Wu Cuixiu , Huang Wanyuan , Du Fengyi , Zhang Miaomiao , Qian Hanliang 
Published: January 2024

Abstract
Zeolitic imidazolate framework-8 nanoparticles (ZIF-8 NPs) are emerging metal–organic framework nanomaterials composed of 2-methylimidazole and zinc ions, which are widely used in biomedical fields due to their distinctive features such as high porosity, bioresponsive degradation, and superior biocompatibility. Especially, the advanced research of ZIF-8 NPs in smart drug delivery systems is providing unique insights into the rational design of versatile nanomedicines for the treatment and diagnosis of serious diseases. This article provides a comprehensive review and outlook on ZIF-8 NPs-based smart drug delivery systems (SDDSs) including the synthesis methods, drug loading strategies, surface modification, and stimuli-responsive release. In particular, we focus on the advantages of ZIF-8 NPs-based drug loading strategies between the metal coordination-based active loading and the physical packaging-based passive loading. Finally, the opportunities and challenges of ZIF-8 NPs as smart drug delivery carriers are discussed.
Dalston Children’s Centre
Authors: Brooke Stephen 
Published: January 2024

Abstract
The Dalston Children’s Centre was founded in the early 1980s to provide free and non-sexist, non-racist, non-heterosexist childcare to parents in Hackney. This chapter explores the history of the Dalston Children’s Centre as an example of alternative culture in 1980s London. In particular, it considers the Centre as an experiment in feminism, lesbian rights, and anti-racism. There are connections here with the struggles of Gay’s the Word bookshop and feminism in the 1980s. The chapter also reflects upon the tensions within radical or alternative politics in the 1980s.
The Anti-Apartheid March
Authors: Brooke Stephen 
Published: January 2024

Abstract
In June 1984, Margaret Thatcher hosted P. W. Botha, the Prime Minister of apartheid South Africa, on a state visit to London. The visit provoked intense opposition from the anti-apartheid movement in London, and a major demonstration was held to protest against the visit. This chapter examines that march as an illustration of London’s place as a locus of global radicalism, in this case the anti-apartheid movement. As the chapter shows, London had long been a centre of anti-apartheid activism. In the 1980s, that profile was heightened, in part by the growing visibility and strength of a global anti-apartheid movement, and in part by the support lent to the anti-apartheid cause by the GLC. The chapter argues that questions of race and anti-racism in the 1980s could only be discussed as a connection between the local and the global.
An Intersectoral Approach to Hypertension Care: Solutions for Improving Blood Pressure Control in São Paulo, Brazil
Authors: Avezum Álvaro , Drager Luciano F , Reiker Theresa , Bigoni Alessandro , Leonel Lays P , Abreu Ariane , Bortolotto Luiz , Palmeirim Marta Sólveig , Silveira Mariana , Aquino Beatriz , Maggion Rafael Venijio , Baxter Yara Carnevalli , Cobos Muñoz Daniel , Dib Karina Mauro , Amaral Amaury Zatorre , Saric Jasmina , Jarrett Caitlin , Boch Johannes 
Published: January 2024

Abstract

BACKGROUND
Hypertension is the leading risk factor for cardiovascular diseases (CVDs) and a major public health issue worldwide. In Brazil, it affects approximately 52.5% of the adult population. We describe the solutions package and the impact of a population health initiative in São Paulo city, following the CARDIO4Cities approach for the management of cardiovascular risk.

METHODS
Using a design thinking approach, interventions were developed with a coalition of local and international stakeholders to address needs of patients, healthcare professionals, and the health system. The resulting solution package was checked to comply with guidelines for non-communicable disease and hypertension management. Clinical impact was measured by extracting the hypertension cascade of care—monitored, diagnosis, treatment, and control—from medical records.

RESULTS
Under the leadership of the municipal health authorities, nine solutions were piloted and scaled across the city. Solutions conform with local and international best-practices. Between October 2017 and December 2021, 11,406 patient records were analyzed. Results showed a 40% increase in monitored patients (patients with at least one blood pressure, BP, measurement); reduced proportions of patients diagnosed among those with available BP measurements (72%–53%) and treated among diagnosed (93%–85%); and an improvement in controlled patients among those receiving treatment (16%–27%).

CONCLUSIONS
The solution package described in this study was correlated with increased BP control. The implementation methodology and results add to the body of real-world evidence supporting population health implementation science in Brazil and beyond.
The Pathogenesis and Impact of Arterial Stiffening in Hypertension: The 2023 John H. Laragh Research Award
Authors: Liu Jing , Wu Jing 
Published: January 2024

Abstract
Fifty years ago, Dr. John Laragh brought forward the “vasoconstriction-volume hypothesis” of hypertension. This is Ohm’s Law in blood pressure regulation, explicating hypertension as a consequence of increased peripheral vascular resistance, cardiac output, or both. Resistance vessels, those of a diameter less than 200 μm, determines mean arterial pressure by controlling peripheral vascular resistance. In comparison, large capacitance arteries, particularly the aorta, confines the systolic and diastolic blood pressure in physiological range through the “windkessel effect.” Loss of this cushioning function results in aortic stiffening and isolated systolic hypertension, both of which are independently associated with increased risk for coronary, cerebral, and renal diseases. Aortic stiffening is both a cause and a consequence of hypertension. On one hand, aortic stiffness precedes the onset of hypertension in populations and experimental models, and hemodynamic derangements related to aortic stiffening contributes to the development of hypertension by promoting renal dysfunction. On the other hand, the vasculature itself is a hypertensive target organ and hypertensive mechanical stretch directly induces the pathogenesis of aortic adventitial remodeling. Various cell types, including bone marrow-derived circulating fibrocytes, vascular stem cell antigen-1 positive progenitors, and endothelial to mesenchymal transition, and to a lesser extent resident fibroblasts, contribute to adventitial matrix deposition and aortic stiffening in hypertension. Vascular smooth muscle stiffness is another important contributor of aortic stiffening. Understanding the roles of immune components and specific signal pathways in the pathogenesis aortic stiffening paves the path to novel antihypertensive and anti-fibrosis therapies.
Hypertension and Mild Cognitive Impairment: State-of-the-Art Review
Authors: Shajahan Sultana , Peters Ruth , Carcel Cheryl , Woodward Mark , Harris Katie , Anderson Craig S 
Published: January 2024

Abstract

BACKGROUND
Mid-life hypertension is associated with cognitive decline and dementia in later life. Reducing high blood pressure (BP) with antihypertensive agents is a well-researched strategy to prevent dementia and mild cognitive impairment (MCI). However, there is still limited direct evidence to support the approach, and particularly for the treatment of the very old and those with existing MCI.

METHODS
This review presents an overview of the current evidence for the relationship between MCI and hypertension, and of the potential pathophysiological mechanisms related to cognitive decline and incidence dementia in relation to aging.

RESULTS
Although observational data are near consistent in showing an association between mid-life hypertension and MCI and/or dementia, the evidence in relation to hypertension in younger adults and the very old (age &gt;80 years) is much more limited. Most of the commonly available antihypertensive agents appear to provide beneficial effects in reducing the risk dementia, but there is limited evidence to support such treatment in those with existing MCI.

CONCLUSIONS
Further studies are needed to determine the optimal levels of BP control across different age groups, especially in adults with MCI, and which class(es) of antihypertensive agents and duration of treatment best preserve cognitive function in those at risk of, or with established, MCI.
Seq-InSite: sequence supersedes structure for protein interaction site prediction
Authors: Hosseini SeyedMohsen , Golding G Brian , Ilie Lucian 
Published: January 2024

Abstract

Motivation
Proteins accomplish cellular functions by interacting with each other, which makes the prediction of interaction sites a fundamental problem. As experimental methods are expensive and time consuming, computational prediction of the interaction sites has been studied extensively. Structure-based programs are the most accurate, while the sequence-based ones are much more widely applicable, as the sequences available outnumber the structures by two orders of magnitude. Ideally, we would like a tool that has the quality of the former and the applicability of the latter.

Results
We provide here the first solution that achieves these two goals. Our new sequence-based program, Seq-InSite, greatly surpasses the performance of sequence-based models, matching the quality of state-of-the-art structure-based predictors, thus effectively superseding the need for models requiring structure. The predictive power of Seq-InSite is illustrated using an analysis of evolutionary conservation for four protein sequences.

Availability and implementation
Seq-InSite is freely available as a web server at http://seq-insite.csd.uwo.ca/ and as free source code, including trained models and all datasets used for training and testing, at https://github.com/lucian-ilie/Seq-InSite.
methyLImp2: faster missing value estimation for DNA methylation data
Authors: Plaksienko Anna , Di Lena Pietro , Nardini Christine , Angelini Claudia 
Published: January 2024

Abstract

Motivation
methyLImp, a method we recently introduced for the missing value estimation of DNA methylation data, has demonstrated competitive performance in data imputation compared to the existing, general-purpose, approaches. However, imputation running time was considerably long and unfeasible in case of large datasets with numerous missing values.

Results
methyLImp2 made possible computations that were previously unfeasible. We achieved this by introducing two important modifications that have significantly reduced the original running time without sacrificing prediction performance. First, we implemented a chromosome-wise parallel version of methyLImp. This parallelization reduced the runtime by several 10-fold in our experiments. Then, to handle large datasets, we also introduced a mini-batch approach that uses only a subset of the samples for the imputation. Thus, it further reduces the running time from days to hours or even minutes in large datasets.

Availability and implementation
The R package methyLImp2 is under review for Bioconductor. It is currently freely available on Github https://github.com/annaplaksienko/methyLImp2.
Microbial interactions from a new perspective: reinforcement learning reveals new insights into microbiome evolution
Authors: Ghadermazi Parsa , Chan Siu Hung Joshua 
Published: January 2024

Abstract

Motivation
Microbes are essential part of all ecosystems, influencing material flow and shaping their surroundings. Metabolic modeling has been a useful tool and provided tremendous insights into microbial community metabolism. However, current methods based on flux balance analysis (FBA) usually fail to predict metabolic and regulatory strategies that lead to long-term survival and stability especially in heterogenous communities.

Results
Here, we introduce a novel reinforcement learning algorithm, Self-Playing Microbes in Dynamic FBA, which treats microbial metabolism as a decision-making process, allowing individual microbial agents to evolve by learning and adapting metabolic strategies for enhanced long-term fitness. This algorithm predicts what microbial flux regulation policies will stabilize in the dynamic ecosystem of interest in the presence of other microbes with minimal reliance on predefined strategies. Throughout this article, we present several scenarios wherein our algorithm outperforms existing methods in reproducing outcomes, and we explore the biological significance of these predictions.

Availability and implementation
The source code for this article is available at: https://github.com/chan-csu/SPAM-DFBA.
nf-core/nanostring: a pipeline for reproducible NanoString nCounter analysis
Authors: Peltzer Alexander , Mohr Christopher , Stadermann Kai B , Zwick Matthias , Schmid Ramona 
Published: January 2024

Abstract

Motivation
The NanoString™ nCounter® technology platform is a widely used targeted quantification platform for the analysis of gene expression of up to ∼800 genes. Whereas the software tools by the manufacturer can perform the analysis in an interactive and GUI driven approach, there is no portable and user-friendly workflow available that can be used to perform reproducible analysis of multiple samples simultaneously in a scalable fashion on different computing infrastructures.

Results
Here, we present the nf-core/nanostring open-source pipeline to perform a comprehensive analysis including quality control and additional features such as expression visualization, annotation with additional metadata and input creation for differential gene expression analysis. The workflow features an easy installation, comprehensive documentation, open-source code with the possibility for further extensions, a strong portability across multiple computing environments and detailed quality metrics reporting covering all parts of the pipeline. nf-core/nanostring has been implemented in the Nextflow workflow language and supports Docker, Singularity, Podman container technologies as well as Conda environments, enabling easy deployment on any Nextflow supported compatible system, including most widely used cloud computing environments such as Google GCP or Amazon AWS.

Availability and implementation
The source code, documentation and installation instructions as well as results for continuous tests are freely available at https://github.com/nf-core/nanostring and https://nf-co.re/nanostring.
Targeted deletion of NR2F2 and VCAM1 in theca cells impacts ovarian follicular development: insights into polycystic ovary syndrome?
Authors: Candelaria Nicholes R , Richards JoAnne S 
Published: January 2024

AbstractDefining features of polycystic ovary syndrome (PCOS) include elevated expression of steroidogenic genes, theca cell androgen biosynthesis, and peripheral levels of androgens. In previous studies, we identified vascular cell adhesion molecule 1 (VCAM1) as a selective androgen target gene in specific NR2F2/SF1 (+/+) theca cells. By deleting NR2F2 and VCAM1 selectively in CYP17A1 theca cells in mice, we documented that NR2F2 and VCAM1 impact distinct and sometimes opposing theca cell functions that alter ovarian follicular development in vivo: including major changes in ovarian morphology, steroidogenesis, gene expression profiles, immunolocalization images (NR5A1, CYP11A1, NOTCH1, CYP17A1, INSL3, VCAM1, NR2F2) as well as granulosa cell functions. We propose that theca cells impact follicle integrity by regulating androgen production and action, as well as granulosa cell differentiation/luteinization in response to androgens and gonadotropins that may underlie PCOS.
Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study
Authors: Peña-Martín Jesús , Belén García-Ortega María , Palacios-Ferrer José Luis , Díaz Caridad , Ángel García María , Boulaiz Houria , Valdivia Javier , Jurado José Miguel , Almazan-Fernandez Francisco M , Arias Santiago Salvador , Vicente Francisca , del Val Coral , Pérez del Palacio José , Marchal Juan Antonio 
Published: January 2024

Abstract

Background
Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge.

Objectives
To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management.

Methods
In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM.

Results
We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample.

Conclusions
These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM.
Long-term oncological outcomes of robotic versus laparoscopic gastrectomy for gastric cancer: multicentre cohort study
Authors: Li Zheng-yan , Wei Bo , Zhou Yan-bing , Li Tai-yuan , Li Ji-peng , Zhou Zhi-wei , She Jun-jun , Qin Xin-gan , Hu Jian-kun , Li Yong-Xiang , Qian Feng , Shi Yan , Cui Hao , Tian Yu-long , Gao Geng-mei , Gao Rui-zi , Liang Cheng-cai , Shi Fei-yu , Yu Li-Jun , Yang Kun , Zhang Shang-xin , Yu Pei-wu , Zhao Yong-liang 
Published: January 2024

Abstract

Background
The aim of this multicentre cohort study was to compare the long-term oncological outcomes of robotic gastrectomy (RG) and laparoscopic gastrectomy (LG) for patients with gastric cancer.

Methods
Patients with gastric cancer who underwent radical gastrectomy by robotic or laparoscopic approaches from 1 March 2010 to 31 December 2018 at 10 high-volume centres in China were selected from institutional databases. Patients receiving RG were matched 1 : 1 by propensity score with patients undergoing LG. The primary outcome was 3-year disease-free survival. Secondary outcomes were overall survival and disease recurrence.

Results
Some 2055 patients who underwent RG and 4309 patients who had LG were included. The propensity score-matched cohort comprised 2026 RGs and 2026 LGs. Median follow-up was 41 (i.q.r. 39–58) months for the RG group and 39 (38–56) months for the LG group. The 3-year disease-free survival rates were 80.8% in the RG group and 79.5% in the LG group (log rank P = 0.240; HR 0.92, 95% c.i. 0.80 to 1.06; P = 0.242). Three-year OS rates were 83.9 and 81.8% respectively (log rank P = 0.068; HR 0.87, 0.75 to 1.01; P = 0.068) and the cumulative incidence of recurrence over 3 years was 19.3% versus 20.8% (HR 0.95, 0.88 to 1.03; P = 0.219), with no difference between groups.

Conclusion
RG and LG in patients with gastric cancer are associated with comparable disease-free and overall survival.