bluuebunny/crossref_metadata_2025_split huggingface dataset:
Health hazards of particles in additive manufacturing: a cross-disciplinary study on reactivity, toxicity and occupational exposure to two nickel-based alloys
Authors: Karlsson Hanna L. , Vallabani N. V. Srikanth , Wang Xuying , Assenhöj Maria , Ljunggren Stefan , Karlsson Helen , Odnevall Inger 
Published: November 2023

AbstractThe increasing use of additive manufacturing (AM) techniques (e.g., 3D-printing) offers many advantages but at the same time presents some challenges. One concern is the possible exposure and health risk related to metal containing particles of different sizes. Using the nickel-based alloys Hastelloy X (HX) and Inconel 939 (IN939) as a case, the aim of this cross-disciplinary study was to increase the understanding on possible health hazards and exposure. This was done by performing in-depth characterization of virgin, reused and condensate powders, testing in vitro toxicity (cytotoxicity, genotoxicity, oxidative stress), and measuring occupational airborne exposure. The results showed limited metal release from both HX and IN939, and slightly different surface composition of reused compared to virgin powders. No or small effects on the cultured lung cells were observed when tested up to 100 µg/mL. Particle background levels in the printing facilities were generally low, but high transient peaks were observed in relation to sieving. Furthermore, during post processing with grinding, high levels of nanoparticles (> 100,000 particles/cm3) were noted. Urine metal levels in AM operators did not exceed biomonitoring action limits. Future studies should focus on understanding the toxicity of the nanoparticles formed during printing and post-processing.
Impact of a history of cardiovascular disease and physical activity habits on the incidence of functional disability
Authors: Kodera Remi , Fujihara Kazuya , Koyama Tetsuya , Shiozaki Haruka , Mutsuma Yurie , Yagyuda Noriko , Hatta Mariko , Tsuruoka Kahori , Takeda Yasunada , Araki Atsushi , Sone Hirohito 
Published: November 2023

AbstractWe examined the impact of a history of coronary artery disease (CAD) or cerebrovascular disease (CVD) and physical activity habits on functional disability among community-dwelling Japanese adults. This population-based retrospective cohort study included 10,661 people aged 39–98 years in Japan (5054, men). Median follow-up was 3.7 years. During the study period, 209 functional disabilities occurred in the overall study population. In multivariable analysis, a history of CVD (hazard ratio [HR] 1.57 [95% CI: 1.00–2.45]) and no physical activity habit (HR 1.74 [1.27–2.39]) presented increased risks for functional disability. HRs for functional disability among patients with a CVD history with and without a physical activity habit were 1.68 (0.75–3.74) and 2.65 (1.49–4.71), respectively, compared with individuals without a history of CVD with a physical activity habit. Similar results were observed for CAD. We found no significant difference in the incidence of functional disability between the group with a history of CAD or CVD and physical activity habits and the group with no history of CAD or CVD and without physical activity habits. Physical activity habits had a favorable influence on avoiding functional disability regardless of a history of CAD or CVD. Future prospective studies are needed to clarify these associations.
Efficacy and safety of 5-hydroxytryptamine-3 (5-HT3) receptor antagonists in augmentation with selective serotonin reuptake inhibitors (SSRIs) in the treatment of moderate to severe obsessive–compulsive disorder: a systematic review and meta-analysis of randomized clinical trials
Authors: Eissazade Negin , Mosavari Hesam , Eghdami Shayan , Boroon Mahsa , Ashrafi Faria , Shalbafan Mohammadreza 
Published: November 2023

AbstractObsessive–compulsive disorder (OCD) is the fourth most common mental disorder, and selective serotonin reuptake inhibitors (SSRIs) are the cornerstone of its pharmacological treatment. About 40–60% of the cases are treatment-refractory, and this makes searching for second-line treatment necessary. 5-Hydroxytryptamine-3 (5-HT3) antagonists are among the many medications that have been used in augmentation with SSRIs. In this systematic review and meta-analysis, we assessed the efficacy and safety of 5-HT3 receptor antagonists in augmentation with SSRIs in treating moderate to severe OCD. We searched PubMed, Web of Science, Scopus, Cochrane library, and Google Scholar for relevant trials published up to December 2022. The effect size was the mean difference in Yale-Brown obsessive compulsive scale (Y-BOCS) scores before and after receiving 5-HT3 receptor antagonist drugs in augmentation with SSRIs in moderate to severe OCD patients. We included 6 randomized-controlled trails (RCTs) with 334 patients assessing the effect of the augmentation of SSRIs with ondansetron, granisetron, and tropisetron on treating moderate to severe OCD. Our results were in favor of the experimental group in total (Z = 8.37, P < 0.00001), in the compulsion subgroup (Z = 5.22, P < 0.00001), and in the obsession subgroup (Z = 8.33, P < 0.00001). They are well-tolerated, and have mild side effects and do not result in withdrawal. Augmentation of 5-HT3 antagonists with SSRIs can be beneficial in treating moderate to severe OCD. Further multi-center trials under adequate conditions in longer periods are needed to help come up with a comprehensive action plan.
MESIA: multi-epigenome sample integration approach for precise peak calling
Authors: Park Seung Gwa , Kim Woo-Jin , Moon Jae-I , Kim Ki-Tae , Ryoo Hyun-Mo 
Published: November 2023

AbstractThe assay for transposase-accessible chromatin with sequencing (ATAC-seq) is the most widely used method for measuring chromatin accessibility. Researchers have included multi-sample replication in ATAC-seq experimental designs. In epigenomic analysis, researchers should measure subtle changes in the peak by considering the read depth of individual samples. It is important to determine whether the peaks of each replication have an integrative meaning for the region of interest observed during multi-sample integration. We developed multi-epigenome sample integration approach for precise peak calling (MESIA), which integrates replication with high representativeness and reproducibility in multi-sample replication and determines the optimal peak. After identifying the reproducibility between all replications, our method integrated multiple samples determined as representative replicates. MESIA detected 6.06 times more peaks, and the value of the peaks was 1.32 times higher than the previously used method. MESIA is a shell-script-based open-source code that provides researchers involved in the epigenome with comprehensive insights.
Understanding the social determinants of child mortality in Latin America over the last two decades: a machine learning approach
Authors: Chivardi Carlos , Zamudio Sosa Alejandro , Cavalcanti Daniella Medeiros , Ordoñez José Alejandro , Diaz Juan Felipe , Zuluaga Daniela , Almeida Cristina , Serván-Mori Edson , Hessel Philipp , Moncayo Ana L. , Rasella Davide 
Published: November 2023

AbstractThe reduction of child mortality rates remains a significant global public health challenge, particularly in regions with high levels of inequality such as Latin America. We used machine learning (ML) algorithms to explore the relationship between social determinants and child under-5 mortality rates (U5MR) in Brazil, Ecuador, and Mexico over two decades. We created a municipal-level cohort from 2000 to 2019 and trained a random forest model (RF) to estimate the relative importance of social determinants in predicting U5MR. We conducted a sensitivity analysis training two more ML models and presenting the mean square error, root mean square error, and median absolute deviation. Our findings indicate that poverty, illiteracy, and the Gini index were the most important variables for predicting U5MR according to the RF. Furthermore, non-linear relationships were found mainly for Gini index and U5MR. Our study suggests that long-term public policies to reduce U5MR in Latin America should focus on reducing poverty, illiteracy, and socioeconomic inequalities. This research provides important insights into the relationships between social determinants and child mortality rates in Latin America. The use of ML algorithms, combined with large longitudinal data, allowed us to evaluate the effects of social determinants on health more carefully than traditional models.
Practical prototype for energy management system in smart microgrid considering uncertainties and energy theft
Authors: Saeed Mohammed A. , Sedhom Bishoy E. , Elbaghdadi Abdelrahman S. , Fadl Ahmed W. , Abdelwahab Mohammed S. , Elden Menna H. , Alhasnawi Bilal Naji , Eladl Abdelfattah A. 
Published: November 2023

AbstractThe conventional electrical grid faces significant issues, which this paper aims to address one of most of them using a proposed prototype of a smart microgrid energy management system. In addition to relying too heavily on fossil fuels, electricity theft is another great issue. The proposed energy management system can simultaneously detect electricity theft and implement demand response tactics by employing time-of-use pricing principles and comparing real electricity consumption with grid data. The system uses the Al-Biruni earth radius (BER) optimization algorithm to make smart choices about how to distribute the load, intending to reduce energy consumption and costs without sacrificing comfort. As a bonus, it considers limitations imposed by battery charging/discharging and decentralized power generation. Incorporating sensors and SCADA-based monitoring, the system provides accurate measurement and management of energy usage through load monitoring and control. An intuitive mobile app also helps consumers connect, allowing for more active participation and better control over energy use. Extensive field testing of the prototype shows that by moving loads from peak period to another off-peak period, electricity expenditures can be reduced by up to 48.45%. The energy theft value was calculated to be 1199 W, proving that the system's theft detection model was effective.
Development of an early alert model for pandemic situations in Germany
Authors: Wang Danqi , Lentzen Manuel , Botz Jonas , Valderrama Diego , Deplante Lucille , Perrio Jules , Génin Marie , Thommes Edward , Coudeville Laurent , Fröhlich Holger 
Published: November 2023

AbstractThe COVID-19 pandemic has pointed out the need for new technical approaches to increase the preparedness of healthcare systems. One important measure is to develop innovative early warning systems. Along those lines, we first compiled a corpus of relevant COVID-19 related symptoms with the help of a disease ontology, text mining and statistical analysis. Subsequently, we applied statistical and machine learning (ML) techniques to time series data of symptom related Google searches and tweets spanning the time period from March 2020 to June 2022. In conclusion, we found that a long-short-term memory (LSTM) jointly trained on COVID-19 symptoms related Google Trends and Twitter data was able to accurately forecast up-trends in classical surveillance data (confirmed cases and hospitalization rates) 14 days ahead. In both cases, F1 scores were above 98% and 97%, respectively, hence demonstrating the potential of using digital traces for building an early alert system for pandemics in Germany.
Randomised clinical trial for morphological changes of trabecular meshwork between Kahook dual-blade goniotomy and ab interno trabeculotomy with a microhook
Authors: Arimura Shogo , Iwasaki Kentaro , Orii Yusuke , Komori Ryohei , Takamura Yoshihiro , Inatani Masaru 
Published: November 2023

AbstractWe demonstrated whether the difference of trabecular meshwork remodeling occur depending on the incisional cross-sectional area by comparing Kahook dual-blade goniotomy (KDB) and ab interno trabeculotomy with a microhook. Phakic eyes with primary open-angle or exfoliative glaucoma were randomised into a KDB or a microhook group. The primary outcome was an incisional cross-sectional area quantified by anterior segment optical coherence tomography. In subgroup analysis, the number of patients with the unidentifiable incisional area was compared between the groups. Secondary outcomes were the rate of intraocular pressure changes, the laser flare metre values, corneal endothelial cell densities, the number of glaucoma medications, the usage rate per glaucoma medication type and postoperative complications between the two groups. A total of 29 eyes in 29 patients in the KDB and microhook group were included respectively, with an overall mean age of 72.6 ± 8.1 years. The incisional cross-sectional area of the KDB group was significantly larger at 1 week and at 1, 6 and 12 months (p < 0.01) postoperatively. The number of patients with the nonidentified incisional area was higher at 1, 6 and 12 months postoperatively (p ≤ 0.03) in the microhook group. The flare values in the KDB group were higher than those in the microhook group at 12 months postoperatively (p = 0.02). No significant differences were observed in other secondary outcomes. Incisional cross-sectional area remains larger in eyes treated with KDB goniotomy than in those treated with ab interno trabeculotomy with the microhook, whereas KDB goniotomy did not have an advantage in controlling intraocular pressure postoperatively.Trial registration: UMIN000041290 (UMIN, University Hospital Medical Information Network Clinical Trials Registry of Japan; date of access and registration, 03/08/2020).
Centrosome clustering control in osteoclasts through CCR5-mediated signaling
Authors: Lee Ji-Won , Lee In-Hee , Watanabe Haruhisa , Liu Yunqing , Sawada Kazuaki , Maekawa Masashi , Uehara Shunsuke , Kobayashi Yasuhiro , Imai Yuuki , Kong Sek Won , Iimura Tadahiro 
Published: November 2023

AbstractOsteoclasts uniquely resorb calcified bone matrices. To exert their function, mature osteoclasts maintain the cellular polarity and directional vesicle trafficking to and from the resorbing bone surface. However, the regulatory mechanisms and pathophysiological relevance of these processes remain largely unexplored. Bone histomorphometric analyses inCcr5-deficient mice showed abnormalities in the morphology and functional phenotype of their osteoclasts, compared to wild type mice. We observed disorganized clustering of nuclei, as well as centrosomes that organize the microtubule network, which was concomitant with impaired cathepsin K secretion in culturedCcr5-deficient osteoclasts. Intriguingly, forced expression of constitutively active Rho or Rac restored these cytoskeletal phenotypes with recovery of cathepsin K secretion. Furthermore, a gene-disease enrichment analysis identified thatPLEKHM1, a responsible gene for osteopetrosis, which regulates lysosomal trafficking in osteoclasts, was regulated by CCR5. These experimental results highlighted that CCR5-mediated signaling served as an intracellular organizer for centrosome clustering in osteoclasts, which was involved in the pathophysiology of bone metabolism.
An efficient framework for obtaining the initial cluster centers
Authors: Mishra B. K. , Mohanty Sachi Nandan , Baidyanath R. R. , Ali Shahid , Abduvalieva D. , Awwad Fuad A. , Ismail Emad A. A. , Gupta Manish 
Published: November 2023

AbstractClustering is an important tool for data mining since it can determine key patterns without any prior supervisory information. The initial selection of cluster centers plays a key role in the ultimate effect of clustering. More often researchers adopt the random approach for this purpose in an urge to get the centers in no time for speeding up their model. However, by doing this they sacrifice the true essence of subgroup formation and in numerous occasions ends up in achieving malicious clustering. Due to this reason we were inclined towards suggesting a qualitative approach for obtaining the initial cluster centers and also focused on attaining the well-separated clusters. Our initial contributions were an alteration to the classical K-Means algorithm in an attempt to obtain the near-optimal cluster centers. Few fresh approaches were earlier suggested by us namely, far efficient K-means (FEKM), modified center K-means (MCKM) and modified FEKM using Quickhull (MFQ) which resulted in producing the factual centers leading to excellent clusters formation. K-means, which randomly selects the centers, seem to meet its convergence slightly earlier than these methods, which is the latter’s only weakness. An incessant study was continued in this regard to minimize the computational efficiency of our methods and we came up with farthest leap center selection (FLCS). All these methods were thoroughly analyzed by considering the clustering effectiveness, correctness, homogeneity, completeness, complexity and their actual execution time of convergence. For this reason performance indices like Dunn’s Index, Davies–Bouldin’s Index, and silhouette coefficient were used, for correctness Rand measure was used, for homogeneity and completeness V-measure was used. Experimental results on versatile real world datasets, taken from UCI repository, suggested that both FEKM and FLCS obtain well-separated centers while the later converges earlier.
Recurrent connectivity supports higher-level visual and semantic object representations in the brain
Authors: von Seth Jacqueline , Nicholls Victoria I. , Tyler Lorraine K. , Clarke Alex 
Published: November 2023

AbstractVisual object recognition has been traditionally conceptualised as a predominantly feedforward process through the ventral visual pathway. While feedforward artificial neural networks (ANNs) can achieve human-level classification on some image-labelling tasks, it’s unclear whether computational models of vision alone can accurately capture the evolving spatiotemporal neural dynamics. Here, we probe these dynamics using a combination of representational similarity and connectivity analyses of fMRI and MEG data recorded during the recognition of familiar, unambiguous objects. Modelling the visual and semantic properties of our stimuli using an artificial neural network as well as a semantic feature model, we find that unique aspects of the neural architecture and connectivity dynamics relate to visual and semantic object properties. Critically, we show that recurrent processing between the anterior and posterior ventral temporal cortex relates to higher-level visual properties prior to semantic object properties, in addition to semantic-related feedback from the frontal lobe to the ventral temporal lobe between 250 and 500 ms after stimulus onset. These results demonstrate the distinct contributions made by semantic object properties in explaining neural activity and connectivity, highlighting it as a core part of object recognition not fully accounted for by current biologically inspired neural networks.
Reduced neural progenitor cell count and cortical neurogenesis in guinea pigs congenitally infected with Toxoplasma gondii
Authors: Grochow Thomas , Beck Britta , Rentería-Solís Zaida , Schares Gereon , Maksimov Pavlo , Strube Christina , Raqué Lisa , Kacza Johannes , Daugschies Arwid , Fietz Simone A. 
Published: November 2023

AbstractToxoplasma (T.) gondii is an obligate intracellular parasite with a worldwide distribution. Congenital infection can lead to severe pathological alterations in the brain. To examine the effects of toxoplasmosis in the fetal brain, pregnant guinea pigs are infected with T. gondii oocysts on gestation day 23 and dissected 10, 17 and 25 days afterwards. We show the neocortex to represent a target region of T. gondii and the parasite to infect neural progenitor cells (NPCs), neurons and astrocytes in the fetal brain. Importantly, we observe a significant reduction in neuron number at end-neurogenesis and find a marked reduction in NPC count, indicating that impaired neurogenesis underlies the neuronal decrease in infected fetuses. Moreover, we observe focal microglioses to be associated with T. gondii in the fetal brain. Our findings expand the understanding of the pathophysiology of congenital toxoplasmosis, especially contributing to the development of cortical malformations.
The structural basis for light acclimation in phycobilisome light harvesting systems systems in Porphyridium purpureum
Authors: Dodson Emma Joy , Ma Jianfei , Suissa Szlejf Maayan , Maroudas-Sklare Naama , Paltiel Yossi , Adir Noam , Sun Shan , Sui Sen-Fang , Keren Nir 
Published: November 2023

AbstractPhotosynthetic organisms adapt to changing light conditions by manipulating their light harvesting complexes. Biophysical, biochemical, physiological and genetic aspects of these processes are studied extensively. The structural basis for these studies is lacking. In this study we address this gap in knowledge by focusing on phycobilisomes (PBS), which are large structures found in cyanobacteria and red algae. In this study we focus on the phycobilisomes (PBS), which are large structures found in cyanobacteria and red algae. Specifically, we examine red algae (Porphyridium purpureum) grown under a low light intensity (LL) and a medium light intensity (ML). Using cryo-electron microscopy, we resolve the structure of ML-PBS and compare it to the LL-PBS structure. The ML-PBS is 13.6 MDa, while the LL-PBS is larger (14.7 MDa). The LL-PBS structure have a higher number of closely coupled chromophore pairs, potentially the source of the red shifted fluorescence emission from LL-PBS. Interestingly, these differences do not significantly affect fluorescence kinetics parameters. This indicates that PBS systems can maintain similar fluorescence quantum yields despite an increase in LL-PBS chromophore numbers. These findings provide a structural basis to the processes by which photosynthetic organisms adapt to changing light conditions.
Estimating tolerable communication delays for distributed optimization problems in control of heterogeneous multi‐agent systems
Authors: Rahimi Farshad , Mahboobi Esfanjani Reza 
Published: November 2023

AbstractThis study addresses the problem of distributed optimization in control of heterogeneous linear multi‐agent systems. Instead of assuming a perfect communication medium as in many existing approaches, two important issues arising from communication networks are considered. First, the existence of communication delays is assumed when each agent receives information from its neighbors. Second, since communication networks are generally unreliable, it is assumed that each agent interacts with other agents through random digraphs. Finally, delay‐dependent sufficient conditions are derived in the form of linear matrix inequalities (LMIs) to prove convergence to optimal solutions. Numerical simulation results are analyzed to demonstrate the effectiveness of the proposed approach.
Tensor‐based matched‐field processing applied to the SWellEx‐96 data
Authors: Zhu Fangwei , Zheng Guangying , Guo Xiaowei , Wang Fangyong , Du Shuanping , Bai Linlang 
Published: November 2023

AbstractThis study proposed a matched field source localization method based on tensor decomposition. By considering the advantages of tensors in multidimensional data processing, a three‐dimensional tensor signal model of space‐time‐frequency is constructed, and the signal subspace is estimated using high‐order singular value decomposition. The source position is estimated by matching the measured data tensor signal subspace with the replica field tensor signal subspace. The S5 event data of SWellEx‐96 is processed by the proposed tensor‐based matched‐field processing (TMFP). The comparison with the results of conventional matched field processing shows that TMFP has a better suppression effect on ambient noise under low SNR and better source localization performance.