bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ascorbic acid enhances chondrocyte differentiation of ATDC5 by accelerating insulin receptor signaling
Authors: Okita Kaede , Hikiji Hisako , Koga Ayaka , Nagai‐Yoshioka Yoshie , Yamasaki Ryota , Mitsugi Sho , Fujii Wataru , Ariyoshi Wataru 
Published: June 2023

AbstractChondrogenesis is strictly regulated by several factors, including cytokines, hormones, and extracellular matrix proteins. Mouse teratocarcinoma‐derived lineage cells, differentiate into chondrocytes in the presence of insulin. Although ascorbic acid promotes chondrogenic differentiation, the detailed regulative mechanisms underlying its role in chondrogenesis remain unclear. Therefore, in this study, we evaluated the effects of ascorbic acid on insulin‐induced chondrogenic differentiation of ATDC5 cells and the underlying intracellular signaling. The results revealed that insulin‐stimulated collagen deposition, matrix formation, calcification, and expression of chondrogenic differentiation marker genes in ATDC5 cells. This enhancement by insulin was amplified with the addition of ascorbic acid. Molecular analysis revealed that the activation of insulin‐induced phosphoinositide 3‐kinase (PI3K)/Akt signaling was enhanced in the presence of ascorbic acid. In contrast, Wnt/β‐catenin signaling was suppressed during chondrocyte differentiation via upregulation of the Wnt agonist, secreted Frizzled‐related protein 1 (sFRP‐1) and 3 (sFRP‐3). Notably, ascorbic acid upregulated the expression of insulin receptors and their substrates (IRS‐1 and IRS‐2). Furthermore, ascorbic acid reversed the suppression of IRS‐1 and IRS‐2 protein by insulin. These results indicate that ascorbic acid positively regulates the chondrogenic differentiation of ATDC5 cells via enhancement of insulin signaling. Our findings provide a substantial basis for further elucidation of the regulatory mechanisms of chondrocyte differentiation and the pathophysiology of OA, thus aiding in development of effective treatment strategies.
Bilateral vocal fold paresis and glottal bridge synechia in COVID‐19
Authors: Tardue‐Breiter Antonia , Glück Anna , Dier Helga , Sprinzl Georg Mathias 
Published: June 2023

Key Clinical MessageBilateral vocal fold paresis (BVFP) is a rare complication in COVID‐19 and should be considered as differential diagnosis in COVID‐19‐patients presenting with dyspnea and stridor. High‐dose intravenous corticosteroids can be useful treating COVID‐19‐related laryngeal edema and vocal fold paresis. This case shows the complexity of laryngeal complications in COVID‐19 requiring surgeries and functional therapies.AbstractAlthough COVID‐19 is known to affect peripheral as well as cranial nerves, there is a paucity of reports on vocal fold paresis in COVID‐19, bilateral vocal fold paresis (BVFP) in particular. We describe a case of BVFP and glottal bridge synechia following COVID‐19‐pneumonia discussing pathomechanisms and treatment options.
Synergistic Syngas Production: Needleless Electrospinning Synthesis of Co/CeO2–La2O3 Catalyst for Efficient Dry Reforming of Methane
Authors: Rosli Siti Nor Amira , Othman Nur Hidayati , Nguyen Van Cuong , Zainal Abidin Sumaiya 
Published: June 2023

AbstractThe prime cause for catalyst deactivation during dry reforming of methane (DRM) has been attributed to the deposition of carbon. Nanofibrous (NF) catalysts are attractive candidates that offer high catalytic activity and stability in DRM. A comparative study between electrospun and impregnated Co/CeO2–La2O3 catalysts in the DRM reaction was carried out to evaluate the merits of the NF catalyst. Application of the electrospun catalyst yielded the highest activity in DRM and showed a substantial improvement in resistance to carbon formation. The unique structure of the NF electrospun catalyst, the robust metal‐support interaction, and the increased surface area could more effectively suppress deactivation of the catalyst during an 8‐h DRM reaction than the impregnated catalyst.
Moisture content prediction of semen ziziphi spinosae based on hyperspectral images coupled with convolutional neural networks and subregional voting
Authors: Li Xiong , Liu Yande , Liu Liangfeng , Jiang Xiaogang , Wang Guantian 
Published: June 2023

AbstractDeep learning algorithms represented by convolutional neural networks bring new opportunities for spectral analysis technology. Convolutional neural networks are more straightforward than traditional chemometric algorithms for detecting the quality of agricultural products, reducing the procedures of spectral preprocessing and band selection, and with higher prediction accuracy. However, there are few research papers on the relevance of the explanation of the convolutional neural networks model mechanism, and the reader cannot fully understand convolutional neural networks feature learning. In this study, convolutional neural networks combined with the subregional voting method were used to predict the moisture content of semen ziziphi spinosae. Firstly, 10 regions of interest were divided using the subregional voting method, and the results of network models were compared. It was found that the average spectrum of the fifth region of interest had the best prediction of moisture content because it was closest to the central region of semen ziziphi spinosae. Based on this, a convolutional neural network containing three convolutional layers, three pooling layers, and one fully connected layer is proposed. Partial least squares regression, backpropagation neural network, and convolutional neural networks were established to predict the moisture content of semen ziziphi spinosae. The correlation coefficient of the prediction set of the partial least squares regression is 0.98 after the multiplicative scatter correction preprocessed the spectra, and correlation coefficient of the prediction set of the backpropagation neural network is 0.83 after the standard normal variate preprocessed the spectra. The correlation coefficient of the prediction set of the convolutional neural networks established by using the raw spectra reached 0.99. The spectral preprocessing method can improve the prediction set correlation coefficient of partial least squares regression and backpropagation neural network. Still, it will reduce the prediction ability of convolutional neural networks. This study also analyzed the effect of different learning rates on the performance of convolutional neural networks, and it was found that the training loss and training accuracy performed most consistently when the learning rate was 0.01. Secondly, this study also visualized the output feature maps of the three convolutional layers of convolutional neural networks and verified the effectiveness of convolutional neural networks feature band extraction. This study provides new ideas for deep learning in the online detection of seed moisture content.
Chemical Recycling of Polyolefinic Waste to Light Olefins by Catalytic Pyrolysis
Authors: Netsch Niklas , Vogt Jonas , Richter Frank , Straczewski Grazyna , Mannebach Gerd , Fraaije Volker , Tavakkol Salar , Mihan Shahram , Stapf Dieter 
Published: June 2023

AbstractCatalytic pyrolysis of post‐industrial and post‐consumer waste is studied in an auger‐type reactor at pilot scale by applying two different zeolites and an amorphous silica‐alumina catalyst in‐situ at 400–550 °C. Contrary to thermal pyrolysis, of polyolefin‐rich waste, high gaseous pyrolysis product yields of approx. 85 wt % are achieved with C2–C4 olefin contents of up to 67 wt %. After deactivation by coke deposition catalyst regeneration is proved feasible for maintaining the gaseous product yield and composition. Waste feedstocks with significant nitrogen and halogen heteroatom content are not suitable for in‐situ catalytic pyrolysis.
Biobased Silicon and Biobased Silica: Two Production Routes Whose Time has Come**
Authors: Ciriminna Rosaria , Laine Richard M. , Pagliaro Mario 
Published: June 2023

AbstractThis study offers an updated bioeconomy perspective on biobased routes to high‐purity silicon and silica in the context of the societal, economic and environmental trends reshaping chemical processes. We summarize the main aspects of the green chemistry technologies capable of transforming current production methods. Coincidentally, we discuss selected industrial and economic aspects. Finally, we offer perspectives of how said technologies could/will reshape current chemical and energy production.
High purity and integrity RNA from human cell lines stored in liquid nitrogen for over 20 years
Authors: Voinsky Irena , Shapira Elad , Gurwitz David 
Published: June 2023

AbstractBiobanks are a key resource for obtaining human cell lines for biomedical research, including for drug development projects. Such projects often include comparative RNA‐sequencing of large panels of human cell lines from individuals affected by certain disorders and healthy controls, or from individuals with different drug response phenotypes. RNA extractions are typically done from growing cell cultures, a process that may take several weeks. However, maintaining large numbers of cell lines in parallel increases the project workload. Here, we show that extracting RNAs directly from frozen vials of human cell lines stored for over 20 years in a liquid nitrogen freezer yields RNAs with the high purity and integrity parameters that conform to those required for optimal RNA‐sequencing and are closely similar to those obtained for RNAs extracted from growing human cell lines.
Interactions between large‐scale and local factors influence seed predation rates and seed loss
Authors: Calixto Eduardo S. , Maron John L. , Hahn Philip G. 
Published: June 2023

AbstractHerbivores often have highly variable impacts on plant fecundity. The relative contribution of different environmental factors operating at varying spatial scales in affecting this variability is often unclear. We examined how density‐dependent seed predation at local scales and regional differences in primary productivity are associated with variation in the magnitude of pre‐dispersal seed predation on Monarda fistulosa (Lamiaceae). Within M. fistulosa populations growing in a low‐productivity region (LPR), Montana, USA, and a high‐productivity region (HPR), Wisconsin, USA, we quantified the magnitude of pre‐dispersal seed predation among individual plants differing in seed head densities. Out of a total of 303 M. fistulosa plants that were surveyed, we found half as many herbivores in seed heads in the LPR (n = 133 herbivores) compared to the HPR (n = 316). In the LPR, 30% of the seed heads were damaged in plants with low seed head density, while 61% of seed heads were damaged in plants with high seed head density. Seed head damage was consistently high in the HPR (about 49% across the range of seed head density) compared to the LPR (45% across a range of seed head density). However, the proportion of seeds per seed head that were destroyed by herbivores was nearly two times higher (~38% loss) in the LPR compared to HPR (22% loss). Considering the combined effects of probability of damage and seed loss per seed head, the proportion seed loss per plant was consistently higher in the HPR regardless of seed head density. Nevertheless, because of greater seed head production, the total number of viable seeds produced per plant was higher in HPR and high‐density plants, despite being exposed to greater herbivore pressure. These findings show how large‐scale factors can interact with local‐scale factors to influence how strongly herbivores suppress plant fecundity.
An automated approach for counting groups of flying animals applied to one of the world's largest bat colonies
Authors: Koger Benjamin , Hurme Edward , Costelloe Blair R. , O'Mara M. Teague , Wikelski Martin , Kays Roland , Dechmann Dina K. N. 
Published: June 2023

AbstractEstimating animal populations is essential for conservation. Censusing large congregations is especially important since these are priorities for protection, but efficiently counting hundreds of thousands of moving animals remains a challenge. We developed a deep learning‐based system using consumer cameras that not only counts but also records behavioral information for large numbers of flying animals in a range of lighting conditions including near darkness. We built a robust training set without human labeling by leveraging data augmentation and background subtraction. We demonstrate this approach by estimating the size of a straw‐colored fruit bat (Eidolon helvum) colony in Kasanka National Park, Zambia with cameras encircling the colony to record evening emergence. Detection of bats was robust to deteriorating lighting conditions and changing backgrounds. Combined over five days, our population estimates ranged between 750,000 and 976,000 bats with a mean of 857,233. In addition to counts, we extracted wingbeat frequency, flight altitude, and local group polarity for 639,414 individuals. This open access method is an inexpensive but powerful approach that, in addition to radial emergences from central locations, can also be applied to unidirectional movements of flying groups, such as migratory streams of birds.
Longer‐term verbal and visual memory patterns in patients with temporal lobe and genetic generalized epilepsies
Authors: Puteikis Kristijonas , Wolf Peter , Mameniškienė Rūta 
Published: June 2023

AbstractObjectiveTo compare forgetting patterns between patients with temporal lobe (TLE) and generalized (GGE) epilepsies and to assess whether recall is associated with epileptic activity.MethodsThirty‐three patients with TLE (13 left, 17 right, and 3 nonlateralized TLE), 42 patients with GGE, and 57 healthy controls (HCs) were asked to recall words, verbal story material, and the Rey‐Osterrieth complex figure at two delays. Accelerated long‐term forgetting (ALF) was defined by group performance comparable to HCs at 30 min and worse recall than HCs after 4 weeks. ALF was assessed by comparing raw test scores in a two‐way repeated measures analysis of variance (ANOVA) adjusted for the learning capacity.ResultsCompared to HCs, patients with R‐TLE remembered fewer items of the word list after 30 min as well as after 4 weeks. Patients with L‐TLE and GGE had comparable learning‐adjusted performance to HCs at the 30 min delay but scored less after 4 weeks (group by delay interaction F(3, 124) = 3.2, P = 0.026,  = 0.07). The epilepsy group (patients with TLE and GGE combined) performed as well as HCs at 30 min but worse after 4 weeks irrespective of experienced seizures during the 4‐week delay or interictal bilateral (TLE) or generalized (GGE) activity before the study. We noted no statistically significant differences between patient and HC verbal story (group by delay interaction F(3, 124) = 0.7, P = 0.570,  = 0.02) or complex figure (F(3, 124) = 0.8, P = 0.488,  = 0.02) recall.SignificanceOur data support verbal and visual memory impairment in both TLE and GGE with different performances between these groups in the task of word recall. We suggest the presence of ALF in patients with GGE and left TLE after adjusting for learning capacity. We could not confirm the influence of epileptic activity on long‐term forgetting patterns. Future studies are required to better define domain‐specific differences in memory impairment in TLE and GGE.
Sonographic evaluation of median nerve cross‐sectional area in a normal Iranian population: A cross‐sectional study
Authors: Rayegani Seyed Mansoor , Bayat Masume 
Published: June 2023

AbstractIntroductionConsidering disagreements on the normal range of median nerve cross‐sectional area (MNCSA) and insufficient data in the Iranian population, this study aimed to measure normal MNCSA.MethodsIn this cross‐sectional study, bilateral upper limbs of 99 subjects were assessed by sonography, and MNCSA was measured at three levels: forearm, carpal tunnel inlet (CTI), and carpal tunnel outlet (CTO). The association between MNCSA and demographic factors was assessed.ResultsMean MNCSA was 6.33 mm2 at the forearm, 9.41 mm2 at CTI, and 10.67 mm2 at CTO. MNCSA was significantly higher in males (6.78 vs. 5.94 mm2 at the forearm, 9.98 vs. 8.92 mm2 at CTI, and 11.24 vs. 10.84 mm2 at CTO in males and females, respectively) and taller (>170 cm) subjects in all three levels (6.69 vs. 6.03 mm2 at the forearm, 9.80 vs. 9.02 mm2 at CTI, and 11.27 vs. 10.12 mm2 at CTO in taller and shorter subjects, respectively). MNCSA was not significantly associated with wrist ratio (WR) or body mass index (BMI).ConclusionThe normal MNCSA range in the Iranian population is 6.31 mm2 (forearm) to 10.74 mm2 (CTO). MNCSA is significantly higher in males and taller subjects but is not associated with BMI and WR.
On the computational approaches for supporting triage systems
Authors: Defilippo Annamaria , Bertucci Giuseppe , Zurzolo Cosimo , Veltri Pierangelo , Guzzi Pietro Hiram 
Published: June 2023

AbstractTriage procedure is used in Emergency Departments (ED) to manage the patient's treatment and prioritise care access. This is a largely resource‐consuming phase and relevant to reduce risk and optimise resource management. Moreover, the presence of patients in the ED (both in treatment rooms and in waiting rooms after triage) may increase the patients' time of stay, thus creating problems for critical patients and for healthcare process management. Moreover, it has been proved that a large fraction of ED incoming patients do not require emergency treatments and might be treated in ambulatory or by family doctors. In such cases, the triage wastes resources and time. In addition, the decision of a low priority or no ED necessity is relevant considering that underestimating treatment necessity may cause errors in patient treatments. Improving triage related decisions is a relevant task. It has been shown that computational methods such as machine learning (ML) may support triage by providing better stratification of patients as well as better results in terms of outcome. We here present a literature review discussing some recent approaches to predict the severity of patients and in particular, we present recent approaches based on ML. We use PRISMA methodology to include works in our analysis. Finally, the future directions of research and open problems are highlighted.
From extremely acidic to alkaline: Aquatic invertebrates in forest mining lakes under the pressure of acidification
Authors: Spyra Aneta , Cieplok Anna , Kaszyca‐Taszakowska Natalia 
Published: June 2023

AbstractHuman activities, including the mining industry, have considerably degraded water habitats worldwide. Acidification has severely affected aquatic environments and biodiversity by altering food webs and reducing species richness. The study area in southern Poland is unique in addressing the effects of mining‐related acidification on biodiversity in freshwater ecosystems along a broad pH gradient (2.4–9.6) in mining lakes. Study was designed to test for effect of human induced acidification. Using multivariate ordination techniques, we analyzed how variations in invertebrate composition are related to environmental factors. The results indicated that pH, hardness, total dissolved solids, and the content of ammonia and calcium were significantly associated with the distribution of invertebrates in the studied mining lakes. The highest iron content, relatively high values of conductivity, and chlorides were found in the extremely acidic mining lakes. A clear trend in decreasing density with decreasing pH was observed for taxa such as Oligochaeta, Chironomidae, Glossiphonidae, and certain taxa of snails. However, the density of other taxa such as Lestidae, Libellulidae, Caenidae, Sialidae, Helodidae, Hydrophilidae, and Polycentropodidae increased with decreasing pH. Specific communities were found with increasing acidity. Therefore, a further increase in acidity will probably cause a stronger decline in most of taxa and their density, and on water chemistry (e.g., calcium concentration, nitrites, and hardness). The data yielded offer an opportunity to fill knowledge gaps on acidic stress concerning less‐studied environments such as mining lakes and link environmental pollution with communities, which is especially important, because aquatic forest habitats are especially exposed to different climatic factors and threats.
The reproductive and transgenerational toxicity of microplastics and nanoplastics: A threat to mammalian fertility in both sexes
Authors: He Yuchong , Yin Ruocheng 
Published: June 2023

AbstractMicroplastics (MPs) and nanoplastics (NPs) are extensively distributed in the environment. However, a comprehensive review and in‐depth discussion on the effects of MPs and NPs to reproductive capacity and transgenerational toxicity on mammals, especially on humans, is lacked. It is suggested that microplastics and nanoplastics could accumulate in mammalian reproductive organs and exert toxic effects on the reproductive system for both sexes. For males, the damage of microplastics consists of abnormal testicular and sperm structure, decreased sperm vitality, and endocrine disruption, which were caused by oxidative stress, inflammation, apoptosis of testicular cells, autophagy, abnormal cytoskeleton, and abnormal hypothalamic‐pituitary‐testicular axis. For females, the damage of microplastics includes abnormal ovary and uterus structure and endocrine disruption, which were caused by oxidative stress, inflammation, granulosa cell apoptosis, hypothalamic‐pituitary‐ovary axis abnormalities, and tissue fibrosis. For transgenerational toxicity, premature mortality existed in the rodent offspring after maternal exposure to microplastics. Among the surviving offspring, metabolic disorders, reproductive dysfunction, immune, neurodevelopmental, and cognitive disorders were detected, and these events directly correlated with transgenerational translocation of MPs and NPs. Studies on human‐derived cells or organoids demonstrated that transgenerational toxicity studies for both sexes are yet in the phase of exploring suitable experimental models, and more detailed research on the threat of MPs and NPs to human fertility is still urgently needed. Further studies will help assess the MPs and NPs threat to public fertility and reproductive health risks.
Osteosclerotic Metaphyseal Dysplasia Due to a Likely Pathogenic LRRK1 Variant as a Cause of Recurrent Long Bone Fractures
Authors: van Velsen Evert F.S. , Demirdas Serwet , Hanff David , Zillikens M. Carola 
Published: June 2023

ABSTRACTOsteosclerotic metaphyseal dysplasia (OSMD) is a very rare autosomal‐recessive disease caused by mutations in the leucine‐rich repeat kinase 1 (LRRK1) gene. It is a sclerosing skeletal dysplasia characterized by osteosclerosis of the long bones, predominantly at the metaphyses and vertebrae. Phenotypic features can be short stature, pathological fractures, delayed development, and hypotonia, but they are not uniformly present, and relatively few cases are known from the literature. A 40‐year‐old man was seen at our bone center because of nonspontaneous multiple peripheral low‐energy trauma fractures since puberty. He had no other complaints and his family history was negative. Except for a relatively short stature (167 cm; −1.5 SD), there were no abnormalities on examination, including laboratory tests. Initially, a suspicion was raised of osteogenesis imperfecta, but bone mineral density was high and X‐rays of the whole skeleton showed osteosclerosis of the metaphyses of long bones and vertebrae. Whole‐exome sequencing showed a homozygous, likely pathogenic, variant (American College of Medical Genetics and Genomics criteria class 4) in the LRRK1 gene, fitting the diagnosis of OSMD. In conclusion, we described a 40‐year‐old patient with osteosclerotic metaphyseal dysplasia caused by a homozygous variant in the LRRK1 gene, resulting in multiple fractures of the long bones without other features of the disease, adding to the phenotypic variation of OSMD. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.