bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of the safety and feasibility of electrochemotherapy with intravenous bleomycin as local treatment of bladder cancer in dogs
Authors: Rangel Marcelo Monte Mor , Linhares Laís Calazans Menescal , de Oliveira Krishna Duro , Suzuki Daniela Ota Hisayasu , Maglietti Felipe Horacio , de Nardi Andrigo Barboza 
Published: November 2023

AbstractLocal treatment of canine urothelial carcinoma (UC) of the bladder is a challenge. More than 90% of the cases invade the muscular layer, more than 50% develop on bladder sites with a difficult surgical approach and often requiring radical surgical procedures. This study aims to evaluate the safety and feasibility of electrochemotherapy (ECT) with intravenous bleomycin (BLM) as a local therapy for bladder UC. This prospective study included 21 dogs with spontaneous bladder UC. Regional/distant metastases and neoplastic infiltration of the serosa was considered the main exclusion criteria. We had no deaths during ECT or in the immediate postoperative period, and no suture dehiscence. Most dogs (19/21) developed mild adverse effects, whereas two dogs developed ureteral stenosis. Complete response (CR) was achieved in 62% of the cases (13/21), while partial response (PR) was achieved in 24% (5/21). The median survival and disease-free survival times were 284 and 270 days, respectively. Overall survival was significantly better in the dogs who achieved a CR. In conclusion, ECT was well-tolerated in dogs with UC, demonstrating its safety and feasibility. These data pave the way for new studies aimed at evaluating the effectiveness of ECT in canine bladder UC as a translational model for human disease.
Using network analysis to identify leverage points based on causal loop diagrams leads to false inference
Authors: Crielaard Loes , Quax Rick , Sawyer Alexia D. M. , Vasconcelos Vítor V. , Nicolaou Mary , Stronks Karien , Sloot Peter M. A. 
Published: November 2023

AbstractNetwork analysis is gaining momentum as an accepted practice to identify which factors in causal loop diagrams (CLDs)—mental models that graphically represent causal relationships between a system’s factors—are most likely to shift system-level behaviour, known as leverage points. This application of network analysis, employed to quantitatively identify leverage points without having to use computational modelling approaches that translate CLDs into sets of mathematical equations, has however not been duly reflected upon. We evaluate whether using commonly applied network analysis metrics to identify leverage points is justified, focusing on betweenness- and closeness centrality. First, we assess whether the metrics identify the same leverage points based on CLDs that represent the same system but differ in inferred causal structure—finding that they provide unreliable results. Second, we consider conflicts between assumptions underlying the metrics and CLDs. We recognise six conflicts suggesting that the metrics are not equipped to take key information captured in CLDs into account. In conclusion, using betweenness- and closeness centrality to identify leverage points based on CLDs is at best premature and at worst incorrect—possibly causing erroneous identification of leverage points. This is problematic as, in current practice, the results can inform policy recommendations. Other quantitative or qualitative approaches that better correspond with the system dynamics perspective must be explored.
Integration of fluorescence in situ hybridization and chromosome-length genome assemblies revealed synteny map for guinea pig, naked mole-rat, and human
Authors: Romanenko Svetlana A. , Kliver Sergei F. , Serdyukova Natalia A. , Perelman Polina L. , Trifonov Vladimir A. , Seluanov Andrei , Gorbunova Vera , Azpurua Jorge , Pereira Jorge C. , Ferguson-Smith Malcolm A. , Graphodatsky Alexander S. 
Published: November 2023

AbstractDescriptions of karyotypes of many animal species are currently available. In addition, there has been a significant increase in the number of sequenced genomes and an ever-improving quality of genome assembly. To close the gap between genomic and cytogenetic data we applied fluorescent in situ hybridization (FISH) and Hi-C technology to make the first full chromosome-level genome comparison of the guinea pig (Cavia porcellus), naked mole-rat (Heterocephalus glaber), and human. Comparative chromosome maps obtained by FISH with chromosome-specific probes link genomic scaffolds to individual chromosomes and orient them relative to centromeres and heterochromatic blocks. Hi-C assembly made it possible to close all gaps on the comparative maps and to reveal additional rearrangements that distinguish the karyotypes of the three species. As a result, we integrated the bioinformatic and cytogenetic data and adjusted the previous comparative maps and genome assemblies of the guinea pig, naked mole-rat, and human. Syntenic associations in the two hystricomorphs indicate features of their putative ancestral karyotype. We postulate that the two approaches applied in this study complement one another and provide complete information about the organization of these genomes at the chromosome level.
Using trials of caloric restriction and bariatric surgery to explore the effects of body mass index on the circulating proteome
Authors: Goudswaard Lucy J. , Smith Madeleine L. , Hughes David A. , Taylor Roy , Lean Michael , Sattar Naveed , Welsh Paul , McConnachie Alex , Blazeby Jane M. , Rogers Chris A. , Suhre Karsten , Zaghlool Shaza B. , Hers Ingeborg , Timpson Nicholas J. , Corbin Laura J. 
Published: November 2023

AbstractThousands of proteins circulate in the bloodstream; identifying those which associate with weight and intervention-induced weight loss may help explain mechanisms of diseases associated with adiposity. We aimed to identify consistent protein signatures of weight loss across independent studies capturing changes in body mass index (BMI). We analysed proteomic data from studies implementing caloric restriction (Diabetes Remission Clinical trial) and bariatric surgery (By-Band-Sleeve), using SomaLogic and Olink Explore1536 technologies, respectively. Linear mixed models were used to estimate the effect of the interventions on circulating proteins. Twenty-three proteins were altered in a consistent direction after both bariatric surgery and caloric restriction, suggesting that these proteins are modulated by weight change, independent of intervention type. We also integrated Mendelian randomisation (MR) estimates of the effect of BMI on proteins measured by SomaLogic from a UK blood donor cohort as a third line of causal evidence. These MR estimates provided further corroborative evidence for a role of BMI in regulating the levels of six proteins including alcohol dehydrogenase-4, nogo receptor and interleukin-1 receptor antagonist protein. These results indicate the importance of triangulation in interrogating causal relationships; further study into the role of proteins modulated by weight in disease is now warranted.
Spectrofluorometric quantitative analysis of aripiprazole based on quenching of natural derived carbon quantum dots in spiked human plasma
Authors: Alaqel Saleh I. , Alqahtani Arwa S. , Alharbi Adnan , Althobaiti Yusuf S. , Bamaga Ahmed K. , Algarni Majed A. , Almrasy Ahmed A. , Almalki Atiah H. 
Published: November 2023

AbstractAutism spectrum disorder is a significant concern worldwide, particularly in Middle Eastern countries. Aripiprazole, a psychiatric medicine that works as a partial agonist at D2 receptors, is often used for autism-related behavior issues in children. Monitoring the therapy of aripiprazole could enhance the safety and effectiveness of treatment for autistic individuals. The purpose of this study was to develop a highly sensitive and environmentally friendly method for analysis of aripiprazole in plasma matrix. To achieve this, water-soluble N-carbon quantum dots were produced from a natural green precursor, guava fruit, and used in fluorescence quenching spectroscopy to determine the presence of aripiprazole. The synthesized dots were analyzed and characterized using transmission electron microscopy and Fourier transform infrared spectroscopy, and they showed a strong fluorescence emission peak at 475 nm. The proposed method was validated according to ICH M10 guidelines and was shown to be highly sensitive, allowing for nanoscale determination of aripiprazole in plasma matrix. Additionally, the method was compared to a previously reported spectrophotometric method, and it was found to be more sensitive and consistent with the principles of green analytical chemistry.
Improving PM2.5 prediction in New Delhi using a hybrid extreme learning machine coupled with snake optimization algorithm
Authors: Masood Adil , Hameed Mohammed Majeed , Srivastava Aman , Pham Quoc Bao , Ahmad Kafeel , Razali Siti Fatin Mohd , Baowidan Souad Ahmad 
Published: November 2023

AbstractFine particulate matter (PM2.5) is a significant air pollutant that drives the most chronic health problems and premature mortality in big metropolitans such as Delhi. In such a context, accurate prediction of PM2.5concentration is critical for raising public awareness, allowing sensitive populations to plan ahead, and providing governments with information for public health alerts. This study applies a novel hybridization of extreme learning machine (ELM) with a snake optimization algorithm called the ELM-SO model to forecast PM2.5concentrations. The model has been developed on air quality inputs and meteorological parameters. Furthermore, the ELM-SO hybrid model is compared with individual machine learning models, such as Support Vector Regression (SVR), Random Forest (RF), Extreme Learning Machines (ELM), Gradient Boosting Regressor (GBR), XGBoost, and a deep learning model known as Long Short-Term Memory networks (LSTM), in forecasting PM2.5concentrations. The study results suggested that ELM-SO exhibited the highest level of predictive performance among the five models, with a testing value of squared correlation coefficient (R2) of 0.928, and root mean square error of 30.325 µg/m3. The study's findings suggest that the ELM-SO technique is a valuable tool for accurately forecasting PM2.5concentrations and could help advance the field of air quality forecasting. By developing state-of-the-art air pollution prediction models that incorporate ELM-SO, it may be possible to understand better and anticipate the effects of air pollution on human health and the environment.
A novel approach to estimate the weight of food items based on features extracted from an image using boosting algorithms
Authors: Konstantakopoulos Fotios S. , Georga Eleni I. , Fotiadis Dimitrios I. 
Published: November 2023

AbstractManaging daily nutrition is a prominent concern among individuals in contemporary society. The advancement of dietary assessment systems and applications utilizing images has facilitated the effective management of individuals' nutritional information and dietary habits over time. The determination of food weight or volume is a vital part in these systems for assessing food quantities and nutritional information. This study presents a novel methodology for evaluating the weight of food by utilizing extracted features from images and training them through advanced boosting regression algorithms. Α unique dataset of 23,052 annotated food images of Mediterranean cuisine, including 226 different dishes with a reference object placed next to the dish, was used to train the proposed pipeline. Then, using extracted features from the annotated images, such as food area, reference object area, food id, food category, and food weight, we built a dataframe with 24,996 records. Finally, we trained the weight estimation model by applying cross validation, hyperparameter tuning, and boosting regression algorithms such as XGBoost, CatBoost, and LightGBM. Between the predicted and actual weight values for each food in the proposed dataset, the proposed model achieves a mean weight absolute error 3.93 g, a mean absolute percentage error 3.73% and a root mean square error 6.05 g for the 226 food items of the Mediterranean Greek Food database (MedGRFood), setting new perspectives in food image-based weight and nutrition estimate models and systems.
Melanin pigmentation variations in the larval cuticle of almond moth, Ephestia cautella caused by gamma radiation
Authors: Hamza Ali , Zahran Nagwan 
Published: November 2023

AbstractTo determine the effects of gamma radiation on the melanization process and phenoloxidase activity, Ephestia cautella larvae were exposed to dosages of 200, 400, 600, 800, and 1000 Gy. After irradiation, the number of non melanized larvae and the number exhibiting a slight melanization usually increased. The degree of melanization in treated larvae differed significantly from untreated larvae. The amount of melanin usually decreases as the dosage increases and as time passes after the treatment. The results of the phenoloxidase assay indicate that the enzyme activity responds differently to radiation. For instance, at doses of 200, 400, and 800 Gy, the enzyme activity remained consistent in both control and irradiated larvae. However, at doses of 600 and 1000 Gy, the enzyme activity increased to 14.92 and 13.37 O.D. units, respectively, compared to 8.81 O.D. units in the control. In order to determine if irradiated larvae have been previously exposed to ionizing radiation, a quick and easy test based on phenoloxidase activity or the melanization response is presented for use in quarantine treatment. Histological changes, specifically in the pigment granules of melanin, were studied using a light microscope. Upon inspection of the unirradiated larvae, it was observed that brown melanin pigment granules were deposited in the epicuticle and exocuticle layers of the cuticle. When gamma radiation dosages were administered to larvae, it was observed that the melanin pigment gradually diminished until it vanished at the highest dose (1000 Gy).
Narcissistic coaches and athletes’ individual rowing performance
Authors: Nevicka Barbara , van Gerven Emma J. G. , Sedikides Constantine 
Published: November 2023

AbstractNarcissism, a personality trait marked by an excessively self-aggrandizing, entitled, and dominant orientation, has been associated with high performance under competitive pressure, as these contexts afford the opportunity to self-enhance. Narcissism is often characteristic of organizational and political leaders, yet little is known about narcissism in sports coaches. We propose that in a competitive context narcissistic coaches could inspire and motivate their athletes to raise their performance. We investigated the association between coach narcissism and athletes’ performance, and the role of athletes’ perceived self-enhancement opportunity as a potential mediating mechanism. We examined coach narcissism, athletes’ individual end times (i.e., performance), and athletes’ perceptions of self-enhancement opportunity during annual national indoor rowing competitions in 266 national level competitive rowers from 52 rowing clubs. Results of multilevel analyses showed that coach narcissism positively predicted athlete performance, and this was explained by athletes’ perceived opportunity to self-enhance during the competition. Thus, narcissistic coaches seem to reinforce athletes’ perceptions that competition provides them with an opportunity to show off their skills, which in turn accounts for athletes’ better performance in comparison to athletes who do not train with narcissistic coaches. The findings point to a potentially functional side of narcissism in coaching.
Long-term warming and human-induced plankton shifts at a coastal Eastern Mediterranean site
Authors: Kalloniati K. , Christou E. D. , Kournopoulou A. , Gittings J. A. , Theodorou I. , Zervoudaki S. , Raitsos D. E. 
Published: November 2023

AbstractPlankton are key ecological indicators for assessing the impacts of human-induced pressures like climate change and waste-water discharge. Here, 26 years (1988–2015) of biweekly in-situ chlorophyll-a concentration, mesozooplankton biomass and remotely-sensed sea surface temperature (SST) data are utilized to investigate long-term changes of plankton biomass and timing of growth (phenology) in relation to warming, in a coastal region of the Saronikos Gulf (Aegean Sea). A Waste-Water Treatment Plant (WWTP) was established in 1995, leading to decreased nutrient concentrations circa 2004. Overall, the results indicate an interplay between warming and changes in ecological status. During higher nutrient input (1989–2004), a temporal mismatch between zooplankton and phytoplankton, and a positive zooplankton growth—SST association, are evident. Conversely, in the warmer, less mesotrophic period 2005–2015, an earlier timing of zooplankton growth (related to copepod abundance) synchronizes with phytoplankton growth, including a secondary autumn growth period. Concurrently, an abrupt negative interannual relationship between SST and mesozooplankton, and a summer biomass decrease (linked with cladoceran abundance) are observed. This work provides evidence that current warming could alter plankton abundance and phenology in nearshore Eastern Mediterranean ecosystems, suggesting shifts in plankton community composition that could trigger potential cascading effects on higher trophic levels.
Artificial intelligence-based forensic sex determination of East Asian cadavers from skull morphology
Authors: Kondou Hiroki , Morohashi Rina , Kimura Satoko , Idota Nozomi , Matsunari Ryota , Ichioka Hiroaki , Bandou Risa , Kawamoto Masataka , Ting Deng , Ikegaya Hiroshi 
Published: November 2023

AbstractIdentification of unknown cadavers is an important task for forensic scientists. Forensic scientists attempt to identify skeletal remains based on factors including age, sex, and dental treatment remains. Forensic scientists commonly consider skull or pelvic shape to evaluate the sex; however, these evaluations require sufficient experience and knowledge and lack objectivity and reproducibility. To ensure objectivity and reproducibility for sex evaluation, we applied a gated attention-based multiple-instance learning model to three-dimensional (3D) skull images reconstructed from postmortem head computed tomography scans. We preprocessed the images, trained with 864 training data, validated the model with 124 validation data, and evaluated the performance of our model in terms of accuracy with 246 test data. Furthermore, three forensic scientists evaluated the 3D skull images, and their performances were compared with those of the model. Our model showed an accuracy of 0.93, which was higher than that of the forensic scientists. Our model primarily focused on the entire skull owing to visualization but focused less on the areas often investigated by forensic scientists. In summary, our model may serve as a supportive tool to identify cadaver sex based on skull shape. Further studies are required to improve the model’s performance.
Cranial midline shift is a predictor of the clinical prognosis of acute cerebral infarction patients undergoing emergency endovascular treatment
Authors: Xu Xiao-Min , Zhang Hao , Meng Ren-Liang 
Published: November 2023

AbstractEndovascular treatment is widely used in acute cerebral infarction (ACI), but patient prognosis varies greatly. We aimed to investigate the predictive value of midline shift (MLS) threshold for the clinical prognosis of patients with ACI who undergo emergency endovascular treatment. We prospectively enrolled patients with ACI who received endovascular treatment within 24 h of onset. Cranial images were collected within 24 h after endovascular treatment. We assessed MLS at the level of the midbrain, pineal calcification, septum pellucida, and falx cerebri and noted the maximum MLS (MLS[max]) among these locations. Functional outcomes were assessed at 90 days using the modified Rankin Scale. Receiver operating characteristic curves and optimal cutoff points were used to analyze the predictive value of MLS. We enrolled 82 patients, including 46 with poor outcomes. Although the MLS values at all levels were significantly different between the poor and favorable outcome groups (p < 0.01), the MLS(max) tended to be a better marker for 90-day poor outcome. To predict poor outcome, the optimal cutoff values for MLS(max) within 24 and 48 h after intervention were 0.45 and 2.35 mm, respectively. MLS(max) has predictive value for patient prognosis.
Amplification of poly(I:C)-induced interleukin-6 production in human bronchial epithelial cells by priming with interferon-γ
Authors: Okuma Norikazu , Ito Masa-aki , Shimizu Tomoyoshi , Hasegawa Atsuya , Ohmori Shin’ya , Yoshida Kazuki , Matsuoka Isao 
Published: November 2023

AbstractProinflammatory cytokine interleukin (IL)-6 was associated with disease severity in patients with COVID-19. The mechanism underlying the excessive IL-6 production by SARS-Cov-2 infection remains unclear. Respiratory viruses initially infect nasal or bronchial epithelial cells that produce various inflammatory mediators. Here, we show that pretreatment of human bronchial epithelial cells (NCl-H292) with interferon (IFN)-γ (10 ng/mL) markedly increased IL-6 production induced by the toll-like receptor (TLR) 3 agonist poly(I:C) (1 µg/mL) from 0.4 ± 0.1 to 4.1 ± 0.4 ng/mL (n = 3, P < 0.01). A similar effect was observed in human alveolar A549 and primary bronchial epithelial cells. TLR3 knockdown using siRNA in NCl-H292 cells diminished the priming effects of IFN-γ on poly(I:C)-induced IL-6 production. Furthermore, the Janus kinase (JAK) inhibitor tofacitinib (1 µM) inhibited IFN-γ-induced upregulation of TLR3, and suppressed poly(I:C)-induced IL-6 production. Quantitative chromatin immunoprecipitation revealed that IFN-γ stimulated histone modifications at the IL-6 gene locus. Finally, IFN-γ priming significantly increased lung IL-6 mRNA and protein levels in poly(I:C)-administrated mice. Thus, priming bronchial epithelial cells with IFN-γ increases poly(I:C)-induced IL-6 production via JAK-dependent TLR3 upregulation and chromatin remodeling at the IL-6 gene locus. These mechanisms may be involved in severe respiratory inflammation following infection with RNA viruses.
Ligilactobacillus acidipiscis YJ5 modulates the gut microbiota and produces beneficial metabolites to relieve constipation by enhancing the mucosal barrier
Authors: Shen Fei , Wang Qianqian , Ullah Sami , Pan Ya , Zhao Minjie , Wang Jing , Chen Ming , Feng Fengqin , Zhong Hao 
Published: November 2023

Ligilactobacillus acidipiscis YJ5 modulates the gut microbiota and produces beneficial metabolites to relieve constipation by enhancing the mucosal barrier.
Die Rolle von Pneumocystis jirovecii Infektionen bei
Rheuma-Patienten
Authors: Vagedes Daniel 
Published: November 2023

ZusammenfassungBei immunsuppremierten Patienten, Patienten mit einer fortgeschrittenen
HIV-Infektion, onkologische Patienten mit und ohne Therapie sowie Patienten mit
rheumatologischen Grunderkrankungen kann es zu Infektionen mit Pneumocystis
jirovecii kommen. In diesem Artikel wird die in veröffentlichen Analysen
/ Registerdaten beschriebene Häufigkeit bei Patienten mit
verschiedenen rheumatologischen Grunderkrankungen, an einer Pneumocystis
jirovecii Infektion zu erkranken und eine Pneumonie zu entwickeln, untersucht.
Ferner wird die Frage nach auslösenden antirheumatischen Therapien sowie
nach der Notwendigkeit der Gabe einer Prophylaxe gestellt. Insgesamt ist jedoch
das Risiko, an einer Infektion mit Pneumocystis jirovecii zu erkranken,
für Patienten mit rheumatologischen Grunderkrankungen gering.