bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antipsychotic dose, dopamine D2 receptor occupancy and extrapyramidal side-effects: a systematic review and dose-response meta-analysis
Authors: Siafis Spyridon , Wu Hui , Wang Dongfang , Burschinski Angelika , Nomura Nobuyuki , Takeuchi Hiroyoshi , Schneider-Thoma Johannes , Davis John M. , Leucht Stefan 
Published: August 2023

AbstractAntipsychotic drugs differ in their propensity to cause extrapyramidal side-effects (EPS), but their dose-effects are unclear. Therefore, we conducted a systematic review and dose-response meta-analysis. We searched multiple electronic databases up to 20.02.2023 for fixed-dose studies investigating 16 second-generation antipsychotics and haloperidol (all formulations and administration routes) in adults with acute exacerbations of schizophrenia. The primary outcome was the number of participants receiving antiparkinsonian medication, and if not available, the number of participants with extrapyramidal side-effects (EPS) and the mean scores of EPS rating scales were used as proxies. The effect-size was odds ratio (ORs) compared with placebo. One-stage random-effects dose-response meta-analyses with restricted cubic splines were conducted to estimate the dose-response curves. We also examined the relationship between dopamine D2 receptor (D2R) occupancy and ORs by estimating occupancies from administrated doses. We included data from 110 studies with 382 dose arms (37193 participants). Most studies were short-term with median duration of 6 weeks (range 3–26 weeks). Almost all antipsychotics were associated with dose-dependent EPS with varied degrees and the maximum ORs ranged from OR = 1.57 95%CI [0.97, 2.56] for aripiprazole to OR = 7.56 95%CI [3.16, 18.08] for haloperidol at 30 mg/d. Exceptions were quetiapine and sertindole with negligible risks across all doses. There was very low quality of findings for cariprazine, iloperidone, and zotepine, and no data for clozapine. The D2R occupancy curves showed that the risk increased substantially when D2R occupancy exceeded 75–85%, except for D2R partial agonists that had smaller ORs albeit high D2R occupancies. In conclusion, we found that the risk of EPS increases with rising doses and differs substantially in magnitude among antipsychotics, yet exceptions were quetiapine and sertindole with negligible risks. Our data provided additional insights into the current D2R therapeutic window for EPS.
NeuMa - the absolute Neuromarketing dataset en route to an holistic understanding of consumer behaviour
Authors: Georgiadis Kostas , Kalaganis Fotis P. , Riskos Kyriakos , Matta Eleftheria , Oikonomou Vangelis P. , Yfantidou Ioanna , Chantziaras Dimitris , Pantouvakis Kyriakos , Nikolopoulos Spiros , Laskaris Nikos A. , Kompatsiaris Ioannis 
Published: August 2023

AbstractNeuromarketing is a continuously evolving field that utilises neuroimaging technologies to explore consumers’ behavioural responses to specific marketing-related stimulation, and furthermore introduces novel marketing tools that could complement the traditional ones like questionnaires. In this context, the present paper introduces a multimodal Neuromarketing dataset that encompasses the data from 42 individuals who participated in an advertising brochure-browsing scenario. In more detail, participants were exposed to a series of supermarket brochures (containing various products) and instructed to select the products they intended to buy. The data collected for each individual executing this protocol included: (i) encephalographic (EEG) recordings, (ii) eye tracking (ET) recordings, (iii) questionnaire responses (demographic, profiling and product related questions), and (iv) computer mouse data. NeuMa dataset has both dynamic and multimodal nature and, due to the narrow availability of open relevant datasets, provides new and unique opportunities for researchers in the field to attempt a more holistic approach to neuromarketing.
Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney
Authors: Kuo Willy , Rossinelli Diego , Schulz Georg , Wenger Roland H. , Hieber Simone , Müller Bert , Kurtcuoglu Vartan 
Published: August 2023

AbstractThe performance of machine learning algorithms, when used for segmenting 3D biomedical images, does not reach the level expected based on results achieved with 2D photos. This may be explained by the comparative lack of high-volume, high-quality training datasets, which require state-of-the-art imaging facilities, domain experts for annotation and large computational and personal resources. The HR-Kidney dataset presented in this work bridges this gap by providing 1.7 TB of artefact-corrected synchrotron radiation-based X-ray phase-contrast microtomography images of whole mouse kidneys and validated segmentations of 33 729 glomeruli, which corresponds to a one to two orders of magnitude increase over currently available biomedical datasets. The image sets also contain the underlying raw data, threshold- and morphology-based semi-automatic segmentations of renal vasculature and uriniferous tubules, as well as true 3D manual annotations. We therewith provide a broad basis for the scientific community to build upon and expand in the fields of image processing, data augmentation and machine learning, in particular unsupervised and semi-supervised learning investigations, as well as transfer learning and generative adversarial networks.
Impact of Navier’s slip and MHD on laminar boundary layer flow with heat transfer for non-Newtonian nanofluid over a porous media
Authors: Maranna T. , Sachhin S. M. , Mahabaleshwar U. S. , Hatami M. 
Published: August 2023

AbstractThe current studies analytically summarize the impact of magnetohydrodynamic and thermal radiation on the non-Newtonian continuous uniform motion of viscid non-compressible nanofluid across a penetrable stretching/shrinking sheet, even though accomplish Navier's first and second order slips along mass transpiration. Blood-bearing silver and copper nanomaterials have distinct flow and heat transfer properties when exposed to heat. Silver (Ag) as well as copper (Cu) nanoparticles are assumed to be present in blood as the non-Newtonian liquid; this fluid serves as the base. We anticipate that the current study will be useful in fields including food, petrochemical products, and medicines, as well as blood circulation, and highly beneficial for patients who are dealing with blood clotting in the uterus, which may result in infertility or cancer, to evaluate the blood flow in the tube. Employing the similarity conversion technique, the ruling partial differential equations are modified into a couple of non-linear ordinary differential equations. Then the transformed ordinary differential equations are analytically solved with the Laplace transformation and expressed in terms of an incomplete gamma function. The current analytical results are compared to previous studies. It is addressed how several physical features such as magnetic field M, Navier’s first and second order slip, permeability, Prandtl number Pr, and radiation parameter affect non-dimensional velocity as well as temperature patterns through graphs. The results obtained reveal that there is an enhancement in the rate of heat transfer with the rise in nanoparticle volume fraction and radiation. The temperature distribution is also influenced by the presence of Prandtl numbers, radiation, solid volume fraction, permeability, and slip conditions. This shows that the solid volume fraction of nanoparticles can be used to control the behaviour of heat transfer and nanofluid flows.
Toward a stable and low-resource PLM-based medical diagnostic system via prompt tuning and MoE structure
Authors: Dong Bowen , Wang Zhuo , Li Zhenyu , Duan Zhichao , Xu Jiacheng , Pan Tengyu , Zhang Rui , Liu Ning , Li Xiuxing , Wang Jie , Liu Caiyan , Dong Liling , Mao Chenhui , Gao Jing , Wang Jianyong 
Published: August 2023

AbstractMachine learning (ML) has been extensively involved in assistant disease diagnosis and prediction systems to emancipate the serious dependence on medical resources and improve healthcare quality. Moreover, with the booming of pre-training language models (PLMs), the application prospect and promotion potential of machine learning methods in the relevant field have been further inspired. PLMs have recently achieved tremendous success in diverse text processing tasks, whereas limited by the significant semantic gap between the pre-training corpus and the structured electronic health records (EHRs), PLMs cannot converge to anticipated disease diagnosis and prediction results. Unfortunately, establishing connections between PLMs and EHRs typically requires the extraction of curated predictor variables from structured EHR resources, which is tedious and labor-intensive, and even discards vast implicit information.In this work, we propose an Input Prompting and Discriminative language model with the Mixture-of-experts framework (IPDM) by promoting the model’s capabilities to learn knowledge from heterogeneous information and facilitating the feature-aware ability of the model. Furthermore, leveraging the prompt-tuning mechanism, IPDM can inherit the impacts of the pre-training in downstream tasks exclusively through minor modifications. IPDM remarkably outperforms existing models, proved by experiments on one disease diagnosis task and two disease prediction tasks. Finally, experiments with few-feature and few-sample demonstrate that IPDM achieves significant stability and impressive performance in predicting chronic diseases with unclear early-onset characteristics or sudden diseases with insufficient data, which verifies the superiority of IPDM over existing mainstream methods, and reveals the IPDM can powerfully address the aforementioned challenges via establishing a stable and low-resource medical diagnostic system for various clinical scenarios.
Development and verification of a nomogram for predicting short-term mortality in elderly ischemic stroke populations
Authors: Jin Guangyong , Hu Wei , Zeng Longhuan , Diao Mengyuan , Chen Hui , Chen Jiayi , Gu Nanyuan , Qiu Kai , Lv Huayao , Pan Lu , Xi Shaosong , Zhou Menglu , Liang Dongcheng , Ma Buqing 
Published: August 2023

AbstractStroke is a major healthcare problem worldwide, particularly in the elderly population. Despite limited research on the development of prediction models for mortality in elderly individuals with ischemic stroke, our study aimed to address this knowledge gap. By leveraging data from the Medical Information Mart for Intensive Care IV database, we collected comprehensive raw data pertaining to elderly patients diagnosed with ischemic stroke. Through meticulous screening of clinical variables associated with 28-day mortality, we successfully established a robust nomogram. To assess the performance and clinical utility of our nomogram, various statistical analyses were conducted, including the concordance index, integrated discrimination improvement (IDI), net reclassification index (NRI), calibration curves and decision curve analysis (DCA). Our study comprised a total of 1259 individuals, who were further divided into training (n = 894) and validation (n = 365) cohorts. By identifying several common clinical features, we developed a nomogram that exhibited a concordance index of 0.809 in the training dataset. Notably, our findings demonstrated positive improvements in predictive performance through the IDI and NRI analyses in both cohorts. Furthermore, calibration curves indicated favorable agreement between the predicted and actual incidence of mortality (P > 0.05). DCA curves highlighted the substantial net clinical benefit of our nomogram compared to existing scoring systems used in routine clinical practice. In conclusion, our study successfully constructed and validated a prognostic nomogram, which enables accurate short-term mortality prediction in elderly individuals with ischemic stroke.
Tracing the formation of exceptional fronts driving historical fires in Southeast Australia
Authors: Magaritz-Ronen Leehi , Raveh-Rubin Shira 
Published: August 2023

AbstractExtreme cold fronts are closely associated with the spread of large wildfires in Australia. The strength of a front is determined by the drop in temperature across it, which will in turn be determined by the warm and cold temperature anomalies on either side of the front. Here, we examine the Black Saturday and Ash Wednesday fires in southeast Australia through a Lagrangian decomposition framework, exploring the origin of the potential temperature anomalies that formed these extreme cold fronts. We identify the contributions of three processes: an initial anomaly at the origin, adiabatic transport of climatologically different air, and diabatic heating along the air-parcel trajectory. We find that on both sides of the cold front descending trajectories contribute to the extreme anomalies. In the warm sector, positive anomalies arrive with descending trajectories from the Indian Ocean. In the cold sector, negative anomalies are dominated by strongly descending dry intrusions forming as part of the cyclonic system. The dry intrusions advect colder air, overcompensating for its adiabatic warming during its descent. Identification of the precursors and the mechanisms contributing to extreme cold fronts associated with large wildfires can improve the forecast of such events and help evaluate them in future climate projections.
Aerosolization flux, bio-products, and dispersal capacities in the freshwater microalga Limnomonas gaiensis (Chlorophyceae)
Authors: Tesson Sylvie V. M. , Barbato Marta , Rosati Bernadette 
Published: August 2023

AbstractLittle is known on the spreading capacities of Limnomonas gaiensis across freshwater lakes in Northern Europe. In this study, we show that the species could successfully be aerosolized from water sources by bubble bursting (2-40 particles.cm−3), irrespectively of its density in the water source or of the jet velocity used to simulate wave breaking. The species viability was impacted by both water turbulences and aerosolization. The survival rate of emitted cells was low, strain-specific, and differently impacted by bubble busting processes. The entity “microalga and bionts” could produce ethanol, and actively nucleate ice (principally ≤−18 °C) mediated soluble ice nucleation active proteins, thereby potentially impacting smog and cloud formation. Moreover, smallest strains could better cope with applied stressors. Survival to short-term exposure to temperatures down to −21 °C and freezing events further suggest that L. gaiensis could be air dispersed and contribute to their deposition.
13C- and 15N-labeling of amyloid-β and inhibitory peptides to study their interaction via nanoscale infrared spectroscopy
Authors: Paul Suman , Jeništová Adéla , Vosough Faraz , Berntsson Elina , Mörman Cecilia , Jarvet Jüri , Gräslund Astrid , Wärmländer Sebastian K. T. S. , Barth Andreas 
Published: August 2023

AbstractInteractions between molecules are fundamental in biology. They occur also between amyloidogenic peptides or proteins that are associated with different amyloid diseases, which makes it important to study the mutual influence of two polypeptides on each other’s properties in mixed samples. However, addressing this research question with imaging techniques faces the challenge to distinguish different polypeptides without adding artificial probes for detection. Here, we show that nanoscale infrared spectroscopy in combination with 13C, 15N-labeling solves this problem. We studied aggregated amyloid-β peptide (Aβ) and its interaction with an inhibitory peptide (NCAM1-PrP) using scattering-type scanning near-field optical microscopy. Although having similar secondary structure, labeled and unlabeled peptides could be distinguished by comparing optical phase images taken at wavenumbers characteristic for either the labeled or the unlabeled peptide. NCAM1-PrP seems to be able to associate with or to dissolve existing Aβ fibrils because pure Aβ fibrils were not detected after mixing.
Revealing protonation states and tracking substrate in serine hydroxymethyltransferase with room-temperature X-ray and neutron crystallography
Authors: Drago Victoria N. , Campos Claudia , Hooper Mattea , Collins Aliyah , Gerlits Oksana , Weiss Kevin L. , Blakeley Matthew P. , Phillips Robert S. , Kovalevsky Andrey 
Published: August 2023

AbstractPyridoxal 5’-phosphate (PLP)-dependent enzymes utilize a vitamin B6-derived cofactor to perform a myriad of chemical transformations on amino acids and other small molecules. Some PLP-dependent enzymes, such as serine hydroxymethyltransferase (SHMT), are promising drug targets for the design of small-molecule antimicrobials and anticancer therapeutics, while others have been used to synthesize pharmaceutical building blocks. Understanding PLP-dependent catalysis and the reaction specificity is crucial to advance structure-assisted drug design and enzyme engineering. Here we report the direct determination of the protonation states in the active site of Thermus thermophilus SHMT (TthSHMT) in the internal aldimine state using room-temperature joint X-ray/neutron crystallography. Conserved active site architecture of the model enzyme TthSHMT and of human mitochondrial SHMT (hSHMT2) were compared by obtaining a room-temperature X-ray structure of hSHMT2, suggesting identical protonation states in the human enzyme. The amino acid substrate serine pathway through the TthSHMT active site cavity was tracked, revealing the peripheral and cationic binding sites that correspond to the pre-Michaelis and pseudo-Michaelis complexes, respectively. At the peripheral binding site, the substrate is bound in the zwitterionic form. By analyzing the observed protonation states, Glu53, but not His residues, is proposed as the general base catalyst, orchestrating the retro-aldol transformation of L-serine into glycine.
Harnessing neutrophil plasticity for HCC immunotherapy
Authors: Ramon-Gil Erik , Geh Daniel , Leslie Jack 
Published: August 2023

Abstract
Neutrophils, until recently, have typically been considered a homogeneous population of terminally differentiated cells with highly conserved functions in homeostasis and disease. In hepatocellular carcinoma (HCC), tumour-associated neutrophils (TANs) are predominantly thought to play a pro-tumour role, promoting all aspects of HCC development and progression. Recent developments in single-cell technologies are now providing a greater insight and appreciation for the level of cellular heterogeneity displayed by TANs in the HCC tumour microenvironment, which we have been able to correlate with other TAN signatures in datasets for gastric cancer, pancreatic ductal adenocarcinoma (PDAC) and non-small cell lung cancer (NSCLC). TANs with classical pro-tumour signatures have been identified as well as neutrophils primed for anti-tumour functions that, if activated and expanded, could become a potential therapeutic approach. In recent years, therapeutic targeting of neutrophils in HCC has been typically focused on impairing the recruitment of pro-tumour neutrophils. This has now been coupled with immune checkpoint blockade with the aim to stimulate lymphocyte-mediated anti-tumour immunity whilst impairing neutrophil-mediated immunosuppression. As a result, neutrophil-directed therapies are now entering clinical trials for HCC. Pharmacological targeting along with ex vivo reprogramming of neutrophils in HCC patients is, however, in its infancy and a greater understanding of neutrophil heterogeneity, with a view to exploit it, may pave the way for improved immunotherapy outcomes. This review will cover the recent developments in our understanding of neutrophil heterogeneity in HCC and how neutrophils can be harnessed to improve HCC immunotherapy.
Maiden application of TIDμ1NDμ2 controller for effective load frequency control of non‐linear two‐area power system
Authors: Tabak Abdulsamed , Duman Serhat 
Published: August 2023

AbstractIn the paper, the maiden application of Tilted Integral Fractional Derivative with Filter plus Fractional Derivative controller (), called TIFDNFD controller, is proposed to achieve load frequency control (LFC) of two area‐multi source power system. In the study, both areas include thermal power, hydropower, and gas turbine power systems. In this study, generation rate constraint and governor dead‐band are integrated into the power system to evaluate the performance of the controller in a non‐linear environment. The wild horse optimizer (WHO) is used for controller parameter tuning in the LFC problem for the first time. The performance of the proposed controller is demonstrated by comparing it with the recently published studies including different controllers. In this study, to obtain more realistic results, solar photovoltaic (PV) power, wind power, and load demand with stochastic form have been added to the power system. In addition, the dynamic effect of the hydrogen storage system, consisting of an electrolyser and a fuel cell, is considered a grid supporter. The superiority of the WHO algorithm in optimization has been verified by comparing it with three optimization algorithms recently proposed. Finally, the resilience and robustness of the power system are evaluated in perturbed system parameters.
Success rates of fixation techniques on prevention of esophageal stent migration: a systematic review and meta-analysis
Authors: Papaefthymiou Apostolis , Gkolfakis Paraskevas , Basiliya Kirill , Ramai Daryl , Tziatzios Georgios , Sehgal Vinay , Telese Andrea , Norton Benjamin , Aslam Nasar , Johnson Gavin , Haidry Rehan 
Published: August 2023

Background Esophageal stenting is an important intervention for managing malignant and benign dysphagia, with stent migration representing a common drawback. This systematic review with meta-analysis aimed to assess the benefit of stent fixation over nonfixation.
Methods A systematic search was performed in MEDLINE, Cochrane, Scopus, and ClinicalTrials.gov databases until January 2023 for comparative studies evaluating the migration rates of esophageal stents with versus without (control) fixation. The primary outcome was migration rate. Secondary outcomes included adverse event rate. A subgroup analysis stratified the results based on different fixation techniques: suturing, over-the-scope (OTS) clipping, and through-the-scope (TTS) clipping. Meta-analysis was based on a random effects model and the results were reported as odds ratios (ORs) with 95 %CIs.
Results 10 studies (1014 patients) were included. The rate of stent migration was significantly lower after fixation (OR 0.20, 95 %CI 0.11–0.37; I2
= 59 %, P = 0.01). The adverse event rate was similar between fixation and control groups (OR 0.65, 95 %CI 0.28–1.52; I2
= 55 %, P = 0.06). In the subgroup analysis, all fixation techniques remained superior to nonfixation of stents (suturing OR 0.23, 95 %CI 0.10–0.53; OTS clips OR 0.31, 95 %CI 0.17–0.58; TTS clips OR 0.10, 95 %CI 0.03–0.38); however, only the OTS and TTS clip groups achieved nonsignificant heterogeneity (I2
= 0 %, P = 0.67 and P = 0.73, respectively). No difference between techniques was recorded for migration rates.
Conclusion Esophageal stent fixation was associated with significantly lower migration rates compared with nonfixation of stents, regardless of fixation technique and stenting indication.
Total Synthesis and Structure Revision of Saniculamoid D
Authors: Ota Koichiro , Miyaoka Hiroaki , Kamaike Kazuo 
Published: August 2023

AbstractWe present the first asymmetric total synthesis of the norsesquiterpenoid saniculamoid D, from a previously known pure chiral imide, with a longest linear sequence of seven steps. The key highlight of the synthesis is the formation of the bicyclo[3.1.0]hexane moiety through the Julia–Kocienski olefination and Hodgson cyclopropanation. Notably, the NMR spectra and specific rotation value of the synthesized structure did not agree with those of the natural compound. However, a meticulous comparison of the data prompted the reassignment of the correct structure of saniculamoid D, which now corresponds to the structure initially proposed for chromolaevanedione.