bluuebunny/crossref_metadata_2025 huggingface dataset:
The fear of spiders: perceptual features assessed in augmented reality
Authors: Frumento Sergio , Frumento Paolo , Laurino Marco , Menicucci Danilo , Gemignani Angelo
Published: February 2024

Background

Persons with specific phobias typically generalize the dangerousness of the phobic animal to all members of its species, possibly as a result of malfunctioning brain circuitry normally providing quick and dirty identification of evolutionary-relevant stimuli. An objective assessment of which perceptual features make an animal more or less scary to phobic and non-phobic people would help overcome the limitations of the few studies available so far, based on self-reports.

Objective

To achieve this aim, we built an augmented reality setting where volunteers with different levels of fear of spiders were asked to make holographic spiders that look either dangerous or harmless. To reach this goal, a computerized interface allowed participants to modify the spider’s perceptual features (hairiness, body/leg size, and locomotion) in real time.

Results

On average, the dangerous spiders were made hairy, thick, and moving according to spider-like locomotion; coherently, the harmless spiders were made hairless, slim, and moving according to a butterfly-like locomotion. However, these averaged preferences could not fully describe the complex relationship between perceptual preferences with each other and with arachnophobia symptoms. An example of a key finding revealed by cluster analysis is the similarity in perceptual preferences among participants with little or no fear of spiders, whereas participants with more arachnophobia symptoms expressed more varying preferences.

Conclusion

Perceptual preferences toward the spider’s features were behaviorally assessed through an observational study, objectively confirming a generalization effect characterizing spider-fearful participants. These results advance our knowledge of phobic preferences and could be used to improve the acceptability of exposure therapies.
Therapeutic inertia in the management of neuromyelitis optica spectrum disorder
Authors: Cobo-Calvo Álvaro , Gómez-Ballesteros Rocío , Orviz Aida , Díaz Sánchez María , Boyero Sabas , Aguado-Valcarcel Marta , Sepúlveda María , Rebollo Pablo , López-Laiz Paloma , Maurino Jorge , Téllez Lara Nieves
Published: February 2024

Introduction and objective

Limited information is available on how neurologists make therapeutic decisions in neuromyelitis optica spectrum disorder (NMOSD), especially when new treatments with different mechanisms of action, administration, and safety profile are being approved. Decision-making can be complex under this uncertainty and may lead to therapeutic inertia (TI), which refers to lack of treatment initiation or intensification when therapeutic goals are not met. The study aim was to assess neurologists’ TI in NMOSD.

Methods

An online, cross-sectional study was conducted in collaboration with the Spanish Society of Neurology. Neurologists answered a survey composed of demographic characteristics, professional background, and behavioral traits. TI was defined as the lack of initiation or intensification with high-efficacy treatments when there is evidence of disease activity and was assessed through five NMOSD aquaporin-4 positive (AQP4+) simulated case scenarios. A multivariate logistic regression analysis was used to determine the association between neurologists’ characteristics and TI.

Results

A total of 78 neurologists were included (median interquartile range [IQR] age: 36.0 [29.0–46.0] years, 55.1% male, median [IQR] experience managing demyelinating conditions was 5.2 [3.0–11.1] years). The majority of participants were general neurologists (59.0%) attending a median (IQR) of 5.0 NMOSD patients (3.0–12.0) annually. Thirty participants (38.5%) were classified as having TI. Working in a low complexity hospital and giving high importance to patient’s tolerability/safety when choosing a treatment were predictors of TI.

Conclusion

TI is a common phenomenon among neurologists managing NMOSD AQP4+. Identifying TI and implementing specific intervention strategies may be critical to improving therapeutic decisions and patient care.
Feasibility of video-based real-time nystagmus tracking: a lightweight deep learning model approach using ocular object segmentation
Authors: Cho Changje , Park Sejik , Ma Sunmi , Lee Hyo-Jeong , Lim Eun-Cheon , Hong Sung Kwang
Published: February 2024

Background

Eye movement tests remain significantly underutilized in emergency departments and primary healthcare units, despite their superior diagnostic sensitivity compared to neuroimaging modalities for the differential diagnosis of acute vertigo. This underutilization may be attributed to a potential lack of awareness regarding these tests and the absence of appropriate tools for detecting nystagmus. This study aimed to develop a nystagmus measurement algorithm using a lightweight deep-learning model that recognizes the ocular regions.

Method

The deep learning model was used to segment the eye regions, detect blinking, and determine the pupil center. The model was trained using images extracted from video clips of a clinical battery of eye movement tests and synthesized images reproducing real eye movement scenarios using virtual reality. Each eye image was annotated with segmentation masks of the sclera, iris, and pupil, with gaze vectors of the pupil center for eye tracking. We conducted a comprehensive evaluation of model performance and its execution speeds in comparison to various alternative models using metrics that are suitable for the tasks.

Results

The mean Intersection over Union values of the segmentation model ranged from 0.90 to 0.97 for different classes (sclera, iris, and pupil) across types of images (synthetic vs. real-world images). Additionally, the mean absolute error for eye tracking was 0.595 for real-world data and the F1 score for blink detection was ≥ 0.95, which indicates our model is performing at a very high level of accuracy. Execution speed was also the most rapid for ocular object segmentation under the same hardware condition as compared to alternative models. The prediction for horizontal and vertical nystagmus in real eye movement video revealed high accuracy with a strong correlation between the observed and predicted values (r = 0.9949 for horizontal and r = 0.9950 for vertical; both p < 0.05).

Conclusion

The potential of our model, which can automatically segment ocular regions and track nystagmus in real time from eye movement videos, holds significant promise for emergency settings or remote intervention within the field of neurotology.
Case report: Mirror paraclinoid aneurysm associated with mirror clinoidal meningioma
Authors: Paitán Alexander Feliciano Vilcahuamán , Gibbon Frederico de Lima , Korotkov Dmitriy , Castillo Ileane Camallery , Moguel Ambar E. Riley , Salvagni Felipe Pereira , Chaddad-Neto Feres
Published: February 2024

Introduction

Clinoidal meningiomas and paraclinoid aneurysms are individually uncommon, with the coexistence of mirror paraclinoid aneurysms and clinoidal meningiomas presenting an even rarer scenario. While the association between meningiomas and aneurysms is documented, the simultaneous presence of mirror lesions for both pathologies is not reported in the literature.

Clinical presentation

We report a 62-year-old female with a three-month history of moderate bifrontal headaches. Magnetic Resonance Angiography (MRA) revealed mirror paraclinoid aneurysms, prompting surgical intervention. During the procedure, mirror clinoidal meningiomas were incidentally discovered. The left aneurysm was addressed first due to higher rupture risk, followed by the right aneurysm 3 months later. Both meningiomas were confirmed as Transitional Meningiomas (Grade 1; OMS, 2021). The aneurysms were successfully clipped, and the patient had an excellent postoperative outcome.

Conclusion

This case represents a unique occurrence of mirror ophthalmic segment internal carotid artery aneurysms associated with mirror clinoidal meningiomas, a combination not previously reported. Despite the limitations of MRA in detecting small meningiomas, it remains a valuable non-invasive screening tool for neurovascular diseases. The case underscores the need for further research to elucidate the association between cerebral aneurysms and meningiomas.
Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder
Authors: Proshina Ekaterina , Martynova Olga , Portnova Galina , Khayrullina Guzal , Sysoeva Olga
Published: February 2024

Introduction

Mental disorders are a significant concern in contemporary society, with a pressing need to identify biological markers. Long-range temporal correlations (LRTC) of brain rhythms have been widespread in clinical cohort studies, especially in major depressive disorder (MDD). However, research on LRTC in obsessive-compulsive disorder (OCD) is severely limited. Given the high co-occurrence of OCD and MDD, we conducted a comparative LRTC investigation. We assumed that the LRTC patterns will allow us to compare measures of brain cortical balance of excitation and inhibition in OCD and MDD, which will be useful in the area of differential diagnosis.

Methods

In this study, we used the 64-channel resting state EEG of 29 MDD participants, 26 OCD participants, and a control group of 37 volunteers. Detrended fluctuation analyzes was used to assess LRTC.

Results

Our results indicate that all scaling exponents of the three subject groups exhibited persistent LRTC of EEG oscillations. There was a tendency for LRTC to be higher in disorders than in controls, but statistically significant differences were found between the OCD and control groups in the entire frontal and left parietal occipital areas, and between the MDD and OCD groups in the middle and right frontal areas.

Discussion

We believe that these results indicate abnormalities in the inhibitory and excitatory neurotransmitter systems, predominantly affecting areas related to executive functions.
EZH2 inhibition reactivates epigenetically silenced FMR1 and normalizes molecular and electrophysiological abnormalities in fragile X syndrome neurons
Authors: Fang Minggang , Deibler Sara K. , Krishnamurthy Pranathi Meda , Wang Feng , Rodriguez Paola , Banday Shahid , Virbasius Ching-Man , Sena-Esteves Miguel , Watts Jonathan K. , Green Michael R.
Published: February 2024

Fragile X Syndrome (FXS) is a neurological disorder caused by epigenetic silencing of the FMR1 gene. Reactivation of FMR1 is a potential therapeutic approach for FXS that would correct the root cause of the disease. Here, using a candidate-based shRNA screen, we identify nine epigenetic repressors that promote silencing of FMR1 in FXS cells (called FMR1 Silencing Factors, or FMR1- SFs). Inhibition of FMR1-SFs with shRNAs or small molecules reactivates FMR1 in cultured undifferentiated induced pluripotent stem cells, neural progenitor cells (NPCs) and post-mitotic neurons derived from FXS patients. One of the FMR1-SFs is the histone methyltransferase EZH2, for which an FDA-approved small molecule inhibitor, EPZ6438 (also known as tazemetostat), is available. We show that EPZ6438 substantially corrects the characteristic molecular and electrophysiological abnormalities of cultured FXS neurons. Unfortunately, EZH2 inhibitors do not efficiently cross the blood-brain barrier, limiting their therapeutic use for FXS. Recently, antisense oligonucleotide (ASO)-based approaches have been developed as effective treatment options for certain central nervous system disorders. We therefore derived efficacious ASOs targeting EZH2 and demonstrate that they reactivate FMR1 expression and correct molecular and electrophysiological abnormalities in cultured FXS neurons, and reactivate FMR1 expression in human FXS NPCs engrafted within the brains of mice. Collectively, our results establish EZH2 inhibition in general, and EZH2 ASOs in particular, as a therapeutic approach for FXS.
Exploring the dynamics of adult Axin2 cell lineage integration into dentate gyrus granule neurons
Authors: Sharifi Khadijeh A. , Farzad Faraz , Soldozy Sauson , DeWitt Matthew R. , Price Richard J. , Sheehan Jason , Kalani M. Yashar S. , Tvrdik Petr
Published: February 2024

The Wnt pathway plays critical roles in neurogenesis. The expression of Axin2 is induced by Wnt/β-catenin signaling, making this gene a reliable indicator of canonical Wnt activity. We employed pulse-chase genetic lineage tracing with the Axin2-CreERT2 allele to follow the fate of Axin2+ lineage in the adult hippocampal formation. We found Axin2 expressed in astrocytes, neurons and endothelial cells, as well as in the choroid plexus epithelia. Simultaneously with the induction of Axin2 fate mapping by tamoxifen, we marked the dividing cells with 5-ethynyl-2′-deoxyuridine (EdU). Tamoxifen induction led to a significant increase in labeled dentate gyrus granule cells three months later. However, none of these neurons showed any EdU signal. Conversely, six months after the pulse-chase labeling with tamoxifen/EdU, we identified granule neurons that were positive for both EdU and tdTomato lineage tracer in each animal. Our data indicates that Axin2 is expressed at multiple stages of adult granule neuron differentiation. Furthermore, these findings suggest that the integration process of adult-born neurons from specific cell lineages may require more time than previously thought.
Mito-metformin protects against mitochondrial dysfunction and dopaminergic neuronal degeneration by activating upstream PKD1 signaling in cell culture and MitoPark animal models of Parkinson’s disease
Authors: Ay Muhammet , Charli Adhithiya , Langley Monica , Jang Ahyoung , Padhi Piyush , Jin Huajun , Anantharam Vellareddy , Kalyanaraman Balaraman , Kanthasamy Arthi , Kanthasamy Anumantha G.
Published: February 2024

Impaired mitochondrial function and biogenesis have strongly been implicated in the pathogenesis of Parkinson’s disease (PD). Thus, identifying the key signaling mechanisms regulating mitochondrial biogenesis is crucial to developing new treatment strategies for PD. We previously reported that protein kinase D1 (PKD1) activation protects against neuronal cell death in PD models by regulating mitochondrial biogenesis. To further harness the translational drug discovery potential of targeting PKD1-mediated neuroprotective signaling, we synthesized mito-metformin (Mito-Met), a mitochondria-targeted analog derived from conjugating the anti-diabetic drug metformin with a triphenylphosphonium functional group, and then evaluated the preclinical efficacy of Mito-Met in cell culture and MitoPark animal models of PD. Mito-Met (100–300 nM) significantly activated PKD1 phosphorylation, as well as downstream Akt and AMPKα phosphorylation, more potently than metformin, in N27 dopaminergic neuronal cells. Furthermore, treatment with Mito-Met upregulated the mRNA and protein expression of mitochondrial transcription factor A (TFAM) implying that Mito-Met can promote mitochondrial biogenesis. Interestingly, Mito-Met significantly increased mitochondrial bioenergetics capacity in N27 dopaminergic cells. Mito-Met also reduced mitochondrial fragmentation induced by the Parkinsonian neurotoxicant MPP+ in N27 cells and protected against MPP+-induced TH-positive neurite loss in primary neurons. More importantly, Mito-Met treatment (10 mg/kg, oral gavage for 8 week) significantly improved motor deficits and reduced striatal dopamine depletion in MitoPark mice. Taken together, our results demonstrate that Mito-Met possesses profound neuroprotective effects in both in vitro and in vivo models of PD, suggesting that pharmacological activation of PKD1 signaling could be a novel neuroprotective translational strategy in PD and other related neurocognitive diseases.
Gulf war toxicant-induced effects on the hippocampal dendritic arbor are reversed by treatment with a Withania somnifera extract
Authors: Shaikh Amaan L. , Murray Kathleen E. , Ravindranath Vijayalakshmi , Citron Bruce A.
Published: February 2024

Gulf War Illness (GWI) is a multi-symptom disorder that manifests with fatigue, sleep disturbances, mood-cognition pathologies, and musculoskeletal symptoms. GWI affects at least 25% of the military personnel that served in Operations Desert Shield and Desert Storm from 1990 to 1991. We modeled Gulf War toxicant exposure in C57BL/6J mice by combined exposure to pyridostigmine bromide (an anti-sarin drug), chlorpyrifos (an organophosphate insecticide), and DEET (an insect repellent) for 10 days followed by oral treatment with Withania somnifera root extract for 21 days beginning at 12 weeks post-exposure. W. somnifera, commonly referred to as ashwagandha, has been used in traditional Ayurvedic medicine for centuries to improve memory and reduce inflammation, and its roots contain bioactive molecules which share functional groups with modern pain, cancer, and anti-inflammatory drugs. Previously, we observed that GWI mice displayed chronic reductions in dendritic arbor and loss of spines in granule cells of the dentate gyrus of the hippocampus at 14 weeks post-exposure. Here, we examined the effects of treatment with W. somnifera root extract on chronic dendrite and spine morphology in dentate granule cells of the mouse hippocampus following Gulf War toxicant exposure. GWI mice showed approximately 25% decreases in dendritic length (p < 0.0001) and overall dendritic spine density with significant reductions in thin and mushroom spines. GWI mice treated with the Ayurvedic W. somnifera extract exhibited dendritic lengths and spine densities near normal levels. These findings demonstrate the efficacy of the Ayurvedic treatment for neuroprotection following these toxic exposures. We hope that the extract and the neuronal processes influenced will open new avenues of research regarding treatment of Gulf War Illness and neurodegenerative disorders.
Machine learning-based evaluation of spontaneous pain and analgesics from cellular calcium signals in the mouse primary somatosensory cortex using explainable features
Authors: Bak Myeong Seong , Park Haney , Yoon Heera , Chung Geehoon , Shin Hyunjin , Shin Soonho , Kim Tai Wan , Lee Kyungjoon , Nägerl U. Valentin , Kim Sang Jeong , Kim Sun Kwang
Published: February 2024

Introduction

Pain that arises spontaneously is considered more clinically relevant than pain evoked by external stimuli. However, measuring spontaneous pain in animal models in preclinical studies is challenging due to methodological limitations. To address this issue, recently we developed a deep learning (DL) model to assess spontaneous pain using cellular calcium signals of the primary somatosensory cortex (S1) in awake head-fixed mice. However, DL operate like a “black box”, where their decision-making process is not transparent and is difficult to understand, which is especially evident when our DL model classifies different states of pain based on cellular calcium signals. In this study, we introduce a novel machine learning (ML) model that utilizes features that were manually extracted from S1 calcium signals, including the dynamic changes in calcium levels and the cell-to-cell activity correlations.

Method

We focused on observing neural activity patterns in the primary somatosensory cortex (S1) of mice using two-photon calcium imaging after injecting a calcium indicator (GCaMP6s) into the S1 cortex neurons. We extracted features related to the ratio of up and down-regulated cells in calcium activity and the correlation level of activity between cells as input data for the ML model. The ML model was validated using a Leave-One-Subject-Out Cross-Validation approach to distinguish between non-pain, pain, and drug-induced analgesic states.

Results and discussion

The ML model was designed to classify data into three distinct categories: non-pain, pain, and drug-induced analgesic states. Its versatility was demonstrated by successfully classifying different states across various pain models, including inflammatory and neuropathic pain, as well as confirming its utility in identifying the analgesic effects of drugs like ketoprofen, morphine, and the efficacy of magnolin, a candidate analgesic compound. In conclusion, our ML model surpasses the limitations of previous DL approaches by leveraging manually extracted features. This not only clarifies the decision-making process of the ML model but also yields insights into neuronal activity patterns associated with pain, facilitating preclinical studies of analgesics with higher potential for clinical translation.
Ketogenic therapy towards precision medicine for brain diseases
Authors: Liu Yang , Fan Linlin , Yang Haoying , Wang Danli , Liu Runhan , Shan Tikun , Xia Xue
Published: February 2024

Precision nutrition and nutrigenomics are emerging in the development of therapies for multiple diseases. The ketogenic diet (KD) is the most widely used clinical diet, providing high fat, low carbohydrate, and adequate protein. KD produces ketones and alters the metabolism of patients. Growing evidence suggests that KD has therapeutic effects in a wide range of neuronal diseases including epilepsy, neurodegeneration, cancer, and metabolic disorders. Although KD is considered to be a low-side-effect diet treatment, its therapeutic mechanism has not yet been fully elucidated. Also, its induced keto-response among different populations has not been elucidated. Understanding the ketone metabolism in health and disease is critical for the development of KD-associated therapeutics and synergistic therapy under any physiological background. Here, we review the current advances and known heterogeneity of the KD response and discuss the prospects for KD therapy from a precision nutrition perspective.
Prediction of risk factors for linezolid-induced thrombocytopenia based on neural network model
Authors: Zhao Xian , Peng Qin , Hu Dongmei , Li Weiwei , Ji Qing , Dong Qianqian , Huang Luguang , Piao Miyang , Ding Yi , Wang Jingwen
Published: February 2024

Background: Based on real-world medical data, the artificial neural network model was used to predict the risk factors of linezolid-induced thrombocytopenia to provide a reference for better clinical use of this drug and achieve the timely prevention of adverse reactions.

Methods: The artificial neural network algorithm was used to construct the prediction model of the risk factors of linezolid-induced thrombocytopenia and further evaluate the effectiveness of the artificial neural network model compared with the traditional Logistic regression model.

Results: A total of 1,837 patients receiving linezolid treatment in a hospital in Xi ‘an, Shaanxi Province from 1 January 2011 to 1 January 2021 were recruited. According to the exclusion criteria, 1,273 cases that did not meet the requirements of the study were excluded. A total of 564 valid cases were included in the study, with 89 (15.78%) having thrombocytopenia. The prediction accuracy of the artificial neural network model was 96.32%, and the AUROC was 0.944, which was significantly higher than that of the Logistic regression model, which was 86.14%, and the AUROC was 0.796. In the artificial neural network model, urea, platelet baseline value and serum albumin were among the top three important risk factors.

Conclusion: The predictive performance of the artificial neural network model is better than that of the traditional Logistic regression model, and it can well predict the risk factors of linezolid-induced thrombocytopenia.
Evaluation of the hepatotoxicity of Psoralea corylifolia L. based on a zebrafish model
Authors: Gao Shu-Yan , Zhao Jing-Cheng , Xia Qing , Sun Chen , Aili Maimaiti , Talifu Ainiwaer , Huo Shi-Xia , Zhang Yun , Li Zhi-Jian
Published: February 2024

Objective:Psoralea corylifolia L. (FP) has received increasing attention due to its potential hepatotoxicity.

Methods: In this study, zebrafish were treated with different concentrations of an aqueous extract of FP (AEFP; 40, 50, or 60 μg/mL), and the hepatotoxic effects of tonicity were determined by the mortality rate, liver morphology, fluorescence area and intensity of the liver, biochemical indices, and pathological tissue staining. The mRNA expression of target genes in the bile acid metabolic signaling pathway and lipid metabolic pathway was detected by qPCR, and the mechanism of toxicity was initially investigated. AEFP (50 μg/mL) was administered in combination with FXR or a peroxisome proliferator-activated receptor α (PPARα) agonist/inhibitor to further define the target of toxicity.

Results: Experiments on toxic effects showed that, compared with no treatment, AEFP administration resulted in liver atrophy, a smaller fluorescence area in the liver, and a lower fluorescence intensity (p < 0.05); alanine transaminase (ALT), aspartate transaminase (AST), and γ-GT levels were significantly elevated in zebrafish (p < 0.01), and TBA, TBIL, total cholesterol (TC), TG, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels were elevated to different degrees (p < 0.05); and increased lipid droplets in the liver appeared as fatty deposits. Molecular biological validation revealed that AEFP inhibited the expression of the FXR gene, causing an increase in the expression of the downstream genes SHP, CYP7A1, CYP8B1, BSEP, MRP2, NTCP, peroxisome proliferator-activated receptor γ (PPARγ), ME-1, SCD-1, lipoprotein lipase (LPL), CPT-1, and CPT-2 and a decrease in the expression of PPARα (p < 0.05).

Conclusion: This study demonstrated that tonic acid extracts are hepatotoxic to zebrafish through the inhibition of FXR and PPARα expression, thereby causing bile acid and lipid metabolism disorders.
A feasibility study using an array of LaBr3(Ce) scintillation detectors as a Compton camera for prompt gamma imaging during BNCT
Authors: Nutter Kiran , Price Tony , Kokalova Tzany , Green Stuart , Phoenix Ben
Published: February 2024

Boron Neutron Capture Therapy (BNCT) is a binary cancer therapy where a low energy neutron beam is incident upon a patient who has been administered a tumour-seeking 10B loaded compound. The neutron capture reaction on 10B results in the production of two short range particles, 7Li and 4He, that deposit all of their energies within the targeted cell. However, accurate, online dosimetry during BNCT is challenging as it requires knowledge of both the neutron fluence and 10B concentration in cells. An additional product in the neutron capture reaction on 10B is a 478 keV prompt gamma ray, and if the production vertices of these gamma rays could be imaged by an external camera, the density of the vertices could be used to infer the dose delivered to the patient. In this study, the feasibility of using an array of LaBr3 scintillators as a modified Compton camera for prompt gamma imaging during BNCT was investigated using Geant4 simulations. These simulations demonstrated that a phantom containing a 3 cm diameter region of 400 ppm 10B could be reconstructed using clinically relevant neutron fluences. This result opens up more possibilities for future research to improve dosimetry during BNCT.
Experimental study on flexural mechanical properties of steel fiber reinforced alkali-activated slag concrete beams
Authors: Yuan Xiaohui , Huo Ruijin , Zhang Xin
Published: February 2024

As an environmentally friendly alternative to ordinary concrete, slag concrete is subject to limitations such as drying shrinkage and micro-cracking during its promotion and application. In order to address these challenges, steel fibers, known for their excellent tensile, shear, crack-resistance, and toughness properties, have been introduced to enhance the ductility of alkali-activated slag concrete. This study utilized steel fiber content as a variable and produced eight steel fiber-reinforced alkali-activated slag concrete beams to investigate their flexural mechanical properties. By exploring the influence of steel fiber content variation on the mechanical behavior of alkali-activated slag concrete beams and conducting validation through finite element analysis, the study unveiled the impact of steel fibers on the performance of alkali-activated slag concrete beams. The research findings demonstrate a significant enhancement in the flexural mechanical properties of alkali-activated slag concrete beams with the addition of steel fibers, leading to a reduction in surface cracking and an improvement in the durability of the elements. The outcomes of this study hold crucial theoretical implications for the widespread application of steel fiber-reinforced alkali-activated slag concrete.
Robust human locomotion and localization activity recognition over multisensory
Authors: Khan Danyal , Alonazi Mohammed , Abdelhaq Maha , Al Mudawi Naif , Algarni Asaad , Jalal Ahmad , Liu Hui
Published: February 2024

Human activity recognition (HAR) plays a pivotal role in various domains, including healthcare, sports, robotics, and security. With the growing popularity of wearable devices, particularly Inertial Measurement Units (IMUs) and Ambient sensors, researchers and engineers have sought to take advantage of these advances to accurately and efficiently detect and classify human activities. This research paper presents an advanced methodology for human activity and localization recognition, utilizing smartphone IMU, Ambient, GPS, and Audio sensor data from two public benchmark datasets: the Opportunity dataset and the Extrasensory dataset. The Opportunity dataset was collected from 12 subjects participating in a range of daily activities, and it captures data from various body-worn and object-associated sensors. The Extrasensory dataset features data from 60 participants, including thousands of data samples from smartphone and smartwatch sensors, labeled with a wide array of human activities. Our study incorporates novel feature extraction techniques for signal, GPS, and audio sensor data. Specifically, for localization, GPS, audio, and IMU sensors are utilized, while IMU and Ambient sensors are employed for locomotion activity recognition. To achieve accurate activity classification, state-of-the-art deep learning techniques, such as convolutional neural networks (CNN) and long short-term memory (LSTM), have been explored. For indoor/outdoor activities, CNNs are applied, while LSTMs are utilized for locomotion activity recognition. The proposed system has been evaluated using the k-fold cross-validation method, achieving accuracy rates of 97% and 89% for locomotion activity over the Opportunity and Extrasensory datasets, respectively, and 96% for indoor/outdoor activity over the Extrasensory dataset. These results highlight the efficiency of our methodology in accurately detecting various human activities, showing its potential for real-world applications. Moreover, the research paper introduces a hybrid system that combines machine learning and deep learning features, enhancing activity recognition performance by leveraging the strengths of both approaches.
More than a meat- or synthetic nitrogen fertiliser-substitute: a review of legume phytochemicals as drivers of ‘One Health’ via their influence on the functional diversity of soil- and gut-microbes
Authors: Duarte Rafael D. C. , Iannetta Pietro P. M. , Gomes Ana M. , Vasconcelos Marta W.
Published: February 2024

Legumes are essential to healthy agroecosystems, with a rich phytochemical content that impacts overall human and animal well-being and environmental sustainability. While these phytochemicals can have both positive and negative effects, legumes have traditionally been bred to produce genotypes with lower levels of certain plant phytochemicals, specifically those commonly termed as ‘antifeedants’ including phenolic compounds, saponins, alkaloids, tannins, and raffinose family oligosaccharides (RFOs). However, when incorporated into a balanced diet, such legume phytochemicals can offer health benefits for both humans and animals. They can positively influence the human gut microbiome by promoting the growth of beneficial bacteria, contributing to gut health, and demonstrating anti-inflammatory and antioxidant properties. Beyond their nutritional value, legume phytochemicals also play a vital role in soil health. The phytochemical containing residues from their shoots and roots usually remain in-field to positively affect soil nutrient status and microbiome diversity, so enhancing soil functions and benefiting performance and yield of following crops. This review explores the role of legume phytochemicals from a ‘one health’ perspective, examining their on soil- and gut-microbial ecology, bridging the gap between human nutrition and agroecological science.
Demographic patterns of two related desert shrubs with overlapping distributions in response to past climate changes
Authors: Yu Qiushi , Hu Jing , Hu Xiaoke , Zhou Yongfeng , Wang Fanglin , Jiang Shengxiu , Wang Yuqi
Published: February 2024

Numerous studies have revealed that past geological events and climatic fluctuations had profoundly affected the genetic structure and demographic patterns of species. However, related species with overlapping ranges may have responded to such environmental changes in different ways. In this study, we compared the genetic structure and population dynamics of two typical desert shrubs with overlapping distributions in northern China, Nitraria tangutorum and Nitraria sphaerocarpa, based on chloroplast DNA (cpDNA) variations and species distribution models. We sequenced two cpDNA fragments (trnH-trnA and atpH-atpI) in 633 individuals sampled from 52 natural populations. Twenty-four chlorotypes, including eight rare chlorotypes, were identified, and a single dominant haplotype (H4) widely occurred in the entire geographical ranges of the two species. There were also a few distinctive chlorotypes fixed in different geographical regions. Population structure analyses suggested that the two species had significantly different levels of total genetic diversity and interpopulation differentiation, which was highly likely correlated with the special habitat preferences of the two species. A clear phylogeographic structure was identified to exist among populations of N. sphaerocarpa, but not exist for N. tangutorum. The neutral tests, together with the distribution of pairwise differences revealed that N. tangutorum experienced a sudden demographic expansion, and its expansion approximately occurred between 21 and 7 Kya before present, while a rapid range expansion was not identified for N. sphaerocarpa. The ecological niche modeling (ENM) analysis indicated that the potential ranges of two species apparently fluctuated during the past and present periods, with obvious contraction in the Last Glacial Maximum (LGM) and recolonization in the present, respectively, comparing to the Last Interglacial (LIG). These findings suggest that the two species extensively occurred in the Northwest of China before the Quaternary, and the current populations of them originated from a few separated glacial refugia following their habitat fragmentation in the Quarternary. Our results provide new insights on the impact of past geological and climatic fluctuations on the population dynamics of desert plants in northwestern China, and further enforce the hypothesis that there were several independent glacial refugia for these species during the Quaternary glaciations.
Integrated microbiome and metabolomics analysis reveal the relationship between plant-specialized metabolites and microbial community in Phellodendron amurense
Authors: Zhang Wanran , Gao Ranran , Tian Lixia , Xu Zhichao
Published: February 2024

Phellodendron amurense is the essential source of bisbenzylisoquinoline alkaloids (BIAs), making it a highly valued raw material in traditional Chinese medicine. The plant’s root secondary metabolism is intricately linked to the microbial communities that surround it. However, the root-associated microbiomes of P. amurense, as well as the potential correlation between its bioactive compounds and these microbiomes, remain poorly understood. Here, the metabolic profiles of root, rhizosphere, and bulk soils of P. amurense revealed the dramatic differences in the relative content of plant-specialized metabolites. A total of 31, 21, and 0 specialized metabolites in P. amurense were identified in the root, rhizosphere soil, and bulk soil, respectively, with higher content of the seven major BIAs observed in the rhizosphere compared with that in the bulk soils. The composition of the bulk and rhizosphere microbiomes was noticeably distinct from that of the endospheric microbiome. The phylum Cyanobacteria accounted for over 60% of the root endosphere communities, and the α-diversity in root was the lowest. Targeted seven BIAs, namely, berberine, palmatine, magnocurarine, phellodendrine, jatrorrhizine, tetrahydropalmatine, and magnoflorine, were significantly positively correlated with Nectriaceae and Sphingobacteriaceae. This study has illuminated the intricate interaction networks between P. amurense root-associated microorganisms and their key chemical compounds, providing the theoretical foundation for discovering biological fertilizers and laying the groundwork for cultivating high-quality medicinal plants.
Romantic relationship obsessive-compulsive doubts, perfectionism, and DSM-5 personality traits in LGB people: a comparison with heterosexual individuals
Authors: Angelo Nicole Loren , Brullo Greta , Marsiglia Alessandro , Tirelli Alessandra , Piroddi Elisa , Viti Chiara , Aicardi Ilaria , Pozza Andrea
Published: February 2024

Introduction

Relationship Obsessive-Compulsive Disorder is characterized by the presence of relationship-centered or partner-focused obsessions and compulsions that determine a great sense of doubt toward the partner or the relationship. Personality characteristics, including perfectionism, are involved in the development of Relationship Obsessive-Compulsive Disorder, and could predispose the individual to excessive doubts and preoccupations regarding the “adequacy of the couple” or the physical appearance of one’s partner. Evidence from epidemiological research shows that the LGB community can present a high risk and prevalence of obsessive-compulsive symptoms and recent research demonstrated the usefulness of the DSM-5 personality model in understanding the personality of sexual minorities. However, further research is necessary to deepen our knowledge of the relationship between these variables in the LGB community. The aim of the present study was to compare a group of heterosexual individuals to a group of LGB individuals regarding personality traits, perfectionism, and relationship obsessive-compulsive symptoms.

Methods

A total of 200 participants, 98 in the heterosexual group and 102 in the LGB group, were enrolled in the study and completed a psychological battery comprised of the Obsessive-Compulsive Inventory-Revised, Personality Inventory for DSM-5, Relationship Obsessive-Compulsive Inventory, Partner-Related Obsessive-Compulsive Symptom Inventory, and Multidimensional Perfectionism Scale.

Results

The results show that LGB individuals tend to report greater feelings of doubt regarding the partner’s love, more negative emotions (Negative Affect) and Antagonism, and greater perfectionism traits compared to heterosexual individuals.

Conclusion

These findings underline the necessity to consider the implementation of personalized interventions in clinical practice and the importance of initiating early preventive programs in sexual minority communities.
The influence of segmental and suprasegmental phonological awareness on word and pseudoword reading—A comparison between native English speakers and native Chinese speakers of English
Authors: Jiang Ying , Gai Xiaosong , Wang Zhe , Thomson Jenny
Published: February 2024

Segmental and suprasegmental phonological awareness (PA) are closely related to word reading skills in native speakers learning to read an alphabetic script as used in English. However, their roles in English word and pseudoword reading among native Chinese (NC) speakers, and how English proficiency might affect these relationships, remain less clear. This study examined the links between English segmental/suprasegmental PA and word/pseudoword reading in NC and native English (NE) speakers. Both child and adult participants were assessed on English segmental and suprasegmental PA, alongside vocabulary, at a single time point. The results showed that both segmental PA (elision and segmenting nonwords) and suprasegmental PA (aural suffix judgment and written suffix judgment) were significantly correlated with English real word and pseudoword reading of both NE and NC children, and NC adults, but not NE adults. Moreover, for NE and NC children, segmental PA correlated stronger with real word reading than suprasegmental PA after controlling for vocabulary. Among NC adults, both segmental and suprasegmental PA significantly contributed to real word reading. For pseudoword reading, after controlling for vocabulary, segmental PA had a stronger correlation among NC children and adults, while suprasegmental PA was more influential for NE children. This research gives insights into factors influencing NC speakers’ English word reading ability, bearing essential implications for enhancing second language literacy in learners from a logographic background.
What kind of children do kindergarten teachers prefer? —Typology of the preferred types of children
Authors: Shi Song , Zhang Huayuan , Zhang Zizai , Sun Jiahui , Qi Xin , Li Shunian
Published: February 2024

The teacher’s pets are a common occurrence in the field of education. To investigate the preferences teachers exhibit toward certain children, the study focused on kindergarten teachers and employed a mixed research methodology. Initially, qualitative interviews were conducted with 15 kindergarten teachers to identify specific criteria influencing teacher preferences. Subsequently, A comprehensive model of teacher’s pets was developed through a questionnaire survey involving 463 participants. This model encapsulated 32 distinct indicators, categorized into 7 types: children with good appearance (GA), exceptional abilities (OA), commendable conduct (GC), proactive and enthusiastic demeanor (PE), compliant and carefree nature (OC), children from vulnerable groups (VC), and those influenced by their parents (PI). The resulting model demonstrated a sound structure. Not only did it validate existing findings, but it also expanded upon the identified types of teacher’s pets. An analysis based on game theory revealed the weighted combinations, highlighting the top three types of teacher’s pets: children influenced by parental factors (24.3%), proactive and enthusiastic individuals (15.7%), and obedient, carefree children (14.8%), respectively. Conversely, the representation of vulnerable-concerned children (11.1%) was the lowest among the identified types.
General infection prevention, mitigation, and control procedures implemented in the university education during the COVID-19 pandemic to achieve classroom attendance: a successful community case study
Authors: Monge Diana , Gallego-Gil Ana , Neria Fernando , Canellas Soledad , Caballero Fernando , Díaz de Bustamante Ana , Samper Mónica
Published: February 2024

Introduction

The COVID-19 pandemic entailed confinement and elimination of face-to-face university classes in Spain. The Francisco de Vitoria University in Madrid (UFV by its Spanish acronym) implemented risk management systems to enable on-campus university activity to avoid a negative impact on students, teachers, and faculties.

Methods

A tracking/registry system was implemented to collect data, identify COVID-19-related cases, implement containment measures, and do follow-up in the UFV community (administration/services personnel [ASP], teaching/research personnel [TRP], and students), from September 2020 to April 2022. In addition, a prevention plan was implemented on campus to avoid COVID-19 spreading. Satisfaction with these measures was assessed through an online questionnaire.

Results

A total of 7,165 suspected COVID-19 cases (84.7% students, 7.7% ASP, 6.5% TRP) were tracked (62.5% female cases, mean age (±SD) 24.8 years (±9.2 years)), and 45% of them confirmed (82% symptomatic/16% asymptomatic), being the student group that with the highest percentage (38.3% total tracked cases). The source of infection was identified in 50.6% of the confirmed cases (90.2% located off-campus). Nineteen COVID-19 outbreaks were registered (inside-10/outside-9). COVID-19 incidence rates were similar or lower than those reported in the Community of Madrid, except in the last wave, corresponding to Omicron variant. The degree of satisfaction (scale 1–6) with the implemented measures was high (scores 4.48–5.44).

Conclusion

During the COVID-19 pandemic, UFV control measures, periodic monitoring, and the effectiveness of the tracking system have contributed to maintaining classroom teaching, guaranteeing health and safety. UFV has adapted to a new reality as an example of good practice for future pandemics or emergency situations.
Application of inverse weighting analysis to assess the association of youth perceptions with the age of initiation of tobacco products
Authors: Atem Folefac D. , Bluestein Meagan A. , Chen Baojiang , Harrell Melissa B. , Messiah Sarah E. , Kuk Arnold E. , Pérez Adriana
Published: February 2024

Introduction

To examine if perceptions of harmfulness and addictiveness of hookah and cigarettes impact the age of initiation of hookah and cigarettes, respectively, among US youth. Youth (12-17 years old) users and never users of hookah and cigarettes during their first wave of PATH participation were analyzed by each tobacco product (TP) independently. The effect of perceptions of (i) harmfulness and (ii) addictiveness at the first wave of PATH participation on the age of initiation of ever use of hookah was estimated using interval-censoring Cox proportional hazards models.

Methods

Users and never users of hookah at their first wave of PATH participation were balanced by multiplying the sampling weight and the 100 balance repeated replicate weights with the inverse probability weight (IPW). The IPW was based on the probability of being a user in their first wave of PATH participation. A Fay’s factor of 0.3 was included for variance estimation. Crude hazard ratios (HR) and 95% confidence intervals (CIs) are reported. A similar process was repeated for cigarettes.

Results

Compared to youth who perceived each TP as “a lot of harm”, youth who reported perceived “some harm” had younger ages of initiation of these tobacco products, HR: 2.53 (95% CI: 2.87-4.34) for hookah and HR: 2.35 (95% CI: 2.10-2.62) for cigarettes. Similarly, youth who perceived each TP as “no/little harm” had an earlier age of initiation of these TPs compared to those who perceived them as “a lot of harm”, with an HR: 2.23 (95% CI: 1.82, 2.71) for hookah and an HR: 1.85 (95% CI: 1.72, 1.98) for cigarettes. Compared to youth who reported each TP as “somewhat/very likely” as their perception of addictiveness, youth who reported “neither likely nor unlikely” and “very/somewhat unlikely” as their perception of addictiveness of hookah had an older age of initiation, with an HR: 0.75 (95% CI: 0.67-0.83) and an HR: 0.55 (95% CI: 0.47, 0.63) respectively.

Discussion

Perceptions of the harmfulness and addictiveness of these tobacco products (TPs) should be addressed in education campaigns for youth to prevent early ages of initiation of cigarettes and hookah.