bluuebunny/crossref_metadata_2025 huggingface dataset:
Engineering Approach to Assessing the Vulnerability of Water Abstraction
Authors: Margeta Jure
Published: February 2024

Variability in stream flow/discharge results in serious problems for engineers and difficulties in characterizing water systems under future climatic conditions. The management of water security in the engineering domain requires approaches aimed at minimizing the detrimental effects of the hydrological behavior of natural systems. Abstraction facilities must be strengthened to ensure sustainable supply and water security over time and at different scales. Several approaches and methodologies have been developed to translate water security into a framework that provides information on how to improve it. In this study, a scalar range idea is used to evaluate the sensitivity of a water resource system and cause–effect linkages define the vulnerability indicator as management-relevant information to address water security. This intuitively relates the extreme deviations of a particular streamflow to the average system response related to a particular hazard indicator. This determines the current stress in the operation of the abstraction facilities based on historical hydrometeorological changes, which is the basis for assessing future operational conditions and risks. This study uses streamflow extremes and averages as hazard-relevant indicators of water supply security. The results of the two case studies show that the applied approach fully appreciates the internal properties of water resource systems that affect the sensitivity/vulnerability of streamflow, as well as the derived streamflow vulnerability index and function. The obtained results were used to assess the vulnerability of water intake as well as the choice of safety factors and design parameters in accordance with the forecasted average annual and seasonal climate factors.
Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape Matching
Authors: Liu Wenbo , Sun Haonan , Xia Yu , Kang Jie
Published: February 2024

Accurate identification of fruits in greenhouse environments is an essential need for the precise functioning of agricultural robots. This study presents a solution to the problem of distinguishing cucumber fruits from their stems and leaves, which often have similar colors in their natural environment. The proposed algorithm for cucumber fruit identification relies on color segmentation and form matching. First, we get the boundary details from the acquired image of the cucumber sample. The edge information is described and reconstructed by utilizing a shape descriptor known as the Fourier descriptor in order to acquire a matching template image. Subsequently, we generate a multi-scale template by amalgamating computational and real-world data. The target image is subjected to color conditioning in order to enhance the segmenacktation of the target region inside the HSV color space. Then, the segmented target region is compared to the multi-scale template based on its shape. The method of color segmentation decreases the presence of unwanted information in the target image, hence improving the effectiveness of shape matching. An analysis was performed on a set of 200 cucumber photos that were obtained from the field. The findings indicate that the method presented in this study surpasses conventional recognition algorithms in terms of accuracy and efficiency, with a recognition rate of up to 86%. Moreover, the system has exceptional proficiency in identifying cucumber targets within greenhouses. This attribute renders it a great resource for offering technical assistance to agricultural robots that operate with accuracy.
VTG-GPT: Tuning-Free Zero-Shot Video Temporal Grounding with GPT
Authors: Xu Yifang , Sun Yunzhuo , Xie Zien , Zhai Benxiang , Du Sidan
Published: February 2024

Video temporal grounding (VTG) aims to locate specific temporal segments from an untrimmed video based on a linguistic query. Most existing VTG models are trained on extensive annotated video-text pairs, a process that not only introduces human biases from the queries but also incurs significant computational costs. To tackle these challenges, we propose VTG-GPT, a GPT-based method for zero-shot VTG without training or fine-tuning. To reduce prejudice in the original query, we employ Baichuan2 to generate debiased queries. To lessen redundant information in videos, we apply MiniGPT-v2 to transform visual content into more precise captions. Finally, we devise the proposal generator and post-processing to produce accurate segments from debiased queries and image captions. Extensive experiments demonstrate that VTG-GPT significantly outperforms SOTA methods in zero-shot settings and surpasses unsupervised approaches. More notably, it achieves competitive performance comparable to supervised methods. The code is available on GitHub.
Correction: Gerber, M.; Pillay, N. Automated Design of the Deep Neural Network Pipeline. Appl. Sci. 2022, 12, 12215
Authors: Gerber Mia , Pillay Nelishia
Published: February 2024

The authors would like to make the following corrections to this published paper [...]
Analysis of Volatile Flavor Compounds in Four Commercial Beverages Using Static Headspace Gas Chromatography/Mass Spectrometry: A Qualitative Approach
Authors: Petre Valentina Andreea , Cristea Nicolae Ionuț , Cojocaru Victor Constantin , Pascu Luoana Florentina , Chiriac Florentina Laura
Published: February 2024

Understanding the volatile flavor compounds present in commercial beverages is crucial for the food and beverage industries as these compounds significantly influence product perception and consumer acceptability. This paper aims to comprehensively analyze the composition of volatile organic compounds in various commercial beverages using targeted gas chromatographic–mass spectrometry (GC/MS) approaches. The study employs a screening method based on the Headspace-GC/MS technique to efficiently extract and identify volatile organic compounds found in commercial beverages. This methodology provides a rapid and reliable system for assessing the volatile profile of these beverages. The analysis reveals the presence of a total of 40 volatile organic compounds, including esters, terpenes/terpenoids, alkenes, aldehydes, aromatic hydrocarbons, and alcohols. Medium-chain esters were found to dominate the volatile profile of the beverages, suggesting a significant contribution to their fragrance and taste. This study offers valuable insights into the volatile profile of commercial beverages, creating awareness among consumers about the flavor components present in these products. By understanding the volatile composition, consumers can make informed choices regarding their beverage consumption. The comprehensive analysis provided by this research serves as a foundation for further studies related to flavor characterization and optimization in commercial beverages.
JITScanner: Just-in-Time Executable Page Check in the Linux Operating System
Authors: Caporaso Pasquale , Bianchi Giuseppe , Quaglia Francesco
Published: February 2024

Modern malware poses a severe threat to cybersecurity, continually evolving in sophistication. To combat this threat, researchers and security professionals continuously explore advanced techniques for malware detection and analysis. Dynamic analysis, a prevalent approach, offers advantages over static analysis by enabling observation of runtime behavior and detecting obfuscated or encrypted code used to evade detection. However, executing programs within a controlled environment can be resource-intensive, often necessitating compromises, such as limiting sandboxing to an initial period. In our article, we propose an alternative method for dynamic executable analysis: examining the presence of malicious signatures within executable virtual pages precisely when their current content, including any updates over time, is accessed for instruction fetching. Our solution, named JITScanner, is developed as a Linux-oriented package built upon a Loadable Kernel Module (LKM). It integrates a user-level component that communicates efficiently with the LKM using scalable multi-processor/core technology. JITScanner’s effectiveness in detecting malware programs and its minimal intrusion in normal runtime scenarios have been extensively tested, with the experiment results detailed in this article. These experiments affirm the viability of our approach, showcasing JITScanner’s capability to effectively identify malware while minimizing runtime overhead.
Practical Implementation of a Blockchain-Enabled SDN for Large-Scale Infrastructure Networks
Authors: Kovacs Rudolf , Buzura Sorin , Iancu Bogdan , Dadarlat Vasile , Peculea Adrian , Cebuc Emil
Published: February 2024

The network function virtualization (NFV) feature lies at the core of modern networking, and it allows on-demand real-time integration of new network functions, which is a great benefit for large-scale infrastructure networks. In contrast to the functional benefits, NFV introduces software complexity and computational overhead through additional abstraction layers. The current article addresses the function validation problem in large-scale infrastructure networks of Internet Service Providers (ISPs) and proposes the utilization of blockchain as a validation technology, as opposed to implementing a custom validation solution. The current work showcases a practical architecture implementation to address the service validation in service provider large-scale networks. The POX-based solution to control software-defined networks (SDN) for NFV is extended to offer additional blockchain capabilities. Thus, a blockchain node is integrated and executed in the POX SDN controller. Transaction experiments are performed between two endpoints located in remote locations on the Internet, and the detailed results are presented to validate the utilization of the blockchain technology used on SDNs’ control plane.
Harvesting Insights from the Sky: Satellite-Powered Automation for Detecting Mowing Based on Predicted Compressed Sward Heights
Authors: Dichou Killian , Nickmilder Charles , Tedde Anthony , Franceschini Sébastien , Brostaux Yves , Dufrasne Isabelle , Lessire Françoise , Glesner Noémie , Soyeurt Hélène
Published: February 2024

The extensive identification of mowing events on a territory holds significant potential to help monitor shifts in biodiversity and contribute to assessing the impacts of drought events. Additionally, it provides valuable insights into farming practices and their consequential economic and ecological effects. To overcome challenges in obtaining reference grazing information directly from the field, this study introduces a novel methodology leveraging the compressed sward height (CSH) derived from Sentinel-1, Sentinel-2, and meteorological data, boasting an accuracy of 20 mm. Our central hypothesis posits that the mowing status of a parcel can be automatically discerned by analyzing the distribution and variation of its CSH values. Employing a two-step strategy, we first applied unsupervised algorithms, specifically k-means and isolation forest, and subsequently amalgamated the outcomes with a partial least squares analysis on an extensive dataset encompassing 194,657 pastures spanning the years 2018 to 2021. The culmination of our modeling efforts yielded a validation accuracy of 0.66, as ascertained from a focused dataset of 68 pastures. Depending on the studied year and with a threshold fixed at 0.50, 21% to 57% of all the parcels in the Wallonia dataset were tagged as mown by our model. This study introduces an innovative approach for the automated detection of mown parcels, showcasing its potential to monitor agricultural activities at scale.
Low-Thrust Nonlinear Orbit Control for Very Low Lunar Orbits
Authors: Leonardi Edoardo Maria , Pontani Mauro , Carletta Stefano , Teofilatto Paolo
Published: February 2024

In the next decades, both space agencies and private competitors are targeting the lunar environment as a scientific and technological resource for future space missions. In particular, the confirmed existence of water-ice deposits in the vicinity of the poles (predominantly the south pole) makes polar or near-polar low lunar orbits attractive for the purpose of designing space missions that could search for suitable Lunar base sites. However, traveling very-low-altitude orbits is very challenging, as they are strongly perturbed by the Moon’s gravity field as well as third- and fourth-body effects due to the Earth and the Sun. Several studies demonstrate that these orbits are expected to impact the lunar surface in a few months. Therefore, the definition and implementation of an effective station-keeping strategy represents a crucial issue in order to extend satellites’ lifetime. In this paper, a feedback nonlinear control law is employed in order to perform corrective maneuvers aimed at keeping the state of the satellite within acceptable margins. The satellite is assumed to be equipped with a steerable and throttleable low-thrust propulsion system. The control law is based on the Lyapunov stability theory and does not require any reference path to track, with a considerable decrease in the computational cost. The proposed real-time control law includes control saturation, related to the maximum available thrust magnitude, and is developed employing modified equinoctial elements, in order to avoid singularities and extend its range of application. Finally, the strategy at hand is tested in the presence of all the relevant perturbations (i.e., harmonics of the selenopotential, third- and fourth-body effects) in order to show its effectiveness and efficiency.
The Impacts of Regime Shift in Summer Arctic Oscillation on Precipitation in East Asia
Authors: Zou Xuxin , Yan Li , Xu Jianjun , Zheng Shaojun
Published: February 2024

Using multiple observational and reanalysis data, this paper investigates the impact of the interdecadal shift in summer Arctic Oscillation (AO) on precipitation in East Asia, by removing ENSO influences. The results indicate that the lower-layer activity center of summer AO in Atlantic shifted eastward after the mid-1980s. This regime shift of summer AO has a significant impact on precipitation in East Asia. Before the mid-1980s, the key regions in which precipitation was affected by AO in East Asia were northern East Asia and Northeastern China and adjacent regions. After the mid-1980s, the key regions in which precipitation was affected by AO in East Asia were central Inner Mongolia and Southern China. The mechanism of precipitation changes can be attributed to changes in atmospheric circulation and water vapor transport related to AO changes. After the mid-1980s, the influence of AO on geopotential height over northern East Asia weakened; meanwhile, the impact of AO on geopotential height over China increased. Consistent with the changes in atmospheric circulation, water vapor transport in East Asia also underwent interdecadal changes before and after the mid-1980s. The differences in atmospheric circulation and water vapor transport in East Asia can be traced back to the North Atlantic. Before the mid-1980s, wave activity flux related to summer AO tended to propagate in high latitudes and subtropics; after the mid-1980s, the wave activity flux changed in its subtropical path and propagated eastward from the North Atlantic through the Middle East to China, significantly affecting the summer precipitation in China.
Development of New Open-Set Speech Material for Use in Clinical Audiology with Speakers of British English
Authors: Keshavarzi Mahmoud , Salorio-Corbetto Marina , Reichenbach Tobias , Marriage Josephine , Moore Brian C. J.
Published: February 2024

Background: The Chear open-set performance test (COPT), which uses a carrier phrase followed by a monosyllabic test word, is intended for clinical assessment of speech recognition, evaluation of hearing-device performance, and the fine-tuning of hearing devices for speakers of British English. This paper assesses practice effects, test–retest reliability, and the variability across lists of the COPT. Method: In experiment 1, 16 normal-hearing participants were tested using an initial version of the COPT, at three speech-to-noise ratios (SNRs). Experiment 2 used revised COPT lists, with items swapped between lists to reduce differences in difficulty across lists. In experiment 3, test–retest repeatability was assessed for stimuli presented in quiet, using 15 participants with sensorineural hearing loss. Results: After administration of a single practice list, no practice effects were evident. The critical difference between scores for two lists was about 2 words (out of 15) or 5 phonemes (out of 50). The mean estimated SNR required for 74% words correct was −0.56 dB, with a standard deviation across lists of 0.16 dB. For the participants with hearing loss tested in quiet, the critical difference between scores for two lists was about 3 words (out of 15) or 6 phonemes (out of 50).
Fractal Fractional Derivative Models for Simulating Chemical Degradation in a Bioreactor
Authors: Akgül Ali , Conejero J. Alberto
Published: February 2024

A three-differential-equation mathematical model is presented for the degradation of phenol and p-cresol combination in a bioreactor that is continually agitated. The stability analysis of the model’s equilibrium points, as established by the study, is covered. Additionally, we used three alternative kernels to analyze the model with the fractal–fractional derivatives, and we looked into the effects of the fractal size and fractional order. We have developed highly efficient numerical techniques for the concentration of biomass, phenol, and p-cresol. Lastly, numerical simulations are used to illustrate the accuracy of the suggested method.
A Novel Long Short-Term Memory Approach for Online State-of-Health Identification in Lithium-Ion Battery Cells
Authors: Kopp Mike , Fill Alexander , Ströbel Marco , Birke Kai Peter
Published: February 2024

Revolutionary and cost-effective state estimation techniques are crucial for advancing lithium-ion battery technology, especially in mobile applications. Accurate prediction of battery state-of-health (SoH) enhances state-of-charge estimation while providing valuable insights into performance, second-life utility, and safety. While recent machine learning developments show promise in SoH estimation, this paper addresses two challenges. First, many existing approaches depend on predefined charge/discharge cycles with constant current/constant voltage profiles, which limits their suitability for real-world scenarios. Second, pure time series forecasting methods require prior knowledge of the battery’s lifespan in order to formulate predictions within the time series. Our novel hybrid approach overcomes these limitations by classifying the current aging state of the cell rather than tracking the SoH. This is accomplished by analyzing current pulses filtered from authentic drive cycles. Our innovative solution employs a Long Short-Term Memory-based neural network for SoH prediction based on residual capacity, making it well suited for online electric vehicle applications. By overcoming these challenges, our hybrid approach emerges as a reliable alternative for precise SoH estimation in electric vehicle batteries, marking a significant advancement in machine learning-based SoH estimation.
A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis
Authors: Xu Xi , Li Jianqiang , Zhu Zhichao , Zhao Linna , Wang Huina , Song Changwei , Chen Yining , Zhao Qing , Yang Jijiang , Pei Yan
Published: February 2024

Disease diagnosis represents a critical and arduous endeavor within the medical field. Artificial intelligence (AI) techniques, spanning from machine learning and deep learning to large model paradigms, stand poised to significantly augment physicians in rendering more evidence-based decisions, thus presenting a pioneering solution for clinical practice. Traditionally, the amalgamation of diverse medical data modalities (e.g., image, text, speech, genetic data, physiological signals) is imperative to facilitate a comprehensive disease analysis, a topic of burgeoning interest among both researchers and clinicians in recent times. Hence, there exists a pressing need to synthesize the latest strides in multi-modal data and AI technologies in the realm of medical diagnosis. In this paper, we narrow our focus to five specific disorders (Alzheimer’s disease, breast cancer, depression, heart disease, epilepsy), elucidating advanced endeavors in their diagnosis and treatment through the lens of artificial intelligence. Our survey not only delineates detailed diagnostic methodologies across varying modalities but also underscores commonly utilized public datasets, the intricacies of feature engineering, prevalent classification models, and envisaged challenges for future endeavors. In essence, our research endeavors to contribute to the advancement of diagnostic methodologies, furnishing invaluable insights for clinical decision making.
Validation of a New and Straightforward Algorithm to Evaluate Signal Quality during ECG Monitoring with Wearable Devices Used in a Clinical Setting
Authors: Neri Luca , Gallelli Ilaria , Dall’Olio Massimo , Lago Jessica , Borghi Claudio , Diemberger Igor , Corazza Ivan
Published: February 2024

Background: Wearable devices represent a new approach for monitoring key clinical parameters, such as ECG signals, for research and health purposes. These devices could outcompete medical devices in terms of affordability and use in out-clinic settings, allowing remote monitoring. The major limitation, especially when compared to implantable devices, is the presence of artifacts. Several authors reported a relevant percentage of recording time with poor/unusable traces for ECG, potentially hampering the use of these devices for this purpose. For this reason, it is of the utmost importance to develop a simple and inexpensive system enabling the user of the wearable devices to have immediate feedback on the quality of the acquired signal, allowing for real-time correction. Methods: A simple algorithm that can work in real time to verify the quality of the ECG signal (acceptable and unacceptable) was validated. Based on simple statistical parameters, the algorithm was blindly tested by comparison with ECG tracings previously classified by two expert cardiologists. Results: The classifications of 7200 10s-signal samples acquired on 20 patients with a commercial wearable ECG monitor were compared. The algorithm has an overall efficiency of approximately 95%, with a sensitivity of 94.7% and a specificity of 95.3%. Conclusions: The results demonstrate that even a simple algorithm can be used to classify signal coarseness, and this could allow real-time intervention by the subject or the technician.
A Keratin 12 Expression-Based Analysis of Stem-Precursor Cells and Differentiation in the Limbal–Corneal Epithelium Using Single-Cell RNA-Seq Data
Authors: Wolosin J. Mario
Published: February 2024

The corneal epithelium (CE) is spread between two domains, the outer vascularized limbus and the avascular cornea proper. Epithelial cells undergo constant migration from the limbus to the vision-critical central cornea. Coordinated with this migration, the cells undergo differentiation changes where a pool of unique stem/precursor cells at the limbus yields the mature cells that reach the corneal center. Differentiation is heralded by the expression of the corneal-specific Krt12. Processing data acquired by scRNA-Seq showed that the increase in Krt12 expression occurs in four distinct steps within the limbus, plus a single continuous increase in the cornea. Differential gene analysis demonstrated that these domains reflect discreet stages of CE differentiation and yielded extensive information of the genes undergoing down- or upregulation in the sequential transition from less to more differentiate conditions. The approach allowed the identification of multiple gene cohorts, including (a) the genes which have maximal expression in the most primitive, Krt12-negative cell cohort, which is likely to include the stem/precursor cells; (b) the sets of genes that undergo continuous increase or decrease along the whole differentiation path; and (c) the genes showing maximal positive or negative correlation with the changes in Krt12.
Neuroprotective Effects of the Nutraceutical Dehydrozingerone and Its C2-Symmetric Dimer in a Drosophila Model of Parkinson’s Disease
Authors: Setzu Maria Dolores , Mocci Ignazia , Fabbri Davide , Carta Paola , Muroni Patrizia , Diana Andrea , Dettori Maria Antonietta , Casu Maria Antonietta
Published: February 2024

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic neurons responsible for unintended or uncontrollable movements. Mutations in the leucine-rich repeat kinase 2 locus contribute to genetic forms of PD. The fruit fly Drosophila melanogaster carrying this mutation (LRRK2-Dm) is an in vivo model of PD that develops motor impairment and stands for an eligible non-mammalian paradigm to test novel therapeutic approaches. Dehydrozingerone (DHZ) is a natural phenolic compound isolated from ginger and presents anti-inflammatory, antioxidant and neuroprotective properties, making it a potential therapeutic target for PD. We administered DHZ and its C2-symmetric dimer (DHZ-DIM) at 0.5 and 1 mM for 14 and 21 days in the LRRK2-Dm, with the aim of assessing changes in rescuing motor behavior, brain dopaminergic neurons, mitochondria and synapses (T-bars). The shorter treatment with both molecules revealed efficacy at the higher dose, improving climbing behavior with a prevention of dopaminergic neuronal demise. After 21 days, a recovery of the motor disability, dopaminergic neuron loss, mitochondrial damage and T-bars failure was observed with the DHZ-DIM. Our data indicate that the DHZ-DIM exerts a more potent neuroprotective effect with respect to the monomer in LRRK2-Dm, prompting further investigation of these compounds in rodent models of PD.
Upsetting the Balance: How Modifiable Risk Factors Contribute to the Progression of Alzheimer’s Disease
Authors: Carroll Caitlin M. , Benca Ruth M.
Published: February 2024

Alzheimer’s disease (AD) is a neurodegenerative disorder affecting nearly one in nine older adults in the US. This number is expected to grow exponentially, thereby increasing stress on caregivers and health systems. While some risk factors for developing AD are genetic, an estimated 1/3 of AD cases are attributed to lifestyle. Many of these risk factors emerge decades before clinical symptoms of AD are detected, and targeting them may offer more efficacious strategies for slowing or preventing disease progression. This review will focus on two common risk factors for AD, metabolic dysfunction and sleep impairments, and discuss potential mechanisms underlying their relationship to AD pathophysiology. Both sleep and metabolism can alter AD-related protein production and clearance, contributing to an imbalance that drives AD progression. Additionally, these risk factors have bidirectional relationships with AD, where the presence of AD-related pathology can further disrupt sleep and worsen metabolic functioning. Sleep and metabolism also appear to have a bidirectional relationship with each other, indirectly exacerbating AD pathophysiology. Understanding the mechanisms involved in these relationships is critical for identifying new strategies to slow the AD cascade.
Antiadhesive Hyaluronic Acid-Based Wound Dressings Promote Wound Healing by Preventing Re-Injury: An In Vivo Investigation
Authors: Kim Da , Seong Keum-Yong , Lee Hyeseon , Kim Min , An Sung-Min , Jeong Jea , Kim So , Kang Hyeon-Gu , Jang Sangsoo , Hwang Dae-Youn , Seo Sung-Baek , Jo Seong-Min , Yang Seung , An Beum-Soo
Published: February 2024

Wound dressings are widely used to protect wounds and promote healing. The water absorption and antifriction properties of dressings are important for regulating the moisture balance and reducing secondary damages during dressing changes. Herein, we developed a hyaluronic acid (HA)-based foam dressing prepared via the lyophilization of photocrosslinked HA hydrogels with high water absorption and antiadhesion properties. To fabricate the HA-based foam dressing (HA foam), the hydroxyl groups of the HA were modified with methacrylate groups, enabling rapid photocuring. The resulting photocured HA solution was freeze-dried to form a porous structure, enhancing its exudate absorption capacity. Compared with conventional biopolymer-based foam dressings, this HA foam exhibited superior water absorption and antifriction properties. To assess the wound-healing potential of HA foam, animal experiments involving SD rats were conducted. Full-thickness defects measuring 2 × 2 cm2 were created on the skin of 36 rats, divided into four groups with 9 individuals each. The groups were treated with gauze, HA foam, CollaDerm®, and CollaHeal® Plus, respectively. The rats were closely monitored for a period of 24 days. In vivo testing demonstrated that the HA foam facilitated wound healing without causing inflammatory reactions and minimized secondary damages during dressing changes. This research presents a promising biocompatible foam wound dressing based on modified HA, which offers enhanced wound-healing capabilities and improved patient comfort and addresses the challenges associated with conventional dressings.
The Hormonal Background of Hair Loss in Non-Scarring Alopecias
Authors: Owecka Barbara , Tomaszewska Agata , Dobrzeniecki Krzysztof , Owecki Maciej
Published: February 2024

Hair loss is a common clinical condition connected with serious psychological distress and reduced quality of life. Hormones play an essential role in the regulation of the hair growth cycle. This review focuses on the hormonal background of hair loss, including pathophysiology, underlying endocrine disorders, and possible treatment options for alopecia. In particular, the role of androgens, including dihydrotestosterone (DHT), testosterone (T), androstenedione (A4), dehydroepiandrosterone (DHEA), and its sulfate (DHEAS), has been studied in the context of androgenetic alopecia. Androgen excess may cause miniaturization of hair follicles (HFs) in the scalp. Moreover, hair loss may occur in the case of estrogen deficiency, appearing naturally during menopause. Also, thyroid hormones and thyroid dysfunctions are linked with the most common types of alopecia, including telogen effluvium (TE), alopecia areata (AA), and androgenetic alopecia. Particular emphasis is placed on the role of the hypothalamic–pituitary–adrenal axis hormones (corticotropin-releasing hormone, adrenocorticotropic hormone (ACTH), cortisol) in stress-induced alopecia. This article also briefly discusses hormonal therapies, including 5-alpha-reductase inhibitors (finasteride, dutasteride), spironolactone, bicalutamide, estrogens, and others.
Updated Insights into Probiotics and Hepatobiliary Diseases
Authors: Xu Xiaoyu , Zhang Cheng , Tang Guoyi , Wang Ning , Feng Yibin
Published: February 2024

Hepatobiliary diseases have a high prevalence worldwide, with a wide range of diseases involved in the liver and biliary system. Modifications in gut microbiota have been proven to have an association with unbalanced intestinal homeostasis and the dysfunction of host metabolism and the immune system, which can be the risk factors for many hepatobiliary diseases, such as nonalcoholic fatty liver disease (NAFLD), alcoholic liver disease (ALD), nonalcoholic fatty steatohepatitis (NASH), hepatitis, cirrhosis, hepatocellular carcinoma (HCC) and cholestasis, as well as infection due to liver transplantation. Probiotics are commonly used gut microbiota-targeted strategies to treat dysbiosis and intestinal dysfunction, as well as the gut–liver axis, which can enhance the effectiveness of probiotics in the management of liver diseases. Recent studies have explored more potential single or mixed strains of probiotics, and bioinformatics methods can be used to investigate the potential mechanisms of probiotics on liver diseases. In this review, we summarize the preclinical and clinical studies on the role of probiotics in hepatobiliary diseases from 2018 to 2023, revealing the possible mechanism of probiotics in the treatment of hepatobiliary diseases and discussing the limitations of probiotics in treating hepatobiliary diseases. This review provides updated evidence for the development of probiotic products, exploration of new probiotic strains, and support for clinical studies. Further studies should focus on the safety, viability, and stability of probiotics, as well as medication dosage and duration in clinical practice.
Physical Health and Transition to Psychosis in People at Clinical High Risk
Authors: De Micheli Andrea , Provenzani Umberto , Krakowski Kamil , Oliver Dominic , Damiani Stefano , Brondino Natascia , McGuire Philip , Fusar-Poli Paolo
Published: February 2024

Background: The clinical high risk for psychosis (CHR-P) construct represents an opportunity for prevention and early intervention in young adults, but the relationship between risk for psychosis and physical health in these patients remains unclear. Methods: We conducted a RECORD-compliant clinical register-based cohort study, selecting the long-term cumulative risk of developing a persistent psychotic disorder as the primary outcome. We investigated associations between primary outcome and physical health data with Electronic Health Records at the South London and Maudsley (SLaM) NHS Trust, UK (January 2013–October 2020). We performed survival analyses using Kaplan-Meier curves, log-rank tests, and Cox proportional hazard models. Results: The database included 137 CHR-P subjects; 21 CHR-P developed psychosis during follow-up, and the cumulative incidence of psychosis risk was 4.9% at 1 year and 56.3% at 7 years. Log-rank tests suggested that psychosis risk might change between different levels of nicotine and alcohol dependence. Kaplan-Meier curve analyses indicated that non-hazardous drinkers may have a lower psychosis risk than non-drinkers. In the Cox proportional hazard model, nicotine dependence presented a hazard ratio of 1.34 (95% CI: 1.1–1.64) (p = 0.01), indicating a 34% increase in psychosis risk for every additional point on the Fagerström Test for Nicotine Dependence. Conclusions: Our findings suggest that a comprehensive assessment of tobacco and alcohol use, diet, and physical activity in CHR-P subjects is key to understanding how physical health contributes to psychosis risk.
Competitive Immunoassay in a Microfluidic Biochip for In-Field Detection of Abscisic Acid in Grapes
Authors: Domingues Cristiana , Meirinho Rui , Rodrigues Rodolfo G. , Fortes Ana Margarida , Chu Virginia , Conde João Pedro
Published: February 2024

Viticulture and associated products are an important part of the economy in many countries. However, biotic and abiotic stresses impact negatively the production of grapes and wine. Climate change is in many aspects increasing both these stresses. Routine sample retrievals and analysis tend to be time-consuming and require expensive equipment and skilled personnel to operate. These challenges could be overcome through the development of a miniaturized analytic device for early detection of grapevine stresses in the field. Abscisic acid is involved in several plant processes, including the onset of fruit ripening and tolerance mechanisms against drought stress. This hormone can be detected through a competitive immunoassay and is found in plants in concentrations up to 10−1 mg/mL. A microfluidic platform is developed in this work which can detect a minimum of 10−11 mg/mL of abscisic acid in buffer. Grape samples were tested using the microfluidic system alongside benchmark techniques such as high-performance liquid chromatography. The microfluidic system could detect the increase to 10−5 mg/mL of abscisic acid present in real berry samples at the veraison stage of ripening.
Novel Approaches for the Treatment of Post-Traumatic Stress Disorder: A Systematic Review of Non-Invasive Brain Stimulation Interventions and Insights from Clinical Trials
Authors: Saccenti Daniele , Lodi Leandro , Moro Andrea Stefano , Scaini Simona , Forresi Barbara , Lamanna Jacopo , Ferro Mattia
Published: February 2024

First-line treatments for post-traumatic stress disorder (PTSD) encompass a wide range of pharmacotherapies and psychotherapies. However, many patients fail to respond to such interventions, highlighting the need for novel approaches. Due to its ability to modulate cortical activity, non-invasive brain stimulation (NIBS) could represent a valuable therapeutic tool. Therefore, the aim of this systematic review is to summarize and discuss the existing evidence on the ameliorative effects of NIBS on PTSD and comorbid anxiety and depressive symptoms. Our goal is also to debate the effectiveness of an integrated approach characterized by the combination of NIBS and psychotherapy. This search was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines in the PubMed, PsycINFO, PsycARTICLES, PSYINDEX, MEDLINE, and ERIC databases. Overall, 31 studies met the eligibility criteria, yielding a total of 26 clinical trials employing transcranial magnetic stimulation (TMS) and 5 making use of transcranial direct-current stimulation (tDCS). From these studies, it emerged that NIBS consistently reduced overall PTSD symptoms’ severity as well as comorbid anxiety and depressive symptoms. Moreover, we speculate that combining NIBS with prolonged exposure or cognitive processing therapy might represent a promising therapeutic approach for consistently ameliorating subjects’ clinical conditions.
Identification and Verification of Error-Related Potentials Based on Cerebellar Targets
Authors: Niu Chang , Yan Zhuang , Yin Kuiying , Zhou Shenghua
Published: February 2024

The error-related potential (ErrP) is a weak explicit representation of the human brain for individual wrong behaviors. Previously, ErrP-related research usually focused on the design of automatic correction and the error correction mechanisms of high-risk pipeline-type judgment systems. Mounting evidence suggests that the cerebellum plays an important role in various cognitive processes. Thus, this study introduced cerebellar information to enhance the online classification effect of error-related potentials. We introduced cerebellar regional characteristics and improved discriminative canonical pattern matching (DCPM) in terms of data training and model building. In addition, this study focused on the application value and significance of cerebellar error-related potential characterization in the selection of excellent ErrP-BCI subjects (brain–computer interface). Here, we studied a specific ErrP, the so-called feedback ErrP. Thirty participants participated in this study. The comparative experiments showed that the improved DCPM classification algorithm proposed in this paper improved the balance accuracy by approximately 5–10% compared with the original algorithm. In addition, a correlation analysis was conducted between the error-related potential indicators of each brain region and the classification effect of feedback ErrP-BCI data, and the Fisher coefficient of the cerebellar region was determined as the quantitative screening index of the subjects. The screened subjects were superior to other subjects in the performance of the classification algorithm, and the performance of the classification algorithm was improved by up to 10%.
A Systematic Review of Educational Interventions for Informal Caregivers of People Living with Dementia in Low and Middle-Income Countries
Authors: Evans Isabelle , Patel Ria , Stoner Charlotte R. , Melville Mel , Spector Aimee
Published: February 2024

Objectives: With the increasing prevalence of dementia worldwide, there is a growing need for an integrated approach to dementia care. Little is known at present about the benefits of educational interventions for informal caregivers of people living with dementia (PLWD) in low- and middle-income countries (LMICs). This review aimed to identify and synthesise the current research on these interventions. Method: Four databases (PsycINFO, Medline, Web of Sciences and Scopus) were searched, alongside Google Scholar and reference lists. The Downs and Black checklist was used for quality assessment and data relating to intervention characteristics, outcomes, and educational component features were compared. Results: Eighteen papers detailing 17 studies were included. All studies presented found at least one significant outcome/effect. Study comparison was difficult due to diverse methodologies, intervention structures, and outcomes. Study quality was also variable. Four studies had education as the primary focus, and most interventions utilised multicomponent and group-based designs. Interventions that included group delivery tended to find more significant results than individual approaches. Intervention length did not appear to influence efficacy. Regular delivery and an average intervention dosage of around 12 h appeared most effective. Conclusions: Research into educational interventions for caregivers in LMICs appears to be promising and can help guide future interventions towards clinical implementation. A multicomponent group intervention trialled in Egypt provided particularly favourable findings. Future studies should focus on understanding the active mechanisms within such interventions to optimize their effectiveness. Collaboration between LMICs, high-income countries (HICs), and caregivers is crucial in developing interventions tailored to meet caregiver needs whilst accounting for feasibility and equity for dementia care worldwide.
Relationship between the College Student and the Campus Club: An Evolutionary Game Theory Analysis
Authors: Duan Lei , Wang Zhong , Zhu Guanyu , Zhang Yahui
Published: February 2024

In this paper, we use an evolutionary game theory approach to build a relationship model of students and clubs for the purpose of improving student enthusiasm for participating in club activities. First, the process of the model building is introduced, which mainly includes the basic assumptions and the equilibrium point stability analysis. Based on this analysis, we find that the motivation adjustment of students and clubs is a dynamic process and that unilateral efforts alone cannot achieve an ideal result. Then, we use real data from Yanshan University to evaluate the model, the results of which indicate that the model can analyze the relationship between students and clubs effectively. Finally, we provide relevant suggestions based on the model established in this study, whereby we contribute a theoretical basis and practical guidance for how students can actively participate in clubs, as well as how clubs can better develop themselves.
Pathogenesis of Warthin’s Tumor: Neoplastic or Non-Neoplastic?
Authors: Aoki Ryogo , Tanaka Takuji
Published: February 2024

Warthin’s tumor is the second most frequent neoplasm next to pleomorphic adenoma in the salivary gland, mostly in the parotid gland. The epithelial cells constituting a tumor are characterized by the presence of mitochondria that undergo structural and functional changes, resulting in the development of oncocytes. In addition to containing epithelial cells, Warthin’s tumors contain abundant lymphocytes with lymph follicles (germinal centers) that are surrounded by epithelial cells. The pathogenesis of Warthin’s tumor is not fully understood, and several hypotheses have been proposed. The risk factors for the development of Warthin’s tumor, which predominantly occurs in males, include aging, smoking, and radiation exposure. Recently, it has been reported that chronic inflammation and aging cells promote the growth of Warthin’s tumor. Several reports regarding the origin of the tumor have suggested that (1) Warthin’s tumor is an IgG4-related disease, (2) epithelial cells that compose Warthin’s tumor accumulate mitochondria, and (3) Warthin’s tumor is a metaplastic lesion in the lymph nodes. It is possible that the pathogenesis of Warthin’s tumor includes mitochondrial metabolic abnormalities, accumulation of aged cells, chronic inflammation, and senescence-associated secretory phenotype (SASP). In this short review, we propose that DNA damage, metabolic dysfunction of mitochondria, senescent cells, SASP, human papillomavirus, and IgG4 may be involved in the development of Warthin’s tumor.
PARP Inhibitors: Strategic Use and Optimal Management in Ovarian Cancer
Authors: Hirschl Nicholas , Leveque Wildnese , Granitto Julia , Sammarco Valia , Fontillas Mervyns , Penson Richard T.
Published: February 2024

Poly (ADP-ribose) polymerase (PARP) inhibitors have become an established part of the anticancer armamentarium. Discovered in the 1980s, PARP inhibitors (PARPis) were initially developed to exploit the presence of BRCA mutations, which disrupt the homologous recombination repair of deoxyribonucleic acid (DNA) via synthetic lethality, an intrinsic vulnerability caused by the cell’s dependence on other DNA repair mechanisms for which PARP is an essential contributor. PARPi use expanded with the demonstration of clinical benefit when other mechanisms of high-fidelity DNA damage response were present in cancer cells called homologous repair deficiency (HRD). Recently, new data have resulted in the voluntary withdrawal of later-line treatment indications for all the available PARPis used in ovarian cancer because of a negative impact on overall survival (OS). PARPi switch maintenance to consolidate a response to platinum-based therapy is recommended for earlier treatment lines to have the greatest impact on the chance of cure and length of survival. This article reviews the clinical utility of PARPis and how to integrate them into best practices.
Evaluation of Quality of Life and Treatment Satisfaction in Newly Diagnosed Cutaneous T-Cell Lymphoma Patients
Authors: Ottevanger Rosanne , van Beugen Sylvia , Kersten Juliette M. , Evers Andrea W. M. , Vermeer Maarten H. , Willemze Rein , Quint Koen D.
Published: February 2024

Background: Little is known about the impact of MF on quality of life (QoL) in newly diagnosed patients. Objectives: To describe the impact of the MF diagnosis on QoL, patient expectations, and treatment satisfaction over the first 6 months after diagnosis. Methods: Outcomes of this prospective cohort study of newly diagnosed MF patients conducted between 2020 and 2022 at the Leiden University Medical Center included the Skindex-29, RAND-12 Health Survey, degree of itch, pain, and fatigue (Visual Analogue Scale (VAS)), patient expectations, and Client Satisfaction Questionnaire-8 (CSQ-8), measured at baseline and after six months. Results: A total of 28 patients with MF were included. At baseline, 66% (n = 18) “strongly-totally” expected positive effects of the treatment. At the time of diagnosis, 28% of the patients (n = 8) were moderately to severely affected. There was no statistical change in the Skindex-29 score sum score (20 [10–34] vs. 20 [9–36]; p = 0.81) or in the other three subdomains, the RAND-12 scores, and the VAS itch, pain, and fatigue over time. Treatment satisfaction was high overall. Conclusion: Despite that the newly diagnosed MF patients anticipate a positive treatment effect, few improvements in QoL and symptom reduction were found. These data can be used for adequate expectation management and provide a rationale for further evaluation of treatment regimens in these patients.