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Background: The immune system must carefully balance fighting pathogens with minimization of inflammation and avoidance of autoimmune responses. Over the past ten years, researchers have extensively studied the mechanisms regulating this delicate balance. Comprehending these mechanisms is essential for developing treatments for inflammatory conditions. Aim: This review aims to synthesize knowledge of immunoregulatory processes published from 2014–2024 and to highlight discoveries that provide fresh perspectives on this complex balance. Methods: The keywords "molecular mechanisms", "immune regulation", "immune signaling pathways", and "immune homeostasis" were used to search PubMed for articles published between 2014 and 2024, with a preference for articles published in the past three years. Results: Recent research has pinpointed the impact of factors such as cytokine signaling, T-cell regulation, epigenetic regulation, and immunometabolism on immune function. Discussion: New research highlights the intricate interactions between the immune system and other molecular elements. A key area of interest is the impact of non-coding RNAs and metabolic pathways on the regulation of immune responses. Conclusions: Exploring the mechanisms by which the immune system is regulated will provide new avenues for developing treatments to address autoimmune and inflammatory conditions. [ABSTRACT FROM AUTHOR]

Developing affordable, rapid, and accurate biosensors is essential for SARS-CoV-2 surveillance and early detection. We created a bio-inspired peptide, using the SAGAPEP AI platform, for COVID-19 salivary diagnostics via a portable electrochemical device coupled to Machine Learning algorithms. SAGAPEP enabled molecular docking simulations against the SARS-CoV-2 Spike protein's RBD, leading to the synthesis of Bio-Inspired Artificial Intelligence Peptide 1 (BIAI1). Molecular docking was used to confirm interactions between BIAI1 and SARS-CoV-2, and BIAI1 was functionalized on rhodamine-modified electrodes. Cyclic voltammetry (CV) using a [Fe(CN)6]3−/4 solution detected virus levels in saliva samples with and without SARS-CoV-2. Support vector machine (SVM)-based machine learning analyzed electrochemical data, enhancing sensitivity and specificity. Molecular docking revealed stable hydrogen bonds and electrostatic interactions with RBD, showing an average affinity of −250 kcal/mol. Our biosensor achieved 100% sensitivity, 80% specificity, and 90% accuracy for 1.8 × 10⁴ focus-forming units in infected saliva. Validation with COVID-19-positive and -negative samples using a neural network showed 90% sensitivity, specificity, and accuracy. This BIAI1-based electrochemical biosensor, integrated with machine learning, demonstrates a promising non-invasive, portable solution for COVID-19 screening and detection in saliva. [ABSTRACT FROM AUTHOR]

Marine plankton include organisms driving multiple ecosystem services (ESs). In this study, we identified ESs provided by planktonic consortia worldwide from the analysis of scientific literature. We also mapped the identified ESs onto forty-nine plankton trophic networks derived from presence–absence data obtained from two coastal surveys in three areas along the coast of the Campania region in the Tyrrhenian Sea (NW Mediterranean). The systematic review evidenced that ESs associated with goods provision and ecosystem regulation were the most studied categories, while cultural ESs were the least considered. The mapping of ESs across the Campania coast revealed significant spatiotemporal variations in plankton-based ESs, which depend on seasonal variability and local environmental conditions. Among the ESs, those connected with the regulation and maintenance of marine ecosystems dominated both temporally and spatially, highlighting the crucial role of plankton in ecosystem stability and resilience. Moreover, although the direct provision of goods and materials was less represented, food provision to higher trophic levels was widespread within each coastal sector, highlighting the crucial role of plankton biodiversity in directly sustaining the whole marine ecosystem and related economic activities such as fisheries and aquacultures. [ABSTRACT FROM AUTHOR]

This study investigates how CEO characteristics, board composition, and firm size influence the technical efficiency (TE) of energy firms. We aim to understand how these factors contribute to production inefficiencies, which may help explain fluctuations in oil prices. Using stochastic frontier analysis (SFA), we analyze data from 100 American energy firms over the period from 2006 to 2019. Our results show that inefficiencies in production are primarily driven by specific CEO traits, the size and structure of the board, and the overall size of the firm. Based on the findings of this study, we recommend focusing on the selection of executive managers with specific qualifications, particularly those with extensive experience in managing oil and gas companies. Leadership positions should prioritize seasoned managers with accumulated expertise in this sector, and preference should be given to candidates with advanced educational backgrounds. Encouraging CEOs to acquire equity stakes in the company can significantly boost the technical efficiency of oil and gas firms. Additionally, offering competitive salaries and performance-based bonuses may further enhance managerial effectiveness and drive technical improvements. In addition, expanding the size of boards of directors in oil and gas companies is also anticipated to positively influence their technical efficiency. Finally, pursuing mergers and acquisitions to grow the scale of oil and gas companies represents a strategic approach to improving operational efficiency while contributing to the stability of global energy prices. [ABSTRACT FROM AUTHOR]

The field of computer vision has progressed rapidly over the past ten years, with noticeable improvements in techniques to detect, locate, and classify objects. Concurrent with these advances, improved accessibility through machine learning software libraries has sparked investigations of applications across multiple domains. In the areas of fisheries research and management, efforts have centered on the localization of fish and classification by species, as such tools can estimate the health, size, and movement of fish populations. To aid in the interpretation of computer vision for fisheries research management tasks, a survey of the recent literature was conducted. In contrast to prior reviews, this survey focuses on employed evaluation metrics and datasets as well as the challenges associated with applying machine learning to a fisheries research and management context. Misalignment between applications and commonly used evaluation metrics and datasets mischaracterizes the efficacy of emerging computer vision techniques for fisheries research and management tasks. Aqueous, turbid, and variable lighted deployment settings further complicate the use of computer vision and generalizability of the reported results. Informed by these inherent challenges, culling surveillance data, exploratory data collection in remote settings, and selective passage and traps are presented as opportunities for future research. [ABSTRACT FROM AUTHOR]

Myocardial infarction (MI) is a severe hypoxic event, resulting in the loss of up to one billion cardiomyocytes (CMs). Due to the limited intrinsic regenerative capacity of the heart, cell-based regenerative therapies, which feature the implantation of stem cell-derived cardiomyocytes (SC-CMs) into the infarcted myocardium, are being developed with the goal of restoring lost muscle mass, re-engineering cardiac contractility, and preventing the progression of MI into heart failure (HF). However, such cell-based therapies are challenged by their susceptibility to oxidative stress in the ischemic environment of the infarcted heart. To maximize the therapeutic benefits of cell-based approaches, a better understanding of the heart environment at the cellular, tissue, and organ level throughout MI is imperative. This review provides a comprehensive summary of the cardiac pathophysiology occurring during and after MI, as well as how these changes define the cardiac environment to which cell-based cardiac regenerative therapies are delivered. This understanding is then leveraged to frame how cell culture treatments may be employed to enhance SC-CMs' hypoxia resistance. In this way, we synthesize both the complex experience of SC-CMs upon implantation and the engineering techniques that can be utilized to develop robust SC-CMs for the clinical translation of cell-based cardiac therapies. [ABSTRACT FROM AUTHOR]

With the advent of a variety of vaccines against viral infections, there are multiple viruses that can be prevented via vaccination. However, breakthrough infections or uncovered strains can still cause vaccine-preventable viral infections (VPVIs). Therefore, timely diagnosis, treatment, and surveillance of these viruses is critical to patient care and public health. Point-of-care (POC) viral diagnostics tools have brought significant improvements in the detection and management of VPVIs. These cutting-edge technologies enable prompt and accurate results, enhancing patient care by facilitating timely treatment decisions. This review delves into the advancements in POC testing, including antigen/antibody detection and molecular assays, while focusing on their impact on the diagnosis, treatment, and surveillance of VPVIs such as mpox, viral hepatitis, influenza, flaviviruses (dengue, Zika, and yellow fever virus), and COVID-19. The role of POC tests in monitoring viral infection is crucial for tracking disease progression and managing outbreaks. Furthermore, the application of POC diagnostics has shown to be vital for public health strategies. In this review, we also highlight emerging POC technologies such as CRISPR-based diagnostics and smartphone-integrated POC devices, which have proven particularly beneficial in resource-limited settings. We underscore the importance of continued research to optimize these diagnostic tools for wider global use for mpox, viral hepatitis, influenza, dengue, and COVID-19, while also addressing current challenges related to their sensitivity, specificity, availability, efficiency, and more. [ABSTRACT FROM AUTHOR]

Simple Summary: While considering previously progressed metastatic castration-resistant prostate cancer (mCRPC) patients presenting deleterious BRCA1/2 mutations, poly(adenosine diphosphate–ribose) polymerase (PARP) inhibitors provide survival benefits over the current standard of care (SOC). PARP inhibitors are, however, associated with additional costs and their use is constrained by access to genetic testing, potentially placing an economic strain on the healthcare system. This paper aims to assess the cost-effectiveness of PARP inhibitors as a therapeutic class and not only as a single agent, considering approved and soon-to-be approved therapies. This flexible approach considers multiple treatment options comparing the SOC and PARP inhibitors to represent more accurately the clinical management of mCRPC and the potential impact of PARP inhibitors on the treatment landscape. Results from the Canadian healthcare system perspective suggest that PARP inhibitors are not cost-effective. This research impacts policymakers, guiding future reimbursement negotiations and future health economic research in the field. Background/Objectives: Through phase III clinical trials, PARP inhibitors have demonstrated outcome improvements in mCRPC patients with alterations in BRCA1/2 genes who have progressed on a second-generation androgen receptor pathway inhibitor (ARPI). While improving outcomes, PARP inhibitors contribute to the ever-growing economic burden of PCa. The objective of this project is to evaluate the cost-effectiveness of PARP inhibitors (olaparib, rucaparib, or talazoparib) versus the SOC (docetaxel or androgen receptor pathway inhibitors (ARPI)) for previously progressed mCRPC patients with BRCA1/2 mutations from the Canadian healthcare system perspective. Methods: Partitioned survival models were created to represent mCRPC disease after progression until death. Survival inputs for BRCA1/2-mutated patients were extracted from the PROfound, TRITON3, and TALAPRO-1 clinical trials, while Canadian-specific costs are presented in 2023 dollars. Upon progression, patients were treated with chemotherapy. The considered time horizon was 5 years and outcomes were discounted at 1.5% per year. Results: PARP inhibitors provide an additional survival of 0.19 quality-adjusted life years (QALY) when compared to the current standard of care, with additional costs of CAD 101,679 resulting in an incremental cost-utility ratio (ICUR) of CAD 565,383/QALY. The results were most sensitive to PARP inhibitors' acquisition costs and health-state utilities. PARP inhibitors required price reductions of up to 83% to meet the CAD 50,000/QALY willingness-to-pay threshold (WTP). Conclusions: While providing survival benefits to previously progressed mCRPC patients presenting deleterious BRCA1/2 gene mutations, PARP inhibitors are not cost-effective and require major price reductions to reach local WTP thresholds. [ABSTRACT FROM AUTHOR]

Brain–computer interfaces (BCI) are an effective tool for recognizing motor imagery and have been widely applied in the motor control and assistive operation domains. However, traditional intention-recognition methods face several challenges, such as prolonged training times and limited cross-subject adaptability, which restrict their practical application. This paper proposes an innovative method that combines a lightweight convolutional neural network (CNN) with domain adaptation. A lightweight feature extraction module is designed to extract key features from both the source and target domains, effectively reducing the model's parameters and improving the real-time performance and computational efficiency. To address differences in sample distributions, a domain adaptation strategy is introduced to optimize the feature alignment. Furthermore, domain adversarial training is employed to promote the learning of domain-invariant features, significantly enhancing the model's cross-subject generalization ability. The proposed method was evaluated on an fNIRS motor imagery dataset, achieving an average accuracy of 87.76% in a three-class classification task. Additionally, lightweight experiments were conducted from two perspectives: model structure optimization and data feature selection. The results demonstrated the potential advantages of this method for practical applications in motor imagery recognition systems. [ABSTRACT FROM AUTHOR]

Decision support systems based on machine learning (ML) techniques are already empowering neuro-oncologists. These systems provide comprehensive diagnostics, offer a deeper understanding of diseases, predict outcomes, and assist in customizing treatment plans to individual patient needs. Collectively, these elements represent artificial intelligence (AI) in neuro-oncology. This paper reviews recent studies which apply machine learning algorithms to optical spectroscopy data from central nervous system (CNS) tumors, both ex vivo and in vivo. We first cover general issues such as the physical basis of the optical-spectral methods used in neuro-oncology, and the basic algorithms used in spectral signal preprocessing, feature extraction, data clustering, and supervised classification methods. Then, we review in more detail the methodology and results of applying ML techniques to fluorescence, elastic and inelastic scattering, and IR spectroscopy. [ABSTRACT FROM AUTHOR]

This article delves into the critical integration of domain knowledge into AI/ML systems across various industries, highlighting its importance in developing ethically responsible, effective, and contextually relevant solutions. Through detailed case studies from the healthcare and manufacturing sectors, we explore the challenges, strategies, and successes of this integration. We discuss the evolving role of domain experts and the emerging tools and technologies that facilitate the incorporation of human expertise into AI/ML models. The article forecasts future trends, predicting a more seamless and strategic collaboration between AI/ML and domain expertise. It emphasizes the necessity of this synergy for fostering innovation, ensuring ethical practices, and aligning technological advancements with human values and real-world complexities. [ABSTRACT FROM AUTHOR]

The detection of viral DNA is considered crucial in both diagnosis and prognosis. Nowadays, molecular diagnostic approaches represent the most promising tools for the clinical detection of viral infections. This review aims to investigate the most used and promising DNA-based technologies for viral detection, focusing on herpesviruses because of their ability to undergo latent and reactivation cycles, persisting lifelong in the host in association with several diseases. Molecular technologies, such as PCR-based assays, enhance sensitivity and specificity in identifying viral DNA from clinical samples such as blood, cerebrospinal fluid and saliva, indicating PCR and its derivatives as the gold standard methods for herpesvirus detection. In conclusion, this review underscores the need for continuous innovation in diagnostic methodologies to address the complexities of herpesvirus identification in different clinical samples. [ABSTRACT FROM AUTHOR]

Neuroendocrine prostate cancer (NEPC), an aggressive and lethal subtype of prostate cancer (PCa), often arises as a resistance mechanism in patients undergoing hormone therapy for prostate adenocarcinoma. NEPC is associated with a significantly poor prognosis and shorter overall survival compared to conventional prostate adenocarcinoma due to its aggressive nature and limited response to standard of care therapies. This transdifferentiation, or lineage reprogramming, to NEPC is characterised by the loss of androgen receptor (AR) and prostate-specific antigen (PSA) expression, and the upregulation of neuroendocrine (NE) biomarkers such as neuron-specific enolase (NSE), chromogranin-A (CHGA), synaptophysin (SYP), and neural cell adhesion molecule 1 (NCAM1/CD56), which are critical for NEPC diagnosis. The loss of AR expression culminates in resistance to standard of care PCa therapies, such as androgen-deprivation therapy (ADT) which target the AR signalling axis. This review explores the drivers of NE transdifferentiation. Key genetic alterations, including those in the tumour suppressor genes RB1, TP53, and PTEN, and changes in epigenetic regulators, particularly involving EZH2 and cell-fate-determining transcription factors (TFs) such as SOX2, play significant roles in promoting NE transdifferentiation and facilitate the lineage switch from prostate adenocarcinoma to NEPC. The recent identification of several other key novel drivers of NE transdifferentiation, including MYCN, ASCL1, BRN2, ONECUT2, and FOXA2, further elucidates the complex regulatory networks and pathways involved in this process. We suggest that, given the multifactorial nature of NEPC, novel therapeutic strategies that combine multiple modalities are essential to overcome therapeutic resistance and improve patient outcomes. [ABSTRACT FROM AUTHOR]

High-temperature titanium alloys are significant materials in the aerospace field, and their service life largely depends on creep aging. However, the creep behavior of the TC25 titanium alloy at high temperatures has not been reported. Here, the creep behavior of TC25 before and after heat treatment at 550 °C under different stresses was investigated. It was found that heat treatment significantly enhanced the creep resistance of the TC25 alloy. An increase in creep stress increased the steady-state creep rate and reduced creep life. The smooth αp/βtrans grain boundaries and refined αs improved creep resistance, and the creep mechanism changed from grain boundary sliding to dislocation climbing after heat treatment. This research provides theoretical data support for the application of the TC25 alloy at high temperatures. [ABSTRACT FROM AUTHOR]

Gonadotropins and progestins are the primary regulators of follicle maturation and ovulation in fish, and they require complex communication among the oocyte and somatic cells of the follicle. The major progestin and the maturation-inducing hormone in salmonids is 17α,20β-dihdroxy-4-pregnen-3-one (17,20βP), and traditional nuclear receptors and membrane steroid receptors for the progestin have been identified within the follicle. Herein, RNA-seq was used to conduct a comprehensive survey of changes in gene expression throughout the intact follicle in response to in vitro treatment with these hormones to provide a foundation for understanding the coordination of their actions in regulating follicle maturation and preparation for ovulation. A total of 5292 differentially expressed genes were identified from our transcriptome sequencing datasets comparing four treatments: fresh tissue; untreated control; 17,20βP-treated; and salmon pituitary homogenate-treated follicles. Extensive overlap in affected genes suggests many gonadotropin actions leading to the acquisition of maturational and ovulatory competence are mediated in part by gonadotropin induction of 17,20βP synthesis. KEGG analysis identified signaling pathways, including MAPK, TGFβ, FoxO, and Wnt signaling pathways, among the most significantly enriched pathways altered by 17,20βP treatment, suggesting pervasive influences of 17,20βP on actions of other endocrine and paracrine factors in the follicle complex. [ABSTRACT FROM AUTHOR]

Background: Despite incidence rates and complications, the clinical management of xerostomia lacks guidelines. Aim: The aim of this overview is to summarize the clinical experience over the past 10 years of treating xerostomia using non-pharmacological interventions. Materials and Methods: A literature search was conducted across PubMed, EMBASE, Web of Science, ScienceDirect, and Google Scholar databases, covering publications from 1 January 2013 to 30 January 2023. Results: Topical therapies are the mainstays in cases of longstanding oral dryness. Their aim is to relieve oral discomfort by retaining mouth moisture. Macro-molecular lubricants were largely used in xerostomia due to radiotherapy for Head and Neck cancer (HNC) and xerostomia due to the chronic use of drugs. However, none of them provided stable relief for dry mouth. Traditional Medicine (TM), through the administration of different medicinal herbs and plants, has recently been evaluated against xerostomia in clinical trials. Matricaria chamomilla L., Linum usitatissimum, and Malva sylvestris L. together with Althea digitata Boiss, Licorice root, and Salvia Officinalis are among the most used compounds. They were formulated as water extracts with health benefits that are attributed to the presence of polyphenols. However, the low number of clinical evaluations represents the greatest limitation for validating the efficacy of TM against xerostomia. Regarding acupuncture, it did not show significant effects in the trials in comparison to the control groups. Further, electrostimulation, photo-biomodulation and hyperbaric therapy need more randomized clinical evaluations to effectively demonstrate their ability to relieve dry mouth. Conclusions: No topical treatment has shown stable relief of xerostomia. Consequently, the management of xerostomia and its devastating complications remain a significant void in daily clinical practice. [ABSTRACT FROM AUTHOR]

Simple Summary: Bees, while individually poikilothermic, can maintain group warmth, which is vital for biodiversity. Apis cerana outperforms Apis mellifera in cold tolerance, particularly as a pollinator in harsh conditions. Here, we utilized transcriptome data to identify alternative splicing events and alternative polyadenylation genes associated with cold stress in A. cerana. These genetic changes are linked to signal transduction, energy metabolism, and oxidative stress, with key genes like HSP70 and BAG increasing in expression and others showing a pattern of an initial decrease followed by an increase. This post-transcriptional regulation may help bees adapt to cold, providing insights for breeding cold-resistant bee strains and advancing cold resistance research in insects. Bees, as individual poikilotherms capable of group homeothermy, possess temperature tolerance and regulatory mechanisms crucial for biodiversity conservation. The Asian honeybee (Apis cerana), a key pollinator for alpine and winter-flowering plants, exhibits superior cold tolerance over Apis mellifera, making it a dominant model species for insect cold resistance studies. While extensive research has delved into the behavioral and physiological facets of honeybee cold resistance, the post-transcriptional regulation in response to cold stress remains understudied. In this study, full-length transcriptome data obtained from PacBio and Illumina sequencing identified 25,443 events of alternative splicing (AS) and 2821 genes of alternative polyadenylation (APA) involved in the cold stress response of honeybees. GO and KEGG functional annotations were performed on the differential AS and APA between the cold stress (T vs. CK) and cold tolerance (TR vs. CK) groups in A. cerana workers of different ages, (3 days (Ac3d), 10 days (Ac10d), and 21 days (Ac21d) old), and the results indicated that these differentially expressed AS (DASs) and differentially expressed APAs (DAPAs) implicate signal transduction, energy metabolism, and oxidative metabolism. Venn analysis, expression clustering, and trend analysis highlight the roles of DASs in regulating high-stress proteins like HSP70 and BAG, with increasing expression levels, while DAPAs are mainly associated with signal transduction and energy metabolism, including genes like CUBN and UGCG, with gene expression levels initially decreasing and then increasing. We verified the isoforms of three DASs and the polyadenylation sites of three DAPAs using RT-PCR and 3′ RACE. In conclusion, the post-transcriptional regulation of AS and APA in A. cerana may respond to chilling stress by participating in the regulation of different metabolic pathways and antifreeze proteins. The results of this study have reference value for the study of the molecular mechanisms of insect cold resistance and provide clues for the development of molecular breeding targets for cold-resistant strains of bees. [ABSTRACT FROM AUTHOR]

Self-regulation is a crucial skill in early childhood, due to its influence on school readiness and success, as well as its foundational role in promoting wellbeing across the lifespan. Additionally, self-regulation is malleable, particularly during early childhood. This study investigated the impact of nature-based practices on preschoolers' self-regulation. The Preschool Self-Regulation Assessment (PSRA) and PSRA Assessor Report were administered to 115 children from nine preschool programs at the beginning and end of the school year. While further research is needed, results suggest the potential for nature-based practices to support SR, in particular hot executive function, and particularly in children from lower socio-economic backgrounds in public preschool. This study contributes to the literature regarding effective practices for supporting self-regulation development in young children and adds to the growing body of research surrounding the impact of nature play on child development and school readiness. [ABSTRACT FROM AUTHOR]

Cooperation is essential in social life, involving collaborative efforts for mutual benefits. Individual differences in the cooperativeness trait are pivotal in these interactions. A single-group pretest–posttest design was used in this study to determine if Duchenne smiling with gaze and inter-brain synchrony (IBS) during conversation mediates the relationship between cooperativeness and cooperative behavior. The relationships among the variables were examined using mediation analysis and path analysis. We hypothesized that Duchenne smiling with gaze would mediate cooperativeness' impact on cooperative behavior, while expecting IBS in the left prefrontal region to predict cooperative behavior. The results demonstrated that cooperativeness significantly predicted Duchenne smiling with gaze and cooperative behavior; however, Duchenne smiling with gaze did not mediate the relationship between them. Additionally, IBS during conversation did not predict successive cooperative behavior. These results suggest dispositional factors like cooperativeness may play a more decisive role than momentary expressional cues or neural synchrony in naturalistic unstructured communication in shaping cooperative behavioral outcomes after the communication. The study highlights how personality traits like cooperativeness shape nonverbal communication and social interactions, implying that interventions aimed at developing cooperativeness could lead to more effective collaboration in social settings. [ABSTRACT FROM AUTHOR]

To monitor health risks associated with vaping, we introduce a multi-spectral optical sensor powered by machine learning for real-time characterization of electronic cigarette aerosols. The sensor can accurately measure the mass of particulate matter (PM) in specific particle size channels, providing essential information for estimating lung deposition of vaping aerosols. For the sensor's input, wavelength-specific optical attenuation signals are acquired for three separate wavelengths in the ultraviolet, red, and near-infrared range, and the inhalation pressure is collected from a pressure sensor. The sensor's outputs are PM mass in three size bins, specified as 100–300 nm, 300–600 nm, and 600–1000 nm. Reference measurements of electronic cigarette aerosols, obtained using a custom vaping machine and a scanning mobility particle sizer, provided the ground truth for size-binned PM mass. A lightweight two-layer feedforward neural network was trained using datasets acquired from a wide range of puffing conditions. The performance of the neural network was tested using unseen data collected using new combinations of puffing conditions. The model-predicted values matched closely with the ground truth, and the accuracy reached 81–87% for PM mass in three size bins. Given the sensor's straightforward optical configuration and the direct collection of signals from undiluted vaping aerosols, the achieved accuracy is notably significant and sufficiently reliable for point-of-interest sensing of vaping aerosols. To the best of our knowledge, this work represents the first instance where machine learning has been applied to directly characterize high-concentration undiluted electronic cigarette aerosols. Our sensor holds great promise in tracking electronic cigarette users' puff topography with quantification of size-binned PM mass, to support long-term personalized health and wellness. [ABSTRACT FROM AUTHOR]

Sleep, notably active sleep (AS) and quiet sleep (QS), plays a pivotal role in the brain development and gradual maturation of (pre) term infants. Monitoring their sleep patterns is imperative, as it can serve as a tool in promoting neurological maturation and well-being, particularly important in preterm infants who are at an increased risk of immature brain development. An accurate classification of neonatal sleep states can contribute to optimizing treatments for high-risk infants, with respiratory rate (RR) and heart rate (HR) serving as key components in sleep assessment systems for neonates. Recent studies have demonstrated the feasibility of extracting both RR and HR using near-infrared spectroscopy (NIRS) in neonates. This study introduces a comprehensive sleep classification approach leveraging high-frequency NIRS signals recorded at a sampling rate of 100 Hz from a cohort of nine preterm infants admitted to a neonatal intensive care unit. Eight distinct features were extracted from the raw NIRS signals, including HR, RR, motion-related parameters, and proxies for neural activity. These features served as inputs for a deep convolutional neural network (CNN) model designed for the classification of AS and QS sleep states. The performance of the proposed CNN model was evaluated using two cross-validation approaches: ten-fold cross-validation of data pooling and five-fold cross-validation, where each fold contains two independently recorded NIRS data. The accuracy, balanced accuracy, F1-score, Kappa, and AUC-ROC (Area Under the Curve of the Receiver Operating Characteristic) were employed to assess the classifier performance. In addition, comparative analyses against six benchmark classifiers, comprising K-Nearest Neighbors, Naive Bayes, Support Vector Machines, Random Forest (RF), AdaBoost, and XGBoost (XGB), were conducted. Our results reveal the CNN model's superior performance, achieving an average accuracy of 88%, a balanced accuracy of 94%, an F1-score of 91%, Kappa of 95%, and an AUC-ROC of 96% in data pooling cross-validation. Furthermore, in both cross-validation methods, RF and XGB demonstrated accuracy levels closely comparable to the CNN classifier. These findings underscore the feasibility of leveraging high-frequency NIRS data, coupled with NIRS-based HR and RR extraction, for assessing sleep states in neonates, even in an intensive care setting. The user-friendliness, portability, and reduced sensor complexity of the approach suggest its potential applications in various less-demanding settings. This research thus presents a promising avenue for advancing neonatal sleep assessment and its implications for infant health and development. [ABSTRACT FROM AUTHOR]

Ocean sustainability entails the management of marine ecosystems and their services. Monitoring and evaluation of the health of the sea is challenged by the complexity of the marine environment, whose multitude and interconnected aspects, together with the lack of comprehensive models, make the understanding of its functioning a very arduous endeavour. Observations are costly and time-consuming. For this reason, a European joint action, named Science for Good Environmental Status, tested a new approach to monitor and evaluate effectively the state of health of the sea. This approach is based on the identification of driving physical processes that are present in the sea basins and directing the observation strategy to be designed on the basis of preliminary space–time information and patterns. The proof-of-concept of this approach has been implemented offshore of the Belgian coast in an attempt to achieve ecosystem assessments with targeted data collection methods requiring a reduced combination of variables. The proposed approach can impact monitoring activities implemented by those countries aiming to fulfil the requests of the European Marine Strategy Framework Directive. A map of EU marine areas to further test this process-based approach is also provided. [ABSTRACT FROM AUTHOR]

Engineered nanomaterials (ENMs) have a broad array of applications in agriculture, engineering, manufacturing, and medicine. Decades of toxicology research have demonstrated that ENMs can cause genotoxic effects on bacteria, mammalian cells, and animals. Some metallic ENMs (MENMs), e.g., metal or metal oxide nanoparticles TiO2 and CuO, induce genotoxicity via direct DNA damage and/or reactive oxygen species-mediated indirect DNA damage. There are various physical features of MENMs that may play an important role in promoting their genotoxicity, for example, size and chemical composition. For a valid genotoxicity assessment of MENMs, general considerations should be given to various factors, including, but not limited to, NM characterization, sample preparation, dosing selection, NM cellular uptake, and metabolic activation. The recommended in vitro genotoxicity assays of MENMs include hprt gene mutation assay, chromosomal aberration assay, and micronucleus assay. However, there are still knowledge gaps in understanding the mechanisms underlying the genotoxicity of MENMs. There are also a variety of challenges in the utilization and interpretation of the genotoxicity assessment assays of MENMs. In this review article, we provide mechanistic insights into the genotoxicity of MENMs in the human environment. We review advances in applying new endpoints, biomarkers, and methods to the genotoxicity assessments of MENMs. The guidance of the United States, the United Kingdom, and the European Union on the genotoxicity assessments of MENMs is also discussed. [ABSTRACT FROM AUTHOR]

This review provides an overview of explainable AI (XAI) methods for oncological ultrasound image analysis and compares their performance evaluations. A systematic search of Medline Embase and Scopus between 25 March and 14 April 2024 identified 17 studies describing 14 XAI methods, including visualization, semantics, example-based, and hybrid functions. These methods primarily provided specific, local, and post hoc explanations. Performance evaluations focused on AI model performance, with limited assessment of explainability impact. Standardized evaluations incorporating clinical end-users are generally lacking. Enhanced XAI transparency may facilitate AI integration into clinical workflows. Future research should develop real-time methodologies and standardized quantitative evaluative metrics. [ABSTRACT FROM AUTHOR]

Prostate cancer (PC) is one of the most commonly diagnosed tumours among men. Second-generation androgen receptor axis-targeted (ARAT) agents, namely abiraterone acetate (AbA) and enzalutamide (ENZ), are currently used in the management of metastatic castration-resistant PC (mCRPC). However, the treatment is challenging due to the lack of prognostic biomarkers. Meanwhile, single-nucleotide polymorphisms (SNPs) have emerged as potential prognostic indicators of mCRPC. Thus, this study evaluated the impact of relevant SNPs on the treatment outcomes of 123 mCRPC patients enrolled in a hospital-based cohort study. The CYP17A1 rs2486758 C allele was associated with a 50% reduction in the risk of developing castration resistance (hazard ratio (HR) = 0.55; p = 0.003). Among patients without metastasis at tumour diagnosis and under AbA, a marginal association between YBX1 rs10493112 and progression-free survival was detected (log-rank test, p = 0.056). In the same subgroup, significant associations of HSD3B1 rs1047303 (CC/CA vs. AA; HR = 3.41; p = 0.025), YBX1 rs12030724 (AT vs. AA; HR = 3.54; p = 0.039) and YBX1 rs10493112 (log-rank test, p = 0.041; CC vs. AA/AC; HR = 3.22; p = 0.053) with overall survival were also observed, which were confirmed by multivariate Cox analyses. Although validation with larger cohorts is required, these findings suggest that SNPs could enhance the prognosis assessment of mCRPC patients, leading to a more personalised treatment. [ABSTRACT FROM AUTHOR]

Students at 2-year colleges who wish to enter the mental health professions, particularly students of color in urban community college environments, often lack opportunities for internships and experience-building programming relevant to their field. Some programs targeting such students do exist, but little research has been performed on these models. In addition, while pipeline programs in 2-year college settings often focus on successful transitions to senior colleges, many students in such programs also seek to eventually enter graduate school. The purpose of this case study is to bridge this research gap by focusing on a community college-based peer support and psychoeducational outreach program in the northeastern United States, serving as a career development internship for aspiring mental health professionals. Qualitative data in the form of student participant feedback was analyzed to determine the impact of the program on their experiences later in their educational careers. Results from this qualitative analysis indicate the substantial importance of such a program to the successful academic progress of its student participants, providing insights into how pipeline programs can accommodate student preparation and support, not only toward successful senior college transition, but also specific to graduate school program entry. [ABSTRACT FROM AUTHOR]

A low level of Neurotrophins (NTs), their Tyrosine Kinase Receptors (Trks), Vascular Endothelial Growth Factors (VEGFs) and their receptors, mainly VEGFR1 and VEGFR2, characterizes AD brains. The use of NTs and VEGFs as drugs presents different issues due to their low permeability of the blood−brain barrier, the poor pharmacokinetic profile, and the relevant side effects. To overcome these issues, different functional and structural NT mimics have been employed. Being aware that the N-terminus domain as the key domain of NTs for the binding selectivity and activation of Trks and the need to avoid or delay proteolysis, we herein report on the mimicking ability of two cyclic peptide encompassing the N-terminus of Brain Derived Growth Factor (BDNF), (c-[HSDPARRGELSV-]), cBDNF(1-12) and of Neurotrophin3 (NT3), (c-[YAEHKSHRGEYSV-]), cNT3(1-13). The two cyclic peptide features were characterized by a combined thermodynamic and spectroscopic approach (potentiometry, NMR, UV-vis and CD) that was extended to their copper(II) ion complexes. SH-SY5Y cell assays show that the Cu2+ present at the sub-micromolar level in the complete culture media affects the treatments with the two peptides. cBDNF(1-12) and cNT3(1-13) act as ionophores, induce neuronal differentiation and promote Trks and CREB phosphorylation in a copper dependent manner. Consistently, both peptide and Cu2+ stimulate BDNF and VEGF expression as well as VEGF release; cBDNF(1-12) and cNT3(1-13) induce the expression of Trks and VEGFRs. [ABSTRACT FROM AUTHOR]

The perception of the importance of ciliate in freshwater has changed dramatically since the "microbial loop" conceptualisation, reflecting methodological attempts. The data from two decades (1994–2018) on the surface (0–3 m) ciliate assemblage in the Slapy reservoir (Vltava River, Czech Republic) during two different nutrient-load defined periods were analysed. We grouped the identified, quantified, and biomass-evaluated ciliates in the quantitative protargol-impregnated preparations according to their feeding behaviour. The sampling median and interquartile range data of the ciliates were plotted; the modelled water age, nutrients, bacteria, heterotrophic nanoflagellates, and Rhodomonas spp. were applied as the main explanatory background variables. We validated the differences between the periods, engaging multivariate analyses. The picoplankton-filtering species dominated the assemblages in an annual mean (halteriids and minute strobilidiids followed by peritrichs). Algae hunting urotrichs, Balanion planctonicum, and nanoplankton filtering tintinnids were significant before the spring phytoplankton peak when a maximum of ciliate biomass reflected mixotrophic nanoplankton filtering pelagostrombidiids. Only there did ciliate biomass tightly follow their quantified prey. Heterotrophic and mixotrophic Askenasia and Lagynophrya were typical raptorial/flagellate-hunting cilates; only Mesodinium spp. reached the maximum during autumn. The observed oligotrophication of the reservoir increased the ciliate assemblage biomass in the surface layer during stratification in concordance with the Plankton Ecology Group (PEG) model. [ABSTRACT FROM AUTHOR]

Sea level rise (SLR) is a crucial indicator of climate change, primarily driven by greenhouse gas emissions and the subsequent increase in global temperatures. The impact of SLR, however, varies regionally due to factors such as ocean bathymetry, resulting in distinct shifts across different areas compared to the global average. Understanding the complex factors influencing SLR across diverse spatial scales, along with the associated uncertainties, is essential. This study focuses on the East Coast of the United States and Gulf of Mexico, utilizing historical SLR data from 1993 to 2023. To forecast SLR trends from 2024 to 2103, a weighted ensemble model comprising SARIMAX, LSTM, and exponential smoothing models was employed. Additionally, using historical greenhouse gas data, an ensemble of LSTM models was used to predict real-time SLR values, achieving a testing loss of 0.005. Furthermore, conductance and dissolved oxygen (DO) values were assessed for the entire forecasting period, leveraging forecasted SLR trends to evaluate the impacts on marine life, agriculture, and infrastructure. [ABSTRACT FROM AUTHOR]

Alcohol-associated liver disease (ALD) is a major cause of chronic liver disease, with few effective treatments besides alcohol abstinence. Angelicae Gigantis Radix (AG), Glycyrrhizae Radix et Rhizoma (GR), Paeoniae Radix (PR), and Zizyphi Fructus (ZF) are traditional herbs used to treat various ailments, including liver diseases. While several studies have reported the beneficial effects of GR on ALD, the effects of AG, PR, and ZF remain underexplored. Therefore, their efficacy and mechanisms against ALD were investigated using an alcohol-related liver injury model. The model was induced by ethanol gavage in C57BL/6J mice for 14 days, followed by oral administration of AG, GR, PR, and ZF one hour post-induction. The administration of these herbs reduced liver weight, and improved serum biomarkers of liver injury (ALT, AST, albumin). The herbs enhanced hepatic antioxidant capacity (GSH, SOD, catalase) and suppressed the production of proinflammatory cytokines (TNF-α, IL-1β) and apoptotic changes (caspase-3). The mechanisms of action involved lipid-lowering gene modulation through regulation of the cytochrome P450 2E1/Sirtuin 1/Nrf2 pathways. Histopathological and immunohistochemical analyses revealed that these herbs attenuated hepatocyte damage and steatosis via antioxidant, anti-inflammatory, and antiapoptotic effects. These findings suggest that traditional herbs, particularly AG, could be promising alternative therapies for treating ALD. [ABSTRACT FROM AUTHOR]

Artifacts induced during patient monitoring are a main limitation for near-infrared spectroscopy (NIRS) as a non-invasive method of cerebral hemodynamic monitoring. There currently does not exist a robust "gold-standard" method for artifact management for these signals. The objective of this review is to comprehensively examine the literature on existing artifact management methods for cerebral NIRS signals recorded in animals and humans. A search of five databases was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. The search yielded 806 unique results. There were 19 articles from these results that were included in this review based on the inclusion/exclusion criteria. There were an additional 36 articles identified in the references of select articles that were also included. The methods outlined in these articles were grouped under two major categories: (1) motion and other disconnection artifact removal methods; (2) data quality improvement and physiological/other noise artifact filtering methods. These were sub-categorized by method type. It proved difficult to quantitatively compare the methods due to the heterogeneity of the effectiveness metrics and definitions of artifacts. The limitations evident in the existing literature justify the need for more comprehensive comparisons of artifact management. This review provides insights into the available methods for artifact management in cerebral NIRS and justification for a homogenous method to quantify the effectiveness of artifact management methods. This builds upon the work of two existing reviews that have been conducted on this topic; however, the scope is extended to all artifact types and all NIRS recording types. Future work by our lab in cerebral NIRS artifact management will lie in a layered artifact management method that will employ different techniques covered in this review (including dynamic thresholding, autoregressive-based methods, and wavelet-based methods) amongst others to remove varying artifact types. [ABSTRACT FROM AUTHOR]

Background/Objectives: Schools can play a key role in promoting health among adolescents, and Hungarian legislation gives them sufficient space to do so. In our study, we examined the impact of a multiyear school health promotion programme on pupils' health behaviour and well-being. Methods: We carried out our investigation in an intervention and a control primary school in Hungary. All 5th and 7th grade pupils were invited to participate in the questionnaire-based survey between 2017 and 2021. The effect of the intervention was quantified using univariate and multivariate logistic regression analyses. Results: Our results show that for those behaviours where pupils' personal choices had a greater influence (unhealthy eating, smoking, screen time), the health promotion programme was more effective. For those behaviours where family background and parental influence were more pronounced (healthy eating, physical activity), the intervention had less impact. Self-perceived health was better in the 7th-grade intervention group. Conclusions: Our findings are in line with the conclusion of systematic reviews that more intensive, longer-term, multi-behavioural school health promotion programmes can be effective in promoting positive behaviour. To be more effective, it would be worth using a well-structured curriculum, well-developed teaching materials, and greater involvement of teachers, parents, and various local organisations. [ABSTRACT FROM AUTHOR]

Accurate and early diagnosis of monkeypox virus (MPXV) is crucial for controlling epidemics and treating affected individuals promptly. This study aimed to assess the analytical and clinical performance of the MolecisionTM Monkeypox Virus qPCR Assay, Biorain Monkeypox Virus ddPCR Assay, and MAGLUMI® Monkeypox Virus Ag (chemiluminescence immunoassay, CLIA) Assay. Additionally, it aimed to compare the clinical application of antigen and nucleic acid assays to offer insights into using commercial monkeypox assay kits. Specimens from 117 clinical patients, serial diluted virus cell culture supernatant, and artificially created positive samples were tested to evaluate the performance of these assay kits for MPXV diagnostics. The Biorain Monkeypox Virus ddPCR Assay had a limit of detection (LoD) of 3.89 CCID50/mL, while the MolecisionTM Monkeypox Virus qPCR Assay had an LoD of 15.55 CCID50/mL. The MAGLUMI® Monkeypox Virus Ag (CLIA) Assay had an LoD of 0.500 pg/mL. The accuracy of the MolecisionTM Monkeypox Virus qPCR Assay was comparable to the Biorain Monkeypox Virus ddPCR Assay, and the MAGLUMI® Monkeypox Virus Ag (CLIA) Assay demonstrated high sensitivity. The specificity of all three MPXV diagnostic assays for clinical specimens with potential cross-reacting substances was 100%. In conclusion, this study provides valuable insights into the clinical application of monkeypox assays, supporting efforts to mitigate and control the spread of monkeypox. [ABSTRACT FROM AUTHOR]

Repeated exposure to tobacco smoke causes neuroinflammation and neuroplasticity, which correlates with smoking withdrawal-induced anxiety. The purpose of this study was to investigate the anticipated involvement of antioxidant-rich nanoparticles (NPs) prepared by oxidation-triggered polymerization of green tea catechins in impacting these effects in a rat model of tobacco smoke exposure. Exposure to tobacco smoke was carried out for 2 h a day, 5 days a week, for a total of 36 days. Weekly behavioral tests were conducted prior to recommencing the exposure. Following a 20-day exposure period, rats were administered either distilled water or green tea (GT) NPs (20 mg/kg, orally) for an additional 16 days. Our findings revealed that tobacco smoke exposure induced anxiety-like behavior indicative of withdrawal, and this effect was alleviated by GT NPs. Tobacco smoke exposure caused a marked increase in the relative mRNA and protein expression of nuclear factor-kappa B (NF-κB) and reduced the relative mRNA and protein expression of brain-derived neurotrophic factor (BDNF) in the hippocampus (HIP) and hypothalamus (HYP) brain subregions. The intervention of GT NPs effectively inhibited these effects. Our findings demonstrate the potent protective role of GT NPs in reducing withdrawal-induced anxiety-like behavior, neuroinflammation, and neuroplasticity triggered by tobacco smoke exposure. [ABSTRACT FROM AUTHOR]

Traumatic brain injuries (TBIs) constitute a significant public health issue and a major source of disability and death in the United States and worldwide. TBIs are strongly associated with high morbidity and mortality rates, resulting in a host of negative health outcomes and long-term complications and placing a heavy financial burden on healthcare systems. One promising avenue for the prevention and treatment of brain injuries is the design of TBI-specific supplementation and dietary protocols centred around nutraceuticals and biochemical compounds whose mechanisms of action have been shown to interfere with, and potentially alleviate, some of the neurophysiological processes triggered by TBI. For example, evidence suggests that creatine monohydrate and omega-3 fatty acids (DHA and EPA) help decrease inflammation, reduce neural damage and maintain adequate energy supply to the brain following injury. Similarly, melatonin supplementation may improve some of the sleep disturbances often experienced post-TBI. The scope of this narrative review is to summarise the available literature on the neuroprotective effects of selected nutrients in the context of TBI-related outcomes and provide an evidence-based overview of supplementation and dietary protocols that may be considered in individuals affected by—or at high risk for—concussion and more severe head traumas. Prophylactic and/or therapeutic compounds under investigation include creatine monohydrate, omega-3 fatty acids, BCAAs, riboflavin, choline, magnesium, berry anthocyanins, Boswellia serrata, enzogenol, N-Acetylcysteine and melatonin. Results from this analysis are also placed in the context of assessing and addressing important health-related and physiological parameters in the peri-impact period such as premorbid nutrient and metabolic health status, blood glucose regulation and thermoregulation following injury, caffeine consumption and sleep behaviours. As clinical evidence in this research field is rapidly emerging, a comprehensive approach including appropriate nutritional interventions has the potential to mitigate some of the physical, neurological, and emotional damage inflicted by TBIs, promote timely and effective recovery, and inform policymakers in the development of prevention strategies. [ABSTRACT FROM AUTHOR]

Ferroptosis, an iron-dependent form of non-apoptotic cell death, plays a pivotal role in various diseases and is gaining considerable attention in the realm of endometriosis. Considering the classical pathomechanism theories, we hypothesized that ferroptosis, potentially driven by increased iron content at ectopic sites, may contribute to the progression of endometriosis. This retrospective case–control study provides a comprehensive immunohistochemical assessment of the expression and tissue distribution of established ferroptosis markers: GPX4, ACSL4, and TfR1 in endometriosis patients. The case group consisted of 38 women with laparoscopically and histologically confirmed endometriosis and the control group consisted of 18 women with other gynecological conditions. Our study revealed a significant downregulation of GPX4 in stromal cells of endometriosis patients (M = 59.7% ± 42.4 versus 90.0% ± 17.5 in the control group, t (54) = −2.90, p = 0.005). This finding aligned with slightly, but not significantly, higher iron levels detected in the blood of endometriosis patients, using hemoglobin as an indirect predictor (Hb 12.8 (12.2–13.5) g/dL versus 12.5 (12.2–13.4) g/dL in the control group; t (54) = −0.897, p = 0.374). Interestingly, there was no concurrent upregulation of TfR1 (M = 0.7 ± 1.2 versus 0.2 ± 0.4 for EM, t (54) = 2.552, p = 0.014), responsible for iron uptake into cells. Our empirical findings provide support for the involvement of ferroptosis in the context of endometriosis. However, variances in expression patterns within stromal and epithelial cellular subsets call for further in-depth investigations. [ABSTRACT FROM AUTHOR]

James German's work to establish the natural history and cancer risk associated with Bloom syndrome (BS) has had a strong influence on the generation of scientists and clinicians working to understand other RECQ deficiencies and heritable cancer predisposition syndromes. I summarize work by us and others below, inspired by James German's precedents with BS, to understand and compare BS with the other heritable RECQ deficiency syndromes with a focus on Werner syndrome (WS). What we know, unanswered questions and new opportunities are discussed, as are potential ways to treat or modify WS-associated disease mechanisms and pathways. [ABSTRACT FROM AUTHOR]

High-frequency radars (HFRs) provide remote information on ocean surface velocity in extended coastal areas at high resolutions in space (O (km)) and time (O (h)). They directly produce radial velocities (in the radar antenna's direction) combined to provide total vector velocities in areas covered by at least two radars. HFRs are a key element in ocean observing systems, with several important environmental applications. Here, we provide an assessment of the HFR-TirLig network in the NW Mediterranean Sea, including results from the gap-filling open-boundary modal analysis (OMA) using in situ velocity data from drifters. While the network consists of three radars, only two were active during the assessment experiment, so the test also includes an area where the radial velocities from only one radar system were available. The results, including several metrics, both Eulerian and Lagrangian, and configurations, show that the network performance is very satisfactory and compares well with the previous results in the literature in terms of both the radial and total combined vector velocities where the coverage is adequate, i.e., in the area sampled by two radars. Regarding the OMA results, not only do they perform equally well in the area sampled by the two radars but they also provide results in the area covered by one radar only. Even though obviously deteriorated with respect to the case of adequate coverage, the OMA results can still provide information regarding the velocity structure and speed as well as virtual trajectories, which can be of some use in practical applications. A general discussion on the implications of the results for the potential of remote sensing velocity estimation in terms of HFR network configurations and complementing gap-filling analysis is provided. [ABSTRACT FROM AUTHOR]

The aim of this study was to identify key proteins of synaptic transmission in the cochlear nucleus (CN) that are involved in normal hearing, acoustic stimulation, and tinnitus. A gene list was compiled from the GeneCards database using the keywords "synaptic transmission" AND "tinnitus" AND "cochlear nucleus" (Tin). For comparison, two gene lists with the keywords "auditory perception" (AP) AND "acoustic stimulation" (AcouStim) were built. The STRING protein–protein interaction (PPI) network and the Cytoscape data analyzer were used to identify the top two high-degree proteins (HDPs) and their high-score interaction proteins (HSIPs), together referred to as key proteins. The top1 key proteins of the Tin-process were BDNF, NTRK1, NTRK3, and NTF3; the top2 key proteins are FOS, JUN, CREB1, EGR1, MAPK1, and MAPK3. Highly significant GO terms in CN in tinnitus were "RNA polymerase II transcription factor complex", "late endosome", cellular response to cadmium ion", "cellular response to reactive oxygen species", and "nerve growth factor signaling pathway", indicating changes in vesicle and cell homeostasis. In contrast to the spiral ganglion, where important changes in tinnitus are characterized by processes at the level of cells, important biological changes in the CN take place at the level of synapses and transcription. [ABSTRACT FROM AUTHOR]

The investigation of gait and its neuronal correlates under more ecologically valid conditions as well as real-time feedback visualization is becoming increasingly important in neuro-motor rehabilitation research. The Gait Real-time Analysis Interactive Lab (GRAIL) offers advanced opportunities for gait and gait-related research by creating more naturalistic yet controlled environments through immersive virtual reality. Investigating the neuronal aspects of gait requires parallel recording of brain activity, such as through mobile electroencephalography (EEG) and/or mobile functional near-infrared spectroscopy (fNIRS), which must be synchronized with the kinetic and /or kinematic data recorded while walking. This proof-of-concept study outlines the required setup by use of the lab streaming layer (LSL) ecosystem for real-time, simultaneous data collection of two independently operating multi-channel EEG and fNIRS measurement devices and gait kinetics. In this context, a customized approach using a photodiode to synchronize the systems is described. This study demonstrates the achievable temporal accuracy of synchronous data acquisition of neurophysiological and kinematic and kinetic data collection in the GRAIL. By using event-related cerebral hemodynamic activity and visually evoked potentials during a start-to-go task and a checkerboard test, we were able to confirm that our measurement system can replicate known physiological phenomena with latencies in the millisecond range and relate neurophysiological and kinetic data to each other with sufficient accuracy. [ABSTRACT FROM AUTHOR]

Simple Summary: This research aims to evaluate the effectiveness of a machine learning algorithm, XGBoost, in predicting treatment recommendations for patients with hepatocellular carcinoma (HCC). The study uses clinical and imaging data from patients discussed at a multidisciplinary tumor board. The findings suggest that the algorithm can accurately predict all eight treatment recommendations made by the board, potentially aiding clinical decision-making in settings lacking subspecialty expertise. This study addresses the potential of machine learning in predicting treatment recommendations for patients with hepatocellular carcinoma (HCC). Using an IRB-approved retrospective study of patients discussed at a multidisciplinary tumor board, clinical and imaging variables were extracted and used in a gradient-boosting machine learning algorithm, XGBoost. The algorithm's performance was assessed using confusion matrix metrics and the area under the Receiver Operating Characteristics (ROC) curve. The study included 140 patients (mean age 67.7 ± 8.9 years), and the algorithm was found to be predictive of all eight treatment recommendations made by the board. The model's predictions were more accurate than those based on published therapeutic guidelines by ESMO and NCCN. The study concludes that a machine learning model incorporating clinical and imaging variables can predict treatment recommendations made by an expert multidisciplinary tumor board, potentially aiding clinical decision-making in settings lacking subspecialty expertise. [ABSTRACT FROM AUTHOR]

The mutation HBA2:c.*94A>G (AATAAA>AATAAG; rs63751269) is a 3′-UTR (3 prime untranslated region) single-nucleotide substitution in the polyadenylation (PA) signal of HBA2 (αPA:A→G). This pathogenic (CADD score, 14.92) variant is sporadic in the Arabian Peninsula. It results in inefficient mRNA processing, transcription termination, and possibly using an alternate cryptic downstream polyadenylation signal. As a result, the allele αT (or αT-Saudi) poses challenges in premarital counseling with respect to fetal risk of hemoglobin H disease. Homozygous HBA2:c.*94A>G (αTα/αTα) results in moderate-to-severe microcytosis (mean red cell volume, MCV, 55 to 65 fL), reflecting markedly impaired hemoglobin synthesis (hemoglobin H disease). Homozygous rightward −α3.7 (a 3804-neocleotide deletion allele, NM_000517.4:c.[-2_-3delAC; −α3.7]), on the other hand, results in mild microcytosis (MCV, 70 to 75 fL, alpha-thalassemia trait). Thus, HBA2:c.*94A>G is more damaging than −α3.7. Consistently, the value of MCV in compound heterozygosity, HBA2:c.*94A>G and −α3.7, is 65 to 70 fL. We report here a healthy couple who presented for premarital counseling on their hemoglobinopathy. The man has homozygous HBA2:c.*94A>G (αTα/αTα), and the woman has compound heterozygous (−α3.7/αTα, also annotated as: −3.7α/αTα). As a result, the genotype of their offspring would be that of the father (αTα/αTα) or the mother (−α3.7/αTα). The counseling was mainly based on the benign phenotypes of the parents. As both were asymptomatic and their anemia was clinically insignificant, they proceeded with the marriage. [ABSTRACT FROM AUTHOR]

Participant movement is a major source of artifacts in functional near-infrared spectroscopy (fNIRS) experiments. Mitigating the impact of motion artifacts (MAs) is crucial to estimate brain activity robustly. Here, we suggest and evaluate a novel application of the nonlinear Hammerstein–Wiener model to estimate and mitigate MAs in fNIRS signals from direct-movement recordings through IMU sensors mounted on the participant's head (head-IMU) and the fNIRS probe (probe-IMU). To this end, we analyzed the hemodynamic responses of single-channel oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) signals from 17 participants who performed a hand tapping task with different levels of concurrent head movement. Additionally, the tapping task was performed without head movements to estimate the ground-truth brain activation. We compared the performance of our novel approach with the probe-IMU and head-IMU to eight established methods (PCA, tPCA, spline, spline Savitzky–Golay, wavelet, CBSI, RLOESS, and WCBSI) on four quality metrics: SNR, △AUC, RMSE, and R. Our proposed nonlinear Hammerstein–Wiener method achieved the best SNR increase (p < 0.001) among all methods. Visual inspection revealed that our approach mitigated MA contaminations that other techniques could not remove effectively. MA correction quality was comparable with head- and probe-IMUs. [ABSTRACT FROM AUTHOR]

Acne vulgaris is a common dermatological condition that can present across different ages but predominantly affects adolescents and young adults. Characterized by various lesion types, the pathogenesis of acne is complex, involving genetic, hormonal, microbial, and inflammatory factors. This review comprehensively addresses current and emerging acne management strategies, emphasizing both topical and systemic treatments, procedural therapies, and dietary modifications. Key topical agents include retinoids, benzoyl peroxide, antibiotics, and other specialized compounds. Systemic options like antibiotics, hormonal therapies, and retinoids offer significant therapeutic benefits, particularly for moderate to severe cases. Procedural treatments such as laser devices, photodynamic therapy, chemical peels, and intralesional injections present viable alternatives for reducing acne symptoms and scarring. Emerging therapies focus on novel biologics, bacteriophages, probiotics, and peptides, providing promising future options. This review underscores the importance of personalized approaches to treatment due to the multifaceted nature of acne, highlighting the potential of innovative therapies for improving patient outcomes. [ABSTRACT FROM AUTHOR]

Cytokinins (CKs) and abscisic acid (ABA) play an important role in the life of both plants and pathogenic fungi. However, the role of CKs and ABA in the regulation of fungal growth, development and virulence has not been sufficiently studied. We compared the ability of two virulent isolates (SnB and Sn9MN-3A) and one avirulent isolate (Sn4VD) of the pathogenic fungus Stagonospora nodorum Berk. to synthesize three groups of hormones (CKs, ABA and auxins) and studied the effect of exogenous ABA and zeatin on the growth, sporulation and gene expression of necrotrophic effectors (NEs) and transcription factors (TFs) in them. Various isolates of S. nodorum synthesized different amounts of CKs, ABA and indoleacetic acid. Using exogenous ABA and zeatin, we proved that the effect of these hormones on the growth and sporulation of S. nodorum isolates can be opposite, depends on both the genotype of the isolate and on the concentration of the hormone and is carried out through the regulation of carbohydrate metabolism. ABA and zeatin regulated the expression of fungal TF and NE genes, but correlation analysis of these parameters showed that this effect depended on the genotype of the isolate. This study will contribute to our understanding of the role of the hormones ABA and CKs in the biology of the fungal pathogen S. nodorum. [ABSTRACT FROM AUTHOR]

Recently, we and others have shown that manipulating the activity of cholinergic interneurons (CIN) present in the NAc can modulate binge alcohol consumption. The present study is designed to examine the relationship between binge alcohol consumption and the activity of the CIN in real time by using an in vivo microendoscopic technique. We hypothesized that mice exposed to Drinking in the Dark (DID)—a recognized mouse model for binge drinking—would exhibit increased activity in the accumbal shell region (NAcSh). To test this hypothesis, male mice expressing Cre-recombinase in the cholinergic neurons were exposed to binge alcohol consumption (alcohol group), employing the DID method, and utilized in vivo calcium imaging to observe CIN activity in real time during alcohol consumption. The control (sucrose) group was exposed to 10% (w/v) sucrose. As compared to sucrose, mice in the alcohol group displayed a significant increase in the frequency and amplitude of discharge activity, which was measured using calcium transients in the CIN present in the NAcSh. In summary, our findings suggest that the activity of CIN in the NAcSh plays a crucial role in alcohol self-administration. These results emphasize the potential significance of targeting CIN activity as a therapeutic approach for addressing AUD. [ABSTRACT FROM AUTHOR]

Epidemiologic studies have established that mpox (formerly known as monkeypox) outbreaks worldwide in 2022–2023, due to Clade IIb mpox virus (MPXV), disproportionately affected gay, bisexual, and other men who have sex with men. More than 35% and 40% of the mpox cases suffer from co-infection with HIV and sexually transmitted infections (STIs) (e.g., Chlamydia trachomatis, Neisseria gonorrhoeae, Treponema pallidum, and herpes simplex virus), respectively. Bacterial superinfection can also occur. Co-infection of MPXV and other infectious agents may enhance disease severity, deteriorate outcomes, elongate the recovery process, and potentially contribute to the morbidity and mortality of the ensuing diseases. However, the interplays between MPXV and HIV, bacteria, other STI pathogens and host cells are poorly studied. There are many open questions regarding the impact of co-infections with HIV, STIs, or bacterial superinfections on the diagnosis and treatment of MPXV infections, including clinical and laboratory-confirmed mpox diagnosis, suboptimal treatment effectiveness, and induction of antiviral drug resistance. In this review article, we will discuss the progress and knowledge gaps in MPXV biology, antiviral therapy, pathogenesis of human MPXV and its co-infection with HIV, STIs, or bacterial superinfections, and the impact of the co-infections on the diagnosis and treatment of mpox disease. This review not only sheds light on the MPXV infection and co-infection of other etiologies but also calls for more research on MPXV life cycles and the molecular mechanisms of pathogenesis of co-infection of MPXV and other infectious agents, as well as research and development of a novel multiplex molecular testing panel for the detection of MPXV and other STI co-infections. [ABSTRACT FROM AUTHOR]

Concerns over both water quality and quantity continue to increase globally. As the need for useable and potable water becomes more of a widespread issue, there is an opportunity to review and consider alternatives to how water is used, consumed, and sustained for future use by the world's population. A review of data across cities within North America shows improvement opportunities in water infrastructure systems. Using water audit and loss control data from the American Water Works Association (AWWA) and the Water Research Foundation (WRF), an analysis is provided to define opportunities for mitigating water losses among select North American Water Infrastructure systems in the U.S. states of Georgia and California. The research methodology used includes statistical analysis data while grouping utility sizes to identify utility cost opportunities. Variables on water loss and customer cost that have a positive impact on overall and long-term water system sustainability are identified. The analysis shows California, while having firm water guidance and higher rates compared to Georgia, also demonstrates less overall water loss. The results of the analysis are presented, showing comparison characteristics and opportunities for additional change to improve utility funding. [ABSTRACT FROM AUTHOR]

Real estate developers typically assess potential projects using feasibility analyses and industry-standard heuristics, which include capital costs, return on costs, and a subjective risk measure. This study explores real estate developers' decision-making practices in selecting hurdle rates and common feasibility analysis techniques, surveying 225 Australian and New Zealand developers. The main findings are that most developers use specific 'go/no-go' hurdle rate mechanisms irrespective of primary real estate type, with the majority using margin on development cost (MDC) or internal rate of return (IRR); the boundaries between traditional speculative development and real estate investment through the use of securitization methods have become blurred; many developers use both quantitative metrics, with qualitative methods and specific structural checks to manage the risks involved; and the two most frequent methods of determining site value prior to acquisition are the residual land value and discounted cash flow methods. Most place a heavy reliance on industry-accepted heuristics and do not have a predetermined process and method for altering or adapting the chosen hurdle rates and benchmarks. This research provides a contribution to property development practice from the Antipodean perspective which until now has been more focused on the UK view, enabling more generalized application internationally. [ABSTRACT FROM AUTHOR]