Search Results (17)

Hurricanes and flooding events substantially elevate indoor fungal spore levels, which have been associated with increased risks of developing childhood asthma and other adverse respiratory outcomes. Although environmental fungal compositions following major hurricanes have been well characterized, the fungal communities within the nasal cavity (i.e., the nasal mycobiome) of exposed individuals remain unexplored. We collected nasal swab samples from infants following Hurricane Maria in San Juan, Puerto Rico, during two periods (March to August 2018 and February to September 2019). We processed a total of 58 samples (26 from the first year and 32 from the second year post-Hurricane Maria) and performed internally transcribed spacer (ITS) rRNA gene sequencing to characterize and compare the infant nasal mycobiome between the two groups. Although alpha-diversity did not differ significantly, beta-diversity analyses revealed significantly different fungal compositions between the two groups (p <0.01). Infants exposed during the first year post-Hurricane Maria had significantly higher abundances of Alternaria, Eutypella, Schizophyllum, and Auricularia, compared to infants from the second year. Alternaria was also more prevalent in the first-year than in the second-year infants (42% vs. 9%, p = 0.01). Our study provides evidence linking early-life hurricane exposures to elevated risks of developing childhood asthma. Full article

Background: Parkinson’s disease (PD) is one of the most prevalent, widespread, and intricate neurodegenerative disorders. According to the experts, at least 1% of people over the age of 60 are affected worldwide. In the present time, the early detection of PD remains difficult due to the absence of a clear consensus on its brain characterization. Therefore, there is an urgent need for a more reliable and efficient technique for early detection of PD. Using the potential of electroencephalogram (EEG) signals, this study introduces an innovative method for the detection or classification of PD patients through machine learning, as well as a more accurate deep learning approach. Methods: We propose an innovative EEG-based PD detection approach by integrating advanced spectral feature engineering with machine learning and deep learning models. Using (a) the UC San Diego Resting State EEG dataset and (b) IOWA dataset, we extract a standardized EEG feature from five key frequency bands—alpha, beta, theta, gamma, delta ($\alpha ,\beta ,\theta ,\gamma ,\delta$) and employ an SVM (Support Vector Machine) classifier as a baseline, achieving a notable accuracy. Furthermore, we implement a deep learning classifier (CNN) with a complex multi-dimensional feature set by combining power values from all frequency bands, which gives superior performance in distinguishing PD patients (both with medication and without medication states) from healthy patients. Results: With the five-fold cross-validation on these two datasets, our approaches successfully achieve promising results in a subject dependent scenario. The SVM classifier achieves competitive accuracies of 82% and 94% in the UC San Diego Resting State EEG dataset (using gamma band) and IOWA dataset, respectively in distinguishing PD patients from non-PD patients in subject. With the CNN classifier, our model is able to capture major cross-frequency dependencies of EEG; therefore, the classification accuracies reach beyond 96% and 99% with those two datasets, respectively. We also perform our experiments in a subject independent environment, where the SVM generates 68.09% accuracy. Conclusions: Our findings, coupled with advanced feature extraction and deep learning, have the potential to provide a non-invasive, efficient, and reliable approach for diagnosing PD, with further work aimed at enhancing feature sets, inclusion of a large number of subjects, and improving model generalizability across more diverse environments. Full article

Gwakhyangjeonggi-san (GJS) is a traditional herbal medicine used in East Asia for the treatment of symptoms involving lower intestinal abnormalities; however, the effects of GJS on innate immunity and its cellular mechanisms of action have not been elucidated. In this study, we assessed the immune-enhancing activity and underlying mechanisms of GJS using RAW 264.7 murine macrophages. The results showed that GJS treatment significantly increased the secretion of nitric oxide and cytokines and their mRNA expression in macrophage RAW 264.7 cells without causing cytotoxicity. GJS treatment also significantly increased the production of reactive oxygen species, as well as inducing phagocytic activity, adhesion function, and migration ability, all of which improved the immune response. In addition, GJS activated nuclear factor-κB by promoting the phosphorylation and degradation of inhibitor of nuclear factor-κB alpha. Furthermore, GJS markedly increased the phosphorylation of mitogen-activated protein kinase in RAW 264.7 cells. These findings indicate that GJS has potential value as a dietary supplement for strengthening immunity. Full article

(1) Background: Neurofeedback training (NFT) has emerged as a promising approach for enhancing cognitive functions and reducing anxiety, yet its specific impact on university student populations requires further investigation. This study aims to examine the effects of NFT on working memory improvement and anxiety reduction within this demographic. (2) Methods: A total of forty healthy university student volunteers were randomized into two groups: an experimental group that received NFT and a control group. The NFT protocol was administered using a 14-channel Emotiv Epoc X headset (EMOTIV, Inc., San Francisco, CA 94102, USA) and BrainViz software version Brain Visualizer 1.1 (EMOTIV, Inc., San Francisco, CA 94102, USA), focusing on the alpha frequency band to target improvements in working memory and reductions in anxiety. Assessment tools, including the Corsi Block and Memory Span tests for working memory and the State-Trait Anxiety Inventory-2 (STAI-2) for anxiety, were applied pre- and post-intervention. (3) Results: The findings indicated an increase in alpha wave amplitude in the experimental group from the second day of NFT, with statistically significant differences observed on days 2 (p < 0.05) and 8 (p < 0.01). Contrary to expectations based on the previous literature, the study did not observe a concurrent positive impact on working memory. Nonetheless, a significant reduction in state anxiety levels was recorded in the experimental group (p < 0.001), corroborating NFT’s potential for anxiety management. (4) Conclusions: While these results suggest some potential of the technique in enhancing neural efficiency, the variability across different days highlights the need for further investigation to fully ascertain its effectiveness. The study confirms the beneficial impact of NFT on reducing state anxiety among university students, underscoring its value in psychological and cognitive performance enhancement. Despite the lack of observed improvements in working memory, these results highlight the need for continued exploration of NFT applications across different populations and settings, emphasizing its potential utility in educational and therapeutic contexts. Full article

The development of collaborative nurse prescribing (NP) in Andalusia (Spain) in 2018 gives us the opportunity to measure the impact of this practice. Scientific evidence indicates that prescribing is not more costly when performed by nurses and, in fact, is more economical in some cases. The aim of this study is to determine the effects of NP on the effectiveness, health outcomes and adverse events related to prescribing including in the follow-up of patients treated with antivitamin K oral anticoagulants in primary care (PC) by nurses. The design is a randomized clinical trial. The population comprises 1208 anticoagulated patients in 2019. The sample size calculation considers an alpha error of 0.05, a power of 99% and an effect size of 0.5, resulting in 127 users per group. Therefore, a total sample of 254 participants is needed. However, as the project intends to treat patients it will include the universal sample that meets the criteria in the two health centers participating in the study, with 575 participants in total. Data collection was carried out in the PC District of the Alamillo-San Jerónimo Clinical Management Unit of Sevilla for one year from January 2020. Data analysis is performed using the SPSS Statistics 25 package. We intend to study if nurse collaborative prescription in the follow-up and management of patients taking antivitamin K oral anticoagulants in PC is as effective as the traditional approach to follow-ups carried out by a family physician. Full article

Disinfection of alginate impressions used in dental prosthetics is a very problematic procedure, during which the dimensions of the obtained model can change, and it can be easily mechanically damaged. Therefore, it would be beneficial to create a material with bacteriostatic properties for this application. In this work, we investigated alginate materials with the addition of 0.25–1.0 wt% of zirconium phosphate-based ion exchange resin containing silver and compared them with commercial alginate impression products. The obtained materials passed the normative requirements of ISO 21563:2021 (setting time, elastic recovery, strain in compression, compatibility with gypsum, detail reproduction, tearing strength, and linear dimensional change) as well as bacteriostatic properties in relation to Streptococcus mutans. The newly developed alginate materials met all the properties required by the standards. Their setting time was comparable to the commercial materials, and their 24 h contraction did not exceed 1.3%. Furthermore, the tearing strength was 0.42–0.48 MPa, less than that of the comparative commercial materials (0.52–0.56 MPa). From the point of view of clinical practice, it will be possible to create an alginate material with bacteriostatic properties that will prevent the transmission of cross-infections. Full article

The impact of SARS-CoV-2 variants on maternal and neonatal outcomes during pregnancy is still poorly understood, and the emergence of different variants has further complicated our understanding of the virus’s effects. This retrospective, monocentric study aimed to fill this knowledge gap by analyzing the outcomes of pregnant women with acute SARS-CoV-2 infection caused by the Alpha, Delta, and Omicron variants. The study, conducted between December 2020 and March 2022 at San Marco Hospital, included 313 pregnant women with confirmed SARS-CoV-2 infection. The results showed that the Delta variant was associated with a significantly higher incidence of adverse outcomes, such as premature births, maternal intensive care unit admission, intrauterine growth restriction, and small for gestational age infants. Additionally, the Delta variant was linked to lower Apgar scores, higher maternal and fetal mortality rates, and increased levels of various biomarkers indicating more severe illness. Finally, the Delta variant also presented a greater possibility of vertical transmission. These findings underscore the complexity of understanding the impact of SARS-CoV-2 on pregnancy outcomes, especially considering the distinctive characteristics of different variants. By better understanding the specific impacts of each variant, appropriate preventive measures and management strategies can be implemented to optimize maternal and neonatal outcomes. Full article

(1) Background: Gastrointestinal pain and fatigue are the most reported concerns of patients with inflammatory bowel disease (IBD). Commonly prescribed drugs focus on decreasing excessive inflammation. However, up to 20% of IBD patients in an “inactive” state experience abdominal pain. The medicinal herb Ojeok-san (OJS) has shown promise in the amelioration of visceral pain. However, no research on OJS has been conducted in preclinical models of IBD. The mechanism by which OJS promotes analgesia is still elusive, and it is unclear if OJS possesses addictive properties. (2) Aims: In this study, we examined the potential of OJS to promote analgesic effects and rewarding behavior. Additionally, we investigated if tumor necrosis factor alpha (TNFα) from macrophages is a primary culprit of IBD-induced nociception. (3) Methods: Multiple animal models of IBD were used to determine if OJS can reduce visceral nociception. TNFα-macrophage deficient mice were used to investigate the mechanism of action by which OJS reduces nociceptive behavior. Mechanical sensitivity and operant conditioning tests were used to determine the analgesic and rewarding effects of OJS. Body weight, colon length/weight, blood in stool, colonic inflammation, and complete blood count were assessed to determine disease progression. (4) Results: OJS reduced the evoked mechanical nociception in the dextran sulphate sodium model of colitis and IL-10 knockout (KO) mice and delayed aversion to colorectal distension in C57BL/6 mice. No rewarding behavior was observed in OJS-treated IL-10 KO and mdr1a KO mice. The analgesic effects of OJS are independent of macrophage TNFα levels and IBD progression. (5) Conclusions: OJS ameliorated elicited mechanical and visceral nociception without producing rewarding effects. The analgesic effects of OJS are not mediated by macrophage TNFα. Full article

Aquatic beetle diversity was compared between three study sites in the state of Tlaxcala, central Mexico: Stream 1 (San Ambrosio), stream 2 (San Tadeo), and a lake (Acuitlapilco). Sampling took place bimonthly during an annual cycle. A total of 2968 specimens were obtained, which were grouped into twenty three species, fifteen genera, and six families (Elmidae, Dryopidae, Dytiscidae, Gyrinidae, Haliplidae, and Hydrophilidae). Stream 2 showed the highest values of abundance (1570 individuals), while stream 1 had the highest richness (18 species). Abundance values showed two peaks each in rainy and dry seasons. The proportion of rare and dominant species was similar in all study sites. Based on species accumulation curves, the maximum estimated number of species has not been achieved in either of the three sites. Regarding alpha diversity (effective number of species), stream 1 presented the highest zero-order diversity estimated with 18.5 species. Regarding beta diversity, lotic systems (streams 1 and 2) presented a similarity of 75%. Finally, regarding the trophic structure of the adult aquatic beetle community, herbivores, predators, and decomposers were most representative in this study. Based on our results, Tlaxcala probably holds a significant diversity of aquatic beetles. This appears to indicate that species composition in geographic areas, regardless of their relatively small size, is worth documenting and, of course, preserving. Full article

Background and Objectives: The Temperament Evaluation of Memphis, Pisa, Paris and San Diego Autoquestionnaire (TEMPS-A) is designed to assess affective temperaments. The short version of the TEMPS-A (TEMPS-A-SV) has been translated into various languages for use in research and clinical settings. However, no research has been conducted to validate the Korean version of the TEMPS-A-SV in patients with mood disorders. The goal of this study is to evaluate the reliability and validity of the TEMPS-A-SV in Korean mood disorder patients. Materials and Methods: In this cross-sectional retrospective study, a total of 715 patients (267 patients with major depressive disorder, 94 patients with bipolar disorder I, and 354 patients with bipolar disorder II) completed the Korean TEMPS-A-SV. Cronbach’s alpha and McDonald’s omega were used to assess the reliability. Exploratory factor analysis (EFA) was also performed. Spearman’s correlation coefficient was used to examine associations between the five temperaments. The difference in five temperament scores between the gender or diagnosis groups was analyzed, and the correlation between five temperament scores and age was tested. Results: The Korean TEMPS-A-SV displayed good internal consistency (α = 0.65–0.88, ω = 0.66–0.9) and significant correlations between the subscales except one (the correlation between hyperthymic and anxious). Using EFA, a two-factor structure was produced: Factor I (cyclothymic, depressive, irritable, and anxious) and Factor II (hyperthymic). The cyclothymic temperament score differed by gender and the anxious temperament score was significantly correlated with age. All the temperaments, except for irritable temperament, showed significant differences between diagnosis groups. Conclusions: Overall, the results show that the TEMPS-A-SV is a reliable and valid measurement that can be used for estimating Koreans’ affective temperaments. However, more research is required on affective temperaments and associated characteristics in people with mood disorders. Full article

The San Carlos Gestational Diabetes Mellitus (GDM) prevention study, a nutritional intervention RCT based on a Mediterranean Diet (MedDiet), has been shown to reduce the incidence of GDM. The objective of this study is to investigate the relationship of leptin, adiponectin, interleukin-6 (IL-6), tumour necrosis factor-alpha (TNF-α), insulin and HOMA-IRand circulating miRNAs (miR-29a-3p, miR-103a-3p, miR-132-3p, miR-222-3p) with the appearance of GDM and with MedDiet-based nutritional intervention, at 24–28 gestational weeks (GW), and in glucose regulation 2–3 years post-delivery (PD). A total of 313 pregnant women, 77 with GDM vs. 236 with normal glucose tolerance (NGT), 141 from the control group (CG, MedDiet restricting the consumption of dietary fat including EVOO and nuts during pregnancy) vs. 172 from the intervention group (IG, MedDiet supplemented with extra virgin olive oil (EVOO) and pistachios during pregnancy) were compared at Visit 1 (8–12 GW), Visit 2 (24–28 GW) and Visit 3 (2–3 years PD). Expression of miRNAs was determined by the Exiqon miRCURY LNA RT-PCR system. Leptin, adiponectin, IL-6 and TNF-α, were measured by Milliplex^® immunoassays on Luminex 200 and insulin by RIA. Women with GDM vs. NTG had significantly higher leptin median (Q1–Q3) levels (14.6 (9.2–19.4) vs. 9.6 (6.0–15.1) ng/mL; p < 0.05) and insulin levels (11.4 (8.6–16.5) vs. 9.4 (7.0–12.8) µUI/mL; p < 0.001) and lower adiponectin (12.9 (9.8–17.2) vs. 17.0 (13.3–22.4) µg/mL; p < 0.001) at Visit 2. These findings persisted in Visit 3, with overexpression of miR-222-3p (1.45 (0.76–2.21) vs. 0.99 (0.21–1.70); p < 0.05)) and higher levels of Il-6 and TNF-α. When the IG is compared with the CG lower levels of insulin, HOMA-IR-IR, IL-6 levels at Visit 2 and 3 and leptin levels only at Visit 2 were observed. An overexpression of miR-222-3p and miR-103a-3p were also observed in IG at Visit 2 and 3. The miR-222-3p and miR103a-3p expression correlated with insulin levels, HOMA-IR, IL-6 and TNF-α at Visit 2 (all p < 0.05). These data support the association of leptin, adiponectin and insulin/HOMA-IR with GDM, as well as the association of insulin/HOMA-IR and IL-6 and miR-222-3p and miR-103a-3p expression with a MedDiet-based nutritional intervention. Full article

Parkinson’s disease (PD) is a very common brain abnormality that affects people all over the world. Early detection of such abnormality is critical in clinical diagnosis in order to prevent disease progression. Electroencephalography (EEG) is one of the most important PD diagnostic tools since this disease is linked to the brain. In this study, novel efficient common spatial pattern-based approaches for detecting Parkinson’s disease in two cases, off–medication and on–medication, are proposed. First, the EEG signals are preprocessed to remove major artifacts before spatial filtering using a common spatial pattern. Several features are extracted from spatially filtered signals using different metrics, namely, variance, band power, energy, and several types of entropy. Machine learning techniques, namely, random forest, linear/quadratic discriminant analysis, support vector machine, and k-nearest neighbor, are investigated to classify the extracted features. The impacts of frequency bands, segment length, and reduction number on the results are also investigated in this work. The proposed methods are tested using two EEG datasets: the SanDiego dataset (31 participants, 93 min) and the UNM dataset (54 participants, 54 min). The results show that the proposed methods, particularly the combination of common spatial patterns and log energy entropy, provide competitive results when compared to methods in the literature. The achieved results in terms of classification accuracy, sensitivity, and specificity in the case of off-medication PD detection are around 99%. In the case of on-medication PD, the results range from 95% to 98%. The results also reveal that features extracted from the alpha and beta bands have the highest classification accuracy. Full article

In Europe and the United States, approximately 1100 and 1800 liver transplantations, respectively, are performed every year for hepatocellular carcinoma (HCC), compared with an annual incidence of 65,000 and 39,000 new cases, respectively. Because of organ shortages, proper patient selection is crucial, especially for those exceeding the Milan criteria. Downstaging is the reduction of the HCC burden to meet the eligibility criteria for liver transplantation. Many techniques can be used in downstaging, including ablation, chemoembolisation, radioembolisation and systemic treatments, with a reported success rate of 60–70%. In recent years, an increasing number of patient responders to downstaging procedures has been included in the waitlist, generally with a comparable five-year post-transplant survival but with a higher probability of dropout than HCC patients within the Milan criteria. While the Milan criteria are generally accepted as the endpoint of downstaging, the upper limits of tumour burden for downstaging HCC for liver transplantation are controversial. Very challenging situations involve HCC patients with large nodules, macrovascular invasion or even extrahepatic metastasis at baseline who respond to increasingly more effective downstaging procedures and who aspire to be placed on the waitlist for transplantation. This narrative review analyses the most important evidence available on cohorts subjected to “extended” downstaging, including HCC patients over the up-to-seven criteria and over the University of California San Francisco downstaging criteria. We also address surrogate markers of biological aggressiveness, such as alpha-fetoprotein and the response stability to locoregional treatments, which are very useful in selecting responders to downstaging procedures for waitlisting inclusion. Full article

Several models have been developed using conventional regression approaches to extend the criteria for liver transplantation (LT) in hepatocellular carcinoma (HCC) beyond the Milan criteria. We aimed to develop a novel model to predict tumor recurrence after LT by adopting artificial intelligence (MoRAL-AI). This study included 563 patients who underwent LT for HCC at three large LT centers in Korea. Derivation (n = 349) and validation (n = 214) cohorts were independently established. The primary outcome was time-to-recurrence after LT. A MoRAL-AI was derived from the derivation cohort with a residual block-based deep neural network. The median follow-up duration was 74.7 months (interquartile-range, 18.5–107.4); 204 patients (36.2%) had HCC beyond the Milan criteria. The optimal model consisted of seven layers including two residual blocks. In the validation cohort, the MoRAL-AI showed significantly better discrimination function (c-index = 0.75) than the Milan (c-index = 0.64), MoRAL (c-index = 0.69), University of California San Francisco (c-index = 0.62), up-to-seven (c-index = 0.50), and Kyoto (c-index = 0.50) criteria (all p < 0.001). The largest weighted parameter in the MoRAL-AI was tumor diameter, followed by alpha-fetoprotein, age, and protein induced by vitamin K absence-II. The MoRAL-AI had better predictability of tumor recurrence after LT than conventional models. The MoRAL-AI can also evolve with further data. Full article

Background: In traditional Chinese medicine, the Shugan-Jianpi recipe is often used in the treatment of nonalcoholic fatty liver disease (NAFLD). This study aimed to explore the mechanism of the Shugan-Jianpi recipe in relation to rats with NAFLD induced by a high-fat diet. Methods: Rats were randomly divided into eight groups: normal group (NG), model group (MG), low-dose Chaihu–Shugan–San group (L-CG), high-dose Chaihu–Shugan–San group (H-CG), low-dose Shenling–Baizhu–San group (L-SG), high-dose Shenling–Baizhu–San group (H-SG), low dose of integrated-recipes group (L-IG), and high dose of integrated-recipes group (H-IG). After 26 weeks, a lipid profile, aspartate, and alanine aminotransferases in serum were detected. The serum levels of inflammatory factors including interleukin (IL)-1β, IL-6, and tumor necrosis factor-alpha (TNF-α) were analyzed using the enzyme linked immunosorbent assay (ELISA) method. Hepatic pathological changes were observed with hematoxylin-eosin (HE) and oil red O staining. The expression of the p38 mitogen-activated protein kinases (MAPK)/nuclear factor-κB (NF-κB) pathway was detected by quantitative real-time PCR and Western blotting. Results: A pathological section revealed that NAFLD rats have been successfully reproduced. Compared with the model group, each treatment group had different degrees of improvement. The Shugan-Jianpi recipe can inhibit the serum levels of IL-1β, IL-6, and TNF-α in NAFLD rats. The expression of mRNA and a protein related to the p38 MAPK/NF-κB signaling pathway were markedly decreased as a result of the Shugan-Jianpi recipe. Conclusions: The Shugan-Jianpi recipe could attenuate NAFLD progression, and its mechanism may be related to the suppression of the p38 MAPK/NF-κB signaling pathway in hepatocytes. Full article