In vitro and in silico studies of the acaricidal and anticholinesterase activities of Randia aculeata seeds against the southern cattle tick Rhipicephalus (Boophilus) microplus.

Rhipicephalus (Boophilus) microplus is a leading cause of significant economic losses in the livestock industry, and tick populations have developed multiple forms of resistance to acaricides; therefore, the potential of novel natural bioactive compounds that are effective for targeting ticks must be addressed. The aim of this study was to evaluate the acaricidal and anticholinesterase activities of R. aculeata seeds and to identify naturally occurring compounds that potentially inhibit anticholinesterase through in silico docking. The acaricidal activity of the extract of R. aculeata seeds against larval and adult R. microplus ticks was assessed through immersion tests. Inhibition of anticholinesterase activity was measured spectrophotometrically. Extracts of R. aculeata seeds showed activity against larvae and engorged females of R. microplus, and a reduction in the reproductive index were also observed. Rutin, chlorogenic acid, quercetin, and epicatechin exhibited noteworthy interactions with the active site residues of RmAChE. These findings could significantly contribute to the exploration of novel natural products that can potentially inhibit RmAChE and could be used in the development of new acaricides for tick control.

An innovative 12-lead resting electrocardiogram dataset in professional football.

This paper aims to provide a comprehensive and innovative 12-lead electrocardiogram (ECG) dataset tailored to understand the unique needs of professional football players. Other ECG datasets are available but collected from common people, normally with diseases confirmed, while it is well known that ECG characteristics change in athletes and elite players as a result of their intense long-term physical training. This initiative is part of a broader research project employing machine learning (ML) to analyse ECG data in this athlete population and explore them according to the International criteria for ECG interpretation in athletes. The dataset is generated through the establishment of a prospective observational cohort consisting of 54 male football players from La Liga, representing a UEFA Pro-level team. Named the Pro-Football 12-lead Resting Electrocardiogram Database (PF12RED), it comprises 163 10-s ECG recordings, offering a detailed examination of the at-rest heart activity of professional football athletes. Data collection spans five phases over multiple seasons, including the 2018-2019 postseason, the 2019-20 preseason, the 2020-21 preseason, and the 2021-22 preseason. Athletes undergo medical evaluations that include a 10-s resting 12-lead ECG performed with General Electric's USB-CAM 14 module (https://co.services.gehealthcare.com/gehcstorefront/p/900995-002), with data saved using General Electric's CardioSoft V6.73 12SL V21 ECG Software. (https://www.gehealthcare.es/products/cardiosoft-v7) The data collection adheres to ethical principles, with clearance granted by the Autonomous Community of Andalusia Ethics Committee (Spain) under protocol number 1573-N-19 in December 2019. Participants provide informed consent, and data sharing is permitted following anonymization. The study aligns with the Declaration of Helsinki and adheres to the recommendations of the International Committee of Medical Journal Editors (ICMJE). The generated dataset serves as a valuable resource for research in sports cardiology and cardiac health. Its potential for reuse encompasses:1.International Comparison: Enabling cross-regional comparisons of cardiac characteristics among elite football players, enriching international studies.2.ML Model Development: Facilitating the development and refinement of machine learning models for arrhythmia detection, serving as a benchmark dataset.3.Validation of Diagnostic Methods: Allowing the validation of automatic diagnostic methods, contributing to enhanced accuracy in detecting cardiac conditions.4.Research in Sports Cardiology: Supporting future investigations into specific cardiac adaptations in elite athletes and their relation to cardiovascular health.5.Reference for Athlete Protection Policies: Influencing athlete protection policies by providing data on cardiac health and suggesting guidelines for medical assessments.6.Health Professionals Training: Serving as a training resource for health professionals interested in interpreting ECGs in sports contexts.7.Tool and Application Development: Facilitating the development of tools and applications related to the visualization, simulation and analysis of ECG signals in athletes.

Comparing the clinical applicability of wavefront phase imaging in keratoconus versus normal eyes.

The aim of this work is to quantitatively assess the wavefront phase of keratoconic eyes measured by the ocular aberrometer t·eyede (based on WaveFront Phase Imaging Sensor), characterized by a lateral resolution of 8.6 µm without requiring any optical element to sample the wavefront information. We evaluated the parameters: root mean square error, Peak-to-Valley, and amplitude of the predominant frequency (Fourier Transform analysis) of a section of the High-Pass filter map in keratoconic and healthy cohorts. Furthermore, we have analyzed keratoconic eyes that presented dark-light bands in this map to assess their period and orientation with the Fourier Transform. There are significant statistical differences (p value < 0.001) between healthy and keratoconic eyes in the three parameters, demonstrating a tendency to increase with the severity of the disease. Otherwise, the quantification of the bands reveals that the width is independent of eye laterality and keratoconic stage as orientation, which tends to be oblique. In conclusion, the quantitative results obtained with t·eyede could help to diagnose and monitor the progression of keratoconus.

Correction: Unbridled Threat of Gas Gangrene in a Patient With Uncontrolled Diabetes Mellitus: A Compelling Case Report of Clostridium perfringens Infection.

[This corrects the article DOI: 10.7759/cureus.50614.].

Correction: Wunderlich Syndrome in a Patient With Type 1 Diabetes Mellitus: Surgical Challenges and Management Strategies.

[This corrects the article DOI: 10.7759/cureus.50481.].

Simultaneous detection of mycotoxins and pesticides in human urine samples: A 24-h diet intervention study comparing conventional and organic diets in Spain.

Pesticides and mycotoxins, prominent chemical hazards in the food chain, are commonly found in plant-based foods, contributing to their pervasive presence in the human body, as evidenced by biomonitoring programs. Despite this, there is limited knowledge about their co-occurrence patterns. While intervention studies have demonstrated that organic diets can significantly reduce pesticide levels, their impact on mycotoxin exposure has been overlooked. To address this gap, this study pursued two objectives: first, to characterize the simultaneous presence of mycotoxins and pesticides in human urine samples by means of the control of the biomarkers of exposure, and second, to investigate the influence of consuming organic foods on these co-exposure patterns. A pilot study involving 20 healthy volunteers was conducted, with participants consuming either exclusively organic or conventional foods during a 24-h diet intervention in autumn 2021 and spring 2022 to account for seasonal variability. Participants provided detailed 24-h dietary records, and their first-morning urine samples were collected, minimally treated and analysed using LC-Q-ToF-MS by means of a multitargeted method in order to detect the presence of these residues. Results indicated that among the 52 screened compounds, four mycotoxins and seven pesticides were detected in over 25% of the samples. Deoxynivalenol (DON) and the non-specific pesticide metabolite diethylphosphate (DEP) exhibited the highest frequency rates (100%) and concentration levels. Correlations were observed between urine levels of mycotoxins (DON, ochratoxin alpha [OTα], and enniatin B [ENNB]) and organophosphate pesticide metabolites DEP and 2-diethylamino-6-methyl-4-pyrimidinol (DEAMPY). The pilot intervention study suggested a reduction in ENNB and OTα levels and an increase in ß-zearalenol levels in urine after a short-term replacement with organic food. However, caution is advised due to the study's small sample size and short duration, emphasizing the need for further research to enhance understanding of the human chemical exposome and refine chemical risk assessment.

Association of CYP3A4-392A/G, CYP3A5-6986A/G, and ABCB1-3435C/T Polymorphisms with Tacrolimus Dose, Serum Concentration, and Biochemical Parameters in Mexican Patients with Kidney Transplant.

Tacrolimus (TAC) is an immunosuppressant drug that prevents organ rejection after transplantation. This drug is transported from cells via P-glycoprotein (ABCB1) and is a metabolic substrate for cytochrome P450 (CYP) 3A enzymes, particularly CYP3A4 and CYP3A5. Several single-nucleotide polymorphisms (SNPs) have been identified in the genes encoding CYP3A4, CYP3A5, and ABCB1, including CYP3A4-392A/G (rs2740574), CYP3A5 6986A/G (rs776746), and ABCB1 3435C/T (rs1045642). This study aims to evaluate the association among CYP3A4-392A/G, CYP3A5-6986A/G, and ABCB1-3435C/T polymorphisms and TAC, serum concentration, and biochemical parameters that may affect TAC pharmacokinetics in Mexican kidney transplant (KT) patients. METHODS: Forty-six kidney transplant recipients (KTR) receiving immunosuppressive treatment with TAC in different combinations were included. CYP3A4, CYP3A5, and ABCB1 gene polymorphisms were genotyped using qPCR TaqMan. Serum TAC concentration (as measured) and intervening variables were assessed. Logistic regression analyses were performed at baseline and after one month to assess the extent of the association between the polymorphisms, intervening variables, and TAC concentration. RESULTS: The GG genotype of CYP3A5-6986 A/G polymorphism is associated with TAC pharmacokinetic variability OR 4.35 (95%CI: 1.13-21.9; p = 0.0458) at one month of evolution; in multivariate logistic regression, CYP3A5-6986GG genotype OR 9.32 (95%CI: 1.54-93.08; p = 0.028) and the use of medications or drugs that increase serum TAC concentration OR 9.52 (95%CI: 1.79-88.23; p = 0.018) were strongly associated with TAC pharmacokinetic variability. CONCLUSION: The findings of this study of the Mexican population showed that CYP3A5-6986 A/G GG genotype is associated with a four-fold increase in the likelihood of encountering a TAC concentration of more than 15 ng/dL. The co-occurrence of the CYP3A5-6986GG genotype and the use of drugs that increase TAC concentration correlates with a nine-fold increased risk of experiencing a TAC at a level above 15 ng/mL. Therefore, these patients have an increased susceptibility to TAC-associated toxicity.

Classification of skin blemishes with cell phone images using deep learning techniques.

Skin blemishes can be caused by multiple events or diseases and, in some cases, it is difficult to distinguish where they come from. Therefore, there may be cases with a dangerous origin that go unnoticed or the opposite case (which can lead to overcrowding of health services). To avoid this, the use of artificial intelligence-based classifiers using images taken with mobile devices is proposed; this would help in the initial screening process and provide some information to the patient prior to their final diagnosis. To this end, this work proposes an optimization mechanism based on two phases in which a global search for the best classifiers (from among more than 150 combinations) is carried out, and, in the second phase, the best candidates are subjected to a phase of evaluation of the robustness of the system by applying the cross-validation technique. The results obtained reach 99.95% accuracy for the best case and 99.75% AUC. Comparing the developed classifier with previous works, an improvement in terms of classification rate is appreciated, as well as in the reduction of the classifier complexity, which allows our classifier to be integrated in a specific purpose system with few computational resources.

Characterization of the iron-sulfur clusters in the nitrogenase-like reductase CfbC/D required for coenzyme F430 biosynthesis.

Coenzyme F430 is a nickel-containing tetrapyrrole, serving as the prosthetic group of methyl-coenzyme M reductase in methanogenic and methanotrophic archaea. During coenzyme F430 biosynthesis, the tetrapyrrole macrocycle is reduced by the nitrogenase-like CfbC/D system consisting of the reductase component CfbC and the catalytic component CfbD. Both components are homodimeric proteins, each carrying a [4Fe-4S] cluster. Here, the ligands of the [4Fe-4S] clusters of CfbC2 and CfbD2 were identified revealing an all cysteine ligation of both clusters. Moreover, the midpoint potentials of the [4Fe-4S] clusters were determined to be -256 mV for CfbC2 and -407 mV for CfbD2. These midpoint potentials indicate that the consecutive thermodynamically unfavorable 6 individual "up-hill" electron transfers to the organic moiety of the Ni2+-sirohydrochlorin a,c-diamide substrate require an intricate interplay of ATP-binding, hydrolysis, protein complex formation and release to drive product formation, which is a common theme in nitrogenase-like systems.

Relationship between Depressive Symptoms, Caregiver Strain, and Social Support with Dementia Grief in Family Caregivers.

Background and Objectives: Dementia grief in family caregivers of people with dementia refers to grieving prior to the death of the care recipient. It is related to psychosocial risk factors that may have a negative impact on the health of these family caregivers. This study aimed to describe the relationship between depressive symptoms, caregiver strain, and social support with dementia grief in family caregivers of people with dementia. Materials and Methods: A descriptive correlational cross-sectional study was conducted. A total of 250 family caregivers of people with dementia participated. Dementia grief was the main variable, and depressive symptoms, caregiver strain, and social support were assessed. Additionally, socio-demographic data were collected. Descriptive statistics were calculated, and a bivariate correlation analysis and a multiple linear regression analysis were performed for dementia grief. Results: Higher scores for dementia grief were found in women, in family caregivers of patients at advanced stages of dementia, and in family caregivers with a low level of education. High levels of depressive symptoms and caregiver strain and low levels of social support indicated greater intensity of dementia grief. Depressive symptomatology was the variable with the greatest influence on dementia grief. Caregiver strain and social support also related to dementia grief, but to a lesser extent. Conclusions: In family caregivers, depressive symptoms, caregiver strain, and social support are related to the intensity of dementia grief, with a greater influence of depressive symptoms. Moreover, being female, having a low level of education, and caring for a care recipient at an advanced stage of dementia are factors associated with increased dementia grief. Concerning study limitations, the sample was restricted, belonging to a specific region of Spain and to a Provincial Federation of associations. It is necessary to exercise caution in generalizing results due to the sociodemographic and geographical characteristics of the sample.

Personalized Management of Fatigue in Individuals With Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Long COVID Using a Smart Digital mHealth Solution: Protocol for a Participatory Design Approach.

BACKGROUND: Fatigue is the most common symptom in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID, impacting patients' quality of life; however, there is currently a lack of evidence-based context-aware tools for fatigue self-management in these populations. OBJECTIVE: This study aimed to (1) address fatigue in ME/CFS and long COVID through the development of digital mobile health solutions for self-management, (2) predict perceived fatigue severity using real-time data, and (3) assess the feasibility and potential benefits of personalized digital mobile health solutions. METHODS: The MyFatigue project adopts a patient-centered approach within the participatory health informatics domain. Patient representatives will be actively involved in decision-making processes. This study combines inductive and deductive research approaches, using qualitative studies to generate new knowledge and quantitative methods to test hypotheses regarding the relationship between factors like physical activity, sleep behaviors, and perceived fatigue in ME/CFS and long COVID. Co-design methods will be used to develop a personalized digital solution for fatigue self-management based on the generated knowledge. Finally, a pilot study will evaluate the feasibility, acceptance, and potential benefits of the digital health solution. RESULTS: The MyFatigue project opened to enrollment in November 2023. Initial results are expected to be published by the end of 2024. CONCLUSIONS: This study protocol holds the potential to expand understanding, create personalized self-management approaches, engage stakeholders, and ultimately improve the well-being of individuals with ME/CFS and long COVID. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/50157.

Clinical course and disease burden of patients with generalized pustular psoriasis in Portugal: a multicenter retrospective cohort study.

OBJECTIVES: Generalized pustular psoriasis (GPP) is a rare, life-threatening skin inflammatory disorder. This study aimed to describe the disease course, treatment strategies, and healthcare utilization among patients with GPP in Portugal. METHODS: This multicentric, observational, retrospective study included consecutive adult patients with GPP undergoing a dermatology evaluation in different reporting institutions by experienced dermatologists between 2002 and 2023. RESULTS: A total of 59 patients were assessed. Most of the cohort had a previous history of plaque psoriasis (71%) and 83% presented at least one comorbidity. At the initial encounter, 64% of the cohort needed hospitalization. Systemic involvement was common, including fever (37%), and elevated white blood cell count and erythrocyte sedimentation rate/C-reactive protein (49%). Nearly, 73% of patients initiated systemic drugs, and 70% had to discontinue the first treatment. During the study, 98% of patients experienced at least one flare. At the last visit, 3.4% of patients had died, and 71.2% exhibited signs of active disease despite undergoing treatment. CONCLUSIONS: Our study demonstrates that GPP is a chronic, debilitating condition associated with systemic involvement, frequent flares, and hospitalizations, despite receiving multiple systemic treatments. Improved disease awareness and new treatments are needed to improve patient care and decrease the burden of the disease.

One sixth of Amazonian tree diversity is dependent on river floodplains.

Amazonia's floodplain system is the largest and most biodiverse on Earth. Although forests are crucial to the ecological integrity of floodplains, our understanding of their species composition and how this may differ from surrounding forest types is still far too limited, particularly as changing inundation regimes begin to reshape floodplain tree communities and the critical ecosystem functions they underpin. Here we address this gap by taking a spatially explicit look at Amazonia-wide patterns of tree-species turnover and ecological specialization of the region's floodplain forests. We show that the majority of Amazonian tree species can inhabit floodplains, and about a sixth of Amazonian tree diversity is ecologically specialized on floodplains. The degree of specialization in floodplain communities is driven by regional flood patterns, with the most compositionally differentiated floodplain forests located centrally within the fluvial network and contingent on the most extraordinary flood magnitudes regionally. Our results provide a spatially explicit view of ecological specialization of floodplain forest communities and expose the need for whole-basin hydrological integrity to protect the Amazon's tree diversity and its function.

Machine Learning Classification of Event-Related Brain Potentials during a Visual Go/NoGo Task.

Machine learning (ML) methods are increasingly being applied to analyze biological signals. For example, ML methods have been successfully applied to the human electroencephalogram (EEG) to classify neural signals as pathological or non-pathological and to predict working memory performance in healthy and psychiatric patients. ML approaches can quickly process large volumes of data to reveal patterns that may be missed by humans. This study investigated the accuracy of ML methods at classifying the brain's electrical activity to cognitive events, i.e., event-related brain potentials (ERPs). ERPs are extracted from the ongoing EEG and represent electrical potentials in response to specific events. ERPs were evoked during a visual Go/NoGo task. The Go/NoGo task requires a button press on Go trials and response withholding on NoGo trials. NoGo trials elicit neural activity associated with inhibitory control processes. We compared the accuracy of six ML algorithms at classifying the ERPs associated with each trial type. The raw electrical signals were fed to all ML algorithms to build predictive models. The same raw data were then truncated in length and fitted to multiple dynamic state space models of order nx using a continuous-time subspace-based system identification algorithm. The 4nx numerator and denominator parameters of the transfer function of the state space model were then used as substitutes for the data. Dimensionality reduction simplifies classification, reduces noise, and may ultimately improve the predictive power of ML models. Our findings revealed that all ML methods correctly classified the electrical signal associated with each trial type with a high degree of accuracy, and accuracy remained high after parameterization was applied. We discuss the models and the usefulness of the parameterization.

The influence of carvedilol posology timing on clinically significant portal hypertension: insights from elastography measurements.

BACKGROUND AND AIMS: Carvedilol has emerged as the preferred ß-blocker for treating portal hypertension. However, there is still a debate in dosing regimen, with a potential lower bioavailability in once-daily regimens. The aim of this study is to assess the acute effects of carvedilol posology in patients with clinically significant portal hypertension (CSPH), as a surrogate marker of bioavailability. METHODS: In this experimental study, 34 patients with CSPH receiving carvedilol twice daily were asked to suppress the night dose of carvedilol, creating a standardized 24-hour dose interval. Spleen stiffness measurement (SSM) and liver stiffness measurement (LSM) by transient elastography (TE) were performed, with the exact interval between the last carvedilol administration and TE measurements consistently maintained at 24 hours and compared with values prior and under treatment. RESULTS: Thirty-four patients were included, predominantly male (82.9%). SSM after suspending carvedilol for 24 hours [mean, 73.9kPa (SD, 17.0)] was significantly higher ( P < 0.001) than under treatment [mean, 56.3kPa (SD, 13.2)] and was not significantly different ( P = 0.908) from SSM prior to introduction of carvedilol [mean, 74.5kPa (SD, 12.4)]. Differences were also found in stratified analysis for carvedilol dosage, D'Amico classification stages, MELDNa scores, MELD3.0 scores, Child-Pugh class A and CSPH due to alcoholic cirrhosis. LSM after suspension was not significantly different from both under treatment and prior to treatment. CONCLUSION: The differences in SSM after skipping one dose of carvedilol show both the importance of strict adherence to the prescribed dosing regimen to achieve the expected therapeutic benefits and the impact of twice daily prescription in bioavailability throughout the day.

Identification of keystone taxa in root canals and periapical lesions of post-treatment endodontic infections: Next generation microbiome research.

AIM: The aim of this study was to analyse and compare the microbiome present in root canals and periapical lesions of teeth with post-treatment infections, and to identify the presence of keystone taxa in both habitats using next-generation sequencing analysis. METHODOLOGY: Apices and periapical lesions of patients with post-treatment apical periodontitis were surgically extracted. Specimens were cryo-pulverized, bacterial DNA was extracted, and the V3-V4 hypervariable regions of the 16S rRNA gene were sequenced using the Illumina Miseq platform. Bioinformatic analysis was carried out with Mothur software, whilst diversity indices were obtained using operational taxonomic units (OTUs). The diversity indices were compared with the Kruskal-Wallis test, and community composition differences were explored with Permutational Multivariate Analysis of Variance (PERMANOVA). A bacterial functional study was performed with the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis. Co-occurrence network analyses were performed using the Sparse Correlations for Compositional data (SparCC). Eigencentrality, clr-based abundance and ubiquitousness were applied to infer keystone taxa. P values <.05 were considered statistically significant. RESULTS: Thirty-two apices and thirty-nine periapical lesions were sequenced and analysed. A similar alpha-diversity (p < .05) and community composition (p = .91) was observed for apices and lesion samples. The most abundant OTUs identified amongst all samples included Fusobacterium nucleatum, Prevotella loescheii, Streptococcus intermedius, Porphyromonas gingivalis, Parvimonas micra, Synergistetes bacterium, Tannerella forsythia and Peptostreptococcus stomatis. The metabolic pathways with >0.81% abundances included membrane transport, genetic information processing and metabolic pathways. F. nucleatum was identified as a keystone taxon as it showed ubiquitousness, an eigenvector centrality value of 0.83 and a clr-based abundance >4. CONCLUSIONS: The microbiome in apices and periapical lesions of post-treatment endodontic infections showed a similar diversity and taxonomic composition. Co-occurrence network analyses at OTU level identified F. nucleatum as a keystone taxon candidate in these infections.