Combined Frequency Research Articles

Novel real-time automation of combined frequency and low voltage substrate mapping to guide ablation for Brugada syndrome: a case report

Abstract Background Brugada syndrome (BrS) is an inherited cardiac condition that increases the risk of sudden cardiac death (SCD) due to ventricular arrhythmias. Catheter ablation has been shown to effectively reduce recurrent ventricular fibrillation (VF) episodes through targeting of abnormal electrograms predominantly located within the anterior surface of the right ventricular outflow tract. Signal frequency mapping is an emerging concept that provides further definition of pathological ventricular substrate. Case summary A 66-year-old male with BrS was admitted to our institution with ICD shocks for VF. Electro-anatomical mapping (EAM) and ablation was performed utilising a novel automated frequency-based strategy. Combined automated frequency and low voltage maps were generated to define high frequency, low voltage (HF-LVo) depolarisation abnormalities within the QRS complex. Low frequency, low voltage (LF-LVo) regions from the QRS terminal notch to the T-wave offset were also identified. The combined HF-LVo and LF-LVo map areas totalled 12.4cm2, compared to the conventional low voltage and late potential map areas, which were 44cm2 and 27.8cm2 respectively. The ablation strategy targeted HF-LVo and LF-LVo regions only. Following ablation, re-mapping demonstrated near complete abolition of HF-LVo and LF-LVo regions, with no inducible ventricular arrhythmias during extra-stimulation testing. During follow-up, ECG normalisation was observed, with no further ventricular arrhythmias and a negative ajmaline challenge at 6 months. Discussion Catheter ablation for BrS utilising a novel automated combined frequency and low voltage EAM approach can objectively identify relevant substrate. The results demonstrate adequate substrate modification with comparable ablation target areas to previous studies and encouraging clinical outcomes.

Multimorbidity patterns in adults admitted to hospital with heart failure: an analysis of 175 million hospitalisation episodes

Abstract Background The prevalence of heart failure (HF) is increasing as a result of population ageing, improved survival following myocardial infarction and the widespread uptake of evidence-based HF treatments. Greater understanding of multimorbidity patterns in patients with HF may enable the development of treatment strategies that target multiple, related long-term conditions (LTCs), producing synergistic benefits. Purpose To characterise multimorbidity patterns in patients with HF and compare these to a matched population without HF. Methods A retrospective matched cohort study was conducted using the United States National Readmission Database (NRD), 2010–2020. International Classification of Disease (ICD) codes were used to identify HF and 92 other common LTCs. The most frequent combinations of LTCs were identified for individuals with HF and a control cohort of individuals of the same age and sex, with a non-HF-related hospital admission in the same year (matched in a 1:5 ratio). Multivariable regression analysis (adjusted for age, sex, socioeconomic status, tobacco use, year of hospitalisation, and hospital characteristics) was used to evaluate the association between multimorbidity burden, length of stay (LOS; negative binomial regression) and 30-day readmission (logistic regression). Results From a total of 175,388,410 hospitalisation episodes, 3,913,924 individuals with an HF-related hospitalisation were identified and matched to 19,552,954 controls (Figure 1a). The median (interquartile range, IQR) age of a patient admitted with HF was 74 (63–85) years; 1,856,268 (47.5%) were female. The most common comorbidities in those with HF were hypertension (87.2 vs. 72.8% in matched controls), chronic kidney disease (CKD; 55.3 vs. 34.6%), coronary artery disease (CAD; 53.7 vs. 31.0%), dyslipidaemia (46.9 vs. 39.7%), diabetes (46.6 vs. 33.9%), atrial fibrillation (AF; 43.0 vs. 23.0%) and anaemia (33.2 vs. 30.1%; p all < 0.001). Patients with HF had a greater number of LTCs compared with matched controls (median [IQR] 7 [5–9] vs. 6 [4–8]; p < 0.001). From 2010–2020, the number of LTCs in those with an HF admission increased (from 6 [4–8] in 2020, to 8 [6–10] in 2020; Figure 1b). The most common multimorbidity patterns in those with HF are presented in Figure 2. In the HF cohort, a greater multimorbidity burden was associated with a longer LOS (+6% for each additional LTC; 95% confidence interval [CI] 5–7%; p<0.001) and greater risk of 30-day readmission (adjusted odds ratio [aOR] for 6 vs. 0 LTCs: 1.15, 95% CI 1.08–1.22; aOR for ≥12 vs. 0 LTCs: 1.54, 95% CI 1.45–1.64). Conclusions Patients admitted to hospital with HF have a significant burden of multimorbidity, which has increased over time and is associated with increased length of stay and unplanned hospital re-admission. The high prevalence of multiple LTCs warrants the development of novel treatment strategies that target common multimorbidity patterns observed in HF.

Persistent angina following revascularization for chronic coronary syndromes: a systematic review and meta-analysis of randomized controlled trials

Abstract Introduction Recent randomized clinical trials (RCTs) have demonstrated that revascularization plus optimal medical therapy for patients with chronic coronary syndromes (CCS) results in greater reduction in angina than medical therapy alone. However, the frequency of persistent angina following revascularization for CCS is not well understood. Purpose To quantify the frequency of persistent angina following revascularization in contemporary RCTs of revascularization plus medical therapy vs. medical therapy alone among patients with CCS. Methods A literature search through January of 2024 was conducted in PubMed and Cochrane Central Register of Controlled Trials for contemporary RCTs reporting angina frequency following randomization to revascularization plus medical therapy vs. medical therapy alone. The primary outcome of interest was the frequency of persistent angina in the revascularization arms of these studies at early (3-12 months) and late (3-5 years) time points. A random effects model was used to combine results from individual studies. Results From a total of 5287 citations, the search yielded 7 RCTs that met inclusion criteria. These studies randomized 5719 patients to an invasive or revascularization strategy. Revascularization was exclusively by percutaneous coronary intervention (PCI) in 4 studies and by coronary artery bypass grafting or PCI in 3 studies. At the early time point, the combined frequency of persistent angina was 39.6% (95% CI: 30.6-49.4). For the two blinded, sham-controlled studies, the rate of persistent angina was significantly greater at 67.2% (95%CI: 54.9-77.4) compared to 30.5% (95% CI: 23.1-39) in the unblinded studies (P<0.001). In the 5 studies with 3-5 years of follow-up, the frequency of persistent angina was 33.3% (95% CI: 19.2-51.2). Conclusion Persistent angina is common after revascularization for CCS and suggests alternative causes and treatments of residual angina should be considered.

Diversity and distribution of Mdace mutations involved in propoxur resistance in the house fly (Musca domestica L.) in China.

The house fly is a public health pest due to its ability to transmit various pathogens worldwide. The suppression of house flies is frequently controlled by organophosphate and carbamate insecticides, but recurrent selection has led to the mutated target. To understand the spread and evolution of Mdace mutations in house flies, we sampled flies in eight different China provinces, sequenced, and then estimated the frequencies of mutations. The inhibition of AChE towards propoxur varied geographically and was lowest in the Heilongjiang field population, and highest in Jiangsu population. The overall frequencies of the different Mdace mutations (V260L, G342A, G342V, F407Y) varied considerably between populations. Strong positive correlations were found between acetylcholinesterase (AChE) insensitivity and the frequencies of G342V allele, 342A/V genotype and combination (260V/L-342A/V-407Y/Y) for the field populations. Eighteen combinations of Mdace at three sites (V260L, G342A/V, F407Y) were observed, with the majority of flies being categorized into the combination (260V/L-342A/V-407Y/Y), ranging in frequency from 24% (in field populations in Hubei and Hainan) to 96% (Jiangsu). Based on comparison with historical data, the mutations responsible for the extremely high resistance to the level of insecticide resistance spread widely, propoxur should be limited to use for house fly control in China. © 2024 Society of Chemical Industry.

Pharmacoepidemiology of combination pulmonary vasodilator therapy in critically ill infants.

New drugs to target different pathways in pulmonary hypertension has resulted in increased combination therapy, but details of this use in infants are not well described. In this large multicenter database study, we describe the pharmacoepidemiology of combination pulmonary vasodilator therapy in critically ill infants. We identified inborn infants discharged home from a Pediatrix neonatal ICU from 1997 to 2020 exposed to inhaled nitric oxide, sildenafil, epoprostenol, or bosentan for greater than two consecutive days. We compared clinical variables and drug utilisation between infants receiving simultaneous combination and monotherapy. We reported each combination's frequency, timing, and duration and graphically represented drug use over time. Of the 7681 infants that met inclusion criteria, 664 (9%) received combination therapy. These infants had a lower median gestational age and birth weight, were more likely to have cardiac and pulmonary anomalies, receive cardiorespiratory support, and had higher in-hospital mortality than those receiving monotherapy. Inhaled nitric oxide and sildenafil were most frequently used, and utilisation of combination and monotherapy for all drugs increased over time. Inhaled nitric oxide and epoprostenol were used in infants with a higher gestational age, earlier postnatal age, and shorter duration than sildenafil and bosentan. Dual therapy with inhaled nitric oxide and sildenafil was the most common combination therapy. Our study revealed an increased use of combination pulmonary vasodilator therapy, favouring inhaled nitric oxide and sildenafil, yet with considerable practice variation. Further research is needed to determine the optimal combination, sequence, dosing, and disease-specific indications for combination therapy.

Systematic analysis and network mapping of disease associations in autoimmune polyglandular syndrome.

The purpose of our work was to provide a data-driven perspective to APS, a complex autoimmune disorder, supplementing traditional clinical observations. Medical records of 7559 patients were analyzed, autoimmune origin was proved in 3180 cases of which 380 (12%) had APS. Associations of component disorders were investigated by computational methods to reveal typical patterns of disease development. Twenty-eight distinct autoimmune disorders were diagnosed forming 113 combinations. The 10 most frequent combinations were responsible for 51,3% of cases. HT and GD were differentiated as main cornerstones of APS, sharing several comorbidities. HT was the most common manifestation (67.4%), followed by GD (26.8%) and T1D (20.8%). APS started significantly earlier in men than in women. Thyroid autoimmunity was frequently linked to gastrointestinal and systemic manifestations and these patterns of associations substantially differed from that of T1D, AD or CeD when present as first manifestations, suggesting the possibility of a common biological cause. APS is more frequent than reported. Classifying APS requires a shift of perspective towards disease associations rather than disorder prevalence.

Radiotherapist’s View on the Role of Current Diagnostic Imaging in Pre-Radiation Preparation of Patients with Oligometastatic Disease for Conformal Radiotherapy

Diagnostic imaging of oligometastatic disease is a difficult task, since it requires determining the exact locoregional stage of the underlying disease and assessing the condition of the entire body in terms of possible diffuse spread of distant metastases, which presupposes a fairly frequent combination of various instrumental methods. In each specific case, a more accurate imaging method is chosen depending on the type of tumor, time of diagnosis, possible previously implemented stage of special antitumor treatment, as well as the individual risk of developing distant metastases, the most characteristic for this type of tumor process. Today, along with some diagnostic techniques that were previously constantly used in everyday practice, but are gradually losing their long-standing clinical application, such imaging methods as contrastenhanced computed tomography (CT), magnetic resonance imaging, as well as metabolic and specific receptor imaging, for example, CT combined with positron emission tomography with 18F-fluorodeoxyglucose, are most commonly performed, alone or in various combinations.

Analysis of medication rule of Traditional Chinese Medicine in treating depression based on data mining

ObjectiveDepression is a mental disorder characterized by persistent feelings of sadness, decreased interest or pleasure in activities and reduced energy. As a highly prevalent disorder, it seriously endangers the psychosocial functioning of patients. Many scholars have conducted clinical studies on the treatment of depression using different herbal remedies, but there are no studies that integrate these remedies to explore the general medication rule. This study aims to explore the medication pattern of Traditional Chinese Medicine (TCM) treatment for depression through data mining methods, so as to provide scientific theoretical basis and reference for clinical treatment and new prescription development. MethodsBased on the PRISMA principle, 121 articles involving 10810 patients with depression of TCM treatment were collected. We then performed frequency, association rule, and hierarchical clustering analysis of Chinese herbs using Microsoft Excel 2016, SPSS Modeler 18.0 and IBM SPSS Statistics 23. ResultsAmong the 270 herbs collected, the three most frequently occurring herbs are Gancao, Chaihu, and Shaoyao. The categories of high-frequency herbs are mainly deficiency-tonifying, Qi-regulating and blood-activating and stasis-eliminating herbs. Through the Apriori algorithm, we mined 21 herbal groups of association rules, and among which the combination of Chaihu-Shaoyao-Gancao has the highest level of support. Furthermore, five novel clustering combinations were identified, predominantly derived from Xiaoyao-San, Chaihu-Shugan-San, Sini powder, Kaixin-San and Chaihu-Jia-Longgu-Muli Decoction. ConclusionThe current study not only concluded the frequent combinations but also developed five new drug cluster combinations for depression, which can provide evidence-based references for the future clinical treatment and is helpful to understand the potential pharmaceutical mechanism from the properties, tastes, meridian tropisms and categories. The clinical effectiveness of these combinations needs to be verified by future study.

CD14 gene polymorphism in COVID-19 convalescents: analysis of (C-159)T

Cluster of differentiation 14 (CD14) is a pattern recognition receptor for lipopolysaccharide of gram-negative flora and has a close relationship with toll-like receptor 4 (TLR4). The interaction between CD14 and TLR 4 leads to the synthesis of cytokines such as interleukin-1, interleukin-6 and tumor necrosis factor-á. The TLR4 receptor is associated with the penetration of the new coronavirus infection virus into the cell, additionally stimulating the expression of the angiotensin converting enzyme 2 molecule and suppressing apoptosis in infected cells. Work on the study of the (159C)T polymorphism of the CD14 gene in COVID-19 is represented by only a few publications describing observations only in the Western European region. The purpose of our study was to study the association between single nucleotide polymorphism (SNP) of the CD14 gene – (159C)T (rs2569190) and susceptibility to a new coronavirus infection in the population of the Republic of Crimea. The study included 158 patients (87 women (55%) and 71 (45%) men, average age 45.6±6.14 years) who had COVID-19. Verification of previous COVID-19 was based on anamnestic data and data from studies performed at the time of illness (PCR). The control group consisted of 85 respondents who had not suffered a new coronavirus infection. To analyze the (C-159)T polymorphism of the CD14 gene, allele-specific PCR with electrophoretic detection in a 3% agarose gel (NPF "Litekh", Russia) was used. To compare the frequencies of allele combinations, the ÷2 test and odds ratio (95% CI) were used. The distribution of CD14 mutations followed Hardy-Weinberg equilibrium (p 0.05). The results of the study showed that the distribution of CD14 gene genotypes did not differ significantly in all study groups. The dominant genotype was the heterozygous genotype CT of the (C-159)T polymorphism of the CD14 gene. The analysis showed that the presence of CT and TT SNPs was not associated with the risk of developing a new coronavirus infection (p 0.05). Conclusions. The CD14 SNP (C-159)T is not associated with a higher risk of COVID-19 infection. The distribution of occurrence of SNP variants in the group of recovered individuals did not differ significantly from that in the control group (p 0.05).

Coupling vibration mechanism of rotating shaft–disc–blade system with blade crack—A systematical investigation on the effect of crack, condition, and structure parameters

Rotating shaft–disc–blade (RSDB) system is one of the most important parts of turbomachinery, such as aero-engine, gas turbine, and power plant. Understating and revealing the coupling vibration mechanism of RSDB system is significant for blade health monitoring and blade crack detection. However, the multi-structure, multi-vibration source, and multi-stress coupling makes it a very tough task. This study aims to reveal the coupling vibration mechanism of RSDB system by systematically investigating the steady-state vibration responses under the influences of different blade crack, operation condition, and structure parameters. First and foremost, a coupling vibration model of RSDB system that comprehensively considers the multi-structure, multi-vibration source, and multi-stress coupling effects is presented. And then, a novel condition indicator for blade health monitoring, called blade–blade distance, is proposed to better characterize and analyse the coupling vibration of RSDB system with blade crack. At last, the comprehensive effects of blade crack, operating condition, and structure parameters on the coupling vibration mechanism of the RSDB system with blade crack are systematically studied. The comparative results demonstrate the effectiveness of blade–blade distance and super-harmonic components of shaft torsional vibration and blade bending vibration for indicating the presence of blade crack and tracking the crack severity. Another observation should be noted is that the vibration behaviour including the blade–blade distance, super-harmonic components of shaft torsional vibration and blade bending vibration, the combination frequency components of shaft bending vibration are co-affected by blade crack, operating condition, and structure parameters. It is indicated that the blade health monitoring and crack detection of rotating blade should comprehensively consider different indicators to obtain a more robust and accurate results.

Incidence, severity and changes of abnormal vital signs in trauma patients: A national population-based analysis

BackgroundPhysiological criteria are used to assess the potential severity of injury in the early phase of a trauma patient's care trajectory. Few studies have described the extent of abnormality in vital signs and different combinations of these at a national level. Aim of the study was to identify physiologic abnormalities in trauma patients and describe different combinations of abnormalities and changes between the pre-hospital and emergency department (ED) settings. MethodNorwegian Trauma Registry (NTR) data between 01.01.15 – 31.12.18, where evaluated on the prevalence and characteristics of abnormal physiologic variables. Primary outcome were rates of hypoventilation (respiratory rate [RR] < 10 breaths per min), hyperventilation (RR > 29 breaths per min), hypotension (systolic blood pressure [SBP] < 90 mmHg), and reduced level of consciousness (Glasgow Coma Scale [GCS] < 13). ResultsA total of 24,482 patients were included. Documented values for RR, SBP and GCS were 77.6%, 78.5% and 81.9% in the pre-hospital phase, and the corresponding percentages in the ED were 95.5%, 99.2% and 98.6%, respectively. In the pre-hospital phase, 3,615 (14.8%) patients had at least one abnormal vital sign, whereas the corresponding numbers in the ED, were 3,616 (14.8%) patients. The most frequent combination was low GCS and hyperventilation. A worsened RTS-score from pre-hospital phase to the ED was observed for RR, SBP and GCS in 3.9%, 1.2% and 1.9% of incidents, respectively. Overall 30-day mortality was 3.1% (n=752). Of these, 60.8% had abnormal vital signs, with decreased GCS as the most prevalent (61.3%). ConclusionMost trauma patients had normal vital signs. According to the RTS-score, there were few deteriorations in RR, SBP and GCS between pre-hospital phase and the ED. The most frequent abnormality was low GCS, with a higher proportion in those who died within 30 days.

MTOR gene variant rs2295080 might be a risk factor for atherosclerosis in Iranian women with type 2 diabetes mellitus

BackgroundType 2 diabetes mellitus, one of the most prevalent metabolic disorders worldwide, is closely linked with an enhanced risk of atherosclerosis. However, the molecular mechanism of this linkage is not still clear. Genetic variations in the mTOR gene may increase the susceptibility of individuals to these diseases.MethodsOne hundred nine diabetic patients and 375 healthy subjects participated in this study. mTOR Single Nucleotide Polymorphism (SNP) rs2295080 was determined using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP).ResultsComparison of genotypic, allelic, and genotypic combination frequencies between cases and controls revealed no significant result. Nevertheless, the frequency of rs2295080 GT + TT genotype was significantly more in diabetic women with atherosclerosis compared with those without atherosclerosis (p = 0.047). Besides, the rs2295080 G allele was more frequently detected in diabetic women without atherosclerosis compared to those with atherosclerosis (p = 0.046).ConclusionThe rs2295080 GT + TT genotype predisposes Iranian diabetic women to atherosclerosis, while the rs2295080 G allele protects them against atherosclerosis. However, additional experiments using larger sample sizes are needed to verify this result.

Hypermethylation of the BRCA2 gene promoter and its co-hypermethylation with the BRCA1 gene promoter in patients with breast cancer.

The BRCA2 gene is an important tumour suppressor in breast cancer, and alterations in BRCA2 may lead to cancer progression. The aim of the study was to investigate the association of hypermethylation of the BRCA2 gene promoter and its co-hypermethylation with the BRCA1 gene promoter with the development and course of breast cancer in women. This study included 74women with breast cancer (tumour tissue samples and peripheral blood) and 62women without oncological pathology (peripheral blood)- control group. Hypermethylation of the BRCA2 gene was significantly more frequently detected in the tumour tissue of women with breast cancer compared to their peripheral blood and peripheral blood of control subjects (p= 0.0006 and p= 0.00001, respectively). Hypermethylation of BRCA2 was more frequently detected in patients with breast cancer over the age of 50 and in patients with higher Ki67 expression levels (p= 0.045 and p= 0.045, respectively). There was a high frequency of unmethylated BRCA1 and BRCA2 gene combination in women of the control group compared to women with breast cancer, both in blood samples and tumour tissue samples (p= 0.014 and p= 0.00001, respectively). Our study confirms the hypothesis that BRCA2 hypermethylation plays an important role in the pathogenesis of breast cancer and the importance of assessing its co-hypermethylation with BRCA1 in predicting the course of the disease.

EEG-CogNet: A deep learning framework for cognitive state assessment using EEG brain connectivity

The assessment of cognitive states such as workload, attention, and fatigue is crucial in cognitive science and human performance fields due to its significant impact on work efficiency and decision-making. This paper introduces a deep learning framework for cognitive state assessment using Electroencephalogram (EEG) brain connectivity. The framework was evaluated using EEG data from 26 participants through three computer-based tasks: the Dual N-Back Task, Visual Search Task, and Continuous Performance Task, each designed to induce varying levels of cognitive workload, attention, and fatigue, respectively. A comprehensive dataset was meticulously compiled, including physiological, behavioral, and subjective data to ensure robust analyses. The EEG data underwent rigorous pre-processing and feature extraction processes, focusing on brain connectivity metrics such as Coherence and Phase-Locking Value across multiple frequency bands and employing three neural network architectures: Convolutional Neural Networks (CNN), Graph Convolutional Networks (GCN), and Convolutional Long Short-Term Memory networks (ConvLSTM) for classification. The proposed work achieved classification accuracies of 96.53% for workload, 98.40% for attention, and 97.86% for fatigue in the combined frequency bands. The study’s findings underscore the potential of EEG-based methods for non-invasive cognitive state monitoring. By addressing existing limitations such as small sample sizes and task-specific models, this research enhances the generalizability and applicability of EEG-based cognitive assessments. The implications of these advancements are significant for fields requiring continuous cognitive monitoring, such as defense, healthcare, and high-risk operational environments.

Deep Learning Frequency Loss Functions for Predicting the Seismic Responses of Structures

Novel loss functions for seismic response prediction, such as physics-informed loss functions, have attracted considerable attention. However, existing loss functions are based on the time domain and do not consider the frequency domain differences contained in structure response signals. This study accordingly designed three loss functions based on frequency domain information — one pure frequency domain loss function and two combined frequency- and time-domain loss functions — using Fourier transforms. The proposed loss functions were applied using a trusted publicly available dataset for a frame structure, and their performances were compared with those obtained using the conventional mean squared error (MSE) loss function. The proposed frequency domain loss function exhibited superior performance, accelerating the convergence of learning curves for long-period signals while simultaneously enhancing their frequency domain accuracy and facilitating the prediction of high-sampling-rate response signals. In addition, the designed loss functions exhibited more stable performances and superior accuracy than the MSE when random dataset partitioning was employed. Finally, the combined time- and frequency-domain loss functions were shown to predict the seismic displacement time-history of tall, long-span bridges more accurately than the MSE by training the model to predict structural acceleration responses, then integrating them to predict displacement responses.

Age distribution of patients with multiple High-Risk Human Papilloma Virus (HR-HPV) genotypes and HPV vaccine recommendations by age

Introduction: The aim of this study to identify the age distribution of patients with multiple high risk Human Papilloma Virus (HR-HPV) genotypes and to evaluate HPV vaccination programs through age distribution. Methods: Patients between the ages of 20-70, who had cervical screening (cervical smear) and HPV genotype tests between January 2017 and December 2021 in Gynecology and Obstetrics Department in Tınaztepe University Hospital, were included in this study. HR-HPV genotype tests and age information which were performed evaluated retrospectively. Results: The study consisted of 66 patients analysis with multiple HR-HPV genotypes. The median age of the patients with multiple HR- HPV was found to be 32.6 years old. The most frequent combination of multiple HR-HPV was found two sub-types of HR-HPV (66.7%), median age was found as 36.6 years old. In this study the frequency for three sub-types of HR-HPV was found 24.2% and median age for this group was found to be 34.7 years old. We found frequency in patients with four or more sub-types of HR-HPV as 9.1%, and the median age for this group as 33.1 years old was found. Conclusion: The most common cause of cervical cancer is HPV infection. Multiple HR-HPV infection progression may promote high risk cervical lesions and neoplasia. HPV genotype testing results considering combination of subtypes may direct individual treatment, follow-up protocols for patients. HPV vaccination research may comprise multiple HR-HPV subtypes relations and age distribution for optimal immunization.

Identification and comparison of intestinal microbial diversity in patients at different stages of hepatic cystic echinococcosis

There is a significant focus on the role of the host microbiome in different outcomes of human parasitic diseases, including cystic echinococcosis (CE). This study was conducted to identify the intestinal microbiome of patients with CE at different stages of hydatid cyst compared to healthy individuals. Stool samples from CE patients as well as healthy individuals were collected. The samples were divided into three groups representing various stages of hepatic hydatid cyst: active (CE1 and CE2), transitional (CE3), and inactive (CE4 and CE5). One family member from each group was selected to serve as a control. The gut microbiome of patients with different stages of hydatid cysts was investigated using metagenomic next-generation amplicon sequencing of the V3–V4 region of the 16S rRNA gene. In this study, we identified 4862 Operational Taxonomic Units from three stages of hydatid cysts in CE patients and healthy individuals with a combined frequency of 2,955,291. The most abundant genera observed in all the subjects were Blautia, Agathobacter, Faecalibacterium, Bacteroides, Bifidobacterium, and Prevotella. The highest microbial frequency was related to inactive forms of CE, and the lowest frequency was observed in the group with active forms. However, the lowest OTU diversity was found in patients with inactive cysts compared with those with active and transitional cyst stages. The genus Agatobacter had the highest OTU frequency. Pseudomonas, Gemella, and Ligilactobacillus showed significant differences among the patients with different stages of hydatid cysts. Additionally, Anaerostipes and Candidatus showed significantly different reads in CE patients compared to healthy individuals. Our findings indicate that several bacterial genera can play a role in the fate of hydatid cysts in patients at different stages of the disease.

Introduction of novel complex integrated care models supported by digital health interventions in European primary settings: a scoping review

IntroductionThere remains the need to develop comprehensive organisational care models supported by digital health interventions (DHIs) to manage chronic conditions in primary healthcare. Objectivethis review aimed to identify and map methods, interventions and outcomes investigated regarding the introduction of novel complex integrated care models supported by DHIs in the European primary care setting, as well as the level of integration achieved. Methodsa scoping review to identify literature from 2013 to 2023 in the European context was conducted across PubMed, Scopus and Web of Science. DHIs description, care models and outcomes were reported using the PRISMA- ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. ResultsA total of 53 studies was included. The models introduced, along with a DHI, at least one innovation in their structure or in the modality of care delivery: either a new figure (44%), interprofessional collaboration (37%), new functions like person-centred care (59%) or population stratification (11%). As regarding the DHIs, 56% implemented monitoring/management platforms and apps for chronic conditions. The most frequent combination of care model-DHI was the introduction of an app/platform, supported by phone calls/texts and electronic health records, paired with the introduction of a new healthcare professional/person centred care/ multidisciplinary team. All the studies reaching statistically significant outcomes introduced, along with one or more DHIs, either a new figure or a multidisciplinary team as part of the organizational change to support the technology. Conclusionsnovel complex integrated care models are focusing on introducing multidisciplinary perspectives and personalization of care, in line with the complex needs of chronic patients. The predominant development of monitoring/management platforms for patients is a further confirmation of this trend. Future research efforts should focus on the investigation of the effectiveness of current complex integrated care models integrating DHIs.

Unveiling the Structure in Mental Disorder Presentations

DSM criteria are polythetic, allowing for heterogeneity of symptoms among individuals with the same disorder. In empirical research, most combinations were not found or only rarely found, prompting criticism of this heterogeneity. To elaborate how symptom-based definitions and assessments contribute to a distinct probability pattern for the occurrence of symptom combinations. This cross-sectional study involved a theoretical argument, simulation, and secondary data analysis of 4 preexisting datasets, each consisting of symptoms from 1 of the following syndromes: posttraumatic stress disorder, depression, schizophrenia, and anxiety. Data were obtained from various sources, including the National Institute of Mental Health Data Archive and Department of Veteran Affairs. A total of 155 474 participants were included (individual studies were 3930 to 63 742 individuals in size). Data were analyzed between July 2021 and January 2024. For each participant, the presence or absence of each assessed symptom and their combination was determined. The number of all combinations and their individual frequencies were assessed. Probability or frequency of unique symptom combinations and their distribution. Among the 155 474 participants, the mean (SD) age was 47.5 (14.8) years; 33 933 (21.8%) self-identified as female and 121 541 (78.2%) as male. Because of the interrelation between symptoms, some symptom combinations were significantly more likely than others. The distribution of the combinations' probability was heavily skewed with most combinations having a very low probability. Across all 4 empirical samples, the 1% most common combinations were prevalent in a total of 33.1% to 78.6% of the corresponding sample. At the same time, many combinations (ranging from 41.7% to 99.8%) were reported by less than 1% of the sample. This study found that within-disorder symptom heterogeneity followed a specific pattern consisting of few prevalent, prototypical combinations and numerous combinations with a very low probability of occurrence. Future discussions about the revision of diagnostic criteria should take this specific pattern into account by focusing not only on the absolute number of symptom combinations but also on their individual and cumulative probabilities. Findings from clinical populations using common diagnostic criteria may have limited generalizability to the large group of individuals with a low-probability symptom combination.

Numerical Analysis of Dynamic Stability of Flutter Panels in Supersonic Flow

This paper introduces a novel numerical method for investigating the dynamic stability of a flutter panel exposed to a supersonic gas flow and a fluctuating axial excitation force. Initially, the system equation of motion was derived using Lagrange’s equation, where the first two modes are coupled Mathieu–Hill equations with damping, constituting a system of linear second-order differential equations with periodically variable coefficients. Subsequently, a new numerical method was proposed to analyze the dynamic stability of coupled Mathieu–Hill equations with damping. This method involves breaking down an arbitrary parametric load into discrete segments to approximate the variable excitation function using a step function. The system responses of each segment are then accumulated in matrix form. The proposed numerical method proves particularly effective for dynamic systems whose parameters cannot be treated as small. In practical application, the method allows the construction of instability regions corresponding to natural frequencies, subharmonics, and combination frequencies. Dynamic stability diagrams were generated based on dynamic pressure ratio, air/panel density ratio, Mach number, panel thickness—length ratio, and excitation frequency. The results demonstrated general agreement with those obtained through Hsu’s perturbation method, however, our numerical results have proven more accurate. The paper concludes by offering suggestions for suppressing panel flutter through appropriate parameter combinations.