Automated identification of normal and diabetes heart rate signals using nonlinear measures

Diabetes mellitus (DM) affects considerable number of people in the world and the number of cases is increasing every year. Due to a strong link to the genetic basis of the disease, it is extremely difficult to cure. However, it can be controlled to prevent severe consequences, such as organ damage. Therefore, diabetes diagnosis and monitoring of its treatment is very important. In this paper, we have proposed a non-invasive diagnosis support system for DM. The system determines whether or not diabetes is present by determining the cardiac health of a patient using heart rate variability (HRV) analysis. This analysis was based on nine nonlinear features namely: Approximate Entropy (ApEn), largest Lyapunov exponet (LLE), detrended fluctuation analysis (DFA) and recurrence quantification analysis (RQA). Clinically significant measures were used as input to classification algorithms, namely AdaBoost, decision tree (DT), fuzzy Sugeno classifier (FSC), k-nearest neighbor algorithm (k-NN), probabilistic neural network (PNN) and support vector machine (SVM). Ten-fold stratified cross-validation was used to select the best classifier. AdaBoost, with least squares (LS) as weak learner, performed better than the other classifiers, yielding an average accuracy of 90%, sensitivity of 92.5% and specificity of 88.7%.

The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics

Sexually antagonistic (SA) genetic variation-in which alleles favored in one sex are disfavored in the other-is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterization of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research-including F ST and F IS statistics, genome-wide association studies, pedigree analyses, reciprocal transplant studies, and evolve-and-resequence experiments-to evaluate methods for identifying SA genes and genome-wide signals of SA genetic variation. We begin by developing theoretical models for between-sex F ST and F IS, including explicit null distributions for each statistic, and using them to critically evaluate putative multilocus signals of sex-specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of F ST and F IS, along with applications of more direct approaches for characterizing SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work.

Hyperplectonemes: A Higher Order Compact and Dynamic DNA Self-Organization

Bacterial chromosome has a compact structure that dynamically changes its shape in response to bacterial growth rate and growth phase. Determining how chromatin remains accessible to DNA binding proteins, and transcription machinery is crucial to understand the link between genetic regulation, DNA structure, and topology. Here, we study very large supercoiled dsDNA using high-resolution characterization, theoretical modeling, and molecular dynamics calculations. We unveil a new type of highly ordered DNA organization forming in the presence of attractive DNA-DNA interactions, which we call hyperplectonemes. We demonstrate that their formation depends on DNA size, supercoiling, and bacterial physiology. We compare structural, nanomechanic, and dynamic properties of hyperplectonemes bound by three highly abundant nucleoid-associated proteins (FIS, H-NS, and HU). In all these cases, the negative supercoiling of DNA determines molecular dynamics, modulating their 3D shape. Overall, our findings provide a mechanistic insight into the critical role of DNA topology in genetic regulation.

Temporal control of Dickeya dadantii main virulence gene expression by growth phase-dependent alteration of regulatory nucleoprotein complexes

In bacteria, important genes are often controlled at the transcriptional level by several factors, forming a complex and intertwined web of interactions. Yet, transcriptional regulators are often studied separately and little information is available concerning their interactions. In this work, we dissect the regulation of the major virulence gene pelD in D. dadantii by taking into account the effects of individual binding sites for regulatory proteins FIS and CRP, and the impact of a newly discovered divergent promoter div. Using a combination of biochemistry and genetics approaches we provide an unprecedented level of detail on the multifactorial regulation of bacterial transcription. We show that the growth phase dependent regulation of pelD is under the control of changing composition of higher-order nucleoprotein complexes between FIS, CRP, div and pelD during the growth cycle that allow sequential expression of div and pelD in the early and late exponential growth phases, respectively. This work highlights the importance of "orphan" promoters in gene regulation and that the individual binding sites for a regulator can serve several purposes and have different effects on transcription, adding a new level of complexity to bacterial transcriptional regulation.

MioC and GidA proteins promote cell division in E. coli

The well-conserved genes surrounding the E. coli replication origin, mioC and gidA, do not normally affect chromosome replication and have little known function. We report that mioC and gidA mutants exhibit a moderate cell division inhibition phenotype. Cell elongation is exacerbated by a fis deletion, likely owing to delayed replication and subsequent cell cycle stress. Measurements of replication initiation frequency and origin segregation indicate that mioC and gidA do not inhibit cell division through any effect on oriC function. Division inhibition is also independent of the two known replication/cell division checkpoints, SOS and nucleoid occlusion. Complementation analysis indicates that mioC and gidA affect cell division in trans, indicating their effect is at the protein level. Transcriptome analysis by RNA sequencing showed that expression of a cell division septum component, YmgF, is significantly altered in mioC and gidA mutants. Our data reveal new roles for the gene products of gidA and mioC in the division apparatus, and we propose that their expression, cyclically regulated by chromatin remodeling at oriC, is part of a cell cycle regulatory program coordinating replication initiation and cell division.

The role of neuroticism, perfectionism and depression in chronic fatigue syndrome. A structural equation modeling approach

OBJECTIVE

Previous studies have reported consistent associations between Neuroticism, maladaptive perfectionism and depression with severity of fatigue in Chronic Fatigue Syndrome (CFS). Depression has been considered a mediator factor between maladaptive perfectionism and fatigue severity, but no studies have explored the role of neuroticism in a comparable theoretical framework. This study aims to examine for the first time, the role of neuroticism, maladaptive perfectionism and depression on the severity of CFS, analyzing several explanation models.

METHODS

A sample of 229 CFS patients were studied comparing four structural equation models, testing the role of mediation effect of depression severity in the association of Neuroticism and/or Maladaptive perfectionism on fatigue severity.

RESULTS

The model considering depression severity as mediator factor between Neuroticism and fatigue severity is the only one of the explored models where all the structural modeling indexes have fitted satisfactorily (Chi square=27.01, p=0.079; RMSE=0.047, CFI=0.994; SRMR=0.033). Neuroticism is associated with CFS by the mediation effect of depression severity. This personality variable constitutes a more consistent factor than maladaptive perfectionism in the conceptualization of CFS severity.

An Interplay among FIS, H-NS, and Guanosine Tetraphosphate Modulates Transcription of the Escherichia coli cspA Gene under Physiological Growth Conditions

CspA, the most characterized member of the csp gene family of Escherichia coli, is highly expressed not only in response to cold stress, but also during the early phase of growth at 37°C. Here, we investigate at molecular level the antagonistic role played by the nucleoid proteins FIS and H-NS in the regulation of cspA expression under non-stress conditions. By means of both probing experiments and immunological detection, we demonstrate in vitro the existence of binding sites for these proteins on the cspA regulatory region, in which FIS and H-NS bind simultaneously to form composite DNA-protein complexes. While the in vitro promoter activity of cspA is stimulated by FIS and repressed by H-NS, a compensatory effect is observed when both proteins are added in the transcription assay. Consistently with these findings, inactivation of fis and hns genes reversely affect the in vivo amount of cspA mRNA. In addition, by means of strains expressing a high level of the alarmone guanosine tetraphosphate ((p)ppGpp) and in vitro transcription assays, we show that the cspA promoter is sensitive to (p)ppGpp inhibition. The (p)ppGpp-mediated expression of fis and hns genes is also analyzed, thus clarifying some aspects of the regulatory loop governing cspA transcription.

Quality of life improvement in HIV-1 patients treated with raltegravir in a real-life observational study: RACING

BACKGROUND

Good efficacy and safety of raltegravir in person living with HIV was demonstrated in clinical trials over five years, but real-life data, particularly about quality of life (QoL), are lacking. QoL was evaluated over time in adult patients first treated or switched to regimens containing raltegravir in an observational cohort study.

METHODS

Patient QoL was evaluated using the Fatigue Impact Scale (FIS) and the HIV Symptom Index (HSI). Data were collected at baseline and at 1, 3, 6, 12, 18, and 24 months. Baseline FIS and HSI subscores were compared with the scores at each visit using the paired Wilcoxon test. The impact of time, sociodemographic and medical variables upon patient-perceived fatigue and symptoms was also assessed using mixed multivariate models.

RESULTS

From baseline, all FIS and HSI subscores improved significantly after one month of treatment. In addition, psychosocial FIS subscores and both the frequency of bothersome symptoms and HSI subscores improved significantly at each visit. Physical FIS subscores also improved significantly, except at month 18, whereas both cognitive and total FIS subscores improved only after 6 months and 24 months, respectively. In multivariate analysis, employment was independently associated over time with improved improvement in both FIS and HSI subscores.

CONCLUSION

Patient QoL improved significantly over a 24-month period of treatment with a raltegravir-containing regimen. FIS and HSI are sensitive tools to measure the impact of new antiretroviral combinations on a patient's perception of QoL.

Parental perception on oral health-related quality of life and dental features of ectodermal dysplasia and isolated hypodontia in children

Background

Children missing 6 or more permanent teeth often present with complex dental care needs and significant impacts on their oral health related quality of life (OHRQoL). The most important facet in the overall care for these children is the child’s own experience, but parents primarily make the decisions regarding their child’s dental management. Understanding the parental perspective could have a positive impact on planning and provision of care for these patient groups in the future. The study compared the parental perspectives on OHRQoL impact and dental experience for children with ectodermal dysplasia (ED), severe isolated hypodontia (IH), and matched controls following assessment of their dental features.

Design

A cross-sectional study of 172 children (mean age: 12.4 years old) was conducted; 86 with severe hypodontia (≥ 6 missing teeth; ED: 29; IH: 57) and 86 age and gender matched controls. The Parental-Caregiver Perceptions Questionnaire (P-CPQ), Family Impact Scale (FIS) and a supplemental questionnaire were used to gather information on parental perceptions of OHRQoL and dental experiences, respectively. Clinical examinations were used to assess and compare the dental features between children with ED, IH and their respective controls.

Results

Higher scores (p < 0.05) were found in P-CPQ and FIS scores between the children with ED, IH and their respective controls. P-CPQ scores for males with ED had a moderate correlation with functional limitations (R_s = 0.576; p = 0.001*), oral symptoms (R_s = 0.444; p = 0.016*) and overall QoL (R_s = 0.499; p = 0.006*). The ED group reported earlier awareness of issues, the youngest attendance (3.24 years) and highest perceived number of appointments (“20 or more”; 58.6%). The mean number of missing teeth in the ED group was almost twice that of the IH group (ED: 20.17; IH: 10.68) and the median number of missing teeth (Radiographically: ED = 21; IH = 9; Clinically: ED = 11; IH = 6), was significantly greater in the ED group when compared to the IH group (p < 0.001*).

Conclusion

Parents of children with ED and IH perceive a greater impact on QoL, for both the child and their family. Children with ED need earlier intervention and more extensive treatment than children with IH and their controls.

Introducing an integrated approach for fire safety assessment in healthcare facilities by interval valued neutrosophic-AHP and Fuzzy Inference System

Fire safety in healthcare facilities is extremely important due to limited evacuation capacity of occupants. Therefore, poor fire safety precautions lead to more fatalities and financial losses. This study introduces an effective fire risk management approach for healthcare buildings utilizing an interval valued neutrosophic-fuzzy framework. This framework identifies fire risks and determine appropriate safety measures. In addition, essential fire risk criteria in healthcare centers were systematically identified through a multi-factor decision-making process, employing the Fuzzy-Delphi technique and a comprehensive literature review. The proposed framework initially determines the importance weights of these factors using the Interval Valued Neutrosophic-Analytical Hierarchy Process (IVN-AHP). Subsequently, three main parameters - Potential Risk Level (PRL), Acceptance Risk Level (ARL) and Protection Level (PL) - were calculated as alternatives in IVN-AHP technique using novel mathematical equations. A fuzzy inference system (FIS) was then employed to estimate the risk magnitude and subsequently classify departments within the healthcare building based on their risk level. The fire risk control strategy is then determined based on this risk classification. The proposed approach was applied to departments within a hospital in Iran. Its validity was evaluated by comparing the results with the comprehensive Fire Risk Assessment Method for Engineering (FRAME) technique. Additionally, the sensitivity of the IVN-AHP in determining the weights of factors and alternatives was validated using real data. The results revealed that the utilities and kitchen departments exhibited a critical risk class exceeding 50 %. Furthermore, the operating room, laundry, post-NICU 1 and 2, and waste disposal were classified as critical, with more than 50 % falling within the major risk class. A strong correlation coefficient of 99.1 % was observed between the Fire Risk Magnitude (FRM) obtained using the proposed farmwork and the FRM for occupants obtained using the FRAME technique. These findings demonstrate the applicability and reliability of the proposed approach as a valuable tool for risk management and decision-making in healthcare facilities.

A new method for ecologists to estimate heterozygote excess and deficit for multi-locus gene families

The fixation index, F IS, has been a staple measure to detect selection, or departures from random mating in populations. However, current Next Generation Sequencing (NGS) cannot easily estimate F IS, in multi-locus gene families that contain multiple loci having similar or identical arrays of variant sequences of ≥1 kilobase (kb), which differ at multiple positions. In these families, high-quality short-read NGS data typically identify variants, but not the genomic location, which is required to calculate F IS (based on locus-specific observed and expected heterozygosity). Thus, to assess assortative mating, or selection on heterozygotes, from NGS of multi-locus gene families, we need a method that does not require knowledge of which variants are alleles at which locus in the genome. We developed such a method. Like F IS, our novel measure, 1 H IS, is based on the principle that positive assortative mating, or selection against heterozygotes, and some other processes reduce within-individual variability relative to the population. We demonstrate high accuracy of 1 H IS on a wide range of simulated scenarios and two datasets from natural populations of penguins and dolphins. 1 H IS is important because multi-locus gene families are often involved in assortative mating or selection on heterozygotes. 1 H IS is particularly useful for multi-locus gene families, such as toll-like receptors, the major histocompatibility complex in animals, homeobox genes in fungi and self-incompatibility genes in plants.

Pangenome-level analysis of nucleoid-associated proteins in the Acidithiobacillia class: insights into their functional roles in mobile genetic elements biology

Mobile genetic elements (MGEs) are relevant agents in bacterial adaptation and evolutionary diversification. Stable appropriation of these DNA elements depends on host factors, among which are the nucleoid-associated proteins (NAPs). NAPs are highly abundant proteins that bind and bend DNA, altering its topology and folding, thus affecting all known cellular DNA processes from replication to expression. Even though NAP coding genes are found in most prokaryotic genomes, their functions in host chromosome biology and xenogeneic silencing are only known for a few NAP families. Less is known about the occurrence, abundance, and roles of MGE-encoded NAPs in foreign elements establishment and mobility. In this study, we used a combination of comparative genomics and phylogenetic strategies to gain insights into the diversity, distribution, and functional roles of NAPs within the class Acidithiobacillia with a special focus on their role in MGE biology. Acidithiobacillia class members are aerobic, chemolithoautotrophic, acidophilic sulfur-oxidizers, encompassing substantial genotypic diversity attributable to MGEs. Our search for NAP protein families (PFs) in more than 90 genomes of the different species that conform the class, revealed the presence of 1,197 proteins pertaining to 12 different NAP families, with differential occurrence and conservation across species. Pangenome-level analysis revealed 6 core NAP PFs that were highly conserved across the class, some of which also existed as variant forms of scattered occurrence, in addition to NAPs of taxa-restricted distribution. Core NAPs identified are reckoned as essential based on the conservation of genomic context and phylogenetic signals. In turn, various highly diversified NAPs pertaining to the flexible gene complement of the class, were found to be encoded in known plasmids or, larger integrated MGEs or, present in genomic loci associated with MGE-hallmark genes, pointing to their role in the stabilization/maintenance of these elements in strains and species with larger genomes. Both core and flexible NAPs identified proved valuable as markers, the former accurately recapitulating the phylogeny of the class, and the later, as seed in the bioinformatic identification of novel episomal and integrated mobile elements.

Fuzzy-Based Efficient Healthcare Data Collection and Analysis Mechanism Using Edge Nodes in the IoMT

The Internet of Things (IoT) is an advanced technology that comprises numerous devices with carrying sensors to collect, send, and receive data. Due to its vast popularity and efficiency, it is employed in collecting crucial data for the health sector. As the sensors generate huge amounts of data, it is better for the data to be aggregated before being transmitting the data further. These sensors generate redundant data frequently and transmit the same values again and again unless there is no variation in the data. The base scheme has no mechanism to comprehend duplicate data. This problem has a negative effect on the performance of heterogeneous networks.It increases energy consumption; and requires high control overhead, and additional transmission slots are required to send data. To address the above-mentioned challenges posed by duplicate data in the IoT-based health sector, this paper presents a fuzzy data aggregation system (FDAS) that aggregates data proficiently and reduces the same range of normal data sizes to increase network performance and decrease energy consumption. The appropriate parent node is selected by implementing fuzzy logic, considering important input parameters that are crucial from the parent node selection perspective and share Boolean digit 0 for the redundant values to store in a repository for future use. This increases the network lifespan by reducing the energy consumption of sensors in heterogeneous environments. Therefore, when the complexity of the environment surges, the efficiency of FDAS remains stable. The performance of the proposed scheme has been validated using the network simulator and compared with base schemes. According to the findings, the proposed technique (FDAS) dominates in terms of reducing energy consumption in both phases, achieves better aggregation, reduces control overhead, and requires the fewest transmission slots.

Concordant Patterns of Population Genetic Structure in Food-Deceptive Dactylorhiza Orchids

BACKGROUND

The patterns of inbreeding coefficients (FIS) and fine spatial genetic structure (FSGS) were evaluated regarding the mating system and inbreeding depression of food-deceptive orchids, Dactylorhiza majalis, Dactylorhiza incarnata var. incarnata, and Dactylorhiza fuchsii, from NE Poland.

METHODS

We used 455 individuals, representing nine populations of three taxa and AFLPs, to estimate percent polymorphic loci and Nei's gene diversity, which are calculated using the Bayesian method; FIS; FST; FSGS with the pairwise kinship coefficient (Fij); and AMOVA in populations.

RESULTS

We detected a relatively high proportion of polymorphic fragments (40.4-68.4%) and Nei's gene diversity indices (0.140-0.234). The overall FIS was relatively low to moderate (0.071-0.312). The average Fij for the populations of three Dactylorhiza showed significantly positive values, which were observed between plants at distances of 1-10 m (20 m). FST was significant in each Dactylorhiza taxon, ranging from the lowest values in D. fuchsii and D. majalis (0.080-0.086, p < 0.05) to a higher value (0.163, p < 0.05) in D. incarnata var. incarnata. Molecular variance was the highest within populations (76.5-86.6%; p < 0.001).

CONCLUSIONS

We observed concordant genetic diversity patterns in three food-deceptive, allogamous, pollinator-dependent, and self-compatible Dactylorhiza. FIS is often substantially higher than Fij with respect to the first class of FSGSs, suggesting that selfing (meaning of geitonogamy) is at least responsible for homozygosity. A strong FSGS may have evolutionary consequences in Dactylorhiza, and combined with low inbreeding depression, it may impact the establishment of inbred lines of D. majalis and D. incarnata var. incarnata.

Effects of an alternative bleaching method for yerba mate leaves on total phenolic content: evaluation and prediction with soft-computing approaches

BACKGROUND

The effects of an alternative bleaching method on the total phenolic content (TPC) and antioxidant activity (AA) of yerba mate extracts were evaluated. Traditional bleaching ('zapeco') was compared with submerging the leaves in water followed by a hot air oven-drying process. Seven different approaches, i.e. linear model (LM), response surface model (RSM), Mamdani, Larsen, adaptive neuro-fuzzy inference system (ANFIS) with the product (Prod) and the minimum (Min) operators, and ANFIS with automatically membership functions (Auto), were employed to compare the TPC of yerba mate extracts based on drying temperature and AA assays.

RESULTS

The results showed that if leaves were bleached followed by drying at higher temperatures, we obtained higher AA and TPC values. For submerging bleaching treatment, RSM model delivered the best accuracy measures with a mean absolute error (MAE), average absolute percentage error (MAPE), and mean squared error (MSE) of 0.128, 0.006, and 0.028, respectively. The ANFIS Auto model was the best for traditional bleaching treatment, with MAE, MAPE, and MSE of 0.490, 0.013, and 0.612, respectively.

CONCLUSION

The results suggest a second-order linear relation between drying temperature, AA assays to TPC, and a high level of relation complexity of drying temperature, AA assays, and TPC. The evaluated soft-computing approaches have the excellent ability to estimate TPC from bleached leaves. © 2022 Society of Chemical Industry.