Analysis Of Variability Research Articles

Exploring rice genotypes for anaerobic germination: Towards sustainable direct seeding

Direct-seeded rice (DSR) production is the primary focus of this study, which explores the diversity of rice genotypes concerning their ability to withstand anaerobic germination conditions. Using advanced statistical analysis, a total of 250 rice cultivars were assessed for several anaerobic germination attributes. Significant variability was observed among genotypes for key traits including germination % (ARC14855, AG 387), shoot length and seedling dry weight, indicating potential donors for anaerobic germination tolerance. Trait association analysis, variability analysis, principal component analysis and cluster analysis were employed to uncover the genetic and phenotypic factors influencing anaerobic germination tolerance. The genotypes of cluster III could be used as donors for anaerobic germination studies, as the genotypes have revealed high average values for all the traits. The findings underscore the importance of genetic variability and heritability in breeding resilient rice varieties suited for DSR cultivation, offering valuable insights for enhancing rice cultivation practices in the face of challenges such as water scarcity and labour shortages. To improve the sustainability and productivity of paddy production systems, this research advances rice breeding procedures that aim to create varieties tolerant to anaerobic conditions.

Future of neurocritical care: Integrating neurophysics, multimodal monitoring, and machine learning

Multimodal monitoring (MMM) in the intensive care unit (ICU) has become increasingly sophisticated with the integration of neurophysical principles. However, the challenge remains to select and interpret the most appropriate combination of neuromonitoring modalities to optimize patient outcomes. This manuscript reviewed current neuromonitoring tools, focusing on intracranial pressure, cerebral electrical activity, metabolism, and invasive and noninvasive autoregulation monitoring. In addition, the integration of advanced machine learning and data science tools within the ICU were discussed. Invasive monitoring includes analysis of intracranial pressure waveforms, jugular venous oximetry, monitoring of brain tissue oxygenation, thermal diffusion flowmetry, electrocorticography, depth electroencephalography, and cerebral microdialysis. Noninvasive measures include transcranial Doppler, tympanic membrane displacement, near-infrared spectroscopy, optic nerve sheath diameter, positron emission tomography, and systemic hemodynamic monitoring including heart rate variability analysis. The neurophysical basis and clinical relevance of each method within the ICU setting were examined. Machine learning algorithms have shown promise by helping to analyze and interpret data in real time from continuous MMM tools, helping clinicians make more accurate and timely decisions. These algorithms can integrate diverse data streams to generate predictive models for patient outcomes and optimize treatment strategies. MMM, grounded in neurophysics, offers a more nuanced understanding of cerebral physiology and disease in the ICU. Although each modality has its strengths and limitations, its integrated use, especially in combination with machine learning algorithms, can offer invaluable information for individualized patient care.

Can a Sacrococcygeal Epidural of 0.25% Bupivacaine Prevent the Activation of the Sympathetic Nervous System during Feline Ovariectomy?

The ovariectomy (OVE) procedure can trigger somatosensory and visceral peritoneal nociception. Sacrococcygeal epidural (ScE) anesthesia may complement or replace systemic analgesia used for feline OVE, reducing opioid consumption and their related undesirable adverse effects and consequently reducing or completely blocking the sympathetic nervous system activation during this procedure. The present study aimed to evaluate the activation of the sympathetic nervous system resulting from adding an ScE injection of bupivacaine 0.25% (0.3 mL kg-1) in feline OVE and identify whether this translates to hemodynamic variables stability. A Parasympathetic Tone Activity (PTA) monitor was applied given that it performs analysis of heart rate variability (HRV) detecting changes in sympathetic and parasympathetic tone, making it a good tool for detecting activation of the sympathetic nervous system during the study. Two groups of animals were evaluated in five perioperative times, namely, the control group (CG) (n = 18) with systemic analgesia alone and the sacrococcygeal epidural group (ScEG) (n = 20) with 0.25% bupivacaine combined with systemic analgesia. Thirty-eight female cats were selected. All animals assigned to CG and ScEG were premedicated with dexmedetomidine (20 μg kg-1 IM) and methadone (0.2 mg kg-1 IM). General anesthesia was induced with propofol IV ad effectum and maintained with isoflurane in 100% oxygen. Heart rate, non-invasive systolic and median blood pressure, respiratory rate, and instantaneous parasympathetic tone activity were recorded. Compared to systemic analgesia alone (CG), sacrococcygeal epidural (ScEG) reduced the rise of common hemodynamic variables but did not prevent sympathetic nervous system activation.

RhoG facilitates a conformational transition in the guanine nucleotide exchange factor complex DOCK5/ELMO1 to an open state

The dedicator of cytokinesis (DOCK)/engulfment and cell motility (ELMO) complex serves as a guanine nucleotide exchange factor (GEF) for the GTPase Rac. RhoG, another GTPase, activates the ELMO-DOCK-Rac pathway during engulfment and migration. Recent cryo-EM structures of the DOCK2/ELMO1 and DOCK2/ELMO1/Rac1 complexes have identified closed and open conformations that are key to understanding the autoinhibition mechanism. Nevertheless, the structural details of RhoG-mediated activation of the DOCK/ELMO complex remain elusive. Herein, we present cryo-EM structures of DOCK5/ELMO1 alone and in complex with RhoG and Rac1. The DOCK5/ELMO1 structure exhibits a closed conformation similar to that of DOCK2/ELMO1, suggesting a shared regulatory mechanism of the autoinhibitory state across DOCK-A/B subfamilies (DOCK1−5). Conversely, the RhoG/DOCK5/ELMO1/Rac1 complex adopts an open conformation that differs from that of the DOCK2/ELMO1/Rac1 complex, with RhoG binding to both ELMO1 and DOCK5. The alignment of the DOCK5 PIP3 binding site with the RhoG C-terminal lipidation site suggests simultaneous binding of RhoG and DOCK5/ELMO1 to the plasma membrane. Structural comparison of the apo and RhoG-bound states revealed that RhoG facilitates a closed-to-open state conformational change of DOCK5/ELMO1. Biochemical and surface plasmon resonance (SPR) assays confirm that RhoG enhances the Rac GEF activity of DOCK5/ELMO1 and increases its binding affinity for Rac1. Further analysis of structural variability underscored the conformational flexibility of the DOCK5/ELMO1/Rac1 complex core, potentially facilitating the proximity of the DOCK5 GEF domain to the plasma membrane. These findings elucidate the structural mechanism underlying the RhoG-induced allosteric activation and membrane binding of the DOCK/ELMO complex.

Effects of Probiotics on Inflammatory Biomarkers and Its Associations With Cardiac Autonomic Function in Women With Arterial Hypertension: A Secondary Analysis of a Randomized Clinical Trial.

Preclinical evidence suggests that probiotic administration may exert an anti-inflammatory effect and reduce autonomic dysfunction and blood pressure. This study evaluated the effects of probiotic therapy on inflammatory biomarkers and characterized the correlations between inflammation and cardiac autonomic function in women with arterial hypertension. Women were randomized into probiotics (n = 20) or placebo (n = 20). The probiotic group received 109CFU/day of Lactobacillus (L.) paracasei LPC-37, L. rhamnosus HN001, L. acidophilus NCFM, and Bifidobacterium lactis HN019, and the placebo group received polydextrose. Clinical, electrocardiogram, heart rate variability (HRV) analysis, and cytokine levels were assessed at baseline and after 8weeks. Women who received probiotics for 8weeks had increased serum levels of IL-17A (p = 0.02) and decreased INF-γ (p = 0.02) compared to baseline. Probiotic supplementation increased serum levels of IL-10 compared to the placebo group (p = 0.03). Probiotic or placebo administration did not change serum levels of TNFα and IL-6. Serum levels of IL-2 (p = 0.001, and p = 0.001) and IL-4 (p = 0.001, and p = 0.001) were reduced in women receiving placebo or probiotics, respectively. Correlations between HRV indices and inflammatory variables showed that INF-γ was positively correlated with heart rate (HR) and sympathetic HRV indices and negatively correlated with vagal HRV indices. IL-10 was negatively correlated with HR and sympathetic HRV indices. IL-6 was negatively correlated with parasympathetic HRV indices and positively correlated with SD2/SD1 ratio. Probiotic therapy has a discreet anti-inflammatory effect in hypertensive women, and pro-inflammatory cytokines were negatively correlated with vagal modulation and positively correlated with sympathetic modulation of HRV.The clinical trial was registered in the Brazilian Registry of Clinical Trials (ReBEC) with the identification RBR-9mj2dt.

Heart rate variability in children of younger school age in the speleoclimatotherapy

The autonomic nervous system is a key link in the course of adaptation and adaptive reactions of the organism to various environmental factors. The aim of this study was to assess the heart rate variability of primary school children during a course of speleoclimatotherapy. The heart rate variability were evaluated in 175 practically healthy children aged 7–10 years. In the course of the study the effect of speleoclimatotherapy on the balance sympathetic and parasympathetic nervoussystem was studied using the parameters of spectral analysis of heart rate variability (HRV). HRV data were analysed in the frequency domain: total wave power (TP), high frequency waves (HF), low frequency waves (LF), very low frequency waves (VLF), vagosympathetic index LF/HF. After a course of speleoclimatotherapy the analysis of the obtained results allowed us to establish statistically significant differences in the groups of boy and girls with vagotonic and normotonic type of regulation. After a course of speleoclimatotherapy reduction of the indexe of a vagosympathetic balance (LF/HF) to normal values was found in the groups of sympathotonic boys and sympathotonic girls, while in sympathotonic girls there was an increase in the value of the total power (TP). It is possible to speak about the restoration of vegetative equilibrium and increase of adaptive capabilities of the child’s organism due to adaptation to the microclimate of speleo-chambers.

Unraveling Genetic Variability, Correlation and Path Analysis for Yield and Its Components in Barley (Hordeum vulgare L.)

The current study aimed to assess the genetic variability of yield and yield-related traits while examining the direct and indirect effects of trait interactions. Conducted at a research farm in Chaudhary Charan Singh University, Meerut, Uttar Pradesh, India, the experiment involved fourteen parents and their BC1F1 crosses, analyzed using a randomized block design (RBD). Significant differences were observed among the varieties for most traits, indicating a broad range of mean values and diversity. Both phenotypic and genotypic coefficients of variance (PCV and GCV) were generally low, with biological yield showing the highest values (26.57 for GCV and 40.48 for PCV). PCV values were slightly higher than GCV values. Traits such as seed per spike, biological yield, flag leaf breadth, days of heading, and days of maturity exhibited relatively high heritability. Notably, grain yield showed high heritability and genetic progress, making it a favourable selection indicator. Several traits, including days of anthesis, days of maturity, and spike length, demonstrated significant positive correlations with yield while also showing significant negative correlations with grain filling period and biological yield. Conversely, these traits showed highly non-significant positive correlations with harvest index, plant height, thousand seeds weight, and chlorophyll content and highly non-significant negative correlations with tiller number and seeds per spike.

Unveiling the Complexity of Yield Traits through Genetic Variability, Correlation, and Path Analysis across Diverse Bread Wheat [Triticum aestivum (L.) em. Thell] Germplasm

Unveiling the Complexity of Yield Traits through Genetic Variability, Correlation, and Path Analysis across Diverse Bread Wheat [Triticum aestivum (L.) em. Thell] Germplasm

Genetic Variability, Correlation and Path Analysis Studies in Early Transplanted Rice

Genetic Variability, Correlation and Path Analysis Studies in Early Transplanted Rice

Synoptic‐Scale Extreme Variability of Winter Antarctic Sea‐Ice Concentration and Its Link to Southern Ocean Extratropical Cyclones

AbstractThis study provides a systematic analysis of extreme variability in winter Antarctic sea‐ice concentration (SIC) and its relationship with extratropical cyclones. We characterize sea‐ice variability and cyclone activity in different Southern Ocean sectors using atmospheric reanalyzes and a cyclone‐tracking algorithm, and then quantify the proportion of extreme sea‐ice variability engendered by cyclones of different intensities. The regions with relatively lower sea‐ice area (SIA) (the King Haakon VII, East Antarctic, and Bellingshausen sectors) have an even distribution of cyclones within all intensity ranges, while, in the sectors with higher SIA, the Ross/Amundsen displays a higher number of intense and weak cyclones, and the Weddell sector has the majority of weak cyclones. Our systematic analysis reveals a significant link between extreme variability in winter SIC and: (a) all cyclones in the Ross/Amundsen sector; (b) all but the weakest cyclones in the King Haakon VII, East Antarctic, and Bellingshausen sectors; and (c) all but the most intense cyclones in the Weddell sector. The latter result is explained by the fact that the Weddell sector experiences more frequent, weaker cyclones than the other sectors. Cumulatively, approximately 30%–40% of the extreme sea‐ice variability is caused by extratropical cyclones within all regions.

Heart rate variability for neuro-prognostication after CA: Insight from the Parisian registry

BackgroundHypoxic ischemic brain injury (HIBI) induced by cardiac arrest (CA) seems to predominate in cortical areas and to a lesser extent in the brainstem. These regions play key roles in modulating the activity of the autonomic nervous system (ANS), that can be assessed through analyses of heart rate variability (HRV). The objective was to evaluate the prognostic value of various HRV parameters to predict neurological outcome after CA. MethodsRetrospective monocentric study assessing the prognostic value of HRV markers and their association with HIBI severity. Patients admitted for CA who underwent EEG for persistent coma after CA were included. HRV markers were computed from 5 min signal of the ECG lead of the EEG recording. HRV indices were calculated in the time-, frequency-, and non-linear domains. Frequency-domain analyses differentiated very low frequency (VLF 0.003–0.04 Hz), low frequency (LF 0.04–0.15 Hz), high frequency (HF 0.15–0.4 Hz), and LF/HF ratio. HRV indices were compared to other prognostic markers: pupillary light reflex, EEG, N20 on somatosensory evoked potentials (SSEP) and biomarkers (neuron specific enolase-NSE). Neurological outcome at 3 months was defined as unfavorable in case of best CPC 3–4-5. ResultsBetween 2007 and 2021, 199 patients were included. Patients were predominantly male (64%), with a median age of 60 [48.9–71.7] years. 76% were out-of-hospital CA, and 30% had an initial shockable rhythm. Neurological outcome was unfavorable in 73%. Compared to poor outcome, patients with a good outcome had higher VLF (0.21 vs 0.09 ms2/Hz, p < 0.01), LF (0.07 vs 0.04 ms2/Hz, p = 0.003), and higher LF/HF ratio (2.01 vs 1.01, p = 0.008). Several non-linear domain indices were also higher in the good outcome group, such as SD2 (15.1 vs 10.2, p = 0.016) and DFA α1 (1.03 vs 0.78, p = 0.002). These indices also differed depending on the severity of EEG pattern and abolition of pupillary light reflex. These time–frequency and non-linear domains HRV parameters were predictive of poor neurological outcome, with high specificity despite a low sensitivity. ConclusionIn comatose patients after CA, some HRV markers appear to be associated with unfavorable outcome, EEG severity and PLR abolition, although the sensitivity of these HRV markers remains limited.

Sample and Statistical Analysis on NEOWISE Variability of ATLASGAL Sources

This study focuses on the analysis of mid-infrared variability in a sample of high-mass young stellar objects (YSOs) associated with the cataloged sources from the APEX Telescope Large Area Survey of the Galaxy (ATLASGAL). The Near-Earth Object Wide-field Infrared Survey Explorer Reactivation Mission (NEOWISE) database was used to explore the long-term mid-infrared variability of these high-mass YSOs at a half-year scale. After matching with NEOWISE photometric measurements, a total of 2230 ATLASGAL sources were selected for the variability analysis, out of which 717 were identified as variables. The derived proportions of variables at different evolutionary stages show that the variability rate of high-mass YSOs is highest during the YSO stage and decreases with evolution toward the H ii region stage, resembling the behavior of low-mass YSOs. The variables can be classified into six types based on their light curves, divided into two categories: secular (linear, sin, sin+linear) and stochastic variables (burst, drop, and irregular). The magnitude–color variations observed in ∼160 secular variables can be mainly divided into “bluer when brighter/redder when dimming” and “redder when brighter/bluer when dimming,” likely originating from changes in accretion rate or the effect of extinction due to obscuration. Moreover, several episodic accretion candidates were selected for further observational studies.

Optimal Prescription for Superior Outcomes: A Comparative Analysis of Inter-Individual Variability in Adaptations to Small-Sided Games and Short Sprint Interval Training in Young Basketball Players.

This study compared the inter-individual variability in adaptive responses to six weeks of small-sided games (SSG) and short sprint interval training (sSIT) in young basketball players. Thirty well-trained young athletes (age: 16.4 ± 0.6 years; stature: 190 ± 8.4 cm; weight: 84.1 ± 8.2 kg) voluntarily participated and were randomly assigned to SSG (3 sets of 5 min 3v3 on full length (28 m) and half-width (7.5 m) court, with 2 minutes of passive recovery in-between), sSIT (3 sets of 12 × 5 s sprinting with 20 s recovery between efforts and 2 min of rest between sets), or CON (routine basketball-specific technical and tactical drills) groups, each of ten. Before and after the training period, participants underwent a series of laboratory- and field-based measurements to evaluate their maximum oxygen uptake (V̇O2max), first and second ventilatory threshold (VT1 and VT2), oxygen pulse, peak and average power output (PPO and APO), linear speed, change of direction (COD), countermovement jump (CMJ), and vertical jump (VJ). Both SSG and sSIT sufficiently stimulated adaptive mechanisms involved in enhancement of the mentioned variables (p < 0.05). However, sSIT resulted in lower residuals in percent changes in V̇O2max (p = 0.02), O2pulse (p = 0.005), VT1 (p = 0.001), PPO (p = 0.03), and linear speed (p = 0.01) across athletes compared to the SSG. Moreover, sSIT resulted in more responders than SSG in V̇O2max (p = 0.02, φ = 0.500), O2pulse (p = 0.003, φ = 0.655), VT1 (p = 0.003, φ = 0.655), VT2 (p = 0.05, φ = 0.436), and linear speed (p = 0.05, φ = 0.420). Our results indicate that sSIT creates a more consistent level of mechanical and physiological stimulus than SSG, potentially leading to more similar adaptations across team members.

Studies on genetic variability, character association and path analysis in Niger {Guizotia abyssinica Lf. (Cass)} genotypes

Studies on genetic variability, character association and path analysis in Niger {Guizotia abyssinica Lf. (Cass)} genotypes

Call-Graph-Based Context-Sensitive Points-to Analysis for Java

Pointer analysis or points-to analysis (PTA) is a static program analysis for variables in a program, which determines a set of heap objects that individual variables may refer to at run time. In the literature, various types of context-sensitive analyses have been applied to improve the precision of PTA. In this article, we propose a framework that unifies existing context-sensitive PTA methods, under which we further explore more efficient ways for points-to calculation. In particular, we propose a call-graph-based context generation algorithm that combines the object-sensitive PTA and parameter-sensitive PTA approaches, and we implement the algorithm in the Soot compiler framework. Our new algorithm generates contexts for methods in a more complete and effective way, and it has been shown to achieve better precision with fewer generated contexts and less execution time than some of the known state-of-the-art context-sensitive approaches for PTA when tested with a selection of benchmarks from the DaCapo suite.

Growth, Variability and Decomposition Analysis of Rice in Major States of India

Growth, Variability and Decomposition Analysis of Rice in Major States of India

Identification of Anticancer Enzymes and Biomarkers for Hepatocellular Carcinoma through Constraint-Based Modeling.

Hepatocellular carcinoma (HCC) results in the abnormal regulation of cellular metabolic pathways. Constraint-based modeling approaches can be utilized to dissect metabolic reprogramming, enabling the identification of biomarkers and anticancer targets for diagnosis and treatment. In this study, two genome-scale metabolic models (GSMMs) were reconstructed by employing RNA sequencing expression patterns of hepatocellular carcinoma (HCC) and their healthy counterparts. An anticancer target discovery (ACTD) framework was integrated with the two models to identify HCC targets for anticancer treatment. The ACTD framework encompassed four fuzzy objectives to assess both the suppression of cancer cell growth and the minimization of side effects during treatment. The composition of a nutrient may significantly affect target identification. Within the ACTD framework, ten distinct nutrient media were utilized to assess nutrient uptake for identifying potential anticancer enzymes. The findings revealed the successful identification of target enzymes within the cholesterol biosynthetic pathway using a cholesterol-free cell culture medium. Conversely, target enzymes in the cholesterol biosynthetic pathway were not identified when the nutrient uptake included a cholesterol component. Moreover, the enzymes PGS1 and CRL1 were detected in all ten nutrient media. Additionally, the ACTD framework comprises dual-group representations of target combinations, pairing a single-target enzyme with an additional nutrient uptake reaction. Additionally, the enzymes PGS1 and CRL1 were identified across the ten-nutrient media. Furthermore, the ACTD framework encompasses two-group representations of target combinations involving the pairing of a single-target enzyme with an additional nutrient uptake reaction. Computational analysis unveiled that cell viability for all dual-target combinations exceeded that of their respective single-target enzymes. Consequently, integrating a target enzyme while adjusting an additional exchange reaction could efficiently mitigate cell proliferation rates and ATP production in the treated cancer cells. Nevertheless, most dual-target combinations led to lower side effects in contrast to their single-target counterparts. Additionally, differential expression of metabolites between cancer cells and their healthy counterparts were assessed via parsimonious flux variability analysis employing the GSMMs to pinpoint potential biomarkers. The variabilities of the fluxes and metabolite flow rates in cancer and healthy cells were classified into seven categories. Accordingly, two secretions and thirteen uptakes (including eight essential amino acids and two conditionally essential amino acids) were identified as potential biomarkers. The findings of this study indicated that cancer cells exhibit a higher uptake of amino acids compared with their healthy counterparts.

Study of Genetic Variability and Path Analysis for Yield Attributing Traits in Linseed (Linum usitatissimum L.)

This study was conducted to assess genetic variability, interrelationship among yield attributing traits and their direct and indirect effect on yield. Ninety-two genotypes including four checks was taken in the study and were planted during two seasons i.e., Rabi 2022-23 and Rabi 2023-24 at Research Farm, Department of Genetics &amp; Plant Breeding, College of Agriculture, RVSKVV, Gwalior. These genotypes were evaluated for analysis of genetic variability, phenotypic and genotypic coefficient of variation, correlation and path analysis for seed yield and its related traits. Higher estimates of GCV and PCV were observed for traits like seed yield per plant, harvest index, thousand seed weight, numbers of seeds per capsule, numbers of capsules per plant, numbers of secondary and primary branches. Highly significant and positive correlation with seed yield was documented for numbers of capsules per plant (0.82), numbers of secondary branches per plant (0.64) and thousand seed weight (0.31). Path coefficient analysis revealed that numbers of capsules per plant was the major contributor to the seed yield (0.7950) followed by harvest index (0.1762) and biological yield (0.1211).

Uncertainty quantification in multi-class segmentation: Comparison between Bayesian and non-Bayesian approaches in a clinical perspective.

Automatic segmentation techniques based on Convolutional Neural Networks (CNNs) are widely adopted to automatically identify any structure of interest from a medical image, as they are not time consuming and not subject to high intra- and inter-operator variability. However, the adoption of these approaches in clinical practice is slowed down by some factors, such as the difficulty in providing an accurate quantification of their uncertainty. This work aims to evaluate the uncertainty quantification provided by two Bayesian and two non-Bayesian approaches for a multi-class segmentation problem, and to compare the risk propensity among these approaches, considering CT images of patients affected by renal cancer (RC). Four uncertainty quantification approaches were implemented in this work, based on a benchmark CNN currently employed in medical image segmentation: two Bayesian CNNs with different regularizations (Dropout and DropConnect), named BDR and BDC, an ensemble method (Ens) and a test-time augmentation (TTA) method. They were compared in terms of segmentation accuracy, using the Dice score, uncertainty quantification, using the ratio of correct-certain pixels (RCC) and incorrect-uncertain pixels (RIU), and with respect to inter-observer variability in manual segmentation. They were trained with the Kidney and Kidney Tumor Segmentation Challenge launched in 2021 (Kits21), for which multi-class segmentations of kidney, RC, and cyst on 300 CT volumes are available. Moreover, they were tested considering this and other two public renal CT datasets. Accuracy results achieved large differences across the structures of interest for all approaches, with an average Dice score of 0.92, 0.58, and 0.21 for kidney, tumor, and cyst, respectively. In terms of uncertainties, TTA provided the highest uncertainty, followed by Ens and BDC, whereas BDR provided the lowest, and minimized the number of incorrect certain pixels worse than the other approaches. Again, large differences were seen across the three structures in terms of RCC and RIU. These metrics were associated with different risk propensity, as BDR was the most risk-taking approach, able to provide higher accuracy in its prediction, but failing to assign uncertainty on incorrect segmentation in every case. The other three approaches were more conservative, providing large uncertainty regions, with the drawback of giving alert also on correct areas. Finally, the analysis of the inter-observer segmentation variability showed a significant variation among the four approaches on the external dataset, with BDR reporting the lowest agreement (Dice = 0.82), and TTA obtaining the highest score (Dice = 0.94). Our outcomes highlight the importance of quantifying the segmentation uncertainty and that decision-makers can choose the approach most in line with the risk propensity degree required by the application and theirpolicy.

Impaired autonomic function and somatosensory disturbance in patients with treated autoimmune thyroiditis

Despite treatment with levothyroxine, hypothyroidism and autoimmune thyroiditis (AIT) may be associated with reduced quality of life (QoL), an enigmatic condition referred to as "syndrome T". Peripheral neuropathy, described in untreated thyroid disease, could be a contributing mechanism. We analysed autonomic and somatosensory function in 29 patients with AIT and treated hypothyroidism and 27 healthy volunteers. They underwent heart rate variability (HRV) analysis and quantitative sensory testing (n = 28), comprising 13 parameters of small and large nerve fibre function and pain thresholds. Autonomic cardiovascular function was assessed in rest, deep respiration and orthostasis. Additionally, biomarkers for autoimmunity and thyroid function were measured. Anxiety, depression and QoL were assessed using validated questionnaires. 36% of the patients showed at least one sign of somatosensory small or large fibre dysfunction. 57% presented with mild hyperalgesia to at least one stimulus. Several markers of autonomic function and some detection thresholds were related to the antibody titres. Anxiety, depression scores and QoL correlated to antibody titres and HRV measures. Autonomic and somatosensory dysfunction indicate that in treated hypothyroidism and AIT a subgroup of patients suffers from neuropathic symptoms leading to impaired QoL. Additionally, mild hyperalgesia as a possible sensitisation phenomenon should be considered a target for symptomatic treatment.