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Illusory finger stretching and somatosensory responses in participants with chronic hand-based pain
Current pharmaceutical interventions for chronic pain are reported to be minimally effective, leading researchers to investigate non-pharmaceutical avenues for chronic pain treatment. One such avenue is resizing illusions delivered using augmented reality. These illusions resize the affected body part through stretching or shrinking manipulations and have been shown to give analgesic effects; however, the neural underpinnings of these illusions remain undefined. Steady-state evoked potentials (SSEPs) have been studied within populations without chronic pain undergoing hand-based resizing illusions, finding no convincing differences in SSEP amplitudes during illusory stretching. Here, we present comparable findings from a sample with chronic pain, who are thought to have blurred cortical representations of painful body parts, but again find no clear differences in SSEP amplitude during illusory stretching. However, no significant decreases in pain ratings were found following illusory resizing, and changes in SSEP amplitudes are thought to possibly reflect experiences of illusory analgesia. Despite a lack of illusory analgesia across the sample, several participants experienced clinically meaningful levels of pain reduction following illusory resizing, highlighting the potential of resizing illusions as an analgesia treatment avenue. Subjective illusory experience data showed significantly greater experiences of the illusion in the multisensory (visuotactile) condition compared to non-illusion conditions and a unimodal visual condition, replicating findings from participants without chronic hand-based pain. Exploratory analyses using subjective disownership data show that the multisensory condition did not elicit significant disownership experiences, demonstrating that the pain reductions seen in the multisensory condition do not arise from disownership of the limb, but more likely as a direct result of the illusory resizing manipulations.
Optimization of multiple sampling for solving network boundary specification problem
BCL6 (B-cell lymphoma 6) expression in adenomyosis, leiomyomas and normal myometrium
Adenomyosis and leiomyomas are common benign uterine disorders characterized by abnormal cellular proliferation. The BCL6 protein, a transcriptional repressor implicated in cell proliferation and oncogenesis, has been linked to the pathogenesis of endometriosis. This study investigates BCL6 expression in adenomyosis, leiomyomas, and normal myometrium using immunohistochemistry and deep learning neural networks. We analyzed paraffin blocks from total hysterectomies performed between 2009 and 2017, confirming diagnoses through pathological review. Immunohistochemistry was conducted using an automated system, and BCL6 expression was quantified using Fiji-ImageJ software. A supervised deep learning neural network was employed to classify samples based on DAB staining. Our results show that BCL6 expression is significantly higher in leiomyomas compared to adenomyosis and normal myometrium. No significant difference in BCL6 expression was observed between adenomyosis and controls. The deep learning neural network accurately classified samples with a high degree of precision, supporting the immunohistochemical findings. These findings suggest that BCL6 plays a role in the pathogenesis of leiomyomas, potentially contributing to abnormal smooth muscle cell proliferation. The study highlights the utility of automated immunohistochemistry and deep learning techniques in quantifying protein expression and classifying uterine pathologies. Future studies should investigate the expression of BCL6 in adenomyosis and endometriosis to further elucidate its role in uterine disorders.
UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data
Unraveling multimodality of digital health records by comparing mortality trajectories of diagnoses of diseases from over 12 million patients
Understanding the multimodality of digital health data, including the scope of death records, is essential for adequate data acquisition to build a research framework for the health sciences. In this study, I leveraged the diverse healthcare records of over 12 million patients to reconstitute mortality trajectories that navigate the sequence of disease processes shared among patients from initial presentation through interim conditions that ultimately terminate in fatal outcomes. I conducted a comprehensive analysis of longitudinal discharge records for 10.4 million patients from US hospitals, utilizing the US State Inpatient Data (USSID) including 290,253 records of deaths in clinics. I also scrutinized the cross-sectional records of Korea from the billing reviews, specifically the National Inpatients Set of Korea (NISK), encompassing 2.1 million patients. By tracing the diagnostic timelines of patients diagnosed with significant comorbid diseases (False Discovery Rate (FDR) <0.1), I built mortality trajectories, mapping the temporal progression of disease diagnoses resulting in death. My trajectory model rewired 705 significant mortality trajectories across both datasets (USSID and NISK). The presented mortality trajectories successfully recapitulated established patterns of mortality for each country, while also revealing different trajectories leading to death, influenced by the modality of data. For example, viral hepatitis, a known predisposing feature of liver cancer in Asia, was observed to initiate in younger Koreans. Interestingly, owing to the collection of hospital records, the modeled mortality trajectories derived from the USSID converged towards sepsis. Although a substantial sequence of diagnostic processes is shared between USSID and NISK, the multimodality of these two datasets highlights different diagnoses preceded by fatal outcomes. Unraveling mortality patterns is feasible with an appropriate understanding of the multimodality of digital health data.
Experimental data suggest between population reversal in the condition dependence of two sexually selected traits
Abstract When viewing mate choice as a process of adaptive evolution, the condition-dependence of sexual ornaments represents a central pillar. Experimental tests of condition-dependence are few and refer to one population per species. The first brood size manipulation experiment aimed to test ornament condition-dependence had been reported from a Swedish population of collared flycatchers. Here we report a similar experiment conducted in a Hungarian population, examining the change of white plumage patch sizes of male parents by the next year and the patch sizes of male offspring in adulthood. The results consistently indicate that experimentally modified reproductive effort affects male wing, but not forehead patch size. To the contrary, previous results from the Swedish population indicated significant effects on forehead, but not wing patch sizes. Both patches are sexually selected in both populations, so the diverging results offer the first experimental suggestion of a trait by population crossover in the information content of two sexual ornaments. We conclude that explaining why some ornaments are condition-dependent is still far ahead, and further, preferably experimental population comparisons would be helpful.
Socioeconomic disparities in depression risk: Limitations of the moderate effect of physical activity changes in Korea
This study investigates the influence of changes in physical activity (PA) patterns on depression risk across different socioeconomic statuses (SES) in Korea. Utilizing National Health Insurance Data (NHID) from over 1.2 million individuals during 2013–2016, we matched medical aid beneficiaries with health insurance beneficiaries, excluding those with prior depression or incomplete PA data. Changes in moderate-to-vigorous PA (MVPA) were categorized into 16 groups, and depression incidence was tracked from 2019 to 2021. After adjustment, medical aid beneficiaries consistently showed higher risks of depression compared to health insurance enrollees with the same physical activity (PA) change patterns. For those consistently inactive, the risk was 1.68 times higher (aOR, 1.68; 95% CI, 1.37–2.05). Those who increased PA from inactivity to moderate-to-vigorous activity 3–4 times per week had a 3.33 times higher risk (aOR, 3.33; 95% CI, 1.72–6.43). Additionally, the risk was 2.64 times higher for those increasing from 1–2 times to ≥5 times per week (aOR, 2.64; 95% CI, 1.35–5.15), and 2.83 times higher for those consistently engaging in PA 3–4 times per week (aOR, 2.83; 95% CI, 1.35–5.94). Across the overall PA patterns, medical aid beneficiaries consistently faced higher depression risks, with risk increases of 1.80 times for increased activity, 1.68 times for continuous inactivity, and 1.34 times for decreased activity compared to health insurance beneficiaries with the same PA change patterns. However, in the consistently very active group, no significant difference in the risk of depression was observed between the two groups. Limitations include potential bias in self-reported PA and the NHIS data not fully capturing depression severity. The findings underscore the significant impact of SES on mental health, with consistently high PA levels potentially mitigating SES-related depression risk.
On the time lag between sea-level rise and basin infilling at tidal inlets
Spatio-temporal variation in pollen collected by honey bees (Apis mellifera) in rural-urban mosaic landscapes in Northern Europe
Pollen is a source of protein, lipids, vitamins and minerals for bees and other flower-visiting insects. The composition of macro- and micronutrients of pollen vary among different plant species. Honey bees are long-distance foragers, collecting nectar and pollen from plants within several kilometers of their hive. Availability of pollen within the foraging range of honey bees is highly dynamic, changing seasonally, and across different landscapes. In the present study, the aim was to investigate the composition of pollen collected by honey bees in rural-urban landscape mosaics typical of Northern Europe. Samples of corbiculate pollen were collected 3–9 times during the growing season by citizen scientist bee keepers from a total of 25 observation apiaries across Denmark in 2014–2015. Palynological analysis was conducted identifying 500 pollen grains per sample to pollen type (mostly plant genus). Pollen diversity denoted the number of different pollen types in a sample, while relative abundance was calculated as the proportional representation of a pollen type, if found in >1% of the sample. The quantity of pollen types across study years and sites was measured as the occurrence of each pollen type (number of samples with the pollen type present) and abundance (total number of pollen grains). Pollen diversity was highly variable, with effects of season, year, and area of green urban spaces. In terms of quantity, a few key pollen types occurred repeatedly and abundantly in the samples. Only 17 pollen types were present in >15 samples. These pollen types were consistent across study years and different landscapes. Pollen diversity may impact colony health, and hence foraging decisions by honey bees, especially in late summer. However, the bulk of the pollen collected by colonies came from a limited number of pollen sources, regardless of year and landscape context in the rural-urban landscape mosaics of Denmark.
Inter-reader agreement for diagnosing thymic cysts on chest MRI in two tertiary referral centers
Burnout among intensivists and critical care fellows in South Korea: Current status and associated factors
Burnout among critical care physicians is an important issue that affects patient care and staff well-being. This study, conducted by the Korean Society of Critical Care Medicine, aimed to investigate the prevalence and associated factors of burnout among intensivists and critical care fellows in South Korea. From May to July 2019, a cross-sectional survey was conducted in 51 hospitals and 79 intensive care units offering subspecialty training in critical care medicine. Invitations were sent by email and text, and responses were collected using NownSurvey and Google Forms. Of the 502 invited participants, 253 responded (response rate: 50.4%). Significant contributing factors of burnout included being in an intensivist position (assistant professor/fellow) (odds ratio [OR], 3.916; 95% confidence interval [CI], 1.485–10.327; p = 0.006), working in a medical ICU (OR, 4.557; 95% CI, 1.745–11.900; p = 0.002), the number of stay-home night calls per month (OR, 1.070; 95% CI, 1.005–1.139; p = 0.034), and recent conflicts with colleagues (OR, 5.344; 95% CI, 1.140–25.051; p = 0.033). Similar factors were found to influence severe levels of burnout. This nationwide study indicates that a significant proportion of critical care physicians in South Korea experience burnout. Strategies to reduce overtime and workplace conflict are imperative to reduce burnout among these physicians and protect their mental health. Future research should explore targeted interventions for these specific factors.
Error fields: personalized robotic movement training that augments one’s more likely mistakes
Armed violent conflict and healthcare-seeking behavior for maternal and child health in sub-Saharan Africa: A systematic review
Background Over 630 million women and children worldwide have been displaced by conflict or live dangerously close to conflict zones. While the adverse effects of physical destruction on healthcare delivery are relatively well understood, the effects on healthcare-seeking behavior remain underexplored, particularly in sub-Saharan Africa. This study aims to better understand the interconnections and knowledge gaps between exposure to armed violent conflicts and healthcare-seeking behaviors for maternal and child health in sub-Saharan Africa. Methods Five key electronic databases (PubMed, Scopus, Web of Science, PsycNET, and African Journals Online) were s earched for peer-reviewed publications between 2000 and 2022. The review was designed according to PRISMA-P statement and the protocol was registered with PROSPERO database. The methodological quality and risks of bias were appraised using GRADE. A data extraction instrument was modelled along the Cochrane Handbook for Systematic Reviews and the Centre for Reviews and Dissemination of Systematic Reviews. Result The search results yielded 1,148 publications. Only twenty-one studies met the eligibility criteria, reporting healthcare-seeking behaviors for maternal and child health. Of the twenty-one studies, seventeen (81.0%) reported maternal health behaviors such as antenatal care, skilled birth attendance, postnatal care services, and family planning. Nine studies (42.8%) observed behaviors for child health such as vaccination uptake, case management for pneumonia, diarrhea, malnutrition, and cough. While conflict exposure is generally associated with less favorable healthcare-seeking behaviors, some of the studies found improved health outcomes. Marital status, male partner attitudes, education, income and poverty levels were associated with healthcare-seeking behavior. Conclusion There is a need for multifaceted interventions to mitigate the impact of armed violent conflict on healthcare-seeking behavior, given its overall negative effects on child and maternal healthcare utilization. While armed violent conflict disproportionately affects children’s health compared to maternal health, it is noteworthy that exposure to such conflicts may inadvertently also lead to positive outcomes. Prospero registration number CRD42023484004 .
Optimal multiobjective design of an autonomous hybrid renewable energy system in the Adrar Region, Algeria
Multilevel analysis of factors associated with suicide attempts: Evidence from 2022/2023 Mozambique Demographic and Health Survey
Background This issue represents a major global public health concern, accounting for approximately 703,000 deaths each year. Despite Mozambique having the 9th highest suicide rate in the world and the highest in Africa, there is no national data quantifying the burden of suicide attempts. Therefore, this study aimed to assess the prevalence of suicide attempts and identify individual and community-level factors associated with them using mixed-effects logistic regression. This study is crucial for developing early interventions, which can help reduce the risk of suicide and enhance overall mental health outcomes for young people. Method The data used in this study were drawn from the 2022/2023 Mozambique Demographic and Health Survey (MDHS). A weighted sample of 10,909 individuals (7,716 males and 3,149 females) aged 15–29 was included. The fitted model was evaluated using AIC and BIC, with the model having the lowest Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) is another statistical measure used to assess the quality of a model, similar to the Akaike Information Criterion (AIC). The results of the final model were presented as Adjusted Odds Ratios (AOR) with 95% confidence intervals (CI). Variables were considered statistically significant if their p-value was less than 0.05 in the multivariable analysis. Results About 3.60% (95% CI: 3.33%-4.03%) of participants were seriously considered suicide attempt in the past 12 months of before the survey. Educational status, occupation, marital status, depression, anxiety, and geographic region were significant factors associated with suicidal attempt. Conclusion The findings of this study enhance our understanding of the intricate relationships between suicide attempts and their predictors. Additionally, the results highlight the need for targeted interventions and mental health promotion strategies that consider the identified individual and community-level factors to reduce suicide rates in Mozambique.
CADD based designing and biological evaluation of novel triazole based thiazolidinedione coumarin hybrids as antidiabetic agent
Correction: Evaluation of TNF-α, IL-10 and IL-6 Cytokine Production and Their Correlation with Genotype Variants amongst Tuberculosis Patients and Their Household Contacts
Halodule uninervis extract facilitates the green synthesis of gold nanoparticles with anticancer activity
Abstract Gold nanoparticles (AuNPs) have been utilized in a plethora of applications due to their unique optical properties, high stability, and great biocompatibility. The use of plant extracts in the biosynthesis of AuNPs has emerged as an eco-friendly, inexpensive, and nontoxic approach. In the present study, the ethanolic extract of Halodule uninervis (HUE) was used for the first time in the green synthesis of AuNPs. The biogenic AuNPs were characterized using several spectroscopic and microscopic techniques and their anticancer potential was investigated. They displayed a surface plasmon resonance (SPR) band at 550 nm. Scanning electron microscopy (SEM) and Dynamic light scattering (DLS) analysis proved the synthesis of small and spherical AuNPs with a zeta potential of − 27.66 mV. X-ray diffraction (XRD) pattern established the crystalline nature of AuNPs. Thermogravimetric analysis (TGA) and Fourier transform infra-red spectroscopy (FTIR) data confirmed the role of HUE in the capping and stabilization of the manufactured AuNPs. The produced AuNPs exhibited anticancer activity against several human cancer cell lines, highlighting their potential efficacy as anticancer therapeutic agents. Further analysis revealed that this observed cytotoxicity is mediated via the induction of apoptosis. Overall, our data validate the effective use of H. uninervis extract in the biosynthesis of AuNPs with significant biological properties.
Simulation study for the energy and position reconstruction performances of the beam monitoring system of Carbon Ion Radiation Therapy using GEANT4
Carbon Ion Radiation Therapy is operated in several countries because of its advantage to have high dose concentration and/or high linear energy transfer (LET). To estimate the beam performance of Carbon Ion Radiation Therapy, we target the 1% energy and 1 mm2 position resolutions of the beam monitoring system. The beam monitoring system consists of a scintillation crystal and fiber hodoscope. The scintillation crystal is 20 × 20 × 120mm3 and its candidates are LYSO, CsI and BGO. The fiber hodoscope is composed of 1 mm thickness scintillation fibers and the fibers are arranged vertically for 2D reconstruction. With GEANT4 simulation, we verify the performance of our beam monitoring system. The energy response of the LYSO and BGO scintillators is linear within ± 2%. The energy resolution of each crystal candidate achieves the goal; LYSO (0.061%), CsI (0.20%) and BGO (0.10%). The position is reconstructed via fiber hodoscope within 5% uncertainty.