Browse Articles

Bioinformatic and genomic analysis identifies C allele of APOE rs7412 as the most prominent variant limiting extreme human longevity

Fully secure and hierarchical identity based signature for automatic dependent surveillance broadcast systems

Beyond accuracy: a framework for evaluating algorithmic bias and performance, applied to automated sleep scoring

Utility of the serum alanine aminotransferase to high density lipoprotein cholesterol ratio in evaluating nonalcoholic fatty liver disease and liver fibrosis

A novel compound DBZ alleviates chronic inflammatory pain and anxiety-like behaviors by targeting the JAK2-STAT3 signaling pathway

Calibrated muscle models improve tracking simulations without enhancing gait predictions

Objectives : This study presents two main aims: (i) to assess functionally-calibrated musculoskeletal models (FCMs) in both tracking and predictive simulations of human motion, against non-linearly scaled models (NSMs), and (ii) to examine the effects of three different variations of our baseline functional calibration approach on the results of tracking and predictive simulations. Methods : Motion capture experiments of six functional activities were performed with three healthy subjects. The musculotendon (MT) parameters of 18 muscles per leg were estimated using an optimal control problem. A baseline problem formulation and three variations were developed to generate four different FCMs per subject. Then, the FCMs were compared against NSMs in tracking simulations of the motions excluded from the calibration and fully-predictive simulations of gait. Results : In the tracking simulations, the FCMs led to more accurate joint torques estimations. Including gait in the calibration problems improved the knee torques accuracy (normalised root mean square error: 0.31 ± 0.11), compared to the baseline calibration (normalised root mean square error: 0.70 ± 0.21). Regarding the gait predictive simulations, the NSMs consistently yielded more accurate subtalar inversion/eversion torques and knee flexion angles, compared to the FCMs. The accuracy of the predicted muscle excitations was generally consistent between NSMs and FCMs. Conclusion : The results suggest that, while the FCMs led to more accurate joint torques estimations in the tracking simulations, they did not outperform the NSMs in the fully-predictive gait simulations.

Retrospective comparative study on efficacy and safety of different surgical procedures for pelvic organ prolapse

Serum proteomics identify biomarkers and pathogenesis of portopulmonary hypertension diagnosed based on echocardiography

PI3K/AKT signaling pathway plays an important role in the pathogenesis of metabolic dysfunction-associated steatotic liver disease

Enhancing mental well-being in university students through multicomponent low intensity positive education and the mediating role of civic engagement

Efficacy of combined TAE, HAIC, targeted, and immunotherapy in unresectable HCC: a multicenter propensity score matching study

Reduced hair cortisol concentrations are associated with improved emotional wellbeing in older adults following repeated forest walking

Abstract The main hypothesis of this study in older adults is that repeated walks in a forest but not an urban environment for one month lead to reduced chronic stress compared to the previous month without any intervention. This was achieved by the measurement of cumulative cortisol concentrations in hair. Older adults of both sexes ( n  = 54; 71 ± 6.2 years) participated in a randomised, parallel-group trial. They were randomly assigned to a forest or an urban walking group. They completed two 40-minute walking sessions per week over one month. Hair samples and morning, as well as afternoon salivary samples, were collected at baseline and following one month of walking interventions. A significant reduction in cumulative hair cortisol was observed during the month of repeated forest but not urban walking compared to the previous month, indicating decreased chronic stress. Salivary cortisol concentrations decreased in the forest group only. No differences in salivary alpha-amylase activity were noticed. Walking activities had no negative impact on the diurnal rhythmicity of stress markers. Quality of life measures showed improvements in emotional well-being in the forest group. A negative correlation was found between hair cortisol and certain quality of life dimensions in urban but not forest groups. Repeated forest walks affect objective measures of chronic stress in older adults, evidenced by lower cumulative hair cortisol concentrations and improved emotional well-being. These findings encourage incorporating forest-based interventions into mental health programs for older adults aimed at enhancing well-being, stress coping, and cognitive functions.

Globalized parameter tuning of microwave passives by dimensionality-reduced surrogates and multi-fidelity simulations

Abstract Parameter tuning is an essential but demanding aspect of microwave component design, particularly when global optimization is required. The process becomes especially demanding due to the extensive electromagnetic (EM) simulations involved, which—when using popular nature-inspired methods—can lead to unmanageable computational costs. Traditional mitigation approaches, such as surrogate-based methods, often struggle with the curse of dimensionality and the highly nonlinear responses of microwave circuits. This study introduces an alternative approach for rapid global optimization of microwave passive components using artificial intelligence (AI) techniques, specifically, machine learning (ML). The core elements of our methodology include reduction of the problem dimensionality using a rapid global sensitivity analysis, multi-fidelity EM simulations, and a two-stage search process. During the global optimization stage, surrogate-assisted ML is confined to a reduced-dimensionality region, leading to significant computational savings and enhanced predictive accuracy of the surrogate models. Additional speedup is achieved by performing the search using low-fidelity EM models. The final local refinement stage employs high-resolution models and is executed within the design space of full dimensionality, ensuring the quality of the final design. Our procedure was comprehensively validated using four microstrip circuits and has demonstrated superiority over state-of-the-art benchmark methods. The average optimization cost is equivalent to only about ninety EM simulations. Further, the quality of the resulting designs remains competitive with those rendered using the benchmark methods.

Dielectric properties of individual cryoprotective agents and cocktails VS55, M22, DP6 at subzero temperatures for cryopreservation

High-throughput epigenetic profiling immunoassays for accelerated disease research and clinical development

Far-red LED light alters circadian rhythms and elicits dark-adapted ERG responses in rodents

Rodents are assumed to be blind to red light, thus red light is often used in the dark phase of a light/dark cycle to facilitate study procedures using nocturnal rodents. However, effects of red light in dark phase on behaviors and circadian rhythms in rodents are not yet clear. Thus, we evaluated effects of various long wavelength red light-emitting diode (LED) light on circadian rhythm and electroretinogram (ERG) in C57BL/6J mice and Wistar Han rats. Animals were implanted with telemetry devices to measure body temperature, heart rate, blood pressure, and locomotor activity for circadian rhythm assessment. In contrary to infra-red light, all visible long wavelength red lights, including the far-red LED light with a peak at 741 nm, induced significant alterations in circadian rhythms and dark-adapted rod photoreceptor-mediated ERG responses in mice and/or rats. However, far-red light did not elicit light-adapted cone photoreceptor-mediated ERG responses in both mice and rats. These findings demonstrate that rodents can perceive all spectrum of long wavelength red lights that are visible to humans, and exposures of red lights in dark phase interfere with their circadian rhythms. A dim far-red LED with peak wavelength in the range of 740–760 nm is recommended to use in the dark phase of a rodent room, and potential impacts are considered when using red light >2 photopic lux.

Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystems

Exploring fungal pathogens to control the plant invasive Rubus niveus on Galapagos Island San Cristobal

How sample handling distorts telomere studies

Abstract Telomere length (TL) is investigated as a biomarker for aging and disease-susceptibility, but measurement using quantitative polymerase chain reaction (qPCR) faces challenges in accuracy and reproducibility. The potential impact of pre-analytical factors on TL measurements remains underexplored. We evaluated the impact of delayed blood processing, a typical feature in population studies. Blood samples from 35 adults were processed for buffy coat extraction either immediately or kept at 4 °C and processed after three and seven days (total n = 105). After processing, samples were stored at -80 °C. Relative TL was measured via qPCR and expressed as T/S ratio. Strikingly, delayed blood processing led to a significant increase in TL: the mean T/S ratio was 0.886 ± 0.205 at day 0, rising to 1.022 ± 0.240 at day 3 (p = 0.03) and to 1.190 ± 0.205 at day 7 (p < 0.001), corresponding to increases of 15% and 34%, respectively. Notably, TL correlated inversely with DNA integrity. These findings underscore the critical impact of delayed sample processing on TL measurements, emphasizing the need for consistent pre-analytical protocols to ensure accurate and reliable research outcomes. The impact of our findings is considerable as it may overshadow not only previously reported results but also real biological differences in TL between studied groups of patients.

A phase 1 safety and feasibility trial of a ketogenic diet plus standard of care for patients with recently diagnosed glioblastoma

Abstract Despite great interest, there is limited clinical evidence to support the use of a ketogenic diet (KD) for cancer patients. We conducted a single-arm phase 1 trial of a KD among patients with recently diagnosed glioblastoma (GBM) receiving standard-of-care (SOC) treatment. Adults with GBM within 3 months of diagnosis followed a supervised 16-week intervention of a 3:1 KD (Fat(g): Carbohydrate + Protein(g)) plus SOC chemoradiation. The primary outcome was safety, evaluated by weekly assessments of weight and body mass index (BMI). Secondary outcomes included feasibility (pre-specified as > 50% of patients maintaining blood ketone levels > 0.3 mM over 50% of study days), progression-free survival (PFS), overall survival (OS), health-related quality-of-life, and cognitive function. Twice daily blood glucose and ketones, weight/BMI, physical activity, and sleep were assessed by remote monitoring. Seventeen patients were evaluable: 53% women, median age 55, median Karnofsky Performance Status 85. All subjects met the primary safety objective with no instances of excessive weight loss or related serious adverse events. Adherence was high: all 17 patients maintained nutritional ketosis (≥ 0.3 mM/dL) > 50% of study days. Median PFS and OS were 12.9 months and 29.4 months from KD initiation respectively. Quality of Life, symptom control, and cognitive function remained stable or improved, although these did not reach statistical significance. This phase 1 trial demonstrates that KD is safe and feasible for GBM patients receiving SOC, may improve outcomes, and provides a foundation for an NCI-funded multicenter randomized diet trial to assess efficacy that is currently underway.