Search Results (288)

Smart glasses are promising alternatives for the continuous, unobtrusive monitoring of heart rate (HR). This study validates HR estimates obtained with the “Essilor Connected Glasses” (SmartEW) during sedentary activities. Thirty participants wore the SmartEW, equipped with an IMU sensor for HR estimation, a commercial smartwatch (Garmin Venu 3), and an ECG device (Movesense Flash). The protocol included six static tasks performed under controlled laboratory conditions. The SmartEW algorithm analyzed 22.5 s signal windows using spectral analysis to estimate HR and provide a quality index (QI). Statistical analyses assessed agreement with ECG and the impact of QI on HR accuracy. SmartEW showed high agreement with ECG, especially with QI threshold equal to 70, as a trade-off between accuracy, low error, and acceptable data coverage (80%). Correlation for QI ≥ 70 was high across all the experimental phases (r² up to 0.96), and the accuracy within ±5 bpm reached 95%. QI ≥ 70 also allowed biases to decrease (e.g., from −1.83 to −0.19 bpm while standing), with narrower limits of agreement, compared to ECG. SmartEW showed promising HR accuracy across sedentary activities, yielding high correlation and strong agreement with ECG and Garmin. SmartEW appears suitable for HR monitoring in static conditions, particularly when data quality is ensured. Full article

Two experiments were carried out to evaluate the inclusion impacts of macroalgae Gigartina skottsbergii (Gs) for grazing sheep. Experiment (Exp.) 1 studied the effect of Gs on in vitro gas production (IVGP), dry matter (DM) digestibility (IVDMD), and methane (CH₄) emission using three fistulated sheep and 96 h incubation of samples. In Exp. 2, ten Dohne Merino ewes [5-year-old; 47 ± 0.14 kg body weight (BW)] were randomly assigned to dietary treatments supplemented with Gs at 0 or 450 g DM/d per animal. The study lasted 31 days and was preceded by an adaptation period of 9 days. The BW, body conditional score (BCS), and blood were sampled at the first and the last day of the trial. The results of Exp. 1 showed that Gs supplementation reduced (MCP, p = 0.026) gas production (A), lag time (p = 0.013), and IVDMD (p = 0.071), while it enhanced partition factor (PF96; p = 0.004) and microbial crude protein (MCP) (p = 0.054). The concentration of CH₄ decreased after 3 h (p = 0.0002), 6 h (p = 0.013), and 12 h (p = 0.010) with a tendency at 9 h (p = 0.109) and 24 h (p = 0.068). In Exp. 2, there were no diet effects on the initial BW (IBW, p = 0.77), final BW (FBW, p = 0.91), and average daily gain (ADG, p = 0.24) of ewes; however, Gs supplementation decreased BCS (p = 0.004). Of all blood parameters, only the concentration of glucose (p = 0.021) and albumin (p = 0.011) decreased in the Gs group. Overall, our results revealed that the dietary inclusion of Gs (at 450 g DM/d) affected neither the BW nor ADG of ewes; however, Gs was accompanied by lesser IVGP and CH₄ emission. Full article

This study investigates the performance prediction of poly-crystalline photovoltaic (PV) systems in Jordan using experimental data, analytical models, and machine learning approaches. Two 5 kWp grid-connected PV systems at Applied Science Private University in Amman were analyzed: one south-oriented and another east–west (EW)-oriented. Both systems are fixed at an 11° tilt angle. Linear regression, Least Absolute Shrinkage and Selection Operator (LASSO), ElasticNet, and artificial neural networks (ANNs) were employed for performance prediction. Among these, linear regression outperformed the others due to its accuracy, interpretability, and computational efficiency, making it an effective baseline model. LASSO and ElasticNet were also explored for their regularization benefits in managing feature relevance and correlation. ANNs were utilized to capture complex nonlinear relationships, but their performance was limited, likely because of the small sample size and lack of temporal dynamics. Regularization and architecture choices are discussed in this paper. For the EW system, linear regression predicted an annual yield of 1510.45 kWh/kWp with a 2.1% error, compared to 1433.9 kWh/kWp analytically (3.12% error). The south-oriented system achieved 1658.15 kWh/kWp with a 1.5% error, outperforming its analytical estimate of 1772.9 kWh/kWp (7.89% error). Productivity gains for the south-facing system reached 23.64% (analytical), 10.43% (experimental), and 9.77% (predicted). These findings support the technical and economic assessment of poly-crystalline PV deployment in Jordan and regions with similar climatic conditions. Full article

Extreme wildfire events (EWEs) are becoming increasingly frequent in Mediterranean regions, posing significant threats to ecosystems. This study aimed to support post-fire restoration planning by developing a prioritization framework that categorizes areas according to different levels of vulnerability to the adverse impacts of EWEs. We developed a multi-criteria decision analysis (MCDA) approach to classify these areas within a fire perimeter. The process begins with the collection of available spatial data to assess the pre- and post-fire conditions. Following this, a set of criteria and sub-criteria was established through a participatory approach with local stakeholders. The analytic hierarchy process (AHP) was used to determine stakeholders’ preferences, which were then processed using the Criterium Decision Plus (CDP) version 4 software to support problem modeling. A combined consistency check was applied to ensure both individual coherence and group agreement. Finally, the methodology was integrated using the Ecosystem Management Decision Support (EMDS) software version 9, resulting in a spatial prioritization map that visually represents the levels of restoration priority and serves as a decision-support tool for post-fire restoration planning. Both the process and its results are discussed for an application to a large fire perimeter in the Vale do Sousa forested landscape. Full article

Purpose: We present our single-institution experience of sarcomatous brain metastasis patients who underwent stereotactic radiosurgery (SRS) over the past 35 years. Methods: In total, 31 patients (16 males) who underwent SRS for sarcoma brain metastases were identified. Median age at presentation to SRS was 47 (range: 4–78) months. Common histopathologies included leiomyosarcoma (eight patients), osteosarcoma (six patients), alveolar sarcoma (three patients), Ewing sarcoma (three patients), and undifferentiated/unclassified sarcoma (three patients). The median Karnofsky Performance Score (KPS) was 90. Nine patients underwent pre-SRS craniotomy. The median dose prescribed was 18 Gy. The median cumulative tumor volume was 1.4 cc. Results: Median patient overall survival (OS) after SRS was 7 (range: 0–155) months. Local tumor control (LTC) was achieved in 105 out of 113 tumors, at a median time of 3 (range: 0–17) months between SRS and progression. LTC rates per patient and per tumor were 74.2% and 92.9%, respectively. Following SRS, 10 patients (32.3%) developed new tumors at a median time of 6 (range: 1–25) months. Four patients experienced adverse radiation effects (AREs). At the last follow-up, all patients died, one patient from intracranial progression, 27 from systemic disease progression, and the remaining from unrelated medical conditions. Conclusions: Given high LTC and low ARE rates, this suggests SRS as a strong candidate for the non-invasive management of sarcomatous brain metastases, which typically present late following initial presentation of the primary disease. Full article

Mineral imbalances in sheep can have significant health and economic consequences, yet regional assessments of trace mineral and toxic element status are limited. Oregon is an endemically selenium (Se)-deficient region, but a statewide evaluation has not been conducted. This study assessed whole blood concentrations of 18 elements in 370 clinically normal ewes from 56 farms across Oregon to determine the prevalence of deficiencies and potential toxic exposures. A deficiency threshold of <120 ng Se/mL whole blood was used. We found that 28% of animals were Se-deficient, and 27% of farms had an average whole blood Se below this threshold. No animals reportedly showed overt clinical signs of deficiency or toxicity, and no excessive exposure to toxic elements such as arsenic, lead, or cadmium was found. We also compared mineral concentrations in blood collected using standard EDTA tubes versus mineral-free EDTA tubes, and in whole blood versus plasma, to assess alternative sampling strategies. Strong correlations (r > 0.9) for Se, cobalt (Co), and molybdenum (Mo) between plasma and whole blood allowed for the derivation of conversion equations. These findings provide updated insights into the mineral status of Oregon sheep, contribute to whole blood reference data, and support practical alternatives to improve trace mineral testing in field conditions. Full article

In sheep production, due to the limitations of breeding conditions, the uteri of ewes are often infected with bacteria, resulting in the failure of embryo implantation or loss, causing huge losses to the sheep industry. Therefore, in this study, by using RT-qPCR, Western blot, and immunofluorescence, we investigated the effects of LPS infusion on the immune microenvironment and endometrial receptivity, which play an important role in the process of embryo implantation in ruminants, during the three critical periods of embryo implantation in sheep. The results showed that LPS infusion at day 12, day 16, and day 20 significantly increased the expression of Th1 cytokines (TNF-α, IL-1β, IL-8, IL-6), while significantly decreasing the expression of Th2 cytokines (IL-4 and IL-10) and disrupting the expression of implantation factors, such as ITGB3, ITGB5, VEGF, and LIF, in the endometrial tissues of sheep. Additionally, the protein expression level of TLR4 and the phosphorylation level of ERK were significantly elevated at day 12, day 16, and day 20 after LPS infusion, suggesting that LPS may impair endometrial receptivity through the TLR4/ERK pathway. Validation was conducted in a receptive model of sEECs using TLR4 and ERK phosphorylation inhibitors. Compared with the LPS group, TLR4 and ERK phosphorylation inhibitors significantly reduced the expression of TLR4 and p-ERK, down-regulated Th1 cytokines, up-regulated Th2 cytokines, and alleviated the disruption of genes for attachment. Treatment with 50 μM PTE can significantly alleviate the abnormal expression of implantation genes caused by LPS, and its mechanism may be related to the regulation of the ERK signaling pathway. Full article

In the South Pacific, an increase in the frequency of climate hazards has resulted in worsened human and animal health outcomes, revealing the need for strengthened early warning to increase hazard preparedness. As Vanuatu is one of the most at-risk countries to natural disasters, an early warning system (EWS) for climate hazards is essential to support industries and communities. Notably, climate variability has been found to exacerbate communicable disease burden and compromise livestock health and productivity; however, forecasting of such hazards and their compounding effects has not been developed in Vanuatu. Therefore, our study aims to explore EWSs that monitor and predict the impact of climate variables on malaria incidence and cattle heat stress in Vanuatu. Using monthly precipitation and temperature, a Bayesian model was developed to predict provincial malaria case burden in Vanuatu. Additionally, this study developed a weekly forecasting model to predict periods of cattle heat stress. This model used the Heat Load Index (HLI) as a proxy for heat stress to identify periods of increased heat load and antecedent conditions for cattle heat stress across the provinces. This study was successful in establishing proof-of-concept risk forecasts during selected case study periods: January 2020 and January 2016 for malaria transmission and cattle heat stress, respectively. To contribute towards a future multi-hazard EWS framework for climate hazards in Vanuatu, bulletins for predicted climate-based malaria transmission and cattle heat stress risk were developed to inform key decision makers. Intended to enhance preparedness for malaria outbreaks and cattle heat stress events, this study’s exploration of EWSs can support the resilience of Vanuatu’s public health and agricultural sectors in the face of escalating climate challenges. Full article

The Duobaoshan mineralization area in Heilongjiang Province is a key copper–molybdenum–gold polymetallic region in China. Its southeastern Fudiyingzi–Bacheli area, located at the intersection of the NW-trending copper and NE-trending gold belts, exhibits favorable mineralization conditions. Despite over 70 years of placer gold mining and the discovery of one small copper deposit and one gold deposit, the area remains underexplored with significant peripheral exploration potential. This study integrates 1:50,000 geological mapping, high-precision magnetic surveys, phase-induced polarization, and soil geochemistry through multi-source data fusion for comprehensive mineral prediction. Key steps include delineating Cu, Au, and Mo anomalies and analyzing their associations with Zn, Cd, Ag, As, etc.; inferring NE-, NW-, and near-EW-trending linear structures via magnetic boundary enhancement; dividing high/low resistivity zones and identifying nine significant and six weak phase anomalies using phase-induced polarization; establishing a mineralization model based on typical deposits; and delineating four priority exploration targets. These results provide a scientific basis for further exploration in shallow coverage areas. Full article

Majority of commercial L-asparaginase (L-ASNase) activity assays are based on coupled enzymatic reaction, which converts aspartate into pyruvate, subsequently reacting with the probe to form a stable chromophore, which can be detected spectrophotometrically. However, in complex biological samples this method can be inaccurate due to poor optical transparency or presence of compounds interfering with the coupled enzyme reaction–for this kind of cases alternative methods have been suggested. Here we suggest a strategy to rationally pick a method of choice in a variety of situations, taking into consideration the upsides and downsides of each method. A high-throughput fluorometric assay employing the substrate Asp-AMC was rigorously validated for L-ASPNase activity screening. Aassay performance is evaluated in complex biological matrices, including bovine serum, whole and diluted human blood, and finally the mouse blood and liver homogenates samples obtained from pharmacokinetic studies. This comprehensive validation process ensures the reliability and applicability of the assay for assessing L-asparaginase activity in diverse and physiologically relevant environments. Potential interfering factors and matrix effects were addressed, and assay conditions were optimized for each matrix. The optimized assay was employed to screen various L-asparaginase types (intracellular L-ASNases type I RrA, periplasmic L-ASNases type II EcA and EwA) and ASPNase formulations (conjugates with polyamines or polyelectrolyte complexes), comparing their kinetic parameters and stability. Fourier-transform infrared (FTIR) spectroscopy was further employed to investigate the fine features of molecular mechanisms of L-asparaginase catalysis. FTIR spectra of Asn during hydrolysis were analyzed in buffer solutions and in complex biological matrices, such as blood sample or liver homogenates which is crucial in the context of pharmacokinetic research. This combined fluorometric and FTIR approach provides a powerful platform for optimizing L-ASNase formulations and therapeutic strategies for ALL. Based on the results obtained we have developed a strategy to choose an approach for L-Asparaginase activity assessment for a variety of difficult situations when dealing with complex biological samples. Full article

Sjögren’s disease (SjD) is a systemic autoimmune disorder primarily causing dry eyes and mouth. It frequently overlaps with other autoimmune diseases (AIDs), including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). However, the genetic basis of SjD remains underexplored, limiting our understanding of its connections to other immune-mediated conditions. In this study, we aimed to identify gene networks associated with SjD through the integration of genetic, transcriptomic, and epigenomic data. We further compared the genetic factors of SjD with other immune-mediated diseases. We analyzed genome-wide association studies (GWAS) summary statistics, DNA methylation, and transcriptomic data using our in-house network-based methods, dmGWAS and EW_dmGWAS, to identify key gene modules associated with SjD. In dmGWAS analysis, discovery and evaluation datasets were used to identify consensus results. We conducted gene-set, cell-type, and disease-enrichment analyses on significant gene modules and explored potential drug targets. Genetic correlations and Mendelian randomization were applied to assess SjD’s link with 17 other AIDs and 16 cancer types. dmGWAS identified 207 and 211 gene modules in the discovery and evaluation phases, respectively, while EW_dmGWAS detected 886 modules. Key modules highlighted 55 genes (discovery), 52 genes (evaluation), and 59 genes (EW_dmGWAS), with at least 50 genes from each analysis linked to AIDs and cancer. Enrichment analyses confirmed their relevance to immune and oncogenic pathways. We pinpointed four candidate drug targets associated with AIDs. We developed a novel integrative omics approach to identify potential genetic markers of SjD and compared them with AIDs and cancers. Our approach can be similarly applied to other disease studies. Full article

Ethiopian pastoralist communities are facing a recurrent drought crisis that significantly affects the availability of water and pasture resources for communities dependent on livestock. The increasing intensity, duration and frequency of droughts in the pastoral community in Ethiopia have drawn the attention of multiple stakeholders and increased stakeholder debates on the role of early warning systems (EWSs) for anticipatory action to build climate resilience in the pastoral community. The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), in collaboration with various partners, has developed an interactive web-based digital EWS to provide near real-time information on water and pasture conditions in pastoral and agro-pastoral regions of Ethiopia. In this study, a stakeholder analysis was conducted to identify key stakeholders, understand stakeholder needs, and facilitate collaboration towards sustaining the EWS. The stakeholder analysis revealed the roles and information needs of key actors engaged in livestock water and pasture monitoring and early warning systems aimed at improving the pastoral communities’ resilience. The analysis showed a pressing need for access to real-time information on water and pasture availability and seasonal climate forecasts by local communities for effective and optimal resources management. Local and national governments need similar data for evidence-based decision-making in resource allocation and policy development. International and non-governmental organizations (INGOs) require the same information for efficient humanitarian responses and targeted development interventions. The private sector seeks insights into market dynamics to better align production strategies with community needs. An EWS serves as a vital tool for development partners, facilitating improved planning, coordination, and impact assessment. It also emphasizes the importance of proactive collaboration among stakeholders, including local communities, government bodies, INGOs, and academic and research institutions. Enhanced communication strategies, such as partnerships with local media, are essential for timely information dissemination. Ultimately, sustained collaboration and adaptive strategies are crucial for optimizing the impact of an EWS towards improving the livelihoods and resilience of pastoral communities amid climate variability. Full article

Quantifying extreme weather events (EWEs) and understanding their impacts on vegetation phenology is crucial for assessing ecosystem stability under climate change. This study systematically investigated the ecosystem growing season length (GL) response to four types of EWEs—extreme heat, extreme cold, extreme wetness (surplus precipitation), and extreme drought (lack of precipitation). The EWE extremity thresholds were found statistically using detrended long time series (2000–2022) ERA5 meteorological data through z-score transformation. The analysis was based on a grassland ecosystem in the Mongolian Plateau (MP) from 2000 to 2022. Using solar-induced chlorophyll fluorescence data and event coincidence analysis, we evaluated the probability of GL anomalies coinciding with EWEs and assessed the vegetation sensitivity to climate variability. The analysis showed that 83.7% of negative and 87.4% of positive GL anomalies were associated with one or more EWEs, with extreme wetness (27.0%) and extreme heat (25.4%) contributing the most. These findings highlight the dominant role of EWEs in shaping phenological shifts. Negative GL anomalies were more strongly linked to EWEs, particularly in arid and cold regions where extreme drought and cold shortened the growing season. Conversely, extreme heat and wetness had a greater influence in warmer and wetter areas, driving both the lengthening and shortening of GL. Furthermore, background hydrothermal conditions modulated the vegetation sensitivity, with warmer regions being more susceptible to heat stress and drier regions more vulnerable to drought. These findings emphasize the importance of regional weather variability and climate characteristics in shaping vegetation phenology and provide new insights into how weather extremes impact ecosystem stability in semi-arid and arid regions. Future research should explore extreme weather events and the role of human activities to enhance predictions of vegetation–climate interactions in grassland ecosystems of the MP. Full article

Tree ring chronologies (tree ring width—TRW, earlywood—EW, latewood—LW) were constructed to investigate fir’s (Abies borisii-regis Mattf.) response to key hydrometeorological factors, namely precipitation, temperature and drought (12-month Standardized Precipitation Evapotranspiration Index, SPEI-12). There has been only one previously published study conducted in the northern area of the species’ expansion (Albania). The current study was conducted in the southern area of the species’ expansion (Central Greece). Precipitation was the most important factor that affected tree growth. May precipitation was positively correlated with LW, while June and July precipitation was positively correlated with both EW and LW. Previous September precipitation was positively correlated with EW and LW. Interestingly, the current September precipitation was negatively correlated with EW. High temperatures in April showed a positive relation with LW, high temperatures in June negatively affected all chronologies, while high temperatures July and August were negatively related with LW. High autumn temperatures in the previous year significantly (negatively) influenced all tree ring chronologies. The SPEI index revealed that wet conditions during May and June positively correlated with high tree growth for both EW and LW, while wet conditions in July and August significantly affect LW formation. Wet conditions in the previous September also had a positive effect on tree growth. SPEI showed similar behavior with precipitation, showing that precipitation is the driving factor in fir growth. The results highlight the importance of summer rainfall and temperature in controlling tree growth in Mediterranean regions. The study revealed significant knowledge on the susceptibility of Abies borisii-regis Mattf. to climate variability and highlighted its consequences for future forest management plans. Full article

Background: to date, there are no specific markers available for diagnosing sepsis. Diagnosis is, indeed, mainly determined by clinical suspicion and the evaluation of the patient’s overall condition. This evaluation involves assessing various inflammatory markers, such as C-reactive protein (CRP) and procalcitonin (PCT), along with markers of tissue hypoxia, such as serum lactate. Additionally, it includes scores that account for complete blood count (CBC), organ function markers, and the patient’s vital parameters, including SOFA, qSOFA, SIRS, and NEWS. Over the years, various potential biomarkers have been studied; among these presepsin appears to offer some significant advantages. Objective: Presepsin, which is the N-terminal fragment of the soluble component of CD14, is primarily elevated in infectious conditions. Its levels rise much earlier in the context of infection compared to currently used biomarkers. As a result, Presepsin shows promise for the early identification of septic patients and could aid in prognostic assessment, allowing clinicians to prioritize care for critically ill individuals. Methods: this study aims to evaluate the role of serum presepsin in the early diagnosis of sepsis in patients who present to the emergency room with a clinical suspicion of sepsis. The secondary objectives include comparing the diagnostic performance of presepsin with traditional biomarkers currently used for sepsis diagnosis and assessing its utility as a prognostic biomarker for mortality risk stratification, in comparison with validated severity prediction scores. Result: Presepsin had valuable diagnostic utility for sepsis (AUC 0.946, p < 0.001) comparable to PCT (AUC 0.905, p < 0.001). Conclusions: the combination of Presepsin, PCT, and EWS yielded the highest diagnostic accuracy for sepsis. Full article