Response Metrics Research Articles

Gain scheduling of backstepping sliding mode controller using optimized type-1 Sugeno fuzzy logic approach for quadcopter

Purpose This paper aims to propose an optimized type-1 Sugeno fuzzy logic backstepping sliding mode controller (T1-SFL-BSMC) to control the altitude and rotational behaviour of a quadcopter. The proposed controller improves the performance of the system by overcoming the limitations of conventional trial-and-error techniques for BSMC gain design. Design/methodology/approach In this study, the type-1 Sugeno fuzzy logic controller (T1-SFLC) technique is proposed which dynamically modifies the BSMC gains. In addition, the parameters of T1-SFLC are further tuned by five different optimization techniques, namely, genetic algorithm, particle swarm optimization (PSO), pattern search (PS), simulated annealing (SA) and adaptive neural network (ANN). Findings The effectiveness of these optimization techniques in tuning the T1-SFLCs for the gain scheduled BSMC is evaluated in terms of time response metrics; rising time, settling time and root mean square error (RMSE) for altitude and rotational behaviour. The results demonstrated that PSO-optimized T1-SFL-BSMC provides better responses in terms of time response metrices with reduced rise and settling times and minimized RMSE when compared to other optimized T1-SFL-BSMC. Originality/value This paper proposes a novel approach for controlling quadcopters by combining fuzzy logic with a BSMC. It is then improved by using many optimization strategies. A more dependable and effective approach to controller design is provided by the suggested method, which is essential for unmanned aerial vehicle applications.

Generative Artificial Intelligence Responses to Common Patient-Centric Hand and Wrist Surgery Questions: A Quality and Usability Analysis.

Background: Due to the rapid evolution of generative artificial intelligence (AI) and its implications on patient education, there is a pressing need to evaluate AI responses to patients' medical questions. This study assessed the quality and usability of responses received from two prominent AI platforms to common patient-centric hand and wrist surgery questions. Methods: Twelve commonly encountered hand and wrist surgery patient questions were inputted twice into both Gemini and ChatGPT, generating 48 responses. Each response underwent a content analysis, followed by assessment for quality and usability with three scoring tools: DISCERN, Suitability Assessment of Materials (SAM) and the AI Response Metric (AIRM). Statistical analyses compared the features and scores of the outputs when stratified by platform, question type and response order. Results: Responses earned mean overall scores of 55.7 ('good'), 57.2% ('adequate') and 4.4 for DISCERN, SAM and AIRM, respectively. No responses provided citations. Wrist question responses had significantly higher DISCERN (p < 0.01) and AIRM (p = 0.02) scores compared to hand responses. Second responses had significantly higher AIRM (p < 0.01), but similar DISCERN (p = 0.76) and SAM (p = 0.11), scores compared to the first responses. Gemini's DISCERN (p = 0.04) and SAM (p < 0.01) scores were significantly higher than ChatGPT's corresponding metrics. Conclusions: Although responses are generally 'good' and 'adequate', there is variable quality with respect to platform used, type of question and response order. Given the diversity of publicly available AI platforms, it is important to understand the quality and usability of information patients may encounter during their search for answers to common hand and wrist surgery questions. Level of Evidence: Level IV (Therapeutic).

Advancing Information Governance in AI-Driven Cloud Ecosystem: Strategies for Enhancing Data Security and Meeting Regulatory Compliance

This study explores adaptive information governance models to address critical challenges in AI-driven cloud environments, focusing on enhancing data security and achieving regulatory compliance. Existing frameworks often fail to account for the complexities introduced by AI and cloud integration, leaving significant gaps in incident response, privacy protection, and governance practices. To bridge these gaps, this research evaluates governance components—Privacy-Enhancing Technologies (PETs), ethical oversight, and incident response metrics—through advanced quantitative methods, including Structural Equation Modeling (SEM), Cox Proportional Hazards Modeling, and Difference-in-Differences (DiD) analysis. Key findings highlight the significant influence of incident response metrics (β = 0.51, p &lt; 0.001) and PET integration (β = 0.25, p = 0.001) on governance effectiveness, with model fit indices (RMSEA = 0.04, CFI = 0.96) confirming the robustness of the proposed framework. Industry-specific vulnerabilities were identified, with retail and technology sectors experiencing a 25% increased risk of incidents due to minimal security controls. The adoption of PETs, such as federated learning and homomorphic encryption, significantly improved privacy compliance and data utility, particularly in high-risk sectors. The study recommends the integration of advanced security controls and PETs to mitigate risks and improve compliance, especially in vulnerable industries like retail and technology. It also emphasizes the continuous optimization of AI-driven incident response protocols to reduce the impact of emerging threats. Furthermore, ethical oversight should be prioritized to ensure fairness, accountability, and public trust in AI applications within cloud ecosystems. These actionable strategies provide a roadmap for organizations to achieve secure and ethically governed cloud environments.

Development and validation of the Normalized Organoid Growth Rate (NOGR) metric in brightfield imaging-based assays

This study focuses on refining growth-rate-based drug response metrics for patient-derived tumor organoid screening using brightfield live-cell imaging. Traditional metrics like Normalized Growth Rate Inhibition (GR) and Normalized Drug Response (NDR) have been used to assess organoid responses to anticancer treatments but face limitations in accurately quantifying cytostatic and cytotoxic effects across varying growth rates. Here, we introduce the Normalized Organoid Growth Rate (NOGR) metric, specifically developed for brightfield imaging-based assays. A label-free image analysis model was applied to segment organoids precisely, track their growth rates over time, and classify viable and dead organoids. Testing eleven phenotypically distinct pancreatic cancer organoid models with five chemotherapeutics demonstrates that the NOGR metric more effectively captures cytostatic and cytotoxic drug effects compared to existing methods. This approach enhances the biological relevance of drug sensitivity assessments on organoids and offers a valuable tool for advancing personalized cancer treatment strategies.

Dietary yeast culture can protect against chronic heat stress by improving the survival, antioxidant capacity, immune response, and gut health of juvenile Chinese mitten crab (Eriocheir sinensis)

As global warming intensifies, aquatic species are increasingly threatened by heat stress, urging the aquaculture industry to explore innovative strategies to mitigate the adverse impact of thermal stress on animals. Supplementing diets with yeast culture (YC) has shown promising results in coping with heat stress. This study evaluated the effects of YC on the survival, biochemical responses, transcriptome, and intestinal microbiota of the Chinese mitten crab (Eriocheir sinensis) under chronic heat stress. Juvenile crabs were subjected to four conditions over 42 days: a control temperature of 24 °C and a high temperature of 30 °C supplemented with three YC doses: 0, 3.2, and 6.4 g/kg. Each group had six replicates of 30 crabs each. Chronic heat stress substantially reduced survival rates and increased molting frequency. However, YC supplementation significantly improved survival and antioxidant enzyme activities (SOD and GSH-Px) while reducing MDA levels, indicating a reduction in oxidative stress. The immune response metrics (PO and AKP activities) were comparable to those of the control group when YC was included in the diet. A significant correlation existed between the crab survival rate, antioxidant performance and gut health. Histological assessment revealed that YC maintained the integrity of the intestinal lining under heat stress. 16S rRNA sequencing revealed that YC ameliorated disruptions in the diversity and structure of the intestinal microbiota caused by high temperature. Transcriptomic analysis identified DEGs linked to serine-type peptidases and ascorbate and aldarate metabolism pathways. Significant correlations were detected between Candidatus_Hepatoplasma, Rhodobacter, Aeromonas, and genes related to antioxidant and immune responses. In conclusion, dietary YC at 3.2 g/kg effectively enhanced the resilience of E. sinensis to chronic heat stress by increasing survival rates and antioxidant capacity, restoring immune function, and maintaining gut health.

Does pad displacement correlate to impact severity metrics in football helmets?

As efforts to reduce sport-related head injuries continue, there is a need to better understand the mechanisms of an impact that influence the risk of sustaining a concussion. This study presents a method which can be used to separate football helmet pad displacement into normal and rotational components. Finite element models of three popular football helmets were used to simulate a variety of impacts per the National Football League (NFL) helmet testing protocol. Pad displacement components were evaluated for correlation with impact severity metrics including Head Injury Criterion (HIC), Diffuse Axonal Multi-Axis General Evaluation (DAMAGE), and Head Acceleration Response Metric (HARM). When combining all locations, displacement was not found to correlate well with severity metrics ( R2 &lt; 0.44). However, trends did exist with normal displacement when evaluating data by impact location. Normal displacement was found to correlate strongly with HARM, HIC, and Peak Resultant Linear Acceleration (PRLA) at the side upper (SU) location ( R2 = 0.79–0.8). Overall, it was observed that helmets which maximize normal displacement without bottoming out performed better. Tangential displacement was not found to correlate well with any impact severity metrics even when evaluated by location. This study has provided a method to evaluate components of helmet pad normal displacement during simulations which may help guide design and optimization efforts for helmets under impact in critical locations.

Untangling the Exposure-Response Relationship of Allopurinol in the Setting of Chronic Kidney Disease and Diuretic Use: Implications for Dosing.

Allopurinol dose reduction proportional to creatinine clearance (CLcr) results in suboptimal urate lowering in patients with gout. Similarly, diuretic therapy reduces oxypurinol clearance but is unexpectedly associated with the need for higher allopurinol doses to achieve the serum urate target (<0.36 mmol/L). The authors aimed to clarify the relationship between oxypurinol exposure and urate-lowering response in patients with gout at different stages of chronic kidney disease and those taking diuretics to determine the implications for maintenance dose selection. Oxypurinol and urate data from 5 clinical studies were available. Model-derived steady-state oxypurinol areas under the concentration-time curves (AUCss0-tau) were estimated using a Bayesian methodology. The observed response metrics included the percentage reduction in urate from baseline and achievement of the target urate level. Exposure-response was explored graphically and using logistic regression. In addition, the influence of chronic kidney disease and diuretic use on the allopurinol dose and oxypurinol AUCss0-tau requirements to achieve the serum urate target were explored. Data from 258 patients with gout taking allopurinol representing 1288 paired steady-state oxypurinol and serum urate measurements were available. Higher oxypurinol exposure seems to be required for urate-lowering response normalization and achieve the serum urate target in individuals with reduced kidney function and those taking diuretics. However, allopurinol dose requirements were reduced by 2-fold at the extremes of kidney function and unchanged in those taking or not taking diuretics. A lower allopurinol maintenance dose was required in patients with reduced kidney function (CLcr <30 mL/min), but this was not proportional to CLcr. Diuretic therapy did not influence allopurinol dose requirements.

Recent advances in and applications of ex vivo drug sensitivity analysis for blood cancers.

Blood cancers, including leukemia, multiple myeloma, and lymphoma, pose significant challenges owing to their heterogeneous nature and the limitations of traditional treatments. Precision medicine has emerged as a transformative approach that offers tailored therapeutic strategies based on individual patient profiles. Ex vivo drug sensitivity analysis is central to this advancement, which enables testing of patient-derived cancer cells against a panel of therapeutic agents to predict clinical responses. This review provides a comprehensive overview of the latest advancements in ex vivo drug sensitivity analyses and their application in blood cancers. We discuss the development of more comprehensive drug response metrics and the evaluation of drug combinations to identify synergistic interactions. Additionally, we present evaluation of the advanced therapeutics such as antibody-drug conjugates using ex vivo assays. This review describes the critical role of ex vivo drug sensitivity analyses in advancing precision medicine by examining technological innovations and clinical applications. Ultimately, these innovations are paving the way for more effective and individualized treatments, improving patient outcomes, and establishing new standards for the management of blood cancers.

Arrested development and increased incidence of sandprawn embryonic aberrations along an intertidal human recreation gradient.

Anthropogenic pressures are increasing in coastal ecosystems globally, yet identifying robust indicators of change and managing coastal resources can be complicated by phenotypic plasticity and differential life-history responses of key organisms. We illustrate this using biogeochemical and sandprawn (Kraussillichirus kraussi) response metrics along a human recreation gradient (trampling, sandprawn harvesting) in a South African lagoonal ecosystem. Benthic compaction, oxygen depletion and high porewater ammonia concentrations were associated with greatest recreation intensity. Sandprawn abundance was similar across the recreation gradient and body condition was counter-intuitively greater in areas with maximum recreation, but with higher frequencies of embryonic aberrations and arrested development. These findings suggest different vulnerabilities of life-history stages of sandprawns to recreation, with embryonic stages being highly susceptible. We suggest that embryonic aberrations and developmental changes in endobenthic crustaceans may be sensitive bioindicators of recreation-induced changes in sedimentary systems.

Cerebrovascular reactivity and response times describe recent ischaemic symptomatology in patients with moyamoya.

Moyamoya is a non-atherosclerotic intracranial steno-occlusive condition that places patients at high risk for ischaemic stroke. Randomized trials of surgical revascularization demonstrating efficacy in ischaemic moyamoya have not been performed, and as such, biomarkers of parenchymal haemodynamic impairment are needed to assist with triage and evaluate post-surgical response. In this prospective study, we test the hypothesis that parenchymal cerebrovascular reactivity (CVR) metrics in response to a fixed-inspired 5% carbon dioxide challenge correlate with recent focal ischaemic symptoms. Hypercapnic reactivity blood oxygenation level-dependent MRI (echo time = 35 ms; spatial resolution = 3.5 × 3.5 × 3.5 mm) and catheter angiography assessments of cortical reserve capacity and vascular patency, respectively, in moyamoya disease and syndromic participants (n = 73) were performed in sequence. Cerebrovascular reactivity uncorrected for response time (CVRRAW) was quantified, and time regression analyses were applied to quantify maximum cerebrovascular reactivity (CVRMAX) and cerebrovascular reactivity response time (CVRDELAY). Symptomatology was categorized by a stroke neurologist by hemisphere: symptomatic (lateralizing ischaemic symptoms < 6 months) or asymptomatic (no ischaemic symptom history). Values are presented as median [interquartile range]; logistic regression assessed the association of cerebrovascular reactivity metrics with symptoms, controlling for age and sex. A total of 109 hemispheres, including 39 symptomatic and 70 asymptomatic hemispheres, met inclusion criteria. Symptomatic hemispheres displayed reduced CVRRAW (P < 0.01) (symptomatic = 0.45 [0.28-0.70] z-statistic/ΔEtCO2 versus asymptomatic = 0.67 [0.44-0.98] z-statistic/ΔEtCO2), lengthened CVRDELAY (P < 0.001) (symptomatic = 47.6 [37.7-57.0] seconds versus asymptomatic = 37.7 [30.4-46.4] seconds), and reduced CVRMAX (P = 0.037) (symptomatic = 1.31 [0.99-1.94] z-statistic/ΔEtCO2 versus asymptomatic = 1.64 [1.29-2.12] z-statistic/ΔEtCO2). CVRDELAY (P < 0.001) was found to be significantly related to age in asymptomatic hemispheres (0.33-unit increase/year). Of assessed measures, the receiver operating characteristic curves suggest that CVRDELAY is associated most closely with recent ischaemic symptoms (P < 0.001). Findings support that cerebrovascular reactivity metrics are uniquely altered in hemispheres with recent ischaemic symptoms, further motivating their utilization as biomarkers of ischaemic symptomatology and potential treatment efficacy in moyamoya disease and syndrome.

Visual and behavioral responses to social and non-social threats: A multi-site replication

Researchers have proposed that humans have evolved psychological mechanisms that facilitate the detection, rapid response, and subsequent avoidance of potential threats. However, some inconsistent results in the literature have called into question the robustness of these responses. Here, we sought to replicate previous findings on the rapid detection of both social (i.e., angry faces) and nonsocial (i.e., snakes) threats within a large and diverse sample of adults, and to examine the robustness of our effects across three data-collection sites using two response metrics—visual latency to detect threatening versus non-threatening stimuli and motor (i.e., button press) responses to indicate that threatening versus non-threatening targets had been detected. We found an advantage for both social (angry facial configurations) and non-social (snakes) threats across all three data collection sites, demonstrating that the phenomenon is both replicable and robust. Further, we found that the threat advantage was only significant for visual latency to first detect threatening stimuli and not for subsequent motor responses—the overall replication effect was driven by first fixations—suggesting that biases for threat might be perceptually based.

Neurointerventional surveys between 2000 and 2023: a systematic review

BackgroundSurveys are increasingly used in neurointervention to gauge physicians’ and patients’ attitudes, practice patterns, and ‘real-world’ treatment strategies, particularly in conditions for which few, or no evidence-based, recommendations exist. While...

12423 Pre-treatment Blood Transcriptome Accurately Predicts Growth Response To Daily And Weekly GH Treatment In Children Born Small For Gestational Age

Abstract Disclosure: T. Garner: Grant Recipient; Self; Novo Nordisk. P. Murray: Grant Recipient; Self; Novo Nordisk. M. Hojby: Employee; Self; Novo Nordisk. Stock Owner; Self; Novo Nordisk. R. Ard: Employee; Self; Novo Nordisk. Stock Owner; Self; Novo Nordisk. P.E. Clayton: Grant Recipient; Self; Novo Nordisk. A. Stevens: Grant Recipient; Self; Novo Nordisk. Background: Predicting GH therapy response from gene expression has the potential to improve clinical management of short stature. Treatment in children born small for gestational age (SGA) requires daily GH injections. Although no long-acting GHs (LAGHs) are currently approved for SGA, results from REAL5 (randomised, multinational, open-label, controlled, phase 2 trial; NCT03878446) indicate that the LAGH somapacitan has an efficacy, safety, and tolerability profile similar to daily GH (1). Here, we investigate growth response prediction based on the baseline blood transcriptome with and without clinical variables in daily GH- or somapacitan-treated children in REAL5. Methods: REAL5 tested three somapacitan doses (0.16, 0.20, &amp; 0.24 mg/kg/week; n=12, n=13, &amp; n=12, respectively) versus two daily GH doses (0.035 &amp; 0.067 mg/kg/day; n=12 &amp; n=13, respectively). GH response was explored using four metrics calculated over 52-weeks: height velocity (HV; cm/year), HV standard deviation score (SDS), change in height SDS, and change in IGF-I SDS. Due to small sample sizes, dose groups were combined. Participants were split into tertiles to define fastest/slowest responders to each treatment which were compared to remaining tertiles. Differentially expressed genes (DEGs) were defined to distinguish one tertile from the remaining two. Random forest (RF) models were generated using the top 100 DEGs as well as in combination with a set of clinical variables. Area under the curve (AUC) describes RF prediction accuracy: for somapacitan sufficient samples were available for both training and validation while for daily growth hormone samples were only sufficient for training generating out of bag (OOB) AUCs, accompanied by error rates (ER). Accuracies were calculated for both fast &amp; slow responders across all response metrics in each treatment. Results: We demonstrate excellent predictive ability of the transcriptome to identify SGA children who respond slowest in HV following treatment with either daily GH or somapacitan (OOB AUC (ER)= 1.0 (5.0%) &amp; 0.99 (6.9%), respectively; validation AUC=0.812 for somapacitan), while prediction of other response measures was highly variable, particularly in validation (AUCs=0.56-1.0). The clinical variables combined with the transcriptomic data resulted in reduced accuracies and increased error rates (OOBs AUC(ER)=0.93(25%) [daily] &amp; 0.90(19%) [somapacitan]). Conclusions: In the first use of transcriptomics for growth response prediction in children born SGA we show good performance for those treated with both daily and weekly GH. However, when the transcriptome is combined with clinical data performance is reduced, indicating the importance of gene expression signatures for GH-response prediction. These findings may be promising for personalizing dose in GH-treated SGA patients. (1) Juul et al. EJE 2023:188,19-30. Presentation: 6/3/2024

Characterizing rapid infiltration processes on complex hillslopes: Insights from soil moisture response to rainfall events

Evaluating the soil moisture response characteristics to rainfall events is valuable for understanding eco-hydrological effects in the context of global climate change. However, the effects of soil thickness and rainfall characteristic indicators on soil moisture responses remain unclear, especially in the karst hillslopes characterized by highly complex topography. This study examined the soil moisture response to 35 rainfall events at 5-min intervals by deploying 20 sets of monitoring devices across two hillslope plots (5 × 20 m) with distinct mean soil thicknesses. The response metrics included the soil moisture response time (Tp2p) and wetting front velocity (Vwf), whereas indicator factors considered were soil thickness distribution, slope position, and rainfall characteristics. Overall, the results showed that Tp2p increased from downslope to upslope, as well as from the surface to deep layers. Surprisingly, the mean Vwf (1373 mm h−1) in this study site was significantly higher than that in non-karst regions (17–610 mm h−1). This suggests that rainwater can rapidly infiltrate the soil profile and contribute to subsurface runoff generation. Rainfall characteristics are the primary controlling factors influencing the soil moisture response to rainfall, with their contribution priority (44.3–63.9 %) higher than that of antecedent soil moisture conditions (26.1–35.2 %). The variation in soil moisture response metrics in shallow soil cover hillslopes was more affected by rainfall indicators (41–64 % vs. 31–47 %), thereby potentially weakening the potential influence of topography and soil properties. These findings highlight the effect of refined monitoring in characterizing soil moisture heterogeneity in response to rainfall and emphasize the potential impact of rapid responses on karst eco-hydrological processes.

Seismic performance assessment of high arch dams considering the pulse-like and directionality effects of near-fault ground motions

This paper investigates the pulse-like and directionality effects of near-fault horizontal ground-motion records on the seismic performance of high arch dams. A 3-dimensional arch dam-reservoir-foundation finite-element model is built. Two near-fault bidirectional ground-motion suites (i.e. ordinary and pulse-like suite) are collected. The fault-normal and fault-parallel orientations of the horizontal ground-motion records are rotated to reflect the directionality effect. Nonlinear dynamic analyses are further implemented for the high arch dam excited by both near-fault ground motions with different incidence angles. The results show that the pulse-containing ground-motion records can yield more notable dynamic response and damage for high arch dams as compared to the ordinary records. Moreover, with changing the incidence angles, both the dam dynamic response and damage metrics exhibit periodic variation and constant trends for the pulse-containing and ordinary ground-motion cases, respectively. Therefore, the directionality effect has a significant influence on the seismic performance of high arch dams excited by pulse-containing ground-motion records. Compared with the near-fault ordinary ground motions, the pulse-like ground motions will induce a 40 %-increase in the concrete damage volume of high arch dams. In addition, peak ground velocity could be regarded as a preferable intensity measure for assessing the seismic damage of high arch dams.

Anaerobic Performance Profiling in Elite Amateur Boxers.

While anaerobic fitness is highly important for the performance in Olympic (amateur) boxing, the relationship between anaerobic performance metrics is poorly understood, and profiling boxers according to their anaerobic capacity is still a challenge. With the current study in elite amateur boxers, we aimed to compare the metabolic and cardiovascular responses to different maximal tests and the intercorrelations between performance indices (peak and mean power, duration of the test, punching frequency) of several all-out tests and their correlation to physiological response metrics (blood lactate and heart rate, HR). Twelve male Olympic boxers performed a battery of tests, including 30 s Wingate cycling and arm cranking, boxing bag punching, steep uphill treadmill running to exhaustion, and progressive treadmill running VO2max test. Performance indices of different anaerobic tests were not closely correlated except for the duration of uphill running with body weight scaled (relative) peak and mean power produced during Wingate cycling test and absolute mean power of both Wingate tests. The number of punches landed on a bag per 30 s was associated only with relative power achieved during Wingate cycling test. HRpeak but not peak lactate response correlated strongly across exercise tasks. Finally, no correlation between the highly developed aerobic and anaerobic capacity, suggests a complex picture of the adaptation in elite amateur boxers.

Study on the misalignment deformation threshold of girder end of curved bridge with ballasted track

When a train traverses a curved bridge, it inherently tends to shift laterally outward. To counteract this propensity, the strategy of track superelevation is employed. After earthquake, curved bridges may exhibit diverse degrees of residual deformation. The precise failure mechanisms that compromise train safety and passenger comfort during transit over curved bridges, particularly under the combined influence of residual deformation, centrifugal force, and track superelevation, remain not entirely comprehended. A comprehensive system integrating trains with curved track-bridges is developed to examine the impact of girder end misalignments on residual track irregularities. The analysis concentrated on the dynamic time-history responses of trains traversing bridges featuring girder misalignments, exploring a range of amplitudes, train velocities, and curve radii. The findings revealed significant variances in the dynamic train responses, especially in lateral acceleration and the Nadal index, when contrasting centripetal and centrifugal girder side misalignments. Furthermore, it is discerned that lateral misalignment at the girder ends markedly affects train lateral acceleration and the Nadal index, with a relatively minor influence on other dynamic response metrics. Finally, the thresholds for misalignment deformation were summarized, for curve radii of 800, 1000, and 1200 meters, the comfort deformation thresholds at 100 km/h are determined to be 23, 23, and 20 mm respectively, while the safety deformation thresholds are found to be 26, 30, and 38 mm respectively. At a speed of 120 km/h, the comfort deformation thresholds for the same curve radii are 18, 18, and 15 mm, with the safety deformation thresholds at 12, 15, and 21 mm.

The immunological landscape and silico analysis of key paraptosis regulator LPAR1 in gastric cancer patients

This study aims to identify key regulators of paraptosis in gastric cancer (GC) and explore their potential in guiding therapeutic strategies, especially in stomach adenocarcinoma (STAD). Genes associated with paraptosis were identified from the references and subjected to Cox regression analysis in the TCGA-STAD cohort. Using machine learning models, LPAR1 consistently ranked highest in feature importance. Multiple sequencing data showed that LPAR1 was significantly overexpressed in cancer-associated fibroblasts (CAFs). LPAR1 expression was significantly higher in normal tissues, and ROC analysis demonstrated its discriminative ability. Copy number alterations and microsatellite instability were significantly associated with LPAR1 expression. High LPAR1 expression correlated with advanced tumor grades and specific cancer immune subtypes, and multivariate analysis confirmed LPAR1 as an independent predictor of poor prognosis. LPAR1 expression was associated with different immune response metrics, including immune effector activation and upregulated chemokine secretion. High LPAR1 expression also correlated with increased sensitivity to compounds, such as BET bromodomain inhibitors I-BET151 and RITA, suggesting LPAR1 as a biomarker for predicting drug activity. FOXP2 showed a strong positive correlation with LPAR1 transcriptional regulation, while increased methylation of LPAR1 promoter regions was negatively correlated with gene expression. Knockdown of LPAR1 affected cell growth in most tumor cell lines, and in vitro experiments demonstrated that LPAR1 influenced extracellular matrix (ECM) contraction and cell viability in the paraptosis of CAFs. These findings suggest that LPAR1 is a critical regulator of paraptosis in GC and a potential biomarker for drug sensitivity and immunotherapy response. This underscores the role of CAFs in mediating tumorigenic effects and suggests that targeting LPAR1 could be a promising strategy for precision medicine in GC.

Microplastics and riverine macroinvertebrate communities in a multiple-stressor context: A mesocosm approach

Growing use of synthetic materials has increased the number of stressors that can degrade freshwater ecosystems. Many of these stressors are relatively new and poorly understood, such as microplastics which are now ubiquitous in freshwater systems. The effects of microplastics on freshwater biota must be investigated further in order to better manage and mitigate their impacts. Our experiment provides the first empirical evaluation of stream invertebrate community dynamics in response to microplastics of different concentrations and sizes, in combination with fine sediment, a pervasive known stressor in running waters. In a 7-week streamside experiment using 64 flow-through circular mesocosms, we investigated the effects of exposure to three simulated microplastic influxes (polyethylene microspheres at four levels between 0 and 28,800 items/event) and the addition of fine sediment (to simulate a polluted stream environment). Invertebrate drift was monitored for 48 h immediately after each microplastic influx, and benthic invertebrate communities were sampled after 28 days of microplastic and sediment manipulations. Microplastic concentration, size and fine sediment all had significant factor main effects on several invertebrate drift response metrics, whereas few microplastic main effects were seen in the benthic community. However, interactive stressor effects were common in different combinations between sediment, microplastic size and concentration, suggesting multiple-stressor relationships between microplastics and fine sediment. Microplastic ingestion was witnessed in four of 12 taxa analysed: Hydrobiosidae, Deleatidium spp., Potamopyrgus antipodarum and Archichauliodes diversus. Our findings provide insights into how microplastics affect drift and benthic community dynamics of stream invertebrates in a field-realistic experimental setting and highlight areas requiring further study. These include investigations of invertebrate drift dynamics in response to other types of microplastics, the role invertebrate size may play in determining their vulnerability to microplastic pollution, and framing more microplastic research in a field-realistic multiple-stressor context.

Novel Approach to Personalized Physician Recommendations Using Semantic Features and Response Metrics: Model Evaluation Study.

The rapid growth of web-based medical services has highlighted the significance of smart triage systems in helping patients find the most appropriate physicians. However, traditional triage methods often rely on department recommendations and are insufficient to accurately match patients' textual questions with physicians' specialties. Therefore, there is an urgent need to develop algorithms for recommending physicians. This study aims to develop and validate a patient-physician hybrid recommendation (PPHR) model with response metrics for better triage performance. A total of 646,383 web-based medical consultation records from the Internet Hospital of the First Affiliated Hospital of Xiamen University were collected. Semantic features representing patients and physicians were developed to identify the set of most similar questions and semantically expand the pool of recommended physician candidates, respectively. The physicians' response rate feature was designed to improve candidate rankings. These 3 characteristics combine to create the PPHR model. Overall, 5 physicians participated in the evaluation of the efficiency of the PPHR model through multiple metrics and questionnaires as well as the performance of Sentence Bidirectional Encoder Representations from Transformers and Doc2Vec in text embedding. The PPHR model reaches the best recommendation performance when the number of recommended physicians is 14. At this point, the model has an F1-score of 76.25%, a proportion of high-quality services of 41.05%, and a rating of 3.90. After removing physicians' characteristics and response rates from the PPHR model, the F1-score decreased by 12.05%, the proportion of high-quality services fell by 10.87%, the average hit ratio dropped by 1.06%, and the rating declined by 11.43%. According to whether those 5 physicians were recommended by the PPHR model, Sentence Bidirectional Encoder Representations from Transformers achieved an average hit ratio of 88.6%, while Doc2Vec achieved an average hit ratio of 53.4%. The PPHR model uses semantic features and response metrics to enable patients to accurately find the physician who best suits their needs.