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Study on structural dynamic response of offshore wind turbine under floating ice load

Integrating in vitro and in silico approaches for exploring antidiabetic potential of dimethyl and thiomethyl indolinone derivatives

Diabetes mellitus (DM) is a metabolic disorder caused by insulin deficiency. It is a rapidly growing problem with immense social, economic and health related problems. The market available drugs for the management of DM possess several limitations and therefore the discovery of more effective agents is the need of time. The current study was designed to evaluate two oxindole derivatives: (E)-3-(2,4-Dimethylbenzylidene)-6-chloroindolin-2-one (compound 1), and (E)-3-(4-(Methylthio) benzylidene)-6-chloroindolin-2-one (compound 2) against α-amylase, protein glycation, and DPP-IV. In case of in vitro antidiabetic activities, compound 1 demonstrated significant inhibition at various concentrations with IC50 value of 32.917 µg/mL against α-amylase, 210.592 µg/mL against protein glycation and 31.28 µg/mL against DPP-IV. Similarly, when tested at various concentrations, compound 2 illustrated marked inhibition with IC50 value of 42.691 µg/mL on α- amylase, 341.551 µg/mL on protein glycation and 47.192 µg/mL against DPP-IV. Molecular docking studies identified the binding patterns of oxindoles in the active site of targeted protein and enzymes. Moreover, the docking analysis also showed the potent interaction of test compounds with the target sites against α-amylase, protein glycation and DPP-IV. In conclusion, both the compounds are significant inhibitors of α-amylase, protein glycation and DPP-IV in vitro assays with the support of molecular dynamic studies and therefore are potential candidates for further studies.

Unveiling the crosstalk between unfolded protein response and apoptosis in triclosan induced hepatotoxicity in Labeo rohita

Abstract Triclosan (TCS), a widely used antimicrobial, has emerged as a concerning aquatic pollutant, especially post-COVID-19 due to increased disinfectant use. The study aimed to investigate the toxic impacts of TCS on Labeo rohita, revealing a 96-h LC50 of 0.742 mg/L. Well-acclimatized fish were categorised into three groups: one control and two treatment (T1 and T2) that were exposed to 1/10th and 1/5th of 96-h LC50 i.e., 0.0742 mg/L and 0.148 mg/L, respectively for 6 weeks under semi-static condition. Significantly (p < 0.05) elevated extents of reactive oxygen species (ROS) in the liver indicated enhanced oxidative stress. The activities of enzymatic antioxidants viz. superoxide dismutase (SOD) and catalase (CAT) were significantly (p < 0.05) increased while the reduced glutathione (GSH) levels were significantly (p < 0.05) decreased in a dose- and duration-dependent manner. A significant (p < 0.05) increase was observed in the lipid peroxidation (LPO) rate, which coincided with disruptions in the histological structure of the liver. Significant (p < 0.05) induction in Micronuclei frequency validated genomic instability. Furthermore, Endoplasmic Reticulum (ER) stress was marked by the increased intracellular calcium levels and elevated expression of grp78, chop, atf4, perk, eIF2α and gadd34 in TCS-exposed groups. Moreover, the consequent activation of bax, caspase-3, caspase-9, apaf-1 and the regulation of bcl-2 due to ER-stress, ultimately resulted in apoptosis of hepatocytes. Pearson correlation matrix and Principal Component Analysis (PCA) further underscored key interactions among parameters. Our findings demonstrate that the TCS, at its sub-lethal concentrations, is causing severe anomalies and even cell-death via triggering ER-stress-mediated apoptotic pathway in the fish liver.

Incidence and factors associated with post-intensive care syndrome among caregivers of intensive care unit survivors: Protocol for a cohort study

Background During the last decades, intensive care unit (ICU) mortality rates have significantly decreased but this progress has come with unintended consequences for patients and their caregivers. The adverse health-related effects observed in caregivers during the post-ICU period are referred to as Post-Intensive Care Syndrome-Family (PICS-F). Despite growing awareness of PICS-F, the long-term challenges faced by caregivers of ICU patients are not well characterized with several gaps in knowledge remaining unaddressed. The proposed study aims to determine the incidence of PICS-F impairments and identify associated factors among caregivers of ICU survivors. Methods We plan to conduct a longitudinal prospective cohort study involving 175 caregivers of ICU patients admitted to a public hospital in Chile. Data will be collected during ICU admission, after ICU discharge, 3 months and 6 months after hospital discharge. Questionnaires will evaluate caregivers’ psychological, physical and cognitive outcomes and perceived social support, resilience, family satisfaction and caregiver burden. Factors associated with PICS-F impairments will be explored using generalised linear mixed models. Discussion The current understanding of PICS-F is limited, particularly regarding the risk and protective factors associated with the syndrome among caregivers of ICU survivors. This study will contribute to addressing this gap by providing novel data about PICS-F and exploring previously unexamined factors linked to PICS-F such as family satisfaction, psychological buffers and caregiver burden. Trial Registration Clinicaltrials.gov: NCT05827354. Registered on 25 April 2023.

Parp1 deletion rescues cerebellar hypotrophy in xrcc1 mutant zebrafish

Abstract Defects in DNA single-strand break repair are associated with neurodevelopmental and neurodegenerative disorders. One such disorder is that resulting from mutations in XRCC1, a scaffold protein that plays a central role in DNA single-strand base repair. XRCC1 is recruited at sites of single-strand breaks by PARP1, a protein that detects and is activated by such breaks and is negatively regulated by XRCC1 to prevent excessive PARP binding and activity. Loss of XRCC1 leads to the toxic accumulation and activity of PARP1 at single-strand breaks leading to base excision repair defects, a mechanism that may underlie pathological changes in patients carrying deleterious XRCC1 mutations. Here, we demonstrate that xrcc1 knockdown impairs development of the cerebellar plate in zebrafish. In contrast, parp1 knockdown alone does not significantly affect neural development, and instead rescues the cerebellar defects observed in xrcc1 mutant larvae. These findings support the notion that PARP1 inhibition may be a viable therapeutic candidate in neurological disorders.

Improving microgrid hosting capacity: A two-stage BONMIN solver-based framework for battery storage allocation and operational energy management strategy

The growing concerns over fossil fuel dependency, environmental impacts, and escalating energy expenses highlight the critical importance of enhancing energy system efficiency. This study presents a dual-phase optimization approach for improving grid-connected microgrid (μG) operations, focusing on Sodium-Sulfur (NaS) and Sodium Nickel Chloride (Na-NiCl₂) battery storage systems. The problem was structured as a mixed-integer nonlinear programming (MINLP) model and resolved using GAMS software with its embedded open-source BONMIN solver. The initial phase establishes optimal battery storage system (BSS) allocation methods to optimize renewable energy source (RES) self-consumption (SC), increase hosting capacity (HC), and minimize operational expenses. Building on these results, the second phase develops optimal microgrid operational strategies to reduce total operating costs further. The research evaluates five scenarios with incrementally increasing the number of BSSs, ranging from one to five units. Through this systematic analysis, the work demonstrates that both the quantity and type of BSS units significantly impact μG operating costs. The most efficient configuration emerged in Case 3, where three Na-NiCl₂ BSS units achieved a 32.35% reduction in operating costs. Additionally, the integration of BSS demonstrated notable improvements in both HC and SC rates.

Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification

Nursing regulation in Canada: Insights from a scoping review

Canadian nursing regulators have implemented various innovations to reform regulatory approaches to address workforce challenges, system demands, governance reforms, and a drive for efficiency. Given the significant role that regulators play in influencing patient safety, workforce, and health system outcomes, decision-making must be evidence-informed. This review examined the nature, extent, and range of literature related to nursing regulation in Canada and how the existing scholarship aligns with emerging regulatory and health system trends to inform the development of a research agenda. The review was conducted following the JBI methodology for scoping reviews and with the support of a medical research librarian. A total of 195 sources, including scholarly (n = 156, 80%) and grey literature sources (n = 39, 20%), were included and reviewed. Just over half of the included scholarly sources were empirical studies (n = 80, 51.3%). The number of publications has steadily increased over the last few decades, and the majority of sources were situated in a provincial/territorial context (n = 104, 53.3%), followed by the national (n = 67, 34.4%) and global context (n = 24, 12.3%). The majority of the literature was led by scholars or professional groups unaffiliated with nursing regulators (n = 129, 66.2%). In contrast, nursing regulators led, commissioned, or were involved in a smaller portion of sources (n = 66, 33.8%). The largest category of literature focused on regulatory models, governance structures, and reforms (n = 59, 30.3%); followed by registration and licensure (n = 57, 29.2%); nursing roles and standards (n = 53, 27.2%); conduct, complaints, and discipline (n = 13, 6.7%); continuing competence programs (n = 11, 5.7%); and education program approval/accreditation (n = 2, 1%). The current literature base related to nursing regulation in Canada is largely descriptive and non-empirical and may not provide sufficient evidence to inform regulatory decision-making. This highlights opportunities for regulators and researchers to enhance collaboration to co-create research agendas that can maximize knowledge development and mobilization efforts.

Modeling of total ionizing dose (TID) effects on the nonuniform distribution of Si/SiO2 interface trap energy states in MOS devices

Removing barriers to COVID-19 vaccine intention in a university population: Results of a serial mediation study through the dimensions of the Health Belief Model

Background While many studies have used the Health Belief Model (HBM) to understand vaccine intention, none claim to have used serial mediation to understand the relationship between HBM dimensions and COVID-19 vaccine intention. This study developed a serial mediation model to assess the direct and indirect effects of the latent HBM dimensions on COVID-19 primary vaccine intention. Methods A cross-sectional study: from 01 April to 10 June 2021, a self-administered online questionnaire on vaccine intention against COVID-19 was distributed to staff and students at the University of Liège (Belgium). Direct and indirect effects of the HBM dimensions (perceived susceptibility, severity, benefits, barriers, self-efficacy and cues to action) on vaccine intention (score 0–100) were assessed with serial mediation models. Actually, each permutation of the latent HBM dimensions, i.e., each causal chain, was assessed using partial least squares path modelling (PLS-PM) according to the order of the HBM dimensions in that particular chain. Results The sample was made up of 1256 participants. The final model revealed that the causal chain with the lowest Bayesian Information Criterion (BIC) value was barriers (Effect estimation (CI95%): -0.09 (-0.15 - -0.03)) ↘ severity (-0.13 (-0.20 - -0.07)) ↘ low self-efficacy (0.20 (0.15–0.25)) ↘ low susceptibility (-0.55 (-0.60 - -0.51)) ↘ vaccine intention (outcome). This revealed a significant indirect and direct effect (-0.20 (-0.25 - -0.15)) between barriers and vaccine intention. Conclusions The results demonstrated that perceived barriers are a key determinant in COVID-19 primary vaccine intention. Public health practitioners need to prioritise messaging that addresses the barriers reducing vaccine intention to enable individuals to make an informed choice. These messages could form part of a mass communication campaign aimed at hesitant individuals, with evidence-based information about vaccine safety a priority in order to establish a climate of trust.

A pilot study on treatment content in virtual reality-assisted aggression therapy at a maximum-security forensic psychiatric clinic

Abstract Previous findings on results of treatment of aggression in violent offenders show inconsistent results, and implementations of such treatments have demonstrated varying success with sometimes marginal gains in forensic settings. New methods, incorporating virtual reality as a tool for experiential learning, have been put forward yet require deepened investigations concerning both treatment content and effects. The principal objective of this study is to examine the treatment content of the revised VRAPT intervention. Specifically, the study focuses on understanding how the content of the VRAPT intervention is conceptualized from the perspectives of both patients and therapists. Inductive manifest content analysis was applied on content of treatment workbooks (N = 6 + 7), provided by both patients and therapists as part of seven concluded VRAPT treatments at a maximum-security forensic psychiatric clinic in Sweden. Three manifest content categories were identified, relating to treatment content: Skills-training, Tailoring of the intervention, and Self-awareness. While generally quite similar, some potentially important differences between patients’ and therapists’ perspectives on the VRAPT intervention were apparent. The findings suggest the necessity of further research into optimizing VR-assisted treatments in forensic psychiatry.

Comparison of perceived family state and functioning among individuals with depression and general population in Southern Thailand

Purpose This study aimed to examine perceived family functioning among individuals with depression, then compare these perceptions with those of the general population. Materials and methods A cross-sectional study was conducted among individuals with depression at Songklanagarind Hospital and individuals from the general population; from May to July 2024. Participants completed three questionnaires: 1) Personal and demographic inquiry, 2) the Family State and Functioning Assessment Scale (FSFAS-25), and 3) the Patient Health Questionnaire (PHQ-9). Data analysis involved descriptive statistics, Chi-square or Fisher’s exact test, Wilcoxon rank sum test and Student’s t-test. Results The study compared 41 individuals with depression with 41 from the general population; revealing significant differences in family functioning scores. The depression group reported lower median family functioning scores (76 [IQR 64-84]) compared with the general population (87 [IQR 77-93]). Fewer individuals in the depression group reported high total family functioning scores (56.1% vs. 82.9%, p = 0.016). They also showed lower percentages in family support (61.0% vs. 95.1%, p < 0.001) and discipline dimensions (46.3% vs. 78.0%, p = 0.006). Furthermore, those with residual depression symptoms (PHQ-9 having a score of nine or higher) showed significant differences in family support (37.5% vs. 76.0%, p = 0.033) and emotional status (18.8% vs. 60.0%, p = 0.023) compared with those without residual depression symptoms. Conclusion Individuals with depression demonstrated lower levels of family functioning compared with the general population. Acknowledging and addressing the influence of family dynamics on the development and persistence of the disorder may be essential for improving treatment outcomes. Integrating these factors into person-centered mental health interventions can lead to more comprehensive, individualized, and effective care.

LLM-based robot personality simulation and cognitive system

Mathematical analysis of the dynamics of cyberattack propagation in IoT networks

The growing threat of cyberattacks is a severe concern to governments, military organizations, and industries, especially with the increasing use of Internet of Things (IoT) devices. To tackle this issue, researchers are working on ways to predict and prevent these attacks by studying how malware spreads. In this study, we use a discrete-time approach to better model how cyberattacks spread across IoT networks. We also focus on the role of firewalls, developing a strategy to optimize their effectiveness in slowing down the spread of malware. Additionally, we analyze the reproduction number’s sensitivity and explore the proposed discrete system’s local and global stability. The model was simulated and analyzed using Python packages, providing practical solutions to improve cybersecurity in IoT networks. These insights are supported by numerical simulations based on real-world data.

Effects of intranasal neural stem cells transplantation on olfactory epithelium regeneration in an anosmia-induced mouse model

Pattern mining and prediction techniques for user behavioral trajectories in e-commerce

The trajectory of a user's continuous online access, which manifests as a sequence of dynamic behaviours during online purchases, constitutes fundamental behavioural data. However, a comprehensive computational method for measuring trajectory similarity and thoroughly analyzing user behaviour remains elusive. Analyzing user behaviour sequences requires balancing detail with data reduction while addressing challenges such as excessive spatial complexity and potential null results in predictions. This study addresses two critical aspects: First, it evaluates similarity in the time dimension of user behaviour sequence clustering. Second, it introduces a frequent sub-trajectory mining algorithm that emphasizes the order of user visits for trajectory analysis and prediction. We employ a variable-order Markov model to manage the growth of probability matrix size in forecasts. Additionally, we improve prediction accuracy by aggregating the time spent on specific web pages.

Mesoporous activated carbon from Tabebuia aurea leaves for effective adsorptive removal of 2,4-dichlorophenoxyacetic acid

Abstract The extensive use of herbicides in agriculture contributes to water pollution, posing a significant environmental risk. This study focused on the H3PO4 activation of Tabebuia aurea leaves to prepare activated carbon. The resulting adsorbent was then tested for its capability to eliminate 2,4-dichlorophenoxyacetic acid (2,4-D), the heinous herbicide. The prepared activated carbon demonstrated a mesoporous nature with a high specific surface area (773.21 m2/g). Moreover, the existence of carbon and oxygen was proven using elemental analysis, and a post-adsorption chlorine signal confirmed 2,4-D presence. It was found that pH 2 provided optimal adsorption conditions, with an activated carbon dose of 0.45 g/L and 50 mg/L 2,4-D concentration. The process comprehended pseudo-second-order kinetics, as determined by kinetic modeling. The Langmuir isotherm model described the adsorption equilibrium, indicating a maximum adsorption capacity of 158.28 mg/g. Thermodynamic tests indicated physisorption and exothermicity. The prepared activated carbon also demonstrated substantial regeneration capacity up to five cycles. Consistent adsorption capacity proves its efficacy across diverse water matrices. Adsorption efficiency remained largely unaffected by inorganic ions at 0.1 and 1 mM concentrations. This confirms the viability of the synthesized adsorbents and their affordable use for 2,4-D removal in water remediation.

Correction: Computational phenotypes for patients with opioid-related disorders presenting to the emergency department

Narrative identity differences in autism

Index microvascular resistance (IMR) in heart transplant patients (IMR-HT study): Study protocol

Background Acute allograft rejection (AAR) is an important cause of morbi mortality in heart transplant (HT) patients, particularly during the first year. Endomyocardial biopsy (EMB) is the “gold standard” to guide post- heart transplantation treatment. However, it is associated with complications that can be potentially serious. The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. Detection of coronary microvascular dysfunction (MCD) by IMR may help to identify high risk HT patients. In fact, an increased IMR measured early after HT has been associated with AAR, higher all-cause mortality and adverse cardiac events. A high IMR value early after HT may identify patients at higher risk who require increased surveillance or adjustments in immunosuppressive therapy. Conversely, a low IMR value may support reducing the number of EMBs. Our aim is to evaluate IMR in heart transplant patients within the first year. Changes in management after knowing IMR values and prognostic implications of IMR in a long term follow up will also be assessed. Study design The IMR-HT study (NCT 06656065) is a multicenter, prospective study that will include post-HT consecutive stable patients undergoing coronary physiological assessment in the first three months and one year. Cardiac adverse events will be evaluated at one year for up to five years. A clinical management algorithm is proposed: after knowing IMR values the physician will be able to reduce the number of biopsies established in each center protocol or modify immunosuppression therapy. Conclusions IMR values may vary within the first year after heart transplant. IMR assessment will be useful to identify high risk heart transplant patients, leading to possible changes in management and prognosis.