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Insecticidal activity, chemical characterization, and biochemical responses induced by selected essential oils against Tuta absoluta (Lepidoptera: Gelechiidae)

Abstract The tomato leaf miner, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae), is a major pest causing severe damage to tomato crops worldwide. The present study evaluated the insecticidal efficacy of Cymbopogon nardus (citronella) and Pelargonium graveolens (geranium) essential oils against T. absoluta larvae and their impact on selected biochemical and oxidative stress parameters under laboratory conditions. GC-MS analysis identified citral and related monoterpenes as the major components of citronella oil, while geranium oil was rich in citronellol. Toxicity assays demonstrated dose-dependent larval mortality for both oils, with citronella oil exhibiting slightly higher potency (LC 50  = 3.12%; LC 90  = 6.37%) than geranium oil (LC 50  = 3.88%; LC 90  = 7.65%). Biochemical analyses revealed significant reductions in GABA-transaminase activity, total protein, and total lipid contents in treated larvae, indicating disruption of neurotransmission, metabolism, and energy reserves. Furthermore, oxidative stress markers showed decreased total antioxidant capacity and superoxide dismutase activity, together with increased lipid peroxidation, indicating the induction of oxidative stress in treated larvae. These findings demonstrate that both essential oils possess significant insecticidal activity and induce marked biochemical and oxidative stress responses in T. absoluta larvae. Therefore, citronella and geranium essential oils may represent promising eco-friendly botanical insecticides for incorporation into integrated pest management programs for tomato crops.

Determinants of parental traditional medicine use for children during COVID-19 in Dire Dawa city administration, Eastern Ethiopia, 2023/24: Mixed community based cross-sectional study design

Introduction Globally, 85% of the population uses traditional medicine. Ethiopia is a country with various traditional medicinal practices. However, various studies also reported traditional medicine used in children by their parents has had adverse outcomes and hospitalized them with complications. Various studies had also reported that traditional medicine use was high during COVID-19. Despite the fact that, children are particularly vulnerable population, limited studies exists regarding the prevalence, types, and determinants of parental TM use during COVID-19. In addition the existing studies were also confined to quantitative methods. Therefore, this study uses a mixed study design to explore indigenous methods of traditional medicine knowledge acquisition, preservation, preparation, storage, and dosage of herbs; barriers of disclosure; and prevalence of concomitant use. Methods A community-based concurrent mixed study design was conducted among 941 randomly selected parents from Dec 01/2023 to March 01/2024. The data was cleaned, coded, and entered in Epi-Data version 4.6 and transferred to Stata version 14.1 for analysis. Finally, an AOR with a 95% CI was computed, and variables with a p-value < 0.05 in the multivariable analysis were taken as significant factors. The qualitative data was collected from 16 selected key informants by in-depth face-to-face interviews and analyzed by using thematic analysis. Result The prevalence of parental TM use for children was 87.6%. Sibling relation to child (AOR: 0.45, 95% CI, 0.01–0.77), religion (AOR: 0.11, 95% CI, 0.04–0.29), parental TM use for themselves (AOR: 6.55, 95% CI, 1.67–25.69), easy accessibility (AOR: 2.72, 95% CI, 1.16–6.40), safety & efficacy (AOR: 4.53, 95% CI, 2.3–13.61), and TM skill in the family (AOR: 0.47, 95% CI, 0.19–0.84) were determinants of TM utilization. Lack of awareness, misperception of TM, lack of trust in HCP and negative judgment from HCP were the main-barriers for non-disclosure of TM use. Conclusion This result indicated traditional medicine use was high; nearly 9 out of 10 parents had used TM for their children during COVID-19. There was high concomitant utilization (90.6%) and high non-disclosure rate (98.1%) of traditional medicine use to health workers. Hence, it is better to give priority to strengthening the implementation of TM policy and manage accordingly.

Redefining Early Relapse in Multiple Myeloma — Time to Change the Rules

Greenhouse gas and carbon profile of the US forest products industry: 1990 to 2020

Acid-activated chitosan-modified Iranian bentonite for adsorption of Cu(II) and Zn(II) from water; A green and sustainable water treatment approach

This study evaluates the adsorption performance of an Iranian bentonite modified through two routes: activation with HNO 3 followed by calcination at 500 °C yielding NWF adsorbent and activation with HCl followed by chitosan intercalation to obtain HWF adsorbent. Batch experiments assessed Cu 2+ and Zn 2+ removal from aqueous solutions under varying pH, contact time (5–45 min), sorbent dosage (10–150 mg), initial concentration (20–200 mg/L), and temperatures (20–45°C). Atomic Absorption Spectroscopy was used to evaluate heavy metal concentrations. Nonlinear isotherm fitting showed that the Langmuir model described the data well with high mass normalized capacities under the low-dose condition. Freundlich fits indicated favorable adsorption on heterogeneous surfaces. Kinetics followed the pseudo-second-order model (R² = 0.996–0.998), could be described by chemisorption and in case of NWF, faster uptake (higher k 2 ) achieved. Optimal adsorption performance occurred at a pH of approximately 6–7, achieving equilibrium capacities ( q e ) as high as 99.0 mg/g and blank tests at pH ≥ 8 minimized contributions from metal hydroxide precipitation. Thermodynamic analysis has been carried out to confirm spontaneous and endothermic adsorption in temptatures ranged from 20–45°C. X-ray Diffraction, Fourier Transform Infrared Spectroscopy and Scanning Electron Microscopy corroborated successful modification and enhanced site accessibility. The results of this study showed that acid-activated and chitosan-modified bentonites are low-cost, effective, and sustainable sorbents for Cu 2+ and Zn 2+ removal from water, with practical relevance to wastewater treatment.

Teclistamab in Multiple Myeloma with One to Three Previous Lines of Therapy

Efficient degradation of PFOA by peroxymonosulfate activated with sulfurized nanoscale zero-valent iron: Synergistic radical and non-radical pathways

From manual counting to YOLO: Using computer vision to automate large-scale fecundity assays in C. elegans

Fecundity measurements play a crucial role in life history research, providing insights into reproductive fitness, population dynamics, and environmental responses. In the model nematode Caenorhabditis elegans , fecundity assays are widely used to study development, aging, and genetic or environmental influences on reproduction. C. elegans hermaphrodites have large numbers of offspring (>100), so manual counting of viable offspring is time-consuming and susceptible to human error. Automated counting methods have the potential to enhance throughput, accuracy, and precision in data collection. We applied computer vision to 9972 images of broods from individual C. elegans hermaphrodites from several strains under multiple treatments to capture variation in fecundity. We trained models using You Only Look Once (YOLO) versions v8 to v11 (large and extra-large variants) to detect and count viable offspring, then compared the model results to estimates from manual counting. The best-performing model, YOLO v11-L, detected offspring with high accuracy after fine-tuning, achieving 92.6% recall and 94.9% precision. Manual counts differed from verified ground-truth counts by an average of 2.16 offspring per image, compared to 0.9 for the trained computer vision model. In addition, we detected significant effects of counter identity, experimental block, and their interaction on manual counts. Computer vision counts were not affected by these biases and outperformed manual counting in both speed, consistency, and accuracy. We demonstrate that computer vision can be a powerful tool for fecundity assays in C. elegans and provide a pipeline for applying this approach to new image sets. More broadly, applying computer vision to digital collections can advance ecological and evolutionary research by accelerating the study of fitness and life history. In practice, this reduces months of manual counting to about 2 hours on a consumer GPU, lowering barriers to large-scale fecundity assays.

Phase 2b Trial of a Na _V 1.8 Inhibitor for Acute Pain

Effect of pilates exercises plus breastfeeding positioning adjustment on artificial intelligence-assessed craniovertebral angle in breastfeeding women with forward head posture: a randomized controlled trial

Abstract Forward head posture (FHP), considered a neuromusculoskeletal disorder, includes those associated with breastfeeding. Pilates is recognized for improving posture, flexibility, and core strength. To investigate the effect of Pilates on craniovertebral angle (CVA), cervical spine mobility, pain, neck disability, fatigue, breastfeeding self-efficacy, quality of life (QOL), and infant anthropometric measurements in breastfeeding women with FHP. Seventy‑four breastfeeding women with FHP were randomized into two equal groups. The control group ( n  = 37) received breastfeeding positioning adjustment only, while the intervention group ( n  = 37) received breastfeeding positioning adjustment in addition to Pilates exercises. The Primary outcomes included CVA assessed using Artificial Intelligence Posture Evaluation and Correction System (APECS) and cervical range of motion (ROM), while secondary outcomes included Visual Analogue Scale for pain (VAS-Pain), Neck Disability Index (NDI), Fatigue Severity Scale (FSS), Breastfeeding Self-Efficacy Scale–Short Form (BSES-SF), QOL assessed using Short Form-36 Health Survey (SF-36), and infant anthropometric measurements (weight and length). All outcomes were assessed at the Outpatient Clinic of the Physical Therapy Department, Suez Canal Authority Hospital, Port Said, Egypt, at baseline and after the 8-week intervention. Mixed-design MANOVA demonstrated significant improvements from pre- to post-intervention in both groups across all measured outcomes (all p  < 0.001). However, the study group exhibited significantly greater improvements than the control group in all outcome measures (all p  < 0.001). The magnitude of these effects was large to very large, with partial eta-squared values ranging from 0.621 to 0.990. In breastfeeding women with FHP, Pilates exercises with breastfeeding positioning adjustment significantly improve CVA, cervical spine mobility, breastfeeding self-efficacy, QOL, and infant growth parameters, while reducing pain, neck disability, and fatigue.

Growing up without violence (GWV): Results of a cluster randomised trial of a school-based intervention preventing adolescent sexual abuse and exploitation in Brazil

Introduction Child sexual abuse and exploitation (CSAE) are pervasive problems that significantly affect the health of children and adolescents. This paper presents the results of a cluster randomised controlled trial (cRCT) evaluating a school-based intervention designed to prevent CSAE in Brazil through education. Methods We conducted a two-arm cRCT with parallel assignment in two Brazilian municipalities. Sixty schools were randomly allocated to intervention and control arms (30 per group) using stratified randomisation based on municipality and school type (municipal and state-run). We invited 50 randomly selected students, aged 12–17, from each school to complete surveys at baseline and endline. Teachers enrolled in GWV training completed an implementation questionnaire. Our primary analysis focused on a cross-sectional comparison of students’ CSAE risk knowledge between control and intervention schools. Results We found no statistically significant difference in adolescents’ CSAE risk knowledge between the study arms (adjusted mean difference: 0.02, 95% CI −0.19 to 0.23, p = 0.87). There was borderline evidence of interaction by gender, with a greater difference in knowledge scores among girls (p = 0.032). No significant association was found between the number of GWV components implemented and knowledge scores. Discussion Several factors may contribute to this result: the intervention might not have been implemented with sufficient fidelity or intensity, the true effect of GWV could be minimal and below the study's detection threshold, the intervention may have influenced outcomes that were not measured, or the intervention may simply lack effectiveness. Further rigorous evaluations and implementation studies are essential to ensure that resources are directed toward effective strategies. Trial registration The American Economic Association’s registry for randomised controlled trials (AEA RCT Registry). RCT ID: AEARCTR-0011299, https://www.socialscienceregistry.org/trials/11299

Iptacopan in IgA Nephropathy — Final 24-Month Data

LPP-GKM: a lightweight and privacy-preserving group key management scheme to enhance security in the internet of things

Abstract The rapid proliferation of the Internet of Things (IoT) has enabled large-scale connectivity among heterogeneous and resource-constrained devices. Although this connectivity supports applications in healthcare, transportation, industrial automation, and cyber–physical systems, it also increases the difficulty of providing secure, efficient, and privacy-preserving group communication. Conventional group key management (GKM) schemes may impose substantial rekeying, communication, and credential-management overhead, while static identifiers or public credentials can expose devices to identity tracing and session linkage. This paper presents Lightweight and Privacy-Preserving Group Key Management (LPP-GKM), a group key management scheme for dynamic IoT groups. The revised design combines pseudonym-based ECC mutual authentication, transcript-bound session-key establishment, hierarchy-based encrypted rekeying, and controlled pseudonym refresh. During normal authentication, a device sends its current pseudonym, an ephemeral ECC point, and freshness information without transmitting its stable public key. The trusted Group Manager (GM) resolves the corresponding public key internally from a protected registration record and establishes an authenticated device–GM session key. For membership changes, LPP-GKM uses a balanced symmetric key hierarchy. The GM refreshes the affected keys from the changed member leaf to the root and encrypts replacement keys under keys held only by authorized sibling subtrees. Consequently, a revoked device may record public rekey-update messages but cannot decrypt the replacement hierarchy keys required to derive the new group key. The design requires $$O(\log N)$$ refreshed hierarchy keys and encrypted update components for a single membership change in a balanced group of N active members, while routine rekeying uses symmetric-key operations only. The security analysis scopes mutual authentication, session-key establishment, post-revocation key exclusion, backward secrecy for newly admitted members, replay resistance, and identity protection under the stated trust and cryptographic assumptions. Privacy is limited to protection against direct identity exposure and transcript-level linkage by external observers and honest-but-curious infrastructure; it is not claimed against the trusted GM, traffic analysis, physical-layer tracking, or GM compromise. The performance evaluation distinguishes device-side operations, GM-side processing, and total network-level rekey delivery cost.

Editorial Note: Enhanced audience sentiment analysis in IoT-integrated metaverse media communication

Sex Hormone Influences on Cardiovascular Risk

Design and implementation of a reconfigurable control architecture for flexible manufacturing teaching units based on EtherCAT

Development and internal validation of a prediction model incorporating SOFA, Prognostic Nutritional Index, and Neutrophil-to-Albumin Ratio for early prediction of in-hospital mortality in patients with Sepsis: A single-center retrospective study

Objective Sepsis prognosis is influenced by organ dysfunction, inflammation, and nutritional status. We aimed to develop and internally validate a prediction model incorporating the Sequential Organ Failure Assessment (SOFA) score, prognostic nutritional index (PNI), and neutrophil-to-albumin ratio (NAR) for early risk stratification of in-hospital mortality in patients with sepsis. Methods We conducted a single-center retrospective study of 120 patients with sepsis. A multivariable logistic regression model was developed and internally validated using bootstrap resampling. Model performance was evaluated through discrimination, calibration, and decision curve analysis, with incremental predictive value assessed by net reclassification improvement and integrated discrimination improvement. Results The SOFA score and NAR were independently associated with in-hospital mortality, while PNI did not reach statistical significance in multivariable analysis. The combined model demonstrated good discrimination with an area under the receiver operating characteristic curve of 0.904, higher than SOFA score alone (0.845) and quick SOFA (0.700), although the difference versus SOFA alone was not statistically significant (P = 0.075). Bootstrap internal validation yielded an optimism-corrected AUC of 0.870. Calibration was acceptable (Hosmer-Lemeshow P = 0.057; Brier score = 0.098). Decision curve analysis demonstrated greater net clinical benefit compared with SOFA score alone. The combined model showed potential improvement in risk reclassification (net reclassification improvement = 0.90; integrated discrimination improvement = 0.15; both P < 0.001), although its improvement in discrimination over the SOFA score alone did not reach statistical significance. Conclusions The combined model showed statistically significant improvement in risk reclassification (net reclassification improvement = 0.90; integrated discrimination improvement = 0.15; both P < 0.001), although its improvement in overall discrimination (AUC) over the SOFA score alone did not reach statistical significance (P = 0.075).

LDL Cholesterol Targeting in Cardiovascular Disease

Rapid microwave-assisted synthesis of nanoflakes like β-SnWO4 nanoparticles towards Li-ion battery and dopamine sensing applications

Rainy-weather speed limit strategies on highways with variable longitudinal slopes

Rainfall substantially degrades highway traffic safety by reducing pavement friction, shortening driver perception distance, and amplifying the adverse effects of longitudinal grade on vehicle dynamics. To support refined speed management under rainy-weather conditions, this study develops a dynamic safe speed-limit model that jointly accounts for pavement friction, longitudinal slope, and perception distance. An improved Intelligent Driver Model (IDM) is further proposed to represent rainy-weather car-following behavior and speed adaptation. The proposed model was evaluated using the Hangzhou West-Fuxi highway section, and simulation experiments were conducted under different rainfall intensities and slope conditions. Model validation showed that the simulated speeds were consistent with observed speed characteristics, with RMSE values of 2.13–3.08 km/h and MAPE values of 2.31%−4.12%. The safety evaluation results indicated that the proposed speed-limit strategy reduced conflict rates by 7.1%, 73.6%, and 82.4% across the three rainfall scenarios compared with the unrestricted-speed condition. Sensitivity analysis further showed that increasing rainfall intensity reduced the pavement friction coefficient, increased braking distance, and narrowed the safety boundary, particularly on downhill sections. The results indicate that no additional speed restriction is generally required for rainfall intensities of 0–1.0 mm/min, whereas rainfall intensities of 1.0–5.0 mm/min require progressively stricter speed limits. A longitudinal slope of +1% provides the most favorable operating condition, while a −3% slope represents the most adverse case. These findings provide a quantitative basis for adaptive highway speed-limit control under rainy-weather conditions.