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Radiographic legal age estimation based on third molar development using Machine-learning algorithms

Background Age assessment plays an important role in forensic sciences to aid in criminal or civil matters. Third molars continue developing during the legal age of adulthood. Dental age estimation based on radiographic examination is an operator-dependent procedure. The aim was to test the performance of supervised machine learning (SML) to classify individuals according to the threshold of 18 years using the third molar index (I3m). Methods Panoramic radiographs (n = 597) of 52% males and 48% females between 13 and 26 years were used. Three Convolutional Neural Networks were compared to segment the third molar. Several machine learning algorithms were tested with a 10-fold cross-validation approach to identify the best age classification algorithm. The SML age estimation model was compared to the expert. Results Attention U-Net achieved the highest segmentation scores, and the k-nearest neighbors (KNN) showed the best scores of classification algorithms. The SML (KNN) scored sensitivity = 77.77%, specificity = 96%, and AUC = 0.87 in males. In females, sensitivity = 77.4%, specificity = 86.7%, and AUC = 0.82. The expert scores were: sensitivity = 70.4%, specificity = 100%, AUC = 0.85 for male, and for female: sensitivity = 54.8%, specificity = 93.3%, AUC = 0.74. Conclusion SML classified males and females below and above the legal age with high accuracy compared to manual methods. The presented work suggests that AI, using pixel-level analysis, can detect subtle cues beyond human perception. This signals a possible departure from traditional age estimation indices.

Enthalpy‐Entropy Modulation in Electrolyte Stabilizes 4.8 V‐Class Li‐Rich Mn‐Based Cathodes

ABSTRACT Lithium‐rich manganese‐based (LRM) cathode materials are promising for high‐energy‐density batteries due to their high specific capacity. However, their high operating voltage (4.8 V vs. Li/Li + ) compromises cycling stability in conventional carbonate‐based electrolytes. Here, we design a rational “enthalpy‐entropy modulation” strategy for electrolytes, guided by thermodynamic parameters. By weakening ion‐solvent interactions to enhance anion involvement (enthalpy modulation), while amplifying disorder to increase configurational diversity (entropy modulation), we reconfigure the solvation sheath from a solvent‐dominated state to an anion‐involved, diversified configuration. This reconfiguration facilitates lithium‐ion desolvation and suppresses free solvent decomposition, fostering a stable cathode‐electrolyte interphase. Consequently, the LRM cathode delivers extended cycle life (400 cycles, 76.6% retention at 1C), outstanding fast‐charging capability (1068 cycles at 3C with 1.4 mg cm −2 ), and stable cycling under high mass loading of 20.1 mg cm −2 (0.2C). This work demonstrates a thermodynamically guided approach for developing the next generation of electrolytes for high‐voltage LRM cathodes.

PARP and Androgen-Signaling Inhibition plus ADT in Metastatic Prostate Cancer

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.

Low‐Energy Photons in Radical Chemistry: From Deep‐Red to Near‐Infrared Radical Generation for Organic Synthesis

ABSTRACT Highly reactive radical intermediates enable bond formations that are often inaccessible through conventional ionic processes. Visible‐light irradiation has emerged as a mild and sustainable energy input for generating such radical species. Most photo‐induced radical generation methods have relied on photocatalysts or substrates that absorb high‐energy light. Increasing attention has been directed toward photochemical reactions driven by deep‐red (DR) to near‐infrared (NIR) light through the development of chromophores and catalytic systems capable of harvesting low‐energy photons. Compared with short‐wavelength light‐driven processes, NIR light‐mediated reactions offer distinct advantages, including enhanced penetration through biological tissues and reduced unwanted excitation of intermediates, thereby suppressing side reactions. Nevertheless, the intrinsically low energy of NIR photons imposes fundamental challenges, limiting the scope of accessible transformations. This Review summarizes recent advances in photochemical transformations enabled by DR‐ to NIR‐absorbing catalysts and compounds, with a particular focus on strategies for the efficient utilization of low‐energy photons. The discussion is organized according to four distinct activation modes: single‐photon absorption catalysis, triplet–triplet annihilation upconversion, two‐photon absorption (TPA) catalysis, and direct excitation. Through this mechanistic framework, we highlight key molecular design principles that have driven progress in this rapidly evolving field and outline remaining challenges and future opportunities for low‐energy‐light‐driven radical chemistry.

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.

Neutral Borate Buffer Activates Diazo for Rapid Protein Labeling

ABSTRACT Diazo, a carbene precursor, offers an effective chemistry for bioorthogonal labeling upon activation by acids, metals, and/or photo‐illumination. Here, we report neutral borate buffer can trigger diazo compounds into carbene for protein labeling without the need for acid, metal, or light. We show that such boron‐diazo‐mediated covalent modification rapidly occurs within seconds under physiological conditions and preferentially targets carboxylate‐containing amino acid residues. Towards applications of such boron‐diazo protein chemistry, we exemplify the design of an affinity‐based covalent inhibitor for dihydrofolate reductase by installing diazo on the non‐covalent trimethoprim drug. When extended to stressed cells, we also capture cellular aggresomes using a diazo‐Thioflavin T probe that selectively labels aggregated proteins. Finally, in Alzheimer's disease brain tissue, we employ this boron‐diazo chemistry to label, enrich, and profile amyloid plaques, identifying proteins related to pathological deposition. Together, the boron‐diazo chemistry reported herein provides a rapid and facile protein modification strategy under mild conditions.

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.

The Jekyll and Hyde Nature of Tetrazoles in Polymer Science: From Intrinsic Electronic Duality to Programmable Macromolecular Function

ABSTRACT Nature encodes stability and responsiveness within single‐molecule frameworks, creating systems that remain structurally persistent while retaining access to activated functional states. Tetrazoles embody this principle in synthetic chemistry by combining aromatic persistence with latent reactivity within a single nitrogen‐rich heterocycle. Their intrinsic “Jekyll–Hyde” duality arises from a polarized electronic structure governed by the substitution pattern, which acts as an electronic switch between adaptive, triggerable, and structurally persistent regimes. Although tetrazoles are widely used in small‐molecule chemistry, they remain comparatively underexplored as electronically programmable motifs in polymer science. Their polarity, ion‐binding ability, and photoreactivity are often exploited individually rather than integrated into a broader structure–function framework. This Minireview presents a unifying concept linking tetrazole substitution patterns to electronic identity and, consequently, to macromolecular function in polymer systems. Monosubstituted tetrazoles enable adaptive acid–base responsiveness, hydrogen bonding, and ionic network formation. In contrast, 2,5‐disubstituted tetrazoles serve as photoaddressable precursors for nitrile imine‐mediated ligation, covalent fixation, and fluorescent readout, whereas regio‐defined 1,5‐disubstituted tetrazoles provide electronically locked, highly polar heteroaromatic motifs for persistent polymer architectures. Thus, the mini‐review examines how synthetic strategy governs the formation and preservation of these substitution‐defined tetrazole motifs during polymer synthesis, establishing practical design principles for rational development of functional polymer materials.

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

Flipped Spin‐State Resists Cobalt Poisoning for the Durable Electrocatalytic Deuteration of <i>N</i> ‐Heterocyclic Compounds

ABSTRACT Electrocatalytic deuteration represents a sustainable method for synthesizing deuterated N ‐heterocycles, which are scaffolds for drug development. However, the utility of this transformation is severely restrained by strong orbital interactions between metal sites and the lone pairs of N atoms that lead to irreversible catalyst deactivation. Here, we propose a Mn 3 Co 7 alloy electrocatalyst that triggers a high‐spin‐to‐low‐spin transition in Co. The flipped spin state originates from tuned d ‐electron pairing, promoting electron occupation in antibonding orbitals and weakening the Co–N bond. The reduced adsorption energy that facilitates the desorption of N ‐heterocycles is revealed to be the key factor driving the improved catalytic durability. This strategy enables a scaled‐up electrosynthesis with a yield of 92.5% at 1.25 A to obtain 10 g of deuterated piperazine hydrochloride. The methodological universality of diverse unsaturated N ‐heterocycles highlights the application potential.

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.