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Association between magnesium sulfate use and acute kidney injury in patients undergoing cardiac surgery: a retrospective cohort study
Establishment of a non-invasive age estimation method based on fecal DNA methylation levels in brown bears
Peripheral blood mitochondrial DNA copy number as a non‑invasive biomarker for the duration of mechanical ventilation in children with pneumonia‑associated respiratory failure
Catalyst-free, microdroplet-mediated waste plastic conversion to diacids
Abstract Plastic waste accumulation poses a global threat to both the environment and public health 1–3 . Although catalytic upcycling to value-added chemicals holds promise, its industrial adoption is hindered by additive-induced catalyst deactivation, feedstock heterogeneity, process inflexibility and limited economic viability 4 . Here we report a catalyst-free upcycling strategy that makes use of in situ generation of hydroxyl radicals at microdroplet interfaces 5–8 to enable oxidative cleavage of diverse waste plastics—from polyolefins to rubbers—into carboxylic acids under mild conditions. By eliminating catalyst-dependent pathways, this approach circumvents key challenges of catalyst design and poisoning, while substantially lowering technical barriers and costs 9,10 . Our method achieves complete conversion of polyethylene (PE) with selectivity to short-chain diacids approaching 69% under relatively mild conditions and demonstrated broad applicability to mixed commercial plastics, with scalability demonstrated up to the 300-g scale. Radical intermediate analysis reveals the crucial role of H 2 O in mediating a unique oxidative degradation mechanism: sequential hydroxyl radical addition to alkyl radicals, distinct from classical liquid-phase aerobic oxidation of alkane 11 . This interfacial radical-mediated strategy enables sustainable polymer upcycling with minimal infrastructure. More broadly, this work provides a scalable blueprint for the first, to our knowledge, industrial implementation of microdroplet chemistry, with transformative implications for oxidation processes in organic acid synthesis and beyond.
Entanglement enables coherence transfer and feedforward corrects the state in quantum teleportation on superconducting dynamic circuits
Abstract Quantum teleportation transfers an unknown qubit state from a sender to a receiver using a shared entangled pair and a classically conditioned correction without moving the physical carrier. On the dynamic-circuit hardware, the complete protocol (which includes mid-circuit measurement and conditional feedforward) now runs on a single circuit. We use this to benchmark three-qubit teleportation on a 156-qubit IBM Heron r2 processor (ibm_fez). A single-qubit RY(θ) input was teleported at six angles along a meridian of the Bloch sphere and reconstructed by state tomography alongside two ablation controls; one without entanglement and the other without feedforward. The full protocol returns a mean fidelity of about 0.945, nearly constant across the angles and above the 2/3 full-Bloch-sphere reference at all six sampled angles. Removing feedforward lowered the fidelity to about 0.51, close to a maximally mixed state. On the other hand, removing entanglement yields (1 + cos²θ)/2 with a mean near 0.75, transferring the population but losing the coherence. Together, these results establish that entanglement and feedforward are both necessary. The calibration-limited fidelity serves as a reference for this class of hardware. A separate run returned a Bell-state fidelity value of 0.957. A branch-resolved analysis confirmed that the four measurement branches are Pauli rotations of the target realigned by feedforward. The reported fidelity depends only on the rotation angle and the device noise.
Nanoparticle-enhanced apigenin suppresses androgen receptor signaling and cellular plasticity in LNCaP cells
Abstract Prostate cancer remains highly dependent on androgen receptor (AR) signaling, yet therapeutic escape often emerges through incomplete suppression of AR-driven transcription and activation of compensatory survival pathways. Here, we investigated whether a hyaluronic acid-coated selenium nanoparticle formulation loaded with apigenin (HA-SeNP-Api) could enhance the anti-tumor activity of apigenin in androgen-responsive LNCaP prostate cancer cells. Selenium nanoparticles were generated by reduction of sodium selenite with ascorbic acid, followed by apigenin loading and hyaluronic acid coating. After 72 h treatment, HA-SeNP-Api produced a consistent biological response across several measured endpoints among the tested groups. Apigenin screening identified 6.25 µM as a biologically active sub-IC50 working concentration. At this dose, the nanoformulation reduced AR and PSA mRNA expression to 0.27-fold and 0.42-fold, respectively, and lowered PSA protein to 10% of control. Total apoptosis increased to 44.30%, compared with 31.36% for selenium nanoparticles alone, 9.77% for apigenin, and 3.70% for enzalutamide. The formulation also increased p53 and p21 expression, reduced SOX2, OCT3/4 and SLUG, and retained growth-inhibitory activity in 3D spheroids. These findings suggest that HA-SeNP-Api enhances the biological activity of apigenin under the tested in vitro conditions and modulates AR/PSA-associated readouts, apoptosis-associated responses, and selected plasticity-associated transcripts in LNCaP cells.
Performance evaluation of three multimodal large language models for pediatric profile-based orthodontic screening
Larvicidal and antifungal efficacy of Lasiodiplodia theobromae ethanolic extract against Aedes aegypti larvae and Colletotrichum spp. strains
Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis
A multiuniversity survey on knowledge, attitudes, and practices regarding zoonotic diseases among veterinary students in Vietnam
Abstract Undergraduate students of veterinary science are a key future workforce for zoonotic disease (ZD) prevention and One Health implementation, yet in Vietnam, their understanding of zoonosis-related knowledge, attitudes, and practices (KAP) remains limited. This study aimed to assess KAP toward ZD prevention among veterinary students enrolled at Vietnamese universities and identified factors associated with KAP performance. A cross-sectional survey was conducted between January and November 2021 among undergraduate veterinary science students recruited from ten universities across Vietnam. Participants were invited to complete an online self-administered questionnaire on social demographic characteristics and KAP regarding ZD prevention. Multivariable regression was used to identify factors associated with KAP levels. Among 446 eligible responses to our survey, only 9.6% achieved good knowledge, 83.9% had positive attitudes, and 26.5% reported good practices toward ZDs. Better knowledge was associated with a higher prevalence of positive attitudes (PR 1.13, 95% CI: 1.02–1.27), whereas positive attitudes showed a strong association with good practice (PR 4.66, 95% CI: 2.14–10.17). Senior students (in years 3–5) were more likely to have good knowledge than juniors (PR 2.29, 95% CI: 1.15–4.57), but were less likely to report good practices (PR 0.59, 95% CI: 0.41–0.84). Students in the Central Highlands had lower prevalence of both good knowledge and positive attitudes than those in the North–Central region (PR 0.42, 95% CI: 0.18–0.95 and 0.76, 95% CI: 0.66–0.87, respectively). While veterinary students in Vietnam have a positive professional attitude, there are critical gaps in foundational knowledge and preventive practice relating to ZDs. These findings suggest that strengthening theoretical training, expanding competency-based instruction, and standardizing infection prevention and control protocols may help improve veterinary students’ preparedness and support Vietnam’s One Health strategy.
Challenges of analyzing synthetic tabular data generated from 115 phase 3 oncology trials
Adaptive filtering strategy for maneuvering target tracking with two angle-only sensors
Blood drop patterns and explainable AI reveal livestock anemia signatures
Abstract Anemia significantly limits livestock health and productivity. Existing diagnostic methods remain invasive, infrastructure-dependent, or prone to observer bias. This study evaluated a smartphone-compatible, paper-based blood biosensor combined with machine learning and explainable artificial intelligence for reagent-free image-level anemia classification across goats, sheep, and cattle. For each species, a single drop of whole blood was applied to a glycerol-treated paper substrate, producing bloodspot dispersion patterns associated with packed cell volume (PCV)-defined anemia categories. Standardized smartphone imaging and multi-resolution analysis were used to assess classification performance relative to laboratory hematocrit measurements. Classification performance varied by species, suggesting that species-associated differences in bloodspot morphology and image-pattern consistency may influence the diagnostic information available to image-based models. Sheep showed the highest and most consistent image-level classification performance, while goats and cattle showed more variable species-associated bloodspot patterns. Among the evaluated model configurations, lightweight support vector machine models achieved strong image-level performance with low computational demand. Explainable AI analyses provided complementary evidence that model predictions were associated with spatial bloodspot regions and dominant image-variance components. These findings provide preliminary proof-of-concept evidence for a smartphone-compatible bloodspot imaging framework that may support future development of anemia screening tools for precision livestock management after animal-level and field validation. Because animal-level identifiers were not retained, these results should be interpreted as controlled image-level proof-of-concept performance rather than animal-independent diagnostic accuracy.