Browse Articles

Sine cosine particle swarm optimization algorithm for optimizing large scale issues

Altering the carbohydrate-binding specificity of the legume lectin FRIL through structure-guided engineering

The Eyes Have It

Quantifying mean, variability, and uncertainty in indoor radon exposure in Pennsylvania using random forest and quantile regression forest models

Abstract Radon is a naturally occurring radioactive gas that poses a serious health risk as the primary cause of lung cancer in non-smokers. Despite the well-known adverse association with health outcomes, current radon exposure assessments are limited to county-level or average-level estimates, which fail to capture regional variability. This study uses Machine Learning models, including Random Forest (RF) and Quantile Regression Forest (QRF), to estimate the indoor radon concentrations at the ZCTA (Zip code tabulation area)-level and characterize uncertainties in model estimates. Incorporating geological, meteorological, and building-specific data, the models aim to improve radon risk assessment by capturing mean exposure, variability, and extreme concentration levels. Processed radon test data ( n  = 718,111) were analyzed using average, variability, and quantile prediction methods. Models that estimate the average radon exposure at the ZCTA-level can yield promising model-fit results, but they do not capture the underlying variability of indoor radon exposure within a ZCTA. We utilize volatility analyses to identify characteristics indicative of high variability of indoor radon exposure. We also show that a QRF model can be used to estimate upper quantiles of residential radon exposure, thereby uncovering localized areas of elevated exposure that were not apparent in mean estimates. The results highlighted the need for a deep characterization of exposure risk and show that regions with moderate average exposure levels could still harbor extreme outliers with implications for evaluating health risks. Utilizing multiple radon exposure models allows for a deeper characterization of radon risk within a geographic area and can better identify high-risk areas. The results from this study provide a foundation for developing mitigation strategies and examining associations between radon exposure and health outcomes at fine scales. Future research should extend the geographic scope and incorporate additional environmental risk factors to establish a comprehensive framework for risk assessment.

FeCu dual-single-atom catalyst promotes gradient H2O2 activation for enhanced methane oxidation to methanol

Abstract Hydrogen peroxide is an attractive and sustainable oxidant, yet its effective application in inert alkane oxidation is limited by the inability to precisely match the distribution, concentration, and reactivity of generated oxygen species with substrate activation requirements. Herein, a dual single-atom catalyst, FeCu/ZSM-CI, in which atomically dispersed Fe and Cu are spatially separated within the microporous framework of ZSM-5, with Fe located in the inner channels and Cu on the external surface, thereby enabling a controlled H 2 O 2 activation gradient. This spatial configuration induces differentiated reactive oxygen species evolution: high-valent Fe=O and •OOH species form in the interior to activate methane into CH 3 OOH, while surface Cu sites selectively convert CH 3 OOH into methanol, mitigating overoxidation pathways. The optimized FeCu/ZSM-CI catalyst achieves a methanol yield of 20.2 mmol g cat −1 h −1 with 90.1% selectivity and a remarkable H 2 O 2 utilization efficiency of 74.6%. Mechanistic studies combining kinetic isotope effects, scavenger assays, in-situ EPR/DRIFTS, and DFT calculations reveal that Fe-Cu synergy shifts the rate-determining step from H 2 O 2 activation to C-H bond activation. These findings establish a generalizable strategy for manipulating ROS spatial distribution via spatial-configuration-driven synergy and a transferable design principle, offering new insights for designing advanced catalysts for selective hydrocarbon oxidation under ambient conditions.

Aspirin after PCI in Acute Coronary Syndromes

Seroprevalence, isolation, comprehensive characterization, and pathogenicity of Clostridium perfringens strain from yak in Xizang, China

Vibronically assisted sub-cycle charge transfer at a non-fullerene acceptor heterojunction

Abstract Excited-state charge transfer underpins organic photovoltaics, photocatalysis and photodetection, but is traditionally thought to require large energy offsets and strong donor–acceptor coupling that can limit device performance. Here, we investigate through-space polymer non-fullerene-acceptor based model heterojunctions in which a perylene diimide acceptor is covalently tethered to a low-bandgap polymer donor. These systems feature an exceptionally small energy offset (< 100 meV) between frontier orbitals, with weak donor–acceptor coupling in the Franck–Condon region. We nevertheless achieve a charge-transfer timescale of ~18 fs. This ultrafast charge-transfer is accompanied via the launch of coherent wavepackets along a high-frequency vibrational coordinate (26 fs period) on the non-fullerene acceptor’s potential energy surface. We uncover specific polymer-centered driving vibrational modes that enable such rapid charge-transfer rates, by mixing Frenkel exciton and charge-transfer states following photoexcitation. Our results demonstrate that ultrafast charge-transfer can be achieved—ultimately limited by high-frequency vibrational periods—even in the absence of large energy offsets or strong ground-state coupling.

Semantic clause retrieval for trademark law using transformer encoders and lexical baselines: a cross-domain agri-robotics compliance case study

Martian ionospheric response during the May 2024 solar superstorm

Abstract Solar energetic events can have considerable effects on planetary ionospheres. However, the erratic nature of these solar energetic events make observations difficult. Here we show a mutual radio occultation observation, which serendipitously occurred just 10 minutes after a large solar flare impacted Mars. This resulted in the largest lower ionospheric layer ever recorded, where it was 278% its typical size. We used in-situ soft x-ray irradiance measurements to show a threefold increase in flux. This infers a different relation of soft X-ray to this layer’s density than previously thought, with variations depending on the amount of spectrum ‘hardening’ leading to the increase of ionisation from secondaries.

Rapid decline of elevated homocysteine level in nitrous oxide use

Site-specific profiling of structure and function of Igµ B cell receptor glycans

Sustained release and efficacy of Kn2-7-loaded chitosan nanoparticles under low pH conditions

Lossy phononic metamaterials for valley nonreciprocity

Ancestry and somatic profile indicate acral melanoma origin and prognosis

Abstract Acral melanoma, which is not ultraviolet-associated, is the type of melanoma reported most commonly in several non-European-descent populations 1–3 , including in Mexican people 4 . Latin American samples are substantially under-represented in global cancer genomics studies 5 , which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures 6–8 . To address this, we characterized the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients—a population notable because of its genetic admixture 9 . Compared with other studies of melanoma, we found fewer mutations in classical driver genes such as BRAF , NRAS or NF1 . Although most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations. The tumours with activating BRAF mutations had a transcriptional profile more similar to cutaneous non-volar melanocytes, indicating that acral melanomas in these patients may arise from a distinct cell of origin compared with other tumours arising in these locations. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

Systemic risk mitigation in supply chains through network rewiring

Abstract The networked nature of supply chains makes them susceptible to systemic risk, where local firm failures can propagate through interdependencies and lead to cascading supply chain disruptions. The systemic risk of supply chains can be quantified and is closely related to the topology and dynamics of supply chain networks (SCN). However, how different network topologies contribute to this risk remains unclear. Here, we ask whether systemic risk can be significantly reduced by rewiring supplier-customer pairs. In doing so, we quantify the extent to which the observed systemic risk is a result of fundamental properties of the dynamical system. We minimize systemic risk by employing a method from statistical physics that respects firm-level constraints to production. Analyzing six specific subnetworks of the national SCNs of Ecuador and Hungary, we demonstrate that systemic risk can be considerably mitigated by 16-50% without reducing the production output of firms. A comparison of network properties before and after rewiring reveals that this risk reduction is achieved by changing the connectivity in non-trivial ways. These results suggest that actual SCN topologies carry unnecessarily high levels of systemic risk and that resilience can be substantially enhanced by targeted supplier changes comparable in scale to one year of natural network evolution.

Root wounds facilitate the uptake of microplastics in crop plants

MuGu:mutual guidance learning between pretrained SAM and lightweight model for medical image segmentation

Design-driven optimization of low-cost reagent formulations for reproducible and high-yielding cell-free gene expression

Abstract Access to recombinant proteins is vital in basic science and biotechnology research. Cell-free gene expression systems provide one approach to address this need, but widespread utilization remains limited by the cost, complexity, and inconsistency of current platforms. To address these limitations, we carry out a multi-dimensional definitive screening design to reduce the number of reagent components and remove costly secondary energy substrates. From 1,231 different reagent formulations, we discover a simple and reproducible system based on 12 components. The optimized reagent formulation can produce 2.4 ± 0.3 g/L of protein product at the 15-µL scale (~$60/g protein ) and 3.7 ± 0.2 g/L (~$39/g protein ) at the 4-mL scale with oxygen supplementation. This provides an average 95% reduction in cost over previous cell-free reagent formulations. We further show that the optimized reagent formulation can produce nucleoside triphosphates from nitrogenous bases and ribose and that it is robust to failure across batches of cell lysates, users/locations, and in the synthesis of more than 20 different proteins. For example, we demonstrate the production of fifteen therapeutically relevant products, including full-length aglycosylated monoclonal antibodies. We anticipate that our optimized reagent formulation will democratize the use of cell-free systems for protein manufacturing and synthetic biology applications.

Micropropagation and ex vitro acclimatization of Lonicera caerulea var. altaica: molecular identification and protocol optimization

Abstract L. caerulea var . altaica occurs within diverse ecosystems of the Altai region and is highly valued for its frost tolerance and beneficial bioactive compounds. This study developed an efficient protocol for micropropagation and ex vitro acclimatization of valuable honeysuckle species. Species identification was performed using a dual DNA barcode approach with the combined rbcL and matK markers. Phylogenetic analysis revealed that specimen ABG_LA_kz grouped with the epitype, verifying its taxonomic identity. Shoot multiplication was conducted on QL medium supplemented with 0.5 mg·L⁻¹ 6-BAP, 0.2 mg·L⁻¹ GA₃, and 0.01 mg·L⁻¹ IBA. After 35 days, this treatment yielded an average of 6.53 shoots per explant, with shoot height of 2.96 cm and 37 leaves per explant. For in vitro rooting, ½ QL medium comprising 1.5 mg l − 1 IBA proved to be most effective, with an average 4.52 roots formed per explant and rooting percentage of 83.3% within the same culture period. An ex vitro acclimatization protocol using a peat: perlite (3:1) resulted in an average of 12.16 roots per plantlet, with an 100% survival. Thirty five days after acclimatization, 303 seedlings were transplanted to the nurseries of the RSE on REM “Altai Botanical Garden” and RSE on REM “Mangyshlak Experimental Botanical Garden”.