Browse Articles
Discover research articles across all indexed journals
Phyllosphere microbial communities are modulated by pathogen coinfection, but not a plant defense hormone
Phyllosphere microbial communities play important roles in plant health, yet the roles of plant defense hormones and coinfections in shaping these communities remain unclear. This study investigated how exogenous application of the plant defense hormone salicylic acid and fungal coinfection influenced microbial communities on leaves of tall fescue. In a factorial experiment, we treated leaves with salicylic acid (at 100 mg/L) or a control solution and inoculated them with one of four inoculation treatments: Rhizoctonia solani alone, mock inoculation, co-inoculation with both R. solani and Colletotrichum cereale , or mock co-inoculation. We characterized the fungal and bacterial communities using ITS and 16S rRNA gene sequencing, respectively. Salicylic acid application did not significantly alter the diversity, composition, or taxa abundances of either fungal or bacterial communities. In contrast, co-inoculation significantly shifted fungal community composition and increased fungal diversity compared to inoculation with R. solani alone. Bacterial communities were not significantly impacted by either inoculation treatment. These results suggest that in this system, coinfection has a stronger influence on phyllosphere fungal communities than exogenous salicylic acid application. Our findings highlight the potential for pathogen coinfections to shape plant-associated microbial communities, particularly fungi, and emphasize the need for further research on the effects of salicylic acid across different host species and experimental approaches.
Structural basis for transcriptional regulation by the cell division regulator MraZ in Mycoplasma genitalium
SENTINEL-DL: a forensic framework for device attribution using motion sensor data
Abstract This paper introduces SENTINEL-DL-a novel forensic framework which leverages accelerometer sensory data to associate motion-based digital evidence to its corresponding smartphone or smartwatch models. SENTINEL-DL analyzes robust tamper-resistant intrinsic motion signatures (profiled using built-in 3D accelerometers) to establish device associations. Technically speaking, it leverages small differences in linear acceleration to identify and associate the readings with its generating device. SENTINEL-DL utilizes machine learning models including random forest (RF), deep neural networks (DNN) and convolutional neural networks (CNN) to drive its association during the matching process, i.e., unknown sensory data against a reference database containing device profiles from known sources. The results of empirical tests show that SENTINEL-DL for smartphones and smartwatches, respectively, achieves a true positive rate (TPR) of 93.99% and 92.65%, a false acceptance rate (FAR) of 0.66% and 1.22%, and an overall accuracy of 98.76% and 98.97%. SENTINEL-DL being light-weight promises investigators a dependable analysis solution for motion sensor evidence while providing digital fingerprinting capabilities and forensic authentication support. The research demonstrates how motion sensor data can be utilized in digital forensic investigations to develop improved device fingerprinting and forensic verification methodologies.
Synergistic enhancement of Al-Si7Mg alloy: Strengthening mechanical properties through combined electromagnetic agitation and AL-10%Ti refinement
Al-Si7Mg alloy is widely used in automotive and aerospace applications due to its favorable strength-to-weight ratio and corrosion resistance. However, further enhancement of its mechanical properties remains a key challenge. While grain refinement through chemical additives is common, the synergistic effect of combining a chemical grain refiner with external electromagnetic agitation during solidification has not been fully explored. This study investigates the simultaneous application of Al-10%Ti grain refiner and electromagnetic agitation, via a custom electromagnetic force (EMF) coil, on the microstructure and mechanical properties of Al-Si7Mg alloy. The EMF voltage was varied from 0 to 220 V. Microstructural analysis revealed that the combined treatment effectively transformed coarse, acicular silicon phases into a fine, closed-grain structure. This refinement is attributed to the electromagnetic agitation promoting uniform dispersion and increased potency of Al-10%Ti particles, which act as heterogeneous nucleation sites. The optimized microstructure led to significant improvements in mechanical properties: the sample treated with Al-10%Ti and 180 V EMF exhibited a maximum ultimate tensile strength of 173.3 N/mm², representing a 15% increase over the untreated baseline. Hardness improved by 21%, elongation increased by 60%, and wear resistance was notably enhanced, particularly at higher EMF levels (180–220 V). The results demonstrate that the combined approach offers a synergistic mechanism for microstructural refinement and property enhancement in Al-Si7Mg alloy, providing a promising route for advanced casting processes.
Domain-specific schema reuse supports flexible learning to learn in the primate brain
Abstract Prior knowledge accelerates subsequent learning of similarly structured problems – a phenomenon termed learning to learn – by forming generalizable neural representations called neural correlates of schema (NCS). However, how the brain exploits stable NCS while remaining flexible towards changes (the stability-plasticity dilemma) remains unclear. Here, we show that the primate brain addresses this dilemma by representing the stable NCS and task-unique changes in a near-orthogonal manner. We analyzed neural activities in the dorsolateral premotor cortex of three male macaques trained to perform a series of visuomotor mapping tasks. By delineating decision and stimulus-related subspaces, we identified NCS within the decision subspace, whose reuse facilitated subsequent learning. In addition, the decision subspace exhibited a near-orthogonal relationship with the stimulus-related subspace, minimizing cross-domain interference. Our results reveal that restricting NCS to specific functional domains can preserve useful knowledge while maintaining near-orthogonality with other subspaces, enabling flexible adaptation to new environments, thereby resolving the stability-plasticity dilemma.
Key crops for processed foods have spatially variable biodiversity impacts not captured in other environmental impact indicators
Abstract We must urgently address unsustainable food system practices to protect important ecosystems. Most research quantifying the environmental impacts of food production and consumption has not measured biodiversity impacts directly or spatially, limiting our ability to evaluate how producing and consuming countries are contributing to food system sustainability. Here, we quantify the biodiversity impacts of food crops commonly found in processed foods using a range of accessible metrics. We focus on ingredients found in popular processed foods, such as chocolate digestive biscuits, and show globally reaching impacts. Land-use and fertiliser impacts were greatest for the food crops considered. We also identified Critically Endangered species at risk from habitat loss associated with crops being supplied to the UK specifically. For instance, cocoa production overlaps with nearly 20% of the range of both the Critically Endangered Roloway and Miss Waldron’s Red Colobus monkeys. As crop-specific farm and trade data are not publicly available, it is difficult to know the origin of all ingredients, limiting biodiversity impact estimation. If such data are released in future, our approach can be used to further evaluate biodiversity impacts of foods to inform more sustainable decision-making at consumer, business, and government levels.
How frailty index impacts death in chronic kidney disease: A retrospective observational investigation
Background The present study assessed the link between the frailty index and deaths from all causes or specific causes in patients with chronic kidney disease (CKD). The study data were derived from the National Health and Nutrition Examination Survey (NHANES) (1999–2018) involving 3262 CKD patients. Methods We used 53 multifaceted assessment instruments to measure frailty degree. Multivariable Cox regression analysis was performed, and hazard ratio (HR) and 95% confidence interval (CI) were calculated. Results The median frailty index was 0.166 (interquartile range [IQR]: 0.01 to 0.665). During the median follow-up period of 9.4 years, a total of 1102 deaths from all causes were recorded, which included 196 cancer-related deaths and 402 heart disease-related deaths. Patients in the highest frailty index tertile showed more risk of dying from cardiovascular illness (adjusted HR 2.00, 95% CI 1.52–2.64), all causes (adjusted HR 1.81, 95% CI 1.54–2.13), and cancer (adjusted HR 1.59, 95% CI 1.09–2.33). The increase in cardiovascular-related deaths, all-cause-related deaths, and cancer-related deaths was 112% (P < 0.001), 85% (P < 0.001), and 72% (P < 0.001), respectively, for every logarithmic unit increase in the frailty index. These associations remained robust in stratified tests by sex, body mass index, age, race, diabetes history, hypertension status, and CKD stages. Conclusions Our findings suggest that among patients with CKD, the frailty index is linked to both cause-specific and all-cause deaths. A key element of managing CKD should be frailty intervention as the frailty index may indicate prognosis in these patients.
Defect-interface coupling for stable lattice-oxygen-driven oxygen evolution at industrial current densities
Mechano-stress endorsing heterogeneous lung cancer cells migration into confined channels and investigating tumor spheroids growth of confined space migrating cells
Retraction: Chemical mechanisms of biogas production from wastewater algal biomass via cobalt-catalysed pyrolysis and methanogenic co-digestion
RNA-triggered Cas12a3 cleaves tRNA tails to execute bacterial immunity
Abstract In all domains of life, tRNAs mediate the transfer of genetic information from mRNAs to proteins. As their depletion suppresses translation and, consequently, viral replication, tRNAs represent long-standing and increasingly recognized targets of innate immunity 1–5 . Here we report Cas12a3 effector nucleases from type V CRISPR–Cas adaptive immune systems in bacteria that preferentially cleave tRNAs after recognition of target RNA. Cas12a3 orthologues belong to one of two previously unreported nuclease clades that exhibit RNA-mediated cleavage of non-target RNA, and are distinct from all other known type V systems. Through cell-based and biochemical assays and direct RNA sequencing, we demonstrate that recognition of a complementary target RNA by the CRISPR RNA triggers Cas12a3 to cleave the conserved 5′-CCA-3′ tail of diverse tRNAs to drive growth arrest and anti-phage defence. Cryogenic electron microscopy structures further revealed a distinct tRNA-loading domain that positions the tRNA tail in the RuvC active site of the nuclease. By designing synthetic reporters that mimic the tRNA acceptor stem and tail, we expanded the capacity of current CRISPR-based diagnostics for multiplexed RNA detection. Overall, these findings reveal widespread tRNA inactivation as a previously unrecognized CRISPR-based immune strategy that broadens the application space of the existing CRISPR toolbox.
Middle East dust as an important external driver of the Indian Ocean Dipole
Postoperative nausea and vomiting following orthognathic and temporomandibular joint surgery: a prospective two-center cohort study
Bioinspired triboelectric droplet sensor for ammonia monitoring
Effect of micro-aeration stirring on nitrogen removal in anammox reactor
The disappearing quasi-biennial oscillation under sustained global warming
Structural and physicochemical stability of 3D-printed bolus materials used in radiotherapy
Abstract In radiotherapy, boluses ensure dose buildup at the skin and adapt to complex anatomy, requiring stable, well-conforming materials. This study aimed to investigate the effect of ionising radiation (70 Gy, 6 MV) on changes in the physicochemical properties of two materials used for 3D printing bolus materials for radiotherapy: acrylonitrile butadiene styrene ABS and thermoplastic copolyester TPC. Surface roughness, tribological parameters, hardness, dimensional stability, Fourier transform infrared spectra FTIR, and differential scanning calorimetry DSC data were assessed. After irradiation, small statistically significant changes in roughness parameters were observed for both materials, with ABS exhibiting greater surface degradation. In tribological tests, ABS demonstrated a 70% reduction in coefficient of friction, while TPC remained stable. FTIR spectra revealed changes characteristic of ABS degradation and oxidation (decreases in the intensity of butadiene bands, CH₂ shifts, and increases in carbonyl bands). Subtle chemical stability and potential cross-linking were observed in TPC. DSC suggests no changes in TPC and a decrease in the glass transition temperature of ABS, suggesting slight structural degradation. A slight increase in hardness was observed in ABS and TPC after irradiation, with only minimal dimensional changes in ABS. Based on the data obtained, X-ray radiation affected the tested materials differently. Although both retain their function after exposure to therapeutic doses, TPC exhibits greater chemical and mechanical resistance. Combined with its greater flexibility, this may result in improved clinical adhesion and reproducibility during radiotherapy. Further studies will include analysis of adhesion and dose distribution (Part 2).