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Self-driving laboratories, advanced immunotherapies and five more technologies to watch in 2025

Young people are crucial to research — how can they be paid fairly?

Science on the go: bringing labs into the field

I explore the impact of wildfires on Hawaii’s coral reefs

Mines for a clean-energy metal have a surprise climate effect

Trump will weaken climate action — the rest of the US must not follow suit

Illuminating the multidimensional contributions of small-scale fisheries

Got flu? Promising drug shortens symptoms

Long-lived entanglement of molecules in magic-wavelength optical tweezers

Abstract Realizing quantum control and entanglement of particles is crucial for advancing both quantum technologies and fundamental science. Substantial developments in this domain have been achieved in a variety of systems1–5. In this context, ultracold polar molecules offer new and unique opportunities because of their more complex internal structure associated with vibration and rotation, coupled with the existence of long-range interactions6,7. However, the same properties make molecules highly sensitive to their environment8–10, affecting their coherence and utility in some applications. Here we show that by engineering an exceptionally controlled environment using rotationally magic11,12 optical tweezers, we can achieve long-lived entanglement between pairs of molecules using detectable hertz-scale interactions. We prepare two-molecule Bell states with fidelity $$0.92{4}_{-0.016}^{+0.013}$$ 0.92 4 − 0.016 + 0.013 , limited by detectable leakage errors. When correcting for these errors, the fidelity is $$0.97{6}_{-0.016}^{+0.014}$$ 0.97 6 − 0.016 + 0.014 . We show that the second-scale entanglement lifetimes are limited solely by these errors, providing opportunities for research in quantum-enhanced metrology7,13, ultracold chemistry14 and the use of rotational states in quantum simulation, quantum computation and as quantum memories. The extension of precise quantum control to complex molecular systems will enable their additional degrees of freedom to be exploited across many domains of quantum science15–17.

Clouds reduce downwelling longwave radiation over land in a warming climate

AI-designed proteins tackle century-old problem — making snake antivenoms

Bilayer nanographene reveals halide permeation through a benzene hole

Abstract Graphene is a single-layered sp 2-hybridized carbon allotrope, which is impermeable to all atomic entities other than hydrogen1,2. The introduction of defects allows selective gas permeation3–5; efforts have been made to control the size of these defects for higher selectivity6–9. Permeation of entities other than gases, such as ions10,11, is of fundamental scientific interest because of its potential application in desalination, detection and purification12–16. However, a precise experimental observation of halide permeation has so far remained unknown11,15–18. Here we show halide permeation through a single benzene-sized defect in a molecular nanographene. Using supramolecular principles of self-aggregation, we created a stable bilayer of the nanographene19–23. As the cavity in the bilayer nanographene could be accessed only by two angstrom-sized windows, any halide that gets trapped inside the cavity has to permeate through the single benzene hole. Our experiments reveal the permeability of fluoride, chloride and bromide through a single benzene hole, whereas iodide is impermeable. Evidence for high permeation of chloride across single-layer nanographene and selective halide binding in a bilayer nanographene provides promise for the use of single benzene defects in graphene for artificial halide receptors24,25, as filtration membranes26 and further to create multilayer artificial chloride channels.

All-solid-state Li–S batteries with fast solid–solid sulfur reaction

Atmospheric pressure plasma jet for respiratory face masks decontamination and re-use: Considerations on microbiological efficacy, material impact and product lifecycle

Disposable filtering face piece respirators (FFRs) are not approved for reuse as standard of care. However, lessons learnt from the SARS-CoV-2 pandemic, FFRs decontamination and reuse may be needed as crisis capacity strategy to ensure availability in medical facilities. We studied a decontamination methodology based on atmospheric pressure plasma technology, which allows for rapid, contact-free decontamination without utilisation of harmful chemicals, and suitable to access small pores and microscopic filters openings. Promising performances in terms of bioburden reduction (Log6) were achieved while imparting mainly transient chemical surface modifications to the masks filtering layers. The plasma decontamination process proposed was also considered in terms of the environmental impact of re-use technology for FFR medical devices in order to understand its sustainability. This study assessed the feasibility of an atmospheric pressure plasma approach for the decontamination of disposable filtering face piece respirators (FFR) or respiratory masks commonly used in hospital settings.

Characteristics influencing COVID-19 testing and vaccination among Spanish-speaking Latine persons in North Carolina

Background Latine populations in the United States continue to be disproportionately affected by COVID-19 with high rates of infection and mortality. Our community-based participatory research partnership examined factors associated with COVID-19 testing and vaccination within a particularly hidden, underserved, and vulnerable population: Spanish-speaking Latines. Methods In 2023, native Spanish-speaking Latine interviewers conducted phone-based structured individual assessments with 180 Spanish-speaking, predominantly immigrant Latines across North Carolina. We used univariate and multivariable logistic regression analyses to examine associations between participant characteristics and COVID-19 testing and vaccination. Results Participant mean age was 41.7 (SD = 13), and 77.2% of the sample reported being cisgender women. Most participants reported immigrating from Latin American countries (89.9%), being uninsured (66.1%), and lacking US immigration documentation (51.1%). While most reported ever being COVID-19 tested (83.3%) and ever being vaccinated against COVID-19 (84.4%), only 24% were up to date with vaccination. Nearly half of the sample reported one or more barriers to COVID-19 testing, and over one-quarter reported one or more barriers to COVID-19 vaccination. Higher educational attainment was significantly associated with ever being tested (P = .031). Fewer concerns about the vaccine, including fewer worries about side effects and having more confidence in vaccine effectiveness and safety, was associated with ever being vaccinated (P < .001). Conclusions Spanish-speaking Latines face barriers to getting tested and vaccinated against COVID-19. Although ever testing and ever vaccination rates were high, being up to date with recommended vaccinations was low. Educational attainment and concerns about the vaccine were associated with COVID-19 testing and vaccination, respectively. Our findings suggest the need for culturally congruent strategies to address the challenges facing Spanish-speaking Latines in the United States.

A study on the determination of the factors affecting the happiness levels of older individuals during the COVID-19 pandemic in Turkish society

This study aims to determine the factors affecting the happiness levels of older individuals in Türkiye during the COVID-19 pandemic. The microdata set from the 2020 Life Satisfaction Survey conducted by the Turkish Statistical Institute was utilized, involving 1,863 individuals aged 60 and above. The relationship between happiness levels and various factors was investigated using the chi-square independence test, and the factors affecting happiness were further analyzed through generalized ordered logistic regression. According to the generalized ordered logistic regression model, participants in the 60–64 age group are 10.1% less likely to report happiness compared to those aged 65 and older. Men are 4.3% less likely than women to report happiness. Furthermore, individuals with no formal education and those with primary school education have a 14.4% and 9.4% higher likelihood of happiness, respectively, compared to university graduates. The literature on happiness demonstrates the relationship between different factors and happiness. This study determined that such factors as gender, age, educational status, source of happiness, health satisfaction, hope scale, and homeownership have an impact on the happiness levels of older individuals. The amount of societal support provided to older individuals can be an indicator of their level of happiness.

Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors

This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind direction. Along with Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), the following ML models were looked at: Linear Regression (LR), Support Vector Regressor (SVR), Random Forest (RF), Extra Trees (ET), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM). Using a dataset of 40,000 observations, the models were assessed based on R-squared, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). ET achieved the highest performance among ML models, with an R-squared value of 0.7231 and a RMSE of 0.1512. Among DL models, ANN demonstrated the best performance, achieving an R-squared value of 0.7248 and a RMSE of 0.1516. The results show that DL models, especially ANN, did slightly better than the best ML models. This means that they are better at modeling non-linear dependencies in multivariate data. Preprocessing techniques, including feature scaling and parameter tuning, improved model performance by enhancing data consistency and optimizing hyperparameters. When compared to previous benchmarks, the performance of both ANN and ET demonstrates significant predictive accuracy gains in WT power output forecasting. This study’s novelty lies in directly comparing a diverse range of ML and DL algorithms while highlighting the potential of advanced computational approaches for renewable energy optimization.

Correction: Correction: Association of dietary sodium intake with impaired fasting glucose in adult cancer survivors: A population-based cross-sectional study

Anti-oxidation enhancement, inflammation alleviation, and microbial composition optimization of using tussah (Antheraea pernyi) silk fibroin peptides for hyperglycaemia remission

Objective This study aimed to evaluate the positive effects on anti-oxidation, anti-inflammation, and microbial composition optimization of diabetic mice using tussah (Antheraea pernyi) silk fibroin peptides (TSFP), providing the theoretical foundation for making the use of silk resources of A. pernyi and incorporating as a supplement into the hypoglycemic foods. Method The animal model of diabetes was established successfully. Alloxan-induced diabetic mice were orally administered using TSFP, and the hypoglycaemic effects in vivo were systematically investigated. Results The results indicated that TSFP could significantly reduce the fasting blood glucose (FBG) levels and suppress the mRNA expression of glycometabolism genes of diabetic mice. In addition, the TSFP could ameliorate the lipid dysbolism and contribute to a higher anti-oxidation capacity. Moreover, TSFP could alleviate pathological damages and hinder inflammatory processes of diabetic mice. Besides, the supplementation of TSFP presented a greater ability to shape and optimize the gut microbial composition by enriching the profitable bacteria and inhibiting the pathogenic microorganisms. Correlation analysis also revealed that the abundances of functional bacteria in the TSFP-treated groups exhibited better correlations with serum parameters, which would be of positive significance for blood glucose regulation and inflammation remission. Conclusions These results collectively corroborated the feasibility and superiority of using TSFP for hyperglycaemia remission via anti-oxidation enhancement, inflammation alleviation, and microbial composition optimization, contributing to a safely feasible and biologically efficient strategy for improving anti-diabetic effects.

Correction: Time series models for prediction of leptospirosis in different climate zones in Sri Lanka