Browse Articles

Tunable effective diffusion of CO ₂ in aqueous foam

Aqueous foams are solid materials composed of gases and liquids, exhibiting a large gas/liquid surface area and enabling dynamic exchanges between their fluid components. The structure of binary-gas foams, whose bubbles consist of a mixture of two gases having different affinities with the liquid, thus offers real potential for the dynamic separation of these gases at low cost. In single-gas foams, the structure evolves under the effect of gas flow induced by Laplace pressure differences, arising from heterogeneities in bubble size. This leads to the well-documented Ostwald ripening. In addition to these capillary effects, the structure of binary-gas foams can evolve under the effect of gas flow induced by partial pressure differences, arising from heterogeneities in bubble composition. We experimentally investigate the shrinking of CO 2 -laden 2D foams exposed to air, observing a crust of tiny bubbles at the front. We derive a nonlinear diffusion model for the gas in the foam and propose a description of the whole foam as an effective, homogeneous medium, the key parameter being the gas permeability ratio across the foam’s soap films (≠1 for CO 2 /air). The effective diffusivity of the gas in the foam emerges from the coupling between foam structure and gas transport across soap films. We extrapolate it for various permeability ratios and show that it can vary continuously between the diffusivity of the gas in the liquid and that of the gas in the atmosphere, enabling tunable gas retention and release by controlling the composition of the atmosphere.

Epidemiology and co-infection patterns of community-acquired pneumonia among children from 2015 to 2023 in Henan Province, China: longitudinal surveillance study

Prediction of the ectasia screening index from raw Casia2 volume data for keratoconus identification by using convolutional neural networks

Purpose Prediction of the ectasia screening index, an estimator provided by the Casia2 instrument for identifying keratoconus, from raw optical coherence tomography data using convolutional neural networks. Methods Three convolutional neural networks models (ResNet18, DenseNet121 and EfficientNetB0) were employed to predict the ectasia screening index. Mean absolute error was used as the performance metric for predicting the ectasia screening index by the adapted convolutional neural network models on the test set. Scans with an ectasia screening index value higher than a certain threshold were classified as Keratoconus, while the remaining scans were classified as Not Keratoconus. The architectures’ performance was evaluated using metrics such as accuracy, sensitivity, specificity, positive predictive value and F1 score on data collected from patients examined at the eye clinic of the Homburg University Hospital. The raw data from the Casia2 instrument, in 3dv format, was converted into 16 images per examination of one eye. For the training, validation and testing phases, 3689, 1050 and 1078 scans (3dv files) were selected, respectively. Results In the prediction of the ectasia screening index, the mean absolute error values for the adapted ResNet18, the adapted DenseNet121 and the adapted EfficientNetB0, rounded to two decimal places, were 7.15, 6.64 and 5.86, respectively. In the classification task, the three networks yielded an accuracy of 94.80%, 95.27% and 95.83%, respectively; a sensitivity of 92.07%, 94.64% and 94.17%, respectively; a specificity of 96.61%, 95.69% and 96.92%, respectively; a positive predictive value of 94.72%, 93.55% and 95.28%, respectively; and a F1 score of 93.38%, 94.09% and 94.72%, respectively. Conclusions Our results show that the prediction of keratoconus based on the ectasia screening index values estimated from raw data outperforms previous approaches using processed data. adapted EfficientNetB0 outperformed both the other adapted models and those in state-of-the-art studies, with the highest accuracy and F1 score.

STAGE: A compact and versatile TnpB-based genome editing toolkit for <i>Streptomyces</i>

Streptomyces are naturally endowed with the capacity to produce a wide array of natural products with biomedical and biotechnological value. They have garnered great interest in synthetic biology applications given the abundance of uncharacterized biosynthetic gene clusters (BGCs). However, progress has been hindered by the limited availability of genetic tools for manipulating these bacteria. Several representative CRISPR-Cas systems have been established in Streptomyces to streamline experimental workflows and improve editing efficiency. Nevertheless, their broader applicability has been constrained by issues such as nuclease activity-related cytotoxicity and the large size of effector proteins. To address these challenges, we present Streptomyces -compatible TnpB-assisted genome editing (STAGE), a genetic toolkit based on ISDra2 TnpB, which is approximately one-third the size of Cas9 and enables precise, site-specific gene editing. We demonstrated that STAGE introduces genetic mutations with high efficiency and minimal off-target effects in two industrially important Streptomyces strains. Building on this platform, we developed STAGE-cBEST and STAGE-McBEST, enabling single and multiplexed C·G-to-T·A base editing, respectively, with editing efficiencies exceeding 75%. To further enhance performance, we engineered the ISDra2 TnpB system using an AI-assisted protein engineering framework, resulting in two variants that achieve nearly 100% genome editing efficiency. Additionally, through sequence homology analysis, we identified a TnpB ortholog from the same biological origin of ISDra2 TnpB, which also functions effectively as a gene editing tool. Our study establishes STAGE as a highly precise, programmable, and versatile genome editing platform for Streptomyces , paving the way for advanced genetic manipulation and synthetic biology applications in these industrially important bacteria.

Impact of cone system compatibility on single cone bioceramic obturation in canals prepared with variable taper NiTi rotary files

Cancer disparities: Projection, COVID-19, and scenario-based diagnosis delay impact

There has been limited research on how disparities in cancer mortality may evolve in the future, although relevant socio-economic and regional disparities in cancer risk are well-documented. We studied future trends in breast cancer (BC) and lung cancer (LC) mortality up to 2036 across affluent and deprived communities in nine regions of England, motivated by the distinct socio-economic patterns and burden of these cancer types. We used cancer death registrations from the Office for National Statistics on population and deaths in nine regions of England by underlying cause of death from 2001 to 2018, stratified by sex, 5-year age group, and income deprivation. We applied a gender- and cause-specific Bayesian hierarchical model to obtain robust estimates of cancer mortality by age group, gender, deprivation quintile, and region, up to 2036. In these models, we also used a data-driven proxy for age-at-diagnosis as an additional risk factor, and non-smoker prevalence rates as a proxy for smoking. We found that if pre-COVID conditions and trends remained the same, socio-economic disparities in LC would persist during our projection period. LC mortality rates for women in 2036 were found to be around 60% lower in the least deprived areas of London, as compared to the most deprived in the same region, with the disparities being even higher in northern regions and among men. Using data from the period 2011-2018, our model estimated 2% fewer LC deaths than those registered during the pandemic years (2020-2022) across England (and 4% fewer for men). Scenarios linked to delays in LC diagnosis led to stark differences in future excess mortality – significantly higher excesses in the northern regions compared to the southern regions, and in the most deprived areas compared to the least deprived areas. Additionally, our findings show that if pre-COVID conditions and trends remained unchanged, BC mortality would continue to decline up to 2036, with comparable rates in the regions of England. During the pandemic years, BC deaths were estimated to decline by 1% across England compared to the pre-pandemic trends (2001-2018). However, our analysis shows 10% to 13% increase in BC deaths for women aged 80+ in the same years. Cancer disparities are predicted to persist in the future unless targeted interventions are implemented. Our results underscore the notable impact of delays in cancer diagnosis on cancer mortality and related inequalities. Future research that models different causes of death while adjusting model outputs for competing risk factors might be beneficial. Further models with individual-level socio-economic risk factors would also be useful.

Specificities of chemosensory receptors in the human gut microbiota

The human gut is rich in metabolites and harbors a complex microbial community, yet surprisingly little is known about the spectrum of chemical signals detected by the large variety of sensory receptors present in the gut microbiome. Here, we systematically mapped the ligand specificities of selected extracytoplasmic sensory domains from twenty members of the human gut microbiota, with a primary focus on the abundant and physiologically important class of Clostridia. Twenty-five metabolites from different chemical classes—including amino acids, nucleobase derivatives, amines, indole, and carboxylates—were identified as specific ligands for fifteen sensory domains from nine bacterial species, which represent all three major functional classes of transmembrane receptors: chemotaxis receptors, histidine kinases, and enzymatic sensors. We have further characterized the specificity and evolution of ligand binding to Cache superfamily sensors specific for lactate, dicarboxylic acids, and for uracil and short-chain fatty acids (SCFAs). Structural and biochemical analysis of the dCache sensor of uracil and SCFAs revealed that its two different ligand types bind at distinct sensory modules. Overall, combining experimental identification with computational analyses, we were able to assign ligands to approximately half of the Cache-type chemotaxis receptors found in the eleven gut commensal genomes from our set, with carboxylic acids representing the largest ligand class. Among these, the most commonly found ligand specificities were for lactate and formate, indicating a particular importance of these metabolites in the human gut microbiota and consistent with their observed growth-promoting effects on selected bacterial commensals.

Comparison of dental findings between dentists and pediatricians using intraoral scan-based teledentistry in children

Abstract Background Asynchronous transmission of health information via teledentistry offers the potential for remote diagnosis in pediatric dentistry. The aim of this study was to compare teledental findings obtained from intraoral scans (IOS) with those from conventional visual examinations (VIS) in children. Specifically, the study assessed the diagnostic accuracy of teledentistry using IOS in evaluating oral health and determining treatment needs focusing on comparisons between dentists and pediatricians. Methods Children (mean age 10.04 ± 2.90 years) underwent VIS during routine dental examinations. Two examiners performed the VIS, followed by digital IOS imaging of the oral cavity. Independent teledental evaluations based on the IOS data were then performed by a dentist (DEN) and a pediatrician (PED). Evaluation criteria included general dental status, presence of caries and molar incisor hypomineralization (MIH) (yes/no), restorations (yes/no; and type, if applicable), urgency of dental intervention, and treatment recommendations (no treatment, prophylaxis, follow-up, or immediate intervention). Agreement was analyzed using Gwet’s AC1, Cohen’s d, sensitivity, specificity, and area under the curve (AUC). Results Almost perfect agreement (AC1 ≥ 0.81) was found for all test criteria, with two exceptions showing substantial agreement (AC1 = 0.61–0.80). Agreement values of overall dental status were 0.953/0.962 (primary dentition/permanent dentition (pD/PD)) for DEN and 0.908/0.923 for PED. Caries detection (yes/no) showed an agreement of 0.965/0.995 for DEN vs. 0.930/0.979 for PED, while restorations agreement was 0.988/0.993 (DEN) vs. 0.950/0.946 (PED). MIH assessment showed agreement of 0.996 (DEN) vs. 0.987 (PED). Cohen’s d for the comparison between DEN and PED ranged from small for MIH (0.17), caries detection (0.23) and overall dental status (0.34/0.35) to large for restoration type (0.89). The clinically most relevant item “urgency of dental intervention” showed almost perfect agreement (0.903 for DEN vs. 0.878 for PED), and the final treatment recommendations showed an almost perfect to substantial agreement of 0.832 (DEN) vs. 0.775 (PED). Notably, both examiners showed similar accuracy in assessing the urgency of intervention. Conclusions This study demonstrates the potential of IOS-based teledentistry for pediatric dental assessments. The results indicate that pediatricians can effectively assess oral health and provide reliable treatment recommendations. This approach has the potential to increase access to dental care and to promote interdisciplinary collaboration in pediatric health care.

Influence of main parameters on the displacement process by spontaneous imbibition based on LBM

The imbibition of water into the pores of tight oil/gas reservoir can displace the oil/gas out. Thus it is an important method to improve the recovery efficiency of tight shale gas and oil. This paper investigated the influence of four main dimensionless parameters on the spontaneous imbibition based on a pores distribution of a real shale sample. The results show that the connectivity has the greatest impact on the average imbibition velocity while the impact of the contact angle is the smallest. The capillary number has the greatest impact on the oil displacement efficiency. The impact of main factors on imbibition and displacement is not monotonic, but rather a combination of these factors.

Seeding of visceral adipose tissue with perinatally generated regulatory T cells shapes the metabolic tenor in mice

The Foxp3 + CD4 + regulatory T cells (Tregs) generated around birth are phenotypically and functionally distinct from those engendered during adulthood. That perinatally produced Tregs persist for a protracted period in peripheral lymphoid organs has been well documented, as has their superior ability to protect the organism from many autoimmune diseases. However, their contribution to pools of nonlymphoid-tissue Tregs and their homeostatic functions therein have been little studied. We show that perinatal Tregs preferentially derive from a CD25 + Foxp3 − thymocyte progenitor; that they seed and persist to varying degrees in every nonlymphoid tissue examined; and that transient depletion of perinatally generated Tregs in adults, but not in neonates, is followed by poor reconstitution of Treg numbers and phenotypes in epididymal visceral-adipose tissue (eVAT) and the skin but not in several lymphoid and other nonlymphoid tissues. Potential clinical implications of such a deficiency are highlighted by findings on mice subjected to weight cycling: Imposing a low-fat–high-fat–low-fat diet regimen in adult, but not juvenile, mice results in an impoverished eVAT, but not spleen, Treg compartment, accompanied by normal weight gain and glucose tolerance but profound insulin resistance. These findings point to a layered immune system, the different layers exerting specialized, nonredundant functions.

Deep learning model for screening causes of activated partial thromboplastin time prolongation using clot waveform analysis at multiple wavelengths

A quantitative projection of the net health effects of cannabis legalization in Germany

Background/Aim Cannabis consumption in Germany has been on the rise, culminating in the legalization of recreational cannabis in 2024. This shift aims to minimize the harms associated with black-market cannabis, such as exposure to contaminants, while regulating consumption to reduce health risks. The primary aim of this study is to quantitatively assess the net health effects of cannabis legalization in Germany by balancing harm reduction from fewer contaminants against potential risks from increased consumption. Methods A quantitative projection model was employed to evaluate the potential net health effects of cannabis legalization in Germany. By estimating the likely increase in consumption and corresponding health risks, the study calculated quality-adjusted life year (QALY) losses due to cannabis use disorder (CUD) and long-term health impacts from both cannabis dependence and contamination exposure. Results Projected increases in adult cannabis consumption may lead to 400,000–800,000 new users, resulting in approximately 2,300 additional cases of severe long-term mental health conditions. The corresponding QALY losses from CUD-related harms are estimated to be approximately nineteen times greater than the health gains from reduced contamination-related harm. Sensitivity analysis shows that consumption rates have a strong influence on net QALY outcomes, with even a 1% increase in cannabis use sufficient to produce net population-level harm. Conclusions The findings suggest that cannabis legalization in Germany may not achieve the intended health benefits. Increased consumption, particularly among new users, may result in considerable public health burdens, with QALY losses associated with CUD outweighing gains from reduced contamination. Effective regulation and public health interventions are needed to minimize adverse health outcomes while avoiding a resurgence of black-market sales.

STIM1 transmembrane helix dimerization captured by AI-guided transition path sampling

Stromal interaction molecule 1 (STIM1) is a Ca 2+ -sensing protein in the endoplasmic reticulum (ER) membrane. The depletion of ER Ca 2+ stores induces a large conformational transition of the cytosolic STIM1 C-terminus, initiated by the dimerization of the transmembrane (TM) domain. We use the AI-guided transition path sampling algorithm aimmd to extensively sample the dimerization of STIM1-TM helices in an ER-mimicking lipid bilayer. In nearly 0.5 ms of all-atom molecular dynamics simulations without bias potentials, we harvest over 170 transition paths, each about 1.2 μs long on average. We find that STIM1 dimerizes into three distinct and coexisting configurations, which reconciles conflicting results from earlier crosslinking studies. The dominant X-shaped bound state centers around contacts supported by the SxxxG TM interfacial motif. Mutating residues in this contact interface allows us to tune the STIM1-dimerization propensity in fluorescence experiments. From the trained model of the committor probability of dimerization, we identify the transition state ensemble for TM-helix dimerization. At the transition state, interhelical contacts in the luminal halves of the two monomers dominate, which likely enables the luminal Ca 2+ -sensing domain in STIM1 to condition the dimerization of the TM helices. Our work demonstrates the unique power of AI-guided simulations to sample rare and slow molecular transitions and to produce detailed atomistic insight into the mechanism of STIM1 TM-helix dimerization as a key step in ER Ca 2+ -sensing.

Hydrogeochemical evaluation of groundwater in Deccan Volcanic Province, Maharashtra, India through GIS and statistical techniques

Evaluating the effectiveness of mindfulness-based interventions on rumination and negative emotions in Chinese University Students: A randomized controlled trial

Objectives Rumination and negative emotions are prevalent among university students and are strongly linked to mental health disorders, including depression and anxiety. Group counseling involving a mindfulness-based strategies may help prevent university students from developing rumination and negative emotions and subsequent mental health disorders. This study aims to evaluate the alleviating effect of mindfulness intervention on rumination and negative emotions in university students in China. Methods A randomized controlled trial (RCT) with 2 arms (Intervention Group and Control Group), three assessment time points (pre-intervention, post-intervention, and 3-month follow-up) is proposed. A total of 196 university students are randomly assigned to an intervention group (n = 98) receiving a 2-week, daily 1.5-hour mindfulness training (MT) and a control group (n = 98) receiving peer support (PS) sessions. Participants complete the Mindful Attention Awareness Scale (MAAS), Depression-Anxiety-Stress Scale (DASS-21), and Ruminative Responses Scale (RRS) before, immediately after, and three months post-intervention. Statistical analysis will compare outcomes between groups to evaluate the effectiveness using a repeated-measures ANOVA. Results Before the intervention, no significant differences are observed between groups. After the intervention, the MT group shows significant improvements in MAAS scores and reductions in DASS-21 scores (p &lt; 0.05) compared to the PS group. While immediate improvements in rumination (RRS) are not significant, the MT group exhibits significant reductions in rumination three months post-intervention. Conclusion This study contributes to a better understanding of the effectiveness of mindfulness intervention in alleviating rumination and negative emotions in university students, and it is expected that with the proposed intervention university students can improve their psychological well-being. Besides, mindfulness interventions can potentially be extended to participants suffering from other psychological issues in the future.

Ovarian germline stem cell dedifferentiation is cytoneme dependent

Progenitor cell dedifferentiation is important for stem cell maintenance during tissue repair and age-related stem cell decline. Here, we use the Drosophila ovary as a model to study the role of cytonemes in bone morphogenic protein (BMP) signaling–directed germline stem cell (GSC) maintenance and dedifferentiation of germ cells to GSCs. We provide evidence that differentiating germ cell cysts extend longer cytonemes that are more polarized toward the niche during dedifferentiation to reactivate BMP signaling. The presence of additional somatic cells in the niche is associated with a failure of germ cell dedifferentiation, consistent with the formation of a physical barrier to cytoneme–niche contact and outcompetition of germ cells for BMP. Using BMP beads in vitro, we show that these are sufficient to induce cytoneme-dependent contacts in Drosophila tissue culture cells. We demonstrate that the Enabled (Ena) actin polymerase is localized to the tips of germ cell cytonemes and is necessary for robust cytoneme formation, as its mislocalization reduces the frequency, length, and directionality of cytonemes. During homeostasis, specifically perturbing cytoneme function through Ena mislocalization impairs GSC fitness by reducing GSC BMP signaling and niche occupancy. Disrupting cytonemes by targeting Ena during dedifferentiation reduces germ cell BMP responsiveness and the ability of differentiating cysts to dedifferentiate. Overall, our results provide evidence that cytonemes play a fundamental role in establishing polarized signaling and niche occupancy during stem cell maintenance and dedifferentiation.

A novel technique for ransomware detection using image based dynamic features and transfer learning to address dataset limitations

Adverse drug events associated with sodium zirconium cyclosilicate: A real-world pharmacovigilance study based on the FAERS database

Background Sodium zirconium cyclosilicate (SZC, Lokelma) is a novel hyperkalemia therapy, but comprehensive real-world safety data are lacking. This study aimed to characterize SZC-associated adverse events (AEs) using post-marketing surveillance. Research Design and Methods AE reports for SZC/Lokelma were extracted from the FDA Adverse Event Reporting System (FAERS) (2004–2023). Four disproportionality algorithms (ROR, PRR, BCPNN, MGPS) identified safety signals. Significant system organ class (SOC) signals required ROR ≥ 2; preferred term (PT) signals met all algorithm thresholds, with false discovery rate adjustment. Results Among 1,564 AE reports (49% males, 29.5% females), four SOCs showed significant signals: metabolism/nutrition, renal/urinary, cardiac, and general disorders. Eighteen PT signals included hypokalemia, cardiac failure, and hypertension. Previously unreported AEs (e.g., ileus, ventricular fibrillation) emerged. AEs peaked early (41.87% within 30 days). Subgroup analyses confirmed robustness. Conclusions This study highlights both previously recognized and potentially novel adverse event signals associated with SZC, particularly during the early phase of treatment. While limited by the inherent constraints of spontaneous reporting systems—such as underreporting and missing data—our findings suggest that clinicians may consider closer monitoring of metabolic, renal, and cardiac adverse events during initial therapy. Observed early signals merit further validation in prospective studies, while long-term risks remain to be clarified.

Ice as a kinetic and mechanistic driver of oxalate-promoted iron oxyhydroxide dissolution

Ice often mediates unexpected reactions in the Cryosphere, acting as a fascinating geochemical reactor. Mineral–organic interactions in frozen environments, such as soils and permafrost, are crucial for explaining the flux of soluble iron during melting events, yet the mechanisms remain misunderstood. This study elucidates the unique roles of freezing in the dissolution of iron oxyhydroxide nanoparticles (α–FeOOH) by oxalate, a low molecular weight dicarboxylate, under acidic conditions. From time-resolved experiments conducted over 4 d, we demonstrate that soluble iron was released through reactions in minute volumes of liquid water trapped between ice micrograins. Freeze concentration of nanoparticles, oxalate, and protons into this liquid water drove oxalate- and proton-promoted dissolution reactions at temperatures as low as −30 °C. Remarkably, ice at −10 °C dissolved more iron than liquid water at 4 °C under high oxalate loadings, and even more than at 25 °C under low oxalate loadings. In contrast, high salinity subdued dissolution. Also, sequential freeze-thaw cycles enhanced dissolution by releasing unreacted oxalate that was previously locked in ice. By resolving the chemical controls on mineral dissolution in ice, this work can help explain how freeze-thaw events are supplying new fluxes of soluble iron to nature.

Synthesis and characterisation of new modified polyesteramide resins based on sunflower oil for anticorrosive protective coatings

Abstract Polyesteramide resins were successfully synthesized via aminolysis of sunflower oil with diethanolamine under mild catalytic conditions, yielding N,N-bis(2-hydroxyethyl) sunflower amide (HESA) with a hydroxyl value of 9.02 mg KOH/g. HESA was then polymerised with N,N-Bis(4-hydroxyphenyl)maleamic acid (BHPMA) and N,N-Bis(4-sulfonicphenyl)maleamic acid (BSPMA) to form modified polyesteramide resins for protective coating applications. The synthesized coatings, with a thickness of approximately 30 ± 5 µm, were evaluated for mechanical and chemical properties, including drying times ranging from 58 to 60 h under air-drying conditions, and enhanced corrosion resistance confirmed by 500-h salt spray tests. Analytical techniques such as FTIR, 1H NMR, and SEM confirmed the structure and morphology of the resins. The improved anticorrosive performance was attributed to the incorporation of sulfonic and aromatic groups, which enhance film density, chemical stability, and resistance to ionic penetration. The results support the application of these bio-based resins as eco-friendly and efficient protective coatings for industrial surfaces.