Browse Articles

Cellulose nanofiber from sunflower heads and pomegranate peels as sustainable reinforcing agents in biopolymer-based films for active packaging of bread

Abstract Pomegranate peels and sunflower heads were used to prepare cellulose nanofibers (CNFs) via chemical and physical processes. The CNFs were characterized using FT-IR, TEM, and XRD, then incorporated into carboxymethyl cellulose (CMC) with clove, cumin, or cinnamon essential oils to form bioactive edible coating films. TEM revealed homogeneous nanofibers (diameters 6–15 nm), while XRD showed crystallinity of 69% (sunflower) and 72.5% (pomegranate). Essential oils were evaluated for chemical properties and antimicrobial activities. GC-MS identified eugenol (85.65%) and cinnamaldehyde (84.51%) as major constituents of clove and cinnamon oils, respectively. Clove oil showed the highest total phenolics and antioxidant activity, whereas cinnamon oil exhibited the strongest antimicrobial activity. Mechanical optimization was performed using CMC films reinforced with sunflower-derived CNFs, the maximum increases in tensile strength (from 10.4 to 28.5 MPa) and Young’s modulus (from 450 to 1603 MPa) at 10% CNFs loading, representing increases of 174% and 256%, respectively. Bread coated with films containing the cinnamon/cumin oil mixture had the lowest microbial counts after 72 h of open-air storage (bacteria: 9.4–9.5 × 10 4 CFU/g; mold/yeast: 7.0-7.5 × 10 3 CFU/g), which were lower than those of the uncoated control. Bread coated with pomegranate CNFs and clove oil showed the slowest weight loss and best freshness retention during the tested 72 h storage period. Organoleptic evaluation gave coated bread higher scores for crust color and aroma than uncoated controls. The CNF/essential oil containing coatings helped maintain bread quality and lowered microbial counts relative to the uncoated control during the tested 72 h open-air storage. This study demonstrates that agricultural wastes can be valorized through CNF extraction and that CNF-reinforced bionanocomposites with essential oils are promising candidates for short-term bioactive food-coating applications.

Genetic and health determinants of cancer risk in Bangladeshi and Pakistani individuals in the UK

Abstract South Asian populations remain underrepresented in cancer genomics, despite elevated risk for certain malignancies and distinct clinical profiles. This gap is especially pronounced for British Bangladeshi and Pakistani communities. We analyse data from 57,416 individuals of Bangladeshi and Pakistani ancestry in the UK-based Genes & Health cohort, integrating electronic health records, cancer registry data, and whole-exome sequencing (n = 43,462). Among them, 2,782 (4.8%) has cancer, with earlier onset across multiple types compared to national benchmarks. A phenome-wide case–control analysis identifies 132 significant cancer–comorbidity associations, with larger effect sizes observed for topographically concordant cancer-comorbidity pairs, and stronger associations for systemic disorders such as obesity and hypertension. Exome-wide analyses reveal 39 variant-level and 31 gene-level associations, over 60% absent from major genomic databases assessed and enriched for ultra-rare coding variations. Notable loci included ARHGAP45 , CBR1 , FKBP6 , NF1 , and ZNF155 , with several ancestry-specific associations. These findings highlight distinct cancer risk architectures in this South Asian subpopulation, emphasising the need for population-tailored risk models and screening strategies.

Neurovascular and inflammatory effects of biperiden in the acute phase of moderate traumatic brain injury: evidence from a non-human primate model

Structural choreography of bacteriophage N4 ejection proteins and the giant virion-associated RNA polymerase

Effects of guava pomace combined with gut modulators on growth performance, cecal histomorphology and gene expression in rabbits

Abstract Sustainable intensification of rabbit production necessitates the exploration of non-conventional feed resources to mitigate the rising costs and limited availability of conventional ingredients. The present study evaluated the effects of dietary inclusion of dried guava pomace (DGP), alone or combined with a prebiotic source of mannan-oligosaccharides and β-glucan or an organic acid blend, on growth performance, selected hemato-biochemical parameters, cecal histomorphology and some growth and immune-related gene expression in healthy New Zealand White growing, 28-day old, male rabbits. Compared with the control diet, the DGP-based diet presented significant improvements in final weight, final weight gain, feed intake, and feed conversion ratio as well as performance index ( P  < 0.01). Furthermore, fortification of diets with an organic acid blend plus DGP improved selected hematological indices, with no signs of liver or kidney impairment. Examination of cecal histomorphology showed increased villus height and preserved mucosal integrity in rabbits fed DGP-based diets. Gene expression analysis revealed increased muscle insulin-like growth factor-1 (IGF-1) in supplemented groups, whereas expression of inflammatory markers (TNF-α and IL-1β) showed tissue-specific response. Cecal inflammatory gene expression was not significantly affected. These findings indicate that DGP can be used in rabbit diets, alone or with functional additives, as a promising strategy for supporting rabbit health and productivity. Further study is needed to evaluate optimal inclusion levels, characterize bioactive components, assess long-term physiological effects, gut microbiota outcomes, and assess economic viability under commercial production conditions.

Process-separated cascade catalysis for highly efficient alkane-to-aromatic conversion

Predicting corrosion degradation of power system equipment in high humidity environment using XGBoost algorithm with a coupled environmental operational modeling approach

The hippocampus becomes topographically and functionally specialized along the longitudinal axis with development

Insights into ctDNA assessment to detect minimal residual disease (MRD) in localized colorectal cancer

Sulfonyl-PYBOX/ErCl3 complex enable highly enantioselective synthesis of α,α-dialkyl and α-alkyl-α-aryl hydrazinonitriles

Abstract We report the highly enantioselective nucleophilic addition reaction of simple ketone-derived hydrazones. Accordingly, a ErCl₃-catalyzed cyanation of both aliphatic and aryl ketone hydrazones is achieved for the facile access of C α -tetrasubstituted α-hydrazino nitriles in up to 96% ee, by using the sterically confined pyridinebisoxazoline (PYBOX) ligand featuring a sulfonyl group at the pyridine C4 position. This method enables the shortest catalytic enantioselective total synthesis of L-carbidopa , a drug that could treat the symptoms of Parkinson’s disease, with 82% overall yield in four steps. These adducts are valuable synthons to various α-tertiary hydrazines and related azacycles that are interesting targets for medicinal studies and pesticide research. From our biological analysis, a chiral α-hydrazino nitrile with good insecticidal activity against Aphis gossypii (LC 50  = 15.11 mg∙L –1 ) was identified, rivaling commercial insecticides.

Integrating physical modeling with artificial intelligence for predicting fish survival zones in polluted rivers to maintain a sustainable aquaculture industry

Abstract Water quality prediction and management are crucial for ensuring the sustainability of water supplies. Contaminated water can harm humans and aquatic life. As the demand for seafood grows, the aquaculture industry faces several obstacles, including disease management, feeding optimization, water quality monitoring, and aquaculture area extraction. Recently, aquaculture systems have increasingly used AI techniques to successfully and sustainably handle these issues. However, traditional AI techniques such as random forest (RF) and multi-layer perceptron (MLP) among others frequently face data scarcity and poor physical consistency. This research bridges this gap by integrating physical sciences with AI algorithms through the solution of the two coupled pollution–aeration equations to generate a high-fidelity physics-derived dataset of 50,000 observations over an extended spatial domain ranging from 0 to 4. This dataset is then used to train a novel hybrid RF–MLP algorithm to identify fish-survival zones within a polluted river at a given time, while determining the minimum allowable water velocity and the upstream dissolved oxygen level required to maintain environmentally safe conditions along the entire river reach. The proposed algorithm employs a three-stage sequential residual learning logic, combining RF’s stable feature partitioning with MLP’s improved non-linear error correction. The algorithm’s performance was benchmarked against nine standalone AI algorithms using a comprehensive suite of metrics. The experiments demonstrated exceptional precision with a Correlation Coefficient (CC) of 0.9999999973, a Scatter Index (SI) of 0.00007326, a Willmott’s Index (WI) of 0.9999999986, a Test RMSE of 0.00012966, and a 0.9999999692. Beyond accuracy, the hybrid algorithm demonstrated superior computational efficiency, training in just 22.58 s—a 24.45-fold reduction compared to BiLSTM architectures. These results provide a robust tool for decision-makers to identify optimal river reaches for fish farms based on minimum water velocity and permissible dissolved oxygen transfer levels, bridging the gap between theoretical physics and industrial aquaculture management.

Inducible T-bet deletion reveals tissue-specific requirements in NKp46+ ILC immunobiology and response to murine cytomegalovirus

Abstract The requirement for the T-box transcription factors (TF) T-bet and Eomes in innate lymphoid cells (ILCs) beyond their development is not well understood. Here, we generate an inducible, NKp46-specific T-bet knock-out (KO) model and compare it to corresponding Eomes KO and combined T-bet Eomes double KO mice to define T-box TFs requirement in the homeostasis and function of mature NK cell and other NKp46 + ILC. Inducible T-bet deletion reduces stage IV NK cell numbers in the spleen and tissues, while preserving NK cells in the bone marrow and lymph nodes. Liver ILC1 and small intestine lamina propria NKp46 + ILC3 are also lost upon T-bet deletion, indicating the requirement for continuous T-bet expression in these ILC types. Combined T-bet and Eomes KO leads to a rapid loss of NK cells, markedly greater than with individual T-bet or Eomes KO. Direct comparison of inducible T-bet and Eomes KO models reveals that Eomes is critical for host protection against murine cytomegalovirus, whereas T-bet is dispensable, despite loss of ILC1. These findings establish the tissue-specific and non-redundant roles for T-box TFs in NKp46 + ILCs homeostasis and response to viral infection.

Enzymatic deinking of used-paper using laccase and cellulase from Metarhizium granulomatis and Aspergillus niger: a sustainable upcycling approach

Editorial Expression of Concern: Functional proteomic identification of DNA replication proteins by induced proteolysis in vivo

A randomized controlled trial of a health literacy–based digital intervention to promote postpartum recovery and self-care

Comparative analysis of gut microbiome alterations in early- and late-onset preeclampsia: A case control study

Preeclampsia (PE) is a complication during pregnancy characterized by hypertension, organ damage, and systemic inflammation. Increasing evidence suggests that the gut microbiome may play a role in the pathophysiology of PE. However, previous studies on the gut microbiome have generally overlooked the distinction between subgroups of PE, although clinical manifestations may differ. Also, most studies have not used deep sequencing techniques. Therefore, this study aimed to explore further potential differences in gut dysbiosis in different PE subgroups compared to controls using shotgun metagenomics. We studied the bacterial gut microbiome using shotgun metagenomic sequencing in 37 pregnant patients in the third trimester from a Swedish cohort, separating patients according to subtype (healthy controls N = 21, late-onset PE N = 8, early-onset PE N = 8). Differential relative abundances and alpha diversity were evaluated using Wilcoxon rank sum test, and beta diversity was evaluated using PERMANOVA. Multiple linear regression was used to study associations between gut microbiome composition differences and clinical parameters. Late-onset PE and early-onset PE were both associated with significantly different beta diversity compared to controls. Differences remained significant after adjusting for age, and were not affected by gestational age, BMI or parity. Alpha diversity was lower in late-onset PE compared to controls. While no significant differences in taxonomic abundances were seen after correcting for multiple testing, several interesting leads were identified, including a higher abundance of genus Blautia in late-onset PE, and lower abundance of Coprococcus catus and unclassified Lachnospiraceae in early-onset PE. Functional analysis did not reveal any significant differences after false discovery rate (FDR) correction. In conclusion, our results showed subgroup-specific gut microbiome differences in PE with more pronounced associations in late-onset PE, despite limited power due to the observational design and small cohort. Accordingly, our results highlight the importance of subgroup analysis when studying PE.

Approaching background sounds extend the duration of foreground auditory stimuli

Nuclear shell structure governs short-range nucleon pairing

Focus shifts in contextual and lexical cue interactions in GPT models

Transformer-based language models have demonstrated sensitivity to a range of linguistic dependencies, yet it remains unclear how they represent information-structural focus and integrate discourse and lexical focus cues during ellipsis resolution. We investigated GPT-style models’ interpretation of elliptical remnant continuations in double-object constructions by manipulating contextual focus via preceding interrogatives ( who vs. what ) and lexical focus via the particle only , whose surface position was varied. Using word-by-word surprisal as an index of processing difficulty, we conducted three experiments with GPT-2 models (Small–XL) and GPT-Neo. In Experiment 1 (no only ), models robustly tracked the wh -induced discourse focus, assigning higher surprisal to remnants that mismatched the contextually focused constituent. In Experiment 2 ( only preceding the indirect object), contextual focus continued to dominate, indicating that discourse cues were maintained despite the presence of a competing lexical marker. In Experiment 3 ( only preceding the direct object), lexical focus effects became stronger: models favored remnants aligned with the lexically biased direct object, consistent with locality-based cue weighting when only is adjacent to that object. Comparisons with human reaction-time data revealed broad convergence in contextual-focus sensitivity but divergence when the remnant was compatible with one cue but not the other, with GPT-style models exhibiting a stronger bias toward alignment with only than humans. Together, these findings suggest that the tested models maintain discourse-level focus representations while integrating multiple focus cues in a proximity-sensitive manner, revealing both overlap and limits in their alignment with human processing.

Multi-pathogen serosurveillance in Tonga examining demographic correlates and geographic clustering of 17 pathogens