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PubMed2026

Dissociating behavioral, neural and experiential effects of prefrontal HD-tDCS during conflict resolution.

Inconsistent evidence regarding the cognitive effects of transcranial direct current stimulation (tDCS) highlights the need for more comprehensive approaches to assess its impact. This study aimed to investigate the effects of high-definition tDCS (HD-tDCS) on conflict resolution by combining behavioral, neural, and subjective experience measures. Sixty participants were randomly assigned to anodal, cathodal, or sham HD-tDCS groups and completed a 30-min flanker task. EEG was recorded during the first and last blocks (without stimulation), while stimulation was applied during the intermediate blocks of the task. Using a multidimensional methodological approach including Drift-Diffusion Modeling (DDM), EEG spectral analysis, Lempel-Ziv complexity, and Temporal Experience Tracing (TET), we assessed the cognitive, neural, and phenomenological effects of stimulation. Behavioral results indicated no significant improvements in reaction times or accuracy across the stimulation groups. Similarly, DDM parameters showed no effect of HD-tDCS on latent cognitive processes. However, EEG data revealed a significant reduction in neural complexity in the anodal group during resting-state, suggesting a stabilization or reorganization of neural dynamics. Subjective experience analysis identified two distinct clusters of task-related feelings, though time spent in these experiential states did not differ between groups. Interestingly, sensation of stimulation was significantly higher for anodal stimulation than sham when analyzed as a single dimension. Despite null behavioral effects, this study provides important insights into the neural and subjective responses to HD-tDCS and highlights the value of integrating complementary multidimensional approaches to better characterize brain stimulation effects. These findings contribute to the ongoing debate about the efficacy of tDCS in cognitive enhancement.

Humans↗

PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Engineered MXene-based nanozyme platform: NIR-II photothermal and dual enzyme-mimetic potentiated chemodynamic synergy for precision tumor eradication.

The antioxidant defense barrier in the tumor microenvironment, particularly glutathione (GSH), considerably restricts the therapeutic efficacy of chemodynamic therapy (CDT). Moreover, CDT generally exhibits relatively mild therapeutic efficacy owing to its intrinsic reaction kinetics, making it difficult to achieve complete tumor eradication within a short time. To address these issues, we construct a functionalized nanotherapeutic platform, Nb2CTx@Ru-PEG2000-FA (NCRPF), for tumor photothermal ablation and enhanced CDT resulting from GSH depletion. NCRPF possesses three key advantages: 1. Efficient near-infrared II photothermal conversion (η = 42.08%), raising the tumor temperature above 45 °C within 90 s for rapid ablation; 2. Dual peroxidase-like and glutathione peroxidase-like activities, simultaneously depleting GSH and generating a burst of ·OH to eliminate residual tumors; 3. Targeted tumor accumulation with 2.9-fold higher efficiency than passive diffusion. Both in vitro and in vivo results confirm that this combined strategy achieves complete tumor eradication with favorable biosafety. Collectively, the NCRPF nanotherapeutic system provides a powerful new paradigm with high translational potential for the complete eradication of breast cancer.

Animals↗

PubMed2026

Innovation-related perception as a key driver of alternative protein acceptance: evidence from an early-stage model for cultivated meat and algae-/microalgae-based alternative protein products in Italy.

Alternative proteins are increasingly considered part of the transition toward more sustainable food systems, yet their diffusion depends critically on consumer acceptance. This study investigates the early-stage acceptance of two alternative protein categories in Italy-cultivated meat and algae-/microalgae-based alternative protein products. Focusing on the first three phases of acceptance, the analysis examines how innovation-related perception (IRP) shapes consumer perceived value (CPV), consumer perceived risk (CPR), and subsequent affective (AFF), cognitive (COG), and conative (CON) responses. Data were collected through an online survey administered to 238 Italian respondents and analysed using partial least squares structural equation modelling (PLS-SEM). The results show that IRP is the main upstream driver of early-stage acceptance in both product domains: more favourable perceptions strongly increase perceived value and reduce perceived risk. In turn, CPV exerts a much stronger influence than CPR on both affective and cognitive attitudes. A tentative cross-model comparison suggests only a descriptive variation in the final transition toward conative acceptance: affective and cognitive responses were both significant in the two models, with a relatively larger affective coefficient for cultivated meat and more balanced coefficients for algae-/microalgae-based products. Overall, the findings support a process-based interpretation of alternative protein acceptance and highlight the central role of innovation-related perception in shaping early consumer responses. These results provide relevant implications for communication strategies, product positioning, and policy actions aimed at improving the acceptability of alternative proteins in food cultures characterised by strong culinary traditions.

Italy↗

PubMed2026

In situ product monitoring in heterogeneous reaction of gaseous trimethylamine on Fe2O3/Fe(NO3)3: Effect of environmental factor and particle property.

Gas-particle reactions represent an important atmospheric heterogeneous transformation process for organic amines (OAs). Environmental factors and particle properties may impact the gas-particle reaction products. Although the products from gas-particle reactions can be monitored by various in situ techniques, related data remain scarce. Here, the interfacial and gaseous products from the reaction of trimethylamine on Fe2O3/Fe(NO3)3 particles under light irradiation with mixed NO2, O2, SO2 and H2O were monitored using in-situ diffuse reflectance Fourier transform infrared spectroscopy and proton transfer reaction time-of-flight mass spectrometry. Dark reaction of gaseous trimethylamine on Fe2O3/Fe(NO3)3 generated two interfacial products types: N-containing ones (CH3NCH2, CH3NO2, (CH3)2NCHO, and CH3N(OH)CHO) and N-free ones (alcohols, aldehydes and acids), both accumulating with reaction progression. Light irradiation and O2 oxidation enhanced formation of these products, while NO2 promoted the production of CH3NO2 and (CH3)2NCHO. H2O and SO2 occupied the active sites of particles to inhibit the formation of all products. Compared to Fe(NO3)3, Fe2O3 showed absolute dominance in contribution to the formation of products. Considering the smaller particle size of Fe2O3 and excess Fe(NO3)3, the physical mixing of them reduced the generation of interfacial products. Furthermore, gaseous products of CH3OH, HCHO, CH3CHO, HCOOH and CH3COOH detection clarified the N-free interfacial products. The presence of Fe(NO3)3 inhibited the formation of HCOOH and favored the formation of CH3CHO in the gas phase. By combining product information with thermodynamic calculations, the heterogeneous reaction pathways of trimethylamine were tentatively proposed. These findings provide a guiding significance for the migration of OAs in real atmospheric environment.

Methylamines↗

PubMed2026

Quantifying the combined effects of semi-closed terrain and monsoon on PM2.5 and O3 pollution aggregation in the North China Plain.

The North China Plain (NCP) and its surrounding regions represent one of the key priority areas for air pollution control. As anthropogenic emissions decline significantly, the effect of terrain and meteorology on air pollution pattern has become increasingly prominent, particularly given the NCP's unique semi-closed terrain and East Asian monsoon dynamics. However, quantitative characterization of terrain-dominated blocking effects remains unexplored. Here we quantitatively assess the blocking effects of mountains and terrain-coupled meteorological factors on air pollutant dispersion. We find the NCP on the eastern side of the Taihang Mountains showed high PM2.5 and O3 pollution levels, with winter PM2.5 and summer O3 high-value zones showing opposite north-south aggregation patterns. PM2.5 and O3 concentrations were highest in plains, followed by platforms, hills, and finally mountains. Within the 120-km buffer zones of the typical mountains in the NCP and its surrounding regions, PM2.5 and O3 concentrations increased initially with altitude but then decreased markedly above a threshold altitude. Above the threshold altitude, mountain blocking effects became dominant. The effective blocking altitudes of typical mountains in the NCP and its surrounding regions ranged between 22 and 929 m for winter PM2.5 pollution, and between 19 and 1060 m for summer O3 pollution. The Terrain-Wind Close Index indicates that the terrain-coupled East Asian monsoon showed stronger blocking effects on PM2.5 dispersion in southern NCP during winter and on O3 diffusion in northern NCP during summer, matching observed high-pollution zones. This study offers key insights for regional joint air pollution mitigation strategies, as well as regional pollution assessment.

Particulate Matter↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans↗

PubMed2026

Interface-dependent V. parahaemolyticus biofilm under varying temperatures, media, and oxygen conditions: implications for seafood safety.

Vibrio parahaemolyticus biofilms play a critical role in pathogen persistence in marine and seafood-processing environments, where oxygen availability, temperature, and surface interfaces vary widely. This study investigated biofilm development by three strains on partially submerged stainless-steel coupons under gas-liquid-wall (GLW) and fully submerged (SM) interfaces. Viable cell counts (log₁₀CFU/cm2) along with normalized protein concentration per viable cell (nProt) and normalized polysaccharide concentration per viable cell (nPol) were measured, under aerobic and anaerobic conditions across a temperature range of 15-30 °C, using tryptic soy broth with 3% NaCl (TSB) and seawater-based medium (SW). GLW biofilms consistently exhibited higher cell counts (6.4-7.3 log₁₀CFU/cm2) compared to SM biofilms (5.9-6.3 log₁₀CFU/cm2), suggesting that enhanced oxygen diffusion promotes bacterial proliferation. Conversely, SM biofilms exhibited significantly higher nProt and nPol levels (p < 0.001), indicating increased production of the extracellular polymeric substance (EPS) matrix under low-oxygen, high-nutrient conditions. Microscopy and three-dimensional surface plot analyses revealed relatively uniform biofilm layers at the GLW interface, whereas SM biofilms formed heterogeneous, tower-like structures. EPS production was further influenced by medium composition, oxygen, and temperature. SM biofilms grown in SW exhibited significantly higher nProt and nPol than those in TSB under aerobic conditions (p < 0.001), indicating enhanced matrix stabilization. Under anaerobic conditions at 15 °C, nProt and nPol were higher, whereas under aerobic conditions, peak nProt and nPol occurred at elevated temperatures. These findings highlight a trade-off between bacterial growth and matrix production and provide insight into biofilm adaptation and persistence in seafood-processing environments. These insights may help develop improved biofilm control and seafood safety management.

Biofilms↗