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Enhancing breath-based diagnostics through eXplainable Artificial Intelligence
Breath analysis is emerging as a non-invasive and promising diagnostic approach capable of assessing a patient’s metabolic state by detecting volatile organic compounds in exhaled breath. This study investigates the potential of breath analysis for the early detection of lung cancer, respiratory and gastrointestinal diseases using open-access data from three distinct datasets. An artificial intelligence methodology is implemented to predict diagnostic labels while addressing class imbalance, an inherent challenge in medical datasets. After evaluating model performance and stability, the most relevant volatile organic compounds identified by the best-performing model for each dataset are analyzed. Using eXplainable Artificial Intelligence, the influence of volatile organic compound abundances on predictions is examined, enabling the identification of key variables and improving model interpretability. The proposed methodology provides a robust framework for breath-based diagnostics, emphasizing the potential of integrating breath analysis with machine learning to advance clinical decision-making despite ongoing challenges related to sampling variability, detection sensitivity, and standardization across studies.
Removal efficiency of pesticide residues on pesticide-spiked Perilla Leaf and Broccoli surfaces using microplasma-treated water
In the current study, we evaluated the applicability of a microplasma device to reduce pesticide residues from the surface of perilla leaf and broccoli. We compared the pesticide removal efficiencies of four different washing methods: soaking in water, bubbling water, microplasma- treated water, and chlorine water. Pesticide-spiked food produce surfaces were treated individually with 2 mL of 2000 ppm of the pesticide solutions diazinon and chlorpyrifos. Washing water treated with microplasma was applied in two different ways, i.e., in bubbling and aerosolized modes. The removal efficiency of pesticides from the produce surface was determined by HPLC analysis following 4 min of treatment. Washing with microplasma-treated water (both under water and aerosolized modes) and chlorine water removed 80.84–87.17% of pesticides from perilla leaves and 51.74–67.77% from broccoli, irrespective of pesticide type. Evaluation of the effective washing systems at different temperatures showed that reducing the temperature from 22°C to 10°C resulted in greater pesticide removal and/or degradation in the case of washing with microplasma-treated water; however, chlorine water washing showed a reverse trend. No significant color differences were observed for any of the washing treatments (p > 0.05), even after one week of refrigerated storage.
Enhanced Formation of Dicarboxylic Acids in the Catalytic Oxidation of Polyethylene With O <sub>2</sub> and NO <sub>x</sub>
ABSTRACT A promising strategy to valorize polyethylene is its oxidation to dicarboxylic acids with O 2 and NO x . However, it remains unclear whether and how the formation of dicarboxylic acids from polyethylene can be increased through catalyst design and reaction parameters adjustment. In this work, it was found that through proper reaction condition selection and in the absence of a catalyst the yield toward dicarboxylic acids could reach ∼29 mol% with only little overoxidation to undesired CO and CO 2 . At high NO partial pressure, the formation of gaseous products is suppressed, yielding an excellent carbon recovery for a variety of polyethylene types. The yield toward dicarboxylic acids can be further enhanced through the addition of a Cu 2+ /V 5+ catalyst up to ∼51 mol% (>90% wt.% diacid), while the excellent carbon recovery can be maintained. It was found that the catalyst system was both robust and tolerant as the use of post‐consumer plastic waste, a mixture of polyethylene and polypropylene, yielded a similar product slate.
FGF18 mediates fibroblast-leukemia crosstalk to promote acute myeloid leukemia progression
Non‑hematopoietic stromal cells are essential regulators of hematopoiesis; however, their contribution to leukemogenesis and immune dysfunction remains poorly defined. Here, we identified fibroblast‑derived fibroblast growth factor 18 (FGF18) as a novel stromal cytokine that reprograms leukemia-immune interactions. Single-cell RNA sequencing of the bone marrow (BM) niche during acute myeloid leukemia (AML) revealed the upregulation of Fgf18 in stromal fibroblasts. Administration of recombinant FGF18 accelerated AML progression, whereas fibroblast-specific Fgf18 depletion markedly delayed disease development and improved the survival of mice. We performed a pooled CRISPR-Cas9 screen in AML cells and identified FGFR3 signaling as a critical mediator of leukemic fitness in the FGF18‑rich microenvironment. Genetic loss of Fgfr3 in AML cells recapitulated the effects of FGF18 deficiency and limited leukemic expansion in vivo. Mechanistically, FGF18 binds to its receptor, FGFR3, on AML cells, activating the AKT-mTOR signaling pathway and inducing interleukin (IL)-6 production. IL‑6 acts autocrinely to reinforce leukemic signaling and paracrinely to activate fibroblast JAK-STAT3 signaling, thereby amplifying stromal fibroblast FGF18 expression and forming a feed‑forward loop that suppresses CD8⁺ T‑cell effector function and weakens anti‑leukemic immunity. Clinically, elevated FGF18 expression correlates with poor prognosis in AML patients. To therapeutically target this malignant crosstalk, we generated an FGF18‑neutralizing antibody that disrupted the stromal-leukemia feedback loop, restored CD8⁺ T cell effector function, and synergized with anti-PD-1 therapy to elicit durable anti‑leukemic immunity in vivo. Collectively, these findings identify FGF18-dependent stromal-leukemia crosstalk that drives AML progression and immune dysfunction, highlighting FGF18 neutralization as a potential therapeutic strategy.
Hybrid deep learning for mental workload classification using EEG with enhanced preprocessing and interpretability
Mental workload classification is critical in safety-sensitive fields such as healthcare and aviation. However, electroencephalography-based approaches still face challenges with generalizability, noise robustness, and interpretability. In this study, we propose an integrated hybrid deep learning framework to address these limitations and enable robust, interpretable electroencephalography-based mental workload classification. The proposed approach uses a Variational Autoencoder to enhance noise reduction and feature extraction from band-wise topographical videos, a Convolutional Block Attention Module to adaptively focus on important spatial-channel Electroencephalogram features, and a Bidirectional Long Short-Term Memory network to capture complex temporal dependencies under leave-one-subject-out cross-validation. We conducted ablation studies to identify each architecture component’s contribution and sensitivity analyses to determine the optimal parameters. The model achieved the highest overall accuracy among the baselines and reached an average accuracy of 83.9% across subjects for classifying four mental workload levels. Ablation studies confirmed the added value of all three architecture components for improving performance. Sensitivity analyses identified optimal parameters, including a 10-second window length that balances temporal context and specificity. For better interpretability and neurophysiological insight, we used Gradient-weighted Class Activation Mapping to visualize key frontal-parietal brain regions and frequency bands associated with workload dynamics. Future research could explore adaptive windowing strategies, multimodal data integration, cross-dataset benchmarking, and evaluation against transformer-based and graph neural network architectures under consistent subject-independent evaluation settings to further enhance model generalizability.
An Efficient Photocatalytic Process for Hydrogen Production and Acetic Acid Synthesis on FAPbBr <sub>3</sub> Perovskite
ABSTRACT Perovskite‐based photocatalytic hydrogen bromide (HBr) splitting offers a promising route for solar‐driven hydrogen production. However, the accumulation of the oxidation product bromine often impedes reaction kinetics due to its sluggish oxidation, which faces a substantial energy barrier of 1.09 V versus NHE. This study introduces acetaldehyde as a stable and highly reductive agent in a perovskite‐saturated HBr system, enabling simultaneous high‐performance H 2 evolution and oxidative upgrading of acetaldehyde to valuable acetic acid. Using a Pt single‐atom‐modified FAPbBr 3 perovskite with exposed (100) and (111) facets, which is different from the traditional morphology of perovskites and provides efficient charge separation, the system achieves remarkable production rates of 1033.13 µmol h −1 for H 2 and 1017.20 µmol h −1 for acetic acid. High apparent quantum efficiencies of 30.62% at 450 nm and 31.78% at 520 nm are attained, with acetaldehyde conversion exceeding 90%. The process demonstrates stability over 15 h, recovering 0.8 mL of acetic acid at an 85% extraction efficiency. This strategy effectively utilizes both electrons and holes to simultaneously produce clean energy hydrogen and high‐value organic products.
Farmers’ indigenous knowledge on local herbaceous forages in the Northeastern highlands of Ethiopia
Natural pasture (NP) occupies the top place in livestock feed, particularly in frost-affected highland areas of Ethiopia. Despite numerous studies reporting the huge contribution of local herbaceous forages (LHF) in livestock production, the implementation of those results was not fruitful, attributable to overlooking farmers’ knowledge and experience. Therefore, the study was carried out to scrutinize the indigenous knowledge on LHF in the NP of the northeastern Highlands of Ethiopia. In the present study, we use 323 smallholder farmers (SHF) selected using systematic random sampling from two purposively selected Districts (Mekidela and Tenta) and eight Kebeles employing a multistage sampling procedure. The study analyzed the primary data and highlighted the relevance of SHF’s deep-rooted indigenous knowledge to improving NP and LHF. The findings confirmed that livestock production is mainly dependent on NP in the study area. However, farmers perceived that the NP has been declining with time at an alarming rate, mainly due to forestland (index ( I) = 0.456), cropland ( I = 0.338), and resettlement ( I = 0.139) expansion. The study elucidated that land shortage ( I = 0.172), lack of awareness ( I = 0.17), and eucalyptus expansion ( I = 0.151) were the first, second, and third ranked challenges of utilizing LHF. Farmers reduced animal numbers ( I = 0.234) and practiced zero grazing ( I = 0.34) to improve the LHF in the NP during the dry and wet seasons, respectively. Moreover, further investigations are required to elucidate more merits of LHF species, determine their species diversity, and evaluate their morphological characters.
Interfacial Donor‐Acceptor Engineering in MOFs: Synergizing Self‐Excitation and External Charge Utilization for High‐Efficiency Photocatalytic Hydrogen Evolution
ABSTRACT Aiming at the core challenges in MOF photocatalysts—severe bulk charge recombination and insufficient surface active sites—this study innovatively proposes an interfacial D‐A (Donor‐Acceptor) system. Through a self‐optimized process of nanoconfinement, irradiation decomposition, recapture, and redistribution, three PtL acceptors with different coordination environments, anchored on NH 2 ‐MIL‐125 via amide bonds like antennas, not only undergo self‐excitation under light irradiation but also act as electron acceptors to capture and converge the electrons supplied by the MOF host. Furthermore, the precise tuning of the Pt–N 3 ← Pt–N 2 → Pt‐S 2 coordination microenvironment was achieved, and the optimized d‐band center of Pt‐S 2 effectively balances the activation of water molecules and the transformation kinetics of hydrogen intermediates. Ultimately, NML‐Ptbtp achieves a high hydrogen evolution rate of 901.7 mmol g −1 Pt h −1 and an apparent quantum yield of 14.5% at 365 nm. This work proposes the concept of an interfacial D‐A system for the first time and, through in situ experiments combined with theoretical simulations, confirms its self‐excited reaction behavior and electron‐acceptor‐induced bifunctionality, thereby revealing a novel optimization mechanism for photogenerated charge separation and surface reaction processes.
Interprofessional collegiality and workplace abuse among healthcare workers in eastern Uganda: A convergent mixed-methods study
Interprofessional collegiality reflects mutual respect, empathy and solidarity among different health professionals. Limited studies have explored interprofessional collegiality in Uganda. This study was conducted to determine the magnitude of interprofessional collegiality among healthcare workers in Eastern Uganda. We used a mixed-methods study design. The study was conducted among healthcare workers in two institutions in Eastern Uganda. We used the Practice Environment Scale to assess interprofessional collegiality among a sample size of 136 healthcare workers. The Likert Scale was used to assess the different dimensions of interprofessional collegiality. Ethical approval was obtained. Descriptive statistics were used for quantitative data, while thematic analysis was used for qualitative data. The majority of the participants were nurses/midwives (48%), allied health professionals (40%) and medical doctors (11%). The majority (65%) of participants strongly agreed and agreed that there was effective interprofessional collaboration in their workplace. Participants strongly agreed/agreed that there were good working relations (60%) and good teamwork (56%) between nurses/midwives and medical doctors. However, uncivil behaviours were common among healthcare workers, including psychological/emotional abuse (78%), physical abuse (4%), and sexual abuse (4%). In a qualitative study, uncivil behaviours occurred in the form of cold wars, name-calling, political interference, silent hatred, psychological stress, demotivation, absenteeism, and poor work relations. Poor collegial relations occurred from the individual (gender bias, perceived lack of capacity, poor supervision and leadership), interpersonal (lack of interpersonal respect, perceived lack of role clarity) and institutional factors (workload, poor working conditions, and maldistribution of incentives). Despite the high interprofessional collegiality reported between nurses/midwives and medical doctors, workplace abuse among healthcare workers was high in our setting. Policymakers could prioritise strategies that address individual, interpersonal and institutional factors that result in poor work relations among healthcare workers.
Radical‐Mediated Dispersion Breaks Aggregation Limits in Carbon Thermoelectrics
ABSTRACT Carbon‐based materials, particularly single‐walled carbon nanotubes (SWCNTs), are promising candidates for flexible thermoelectric applications due to their excellent electrical conductivity and mechanical robustness. However, severe self‐aggregation of SWCNTs leads to suboptimal and degraded thermoelectric performance. Conventional dispersion strategies have proved largely ineffective in overcoming this limitation. Here, we present a pioneered radical‐mediated dispersion (RMD) strategy, enabled by a rationally designed small molecule, OTN, which incorporates a donor‐acceptor conjugated backbone and pendant free‐radical terminals. The RMD strategy mechanism functions through dual interactions: The donor‐acceptor backbone enhances π‐interactions with SWCNTs, while the pendant radicals facilitate radical‐radical interactions to further suppress nanotube aggregation. This synergistic molecular design enables OTN‐SWCNT hybrid films to achieve a high power factor of 30.1 µW cm −1 K −2 , far exceeding previous reports, while maintaining excellent free‐standing mechanical flexibility. Furthermore, a nine‐leg thermoelectric device assembled from these films delivers a normalized power density of 0.653 µW cm −2 K −2 , representing one of the best performances for CNT‐based thermoelectrics to date. This pioneering molecular design, together with the derived innovative RMD strategy overcomes the long‐standing aggregation of SWCNTs and is anticipated to open new avenues for advancing carbon‐based thermoelectric materials toward practical, flexible energy‐harvesting applications.
Dissolved inorganic carbon driven dynamics of calcite shell formation in 12 strains of the freshwater algae Phacotus lenticularis (Chlorophyta)
The present rise in temperature, pCO 2 and altered precipitation impact lake water alkalinity and dissolved inorganic carbon (DIC) dynamics. Such changes on carbonate chemistry have been shown to modify calcification of shell-forming phytoplankton in marine ecosystems. Similar responses in freshwater systems remain largely unexplored. In this study, we investigate the direct effects of DIC concentration changes on the calcification state of Phacotus lenticularis, a globally abundant unicellular freshwater phytoplankton. The flagellated green algae are major contributors to modern lake carbonate production during bloom formation. P. lenticularis shells have a high CaCO 3 content compared to other pelagic calcifiers and are likely more sensitive to changing lake water carbonate chemistry. We isolated 12 P. lenticularis strains and exposed them to an ecologically relevant range of DIC (0.2 to 12 mmol L -1 total scale) in a culture experiment. By means of high resolution scanning electron microscopy (SEM) and automatic image analysis we measured functional responses and strain-specific variability in response to DIC changes. All P. lenticularis strains showed reduced shell thickness by up to 60% and dissolved calcite crystals structures at declining DIC < 4 mmol L -1 , while increasing DIC > 4 mmol L -1 had no significant effect on shell morphology. We also found no dependence of growth rates up to a lethal DIC of >10 mmol L -1 , pointing to an efficient photosynthetic rate of P. lenticularis in an under-saturated as well as saturated inorganic carbon environment. Phacotus strains showed a preadaptation to ambient DIC concentrations measured in their lake of origin. Strains from the more environmentally dynamic lake Gönningersee exhibited more variable growth rates and cell densities compared to strains from the more stable Großer Ostersee. We hypothesize, that reduced availability of dissolved inorganic carbon and a lowered saturation state with regard to calcite will drive a negative calcification response in P. lenticularis . However, intraspecific variations in sensitivity to DIC changes were evident in our study and may represent a geographically available potential to adapt to new stressors.
Sustainable Pd‐Catalyzed Aminations “on <i>Dirty</i> Water”
ABSTRACT A new approach to Pd‐catalyzed C─N bond formation is disclosed based on observations from Nature, where its use of an “on water” phenomenon allows for variations in its pH and content. By employing highly basic conditions generated from addition of a certain amount of KOH ( i.e ., the “dirt”) to the water, aminations take place quickly. This “on dirty water” approach also provides the needed base, further simplifying reactions. The viscosity of the KOH/water ( i.e ., 30% KOH) presumably prevents dissolution of the organic coupling partners; hence, base‐sensitive groups ( e.g ., esters, nitriles, etc.) are readily accommodated, thereby broadening the scope of this process. Recycling of this highly basic medium is also illustrated, resulting in a very low complete E‐Factor. Several comparisons with recent literature routes are made using not only Pd catalysis, but also with aminations based on earth‐abundant metals such as Ni and Cu, which tend to be carried out in various organic solvents. Water‐based sequences are also shown, including chemoenzymatic catalysis. Prospects for extending this discovery to several other types of valuable bond formations in synthetic chemistry are also presented,
A GIS-based multi-criteria framework for mapping potential irrigated agricultural zones in newly reclaimed arid agroecosystem
Geographic assessment of natural resources is a pillar for sustainable agriculture in newly developed agroecosystems. The current work provides a new framework to discriminate agricultural potential zones by integrating the analytical hierarchy process (AHP) with fuzzy logic under the geographic information system (GIS) platform. The study was conducted on 303.54 km 2 (30354 ha) in the western Nile Delta fringes, Egypt. Topographic maps, field surveys, and laboratory analyses were employed to specify parameters characterizing terrain, soil, and groundwater qualities. The main criteria and their respective sub-criteria were ranked and weighted using the AHP. The GIS tools were employed to generate raster layers using ordinary kriging geostatistical models, normalize the thematic layers using fuzzy membership functions, and integrate the fuzzified layers with their AHP-derived weights using the weighted sum algorithm. Results revealed that the consistency ratio of all the developed pairwise comparison models did not exceed 10%, indicating the efficacy of AHP in allocating the specific contribution of each criterion. Salinity, sodicity, and depth were key parameters controlling soil performance; meanwhile, potential salinity and infiltration problems primarily determined the feasibility of groundwater irrigation. Among four major criteria, the greatest impact was due to groundwater quality (50%), followed by chemical soil quality (24%) and physical soil quality (21%), while slope had the least contribution (5%). The potentiality analysis indicated that the studied soils are promising since good-quality soils occupied more than 60% of the studied area. Groundwaters with good, marginal, and poor quality occupied 40, 23, and 37% of the total area, respectively. The overall potentiality map showed that 36, 26, and 38% of the studied area displayed high, moderate, and low potential for agricultural expansion, respectively. The integration of AHP with GIS tools (geostatistical analysis and fuzzy set) can enhance insight into sustainable land-use planning and suggest also timely cropping practices. Further investigations are advocated to quantify the suitable cropping patterns in the studied region.
Environmental Identification of Novel Enzymes for Polyurethane and Polyamide Degradation
ABSTRACT Better enzymes are needed to develop sustainable methods to recycle plastics with C‐X heterobonds such as polyurethane (PUR) and nylon, for which no industrial‐scale solutions exist. Current methods rely largely on sequence mining based on a small number of known enzymes. Here, we expand the pool of PURases and nylonases by bioprospecting legacy plastic waste with fluorophore plastic mimics combined with fluorescence‐assisted cell sorting (FACS). We identify 29 plastic‐degrading bacteria, from which 12 enzymes are identified by mass spectrometry and homology searches. Compared to existing enzymes, these enzymes show higher thermostability and hydrolytic activities against different high‐molecular weight PUR polymers and nylon textiles compared to previously described wildtype enzymes. To our knowledge, this is the first reported example of enzymes capable of hydrolyzing longer chains of untreated PUR and nylon as well as crosslinked PUR. This study significantly increases the number of known PURases and nylonases and provides starting points for optimization campaigns through protein engineering and for in silico discovery.
Hydrolyzed corn starch with maltotetraose for skin defense through NRF2 pathway activation in human keratinocytes
Oxidative stress, which can be triggered by various external stimuli, such as ultraviolet radiation and pollution, compromises skin health, accelerates aging and skin disorders, and impacts quality of life. This study investigated the potential of hydrolyzed corn starch containing maltotetraose in skin defense through nuclear factor erythroid 2-related factor 2 (NRF2) pathway activation in human keratinocytes. Using DNA microarray analysis and assessing key antioxidant-responsive genes, we evaluated the capacity of this ingredient to enhance cellular defense mechanisms. Human keratinocytes treated with it demonstrated significant upregulation of antioxidant-responsive genes, including HMOX1 , GPX2 , and NQO1 , which are known targets of NRF2. These findings were corroborated by western blotting and immunostaining analyses, which confirmed increased NRF2 protein expression and NRF2 nuclear translocation. Moreover, fluorescence assays and microscopy showed that treatment with the ingredient effectively reduced reactive oxygen species levels in keratinocytes exposed to oxidative stress. These results suggest that activation of the NRF2 pathway by this ingredient enhances the cellular antioxidative response and reduces reactive oxygen species levels in keratinocytes. This NRF2-mediated antioxidative activity positions hydrolyzed corn starch containing maltotetraose as a promising ingredient for cosmetic products, with potential implications for improving skin health, reducing pigmentation, and combating aging. However, these effects were not directly evaluated in this study. Future studies are warranted to evaluate its efficacy in vivo.
Light‐Controlled Modulation of 15‐Lipoxygenase‐1 Regulates Intestinal Inflammatory Signaling
ABSTRACT Photopharmacology offers powerful opportunities for the spatiotemporal control of biological processes, yet the rational design of photoswitchable enzyme inhibitors remains challenging. Here, we report a target‐guided strategy for the development of diazo‐based photoswitchable inhibitors of human 15‐lipoxygenase‐1 (15‐LOX‐1), a key enzyme in inflammatory signaling, ferroptosis, and cancer. Guided by the structural features of known ligands, we developed three complementary photoswitch classes: reversible azobenzenes (ABs), azo‐heteroarenes (HAs), and covalent azo‐bis‐alkynes (BAs). These compounds exhibit efficient E / Z photoisomerization and high bistability, supported by single‐crystal x‐ray diffraction and density functional theory calculations. Enzymatic inhibitory and kinetic studies revealed distinct activity and selectivity profiles within the tested substrates/isoenzyme: AB and HA derivatives function as E ‐ON/Z‐OFF inhibitors, whereas BA derivatives display Z ‐ON/ E ‐OFF behavior, enabling programmable light‐controlled modulation. We validated 15‐LOX‐1 as a therapeutic target in cellular and in vivo mouse models of colonic inflammation, where inhibition suppressed IL‐8 expression. Finally, using our reversible and covalent photoswitches, we demonstrate photoisomer‐dependent suppression of IL‐8. Beyond 15‐LOX‐1, this work establishes a generalizable framework for the rational development of selective photoswitchable inhibitors with tunable biological outcomes.
Evaluating the quality of systematic reviews and meta-analyses published in behaviour analysis journals: An umbrella review
High-quality systematic reviews and meta-analyses are essential for translating evidence into practice. We conducted an umbrella review to evaluate the methodological quality of systematic reviews and meta-analyses published in the field of behaviour analysis up to and including 2023. Eligible studies were identified through targeted searches of seven behaviour analysis journals using APA PsycINFO. Quality was assessed using the Assessing the Methodological Quality of Systematic Reviews (AMSTAR 2) and Revised AMSTAR (R-AMSTAR) instruments. Temporal trends were analysed using Bayesian multilevel regression. The protocol was preregistered on the Open Science Framework (doi.org/10.17605/OSF.IO/U38Z4). We identified 64 reviews (16 of which included a meta-analysis), all of which were rated as ‘critically low’ quality using the AMSTAR 2 criteria. Methodological shortcomings included absent protocol registration, inadequate risk of bias assessment, and failure to assess publication bias. Mean R-AMSTAR adherence was 43.8% (range 11–66%) and increased by 1.08% per year (population-level average marginal effect from the multilevel logistic model (95% CI [0.59, 1.58]), indicating robust methodological improvement over time. Currently, many systematic reviews and meta-analyses in behaviour analysis do not yet meet contemporary standards of methodological rigour. Enhancing the quality, transparency, and consistency of evidence synthesis is vital if systematic reviews are to meaningfully inform practice.
Modulating Surface Potential and Electron/Hole Overlap of Singlet Excited State in Asymmetry End‐Capped Dimeric Acceptors for Efficient and Stretchable Organic Solar Cells
ABSTRACT Back‐to‐back dimeric acceptors have attracted widespread attention for organic solar cells (OSCs) due to their exceptional stability and unique three‐dimensional (3D) charge transport channels. However, these dimers suffer from inferior intermolecular interactions and molecular packing, limiting the development of OSCs. Here, we first employed an asymmetry end‐group strategy to develop a novel asymmetry back‐to‐back dimer DQx‐FCl. Breaking structural symmetry in DQx‐FCl alters the electrostatic surface potential to strengthen intermolecular π ‐ π interactions. Meanwhile, it also reduces the overlap of electron and hole in the singlet excited state to promote charge separation. Thus, the asymmetric DQx‐FCl‐based binary device achieved a superior power conversion efficiency (PCE) of 19.11% along with improved stability, relative to its symmetric DQx‐F. More notably, DQx‐FCl‐based ternary device achieves a record PCE of 20.27% among reported back‐to‐back dimer‐based OSCs. Furthermore, the reinforced intermolecular interactions also enhance the mechanical robustness of OSCs. Flexible devices based on the PM6:L8‐BO:DQx‐FCl attain a PCE of 17.27% with a crack‐onset strain of 14.6%, while the intrinsically stretchable OSC retains 80% of its initial efficiency under a tensile strain exceeding 23%. This study demonstrates the great potential of asymmetric back‐to‐back dimeric acceptors for improving efficiency, stability, and mechanical flexibility toward high‐performance OSCs.
High-yield recombinant production of the semaglutide main chain P29 intermediate using SNAC-tagged enterokinase-cleavable fusion peptides
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insufficient insulin secretion or impaired cellular response to insulin, resulting in increased blood sugar levels and persistent hyperglycemia. The diabetes-related health expenditure worldwide is estimated to have surpassed 1,000 billion USD according to the new data from the International Diabetes Federation. Semaglutide, a long-acting glucagon-like peptide-1 (GLP-1) receptor agonist, has demonstrated high efficacy in glycemic control and body weight loss, is approved for T2DM and obesity treatment. However, up to now, industrial production of semaglutide remains constrained by limited yield and high cost associated with conventional approaches. Therefore, improving production efficiency while reducing manufacturing cost remains a challenge. In this study, we report a new strategy for obtaining semaglutide main chain P29, also known as Arg 34 GLP-1 (9–37), which is a key intermediate precursor in semaglutide synthesis. The method employs a series of semaglutide-derived helical fusion pro-peptides containing the sequence GSHHWHHHSSGDDDDK, which could be cleaved by a 2-step processing via sequence-specific nickel-assisted chemical protein cleavage followed by enterokinase cleavage. Using this strategy, semaglutide main chain P29 was highly expressed and purified to 98% purity, with yields exceeding 5 grams per liter of broth. This process provides improved productivity compared with previously reported strategies. The work establishes an efficient and scalable platform for semaglutide intermediate production and shows potential for large-scale industrial production.
Neuroprotective mechanisms of Thai traditional brain tonic Phy-Blica-O against LPS-induced neuroinflammation: Inhibition of NF-κB in microglia and mice
Phy-Blica-O (PBO) is a traditional Thai polyherbal formulation historically regarded as a brain tonic and memory enhancer. Despite its long-standing ethnomedicinal use, its neuroprotective mechanisms have not been scientifically validated. This study provides the first experimental evidence that PBO alleviates lipopolysaccharide (LPS)-induced neuroinflammation (a process strongly linked to the development of neurodegenerative diseases) through the NF-κB signaling pathway. This study investigates the neuroprotective effects of PBO in lipopolysaccharide (LPS)-induced neuroinflammation, focusing on its ability to modulate the nuclear factor kappa B (NF-κB) signaling pathway in vivo and in vitro . The key constituents of PBO were quantified via high-performance liquid chromatography (HPLC). Antioxidant capacity was evaluated using DPPH, ABTS, and FRAP assays. The anti-neuroinflammatory effects of PBO were assessed in BV-2 microglial cells and male C57BL/6J mice challenged with LPS. Inflammatory mediators and cytokines were quantified at the mRNA and protein levels. NF-κB and MAPK signaling pathway activities were evaluated to elucidate the mechanisms of action of PBO. PBO pretreatment significantly reduced LPS-induced overproduction of nitric oxide (NO) (from 15.69 ± 1.63 to 8.74 ± 0.25 µM at 250 µg/mL, p < 0.001), pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6 mRNA expression reduced by 25%, 31%, and 19%, respectively, p < 0.05), and inflammatory mediators (iNOS and COX-2 protein expression decreased by 41% and 29%, respectively, p < 0.05). Mechanistic analysis revealed that PBO exerts its protective effects primarily through inhibition of the NF-κB signaling pathway, reducing p-IκBα levels by 23% (p = 0.018) and p-p65 levels by 34% (p = 0.039) at 250 µg/mL in vitro, with no significant effect on MAPK signaling. These in vitro findings were corroborated by in vivo outcomes, where oral PBO administration (100 mg/kg for 7 days) significantly lowered iNOS and COX-2 mRNA expression (p = 0.041 and p = 0.018, respectively) and pro-inflammatory cytokine levels in the brains of LPS-challenged mice. Collectively, the results substantiate the traditional use of PBO as a neuroprotective tonic and highlight its potential as a cost-effective therapeutic candidate for preventing or managing neuroinflammatory conditions associated with neurodegeneration. Further studies are warranted to assess its bioavailability, long-term safety, and behavioral efficacy.