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Comparison of cognitive ability and its distribution between men with autism spectrum disorder and attention-deficit/hyperactivity disorder

Objectives Clarification of the strengths and weaknesses of cognitive ability is essential to our understanding of the characteristics of autism spectrum disorder and attention deficit/hyperactivity disorder. However, whether individuals with these conditions exhibit distinct patterns of cognitive ability remains unclear. To address this point, we aimed to compare the cognitive profiles of patients with autism spectrum disorder with those of patients with attention deficit/hyperactivity disorder by placing special emphasis on the distribution of cognitive function within each group. Methods This study compared the Wechsler Adult Intelligence Scale index scores of men with autism spectrum disorder and attention deficit/hyperactivity disorder. A machine learning model was trained to classify autism spectrum disorder and attention deficit/hyperactivity disorder based on the subtest scores. The conformity of the within-group distribution of each index score to a normal distribution was also tested. Results Individuals with autism spectrum disorder scored higher than those with attention deficit/hyperactivity disorder in the Verbal Comprehension Index and Working Memory Index, while the opposite pattern was observed for the Perceptual Organization Index. The classification performance of the machine learning model was above chance level. The distributions of the Verbal Comprehension Index and Perceptual Organization Index deviated significantly from a normal distribution only in the autism spectrum disorder group. The results of Gaussian mixture clustering indicated that men with autism spectrum disorder could be divided into two distinct clusters based on their Verbal Comprehension Index scores. Conclusions Our findings indicate that men with autism spectrum disorder and attention deficit/hyperactivity disorder show distinct cognitive profile patterns from each other. The distribution of some of the index scores deviated from the normal distribution only in autism spectrum disorder, which supports the view that autism spectrum disorder comprises heterogeneous subgroups with different cognitive profiles.

Stochastic Poisson-embedded privacy framework for federated learning with secure homomorphic encryption in medical AI

Dynamic stability analysis of mixed-composition platoons with spatially weighted cooperative control

In mixed traffic environments, the spatial distribution of Connected and Automated Vehicles (CAVs) plays a decisive yet previously unquantified role in platoon stability and safety. This study establishes a generalized stability modeling framework for heterogeneous platoons composed of Human-Driven Vehicles (HDVs), Autonomous Vehicles (AVs), and CAVs. By introducing a spatial weighting coefficient (γ), the proposed model captures the influence of longitudinal CAV positioning and allows for flexible representation of any vehicle composition pattern. Linear stability analysis and time-domain simulations are conducted to investigate the interaction between spatial distribution, communication delay, and dynamic response. The results demonstrate that front- and center-loaded CAV configurations effectively suppress velocity perturbations and maintain string stability even under moderate delay, while rear-loaded configurations exhibit early instability. Furthermore, an optimal γ range of 0.3–0.5 is identified to minimize oscillation amplitude, providing a practical guideline for cooperative control strategies in mixed platoons. The findings offer theoretical insights and quantitative evidence for optimizing CAV deployment to enhance stability and robustness in future intelligent transportation systems.

Automated landscape element recognition and layout optimization based on image segmentation and object detection

Singlet Exciton Drives Intracellular Photoredox Catalysis for Pyroptosis in Cancer Cells

ABSTRACT Hypoxia continues to pose a significant challenge in photodynamic therapy (PDT) due to the reliance of conventional photosensitizers on oxygen‐dependent mechanisms, which markedly diminishes their efficacy in hypoxic tumor regions. Current improving strategies are often hindered by reduced catalytic efficiency or intricate synthetic processes, highlighting the pressing need for innovative molecular designs. In this study, for the first time, we introduce a self‐adapting function, mitochondria‐targeted photosensitizer TPP‐Cy that employs a novel singlet exciton‐driven electron transport chain (ETC) breakdown mechanism (named Type‐sETC) to achieve oxygen‐independent PDT. Specifically speaking, TPP‐Cy proficiently generates free radical species under normoxia conditions, while directly photocatalyzing critical mitochondrial biomolecules such as NADH and Cyt c in hypoxic, better than most previously reported metal catalysts. Additionally, even under hypoxia conditions, TPP‐Cy ’s photoredox catalysis significantly disrupts ETC, leading to a severe energetic crisis that compromises cellular viability. Importantly, this photon‐driven cell death occurs through immunogenic pyroptosis, thus possessing the potential for antitumor immunotherapy. Mechanistically, TPP‐Cy breaks the traditional triplet sensitization paradigm, achieving efficient electron transfer with biological substrates through singlet exciton dissociation mechanism. This approach minimizes energy loss during intersystem crossing and broadens the range of catalytic substrates, thereby establishing a novel concept for effective PDT.

Combined machine learning - 3D physics based approach for building damage evaluation: the case of L’Aquila 2009

Suppression of NO ₂ Generation During One‐Step Deep Oxidation of NO at a Semi‐Artificial Photoenzyme Based on Cytochrome <i>c</i>

ABSTRACT Solar‐driven catalysis holds promise in molecular oxygen activation and low‐concentration NO x elimination but achieving highly selective conversion of NO to nontoxic nitrate (NO 3 − ), while suppressing toxic NO 2 formation remains challenging. Here, we report a semi‐artificial photoenzyme catalyst constructed by immobilizing mono‐heme cytochrome c (cyt c ) on carbon nitride (CN) to refine reactive species generation for deep NO oxidation. The hybrid photoenzyme catalyst establishes localized internal electric fields (IEF) between cyt c and CN that promote exciton dissociation, and creates polarized active sites on cyt c that preferentially adsorb O 2 , and activate O 2 to active peroxides (•O 2 − and *O 2 2− ) via an electron transfer pathway with inhibiting 1 O 2 formation. The one‐step NO oxidation to NO 3 − is boosted over cyt c /CN, showing exceptional 97.4% NO conversion with ultralow NO 2 selectivity (1.5%, 6.5 ppb) and long‐term stability (98.1% after 300 min) at a weight hourly space velocity (WHSV) of 850 L g −1 ·h −1 across wide humidity ranges. The undesirable NO 2 generation is significantly lower than that of bare CN (17.0%, 104.7 ppb) and reported catalysts. The catalyst exhibits high activity in direct NO 2 removal (92.9%) and rapidly reduces NO levels to below the safe concentration (52 ppb) in a simulated environment chamber.

Differential distribution of antiviral serology across multiple sclerosis phenotypes and its implications for disease pathogenesis

Aminal‐linked Covalent Organic Frameworks for Light Energy Upconversion

ABSTRACT The conversion of two low‐energy photons into a single higher‐energy photon at low irradiance is highly desirable for bioimaging and solar energy harvesting. Yet translating established solution‐phase triplet–triplet annihilation upconversion (TTA‐UC) systems into robust solid‐state platforms remains a challenge. Here, we report the first covalent organic frameworks (COFs) capable of sensitized TTA‐UC. Two aminal‐linked frameworks integrating anthracene chromophores, Ant‐COF‐H and Ant‐COF‐OH , were synthesized and structurally characterized, revealing high crystallinity and strong photoluminescence ( Φ F ≈ 40%). When sensitized with a palladium porphyrin complex, both COFs display upconverted emission with quantum yields up to 1.8%, surpassing the performance of the conventional all‐in‐solution reference system. Notably, the onset of saturation occurs at excitation power densities as low as 100 mW cm −2 . Time‐resolved emission spectroscopy reveals fast energy‐transfer consistent with intra‐framework triplet migration rather than diffusion. Finally, we correlate framework structural features with energy‐loss pathways, providing design guidelines for further improvement. This work establishes a foundation for practical, low‐power light management in crystalline polymers by demonstrating that aminal‐linked COFs can be engineered to support efficient energy transfer and function as solid‐state upconverters.

Molecular basis for inhibition of α-thrombin activity by bacterial lipopolysaccharides

Abstract Dysregulation of the coagulation pathway is a hallmark of endotoxemia and Gram-negative sepsis, leading to disseminated intravascular coagulation resulting from aberrant thrombin generation. Bacterial components such as lipopolysaccharides (LPS) have been shown to indirectly contribute to thrombin generation by activating or assembling members of the coagulation cascade in an LPS-chemotype dependent manner. Conversely, studies have shown that LPS may directly inhibit thrombin activity through an undefined mechanism. We studied whether the LPS chemotypes from bacteria including Escherichia coli (O111:B4, O26:B6), Klebsiella pneumoniae , and Pseudomonas aeruginosa bind and regulate thrombin activity. We found that these LPS chemotypes bound thrombin exosites via their polysaccharide regions. Only the E.coli O26:B6 and K.pneumoniae LPS chemotypes induced global structural changes in thrombin. Both the monomeric forms of E.coli O26:B6 and K.pneumoniae LPS chemotypes reduced the catalytic efficiency of thrombin and thrombin-dependent fibrin polymerization in purified systems. The E.coli O26:B6 LPS chemotype retained anticoagulant activity in plasma as an Ca 2+ -stabilized aggregate form. Our data suggests that select LPS chemotypes bind and inhibit the proteolytic activity of thrombin in a manner dependent on their supramolecular state. The heterogeneity of physicochemical properties of bacterial envelope components may contribute to the dysregulation of the coagulation pathway during endotoxemia.

Elucidating the Stereodirecting Effect of C‐4 Acyl Groups on Galactosyl Donors

ABSTRACT The stereoselective synthesis of 1,2‐ cis glycosidic bonds is a significant challenge in carbohydrate chemistry. 1,2‐ Cis galactosides can be obtained by using C‐4 acyl protection groups as a stereodirecting group, yet the underlying mechanism that steers selective galactosylation has remained elusive. Herein, we investigate the stereodirecting effect of C‐4 acyl groups in galactosides using glycosylation reactions, exchange NMR spectroscopy and DFT‐calculations. We found no experimental evidence for C‐4 dioxepanium ion formation through C‐4 acyl neighboring group participation. Instead, β‐glycosyl triflates were detected using exchange NMR which could afford α‐galactosides via S N 2‐like displacement. Computational studies of the product‐forming transition state geometries reveal that the C‐4 benzoate group shields the β‐face of the galactosyl donor, thereby disfavoring reactions that proceed via the α‐glycosyl triflate pathway. These findings can explain the stereodirecting effect of C‐4 acyl groups on galactosyl donors, and provides fundamental insights for the development of stereoselective glycosylation methods in the future.

Assessing the prevalence of non-use of cervical cancer screening in Khouribga, Morocco

A Chalcogen Bonding Catalysis Platform for Isoprenoid Cyclization: Broad Scope and Diverse Product Frameworks

ABSTRACT Cyclization of isoprenoids is one of the most important biosynthetic events that yields the largest class of natural products. Yet, a noncovalent catalysis strategy for isoprenoid cyclization remains elusive. Furthermore, a general synthetic method using artificial catalyst that enables isoprenoid cyclization with diverse functional groups remains underdeveloped. Herein, we report a noncovalent catalysis strategy for isoprenoid cyclization, and demonstrate that chalcogen bonding with isoprenoids can catalyze a wide range of cyclization reactions. This chalcogen bonding catalysis platform is highlighted by the broad scope since arene, heteroarene, carboxylic acid, alcohol, phenol, enol, sulfamide, ester, and alkyne can participate in the cyclization events, giving diverse classes of products. Moreover, the product frameworks could be varied, affording different ring sizes including seven‐membered heterocycles and diverse product structures involving fused‐, spiro‐, and bridged‐ring architectures. As a highlight of this catalysis platform, unusual cyclization reactions between prenyl and alkynes that enable the formation of seven‐membered ring and six‐membered allene were achieved by chalcogen bonding catalysis while the conventional gold catalysis approach gave different ring systems.

Synergetic effect of Camellia sinensis waste extract and zinc oxide nanoparticle for improving performance and appearance attributes of viscose fabrics

Abstract Eco-friendly textile dyeing technologies are increasingly popular because of raised environmental consciousness and the need for less polluting substitutes wefor synthetic dyes. Waste of black tea is an appropriate source of polyphenols and tannins with ecological as well as functional benefits, such as microbial resistance, and antioxidant activity. Herein, a new method for eco-friendlier dyeing and finishing of viscose fabric using black tea waste extract (BTWE) as a sustainable natural colorant for dyeing and functional finishing of viscose fabric was examined. The dyeing conditions, like pH, temperature, dye concentration, and time, were systematically regulated to assign the proper conditions for maximum color strength (K/S). The colorfastness of the dyed fabric against washing, perspiration, crocking, and light was determined. Using zinc oxide nanoparticles (ZnO-NPs) improved the performance of the dyed fabrics by making them more resistant to some pathogens. The results revealed that the optimum dyeing conditions were found to be pH 3, 45 °C, 4% dye, for 60 min. Finishing the dyed samples with ZnO-NPs enhanced the K/S and antimicrobial activity without negative impact on the mechanical strength. The dyed viscose fabric exhibited excellent resistance towards Gram-positive ( Staphylococcus aureus ) and Gram-negative ( Escherichia coli ) bacteria as well as the fungus Candida albicans . The antioxidant activity of the dyed samples was greatly improved compared to undyed viscose fabric. However, enhancement of the ultraviolet protection factor of the dyed fabric was limited, likely due to inadequate surface coverage and lack of coating operations. The discrepancy in the chemical and morphological structures between the undyed and the corresponding dyed viscose fabrics was monitored using Fourier transform infrared spectroscopy and scanning electron microscopy, respectively. The correlation between the different dyeing parameters and the color strength as well as the colorimetric data was assigned using analysis of variance (ANOVA). The findings of this investigation justify the potential application of BTWE as a green colorant for one-pot sustainable dyeing and functional finishing of viscose fabrics.

Mechanical Peeling of Anthracene Dimers

ABSTRACT In polymer mechanochemistry, mechanophores are activated by the pulling action of polymer arms. This activation can be achieved from various pulling geometries, the most common being shearing, where tensile stress is distributed across the entire structure, and peeling, which concentrates tension on one scissile bond at a time. The latter usually leads to a better activation and is often associated to pulling points with a cis arrangement in cyclic mechanophores. Here we show that such a cis arrangement is not always conducive of an efficient peeling activation. The investigation of four isomers of butterfly‐shaped anthracene dimers show that only one of the cis isomers undergoes a formal retro‐[4+4] cycloaddition to regenerate the anthracene cores. Combining with experimental and theoretical studies, we have revealed the reaction pathway and shown that the asymmetric force transmission is crucial for the mechanochemical activation. Furthermore, altering the rigidity of the anchoring handle from a flexible alkyl chain to a rigid phenyl handle accelerates the reaction by sevenfold. Our findings establish new structural and geometric design principles for mechanochemical transformations.

Polydopamine-doped PEDOT interfaces improve cell-electrode interactions and neural signal transmission

Isolable Monocyclic <i>N</i> ‐Heterocyclic Radicals Supported by Rare‐Earth Organometallics

ABSTRACT Monocyclic N ‐heterocyclic radicals are the elementary reactive intermediates in synthetic chemistry and biochemical processes, but their isolation remains a central challenge due to extremely high reactivity. Here we report the first structurally characterized example of monocyclic pyridine radical supported by metal ions, [K(crypt‐222)][Cp* 2 RE(PyS 2‐• )] ( 2‐RE , PyS 2‐• = radical anion of pyridine‐2‐thiolate), and the first stable monocyclic triazine radical for any species, [K(crypt‐222)][(Cp* 2 RE) 3 (TrizS 4‐• )] ( 4‐RE , TrizS 4‐• = radical anion of 1,3,5‐triazine‐2,4,6‐tris(thiolate)), based on rare earth thiolate systems. Detailed structural, computational, UV–vis, and EPR data support the presence of heterocyclic radicals, which show a complicated, uneven spin density distribution at both pyridine and triazine rings. Remarkably, the unusual bonding characters between the lanthanide centers and the SOMO π*‐orbital of the radical promote strong ferromagnetic coupling from radical to lanthanide ions and achieve the largest gadolinium‐radical ferromagnetic coupling observed to date, J Gd–rad = +28.55(57) cm −1 ( Ĥ = ‐2 J Gd‐Rad Ŝ Gd · Ŝ Rad ) in 2‐Gd , while compound 4‐Dy exhibits slow magnetic relaxation. Furthermore, the initial exploration on reactivity revealed the potential ability of the pyridine radical to activate inert bonds. Those results contribute to a better understanding of highly reactive species involving monocyclic heterocyclic radicals.

Soil classification in the Sudan Savanna using sentinel products and topographic information with machine learning models

Abstract Accurate soil information is crucial for sustainable agricultural planning and land management, particularly in data-scarce regions, such as the Sudan Savanna, the largest sorghum-producing area in Africa. A recent study reported that soils in this region corresponded well with the topography, having formed primarily through erosion–deposition processes, resulting in systematic variation in soil types along the landscape. Therefore, this study compared the performances of three machine learning models, i.e., Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM), for soil classification based on multisource remote sensing and topographic data. Ground-truth data with four different soil types, Lixisols, Petric Plinthosols, Pisoplinthic Petric Plinthosols, and Gleysols, were used to train and validate the models using 19 remote sensing-derived covariates including Sentinel-1 SAR, Sentinel-2 bands, spectral indices, and Topographic Wetness Index. Machine learning classification was analyzed under different scenarios of remote sensing feature combination. Results showed that the XGBoost with the selected feature combination achieved the highest performance with an overall accuracy of 78.9%, followed by RF (72.3%) and SVM (65.2%). Among the selected features, topographic parameters appeared the most important and provided complementary information for accurate soil classification. This study demonstrates the effectiveness of integrating optical, radar, and topographic information for soil mapping and provides a valuable management tool to support agricultural and environmental strategies in the Sudan Savanna.

Residue‐Specific Signatures of Structural Water Identified by Dissolution Dynamic Nuclear Polarization with UV‐Generated Radicals

ABSTRACT Conserved structural water molecules stabilize protein folds and modulate their function, yet remain difficult to observe in solution because exchange‐based readouts favor solvent‐exposed sites. Here, we introduce a protocol to detect structural water molecules under native conditions, using long‐lived hyperpolarized water (HyperW) enabled by UV‐induced, nonpersistent radicals. In the model protein chymotrypsin inhibitor 2, HyperW‐enhanced two‐dimensional NMR correlation spectra across pD 5.5–8.4 reveal strong exchange‐driven enhancements at solvent‐exposed residues. By contrast, a distinct group of four residues shows hyperpolarized amide signals, which disappear when through‐space polarization transfer via nuclear Overhauser effect (NOE) is suppressed using a CLEANEX‐PM experiment. The CLEANEX‐negative/HyperW‐positive signature, together with the spatial proximity of these residues to crystallographically conserved water molecules, supports NOE‐mediated transfer from long‐residence internal water, not distinguishable by standard NMR methods. The combined observables establish HyperW NMR as a residue‐specific reporter of structural hydration and hydration‐coupled dynamics under native conditions, providing a route to link conserved water observed in crystals to their roles in solution.

Graph attention network-based multimodal approach for lung diseases classification