Environmental sampling of fungal spores is critical for assessing exposure risks, but current methods often miss low-abundance or spatially dispersed spores, highlighting the need for more sensitive sampling methods. This study explores the use of plasma polymerization to chemically modify air filters for enhanced fungal spore capture. Polyethylene terephthalate (PET) filters are coated with nanothin films from four monomers -acrylic acid, 2-methyl-2-oxazoline (POX), 1,7-octadiene, and perfluorooctane (PFO)- and characterized using ellipsometry, X-ray photoelectron spectroscopy, and contact angle measurements to evaluate film thickness, chemistry, and wettability. A custom aerosolization chamber was used to test the capture efficiency of plasma-modified filters for airborne spores from four species: Aspergillus niger, Cladosporium sp., Penicillium roqueforti, and Rhodotorula glutinis. Quantitative analysis using hemocytometry and dry biomass measurement reveals species-specific adhesion patterns that are predominantly driven by surface chemistry. Hydrophobic PFO-coated filters achieved the highest capture of filamentous fungi, while hydrophilic POX coatings best captured the tested yeast. Coating thickness had no significant effect, highlighting the primacy of surface chemistry over film depth. These findings establish plasma polymerization as an effective strategy to tailor filter surfaces for selective fungal spore capture, providing a proof-of-concept for functionalized air filters that support improved bioaerosol monitoring in built environments.
The separation of xenon (Xe) and krypton (Kr), being an energy-intensive process, has attracted considerable research interest in developing alternative separation methods and materials over the past two decades. Considerable progress has been achieved in discovering sorbent materials with high Xe/Kr selectivity. Due to their tunable pore geometries and interaction strengths, metal-organic frameworks (MOFs) have gained consensus as promising alternatives. For this goal, computational screening methods have been widely adopted to accelerate the discovery of high-performing candidates. However, the computational cost of brute-force screening involving adsorption simulations for millions of structures is prohibitive. Therefore, a practical approach is to partition large-scale screening into manageable subsets focusing on materials with shared chemical features. To conserve computational resources, applying reasonable filters on pore-related geometric features demonstrating significant variation is advisable. Based on these considations, we present a ligand-focused screening strategy employing preliminary geometric filters, including a pore-limiting diameter (PLD) ranging from 3.3 to 8.2 Å and a largest cavity diameter (LCD)/PLD ratio between 1 and 2, together with the restriction to single-ligand-assembled MOFs to facilitate structure-property interpretation. The procedure is exemplified using the ligand 1,1,2,2-tetra(4-carboxyphenyl)ethylene (H4TCPE), and experimentally validated the in silico workflow through laboratory synthesis and adsorption measurements. The optimal cerium-based framework exhibits a 143% improvement in the adsorbent performance indicator (API), which comprehensively considers selectivity, uptake, and enthalpy, compared to the prior Ca-based analog. Rather than targeting high-throughput discovery, this study demonstrates an efficient and chemically interpretable screening approach for a structurally coherent MOF subfamily. The resulting materials are further contextualized against representative benchmark adsorbents, highlighting their competitive performance and application-relevant advantages.
Continuous monitoring of vital signs after hospital discharge may support early recognition of deviating vital signs. However, the utility may be challenged by high alert frequencies. This exploratory study aimed to assess the impact of evidence-based augmented filtering algorithms on alert frequency following discharge. Adult patients (≥ 18 years) discharged after acute medical admission were monitored continuously using wearable devices that measured heart rate, respiratory rate, blood pressure, and oxygen saturation. The primary outcome was the number of alerts per patient per day. We compared outcomes across three filtering strategies: (1) no filtering, (2) artefact removal, and (3) filtering with artefact removal and clinical criteria based upon severity and duration. Ninety-eight patients were enrolled; the total vital sign alert frequency was reduced from a median of 74 [IQR 36-125] to 5 [IQR 1-13] alerts/patient/day following application of the clinical criteria filters, corresponding to an 84% reduction (p < 0.001). Alert frequency following the three filtering approaches was 74 [IQR 36-125], 67 [IQR 33-103], and 5 [IQR 1-13] alerts/patient/day, respectively, p < 0.001. Artefact removal and the application of filters based on severity and event duration significantly reduced alert frequency in patients continuously monitored at home after hospital discharge. Further studies are needed to evaluate clinical safety and predictive value.
Patient-specific ridge filters (PSRFs) can enable conformal single-energy proton FLASH delivery without energy switching. However, converting optimized spot-based dose distributions into physically adjacent ridge-filter structures may introduce inter-beamlet modulation errors not captured by conventional isolated-spot optimization. This study characterized ridge-filter (RF) crosstalk, evaluated its dependence on the beam-width-to-pitch relationship, and developed an iterative mitigation strategy. A Monte Carlo dose influence matrix was generated for monoenergetic proton beamlets passing through RFs of varying thickness. A baseline spot-weighted IMPT plan was optimized to meet dose constraints and converted into PSRF geometries. PSRF dose distributions were calculated by explicitly modeling the PSRF in the scanned beam path. RF crosstalk was quantified by comparing PSRF and baseline IMPT plans. Lateral beamlet spacings of 8, 10, 12, and 15 mm were evaluated using gamma analysis, DVH metrics, and mean relative dose difference. An iterative re-optimization method was tested in water-phantom and patient CT geometries. RF crosstalk produced hot and cold spots, reducing agreement between PSRF and baseline IMPT plans. For the same spot size and target geometry, crosstalk increased as beamlet spacing decreased. Iterative re-optimization substantially reduced dose discrepancies, lowering the mean relative dose difference in the target from 8.9% to 3.4% in water and from 3.7% to 1.8% in CT. RF crosstalk is an important source of dose inconsistency in ridge-filter-based conformal proton FLASH planning. Its dependence on the beam-width-to-pitch relationship and mitigation through iterative re-optimization provide a practical framework for improving the accuracy and robustness of patient-specific single-energy proton FLASH delivery.
Mucin-domain glycoproteins are densely O-glycosylated proteins that comprise a major component of the glycocalyx and play central roles in immune regulation, host-pathogen interactions, cancer biology, and cell-cell communication. Despite their biological importance, the structural and functional characterization of mucin-type O-glycosylation remains analytically challenging due to extensive microheterogeneity, resistance to conventional proteases, and the combinatorial complexity of glycoforms. This chapter outlines practical, mass spectrometry-compatible enrichment and analysis strategies designed to overcome these barriers and enable robust O-glycoproteomic investigations. Two complementary enrichment approaches are described. The first leverages an inactive point mutant of the mucinase StcE (StcEE447D) conjugated to a solid support to selectively isolate mucin-domain glycoproteins from complex biological samples, functioning as a targeted mucinome probe. The second, termed GlycoFASP, employs molecular weight cut-off filters in combination with O-glycoproteases or mucinases to enrich O-glycopeptides more broadly, making it well suited for biofluids and diverse O-glycoproteomes. Both workflows are coupled to enzymatic digestion strategies that rely on glycoproteases with dual recognition motifs dependent on peptide sequence and glycosylation status, followed by desalting and LC-MS analysis with electron-based fragmentation to enable site-specific glycan localization. Detailed protocols, rationale, optimization strategies, and troubleshooting guidance are provided to facilitate implementation across a range of sample types. Together, these approaches offer accessible and adaptable solutions for mapping mucin-domain O-glycoproteins with molecular precision, advancing the study of glycoprotein structure and function in health and disease.
Trillions of cigarette butts are discarded annually worldwide, releasing over 7000 toxic chemicals and becoming one of the most prevalent solid wastes in society. Cigarette filters are composed primarily of cellulose acetate fibers, a nonbiodegradable material that poses significant environmental challenges. This systematic review surveyed the ScienceDirect, Web of Science, and Scopus databases to evaluate recent research on the incorporation of cigarette butt fibers into building materials such as mortar, concrete, gypsum composites, asphalt, and bricks. Few studies were found in these areas, and their results were analyzed and compared, allowing for the identification of gaps in the literature. It was observed that, in small proportions, the incorporation of cigarette butts can reduce density, improve thermal insulation, and decrease energy consumption. On the other hand, higher levels compromise mechanical strength and durability, and there is still a lack of fundamental tests that limit the practical application of these materials.
Soil microbiomes are critical for ecosystem functioning, yet the global influences of climate and agricultural practices on their diversity and structure remain incompletely characterized. Here we analyzed 1921 soil samples from 33 countries worldwide across diverse biomes to assess how climate gradients and agricultural inputs, including pesticides and fertilizers, shape prokaryotic and fungal communities. We found that microbial diversity peaks at intermediate temperatures and differs markedly between natural and agricultural soils, with agriculture increasing microbial diversity while altering community composition and ecological guilds. Pesticide use selectively reduced bacterial diversity and shifted fungal guilds, decreasing ectomycorrhizal fungi while increasing saprotrophs, whereas fertilization reduced microbial network cohesion, with organic and inorganic fertilizers eliciting distinct community responses. These findings reveal that climatic factors and agricultural management jointly influence soil microbial diversity, community structure, and network connectivity, with implications for soil health and ecosystem resilience in managed landscapes. Overall, our results demonstrate that agricultural practices, including the use of pesticides and both organic and inorganic fertilizers, act as strong ecological filters that reshape soil microbiomes worldwide-enhancing apparent diversity but driving a functional shift toward less mutualistic, more fragmented, and potentially less resilient communities.
Septic shock with acute kidney injury is associated with high mortality. Hemoadsorption methods such as CytoSorb in conjunction with standard continuous renal replacement therapy (CRRT) and oXiris-based CRRT are increasingly used; however, comparative data are scarce. This study assessed the effects of both filters on vasopressor-free days and key clinical outcomes in septic shock. This retrospective single-center cohort included adults with septic shock treated with CytoSorb in conjunction with CRRT or oXiris-based CRRT between 1st January 2023 and 31st December 2024. The primary endpoint was vasopressor-free days to day 28, with secondary outcomes including Sequential Organ Failure Assessment (SOFA) score, lactate levels, norepinephrine equivalent dose (NEED), mean arterial pressure, ventilator-free days, intensive care unit (ICU) length of stay, and mortality. A total of 97 patients were included in the analysis. (CytoSorb: n=75; oXiris: n=22). Both extracorporeal blood purification modalities were associated with comparable reductions in lactate levels (median [IQR]: -39.7% [-47.2% to -19.3%] vs. 44.5% [-54.0% to -33.3%], respectively, P=0.14), and NEED (median [IQR]: -36.1% [-66.7% to -9.1%] vs. -56.4% [-83.3% to -12.5%], respectively, P=0.36), along with similar increases in mean arterial pressure (9.6% [7.7%-18.2%] vs. 9.8% [7.7%-16.7%], respectively, P=0.94). No significant differences were found between the two modalities. Vasopressor-free days were similar (median [IQR]: 0 [0-24.0] days with CytoSorb vs. 20.5 [0-25.0] days with oXiris, P=0.55). In the multivariable competing-risks analysis, extracorporeal blood purification modality was not independently associated with vasopressor-free days after adjustment for potential confounders (subhazard ratio =0.97, 95% confidence interval: 0.48 to 1.94, P=0.93). Ventilator-free days, ICU stay, and ICU and hospital mortality were likewise comparable. CytoSorb in addition with CRRT and oXiris-based CRRT demonstrated similar hemodynamic and clinical outcomes. Larger prospective studies are needed to define the optimal role of extracorporeal CRRT-based blood purification in septic shock.
The vaccine and viral vector industry is growing at an accelerated rate. To improve harvest and purification processes, the development of continuous membrane-based operations, such as normal flow filtration (NFF) and single pass tangential flow filtration (SPTFF) for concentration were explored. This work was conducted using two model viruses, non-enveloped porcine parvovirus (PPV) and enveloped Suid herpesvirus (SuHV). The viruses are in the same family as the gene therapy vectors adeno associated virus and herpes simplex virus, respectively. SPTFF design started with batch TFF for membrane selection. Hollow fiber membranes with a 100 and 300 kDa molecular weight cut off were defined for PPV and SuHV SPTFF operations, respectively. The SPTFF runs for PPV did not provide any concentration of the virus and low protein and DNA removal, unlike batch TFF. Two hollow fiber membranes run at 10 mL/min and 2 psi were the best condition for SuHV concentration, with approximately 100-fold titer concentration and protein and DNA removal of 37% ± 5% and 32% ± 8%, respectively. This concentration was superior to the batch TFF and indicated a strong dependence on flow rate and transmembrane pressure. For NFF, filters selection and performance tests were carried out for NFF of PPV and SuHV, as well as cleaning protocols for hollow fiber membranes. The ultimate goal is to integrate this work into the continuous purification of viral vectors produced in mammalian cell cultures to reduce costs and increase throughput.
In gas chromatography (GC) analysis, the gas flow control performance of the Electronic Pressure Control (EPC) system that is responsible for signal analysis and processing, critically determines the reliability and accuracy of analytical results. However, during the gas flow control, unknown hysteresis characteristics, voltage saturation, and state constraints significantly impact control performance. This study addresses the fuzzy adaptive practically finite-time output feedback and signal processing problem for the EPC system in GC, incorporating system state constraints and unknown hysteresis characteristics. First, a modified Prandtl-Ishlinskii model is employed to accurately describe the valve's unknown asymmetric hysteresis. A dynamic model reflecting the actual system, incorporating gas resistance characteristics, is then established. Second, a fuzzy state observer based on a fuzzy logic system (FLS) is designed to estimate unmeasurable system states. Third, considering state constraints and potential computational complexity, a fuzzy adaptive practically finite-time controller is proposed. This controller, built upon the observer, integrates backstepping, dynamic surface control (DSC), and barrier Lyapunov functions (BLF), utilizing filters for smooth processing of virtual signals. System stability is then proven via Lyapunov theory. Finally, experimental verification is performed using both step and dynamic gas flow targets with a newly constructed EPC system. The results demonstrate that the proposed controller achieves precise and stable tracking control of gas flow, even in the presence of unknown hysteresis, state constraints, and voltage saturation.
To investigate the current status of knowledge, attitudes and practices(KAP) related to drinking water and health among adult residents in China. From March to April 2022, an online questionnaire survey was conducted using geographical stratified combined with convenience sampling, covering 234 prefecture-level cities across 31 provinces in China. A total of 11 558 questionnaires were collected, and 9956 valid questionnaires were finally included. The questionnaire consisted of demographic characteristics, knowledge on drinking water and health, attitudes toward safe drinking water, and drinking water-related behaviors. The χ~2 test was used to compare differences among groups by gender, age, BMI, household income and smoking status. The participants were predominantly female(n=5952, 59.9%) and relatively young(18-34 years old, n=4470, 44.9%). Most were non-smokers(n=8353, 83.9%), and the largest household income group was 50 000-100 000 yuan(n=3306, 33.1%). The awareness rate of the health hazards of inadequate water intake was high(n=8795, 88.3%), while awareness of what constitutes healthy drinking water was low(n=5536, 55.6%). Differences in knowledge awareness by gender, age, smoking status and household income were all statistically significant(χ~2=14.30-183.54, P<0.01). A total of 95.0%(n=9458) of respondents agreed that drinking water is closely related to health, with a higher proportion among females(P<0.01). Only 29.2%(n=2897) regarded drinking water as"very safe", with higher rates in males and smokers(P<0.01). No significant difference in safety perception was found across age groups(P=0.28). Regarding behaviors, 65.2%(n=6494) of participants endorsed regular water drinking, and the proportion increased with age.57.8%(n=5759) of participants used filtered water purification devices, with higher usage among females, non-smokers and normal-weight individuals. Differences in drinking water behaviors by gender and age were both statistically significant(P<0.01). Chinese adult residents possess a general awareness of the link between drinking water and health. However, deficiencies exist in specific knowledge, perception of safety, and the practice of healthy behaviors, with significant differences observed across various demographic groups.
Direct saline water electrolysis technology can generate reactive chlorine species to achieve environmental remediation and disinfection. However, the high-concentration chloride ions in the electrolyte tend to cause corrosion to the catalytic system, leading to the attenuation of catalyst activity and the decline of stability. Herein, the filtered cathodic vacuum arc (FCVA) co-deposition technology was adopted to successfully construct a MnFeCoNiCu high-entropy catalytic current collector (MFCNC). Relying on the synergistic effect among elements, this high-entropy structure exhibits excellent salt tolerance and is compatible with the reactive chlorine electrolysis systems. It enables the electrochemical synthesis of reactive chlorine while realizing hydrogen production. Long-term stability tests show that the catalytic current collector can operate stably for more than 100 h during the electrolysis process. Moreover, it can significantly reduce the overpotential of the catalytic reaction, optimize the reaction process from a kinetic perspective, and effectively lower the energy consumption of the system. Additionally, the MFCNC has dual application values of pollutant removal and disinfection in practical water treatment scenarios. This work provides a new solution to realize direct saline water electrolysis technology, promoting the development of this technology toward efficient, stable, and low-energy-consumption practical applications.
Degradation in drylands is widespread, yet our ability to restore dryland native plant communities is nearly nonexistent. Recruitment from seed is often <10%, due to many factors including harsh conditions that lead to seed dormancy and seedling mortality and high levels of competition with invasive species. Degradation exacerbates these challenges by decreasing topography, water-holding capacity in soil, and perennial vegetation which can act as microsites for seed regeneration. In this experiment, we tested soil pits, biochar soil amendments, and seed pellets as three strategies to create seed microsites and ameliorate harsh conditions in a degraded landscape. We measured seedling density and biomass of both native and non-native species after one growing season. We also assessed impacts of the treatments on soil microbial communities. Seeding alone, with or without a seed pellet, did not result in seedlings in the absence of other treatments. Microsite creation increased native plant density by about 10-fold, and biomass by about 100-fold, compared to controls. Native plant biomass was even higher-about 300-fold greater than controls-with the addition of biochar to the microsites. Non-native seedling density and biomass was also highest, by about 10-fold and 6-10-fold, in pits and pits with biochar, respectively. Soil moisture was significantly higher in microsites, likely driving these native and non-native vegetation trends. There was no effect of seed pellets on plant density or biomass, and in most cases, pellets performed slightly worse than broadcast bare seeds. Bacterial communities in reference soils did not differ from those in degraded areas, but there were differences in response to the microsite treatments. Our results support our hypothesis that microsite limitation, coupled with seed limitation, poses a barrier to seeded restoration in highly degraded semiarid grasslands. Addressing this barrier could improve stubbornly low plant recruitment rates in dryland restoration, making projects more effective.
Taiwan currently operates 20 SRF-utilizing facilities consuming about 1.867 million tons of SRF/RDF annually. Due to the heterogeneous composition of SRF and the limited adaptation of conventional combustion systems, high co-firing ratios may result in unstable combustion and elevated emissions of hazardous air pollutants. The PCDD/F concentrations in flue gas were highest at Plastic-HT (0.072 ± 0.008 ng I-TEQ/m3), followed by Plastic-LT, likely due to lower combustion temperature and incomplete combustion. Pulp-HT exhibited lower PCDD/F levels due to simpler fuel composition and more effective control by catalytic filter bags. In contrast, the highest PAHs (191 ± 26.6 ng BaPeq/m3) emission was measured at Pulp-HT, attributed to the highest coal and organic-rich fuel. Ambient PM2.5 and toxic equivalents of PCDD/Fs, PCBs, PCNs, PAHs, and WSIs generally showed higher concentrations in winter. High-chlorinated PCDD/Fs dominated, indicating industrial combustion sources, while PAHs were mainly high-molecular-weight species from pyrolysis and traffic emissions. WSIs were primarily secondary inorganic aerosols (>50%). Compared to urban areas, higher levels of PCDD/Fs, PCBs, and PCNs were observed in SRF vicinity and industrial areas, while PAHs were highest in SRF vicinity. The PMF results for ambient air near SRF facilities indicate that the major sources of PCDD/Fs are coal-fired boilers (25%) and SRF plants (26%). PCBs are primarily associated with waste incineration (82%), while PCNs are mainly derived from municipal waste incinerators (74%). In contrast, the dominant sources of PAHs are coal-fired power plants (35%) and sintering processes (38%). The total exposure risk of POPs were around 1.67- 4.86 × 10-6, with PCDD/Fs being the dominant contributors. In comparison, the exposure risk of PAHs ranged from 4.31 × 10-8 to 5.90 × 10-7, remaining below one in a million.
Teleconsultations are exposed to digital impersonation and synthetic media attacks that can alter identity, articulation, or consent evidence, introducing emerging AI-enabled biosecurity risks to digitally mediated healthcare workflows. We evaluate an explainable integrity control based on motion dynamics and audiovisual temporal coherence, designed for conservative operation at extremely low false alarm rates with auditable evidence reporting to support governance and risk-based escalation. Our contribution is a reproducibility-oriented evaluation protocol and an evidence atlas of temporally grounded cues, together with a staged fusion that supports scalable prescreening and targeted verification under platform-style degradations characteristic of real-world dissemination chains. Building on prior biomarker-oriented analyses of physiological and structural cues for synthetic media detection, this work advances toward a calibrated, deployment-oriented integrity control architecture optimized for operational screening in telemedicine workflows. We use the DeepFake RealWorld (DFRW) dataset with 46,371 clips (229.28 h), combining 4,186 Open-Source Intelligence (OSINT) samples and 42,185 controlled, systematically degraded variants emulating recompression, resizing, filtering, and recapture. On the held-out binary-labeled test split, descriptor fusion reaches an AUC of 0.91 and achieves a true positive rate (TPR) of 18.5% (95% CI 16.2-20.8) at a false positive rate (FPR) of 0.1%, compared with 6.2% (95% CI 4.8-7.6) for an Xception baseline fine-tuned on the DFRW dataset. Microbenchmarked latencies motivate a two-stage deployment with explicit abstention and a structured integrity report aligned with healthcare governance and post-incident auditing requirements. This study evaluates telemedicine-oriented integrity controls using a benchmark dataset and does not claim demographic or clinical subgroup generalizability. Before deployment in clinical workflows, the proposed approach requires broader validation across age groups, ethnic backgrounds, speech characteristics, capture conditions, and medical conditions that may affect facial motion, articulation, or voice production. Prospective subgroup validation and governance-oriented assessment should therefore be treated as necessary directions for future work.
Early-life exposure to fine particulate matter (PM₂.₅) is increasingly implicated in the developmental origins of chronic respiratory diseases; however, the underlying molecular mechanisms remain poorly defined. This study employed Weighted Gene Co-expression Network Analysis (WGCNA) to investigate transcriptomic alterations associated with intrauterine and early neonatal PM₂.₅ exposure in the developing murine lung. Microarray data (GSE104656) spanning embryonic (E14.5, E18.5) and postnatal (P40) stages were processed using robust normalization and variance filtering to construct a scale-free co-expression network. Principal component analysis revealed that developmental maturation was the primary driver of global transcriptional variation, with no distinct separation attributable to PM₂.₅ exposure. WGCNA identified biologically relevant gene modules involved in immune and metabolic processes as well as cell cycle regulation, that exhibited strong correlations with developmental progression. Functional enrichment analysis confirmed significant involvement in immune activation, leukocyte adhesion, DNA replication, and chromosomal organisation. Although differential expression analysis under stringent thresholds did not detect significant PM₂.₅-responsive genes, integrative network analysis identified eleven exposure-associated genes embedded within key modules. These genes, including Vnn1, Gprc6a, Mfap1a, Rgs16, and Fpr1, represent highly connected hub nodes implicated in oxidative stress regulation, extracellular matrix remodelling, metabolic signalling, and immune modulation. It was concluded that early-life PM₂.₅ exposure did not globally disrupt lung transcriptomic architecture but selectively perturbs critical hub genes within developmental networks. This targeted sub-network vulnerability provided a mechanistic basis for the developmental programming of COPD susceptibility, linking early environmental insults to long-term respiratory dysfunction.
Early and accurate diagnosis of Alzheimer's disease (AD) is critical. In MRI-based computer-aided diagnosis, convolutional neural networks (CNNs) excel at extracting local features but struggle to model long-range dependencies, while Vision Transformers (ViTs) offer strong global modeling capabilities but suffer from high computational complexity, limiting their deployment in resource-constrained settings. This paper proposes HDFT-MViT, a lightweight hybrid architecture based on MobileViT that integrates a hierarchical dynamic filter with a lightweight Transformer. The model adopts a progressive Core-Enhanced Mix design: Shallow layers employ MobileNetV2 inverted residual blocks for efficient local feature extraction; intermediate and deep layers incorporate a dual-branch module that integrates a dynamic filter for frequency-domain global modulation and a lightweight Transformer for spatial long-range dependency modeling, followed by hierarchical fusion via learnable weights. A channel attention mechanism is further introduced to enhance feature discriminability. Evaluations on the public ADNI-1 (3-class) and ADNI-2 (4-class) MRI datasets show that HDFT-MViT achieves state-of-the-art classification accuracies of 98.85 ± 0.27% and 98.07 ± 0.54%, respectively, while maintaining a lightweight profile with only 3.46 M parameters, confirming its effectiveness and efficiency. HDFT-MViT achieves an optimal balance between local detail perception and global semantic understanding within a computationally efficient framework, offering a promising tool for clinical AD diagnosis. Code will be released upon acceptance.
Most contemporary cognitive training programs incorporate gamified elements, yet the cognitive mechanisms through which gamification influences training and transfer remain poorly understood. Although gamification may enhance engagement, it can also introduce salient, task-irrelevant features that increase demands on executive control, particularly inhibitory control (IC). We therefore tested whether baseline IC moderates transfer following working memory training, hypothesizing that lower IC would constrain transfer by impairing the filtering of irrelevant information during training. We first examined this hypothesis in a secondary analysis of a published working memory training dataset in younger adults. We then tested its robustness in older adulthood in a preregistered, double-blind randomized crossover trial in which healthy older adults completed 40 sessions of N-back training in game and nongame conditions. The results of the latter showed that baseline IC significantly moderated transfer to Untrained N-back and Complex Span outcomes, whereas general cognitive ability did not. These findings identify IC as a key individual-difference factor in cognitive plasticity and suggest that baseline profiling may help tailor interventions for populations at risk of age-related cognitive decline.
Acid phosphatase (ACP) functions as a critical biomarker for prostate cancer. However, the prevalent use of single-mode readout in ACP detection makes these methods vulnerable to environmental and instrumental interferences, ultimately compromising both accuracy and reproducibility. Carbon dots (CDs) have emerged as promising nanomaterials for biosensing owing to their favorable biocompatibility, low cytotoxicity, and tunable optical properties. Nevertheless, most reported CDs exhibit blue-green emission, which suffers from significant background interference from endogenous fluorophores that compromises detection reliability. Thus, developing a robust multi-mode sensing platform based on hydrophilic red-emitting CDs capable of providing cross-validated signals holds substantial value for ACP quantification. In this work, a fluorescence/colorimetric dual-mode sensing platform was constructed for ACP detection by integrating red-emitting neutral red CDs (NR-CDs) with CeO2 nanosheets exhibiting oxidase-mimicking activity. The detection principle relied on the CeO2-catalyzed oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to generate blue-colored oxidized TMB (oxTMB), which showed a characteristic absorption peak at 652 nm and simultaneously quenched the fluorescence of NR-CDs via the inner filter effect (IFE). Upon addition of ACP, sodium ascorbyl phosphate could be hydrolyzed to ascorbic acid (AA), which inhibited the formation of oxTMB, leading to a decrease in absorbance at 652 nm and a concomitant recovery of NR-CDs fluorescence. Based on this signal-switching mechanism, dual-mode quantification of ACP activity was achieved with detection limits of 0.0026 U/L (fluorescence) and 0.0038 U/L (colorimetry). Moreover, by coupling agarose hydrogel with smartphone-based RGB analysis, a portable visual detection system was developed for on-site ACP assessment. The method was successfully employed for the detection of ACP in human serum with high accuracy and was further extended to the screening of ACP inhibitors using sodium orthovanadate as a model compound. This study presents the initial integration of multi-mode optical and visual sensing platform for ACP activity analysis, demonstrating the practical potential of the proposed platform in point-of-care testing and biomedical research.
Soil fungi, as key players in maintaining ecological functioning and stability, have been widely studied in alpine ecosystems. However, prior studies focused mainly on their spatial patterns and temporal dynamics, as well as their driving factors. In-depth research on community assembly mechanisms, particularly how biotic interactions influence this, is lacking. In this study, we collected root samples of an ectomycorrhizal plant, Bistorta macrophylla, and bulk soil around them, along a 4300-4750 m gradient in alpine meadows of Baima Snow Mountain, northwestern Yunnan, China, and obtained ITS2 sequences using high-throughput sequencing, which were subjected to bioinformatic processing and statistical analyses, including differential abundance analyses, inference of community assembly mechanisms and interpretation of co-occurrence networks. Our results reveal that fungal community assembly in soil is influenced more by stochastic processes with the increase of elevation, but homogeneous selection consistently acts as the predominant process in shaping root-associated communities. This helps keep a stable core mycobiota dominated by Cenococcum and Phialocephala, both being melanized fungi, in the root systems of B. macrophylla. Nevertheless, members of the order Helotiales and certain EcM genera consistently act as key nodes in fungal co-occurring networks in both soil and root samples. Further, we find that the elevational change trend of positive correlations between ectomycorrhizal and saprotrophic fungi matches with the theoretical expectation by the stress gradient hypothesis. Our results emphasize the pivotal role of compartment filtering by plant roots in selecting symbiotic partners and shaping fungal correlation networks, and highlight that the stress gradient hypothesis could be applicable in harsh alpine environments.