Dust event identification and characterization with one-year online observations in Beijing.

Dust storms have a profound impact on air quality, atmospheric chemistry, and human well-being by carrying vast amounts of particles over distances of thousands of kilometers. However, the overall characteristics of these dust events and their influence on secondary pollution in the northern China region are not yet well understood, due to a lack of long-term, comprehensive observations and objective identification techniques. Based on principal component analysis combined with high-time-resolution observations of particulate matter components, here we developed a robust method to identify dust storm events and identified 14 dust events in Beijing in 2019. We further classified these 14 events into two distinct types using Lagrangian particle dispersion models and backward trajectory analysis. The first type (Type I, 9 cases) is characterized by synoptic patterns in Mongolia, originating from the north and directly impacting the Beijing area. The second type (Type II, 5 cases) involves air masses from the north or northwest that temporarily pass through polluted regions south of Beijing before being carried back into the city. Consistently, during Type I dust events, we observed a sharp decrease in secondary inorganic aerosols (SIA) from 65 % to 7 %, as well as in the sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) (from 0.52 to 0.19, and 0.27 to 0.018 respectively). In contrast, during Type II dust events, SIA concentrations increased by 91 %, along with an increase in SOR (1.7 %), NOR (69 %), and f44/f43 (3.0 %), suggesting an enhancement of secondary aerosol formation resulting from the interaction between dust aerosols and gaseous anthropogenic pollutants. Our results demonstrate that dust events and the sub-type of dust events can be identified in an objective manner using the protocol developed in this study and the dynamics should be considered when discussing impacts of dust events on atmospheric chemistry.

Dopamine-integrated all-hydrogel multi-electrode arrays for neural activity recording.

Investigation of brain neural circuits is essential for deciphering the diagnostics and therapeutics of neurodegenerative diseases. The main concerns with traditional rigid metal electrodes include intrinsic mechanical mismatch between sensing electrodes and tissues, unavoidable foreign body responses, and inadequate spatiotemporal resolution, resulting in a deficiency of sensing performance. All-hydrogel neural electrodes with multi-electrode arrays (MEAs) suggest a viable way to modulate the trade-off between tissue-mechanical compliance and excellent spatiotemporal recording capacity, but still face the issues of insufficient conductivity and unstable interlayer bonding. Herein, we constructed a four-layer all-hydrogel neural electrode, by sandwiching a conductive hydrogel layer within two encapsulation hydrogel layers, with a shielding hydrogel layer located on top. We introduce a dual-strategy treatment to induce controllable phase separation in poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) hydrogel, which achieved ultra-high conductivity (up to 4176 S cm-1) comparable to that of metals and precise spatial resolution (∼15 µm) suitable for single neuron recording. In addition, the utilization of polyphenol chemistry mediated adaptive adhesion endowed this neural electrode with flexible and stable interlayer bonding among conductive-encapsulation-shielding layers and the tissue-electrode interface. Consequently, the all-hydrogel neural electrode exhibited a tenfold higher signal-to-noise ratio than a commercial silver electrode, realized the recording of weak neural activity signals within single and multiple neurons in epileptic rats, and applied man-made stimulation to the cerebral cortex of rats during seizures. This work provides a useful tool to understand the development, function and treatment of neurodegenerative diseases.

Stereo-selectivity of enantiomeric inhibitors to ubiquitin-specific protease 7 (USP7) dissected by molecular docking, molecular dynamics simulations, and binding free energy calculations.

The ubiquitin-specific protease 7 (USP7), as a member of deubiquitination enzymes, represents an attractive therapeutic target for various cancers, including prostate cancer and liver cancer. The change of the inhibitor stereocenter from the S to R stereochemistry (S-ALM → R-ALM34) markedly improved USP7 inhibitory activity. However, the molecular mechanism for the stereo-selectivity of enantiomeric inhibitors to USP7 is still unclear. In this work, molecular docking, molecular dynamics (MD) simulations, molecular mechanics/Generalized-Born surface area (MM/GBSA) calculations, and free energy landscapes were performed to address this mystery. MD simulations revealed that S-ALM34 showed a high degree of conformational flexibility compared to the R-ALM34 counterpart, and S-ALM34 binding led to the enhanced intradomain motions of USP7, especially the BL1 and BL2 loops and the two helices α4 and α5. MM/GBSA calculations showed that the binding strength of R-ALM34 to USP7 was stronger than that of S-ALM34 by - 4.99 kcal/mol, a similar trend observed by experimental data. MM/GBSA free energy decomposition was further performed to differentiate the ligand-residue spectrum. These analyses not only identified the hotspot residues interacting with R-ALM34, but also revealed that the hydrophobic interactions from F409, K420, H456, and Y514 play the major determinants in the binding of R-ALM34 to USP7. This result is anticipated to shed light on energetic basis and conformational dynamics information to aid in the design of more potent and selective inhibitors targeting USP7.

Association of plasma VEGF with futile recanalization and intracranial angiogenesis in ischemic stroke post-endovascular treatment.

OBJECTIVE: This study aimed to compare baseline and subsequent vascular endothelial growth factor (VEGF) levels in predicting futile recanalization (FR) in acute ischemic stroke (AIS) patients undergoing endovascular treatment (EVT), and to explore the association between angiogenesis and VEGF. METHODS: 84 participants were recruited, including 46 AIS in the EVT group, 20 AIS in the conventional treatment group, and 18 healthy controls. Plasma VEGF levels were measured at different time points. FR was defined as a modified Rankin scale score of 3-6 at 3 months. Multivariable analysis evaluated whether VEGF levels at different time points independently predicted FR, and receiver operating characteristic (ROC) curves assessed their predictive value. Using intracranial lesion side vascular imaging, the Maas scoring system assessed angiogenesis post-onset, with scores of 4 to 5 indicating angiogenesis. RESULTS: In the conventional treatment group, VEGF levels significantly decreased by day 7, while in the EVT group, reduction was observed as early as day 3. After adjusting for potential confounders, only VEGF levels on day 3 emerged as an independent predictor of FR. The combined model incorporating VEGF levels on day 3 with other factors effectively predicted FR (area under the curve = 0.916; sensitivity = 84.21 %; specificity = 100 %, P<0.0001). Plasma VEGF levels were notably higher in patients with angiogenesis in specific brain regions compared to those without angiogenesis at days 1, 3, 7, and 14 (P<0.05). CONCLUSION: VEGF levels on the 3rd day post-EVT demonstrate superior predictive value for FR. Elevated VEGF levels correlate with angiogenesis, suggesting its potential as a therapeutic target.

Semiconductor Effect from Pd(II) Porphyrin Metal to Its Ligand in Photocatalytic N-Dealkylation.

In this work, four saddled Pd(II) porphyrins were developed as photocatalyst for N-dealkylation of triethyl Rhodamine (TER) under visible light, and their catalytic ability was found to be negatively related to the out-of-plane of their macrocycles. Two important relationships involving the metalloporphyrins as catalyst were revealed: (1) a photoexcitative semiconductor effect between the 4dx 2-γ 2(Pd) and a2u(π) orbitals of Pd(II) porphyrin on the dealkylation. (2) a domino process from strap length, ring geometry, core deformation, d-π gap variation, to photocatalytic activity. Two revelations imply a unidirectional electron transfer route from axial ligand, to central metal, to porphyrin ring based on photoexcitation and guide the design and development of complex photocatalysts, and their revelation is attributed to the acquisition of a series of Pd(II) porphyrins with continuous ring distortion. The findings help to understand the photocatalytic single electron transfer (SET)-first mechanism based on metallic complex.

An Experimental Study in Laser-Assisted Machining of AerMet100 Steel.

To solve the problems of poor surface quality and low tool life in conventional machining (CM) of AerMet100 steel, an experimental study was conducted in laser-assisted machining (LAM) of AerMet100 steel. The effects of laser power, cutting speed, feed rate, and depth of cut on the surface roughness of AerMet100 steel were studied based on a single-factor experiment. The degree of influence of each factor on the surface roughness was evaluated by analyses of variance and range in the orthogonal experiment, and the combination of process parameters for the optimal surface roughness was obtained. The order of influence was as follows: laser power > cutting speed > depth of cut > feed rate; the optimal combination of process parameters was laser power 200 W, cutting speed 56.5 m/min, feed rate 0.018 mm/rev, and depth of cut 0.3 mm. Compared to CM, the surface morphology of the workpiece under the optimization of LAM was relatively smooth and flat, the surface roughness Ra was 0.402 µm, which was reduced by 62.11%, the flank wear was reduced from 208.69 µm to 52.17 µm, there were no tipping or notches, and the tool life was significantly improved. The study shows that the LAM of AerMet100 steel has obvious advantages in improving surface quality and reducing tool wear.

Simulation dataset of annual crop growth, GHG emission and SOC stock dynamics under current and projected climate conditions for major crops with current and reduced fertiliser inputs in Southwest, England.

For mitigating the unintended environmental impacts associated with intensive farming across the world, it is crucial to understand the complex impacts of potential reductions in fertiliser use on multiple ecosystem services, including crop production, GHG emissions and changes in soil organic carbon (SOC) stocks. Using site specific spatial data and information, a novel integrated modelling approach using established agroecosystem models (SPACSYS and RothC) was implemented to evaluate the impacts of various fertiliser reductions (10 %, 30 % and 50 %) under current / baseline and projected (RCP2.6, RCP4.5 and RCP8.5) climate scenarios in a study catchment in southwest England. 48 unique combinations of soil types, climate conditions and fertiliser inputs were evaluated for five major arable crops (winter wheat, maize, winter barley, spring barley, winter oilseed rape) plus ryegrass. Modelled annual estimates of crop yields and biomass, emissions of gases with warming potentials (nitrous oxide, methane, carbon) and SOC stocks in the topsoil (0-30 cm) were tabulated for all combinations considered. These simulated data series could be further analysed to evaluate inter-annual variations and their implications for climate resilience and combined with additional data to quantify nutrient use efficiency and undertake cost- benefit analysis, and to contribute to inter-regional comparisons of fertiliser management at broad scale.

Potential prognostic value of CSF-targeted proteomics across the Alzheimer's disease continuum.

BACKGROUND: Core biomarkers for Alzheimer's disease (AD), such as Aß42 and tau, have demonstrated high prognostic accuracy but do not fully capture the complex pathophysiology of AD. In this study, our objective was to identify novel cerebrospinal fluid (CSF) biomarkers using proteomics across the entire AD continuum to predict conversion to AD and explore their involvement in AD pathogenesis. METHODS: A cohort of 186 cognitively normal (CN), 127 subjective memory complaint (SMC), 79 early mild cognitive impairment (EMCI), 249 late MCI (LMCI), and 132 AD individuals was analyzed, with a follow-up period of over 3 years for non-AD participants. CSF 65 peptides, as well as hippocampal and entorhinal volumes were analyzed, and cognitive function was evaluated using the 13-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-Cog 13). Cox proportional hazards models and mediation analysis were performed to investigate associations and causal relationships. RESULTS: During the follow-up, approximately one-fourth (146/580) of the non-AD participants progressed to AD. After adjusting for baseline diagnosis (CN to LMCI) and other variables, multivariable Cox regression analysis identified three peptides (VAELEDEK, VSFELFADK, and VVSSIEQK) as significant predictors of conversion to AD. Incorporating these three peptides into the initial model significantly improved the C-statistic from 0.82 to 0.85 for predicting AD conversion, surpassing the predictive ability of Aß42 and P-tau. Moreover, hippocampal and entorhinal volumes mediated 30.3-53.8% of the association between the three peptides and ADAS-Cog 13 scores. CONCLUSIONS: These findings underscore the potential of these three peptides as robust prognostic biomarker candidates for AD conversion across the entire AD continuum, with a mechanism involving the mediation of hippocampal and entorhinal volumes.

Investigation of Synthesis, Characterization, and Finishing Applications of Spherical Al2O3 Magnetic Abrasives via Plasma Molten Metal Powder and Powder Jetting.

Magnetic abrasive finishing (MAF) is an efficient finishing process method using magnetic abrasive particles (MAPs) as finishing tools. In this study, two iron-based alumina magnetic abrasives with different particle size ranges were synthesized by the plasma molten metal powder and powder jetting method. Characterization of the magnetic abrasives in terms of microscopic morphology, phase composition, magnetic permeability, particle size distribution, and abrasive ability shows that the magnetic abrasives are spherical in shape, that the hard abrasives are combined in the surface layer of the iron matrix and remain sharp, and that the hard abrasives combined in the surface layer of the magnetic abrasives with smaller particle sizes are sparser than those of the magnetic abrasives with larger particle sizes. The magnetic abrasives are composed of α-Fe and Al2O3; the magnetic permeability of the magnetic abrasives having smaller particle sizes is slightly higher than that of the magnetic abrasives having larger particle sizes; the two magnetic abrasives are distributed in a range of different particle sizes; the magnetic abrasives have different magnetic permeabilities, which are higher than those of the larger ones; both magnetic abrasives are distributed in the range of smaller particle sizes; and AZ31B alloy can obtain smaller surface roughness of the workpiece after the grinding process of the magnetic abrasives with a small particle size.

Synergistic Therapeutic Effects of D-Mannitol-Cerium-Quercetin (Rutin) Coordination Polymer Nanoparticles on Acute Lung Injury.

Acute lung injury (ALI) remains a significant global health issue, necessitating novel therapeutic interventions. In our latest study, we pioneered the use of D-mannitol-cerium-quercetin/rutin coordination polymer nanoparticles (MCQ/R NPs) as a potential treatment for ALI. The MCQ/R NPs, which integrate rutin and quercetin for their therapeutic potential and D-mannitol for its pulmonary targeting, displayed exceptional efficacy. By utilizing cerium ions for optimal nanoparticle assembly, the MCQ/R NPs demonstrated an average size of less than 160 nm. Impressively, these nanoparticles outperformed conventional treatments in both antioxidative capabilities and biocompatibility. Moreover, our in vivo studies on LPS-induced ALI mice showed a significant reduction in lung tissue inflammation. This groundbreaking research presents MCQ/R NPs as a promising new approach in ALI therapeutics.

Risk factors, prognostic factors, and nomograms for synchronous brain metastases of solid tumors: a population-based study.

In previous literatures, we found that similar studies on the short-term prognosis of synchronous brain metastases (S-BM) from other systems are rare. Our aim was to evaluate the early mortality rate of patients with S-BM from the Surveillance, Epidemiology, and End Result (SEER) database and explore the risk factors for early mortality (≤ 1 year). We used Kaplan-Meier (KM) curves to evaluate early mortality in patients with S-BM from the SEER database. Logistic regression analyses were used to identify significant independent prognostic factors in patients with a follow-up time > 12 months. And the meaningful factors were used to construct a nomogram of overall early death. The receiver operating characteristic (ROC) curve was used to test the predictive ability of the model, while the decision curve analysis (DCA) curve was used to validate the clinical application ability of the model. A total of 47,284 patients were used for univariate and multivariate logistic regression analysis to screen variables to constructing a nomogram. In the all-cause early mortality specific model, the area under the ROC (AUC) curve of the training set was 0.764 (95% confidence interval (CI): 0.758-0.769), and the AUC of the validation set was 0.761 (95% CI: 0.752-0.770). The DCA calibration curves of the training set and validation set indicate that the 1-year early mortality rate predicted by this model is consistent with the actual situation. We found that the 1-year early mortality rate was 76.4%. We constructed a validated nomogram using these covariates to effectively predict 1-year early mortality in patients with S-BM. This nomogram can help clinical workers screen high-risk patients to develop more reasonable treatment plans.

Hydrophilicity and Pore Structure Enhancement in Polyurethane/Silk Protein-Bismuth Halide Oxide Composite Films for Photocatalytic Degradation of Dye.

Polyurethane/silk protein-bismuth halide oxide composite films were fabricated using a blending-wet phase transformationin situsynthesis method. The crystal structure, micromorphology, and optical properties were conducted using XRD, SEM, and UV-Vis DRS characterize techniques. The results indicated that loaded silk protein enhanced the hydrophilicity and pore structure of the polyurethane composite films. The active species BiOX were observed to grow as nanosheets with high dispersion on the internal skeleton and silk protein surface of the polyurethane-silk protein film. The photocatalytic efficiency of BiOX/PU-SF composite films was assessed through the degradation of Rhodamine B under visible light irradiation. Among the tested films, the BiOBr/PU-SF composite exhibited the highest removal rate of RhB at 98.9%, surpassing the removal rates of 93.7% for the BiOCl/PU-SF composite and 85.6% for the BiOI/PU-SF composite. Furthermore, an active species capture test indicated that superoxide radical (•O2-) and hole (h+) species played a predominant role in the photodegradation process.

Lead-free dual-frequency ultrasound implants for wireless, biphasic deep brain stimulation.

Ultrasound-driven bioelectronics could offer a wireless scheme with sustainable power supply; however, current ultrasound implantable systems present critical challenges in biocompatibility and harvesting performance related to lead/lead-free piezoelectric materials and devices. Here, we report a lead-free dual-frequency ultrasound implants for wireless, biphasic deep brain stimulation, which integrates two developed lead-free sandwich porous 1-3-type piezoelectric composite elements with enhanced harvesting performance in a flexible printed circuit board. The implant is ultrasonically powered through a portable external dual-frequency transducer and generates programmable biphasic stimulus pulses in clinically relevant frequencies. Furthermore, we demonstrate ultrasound-driven implants for long-term biosafety therapy in deep brain stimulation through an epileptic rodent model. With biocompatibility and improved electrical performance, the lead-free materials and devices presented here could provide a promising platform for developing implantable ultrasonic electronics in the future.

Peripheral Blood Lymphocyte Subsets and Heterogeneity of B Cell Subsets in Patients of Idiopathic Inflammatory Myositis with Different Myositis-specific Autoantibodies.

Idiopathic inflammatory myopathies (IIM) are a group of myopathies that present with muscle weakness and multiple extra-muscular manifestations, in which lymphocytes play central roles in myositis pathogenesis. This study aimed to explore the clinical characteristics of lymphocyte subsets, especially B cell subsets, in patients with IIM. Our study included 176 patients with active IIM and 210 gender/age-matched healthy controls (HCs). Compared to HCs, patients have reduced counts of T cells, B cells, and natural killer cells. In addition, B cell subsets from 153 patients with IIM and 92 HCs were characterized. Patients had a lower percentage of memory B cells and translational memory B cells, while those patients were with an elevated percentage of CD19+ B cells, plasmablast and naïve B cells compared with HCs. Moreover, to further explore the heterogeneity of B cells in IIM, patients were categorized into three clusters based on clustering analysis. Cluster 1 was dominated by CD19+ B cells, Bregs and naïve B cells, cluster 3 was dominated by memory B cells and plasmablast, and cluster 2 had the highest proportion of translational memory B cells. Notably, patients in cluster 1 presented with higher CK levels, indicating muscle damage, whereas patients in cluster 3 showed a higher incidence of chest tightness. Our study indicated that lymphopenia is a common manifestation in patients with IIM. B cell subsets are abnormally expressed and showed high heterogeneity in patients with IIM. The patients with IIM were divided into three different clusters with different percentages of chest tightness and distinct CK levels.

Harvesting Vibration Energy for Efficient Cocatalyst-Free Sonocatalytic H2 Production over Magnetically Separable Ultra-Low-Cost Fe3O4.

The cavitation effect is an important geochemical phenomenon, which generally exists under strong hydrodynamic conditions. Therefore, developing an economical and effective sonocatalyst becomes a vital method in capitalizing on the cavitation effect for energy generation. In this study, we first report a novel Fe3O4 sonocatalyst that can be easily separated using a magnetic field and does not require any additional cocatalysts for H2 production from H2O. When subjected to ultrasonic vibration, this catalyst achieves an impressive H2 production rate of up to 175 µmol/h/USD (where USD stands for dollars), surpassing most previously reported mechanical catalytic materials. Furthermore, the ease and efficiency of separating this catalyst using an external magnetic field, coupled with its effortless recovery, highlight its significant potential for practical applications. By addressing the key limitations of conventional sonocatalysts, our study not only demonstrates the feasibility of using Fe3O4 as a highly efficient sonocatalyst but also showcases the exciting possibility of using a new class of magnetically separable sonocatalysts to productively transform mechanical energy into chemical energy.

The effect analysis of shape design of different charging piles based on Human physiological characteristics using the MF-DFA.

With the rapid development of new energy vehicles, the users have an increasing demand for charging piles. It is generally believed that the charging pile is a kind of practical product, and it only needs to realize the charging function. However, as a product, the shape design of the charging pile will directly affect the user experience, thus affecting product sales. Therefore, in the face of increasingly fierce market competition, when designing the shape of charging piles, it is necessary to adopt the traditional evaluation method and human physiological cognitive characteristics to evaluate the shape of charging piles more objectively. From the user's point of view, using the electroencephalogram (EEG) of the user, with the help of the multifractal detrended fluctuation analysis (MF-DFA) method, this paper comprehensively analyzes the differences in emotional cognitive characteristics between two kinds of charging piles, namely, the charging pile with a curved appearance design and the charging pile with square appearance design. The results show that there are significant differences in human physiological cognitive characteristics between two kinds of charging piles with different shapes. And different shapes of charging piles have different physiological cognitive differences for users. When designing charging pile product shapes, human beings can objectively evaluate the product shape design according to the physiological cognition differences of users, so as to optimize the charging pile product shape design.

Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm.

Ultrashort pulses, characterized by their short pulse duration, diverse spectral content, and high peak power, are widely used in fields including laser processing, optical storage, biomedical sciences, and laser imaging. The complex, highly-nonlinear process of ultrashort pulse evolution within fiber lasers is influenced by numerous aspects such as dispersion, loss, gain, and nonlinear effects. Traditionally, the split-step Fourier transforms method is employed for simulating ultrashort pulses in fiber lasers, which involves traversing multiple parameters within the fiber to attain the pulse's optimal state. The simulation is a significantly time-consuming process. Here, we use a neural network model to fit and predict the impact of multiple parameters on the pulse characteristics within fiber lasers, enabling parameter optimization through genetic algorithms to determine the optimal pulse duration, pulse energy, and peak power. Integrating artificial intelligence algorithms simplifies the acquisition of optimal pulse parameters and enhances our understanding of multiple parameters' impact on the pulse characteristics. The investigation of ultrashort pulse optimization based on artificial intelligence holds immense potential for laser design.

Printing 3D Metallic Structures in Porous Matrix.

The fabrication of metallic micro/nanostructures has great potential for advancing optoelectronic microdevices. Over the past decade, femtosecond laser direct writing (FsLDW) technology has played a crucial role in driving progress in this field. In this study, silica gel glass is used as a supporting medium, and FsLDW is employed to reduce gold and palladium ions using 7-Diethylamino-3-thenoylcoumarin (DETC) as a two-photon sensitizer, enabling the printing of conductive multilayered and 3D metallic structures. How the pore size of the silica gel glass affects the electrical conductivity of printed metal wires is systematically examined. This 3D printing method is versatile and offers expanded opportunities for applying metallic micro/nanostructures in optoelectronic devices.

Health risks and sources of trace elements and black carbon in PM2.5 from 2019 to 2021 in Beijing.

A comprehensive health risk assessment of PM2.5 is meaningful to understand the current status and directions regarding further improving air quality from the perspective of human health. In this study, we evaluated the health risks of PM2.5 as well as highly toxic inorganic components, including heavy metals (HMs) and black carbon (BC) based on long-term observations in Beijing from 2019 to 2021. Our results showed that the relative risks of chronic obstructive pulmonary disease, lung cancer, acute lower respiratory tract infection, ischemic heart disease, and stroke decreased by 4.07%-9.30% in 2020 and 2.12%-6.70% in 2021 compared with 2019. However, they were still at high levels ranging from 1.26 to 1.77, in particular, stroke showed the highest value in 2021. Mn had the highest hazard quotient (HQ, from 2.18 to 2.56) for adults from 2019 to 2021, while Ni, Cr, Pb, As, and BC showed high carcinogenic risks (CR > 1.0×10-6) for adults. The HQ values of Mn and As and the CR values of Pb and As showed constant or slight upwards trends during our observations, which is in contrast to the downward trends of other HMs and PM2.5. Mn, Cr, and BC are crucial toxicants in PM2.5. A significant shrink of southern region sourcesof HMs and BCshrank suggests the increased importance of local sources. Industry, dust, and biomass burning are the major contributors to the non-carcinogenic risks, while traffic emissions and industry are the dominant contributors to the carcinogenic risks in Beijing.