Langevin dynamics simulations for the critical adsorption of end-grafted active polymers.

The critical adsorption of end-grafted active polymer chains on an attractive surface is studied using Langevin dynamics simulations. The active polymers are composed of an active Langevin particle located at the head and a sequential passive chain. Results show that the active force exerted by the active head pulls the active polymer away from the surface. Consequently, the adsorption of the active polymer is hindered, and the critical surface attraction strength, , increases proportionally to the square of the active force, Fa2. The increase in depends on the rotation behavior of the active head. Specifically, for the restricted rotating active polymer (RRAP) chain with a longer rotational persistence time as the rotation of the active head is restricted, increases significantly with Fa. On the other hand, for the freely rotating active polymer (FRAP) chain with a shorter rotational persistence time as the rotation of the active head is free, shows a weak dependence on Fa. The results show that the active force has a significantly stronger pulling effect on the RRAP chain than on the FRAP chain. Furthermore, knotted conformations are observed for the adsorbed RRAP chain at large Fa. These knots reduce the adsorption of monomers near the grafted end. In contrast, no knotted conformations are observed for the FRAP chains due to the comparatively weaker pulling effect of the active force.

Comparison and optimization of different CRISPR/Cas9 donor-adapting systems for gene editing.

Gene knock-in in mammalian cells usually uses homology-directed repair (HDR) mechanism to integrate exogenous DNA template into the target genome site. However, HDR efficiency is often low, and the co-localization of exogenous DNA template and target genome site is one of the key limiting factors. To improve the efficiency of HDR mediated by CRISPR/Cas9 system, our team and previous studies fused different adaptor proteins with SpCas9 protein and expressed them. By using their characteristics of binding to specific DNA sequences, many different CRISPR/SpCas9 donor adapter gene editing systems were constructed. In this study, we used them to knock-in eGFP gene at the 3'-end of the terminal exon of GAPDH and ACTB genes in HEK293T cells to facilitate a comparison and optimization of these systems. We utilized an optimized donor DNA template design method, validated the knock-in accuracy via PCR and Sanger sequencing, and assessed the efficiency using flow cytometry. The results showed that the fusion of yGal4BD, hGal4BD, hLacI, hTHAP11 as well as N57 and other adaptor proteins with the C-terminus of SpCas9 protein had no significant effect on its activity. At the GAPDH site, the donor adapter systems of SpCas9 fused with yGal4BD, hGal4BD, hLacI and hTHAP11 significantly improved the knock-in efficiency. At the ACTB site, SpCas9 fused with yGal4BD and hGal4BD significantly improved the knock-in efficiency. Furthermore, increasing the number of BS in the donor DNA template was beneficial to enhance the knock-in efficiency mediated by SpCas9-hTHAP11 system. In conclusion, this study compares and optimizes multiple CRISPR/Cas9 donor adapter gene editing systems, providing valuable insights for future gene editing applications.

A novel zwitterionic magnetic nanocomposite developed for non-invasive speciation analysis of inorganic chromium.

3-(2-Aminoethylamino)propyltriethoxysilane and carboxyethylsilanetriol sodium salt were grafted on silica-coated Fe3O4 nanoparticles via sol-gel process to prepare novel amine- and carboxyl-bifunctionalized magnetic nanocomposites (SMNPs-(NH2 + COOH)). After well characterized, this doubly functionalized material was used as magnetic solid-phase extraction (MSPE) adsorbent to separate and enrich inorganic chromium species followed by inductively coupled plasma-mass spectrometry detection. The optimization of MSPE operation parameters including pH was conducted. It is reasonably elucidated that the adsorption mechanisms of zwitterionic SMNPs-(NH2 + COOH) towards chromium species are electrostatic and/or coordination interactions. Cr(VI) and Cr(III) can be adsorbed around pH 3.0 and around 10.0 respectively with strong anti-interference ability not only from other co-existing ions but also from the two labile species each other, and eluted by dilute nitric acid solution. With a 15-fold enrichment factor, the limits of detection of Cr(VI) and Cr(III) were 0.008 and 0.009 µg L-1, respectively, profiting from the maximum adsorption capacities of 7.52 and 6.11 mg g-1. The just one magnetic extraction matrix based speciation scheme possesses excellent convenience and friendliness to Cr(VI) and Cr(III) without any oxidation or reduction prior to capture of these two species. This protocol has been successfully applied to the speciation analysis of inorganic chromium in real-world environmental water samples.

Artemisinins ameliorate polycystic ovarian syndrome by mediating LONP1-CYP11A1 interaction.

Polycystic ovary syndrome (PCOS), a prevalent reproductive disorder in women of reproductive age, features androgen excess, ovulatory dysfunction, and polycystic ovaries. Despite its high prevalence, specific pharmacologic intervention for PCOS is challenging. In this study, we identified artemisinins as anti-PCOS agents. Our finding demonstrated the efficacy of artemisinin derivatives in alleviating PCOS symptoms in both rodent models and human patients, curbing hyperandrogenemia through suppression of ovarian androgen synthesis. Artemisinins promoted cytochrome P450 family 11 subfamily A member 1 (CYP11A1) protein degradation to block androgen overproduction. Mechanistically, artemisinins directly targeted lon peptidase 1 (LONP1), enhanced LONP1-CYP11A1 interaction, and facilitated LONP1-catalyzed CYP11A1 degradation. Overexpression of LONP1 replicated the androgen-lowering effect of artemisinins. Our data suggest that artemisinin application is a promising approach for treating PCOS and highlight the crucial role of the LONP1-CYP11A1 interaction in controlling hyperandrogenism and PCOS occurrence.

Molecular ferroelectric with low-magnetic-field magnetoelectricity at room temperature.

Magnetoelectric materials, which encompass coupled magnetic and electric polarizabilities within a single phase, hold great promises for magnetic controlled electronic components or electric-field controlled spintronics. However, the realization of ideal magnetoelectric materials remains tough due to the inborn competion between ferroelectricity and magnetism in both levels of symmetry and electronic structure. Herein, we introduce a methodology for constructing single phase paramagnetic ferroelectric molecule [TMCM][FeCl4], which shows low-magnetic-field magnetoelectricity at room temperature. By applying a low magnetic field (≤1 kOe), the halogen Cl‧‧‧Cl distance and the volume of [FeCl4]- anions could be manipulated. This structural change causes a characteristic magnetostriction hysteresis, resulting in a substantial deformation of ~10-4 along the a-axis under an in-plane magnetic field of 2 kOe. The magnetostrictive effect is further qualitatively simulated by density functional theory calculations. Furthermore, this mechanical deformation significantly dampens the ferroelectric polarization by directly influencing the overall dipole configuration. As a result, it induces a remarkable α31 component (~89 mV Oe-1 cm-1) of the magnetoelectric tensor. And the magnetoelectric coupling, characterized by the change of polarization, reaches ~12% under 40 kOe magnetic field. Our results exemplify a design methodology that enables the creation of room-temperature magnetoelectrics by leveraging the potent effects of magnetostriction.

Air-sea exchange of PAHs in the Taiwan Strait: Seasonal dynamics and regulation mechanisms revealed by machine learning approach.

In this study, to understand the seasonal dynamics of air-sea exchange and its regulation mechanisms, we investigated polycyclic aromatic hydrocarbons (PAHs) at the air-sea interface in the western Taiwan Strait in combination with measurements and machine learning (ML) predictions. For 3-ring PAHs and most of 4- to 6-ring, volatilization and deposition fluxes were observed, respectively. Seasonal variations in air-sea exchange flux suggest the influence of monsoon transitions. Results of interpretable ML approach (XGBoost) indicated that volatilization of 3-ring PAHs was significantly controlled by dissolved PAH concentrations (contributed 24.0 %), and the gaseous deposition of 4- to 6-ring PAHs was related to more contaminated air masses originating from North China during the northeast monsoon. Henry's law constant emerged as a secondary factor, influencing the intensity of air-sea exchange, particularly for low molecular weight PAHs. Among environmental parameters, notably high wind speed emerges as the primary factor and biological pump's depletion of PAHs in surface seawater amplifies the gaseous deposition process. The distinct dynamics of exchanges at the air-water interface for PAHs in the western TWS can be attributed to variations in primary emission intensities, biological activity, and the inconsistent pathways of long-range atmospheric transport, particularly within the context of the monsoon transition.

Development and validation of a prognostic model for assessing long COVID risk following Omicron wave-a large population-based cohort study.

BACKGROUND: Long coronavirus disease (COVID) after COVID-19 infection is continuously threatening the health of people all over the world. Early prediction of the risk of Long COVID in hospitalized patients will help clinical management of COVID-19, but there is still no reliable and effective prediction model. METHODS: A total of 1905 hospitalized patients with COVID-19 infection were included in this study, and their Long COVID status was followed up 4-8 weeks after discharge. Univariable and multivariable logistic regression analysis were used to determine the risk factors for Long COVID. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%), and factors for constructing the model were screened using Lasso regression in the training cohort. Visualize the Long COVID risk prediction model using nomogram. Evaluate the performance of the model in the training and validation cohort using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). RESULTS: A total of 657 patients (34.5%) reported that they had symptoms of long COVID. The most common symptoms were fatigue or muscle weakness (16.8%), followed by sleep difficulties (11.1%) and cough (9.5%). The risk prediction nomogram of age, diabetes, chronic kidney disease, vaccination status, procalcitonin, leukocytes, lymphocytes, interleukin-6 and D-dimer were included for early identification of high-risk patients with Long COVID. AUCs of the model in the training cohort and validation cohort are 0.762 and 0.713, respectively, demonstrating relatively high discrimination of the model. The calibration curve further substantiated the proximity of the nomogram's predicted outcomes to the ideal curve, the consistency between the predicted outcomes and the actual outcomes, and the potential benefits for all patients as indicated by DCA. This observation was further validated in the validation cohort. CONCLUSIONS: We established a nomogram model to predict the long COVID risk of hospitalized patients with COVID-19, and proved its relatively good predictive performance. This model is helpful for the clinical management of long COVID.

MLatom Software Ecosystem for Surface Hopping Dynamics in Python with Quantum Mechanical and Machine Learning Methods.

We present an open-source MLatom@XACS software ecosystem for on-the-fly surface hopping nonadiabatic dynamics based on the Landau-Zener-Belyaev-Lebedev algorithm. The dynamics can be performed via Python API with a wide range of quantum mechanical (QM) and machine learning (ML) methods, including ab initio QM (CASSCF and ADC(2)), semiempirical QM methods (e.g., AM1, PM3, OMx, and ODMx), and many types of ML potentials (e.g., KREG, ANI, and MACE). Combinations of QM and ML methods can also be used. While the user can build their own combinations, we provide AIQM1, which is based on Δ-learning and can be used out-of-the-box. We showcase how AIQM1 reproduces the isomerization quantum yield of trans-azobenzene at a low cost. We provide example scripts that, in dozens of lines, enable the user to obtain the final population plots by simply providing the initial geometry of a molecule. Thus, those scripts perform geometry optimization, normal mode calculations, initial condition sampling, parallel trajectories propagation, population analysis, and final result plotting. Given the capabilities of MLatom to be used for training different ML models, this ecosystem can be seamlessly integrated into the protocols building ML models for nonadiabatic dynamics. In the future, a deeper and more efficient integration of MLatom with Newton-X will enable a vast range of functionalities for surface hopping dynamics, such as fewest-switches surface hopping, to facilitate similar workflows via the Python API.

Temperature dependence of the rain-gas and snow-gas partition coefficients for nearly a thousand chemicals.

Compared to the particle-gas partition coefficients (KPG), the rain-gas (KRG) and snow-gas (KSG) partition coefficients are also essential in studying the environmental behavior and fate of chemicals in the atmosphere. While the temperature dependence for the KPG have been extensively studied, the study for KRG and KSG are still lacking. Adsorption coefficients between water surface-air (KIA) and snow surface-air (KJA), as well as partition coefficients between water-air (KWA) and octanol-air (KOA) are vital in calculating KRG and KSG. These four basic adsorption and partition coefficients are also temperature-dependent, given by the well-known two-parameters Antoine equation logKXY = AXY+BXY/T, where KXY is the adsorption or partition coefficients, AXY and BXY are Antoine parameters (XY stand for IA, JA, WA, and OA), and T is the temperature in Kelvin. In this study, the parameters AXY and BXY are calculated for 943 chemicals, and logKXY can be estimated at any ambient temperature for these chemicals using these Antoine parameters. The results are evaluated by comparing these data with published experimental and modeled data, and the results show reasonable accuracy. Based on these coefficients, temperature-dependence of logKRG and logKSG is studied. It is found that both logKRG and logKSG are linearly related to 1/T, and Antoine parameters for logKRG and logKSG are also estimated. Distributions of the 943 chemicals in the atmospheric phases (gas, particle, and rain/snow), are illustrated in a Chemical Space Map. The findings reveal that, at environmental temperatures and precipitation days, the dominant state for the majority of chemicals is the gaseous phase. All the AXY and BXY values for logKSG, logKRG, and basic adsorption and partition coefficients, both modeled by this study and collected from published work, are systematically organized into an accessible dataset for public utilization.

Coexistence of Superconductivity and Antiferromagnetism in Topological Magnet MnBi2Te4 Films.

The interface of two materials can harbor unexpected emergent phenomena. One example is interface-induced superconductivity. In this work, we employ molecular beam epitaxy to grow a series of heterostructures formed by stacking together two nonsuperconducting antiferromagnetic materials, an intrinsic antiferromagnetic topological insulator MnBi2Te4 and an antiferromagnetic iron chalcogenide FeTe. Our electrical transport measurements reveal interface-induced superconductivity in these heterostructures. By performing scanning tunneling microscopy and spectroscopy measurements, we observe a proximity-induced superconducting gap on the top surface of the MnBi2Te4 layer, confirming the coexistence of superconductivity and antiferromagnetism in the MnBi2Te4 layer. Our findings will advance the fundamental inquiries into the topological superconducting phase in hybrid devices and provide a promising platform for the exploration of chiral Majorana physics in MnBi2Te4-based heterostructures.

Engineering Plateau Phase Transition in Quantum Anomalous Hall Multilayers.

The plateau phase transition in quantum anomalous Hall (QAH) insulators corresponds to a quantum state wherein a single magnetic domain gives way to multiple domains and then reconverges back to a single magnetic domain. The layer structure of the sample provides an external knob for adjusting the Chern number C of the QAH insulators. Here, we employ molecular beam epitaxy to grow magnetic topological insulator multilayers and realize the magnetic field-driven plateau phase transition between two QAH states with odd Chern number change ΔC. We find that critical exponents extracted for the plateau phase transitions with ΔC = 1 and ΔC = 3 in QAH insulators are nearly identical. We construct a four-layer Chalker-Coddington network model to understand the consistent critical exponents for the plateau phase transitions with ΔC = 1 and ΔC = 3. This work will motivate further investigations into the critical behaviors of plateau phase transitions with different ΔC in QAH insulators.

Coagulation and fibrinolytic markers offer utility when distinguishing between benign and malignant gallbladder tumors: A cross-sectional study.

BACKGROUND: The metabolic or proliferative abnormalities that are characteristic of tumor cells can lead to abnormal fibrinolysis or coagulation system activity, with certain tumors exhibiting hypercoagulability or existing in a fibrinolytic state. However, the utility of biomarkers of coagulation and fibrinolysis when seeking to differentiate between benign gallbladder disease and malignant gallbladder tumors remains uncertain. METHODS: This study included a total of 81 patients with benign gallbladder polyps and 94 patients with malignant gallbladder tumors. Pre-biopsy or pretreatment levels of PT, APTT, FIB, D-dimer, FDP, PLT, PIC, TAT, TM, and t-PAIC from these patients were compared using Mann-Whitney tests. The baseline data of the patients were analyzed using chi-square tests, and the diagnostic utility of these biomarkers in distinguishing between benign and malignant gallbladder lesions was evaluated using ROC curves, and Spearman correlation analysis was employed to assess the correlation between these indicators and tumor parameters. RESULTS: The average age of malignant gallbladder tumor group was higher than benign gallbladder polyp group. And the base line analysis showed that there was a statistic difference in age, history of smoking, drinking, biliary tract disease, BMI of over weight between these two groups. In patients with malignant gallbladder tumors, FIB, D-dimer, FDP, PIC, TAT, TM, and t-PAIC levels were significantly elevated relative to those in patients affected by benign gallbladder polyp. The AUC for FIB, D-dimer, and FDP was 0.8469, 0.6514, 0.5950, while for PIC, TAT, TM, t-PAIC and four biomarker combined diagnosed was 0.8455, 0.6554, 0.7130, 0.6806, and 0.8859. Among these, TM was associated with the vascular invasion of tumor patients; TAT and t-PAIC were associated with neural invasion; D-dimer and FDP were related to the maximum tumor diameter; and FDP had a certain correlation with the tumor stage. CONCLUSIONS: In gallbladder tumor patients, conventional coagulation metrics like FIB, D-dimer, and FDP, as well as newer thrombotic indicators such as PIC, TAT, TM, and t-PAIC, were obviously increased. Correlations with tumor parameters suggested their potential as biomarkers to distinguish benign from malignant gallbladder growths.

The Dilemma of Balancing Anti-Tumor Necrosis Factor-Alpha (Anti-TNF-α) Biologics for Psoriatic Arthritis Control With the Risk of Severe Systemic Infection.

The treatment landscape for psoriatic arthritis (PsA) has evolved significantly with the introduction of biologic therapies, such as adalimumab, which effectively inhibits tumor necrosis factor-alpha (TNF-α) activity. However, despite their efficacy in controlling inflammation, biologic therapies are associated with heightened risks of infectious complications and malignancies. We present a case of a 66-year-old female with PsA treated with adalimumab who presented with recurrent systemic bacterial infections. Despite attempts to adjust dosing intervals to minimize infection risks, the patient experienced severe complications, including urosepsis, endocarditis, and liver abscesses. The dilemma arises in balancing PsA control with anti-TNFα therapy while minimizing infection risks. Current evidence supporting prophylactic antibiotics in such cases is limited, and determining the next steps for treatment involves challenging decisions such as withholding TNF inhibitors or switching to alternative immunomodulators. This case underscores the need for further research into prophylactic treatment and monitoring protocols to manage recurrent infections during anti-TNF-α therapy effectively.

Biomechanical comparison of the therapeutic effect of a novel proximal femoral bionic intramedullary nail and traditional inverted triangle hollow screw on femoral neck fracture.

OBJECTIVE: A novel Proximal Femoral Bionic Nail (PFBN) has been developed by a research team for the treatment of femoral neck fractures. This study aims to compare the biomechanical properties of the innovative PFBN with those of the conventional Inverted Triangular Cannulated Screw (ITCS) fixation method through biomechanical testing. METHODS: Sixteen male femoral specimens preserved in formalin were selected, with the donors' age at death averaging 56.1 ± 6.3 years (range 47-64 years), and a mean age of 51.4 years. The femurs showed no visible damage and were examined by X-rays to exclude diseases affecting bone quality such as tumors, severe osteoporosis, and deformities. The 16 femoral specimens were randomly divided into an experimental group (n = 8) and a control group (n = 8). All femurs were prepared with Pauwels type III femoral neck fractures, fixed with PFBN in the experimental group and ITCS in the control group. Displacement and stress limits of each specimen were measured through cyclic compression tests and failure experiments, and vertical displacement and strain values under a 600 N vertical load were measured in all specimens through vertical compression tests. RESULTS: In the vertical compression test, the average displacement at the anterior head region of the femur was 0.362 mm for the PFBN group, significantly less than the 0.480 mm for the ITCS group (p < 0.001). At the fracture line area, the average displacement for the PFBN group was also lower than that of the ITCS group (0.196 mm vs. 0.324 mm, p < 0.001). The difference in displacement in the shaft area was smaller, but the average displacement for the PFBN group (0.049 mm) was still significantly less than that for the ITCS group (0.062 mm, p = 0.016). The situation was similar on the posterior side of the femur. The average displacements in the head area, fracture line area, and shaft area for the PFBN group were 0.300 mm, 0.168 mm, and 0.081 mm, respectively, while those for the ITCS group were 0.558 mm, 0.274 mm, and 0.041 mm, with significant differences in all areas (p < 0.001). The average strain in the anterior head area for the PFBN group was 4947 µm/m, significantly less than the 1540 µm/m for the ITCS group (p < 0.001). Likewise, in the fracture line and shaft areas, the average strains for the PFBN group were significantly less than those for the ITCS group (p < 0.05). In the posterior head area, the average strain for the PFBN group was 4861 µm/m, significantly less than the 1442 µm/m for the ITCS group (p < 0.001). The strain conditions in the fracture line and shaft areas also showed the PFBN group was superior to the ITCS group (p < 0.001). In cyclic loading experiments, the PFBN fixation showed smaller maximum displacement (1.269 mm vs. 1.808 mm, p < 0.001), indicating better stability. In the failure experiments, the maximum failure load that the PFBN-fixated fracture block could withstand was significantly higher than that for the ITCS fixation (1817 N vs. 1116 N, p < 0.001). CONCLUSION: The PFBN can meet the biomechanical requirements for internal fixation of femoral neck fractures. PFBN is superior in biomechanical stability compared to ITCS, particularly showing less displacement and higher failure resistance in cyclic load and failure experiments. While there are differences in strain performance in different regions between the two fixation methods, overall, PFBN provides superior stability.

Stereotactically intracerebral transplantation of neural stem cells for ischemic stroke attenuated inflammatory responses and promoted neurogenesis: an experimental study with monkeys.

BACKGROUND: Ischemic stroke is a common neurovascular disorder with high morbidity and mortality. However, the underlying mechanism of stereotactically intracerebral transplantation of human neural stem cell (hNSC) is not well elucidated. MATERIALS AND METHODS: Four days after ischemic stroke induced by Rose Bengal photo-thrombosis, 7 cynomolgus monkeys were transplanted with hNSCs or vehicles stereotactically and followed up for 84 days. Behavioral assessments, magnetic resonance imaging, blood tests, and pathological analysis were performed before and after treatment. The proteome profiles of the left and right precentral gyrus and hippocampus were evaluated. Extracellular vesicle micro-RNA (miRNA) from the peripheral blood was extracted and analyzed. RESULTS: hNSC transplantation reduced the remaining infarcted lesion volume of cynomolgus monkeys with ischemic stroke without remarkable side effects. Proteomic analyses indicated that hNSC transplantation promoted GABAergic and glutamatergic neurogenesis, and restored the mitochondrial electron transport chain function in the ischemic infarcted left precentral gyrus or hippocampus. Immunohistochemical staining and qRT-PCT confirmed the promoting effects on neurogenesis and revealed that hNSCs attenuated post-infarct inflammatory responses by suppressing resident glia activation and mediating peripheral immune cell infiltration. Consistently, miRNA-sequencing revealed the miRNAs which were related to these pathways were down-regulated after hNSC transplantation. CONCLUSIONS: This study indicates that hNSCs can be effectively and safely used to treat ischemic stroke by promoting neurogenesis, regulating post-infarct inflammatory responses, and restoring mitochondrial function in both the infarct region and hippocampus.

Candidatus Liberibacter asiaticus influences the emergence of the Asian citrus psyllid Diaphorina citri by regulating key cuticular proteins.

The Asian citrus psyllid, Diaphorina citri, is the primary vector of the HLB pathogen, Candidatus Liberibacter asiaticus (CLas). The acquisition of CLas shortens the developmental period of nymphs, accelerating the emergence into adulthood and thereby facilitating the spread of CLas. Cuticular proteins (CPs) are involved in insect emergence. In this study, we investigated the molecular mechanisms underlying CLas-promoted emergence in D. citri via CP mediation. Here, a total of 159 CP genes were first identified in the D. citri genome. Chromosomal location analysis revealed an uneven distribution of these CP genes across the 13 D. citri chromosomes. Proteomic analysis identified 54 differentially expressed CPs during D. citri emergence, with 14 CPs exhibiting significant differential expression after CLas acquisition. Five key genes, Dc18aa-1, Dc18aa-2, DcCPR-24, DcCPR-38 and DcCPR-58, were screened from the proteome and CLas acquisition. The silencing of these 5 genes through a modified feeding method significantly reduced the emergence rate and caused various abnormal phenotypes, indicating the crucial role that these genes play in D. citri emergence. This study provides a comprehensive overview of the role of CPs in D. citri and reveals that CLas can influence the emergence process of D. citri by regulating the expression of CPs. These key CPs may serve as potential targets for future research on controlling huanglongbing (HLB) transmission.

[Ecological characteristics and seasonal changes of macrozoobenthos in the waters of Miaodao Archipelago, China]. / åº™å²›ç¾¤å²›æµ·åŸŸå¤§åž‹åº•æ –åŠ¨ç‰©ç”Ÿæ€ç‰¹å¾åŠå­£èŠ‚å˜åŒ–.

To understand the macrozoobenthic community composition and spatial-temporal distribution characteristics of macrobenthos in the waters of Miaodao Archipelago, Yantai, Shandong and its response to habitat changes, we conducted surveys of macrobenthos and environmental elements in the waters of Miaodao Islands in May (spring), August (summer), and October (autumn) in 2022. Results showed that a total of 127 macrozoobenthic species were recorded, with Mollusca and Annelida (Polychaeta) as the dominant taxa, consisting of 47 and 45 species, respectively. The key dominant species included Sternaspis chinensis, Glycinde bonhourei, Moerella hilaris, and Amphioplus (Lymanella) japonicus. The average annual density and biomass of macrozoobenthos were 190 ind·m-2 and 28.69 g·m-2, respectively. There was no significant seasonal differences in density and biomass. The Shannon diversity index (H), evenness index (J), and richness index (D) averaged 3.10, 0.90, and 2.40, respectively. Cluster analysis results showed low similarity coefficients of community among the three seasons, suggesting a distinct distribution pattern. Factors such as bottom seawater temperature, chlorophyll a, nutrient, sediment grain size, and organic matter content could significantly influence the structure and diversity of macrozoobenthic community. Compared with historical research data, the Changdao National Wetland Nature Reserve and the implementation of enclosure aquaculture have led to notable changes in the dominant species of macrobenthos. Specifically, there was a noticeable decline in both density and H, and an increase in biomass and J. Additionally, body size of benthic fauna was transitioning from small to big.

High-throughput screening of 222 pesticides in road environments in a megacity of northern China: A new approach to urban population exposure.

A large number of pesticides have been widely manufactured and applied, and are released into the environment with negative impact on human health. Pesticides are largely used in densely populated urban environments, in green zones, along roads and on private properties. In order to characterize the potential exposure related health effects of pesticide and their occurrence in the urban environment, 222 pesticides were screened and quantified in 228 road dust and 156 green-belt soil samples in autumn and spring from Harbin, a megacity in China, using GC-MS/MS base quantitative trace analysis. The results showed that a total of 33 pesticides were detected in road dust and green-belt soil, with the total concentrations of 650 and 236 ng/g (dry weight = dw), respectively. The concentrations of pesticides in road dust were significantly higher than that in green-belt soil. Pesticides in the environment were influenced by the seasons, with the highest concentrations of insecticides in autumn and the highest levels of herbicides in spring. In road dust, the concentrations of highways in autumn and spring (with the mean values of 94.1 and 68.2 ng/g dw) were much lower than that of the other road classes (arterial roads, sub-arterial roads and branch ways). Whereas in the green-belt soil, there was no significant difference in the concentration of pesticides between the different road classes. A first risk assessment was conducted to evaluate the potential adverse health effects of the pesticides, the results showed that the highest hazard index (HI) for a single pesticide in dust and soil was 0.12, the hazard index for children was higher than that for adults, with an overall hazard index of less than 1. Our results indicated that pesticide levels do not have a significant health impact on people.

Application of deep learning classification model for regional evaluation of roof pressure support evolution effects over time in coal mining face.

Hydraulic support leg pressure serves as a crucial indicator for assessing work face support quality. Current evaluation methods for support quality primarily concentrate on static analyses-like inadequate initial support force, pressure overrun, and uneven bracket force-while neglecting dynamic column pressure changes. This paper introduces a model for assessing hydraulic support quality using deep learning techniques. Real-time data is preprocessed into a spatio-temporal pressure sub-matrix sample, which is then inputted into the model. This process assesses the support quality type and characterizes its dynamic evolution within the area. The model facilitates the identification of dynamic support quality effects in the working face area, aiding operators in making targeted adjustments to hydraulic support status. Experimental results revealed that the optimized LeNet-5 network-adjusting parameters like convolutional layer count, kernel size, and ReLU activation function-achieved the highest classification accuracy of 85.25 % for support quality, surpassed other networks. Furthermore, the improved LeNet-5 network outperformed other networks in both F1 score and recall. Additionally, the improved LeNet-5 network achieved faster convergence to the optimal solution, accelerated training speed. This highlighted its advantages in evaluating the spatio-temporal support quality of hydraulic supports in smart mining operations.

Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.

OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who underwent radical radiotherapy using a pairwise machine learning algorithm. METHODS: The 130 datasets enrolled were randomly divided into a training set and a testing set in a 7:3 ratio. Clinical factors were included and radiomics features were extracted from pretreatment CT scans using pyradiomics-based software, and a pairwise naive Bayes (NB) model was developed. The performance of the model was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). To facilitate practical application, we attempted to construct an automated esophageal cancer diagnosis system based on trained models. RESULTS: To the follow-up date, 64 patients (49.23%) had experienced LR. Ten radiomics features and two clinical factors were selected for modeling. The model demonstrated good prediction performance, with area under the ROC curve of 0.903 (0.829-0.958) for the training cohort and 0.944 (0.849-1.000) for the testing cohort. The corresponding accuracies were 0.852 and 0.914, respectively. Calibration curves showed good agreement, and DCA curve confirmed the clinical validity of the model. The model accurately predicted LR in elderly patients, with a positive predictive value of 85.71% for the testing cohort. CONCLUSIONS: The pairwise NB model, based on pre-treatment enhanced chest CT-based radiomics and clinical factors, can accurately predict LR in elderly patients with ESCC. The esophageal cancer automated diagnostic system embedded with the pairwise NB model holds significant potential for application in clinical practice.