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Abstract Background Identification of active components of traditional Chinese Medicine (TCM) and their respective targets is important for understanding the mechanisms underlying TCM efficacy. However, there are still no effective technical methods to achieve this. Methods Herein, we have established a method for rapidly identifying targets of a specific TCM and interrogating the targets with their corresponding active components based on Isothermal Shift Assay (iTSA) and database interrogation. Results We optimized iTSA workflow and identified 110 targets for Danhong injection (DHI) which is used as an effective remedy for cardiovascular and cerebrovascular diseases. Moreover, we identified the targets of the nine major ingredients found in DHI. Database interrogation found that the potential targets for DHI, in which we verified that ADK as the target for salvianolic acid A and ALDH1B1 as the target for protocatechualdehyde in DHI, respectively. Conclusion Overall, we established a novel paradigm model for the identification of targets and their respective ingredients in DHI, which facilitates the discovery of drug candidates and targets for improving disease management and contributes to revealing the underlying mechanisms of TCM and fostering TCM development and modernization. Graphical Abstract

Abstract Urban greening is becoming an important strategy in improving urban ecosystem services and sustainability. Identifying the response of vegetation to urbanization and urban landscape patterns can help in planning for urban greening. Urbanization may lead to both direct and indirect effects on vegetation, and the indirect effects of urbanization on vegetation growth (UIE-VG) have been paid much attention recently in large scale. In this study, we investigated the spatiotemporal evolution of UIE-VG and the effects of landscape patterns on UIE-VG using the boosted regression tree model and remotely sensed data. An increase in average UIE-VG from 4 to 56% was found during urbanization of Kunming, the case study area in southwest China. However, UIE-VG exhibited high variations due to landscape pattern changes at the local scale. Overall, area-related and aggregation-related landscape metrics had greater effects on UIE-VG than the other metrics. The increase and aggregation of built-up land enhanced UIE-VG by 3.1–81.3% while the increase and aggregation of unused land and waterbodies reduced UIE-VG by 0.7–20.6%. Moreover, we found that the large and aggregated vegetation areas may mitigate the negative UIE-VG in low urbanization areas. Our findings have important implications for integrating urban landscape planning into sustainable urban greening strategies.

Soil organic matter (SOM) is critical for soil fertility, crop growth, and plays an important role in the global carbon cycle and climate change. Therefore, spatial prediction of SOM is important to rational soil resource utilization, agricultural production, and ecological environment management. However, large-area SOM mapping research heavily relies on legacy soil data, and large-scale recent SOM mapping may not be possible or have lower accuracy due to limited or less recent data availability. In this study, we aimed to improve SOM prediction and mapping accuracy by combining legacy data with limited recent data. Three models, namely, partial least squares regression (PLSR), random forest (RF), and one-dimensional convolutional neural network (1D-CNN), were applied and compared. The results showed that combining legacy and recent data effectively improved SOM prediction accuracy compared to using only recent data. Among the three modeling methods, 1D-CNN exhibited superior performance, with an averaged determination coefficient of the prediction (R2) of 0.58, a root mean square error (RMSE) of 4.56 g/kg, and a ratio of performance to interquartile distance (RPIQ) of 2.05. The predicted SOM content for both legacy (1980 s) and recent (2010 s) periods showed similar spatial distribution patterns throughout the Huanghuaihai Plain. Generally, there was a noticeable trend of increasing SOM content from northwest to southeast, with higher values observed in Jiangsu and lower values concentrated in Henan, Hebei, and Shandong regions within the study area. Over time, SOM contents in the Huanghuaihai Plain showed an increasing trend, with an average increase of 5.90 g/kg from legacy to recent period. This study provides a promising approach for improving SOM prediction and mapping accuracy at large scales, particularly when recent data availability is limited.

Abstract Sulfide solid‐state electrolytes (SSEs) with superior ionic conductivity and processability are highly promising candidates for constructing all‐solid‐state lithium metal batteries (ASSLMBs). However, their practical applications are limited by their intrinsic air instability and serious interfacial incompatibility. Herein, a novel glass‐ceramic electrolyte Li3.12P0.94Bi0.06S3.91I0.18 was synthesized by co‐doping Li3PS4 with Bi and I for high‐performance ASSLMBs. Owing to the strong Bi‒S bonds that are thermodynamically stable to water, increased unit cell volume and Li+ concentration caused by P5+ substitution with Bi3+, and the in situ formed robust solid electrolyte interphase layer LiI at lithium surface, the as‐prepared Li3.12P0.94Bi0.06S3.91I0.18 SSE achieved excellent air stability with a H2S concentration of only 0.205 cm3 g−1 (after 300 min of air exposure), outperforming Li3PS4 (0.632 cm3 g−1) and the most reported sulfide SSEs, together with high ionic conductivity of 4.05 mS cm−1. Furthermore, the Li3.12P0.94Bi0.06S3.91I0.18 effectively improved lithium metal stability. With this SSE, an ultralong cyclability of 700 h at 0.1 mA cm−2 was realized in a lithium symmetrical cell. Moreover, the Li3.12P0.94Bi0.06S3.91I0.18‐based ASSLMBs with LiNi0.8Mn0.1Co0.1O2 cathode achieved ultrastable capacity retention rate of 95.8% after 300 cycles at 0.1 C. This work provides reliable strategy for designing advanced sulfide SSEs for commercial applications in ASSLMBs.

Background The objective of this study was to compare and analyze the representative opening and closing movement of Tai Chi elastic band exercise with the reverse fly movement of elastic band resistance training. The aim was to explore the biomechanical differences between the two exercises and provide theoretical support for the application of Tai Chi elastic band exercise in health intervention. Methods A total of 26 male participants were recruited and randomly divided into two groups in a 1:1 ratio. There were 13 participants in each Tai Chi elastic band exercise group and elastic band resistance training group. Both groups of participants used an elastic band to perform movement in the experiment. Experimental data were collected using the Vicon infrared motion capture system and Delsys surface EMG system. The AnyBody software was utilized to simulate the creation of a musculoskeletal model for both exercises. Result The study found that the Tai Chi elastic band exercise group exhibited smaller horizontal abduction angle and flexion angle of the shoulder joint, as well as normalized RMS of the anterior deltoid and triceps brachii, compared to the elastic band resistance training group (P < 0.01); the Tai Chi elastic band exercise group exhibited greater elbow flexion angle, elbow flexion torque, and muscle strength of the infraspinatus, coracobrachialis, biceps brachii, brachialis and brachioradialis, compared to the elastic band resistance training group (P < 0.01); the Tai Chi elastic band exercise group exhibited smaller horizontal abduction angular velocity of the shoulder joint and a lower normalized RMS of the posterior deltoid, compared to the elastic band resistance training group (P < 0.05). Conclusion (1) The opening and closing movement of Tai Chi elastic band exercise is characterized by a large elbow flexion angle, a small shoulder joint horizontal angle and flexion angle, and a slow and uniform speed of movement. The reverse fly movement of elastic band resistance training is characterized by a large horizontal abduction angle of the shoulder joint, a large flexion angle of the shoulder joint, a small flexion angle of the elbow joint, and a fast and uneven speed. (2) The opening and closing movement exerts a greater torque on the elbow flexion, while the reverse fly movement exerts a greater torque on the shoulder joint horizontal abduction and external rotation. (3) The opening and closing movement provide greater stimulation to the infraspinatus, coracobrachialis, and elbow flexor, while the reverse fly movement provides greater stimulation to the posterior deltoid, anterior deltoid, subscapularis, and elbow extensor. In summary, the variation in joint angle, joint angular velocity, and hand position could be the factor contributing to the differences in joint torque and muscle activity between the opening and closing movement of Tai Chi elastic band exercise and the reverse fly movement of elastic band resistance training.

Soil’s pivotal role in environmental and agricultural processes underscores the importance of accurate soil property predictions for informed decisions and sustainable land management. Spectroscopic techniques, particularly mid-infrared (MIR) spectroscopy, have emerged as rapid and non-destructive tools for soil analysis. Despite advances in predicting soil properties using spectroscopy, quantifying prediction uncertainties has often been overlooked. Accurate uncertainty quantification helps risk assessment and decision-making processes. This study introduces an enhanced version of the variational inference technique to capture uncertainty when using Bayesian Convolutional Neural Networks (Bayesian CNNs). This Bayesian CNNs method was evaluated against two other methods — Bootstrapped Partial Least-Squares regression (Bootsrapped PLS) and Generalised Additive Models (GAM) for their ability to quantify uncertainty in six soil property predictions (clay, sand, silt, pH, phosphorus retention, and carbon) based on MIR spectroscopy. In terms of predictive performance and quality of prediction, our evaluation indicated that both GAMs and Bayesian CNNs outperformed PLS-BS for all six soil properties. The ability of GAMs and Bayesian CNNs to capture non-linear relationships in the data allowed for better fitting to the underlying patterns. Bayesian CNNs, in particular, demonstrated superior performance by combining accurate predictions with robust uncertainty quantification. Our results also showed that, on our dataset, bootstrapping failed to provide satisfactory prediction intervals. We suggest therefore that the evaluation of models should extend beyond standard validation metrics, which typically focuses on prediction accuracy, to include an assessment of the predicted uncertainty.

The investigation was conducted to describe the status of coverage of HBV vaccination among the health care workers in Gansu province and to explore the associated factors of HBV vaccination in this study. A cross-sectional study was conducted among 1544 health care workers from 64 hospitals in Gansu province. A self-designed questionnaire was used to interview the health care workers about HBV vaccination coverage. A multivariate logistic regression model explored the associated factors with HBV vaccination. The vaccination coverage was 89.17% for health care workers, nurses (90.40%) had the highest rate, followed by administration staff (89.38%) and medical technicians (89.30%). The full-dose HBV vaccination coverage was 64.25% for health care workers, and administration staff (65.04%) had the highest rate, followed by nurses (65.00%). This study found that the associated factors with HBV vaccination and full-dose vaccination were the history of training and the detection of serological indicators. The coverage of HBV vaccination among health care workers in Gansu province was high, but full-dose HBV vaccination coverage was low. It is necessary to strengthen the HBV knowledge and training in HBV prevention and treatment among health care workers in Gansu Province.

BackgroundCoronary heart disease (CHD) is the leading cause of death in both developed and many developing countries. Exercise training is a fundamental component of cardiac rehabilitation programs for patients with CHD. This study aims to investigate the effects of a Tai Chi rehabilitation program, which is provided through a hybrid online and offline mode, on oxidative stress and inflammatory responses in patients with CHD.MethodsA total of 34 patients with coronary heart disease were randomly assigned to two groups: an experiment group (n = 14, age 62.07 ± 9.076 years) and a control group (n = 20, age 61.90 ± 9.700 years). The experiment group underwent a 12-week Tai Chi cardiac rehabilitation program (TCCRP), while the control group followed a conventional exercise rehabilitation program (CERP) consisting of 1-h sessions, 3 times per week, for a total of 36 sessions. Participants were studied at baseline and post-intervention. The main assessments include the levels of Malondialdehyde (MDA), Superoxide dismutase (SOD), Tumor necrosis factor (TNF-α) and Interleukin-10 (IL − 10) in blood samples. Pearson correlation analysis was used, and the differences between the two groups were subsequently tested using two-way repeated ANOVA. Statistical significance was defined as a two-sided p-value of

In order to study the effect of magnesium salt (magnesium chloride hexahydrate + magnesium hydroxide) on the retarding characteristics of coal spontaneous combustion, the effects of inhibitor dosage and silane coupling agent on the characteristic temperature and thermal effect of coal spontaneous combustion were studied by synchronous thermal analysis and programmed heating-gas chromatography. The results of simultaneous thermal analysis showed that the inhibitory effect was relatively best when the magnesium salt inhibitor was added at 30%, the pyrolysis temperature T3 was delayed by 40 °C compared with the raw coal sample, and the total heat release was reduced by 165.14 J/mg. F@M30%·G resisted coal sample adding silane coupling agent mainly delayed the occurrence of coal pyrolysis and ignition, in which the pyrolysis temperature T3 was 49 °C higher than that of raw coal, and the ignition temperature T4 was increased by 26 °C. F@M30% inhibited coal samples can reduce the volume fraction of CO, and the effect of inhibiting spontaneous combustion of coal is gradually enhanced with the increase of temperature. After adding silane coupling agent, the volume fraction of CO of inhibited coal samples can be reduced by about 4×10-6. The inhibition rate of F@M30% inhibited coal samples is 30.87%, and that of F@M30%•G inhibited coal samples is as high as 91.57%.

ABSTRACTThe bacterial communities of Zaopocu (ZPC), a tropical specialty fermented food in Hainan Island, were characterized in this study using high-throughput sequencing. Firmicutes and Proteobacteria were the two dominant phyla. The primary genus in ZPC_A was Weissella, while ZPC_B and ZPC_C had Lactobacillus as the dominant genus. The biomarker lactic acid bacteria (LAB) in ZPC_A were Lactobacillus brevis, Weissella confusa, and Leuconostoc citreum, whereas Lactobacillus amylolyticus and Lactobacillus helveticus were significantly higher in ZPC_B. In contrast, Lactobacillus pontis and Lactobacillus fermentum were the core LAB in ZPC_C. ZPC_A has the highest value of titratable acid (TA), amino acid, and lactic acid. TA had the most powerful influence on the structure of the bacterial communities, whereas salinity had a negligible effect. It is worth noting that ZPC may also faces food safety issue because opportunistic pathogenic bacteria like Stenotrophomonas and genes closely associated with Staphylococcus aureus infection were highly detected.

Abstract Objective To investigate the CBCT findings of the apical anatomy of immature maxillary central incisors. Methods CBCT images of 100 immature maxillary central incisors in Nolla 8 and 100 immature maxillary central incisors in Nolla 9 were collected. The mesiodistal and carniocaudal diameters of the apical foramen of immature maxillary central incisors were measured by software included with CBCT, as well as the mesiodistal, carniocaudal and facioligual diameters of the apical shadow. The apical shadow and apical foramen diameters were compared between Nolla 8 and Nolla 9. Data were analyzed using the MedCalc software package. Results For immature maxillary central incisors, the mesiodistal and facioligual diameters of the apical foramen were 2.75±0.68 mm and 3.28±0.74 mm in Nolla 8 and 1.50±0.51 mm and 1.92±0.79 mm in Nolla 9. The mesiodistal, facioligual and carniocaudal diameters of the apical shadow were 3.84±0.73 mm, 4.49±0.68 mm and 3.41±1.27 mm in Nolla 8 and 2.76±0.60 mm, 3.41±0.80 mm and 2.06±0.65 mm in Nolla 9, respectively. Conclusions The immature maxillary central incisors in Nolla 8 have a larger apical shadow and apical foramen than those in Nolla 9. The apical region of the maxillary central incisors in Nolla 8 was more likely to have a broad, blurred lamina dura. With the development of the apical foramen, the lamina dura in the apical region tended to be clear and sharp. Clinical significance To our knowledge, this is the first study to radiologically analyse the in vivo anatomy of the apical foramen and apical shadow of immature maxillary central incisors. The results of this study provide a more detailed understanding of the apical anatomy of the immature maxillary central incisor for the diagnosis and treatment of apical lesions.

Over the past few decades, advances in immunological knowledge have led to the identification of novel immune checkpoints, reinvigorating cancer immunotherapy. Immunotherapy, represented by immune checkpoint inhibitors, has become the leader in the precision treatment of cancer, bringing a new dawn to the treatment of most cancer patients. Galectin-9 (LGALS9), a member of the galectin family, is a widely expressed protein involved in immune regulation and tumor pathogenesis, and affects the prognosis of various types of cancer. Galectin-9 regulates immune homeostasis and tumor cell survival through its interaction with its receptor Tim-3. In the review, based on a brief description of the signaling mechanisms and immunomodulatory activities of galectin-9 and Tim-3, we summarize the targeted expression patterns of galectin-9 in a variety of malignancies and the promising mechanisms of anti-galectin-9 therapy in stimulating anti-tumor immune responses.

Flash drought (FD) has attracted much attention due to its severe stress on vegetation ecosystems. Yet to date, the impacts of FD on vegetation ecosystems in different regions have not been fully evaluated and explored, especially for ecologically fragile areas. In this study, we identified the FD events in the Loess Plateau from 2000 to 2023 based on the attenuation rate in soil moisture percentile over time. The evolution process of FD, the driving roles of meteorological conditions and the responses of different vegetation types to FD were explored by vegetation indicators such as solar-induced chlorophyll fluorescence (SIF), SIFyield, SIF-RCI, etc. The results showed that FD events were predominantly concentrated in wetter areas with dense vegetation, with the highest frequency being 29. Meteorological factors contributed differently to the occurrence and development of FD. The responses of vegetation to FD were not only related to vegetation types (cropland was more sensitive to FD than forest and grassland) but were also significantly influenced by background climate. The SIFyield anomaly of vegetation was more sensitive than SIF anomaly and SIF-RCI. The results advance our understanding of the formation mechanisms of FD and facilitate the exploration of vegetative photosynthetic responses to FD.

As an environmentally friendly material, biochar is increasingly being utilized in the field of heat transfer and thermal conduction. In this study, nano-biochar was prepared from high-pressure homogenization (HPH) using sesame stalks as the raw material. It was incorporated into ethylene glycol (EG) and its dispersion stability, viscosity, and thermal conductivity were investigated. The nano-biochar was stably dispersed in EG for 28 days. When the concentration of the nano-biochar added to EG was less than 1%, the impact on viscosity was negligible. The addition of 5 wt.% nano-biochar to EG improved the thermal conductivity by 6.72%, which could be attributed to the graphitized structure and Brownian motion of the nano-biochar. Overall, nano-biochar has the potential to be applied in automotive thermal management.

Metastatic triple-negative breast cancer (mTNBC) has the worst prognosis among breast cancer subtypes. Immune checkpoint inhibitors (ICIs) plus chemotherapy have promising survival benefits. Herein, we report a 51-year-old woman whose metastatic lesions were diagnosed as triple-negative subtype and who received tislelizumab plus eribulin treatment and achieved excellent efficacy. To our knowledge, this study is the first attempt to present tislelizumab in combination with eribulin for mTNBC treatment. New treatments resulting in prolonged survival and durable clinical responses would benefit mTNBC patients. Then, we summarize the possible influencing factors of the interaction between tislelizumab and eribulin.

DNA synthesis and assembly primarily revolve around the innovation and refinement of tools that facilitate the creation of specific genes and the manipulation of entire genomes. This multifaceted process encompasses two fundamental steps: the synthesis of lengthy oligonucleotides and the seamless assembly of numerous DNA fragments. With the advent of automated pipetting workstations and integrated experimental equipment, a substantial portion of repetitive tasks in the field of synthetic biology can now be efficiently accomplished through integrated liquid handling workstations. This not only reduces the need for manual labor but also enhances overall efficiency. This review explores the ongoing advancements in the oligonucleotide synthesis platform, automated DNA assembly techniques, and biofoundries. The development of accurate and high-throughput DNA synthesis and assembly technologies presents both challenges and opportunities.

In recent years, millimeter-wave radar has been widely used in safety detection, nondestructive detection of parts, and medical diagnosis because of its strong penetration ability, small size, and high detection accuracy. However, due to the limitation of hardware transmission bandwidth, achieving ultra-high two-dimensional resolution using millimeter-wave radar is challenging. Two-dimensional high-resolution imaging of altitude and azimuth can be realized using radar platform scanning to form a two-dimensional aperture. However, during the scanning process, the millimeter-wave radar produces sparse tracks in the height dimension, resulting in a sparse sampling of the altitude echo, thus reducing the imaging quality. In this paper, a high-resolution three-dimensional imaging algorithm for millimeter-wave radar based on Hankel transformation matrix filling is proposed to solve this problem. The matrix filling algorithm restores the sparse sampling echo, which guarantees the imaging accuracy of the millimeter-wave radar in the scanning plane. First, the low-rank prior characteristics of the millimeter-wave radar's elevation-range section were analyzed. To solve the problem of missing whole rows and columns of data during sparse trajectory sampling, the echo data matrix was reconstructed using the Hankel transform, and the sparse low-rank prior characteristics of the constructed matrix were analyzed. Furthermore, a matrix filling algorithm based on truncated Schatten-p norm combining low-rank and sparse priors was proposed to fill and reconstruct the echoes to ensure the three-dimensional resolution of the sparse trajectory millimeter-wave radar. Finally, using simulation and several sets of measured data, the proposed method was proved to achieve high-resolution three-dimensional imaging even when only 20%–30% of the height echo was used.

Abstract Interlayer decoupling plays an essential role in realizing unprecedented properties in atomically thin materials, but it remains relatively unexplored in the bulk. It is unclear how to realize a large crystal that behaves as its monolayer counterpart by artificial manipulation. Here, we construct a superlattice consisting of alternating layers of NbSe2 and highly porous hydroxide, as a proof of principle for realizing interlayer decoupling in bulk materials. In (NaOH)0.5NbSe2, the electric decoupling is manifested by an ideal 1D insulating state along the interlayer direction. Vibration decoupling is demonstrated through the absence of interlayer models in the Raman spectrum, dominant local modes in heat capacity, low interlayer coupling energy and out-of-plane thermal conductivity (0.28 W/mK at RT) that are reduced to a few percent of NbSe2’s. Consequently, a drastic enhancement of CDW transition temperature (>110 K) and Pauling-breaking 2D superconductivity is observed, suggesting that the bulk crystal behaves similarly to an exfoliated NbSe2 monolayer. Our findings provide a route to achieve intrinsic 2D properties on a large-scale without exfoliation.

Introduction: Currently, revealing how to prevent and control hyperuricemia has become an essential public health issue. Sulforaphane has a wide range of applications in the management of hyperuricemia. Objective: The study objective was to verify the uric acid-lowering effects and the regulation of the gut-kidney axis mediated by sulforaphane and identify host-microbial co-metabolites in hyperuricemia. Methods: A hyperuricemia model was established by administering feedstuffs with 4% potassium oxonate and 20% yeast. Forty male Sprague–Dawley rats were randomly divided into the normal control, hyperuricemia, allopurinol, and sulforaphane groups. Animals were treated by oral gavage for six consecutive weeks, and then phenotypic parameters, metabolomic profiling, and metagenomic sequencing were performed. Results: Sulforaphane could lower uric acid by decreasing urate synthesis and increasing renal urate excretion in hyperuricemic rats (P＜0.05). We identified succinic acid and oxoglutaric acid as critical host-gut microbiome co-metabolites. Moreover, sulforaphane improved the diversity of microbial ecosystems and functions, as well as metabolic control of the kidney. Notably, sulforaphane exerted its renoprotective effect through epigenetic modification of Nrf2 and interaction between gut microbiota and epigenetic modification in hyperuricemic rats. Conclusion: We revealed that sulforaphane could ameliorate the progression of hyperuricemia by reprogramming the gut microbiome and metabolome. Our findings may provide a good means for efficiently preventing and treating hyperuricemia.

Graphene and related two-dimensional materials have attracted great research interests due to prominently optical and electrical properties and flexibility in integration with versatile photonic structures. Here, we report an in-fiber photoelectric device by wrapping a few-layer graphene and bonding a pair of electrodes onto a tilted fiber Bragg grating (TFBG) for photoelectric and electric-induced thermo-optic conversions. The transmitted spectrum from this device consists of a dense comb of narrowband resonances that provides an observable window to sense the photocurrent and the electrical injection in the graphene layer. The device has a wavelength-sensitive photoresponse with responsivity up to 11.4 A/W, allowing the spectrum analysis by real-time monitoring of photocurrent evolution. Based on the thermal-optic effect of electrical injection, the graphene layer is energized to produce a global red-shift of the transmission spectrum of the TFBG, with a high sensitivity approaching 2.167×104 nm/A2. The in-fiber photoelectric device, therefore as a powerful tool, could be widely available as off-the-shelf product for photodetection, spectrometer and current sensor.

The conversion-efficiency for second-harmonic (SH) in optical fibers is significantly limited by extremely weak second-order nonlinearity of fused silica, and pulse pump lasers with high peak power are widely employed. Here, we propose a simple strategy to efficiently realize the broadband and continuous wave (CW) pumped SH, by transferring a crystalline GaSe coating onto a microfiber with phase-matching diameter. In the experiment, high efficiency up to 0.08 %W-1mm-1 is reached for a C-band pump laser. The high enough efficiency not only guarantees SH at a single frequency pumped by a CW laser, but also multi-frequencies mixing supported by three CW light sources. Moreover, broadband SH spectrum is also achieved under the pump of a superluminescent light-emitting diode source with a 79.3 nm bandwidth. The proposed scheme provides a beneficial method to the enhancement of various nonlinear parameter processes, development of quasi-monochromatic or broadband CW light sources at new wavelength regions.

Background: According to statistics, about one-fifth of the world's elderly people suffer from sleep disorders, and the problem of sleep disorders in the elderly is extremely serious, and this problem is one of the important causes of chronic diseases such as hypertension, hyperlipidemia, diabetes mellitus, and coronary heart disease in the elderly. The positive effect of Tai Chi exercise therapy on sleep problems has been confirmed, but at present, the effect of the specific duration of Tai Chi exercise on the improvement of elderly people with moderate to severe sleep disorders varies. Objective: META analysis was used to investigate and find that long-term Tai Chi exercise therapy has the best effect on improving sleep in elderly patients with moderate to severe sleep disorders. Methods: META analysis was performed using Revman 5.3 after searching Web of science, Pubmed, Scopus, The Cochroae Library, OVID, CBM, CNKI, VIP, and other databases, and then filtering and extracting. Results: A total of seven papers were included. Meta-analysis showed that tai chi exercise was more effective in improving sleep problems in elderly patients with sleep disorders compared to the control group, and the difference was significant. This was demonstrated by a decrease in the global Pittsburgh Sleep Quality Index (PSQI) score [SMD = −0.66, 95 % CI (−0.91, −0.41), P

Utilizing MgO as the precursor and deionized water as the solvent, this study synthesized nanoparticles of Mg(OH)2 via hydrothermal methods, aiming to control its purity, particle size, and morphology by understanding its growth under non-uniform nucleation. Characterization of crystal morphology and structure was conducted through scanning electron microscopy and X-ray diffraction, while laser particle size detection assessed the secondary particle size distribution. The study focused on how MgO’s hydrothermal process conditions influence Mg(OH)2 crystal growth, particularly through ion concentration and release rate adjustments to direct crystal growth facets. These adjustments shifted the dominant growth plane, enhancing the peak intensity ratio I001/I101 from 1.03 to 2.14, thereby reducing surface polarity and secondary aggregation of crystals. The study of the physicochemical properties of the same sample at different times revealed the pattern of crystal dissolution and recrystallization. A 2 h hydrothermal reaction notably altered the particle size distribution, with a decrease in particles sized 0.2~0.4 μm and an increase in those sized 0.4~0.6 μm, alongside new particles over 1 μm, indicating a shift toward uniformity through dissolution and recrystallization. Optimal conditions (6% magnesium oxide concentration, 160 °C, 2 h) led to the synthesis of highly dispersed, uniformly sized magnesium hydroxide, showcasing a simple, eco-friendly, and high-yield process.

Soil health has gained increasing attention under the rapid development of industrialization and the requirement for green agriculture. Therefore, up-to-date soil information related to soil health is urgently needed to ensure food security and biodiversity protection. Previous studies have shown the potential of proximal soil sensing in measuring soil information, while it remains challenging to get cost-efficient and robust estimates of multiple soil health indicators simultaneously via sensor fusion. In this study, we investigated the potential of visible near-infrared (vis-NIR), and mid-infrared (MIR) spectroscopy as well as three model averaging methods in predicting three soil health properties, including soil organic matter (SOM), pH, cation exchange capacity (CEC). The model averaging methods are not only used for model fusion but also for high-level sensor fusion, which include Granger-Ramanathan (GR), Bayesian Model Averaging and Spectral-Guided Ensemble Modelling (S-GEM). Here, S-GEM is a recently proposed algorithm that can improve soil spectroscopic prediction by including spectral information in ensemble modelling. Four widely used prediction models were evaluated, including partial least square regression, Cubist, memory based learning and convolutional neural network. For SOM, sensor fusion based on model averaging algorithms was comparable to that of Sensorsingle + Modelmultiple (MIR singly based on S-GEM) with R2 of 0.86. However, MIR only with S-GEM performed the best among all methods (LCCC of 0.92, RMSE of 3.66 g kg−1 and RPIQ of 3.68). The 10-fold cross-validation results indicated that Sensorsingle + Modelmultiple (MIR singly based on S-GEM) performed best among all methods for pH, with R2 of 0.84, LCCC of 0.90, RMSE of 0.45 and RPIQ of 3.65. For CEC, Sensormultiple + Modelmultiple based on GR performed best with R2 of 0.66, LCCC of 0.80, RMSE of 3.48 cmol + kg−1 and RPIQ was 2.22. Our results also showed that sensor fusion failed to improve spectral prediction of soil information when the performance among sensors differed a lot (△R2 > 0.2), and the use of a single best sensor is therefore suggested in this case. When the sensors have a close model performance (△R2

The application of visible and near-infrared (vis-NIR) spectroscopy for predicting soil properties presents a cost-effective and time-efficient approach for evaluating various soil properties. However, the accuracy of these predictions can be adversely affected by soil moisture. Consequently, previous research focused on removing moisture effects from the spectra, resulting in the loss of valuable information on soil moisture. In this study, we propose a novel approach to directly predict both soil moisture and a range of soil properties using vis-NIR spectra. To achieve this, we employed the fractional-order derivative (FOD) technique in combination with a one-dimensional convolutional neural network (1D-CNN) to mitigate the influence of soil moisture and enhance the prediction accuracy of soil properties. We calibrated 1D-CNN, partial least squares regression (PLSR) and support vector machine (SVM) models using FOD spectra with various orders (ranging from 0 to 2 with 0.1 intervals). The results demonstrated that the FOD spectra consistently outperformed the original and integer-order differential spectra. Moreover, the 1D-CNN models exhibited superior performance compared to PLSR and SVM models in predicting soil moisture content (SMC), soil organic matter (SOM), sand, silt, clay, and iron contents. However, it is challenging to predict all six soil properties using a single 1D-CNN model with spectra of a single FOD order. Our findings identified the optimal FOD order for different soil properties. Specifically, a FOD order of 0.5 yielded the best results for predicting SMC and SOM, while an order of 0.7 was optimal for iron oxides, clay, silt, and sand contents. Consequently, we propose the combined use of FOD and 1D-CNN to estimate multiple soil properties simultaneously.

Abstract Background Aggressive B-cell non-Hodgkin’s lymphoma (B-NHL) patients often develop drug resistance and tumor recurrence after conventional immunochemotherapy, for which new treatments are needed. Methods We investigated the antitumor effects of CBL0137. In vitro, cell proliferation was assessed by CCK-8 and colony formation assay. Flow cytometry was performed to analyze cell cycle progression, apoptosis, mitochondrial depolarization, and reactive oxygen species (ROS) production. Autophagy was detected by transmission electron microscopy and mGFP-RFP-LC3 assay, while western blotting was employed to detect proteins involved in apoptosis and autophagy. RNA-sequencing was conducted to analyze the transcription perturbation after CBL0137 treatment in B-NHL cell lines. Finally, the efficacy and safety of CBL0137, rituximab, and their combination were tested in vivo. Results CBL0137, a small molecule anticancer agent that has significant antitumor effects in B-NHL. CBL0137 sequesters the FACT (facilitates chromatin transcription) complex from chromatin to produce cytotoxic effects in B-NHL cells. In addition, we discovered novel anticancer mechanisms of CBL0137. CBL0137 inhibited human B-NHL cell proliferation by inducing cell cycle arrest in S phase via the c-MYC/p53/p21 pathway. Furthermore, CBL0137 triggers ROS generation and induces apoptosis and autophagy in B-NHL cells through the ROS-mediated PI3K/Akt/mTOR and MAPK signaling pathways. Notably, a combination of CBL0137 and rituximab significantly suppressed B-NHL tumor growth in subcutaneous models, consistent with results at the cellular level in vitro. Conclusions CBL0137 has potential as a novel approach for aggressive B-NHL, and its combination with rituximab can provide new therapeutic options for patients with aggressive B-NHL. Video Abstract

In this investigation, a series of Na _0.5 Bi _0.47 Sr _0.02 TiO _3- _δ samples, sintered from 1000 to 1100 °C, were synthesized utilizing the solid-state method. The XRD results indicate that all samples exhibit a perovskite phase, with the exception of those sintered at 1100 °C, which display no discernible impurity peaks. The SEM results indicate that the average grain size exhibits an increase proportionate to the sintering temperature, which attributes to the variations in the actual Na/Bi ratio. From the study of grain conductivity we can obtain that the dominant factor affecting grain conductivity is the activation energy. At 1100 °C, the oxygen vacancy concentration emerges as the primary determinant of grain conductivity. It should be noticed that the phase transition temperature of the sample increases (350 °C→400 °C) with the increase of sintering temperature, which is due to the local A-site disorder aggravated by high temperature sintering. Therefore, reducing the sintering temperature is beneficial to improve the grain conductivity. The grain boundary conductivity initially rises, then diminishes with increasing sintering temperature. It is evident that the enhanced macroscopic grain boundary conductivity stems from a marked reduction in space charge potential within the 1000–1025 °C temperature range. Within the 1050 °C−1100 °C temperature range, the space charge potential barely changed, the significant decrease of intrinsic grain boundary conductivity can be attributed to the surge in the coverage ratio of grain boundary impurities and the number of grain boundary impurities increased caused by the rapid reduction of grain boundary area and thermal evaporation. The research on electrical performance of NBT-based oxygen-ion conductors will promote the application of NBT-based oxygen ion conductors in solid oxide fuel cells, oxygen sensors and other fields.

As the main expenditure item in water balance, evapotranspiration has an important impact on the surface ecosystem. Assessing the impact of changes in meteorological elements on evapotranspiration is essential to identify the spatiotemporal heterogeneity of hydrographic responses to climate changes. Based on the actual evapotranspiration (ETa) product (GPR-ET) generated by Gaussian process regression (GPR), as well as temperature and precipitation datasets, our study employed various statistical analysis methods, including geographic detector, the center of gravity migration model, spatial variation coefficients, and partial differential models, to investigate the spatiotemporal variation in ETa in China from 2000 to 2018. The analysis covered future trends in ETa changes and the contribution of meteorological factors. Our results showed that the ETa in northwest China had stronger spatial heterogeneity and the mean value was generally lower than that in the southeast. But the center of gravity of ETa was shifting towards the northwest. In most areas, the future trend was expected to be inconsistent with the current stage. ETa in the regions of north and west was mainly driven by precipitation, while its increase in southeast China was largely attributed to temperature. In addition to spatial variations, the joint enhancement effect of temperature and precipitation on ETa exists. According to the contribution analysis, precipitation contributed more to the change in ETa than temperature. These findings have enhanced our comprehension of the contribution of climate variability to ETa changes, providing scientific proof for the optimization apportion of future water resources.

Abstract The aim was to analyze the clinical characteristics of adverse drug reactions (ADRs) induced by Osimertinib and their effects on the prognosis, so as to further provide reference for clinical medication. This was a retrospective study, and 66 nonsmall cell lung cancer (NSCLC) patients who had ADR in the 2nd‐line treatment with Osimertinib from January 2017 to December 2018 were included. Clinical characteristics and survival in subgroups of Osimertinib‐related ADRs were analyzed. The majority of patients who developed ADRs after the 2nd‐line treatment of Osimertinib were mainly middle‐aged and elderly women. Osimertinib‐related ADRs were mainly found in the skin, respiratory and digestive systems. The most common ADRs were rash (69.70%), diarrhea (66.67%), stomatitis (54.55%), and fatigue (51.52%). The degree of Osimertinib‐related ADRs was tolerable. Only seven patients experienced grade 3 ADRs, all of which involved the skin system. Exactly 92.42% of patients had more than two adverse reactions. The median PFS was influenced by the type, quantity, and severity of Osimertinib‐related ADRs. Osimertinib‐related ADRs are closely related to the prognosis of patients so that more attention should be paid to monitoring the occurrence of ADRs in clinical use of Osimertinib, especially ADRs in the skin, respiratory system and digestive system.

Metal beneficiation activities may cause soil pollution in the surrounding cropland, making it crucial to conduct heavy metal pollution assessment and source analysis of the cultivated land in mining areas for the protection of the ecological environment and human health. In this study, a total of 205 surface soil samples (0–20 cm) were collected on site from the Tianheba cropland near the lead–zinc concentrator in Xieping Village, Huixian County, Gansu Province, China; their pH values and their SOM, Zn, As, Cd, Cr, Hg, and Pb contents were determined. Based on the data, we used the Kriging spatial interpolation, the Nemero index, the index of geoaccumulation, and the PMF model to analyze the characteristics of the spatial distribution of soil heavy metals in the region, the degree of contamination, the sources, and the contribution rate. The results indicated that the heavy metals with contamination levels in the Tianheba cropland were Cd, Zn, Pb, Hg, As, and Cr in descending order, with the average concentrations of Cd (0.39 mg/kg), Zn (122 mg/kg), Pb (30.4 mg/kg), and Hg (0.07 mg/kg) being significantly higher than the background values of the Gansu soils. The soil in the region as a whole was heavily polluted; it was heavily polluted with Cd, moderately polluted with Zn, and mildly polluted with Pb. Hg had a larger value in the index of geoaccumulation. By analyzing the spatial distribution and sources of the soil metals, it was found that the cropland contaminated with heavy metals in Tianheba was distributed around the mineral processing plant and the infiltration area of the canal. The PMF model revealed three pollution sources: the industrial source related to mining activities, the fertilizer application source, and the natural source. This study provides a scientific basis for the precise management of heavy metal pollution in the area.

Objective: For several years, computer technology has been utilized to diagnose lung nodules. When compared to traditional machine learning methods for image processing, deep-learning methods can improve the accuracy of lung nodule diagnosis by avoiding the laborious pre-processing step of the picture (extraction of fake features, etc.). Our goal is to investigate how well deep-learning approaches classify lung nodule malignancy. Method: We evaluated the performance of deep-learning methods on lung nodule malignancy classification via a systematic literature search. We conducted searches for appropriate articles in the PubMed and ISI Web of Science databases and chose those that employed deep learning to classify or predict lung nodule malignancy for our investigation. The figures were plotted, and the data were extracted using SAS version 9.4 and Microsoft Excel 2010, respectively. Results: Sixteen studies that met the criteria were included in this study. The articles classified or predicted pulmonary nodule malignancy using classification and summarization, using convolutional neural network (CNN), autoencoder (AE), and deep belief network (DBN). The AUC of deep-learning models is typically greater than 90% in articles. It demonstrated that deep learning performed well in the diagnosis and forecasting of lung nodules. Conclusion: It is a thorough analysis of the most recent advancements in lung nodule deep-learning technologies. The advancement of image processing techniques, traditional machine learning techniques, deep-learning techniques, and other techniques have all been applied to the technology for pulmonary nodule diagnosis. Although the deep-learning model has demonstrated distinct advantages in the detection of pulmonary nodules, it also carries significant drawbacks that warrant additional research.

Cattle behavior classification technology holds a crucial position within the realm of smart cattle farming. Addressing the requisites of cattle behavior classification in the agricultural sector, this paper presents a novel cattle behavior classification network tailored for intricate environments. This network amalgamates the capabilities of CNN and Bi-LSTM. Initially, a data collection method is devised within an authentic farm setting, followed by the delineation of eight fundamental cattle behaviors. The foundational step involves utilizing VGG16 as the cornerstone of the CNN network, thereby extracting spatial feature vectors from each video data sequence. Subsequently, these features are channeled into a Bi-LSTM classification model, adept at unearthing semantic insights from temporal data in both directions. This process ensures precise recognition and categorization of cattle behaviors. To validate the model’s efficacy, ablation experiments, generalization effect assessments, and comparative analyses under consistent experimental conditions are performed. These investigations, involving module replacements within the classification model and comprehensive analysis of ablation experiments, affirm the model’s effectiveness. The self-constructed dataset about cattle is subjected to evaluation using cross-entropy loss, assessing the model’s generalization efficacy across diverse subjects and viewing perspectives. Classification performance accuracy is quantified through the application of a confusion matrix. Furthermore, a set of comparison experiments is conducted, involving three pertinent deep learning models: MASK-RCNN, CNN-LSTM, and EfficientNet-LSTM. The outcomes of these experiments unequivocally substantiate the superiority of the proposed model. Empirical results underscore the CNN-Bi-LSTM model’s commendable performance metrics: achieving 94.3% accuracy, 94.2% precision, and 93.4% recall while navigating challenges such as varying light conditions, occlusions, and environmental influences. The objective of this study is to employ a fusion of CNN and Bi-LSTM to autonomously extract features from multimodal data, thereby addressing the challenge of classifying cattle behaviors within intricate scenes. By surpassing the constraints imposed by conventional methodologies and the analysis of single-sensor data, this approach seeks to enhance the precision and generalizability of cattle behavior classification. The consequential practical, economic, and societal implications for the agricultural sector are of considerable significance.

Abstract Polycyclic aromatic hydrocarbons (PAHs) are continuously released from multiple sources and are prone to long‐range transport. Little is known regarding their presence, transport and fate in remote and deep oceans. Polyethylene passive samplers were hence deployed at deep moorings and surface seawater in the Fram Strait and Canadian Archipelago, as well as in air and surface water of the lower Great Lakes, a potential high‐emission region, to understand the transport of PAHs to the Arctic. Dissolved PAHs showed significantly higher concentrations in the lower Great Lakes than those in the high Arctic. Concentrations of dissolved PAHs (Σ19PAHs) ranged from 33 to 300 pg/L in the Fram Strait; the vertical profiles generally exhibited a decreasing trend toward deep waters, which was potentially influenced by hydrological and biogeochemical processes. PAHs were exported from the Arctic Ocean to the North Atlantic through the Fram Strait and the Davis Strait.

As a typical voltage source converter topology, Modular multilevel converter (MMC) widespread used in high voltage direct current (MMC-HVDC) power systems due to its modularization, low harmonic, easy expansion, and high efficiency. The failure of SMs will cause inhibit circulating current growth and unbalanced system voltage. Therefore, the handling of faulty SM has an utmost significance for MMC-HVDC. This paper proposes a hybrid control method of redundant SMs with semi-hot and cold standby redundant SM control methods. In normal operation, some redundant SMs are pre-charged to become semi-hot standby SMs. When the SM fails, one semi-hot standby SM is charged to become a working SM, and one cold standby SM is charged to become a semi-hot standby SM. In this paper, the proposed method is verified by simulation. The simulation shows two working states of MMC-HVDC, one is the voltage balance control of semi-hot standby SM in the normal working condition, another is the SM failure and redundant SM insertion control. Compared to using only one SM strategy, the implementation of the hybrid redundant strategy is easier and the loss is also lower.

Proteins post-translational modification (PTMs) is necessary in the whole life process of organisms. Among them, lysine 2-hydroxyisobutyrylation (Khib) plays an important role in protein synthesis, transcriptional regulation, and cell metabolism. Khib is a newly identified PTM in several plant species. However, the function of Khib in maize was unclear. In this study, western blotting results showed that Khib modification level increased significantly after Fusarium graminearum infection, and 2,066 Khib modified sites on 728 proteins were identified in maize, among which 24 Khib sites occurred on core histones. Subcellular localization results showed that these Khib modified proteins were localized in cytoplasm, chloroplast, and nucleus. Then, comparative proteomic analysis of the defense response to F. graminearum infection showed that Khib modification participated in plant resistance to pathogen infection by regulating glycolysis, TCA cycle, protein synthesis, peroxisome, and secondary metabolic processes, such as benzoxazinoid biosynthesis, phenylpropanoid biosynthesis, jasmonic acid synthesis, and tyrosine and tryptophan biosynthesis. In addition, we also demonstrated that lysine 2-hydroxyisobutyrylation sites on histones were involved in the gene expression of pathogenesis-related proteins. Our results provide a new perspective for the study of plant disease resistance, and had directive significance of maize disease resistance for molecular breeding.

The existing distribution system planning methods do not fully consider improving power supply capacity and reliability through the coordination of multiple planning factors, and they are not comprehensive enough in quantifying planning risks. Therefore, this paper proposes a collaborative planning method for sources and networks that considers risk measurement. A multi-layer planning model is first constructed that includes a grid planning layer, a power planning layer, a switch planning layer, and an operation optimization layer. In the model, a risk measurement method combining opportunity constraints and conditional value-at-risk objectives is used to comprehensively assess the risk of the node voltage and branch current exceeding the limit caused by load uncertainty. Then, a solution strategy based on a genetic algorithm and a sparrow search algorithm is proposed to coordinate the contradiction between the solution time and the accuracy of the multi-layer model. Finally, taking a planned area to be expanded as an example, the results show that compared to the existing collaborative planning methods for sources and networks, the proposed method in this paper reduces the planning risks caused by load uncertainty by more than 50% and increases the annual net income of the power distribution company and the DG operators by RMB 1.5 million and RMB 1.1 million, respectively.

The cucurbit vegetable chieh-qua (Benincasa hispida var. chieh-qua How) is an important crop in South China and southeast Asian countries. Viral diseases cause substantial loss of chieh-qua yield. To identify the viruses that affect chieh-qua in China, ribosomal RNA-depleted total RNA sequencing was performed using chieh-qua leaf samples with typical viral symptoms. The virome of chieh-qua comprises four known viruses (melon yellow spot virus (MYSV), cucurbit chlorotic yellows virus (CCYV), papaya ringspot virus (PRSV) and watermelon silver mottle virus (WSMoV) and two novel viruses: cucurbit chlorotic virus (CuCV) in the genus Crinivirus and chieh-qua endornavirus (CqEV) in the genus Alphaendornavirus. The complete genomes of the two novel viruses in chieh-qua and three other isolates of CuCV in pumpkin, watermelon and cucumber were determined and the recombination signals of pumpkin and watermelon isolates of CuCV were detected. A reverse transcriptase PCR indicated that the dominant viruses of chieh-qua in Hainan are MYSV (66.67%) and CCYV (55.56%), followed by CuCV (27.41%), WSMoV (7.41%), cucumber mosaic virus (8.15%), zucchini yellow mosaic virus (6.67%), PRSV (6.67%) and CqEV (35.56%). Our findings support diagnostic and prevalence studies of viruses infecting chieh-qua in China, enabling sustainable control strategies for cucurbit viruses worldwide.

Abstract Plants are colonized by diverse fungal and viral communities that influence their growth and survival as well as ecosystem functioning. Viruses interact with both plants and the fungi they host. Our understanding of plant–fungi–virus interactions is very limited, especially in wild plants. Combining metagenomic and culturomic approaches, we assessed the richness, diversity, and composition of leaf‐associated fungal and viral communities from pools of herbaceous wild plants representative of four sites corresponding to cultivated or natural ecosystems. We identified 161 fungal families and 18 viral families comprising 249 RNA‐dependent RNA polymerase‐based operational taxonomic units (RdRp OTUs) from leaves. Fungal culturomics captured 12.3% of the fungal diversity recovered with metagenomic approaches and, unexpectedly, retrieved viral OTUs that were almost entirely different from those recovered by leaf metagenomics. Ecosystem management had a significant influence on both leaf mycobiome and virome, with a higher fungal community richness in natural ecosystems and a higher viral family richness in cultivated ecosystems, suggesting that leaf‐associated fungal and viral communities are under the influence of different ecological drivers. Both the leaf‐associated fungal and viral community compositions showed a strong site‐specificity. Further research is needed to confirm these trends and unravel the factors structuring plant–fungi–virus interactions in wild plant populations.

This article describes the research agenda for the Visual Analytics and Data Exploration Research (VADER) Lab at Arizona State University. Over the past decade, the VADER Lab has focused on creating novel algorithms, tools and visualizations for spatiotemporal data. This article will highlight past success in spatiotemporal analysis, explainable AI, graph mining, and mathematical topology. While, at first, these topics seem largely disjoint, we will describe how the underpinnings of spatiotemporal analysis has informed the various research directions in the VADER Lab, and how this research agenda has served to form a network of strong international collaborations. Finally, we will outline a vision for the Lab’s future research.

Long-distance extracellular electron transfer has been observed in Gram-negative bacteria. Here, Yang et al. show that a filamentous, unicellular Gram-positive bacterium is capable of bidirectional extracellular electron transfer, and forms centimetre-range conductive networks consisting of 1mm-long cells and conductive appendages.

Micellar-nanocarrier-based drug delivery systems possessing characteristics such as an excellent circulation stability, inhibited premature release and on-demand site-specific release are urgently needed for enhanced therapeutic efficacy. Therefore, a novel kind of shell-sheddable core-crosslinked polymeric micelles with pH and oxidation dual-triggered on-demand drug release behavior was facilely constructed. The multifunctional micelles were self-assembled from a carefully designed amphiphilic triblock PEGylated polyurethane (PEG-acetal-PUBr-acetal-PEG) employing an acid-labile acetal linker at the hydrophilic–hydrophobic interface and pendant reactive bromo-containing polyurethane (PU) as the hydrophobic block, followed by a post-crosslinking via oxidation-cleavable diselenide linkages. These well-defined micelles exhibited an enhanced structural stability against dilution, achieved through the incorporation of diselenide crosslinkers. As expected, they were found to possess dual pH- and oxidation-responsive dissociation behaviors when exposure to acid pH (~5.0) and 50 mM H2O2 conditions, as evidenced using dynamic light-scattering (DLS) and atomic force microscopy (AFM) analyses. An in vitro drug release investigation showed that the drug indomethacin (IND) could be efficiently encapsulated in the micelles, which demonstrated an inhibited premature release compared to the non-crosslinked ones. It is noteworthy that the resulting micelles could efficiently release entrapped drugs at a fast rate in response to either pH or oxidation stimuli. Moreover, the release could be significantly accelerated in the presence of both acid pH and oxidation conditions, relative to a single stimulus, owing to the synergetic degradation of micelles through pH-induced dePEGylation and oxidation-triggered decrosslinking processes. The proposed shell-sheddable core-crosslinked micelles with a pH and oxidation dual-response could be potential candidates as drug carriers for on-demand drug delivery.

Two-dimensional nanomaterials hold great promise as electrode materials for the construction of excellent electrochemical energy storage and transformation apparatuses. In the study, metallic layered cobalt sulfide was, firstly, applied to the area of energy storage as a supercapacitor electrode. By a facile and scalable method for cathodic electrochemical exfoliation, metallic layered cobalt sulfide bulk can be exfoliated into high-quality and few-layered nanosheets with size distributions in the micrometer scale range and thickness in the order of several nanometers. With a two-dimensional thin sheet structure of metallic cobalt sulfide nanosheets, not only was a larger active surface area created, but also, the insertion/extraction of ions in the procedure of charge and discharge were enhanced. The exfoliated cobalt sulfide was applied as a supercapacitor electrode with obvious improvement compared with the original sample, and the specific capacitance increased from 307 F∙g−1 to 450 F∙g−1 at the current density of 1 A∙g−1. The capacitance retention rate of exfoliated cobalt sulfide enlarged to 84.7% from the original 81.9% of unexfoliated samples while the current density multiplied by 5 times. Moreover, a button-type asymmetric supercapacitor assembled using exfoliated cobalt sulfide as the positive electrode exhibits a maximum specific energy of 9.4 Wh∙kg−1 at the specific power of 1520 W∙kg−1.

Background: This study evaluates the association between dietary acid load (DAL) and hyperuricemia in Chinese adults. Methods: The China Health and Nutrition Survey (CHNS) in 2009 was used in this cross-sectional study. Potential renal acid load (PRAL) and net endogenous acid production (NEAP) were applied to estimate DAL. A multiple logistic regression model was used to test the relationship between DAL and hyperuricemia risk. Results: A total of 7947 participants were included in this study, of whom 1172 had hyperuricemia. The PRAL score was positively related to the prevalence of hyperuricemia, even when potential covariates were taken into account. In comparison with Q1, the ORs were 1.12 (95% CI, 0.92–1.38), 1.20 (95% CI, 0.97–1.47) and 1.42 (95% CI, 1.16–1.75) in Q2, Q3 and Q4. However, there was no significant relationship between NEAP scores and hyperuricemia. Every 10 g increase in energy-adjusted fat, protein and animal protein intakes caused a 10%, 17% and 18% increase in hyperuricemia risk, respectively (OR: 1.10, 95% CI: 1.04–1.16; OR: 1.17, 95% CI: 1.11–1.25; OR: 1.18, 95% CI: 1.12–1.24, respectively). An obvious linear correlation was also suggested by the restricted cubic spline. Conclusions: Hyperuricemia risk was associated with higher PRAL among Chinese adults. This means that a diet low in PRAL scores could be a very valuable uric acid-lowering dietary pattern.

This study aims to explore the interaction between a Chinese version of the Mediterranean–DASH intervention for neurodegenerative delay (cMIND) diet and indoor air pollution and its effect on depression among older adults. This cohort study used 2011–2018 data from the Chinese Longitudinal Healthy Longevity Survey. Participants included 2724 adults aged 65 and older without depression. The Chinese version of the Mediterranean–DASH intervention for neurodegenerative delay (cMIND) diet scores ranged from 0 to 12 based on validated food frequency questionnaire responses. Depression was measured using the Phenotypes and eXposures Toolkit. Cox proportional hazards regression models were used to explore the associations, and the analysis was stratified using the cMIND diet scores. A total of 2724 participants (54.3% males and 45.9% 80 years and older) at baseline were included. Living with severe indoor pollution was associated with a 40% increase in the risk of depression (HR: 1.40, 95% CI: 1.07, 1.82) compared to living without indoor pollution. Indoor air pollution exposure was significantly associated with cMIND diet scores. Participants with a lower cMIND diet score (HR: 1.72, 95% CI: 1.24, 2.38) had a greater association with severe pollution than those with a higher cMIND diet score. The cMIND diet may alleviate depression caused by indoor pollution among older adults.

Abstract In this paper, we consider a diffusive predator–prey model with a time delay and prey toxicity. The effect of time delay on the stability of the positive equilibrium is studied by analyzing the eigenvalue spectrum. Delay-induced Hopf bifurcation is also investigated. By utilizing the normal form method and center manifold reduction for partial functional differential equations, the formulas for determining the property of Hopf bifurcation are given.

Soil organic carbon (SOC) storage and redistribution across the landscape (through erosion and deposition) are linked to soil physicochemical properties and can affect soil quality. However, the spatial and temporal variability of soil erosion and SOC remains uncertain. Whether soil redistribution leads to SOC gains or losses continues to be hotly debated. These considerations cannot be modelled using conventional soil carbon models and digital soil mapping. This paper presents a coupled-model combining RothPC-1 which considers soil carbon (C) down to 1 m and a soil redistribution model. The soil redistribution component is based on a cellular automata technique using the multi-direction flow (FD8) algorithm. With the optimized input values based on land use, we simulated SOC changes upon soil profiles to 1 m across the Lower Hunter Valley area (11,300 ha) in New South Wales, Australia from the 1970s to 2016. Results were compared to field observations and showed that erosion was predicted mostly in upslope areas and deposition in low-lying areas. We further simulated SOC trends from 2017 until ~2045 in the area under three climate scenarios and five land use projections. The variation in the magnitude and direction of SOC change with different projections shows that the main factors influencing SOC changes considering soil redistribution are climate change which controlled the trend of SOC stocks, followed by land use change. Neglecting soil erosion in carbon models could lead to an overestimation of SOC stocks. This paper provides a framework for incorporating soil redistribution into the SOC dynamics modelling and also postulates the thinking that soil erosion is not just a removal process by surface runoff.

A mangrove is a unique ecosystem with abundant resources, in which fungi are an indispensable microbial part. Numerous mangrove fungi-derived secondary metabolites are considerable sources of novel bioactive substances, such as polyketides, terpenoids, alkaloids, peptides, etc., which arouse people’s interest in the search for potential natural anti-tumor drugs. This review includes a total of 44 research publications that described 110 secondary metabolites that were all shown to be anti-tumor from 39 mangrove fungal strains belonging to 18 genera that were acquired from the South China Sea between 2016 and 2022. To identify more potential medications for clinical tumor therapy, their sources, unique structures, and cytotoxicity qualities were compiled. This review could serve as a crucial resource for the research status of mangrove fungal-derived natural products deserving of further development.

This study conducted a tribological investigation of base oil (PAO6 and 5W 40) and ionic liquids (IL)-modified lubricants through a four-ball tribometer for 30 min. The lubricants were fabricated via a two-step method using stirring magnetic and ultrasonic dispersion. IL, base oil, and lubricants were, respectively, characterized by XRD and FTIR analysis. In addition, multiple characterizations such as EDS, 3D morphology, and SEM were carried out to evaluate the wear and friction performance of steel balls. Ultimately, the results showed that the coefficient of friction (COF) and wear scar diameter (WSD) of wear scar lubricated by IL-modified lubricants were greatly decreased than that by base oil. IL can well improve the tribological properties of PAO 6 oil and 5W-40 oil due to the tribo-film appearance on the friction surface of wear scar by the effective role of IL. Fascinatingly, this investigation comprehensively and elaborately put a new sight into the lubrication mechanism of how IL reacted with a base oil and enhanced the tribological characteristics.

Viral metagenomics relies on high-throughput sequencing and on bioinformatic analyses to access the genetic content and diversity of entire viral communities. No universally accepted strategy or tool currently exists to define operational taxonomy units (OTUs) and evaluate viral alpha or beta diversity from virome data. Here we present a new bioinformatic resource, the VirAnnot (automated viral diversity estimation) pipeline, which performs the automated identification of OTUs. Reverse-position-specific BLAST (RPS-Blastn) is used to detect conserved viral protein motifs. The corresponding contigs are then aligned and a clustering approach is used to group in the same OTU contigs sharing more than a set identity threshold. A 10% threshold has been validated as producing OTUs that reasonably approach, in many families, the International Committee for the Taxonomy of Viruses taxonomy and can therefore be used as a proxy to viral species.

The viromic profile of Polyscias balfouriana cv. Marginata, a perennial woody and ornamental plant, was determined using ribosomal RNA-depleted total RNA (rRNA-depleted totRNA) sequencing. Five viruses (i.e., polyscias mosaic virus, PoMV; one potential novel rhabdovirus; and three novel viruses of Betaflexiviridae and Closteroviridae) were detected and prevalence-surveyed in Hainan province, China. The genomes of polyscias capillovirus 1 (PCaV-1) and polyscias citrivirus 1 (PCiV-1) of family Betaflexiviridae were completed, and the genomes of polyscias crinivirus 1 (PCrV-1) of Closteroviridae were nearly completed lacking the 5′ and 3′ termini. PCaV-1 shares 68% genome nucleotide (nt) identity and 66% replicase (Rep) amino acid (aa) identity with homologues in apple stem grooving virus (ASGV). PCiV-1 shares 65% genome nt identity and 64% Rep aa identity with homologs in citrus leaf blotch virus (CLBV). Meeting the species demarcation criteria, PCaV-1 and PCiV-1 were considered to be new species in genera Capillovirus and Citrivirus, respectively. PCrV-1 shares high genome nt identity (62%), heat shock protein 70-like protein (HSP70h) and RNA-dependent RNA polymerase (RdRp) aa identity (78–80%) with homologues in tomato chlorosis virus (ToCV). We tentatively consider PCrV-1 to be an unclassified member of the Crinivirus genus. PoMV, PCaV-1, PCiV-1, and PCrV-1 are the prevalent viruses with >73% occurrence in the Xinglong Tropical Botanical Garden, Hainan, China.