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Abstract Background Our previous study found that mouse embryonic neural stem cell (NSC)–derived exosomes (EXOs) regulated NSC differentiation via the miR‐9/Hes1 axis. However, the effects of EXOs on brain microvascular endothelial cell (BMEC) dysfunction via the miR‐9/Hes1 axis remain unknown. Therefore, the current study aimed to determine the effects of EXOs on BMEC proliferation, migration, and death via the miR‐9/Hes1 axis. Methods Immunofluorescence, quantitative real‐time polymerase chain reaction, cell counting kit‐8 assay, wound healing assay, calcein‐acetoxymethyl/propidium iodide staining, and hematoxylin and eosin staining were used to determine the role and mechanism of EXOs on BMECs. Results EXOs promoted BMEC proliferation and migration and reduced cell death under hypoxic conditions. The overexpression of miR‐9 promoted BMEC proliferation and migration and reduced cell death under hypoxic conditions. Moreover, miR‐9 downregulation inhibited BMEC proliferation and migration and also promoted cell death. Hes1 silencing ameliorated the effect of amtagomiR‐9 on BMEC proliferation and migration and cell death. Hyperemic structures were observed in the regions of the hippocampus and cortex in hypoxia‐induced mice. Meanwhile, EXO treatment improved cerebrovascular alterations. Conclusion NSC‐derived EXOs can promote BMEC proliferation and migration and reduce cell death via the miR‐9/Hes1 axis under hypoxic conditions. Therefore, EXO therapeutic strategies could be considered for hypoxia‐induced vascular injury.

In the domain of medical image segmentation, the nnUNet framework is highly respected for its excellent performance and wide range of applications. However, the inherent bias of locality and weight sharing introduced by the continuous convolutional operations currently used limits the network’s performance in modeling long-term dependencies. Furthermore, in the process of implementing residual links, certain limitations are encountered due to the substantial semantic discrepancy between the encoder’s output feature maps and the decoder’s. These limitations are seen in the direct application of skip connections for feature fusion and gradient propagation, which are known to impact the model’s convergence speed and overall performance. In this paper, a novel framework is presented, namely Multi-Attention nnUNet (MulA-nnUNet), which utilizes nnUNet as the foundational network structure and integrates two key attention mechanisms: large kernel convolutional attention (LKA) and pixel attention (PA). LKA is embedded within the deep encoder, maintaining the effectiveness of shallow feature extraction and enhancing the deep neural networks’ ability to understand long-range spatial dependencies. At the same time, the semantic distinction between the encoder and decoder’s output map of features is decreased by the PA module, which helps to improve the effect of skip connection feature fusion. The complexity of the model is reduced by replacing the standard convolutions in the encoder and decoder layers with depthwise separable convolutions (DS), which have fewer parameters. The effectiveness of the proposed framework is confirmed by a set of ablation experiments and comparison experiments with current state-of-the-art models on the computed tomography (CT) subset of the multimodal abdominal multi-organ segmentation dataset (AMOS), which includes 500 CT scans, with 350 scans for training, 75 for validation, and 75 for testing. MulA-nnUNet shows improvements of 1.1% in mean dice similarity coefficient (mDSC) and 1.52% in mean intersection over union (mIoU), while the baseline model requires 5 times the floating point operations (FLOPs) and over 7 times the parameters (Params). Additionally, it demonstrates superior accuracy in segmenting organs such as the liver, stomach, aorta, and pancreas, thereby enhancing the accuracy of 3D abdominal multi-organ image segmentation.

Abstract In view of the limited precision of traditional point cloud registration methods in bridge engineering, as well as the lack of intuitive guidance for bridge construction control regarding relative coordinate relationships of point clouds, this study proposes a novel dual-purpose target for the total station and laser scanner, along with a corresponding algorithm. The scanning point cloud undergoes intensity filtering, clustering, planar denoising, contour extraction, centroid fitting, registration transformation, target recognition, registration, and coordinate transformation. Experimental results demonstrate that the proposed algorithm can accurately extract the centroid coordinates of the targets and effectively handle complex on-site conditions. The coordinate transformation achieves high precision, with an amplification error of only 2.1 mm at a distance of 500 m. The registration precision between planar and spherical targets is nearly identical, surpassing that of planar iterative and ICP algorithms. Application of the algorithm in the context of China’s large double-span steel-tube concrete arch bridge scenario. it was found that the maximum deviation of the radius of the main chord tube was 10.8 mm, the maximum deviation of the distance from the center of the main chord tube was 8.3 mm, the average length of the merging opening was 775.0 mm, the maximum lateral deviation of the merging opening was 9.6 mm, and the maximum deviation of the height of merging opening was 25.2 mm. The results showed that no additional restraining measures were needed, and the smooth jointing could be realized only under a suitable temperature. Comparison with measurements obtained from the TS60 total station exhibits a close match, with a verification error within 3.9 mm, thereby meeting the precision requirements for construction control.

Glucocorticoids are classified in section S9 of the Prohibited List of the World Anti-Doping Agency, due to a potential risk to improving physical performance and causing harm to the health of athletes. Based on the similar physiological actions of glucocorticoids, both differentiating known glucocorticoids and identifying unknown glucocorticoids are important for doping control. Gas chromatography coupled with mass spectrometry plays an important role in structural characterization because of abundant structural diagnostic ions produced by electron ionization. It also provides a chance to study the fragmentation patterns. Thus, an enhanced derivatization procedure was optimized to produce trimethylsilylated glucocorticoids and structural diagnostic ions of nineteen trimethylsilylated glucocorticoids were obtained by gas chromatography-orbitrap high-resolution mass spectrometry. In our study, glucocorticoids were classified as: 3-keto-4-ene, 1,4-diene-3-keto, 3α-hydroxy with saturated A-ring, 21-hydroxy-20-keto and halo substituent glucocorticoids based on their structural difference. Structural diagnostic ions that contributed to structural characterization were specifically presented and the fragment patterns were demonstrated according to the above categories. This study not only gave new insights into the structural characterization of these glucocorticoids but also provided evidence for tracing unknown glucocorticoids or chemically modified molecules.

Species of Diaporthe inhabit a wide range of plant hosts as plant pathogens, endophytes and saprobes. During trips to collect forest pathogens in Beijing, Jiangxi, Shaanxi and Zhejiang Provinces in China, 16 isolates of Diaporthe were obtained from branch cankers and leaf spots. These isolates were studied by applying a polyphasic approach including morphological, cultural data, and phylogenetic analyses of the nuclear ribosomal internal transcribed spacer (ITS), calmodulin (cal), histone H3 (his3), partial translation elongation factor-1α (tef-1α) and β-tubulin (tub2) loci. Results revealed four new taxa, D. celticola, D. meliae, D. quercicola, D. rhodomyrti spp. nov. and two known species, D. eres and D. multiguttulata.

Underwater noise pollution from the world’s longest cross-sea bridge—the Hong Kong-Zhuhai-Macao Bridge (HZMB)—which stretches across the Chinese White Dolphin National Nature Reserve (of the People’s Republic of China, PRC) in the Pearl River Estuary may affect the distribution of local humpback dolphins. In this study, static passive acoustic monitoring was applied to monitor biosonar activity of humpback dolphins and underwater noise adjacent to the tunnel section of the HZMB for more than one year. During the monitoring period, dolphin biosonar signals were detected on 88.5% of days. A significant temporal pattern occurred in dolphin biosonar activity and in anthropogenic noise. Biosonar activity was significantly higher at night than during the day, whereas underwater noise occurred more in the day than at night. Significantly more echolocation signals were detected in winter-spring than in summer-autumn, and highest acoustic activity occurred significantly more during high tide than at other tidal periods. In addition, the negative correlation between elevated underwater noise and dolphin sonar activity in winter suggests that dolphins may avoid noisy waters for short periods, perhaps due to auditory stress, but fish prey movement cannot be ruled out. These findings facilitate understanding activity patterns of humpback dolphins in the Pearl River Estuary and may contribute to conservation efforts.

Traditional strategies for the metabolic profiling of doping are limited by the unpredictable metabolic pathways and the numerous proportions of background and chemical noise that lead to inadequate metabolism knowledge, thereby affecting the selection of optimal detection targets. Thus, a stable isotope labeling-based nontargeted strategy combined with ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC-HRMS) was first proposed for the effective and rapid metabolism analysis of small-molecule doping agents and demonstrated via its application to a novel doping BPC-157. Using 13C/15N-labeled BPC-157, a complete workflow including automatic 13C0,15N0-13C6,15N2 m/z pair picking based on the characteristic behaviors of isotope pairs was constructed, and one metabolite produced by a novel metabolic pathway plus eight metabolites produced by the conventional amide-bond breaking metabolic pathway were successfully discovered from two incubation models. Furthermore, a specific method for the detection of BPC-157 and the five main metabolites in human urine was developed and validated with satisfactory detection limits (0.01~0.11 ng/mL) and excellent quantitative ability (linearity: 0.02~50 ng/mL with R2 > 0.999; relative error (RE)% < 10% and relative standard deviation (RSD)% < 5%; recovery > 90%). The novel metabolic pathway and the in vitro metabolic profile could provide new insights into the biotransformation of BPC-157 and improved targets for doping control.

The coronavirus disease-2019 (COVID-19) pandemic has brought huge and continuous damage to mental health. The mental health of non-medical college students after returning to school remains largely unknown and the influencing factors were awaited to be deciphered. This cross-sectional study was launched among 1,083 non-medical students in Zhanjiang city by means of online survey (WeChat App) from August 1st, 2022 to August 7th, 2022. Knowledge about COVID-19 and attitude toward COVID-19 were assessed by using 7-items and 5-items questionnaires, respectively. Sleep quality, anxiety and depression symptoms were evaluated by Pittsburgh sleep quality index (PSQI), Hamilton depression rating scale-17 (HDRS-17) and self-rating anxiety scale (SAS), respectively. The results showed that more than half of the participants were knowledgeable about COVID-19. The majority of the participants held positive attitude toward COVID-19. The data demonstrated that 6.8% students had poor sleep quality, and 1.86, 0.37 and 0.37% students had mild, moderate and severe anxiety, respectively. About 26.7, 4.7 and 1.7% students had minimal, mild–moderate and severe depression. Female students showed higher proportions of anxiety (p = 0.02) and depression (p

Storage duration detection for frozen meat, especially meat exceeding the state reserve time several times, has always been a big challenge in food safety inspection. Under long freezing times, the physical and chemical properties of meat change complexly. In this paper, the SS-OCT detection method under a low-frequency electric field is firstly (to our knowledge) applied to the predict storage durations of long-expired frozen meat. The average normalized cross-correlation (ANCC) is put forward as a comprehensive parameter to reflect both the electric–kinetic and optical properties of meat’s biological changes. A monotonically increasing inversion rule between ANCC and the storage duration of frozen meat is found after investigating 3840 pork samples, the frozen storage durations of which were from 1 to 13 months. To verify the correctness and accuracy of our method, nine groups of long-expired frozen pork samples were investigated. The maximum relative error for their storage durations is less than 5.71%, which means that our SS-OCT method under a low-frequency electric field is promising in providing a rapid on-site storage duration detection method without any complicated laboratory pretreatments for food safety inspection.

Phocoenidae live in fresh, coastal waters where they often share a significant portion of their habitat with humans. As a result, local activities (e.g., coastal fisheries and shipments) cause underwater noise pollution and threaten their ecosystem. To better conserve the habitat of porpoises, we aimed to study their activities in these waters by recording their echolocation clicks using a passive acoustic monitoring (PAM) system. However, because the off-line PAM instruments were often used in the past that need to be periodically deployed and recovered, data acquisition is typically obtained and analyzed in batches, rather than in real-time. A real-time PAM detection system would help minimize the impact of underwater noise on approaching porpoises. Furthermore, issues of bad quality data–with gaps due to loss or damage of the off-line PAM instruments–could be avoided with a real-time detection system. Therefore, in this study, we developed the Real-time Porpoise Click Detector-II (RPCD-II), equipped with a digital hydrophone, main memory (2 TB storage), a central processing unit, and a wireless transmission module. We deployed the RPCD-II under a docked fishing vessel at the Ganjiang River in Yangzi Zhou Town Fisheries Village, Nanchang City (8–9 December 2021), where it recorded signals of Yangtze finless porpoise and produced a real-time report. To validate the results of RPCD-II, another underwater sound recorder, the SoundTrap 300HF (ST), was also set up (as a control device) under the docked fishing vessel. Both devices recorded consistent results of 9330 clicks, further demonstrating RPCD-II’s ability for the real-time detection of Yangtze finless porpoise in the field.

Heavy metal pollution is a major threat to agricultural produce and it can pose potential ecological risks which subsequently impacts on human health. Strawberries are an economically important produce of China. The intrinsic link of heavy metal pollution risk in the soil-strawberry ecosystem is of concern. In this study, the pollution index of heavy metal pollutants in farmlands of different provinces were evaluated, and the results showed significantly high levels of cadmium. In addition, Nemerow integrated pollution index analysis showed that low-pollution farmlands only accounted for 14.07% of the total arable land area. Then, the transfer factors were used to calculate the migration of heavy metals from the soil into strawberries. The results showed that cadmium and nickel were relatively high in strawberries from the Guangxi province. Similar results were found for mercury in Jiangxi Province. The pollution index of single food pollution also showed that mercury in strawberries from Jiangxi Province was at a moderate pollution level. The comprehensive pollution index indicated that heavy metal pollution in strawberries in Central China may be severe. In addition, spatial clustering analysis showed that cadmium, chromium, lead, arsenic and zinc in strawberries had significant hotspot clustering in central, south and southwest China. Finally, our studies also suggested that the risk of carcinogenic and non-carcinogenic diseases was higher in the (2, 4] years age group than in other age groups. People in Yunnan Province were also found to have a higher non-carcinogenic risk than those in other provinces and cities in China. This study provides a comprehensive view of the potential risks of heavy metal contamination in strawberries, which could provide assistance in the design of regulatory and risk management programs for chemical pollutants in strawberries, thus ensuring the safety of consumption of these edible fruits.

The random forest (RF) algorithm is a typical representative of ensemble learning, which is widely used in rolling bearing fault diagnosis. In order to solve the problems of slower diagnosis speed and repeated voting of traditional RF algorithm in rolling bearing fault diagnosis under the big data environment, an efficient rolling bearing fault diagnosis method based on Spark and improved random forest (IRF) algorithm is proposed. By eliminating the decision trees with low classification accuracy and those prone to repeated voting in the original RF, an improved RF with faster diagnosis speed and higher classification accuracy is constructed. For the massive rolling bearing vibration data, in order to improve the training speed and diagnosis speed of the rolling bearing fault diagnosis model, the IRF algorithm is parallelized on the Spark platform. First, an original RF model is obtained by training multiple decision trees in parallel. Second, the decision trees with low classification accuracy in the original RF model are filtered. Third, all path information of the reserved decision trees is obtained in parallel. Fourth, a decision tree similarity matrix is constructed in parallel to eliminate the decision trees which are prone to repeated voting. Finally, an IRF model which can diagnose rolling bearing faults quickly and effectively is obtained. A series of experiments are carried out to evaluate the effectiveness of the proposed rolling bearing fault diagnosis method based on Spark and IRF algorithm. The results show that the proposed method can not only achieve good fault diagnosis accuracy, but also have fast model training speed and fault diagnosis speed for large-scale rolling bearing datasets.

Ensemble learning has been widely used in various fields. Still, too many base classifiers will affect the classification time of the ensemble classifier under the big data environment, while reducing base classifiers will affect the classification accuracy of the ensemble classifier. Therefore, the multi-objective teaching-learning-based optimization (MO-TLBO) algorithm is used to carry out ensemble pruning of random forest (RF) to improve the classification accuracy and speed of RF. MO-TLBO algorithm aims at maximizing classification accuracy and minimizing classification time, and it can find a sub-forest with higher classification accuracy and faster classification speed. In addition, considering the vast computational time of ensemble pruning of RF via MO-TLBO algorithm under the big data environment, a vote set is constructed to improve the fitness evaluation process. In the Spark platform, the RF improved by the MO-TLBO algorithm (MO-TLBO-RF) is parallelized based on data parallelism. The Shuffle optimization strategy is proposed to reduce the number of Shuffles in the execution of parallel MO-TLBO-RF. The proposed MO-TLBO-RF is applied to rolling bearing fault diagnosis. The experimental results show that the algorithm can obtain an RF with high fault diagnosis accuracy and fast fault diagnosis speed. The results also prove that the ensemble pruning time can be greatly reduced via the vote set and parallelization of MO-TLBO-RF.

Multilevel inverters are preferred solutions for photovoltaic (PV) applications because of lower total harmonic distortion (THD), lower switching stress and lower electromagnetic interference (EMI). In order to reduce the leakage current in the single-phase low-power PV inverters, a five-level transformer-less inverter is proposed in this paper. A total of eleven switches are required, while six of them only withstand a quarter of the dc-bus voltage, so the costs for them are low. Another four switches are turned on or off at the power line cycle, the switching losses for them are ignored. In addition, the flying-capacitors (FCs) voltages are only a quarter of the dc-bus voltage, and they are balanced at the switching frequency, which further reduces the system investment. The experimental results based on a 1 kW prototype show that the proposed modulation strategy can balance the FCs voltages at Vdc/4 very well. And the leakage current can be reduced to about 27 mA under both active and reactive operations, which satisfies the VDE 0126-1-1 standard.

Dynamic line rating is a technology that can be used to improve the transmission efficiency and capacity of the existing power system without changing the system structure or breaking the current technical specification. It is an economical and feasible method to meet the increasing power demands and the needs for new energy integration. In order to ensure the safe and stable operation of power system, the specific technologies and application methods affecting the reliability of DLR are discussed. The main limitations of data acquisition technology of transmission lines are analyzed, the advantages and disadvantages of different perception analysis methods are classified, several application architectures of the DLR system are compared, and some applications of current DLR technologies in actual engineering are discussed. The problems existed in the technologies of DLR are pointed out from four aspects: data acquisition, perception analysis, application architecture, and engineering practice, such as the quality of data acquisition is low, the dependence of perceptual analysis on parameters and the data collected is high, the application architecture is open-loop, the analysis on the overall security of the power grid is deficient. Finally, the future research direction is pointed out.

Nitrogen (N) is an essential macronutrient for plant function and growth and a key component of amino acids, which form the building blocks of plant proteins and enzymes. However, misuse and overuse of N can have many negative impacts on the ecosystem, such as reducing soil exchangeable base cations (BCs) and causing soil acidification. In this research, we evaluated clonal Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) seedlings grown with exponentially increasing N fertilization (0, 0.5, 1, 2 g N seedling−1) for a 100-day trial in a greenhouse. The growth of seedlings, their nutrient contents, and soil exchangeable cations were measured. We found that N addition significantly increased plant growth and N content but decreased phosphorous (P) and potassium (K) contents in plant seedlings. The high nitrogen (2 g N seedling−1) treated seedlings showed a negative effect on growth, indicating that excessive nitrogen application caused damage to the seedlings. Soil pH, soil exchangeable base cations (BCs), soil total exchangeable bases (TEB), soil cation exchange capacity (CEC), and soil base saturation (BS) significantly decreased following N application. Our results implied that exponential fertilization resulted in soil acidification and degradation of soil capacity for supplying nutrient cations to the soil solution for plant uptake. In addition, the analysis of plants and BCs revealed that Na+ is an important base cation for BCs and for plant growth in nitrogen-induced acidified soils. Our results provide scientific insights for nitrogen application in seedling cultivation in soils and for further studies on the relationship between BCs and plant growth to result in high-quality seedlings while minimizing fertilizer input and mitigating potential soil pollution.

Industrial equipment health management is an extension of traditional fault diagnosis, which is a frontier research field of information science. The definition and application area of industrial equipment health management are first clarified, and then technologies related to health management are introduced, including feature analysis, fault diagnosis, fault prognosis and other technologies. The difficulties and bottlenecks of various technologies are expounded through comparative analysis, and a feasible scheme for future health management and integration is also discussed in this article.

Background HIV/AIDS is a chronic disease leading to complications in infected individuals that often require surgical intervention. These patients’ serum CD4 T lymphocyte (CD4) counts represent one of the most important indicators of their ability to tolerate surgical treatment. Previous studies have demonstrated that CD4 cell count (CD4-CC) < 200 cells/μl may increase the risk of surgical complications in these patients, limiting their ability to undergo surgery, which may negatively affect their quality of life. Further investigation into the surgical outcomes of patients with CD4-CC < 200 cells/μl should provide guidance in making appropriate clinical decisions for the optimal healthcare of this patient demographic. Methods All enrolled patients were selected from 14 prefecture-level general hospitals in Guangxi, China, and were referred to AIDS outpost hospitals for inpatient surgical therapy. A total cohort of 168 adult patients was retrospectively analyzed. Multifactorial and stratified analyses were performed to evaluate the in surgical outcome differences for patients with CD4-CC < 200 cells/μl (N = 43), using those with CD4-CC ≥ 200 cells/μl (N = 125) as controls. Results Poor incisional healing was used as the primary outcome indicator, and postoperative complications were used as the secondary outcome indicator. In the patient group with CD4-CC < 200 cells/μl, the risk of surgical complications was significantly increased (OR 2.379; 95% CI [1.049–5.394]) after adjustment. Adjusted stratified analysis of the CD4-CC < 200 cells/μl group revealed that individuals over 60 years (OR 27.504; 95% CI [2.297–329.317]) with erythrocyte counts below 4.00/ml for males or 3.50/ml for females (OR 3.353; 95% CI [1.079–10.419]) had a significantly higher risk of postoperative complications; this finding was statistically different from the control (CD4 ≥ 200 cells/μl) group. However, there was no significant difference between the two groups regarding the risk of poorly healed incision outcomes. Conclusions Preliminary findings suggest that a serum CD4-CC < 200 cells/μl is not a definitive contraindication for surgical therapy and that baseline and surgical characteristics may help predict surgical outcomes in these patients. Further studies are needed to confirm these findings.

Objective To compare the outcomes of patients with non-traumatic cardiac arrest (CA) who received early versus late mechanical cardiopulmonary resuscitation (CPR) with the Lund University Cardiac Assist System (LUCAS) device in the emergency department (ED). Methods This was a retrospective observational study in the ED of a single medical center performed from May 2018 to December 2019; 68 patients with CA were eligible. We grouped the patients according to the time to initiating LUCAS use after CA into an early group (≤4 minutes) and late group (>4 minutes). Results The rate of return of spontaneous circulation (ROSC) was higher in the early group vs the late group (69.2% vs 52.4%, respectively). The 4-hour survival rate was significantly higher in the early group vs the late group (83.3% vs 45.5%, respectively), and CPR duration was significantly shorter in the early group (23.3 ± 12.5 vs 31.1 ± 14.8 minutes, respectively). Conclusion Early mechanical CPR can improve the success of achieving ROSC and the 4-hour survival rate in patients with non-traumatic CA in the ED, considering that more benefits were observed in patients who received early vs late LUCAS device therapy.

The current detection method of carbendazim suffers from the disadvantages of complicated preprocessing and long cycle time. In order to solve the problem of rapid quantitative screening of finite contaminants, this article proposed a qualitative method based on characteristic peaks and a semi-quantitative method based on threshold to detect carbendazim in apple, and finally the method is evaluated by a validation system based on binary output. The results showed that the detection limit for carbendazim was 0.5 mg/kg, and the detection probability was 100% when the concentration was no less than 1 mg/kg. The semi-quantitative analysis method had a false positive rate of 0% and 5% at 0.5 mg/kg and 2.5 mg/kg, respectively. The results of method evaluation showed that when the added concentration was greater than 2.5 mg/kg, the qualitative detection method was consistent with the reference method. When the concentration was no less than 5 mg/kg, the semi-quantitative method is consistent between different labs. The semi-quantitative method proposed in this study can achieve the screening of finite contaminants in blind samples and simplify the test validation process through the detection probability model, which can meet the needs of rapid on-site detection and has a good application prospect.

Abstract Background African swine fever (ASF) is a devastating infectious disease of pigs. ASF poses a potential threat to the world pig industry, due to the lack of vaccines and treatments. In this study, the Geographic Information System (GIS) spatial analysis was applied to analyze the distribution, dispersion of the epidemic and clustering of ASF in Poland. Results The results show that the center of the epidemic moved gradually towards the southwest, and the distribution of the epidemic changed from south-north to east-west. Through space-time scan statistical analysis, the 3 clusters major of wild boar cases involve longer time spans and larger radii, while the other five with higher relative risks involved in domestic pigs. And then, a quantitative model was constructed to analyse the risk of releasing African swine fever virus (ASFV) from Poland by the legal export of pork and pork products. The Latin hypercube sampling results show that the probability is relatively low (the average value is 4.577 × 10− 7). Conclusions All the identification of the spatio-temporal patterns of the epidemic and the risk analysis model would give a further understanding of the dynamics of disease transmission and help to design corresponding measures to minimize the catastrophic consequences of potential ASFV introduction.

To explore the diversity of soil bacteria and changes in the bacterial community structure of Chinese fir plantations of different generations and developmental stages, the genetic diversity of soil bacteria was studied using the 454 sequencing technology. The results showed that the bacterial genetic diversity and community structure of Chinese fir plantation plots under monoculture planting and rotation planting practices were as follows: the Shannon diversity indices of first-generation young plantation of Chinese fir plantations (FYC), second-generation young plantation (SYC), and third-generation young plantation (TYC) initially decreased and then increased to 8.45, 8.1, and 8.43, respectively. Due to different management and tending measures, the phyla showing considerable differences in relative abundance were Cyanobacteria, Nitrospirae, Fibrobacteres, Thermotogae, and Planctomycetes. The bacterial genetic diversity and community structure of Chinese fir plantations at different developmental stages were as follows: the bacterial diversity and the number of operational taxonomic units (OTUs) decreased with increasing forest age; with the increasing forest age of Chinese fir, the bacteria with considerable differences in the relative abundance were Burkholderiales, Xanthomonadales, Ktedonobacteria, Nitrosomonadales, Anaerolineae, and Holophagae. The predominant bacteria of the Chinese fir plantations were Acidothermus, Bradyrhizobium, Lactococcus, Planctomyces, Sorangium, and Bryobacter.

Identifying lncRNA–protein interactions (LPIs) is vital to understanding various key biological processes. Wet experiments found a few LPIs, but experimental methods are costly and time-consuming. Therefore, computational methods are increasingly exploited to capture LPI candidates. We introduced relevant data repositories, focused on two types of LPI prediction models: network-based methods and machine learning-based methods. Machine learning-based methods contain matrix factorization-based techniques and ensemble learning-based techniques. To detect the performance of computational methods, we compared parts of LPI prediction models on Leave-One-Out cross-validation (LOOCV) and fivefold cross-validation. The results show that SFPEL-LPI obtained the best performance of AUC. Although computational models have efficiently unraveled some LPI candidates, there are many limitations involved. We discussed future directions to further boost LPI predictive performance.

Multifractal analysis was successfully used to investigate the structure of river networks. In this paper, we performed a multifractal analysis of river networks in an urban catchment that is located on the Taihu Plain in the lower part of the Yangtze River Delta, China. Spatial and temporal variations in the river networks during the period 1960−2010 were investigated. The generalized multifractal dimensions (Dq) and the multifractal spectrum (f(α)) were calculated using a box-counting method. The results indicate that: (i) the river networks in Wuchengxiyu (WXCY), Yangchengdianmao (YCDM), and Hangjiahu (HJH) had obvious multifractal features with capacity dimensions between 1.90 and 1.91 during the period 1960−2010. The multifractal spectrums are asymmetrical inverted-hook-shaped curves with a dominant left arm. The variation in the singularity component (∆α) changed the most in WCXY (an increase of ~ 7.9%), and the height variation in the multifractal spectrum (∆f) increased by ~ 17.5% in HJH; (ii) the changes in ∆α and ∆f of the tributaries in the three areas during the period 1960−2010 were consistent with those of the overall river network, demonstrating the decisive role that the tributaries play in the complexity of the river networks; (iii) compared to the natural factors, the influences of urbanization on the river networks significantly changed with a higher urbanization level; and (iv) there were no border effects. Further applications of multifractal theory in analyses of the relationship between a flood-forming regime and the multifractal structures of river networks will attract more attention. Generally, this approach, when successfully applied to studies of changes in river networks, is of theoretical significance for better describing and quantifying the evolution of river networks’ structures.

River systems are valuable to human beings; meanwhile, they are intensively influenced by human activities, especially urbanization. In this study, based on the data derived from topographic maps and remote sensing images, the temporal and spatial change of river system geomorphology in the Taihu Region over the past 50 years was investigated in conjunction with urbanization. Results demonstrated that the number of river systems decreased drastically, that the morphology of river channels changed into wider and straighter and that the structure of river network tended to simplify in the Taihu Region in recent 50 years. Meanwhile, the changes in river density, the water surface ratio, the river development coefficient, the main river area length ratio and the box dimension in the rapid urbanization period were much greater than those in the slow urbanization period, but the decrease of river sinuosity in the slow urbanization period was more intense. Moreover, the spatial differences of the changes in the river development coefficient were the largest, and the changes in the river indicators in the low-urbanized regions were the most intense. In addition, the changes in the water surface ratio had the closest correlation with urbanization, and the relational degrees between population urbanization and the changes in river systems were the largest. The results can provide a reliable basis to determine reasonable management and conservation strategies of river systems in the Taihu Region.

Aim: The aim of this study was to investigate the mechanisms of Cr6+-induced red blood cells (RBCs) damage. Methods: The effect of Cr6+ exposure on RBCs was evaluated by hemolytic rate and blood gas assays. After exposure to 20 μM Cr6+, the percentage of phosphatidylserine (PS)-exposing cells, intracellular Ca2+, reactive oxygen species (ROS), and ATP levels were evaluated, and cell morphology was observed. RBCs were exposed to Cr6+ in different Ringer solutions to investigate the role of changes of Ca2+, ROS, and ATP levels in eryptosis and morphology. Results: The Cr6+-induced damage of RBCs was dose-dependent. After a 6 h incubation with Cr6+, RBCs exhibited significant Ca2+ influx, ROS increase, ATP depletion, and PS exposure, but displayed no obvious change in morphology at this time point. After 24 h Cr6+ exposure, the RBCs decreased in size, appeared to be spike-like, and had decreased forward scatter. Inhibition of Ca2+ influx attenuated PS-exposure caused by 6 h Cr6+ exposure, but did not prevent 24 h Cr6+ exposure-induced morphological change in RBCs. Inhibition of rapid ATP consumption using adenine significantly ameliorated Cr6+-caused PS-exposure at 12 h, 24 h and 48 h, and prevented 24 h Cr6+ incubation-induced morphological change in RBCs. Conclusion: Cr6+ can lead to eryptosis. Ca2+ influx, increased ROS levels, and rapid ATP consumption are closely related to Cr6+-induced RBCs damage. Ca2+ influx plays an extremely important role in Cr6+-mediated toxicity.

Mesenchymal stem cell (MSC) therapy shows considerable promise for the treatment of myocardial infarction (MI). However, the inefficient migration and homing of MSCs after systemic infusion have limited their therapeutic applications. Ultrasound-targeted microbubble destruction (UTMD) has proven to be promising to improve the homing of MSCs to the ischemic myocardium, but the concrete mechanism remains unclear. We hypothesize that UTMD promotes MSC homing by upregulating SDF-1/CXCR4, and this study was aimed at exploring this potential mechanism. We analyzed SDF-1/CXCR4 expression after UTMD treatment in vitro and in vivo and counted the number of homing MSCs in MI areas. The in vitro results demonstrated that UTMD not only led to elevated secretion of SDF-1 but also resulted in an increased proportion of MSCs that expressed surface CXCR4. The in vivo findings show an increase in the number of homing MSCs and higher expression of SDF-1/CXCR4 in the UTMD combined with MSCs infusion group compared to other groups. In conclusion, UTMD can increase SDF-1 expression in the ischemic myocardium and upregulate the expression of surface CXCR4 on MSCs, which provides a molecular mechanism for the homing of MSCs assisted by UTMD via SDF-1/CXCR4 axis.

BACKGROUND: To assess the level of CR6-interacting factor 1 (CRIF1), a cell cycle negative regulator, in patients with leukemia and investigate the role of CRIF1 in regulating leukemia cell cycle. METHODS: We compared the CRIF1 level in bone marrow (BM) samples from healthy and acute myeloid leukemia (AML), iron deficiency anemia (IDA) and AML-complete remission (AML-CR) subjects. We also manipulated CRIF1 level in the Jurkat cells using lentivirus-mediated overexpression or siRNA-mediated depletion. Co-culture with the BM stromal cells (BMSCs) was used to induce leukemia cell cycle arrest and mimic the BM microenvironment. RESULTS: We found significant decreases of CRIF1 mRNA and protein in the AML group. CRIF1 overexpression increased the proportion of Jurkat cells arrested in G0/G1, while depletion of endogenous CRIF1 decreased cell cycle arrest. Depletion of CRIF1 reversed BMSCs induced cell cycle arrest in leukemia cells. Co-immunoprecipitation showed a specific binding of CDK2 to CRIF1 in Jurkat cells during cell cycle arrest. Co-localization of two proteins in both nucleus and cytoplasm was also observed with immunofluorescent staining. CONCLUSION: CRIF1 may play a regulatory role in the BM microenvironment-induced leukemia cell cycle arrest possibly through interacting with CDK2 and acting as a cyclin-dependent kinase inhibitor.

Background: Physical chemistry is an important theoretical basic course that supports the development of medicine and pharmacies. Physical chemistry teaching is usually a process of traditional teaching and passive acceptance. The teaching method is singular, and students lack an interest and the ability of autonomous learning. Objectives: The purpose of the study is to explore the application of a hands-on inquiry learning strategy blending independent learning based on information resources flipped classroom teaching, the student-centered micro class auxiliary teaching mode in physical chemistry courses to improve student learning outcomes and develop active learning ability. Materials and Methods: Eighteen students in the experimental pharmacy major class, grade 2020, were recruited to study in a physical chemistry course that applies hands-on inquiry learning. Formative and summative evaluation were used to evaluate the students' achievements related to active learning goals. After the study was completed, a survey was administered to demongstrate the teaching results. Results: Student hands-on inquiry learning performance was positively correlated with the final scores. The results show that comprehensive scores of students of 2020 grade (experimental group) are significantly better than grade 2019 students (control group); in particular, the theoretical scores of 2020 grade students are better, and the data are significantly different. The questionnaire showed that most students believed that hands-on inquiry learning strategy blending independent learning improved their high-level cognitive skills and enhances their social cohesion and sense of responsibility. Conclusion: The hands-on inquiry teaching strategy developed in this study effectively improved students' performance in formative and summative assessment, and provided a reference basis and informative entry point for the implementation of active learning strategy in higher pharmaceutical education. [ABSTRACT FROM AUTHOR]