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Background The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X‐ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicators related to osteoporosis and imaging factors that can better reflect bone quality, such as computed tomography (CT). Objective To construct a novel predicting model based on bone turn‐over markers and CT to identify patients who were more inclined to suffer spine refracture. Methods CT images and clinical information of 383 patients (training set = 240 cases of osteoporotic vertebral compression fractures (OVCF), validation set = 63, test set = 80) were retrospectively collected from January 2015 to October 2022 at three medical centers. The U‐net model was adopted to automatically segment ROI. Three‐dimensional (3D) cropping of all spine regions was used to achieve the final ROI regions including 3D_Full and 3D_RoiOnly. We used the Densenet 121‐3D model to model the cropped region and simultaneously build a T‐NIPT prediction model. Diagnostics of deep learning models were assessed by constructing ROC curves. We generated calibration curves to assess the calibration performance. Additionally, decision curve analysis (DCA) was used to assess the clinical utility of the predictive models. Results The performance of the test model is comparable to its performance on the training set (dice coefficients of 0.798, an mIOU of 0.755, an SA of 0.767, and an OS of 0.017). Univariable and multivariable analysis indicate that T_P1NT was an independent risk factor for refracture. The performance of predicting refractures in different ROI regions showed that 3D_Full model exhibits the highest calibration performance, with a Hosmer–Lemeshow goodness‐of‐fit (HL) test statistic exceeding 0.05. The analysis of the training and test sets showed that the 3D_Full model, which integrates clinical and deep learning results, demonstrated superior performance with significant improvement (p‐value

Abstract Endometrial cancer (EC) stem cells (ECSCs) are pivotal in the oncogenesis, metastasis, immune escape, chemoresistance, and recurrence of EC. However, the specific mechanism of stem cell maintenance in EC cells (ECCs) has not been clarified. We found that WTAP and m6A levels decreased in both EC and ECSCs, and that knocking down WTAP promoted ECCs and ECSCs properties, including proliferation, invasion, migration, cisplatin resistance, and self-renewal. The downregulation of WTAP leads to a decrease in the m6A modification of EGR1 mRNA, and it is difficult for IGF2BP3, as an m6A reader, to recognize and bind to EGR1 mRNA that has lost m6A modification, resulting in a decrease in the stability of EGR1 mRNA. A decrease in the EGR1 level led to a decrease of in the expression tumor suppressor gene PTEN, resulting in deregulation and loss of cellular homeostasis and thereby fostering EC stem cell traits. Notably, the enforced overexpression of WTAP, EGR1, and PTEN inhibited the oncogenic effects of ECCs and ECSCs in vivo, and the combined overexpression of WTAP + EGR1 and EGR1 + PTEN further diminished the tumorigenic potential of these cells. Our findings revealed that the WTAP/EGR1/PTEN pathway is important regulator of EC stem cell maintenance, chemotherapeutic resistance, and tumorigenesis, suggesting a novel and promising therapeutic avenue for treating EC.

Abstract Intelligent fault diagnosis is an important method in rotating machinery fault diagnosis and equipment health management. To deal with co-frequency vibration faults, a type of typical fault in rotating machinery, this paper proposes a fault diagnosis method based on the stacked autoencoder (SAE) and ensembled ResNet-SVM. Furthermore, the time- and frequency-domain features of several co-frequency vibration faults are summarized based on the mechanism analysis and calculated using actual vibration data. To realize and validate the high-precision diagnosis method of rotating equipment with co-frequency faults proposed in this study, the following three criteria are required: First, to improve the effectiveness and robustness of the ensembled model and the sliding window using data augmentation, adding noise, autoencoder (AE) and SAE methods are analyzed in terms of principle and practical effects. Second, ResNet is used as the feature extractor for the ensembled ResNet-SVM model. Feature extraction is carried out twice, and the extracted co-frequency fault features are more comprehensive. Finally, the data augmentation method and ensemble ResNet-SVM are combined for fault diagnosis and compared with other methods. The experimental results show that the accuracy of the proposed method can exceed 99.9%.

Objective Thoracolumbar fractures are one of the most common fractures in clinical practice. Surgical intervention is recommended to restore spinal alignment or decompress the nerves when there are unstable fractures or neurological injuries. However, after excessive forward thrust force restoration, facet joint dislocation often occurs between the upper vertebra and the fractured vertebra, which usually leads to unsatisfactory reduction outcomes. Herein, we propose a novel spinal facet joint toothed plate to assist in fracture reduction. The purpose of this study is to evaluate the effectiveness of the new spinal facet joint toothed plate in preventing facet joint dislocation, and its advantages compared to traditional pedicle screw‐rod decompression. Methods A total of 26 patients in the toothed plate group and 93 patients in the traditional group who experienced thoracolumbar fracture with reduction were retrospectively included. Relevant patients' information and clinical parameters were collected. Furthermore, visual analogue scores (VAS) scores and Oswestry disability index (ODI) scores were also collected. Moreover, imaging parameters were calculated based on radiographs. Correlated data were analyzed by χ2 test and t test. Results All patients in this study had no postoperative complications. Postoperative VAS scores and ODI scores (p

This study systematically examines the energy dissipation mechanisms and ballistic characteristics of foam sandwich panels (FSP) under high-velocity impact using the explicit non-linear finite element method. Based on the geometric topology of the FSP system, three FSP configurations with the same areal density are derived, namely multi-layer, gradient core and asymmetric face sheet, and three key structural parameters are identified: core thickness (tc), face sheet thickness (tf) and overlap face/core number (no). The ballistic performance of the FSP system is comprehensively evaluated in terms of the ballistic limit velocity (BLV), deformation modes, energy dissipation mechanism, and specific penetration energy (SPE). The results show that the FSP system exhibits a significant configuration dependence, whose ballistic performance ranking is: asymmetric face sheet > gradient core > multi-layer. The mass distribution of the top and bottom face sheets plays a critical role in the ballistic resistance of the FSP system. Both BLV and SPE increase with tf, while the raising tc or no leads to an increase in BLV but a decrease in SPE. Further, a face-core synchronous enhancement mechanism is discovered by the energy dissipation analysis, based on which the ballistic optimization procedure is also conducted and a design chart is established. This study shed light on the anti-penetration mechanism of the FSP system and might provide a theoretical basis for its engineering application.

Abstract The co-frequency vibration fault is one of the common faults in the operation of rotating equipment, and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the health state and carrying out vibration suppression of the equipment. In engineering scenarios, co-frequency vibration faults are highlighted by rotational frequency and are difficult to identify, and existing intelligent methods require more hardware conditions and are exclusively time-consuming. Therefore, Lightweight-convolutional neural networks (LW-CNN) algorithm is proposed in this paper to achieve real-time fault diagnosis. The critical parameters are discussed and verified by simulated and experimental signals for the sliding window data augmentation method. Based on LW-CNN and data augmentation, the real-time intelligent diagnosis of co-frequency is realized. Moreover, a real-time detection method of fault diagnosis algorithm is proposed for data acquisition to fault diagnosis. It is verified by experiments that the LW-CNN and sliding window methods are used with high accuracy and real-time performance.

Abstract Background Abnormal lipid metabolism has recently been reported as a crucial signature of idiopathic pulmonary fibrosis (IPF). However, the origin and biological function of the lipid and possible mechanisms of increased lipid content in the pathogenesis of IPF remains undetermined. Methods Oil-red staining and immunofluorescence analysis were used to detect lipid accumulation in mouse lung fibrosis frozen sections, Bleomycin-treated human type II alveolar epithelial cells (AECIIs) and lung fibroblast. Untargeted Lipid omics analysis was applied to investigate differential lipid species and identified LysoPC was utilized to treat human lung fibroblasts and mice. Microarray and single-cell RNA expression data sets identified lipid metabolism-related differentially expressed genes. Gain of function experiment was used to study the function of 3-hydroxy-3-methylglutaryl-Coa Synthase 2 (HMGCS2) in regulating AECIIs lipid metabolism. Mice with AECII-HMGCS2 high were established by intratracheally delivering HBAAV2/6-SFTPC- HMGCS2 adeno-associated virus. Western blot, Co-immunoprecipitation, immunofluorescence, site-directed mutation and flow cytometry were utilized to investigate the mechanisms of HMGCS2-mediated lipid metabolism in AECIIs. Results Injured AECIIs were the primary source of accumulated lipids in response to Bleomycin stimulation. LysoPCs released by injured AECIIs could activate lung fibroblasts, thus promoting the progression of pulmonary fibrosis. Mechanistically, HMGCS2 was decreased explicitly in AECIIs and ectopic expression of HMGCS2 in AECIIs using the AAV system significantly alleviated experimental mouse lung fibrosis progression via modulating lipid degradation in AECIIs through promoting CPT1A and CPT2 expression by interacting with PPARα. Conclusions These data unveiled a novel etiological mechanism of HMGCS2-mediated AECII lipid metabolism in the genesis and development of pulmonary fibrosis and provided a novel target for clinical intervention.

Abstract Mechanoluminescence (ML) sensing technologies open up new opportunities for intelligent sensors, self-powered displays and wearable devices. However, the emission efficiency of ML materials reported so far still fails to meet the growing application requirements due to the insufficiently understood mechano-to-photon conversion mechanism. Herein, we propose to quantify the ability of different phases to gain or lose electrons under friction (defined as triboelectric series), and reveal that the inorganic-organic interfacial triboelectricity is a key factor in determining the ML in inorganic-organic composites. A positive correlation between the difference in triboelectric series and the ML intensity is established in a series of composites, and a 20-fold increase in ML intensity is finally obtained by selecting an appropriate inorganic-organic combination. The interfacial triboelectricity-regulated ML is further demonstrated in multi-interface systems that include an inorganic phosphor-organic matrix and organic matrix-force applicator interfaces, and again confirmed by self-oxidization and reduction of emission centers under continuous mechanical stimulus. This work not only gives direct experimental evidences for the underlying mechanism of ML, but also provides guidelines for rationally designing high-efficiency ML materials.

BackgroudHuman epithelial growth factor receptor 2 (HER2) amplification is an important mechanism of acquired resistance to anti-epidermal growth factor receptor (EGFR) therapy in non-small cell lung cancer (NSCLC) patients. For patients with both EGFR mutation and HER2 amplification, there is currently no unified standard treatment, and further exploration is needed on how to choose the therapy.Methods and resultsA female NSCLC patient developed bone and brain metastases 14 and 42 months after radical surgery, respectively. The second genetic sequencing detected EGFR L858R mutation and HER2 amplification, and therefore initiated treatment with almonertinib and pyrotinib. The patient achieved partial remission and did not show any further progression during the follow-up period.ConclusionFor NSCLC patients with both EGFR mutation and HER2 amplification, the combination of almonertinib and pyrotinib is a valuable therapy that can continuously reduce tumor burden and achieve long-term survival.

Hepatic subcapsular hematoma (HSH) is an uncommon complication of pregnancy and is associated with elevated rates of maternal and foetal mortality. The rupture of an HSH is a critical situation that necessitates immediate and timely intervention to prevent loss of life. We present here, a case of a spontaneously ruptured massive HSH caused by preeclampsia. In addition, we conducted a comprehensive review of existing literature, encompassing 49 cases of HSH associated with pregnancy. If a pregnant woman with gestational hypertension experiences right upper abdominal pain with shoulder pain or radiating shoulder pain, it is crucial for her to have an urgent abdominal ultrasound because of the potential development of HSH and/or rupture. Our review of current literature suggests that opting for a caesarean section may offer notable advantages in preventing HSH rupture.

Abstract Urbanization alters the thermal and dynamic environment of the local climate system, resulting in significant impacts on precipitation in both urban and adjacent areas. Nevertheless, there remains a significant gap in our understanding of urbanization‐induced effects on asymmetrical, symmetrical, and other precipitation patterns in urban agglomerations (UAs) with divergent background climates and geographic regions at different timescales. Specifically, this asymmetrical change pattern is characterized by an increase in heavy (or light) rainfall and a decrease in light (or heavy) rainfall. Here, we assessed the effects of urbanization on precipitation patterns across 18 UAs situated in diverse background climates and geographical areas in China at different timescales. The results demonstrate that urbanization predominantly alters precipitation patterns in UAs located in the humid region. Specifically, urbanization amplified asymmetrical changes in Yangtze River Delta, Pearl River Delta, Beibu Gulf, Middle Yangtze River, and Guanzhong, but exacerbated symmetrical changes in precipitation in some regions such as Chengdu‐Chongqing. Notably, the urbanization effect demonstrates greater significance at the hourly scale, as exemplified in the Yangtze River Delta, Pearl River Delta, and Middle Yangtze River, where the urban impact is nearly twice as pronounced when compared to the daily scale. Moreover, urbanization had either no effect or has a negative impact on precipitation patterns in UAs located within continental and arid regions. This is related to the intensity of urbanization, background climate and complex topography. This finding implies that urban managers should consider the impact of urbanization on precipitation patterns in different contexts to provide scientific guidance for urban planning.

Ferroptosis is a nonapoptotic form of cell death and differs considerably from the well-known forms of cell death in terms of cell morphology, genetics, and biochemistry. The three primary pathways for cell ferroptosis are system Xc−/glutathione peroxidase 4 (GPX4), lipid metabolism, and ferric metabolism. Since the discovery of ferroptosis, mounting evidence has revealed its critical regulatory role in several diseases, especially as a novel potential target for cancer therapy, thereby attracting increasing attention in the fields of tumor biology and anti-tumor therapy. Accordingly, broad prospects exist for identifying ferroptosis as a potential therapeutic target. In this review, we aimed to systematically summarize the activation and defense mechanisms of ferroptosis, highlight the therapeutic targets, and discuss the design of nanomedicines for ferroptosis regulation. In addition, we opted to present the advantages and disadvantages of current ferroptosis research and provide an optimistic vision of future directions in related fields. Overall, we aim to provide new ideas for further ferroptosis research and inspire new strategies for disease diagnosis and treatment.

Abstract Photodynamic therapy (PDT) is a temporally and spatially precisely controllable, noninvasive, and potentially highly efficient method of phototherapy. The three components of PDT primarily include photosensitizers, oxygen, and light. PDT employs specific wavelengths of light to active photosensitizers at the tumor site, generating reactive oxygen species that are fatal to tumor cells. Nevertheless, traditional photosensitizers have disadvantages such as poor water solubility, severe oxygen‐dependency, and low targetability, and the light is difficult to penetrate the deep tumor tissue, which remains the toughest task in the application of PDT in the clinic. Here, we systematically summarize the development and the molecular mechanisms of photosensitizers, and the challenges of PDT in tumor management, highlighting the advantages of nanocarriers‐based PDT against cancer. The development of third generation photosensitizers has opened up new horizons in PDT, and the cooperation between nanocarriers and PDT has attained satisfactory achievements. Finally, the clinical studies of PDT are discussed. Overall, we present an overview and our perspective of PDT in the field of tumor management, and we believe this work will provide a new insight into tumor‐based PDT.

Lavender, an aromatic plant with a history dating back to ancient Egypt and Greece, is consumed because of its diverse pharmacological properties, including sedation, sleep aid, and antidepressant effects. However, the mechanisms underlying these antidepressant properties remain unclear. In this study, we explored the impact of lavender essential oil (LEO) inhalation on the diversity of gut microbiota, metabolites, and differential gene expression in the hippocampus of alcohol-withdrawn depressive rats. Additionally, we examined alterations in the hippocampal transient receptor potential (TRP) channel-mediated inflammatory regulation within the brain-gut axis of depressive rats. The results demonstrated a significant decrease in sucrose preference, diminished activity in the central zone of the open field test, and prolonged immobility time in the forced swim test in alcohol-withdrawn depressive rats, indicating the amelioration of depressive states following lavender essential oil inhalation. 16 S rDNA sequencing analysis revealed a significant reduction in Bacteroidota and Muribaculaceae in the gut of alcohol-withdrawn depressive rats, whereas lavender essential oil significantly increased the relative abundance of Muribaculaceae and other bacterial species. Metabolomic analysis identified 646 distinct metabolites as highly correlated biomarkers between the model and lavender essential oil groups. Furthermore, lavender essential oil inhalation significantly attenuated hippocampal inflammatory factors IL-2, IL-6, IL-1β, and TNF-α. This study identified elevated expression of Trpv4 and Calml4 in the hippocampal region of alcohol-withdrawn depressed rats and showed that lavender essential oil inhalation regulated aberrantly expressed genes. Our research suggests that lavender essential oil downregulates Trpv4, modulates inflammatory factors, and alleviates depressive-like behavior in alcohol withdrawal rats.

Biomass is a renewable alternative to fossil fuels and a valuable source of chemicals. In this study, a facile and efficient method was established to improve the selectivity of methyl lactate (MLA) for the homogeneous Lewis acid catalyzed chemical conversion of glucose and methanol. The effects of catalyst dosage, reaction temperature, and reaction time were systematically investigated, with an emphasis on the variation trends of MLA and other by-products. Through process optimization, the best catalyst molar ratio was 0.075 to 0.1, the reaction temperature was 170 to 180 °C, and the reaction time was 3 h. Under these conditions, the conversion of glucose in methanol exceeded 98%, and the yield of MLA was greater than 40%.

Abstract Oncolytic virotherapy holds promise for cancer treatment, but the factors determining its oncolytic activity remain unclear. Neutrophil extracellular traps (NETs) are associated with cancer progression, yet their formation mechanism and role in oncolytic virotherapy remain elusive. In this study, we demonstrate that, in glioma, upregulation of IGF2BP3 enhances the expression of E3 ubiquitin protein ligase MIB1, promoting FTO degradation via the ubiquitin-proteasome pathway. This results in increased m6A-mediated CSF3 release and NET formation. Oncolytic herpes simplex virus (oHSV) stimulates IGF2BP3-induced NET formation in malignant glioma. In glioma models in female mice, a BET inhibitor enhances the oncolytic activity of oHSV by impeding IGF2BP3-induced NETosis, reinforcing virus replication through BRD4 recruitment with the CDK9/RPB-1 complex to HSV gene promoters. Our findings unveil the regulation of m6A-mediated NET formation, highlight oncolytic virus-induced NETosis as a critical checkpoint hindering oncolytic potential, and propose targeting NETosis as a strategy to overcome resistance in oncolytic virotherapy.

In recent years, the proliferation of mousehole in grasslands has exacerbated desertification and compromised grassland productivity, posing potential threats to human safety. Consequently, the identification and forecasting of mouse-hole dynamics for effective infestation control have emerged as pressing concerns. Manual mousehole detection is labor-intensive and time-consuming, hindering comprehensive spatial understanding. Moreover, prevailing detection models lack robust feature extraction for small targets like mousehole, resulting in suboptimal recognition capabilities and diminished accuracy. Addressing these challenges, we propose an enhanced one-stage detection model BSM-YOLO based on YOLOv5 architecture. Firstly, the model integrates a BiFormer module leveraging Bi-Level Routing Attention to capture both global and local features within mousehole images. Subsequently, the incorporation of Shuffle Attention mechanisms enhances the learning of feature dependencies and intricate relationships. Lastly, the adoption of the MPDIoU loss function accurately delineates bounding box characteristics, mitigating redundant box generation and expediting model convergence. In our experimental framework, we curated a dataset comprising 2397 mousehole images to train the BSM-YOLO model. Results indicate that the BSM-YOLO model achieves an average detection accuracy of 94.5%, representing a 5.4% enhancement over the baseline YOLOv5s model. Additionally, the model demonstrates an 8.7 f/s improvement in detection speed. Furthermore, ablation experiments confirm the efficacy of each refinement incorporated into the BSM-YOLO model.

Fluctuations in the surface water are indicators of climatic and biological environmental variations. The water index method is the predominant approach for water extraction owing to its simplicity of operation and high efficiency. Recognizing the limitations of individual water indices in extracting water over dense time-sequences, this study introduces a combined water index (CWI) frequency method to improve the water extraction results. The research findings indicate the following: 1) CWI demonstrates superior extraction accuracy for various types of water when compared with other water indices, underscoring its higher precision and broader applicability. 2) By integrating CWI with the water frequency method, we propose an effective approach for dynamically monitoring water. This method accurately reflects changes in water under different conditions within dense time-sequence images. 3) Our results highlight the method's ability to precisely monitor dynamic water changes, efficiently extract various water types from Sentinel-2 data, and its potential for large-scale surface water mapping applications.

ABSTRACTAccurate identification and classification of forage grass are pivotal in optimizing forage resources and breeding superior forage varieties. Given the low accuracy in forage image identification and classification, and the loss of some features from preprocessing, we proposed an innovative approach that integrates preprocessing operations directly into the model instead of preceding feature analysis. We captured near-ground hyperspectral imagery of forage in the field and applied two deep learning models – Squeeze and Excitation ResNet (SEResNet) and Convolution Block Attention Module ResNet (CBAMResNet). These models not only harness the automatic learning capabilities of the ResNet deep network but also employ channel attention and a channel-plus-space dual attention mechanism to filter and label important features. This approach enhances data extraction and analysis, strengthen the correlation between the channel and space dimensions while eliminating redundancy and noise. We compared the performance of the proposed methods with the current popular methods by six evaluation parameters, including overall accuracy (OA), average accuracy (AA), Kappa coefficient, etc. Experiment results show the OA of SEResNet and CBAMResNet are 96.57% and 98.35% respectively. The experiments demonstrate the feasibility of incorporating preprocessing into the network and the effectiveness of the new idea for the classification research of forage.

The forecast of rainstorm in flood season has always been the key and difficult point in the meteorological forecasting operation. First, we used the daily precipitation data from 2 227 meteorological stations in Zhejiang Province from 2016 to 2021 during the flood season (April to October), and divided the precipitation region by applying the K-means clustering algorithm, which employed the Euclidean distance as the similarity measure. Then, the regional correction method is formed by combing the spatial-temporally improved bias correction method and divided regions. Finally, we applied this method to perform the regional correction and validation on the Zhejiang Multi-Model Objective Consensus Forecast (OCF), compared with the overall correction not combined with divided regions.The results are as follows. (1) The K-means clustering algorithm can divide Zhejiang Province into 7 precipitation-similar regions, which show distinct regional characteristics closely related to the topographic features of Zhejiang Province. (2) According to validation during the 2021 flood season, the regional correction performed better than the overall correction in the OCF forecasts.Its main advantages lie in effectively reducing the false alarm of precipitation in the clear-rain forecast and substantially increasing the hit rate (POD) for the heavy rain and above, especially for the rainstorm and above from 0.25 to 0.41. (3) The typical validation show that, for both systematic and convective precipitation, the regional correction can significantly improve the intensity and falling area of precipitation for the rainstorm and above. Especially for the systematic precipitation, the regional correction demonstrated more remarkable effects, which can predict heavy rainstorms.

ObjectivesThe aims of this study were to explore the incidence characteristics and trend prediction of lymphoma from 2005 to 2035, and to provide data basis for the prevention and control of lymphoma in China.MethodThe data on lymphoma incidence in China from 2005 to 2017 were obtained from the Chinese Cancer Registry Annual Report. The Joinpoint regression model was used to calculate annual percentage change (APC) and average annual percentage change (AAPC) to reflect time trends. Age–period–cohort models were conducted to estimate age, period, and cohort effects on the lymphoma incidence. A Bayesian age–period–cohort model was used to predict lymphoma incidence trends from 2018 to 2035.ResultsFrom 2005 to 2017, the incidence of lymphoma was 6.26/100,000, and the age-standardized incidence rate (ASIR) was 4.11/100,000, with an AAPC of 1.4% [95% confidence interval (CI): 0.3%, 2.5%]. The ASIR was higher in men and urban areas than in women and rural areas, respectively. The age effect showed that the incidence risk of lymphoma increased with age. In the period effect, the incidence risk of lymphoma in rural areas decreased first and then increased with 2010 as the cutoff point. The overall risk of lymphoma incidence was higher in the cohort before the 1970–1974 birth cohort than in the cohort after. From 2018 to 2035, the lymphoma incidence in men, women, and urban areas will show an upward trend.ConclusionFrom 2005 to 2017, the incidence of lymphoma showed an increasing trend, and was different in regions, genders, and age groups in China. It will show an upward trend from 2018 to 2035. These results are helpful for the formulation and adjustment of lymphoma prevention, control, and management strategies, and have important reference significance for the treatment of lymphoma in China.

Remotely sensed land surface temperature (LST) is critical for retrieving evapotranspiration (ET). However, due to cloud contamination, LST is often limited to clear-sky conditions and the differences between clear-sky and all-sky LST will lead to clear-sky biases of LST. Consequently, the accuracy of ET varies drastically under different weather conditions. To evaluate the impact of clear-sky biases on ET estimation, the monthly ET under clear-sky and all-sky conditions was estimated using a nonparametric method at several sites with different humid conditions and vegetation coverage in 2014. 35.7 % of the clear-sky LST values were acquired in the arid region (Heihe River Basin) with different vegetation coverage. As the climate became more humid, only 14.2 % of the clear-sky LST data were available (Poyang Lake Basin). The clear-sky biases of LST variation at the sites resulted in a significant reduction in the accuracy of monthly ET, with an increase in the relative error (RE) of approximately 16.6 %. The impact of clouds can be reduced by at most half by the introduction of all-sky LST products, with a significant decline (6.3 % ∼ 34.2 % of ET) in the error contribution of LST to monthly ET. The variation in vegetation coverage of land cover and the change in humidity of the climate significantly affected the influence of the clear-sky biases of LST on the ET estimation and the error contribution to ET. Replacing all-sky LST with clear-sky LST in areas with less vegetation coverage exacerbates the underestimation of ET estimation and strengthens the error contribution of LST with the decline in RE (error contribution of LST) from −7.7 % (−6.3 %) in densely vegetated areas to −29.7 % (−34.2 %) in non-vegetated areas, especially in the summer. Similarly, clear-sky biases of LST tended to have a relatively significant impact on the error contributions of LST to monthly ET estimation when the climate became humid, with a relatively significant enlarging from −6.3 % in the arid area to −10.0 % in the humid area, especially in the rainy season in the humid area (−61.3 % of ET). This study contributes to the understanding of the relationship between clear-sky biases and vegetation coverage/humidity. Quantitative analysis of the impact of clear-sky biases of LST on monthly ET estimation will be helpful for improving the accuracy of ET retrieval in the future.

BackgroundThere currently exists some controversy about the efficacy of oblique lumbar interbody fusion (OLIF) and transforaminal lumbar interbody fusion (TLIF) in the treatment of lumbar degenerative diseases.AimThis study compares the application effects of OLIF and TLIF in lumbar degenerative diseases by reviewing the literature and using meta-analysis.MethodsWe included randomized controlled trials and cohort studies comparing TLIF and OLIF in the treatment of lumbar degenerative diseases. We searched for words such as “intervertebral disc degeneration,” “spinal fusion,” and “lumbar vertebrae” in the PubMed, Embase, and Cochrane Library databases. The search date was set from the establishment date of the database to October 2023. Two authors independently conducted document screening, data abstraction, and qualitative assessment. A meta-analysis was performed and adapted to RevMan5.3 software. The odds ratio (OR), weighted mean difference (WMD), and 95% CI were calculated by adopting a fixed-effect model (FEM) or a random-effect model (REM).ResultsA total of 18 cohort studies were included with 1,550 patients, of whom 806 patients underwent TLIF (TLIF group) and 744 patients underwent OLIF (OLIF group). There were no significant differences found in the fusion rate [OR = 1.58 (0.95, 2.64), P = 0.08], complication rate [OR = 1.25 (0.93, 1.68), P = 0.14], and visual analog scale for back pain (VAS-BP) [WMD = 0.00 (−0.13, 0.14), P = 0.96] between the two groups. Compared with the TLIF group, the OLIF group had a lower Oswestry disability index (ODI) [WMD = −0.62 (−1.03, −0.20), P = 0.003], a higher foramen height (FH) [WMD = 2.03 (1.42, 2.46), P

Methicillin-resistant Staphylococcus aureus (MRSA) is a major inducement of nosocomial infections and its biofilm formation render the high tolerance to conventional antibiotics, which highlights the requirement to develop new antimicrobial agents urgently. In this study, we identified a fluorinated benzimidazole derivative, TFBZ, with potent antibacterial efficacy toward planktonic MRSA (MIC = 4 μg/mL, MBC = 8 μg/mL) and its persistent biofilms (≥99%, MBEC = 8 μg/mL). TFBZ manifested significant irreversible time-dependent killing against MRSA as characterized by diminished cell viability, bacterial morphological change and protein leakage. Furthermore, the results from CBD devices, crystal violet assay in conjunction with live/dead staining and scanning electron microscopy confirmed that TFBZ was capable of eradicating preformed MRSA biofilms with high efficiency. Simultaneously, TFBZ reduced the bacterial invasiveness and exerted negligible hemolysis and cytotoxicity toward mammalian cells, which ensuring the robust therapeutic effect on mouse skin abscess model. The transcriptome profiling and quantitative RT-PCR revealed that a set of encoding genes associated with cell adhesion, biofilm formation, translation process, cell wall biosynthesis was consistently downregulated in MRSA biofilms upon exposure to TFBZ. In conclusion, TFBZ holds promise as a valuable candidate for therapeutic applications against MRSA chronic infections.

Gleditsia sinensis, commonly known as Chinese Zaojiao, has important economic value and medicinal compounds in its fruits and thorns, making it widely cultivated artificially in China. However, the available literature on the impact of waterlogging on the growth of G. sinensis seedlings and the accumulation of metabolite compounds in its thorns is limited. To address this knowledge gap, G. sinensis seedlings were planted in soil supplemented with pindstrup substrate, which enhances the water-holding capacity of the soil. The analyses of morphological traits and nutrient elements in one-year-old G. sinensis seedlings grown naturally under ambient conditions and metabolite accumulation in its thorns were conducted. The results showed that the waterlogged soil significantly diminished the height, fresh weight, and dry weight of seedling roots and stems (P

Abstract Hydroxycarboxylic acid receptor 2 (HCAR2) belongs to the family of class A G protein-coupled receptors with key roles in regulating lipolysis and free fatty acid formation in humans. It is deeply involved in many pathophysiological processes and serves as an attractive target for the treatment of cardiovascular, neoplastic, autoimmune, neurodegenerative, inflammatory, and metabolic diseases. Here, we report four cryo-EM structures of human HCAR2–Gi1 complexes with or without agonists, including the drugs niacin (2.69 Å) and acipimox (3.23 Å), the highly subtype-specific agonist MK-6892 (3.25 Å), and apo form (3.28 Å). Combined with molecular dynamics simulation and functional analysis, we have revealed the recognition mechanism of HCAR2 for different agonists and summarized the general pharmacophore features of HCAR2 agonists, which are based on three key residues R1113.36, S17945.52, and Y2847.43. Notably, the MK-6892–HCAR2 structure shows an extended binding pocket relative to other agonist-bound HCAR2 complexes. In addition, the key residues that determine the ligand selectivity between the HCAR2 and HCAR3 are also illuminated. Our findings provide structural insights into the ligand recognition, selectivity, activation, and G protein coupling mechanism of HCAR2, which shed light on the design of new HCAR2-targeting drugs for greater efficacy, higher selectivity, and fewer or no side effects.

Microneedles (MNs) can be used for the topical treatment of skin disorders as they directly deliver therapeutics to the site of skin lesions, resulting in increased therapeutic efficacy while having minimum side effects. MNs are used to deliver different kinds of therapeutics (e.g., small molecules, macromolecules, nanomedicines, living cells, bacteria, and exosomes) for treating various skin disorders, including superficial tumors, wounds, skin infections, inflammatory skin diseases, and abnormal skin appearance. The therapeutic efficacy of MNs can be improved by integrating the advantages of multiple therapeutics to perform combination therapy. Through careful designing, MNs can be further modified with biomimetic structures for the responsive drug release from internal and external stimuli and to enhance the transdermal delivery efficiency for robust therapeutic outcomes. Some studies have proposed the use of drug-free MNs as a promising mechanotherapeutic strategy to promote wound healing, scar removal, and hair regeneration via a mechanical communication pathway. Although MNs have several advantages, the practical application of MNs suffers from problems related to industrial manufacture and clinical evaluation, making it difficult for clinical translation. In this study, we summarized the various applications, emerging challenges, and developmental prospects of MNs in skin disorders to provide information on ways to advance clinical translation.

Abstract This study aims to investigate the effectiveness of umbilical cord mesenchymal stem cells (UCMSCs) in treating osteoarthritis (OA). Sprague–Dawley rats were used in in vivo experiments and divided into four groups: normal, OA model, saline, and UCMSC-treated groups (n = 6). An OA model was established by injecting iodoacetic acid into the joint cavity. The results indicate that UCMSC transplantation significantly reduced joint surface and articular cartilage damage, and the levels of IL-1β, TNF-α, and MMP13 in the joint fluid were significantly reduced after UCMSC treatment. In vitro experiments showed that co-culturing UCMSCs and chondrocytes promoted the expression of aggrecan, COL2, SOX9, and BCL-2; downregulated the expression of BAX and BAD in chondrocytes; and promoted the expression of IL-10 and TGF-β1 in UCMSCs. Additionally, the supernatant of UCMSCs inhibited the expression of IL-1β and TNF-α in the articular cavity and promoted the expression of COL2 and aggrecan in vivo. These effects were impaired when IL-10 and TGF-β1 were removed. Collectively, UCMSC transplantation appears to improve joint pathology, reduce inflammatory factors, and decrease chondrocyte apoptosis, likely through the involvement of IL-10 and TGF-β1, thus providing a potential therapeutic option for patients with OA.

Abstract Background Headache disorders are widely prevalent and pose a considerable economic burden on individuals and society. Globally, misdiagnosis and inadequate treatment of primary headache disorders remain significant challenges, impeding the effective management of such conditions. Despite advancements in headache management over the last decade, a need for comprehensive evaluations of the status of primary headache disorders in China regarding diagnosis and preventative treatments persists. Methods In the present study, we analyzed the established queries in the Survey of Fibromyalgia Comorbidity with Headache (SEARCH), focusing on previous diagnoses and preventative treatment regimens for primary headache disorders. This cross-sectional study encompassed adults diagnosed with primary headache disorders who sought treatment at 23 hospitals across China between September 2020 to May 2021. Results The study comprised 2,868 participants who were systematically examined. Migraine and tension-type headaches (TTH) constituted a majority of the primary headache disorders, accounting for 74.1% (2,124/2,868) and 23.3% (668/2,868) of the participants, respectively. Medication overuse headache (MOH) affected 8.1% (231/2,868) of individuals with primary headache disorders. Over half of the individuals with primary headache disorders (56.6%, 1,624/2,868) remained undiagnosed. The previously correct diagnosis rates for migraine, TTH, TACs, and MOH were 27.3% (580/2,124), 8.1% (54/668), 23.2% (13/56), and 3.5% (8/231), respectively. The misdiagnosis of “Nervous headache” was found to be the most prevalent among individuals with migraine (9.9%, 211/2,124), TTH (10.0%, 67/668), trigeminal autonomic cephalalgias (TACs) (17.9%, 10/56), and other primary headache disorders (10.0%, 2/20) respectively. Only a minor proportion of individuals with migraine (16.5%, 77/468) and TTH (4.7%, 2/43) had received preventive medication before participating in the study. Conclusions While there has been progress made in the rate of correct diagnosis of primary headache disorders in China compared to a decade ago, the prevalence of misdiagnosis and inadequate treatment of primary headaches remains a veritable issue. As such, focused efforts are essential to augment the diagnosis and preventive treatment measures related to primary headache disorders in the future.

Purpose: This research aims to study and compare the effects of moderate-intensity continuous exercise and accumulated exercise with different number of bouts on common carotid arterial stiffness and hemodynamic variables.Methods: Thirty healthy male adults were recruited to complete four trials in a randomized crossover design: no-exercise (CON); continuous exercise (CE, 30-min cycling); accumulated exercise including two or three bouts with 10-min rest intervals (AE15, 2 × 15-min cycling; AE10, 3 × 10-min cycling). The intensity in all the exercise trials was set at 45%–55% heart rate reserve. Blood pressure, right common carotid artery center-line velocity, and arterial inner diameter waveforms were measured at baseline and immediately after exercise (0 min), 10 min, and 20 min.Results: 1) The arterial stiffness index and pressure–strain elastic modulus of the CE and AE15 groups increased significantly at 0 min, arterial diameters decreased in AE15 and AE10, and all indicators recovered at 10 min. 2) The mean blood flow rate and carotid artery center-line velocity increased in all trials at 0 min, and only the mean blood flow rate of AE10 did not recover at 10 min. 3) At 0 min, the blood pressure in all trials was found to be increased, and the wall shear stress and oscillatory shear index of AE10 were different from those in CE and AE15. At 20 min, the blood pressure of AE10 significantly decreased, and the dynamic resistance, pulsatility index, and peripheral resistance of CE partially recovered.Conclusion: There is no significant difference in the acute effects of continuous exercise and accumulated exercise on the arterial stiffness and diameter of the carotid artery. Compared with continuous exercise, accumulated exercise with an increased number of bouts is more effective in increasing cerebral blood supply and blood pressure regulation, and its oscillatory shear index recovers faster. However, the improvement of blood flow resistance in continuous exercise was better than that in accumulated exercise.

Coping capacity is a key aspect of driver-vehicle interaction when drivers observe and make decisions, and is of great importance for drivers. However, different drivers have different self-cognition and assess their driving abilities differently, especially for novice drivers. Based on questionnaire data, this study has investigated the coping capacities of drivers in both static environments and dynamic environments. With the ANOVA analysis method and the structural equation model (SEM), this study has verified the effects of gender and driving factors (driving years, driving frequency, driving time) on drivers' coping capacities based on drivers' self-assessment scores and mutual assessment scores. Drivers' self-assessment scores show significant effects of all factors on drivers' coping capacities, and drivers' mutual assessment scores show significant effects of all factors, excluding driving time, on drivers' coping capacities. Also, it has been found that all drivers in the driving year group have cognitive biases. It seems that first-year drivers are always overconfident with their driving skills, while drivers with a driving experience of more than three years usually score driving skills of themselves and other drivers most conservatively. With increased exposure to various traffic conditions, experienced drivers are more aware of their limitations in dealing with complex traffic situations, while novice drivers do not know their lack of capability to properly respond to any unexpected situation they could encounter.

Selecting an appropriate intensity of epidemic prevention and control measures is of vital significance to promoting the two-way dynamic coordination of epidemic prevention and control and economic development. In order to balance epidemic control and economic development and suggest scientific and reasonable traffic control measures, this paper proposes a SEIQR model considering population migration and the propagation characteristics of the exposed and the asymptomatic, based on the data of COVID-19 cases, Baidu Migration, and the tourist economy. Further, the factor traffic control intensity is included in the model. After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. With Xi'an City as an example. The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. With the continuous rise of traffic control intensity in different simulation scenarios, the cumulative number of cases decreases by a significant amplitude. While balancing the requirements for epidemic prevention and control and for tourist economy development, the model works out the control intensity to be 0.68, under which some traffic control measures are suggested. The model presented in this paper can be used to analyze the impacts of different traffic control intensities on epidemic transmission. The research results in this paper reveal the traffic control measures balancing the requirements for epidemic prevention and control and for economic development.

The economic and health significance of quinoa is steadily growing on a global scale. Nevertheless, the primary obstacle to achieving high yields in quinoa cultivation is pre-harvest sprouting (PHS), which is intricately linked to seed dormancy. However, there exists a dearth of research concerning the regulatory mechanisms governing PHS. The regulation of seed germination by various plant hormones has been extensively studied. Consequently, understanding the mechanisms underlying the role of endogenous hormones in the germination process of quinoa seeds and developing strategies to mitigate PHS in quinoa cultivation are of significant research importance. This study employed the HPLC-ESI-MS/MS internal standard and ELISA method to quantify 8 endogenous hormones. The investigation of gene expression changes before and after germination was conducted using RNA-seq analysis, leading to the discovery of 280 differentially expressed genes associated with the regulatory pathway of endogenous hormones. Additionally, a correlation analysis of 99 genes with significant differences identified 14 potential genes that may act as crucial “transportation hubs” in hormonal interactions. Through the performance of an analysis on the modifications in hormone composition and the expression of associated regulatory genes, we posit a prediction that implies the presence of a negative feedback regulatory mechanism of endogenous hormones during the germination of quinoa seeds. This mechanism is potentially influenced by the unique structure of quinoa seeds. To shed light on the involvement of endogenous hormones in the process of quinoa seed germination, we have established a regulatory network. This study aims to offer innovative perspectives on the breeding of quinoa varieties that exhibit resistance to PHS, as well as strategies for preventing PHS.

Endornaviruses are known to occur widely in plants, fungi, and oomycetes, but our understanding of their diversity and distribution is limited. In this study, we report the discovery of four endornaviruses tentatively named Setosphaeria turcica endornavirus 1 (StEV1), Setosphaeria turcica endornavirus 2 (StEV2), Bipolaris maydis endornavirus 1 (BmEV1), and Bipolaris maydis endornavirus 2 (BmEV2). StEV1 and StEV2 infect Exserohilum turcicum, while BmEV1 and BmEV2 infect Bipolaris maydis. The four viruses encode a polyprotein with less than 40 % amino acid sequence identity to other known endornaviruses, indicating that they are novel, previously undescribed endornaviruses. However, StEV1 and BmEV1 share a sequence identity of 78 % at the full-genome level and 87 % at the polyprotein level, suggesting that they may belong to the same species. Our study also found that each of the four endornaviruses has an incidence of approximately 3.5 % to 5.5 % in E. turcicum or B. maydis. Interestingly, BmEV1 and BmEV2 were found to be unable to transmit between hosts of different vegetative incompatibility groups, which may explain their low incidence.

BackgroundPulmonary hypertension (PH) is linked to higher rates of morbidity and mortality worldwide. Early diagnosis of PH is important for clinical treatment. The estimated pulmonary artery systolic pressure (ePASP ≥ 35 mmHg) measured by echocardiography helps screen PH patients. In this paper, we report a novel PH screening method through a mobile cardiac acoustic monitoring system.MethodsIn the retrospective study, patients admitted to our hospital between January 2022 and April 2023 were classified into PH and control groups using ePASP and compared with acoustic cardiographic parameters. According to ePASP, PH severity was classified as mild, moderate, and severe. We analyzed the first and second heart sound (S1, S2) characteristics, including amplitude (S1A, S2A), energy (S1E, S2E), and frequency (S1F, S2F).ResultsThe study included 209 subjects, divided into PH (n = 121) and control (n = 88) groups. Pearson correlation analysis confirmed the positive correlation between S2F and ePASP. The diagnostic performance of S2F as assessed by the area under the ROC curve was 0.775 for PH. The sensitivity and specificity of diagnosing ePASP ≥ 35 mmHg when S2F ≥ 36 Hz were found to be 79.34% and 67.05%, respectively, according to ROC analysis. Severity classification was performed using S2F, the area under the ROC curve was 0.712–0.838 for mild PH, 0.774–0.888 for moderate PH, and 0.826–0.940 for severe PH.ConclusionsS2F collected by the mobile cardiac acoustic monitoring system offers a convenient method for remote PH screening, potentially improving PH management and outcomes.

Abstract Background Serotonin (5-HT) is a biogenic monoamine with diverse functions in multiple human organs and tissues. During pregnancy, tightly regulated levels of 5-HT in the fetoplacental unit are critical for proper placental functions, fetal development, and programming. Despite being a non-neuronal organ, the placenta expresses a suite of homeostatic proteins, membrane transporters and metabolizing enzymes, to regulate monoamine levels. We hypothesized that placental 5-HT clearance is important for maintaining 5-HT levels in the fetoplacental unit. We therefore investigated placental 5-HT uptake from the umbilical circulation at physiological and supraphysiological levels as well as placental metabolism of 5-HT to 5-hydroxyindoleacetic acid (5-HIAA) and 5-HIAA efflux from trophoblast cells. Methods We employed a systematic approach using advanced organ-, tissue-, and cellular-level models of the human placenta to investigate the transport and metabolism of 5-HT in the fetoplacental unit. Human placentas from uncomplicated term pregnancies were used for perfusion studies, culturing explants, and isolating primary trophoblast cells. Results Using the dually perfused placenta, we observed a high and concentration-dependent placental extraction of 5-HT from the fetal circulation. Subsequently, within the placenta, 5-HT was metabolized to 5-hydroxyindoleacetic acid (5-HIAA), which was then unidirectionally excreted to the maternal circulation. In the explant cultures and primary trophoblast cells, we show concentration- and inhibitor-dependent 5-HT uptake and metabolism and subsequent 5-HIAA release into the media. Droplet digital PCR revealed that the dominant gene in all models was MAO-A, supporting the crucial role of 5-HT metabolism in placental 5-HT clearance. Conclusions Taken together, we present transcriptional and functional evidence that the human placenta has an efficient 5-HT clearance system involving (1) removal of 5-HT from the fetal circulation by OCT3, (2) metabolism to 5-HIAA by MAO-A, and (3) selective 5-HIAA excretion to the maternal circulation via the MRP2 transporter. This synchronized mechanism is critical for regulating 5-HT in the fetoplacental unit; however, it can be compromised by external insults such as antidepressant drugs.

Abstract Grassland is an important resource for China's economic development and the main economic source of animal husbandry. The identification and classification of grassland forage is an important part of the improvement of forage varieties and the monitoring of germplasm resources, which can fundamentally solve the problems of poor forage quality and low reproduction rate. For the problem of low accuracy of forage identification and classification, the authors put forward a new 3DSECNN model to remove the preprocessing operation and directly study the images. The authors took forage hyperspectral image (HSI) images on the field and built dataset, used 3DSECNN to train the images to improve the classification effect. The outstanding contributions of this paper are: (1) The authors took high‐precision forage HSI images in the field, established a dedicated database of forage HSIs, and expanded the datasets; (2) the process of integrating preprocessing ideas into the network and replacing the traditional method of preprocessing the data and then extracting features; (3) proposing the 3DSECNN model, which adds SENet on the basis of the traditional 3DCNN, strengthens the correlation of the spatial dimension, selects the key features for the classification by calculating the channel weight, inhibits the unimportant information, and achieves the purpose of integrating the preprocessing ideas into the network. The experimental results show the overall accuracy (OA) of 3DSECNN is 94.36%, Precision, Recall, F1‐score, Kappa, and Time also showed good levels. The experimental results prove that the 3DSECNN strengthens the correlation between image channels, enhances the performance ability of features, and provides a new method for the identification and classification research of forage.

Infected bone defect is a formidable clinical challenge. Conventional approaches to prevention and treatment for infected bone defects are unsatisfactory. The key elements of the treatment are bone defect reconstruction, anti-infection, and osteogenesis. Conventional treatment methods remain unsatisfactory owing to the absence of composite integrating materials with anti-infective, and osteogenic activities as well as proper mechanical strength at the same time. In this study, we fabricated a vancomycin-encapsulated hydrogel with bacteria-responsive release properties combined with a shaved porous (submicron-micron) three-dimensional-printed Ti6Al4V implant. The implant surface, modified with submicron-sized pores through microarc oxidation (MAO), showed enhanced osteogenic activity and integrated well with the hydrogel drug release system, enabling sustained vancomycin release. In vitro experiments underscored the commendable antibacterial ability, biosafety, and osteoinductive potential. Effective antibacterial and osteogenic abilities of the implant were further demonstrated in vivo in infected rabbit bone defects. These results showed that the vancomycin-encapsulated hydrogel-loaded microarc-oxidized 3D-printed porous Ti6Al4V can repair the infected bone defects with satisfactory anti-infection and osseointegration effects.

In this paper, the stress–strain curves of Ti2AlNb are established based on uniaxial impact tests over wide ranges of temperature and strain rate. The Ti2AlNb exhibited the work hardening effect but did not show an obvious yield stage during a quasi-static compression test. In the SHPB test, an obvious temperature softening effect was found, the strain rate strengthening effect was detected when the strain rate was 4000–8000 s−1, and the strain rate softening effect was detected in the range of 8000–12,000 s−1. A function describing the effect of strain rate on the strain rate strengthening parameters under various temperatures was proposed to modify the basic J-C constitutive model. The relative errors between the experimental measured value and predicted values in various experimental conditions with a modified J-C model were less than 5.0%. The results verified that the modified J-C model could accurately describe the dynamic mechanical properties of Ti2AlNb at high temperatures and strain rates. The research could help to illustrate the cutting mechanism and finite element simulation of Ti2AlNb alloy.

Steam pretreatment at high temperatures enables fresh bamboo to possess antifungal and antiseptic properties. The process produces a large amount of wastewater that urgently needs to be recycled. Soluble bio-tars derived from wastewater under low-temperature (LTS-tar) and high-temperature (HTS-tar) steam pretreatments of moso bamboo were studied with a thermogravimetric analyzer coupled with Fourier transform infrared spectroscopy (TG–FTIR) and pyrolysis–gas-chromatography/mass spectrometry (Py–GC/MS). Thermogravimetric analysis showed that in the three stages of the thermal decomposition process, the final residue of the bamboo and HTS-tar had two main peaks of 0.88 wt% and 6.85 wt%. The LTS-tar had much more complicated thermal decomposition behavior, with six steps and a high residue yield of 23.86 wt%. A large quantity of CH4 was observed at the maximum mass loss rates of the bamboo and bio-tars. Acids, aldehydes, ketones, esters, and phenolic compounds were found in the pyrolysis products of the bamboo and soluble bio-tars. Both bio-tars contained carbohydrates and lignin fragments, but the LTS-tar under mild steam conditions had more saccharides and was much more sensitive to temperature. The lignin in the bamboo degraded under harsh steam conditions, resulting in high aromatic and polymeric features for the HTS-tar. The significant differences between LTS-tar and HTS-tar require different techniques to achieve the resource utilization of wastewater in the bamboo industry.

The catalytic oxidation of alcohols is an important transformation in the chemical industry. Carbon materials with a large surface area and N doping show great promise as metal-free catalysts for the reaction. In this study, a rich N-containing covalent triazine framework polymerized by cyanuric chloride and p-phenylenediamine was used to synthesize N-doped porous carbon with the assistance of a pore-forming agent—NaCl. First, the mass ratio of the polymer/NaCl was optimized to 1:9. Then, the influence of the pyrolysis temperatures (700–1000 °C) on the materials was studied in detail. It was found that the carbon materials were gradually exfoliated by molten salt at high temperatures. XRD and Raman characterizations showed them with a certain graphitization. The optimal doped carbon CNN-1-9-900 achieved the highest surface area of 199.03 m2g−1 with the largest pore volume of 0.29 cm3g−1. Furthermore, it had a high N content of 9.9 at% with the highest relative proportion of pyridinic/graphitic N. Due to the synergistic effect between the surface area and pyridinic/graphitic N, CNN-1-9-900 showed the best performance for benzyl alcohol oxidation with TBHP at moderate conditions, and the process also worked for its derivatives.

Introduction: Medication-overuse headache (MOH) is a secondary chronic headache disorder that occurs in individuals with a pre-existing primary headache disorder, particularly migraine disorder. Obesity is often combined with chronic daily headaches and is considered a risk factor for the transformation of episodic headaches into chronic headaches. However, the association between obesity and MOH among individuals with migraine has rarely been studied. The present study explored the association between body mass index (BMI) and MOH in people living with migraine. Methods: This cross-sectional study is a secondary analysis of data from the Survey of Fibromyalgia Comorbidity with Headache study. Migraine and MOH were diagnosed using the criteria of the International Classification of Headache Disorders, 3rd edition. BMI (kg/m2) is calculated by dividing the weight (kg) by the square of the height (m). Multivariable logistic regression analysis was used to evaluate the association between BMI and MOH. Results: A total of 2,251 individuals with migraine were included, of whom 8.7% (195/2,251) had a concomitant MOH. Multivariable logistic regression analysis, adjusted for age, sex, education level, headache duration, pain intensity, headache family history, chronic migraine, depression, anxiety, insomnia, and fibromyalgia, demonstrated there was an association between BMI (odds ratio [OR], 1.05; 95% confidence interval [CI], 1.01–1.11; P = 0.031) and MOH. The results remained when the BMI was transformed into a category. Compared to individuals with Q2 (18.5 kg/m2 ≤ BMI ≤ 23.9 kg/m2), those with Q4 (BMI ≥ 28 kg/m2) had an adjusted OR for MOH of 1.81 (95% CI, 1.04-3.17; P = 0.037). In the subgroup analyses, BMI was associated with MOH among aged more than 50 years (OR, 1.13; 95%, 1.03-1.24), less than high school (OR, 1.08; 95%, 1.01-1.15), without depression (OR, 1.06; 95%, 1.01-1.12), and without anxiety (OR, 1.06; 95%, 1.01-1.12). An association between BMI and MOH was found in a sensitivity analysis that BMI was classified into four categories according to the World Health Organization guidelines. Conclusion: In this cross-sectional study, BMI was associated with MOH in Chinese individuals with migraine.

Cadmium (Cd) is the most serious heavy metal pollutant in the agricultural soil of China and can transfer and accumulate through the food chain and affect the growth, development and physiological processes of phytophagous insect. Glyphodes pyloalis Walker (G. pyloalis) is one of the most important pests of mulberry, and there are few studies on the adverse effects of heavy metals on insects, especially mulberry pests. To understand the toxicology of Cd exposure on G. pyloalis, we investigated the effects of three different concentrations of Cd (0, 3.89 and 51.69 mg/kg, labeled as control check (CK), low dose (LD) and high dose (HD)) on the development and detoxification mechanism of G. pyloalis and explored the molecular mechanism of Cd on G. pyloalis larvae using RNA-seq technology. Transcriptome analysis showed that compared with the CK, a total of 63 differentially expressed genes (DEGs) were identified in LD exposure, including 24 upregulated and 39 downregulated candidates. In CK versus HD groups, 395 upregulated DEGs and 436 downregulated DEGs were identified and the expression patterns of 12 genes related to detoxification and metabolism were verified using qPCR. These DEGs were relevant to multiple specific peroxisome and drug metabolism-cytochrome P450 pathways. Gene annotation and quantitative real-time PCR revealed that a high concentration of Cd significantly stimulated the expression of metabolic detoxification enzyme genes. The results revealed that Cd exposure changed the pupal weight, adult emergence rate and the activities of AKP, ACP and GST in G. pyloalis and induced notable adverse effects at the molecular level on detoxification and metabolism such as concentration and time differences. In addition, we silenced CYP12A2 by RNA interference. Bioassays showed that after silencing CYP12A2, the survival rate of G. pyloalis under Cd exposure was lower than that of the control group.

Currently, several types of inhalable liposomes have been developed. Among them, liposomal pressurized metered-dose inhalers (pMDIs) have gained much attention due to their cost-effectiveness, patient compliance, and accurate dosages. However, the clinical application of liposomal pMDIs has been hindered by the low stability, i.e., the tendency of the aggregation of the liposome lipid bilayer in hydrophobic propellant medium and brittleness under high mechanical forces. Biomineralization is an evolutionary mechanism that organisms use to resist harsh external environments in nature, providing mechanical support and protection effects. Inspired by such a concept, this paper proposes a shell stabilization strategy (SSS) to solve the problem of the low stability of liposomal pMDIs. Depending on the shell material used, the SSS can be classified into biomineralization (biomineralized using calcium, silicon, manganese, titanium, gadolinium, etc.) biomineralization-like (composite with protein), and layer-by-layer (LbL) assembly (multiple shells structured with diverse materials). This work evaluated the potential of this strategy by reviewing studies on the formation of shells deposited on liposomes or similar structures. It also covered useful synthesis strategies and active molecules/functional groups for modification. We aimed to put forward new insights to promote the stability of liposomal pMDIs and shed some light on the clinical translation of relevant products.

In view of the ecological threat posed by cyanobacteria blooms in Taihu Lake (China), this paper presents a study on the area of cyanobacteria extent based on MODIS data using the quantum particle swarm optimization–random forest (QPSO-RF) machine learning algorithm. This paper selects multiple remote sensing input indices that can represent the characteristics of the primary underlying type in Taihu Lake. The proposed method performs best, with an F1 score of 0.91–0.98. Based on this method, the spatio-temporal variation of cyanobacteria blooms in the Taihu Lake complex was analyzed. During 2010–2022, the average area of cyanobacteria blooms in Taihu Lake increased slightly. Severe-scale cyanobacteria blooms occurred in 2015–2019. Cyanobacteria blooms were normally concentrated from May to November. However, the most prolonged extended duration occurred in 2017, lasting for eight months. Spatially, cyanobacteria blooms were mainly identified in the northwestern part of Taihu Lake, with an average occurrence frequency of about 10.0%. The cyanobacteria blooms often began to grow in the northwestern part of the lake and then spread to the Center of the Lake, and also dissipated earliest in the northwestern part of the lake. Our study is also beneficial for monitoring the growth of cyanobacteria blooms in other similar large lakes in long time series.

The objective of few-shot fine-grained learning is to identify subclasses within a primary class using a limited number of labeled samples. However, many current methodologies rely on the metric of singular feature, which is either global or local. In fine-grained image classification tasks, where the inter-class distance is small and the intra-class distance is big, relying on a singular similarity measurement can lead to the omission of either inter-class or intra-class information. We delve into inter-class information through global measures and tap into intra-class information via local measures. In this study, we introduce the Feature Fusion Similarity Network (FFSNet). This model employs global measures to accentuate the differences between classes, while utilizing local measures to consolidate intra-class data. Such an approach enables the model to learn features characterized by enlarge inter-class distances and reduce intra-class distances, even with a limited dataset of fine-grained images. Consequently, this greatly enhances the model's generalization capabilities. Our experimental results demonstrated that the proposed paradigm stands its ground against state-of-the-art models across multiple established fine-grained image benchmark datasets.