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Abstract Leveraging its ability to handle large and complex datasets, artificial intelligence can uncover subtle patterns and correlations that human observation may overlook. This is particularly valuable for understanding the intricate dynamics of spinal surgery and its multifaceted impacts on patient prognosis. This review aims to delineate the role of artificial intelligence in spinal surgery. A search of the PubMed database from 1992 to 2023 was conducted using relevant English publications related to the application of artificial intelligence in spinal surgery. The search strategy involved a combination of the following keywords: "Artificial neural network," "deep learning," "artificial intelligence," "spinal," "musculoskeletal," "lumbar," "vertebra," "disc," "cervical," "cord," "stenosis," "procedure," "operation," "surgery," "preoperative," "postoperative," and "operative." A total of 1,182 articles were retrieved. After a careful evaluation of abstracts, 90 articles were found to meet the inclusion criteria for this review. Our review highlights various applications of artificial neural networks in spinal disease management, including (1) assessing surgical indications, (2) assisting in surgical procedures, (3) preoperatively predicting surgical outcomes, and (4) estimating the occurrence of various surgical complications and adverse events. By utilizing these technologies, surgical outcomes can be improved, ultimately enhancing the quality of life for patients.

Abstract Background Many personnel respond to natural disasters like earthquakes and tsunamis and frequent public health events like Ebola and COVID-19. However, research on emergency assistance personnel remains limited. This study aims to describe the perceived well-being among responders deployed in isolated or emergency international missions while providing practical references to intervene in developing similar missions. Methods For this qualitative phenomenological study, purposive sampling was used following the principle of maximum differentiation to select personnel deployed on an emergency mission for over a year. Data collection continued until data saturation. Phenomenologically semi-structured interviews helped explore the physical and psychological status of the participants with Colaizzi’s method. Results Eleven personnel were interviewed after the mission, with four major themes being identified: ‘perceived somatic change,’ ‘perceived emotional change,’ ‘behavioral change,’ and ‘coping with perceived change.’ Conclusions The mental health status of the emergency assistance personnel was affected by multiple factors from external and internal environments. The current study explored the physical and psychological feelings and emotions of emergency assistance personnel during an emergency mission. The study provided a practical reference for health management under similar missions. Registrations Not registered.

Abstract Understanding the impacts of COVID-19 on citizens from different cities is crucial for urban resilience-building and reducing inequal resilience distribution. However, little research focuses on urban life at the individual level, particularly in second- and third-tier cities. An online survey was therefore conducted to collect data on how COVID-19 affected the cities and urban residents in mainland China. The results indicate that COVID-19 limited citizens’ access to healthcare facilities and socioeconomic activities apart from the immediate health crisis. Most citizens suffered reduced income, unemployment, and social anxiety. However, COVID-19 also raised social awareness and actions for disaster adaptation. The Chinese pandemic management has strengthened governmental leadership and credibility among most citizens in the early stage. Importantly, the results suggested that citizens in first-tier cities appeared more resilient to pandemics than those in second-tier cities. A networked resilience framework was therefore discussed for resilience-building policy implications.

Solid oral controlled release formulations feature numerous clinical advantages for drug candidates with adequate solubility and dissolution rate. However, most new chemical entities exhibit poor water solubility, and hence are exempt from such benefits. Although combining drug amorphization with controlled release formulation is promising to elevate drug solubility, like other supersaturating systems, the problem of drug recrystallization has yet to be resolved, particularly within the dosage form. Here, we explored the potential of an emerging, non-leachable terpolymer nanoparticle (TPN) pore former as an internal recrystallization inhibitor within controlled release amorphous solid dispersion (CRASD) beads comprising a poorly soluble drug (celecoxib) reservoir and insoluble polymer (ethylcellulose) membrane. Compared to conventional pore former, polyvinylpyrrolidone (PVP), TPN-containing membranes exhibited superior structural integrity, less crystal formation at the CRASD bead surface, and greater extent of celecoxib release. All-atom molecular dynamics analyses revealed that in the presence of TPN, intra-molecular bonding, crystal formation tendency, diffusion coefficient, and molecular flexibility of celecoxib were reduced, while intermolecular H-bonding was increased as compared to PVP. This work suggests that selection of a pore former that promotes prolonged molecular separation within a nanoporous controlled release membrane structure may serve as an effective strategy to enhance amorphicity preservation inside CRASD.

Abstract Background Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. Methods We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI. Results Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance. Conclusions This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.

This study delves into the intricate usage of certainty stance adverbs in the academic writings of the Chinese. The object of this study is to conduct a contrastive analysis of certainty stance adverbs between Chinese linguistic MA novices and linguistic experts. The subject of this study is to explore the similarities and differences in the use of these adverbs within the academic discourse of the two groups mentioned. In addressing these disparities, the study seeks to analyze them from the perspective of interlanguage and interpersonal function, with the ultimate goal of enhancing the production of high-quality academic papers by the Chinese. The study employs two key methods: the contrastive analysis method and the corpus-based method. The novelty of the study lies in its contrastive examination of certainty stance adverbs between Chinese linguistic MA novices and experts. Through an in-depth analysis of theoretical frameworks and linguistic data extracted from the MA theses of Chinese linguistic novices and research articles of linguistic experts, the study underscores the importance of considering the similarities and differences in the use of certainty stance adverbs within the realm of second language acquisition and pragmatic studies. This consideration aims to refine learners’ syntactical and pragmatic command of certainty stance adverbs to align with expert academic discourse, ultimately fostering effective interpersonal communication in academic writing. The findings of this research offer valuable insights into the specific linguistic challenges encountered by the Chinese, thereby laying a solid groundwork for the development of targeted pedagogical strategies to bolster their academic writing skills.

The investigation of staggered finned manifold microchannel (MMC) for addressing thermal management challenges in high heat flux electronic devices presents promising insights. The research indicates that staggered finned MMCs exhibit superior heat transfer characteristics in comparison to traditional rectangular microchannels, particularly under single-phase flow conditions. When staggered finned microchannels reduce the maximum temperature of the heating surface by around 10 K, the pressure drop is reduced by 1.3 kPa. Notably, as the heat flux escalates, the advantages of staggered finned MMCs become increasingly pronounced, while higher flow rates lead to a gradual diminishment of these advantages. Furthermore, in scenarios involving flow boiling with low heat flux and high flow conditions, staggered finned MMCs demonstrate enhanced heat transfer performance over traditional rectangular microchannels. When staggered finned microchannels reduce the maximum temperature of the heating surface by around 3 K, the pressure drop is improved by 1.2 kPa. Moreover, the study underscores that at lower flow rates, staggered finned MMCs experience a reduced pressure drop relative to traditional rectangular microchannels, whereas at higher flow rates, this trend is reversed. These findings carry significant implications for the optimization of thermal management strategies for electronic devices operating under high heat flux conditions.

Background: Symptomatic Tarlov cysts are extremely rare, and there is no consensus on the optimal treatment for this condition. Here, we encountered a patient with a symptomatic giant sacral Tarlov cyst and reviewed the relevant literature.Case descriptionA 55-year-old male patient was diagnosed with a large sacral canal cyst based on an MRI examination four years ago. Due to mild symptoms, the patient received conservative treatment. In 2023, the patient's symptoms worsened, significantly affecting daily activities. It was suspected that the symptoms were related to the cyst. Subsequently, the patient underwent laminectomy and microsurgical excision of the cyst. Postoperatively, the patient experienced an improvement in symptoms. We conducted a review of the surgical approach used for this patient and explored alternative treatment methods proposed in the literature for similar conditions. Conclusions: We achieved favorable outcomes by performing microsurgical excision of symptomatic giant Tarlov cysts in a 55-year-old patient. Additionally, we reviewed relevant literature regarding Tarlov cysts. The treatment approaches for this condition vary, and conservative, interventional, or surgical treatments have all shown efficacy. Therefore, it is crucial to choose an appropriate treatment plan based on the patient's specific circumstances.

Abstract Purpose We aimed to explore the relationship between bone mineral density (BMD), bone metabolism markers, and blood lipid-related indicators, body mass index (BMI) in elderly individuals. Methods A retrospective analysis was conducted on 710 patients. Patients’ gender, age, height, weight, bone density values, T-scores, bone metabolism markers (including serum N-terminal propeptide of type I collagen (s-PINP), serum C-terminal telopeptide of type I collagen (s-CTX) and 1,25-dihydroxyvitamin D3 (1,25(OH)2D3) and lipid-related indicators (including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG) and Castelli index 1 (TC/HDL-C index) and Castelli index 2 (LDL-C/HDL-C index) were recorded. Correlations between variables were analyzed, and patients were grouped according to gender and T-score for intergroup comparisons. Results HDL-C negatively correlates with BMD and s-CTX. TG, Castelli index, and BMI positively correlate with BMD. BMI negatively correlates with s-PINP. 1,25(OH)2D3 negatively correlates with TC, LDL-C, and Castelli index. LDL-C positively correlates with BMD in males, and TC negatively correlates with s-PINP. In females, HDL-C negatively correlates with BMD, and s-CTX positively correlates with Castelli index. 1,25(OH)2D3 negatively correlates with TC, LDL-C, and Castelli index. TG and Castelli index were higher in normal bone mass group, while HDL-C is higher in the osteoporosis group. TG and BMI positively predicted bone mass density, while HDL-C negatively predicted bone mass density. Conclusions HDL-C may have a predictive role in osteoporosis, particularly in women. The likelihood of osteoporosis is lower in individuals with high BMI or hyperlipidemia. Some lipid metabolism markers can be used to predict osteoporosis, and further research is needed.

For the protection, restoration, and sustainable management of wetland ecosystems, precision in extracting high-quality wetland land cover information is crucial. This study focused on the National Nature Reserve of Liaohe Estuary in Panjin City, Liaoning Province, China. To enhance the classification accuracy of wetland land covers exhibiting similar spectral characteristics and alleviate the occurrence of the ‘salt-and-pepper’ effect, where certain land parcels are erroneously classified into multiple categories by pixel-based methods, an approach integrating object-oriented techniques and temporal features was employed for precise wetland land cover classification. The analysis utilized multi-temporal Sentinel-2 multispectral images. Initially, the images underwent segmentation using the SNIC method to generate uniform polygons, effectively mitigating misclassification issues. Subsequently, texture, geometry, band reflectance, and spectral deviation features were extracted for each segmented object. A total of 57 features, including vegetation and moisture components, were integrated to construct temporal characteristics. By applying the Random Forest (RF) algorithm in combination with Extreme Randomized Trees (ERT), 18 significant features influencing wetland extraction were identified. These selected features were then utilized to train a Random Forest (RF) model for classifying wetland land cover in the study area. The findings revealed that the integrated object-oriented and temporal feature classification approach achieved an impressive overall accuracy of 95.52% and a Kappa coefficient of 0.95 for the Liaohe Estuary wetland region. The accuracy for various land cover types reached 0.87 for both user and producer accuracy. Compared to alternative machine learning algorithms such as SegUnet++, SVM, and RF, the proposed method demonstrated a performance increase of 16.35%, 14.06%, and 6.14%, respectively. The incorporation of temporal features notably reduced land cover misclassifications, resulting in a 6.14% increase in overall accuracy and a 0.07 improvement in the Kappa coefficient compared to a method lacking temporal features. Particularly for categories like canals, aquaculture, rivers, and reservoirs, producer accuracy improved by over 7.5% and user accuracy by more than 2.9%. The effectiveness of the object-oriented approach was evident in addressing the “salt-and-pepper” effect, showcasing a rise of 2.81% in overall accuracy and 0.03 in Kappa coefficient compared to an approach not utilizing object-oriented techniques. In summary, the proposed classification method, integrating object-oriented methods and temporal features, offers superior accuracy in fine wetland land cover classification and mapping.

The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and they improve the time and efficiency of urban flood emergency decision-making. HIGHLIGHTS The GPU-based hydrodynamic model is used to evaluate sponge city rainstorm inundation.; Significant speedup of the model executed on multi-GPU compared to a single GPU.; The model is efficient for performing high-resolution sponge city inundation simulation.; Validation and speedup computing performance tests on real urban city-scale areas.;

High-resolution (HR) optical remote sensing images are typically small in swath and, due to cloud cover, their revisit period, mosaic error, and other problems, it is often infeasible to obtain a large range of remote sensing images for a study area. Meanwhile, low-resolution (LR) satellite images suffer from insufficient spatial and texture information for ground objects. Therefore, classifying a study area with high spatial resolution, large area, and no cloud occlusion using optical remote sensing imagery is very difficult. In recent years, the rapid development of super-resolution reconstruction (SRR) technology has made high-quality spatial resolution reconstruction possible. The SRR of real images is usually accompanied by problems such as sensor spectral range differences, cloud occlusion in the research area, and the SRR algorithm sacrificing a lot of the original information. In this study, with an improved PGGAN, we use only a small number of samples, the wide-swath medium-resolution satellite was restored to the same resolution as the high-resolution satellite, a new method for SRR multi-spectral optical remote sensing image classification based on texture reconstruction information is proposed, and a wide range of high-precision feature classifications are achieved in the study area. In order to solve the problem of spectral distortion in the process of multi-spectral image SRR and the weak generalization of optical remote sensing image ground object classification due to the difference between temporal and spatial features, we combine the idea of ground object classification with texture features obtained after super-resolution reconstruction. We used the support vector machine (SVM) and random forest (RF) classification methods to evaluate the classification effect of each texture spectral feature combination, with the overall accuracy (OA) of the SVM and RF classifiers reaching 98.93% and 98.51%, respectively. The land-use and land-cover (LULC) classification accuracy of the SRR images combined with texture features is much higher than that when directly classifying the original GaoFen-1 and Sentinel-2 images. The obtained results imply that the method of superimposing texture features allows for better classification results in the Liaohe estuary area, providing a new technical idea for the study of LULC classification.

Abstract Background To date, few reports have evaluated the long-term outcome of percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fractures (OVCFs) and the factors influencing the long-term outcome of this procedure are uncertain. Methods A total of 91 patients underwent PKP for thoracolumbar OVCFs from June 2012 to December 2012. Pain Visual Analogue Scores (VAS) and Oswestry Disability Index (ODI) were recorded preoperatively and after 10-year follow-up. Factors that may affect surgical outcome, such as gender, age, height, weight, hypertension, diabetes, cause of injury, fracture segment, length of hospitalization, history of previous spinal surgery, preoperative bone mineral density (BMD), preoperative VAS and ODI scores, length of surgery, bone cement dosage, postoperative standardized anti-osteoporosis treatment, and other new vertebral fractures, were analyzed by multiple linear regression with VAS and ODI scores at the last follow-up. The correlation factors affecting the efficacy were analyzed. Results The preoperative and final follow-up pain VAS was 7.9 ± 1.1 and 2.2 ± 1.1. ODI scores were 30.4 ± 4.2 and 10.7 ± 2.6. The difference was statistically significant (P 0.05). Conclusion The long-term outcome after PKP is satisfactory. Age, gender, cause of injury, and standardized postoperative anti-osteoporosis treatment may be factors affecting the long-term outcome.

This study is a bibliometric analysis of urban studies publications from 2001 to 2021 that unravels the evolution and growing complexity of the field. Although developed regions still dominate and lead this area of inquiry, urban studies led by Asian scholars have increased dramatically over the last decade. There is also topic diffusion from developed regions to less-developed regions despite some unique emphases within each region caused by their local socio-economic-ecological contexts. Climate change adaptation and sustainable development, inequality, and urban governance are receiving growing attention globally. The findings suggest the rising importance of cross-continent knowledge transfer and multi-disciplinary collaboration, particularly among urban studies, sustainability policies and management, public administration, and development studies. Also, urban researchers need to pay more attention to issues faced by many growing cities in developing economies in Asia and Africa as more of the world's population will reside in those urban settings in the coming decades.

Long-term exposure to ultraviolet (UV) rays can result in skin photoaging, which is primarily characterized by dryness, roughness, pigmentation, and a loss of elasticity. However, the clinical drugs commonly employed to treat photoaged skin often induce adverse effects on the skin. Anthocyanins (ACNs) are water-soluble pigments occurring abundantly in various flowers, fruits, vegetables, and grains and exhibiting a range of biological activities. Studies have demonstrated that ACNs contribute to the repair of photoaged skin due to their diverse biological characteristics and minimal side effects. Evidence suggests that the stability of ACNs can be enhanced through encapsulation or combination with other substances to improve their bioavailability and permeability, ultimately augmenting their efficacy in repairing photoaged skin. A growing body of research utilizing cell lines, animal models, and clinical studies has produced compelling data demonstrating that ACNs mitigate skin photoaging by reducing oxidative stress, alleviating the inflammatory response, improving collagen synthesis, alleviating DNA damage, and inhibiting pigmentation. This review introduces sources of ACNs while systematically summarizing their application forms as well as mechanisms for repairing photoaged skin. Additionally, it explores the potential role of ACNs in developing functional foods. These findings may provide valuable insight into using ACNs as promising candidates for developing functional products aimed at repairing photoaged skin.

In recent years, accurate field monitoring has been a research hotspot in the domains of aerial remote sensing and satellite remote sensing. In view of this, this study proposes an innovative cross-platform super-resolution reconstruction method for remote sensing images for the first time, aiming to make medium-resolution satellites capable of field-level detection through a super-resolution reconstruction technique. The progressive growing generative adversarial network (PGGAN) model, which has excellent high-resolution generation and style transfer capabilities, is combined with a deep residual network, forming the Res-PGGAN model for cross-platform super-resolution reconstruction. The Res-PGGAN architecture is similar to that of the PGGAN, but includes a deep residual module. The proposed Res-PGGAN model has two main benefits. First, the residual module facilitates the training of deep networks, as well as the extraction of deep features. Second, the PGGAN structure performs well in cross-platform sensor style transfer, allowing for cross-platform high-magnification super-resolution tasks to be performed well. A large pre-training dataset and real data are used to train the Res-PGGAN to improve the resolution of Sentinel-2’s 10 m resolution satellite images to 0.625 m. Three evaluation metrics, including the structural similarity index metric (SSIM), the peak signal-to-noise ratio (PSNR), and the universal quality index (UQI), are used to evaluate the high-magnification images obtained by the proposed method. The images generated by the proposed method are also compared with those obtained by the traditional bicubic method and two deep learning super-resolution reconstruction methods: the enhanced super-resolution generative adversarial network (ESRGAN) and the PGGAN. The results indicate that the proposed method outperforms all the comparison methods and demonstrates an acceptable performance regarding all three metrics (SSIM/PSNR/UQI: 0.9726/44.7971/0.0417), proving the feasibility of cross-platform super-resolution image recovery.

Abstract Background Exercise is postulated to be a promising non-pharmacological intervention for the improvement of neurodegenerative disease pathology. However, the mechanism of beneficial effects of exercise on the brain remains to be further explored. In this study, we investigated the effect of an exercise-induced metabolite, lactate, on the microglia phenotype and its association with learning and memory. Results Microglia were hyperactivated in the brains of AlCl3/D-gal-treated mice, which was associated with cognitive decline. Running exercise ameliorated the hyperactivation and increased the anti-inflammatory/reparative phenotype of microglia and improved cognition. Mice were injected intraperitoneally with sodium lactate (NaLA) had similar beneficial effects as that of exercise training. Exogenous NaLA addition to cultured BV2 cells promoted their transition from a pro-inflammatory to a reparative phenotype. Conclusion The elevated lactate acted as an “accelerator” of the endogenous “lactate timer” in microglia promoting this transition of microglia polarization balance through lactylation. These findings demonstrate that exercise-induced lactate accelerates the phenotypic transition of microglia, which plays a key role in reducing neuroinflammation and improving cognitive function.

Abstract Background Abnormal serum ferritin levels are associated with a variety of diseases. Meanwhile, abnormal serum ferritin is influenced by a variety of risk factors, but its correlation with obesity remains poorly described. Objective This study aimed to investigate the association of body mass index (BMI) and weight waist adjustment index (WWI) with serum ferritin in US adults. Methods Participants in this study took part in the National Health and Nutrition Examination Survey (NHANES) prior to the pandemic from 2017 to March 2020. Serum ferritin was used as the sole response variable and BMI and WWI were used as independent variables. Multiple linear regression was used to assess the relationship between serum ferritin and the independent variables, and smoothed curve fitting and threshold effects analysis were performed to assess the presence of non-linear relationships. To validate the sensitive individuals for the correlation between the independent and the dependent variables, a subgroup analysis was performed. Results A final total of 7552 participants were included in this study. Both independent variables had a positive relationship with serum ferritin, with effect values of (β = 0.68, 95% CI: 0.17–1.19) when BMI was the independent variable and (β = 8.62, 95% CI: 3.53–13.72) when WWI was the independent variable in the fully adjusted model. This positive association between the two obesity-related indexes and serum ferritin became more significant as BMI and WWI increased (P for trend

Abstract Background The aim of this study was to comprehensively evaluate the short-term clinical efficacy and safety of unilateral biportal endoscopic transforaminal lumbar interbody fusion (UBE-TLIF) versus minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) for the treatment of lumbar degenerative diseases by meta-analysis. Methods A computer-based search of PubMed, Embase, Web of Science, Cochrane Database, China National Knowledge Infrastructure (CNKI), Wanfang Database, and Chinese Science and Technology Journal Database (VIP) was conducted from the inception of the each database to April 2023. The searched literature was then screened according to strict inclusion and exclusion criteria. The critical data were extracted and analyzed using Review Manager software5.4.1. Pooled effects were calculated on the basis of data attributes by mean difference (MD) or odds ratio (OR) with 95% confidence interval (CI). The Newcastle–Ottawa Scale was used to assess the quality of the studies. Results A total of 13 studies and 949 patients met the inclusion criteria for this meta-analysis, 445 in the UBE-LIF group and 504 in the MIS-TLIF group. UBE-TLIF was superior to MIS-TLIF in terms of intraoperative blood flow, postoperative drainage flow, duration of hospital stay, VAS score for low back pain and ODI score, but the operative time was longer than MIS-TLIF group. There were no significant differences between the two groups in terms of total complication rate, modified Macnab grading criteria, fusion rate, VAS score of leg pain, lumbar lordosis, intervertebral disk height. Conclusion Both UBE-TLIF and MIS-TLIF are effective surgical modalities for the treatment of degenerative lumbar spine diseases. They have similar treatment outcomes, but UBE-TLIF has the advantages of less intraoperative blood loss, shorter postoperative hospital stay, and faster recovery. Trial registration: This study has been registered at INPLASY.COM (No. INPLASY202320087).

In order to determine the effect of different silicon window areas on the preservation of garlic in silicon windows, garlic was packed in polyethylene (PE) bags with an area of 30 cm×25 cm at low temperature in combination with 1, 3, 6 and 9 cm2 silicon window films, and a control group of polyethylene (PE) bags without silicon windows, and the quality indexes were measured within 120 d of storage. The results showed that the area of the silicon window had a greater influence on the weight loss, bud to cloves ratio and colour (ΔE) of the garlic after harvesting, and a smaller influence on the hardness and water content was observed. The optimal silicon window area was 6 cm2, the alliin content of garlic in the low temperature combined with 6 cm2 silicon window treatment group reached 0.38±0.00 g/100 g during 120 days of storage. Compared with 0 d, the alliin content increased by 50.97%, the malic acid content decreased by 92.38%, and the contents of citric acid, tartaric acid and fumaric acid increased by 21.13%, 65.87% and 43.26% respectively. The principal component analysis revealed that the key indicators of garlic freshness were ΔE value, weight loss, shoot to clove ratio, water content and tartaric acid content. Considering the variation of each index and the results of the principal component analysis, it was concluded that the use of 6 cm2 silicon window area combined with 30 cm×25 cm polyethylene (PE) bags at low temperature could effectively alleviate the deterioration of garlic storage quality. This study can provide a theoretical reference for the storage and processing of white-skinned garlic.

Groundwater resources are essential for sustaining ecosystems and human activities, especially under the pressures of climate change. This study employed Electrical Resistivity Tomography (ERT) to assess the impact of Gully Land Consolidation (GLC) engineering on the groundwater hydrological field of small watersheds in the China Loess Plateau (CLP). Results revealed ample subsurface water storage in backfilled areas, primarily migrating along the original river path owing to topographical limitations. Although the distribution patterns of soil moisture in each backfilling block varied slightly, the boundaries of soil moisture content and variation mainly appeared at depths of 8 m and 20 m underground. Significant moisture variation occurred across the 0–20 m underground layers, suggesting the 8–20 m layer could function as a groundwater collection zone in the study area. Human activities could disturb groundwater, altering migration pathways from the original river path. An optimized “Drainage–Conveyance–Barrier” system is proposed to enhance GLC sustainability, involving upstream groundwater level control, midstream soil moisture management, and downstream hydrological connectivity improvement. These findings carry substantial implications for guiding the planning and execution of GLC engineering initiatives. The novelty of this study lies in its application of ERT to provide a detailed spatial and temporal understanding of soil moisture dynamics in the GLC areas. Future research should focus on factors such as soil types and topographical changes for a comprehensive assessment of GLC’s impact on small watershed groundwater hydrology.

Abstract Objectives This study aimed to evaluate the clinical efficacy and safety of percutaneous endoscopic interlaminar discectomy (PEID) for treating highly downward-migrated disc herniation. Methods We conducted a retrospective study on 39 patients with highly downward-migrated disc herniation who underwent PEID treatment between January 2015 and October 2020. The clinical outcomes, including the preoperative and postoperative visual analogue scale (VAS) for the back and leg, Oswestry Disability Index (ODI), and MacNab criteria for surgical success, were evaluated and compared to thirty-seven patients treated with posterior lumbar interbody fusion (PLIF). Results The mean operation time of PEID was 93.00(77.00,110.00) min, while that of PLIF was 169.00(157.00,183.00) min. Continued improvement in both PEID and PLIF was observed in the VAS and ODI scores immediately after the surgery to the last follow‐up. The VAS and ODI scores of PEID one week after surgery were significantly different from those of PLIF. One patient with recurrent lumbar disc herniation in the same segment improved after undergoing repeat PEID, two patients had dura tears, and conservative treatment helped relieve the symptoms. The overall percentage of patients with good to excellent results of PELD according to the modified MacNab criteria was 97.43%, while that of PLIF was 94.60%. Conclusions PEID has reliable efficacy and safety for treating highly downward-migrated disc herniation. And the long-term efficacy of PEID is comparable to PLIF. No severe complications occurred after surgery, and most patients’ symptoms were relieved.

Abstract Cuproptosis is a form of regulated cell death, which is characterized by the lethal accumulation of excessive copper in cells. However, its role in colon adenocarcinoma (COAD) remains elusive. Our study aimed to decipher the biological function of cuproptosis‐related genes (CRGs) in patients with COAD. The expression data were obtained from The Cancer Genome Atlas, while the Gene Expression Omnibus database was used to verify the results. A total of eight differentially expressed CRGs were selected from patients with COAD. Subsequently, patients were stratified into three subtypes with distinct clinical and biological features. In view of the huge differences in the prognosis between subtypes A and C, we selected them for further study, including the variations in clinical progressions, oncogenic pathways, and immune cell infiltration. For the sake of better evaluation, we also established a cuproptosis index (CI) to quantify the heterogeneity of CRGs expression. Enrichment analysis showed that the high‐CI group was enriched in immune activation pathways. Meanwhile, the immunosuppressive cell infiltration and immune checkpoints were elevated in the high‐CI group. The CI we constructed had its predicting function in different clinical groups. Besides, we noticed that CRGs, especially CDKN2A, were closely related to the clinical progression in patients with COAD and immune cell infiltration in tumors. Moreover, CDKN2A could become a potential novel target for immunotherapy in the setting of COAD.

BackgroundThe long non-coding RNA cancer susceptibility candidate (CASC) has abnormal expression in lung cancer tissues and may correlate with lung cancer prognosis. This study aimed to comprehensively evaluate the association between CASC expression and the cancer prognosis.MethodsPubMed, Embase, Web of Science, Google Scholar, Cochrane Library, and China National Knowledge Infrastructure databases were searched until April 1, 2023, to obtain the relevant literature. Studies that met the predefined eligibility criteria were included, and their quality was independently assessed by 2 investigators according to the Newcastle-Ottawa Scale (NOS) score. Detailed information was obtained, such as first author, year of publication, and number of patients. Hazard ratio (HR) with a 95% confidence interval (CI) was extracted and grouped to assess the relationship between CASC expression and cancer prognosis. The dichotomous data was merged and shown as the odds ratio (OR) with a 95% CI was extracted to assess the relationship between CASC expression and clinicopathological parameters.ResultsA total of 12 studies with 746 patients with lung cancer were included in the meta-analysis. The expression levels of lncRNA CASC2 and CASC7 were decreased, while those of CASC9, 11, 15, and 19 were induced in lung cancer tissues compared with paracancerous tissues. In the population with low CASC expression (CASC2 and CASC7), high CASC expression indicated a good lung cancer prognosis (HR = 0.469; 95% CI, 0.271-0.668). Conversely, in the population with high CASC expression (CASC9, 11, 15, and 19), high CASC expression predicted a poor lung cancer outcome (HR = 1.910; 95% CI, 1.628-2.192). High CASC expression also predicted worse disease-free survival (DFS) (HR = 2.803; 95% CI, 1.804-6.319). Combined OR with 95% CI revealed an insignificant positive association between high CASC expression and advanced TNM stage (OR = 1.061; 95% CI, 0.775-1.454), LNM (OR = 0.962; 95% CI, 0.724-1.277), tumor size (OR = 0.942; 95% CI, 0.667-1.330), and histological grade (OR = 1.022; 95% CI, 0.689-1.517).ConclusionThe CASC expression levels negatively correlate with lung cancer prognosis. Therefore, CASC expression may serve as a prognostic marker and a potential therapeutic target for lung cancer.

Abstract The novel targeted therapeutics for hepatitis C virus (HCV) in last decade solved most of the clinical needs for this disease. However, despite antiviral therapies resulting in sustained virologic response (SVR), a challenge remains where the stage of liver fibrosis in some patients remains unchanged or even worsens, with a higher risk of cirrhosis, known as the irreversible group. In this study, we provided novel tissue level collagen structural insight into early prediction of irreversible cases via image based computational analysis with a paired data cohort (of pre- and post-SVR) following direct-acting-antiviral (DAA)-based treatment. Two Photon Excitation and Second Harmonic Generation microscopy was used to image paired biopsies from 57 HCV patients and a fully automated digital collagen profiling platform was developed. In total, 41 digital image-based features were profiled where four key features were discovered to be strongly associated with fibrosis reversibility. The data was validated for prognostic value by prototyping predictive models based on two selected features: Collagen Area Ratio and Collagen Fiber Straightness. We concluded that collagen aggregation pattern and collagen thickness are strong indicators of liver fibrosis reversibility. These findings provide the potential implications of collagen structural features from DAA-based treatment and paves the way for a more comprehensive early prediction of reversibility using pre-SVR biopsy samples to enhance timely medical interventions and therapeutic strategies. Our findings on DAA-based treatment further contribute to the understanding of underline governing mechanism and knowledge base of structural morphology in which the future non-invasive prediction solution can be built upon.

Abstract Complex pollutants are discharging and accumulating in rivers and oceans, requiring a coupled strategy to resolve pollutants efficiently. A novel method is proposed to treat multiple pollutants with C,N co-doped TiO2 hollow nanofibers coated stainless steel meshes which can realize efficient oil/water separation and visible light-drove dyes photodegradation. The poly(divinylbenzene-co-vinylbenzene chloride), P(DVB-co-VBC), nanofibers are generated by precipitate cationic polymerization on the mesh framework, following with quaternization by triethylamine for N doping. Then, TiO2 is coated on the polymeric nanofibers via in-situ sol–gel process of tetrabutyl titanate. The functional mesh coated with C,N co-doped TiO2 hollow nanofibers is obtained after calcination under nitrogen atmosphere. The resultant mesh demonstrates superhydrophilic/underwater superoleophobic property which is promising in oil/water separation. More importantly, the C,N co-doped TiO2 hollow nanofibers endow the mesh with high photodegradation ability to dyes under visible light. This work draws an affordable but high-performance multifunctional mesh for potential applications in wastewater treatment.

This study investigated the bactericidal effects of ultraviolet (UV) radiation, a high-voltage electric field (HVEF), and their combination on Escherichia coli. The results indicated that UV and combined disinfection were more effective with longer exposure, leading to significant reductions in microbial activity. Specifically, the single UV disinfection alone reduced activity by 3.3 log after 5 min, while combined disinfection achieved a 4.2 log reduction. In contrast, short-term HVEF treatment did not exhibit significant bactericidal effects, only achieving a reduction of 0.17 log in 5 min. Furthermore, prolonged exposure to both UV disinfection and an HVEF was found to damage cell membranes, ultimately causing cell death, while shorter durations did not. Despite rapid cell count decreases, flow cytometry did not detect apoptotic or necrotic cells, likely due to rapid cell rupture. This study suggests that combining UV radiation and an HVEF could be a promising approach for inhibiting bacterial reproduction, with HVEF enhancing UV effects. These findings provide insights for using combined HVEF and UV disinfection in food safety and preservation.

Equatorial plasma bubbles (EPBs) occur frequently in low-latitude areas and have a non-negligible impact on navigation satellite signals. To systematically analyze the effects of a single EPB event on multi-frequency signals of GPS, Galileo, GLONASS, and BDS, all-sky airglow images over South China are jointly used to visually determine the EPB structure and depletion degree. The results reveal that scintillations, or GNSS signal fluctuations, are directly linked to EPBs and that the intensity of scintillation is positively correlated with the airglow depletion intensity. The center of the airglow depletion often corresponds to stronger GNSS scintillation, while the edge of the bubble, which is considered to have the largest density gradient, corresponds to relatively smaller scintillation instead. This work also systematically analyzes the responses of multi-constellation and multi-frequency signals to EPBs. The results show that the L2 and L5 frequencies are more susceptible than the L1 frequency is. For different constellations, Galileo’s signal has the best tracking stability during an EPB event compared with GPS, GLONASS, and BDS. The results provide a reference for dual-frequency signal selection in precise positioning or TEC calculation, that is, L1C and L2L for GPS, L1C and L5Q for Galileo, L1P and L2C for GLONASS, and L1P and L5P for BDS. Notably, BDS-2 is significantly weaker than BDS-3. And inclined geosynchronous orbit (IGSO) satellites have abnormal data error rates, which should be related to the special signal path trajectory of the IGSO satellite.

The chemical composition and nutritional content of garlic are greatly impacted by its production location, leading to distinct flavor profiles and functional properties among garlic varieties from diverse origins. Consequently, these variations determine the preference and acceptance among diverse consumer groups. In this study, purple-skinned garlic samples were collected from five regions in China: Yunnan, Shandong, Henan, Anhui, and Jiangsu Provinces. Mid-infrared spectroscopy and ultraviolet spectroscopy were utilized to analyze the components of garlic cells. Three preprocessing methods, including Multiple Scattering Correction (MSC), Savitzky–Golay Smoothing (SG Smoothing), and Standard Normalized Variate (SNV), were applied to reduce the background noise of spectroscopy data. Following variable feature extraction by Genetic Algorithm (GA), a variety of machine learning algorithms, including XGboost, Support Vector Classification (SVC), Random Forest (RF), and Artificial Neural Network (ANN), were used according to the fusion of spectral data to obtain the best processing results. The results showed that the best-performing model for ultraviolet spectroscopy data was SNV-GA-ANN, with an accuracy of 99.73%. The best-performing model for mid-infrared spectroscopy data was SNV-GA-RF, with an accuracy of 97.34%. After the fusion of ultraviolet and mid-infrared spectroscopy data, the SNV-GA-SVC, SNV-GA-RF, SNV-GA-ANN, and SNV-GA-XGboost models achieved 100% accuracy in both training and test sets. Although there were some differences in the accuracy of the four models under different preprocessing methods, the fusion of ultraviolet and mid-infrared spectroscopy data yielded the best outcomes, with an accuracy of 100%. Overall, the combination of ultraviolet and mid-infrared spectroscopy data fusion and chemometrics established in this study provides a theoretical foundation for identifying the origin of garlic, as well as that of other agricultural products.

Millions of people worldwide suffer from intervertebral disc degeneration (IVDD), which imposes a significant socioeconomic burden on society. There is an urgent clinical demand for more effective treatments for IVDD because conventional treatments can only alleviate the symptoms rather than preventing the progression of IVDD. Hydrogels, a class of elastic biomaterials with good biocompatibility, are promising candidates for intervertebral disc repair and regeneration. In recent years, various hydrogels have been investigated in vitro and in vivo for the repair of intervertebral discs, some of which are ready for clinical testing. This review summarizes the latest findings and developments in using bioactive factors-released bioactive injectable hydrogels for the repair and regeneration of intervertebral discs. It focuses on the analysis and summary of the use of multifunctional injectable hydrogels to delivery bioactive factors (cells, exosomes, growth factors, genes, drugs) for disc regeneration, providing guidance for future study. Finally, we discussed and analyzed the optimal timing for the application of controlled-release hydrogels in the treatment of IVDD to meet the high standards required for intervertebral disc regeneration and precision medicine.

The wind turbine power curve model is critical to a wind turbine’s power prediction and performance analysis. However, abnormal data in the training set decrease the prediction accuracy of trained models. This paper proposes a sample average approach-based method to construct an interval model of a wind turbine, which increases robustness against abnormal data and further improves the model accuracy. We compare our proposed methods with the traditional neural network-based and Bayesian neural network-based models in experimental data-based validations. Our model shows better performance in both accuracy and computational time.

Dynamic transmission requirements and the limited cache space bring great challenges to wireless data transmission in the malicious jamming environment.Aiming at the above problems, a collaborative anti-jamming channel selection and data scheduling joint decision method for distributed internet of things was studied from the perspective of frequency domain and time domain.A data transmission model based on multi-user Markov decision process was constructed and a collaborativeanti-jamming joint-channel-and-data decision algorithm based on multi-agent deep reinforcement learning was proposed.Simulation results show that the proposed algorithm can effectively avoid the malicious jamming and the co-channel interference.Compared with the comparison algorithm, the network throughput is significantly improved, and the number of packet dropout is significantly reduced.

In the complex electromagnetic countermeasure environment, the intelligent development of jammer has caused a serious threat to wireless communication, while the traditional anti-jamming methods often passively adjusted the working mode or parameters, which will be at a disadvantage or even suppressed in the face of intelligent jammer.To solve this problem, a technical framework of active defense against jammer was proposed, aiming to disrupt the learning process of the intelligent jammer and reduce the jamming efficacy.In order to gradually achieve the goals of “understanding opponent”“controlling opponent” and “defeating opponent”, under the guidance of game theory and adversarial machine learning, the key technologies were discussed from three aspects: backward reasoning of jammer, algorithm vulnerability analysis and confrontational strategy design, independent optimization and online decision-making of anti-jamming strategy.Finally, combined with two specific cases, the feasibility and effectiveness of the proposed technical framework were verified.

Background At present, it has been controversial whether primary tumor resection (PTR) can bring survival advantage to patients with metastatic small intestine neuroendocrine tumors (SI-NETs). To answer this question, we conducted a retrospective cohort study to evaluate the effect of PTR on the survival of patients with metastatic SI-NETs. Methods Information on SI-NETs patients from 2004 to 2015 was extracted from Surveillance, Epidemiology, and End Results (SEER) databases. Demographics, tumor characteristics, treatment, and survival were compared. Propensity score-matched (PSM) was used 1:1 in the filtered queue. Cox proportional hazard regression model was used to evaluate the correlation between PTR and treatment results. Results Before PSM, survival analysis showed that PTR significantly prolonged the survival of metastatic SI-NETs patients. After PSM, there was no significant difference in overall survival (OS) and cancer-specific survival (CSS) between the PTR group and the non-PTR group. Multivariate analysis showed no significant difference in OS and CSS between the two groups (p > 0.05). Conclusion Our study shows that OS and CSS are comparable between the PTR group and the non-PTR group. Thus, we believe that PTR should not be actively performed on such patients. Meanwhile, it is undeniable that properly selected patients may also benefit from PTR. Therefore, prospective randomized controlled trials are still needed to verify the effect of PTR on patients in the future.

Abstract Background P16INK4A is a surrogate signature compensating for the specificity and/or sensitivity deficiencies of the human papillomavirus (HPV) DNA and Papanicolaou smear (Pap) co‐test for detecting high‐grade cervical squamous intraepithelial lesions or worse (HSIL+). However, traditional p16INK4A immunostaining is labour intensive and skill demanding, and subjective biases cannot be avoided. Herein, we created a high‐throughput, quantitative diagnostic device, p16INK4A flow cytometry (FCM) and assessed its performances in cervical cancer screening and prevention. Methods P16INK4A FCM was built upon a novel antibody clone and a series of positive and negative (p16INK4A‐knockout) standards. Since 2018, 24 100‐women (HPV‐positive/‐negative, Pap‐normal/‐abnormal) have been enrolled nationwide for two‐tier validation work. In cross‐sectional studies, age‐ and viral genotype‐dependent expression of p16INK4A was investigated, and optimal diagnostic parameter cut‐offs (using colposcopy and biopsy as a gold standard) were obtained. In cohort studies, the 2‐year prognostic values of p16INK4A were investigated with other risk factors by multivariate regression analyses in three cervicopathological conditions: HPV‐positive Pap‐normal, Pap‐abnormal biopsy‐negative and biopsy‐confirmed LSIL. Results P16INK4A FCM detected a minimal ratio of 0.01% positive cells. The p16INK4A‐positive ratio was 13.9 ± 1.8% among HPV‐negative NILM women and peaked at the ages of 40–49 years; after HPV infection, the ratio increased to 15.1 ± 1.6%, varying with the carcinogenesis of the viral genotype. Further increments were found in women with neoplastic lesions (HPV‐negative: 17.7 ± 5.0–21.4 ± 7.2%; HPV‐positive: 18.0 ± 5.2–20.0 ± 9.9%). Extremely low expression of p16INK4A was observed in women with HSILs. As the HPV‐combined double‐cut‐off‐ratio criterion was adopted, a Youden's index of 0.78 was obtained, which was significantly higher than that (0.72) of the HPV and Pap co‐test. The p16INK4A‐abnormal situation was an independent HSIL+ risk factor for 2‐year outcomes in all three cervicopathological conditions investigated (hazard ratios: 4.3–7.2). Conclusions FCM‐based p16INK4A quantification offers a better choice for conveniently and precisely monitoring the occurrence of HSIL+ and directing risk‐stratification‐based interventions.

In view of the characteristics and risks of ammonia, its removal is important for industrial production and environmental safety. In this study, viscose-based activated carbon fiber (ACF) was used as a substrate and chemically modified by nitric acid impregnation to enhance the adsorption capacity of the adsorbent for ammonia. A series of modified ACF-based adsorbents were prepared and characterized using BET, FTIR, XPS, and Boehm titration. Isotherm tests (293.15 K, 303.15 K, 313.15 K) and dynamic adsorption experiments were performed. The characterization results showed that impregnation with low concentrations of nitric acid not only increased the surface acidic functional group content but also increased the specific surface area, while impregnation with high concentrations of nitric acid could be able to decrease the specific surface area. ACF-N-6 significantly increased the surface functional group content without destroying the physical structure of the activated carbon fibers. The experimental results showed that the highest adsorption of ammonia by ACFs was 14.08 mmol-L−1 (ACF-N-6) at 293 K, and the adsorption capacity was increased by 165% compared with that of ACF-raw; by fitting the adsorption isotherm and calculating the equivalent heat of adsorption and thermodynamic parameters using the Langmuir–Freundlich model, the adsorption process could be found to exist simultaneously. Regarding physical adsorption and chemical adsorption, the results of the correlation analysis showed that the ammonia adsorption performance was strongly correlated with the carboxyl group content and positively correlated with the relative humidity (RH) of the inlet gas. This study contributes to the development of an efficient ammonia adsorption system with important applications in industrial production and environmental safety.

This study aims at the lubricant film between the slipper and swashplate of an axial piston pump. Based on a single piston/slipper assembly model, a mathematical model for the squeeze film effect is developed according to the pressure-flow transfer process as well as the dynamics of the piston/slipper assembly. The squeeze film effect on the slipper lubricant film has been predicted by nonlinear numerical calculations and computational fluid dynamic (CFD). The slipper lubricant film thickness and leakage flow, sealing land pressure distribution, and load carrying capacity are evaluated as important parameters to indicate the performance of slipper oil film. The influence of piston/slipper assembly geometric parameters, oil compressibility, and oil viscosity on the squeeze film effect under pressure pulse has been studied, and the effect of squeeze film speed on the support force of slipper lubricant film has been given out.

BackgroundLumbar disc herniation (LDH) linked with posterior ring apophysis separation (PRAS) is a rare and distinct subset of disc herniation. Few studies have evaluated the clinical efficacy of percutaneous endoscopic lumbar discectomy (PELD), which is a procedure used to treat LDH linked with PRAS.ObjectivesTo evaluate the clinical efficacy and safety of PELD in the treatment of LDH linked with PRAS.MethodsPatients who met inclusion criteria (n = 67; 40 males and 27 females) underwent PELD. General and operation-related information and perioperative complications of the patients were recorded. Clinical efficacy was measured using the Visual Analog Scale (VAS) and Oswestry Disability Index (ODI) during the follow-up period.ResultsThe mean operation time was 118.04 ± 19.31 min and the mean blood loss was 22.84 ± 15.89 ml. The VAS and ODI scores continued to improve immediately after the surgery to the last follow-up. Four patients experienced postoperative complications i.e., herniation recurrences. The conditions of the patients with the complications improved after treatment.ConclusionsPELD has reliable efficacy and safety in the treatment of LDH linked with PRAS.

The new-generation smart vehicles are intelligent network terminals that integrate smart vehicle, smart transportation, smart city, and smart energy (i.e., 4S integration). They move flexibly to connect the flow of people, materials, energy, and information of a city, and have more strategic values than traditional vehicles. This study aims to clarify the significance in developing the newgeneration smart vehicles based on 4S integration, determine the technology path for the innovative development of the new-generation smart vehicle industry, and establish a novel technology system by summarizing relevant key technologies. The new-generation smart vehicles based on 4S integration is an upgrade of smart vehicles in terms of value, function, and technology. China should select a smart vehicle technology path considering vehicle infrastructure cooperation to acquire the leadership in scientific and technological innovation. To establish the technology system of the new-generation smart vehicles based on 4S integration, the automation and connectivity levels of vehicles should be coordinated simultaneously, and common basic technologies such as big data, cloud computing, information, and communications should be promoted, together with the core key technologies related to vehicles, roads, and cloud. Furthermore, we propose suggestions from the aspects of top-level design, industrial integration, technological innovation, and practical implementation, hoping to provide theoretical references for long-term development of China’s smart vehicle industry.

As the population ages, spinal degeneration seriously affects quality of life in middle-aged and elderly patients, and prevention and treatment remain challenging for clinical surgeons. In recent years, biomaterials-based injectable therapeutics have attracted much attention for spinal degeneration treatment due to their minimally invasive features and ability to perform precise repair of irregular defects. However, the precise design and functional control of bioactive injectable biomaterials for efficient spinal degeneration treatment remains a challenge. Although many injectable biomaterials have been reported for the treatment of spinal degeneration, there are few reviews on the advances and effects of injectable biomaterials for spinal degeneration treatment. This work reviews the current status of the design and fabrication of injectable biomaterials, including hydrogels, bone cements and scaffolds, microspheres and nanomaterials, and the current progress in applications for treating spinal degeneration. Additionally, registered clinical trials were also summarized and key challenges and clinical translational prospects for injectable materials for the treatment of spinal degenerative diseases are discussed.

Abstract This paper investigates the joint relay and channel selection problem using a deep reinforcement learning (DRL) algorithm for cooperative communications in a dynamic jamming environment. The latest types of jammers include the mobile and smart jammer that contains multiple jamming patterns. This new type of jammer poses serious challenges to reliable communications such as huge environment states, tightly coupled joint action selections and real‐time decision requirements. To cope with these challenges, a DRL‐based relay‐assisted cooperative communication scheme is proposed. In this scheme, the joint selection problem is constructed as a Markov decision process (MDP) and a double deep Q network (DDQN) based anti‐jamming scheme is proposed to address the unknown and dynamic jamming behaviors. Concretely, a joint decision‐making network composed of three sub‐networks is designed and the independent learning method of each sub‐network is proposed. The simulation results show that the user agent is able to anticipate the jammer behaviors and elude the jamming in advance. Furthermore, compared with the sensing‐based algorithm, the Q learning‐based algorithm and the existing DRL‐based anti‐jamming approaches, the proposed algorithm maintains a higher average normalized throughput.

Precipitation variations mostly affect the water resource planning in semi-arid regions of northwest China. The objective of this study is to quantitatively explore the spatial and temporal variations of precipitation in different time scales in Xi'an city area. The Mann–Kendall test and wavelet analysis methods were applied to analyze the precipitation variability. In terms of temporal variation of precipitation, the results indicated that the annual precipitation exhibited a significant decreasing trend during 1951–2018. Except for summer precipitation representing a slightly increasing trend, the other seasonal precipitations had a similar decreasing trend to annual precipitation throughout 1951–2018. The monthly precipitation had different change trends, showing the precipitation from June to September could account for 58.4% of the total annual precipitation. In addition, it was clear that annual precipitation had a significant periodic change, with the periods of 6, 13, 19, and 27 years. For the spatial variation of precipitation during 1961–2018, the results showed that annual and seasonal precipitation exhibited obvious spatial differences, indicating an increasing spatial trend from north to south. Thus, understanding the precipitation variation in Xi'an city can provide a theoretical foundation of future water resources management for other cities in semi-arid regions of northwest China. HIGHLIGHTS There were different variation trends in annual, seasonal and monthly precipitation at a temporal scale.; The annual precipitation in Xi'an city had a significantly increasing trend during 1951–2018.; The annual and seasonal precipitation exhibited obvious spatial differences during 1961–2018.; Findings could guide future water resource management and allocation of other cities in semiarid regions of northwest China.;

Berberidis radix polysaccharide (BRP) extracted as capping agents was applied to prepare BRP-selenium nanoparticles (BRP-SeNPs) in the redox reaction system of sodium selenite and ascorbic acid. The stability and characterization of BRP-SeNPs were investigated by physical analysis method. The results revealed that BRP were tightly wrapped on the surface of SeNPs by forming C-O⋯Se bonds or hydrogen bonding interaction (O-H⋯Se). BRP-SeNPs presented irregular, fragmented and smooth surface morphology and polycrystalline nanoring structure, and its particle size was 89.4 nm in the optimal preparation condition. The pharmacologic functions of BRP-SeNPs were explored in vitro and in vivo. The results showed that BRP-SeNPs could heighten the cell viabilities and the enzyme activity of GSH-Px and decrease the content of MDA on H2O2-induced AML-12 cells injury model. In vivo tests, the results displayed that BRP-SeNPs could increase the body weight of mice, promote the enzyme activity like SOD and GSH-Px, decrease the liver organ index and the hepatic function index such as ALT, AST, CYP2E1, reduce the content of MDA, and relieve the proinflammation factors of NO, IL-1β and TNF-α in CCl4-induced mice injury model. Liver tissue histopathological studies corroborated the improvement of BRP-SeNPs on liver of CCl4-induced mice. The results of Western blot showed that BRP-SeNPs could attenuate oxidant stress by the Nrf2/Keap1/MKP1/JNK pathways, and downregulate the proinflammatory factors by TLR4/MAPK pathway. These findings suggested that BRP-SeNPs possess the hepatoprotection and have the potential to be a green liver-protecting and auxiliary liver inflammation drugs.

Every fifth individual with type 1 diabetes (T1D) suffers from an additional autoimmune disorder due to shared genetic factors and dysregulated immunity. Here we report an extremely rare case of T1D complicated with cyclic vomiting and hypoglycaemia. A 27-year-old Chinese woman with 14-year history of T1D was periodically hospitalized for severe vomiting of more than 30 times a day without apparent organic causes. The vomiting developed acutely and remitted spontaneously after 2-3 days, followed with intractable hypoglycaemia for another 3-4 days during the hospitalization. A few weeks after discharge, she was admitted once again with the same symptoms and disease course. Cyclic vomiting syndrome (CVS) was diagnosed according to the Rome IV criteria, a system developed to define the functional gastrointestinal disorders. Dynamic association and disassociation of exogenous insulin and insulin antibodies (IAs) were identified in her blood during hypoglycaemia, leading to the diagnosis of exogenous insulin antibody syndrome (EIAS). Treatment with rituximab to suppress the IAs was associated with a striking amelioration of hypoglycaemia. Unexpectedly, the episodes of cyclic vomiting were also dramatically reduced. In conclusion, we identified the first case with alternating CVS and EIAS in the setting of T1D. Dynamic measurements of free and total insulin are helpful for the diagnosis of EIAS. CVS is likely to be a latent autoimmune disorder considering the good response to rituximab treatment.

Differential diagnosis of hypoglycaemia can at times be challenging for patients who appear to be well. Here we identify the case of a 66-year-old Chinese man presenting with recurrent episodes of fasting hypoglycaemia and confusion without any other manifestations. He had no personal or family history of diabetes, nor was he on any hypoglycaemic drugs. The fasting insulin levels were elevated while the C-peptide and pro-insulin levels were slightly low or normal. Antibodies against insulin were negative and levels of insulin-like growth factors were normal. A series of imaging diagnosis excluded the presence of insulinoma or ectopic insulin-secreting neuroendocrine tumor. Ultimately, insulin receptor autoantibodies (IRAb) were detected by both immunoprecipitation assay and enzyme-linked immunosorbent assay (ELISA) developed in house. In a cell study, the immunoglobulins isolated from this patient exerted insulin-like effects on stimulation of post-insulin receptor signaling and glucose uptake as well as inhibited 125I-insulin binding with insulin receptors. Collectively, this patient was diagnosed with IRAb-induced autoimmune hypoglycaemia. Although this patient had no obvious immune disorders, several autoantibodies were identified in his plasma samples, suggesting the patient might have mild aberrant autoimmunity and therefore generated IRAb. IRAb-related disease is uncommon and possibly underdiagnosed or missed due to the lack of simple detection methods for IRAb. Our in-house user-friendly ELISA kit provides a valuable tool for diagnosis of this disease.

Abstract Background Inadequate refilling from extravascular compartments during hemodialysis can lead to intradialytic symptoms, such as hypotension, nausea, vomiting, and cramping/myalgia. Relative blood volume (RBV) plays an important role in adapting the ultrafiltration rate which in turn has a positive effect on intradialytic symptoms. It has been clinically challenging to identify changes RBV in real time to proactively intervene and reduce potential negative consequences of volume depletion. Leveraging advanced technologies to process large volumes of dialysis and machine data in real time and developing prediction models using machine learning (ML) is critical in identifying these signals. Method We conducted a proof-of-concept analysis to retrospectively assess near real-time dialysis treatment data from in-center patients in six clinics using Optical Sensing Device (OSD), during December 2018 to August 2019. The goal of this analysis was to use real-time OSD data to predict if a patient’s relative blood volume (RBV) decreases at a rate of at least − 6.5 % per hour within the next 15 min during a dialysis treatment, based on 10-second windows of data in the previous 15 min. A dashboard application was constructed to demonstrate how reporting structures may be developed to alert clinicians in real time of at-risk cases. Data was derived from three sources: (1) OSDs, (2) hemodialysis machines, and (3) patient electronic health records. Results Treatment data from 616 in-center dialysis patients in the six clinics was curated into a big data store and fed into a Machine Learning (ML) model developed and deployed within the cloud. The threshold for classifying observations as positive or negative was set at 0.08. Precision for the model at this threshold was 0.33 and recall was 0.94. The area under the receiver operating curve (AUROC) for the ML model was 0.89 using test data. Conclusions The findings from our proof-of concept analysis demonstrate the design of a cloud-based framework that can be used for making real-time predictions of events during dialysis treatments. Making real-time predictions has the potential to assist clinicians at the point of care during hemodialysis.

Reports indicate that high-cost, insecurity, and difficulty in complex environments hinder the traditional urban road inundation monitoring approach. This work proposed an automatic monitoring method for experimental urban road inundation based on the YOLOv2 deep learning framework. The proposed method is an affordable, secure, with high accuracy rates in urban road inundation evaluation. The automatic detection of experimental urban road inundation was carried out under both dry and wet conditions on roads in the study area with a scale of a few m2. The validation average accuracy rate of the model was high with 90.1% inundation detection, while its training average accuracy rate was 96.1%. This indicated that the model has effective performance with high detection accuracy and recognition ability. Besides, the inundated water area of the experimental inundation region and the real road inundation region in the images was computed, showing that the relative errors of the measured area and the computed area were less than 20%. The results indicated that the proposed method can provide reliable inundation area evaluation. Therefore, our findings provide an effective guide in the management of urban floods and urban flood-warning, as well as systematic validation data for hydrologic and hydrodynamic models. HIGHLIGHTS First experimental urban road inundation automatic detection study using YOLOv2.; Proposed an inundation area computation method based on a deep learning technique.; Good performance on an experimental urban road inundation detection was tested.;

Technical advancements have significantly improved early diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various practical factors. Here, the authors develop an artificial intelligence assistive diagnostic solution to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria in a large multicenter study.

Lipopolysaccharide (LPS) originating from dysbiotic gut microbiota is regarded as a critical mediator for triggering the inflammation responsible for non-alcoholic fatty liver disease (NAFLD). The preventive effect of plant sterol ester of α-linolenic acid (PS-ALA) on NAFLD was identified in our previous research, yet, the mechanisms linking this effect to gut microbiota and LPS-triggered inflammation remain unclear. In present study, we found that PS-ALA treatment could counteract gut microbial dysbiosis and maintain intestinal barrier function. These beneficial effects of PS-ALA reduced bacterial LPS production and leakage into the portal circulation which attenuated LPS-triggered hepatic inflammation. In addition, PS-ALA inhibited LPS-triggered TLR4/NF-κB signaling pathway activation and reduced pro-inflammatory cytokines release in HepG2 cells. In conclusion, PS-ALA has a dual inhibition effect on endotoxin, including reducing LPS production in the gut and blocking the activation of the LPS-induced TLR4/NF-κB signaling pathway, thereby mitigating inflammatory reactions in the liver and preventing NAFLD.