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Background: diabetices foot ulcer (DFU) are serious complications. It is crucial to detect and diagnose DFU early in order to provide timely treatment, improve patient quality of life, and avoid the social and economic consequences. Machine learning techniques can help identify risk factors associated with DFU development. Objective: The aim of this study was to establish correlations between clinical and biochemical risk factors of DFU through local foot examinations based on the construction of predictive models using automated machine learning techniques. Methods: The input dataset consisted of 566 diabetes cases and 50 DFU risk factors, including 9 local foot examinations. 340 patients with Class 0 labeling (low-risk DFU), 226 patients with Class 1 labeling (high-risk DFU). To divide the training group (consisting of 453 cases) and the validation group (consisting of 113 cases), as well as preprocess the data and develop a prediction model, a Monte Carlo cross-validation approach was employed. Furthermore, potential high-risk factors were analyzed using various algorithms, including Bayesian BYS, Multi-Gaussian Weighted Classifier (MGWC), Support Vector Machine (SVM), and Random Forest Classifier (RF). A three-layer machine learning training was constructed, and model performance was estimated using a Confusion Matrix. The top 30 ranking feature variables were ultimately determined. To reinforce the robustness and generalizability of the predictive model, an independent dataset comprising 248 cases was employed for external validation. This validation process evaluated the model's applicability and reliability across diverse populations and clinical settings. Importantly, the external dataset required no additional tuning or adjustment of parameters, enabling an unbiased assessment of the model's generalizability and its capacity to predict the risk of DFU. Results: The ensemble learning method outperformed individual classifiers in various performance evaluation metrics. Based on the ROC analysis, the AUC of the AutoML model for assessing diabetic foot risk was 88.48 % (74.44–97.83 %). Other results were found to be as follows: 87.23 % (63.33 %–100.00 %) for sensitivity, 87.43 % (70.00 %–100.00 %) for specificity, 87.33 % (76.66 %–95.00 %) for accuracy, 87.69 % (75.00 %–100.00 %) for positive predictive value, and 87.70 % (71.79 %–100.00 %) for negative predictive value. In addition to traditional DFU risk factors such as cardiovascular disorders, peripheral artery disease, and neurological damage, we identified new risk factors such as lower limb varicose veins, history of cerebral infarction, blood urea nitrogen, GFR (Glomerular Filtration Rate), and type of diabetes that may be related to the development of DFU. In the external validation set of 158 samples, originating from an initial 248 with exclusions due to missing labels or features, the model still exhibited strong predictive accuracy. The AUC score of 0.762 indicated a strong discriminatory capability of the model. Furthermore, the Sensitivity and Specificity values provided insights into the model's ability to correctly identify both DFU cases and non-cases, respectively. Conclusion: The predictive model, developed through AutoML and grounded in local foot examinations, has proven to be a robust and practical instrument for the screening, prediction, and diagnosis of DFU risk. This model not only aids medical practitioners in the identification of potential DFU cases but also plays a pivotal role in mitigating the progression towards adverse outcomes. And the recent successful external validation of our DFU risk prediction model marks a crucial advancement, indicating its readiness for clinical application. This validation reinforces the model's efficacy as an accessible and reliable tool for early DFU risk assessment, thereby facilitating prompt intervention strategies and enhancing overall patient outcomes.

The nitrogen and phosphorus in electroplating wastewater were recovered using struvite crystallization method. The effects of pH, concentration of heavy metal ions and mass concentration of fluoride ions on the removal of nitrogen and phosphorus in electroplating wastewater were investigated. The results showed that pH and concentration of heavy metal ions had significantly affect on the process of struvite crystallization, while the effect of low mass concentration（0-40 mg/L） of fluoride ions on the structure of struvite could be ignored. XRD, SEM and XPS characterization were conducted on struvite formed under different conditions, and the influence mechanism of heavy metal ions and fluorine ions on the crystallization process of struvite was analyzed. Heavy metal ions could co-precipitate with struvite and interfere with the formation of struvite crystals. When fluoride ions coexisted with heavy metal ions, fluoride ions would interfere the adsorption of heavy metal ions on the crystal, and generate amorphous phase coprecipitates, changing the crystal morphology of struvite. This study provides a theoretical basis for the recovery of nitrogen and phosphorus from electroplating wastewater by the struvite crystallization method.

Objective Fracture network analysis plays an important role in oil and gas exploration and development. However, complexity analysis of tight sandstone fracture networks and their control factors is relatively lagging. Based on an experimental study of the dynamic evolution of the complex fracture network in tight sandstone, the fractal and multifractal spectral characteristics of the fracture network were defined, and the complexity and main controlling factors of the fracture network were analyzed. Fracture network complexity analysis of tight sandstone plays an important role in hydraulic fracturing optimization, fracture network prediction, and fracture modeling. Methods Rock mechanics and X-ray computed tomography scan experiments determined the characteristics of rock mechanics and fracture networks . The microstructure and fracture network fractal characteristics of tight sandstone were quantitatively characterized by SEM and fracture network fractal analysis. Results The results showed that the quartz content of tight sandstone ranges from 28.08 to 52.88%, clay content ranges from 11.54 to 25.45%, particle size ranges from 61.18 to 184.55 μm, and porosity ranges from 8.125 to 10.296%. Uniaxial compressive strength ranges from 69.09 to 188.33 MPa, and the elastic modulus ranges from 31.69 to 92.76 GPa. The fractal dimension (DB) ranges from 1.28 to 2.35 and average spectral width (Δα) ranges from 1.0851 to 1.3638. Conclusion The initiation and propagation of fractures extend through the entire stress–strain process. The complexity of the fracture network of tight sandstone is mainly controlled by microscopic fabric characteristics, and has obvious confining pressure as well as scale effects. The DB of the three-dimensional fracture network and average Δα of the multifractal spectrum represents the complexity and heterogeneity of the fracture spatial distribution, respectively, and are relatively independent. As the content of quartz, feldspar, and other brittle minerals in sandstone increases, the porosity of the reservoir increases, particle size of the sandstone decreases, DB of the fracture network increases, and average Δα decreases. In the absence of confining pressure, the complexity of the sample fracture network is mainly controlled by the microscopic fabric characteristics, and the complexity increases with increase of axial pressure. When present confining pressure plays a leading role; the higher it is, the lower the DB value, and the higher the mean Δα value. Clay minerals are unconducive to complex fractures formation. The mean values of DB and Δα of small-scale samples are greater than those of large-scale samples. The elastic modulus and compressive strength of sandstone are positively correlated with DB and mean Δα.

Pre-trained language models perform well in various natural language processing tasks. However, their large number of parameters poses significant challenges for edge devices with limited resources, greatly limiting their application in practical deployment. This paper introduces a simple and efficient method called Autocorrelation Matrix Knowledge Distillation (AMKD), aimed at improving the performance of smaller BERT models for specific tasks and making them more applicable in practical deployment scenarios. The AMKD method effectively captures the relationships between features using the autocorrelation matrix, enabling the student model to learn not only the performance of individual features from the teacher model but also the correlations among these features. Additionally, it addresses the issue of dimensional mismatch between the hidden states of the student and teacher models. Even in cases where the dimensions are smaller, AMKD retains the essential features from the teacher model, thereby minimizing information loss. Experimental results demonstrate that BERTTINY-AMKD outperforms traditional distillation methods and baseline models, achieving an average score of 83.6% on GLUE tasks. This represents a 4.1% improvement over BERTTINY-KD and exceeds the performance of BERT4-PKD and DistilBERT4 by 2.6% and 3.9%, respectively. Moreover, despite having only 13.3% of the parameters of BERTBASE, the BERTTINY-AMKD model retains over 96.3% of the performance of the teacher model, BERTBASE. [ABSTRACT FROM AUTHOR]

Extracellular elastin‐derived peptides (EDPs) accumulate in the aging brain and have been associated with vascular dementia and Alzheimer's disease (AD). The activation of inflammatory processes in glial cells with EDP treatment has received attention, but not in neurons. To properly understand EDPs' pathogenic significance, the impact on neuronal function and neuron–microglia crosstalk was explored further. Among the EDP molecules, Val‐Gly‐Val‐Ala‐Pro‐Gly (VGVAPG) is a typical repeating hexapeptide. Here, we observed that EDPs‐VGVAPG influenced neuronal survival and morphology in a dose‐dependent manner. High concentrations of VGVAPG induced synapse loss and microglia hyperactivation in vivo and in vitro. Following EDP incubation, galectin 3 (Gal‐3) released by neurons served as a chemokine, attracting microglial engulfment. Blocking Gal‐3 and EDP binding remedied synapse loss in neurons and phagocytosis in microglia. In response to the accumulation of EDPs, proteomics in matrix remodeling and cytoskeleton dynamics, such as a disintegrin and metalloproteinase (ADAM) family, were engaged. These findings in extracellular EDPs provided more evidence for the relationship between aging and neuron dysfunction, increasing the insight of neuroinflammatory responses and the development of new specialized extracellular matrix remolding‐targeted therapy options for dementia or other neurodegenerative disease. [ABSTRACT FROM AUTHOR]

This study aimed to examine the association between occupational burnout and psychological symptoms among Chinese medical staff, assuming social support to play a moderating role in the aforementioned relationship. The survey was conducted online from May 1 to June 28, 2022, and the questionnaires were distributed and retrieved through a web-based platform. The final sample was comprised of 1461 Chinese medical staff in this cross-sectional study. Several multiple linear regressions were performed to analyze the data. After controlling for potential confounding factors, all three dimensions of occupational burnout were associated with poorer psychological symptoms. Emotional exhaustion (β = 0.33; 95% confidence interval [CI], 1.018, 1.479) had the strongest association with psychological symptoms, followed by depersonalization and diminished personal accomplishment. Moreover, medical staff with higher levels of friend support (β = −0.11; 95% CI, −4.063, −0.573) and significant other support (β = −0.10; 95% CI, −3.965, −0.168) were less likely to suffer from psychological symptoms when faced with occupational burnout. The results suggested that interventions aimed at lessening occupational burnout and boosting social support can be an effective way to promote the psychological health of medical staff. [ABSTRACT FROM AUTHOR]

Coregonus ussuriensis Berg, distributed widely in cold waters above 45° N latitude, is a savored freshwater whitefish that has been included in the list of endangered animals as a consequence of overfishing. Lack of genomic information seriously hampers evolutionary and genetic research on C. ussuriensis warranting the need to assemble a high-quality reference genome to promote its genetic breeding. We assembled and constructed a reference chromosome-level C. ussuriensis genome (sequence length, 2.51 Gb; contig N50 length, 4.27 Mb) using PacBio sequencing and Hi-C assembly technology, 3,109 contigs were assembled into scaffolds, resulting in a genome assembly with 40 chromosomes and a scaffold N50 length of 62.20 Mb. In addition, 43,320 protein-coding genes were annotated. The peak Ks position in the species comparison reflects the whole-genome replication event of C. ussuriensis. This chromosome-level genome provides reference data for further studies on the molecular breeding of C. ussuriensis. [ABSTRACT FROM AUTHOR]

Kagome superconductors AV3Sb5 (A = K, Rb and Cs) have attracted much recent attention due to the coexistence of multiple exotic orders. Among them, the charge density wave (CDW) order has been shown to host various unconventional behaviors. Here, we investigate the CDW order by a combination of both bulk and surface doping methods. While element substitutions in bulk doping change both carriers and the crystal lattice, the surface doping primarily tunes the carrier concentration. As such, our results reveal a two-dimensional phase diagram of the CDW in doped CsV3Sb5. In the lightly bulk doped regime, the existence of CDW order is reversible by tuning the carrier concentration. But excessive bulk doping permanently destroys the CDW, regardless of the carrier doping level. These results provide insights to the origin of the CDW from both electronic and structural degrees of freedom. They also open an avenue for manipulating the exotic CDW order in Kagome superconductors. [ABSTRACT FROM AUTHOR]

Summary: As functional oligosaccharides, feruloyl oligosaccharides (FOs) exhibit the physiological activities of both ferulic acid and oligosaccharides. In this study, FOs were prepared by fermenting wheat bran with the generally recognised as safe (GRAS) bacterium Bacillus amyloliquefaciens IT‐45. On the fourth day of fermentation, the activities of xylanase and cellulase reached 447.67 and 33.41 U/mL, respectively. UV, FTIR, and HPLC were used to characterise the structure properties of wheat bran FOs from B. amyloliquefaciens IT‐45 fermentation. The monosaccharide compositions of FOs were mainly composed of xylose and arabinose. Under the optimal conditions of fermentation time of 4 days, fermentation temperature of 25 °C, initial pH of 6.5 and inoculation amount of 11% (v/v), the maximum yield of FOs in the broth was 0.6397 mM. In vitro antioxidant activity analysis showed that FOs prepared by B. amyloliquefaciens fermentation had good scavenging ability against ABTS, DPPH and hydroxyl radicals, demonstrating the application potential. The results provided a relatively environmentally friendly and food‐safety way to prepare feruloyl oligosaccharides. [ABSTRACT FROM AUTHOR]

The ZDJ9 AC five-wire switch control circuits exhibit the phenomena of arcing, burning, and oxidation of the first and second groups of strengthening contacts of the 2DQJ relays, resulting in poor contact of the contacts. Due to the fact that the first group of front contacts and the second group of rear contacts of 2DQJ relays are shared contacts, oxidation of these contacts can lead to loss of indication of a switch ; at the same time, there is a risk of instantaneous starting current striking and damaging outdoor diodes, which can also lead to loss of indication of a switch. The principle of the switch control circuits is analyzed, the circuit logic is adjusted, and the ZDJ9 AC five-wire switch control circuits are optimized to avoid loss of switch indication failure and improve the overall reliability of the switch equipment. [ABSTRACT FROM AUTHOR]

The receptor-like kinase FERONIA (FER), together with its ligand rapid alkalinization factor 1 (RALF1) peptide, plays a crucial role in regulating stress responses, including its involvement in modulating abscisic acid (ABA) signaling. FER has been shown to activate ABA insensitive 2 in the cytoplasm, leading to the suppression of ABA signaling. However, its regulation of nucleus events in the ABA response remains unclear. FREE1, identified as a plant-specific component of the endosomal sorting complex required for transport in eukaryotes, serves as an important negative regulator in ABA signaling. In this study, we elucidate that upon RALF1 treatment, FER phosphorylates FREE1, promoting the accumulation of FREE1 protein in the nucleus in Arabidopsis (Arabidopsis thaliana). Consequently, FREE1 suppresses ABA sensitivity by inhibiting the expression of ABA-response genes. Mutating the 6 identified phosphorylation sites on FREE1, mediated by FER, to nonphosphorylable residues results in reduced nucleus localization of FREE1 and increased hypersensitivity to ABA. Our data also show that these 6 phosphorylation sites are likely involved in regulating plant survival under salt stress. Collectively, our study not only unveils an additional function of FER in attenuating ABA signaling in the nucleus but also provides a possible insight into the role of the RALF1-FER-FREE1 module in coordinating plant growth and salt stress tolerance., Competing Interests: Conflict of interest statement. The authors declare that there is no conflict of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Some pathogens colonize plant leaves, but others invade the roots, including the vasculature, causing severe disease symptoms. Plant innate immunity has been extensively studied in leaf pathosystems; however, the precise regulation of immunity against vascular pathogens remains largely unexplored. We previously demonstrated that loss of function of the receptor kinase FERONIA (FER) increases plant resistance to the typical vascular bacterial pathogen Ralstonia solanacearum. Here, we show that upon infection with R. solanacearum, root xylem cell walls in Arabidopsis thaliana become highly lignified. FER is specifically upregulated in the root xylem in response to R. solanacearum infection, and inhibits lignin biosynthesis and resistance to this pathogen. We determined that FER interacts with and phosphorylates the transcription factor RESPONSIVE TO DESICCATION 26 (RD26), leading to its degradation. Overexpression and knockout of RD26 demonstrated that it positively regulates plant resistance to R. solanacearum by directly activating the expression of lignin-related genes. Tissue-specific expression of RD26 in the root xylem confirmed its role in vascular immunity. We confirmed that the FER-RD26 module regulates lignin biosynthesis and resistance against R. solanacearum in tomato (Solanum lycopersicum). Taken together, our findings unveil that the FER-RD26 cascade governs plant immunity against R. solanacearum in vascular tissues by regulating lignin deposition. This cascade may represent a key defense mechanism against vascular pathogens in plants., Competing Interests: Conflict of interest statement. The authors declare no competing interests., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objectives: This study aimed to assess the relationship between COVID-19 infection-related conditions and depressive symptoms among medical staff after easing the zero-COVID policy in China, and to further examine the mediating role of professional burnout., Methods: A total of 1716 medical staff from all levels of health care institutions in 16 administrative districts of Beijing, China, were recruited to participate at the end of 2022 in this cross-sectional study. Several multiple linear regressions and mediating effects tests were performed to analyze the data., Results: At the beginning of the end of the zero-COVID policy in China, 91.84% of respondents reported infection with COVID-19. After adjusting for potential confounding variables, the severity of infection symptoms was significantly positively associated with high levels of depressive symptoms (β = 0.06, P < 0.001), and this association was partially mediated by professional burnout. Specifically, emotional exhaustion (95% CI, 0.131, 0.251) and depersonalization (95% CI, 0.009, 0.043) significantly mediated the association between the severity of infection symptoms and depressive symptoms., Conclusions: The mental health of medical staff with more severe symptoms of COVID-19 infection should be closely monitored. Also, interventions aimed at reducing emotional exhaustion and depersonalization may effectively reduce their risk of developing depressive symptoms.