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Osteoarthritis (OA) is an age-related joint disease in which inflammation and extracellular matrix (ECM) degradation play a crucial role in the destruction of articular cartilage. Secoisolariciresinol diglucoside (SDG), the main lignan in wholegrain flaxseed, which has been reported to remarkably suppress inflammation and oxidative stress, may have potential therapeutic value in OA. In this study, the effect and mechanism of SDG against cartilage degeneration were verified in the destabilization of the medial meniscus (DMM) and collagen-induced (CIA) arthritis models and interleukin-1β (IL-1β)-stimulated osteoarthritis chondrocyte models. From our experiments, SDG treatment downregulated the expression of pro-inflammatory factors induced by IL-1β in vitro, including inducible nitric oxide synthase (INOS), cyclooxygenase-2 (COX2), tumor necrosis factor (TNF-α), and interleukin 6 (IL-6). Additionally, SDG promoted the expression of collagen II (COL2A1) and SRY-related high-mobility-group-box gene 9(SOX9), while suppressing the expression of a disintegrin and metalloproteinase with thrombospondin motifs 5(ADAMTS5) and matrix metalloproteinases 13(MMP13), which leads to catabolism. Consistently, in vivo, SDG has been identified to have chondroprotective effects in DMM-induced and collagen-induced arthritis models. Mechanistically, SDG exerted its anti-inflammation and anti-ECM degradation effects by activating the Nrf2/HO-1 pathway and inhibiting the nuclear factor kappa B (NF-κB) pathway. In conclusion, SDG ameliorates the progression of OA via the Nrf2/NF-κB pathway, which indicates that SDG may have therapeutic potential for OA.

ObjectiveFalls in older people have become a major public health, economic and societal problem. Osteoporosis predisposes older adults to high risk of falls, which were the most common outcome attributable to low bone mineral density (LBMD). In this study, we analyze the long-term trends in falls burden attributable to LBMD among people aged 60 years and over from 1990 to 2019, using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019).MethodsData from GBD 2019 were used to assess the long-term trends in mortality and disability-adjusted life-year (DALY) rates by Joinpoint regression. The age-period-cohort (APC) model was used to evaluate the effects of age, period and cohort on mortality rate of falls attributable to LBMD.ResultsThe mortality and DALYs rates of falls attributable to LBMD among people aged 60 years and over increased from 1990 to 2019, with average annual percentage changes (AAPCs) of 1.74% (95% CI: −1.47 to 2.01%) and 0.99% (95% CI: 0.80–1.19%), respectively. APC analysis revealed that the mortality rate due to LBMD significantly increased among the older people over the age of 75 years. The risk of falls mortality due to LBMD during the period of 1990–2019 initially declined but later elevated. An overall increasing risk for falls death attributable to LBMD was presented across birth cohorts, but in cohorts born after 1930, the upward trend has slowed down. The overall net drift per year attributable to LBMD was above 0. The corresponding results showed that the negative impact of period and cohort effects among males was more pronounced than those among females.ConclusionsFalls attributable to LBMD remain an ongoing health burden in the older people in China, and the mortality has been on the rise from 1990 to 2019, especially among the older people aged 80+ years group. The prevention and treatment of LBMD should be emphasized, especially among males and oldest-old people. Furthermore, there is an urgent need to strengthen the implementation of system-wide, integrated and effective public health policies and other health interventions in China.

ABSTRACT Several variants of the plasmid-carried tigecycline resistance gene cluster, tmexCD-toprJ, have been identified. This study characterized another novel variant, tmexC6D6-toprJ1b, located on the chromosome of environmental-origin Pseudomonas mendocina. TMexC6D6-TOprJ1 mediates resistance to multiple drugs, including tigecycline. The promoter activity of tmexC6D6-toprJ1b and negative transcriptional repression by the upstream regulator tnfxB6 are crucial for the expression of tmexC6D6-toprJ1b. tmexC6D6-toprJ1b was found in the plasmids or chromosomes of different Pseudomonas species from six countries. Two genetic backgrounds, class 1 integrons and int-carrying integrase units, were found adjacent to the tmexC6D6-toprJ1b gene cluster and might mediate the transfer of this novel efflux pump gene cluster in Pseudomonas. Further phylogenetic analysis revealed Pseudomonas as the major reservoir of tmexCD-toprJ variants, warranting closer monitoring in the future. IMPORTANCE Tigecycline is one of the treatment options for serious infections caused by multidrug-resistant bacteria, and tigecycline resistance has gained extensive attention. The emergence of a transferable tigecycline resistance efflux pump gene cluster, tmexCD-toprJ, severely challenged the efficiency of tigecycline. In this study, we identified another novel tmexCD-toprJ variant, tmexC6D6-toprJ1b, which could confer resistance to multiple classes of antibiotics, including tigecycline. Although tmexC6D6-toprJ1b was found only in Pseudomonas species, tmexC6D6-toprJ1b might spread to Enterobacteriaceae hosts via mobile genetic elements resembling those of other tmexCD-toprJ variants, compromising the therapeutic strategies. Meanwhile, novel transferable tmexCD-toprJ variants are constantly emerging and mostly exist in Pseudomonas spp., indicating Pseudomonas as the important hidden reservoir and origin of tmexCD-toprJ variants. Continuous monitoring and investigations of tmexCD-toprJ are urgent to control its spread.

IntroductionMultimode thermal therapy (MTT) is an innovative interventional therapy developed for the treatment of liver malignancies. When compared to the conventional radiofrequency ablation (RFA), MTT typically offers improved prognosis for patients. However, the effect of MTT on the peripheral immune environment and the mechanisms underlying the enhanced prognosis have yet to be explored. The aim of this study was to further investigate the mechanisms responsible for the difference in prognosis between the two therapies.MethodsIn this study, peripheral blood samples were collected from four patients treated with MTT and two patients treated with RFA for liver malignancies at different time points before and after the treatment. Single cell sequencing was performed on the blood samples to compare and analyze the activation pathways of peripheral immune cells following the MTT and RFA treatment. ResultsThere was no significant effect of either therapy on the composition of immune cells in peripheral blood. However, the differential gene expression and pathway enrichment analysis demonstrated enhanced activation of T cells in the MTT group compared to the RFA group. In particular, there was a remarkable increase in TNF-α signaling via NF-κB, as well as the expression of IFN-α and IFN-γ in the CD8+ effector T (CD8+ Teff) cells subpopulation, when compared to the RFA group. This may be related to the upregulation of PI3KR1 expression after MTT, which promotes the activation of PI3K-AKT-mTOR pathway. ConclusionThis study confirmed that MTT could more effectively activate peripheral CD8+ Teff cells in patients compared with RFA and promote the effector function, thus resulting in a better prognosis. These results provide a theoretical basis for the clinical application of MTT therapy.

With the advancement of engineering techniques, underground shield tunneling projects have also started incorporating emerging technologies to monitor the forces and displacements during the construction and operation phases of shield tunnels. Monitoring devices installed on the tunnel segment components generate a large amount of data. However, due to various factors, data may be missing. Hence, the completion of the incomplete data is imperative to ensure the utmost safety of the engineering project. In this research, a missing data imputation technique utilizing Random Forest (RF) is introduced. The optimal combination of the number of decision trees, maximum depth, and number of features in the RF is determined by minimizing the Mean Squared Error (MSE). Subsequently, complete soil pressure data are artificially manipulated to create incomplete datasets with missing rates of 20%, 40%, and 60%. A comparative analysis of the imputation results using three methods—median, mean, and RF—reveals that this proposed method has the smallest imputation error. As the missing rate increases, the mean squared error of the Random Forest method and the other two methods also increases, with a maximum difference of about 70%. This indicates that the random forest method is suitable for imputing monitoring data.

The pulses in X-ray-burst (XRB) light curves from soft gamma-ray repeaters (SGRs) are generally thought to arise from magnetic crustal fractures or magnetic reconnection, reflecting the evolution of the energy release process in magnetars. In this study, we conduct a comprehensive timing analysis of 27 XRBs from SGR J0501+4156 detected by the Gamma-ray Burst Monitor on board Fermi. Utilizing a improved pulse-finding algorithm, we identify a total of 95 pulses and fit them using multiple FRED functions to obtain pulse-shape parameters based on the Markov Chain Monte Carlo method. We calculate the minimum variability timescales (MVTs) of the XRBs based on the shortest pulse; the distribution of MVTs follows a log-Gaussian function with a mean of ${7.22}_{-2.11}^{+2.93}$ ms (1 σ ). The distributions of rise time, decay time, waiting time, width, skewness, and peakedness all follow the log-Gaussian function, and multiple power-law dependencies are observed between them; for example, a power-law positive correlation between decay time and rise time with 4.7 σ , and a power-law negative correlation between pulse width and peakedness with 6.8 σ . Besides, there is a positive correlation with 3.7 σ between the number of pulses and burst duration. Our findings favor a magnetospheric origin, and some similarities with gamma-ray bursts imply that they have similar radiation mechanisms, e.g., magnetic reconnection processes.

The overall temporal and spectral characteristics (e.g., duration, fluence, peak flux, peak count rate, and total counts) of X-ray bursts (XRBs) originating from magnetars have been extensively studied to confirm their self-organized criticality (SOC) behaviors. However, for the pulses in XRBs, which are an important part of unraveling radiation processes such as magnetic reconnection and crustal rupture, their variable statistical characteristics are still unclear. In this work, we investigate the distributions of fluctuations in duration, waiting time, peak count rate, and total counts of pulses within bursts from two active and prolific magnetars, SGR J1935+2154 and SGR J1550-5418, observed by Fermi’s Gamma-ray Burst Monitor, Insight-HXMT, and GECAM. We report that the waiting time for pulses follows SOC, whereas previous studies indicated for bursts do not, possibly due to incomplete observations. Besides, the duration, peak count rate, and total counts for pulses are also SOC behaviors. The α -values for the duration of pulses for both magnetars are ∼2, and the inferred Euclidean dimension S is 3. Our findings provide evidence for the SOC of each radiation process during a burst, for example, multiple pulses produced by multiple magnetic reconnections triggered by a single starquake. Finally, the similar statistical characteristics for pulses from both magnetars lend support to their shared radiation processes.

The major observation of the X-ray burst (XRB) in association with the fast radio burst (FRB) FRB 200428 originating from SGR J1935+2154 on 2020 April 28 substantiates magnetars as one of the origins of FRBs. However, it is still unclear why only a few XRBs in association with FRBs have been observed solely in this magnetar. In this study, we investigate the minimum variation timescales (MVTs) of XRBs from SGR J1550-5418, an active magnetar similar to SGR J1935+2154, and conduct a comprehensive comparison of their MVT properties. Our analysis reveals that the distribution of the MVT for SGR J1550-5418 follows a lognormal Gaussian function with the mean 6.4 ± 0.4 ms. Interestingly, we detect an evolution in the MVTs, i.e., the fitted mean of the MVT distribution in 2008 October is about 3 times larger than that in 2009, indicating potential variations in radiation regions possibly attributed to changes in magnetic field topology. Besides, we do not find a significant correlation between the MVT and either duration or energy. Finally, there is no significant difference between the MVT distributions across different energy ranges for SGR J1550-5418 and SGR J1935+2154, which supports a common physical origin.

In the standard Bell experiment, two parties perform local projective measurements on a shared pair of entangled qubits to generate nonlocal correlations. However, these measurements completely destroy the entanglement, rendering the post-measurement state unable for subsequent use. For a long time, it was believed that only unsharp measurements can be used to share quantum correlations. Remarkably, recent research has shown that classical randomness assisted projective measurements are sufficient for sharing nonlocality (Steffinlongo and Tavakoli 2022 Phys. Rev. Lett. 129 230402). Here, by stochastically combining no more than two different projective measurement strategies, we report an experimental observation of double Clauser–Horne–Shimony–Holt inequality violations with two measurements in a sequence made on each pair of maximally and partially entangled polarization photons. Our results reveal that the double violation achieved by partially entangled states can be 11 standard deviations larger than that achieved by maximally entangled ones. Our scheme eliminates the requirement for entanglement assistance in previous unsharp-measurement-based sharing schemes, making it experimentally easier. Our work provides possibilities for sharing other types of quantum correlations in various physical systems with projective measurements.

The confining pressure has a great effect on the internal force of the tunnel. During construction, the confining pressure which has a crucial impact on tunnel construction changes due to the variation of groundwater level and applied load. Therefore, the safety of tunnels must have the magnitude of confining pressure accurately estimated. In this study, a complete tunnel confining pressure time axis was obtained through high-frequency field monitoring, the data are segmented into a training set and a testing set. Using GRU and RNN models, a confining pressure prediction model was established, and the prediction results were analyzed. The results indicate that the GRU model has a fast-training speed and higher accuracy. On the other hand, the training speed of the RNN model is slow, with lower accuracy. The dynamic characteristics of soil pressure during tunnel construction require accurate prediction models to maintain the safety of the tunnel. The comparison between GRU and RNN models not only highlights the advantages of the GRU model but also emphasizes the necessity of balancing speed accuracy in tunnel construction confining pressure prediction modeling. This study is helpful in improving the understanding of soil pressure dynamics and developing effective prediction tools to promote safer and more reliable tunnel construction practices.

Abstract Evidence has suggested that built environments are significantly associated with residents’ health and the conditions of built environments vary between neighborhoods. Recently, there have been remarkable technological advancements in using deep learning to detect built environments on fine spatial scale remotely sensed images. However, integrating the extracted built environment information by deep learning with geographic information systems (GIS) is still rare in existing literature. This method paper presents how we harnessed deep leaning techniques to extract built environments and then further utilized the extracted information as input data for analysis and visualization in a GIS environment. Informative guidelines on data collection with an unmanned aerial vehicle (UAV), greenspace extraction using a deep learning model (specifically U-Net for image segmentation), and mapping spatial distributions of greenspace and sidewalks in a GIS environment are offered. The novelty of this paper lies in the integration of deep learning into the GIS decision-making system to identify the spatial distribution of built environments at the neighborhood scale.

Abstract Background Traumatic spinal cord injury (SCI)-induced neuroinflammation results in secondary neurological destruction and functional disorder. Previous findings showed that microglial pyroptosis plays a crucial role in neuroinflammation. Thus, it is necessary to conduct a comprehensive investigation of the mechanisms associated with post-SCI microglial pyroptosis. The Fanconi Anemia Group C complementation group gene (FANCC) has been previously reported to have an anti-inflammation effect; however, whether it can regulate microglial pyroptosis remains unknown. Therefore, we probed the mechanism associated with FANCC-mediated microglial pyroptosis and neuroinflammation in vitro and in vivo in SCI mice. Methods Microglial pyroptosis was assessed by western blotting (WB) and immunofluorescence (IF), whereas microglial-induced neuroinflammation was evaluated by WB, Enzyme-linked immunosorbent assays and IF. Besides, flow cytometry, TdT-mediated dUTP Nick-End Labeling staining and WB were employed to examine the level of neuronal apoptosis. Morphological changes in neurons were assessed by hematoxylin–eosin and Luxol Fast Blue staining. Finally, locomotor function rehabilitation was analyzed using the Basso Mouse Scale and Louisville Swim Scale. Results Overexpression of FANCC suppressed microglial pyroptosis via inhibiting p38/NLRP3 expression, which in turn reduced neuronal apoptosis. By contrast, knockdown of FANCC increased the degree of neuronal apoptosis by aggravating microglial pyroptosis. Besides, increased glial scar formation, severe myelin sheath destruction and poor axon outgrowth were observed in the mice transfected with short hairpin RNA of FANCC post SCI, which caused reduced locomotor function recovery. Conclusions Taken together, a previously unknown role of FANCC was identified in SCI, where its deficiency led to microglia pyroptosis, neuronal apoptosis and neurological damage. Mechanistically, FANCC mediated microglia pyroptosis and the inflammatory response via regulating the p38/NLRP3 pathway.

A new species of Oreocharis, O. guangwushanensis from the Sichuan Province of south-western China, is described and illustrated here. This new species has a pink corolla that is different from other species of Oreocharis in southwest China and, although it is morphologically similar to O. ronganensis and O. reticuliflora, it has significant differences in the colour and shape of the corolla, the apex of the corolla limb, shape and indumentum of the filaments and a shorter pistil. A detailed description, colour photographs, distribution and habitat, as well as the IUCN conservation status, are also provided.

ObjectiveTo determine the effectiveness of traditional Chinese mind–body exercises in improving cognition, memory, and executive function in older adults with cognitive impairment.Data sourcesRelevant English and Chinese language studies published until September 14th, 2022 were retrieved from PubMed, Web of Science, Cochrane Library, Embase, CINAHL, WAN FANG DATA, VIP Information, CNKI, and SinoMed databases.Review methodsRandomized controlled trials assessing traditional Chinese mind–body exercises (Tai Chi, Baduanjin, Qigong, Mind–Body Therapies, and Yijinjing) in older adults with cognitive impairment were included. Two researchers independently identified eligible studies and extracted data. A risk-of-bias assessment was performed using the Cochrane Risk of Bias Tool.ResultsThis study included 15 randomized controlled trials (1,127 participants) from China, Thailand and American. Most studies had a high risk of bias in the blinding of participants and researchers, one study had a high risk of bias in the random sequence generation and two studies had a high risk of bias in the incomplete outcome data. Compared with conventional therapy alone, traditional Chinese mind–body exercises significantly improved global cognitive function (p

Abstract Background This study aimed to assess the influence factors of the mutual-support willingness and identify the mutual-support needs of elderly living in rural areas of Hunan Province, China. Methods Using the Chi-square test and logistic regression to analyze factors influencing Participants’ mutual-support willingness and needs. Results Factors influencing the mutual-support willingness and needs included individual characteristics, family environment, and so on. And the rural elderly’s demand for mutual-support is at a relatively high level. The total score for social support for the aged was 36.944 ± 6.487, at a moderate level. Conclusions It is necessary to objectively evaluate the factors related to mutual-support willingness and needs and take steps to enhance social support and meet elderly the needs of mutual-support, which is of great significance for improving the happiness of the elderly in their later years and alleviating the crisis of population aging in China.

Abstract Background The role of socioeconomic status (SES) on hypertension prevalence and hypertension control has gotten much attention but with conflicting results. This paper aimed to quantify the association of SES with both hypertension prevalence and hypertension control rate in Nanjing, China. Methods A community-based cross-sectional study was conducted using multistage random sampling on 60,283 adults aged more than 18 years between March 2017 and June 2018. Hypertension was defined as systolic blood pressure (BP) ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg or self-reported diagnosis of hypertension or respondent's report of taking antihypertensive medications. The controlled hypertension was defined by systolic BP

In low signal-to-noise ratio (SNR) environments, the traditional radar emitter recognition (RER) method struggles to recognize multiple radar emitter signals in parallel. This paper proposes a multi-label classification and recognition method for multiple radar-emitter modulation types based on a residual network. This method can quickly perform parallel classification and recognition of multi-modulation radar time-domain aliasing signals under low SNRs. First, we perform time-frequency analysis on the received signal to extract the normalized time-frequency image through the short-time Fourier transform (STFT). The time-frequency distribution image is then denoised using a deep normalized convolutional neural network (DNCNN). Secondly, the multi-label classification and recognition model for multi-modulation radar emitter time-domain aliasing signals is established, and learning the characteristics of radar signal time-frequency distribution image dataset to achieve the purpose of training model. Finally, time-frequency image is recognized and classified through the model, thus completing the automatic classification and recognition of the time-domain aliasing signal. Simulation results show that the proposed method can classify and recognize radar emitter signals of different modulation types in parallel under low SNRs.

This paper considers the problem of target and jamming recognition for the pulse Doppler radar fuze (PDRF). To solve the problem, the matched filter outputs of the PDRF under the action of target and jamming are analyzed. Then, the frequency entropy and peak-to-peak ratio are extracted from the matched filter output of the PDRF, and the time-frequency joint feature is constructed. Based on the time-frequency joint feature, the naive Bayesian classifier (NBC) with minimal risk is established for target and jamming recognition. To improve the adaptability of the proposed method in complex environments, an online update process that adaptively modifies the classifier in the duration of the work of the PDRF is proposed. The experiments show that the PDRF can maintain high recognition accuracy when the signal-to-noise ratio (SNR) decreases and the jamming-to-signal ratio (JSR) increases. Moreover, the applicable analysis shows that he ONBCMR method has low computational complexity and can fully meet the real-time requirements of PDRF.

The traditional tangent impulse interception problem does not consider the influence of actual deviation. However, by taking the actual state deviation of the interceptor into the orbit design process, an interception orbit that is more robust than the nominal orbit can be obtained. Therefore, we study the minimum time interception problem and the minimum terminal interception error problem under tangent impulse conditions and give an orbit optimization method that considers the interception time and the interception uncertainty. First, we express the interceptor's transfer time equation as a form of flight path angle, establish a global optimization model for solving the minimum time tangent impulse interception and give a hybrid optimization algorithm based on Augmented Lagrange Genetic Algorithm - Sequential Quadratic Programming (ALGA-SQP). Secondly, we use the universal time equation and Bootstrap resampling technology to calculate the interceptor's terminal error distribution and establish the relevant global optimization model by using the circumscribed cuboid volume of the interceptor's terminal position error ellipsoid as the optimization index. Finally, we combined the above two single-objective optimization models to establish a global multi-objective optimization model that considers interception time and interception uncertainty and gave a hybrid multi-objective optimization algorithm based on Non-dominated Sorting Genetic Algorithm II - Goal Achievement Method (NSGA2-GAM). The simulation example verifies the effectiveness of this method.

Actinostephanus, a new genus from southern China, is described and colorfully illustrated with a single species, A. enpingensis. This new genus is morphologically most similar to Boeica and Leptoboea, nevertheless, it can be easily distinguished from the latter two by the following characteristics, such as leaves in whorls of three, all closely clustered at the top; corolla bowl-shaped, 5-lobed, actinomorphic; capsule hard, oblong-ovoid, short, 3–4 mm long, densely appressed villous, wrapped by persistent densely pubescent calyx lobes, style persistent. The new genus and related genera were sequenced using the next-generation sequencing technique. The whole plastid genome of the new genus is 154, 315 – 154, 344 bp in length. We reconstructed phylogenetic trees using the dataset of 80 encoded protein genes of the whole plastid genome from 47 accessions based on ML and BI analyses. The result revealed that the new genus was recovering in a polytomy including Boeica, Rhynchotechum, and Leptoboea with strong support, congruent to the morphological evidence. A global conservation assessment was also performed and classifies A. enpingensis as Least Concern (LC). In addition, after a review of recently described species of Gesneriaceae, we propose that plant enthusiasts, especially Gesneriad fans, have been playing an increasingly important role in the process of new taxa-discoveries.

Osteopenia and osteoporosis are among the most common metabolic bone diseases and represent major public health problems, with sufferers having an increased fracture risk. Diabetes is one of the most common diseases contributing to osteopenia and osteoporosis. However, the mechanisms underlying diabetes-induced osteopenia and osteoporosis remain unclear. Bone reconstruction, including bone formation and absorption, is a dynamic process. Large-conductance Ca2+-activated K+ channels (BK channels) regulate the function of bone marrow-derived mesenchymal stem cells, osteoblasts, and osteoclasts. Our previous studies revealed the relationship between BK channels and the function of osteoblasts via various pathways under physiological conditions. In this study, we reported a decrease in the expression of BK channels in mice with diabetes-induced osteopenia. BK deficiency enhanced mitochondrial Ca2+ and activated classical PINK1 (PTEN induced putative kinase 1)-PRKN/Parkin (parkin RBR E3 ubiquitin protein ligase)-dependent mitophagy, whereas the upregulation of BK channels inhibited mitophagy in osteoblasts. Moreover, SLC25A5/ANT2 (solute carrier family 25 (mitochondrial carrier, adenine nucleotide translocator), member 5), a critical inner mitochondrial membrane protein participating in PINK1-PRKN-dependent mitophagy, was also regulated by BK channels. Overall, these data identified a novel role of BK channels in regulating mitophagy in osteoblasts, which might be a potential target for diabetes-induced bone diseases. Abbreviations: AGE, advanced glycation end products; Baf A1, bafilomycin A1; BK channels, big-conductance Ca2+-activated K+ channels; BMSCs, bone marrow-derived mesenchymal stem cells; BSA, bovine serum albumin; FBG, fasting blood glucose; IMM, inner mitochondrial membrane; ITPR1, inositol 1,4,5-trisphosphate receptor 1; MAM, mitochondria-associated ER membrane; OMM, outer mitochondrial membrane; PINK1, PTEN induced putative kinase 1; PPID/CyP-D, peptidylprolyl isomerase D (cyclophilin D); PRKN/PARK2, parkin RBR E3 ubiquitin protein ligase; ROS, reactive oxygen species; SLC25A5/ANT2, solute carrier family 25 (mitochondrial carrier, adenine nucleotide translocator), member 5; STZ, streptozotocin. [ABSTRACT FROM AUTHOR]

Diabetic peripheral neuropathy (DPN) is the most prevalent chronic complication among diabetic patients and a primary risk factor contributing to the deterioration of diabetic foot conditions. The pathogenesis of DPN remains complex and not fully understood, and there are hardly any effective treatment drugs. Maltol (3-hydroxy-2-methyl-4-pyranone) has demonstrated antioxidant and anti-inflammatory properties. However, the potential role of maltol in the treatment of DPN remains unclear. This study aimed to assess maltol's effects on DPN rats and high glucose (HG)/palmitic acid (PA)-induced rat Schwann cells (RSC96). The results indicated maltol's capacity to enhance peripheral nerve function in DPN rats. In RSC96 cells stimulated with high HG and PA, maltol treatment reduced DPN markers and apoptosis-related proteins. Functional enrichment analysis of differentially expressed genes revealed that endoplasmic reticulum (ER) stress pathways were involved in this process. Western blot results demonstrated the activation of ER stress pathway in HG/PA-induced RSC96 cells, with maltol attenuating ER stress-related protein expression. Furthermore, the knockdown of Membrane metallo-endopeptidase (MME) reversed maltol's effects on apoptosis-related protein expression, suggesting a potential therapeutic role for maltol via MME in treating DPN. These findings indicate that maltol may hold promise as a therapeutic agent for DPN treatment. [ABSTRACT FROM AUTHOR]

SPOC is characterized by improving teaching effectiveness. Currently open teaching mode is the popular trend, which is mainly related to several aspects: how to carry out teaching practice by using MOOC proprietary, high-quality online teaching resources in open education, that is, deep integration of curriculum resources and teaching design. On the basis of SPOC development, combined with open education analysis of SPOC with instructional design theory and philosophy from flipped classroom as a guide, the present research tries to propose instructional design model based on flipped classroom, including design of teaching content system, design of personalized learning strategies, design of teaching activities and teaching evaluation system. Four designs above contribute to the effective implementation of the open teaching activities based on the blended model of flipped classroom and SPOC teaching, so as to enhance the quality of education.