Disrupting the Indian hedgehog signaling pathway in vivo attenuates surgically induced osteoarthritis progression in Col2a1-CreERT2; Ihhfl/fl mice

Introduction: Previous observations implicate Indian hedgehog (Ihh) signaling in osteoarthritis (OA) development because it regulates chondrocyte hypertrophy and matrix metallopeptidase 13 (MMP-13) expression. However, there is no direct genetic evidence for the role of Ihh in OA, because mice with cartilage or other tissue-specific deletion of the Ihh gene die shortly after birth. We evaluated the role of Ihh in vivo via a Cre-loxP-mediated approach to circumvent the early death caused by Ihh deficiency. Methods: To evaluate the role of Ihh in OA development, Ihh was specifically deleted in murine cartilage using an Ihh conditional deletion construct (Col2a1-CreERT2; Ihhfl/fl). The extent of cartilage degradation and OA progression after Ihh deletion was assessed by histological analysis, immunohistochemistry, real-time PCR and in vivo fluorescence molecular tomography (FMT) 2 months after OA was induced by partial medial meniscectomy. The effect of Ihh signaling on cartilage was compared between Ihh-deleted mice and their control littermates. Results: Only mild OA changes were observed in Ihh-deleted mice, while control mice displayed significantly more cartilage damage. Typical OA markers such as type X collagen and MMP-13 were decreased in Ihh-deleted mice. In vivo FMT demonstrated decreased cathepsins and MMP activity in knee joints of animals with deletion of Ihh. Conclusions: These findings support the protective role of Ihh deletion in surgically induced OA. Thus, our findings suggest the potential to develop new therapeutic strategies that can prevent and treat OA by inhibiting Ihh signaling in chondrocytes

A Few-Shot Learning Method for SAR Images Based on Weighted Distance and Feature Fusion

Convolutional Neural Network (CNN) has been widely applied in the field of synthetic aperture radar (SAR) image recognition. Nevertheless, CNN-based recognition methods usually encounter the problem of poor feature representation ability due to insufficient labeled SAR images. In addition, the large inner-class variety and high cross-class similarity of SAR images pose a challenge for classification. To alleviate the problems mentioned above, we propose a novel few-shot learning (FSL) method for SAR image recognition, which is composed of the multi-feature fusion network (MFFN) and the weighted distance classifier (WDC). The MFFN is utilized to extract input images’ features, and the WDC outputs the classification results based on these features. The MFFN is constructed by adding a multi-scale feature fusion module (MsFFM) and a hand-crafted feature insertion module (HcFIM) to a standard CNN. The feature extraction and representation capability can be enhanced by inserting the traditional hand-crafted features as auxiliary features. With the aid of information from different scales of features, targets of the same class can be more easily aggregated. The weight generation module in WDC is designed to generate category-specific weights for query images. The WDC distributes these weights along the corresponding Euclidean distance to tackle the high cross-class similarity problem. In addition, weight generation loss is proposed to improve recognition performance by guiding the weight generation module. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset and the Vehicle and Aircraft (VA) dataset demonstrate that our proposed method surpasses several typical FSL methods

A Few-Shot Learning Method for SAR Images Based on Weighted Distance and Feature Fusion

Convolutional Neural Network (CNN) has been widely applied in the field of synthetic aperture radar (SAR) image recognition. Nevertheless, CNN-based recognition methods usually encounter the problem of poor feature representation ability due to insufficient labeled SAR images. In addition, the large inner-class variety and high cross-class similarity of SAR images pose a challenge for classification. To alleviate the problems mentioned above, we propose a novel few-shot learning (FSL) method for SAR image recognition, which is composed of the multi-feature fusion network (MFFN) and the weighted distance classifier (WDC). The MFFN is utilized to extract input images’ features, and the WDC outputs the classification results based on these features. The MFFN is constructed by adding a multi-scale feature fusion module (MsFFM) and a hand-crafted feature insertion module (HcFIM) to a standard CNN. The feature extraction and representation capability can be enhanced by inserting the traditional hand-crafted features as auxiliary features. With the aid of information from different scales of features, targets of the same class can be more easily aggregated. The weight generation module in WDC is designed to generate category-specific weights for query images. The WDC distributes these weights along the corresponding Euclidean distance to tackle the high cross-class similarity problem. In addition, weight generation loss is proposed to improve recognition performance by guiding the weight generation module. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset and the Vehicle and Aircraft (VA) dataset demonstrate that our proposed method surpasses several typical FSL methods

Transcranial direct current stimulation regulates phenotypic transformation of microglia to relieve neuropathic pain induced by spinal cord injury

ObjectiveNeuropathic pain is a common complication after spinal cord injury (SCI). Transcranial direct current stimulation (tDCS) has been confirmed to be effective in relieving neuropathic pain in patients with SCI. The aim of this study is to investigate the effect of tDCS on neuropathic pain induced by SCI and its underlying mechanism.Materials and methodsThe SCI model was induced by a clip-compression injury and tDCS stimulation was performed for two courses (5 days/each). The motor function was evaluated by Basso-Beattie-Bresnahan (BBB) score, and the thermal withdrawal threshold was evaluated by the thermal radiation method. The effects of tDCS on the cerebral cortex, thalamus, midbrain, and medulla were detected by the enzyme-linked immunosorbent assay (ELISA) and immunofluorescence.ResultsThe results showed that SCI reduced the thermal withdrawal threshold and increased the concentration of inflammatory cytokines in the cortex, thalamus, midbrain, and medulla, including the tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6). In addition, the activation of microglia and the proportion of M1 phenotypic polarization increased significantly in the ventral posterolateral (VPL), ventral tegmental (VTA), and periaqueductal gray (PAG) regions after SCI. After tDCS treatment, the thermal withdrawal threshold and motor function of SCI rats were significantly improved compared to the vehicle group. Meanwhile, tDCS effectively reduced the concentration of pro-inflammatory cytokines in the cortex, thalamus, midbrain, and medulla and increased the concentration of anti-inflammatory cytokines interleukin-10 (IL-10) in the thalamus. In addition, tDCS reduced the proportion of the M1 phenotype of microglia in VPL, VTA, and PAG regions and increase the proportion of the M2 phenotype.ConclusionThe results suggest that tDCS can effectively relieve SCI-induced neuropathic pain. Its mechanism may be related to regulating the inflammatory and anti-inflammatory cytokines in corresponding brain regions via promoting the phenotypic transformation of microglia

Breaking Symmetry: Engineering Single-Chain Dimeric Streptavidin as Host for Artificial Metalloenzymes

The biotin-streptavidin technology has been extensively exploited to engineer artificial metalloenzymes (ArMs) that catalyze a dozen different reactions. Despite its versatility, the homotetrameric nature of streptavidin (Sav) and the noncooperative binding of biotinylated cofactors impose two limitations on the genetic optimization of ArMs: (i) point mutations are reflected in all four subunits of Sav, and (ii) the noncooperative binding of biotinylated cofactors to Sav may lead to an erosion in the catalytic performance, depending on the cofactor:biotin-binding site ratio. To address these challenges, we report on our efforts to engineer a (monovalent) single-chain dimeric streptavidin (scdSav) as scaffold for Sav-based ArMs. The versatility of scdSav as host protein is highlighted for the asymmetric transfer hydrogenation of prochiral imines using [Cp*Ir(biot-p-L)Cl] as cofactor. By capitalizing on a more precise genetic fine-tuning of the biotin-binding vestibule, unrivaled levels of activity and selectivity were achieved for the reduction of challenging prochiral imines. Comparison of the saturation kinetic data and X-ray structures of [Cp*Ir(biot-p-L)Cl]·scdSav with a structurally related [Cp*Ir(biot-p-L)Cl]·monovalent scdSav highlights the advantages of the presence of a single biotinylated cofactor precisely localized within the biotin-binding vestibule of the monovalent scdSav. The practicality of scdSav-based ArMs was illustrated for the reduction of the salsolidine precursor (500 mM) to afford (R)-salsolidine in 90% ee and >17âEuro¯000 TONs. Monovalent scdSav thus provides a versatile scaffold to evolve more efficient ArMs for in vivo catalysis and large-scale applications

Efficacy and pharmacoeconomic advantages of Fufang Huangbai Fluid hydropathic compress in diabetic foot infections: a comparative clinical study with antimicrobial calcium alginate wound dressing

Objective: To compare the intervention effects and pharmacoeconomic advantages of Fufang Huangbai Fluid (FFHB) hydropathic compress versus Antimicrobial Calcium Alginate Wound Dressing (ACAWD) in the treatment of diabetic foot infections (DFI).Methods: Patients with DF who were hospitalized in the peripheral vascular Department of Dongzhimen Hospital of Beijing University of Chinese Medicine from December 2020 to February 2022 and met the inclusion and excluding criteria were allocated into the experimental group and control group through minimization randomization. The experimental group was treated with FFHB hydropathic compress for 2 weeks, while the control group was treated with ACAWD for the same duration. The wound healing of both groups was monitored for 1 month post-discharge. Clinical data from all eligible patients were collected, and differences in various indices between cohorts were analyzed.Results: 22 in the experimental group (including two fell off) and 20 in the control group. After the treatment, the negative rate of wound culture in the experimental group was 30% and that in the control group was 10%, There was no significant difference in the negative rate of wound culture and change trend of minimum inhibitory concentration (MIC) value of drug sensitivity (p > 0.05). The infection control rate of the experimental group was 60%, and that of the control group was 25%. The difference between the two groups was statistically significant (χ2 = 5.013, p = 0.025). The median wound healing rate of the experimental group was 34.4% and that of the control group was 33.3%. There was no significant difference between the two groups (p > 0.05). During the follow-up 1 month later, the wound healing rate in the experimental group was higher, and the difference was statistically significant (p = 0.047). Pharmacoeconomic evaluations indicated that the experimental group had greater cost-effectiveness compared to the control group.Conclusion: In the preliminary study, FFHB demonstrated comparable pathogenic and clinical efficacy to ACAWD in the treatment of mild DF infection, and exhibited superior pharmacoeconomic advantages. With the aid of infection control, the wound healing rate in the FFHB group showed notable improvement. Nevertheless, due to the limited sample size, larger-scale studies are warranted to further validate these findings.Clinical Trial Registration: (https://www.chictr.org.cn/showproj.aspx?proj=66175), identifier (ChiCTR2000041443)

Market-Driven Rural Construction—A Case Study of Fuhong Town, Chengdu

Although local government has played an important role in rural China’s development, some disadvantages of government-led rural construction have gradually emerged with changes in socioeconomic structure, which have negative impacts on rural development. To solve the problems of the traditional rural construction pattern, the introduction of market mechanisms into rural construction became the consensus in theory and in practice. Extant studies emphasize the importance of a market-driven rural construction pattern; however, they do not discuss how to practice this pattern in detail. Thus, this paper uses a case study and comparative analysis to illustrate the background, implementation process and outcomes of the market-driven pattern, aiming to identify the intrinsic dynamics among the local government, market capital and villagers in the market-driven pattern. We argue that although the transformation from a government-led to market-driven pattern is a gradual process, the market-driven pattern is an alternative to the traditional pattern and can better fulfill villagers’ interests and enhance sustainable rural development