SHH induces macrophage oxidative phosphorylation and efferocytosis to promote scar formation.

Excessive scar formation such as hypertrophic scars and keloids, resulting from trauma or surgical procedures, present a widespread concern for causing disfigurement, discomfort, and functional limitations. Macrophages play pivotal roles in maintaining tissue homeostasis, orchestrating tissue development, repair, and immune responses, and its transition of function and phenotype plays a critical role in regulating the balance between inflammation and tissue regeneration, which is central to cutaneous scar formation. Recent evidence suggests the involvement of Sonic Hedgehog (SHH) in the induction of anti-inflammatory M2-like macrophage phenotypes within tumor microenvironments. In our study, we observed increased SHH expression in human hypertrophic scars, prompting an investigation into its influence on macrophage polarization, efferocytosis, and cutaneous scar formation. Our findings reveal that SHH can enhance oxidative phosphorylation (OXPHOS) in macrophages, augment macrophage efferocytosis, and promote M2 polarization, finally contributing to the progression of cutaneous scar formation. Notably, targeting SHH signaling with vismodegib exhibited promising potential in mitigating scar formation by reversing the effects of enhanced OXPHOS and M2 polarization in macrophages. In conclusion, this study underscores the critical roles of macrophage metabolism, particularly OXPHOS, efferocytosis and SHH signaling in cutaneous scar formation. Understanding these mechanisms provides new avenues for potential interventions and scar prevention strategies.

Lipotoxicity: The missing link between diabetes and periodontitis?

Lipotoxicity refers to the accumulation of lipids in tissues other than adipose tissue (body fat). It is one of the major pathophysiological mechanisms responsible for the progression of diabetes complications such as non-alcoholic fatty liver disease and diabetic nephropathy. Accumulating evidence indicates that lipotoxicity also contributes significantly to the toxic effects of diabetes on periodontitis. Therefore, we reviewed the current in vivo, in vitro, and clinical evidence of the detrimental effects of lipotoxicity on periodontitis, focusing on its molecular mechanisms, especially oxidative and endoplasmic reticulum stress, inflammation, ceramides, adipokines, and programmed cell death pathways. By elucidating potential therapeutic strategies targeting lipotoxicity and describing their associated mechanisms and clinical outcomes, including metformin, statins, liraglutide, adiponectin, and omega-3 PUFA, this review seeks to provide a more comprehensive and effective treatment framework against diabetes-associated periodontitis. Furthermore, the challenges and future research directions are proposed, aiming to contribute to a more profound understanding of the impact of lipotoxicity on periodontitis.

Asymmetric adhesive SIS-based wound dressings for therapeutically targeting wound repair.

Severe tissue injuries pose a significant risk to human health. Conventional wound dressings fall short in achieving effective tissue regeneration, resulting in suboptimal postoperative healing outcomes. In this study, an asymmetric adhesive wound dressing (marked as SIS/PAA/LAP) was developed, originating from acrylate acid (AA) solution with laponite (LAP) nanoparticles polymerization and photo-crosslinked on the decellularized extracellular matrix small intestinal submucosa (SIS) patch. Extensive studies demonstrated that the SIS/PAA/LAP exhibited higher tissue adhesion strength (~ 33 kPa) and burst strength (~ 22 kPa) compared to conventional wound dressings like Tegaderm and tissue adhesive products. Importantly, it maintained favorable cell viability and demonstrated robust angiogenic capacity. In animal models of full-thickness skin injuries in rats and skin injuries in Bama miniature pigs, the SIS/PAA/LAP could be precisely applied to wound sites. By accelerating the formation of tissue vascularization, it displayed superior tissue repair outcomes. This asymmetrically adhesive SIS-based patch would hold promising applications in the field of wound dressings.

Application of Decellularized Adipose Matrix as a Bioscaffold in Different Tissue Engineering.

With the development of tissue engineering, the application of decellularized adipose matrix as scaffold material in tissue engineering has been intensively explored due to its wide source and excellent potential in tissue regeneration. Decellularized adipose matrix is a promising candidate for adipose tissue regeneration, while modification of decellularized adipose matrix scaffold can also allow it to transcend the limitations of adipose tissue source properties and applied to other tissue engineering fields, including cartilage and bone tissue engineering, neural tissue engineering, and skin tissue engineering. In this review, we summarized the development of the applications of decellularized adipose matrix in different tissue engineering and present future perspectives.Level of Evidence III This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Factors Affecting Patient Satisfaction with Double-Eyelid Blepharoplasty.

BACKGROUND: Blepharoplasty is a common surgical technique performed in individuals seeking aesthetic enhancement. Thus, it is essential to investigate the factors influencing postoperative satisfaction from the patient's perspective. In this study, patient-rated outcome measure questionnaires were used to identify the factors affecting patient satisfaction after full-incision upper blepharoplasty. METHODS: This retrospective study analyzed patients who underwent full-incision upper blepharoplasty at an outpatient clinic in China. The questionnaire responses were collected by telephone, text messaging, or email at 6 and 12 months postoperatively. RESULTS: In total, 149 questionnaires were collected. After a mean follow-up of 23.23 months, the patients' overall satisfaction rate was 89.43%. The factors that significantly affected postoperative satisfaction were the patient's education level, the source of referral to the surgeon, the patient's understanding of the surgical risks, application of a cold compress after surgery as recommended, unsatisfactory postoperative double-eyelid width, postoperative bilateral asymmetry, apparent postoperative cicatrices, and postoperative caterpillar-like appearance of the double eyelids. Education level, apparent postoperative cicatrices, and postoperative bilateral asymmetry influenced the patient's satisfaction with the surgical outcome. The patient's understanding of the surgical risks, unsatisfactory postoperative double-eyelid width, postoperative bilateral asymmetry, apparent postoperative cicatrices, and postoperative caterpillar-like appearance influenced the satisfaction of the patient's family and friends. CONCLUSIONS: Postoperative bilateral asymmetry, apparent postoperative cicatrices, and a low education level of the patient are independent factors that negatively affect patient satisfaction with the outcome of double-eyelid blepharoplasty. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Validation of a physiological type 2 diabetes model in human periodontal ligament stem cells.

OBJECTIVES: Type 2 diabetes (T2DM), a recognized risk factor for periodontitis, is characterized by insulin resistance. However, the molecular mechanisms concerning the role of insulin resistance in linking T2DM and periodontitis remain poorly elucidated due to the absence of an appropriate T2DM cell model. We aimed to explore an appropriate model of T2DM in human periodontal ligament stem cells (hPDLSCs) and uncover the involved mechanisms. MATERIALS AND METHODS: hPDLSCs were incubated with common reagents for recapitulating insulin resistance state including high glucose (HG) (15, 25, 35, 45 mM), glucosamine (0.8, 8, 18, 28, 38 mM), or palmitic acid (PA; 100, 200, 400, 800 µM), combined with LPS for 48 h. The insulin signaling pathway, inflammation, and pyroptosis were detected by western blots and quantitative real-time polymerase chain reaction (RT-qPCR). The effects on osteogenesis were evaluated by alkaline phosphatase staining, alizarin red S staining, RT-qPCR, and western blots. RESULTS: HG failed to recapitulate insulin resistance. Glucosamine was sufficient to induce insulin resistance but failed to trigger inflammation. In total, 100 and 200 µM PA exhibited the most proinflammatory, insulin resistance, and pyroptosis induced role, and inhibited the osteogenic differentiation of hPDLSCs. CONCLUSION: Palmitic acid is a promising candidate for developing T2DM model in hPDLSCs.

Ba3HgGa2S7: A Zero-Dimensional Quaternary Sulfide Featuring a Unique [Hg2Ga4S14]12- String and Exhibiting a High Photocurrent Response.

The discovery of new types of metal sulfides is attractive because of their rich structures and diverse physical properties. Here, a novel quaternary sulfide, Ba3HgGa2S7 (BHGS), is obtained by a solid-state reaction at 1123 K. It crystallizes in the monoclinic space group P21/c, and its zero-dimensional structure features two seesaw-like HgS2 units and four GaS4 tetrahedra, constructing a unique [Hg2Ga4S14]12- string. BHGS has a wide band gap of 3.64 eV and a large birefringence of 0.09 at 2100 nm. Specifically, BHGS exhibits a remarkable photocurrent response. This work may be extended to a new family of AE3MIIMIII2Q7 (AE = Mg, Ca, Sr, Ba; MII = Zn, Cd, Hg; MIII = Al, Ga, In; Q = S, Se) chalcogenides.

Eu2 P2 S6 : The First Rare-Earth Chalcogenophosphate Exhibiting Large Second-Harmonic Generation Response and High Laser-Induced Damage Threshold.

Metal chalcogenophosphates are receiving increasing interest, specifically as promising infrared nonlinear optical (NLO) candidates. Here, a rare-earth chalcogenophosphate Eu2 P2 S6 crystallizing in the monoclinic noncentrosymmetric space group Pn was synthesized using a high-temperature solid-state method. Its structure features isolated [P2 S6 ]4- dimer, and two types of EuS8 bicapped triangular prisms. Eu2 P2 S6 exhibits a phase-matchable second-harmonic generation (SHG) response ≈0.9×AgGaS2 @2.1 µm, and high laser-induced damage threshold of 3.4×AgGaS2 , representing the first rare-earth NLO chalcogenophosphate. The theoretical calculation result suggests that the SHG response is ascribed to the synergetic contribution of [P2 S6 ]4- dimers and EuS8 bicapped triangular prisms. This work provides not only a promising high-performance infrared NLO material, but also opens the avenue for exploring rare-earth chalcogenophosphates as potential IR NLO materials.

Site-Specific Photochemical Desaturation Enables Divergent Syntheses of Illicium Sesquiterpenes.

Desaturation of unactivated alkanes remains a challenging yet desirable strategy to make olefins. The Illicium sesquiterpenes usually possess highly oxygenated cage-like architectures, and some of them exhibit prominent neurotrophic effects. Here, we disclose a unique photochemical desaturation strategy for the efficient, highly stereocontrolled total syntheses of five Illicium sesquiterpenes from inexpensive (R)-pulegone, featuring a 13-step gram-scale synthesis of (-)-merrilactone A. The efficiency of the syntheses derives from an expedient construction of a tetracyclic framework via two annulations, a site-specific photoinduced single-step desaturation in a complex hydrocarbon system, and diverse oxygenation manipulations around the resultant olefin intermediate. This work highlights how late-stage desaturation can dramatically streamline the synthesis of complex terpenes and diverse non-natural analogues for establishing the structure-activity relationship and elucidating their molecular mechanisms of bioactivity.

Noncentrosymmetric Ba6In2Q10 (Q = S, Se): Structural Chemistry and Nonlinear-Optical Activity.

The indispensable condition for laser frequency-doubling crystal materials is that they crystallize in the noncentrosymmetric (NCS) structures. Here, ternary NCS Ba6In2S10 (1) and Ba6In2Se10 (2) (P63) were synthesized via conventional solid-state reactions. Their zero-dimensional structures feature isolated InQ4 tetrahedra and Q22- (Q = S, Se) dimers that are separated by Ba2+ counter cations. The structural relevance and differences with the centrosymmetric Ba12In4S19 and Ba12In4Se20 are analyzed in detail. Both 1 and 2 show obvious laser frequency-doubling activity, and their optical band gaps are 3.72 and 1.78 eV, respectively. This work provides a new type of IR nonlinear-optical materials.

Structural Transformation and Second-Harmonic-Generation Activity in Rare-Earth and d0 Transition-Metal Oxysulfides RE3NbS3O4 (RE = Ce, Sm, Gd, Dy).

Investigations of inorganic compounds with mixed anions have drawn much attention. Here, three oxysulfides, Sm3NbS3O4 (1), Gd3NbS3O4 (2), and Dy3NbS3O4 (3), are obtained by solid-state reactions. 1 and 2 crystallize in the polar space group Pna21, while 3 crystallizes in the centric space group Pnma. The anionic frameworks of 1 and 2 are built by isolated distorted [NbS2O4]7- octahedra, while [NbS3O4]9- is used for 3. 1 and 2 exhibit phase-matchable second-harmonic-generation (SHG) effects of about 0.3 and 0.4 × AGS at 2.1 µm. The [NbS2O4]7- octahedron was first used as a SHG-active motif for nonlinear-optical (NLO) materials. A systematic analysis of the transformation between these crystal structures, NLO performances, and magnetic behaviors, as well as first-principles theoretical studies, is presented. This work enriches the study on relatively rarely explored NLO-active metal oxysulfides.

Nano-Sized NiO Immobilized on Au/CNT for Benzyl Alcohol Oxidation: Influences of Hybrid Structure and Interface.

Tiny gold nanoparticles were successfully anchored on carbon nanotubes (CNT) with NiO decoration by a two-step synthesis. Characterizations suggested that Ni species in an oxidative state preferred to be highly dispersed on CNT. During the synthesis, in situ reduction by NaBH4 and thermal treatment in oxidation atmosphere were consequently carried out, causing the formation of Au-Ni-Ox interfaces and bimetal hybrid structure depending on the Ni/Au atomic ratios. With an appropriate Ni/Au atomic ratio of 8:1, Ni atoms migrated into the sub-layers of Au particles and induced the lattice contraction of Au particles, whilst a higher Ni/Au atomic ratio led to the accumulation of NiO fractions surrounding Au particles. Both contributed to the well-defined Au-Ni-Ox interface and accelerated reaction rates. Nickel species acted as structure promoters with essential Au-Ni-Ox hybrid structure as well as the active oxygen supplier, accounting for the enhanced activity for benzyl alcohol oxidation. However, the over-layer of unsaturated gold sites easily occured under a high Ni/Au ratio, resulting in a lower reaction rate. With an Au/Ni atomic ratio of 8:1, the specific rate of AuNi8/CNT reached 185 µmol/g/s at only 50 °C in O2 at ordinary pressure.

Recent progress in the total synthesis of marine brominated sesquiterpene aplydactone.

Aplydactone is a brominated sesquiterpene isolated from the sea hare Aplysia dactylomela. Structurally, it features a complex cage-like skeleton containing a highly strained tricyclic-[4.2.0.03,8]-4-decanone system. Its unique structural features have fascinated many synthetic chemists. In this review, the synthetic efforts towards aplydactone in the last five years are summarized in two categories including nonbiomimetic synthesis and biomimetic synthesis based on the core synthetic strategy. These syntheses set a classical and instructive example for the syntheses of other marine natural products.

Conformational Design Principles in Total Synthesis.

Conformation is one of the most fundamental concepts in organic chemistry for chemists to visualize a molecule as a three-dimensional object in addition to its constitution and configuration. Conformational factors significantly affect the physical properties, chemical reactivities, and biological activities of a molecule. The significance of conformational design has been generally recognized since its successful application in the total synthesis of complex natural products, such as vitamin B12 and erythronolide. Conformational analysis, especially intentional control of conformational preferences by conformational design, could play a critical role in the synthesis of complex organic molecules by guiding the formation of bonds, stereocenters, or rings. This Minireview highlights selected examples of conformational design in natural-product synthesis, with particular emphasis on the applications and new insights advanced in the last 20 years. The examples discussed herein are divided into three categories by structural features of the substrates: open-chain type, cyclohexane type, and medium- and large-ring type.

A Deep Learning Framework for Signal Detection and Modulation Classification.

Deep learning (DL) is a powerful technique which has achieved great success in many applications. However, its usage in communication systems has not been well explored. This paper investigates algorithms for multi-signals detection and modulation classification, which are significant in many communication systems. In this work, a DL framework for multi-signals detection and modulation recognition is proposed. Compared to some existing methods, the signal modulation format, center frequency, and start-stop time can be obtained from the proposed scheme. Furthermore, two types of networks are built: (1) Single shot multibox detector (SSD) networks for signal detection and (2) multi-inputs convolutional neural networks (CNNs) for modulation recognition. Additionally, the importance of signal representation to different tasks is investigated. Experimental results demonstrate that the DL framework is capable of detecting and recognizing signals. And compared to the traditional methods and other deep network techniques, the current built DL framework can achieve better performance.

Connecting past and present.

A neural signature of serial dependence has been found, which mirrors the attractive bias of visual information seen in behavioral experiments.

Three-Dimensional Evaluation of Condylar Position and Joint Spaces Following Orthodontic Treatment With Quadruple Premolar Extractions.

This study aimed to assess the alterations in the temporomandibular joint among adult patients undergoing orthodontic treatment involving the extraction of four premolars. A cohort of 44 adults, with a mean age of 24.2 years, underwent orthodontic therapy that included quadruple premolar extractions. Cone-beam computed tomography scans were performed before and after the treatment to evaluate the temporomandibular joints. The three-dimensional assessment focused on the condylar position relative to the cranial base and the articular fossa, the axial condylar rotation, and the joint spaces. Notably, a significant posterior shift of the condyle was detected (P≤0.01), averaging a 0.41mm retraction. The posterior joint space narrowed by 0.32mm post-treatment. Additionally, a medial tilt of 0.62° in the condyle's long axis was observed in the frontal plane. No significant changes were recorded for the other condylar positions, rotations, or joint space dimensions. The findings suggest that orthodontic treatment with four premolar extractions may instigate condylar repositioning and rotation. These insights can inform refinements in treatment protocols.

Dietary crude protein and protein solubility manipulation enhances intestinal nitrogen absorption and mitigates reactive nitrogen emissions through gut microbiota and metabolome reprogramming in sheep.

Dietary nutrient manipulation (e.g. protein fractions) could lower the environmental footprints of ruminants, especially reactive nitrogen (N). This study investigated the impacts of dietary soluble protein (SP) levels with decreased crude protein (CP) on intestinal N absorption, hindgut N metabolism, fecal microbiota and metabolites, and their linkage with N metabolism phenotype. Thirty-two male Hu sheep, with an age of six months and an initial BW of 40.37 ± 1.18 kg, were randomly assigned to four dietary groups. The control diet (CON), aligning with NRC standards, maintained a CP content of 16.7% on a dry matter basis. Conversely, the experimental diets (LPA, LPB, and LPC) featured a 10% reduction in CP compared with CON, accompanied by SP adjustments to 21.2%, 25.9%, and 29.4% of CP, respectively. Our results showed that low-protein diets led to significant reductions in the concentrations of plasma creatinine, ammonia, urea N, and fecal total short-chain fatty acids (SCFA) (P < 0.05). Notably, LPB and LPC exhibited increased total SCFA and propionate concentrations compared with LPA (P < 0.05). The enrichment of the Prevotella genus in fecal microbiota associated with energy metabolism and amino acid (AA) biosynthesis pathways was evident with SP levels in low-protein diets of approximately 25% to 30%. Moreover, LPB and LPC diets demonstrated a decrease in fecal NH 4 + -N and NO 2 - -N contents as well as urease activity, compared with CON (P < 0.05). Concomitantly, reductions in fecal glutamic acid dehydrogenase gene (gdh), nitrite reductase gene (nirS), and nitric oxide reductase gene (norB) abundances were observed (P < 0.05), pointing towards a potential reduction in reactive N production at the source. Of significance, the up-regulation of mRNA abundance of AA and peptide transporters in the small intestine (duodenum, jejunum, and ileum) and the elevated concentration of plasma AA (e.g. arginine, methionine, aspartate, glutamate, etc.) underscored the enhancement of N absorption and N efficiency. In summary, a 10% reduction in CP, coupled with an SP level of approximately 25% to 30%, demonstrated the potential to curtail reactive N emissions through fecal Prevotella enrichment and improve intestinal energy and N utilization efficiency.

Transformer With Double Enhancement for Low-Dose CT Denoising.

Increasingly serious health problems have made the usage of computed tomography surge. Therefore, algorithms for processing CT images are becoming more and more abundant. These algorithms can lessen the harm of cumulative radiation in CT technology for the patient while eliminating the noise of image caused by dose reduction. However, the mainstream CNN-based algorithms are inefficient when dealing with features in broad regions. Inspired by the large receptive field of transformer framework, this paper designs an end-to-end low-dose CT (LDCT) denoising network based on the transformer. The overall network contains a main branch and dual side branches. Specifically, the overlapping-free window-based self-attention transformer block is adopted on the main branch to realize image denoising. On the dual side branches, we propose double enhancement module to enrich edge, texture, and context information of LDCT images. Meanwhile, the receptive field of network is further enlarged after processing, which is helpful for building model's long-range dependencies. The outputs of the side branches are concatenated for enhancing information and generating high-quality CT images. In addition, to better train the network, we introduce a compound loss function including mean squared error (MSE), multi-scale perceptual (MSP), and Sobel-L1 (SL) to make the denoised image closer to the targeted norm-dose CT (NDCT) image. Lastly, we conducted experiments on two clinical datasets including abdomen, head, and chest LDCT images with 25%, 25%, and 10% of the full dose, respectively. The experimental results demonstrated that the proposed DEformer achieved better denoising performance than the existing algorithms.

Low-dose CT denoising with a high-level feature refinement and dynamic convolution network.

BACKGROUND: Since the potential health risks of the radiation generated by computer tomography (CT), concerns have been expressed on reducing the radiation dose. However, low-dose CT (LDCT) images contain complex noise and artifacts, bringing uncertainty to medical diagnosis. PURPOSE: Existing deep learning (DL)-based denoising methods are difficult to fully exploit hierarchical features of different levels, limiting the effect of denoising. Moreover, the standard convolution kernel is parameter sharing and cannot be adjusted dynamically with input change. This paper proposes an LDCT denoising network using high-level feature refinement and multiscale dynamic convolution to mitigate these problems. METHODS: The dual network structure proposed in this paper consists of the feature refinement network (FRN) and the dynamic perception network (DPN). The FDN extracts features of different levels through residual dense connections. The high-level hierarchical information is transmitted to DPN to improve the low-level representations. In DPN, the two networks' features are fused by local channel attention (LCA) to assign weights in different regions and handle CT images' delicate tissues better. Then, the dynamic dilated convolution (DDC) with multibranch and multiscale receptive fields is proposed to enhance the expression and processing ability of the denoising network. The experiments were trained and tested on the dataset "NIH-AAPM-Mayo Clinic Low-Dose CT Grand Challenge," consisting of 10 anonymous patients with normal-dose abdominal CT and LDCT at 25% dose. In addition, external validation was performed on the dataset "Low Dose CT Image and Projection Data," which included 300 chest CT images at 10% dose and 300 head CT images at 25% dose. RESULTS: Proposed method compared with seven mainstream LDCT denoising algorithms. On the Mayo dataset, achieved peak signal-to-noise ratio (PSNR): 46.3526 dB (95% CI: 46.0121-46.6931 dB) and structural similarity (SSIM): 0.9844 (95% CI: 0.9834-0.9854). Compared with LDCT, the average increase was 3.4159 dB and 0.0239, respectively. The results are relatively optimal and statistically significant compared with other methods. In external verification, our algorithm can cope well with ultra-low-dose chest CT images at 10% dose and obtain PSNR: 28.6130 (95% CI: 28.1680-29.0580 dB) and SSIM: 0.7201 (95% CI: 0.7101-0.7301). Compared with LDCT, PSNR/SSIM is increased by 3.6536dB and 0.2132, respectively. In addition, the quality of LDCT can also be improved in head CT denoising. CONCLUSIONS: This paper proposes a DL-based LDCT denoising algorithm, which utilizes high-level features and multiscale dynamic convolution to optimize the network's denoising effect. This method can realize speedy denoising and performs well in noise suppression and detail preservation, which can be helpful for the diagnosis of LDCT.