Exploring therapeutic targets for molecular therapy of idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis is a chronic and progressive interstitial lung disease with a poor prognosis. Idiopathic pulmonary fibrosis is characterized by repeated alveolar epithelial damage leading to abnormal repair. The intercellular microenvironment is disturbed, leading to continuous activation of fibroblasts and myofibroblasts, deposition of extracellular matrix, and ultimately fibrosis. Moreover, pulmonary fibrosis was also found as a COVID-19 complication. Currently, two drugs, pirfenidone and nintedanib, are approved for clinical therapy worldwide. However, they can merely slow the disease's progression rather than rescue it. These two drugs have other limitations, such as lack of efficacy, adverse effects, and poor pharmacokinetics. Consequently, a growing number of molecular therapies have been actively developed. Treatment options for IPF are becoming increasingly available. This article reviews the research platform, including cell and animal models involved in molecular therapy studies of idiopathic pulmonary fibrosis as well as the promising therapeutic targets and their development progress during clinical trials. The former includes patient case/control studies, cell models, and animal models. The latter includes transforming growth factor-beta, vascular endothelial growth factor, platelet-derived growth factor, fibroblast growth factor, lysophosphatidic acid, interleukin-13, Rho-associated coiled-coil forming protein kinase family, and Janus kinases/signal transducers and activators of transcription pathway. We mainly focused on the therapeutic targets that have not only entered clinical trials but were publicly published with their clinical outcomes. Moreover, this work provides an outlook on some promising targets for further validation of their possibilities to cure the disease.

Computation-aided Design of Rod-Shaped Janus Base Nanopieces for Improved Tissue Penetration and Therapeutics Delivery.

Despite the development of various drug delivery technologies, there remains a significant need for vehicles that can improve targeting and biodistribution in "hard-to-penetrate" tissues. Some solid tumors, for example, are particularly challenging to penetrate due to their dense extracellular matrix (ECM). In this study, we have formulated a new family of rod-shaped delivery vehicles named Janus base nanopieces (Rod JBNps), which are more slender than conventional spherical nanoparticles, such as lipid nanoparticles (LNPs). These JBNp nanorods are formed by bundles of DNA-inspired Janus base nanotubes (JBNts) with intercalated delivery cargoes. To develop this novel family of delivery vehicles, we employed a computation-aided design (CAD) methodology that includes molecular dynamics and response surface methodology. This approach precisely and efficiently guides experimental designs. Using an ovarian cancer model, we demonstrated that JBNps markedly improve penetration into the dense ECM of solid tumors, leading to better treatment outcomes compared to FDA-approved spherical LNP delivery. This study not only successfully developed a rod-shaped delivery vehicle for improved tissue penetration but also established a CAD methodology to effectively guide material design.

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

Clinical Observations of Percutaneous Tibial Nerve Stimulation Combined with Sacral Nerve Root Magnetic Stimulation for the Treatment of Male Chronic Pelvic Pain and Chronic Prostatitis

Purpose: To investigate the clinical efficacy of percutaneous tibial nerve stimulation combines sacral nerve root magnetic stimulation in the treatment of chronic pelvic pain syndrome and chronic prostatitis. Methods: 60 male patients diagnosed with chronic pelvic pain syndrome or chronic prostatitis were analyzed in this study. Patients in the experimental group were treated with percutaneous tibial nerve stimulation (7 Hz) combined with sacral nerve root magnetic stimulation (5 Hz) whilst patients in the control group receiving treatment with only percutaneous tibial nerve stimulation. The National Institutes of Health-Chronic Prostatitis Symptom Index was used to evaluate prostatitis in the 2 groups before and at 4 weeks after treatment. Results: All patients showed improvements in scores before and after treatment in the two groups (p < 0.05). Further comparison between the two groups showed that patients in the experimental experienced more significant improvements in each of the indicators compare that to the control group patients (p < 0.05). Conclusions: Both percutaneous tibial nerve stimulation and percutaneous tibial nerve stimulation combined with magnetic stimulation of the sacral nerve roots have benefits for patients, but the benefits are more excellent when used together than when used alone. (AU)

Real-world effectiveness and protection of SARS-CoV-2 vaccine among patients hospitalized for COVID-19 in Xi'an, China, December 8, 2021, to January 20, 2022: A retrospective study.

Introduction: In December 2021, a large-scale epidemic broke out in Xi'an, China, due to SARS-CoV-2 infection. This study reports the effect of vaccination on COVID-19 and evaluates the impact of different vaccine doses on routine laboratory markers. Methods: The laboratory data upon admission, of 231 cases with COVID-19 hospitalized from December 8, 2021 to January 20, 2022 in Xi'an, including blood routine, lymphocyte subtypes, coagulative function tests, virus specific antibodies and blood biochemical tests were collected and analyzed. Results: Of the 231 patients, 21 were not vaccinated, 158 were vaccinated with two doses and 52 with three doses. Unvaccinated patients had a higher proportion of moderate and severe symptoms than vaccinated patients, while two-dose vaccinated patients had a higher proportion than three-dose vaccinated patients. SARS-CoV-2 specific IgG levels were significantly elevated in vaccinated patients compared with unvaccinated patients. Particularly, unvaccinated patients had lower counts and percentages of lymphocytes, eosinophils and CD8+ T-lymphocytes, and elevated coagulation-related markers. In addition, vaccination had no effect on liver and kidney function. Conclusions: Vaccination against SARS-CoV-2, inducing high IgG level and increased CD8+ T cells and eosinophils, and regulating coagulation function, can significantly attenuate symptoms of COVID-19, suggesting that the vaccine remains protective against SARS-CoV-2.

LIM Mineralization Protein-1 Enhances the Committed Differentiation of Dental Pulp Stem Cells through the ERK1/2 and p38 MAPK Pathways and BMP Signaling.

Tissue regeneration is the preferred treatment for dentin and bone tissue defects. Dental pulp stem cells (DPSCs) have been extensively studied for their use in tissue regeneration, including the regeneration of dentin and bone tissue. LIM mineralization protein-1 (LMP-1) is an intracellular non-secretory protein that plays a positive regulatory role in the mineralization process. In this study, an LMP-1-induced DPSCs model was used to explore the effect of LMP-1 on the proliferation and odonto/osteogenic differentiation of DPSCs, as well as the underlying mechanisms. As indicated by the cell counting kit-8 assay, the results showed that LMP-1 did not affect the proliferation of DPSCs. Overexpression of LMP-1 significantly promoted the committed differentiation of DPSCs and vice versa, as shown by alkaline phosphatase activity assay, alizarin red staining, western blot assay, quantitative real-time polymerase chain reaction assay, and in vivo mineralized tissue formation assay. Furthermore, inhibiting the activation of the extracellular signal-regulated kinase 1/2 (ERK1/2), p38 mitogen-activated protein kinase (MAPK), and c-Jun N-terminal kinase (JNK) pathways using specific pathway inhibitors showed that the ERK1/2 and p38 MAPK pathways attenuated the differentiation of DPSCs. Besides, the expression of BMP signaling pathway components were also determined, which suggested that LMP-1 could activate BMP-2/Smad1/5 signaling pathway. Our results not only indicated the underlying mechanism of LMP-1 treated DPSCs but also provided valuable insight into therapeutic strategies in regenerative medicine.

Locally weighted PCA regression to recover missing markers in human motion data.

"Missing markers problem", that is, missing markers during a motion capture session, has been raised for many years in Motion Capture field. We propose the locally weighted principal component analysis (PCA) regression method to deal with this challenge. The main merit is to introduce the sparsity of observation datasets through the multivariate tapering approach into traditional least square methods and develop it into a new kind of least square methods with the sparsity constraints. To the best of our knowledge, it is the first least square method with the sparsity constraints. Our experiments show that the proposed regression method can reach high estimation accuracy and has a good numerical stability.

Face image-sketch synthesis via generative adversarial fusion.

Face image-sketch synthesis is widely applied in law enforcement and digital entertainment fields. Despite the extensive progression in face image-sketch synthesis, there are few methods focusing on generating a color face image from a sketch. The existing methods pay less attention to learning the illumination or highlight distribution on the face region. However, the illumination is the key factor that makes the generated color face image looks vivid and realistic. Moreover, existing methods tend to employ some image preprocessing technologies and facial region patching approaches to generate high-quality face images, which results in the high complexity and memory consumption in practice. In this paper, we propose a novel end-to-end generative adversarial fusion model, called GAF, which fuses two U-Net generators and a discriminator by jointly learning the content and adversarial loss functions. In particular, we propose a parametric tanh activation function to learn and control illumination highlight distribution over faces, which is integrated between the two U-Net generators by an illumination distribution layer. Additionally, we fuse the attention mechanism into the second U-Net generator of GAF to keep the identity consistency and refine the generated facial details. The qualitative and quantitative experiments on the public benchmark datasets show that the proposed GAF has better performance than existing image-sketch synthesis methods in synthesized face image quality (FSIM) and face recognition accuracy (NLDA). Meanwhile, the good generalization ability of GAF has also been verified. To further demonstrate the reliability and authenticity of face images generated using GAF, we use the generated face image to attack the well-known face recognition system. The result shows that the face images generated by GAF can maintain identity consistency and well maintain everyone's unique facial characteristics, which can be further used in the benchmark of facial spoofing. Moreover, the experiments are implemented to verify the effectiveness and rationality of the proposed parametric tanh activation function and attention mechanism in GAF.

Random Shapley Forests: Cooperative Game-Based Random Forests With Consistency.

The original random forests (RFs) algorithm has been widely used and has achieved excellent performance for the classification and regression tasks. However, the research on the theory of RFs lags far behind its applications. In this article, to narrow the gap between the applications and the theory of RFs, we propose a new RFs algorithm, called random Shapley forests (RSFs), based on the Shapley value. The Shapley value is one of the well-known solutions in the cooperative game, which can fairly assess the power of each player in a game. In the construction of RSFs, RSFs use the Shapley value to evaluate the importance of each feature at each tree node by computing the dependency among the possible feature coalitions. In particular, inspired by the existing consistency theory, we have proved the consistency of the proposed RFs algorithm. Moreover, to verify the effectiveness of the proposed algorithm, experiments on eight UCI benchmark datasets and four real-world datasets have been conducted. The results show that RSFs perform better than or at least comparable with the existing consistent RFs, the original RFs, and a classic classifier, support vector machines.

Clinical Observations of Percutaneous Tibial Nerve Stimulation Combined with Sacral Nerve Root Magnetic Stimulation for the Treatment of Male Chronic Pelvic Pain and Chronic Prostatitis.

PURPOSE: To investigate the clinical efficacy of percutaneous tibial nerve stimulation combines sacral nerve root magnetic stimulation in the treatment of chronic pelvic pain syndrome and chronic prostatitis. METHODS: 60 male patients diagnosed with chronic pelvic pain syndrome or chronic prostatitis were analyzed in this study. Patients in the experimental group were treated with percutaneous tibial nerve stimulation (7 Hz) combined with sacral nerve root magnetic stimulation (5 Hz) whilst patients in the control group receiving treatment with only percutaneous tibial nerve stimulation. The National Institutes of Health-Chronic Prostatitis Symptom Index was used to evaluate prostatitis in the 2 groups before and at 4 weeks after treatment. RESULTS: All patients showed improvements in scores before and after treatment in the two groups (p < 0.05). Further comparison between the two groups showed that patients in the experimental experienced more significant improvements in each of the indicators compare that to the control group patients (p < 0.05). CONCLUSIONS: Both percutaneous tibial nerve stimulation and percutaneous tibial nerve stimulation combined with magnetic stimulation of the sacral nerve roots have benefits for patients, but the benefits are more excellent when used together than when used alone.

High-throughput sequencing provides insights into oral microbiota dysbiosis in association with inflammatory bowel disease.

Although the prevalence of inflammatory bowel disease (IBD) has been increasing worldwide, the etiology remains elusive. Investigating oral microbiota dysbiosis is essential to understanding IBD pathogenesis. Our study evaluated variations in salivary microbiota and identified potential associations with IBD. The saliva microbiota of 22 IBD patients and 8 healthy controls (HCs) was determined using 16S ribosomal RNA (rRNA) gene sequencing and analyzed using QIIME2. A distinct saliva microbiota dysbiosis in IBD, characterized by alterations in microbiota biodiversity and composition, was identified. Saccharibacteria (TM7), Absconditabacteria (SR1), Leptotrichia, Prevotella, Bulleidia, and Atopobium, some of which are oral biofilm-forming bacteria, were significantly increased. Moreover, levels of inflammatory cytokines associated with IBD were elevated and positively correlated with TM7 and SR1. Functional variations include down-regulation of genetic information processing, while up-regulation of carbohydrate metabolism and protein processing in the endoplasmic reticulum in IBD. Our data implicate salivary microbiota dysbiosis involving in IBD pathogenesis.

Self-assembled biomimetic Nano-Matrix for stem cell anchorage.

Mesenchymal stem cells (MSCs) have been widely applied in biomedicine due to their ability to differentiate into many different cell types and their ability to synthesize a broad spectrum of growth factors and cytokines that directly and indirectly influence other cells in their vicinity. To guide MSC infiltration to a bone fracture site, we developed a novel self-assembled Nano-Matrix which can be used as an injectable scaffold to repair bone fractures. The Nano-Matrix is formed by Janus base nanotubes (JBNTs) and fibronectin (FN). JBNTs are nucleobase-derived nanotubes mimicking collagen fibers, and FN is one of the cell adhesive glycoproteins which is responsible for cell-extracellular matrix interactions and guides stem cell migration and differentiation to desired cells types. Here, we demonstrated the successful fabrication and characterization of the JBNT/FN Nano-Matrix as well as its excellent bioactivity that encouraged human MSC migration and adhesion. This work lays a solid foundation for using the Nano-Matrix as an injectable approach to improve MSC retention and function during bone fracture healing.

Anti-miRNA Oligonucleotide Therapy for Chondrosarcoma.

Chondrosarcoma is a highly aggressive primary malignant bone tumor mostly occurring in adults. There are no effective systemic treatments, and patients with this disease have poor survival. miR-181a is an oncomiR that is overexpressed in high-grade chondrosarcoma and promotes tumor progression. Regulator of G-protein signaling 16 (RGS16) is a target of miR-181a. Inhibition of RGS16 expression by miR-181a enhances CXC chemokine receptor 4 signaling, which in turn increases MMP1 and VEGF expression, angiogenesis, and metastasis. Here, we report the results of systemic treatment with anti-miRNA oligonucleotides (AMO) directed against miR-181a utilizing a nanopiece delivery platform (NPs). NPs were combined with a molecular beacon or anti-miR-181a oligonucleotides and are shown to transfect chondrosarcoma cells in vitro and in vivo Intratumoral injection and systemic delivery had similar effects on miR-181a expression in nude mice bearing chondrosarcoma xenografts. Systemic delivery of NPs carrying anti-miR-181a also restored RGS16 expression, decreased expression of VEGF and MMP1, MMP activity, and tumor volume by 32% at day 38, and prolonged survival from 23% to 45%. In conclusion, these data support that systemic delivery of AMO shows promise for chondrosarcoma treatment.

Perceptual Adversarial Networks With a Feature Pyramid for Image Translation.

This paper investigates the image-to-image translations problems, where the input image is translated into its synthetic form with the original structure and semantics preserved. Widely used methods compute the pixel-wise MSE loss, which are often inadequate for high-frequency content and tend to produce overly smooth results. Concurrent works that leverage recent advances in conditional generative adversarial networks (cGANs) are proposed to enable a universal approach to diverse image translation tasks that traditionally require specific loss functions. Despite the impressive results, most of these approaches are notoriously unstable to train and tend to induce blurs. In this paper, we decompose the image into a set of images by a feature pyramid and elaborate separate loss components for images of specific bandpass. The overall perceptual adversarial loss is able to capture not only the semantic features but also the appearance.

Pleiotropic microRNA-21 in pulmonary remodeling: novel insights for molecular mechanism and present advancements.

MicroRNA-21 (miR-21), probably one of the most studied miRNAs to date, is found pleiotropic in various biological events. Its emerging role in pulmonary remodeling has attracted extensive attention. This review summarizes the genomic information of its primary transcript and various transcriptional regulations on its promoter. In addition, the role of miR-21 in pulmonary remodeling related signaling such as transforming growth factor ß (TGF-ß), bone morphogenetic protein (BMP), epidermal growth factor receptor (EGFR) and Notch signaling is discussed. Various validated miR-21 target genes participate in controlling of the overactive cell accumulation, smooth muscle contraction, inflammatory stress (trigger for lung epithelium damage), extracellular matrix deposition and hypoxia-induced disorders. Moreover, we focus on its particular implication in events including inflammatory stress-driven epithelium damage, epithelial-to-mesenchymal transition (EMT), transdifferentiation of fibroblasts into myofibroblasts, hypoxia stimuli and ROS response, as well as some other pulmonary remodeling related events such as overactive fibroblast (myofibroblast) accumulation, extracellular matrix deposition, and angiogenesis. Here, we summarize the strong potential of miR-21 in pulmonary remodeling and provide novel clues for further research in this area.

Injectable chitosan/ß-glycerophosphate hydrogels with sustained release of BMP-7 and ornidazole in periodontal wound healing of class III furcation defects.

The aim of this study was to determine the effect of bone morphogenetic protein-7 (BMP-7) and ornidazole (ORN) loaded Chitosan/ß-glycerophosphate (CS/ß-GP) thermosensitive hydrogels on periodontal regeneration. CS/ß-GP hydrogels with and without BMP-7 and ORN were compared with respect to physicochemical properties, release kinetics, and antimicrobial activity in vitro, and periodontal regeneration properties in class III furcation defects in beagles via radiography, histology including immunohistochemical staining of osteoblasts and osteoclasts, and histometric analysis. CS/ß-GP hydrogels with and without BMP-7 and ORN had comparable physicochemical properties and gelation kinetics. Release kinetics showed that the hydrogels were capable of stable and sustained release of BMP-7 and ORN. The hydrogels loaded with ORN exhibited obvious antimicrobial activity against P. gingivalis. Histometric analysis quantitatively showed significantly more new bone and cementum, and less connective tissue in defects implanted with BMP-7 loaded hydrogels compared with hydrogels without BMP-7. The number of osteoclasts reduced significantly in the CS/BMP-7/ORN and CS/BMP-7 groups, while the number of osteoblasts increased significantly in these groups. Our findings showed that BMP-7 and ORN conferred additional advantages to the CS/ß-GP hydrogel in periodontal regeneration and suggest potential consideration of this approach for periodontal therapy.

High Relief from Brush Painting.

Relief is an art form part way between 3D sculpture and 2D painting. We present a novel approach for generating a texture-mapped high-relief model from a single brush painting. Our aim is to extract the brushstrokes from a painting and generate the individual corresponding relief proxies rather than recovering the exact depth map from the painting, which is a tricky computer vision problem, requiring assumptions that are rarely satisfied. The relief proxies of brushstrokes are then combined together to form a 2.5D high-relief model. To extract brushstrokes from 2D paintings, we apply layer decomposition and stroke segmentation by imposing boundary constraints. The segmented brushstrokes preserve the style of the input painting. By inflation and a displacement map of each brushstroke, the features of brushstrokes are preserved by the resultant high-relief model of the painting. We demonstrate that our approach is able to produce convincing high-reliefs from a variety of paintings(with humans, animals, flowers, etc.). As a secondary application, we show how our brushstroke extraction algorithm could be used for image editing. As a result, our brushstroke extraction algorithm is specifically geared towards paintings with each brushstroke drawn very purposefully, such as Chinese paintings, Rosemailing paintings, etc.