The potential association between metabolic disorders and pulmonary tuberculosis: a Mendelian randomization study.

BACKGROUND: Metabolic disorders (MetDs) have been demonstrated to be closely linked to numerous diseases. However, the precise association between MetDs and pulmonary tuberculosis (PTB) remains poorly understood. METHOD: Summary statistics for exposure and outcomes from genome-wide association studies (GWASs) for exposures and outcomes were obtained from the BioBank Japan Project (BBJ) Gene-exposure dataset. The 14 clinical factors were categorized into three groups: metabolic laboratory markers, blood pressure, and the MetS diagnostic factors. The causal relationship between metabolic factors and PTB were analyzed using two-sample Mendelian Randomization (MR). Additionally, the direct effects on the risk of PTB were investigated through multivariable MR. The primary method employed was the inverse variance-weighted (IVW) model. The sensitivity of this MR analysis was evaluated using MR-Egger regression and the MR-PRESSO global test. RESULTS: According to the two-sample MR, HDL-C, HbA1c, TP, and DM were positively correlated with the incidence of active TB. According to the multivariable MR, HDL-C (IVW: OR 2.798, 95% CI 1.484-5.274, P = 0.001), LDL (IVW: OR 4.027, 95% CI 1.140-14.219, P = 0.03) and TG (IVW: OR 2.548, 95% CI 1.269-5.115, P = 0.009) were positively correlated with the occurrence of PTB. TC (OR 0.131, 95% CI 0.028-0.607, P = 0.009) was negatively correlated with the occurrence of PTB. We selected BMI, DM, HDL-C, SBP, and TG as the diagnostic factors for metabolic syndrome. DM (IVW, OR 1.219, 95% CI 1.040-1.429 P = 0.014) and HDL-C (IVW, OR 1.380, 95% CI 1.035-1.841, P = 0.028) were directly correlated with the occurrence of PTB. CONCLUSIONS: This MR study demonstrated that metabolic disorders, mainly hyperglycemia, and dyslipidemia, are associated with the incidence of active pulmonary tuberculosis.

Effect of PEAR1, PTGS1 gene polymorphisms on the recurrence of aspirin-treated patients with ischemic stroke in the Han population of China: A 4-year follow-up study.

Platelet endothelial aggregation receptor 1 (PEAR1) and prostaglandin endoperoxide synthase 1 (PTGS1) polymorphisms can affect laboratory aspirin resistance. However, the impact of genetic polymorphisms on the recurrence of ischemic stroke (IS) patients treated with aspirin is not fully understood. This study aimed to examine the relationship between gene polymorphisms of PEAR1 and PTGS1 and IS recurrence in patients treated with aspirin. Peripheral blood samples were collected from 174 patients with nonrecurrent IS and 34 with recurrent IS after aspirin treatment. Follow-up was performed on all patients. PEAR1 rs12041331 and PTGS1 rs10306114 polymorphisms were determined using the PCR fluorescence probe method. And the correlations of them with the clinical characteristics were examined by multivariable logistic regression analysis. The distribution frequencies of PEAR1 rs12041331 and PTGS1 rs10306114 genotypes were in Hardy-Weinberg equilibrium, and there was no significant difference in the distribution of PEAR1 rs12041331 polymorphism. Compared to the nonrecurrent group, the AA genotype of the PTGS1 polymorphism was more frequent in the recurrent group (59.77% vs 35.29%, P = .003), and the A allele also showed a higher frequency than the G allele in the recurrent group (P = .001). Multivariable logistic regression analysis showed that smoking (OR = 5.228, 95% CI: 1.938-14.102, P = .001), coronary heart disease (OR = 4.754, 95% CI: 1.498-15.089, P = .008), and the polymorphism at PTGS1(A>G) AA/AG + GG (OR = 2.955, 95% CI: 1.320-6.616, P = .008) were independently associated with IS recurrence in Chinese patients. Our findings suggested that PTGS rs10306114 polymorphisms should receive more attention in the use of aspirin in patients with IS.

Precirrhotic Primary Biliary Cholangitis with Portal Hypertension: Bile Duct Injury Correlate.

Background/Aims: : The histological characteristics and natural history of precirrhotic primary biliary cholangitis (PBC) with portal hypertension (PH) are unclear. Our aim was to clarify the prevalence, risk factors, and histological characteristics of precirrhotic PBC patients with PH. Methods: : This retrospective study compared the clinical features, histological characteristics, and response to ursodeoxycholic acid (UDCA) between the PH and non-PH groups of precirrhotic PBC patients. Results: : Out of 165 precirrhotic PBC patients, 40 (24.2%) also had PH. According to histological stage 1, 2 and 3 disease, 5.3% (1/19), 17.3% (17/98), and 45.8% (22/48) of patients also had PH, respectively. Precirrhotic PBC with PH was significantly positively correlated with bile duct loss, degree of cytokeratin 7 positivity, and degree of fibrosis in the portal area, but significantly negatively correlated with lymphoid follicular aggregation. Compared to the non-PH group, patients in the PH group showed a higher prevalence of obliterative portal venopathy, incomplete septal fibrosis, portal tract abnormalities and non-zonal sinusoidal dilatation (p<0.05). In addition, patients with PH were more likely to present with symptoms of jaundice, ascites, epigastric discomfort, a poorer response to UDCA, and more decompensation events (p<0.05). High alkaline phosphatase levels, low white blood cell counts, high Mayo scores, and high FIB-4 index values were risk factors for precirrhotic PBC with PH. Conclusions: : Approximately 24.2% of precirrhotic PBC patients have PH, which is histologically related to the injury of bile ducts. High alkaline phosphatase levels, low white blood cell counts, high Mayo scores, and high FIB-4 index values are associated with increased risk of precirrhotic PBC with PH.

Artificial Intelligence-Guided Gut-Microenvironment-Triggered Imaging Sensor Reveals Potential Indicators of Parkinson's Disease.

The gut-brain axis has recently emerged as a crucial link in the development and progression of Parkinson's disease (PD). Dysregulation of the gut microbiota has been implicated in the pathogenesis of this disease, sparking growing interest in the quest for non-invasive biomarkers derived from the gut for early PD diagnosis. Herein, an artificial intelligence-guided gut-microenvironment-triggered imaging sensor (Eu-MOF@Au-Aptmer) to achieve non-invasive, accurate screening for various stages of PD is presented. The sensor works by analyzing α-Syn in the gut using deep learning algorithms. By monitoring changes in α-Syn, the sensor can predict the onset of PD with high accuracy. This work has the potential to revolutionize the diagnosis and treatment of PD by allowing for early intervention and personalized treatment plans. Moreover, it exemplifies the promising prospects of integrating artificial intelligence (AI) and advanced sensors in the monitoring and prediction of a broad spectrum of diseases and health conditions.

The p53-mediated cell cycle regulation is a potential mechanism for emodin-suppressing osteosarcoma cells.

Background: As the most common primary bone cancer, the therapy of osteosarcoma requires further study. An anthraquinone derivative, emodin, has been found to have anticancer potential. We proposed that emodin suppresses osteosarcoma by cell cycle regulation mediated by p53. Methods: This study determined the effect of emodin on viability and apoptosis of 6 osteosarcoma cell lines (p53 null cells MG63, G292, and A-673; p53 mutated cells HOS and SK-PN-DW; p53 expressing cells U2OS and 2 osteoblast cell lines), then knockdown p53 in U2OS, and observed the impacts of emodin on p53, p21, cyclin proteins, and cell cycle. Results: High dose emodin (40-160 µM) induced cell death and apoptosis of all the cell lines; medium dose emodin (20 µM) preferentially inhibited osteosarcoma cells; low dose emodin (1-10 µM) preferentially inhibited p53 expressing osteosarcoma cells. Emodin dose-dependently inhibited p53 and p21 in U2OS. Emodin at 10 µM decreased the expression of Cdk2, E2F, and Cdk1; and increased RB but had no effects on cyclin E and cyclin B. The knockdown of p53 almost eliminated all the impacts of 10 µM emodin on cell cycle proteins. Conclusions: Emodin suppresses U2OS by p53-mediated cell cycle regulation.

A performance degradation model of nitrile butadiene rubber (NBR) O-rings for hydrogen permeation effects under high-pressure.

The integration of molecular chain changes on a microscopic scale to achieve macroscopic performance is crucial in degradation processes concerning O-ring seals. Nonetheless, a comprehensive and compelling mathematical model that can describe molecular chains' material properties and macroscopic material properties simultaneously for O-rings under high-pressure conditions is yet to be established. In this paper, we propose a degradation model based on viscoelasticity and molecular chain statistics for hydrogen permeation. The proposed model aims to establish the relationship between the material molecular chains and macroscopic material properties, with a primary focus on accurately recognizing the performance degradation process of rubber sealing rings. We verify the model's reliability through uniaxial tensile strength experiments and high-pressure hydrogen immersion experiments, respectively. Predictions of the model exhibit favorable conformity with the experimental data concerning the above phenomena. Furthermore, we derive the number of molecular chains and maximum strain of the degradation process. Based on the similarity of the degradation process's descent, it is plausible to speculate that NBR properties' degradation can be characterized by the average number of molecular chains.

Bio-Inspired Fault Diagnosis for Aircraft Fuel Pumps Using a Cloud-Edge System.

The fuel pump serves as the central component of the aircraft fuel system, necessitating real-time data acquisition for monitoring purposes. As the number of sensors increases, there is a substantial rise in data volume, leading to a simultaneous increase in computational processing for traditional Prognostics and Health Management methods while computational efficiency decreases. In response to this challenge, a novel health monitoring approach for aircraft fuel pumps is proposed based on the collaborative utilization of cloud-edge resources. This approach enables efficient cooperation among the sensor side, edge side, and cloud side to achieve timely fault warnings and accurate fault classification for fuel pumps. Within this method, anomaly judgment tasks are allocated to the edge side, and an anomaly judgment method that integrates the 3σ threshold and "3/5 strategy" is devised. Additionally, a fault diagnosis algorithm, founded on a convolutional auto-encoder, is formulated in the cloud to discern various fault types and severities. Comparative results demonstrate that, in contrast to long short-term memory networks, convolutional neural networks, extreme learning machines, and support vector machines, the proposed method yields improvements in accuracy of 4.35%, 6.40%, 17.65%, and 19.35%, respectively. Consequently, it is evident that the proposed method exhibits notable efficacy in the condition monitoring of aircraft fuel pumps.

Imrecoxib attenuates bleomycin-induced pulmonary fibrosis in mice.

Idiopathic pulmonary fibrosis (IPF) is an incurable chronic progressive disease with a low survival rate and ineffective therapeutic options. We examined the effects of imrecoxib, a nonsteroidal anti-inflammatory drug, on experimental pulmonary fibrosis. The mouse IPF model was established by intratracheal instillation of bleomycin. From Day 0 to Day 13, the mice were orally administered imrecoxib (100 mg/kg) and pirfenidone (200 mg/kg) daily, and from Day 7 to Day 13, the mice were orally administered pirfenidone and imrecoxib daily. The tissues were dissected on the 14th day. Mouse body weight was measured, and histopathological examination and hydroxyproline content analysis confirmed that the administration of imrecoxib exerted a similar effect to pirfenidone. Compared with bleomycin-induced mice, imrecoxib-treated mice showed significantly reduced inflammatory factor expression (IL-1 and TNF-α) and inflammatory cell numbers (macrophages, lymphocytes, and neutrophils) in BALF (bronchoalveolar lavage fluid). Our experiment tested the ability of imrecoxib to inhibit the signal pathway involved in gene expression induced by TGF-ß1 in the NIH-3T3 cell line in vitro. Western blotting showed that imrecoxib (20 µM and 40 µM) inhibited the expression of fibronectin, type I collagen and CTGF. In addition, imrecoxib reduced the levels of p-ERK1/2. The changes in the expression of related proteins in mouse lung tissue were similar to those in cells. In summary, our findings suggested that the administration of imrecoxib prevented and treated murine IPF by inhibiting inflammation and the TGF-ß1-ERK1/2 signaling pathway.

Smart nanoparticles for cancer therapy.

Smart nanoparticles, which can respond to biological cues or be guided by them, are emerging as a promising drug delivery platform for precise cancer treatment. The field of oncology, nanotechnology, and biomedicine has witnessed rapid progress, leading to innovative developments in smart nanoparticles for safer and more effective cancer therapy. In this review, we will highlight recent advancements in smart nanoparticles, including polymeric nanoparticles, dendrimers, micelles, liposomes, protein nanoparticles, cell membrane nanoparticles, mesoporous silica nanoparticles, gold nanoparticles, iron oxide nanoparticles, quantum dots, carbon nanotubes, black phosphorus, MOF nanoparticles, and others. We will focus on their classification, structures, synthesis, and intelligent features. These smart nanoparticles possess the ability to respond to various external and internal stimuli, such as enzymes, pH, temperature, optics, and magnetism, making them intelligent systems. Additionally, this review will explore the latest studies on tumor targeting by functionalizing the surfaces of smart nanoparticles with tumor-specific ligands like antibodies, peptides, transferrin, and folic acid. We will also summarize different types of drug delivery options, including small molecules, peptides, proteins, nucleic acids, and even living cells, for their potential use in cancer therapy. While the potential of smart nanoparticles is promising, we will also acknowledge the challenges and clinical prospects associated with their use. Finally, we will propose a blueprint that involves the use of artificial intelligence-powered nanoparticles in cancer treatment applications. By harnessing the potential of smart nanoparticles, this review aims to usher in a new era of precise and personalized cancer therapy, providing patients with individualized treatment options.

Hprt Serves as an Ideal Reference Gene for qRT-PCR Normalization in Rat DRG Neurons.

OBJECTIVE: To identify suitable reference genes for gene expression studies in rat dorsal root ganglia (DRG) neurons. METHODS: The raw cycle threshold (Ct) values of 12 selected reference genes were obtained via quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) in neurons at different developmental stages or under different treatments. Two strategies were employed to screen the most stable reference genes: the genes were ranked according to the coefficient of biological variation and further validated using geNorm and NormFinder programs. The stable and unstable reference genes were subsequently used as internal controls to assess their effects on target gene expression. RESULTS: All reference genes showed varying degrees of fluctuation in Ct values during the growth process of neurons or after different treatments. 18S ribosomal RNA (Rn18s) and ß-actin (Actb) exhibited the most significant changes, while ubiquitin C (Ubc), hypoxanthine phosphoribosyl transferase (Hprt), and mitochondrial ribosomal protein L10 (Mrpl10) showed relatively minor changes. The most stable and unstable genes obtained by different evaluation methods varied slightly. Overall, Actb was found to be the most unstable reference gene, while Hprt was the relatively most stable reference gene. The use of unstable reference genes Actb and ankyrin repeat domain 27 (Ankrd27) as internal controls led to high variability within the control group, ultimately affecting the determination of target gene expression. In contrast, the stable reference gene Hprt had small inter-assay variation and high stability. CONCLUSIONS: Our observations indicate that Hprt is a proper endogenous reference gene for qRT-PCR analysis in rat DRG neurons and thus provides a critical molecular basis for the genetic characterization in neurological disorders.

Activation of melanocortin-1 receptor signaling in melanoma cells impairs T cell infiltration to dampen antitumor immunity.

Inhibition of T cell infiltration dampens antitumor immunity and causes resistance to immune checkpoint blockade (ICB) therapy. By in vivo CRISPR screening in B16F10 melanoma in female mice, here we report that loss of melanocortin-1 receptor (MC1R) in melanoma cells activates antitumor T cell response and overcomes resistance to ICB. Depletion of MC1R from another melanocytic melanoma model HCmel1274 also enhances ICB efficacy. By activating the GNAS-PKA axis, MC1R inhibits interferon-gamma induced CXCL9/10/11 transcription, thus impairing T cell infiltration into the tumor microenvironment. In human melanomas, high MC1R expression correlates with reduced CXCL9/10/11 expression, impaired T cell infiltration, and poor patient prognosis. Whereas MC1R activation is restricted to melanoma, GNAS activation by hotspot mutations is observed across diverse cancer types and is associated with reduced CXCL9/10/11 expression. Our study implicates MC1R as a melanoma immunotherapy target and suggests GNAS-PKA signaling as a pan-cancer oncogenic pathway inhibiting antitumor T cell response.

Cracking the intestinal lymphatic system window utilizing oral delivery vehicles for precise therapy.

Oral administration is preferred over other drug delivery methods due to its safety, high patient compliance, ease of ingestion without discomfort, and tolerance of a wide range of medications. However, oral drug delivery is limited by the poor oral bioavailability of many drugs, caused by extreme conditions and absorption challenges in the gastrointestinal tract. This review thoroughly discusses the targeted drug vehicles to the intestinal lymphatic system (ILS). It explores the structure and physiological barriers of the ILS, highlighting its significance in dietary lipid and medication absorption and transport. The review presents various approaches to targeting the ILS using spatially precise vehicles, aiming to enhance bioavailability, achieve targeted delivery, and reduce first-pass metabolism with serve in clinic. Furthermore, the review outlines several methods for leveraging these vehicles to open the ILS window, paving the way for potential clinical applications in cancer treatment and oral vaccine delivery. By focusing on targeted drug vehicles to the ILS, this article emphasizes the critical role of these strategies in improving therapeutic efficacy and patient outcomes. Overall, this article emphasizes the critical role of targeted drug vehicles to the ILS and the potential impact of these strategies on improving therapeutic efficacy and patient outcomes.

Transjugular liver biopsy: enlarge the indications for liver biopsy with reliable diagnostic quality.

BACKGROUND: Complications and diagnostic efficiency for liver biopsy are main concerns for clinicians. This study aimed to assess the safety and efficacy of transjugular liver biopsy (TJLB) compared with percutaneous liver biopsy (PLB) when patients had equal level of liver function and number of passes, using propensity score matching (PSM). METHODS: The clinical and pathological data of patients who received TJLB or PLB between January 2012 and October 2022 were collected. Matching factors included age, gender, cirrhosis, portal hypertension, liver function, creatinine, number of passes, hemodialysis, history of anti-coagulation and anti-platelet, and comorbidities. Coagulation indexes were not considered as matching factors due to different indications of the two techniques. RESULTS: 2711 PLBs and 30 TJLBs were evaluated. By PSM, 75 patients (50 PLBs, 25 TJLBs) were matched. The complication rates for TJLB and PLB were 4.0% (1/25) and 10.0% (5/50) (P > 0.05). Two PLBs had hepatic hemorrhage, one of which required only close monitoring (Grade 1) and the other needed hemostasis and rehydration therapy (Grade 2). The other 3 cases presented with mild abdominal pain (Grade 1). And only one TJLB presented with mild pain. The median number of complete portal tracts were 6.0 and 10.0 for TJLBs and PLBs (P < 0.05). Moreover, the median length of sample for TJLBs and PLBs were 10.0 and 16.5 mm (P < 0.05). The diagnostic efficiency of hepatopathy of unknown etiology of TJLB versus PLB groups before and after matching were 96.4% vs. 94.1% and 95.7% vs. 93.2%, respectively (P > 0.05). CONCLUSION: TJLB is an effective invasive diagnostic procedure that expands indications for liver biopsy with reliable diagnostic quality.

AutoFibroNet: A deep learning and multi-photon microscopy-derived automated network for liver fibrosis quantification in MAFLD.

BACKGROUND: Liver fibrosis is the strongest histological risk factor for liver-related complications and mortality in metabolic dysfunction-associated fatty liver disease (MAFLD). Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) is a powerful tool for label-free two-dimensional and three-dimensional tissue visualisation that shows promise in liver fibrosis assessment. AIM: To investigate combining multi-photon microscopy (MPM) and deep learning techniques to develop and validate a new automated quantitative histological classification tool, named AutoFibroNet (Automated Liver Fibrosis Grading Network), for accurately staging liver fibrosis in MAFLD. METHODS: AutoFibroNet was developed in a training cohort that consisted of 203 Chinese adults with biopsy-confirmed MAFLD. Three deep learning models (VGG16, ResNet34, and MobileNet V3) were used to train pre-processed images and test data sets. Multi-layer perceptrons were used to fuse data (deep learning features, clinical features, and manual features) to build a joint model. This model was then validated in two further independent cohorts. RESULTS: AutoFibroNet showed good discrimination in the training set. For F0, F1, F2 and F3-4 fibrosis stages, the area under the receiver operating characteristic curves (AUROC) of AutoFibroNet were 1.00, 0.99, 0.98 and 0.98. The AUROCs of F0, F1, F2 and F3-4 fibrosis stages for AutoFibroNet in the two validation cohorts were 0.99, 0.83, 0.80 and 0.90 and 1.00, 0.83, 0.80 and 0.94, respectively, showing a good discriminatory ability in different cohorts. CONCLUSION: AutoFibroNet is an automated quantitative tool that accurately identifies histological stages of liver fibrosis in Chinese individuals with MAFLD.

Cracking Brain Diseases from Gut Microbes-Mediated Metabolites for Precise Treatment.

The gut-brain axis has been a subject of significant interest in recent years. Understanding the link between the gut and brain axis is crucial for the treatment of disorders. Here, the intricate components and unique relationship between gut microbiota-derived metabolites and the brain are explained in detail. Additionally, the association between gut microbiota-derived metabolites and the integrity of the blood-brain barrier and brain health is emphasized. Meanwhile, gut microbiota-derived metabolites with their recent applications, challenges and opportunities their pathways on different disease treatment are focus discussed. The prospective strategy of gut microbiota-derived metabolites potential applies to the brain disease treatments, such as Parkinson's disease and Alzheimer's disease, is proposed. This review provides a broad perspective on gut microbiota-derived metabolites characteristics facilitate understand the connection between gut and brain and pave the way for the development of a new medication delivery system for gut microbiota-derived metabolites.

miR-140 and miR-200 regulate the migratory heterogeneity of location-specific Schwann cell population.

Schwann cells are functional cells in nerve regeneration and are commonly used as seed cells in tissue engineering. Enhanced Schwann cell migration capacity improves recovery effects, and thus, the identification of Schwann cells with greater migration ability is of great importance. In the present study, we examined the biological activities of Schwann cells collected from rat sciatic nerves (SN) and dorsal root ganglia (DRG). Observations from transwell migration assay and wound healing assay demonstrate that DRG Schwann cells migrate at a faster speed as compared with SN Schwann cells. Sequencing and bioinformatics suggest that differentially expressed genes between SN and DRG Schwann cells are associated with cell motility and migration. miR-140 and miR-200, two microRNAs (miRNAs) that are highly expressed in SN Schwann cells negatively influence Schwann cell migration and thus may be key regulators of Schwann cell phenotype. Igsf10, Plxna2, and Lcp1 are screened as candidate downstream targets of miR-140 and miR-200 based on bioinformatic analysis and their expression correlation with miRNAs. Our comparative analysis displays the unique characteristics of Schwann cells in different anatomical localizations and demonstrates that DRG Schwann cells are suitable seed cells for tissue engineering and regenerative medicine.

Baricitinib Attenuates Bleomycin-Induced Pulmonary Fibrosis in Mice by Inhibiting TGF-ß1 Signaling Pathway.

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease with unknown etiology, high mortality and limited treatment options. It is characterized by myofibroblast proliferation and extensive deposition of extracellular matrix (ECM), which will lead to fibrous proliferation and the destruction of lung structure. Transforming growth factor-ß1 (TGF-ß1) is widely recognized as a central pathway of pulmonary fibrosis, and the suppression of TGF-ß1 or the TGF-ß1-regulated signaling pathway may thus offer potential antifibrotic therapies. JAK-STAT is a downstream signaling pathway regulated by TGF-ß1. JAK1/2 inhibitor baricitinib is a marketed drug for the treatment of rheumatoid arthritis, but its role in pulmonary fibrosis has not been reported. This study explored the potential effect and mechanism of baricitinib on pulmonary fibrosis in vivo and in vitro. The in vivo studies have shown that baricitinib can effectively attenuate bleomycin (BLM)-induced pulmonary fibrosis, and in vitro studies showed that baricitinib attenuates TGF-ß1-induced fibroblast activation and epithelial cell injury by inhibiting TGF-ß1/non-Smad and TGF-ß1/JAK/STAT signaling pathways, respectively. In conclusion, baricitinib, a JAK1/2 inhibitor, impedes myofibroblast activation and epithelial injury via targeting the TGF-ß1 signaling pathway and reduces BLM-induced pulmonary fibrosis in mice.

Antifibrotic mechanism of avitinib in bleomycin-induced pulmonary fibrosis in mice.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive interstitial lung disease characterized by alveolar epithelial cell injury and lung fibroblast overactivation. At present, only two drugs are approved by the FDA for the treatment of IPF, including the synthetic pyridinone drug, pirfenidone, and the tyrosine kinase inhibitor, nintedanib. Avitinib (AVB) is a novel oral and potent third-generation tyrosine kinase inhibitor for treating non-small cell lung cancer (NSCLC). However, the role of avitinib in pulmonary fibrosis has not yet been established. In the present study, we used in vivo and in vitro models to evaluate the role of avitinib in pulmonary fibrosis. In vivo experiments first verified that avitinib significantly alleviated bleomycin-induced pulmonary fibrosis in mice. Further in vitro molecular studies indicated that avitinib inhibited myofibroblast activation, migration and extracellular matrix (ECM) production in NIH-3T3 cells, mainly by inhibiting the TGF-ß1/Smad3 signalling pathways. The cellular experiments also indicated that avitinib improved alveolar epithelial cell injury in A549 cells. In conclusion, the present findings demonstrated that avitinib attenuates bleomycin-induced pulmonary fibrosis in mice by inhibiting alveolar epithelial cell injury and myofibroblast activation.

Duvelisib attenuates bleomycin-induced pulmonary fibrosis via inhibiting the PI3K/Akt/mTOR signalling pathway.

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease that seriously threatens the health of patients. The pathogenesis of IPF is still unclear, and there is a lack of effective therapeutic drugs. Myofibroblasts are the main effector cells of IPF, leading to excessive deposition of extracellular matrix (ECM) and promoting the progression of fibrosis. Inhibiting the excessive activation and relieving autophagy blockage of myofibroblasts is the key to treat IPF. PI3K/Akt/mTOR pathway plays a key regulatory role in promoting fibroblast activation and autophagy inhibition in lung fibrosis. Duvelisib is a PI3K inhibitor that can simultaneously inhibit the activities of PI3K-δ and PI3K-γ, and is mainly used for the treatment of relapsed/refractory chronic lymphocytic leukaemia (CLL) and small lymphocytic lymphoma tumour (SLL). In this study, we aimed to examine the effects of Duvelisib on pulmonary fibrosis. We used a mouse model of bleomycin-induced pulmonary fibrosis to evaluate the effects of Duvelisib on pulmonary fibrosis in vivo and further explored the potential pharmacological mechanisms of Duvelisib in lung fibroblasts in vitro. The in vivo experiments showed that Duvelisib significantly alleviated bleomycin-induced collagen deposition and improved pulmonary function. In vitro and in vivo pharmacological experiments showed that Duvelisib dose-dependently suppressed lung fibroblast activation and improved autophagy inhibition by inhibiting the phosphorylation of PI3K, Akt and mTOR. Our results indicate that Duvelisib can alleviate the severity of pulmonary fibrosis and provide potential drugs for the treatment of pulmonary fibrosis.

Twist-Net: A multi-modality transfer learning network with the hybrid bilateral encoder for hypopharyngeal cancer segmentation.

Hypopharyngeal cancer (HPC) is a rare disease. Therefore, it is a challenge to automatically segment HPC tumors and metastatic lymph nodes (HPC risk areas) from medical images with the small-scale dataset. Combining low-level details and high-level semantics from feature maps in different scales can improve the accuracy of segmentation. Herein, we propose a Multi-Modality Transfer Learning Network with Hybrid Bilateral Encoder (Twist-Net) for Hypopharyngeal Cancer Segmentation. Specifically, we propose a Bilateral Transition (BT) block and a Bilateral Gather (BG) block to twist (fuse) high-level semantic feature maps and low-level detailed feature maps. We design a block with multi-receptive field extraction capabilities, M Block, to capture multi-scale information. To avoid overfitting caused by the small scale of the dataset, we propose a transfer learning method that can transfer priors experience from large computer vision datasets to multi-modality medical imaging datasets. Compared with other methods, our method outperforms other methods on HPC dataset, achieving the highest Dice of 82.98%. Our method is also superior to other methods on two public medical segmentation datasets, i.e., the CHASE_DB1 dataset and BraTS2018 dataset. On these two datasets, the Dice of our method is 79.83% and 84.87%, respectively. The code is available at: https://github.com/zhongqiu1245/TwistNet.