CD3, CD8, IFN-γ, tumor and stroma inflammatory cells as prognostic indicators for surgically resected SCLC: evidences from a 10-year retrospective study and immunohistochemical analysis.

Current clinical guidelines limit surgical intervention to patients with cT1-2N0M0 small cell lung cancer (SCLC). Our objective was to reassess the role of surgery in SCLC management, and explore novel prognostic indicators for surgically resected SCLC. We reviewed all patients diagnosed with SCLC from January 2011 to April 2021 in our institution. Survival analysis was conducted using the Kaplan-Meier method, and independent prognostic factors were assessed through the Cox proportional hazard model. In addition, immunohistochemistry (IHC) staining was performed to evaluate the predictive value of selected indicators in the prognosis of surgically resected SCLC patients. In the study, 177 SCLC patients undergoing surgical resection were ultimately included. Both univariate and multivariate Cox analysis revealed that incomplete postoperative adjuvant therapy emerged as an independent risk factor for adverse prognosis (p < 0.001, HR 2.96). Survival analysis revealed significantly superior survival among pN0-1 patients compared to pN2 patients (p < 0.0001). No significant difference in postoperative survival was observed between pN1 and pN0 patients (p = 0.062). Patients with postoperative stable disease (SD) exhibited lower levels of tumor inflammatory cells (TIC) (p = 0.0047) and IFN-γ expression in both area and intensity (p < 0.0001 and 0.0091, respectively) compared to those with postoperative progressive disease (PD). Conversely, patients with postoperative SD showed elevated levels of stromal inflammatory cells (SIC) (p = 0.0453) and increased counts of CD3+ and CD8+ cells (p = 0.0262 and 0.0330, respectively). Survival analysis indicated that high levels of SIC, along with low levels of IFN-γ+ cell area within tumor tissue, may correlate positively with improved prognosis in surgically resected SCLC (p = 0.017 and 0.012, respectively). In conclusion, the present study revealed that the patients with pT1-2N1M0 staging were a potential subgroup of SCLC patients who may benefit from surgery. Complete postoperative adjuvant therapy remains an independent factor promoting a better prognosis for SCLC patients undergoing surgical resection. Moreover, CD3, CD8, IFN-γ, TIC, and SIC may serve as potential indicators for predicting the prognosis of surgically resected SCLC.

Safety and efficacy of apixaban versus vitamin K antagonists in patients undergoing dialysis: a systematic review and meta-analysis.

BACKGROUND: This review aims to evaluate the safety and efficacy of apixaban vs. vitamin K antagonists (VKAs) in patients on dialysis. METHODS: All types of studies published on PubMed, Embase, CENTRAL, and Web of Science up to 10 September 2023 and comparing outcomes of apixaban vs. VKA in dialysis patients were eligible. RESULTS: Two randomized controlled trials (RCTs) and six retrospective studies were included. Apixaban treatment was associated with significantly lower risk of major bleeding (RR: 0.61; 95% CI: 0.48, 0.77; I2 = 50%) and clinically relevant non-major bleeding (RR: 0.82, 95% CI: 0.68, 0.98, I2 = 9%) compared to VKA. Meta-analysis also showed that the risk of gastrointestinal bleeding (RR: 0.74, 95% CI: 0.64, 0.85, I2 = 16%) and intracranial bleeding (RR: 0.64, 95% CI: 0.49, 0.84, I2 = 0%) was significantly reduced with apixaban. Meta-analysis showed no difference in the risk of ischemic stroke (RR: 0.40, 95% CI: 0.06, 2.69, I2 = 0%), mortality (RR: 1.26, 95% CI: 0.74, 2.16, I2 = 94%) and recurrent venous thromboembolism (RR: 1.02, 95% CI: 0.87, 1.21, I2 = 0%) between the two groups. Subgroup analysis of RCTs showed no difference in bleeding outcomes. CONCLUSIONS: Low-quality evidence from a mix of RCTs and retrospective studies shows that apixaban may have better safety and equivalent efficacy as compared to VKA in dialysis patients. Apixaban treatment correlated with significantly reduced risk of major bleeding and clinically relevant nonmajor bleeding in observational studies but not in RCTs. The predominance of retrospective data warrants caution in the interpretation of results.

CircPIAS1 promotes hepatocellular carcinoma progression by inhibiting ferroptosis via the miR-455-3p/NUPR1/FTH1 axis.

BACKGROUND: The role of circRNAs in hepatocellular carcinoma (HCC) progression remains unclear. CircPIAS1 (circBase ID: hsa_circ_0007088) was identified as overexpressed in HCC cases through bioinformatics analysis. This study aimed to investigate the oncogenic properties and mechanisms of circPIAS1 in HCC development. METHODS: Functional analyses were conducted to assess circPIAS1's impact on HCC cell proliferation, migration, and ferroptosis. Xenograft mouse models were employed to evaluate circPIAS1's effects on tumor growth and pulmonary metastasis in vivo. Bioinformatics analysis, RNA immunoprecipitation, and luciferase reporter assays were utilized to elucidate the molecular pathways influenced by circPIAS1. Additional techniques, including RNA pulldown, fluorescence in situ hybridization (FISH), chromatin immunoprecipitation (ChIP), qPCR, and western blotting, were used to further explore the underlying mechanisms. RESULTS: CircPIAS1 expression was elevated in HCC tissues and cells. Silencing circPIAS1 suppressed HCC cell proliferation and migration both in vitro and in vivo. Mechanically, circPIAS1 overexpression inhibited ferroptosis by competitively binding to miR-455-3p, leading to upregulation of Nuclear Protein 1 (NUPR1). Furthermore, NUPR1 promoted FTH1 transcription, enhancing iron storage in HCC cells and conferring resistance to ferroptosis. Treatment with ZZW-115, an NUPR1 inhibitor, reversed the tumor-promoting effects of circPIAS1 and sensitized HCC cells to lenvatinib. CONCLUSION: This study highlights the critical role of circPIAS1 in HCC progression through modulation of ferroptosis. Targeting the circPIAS1/miR-455-3p/NUPR1/FTH1 regulatory axis may represent a promising therapeutic strategy for HCC.

Prophylactic Effects of n-Acethylcysteine on Inflammation-induced Depression-like Behaviors in Mice.

Depression, affecting individuals worldwide, is a prevalent mental disease, with an increasing incidence. Numerous studies have been conducted on depression, yet its pathogenesis remains elusive. Recent advancements in research indicate that disturbances in synaptic transmission, synaptic plasticity, and reduced neurotrophic factor expression significantly contribute to depression's pathogenesis. In our study, we utilized adult male C57BL/6J mice. Lipopolysaccharide (LPS) can induce both chronic and acute depression-like symptoms in mice, a widely used model for studying depression associated with inflammation. N-acetylcysteine (NAC) exhibits anti-inflammatory and ameliorative effects on depressive symptoms. This study sought to determine whether NAC use could mitigate inflammatory depressive behavior through the enhancement of synaptic transmission, synaptic plasticity, and increasing levels of brain-derived neurotrophic factor (BDNF). In this study, we discovered that in mice modeled with depression-like symptoms, the expression levels of dendrites, BDNF, and miniature excitatory postsynaptic potential (mEPSC) in glutamatergic neurons, as well as the α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid glutamate receptors (AMPARs) GluA1 and GluA2 subunits, were significantly decreased. These findings suggest an impairment in the synaptic transmission of glutamatergic neurons. Following treatment with NAC, the previously mentioned levels improved, indicating an enhancement in both synaptic transmission and synaptic plasticity. Our results suggest that NAC exerts a protective effect on mouse models of inflammatory depression, potentially through the enhancement of synaptic transmission and plasticity, as well as the restoration of neurotrophic factor expression. These findings offer vital animal experimental evidence supporting NAC's role in mitigating inflammatory depressive behaviors.

Kaempferol attenuates inflammation in lipopolysaccharide-induced gallbladder epithelial cells by inhibiting the MAPK/NF-κB signaling pathway.

Kaempferol (KPR), a flavonoid compound found in various plants and foods, has garnered attention for its anti-inflammatory, antioxidant, and anticancer properties. In preliminary studies, KPR can modulate several signaling pathways involved in inflammation, making it a candidate for treating cholecystitis. This study aimed to explore the effects and mechanisms of KPR on lipopolysaccharide (LPS)-induced human gallbladder epithelial cells (HGBECs). To assess the impact of KPR on HGBECs, the HGBECs were divided into control, KPR, LPS, LPS + KPR, and LPS + UDCA groups. Cell viability and cytotoxicity were evaluated by MTT assay and lactate dehydrogenase (LDH) assay, respectively, and concentrations of KPR (10-200 µM) were tested. LPS-induced inflammatory responses in HGBECs were to create an in vitro model of cholecystitis. The key inflammatory markers (IL-1ß, IL-6, and TNF-α) levels were quantified using ELISA, The modulation of the MAPK/NF-κB signaling pathway was measured by western blot using specific antibodies against pathway components (p-IκBα, IκBα, p-p65, p65, p-JNK, JNK, p-ERK, ERK, p-p38, and p38). The cell viability and LDH levels in HGBECs were not significantly affected by 50 µM KPR, thus it was selected as the optimal KPR intervention concentration. KPR increased the viability of LPS-induced HGBECs. Additionally, KPR inhibited the inflammatory factors level (IL-1ß, IL-6, and TNF-α) and protein expression (iNOS and COX-2) in LPS-induced HGBECs. Furthermore, KPR reversed LPS-induced elevation of p-IκBα/IκBα, p-p65/p65, p-JNK/JNK, p-ERK/ERK, and p-p38/p38 ratios. KPR attenuates the LPS-induced inflammatory response in HGBECs, possibly by inhibiting MAPK/NF-κB signaling.

Comparison of different machine learning classification models for predicting deep vein thrombosis in lower extremity fractures.

Deep vein thrombosis (DVT) is a common complication in patients with lower extremity fractures. Once it occurs, it will seriously affect the quality of life and postoperative recovery of patients. Therefore, early prediction and prevention of DVT can effectively improve the prognosis of patients. This study constructed different machine learning models to explore their effectiveness in predicting DVT. Five prediction models were applied to the study, including Extreme Gradient Boosting (XGBoost) model, Logistic Regression (LR) model, RandomForest (RF) model, Multilayer Perceptron (MLP) model, and Support Vector Machine (SVM) model. Afterwards, the performance of the obtained prediction models was evaluated by area under the curve (AUC), accuracy, sensitivity, specificity, F1 score, and Kappa. The prediction performances of the models based on machine learning are as follows: XGBoost model (AUC = 0.979, accuracy = 0.931), LR model (AUC = 0.821, accuracy = 0.758), RF model (AUC = 0.970, accuracy = 0.921), MLP model (AUC = 0.830, accuracy = 0.756), SVM model (AUC = 0.713, accuracy = 0.661). On our data set, the XGBoost model has the best performance. However, the model still needs external verification research before clinical application.

Effect of Steel Fibers on Tensile Properties of Ultra-High-Performance Concrete: A Review.

Ultra-high-performance concrete (UHPC) is an advanced cement-based material with excellent mechanical properties and durability. However, with the improvement of UHPC's compressive properties, its insufficient tensile properties have gradually attracted attention. This paper reviews the tensile properties of steel fibers in UHPC. The purpose is to summarize the existing research and to provide guidance for future research. The relevant papers were retrieved through three commonly used experimental methods for UHPC tensile properties (the direct tensile test, flexural test, and splitting test), and classified according to the content, length, type, and combination of the steel fibers. The results show that the direct tensile test can better reflect the true tensile strength of UHPC materials. The tensile properties of UHPC are not only related to the content, shape, length, and hybrids of the steel fibers, but also to the composition of the UHPC matrix, the orientation of the fibers, and the geometric dimensions of the specimen. The improvement of the tensile properties of the steel fiber combinations depends on the effectiveness of the synergy between the fibers. Additionally, digital image correlation (DIC) technology is mainly used for crack propagation in UHPC. The analysis of the post-crack phase of UHPC is facilitated. Theoretical models and empirical formulas for tensile properties can further deepen the understanding of UHPC tensile properties and provide suggestions for future research.

Impacts of cationic lipid-DNA complexes on immune cells and hematopoietic cells in vivo.

The inability to systemic administration of nanoparticles, particularly cationic nanoparticles, has been a significant barrier to their clinical translation due to toxicity concerns. Understanding the in vivo behavior of cationic lipids is crucial, given their potential impact on critical biological components such as immune cells and hematopoietic stem cells (HSC). These cells are essential for maintaining the body's homeostasis, and their interaction with cationic lipids is a key factor in determining the safety and efficacy of these nanoparticles. In this study, we focused on the cytotoxic effects of cationic lipid/DNA complexes (CLN/DNA). Significantly, we observed that the most substantial cytotoxic effects, including a marked increase in numbers of long-term hematopoietic stem cells (LT-HSC), occurred 24 h post-CLN/DNA treatment in mice. Furthermore, we found that CLN/DNA-induced HSC expansion in bone marrow (BM) led to a notable decrease in the ability to reestablish blood cell production. Our study provides crucial insights into the interaction between cationic lipids and vital cellular components of the immune and hematopoietic systems.

CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer.

BACKGROUND: Tumor mutational burden (TMB) is one of the most significant predictive biomarkers of immunotherapy efficacy in non-small cell lung cancer (NSCLC). Radiomics allows high-throughput extraction and analysis of advanced and quantitative medical imaging features. This study develops and validates a radiomic model for predicting TMB level and the response to immunotherapy based on CT features in NSCLC. METHOD: Pre-operative chest CT images of 127 patients with NSCLC were retrospectively studied. The 3D-Slicer software was used to outline the region of interest and extract features from the CT images. Radiomics prediction model was constructed by LASSO and multiple logistic regression in a training dataset. The model was validated by receiver operating characteristic (ROC) curves and calibration curves using external datasets. Decision curve analysis was used to assess the value of the model for clinical application. RESULTS: A total of 1037 radiomic features were extracted from the CT images of NSCLC patients from TCGA. LASSO regression selected three radiomics features (Flatness, Autocorrelation and Minimum), which were associated with TMB level in NSCLC. A TMB prediction model consisting of 3 radiomic features was constructed by multiple logistic regression. The area under the curve (AUC) value in the TCGA training dataset was 0.816 (95% CI: 0.7109-0.9203) for predicting TMB level in NSCLC. The AUC value in external validation dataset I was 0.775 (95% CI: 0.5528-0.9972) for predicting TMB level in NSCLC, and the AUC value in external validation dataset II was 0.762 (95% CI: 0.5669-0.9569) for predicting the efficacy of immunotherapy in NSCLC. CONCLUSION: The model based on CT radiomic features helps to achieve cost effective improvement in TMB classification and precise immunotherapy treatment of NSCLC patients.

Ultraflexible Monolithic Three-Dimensional Static Random Access Memory.

Flexible static random access memory (SRAM) plays an important role in flexible electronics and systems. However, achieving SRAM with a small footprint, high flexibility, and high thermal stability has always been a big challenge. In this work, an ultraflexible six-transistor SRAM with high integration density is realized based on a monolithic three-dimensional (M3D) design. In this design, vertical stacked n-type indium gallium zinc oxide thin film transistors and p-type carbon nanotube transistors share common gate and drain electrodes, respectively, saving interlayer vias used in traditional M3D designs. This compact architecture reduces the footprint of the SRAM cell from a six-transistor to a four-transistor area, saving 33% of the area, and significantly enables the SRAM to have the highest flexibility among the reported ones, withstanding a harsh deforming process (6000 cycles of bending at a radius of 500 µm) without performance degradation. Moreover, this design facilitates the thermal stability of the SRAM under high temperature (333 K). It also exhibits great static and dynamic performance, with the highest normalized hold noise margin of 73.6%, a maximum gain of 151.2, and a minimum static power consumption of 3.15 µW in hold operation among the reported flexible SRAMs. This demonstration provides possibilities for SRAMs to be used in advanced wearable system applications.

Bifidobacterium animalis subsp. lactis boosts neonatal immunity: unravelling systemic defences against Salmonella.

Bifidobacterium animalis subsp. lactis may be a useful probiotic intervention for regulating neonatal intestinal immune responses and counteracting Salmonella infection. However, recent research has focused on intestinal immunity, leaving uncertainties regarding the central, peripheral, and neural immune responses in neonates. Therefore, this study investigated the role and mechanisms of B. animalis subsp. lactis in the systemic immune responses of neonatal rats following Salmonella infection. Through extremely early pretreatment with B. animalis subsp. lactis (6 hours postnatal), the neonatal rat gut microbiota was effectively reshaped, especially the Bifidobacterium community. In the rats pretreated with B. animalis subsp. lactis, Salmonella was less prevalent in the blood, liver, spleen, and intestines following infection. The intervention promoted T lymphocyte subset balance in the spleen and thymus and fostered neurodevelopment and neuroimmune balance in the brain. Furthermore, metabolic profiling showed a strong correlation between the metabolites in the serum and colon, supporting the view that B. animalis subsp. lactis pretreatment influences the systemic immune response by modifying the composition and metabolism of the gut microbiota. Overall, the results imply that B. animalis subsp. lactis pretreatment, through the coordinated regulation of colonic and serum metabolites, influences the systemic immune responses of neonatal rats against Salmonella infection.

Cationic nanoparticles-based approaches for immune tolerance induction in vivo.

The development of autoimmune diseases and the rejection of transplanted organs are primarily caused by an exaggerated immune response to autoantigens or graft antigens. Achieving immune tolerance is crucial for the effective treatment of these conditions. However, traditional therapies often have limited therapeutic efficacy and can result in systemic toxic effects. The emergence of nanomedicine offers a promising avenue for addressing immune-related diseases. Among the various nanoparticle formulations, cationic nanoparticles have demonstrated significant potential in inducing immune tolerance. In this review, we provide an overview of the underlying mechanism of autoimmune disease and organ transplantation rejection. We then highlight the recent advancements and advantages of utilizing cationic nanoparticles for inducing immune tolerance in the treatment of autoimmune diseases and the prevention of transplant rejection.

Can Platelets/Mean Platelet Volume Accurately Diagnose Periprosthetic Joint Infection? Revealing Their Actual Diagnostic Efficacy.

Background: Currently, there is no single test indicator for diagnosing periprosthetic joint infection (PJI) with an acceptable level of sensitivity. Therefore, ratio indicators have been introduced to improve the accuracy of diagnostic algorithms. Platelet count /mean platelet volume (PMR) is reported to be a potential PJI diagnostic biomarker, but its clinical value for diagnosing PJI is still uncertain. This study aims to provide additional evidence to support the effectiveness of PMR in accurately diagnosing PJI. Methods: This study recruited 116 patients with PJI and 137 patients with aseptic loosening, divided them into PJI group and AL group. Collect subjects' preoperative laboratory indicators such as ESR, CRP, PLT, MPV, etc. The area under the curve (AUC) was calculated by plotting the receiver operating characteristic (ROC) curve to determine the diagnostic efficacy of PMR. Results: ESR, CRP, PLT, and PLT/MPV were significantly increased in the PJI group, while MPV levels were decreased (both P< 0.001). The AUC of the PMR was 0.752, and the optimal cut-off value for diagnosing chronic PJI was determined to be 27.8 based on the Youden index. The sensitivity and specificity for diagnosing PJI were 79.3% and 47.9%, respectively, with a positive predictive value of 68.27%, a negative predictive value of 69.80%, and a diagnostic odds ratio of 4.97. The AUC (0.752) of the ratio biomarker was lower than that of ESR (0.825) and CRP (0.900). After predictive model calculation, the combination of PMR, CRP, and ESR had an AUC value of 0.910, with a sensitivity of 84.5% and a specificity of 84.7%, showing good discriminative ability. Conclusion: Compared with traditional biomarkers ESR and CRP, the value of the PMR for diagnosing PJI is not significant, but it can be used as an auxiliary indicator for PJI diagnosis in combination with other indicators (P<0.001).

Lactobacillus paracasei Relieves Constipation by Acting on the Acetic Acid-5-HT-Intestinal Motility Pathway.

Constipation is a major health concern worldwide and requires effective and safe treatment options. In this study, we selected ten strains of two species of lactobacilli to identify whether they were effective against constipation induced by loperamide administration in BALB/c mice. Monitoring of constipation-related indicators indicated that Lactobacillus paracasei (L. paracasei) mainly acted on the whole intestinal peristalsis to relieve constipation. Furthermore, through the detection of biological, chemical, mechanical, and immune barriers in mice, it was discovered that L. paracasei changed the relative abundance of bacteria related to the levels of acetic acid and 5-hydroxytryptamine (5-HT) (such as by increasing the relative abundance of Odoribacter and Clostridium, and reducing the relative abundance of Mucispirillum, Ruminococcus, Coprobacillus, and Dorea), increased the concentration of acetic acid in the intestine, which stimulated enterochromaffin cells, promoted 5-HT synthesis in the colon, enhanced intestinal motility, and relieved constipation. In conclusion, this study provides a theoretical foundation for the development of personalized products for the treatment of constipation.

Blockage of CacyBP inhibits macrophage recruitment and improves anti-PD-1 therapy in hepatocellular carcinoma.

BACKGROUND: Despite remarkable advancements in cancer immunotherapy, the overall response rate to anti-programmed cell death-1 (anti-PD-1) therapy in hepatocellular carcinoma (HCC) patients remains low. Our previous study has demonstrated the critical role of CacyBP/SIP (Calcyclin-Binding Protein and Siah-1 Interacting Protein) as a regulator of HCC development and progression. However, the possible impact of CacyBP on the tumor immune microenvironment has not yet been clarified. METHODS: The expressions of CacyBP and Myd88 in HCC cell lines and tissues was detected by bioinformatics analysis, real-time quantitative PCR, western blotting and immunohistochemistry. The interaction between CacyBP and Myd88 was measured using co-immunoprecipitation and immunofluorescence. In vitro and in vivo assays were used to investigate the regulation of CacyBP on tumor-associated macrophages (TAMs). RESULTS: We identified that CacyBP was positively correlated with Myd88, a master regulator of innate immunity, and Myd88 was a novel binding substrate downstream of CacyBP in HCC. Additionally, CacyBP protected Myd88 from Siah-1-mediated proteasome-dependent degradation by competitively binding to its Toll/interleukin-1 receptor (TIR) domain. Inhibition of CacyBP-Myd88 signaling subsequently diminished HDAC1-mediated H3K9ac and H3K27ac modifications on the CX3CL1 promoter and reduced its transcription and secretion in HCC cells. Moreover, by using in vitro and in vivo strategies, we demonstrated that depletion of CacyBP impaired the infiltration of TAMs and the immunosuppressive state of the tumor microenvironment, further sensitizing HCC-bearing anti-PD-1 therapy. CONCLUSIONS: Our findings suggest that targeting CacyBP may be a novel treatment strategy for improving the efficacy of anti-PD-1 immunotherapy in HCC.

Application of artificial intelligence in quantifying lung deposition dose of black carbon in people with exposure to ambient combustion particles.

BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophage carbon load (MaCL) is a novel cytology method that quantifies lung deposition dose of black carbon, however it has limited feasibility in large-scale epidemiological study due to the labor-intensive manual counting. OBJECTIVE: To assess the association between MaCL and episodic elevation of combustion particles; to develop artificial intelligence based counting algorithm for MaCL assay. METHODS: Sputum slides were collected during episodic elevation of ambient PM2.5 (n = 49, daily PM2.5 > 10 µg/m3 for over 2 weeks due to wildfire smoke intrusion in summer and local wood burning in winter) and low PM2.5 period (n = 39, 30-day average PM2.5 < 4 µg/m3) from the Lovelace Smokers cohort. RESULTS: Over 98% individual carbon particles in macrophages had diameter <1 µm. MaCL levels scored manually were highly responsive to episodic elevation of ambient PM2.5 and also correlated with lung injury biomarker, plasma CC16. The association with CC16 became more robust when the assessment focused on macrophages with higher carbon load. A Machine-Learning algorithm for Engulfed cArbon Particles (MacLEAP) was developed based on the Mask Region-based Convolutional Neural Network. MacLEAP algorithm yielded excellent correlations with manual counting for number and area of the particles. The algorithm produced associations with ambient PM2.5 and plasma CC16 that were nearly identical in magnitude to those obtained through manual counting. IMPACT STATEMENT: Understanding lung black carbon deposition is crucial for comprehending health effects of combustion particles. We developed "Machine-Learning algorithm for Engulfed cArbon Particles (MacLEAP)", the first artificial intelligence algorithm for quantifying airway macrophage black carbon. Our study bolstered the algorithm with more training images and its first use in air pollution epidemiology. We revealed macrophage carbon load as a sensitive biomarker for heightened ambient combustion particles due to wildfires and residential wood burning.

Advances in dendritic cell targeting nano-delivery systems for induction of immune tolerance.

Dendritic cells (DCs) are the major specialized antigen-presenting cells (APCs), play a key role in initiating the body's immune response, maintain the balance of immunity. DCs can also induce immune tolerance by rendering effector T cells absent and anergy, and promoting the expansion of regulatory T cells. Induction of tolerogenic DCs has been proved to be a promising strategy for the treatment of autoimmune diseases, organ transplantation, and allergic diseases by various laboratory researches and clinical trials. The development of nano-delivery systems has led to advances in situ modulation of the tolerance phenotype of DCs. By changing the material composition, particle size, zeta-potential, and surface modification of nanoparticles, nanoparticles can be used for the therapeutic payloads targeted delivery to DCs, endowing them with great potential in the induction of immune tolerance. This paper reviews how nano-delivery systems can be modulated for targeted delivery to DCs and induce immune tolerance and reviews their potential in the treatment of autoimmune diseases, organ transplantation, and allergic diseases.

Selective reduction of visceral adipose tissue with injectable ice slurry.

Reduction in visceral adipose tissue (VAT) mass reduces body weight and metabolic disease risk in obese patients. However surgical removal of VAT is highly invasive and thus not clinically feasible. We developed an injectable ice slurry for selective reduction of adipose tissue through cryolipolysis. The aim of this study was to investigate safety, feasibility and mechanism of ice slurry-induced cryolipolysis of VAT. Perigonadal VAT in diet-induced obese mice and rats was subjected to slurry or sham treatment. Body weight and blood chemistry were monitored for 56 days post-treatment. Histological analysis and molecular studies were performed to elucidate mechanisms of fat reduction. Treatment of VAT was well tolerated in all animals. Slurry induced adipocyte cell death via selective cryolipolysis; significant weight loss was noted at day 21 post-treatment. RNA sequencing from treated VAT samples showed increased expression of genes involved in inflammation, immune response, collagen biosynthesis and wound healing, and decreased expression of adipokines. This study demonstrates that slurry treatment is safe and effective in inducing cryolipolysis of VAT and subsequent weight loss in mice. Ice slurry is promising as a minimally-invasive treatment to reduce visceral adipose tissue.

Generalized efficient robust predictive control for networked interval type-2 T-S fuzzy system with adaptive event-triggered scheme.

This article studies the generalized efficient robust predictive control (GERPC) for the nonlinear systems denoted by interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model over networks with consideration of packet dropout, bounded disturbance and adaptive event-triggered scheme (AETS). First, the packet dropout is described by a Bernoulli process, and an AETS with thresholds that can be self-regulated according to different situations is employed to decide whether to release data into the communication network, so as to reduce the data transmission frequency and the network burden; Second, taking into consideration of packet dropout and AETS, a unified IT2 T-S fuzzy control model based on GERPC is established, and the stability of closed-loop system with bounded disturbance is guaranteed by quadratic boundedness (QB) technique; Third, generalized efficient robust predictive controller is designed to obtain a larger initial feasible region, smaller online computation and acceptable control performance. The unconstrained control law is designed offline, and a new variable will be optimized online to achieve good control performance, which is introduced to adjust the control quantity. Then, the convex LMI reformulation method is utilized to handle non-convex terms in optimization problem, and the effectiveness of the GERPC algorithm is proved by the matrix partition technique. At last, the effectiveness of the designed controller based on the GERPC strategy is verified by a given simulation experiment.