Efficacy and Safety of High-Viscosity Bone Cement in Percutaneous Vertebroplasty for Kummell's Disease.

Background: To analyze and evaluate the clinical outcomes of using high-viscosity bone cement compared to low-viscosity bone cement in percutaneous vertebroplasty (PVP) for treatment of Kummell's disease. Methods: From July 2017 to July 2019, 68 Kummell's disease patients who underwent PVP were chosen and separated into 2 groups: H group (n = 34), were treated with high-viscosity bone cement and L group (n = 34), treated with low-viscosity bone cement during treatment. The operation time, number of fluoroscopy tests done, and amount of bone cement perfusion were recorded for both groups. Clinical outcomes were compared, by measuring their Visual Analog Scale (VAS), Oswestry Disability Index (ODI), Kyphosis Cobb's angle, vertebral height compression rate, and other complications. Results: High-viscosity group showed less operation time and reduced number of fluoroscopy tests than the low-viscosity group (P < 0.05). When compared to preoperative period, both groups' VAS and ODI scores were significantly reduced at 1 day and 1 year postoperatively (P < 0.05). The vertebral height compression rate and Cobb's angle were significantly lower (P < 0.05) in both groups after surgery compared with those before surgery (P < 0.05). The cement leakage rate in group H was 26.5%, which was significantly lower than that in group L, which was 61.8% (P < 0.05). Conclusions: High-viscosity and low-viscosity bone cement in PVP have similar clinical efficacy in reducing pain in patients during the treatment, but in contrast, high-viscosity bone cement shortens the operative time, reduces number of fluoroscopy views and vertebral cement leakage and improves surgical safety.

Robotic wireless capsule endoscopy: recent advances and upcoming technologies.

Wireless capsule endoscopy (WCE) offers a non-invasive evaluation of the digestive system, eliminating the need for sedation and the risks associated with conventional endoscopic procedures. Its significance lies in diagnosing gastrointestinal tissue irregularities, especially in the small intestine. However, existing commercial WCE devices face limitations, such as the absence of autonomous lesion detection and treatment capabilities. Recent advancements in micro-electromechanical fabrication and computational methods have led to extensive research in sophisticated technology integration into commercial capsule endoscopes, intending to supersede wired endoscopes. This Review discusses the future requirements for intelligent capsule robots, providing a comparative evaluation of various methods' merits and disadvantages, and highlighting recent developments in six technologies relevant to WCE. These include near-field wireless power transmission, magnetic field active drive, ultra-wideband/intrabody communication, hybrid localization, AI-based autonomous lesion detection, and magnetic-controlled diagnosis and treatment. Moreover, we explore the feasibility for future "capsule surgeons".

Tailoring photobiomodulation to enhance tissue regeneration.

Photobiomodulation (PBM), the use of biocompatible tissue-penetrating light to interact with intracellular chromophores to modulate the fates of cells and tissues, has emerged as a promising non-invasive approach to enhancing tissue regeneration. Unlike photodynamic or photothermal therapies that require the use of photothermal agents or photosensitizers, PBM treatment does not need external agents. With its non-harmful nature, PBM has demonstrated efficacy in enhancing molecular secretions and cellular functions relevant to tissue regeneration. The utilization of low-level light from various sources in PBM targets cytochrome c oxidase, leading to increased synthesis of adenosine triphosphate, induction of growth factor secretion, activation of signaling pathways, and promotion of direct or indirect gene expression. When integrated with stem cell populations, bioactive molecules or nanoparticles, or biomaterial scaffolds, PBM proves effective in significantly improving tissue regeneration. This review consolidates findings from in vitro, in vivo, and human clinical outcomes of both PBM alone and PBM-combined therapies in tissue regeneration applications. It encompasses the background of PBM invention, optimization of PBM parameters (such as wavelength, irradiation, and exposure time), and understanding of the mechanisms for PBM to enhance tissue regeneration. The comprehensive exploration concludes with insights into future directions and perspectives for the tissue regeneration applications of PBM.

Metagenomics profiling of the microbial community and functional differences in solid-state fermentation vinegar starter (seed Pei) from different Chinese regions.

Introduction: The starter used in solid-state fermentation (SSF) vinegar, known as seed Pei is a microbial inoculant from the previous batch that is utilized during the acetic acid fermentation stage. The seed Pei, which has a notable impact on vinegar fermentation and flavor, is under-researched with comparative studies on microorganisms. Methods: Herein metagenomics was employed to reveal the microbes and their potential metabolic functions of four seed Pei from three regions in China. Results: The predominant microbial taxa in all four starters were bacteria, followed by viruses, eukaryotes, and archaea, with Lactobacillus sp. or Acetobacter sp. as main functional taxa. The seed Pei used in Shanxi aged vinegar (SAV) and Sichuan bran vinegar (SBV) exhibited a higher similarity in microbial composition and distribution of functional genes, while those used in two Zhenjiang aromatic vinegar (ZAV) differed significantly. Redundancy analysis (RDA) of physicochemical factors and microbial communities indicated that moisture content, pH, and reducing sugar content are significant factors influencing microbial distribution. Moreover, seven metagenome-assembled genomes (MAGs) that could potentially represent novel species were identified. Conclusions: There are distinctions in the microbiome and functional genes among different seed Pei. The vinegar starters were rich in genes related to carbohydrate metabolism. This research provides a new perspective on formulating vinegar fermentation starters and developing commercial fermentation agents for vinegar production.

Extracellular Matrix Stiffness-Induced Mechanotransduction of Capillarized Liver Sinusoidal Endothelial Cells.

The mechanobiological response mechanism of the fenestrae of liver sinusoidal endothelial cells (LSECs) to the physical stiffness of the extracellular matrix (ECM) remains unclear. We investigated how the mechanical properties of their substrates affect the LSECs' fenestrae by the nitric oxide (NO)-dependent pathway and how they relate to the progression of hepatic sinus capillarization during liver fibrosis. We detected different stiffnesses of ECM in the progress of liver fibrosis (LF) and developed polyacrylamide hydrogel (PAM) substrates to simulate them. Softer stiffness substrates contributed to LSECs maintaining fenestrae phenotype in vitro. The stiffness of liver fibrosis tissue could be reversed in vivo via treatment with anti-ECM deposition drugs. Similarly, the capillarization of LSECs could be reversed by decreasing the ECM stiffness. Our results also indicate that the NO-dependent pathway plays a key regulatory role in the capillarization of ECM-LSECs. Our study reveals ECM-induced mechanotransduction of capillarized LSECs through a NO-dependent pathway via a previously unrevealed mechanotransduction mechanism. The elucidation of this mechanism may offer precise biomechanics-specific intervention strategies targeting liver fibrosis progression.

[Constructing a predictive model for the death risk of patients with septic shock based on supervised machine learning algorithms].

OBJECTIVE: To construct and validate the best predictive model for 28-day death risk in patients with septic shock based on different supervised machine learning algorithms. METHODS: The patients with septic shock meeting the Sepsis-3 criteria were selected from Medical Information Mart for Intensive Care-IV v2.0 (MIMIC-IV v2.0). According to the principle of random allocation, 70% of these patients were used as the training set, and 30% as the validation set. Relevant predictive variables were extracted from three aspects: demographic characteristics and basic vital signs, serum indicators within 24 hours of intensive care unit (ICU) admission and complications possibly affecting indicators, functional scoring and advanced life support. The predictive efficacy of models constructed using five mainstream machine learning algorithms including decision tree classification and regression tree (CART), random forest (RF), support vector machine (SVM), linear regression (LR), and super learner [SL; combined CART, RF and extreme gradient boosting (XGBoost)] for 28-day death in patients with septic shock was compared, and the best algorithm model was selected. The optimal predictive variables were determined by intersecting the results from LASSO regression, RF, and XGBoost algorithms, and a predictive model was constructed. The predictive efficacy of the model was validated by drawing receiver operator characteristic curve (ROC curve), the accuracy of the model was assessed using calibration curves, and the practicality of the model was verified through decision curve analysis (DCA). RESULTS: A total of 3 295 patients with septic shock were included, with 2 164 surviving and 1 131 dying within 28 days, resulting in a mortality of 34.32%. Of these, 2 307 were in the training set (with 792 deaths within 28 days, a mortality of 34.33%), and 988 in the validation set (with 339 deaths within 28 days, a mortality of 34.31%). Five machine learning models were established based on the training set data. After including variables at three aspects, the area under the ROC curve (AUC) of RF, SVM, and LR machine learning algorithm models for predicting 28-day death in septic shock patients in the validation set was 0.823 [95% confidence interval (95%CI) was 0.795-0.849], 0.823 (95%CI was 0.796-0.849), and 0.810 (95%CI was 0.782-0.838), respectively, which were higher than that of the CART algorithm model (AUC = 0.750, 95%CI was 0.717-0.782) and SL algorithm model (AUC = 0.756, 95%CI was 0.724-0.789). Thus above three algorithm models were determined to be the best algorithm models. After integrating variables from three aspects, 16 optimal predictive variables were identified through intersection by LASSO regression, RF, and XGBoost algorithms, including the highest pH value, the highest albumin (Alb), the highest body temperature, the lowest lactic acid (Lac), the highest Lac, the highest serum creatinine (SCr), the highest Ca2+, the lowest hemoglobin (Hb), the lowest white blood cell count (WBC), age, simplified acute physiology score III (SAPS III), the highest WBC, acute physiology score III (APS III), the lowest Na+, body mass index (BMI), and the shortest activated partial thromboplastin time (APTT) within 24 hours of ICU admission. ROC curve analysis showed that the Logistic regression model constructed with above 16 optimal predictive variables was the best predictive model, with an AUC of 0.806 (95%CI was 0.778-0.835) in the validation set. The calibration curve and DCA curve showed that this model had high accuracy and the highest net benefit could reach 0.3, which was significantly outperforming traditional models based on single functional score [APS III score, SAPS III score, and sequential organ failure assessment (SOFA) score] with AUC (95%CI) of 0.746 (0.715-0.778), 0.765 (0.734-0.796), and 0.625 (0.589-0.661), respectively. CONCLUSIONS: The Logistic regression model, constructed using 16 optimal predictive variables including pH value, Alb, body temperature, Lac, SCr, Ca2+, Hb, WBC, SAPS III score, APS III score, Na+, BMI, and APTT, is identified as the best predictive model for the 28-day death risk in patients with septic shock. Its performance is stable, with high discriminative ability and accuracy.

Shewanella phaeophyticola sp. nov. and Vibrio algarum sp. nov., isolated from marine brown algae.

Two Gram-stain-negative, rod-shaped bacteria, designated as strains KJ10-1T and KJ40-1T, were isolated from marine brown algae. Both strains were catalase-positive, oxidase-positive, and facultative aerobic. Strain KJ10-1T exhibited optimal growth at 25 °C, pH 7.0, and 3 % NaCl, whereas strain KJ40-1T showed optimal growth at 25 °C, pH 7.0, and 2 % NaCl. The respiratory quinones of strain KJ10-1T were ubiquinone-8, ubiquinone-7, menaquinone-7, and methylated menaquinone-7, while the respiratory quinone of strain KJ40-1T was only ubiquinone-8. As major fatty acids, strain KJ10-1T contained C16 : 0, C17 : 1 ω8c, iso-C15 : 0, and summed feature 3 (C16 : 1 ω7c and/or C16 : 1 ω6c) and strain KJ40-1T contained C16 : 0 and summed features 3 and 8 (C18 : 1 ω7c and/or C18 : 1 ω6c). The major polar lipids in strain KJ10-1T were phosphatidylethanolamine, phosphatidylglycerol, and an unidentified aminolipid, whereas those in strain KJ40-1T were phosphatidylethanolamine, phosphatidylglycerol, and diphosphatidylglycerol. The DNA G+C contents of strains KJ10-1T and KJ40-1T were 42.1 and 40.8 mol%, respectively. Based on 16S rRNA gene sequences, strains KJ10-1T and KJ40-1T exhibited the closest relatedness to Shewanella saliphila MMS16-UL250T (98.6 %) and Vibrio rumoiensis S-1T (95.4 %), respectively. Phylogenetic analyses, based on both 16S rRNA and 92 housekeeping genes, showed that the strains formed distinct phylogenic lineages within the genera Shewanella and Vibrio. Digital DNA-DNA hybridization and orthologous average nucleotide identity values between strain KJ10-1T and other Shewanella species, as well as between strain KJ40-1T and other Vibrio species, were below the thresholds commonly accepted for prokaryotic species delineation. Based on the phenotypic, chemotaxonomic, and phylogenetic data, strains KJ10-1T and KJ40-1T represent novel species of the genera Shewanella and Vibrio, respectively, for which the names Shewanella phaeophyticola sp. nov. and Vibrio algarum sp. nov. are proposed, respectively. The type strains of S. phaeophyticola and V. algarum are KJ10-1T (=KACC 22589T=JCM 35409T) and KJ40-1T (=KACC 22588T=JCM 35410T), respectively.

Inhaled corticosteroids on mortality in COVID-19: A systematic review and meta-analysis of randomized controlled trials.

This systematic review and meta-analysis aimed to determine the efficacy of inhaled corticosteroids (ICS) on mortality in patients with coronavirus disease-2019 (COVID-19). A systematic search was made of PubMed, Embase, Cochrane Library, and clinicaltrials.gov, without language restrictions. Randomized controlled trials (RCTs) on the treatment of COVID-19 with ICS were reviewed. Studies were pooled to risk ratios (RRs), with 95% confidence intervals (CIs). Eleven RCTs (enrolling 5832 participants) met the inclusion criteria. There was no statistically significant difference in COVID-19-related death (RR 0.88, 95% CI 0.38-2.04), all-cause death (RR 1.05, 95% CI 0.49-2.23), and invasive ventilation (RR 1.26, 95% CI 0.60-2.62) between the two groups. ICS was not associated with reduced mortality and invasive ventilation in patients with COVID-19.

Unlocking Maximum Synergy: Screen-Printing Fabrication of Heterostructured Microsupercapacitor Stacks.

A cost-effective and scalable approach for the fabrication of heterostructured microsupercapacitors (MSCs) employing screen-printing followed by sequential electrochemical and microspray deposition techniques has been demonstrated. The microsupercapacitor electrode (MSC) that composed of stacked layers of mesoporous carbon, polyaniline (PANI), and MXene hold significant promise for wearable electronics. By adjusting the deposition and spray cycles, the MSC can be readily coated with PANI and MXene. The sequentially stacked two layers of MXene and PANI on the mesoporous carbon spheres (PMPM-MSC) yielded a specific capacitance of 1003 mF cm-2 at 0.5 mA cm-2, surpassing the performance of PANI/mesoporous carbon electrode by 1.6 times (771 mF cm-2). After 10,000 cycles of charge and discharge, PMPM-MSCs retained more than 86% of their initial capacitance. In-situ Raman spectroscopy confirmed the synergistic effects between MXene and PANI within the heterostructured stacked PMPM-MSC electrodes, including enhanced electronic conductivity and improved electrolyte ion dissociation, which aligned with the electrochemical measurement results, such as fast charge/discharge rates and reduced internal and mass transport resistance. This study demonstrates the potential of screen-printed heterostructured MSC stacks with maximum electrochemical synergy for portable and wearable energy storage devices.

Patient with suspected co-infection of hemorrhagic fever with renal syndrome and malaria: a case report.

Background: Hemorrhagic fever with renal syndrome (HFRS) is a natural epidemic disease that can be caused by the Hantaan virus (HTNV). Malaria is caused by plasmodium and can be transmitted by a mosquito bite. The similar manifestations shared by these disorders pose a challenge for clinicians in differential diagnosis, in particular, coupled with a false-positive serological test. Case presentation: A 46-year-old man was admitted for fever and chills for over 10 days and was suspected of being co-infected with HFRS and malaria due to a history of travel to malaria-endemic areas and a positive HTNV-immunoglobulin M (IgM) test. Although leukocytosis, thrombocytopenia, renal injury, lymphocytosis, overexpression of interleukin-6, and procalcitonin were observed during the hospitalization, the hypotensive, oliguria, and polyuria phases of the HFRS course were not observed. Instead, typical symptoms of malaria were found, including a progressive decrease in erythrocytes and hemoglobin levels with signs of anemia. Furthermore, because the patient had no history of exposure to HFRS endemic areas, exposure to an HTNV-infected rodent, or a positive HTNV-IgG test, and false serological tests of IgM can be caused by various factors, the HFRS coinfection with malaria was ruled out. Conclusion: Misdiagnosis can be easily induced by a false serological test, in particular the IgM test which can be influenced by various factors. A combination of health history, epidemiology, physical examination, precise application of specific examinations involving tests of conventional laboratory parameters as well as well-accepted methods such as the immunochromatographic (ICG) test, real-time reverse transcription-polymerase chain reaction (PCR), and Western blot (WB), and acquaintance with disorders with similar manifestations will contribute to the precise diagnosis in clinical treatment.

Linking Computational Fluid Dynamics Modeling to Device-Induced Platelet Defects in Mechanically Assisted Circulation.

Thrombotic and bleeding events are the most common hematologic complications in patients with mechanically assisted circulation and are closely related to device-induced platelet dysfunction. In this study, we sought to link computational fluid dynamics (CFD) modeling of blood pumps with device-induced platelet defects. Fresh human blood was circulated in circulatory loops with four pumps (CentriMag, HVAD, HeartMate II, and CH-VAD) operated under a total of six clinically representative conditions. Blood samples were collected and analyzed for glycoprotein (GP) IIb/IIIa activation and receptor shedding of GPIbα and GPVI. In parallel, CFD modeling was performed to characterize the blood flow in these pumps. Numerical indices of platelet defects were derived from CFD modeling incorporating previously derived power-law models under constant shear conditions. Numerical results were correlated with experimental results by regression analysis. The results suggested that a scalar shear stress of less than 75 Pa may have limited contribution to platelet damage. The platelet defect indices predicted by the CFD power-law models after excluding shear stress <75 Pa correlated excellently with experimentally measured indices. Although numerical prediction based on the power-law model cannot directly reproduce the experimental data. The power-law model has proven its effectiveness, especially for quantitative comparisons.

Evaluating the performance of thermoplastic 3D bolus used in radiation therapy.

A 3D-printed bolus is being developed to deliver accurate doses to superficial cancers. In this study, flexible thermoplastic filaments, specifically PLA, TPU, PETG, and HIPS, were fabricated into boluses and then compared to commercial bolus for the variation of the dose elevation region of photon beams. The experimental results indicate that the maximum dose depth is similar, and the consistent trend of the percentage depth dose confirms the potential usage as a build-up bolus.

Spin-orbit-splitting-driven nonlinear Hall effect in NbIrTe4.

The Berry curvature dipole (BCD) serves as a one of the fundamental contributors to emergence of the nonlinear Hall effect (NLHE). Despite intense interest due to its potential for new technologies reaching beyond the quantum efficiency limit, the interplay between BCD and NLHE has been barely understood yet in the absence of a systematic study on the electronic band structure. Here, we report NLHE realized in NbIrTe4 that persists above room temperature coupled with a sign change in the Hall conductivity at 150 K. First-principles calculations combined with angle-resolved photoemission spectroscopy (ARPES) measurements show that BCD tuned by the partial occupancy of spin-orbit split bands via temperature is responsible for the temperature-dependent NLHE. Our findings highlight the correlation between BCD and the electronic band structure, providing a viable route to create and engineer the non-trivial Hall effect by tuning the geometric properties of quasiparticles in transition-metal chalcogen compounds.

Radiological Features for Predicting the Status of CD8-Positive Lymphocytes in HER2 Positive Breast Cancer.

Background: The level of tumor-infiltrating lymphocytes (TILs) in human epidermal growth factor receptor type 2 (HER2)-positive breast cancer (BC) is positively correlated with pathological complete response. Aims: To investigate the relationship between ultrasound (US) and magnetic resonance imaging (MRI) features and the level of CD8-positive TILs (CD8+-TILs) in patients with HER2-positive BC. Study Design: Retrospective cohort study. Methods: This retrospective study included 155 consecutive women with HER2-positive BC. Patients were divided into two groups: CD8+-TILlow (< 35%) and CD8+-TILhigh (≥ 35%) groups. US and MRI features were evaluated using the BI-RADS lexicon, and the apparent diffusion coefficient (ADC) value was calculated using RadiAnt software. Univariate and multivariate analyses revealed the optimal US and MRI features for predicting CD8+-TIL levels. Receiver operating characteristic analysis and the Delong test were used to compare the diagnostic performance of US and MRI features. Furthermore, implementing a nomogram will increase clinical utility. Results: Univariate analysis of US features showed significant differences in shape, orientation, and posterior echo between the two groups; however, there were no significant differences in margins, internal echo, and microcalcification. Multifactorial analysis revealed that shape, orientation, and posterior echo were independent risk factors, with odds ratios of 11.62, 2.70, and 0.16, respectively. In terms of MRI features, ADC was an independent predictor of CD8+-TIL levels. These three US features and the ADC performed well, with area under the curve (AUC) values of 0.802 and 0.705, respectively. The combination of US and ADC values had higher predictive efficacy (AUC = 0.888) than either US or ADC alone (p = 0.009, US_ADC vs. US; p < 0.001, US_ADC vs. ADC). Conclusion: US features (shape, orientation, and posterior echo) and ADC value may be a valuable tool for estimating CD8+-TIL levels in HER2-positive BC. The nomogram may help clinicians in making decisions.

Accumulation of ß-aminoisobutyric acid mediates hyperalgesia in ovariectomized mice through Mas-related G protein-coupled receptor D signaling.

Hyperalgesia is typified by reduced pain thresholds and heightened responses to painful stimuli, with a notable prevalence in menopausal women, but the underlying mechanisms are far from understood. ß-Aminoisobutyric acid (BAIBA), a product of valine and thymine catabolism, has been reported to be a novel ligand of the Mas-related G protein coupled receptor D (MrgprD), which mediates pain and hyperalgesia. Here, we established a hyperalgesia model in 8-week-old female mice through ovariectomy (OVX). A significant increase in BAIBA plasma level was observed and was associated with decline of mechanical withdrawal threshold, thermal and cold withdrawal latency in mice after 6 weeks of OVX surgery. Increased expression of MrgprD in dorsal root ganglion (DRG) was shown in OVX mice compared to Sham mice. Interestingly, chronic loading with BAIBA not only exacerbated hyperalgesia in OVX mice, but also induced hyperalgesia in gonadally intact female mice. BAIBA supplementation also upregulated the MrgprD expression in DRG of both OVX and intact female mice, and enhanced the excitability of DRG neurons in vitro. Knockout of MrgprD markedly suppressed the effects of BAIBA on hyperalgesia and excitability of DRG neurons. Collectively, our data suggest the involvement of BAIBA in the development of hyperalgesia via MrgprD-dependent pathway, and illuminate the mechanisms underlying hyperalgesia in menopausal women.

Triterpenoids from the leaves of Eleutherococcus sessiliflorus, and their antiproliferative activities in TNF-α induced HFLS-RA cells.

Five undescribed elesesterpenes L-U, along with nine known 3,4-seco-lupane-type triterpenoids were isolated from the leaves of Eleutherococcus sessiliflorus (Rupr. & Maxim.) S. Y. Hu. Elesesterpene L-S, and U were lupane-type triterpenoids, whereas elesesterpene T was an oleanane-type triterpenoid, probably artifact, as suggested by LC-MS analysis. Out of the nine known compounds, five were initially identified in E. sessiliflorus. Moreover, their structures were definitively determined using spectroscopic analyses, and the absolute configurations of elesesterpenes L-M and sachunogenin 3-O-glucoside were clarified using X-ray crystallographic techniques. The absolute configuration of elesesterpene T was determined by measuring and calculating its ECD. In addition, all compounds were tested to examine their ability to inhibit the proliferation of HFLS-RA cells induced by TNF-α in vitro. Elesesterpene M, chiisanogenin, chiisanoside, and 3-methylisochiisanoside significantly inhibited HFLS-RA proliferation.

Combinatory Nanovesicle with siRNA-Loaded Extracellular Vesicle and IGF-1 for Osteoarthritis Treatments.

Extracellular vesicles (EVs) have been found to have the characteristics of their parent cells. Based on the characteristics of these EVs, various studies on disease treatment using mesenchymal stem cell (MSC)-derived EVs with regenerative activity have been actively conducted. The therapeutic nature of MSC-derived EVs has been shown in several studies, but in recent years, there have been many efforts to functionalize EVs to give them more potent therapeutic effects. Strategies for functionalizing EVs include endogenous and exogenous methods. In this study, human umbilical cord MSC (UCMSC)-derived EVs were selected for optimum OA treatments with expectation via bioinformatics analysis based on antibody array. And we created a novel nanovesicle system called the IGF-si-EV, which has the properties of both cartilage regeneration and long-term retention in the lesion site, attaching positively charged insulin-like growth factor-1 (IGF-1) to the surface of the UCMSC-derived Evs carrying siRNA, which inhibits MMP13. The downregulation of inflammation-related cytokine (MMP13, NF-kB, and IL-6) and the upregulation of cartilage-regeneration-related factors (Col2, Acan) were achieved with IGF-si-EV. Moreover, the ability of IGF-si-EV to remain in the lesion site for a long time has been proven through an ex vivo system. Collectively, the final constructed IGF-si-EV can be proposed as an effective OA treatment through its successful MMP13 inhibition, chondroprotective effect, and cartilage adhesion ability. We also believe that this EV-based nanoparticle-manufacturing technology can be applied as a platform technology for various diseases.

Accurate categorization and rapid pathological diagnosis correction with Micro-Raman technique in human lung adenocarcinoma infiltration level.

Background: In the context of surgical interventions for lung adenocarcinoma (LADC), precise determination of the extent of LADC infiltration plays a pivotal role in shaping the surgeon's strategic approach to the procedure. The prevailing diagnostic standard involves the expeditious intraoperative pathological diagnosis of areas infiltrated by LADC. Nevertheless, current methodologies rely on the visual interpretation of tissue images by proficient pathologists, introducing an error margin of up to 15.6%. Methods: In this study, we investigated the utilization of Micro-Raman technique on isolated specimens of human LADC with the objective of formulating and validating a workflow for the pathological diagnosis of LADC featuring diverse degrees of infiltration. Our strategy encompasses a thorough pathological characterization of LADC, spanning different tissue types and levels of infiltration. Through the integration of Raman spectroscopy with advanced deep learning models for simultaneous diagnosis, this approach offers a swift, precise, and clinically relevant means of analysis. Results: The diagnostic performance of the convolutional neural network (CNN) model, coupled with the microscopic Raman technique, was found to be exceptional and consistent, surpassing the traditional support vector machine (SVM) model. The CNN model exhibited an area under the curve (AUC) value of 96.1% for effectively distinguishing normal tissue from LADC and an impressive 99.0% for discerning varying degrees of infiltration in LADCs. To comprehensively assess its clinical utility, Raman datasets from patients with intraoperative rapid pathologic diagnostic errors were utilized as test subjects and input into the established CNN model. The results underscored the substantial corrective capacity of the Micro-Raman technique, revealing a misdiagnosis correction rate exceeding 96% in all cases. Conclusions: Ultimately, our discoveries highlight the Micro-Raman technique's potential to augment the intraoperative diagnostic precision of LADC with varying levels of infiltration. And compared to the traditional SVM model, the CNN model has better generalization ability in diagnosing different infiltration levels. This method furnishes surgeons with an objective groundwork for making well-informed decisions concerning subsequent surgical plans.