Resveratrol improved mitochondrial biogenesis by activating SIRT1/PGC-1α signal pathway in SAP.

NLRP3 inflammasomes- pyroptosis axis is activated by microcirculation dysfunction and touched off severe acute pancreatitis (SAP). Activation of PGC-1α can improve microcirculation dysfunction by promoting mitochondrial biogenesis. Resveratrol (RSV), one typical SIRT1 agonist, possesses the ability of alleviating SAP and activing PGC-1α. Therefore, the study was designated to explore whether the protective effect of RSV in SAP was though suppressing NLRP3 inflammasomes- pyroptosis axis via advancing SIRT1/PGC-1α-dependent mitochondrial biogenesis. The models of SAP were induced by treating with sodium taurodeoxycholate in rats and AR42J cells. The pathological injury, water content (dry/wet ratio) and microcirculation function of pancreas, activity of lipase and amylase were used to evaluate pancreatic damage. The expression of inflammatory cytokine was measured by ELISA and RT-PCR. The damage of mitochondrial was evaluated by measuring the changes in Mitochondrial Membrane Potential (ΔΨm), mitochondrial ROS, ATP content and MDA as well as relocation of mtDNA and the activity of SOD and GSH. The expressions of NLRP3 inflammasomes- pyroptosis axis proteins were detected by Western blotting as well as SIRT1/PGC-1α/NRF1/TFAM pathway protein. Moreover, the modification of PGC-1α was measured by co-immunoprecipitation. The results displayed that RSV can significantly improve the damage of pancreas and mitochondrial, decrease the expression of pro-inflammatory factor and the activation of NLRP3 inflammasomes- pyroptosis axis, promote the expression of an-inflammatory factor and the deacetylation of PGC-1α together with facilitating SIRT1/PGC-1α-mediating mitochondrial biogenesis. Therefore, the protective effect of RSV in SAP is though inactivation of NLRP3 inflammasomes- pyroptosis axis via promoting mitochondrial biogenesis in a SIRT1/PGC-1α-dependent manner.

Early detection of dementia through retinal imaging and trustworthy AI.

Alzheimer's disease (AD) is a global healthcare challenge lacking a simple and affordable detection method. We propose a novel deep learning framework, Eye-AD, to detect Early-onset Alzheimer's Disease (EOAD) and Mild Cognitive Impairment (MCI) using OCTA images of retinal microvasculature and choriocapillaris. Eye-AD employs a multilevel graph representation to analyze intra- and inter-instance relationships in retinal layers. Using 5751 OCTA images from 1671 participants in a multi-center study, our model demonstrated superior performance in EOAD (internal data: AUC = 0.9355, external data: AUC = 0.9007) and MCI detection (internal data: AUC = 0.8630, external data: AUC = 0.8037). Furthermore, we explored the associations between retinal structural biomarkers in OCTA images and EOAD/MCI, and the results align well with the conclusions drawn from our deep learning interpretability analysis. Our findings provide further evidence that retinal OCTA imaging, coupled with artificial intelligence, will serve as a rapid, noninvasive, and affordable dementia detection.

Rivaroxaban for Thromboembolism Prophylaxis in Patients with Nephrotic Syndrome: A Single-Arm, Prospective Study.

Introduction: Thromboembolism is a recognized complication of nephrotic syndrome (NS). Evidence supporting the use of rivaroxaban to prevent NS-related thrombosis is limited and controversial. This study aimed to explore the impact of NS on rivaroxaban pharmacokinetics and to collect observational data on the efficacy and safety of rivaroxaban as primary thromboprophylaxis in patients with NS. Methods: This prospective study analyzed 141 patients with NS who received rivaroxaban (10 mg/day) for thromboprophylaxis. High-performance liquid chromatography-tandem mass spectrometry was used to measure the trough and peak plasma concentrations (Ctrough and Cmax) of rivaroxaban. The influence of clinical and genetic factors on these concentrations was examined using multivariate logistic regression. Results: The median Cmax and Ctrough were 68.5 ng/mL (interquartile range [IQR], 31.7-105.5 ng/mL) and 4.4 ng/mL (IQR, 1.2-11.9 ng/mL), respectively. The incidence of thromboembolic events (TEs) was 12.8%, while that of bleeding events was 14.2%, although all were classified as minor. Albumin level was the most significant factor affecting Cmax (ρ = 0.55; p < 0.001) and was also significantly associated with TEs (0.81; 0.71-0.91 per 1.0 g/dL increase; p = 0.001) and bleeding risks (1.11; 1.03-1.19 per 1.0 g/dL increase; p = 0.008). Single nucleotide polymorphisms in the ABCB1 gene significantly influenced Ctrough but were not associated with clinical outcomes. Conclusion: Hypoalbuminemia significantly affects the pharmacokinetics of rivaroxaban in NS patients. A dose-adjustment strategy based on rivaroxaban concentrations, accounting for variable albumin levels, may improve the safety and efficacy of thromboprophylaxis in this population.

MR2-Net: Retinal OCTA Image Stitching via Multi-Scale Representation Learning and Dynamic Location Guidance.

Optical coherence tomography angiography (OCTA) plays a crucial role in quantifying and analyzing retinal vascular diseases. However, the limited field of view (FOV) inherent in most commercial OCTA imaging systems poses a significant challenge for clinicians, restricting the possibility to analyze larger retinal regions of high resolution. Automatic stitching of OCTA scans in adjacent regions may provide a promising solution to extend the region of interest. However, commonly-used stitching algorithms face difficulties in achieving effective alignment due to noise, artifacts and dense vasculature present in OCTA images. To address these challenges, we propose a novel retinal OCTA image stitching network, named MR2-Net, which integrates multi-scale representation learning and dynamic location guidance. In the first stage, an image registration network with a progressive multi-resolution feature fusion is proposed to derive deep semantic information effectively. Additionally, we introduce a dynamic guidance strategy to locate the foveal avascular zone (FAZ) and constrain registration errors in overlapping vascular regions. In the second stage, an image fusion network based on multiple mask constraints and adjacent image aggregation (AIA) strategies is developed to further eliminate the artifacts in the overlapping areas of stitched images, thereby achieving precise vessel alignment. To validate the effectiveness of our method, we conduct a series of experiments on two delicately constructed datasets, i.e., OPTOVUE-OCTA and SVision-OCTA. Experimental results demonstrate that our method outperforms other image stitching methods and effectively generates high-quality wide-field OCTA images, achieving a structural similarity index (SSIM) score of 0.8264 and 0.8014 on the two datasets, respectively.

Comparative analysis of brain age prediction using structural and diffusion MRIs in neonates.

Using machine learning techniques to predict brain age from multimodal data has become a crucial biomarker for assessing brain development. Among various types of brain imaging data, structural magnetic resonance imaging (sMRI) and diffusion magnetic resonance imaging (dMRI) are the most commonly used modalities. sMRI focuses on depicting macrostructural features of the brain, while dMRI reveals the orientation of major white matter fibers and changes in tissue microstructure. However, their differential capabilities in reflecting newborn age and clinical implications have not been systematically studied. This study aims to explore the impact of sMRI and dMRI on brain age prediction. Comparing predictions based on T2-weighted(T2w) and fractional anisotropy (FA) images, we found their mean absolute errors (MAE) in predicting infant age to be similar. Exploratory analysis revealed for T2w images, areas such as the cerebral cortex and ventricles contribute most significantly to age prediction, whereas FA images highlight the cerebral cortex and regions of the main white matter tracts. Despite both modalities focusing on the cerebral cortex, they exhibit significant region-wise differences, reflecting developmental disparities in macro- and microstructural aspects of the cortex. Additionally, we examined the effects of prematurity, gender, and hemispherical asymmetry of the brain on age prediction for both modalities. Results showed significant differences (p<0.05) in age prediction biases based on FA images across gender and hemispherical asymmetry, whereas no significant differences were observed with T2w images. This study underscores the differences between T2w and FA images in predicting infant brain age, offering new perspectives for studying infant brain development and aiding more effective assessment and tracking of infant development.

Proximal humeral bone density assessment and prediction analysis using machine learning techniques: An innovative approach in medical research.

Background: Patients with fractures of the proximal humerus often local complications and failures attributed to osteoporosis. Currently, there is a lack of straight forward screening methods for assessing the extent of local osteoporosis in the proximal humerus. This study utilizes machine learning techniques to establish a diagnostic approach for evaluating local osteoporosis by analyzing the patient's demographic data, bone density, and X-ray ratio of the proximal humerus. Methods: A cohort comprising a total of 102 hospitalized patients admitted during the period spanning from 2021 to 2023 underwent random selection procedures. Resulting in exclusion of 5 patients while enrolling 97 patients for analysis encompassing patient demographics, shoulder joint anteroposterior radiographs, and bone density information. Using the modified Tingart index methodology involving multiple measurements denoted as M1 through M4 obtained from humeral shafts. Within this cohort comprised 76 females (78.4 %) and 21 males (21.6 %), with an average age of 73.0 years (range: 43-98 years). There were 25 cases with normal bone density, 35 with osteopenia, and 37 with osteoporosis. Machine learning techniques were used to randomly divide the 97 cases into training (n = 59) and validation (n = 38) sets with a ratio of 6:4 using stratified random sampling. A decision tree model was built in the training set, and significant diagnostic indicators were selected, with the performance of the decision tree evaluated using the validation set. Multinomial logistic regression methods were used to verify the strength of the relationship between the selected indicators and osteoporosis. Results: The decision tree identified significant diagnostic indicators as the humeral shaft medullary cavity ratio M2/M4, age, and gender. M2/M4 ≥ 1.13 can be used as an important screening criterion; M2/M4 < 1.13 was predicted as local osteoporosis; M2/M4 ≥ 1.13 and age ≥83 years were also predicted as osteoporosis. M2/M4 ≥ 1.13 and age <64 years or males aged between 64 and 83 years were predicted as the normal population; M2/M4 ≥ 1.13 and females aged between 64 and 83 years were predicted as having osteopenia. The decision tree's accuracy in the training set was 0.7627 (95 % CI (0.6341, 0.8638)), and its accuracy in the test set was 0.7895 (95 % CI (0.6268, 0.9045)). Multinomial logistic regression results showed that humeral shaft medullary cavity ratios M2/M4, age, and gender in X-ray images were significantly associated with the occurrence of osteoporosis. Conclusion: Utilizing X-ray data of the proximal humerus in conjunction with demographic information such as gender and age enable the prediction of localized osteoporosis, facilitating physicians' rapid comprehension of osteoporosis in patients and optimization of clinical treatment plans. Level of evidence: Level IV retrospective case study.

COSTA: A Multi-center TOF-MRA Dataset and A Style Self-Consistency Network for Cerebrovascular Segmentation.

Time-of-flight magnetic resonance angiography (TOF-MRA) is the least invasive and ionizing radiation-free approach for cerebrovascular imaging, but variations in imaging artifacts across different clinical centers and imaging vendors result in inter-site and inter-vendor heterogeneity, making its accurate and robust cerebrovascular segmentation challenging. Moreover, the limited availability and quality of annotated data pose further challenges for segmentation methods to generalize well to unseen datasets. In this paper, we construct the largest and most diverse TOF-MRA dataset (COSTA) from 8 individual imaging centers, with all the volumes manually annotated. Then we propose a novel network for cerebrovascular segmentation, namely CESAR, with the ability to tackle feature granularity and image style heterogeneity issues. Specifically, a coarse-to-fine architecture is implemented to refine cerebrovascular segmentation in an iterative manner. An automatic feature selection module is proposed to selectively fuse global long-range dependencies and local contextual information of cerebrovascular structures. A style self-consistency loss is then introduced to explicitly align diverse styles of TOF-MRA images to a standardized one. Extensive experimental results on the COSTA dataset demonstrate the effectiveness of our CESAR network against state-of-the-art methods. We have made 6 subsets of COSTA with the source code online available, in order to promote relevant research in the community.

The effects of graphene on low-temperature anammox process: The insights from short-term tests and long-term operation.

Effluent quality deterioration caused by seasonal low temperature is a great challenge to the application of anammox technology. Here, the effects of different graphene materials on anammox process were investigated under both optimal temperature and low-temperature. The batch tests showed that at 30 °C, 300 mg/L of reduced graphene oxide­sodium alginate gel (RGOSA) had the most significant promoting effect, reaching nitrogen removal efficiency (NRE) and nitrogen removal rate (NRR) of 95 % and 8.88 mgN/L/d, respectively. The changes of EPS secretion patterns and increasing of key enzymes activity might contribute to the enhanced anammox activity. During the long-term operation of anammox reactor, the NRE and NRR of the reactor decreased when the temperature dropped to 15 °C, showing an NRE of 50 %-57 % with the addition of 200 mg/L of reduced graphene oxide (RGO) and 40 %-45 % with the addition of 20 mg/L of RGO. Furthermore, specific anammox activity (SAA) of the RGO200 reactor at 15 °C increased by 57.1 % compared to the UASB reactor without graphene addition. Additionally, 16S rRNA and metagenomic analysis results revealed anammox bacteria Ca. Kuenenia was the dominant bacteria. Moreover, the RGO can significantly increase the relative abundance of N-converting functional genes. This study demonstrates the graphene materials can help anammox process adapting to low temperatures, providing a possible solution for the application of anammox technology.

Axonal autophagic vesicle transport in the rat optic nerve in vivo under normal conditions and during acute axonal degeneration.

Neurons pose a particular challenge to degradative processes like autophagy due to their long and thin processes. Autophagic vesicles (AVs) are formed at the tip of the axon and transported back to the soma. This transport is essential since the final degradation of the vesicular content occurs only close to or in the soma. Here, we established an in vivo live-imaging model in the rat optic nerve using viral vector mediated LC3-labeling and two-photon-microscopy to analyze axonal transport of AVs. Under basal conditions in vivo, 50% of the AVs are moving with a majority of 85% being transported in the retrograde direction. Transport velocity is higher in the retrograde than in the anterograde direction. A crush lesion of the optic nerve results in a rapid breakdown of retrograde axonal transport while the anterograde transport stays intact over several hours. Close to the lesion site, the formation of AVs is upregulated within the first 6 h after crush, but the clearance of AVs and the levels of lysosomal markers in the adjacent axon are reduced. Expression of p150Glued, an adaptor protein of dynein, is significantly reduced after crush lesion. In vitro, fusion and colocalization of the lysosomal marker cathepsin D with AVs are reduced after axotomy. Taken together, we present here the first in vivo analysis of axonal AV transport in the mammalian CNS using live-imaging. We find that axotomy leads to severe defects of retrograde motility and a decreased clearance of AVs via the lysosomal system.

Oral soluble shell prepared from OSA starch incorporated with tea polyphenols for the microencapsulation of Sichuan pepper oleoresin: Characterization, flavor stability, release mechanisms and its application in mooncake.

The market share of Sichuan pepper oleoresin (SPO) in the flavor industry is increasing steadily; however, its high volatility, low water solubility, and poor stability continue to pose significant challenges to application. The microencapsulation prepared by emulsion embedding and spray drying is considered as an effective technique to solve the above problems. Sodium octenyl succinate starch (OSA starch) and tea polyphenols (TPs) were used to develop OSA-TPs complex as encapsulants for SPO to prepare orally soluble microcapsules. And the optimum doping of TPs was determined. SPO microcapsules have good properties with high encapsulation efficiency up to 88.13 ± 1.48% and high payload up to 41.58 ± 1.86% with low water content and high heat resistance. The binding mechanism of OSA starch with TPs and its regulation mechanism and effect on SPOs were further analyzed and clarified. The binding mechanism between OSA starch and TPs was clarified in further analyses. The OSA-TPs complexes enhanced the rehydration, release in food matrix and storage stability of SPO, and exhibited good sensory immediacy. Flavor-improved mooncakes were successfully developed, achieving the combination of mooncake flavor and SPO flavor. This study provided a valuable way to prepare flavoring microcapsules suitable for the catering industry, opened up the combined application of SPO and bakery ingredients, and was of great practical value and significance for improving the processing quality of flavor foods, driving the development of the SPO industry, and enhancing the national dietary experience.

The molecular mechanisms of peptidyl-prolyl cis/trans isomerase Pin1 and its relevance to kidney disease.

Pin1 is a member of the peptidyl-prolyl cis/trans isomerase subfamily and is widely expressed in various cell types and tissues. Alterations in Pin1 expression levels play pivotal roles in both physiological processes and multiple pathological conditions, especially in the onset and progression of kidney diseases. Herein, we present an overview of the role of Pin1 in the regulation of fibrosis, oxidative stress, and autophagy. It plays a significant role in various kidney diseases including Renal I/R injury, chronic kidney disease with secondary hyperparathyroidism, diabetic nephropathy, renal fibrosis, and renal cell carcinoma. The representative therapeutic agent Juglone has emerged as a potential treatment for inhibiting Pin1 activity and mitigating kidney disease. Understanding the role of Pin1 in kidney diseases is expected to provide new insights into innovative therapeutic interventions and strategies. Consequently, this review delves into the molecular mechanisms of Pin1 and its relevance in kidney disease, paving the way for novel therapeutic approaches.

Inhibition of Drp1-mediated mitochondrial fission improves contrast-induced acute kidney injury by targeting the mROS-TXNIP-NLRP3 inflammasome axis.

Acute kidney injury (AKI) is a critical complication known for their extremely high mortality rate and lack of effective clinical therapy. Disorders in mitochondrial dynamics possess a pivotal role in the occurrence and progression of contrast-induced nephropathy (CIN) by activating NLRP3 inflammasome. The activation of dynamin-related protein-1 (Drp1) can trigger mitochondrial dynamic disorders by regulating excessive mitochondrial fission. However, the precise role of Drp1 during CIN has not been clarified. In vivo experiments revealed that inhibiting Drp1 through Mdivi-1 (one selective inhibitor of Drp1) can significantly decrease the expression of p-Drp1 (Ser616), mitochondrial p-Drp1 (Ser616), mitochondrial Bax, mitochondrial reactive oxygen species (mROS), NLRP3, caspase-1, ASC, TNF-α, IL-1ß, interleukin (IL)-18, IL-6, creatinine (Cr), malondialdehyde (MDA), blood urea nitrogen (BUN), and KIM-1. Moreover, Mdivi-1 reduced kidney pathological injury and downregulated the interaction between NLRP3 and thioredoxin-interacting protein (TXNIP), which was accompanied by decreased interactions between TRX and TXNIP. This resulted in increasing superoxide dismutase (SOD) and CAT activity, TRX expression, up-regulating mitochondrial membrane potential, and augmenting ATP contents and p-Drp1 (Ser616) levels in the cytoplasm. However, it did not bring impact on the expression of p-Drp1 (Ser637) and TXNIP. Activating Drp-1though Acetaldehyde abrogated the effects of Mdivi-1. In addition, the results of in vitro studies employing siRNA-Drp1 and plasmid-Drp1 intervention in HK-2 cells treated with iohexol were consistent with the in vivo experiments. Our findings revealed inhibiting Drp1 phosphorylation at Ser616 could ameliorate iohexol -induced acute kidney injury though alleviating the activation of the TXNIP-NLRP3 inflammasome pathway.

Cope with copper: From molecular mechanisms of cuproptosis to copper-related kidney diseases.

Cuproptosis has recently been identified as a novel regulatory mechanism of cell death. It is characterized by the accumulation of copper in mitochondria and its binding to acylated proteins. These characteristics lead to the downregulation of iron-sulfur cluster proteins and protein toxicity stress, ultimately resulting in cell death. Cuproptosis is distinct from other types of cell death, including necrosis, apoptosis, ferroptosis, and pyroptosis. Cu induces oxidative stress damage, protein acylation, and the oligomerization of acylated TCA cycle proteins. These processes lead to the downregulation of iron-sulfur cluster proteins and protein toxicity stress, disrupting cellular Cu homeostasis, and causing cell death. Cuproptosis plays a significant role in the development and progression of various kidney diseases such as acute kidney injury, chronic kidney disease, diabetic nephropathy, kidney transplantation, and kidney stones. On the one hand, inducers of cuproptosis, such as disulfiram (DSF), chloroquinolone, and elesclomol facilitate cuproptosis by promoting cell oxidative stress. In contrast, inhibitors of Cu chelators, such as tetraethylenepentamine and tetrathiomolybdate, relieve these diseases by inhibiting apoptosis. To summarize, cuproptosis plays a significant role in the pathogenesis of kidney disease. This review comprehensively discusses the molecular mechanisms underlying cuproptosis and its significance in kidney diseases.

Urethral-sparing laparoscopic simple prostatectomy for the treatment of benign prostatic hyperplasia with asymptomatic urethral stricture after urethral stricture surgery.

OBJECTIVE: To evaluate the efficacy of urethral-sparing laparoscopic simple prostatectomy (US-LSP) for the treatment of large-volume (>80 ml) benign prostatic hyperplasia (BPH) with asymptomatic urethral stricture (urethral lumen > 16 Fr) after urethral stricture surgery. METHODS: We retrospectively analyzed clinical data of 39 large-volume BPH patients with asymptomatic urethral stricture after urethral stricture surgery who underwent US-LSP from January 2016 to October 2021. Postoperative follow-ups were scheduled at 1, 3, and 6 months. RESULTS: All patients affected by significant BPH-related lower urinary tract symptoms (LUTS) including 22 cases with asymptomatic anterior urethral stricture and 17 cases with asymptomatic posterior urethral stricture. Median operative time was 118 min (interquartile range [IQR]100-145). Median estimated blood loss was 224 ml (IQR: 190-255). 33 patients(84.6%) avoided continuous bladder irrigation. Postoperative complications occurred in 5 patients (12.8%), including 4 cases with Clavien-Dindo grade 1 and grade 2 and 1 case with grade 3a. During follow-up, US-LSP presented statistically significant improvements in LUTS compared to baseline (P < 0.05). A total of 25 patients had normal ejaculation preoperatively and 3 patients (12%) complained retrograde ejaculation postoperatively. Two patients (5.1%) reported stress urinary incontinence (SUI) and no patient reported aggravated urethral stricture during follow-up. CONCLUSIONS: US-LSP was safe and effective in treating large-volume BPH with asymptomatic urethral stricture after urethral stricture surgery. Meanwhile, US-LSP could reduce the risk of SUI in patients with asymptomatic posterior urethral stricture and maintain ejaculatory function in a high percentage of patients.

U-NTCA: nnUNet and nested transformer with channel attention for corneal cell segmentation.

Background: Automatic segmentation of corneal stromal cells can assist ophthalmologists to detect abnormal morphology in confocal microscopy images, thereby assessing the virus infection or conical mutation of corneas, and avoiding irreversible pathological damage. However, the corneal stromal cells often suffer from uneven illumination and disordered vascular occlusion, resulting in inaccurate segmentation. Methods: In response to these challenges, this study proposes a novel approach: a nnUNet and nested Transformer-based network integrated with dual high-order channel attention, named U-NTCA. Unlike nnUNet, this architecture allows for the recursive transmission of crucial contextual features and direct interaction of features across layers to improve the accuracy of cell recognition in low-quality regions. The proposed methodology involves multiple steps. Firstly, three underlying features with the same channel number are sent into an attention channel named gnConv to facilitate higher-order interaction of local context. Secondly, we leverage different layers in U-Net to integrate Transformer nested with gnConv, and concatenate multiple Transformers to transmit multi-scale features in a bottom-up manner. We encode the downsampling features, corresponding upsampling features, and low-level feature information transmitted from lower layers to model potential correlations between features of varying sizes and resolutions. These multi-scale features play a pivotal role in refining the position information and morphological details of the current layer through recursive transmission. Results: Experimental results on a clinical dataset including 136 images show that the proposed method achieves competitive performance with a Dice score of 82.72% and an AUC (Area Under Curve) of 90.92%, which are higher than the performance of nnUNet. Conclusion: The experimental results indicate that our model provides a cost-effective and high-precision segmentation solution for corneal stromal cells, particularly in challenging image scenarios.

Sodium butyrate alleviates experimental autoimmune prostatitis by inhibiting oxidative stress and NLRP3 inflammasome activation via the Nrf2/HO-1 pathway.

BACKGROUND: Chronic prostatitis and chronic pelvic pain syndrome (CP/CPPS) leads to severe discomfort in males and loss of sperm quality. Current therapeutic options have failed to achieve satisfactory results. Sodium butyrate (NaB) plays a beneficial role in reducing inflammation, increasing antioxidant capacities, and improving organ dysfunction; additionally NaB has good safety prospects and great potential for clinical application. The purpose of the current research was to study the effect of NaB on CP/CPPS and the underlying mechanisms using a mouse model of experimental autoimmune prostatitis (EAP) mice. METHODS: The EAP mouse model was successfully established by subcutaneously injecting a mixture of prostate antigen and complete Freund's adjuvant. Then, EAP mice received daily intraperitoneal injections of NaB (100, 200, or 400 mg/kg/day) for 16 days, from Days 26 to 42. We then explored anti-inflammatory potential mechanisms of NaB by studying the effects of Nrf2 inhibitor ML385 and HO-1 inhibitor zinc protoporphyrin on prostate inflammation and pelvic pain using this model. On Day 42, hematoxylin-eosin staining and dihydroethidium staining were used to evaluate the histological changes and oxidative stress levels of prostate tissues. Chronic pelvic pain was assessed by applying Von Frey filaments to the lower abdomen. The levels of inflammation-related cytokines, such as interleukin (IL)-1ß, IL-6, and tumor necrosis factor were detected by enzyme-linked immunosorbent assay. The regulation of Nrf2/HO-1 signaling pathway and the expression of NLRP3 inflammasome-related protein in EAP mice were detected by western blot analysis assay. RESULTS: Compared with the EAP group, chronic pain development, histological manifestations, and cytokine levels showed that NaB reduced the severity of EAP. NaB treatment could inhibit NLRP3 inflammasome activation. Mechanism studies showed that NaB intervention could alleviate oxidative stress in EAP mice through Nrf2/HO-1 signal pathway. Nrf2/HO-1 pathway inhibitors can inhibit NaB -mediated oxidative stress. The inhibitory effect of NaB on the activation of NLRP3 inflammasome and anti-inflammatory effect can also be blocked by Nrf2/HO-1 pathway. CONCLUSIONS: NaB treatment can alleviates prostatic inflammation and pelvic pain associated with EAP by inhibiting oxidative stress and NLRP3 inflammasome activation via the Nrf2/HO-1 pathway. NaB has the potential as an effective agent in the treatment of EAP.

Modular preparation of biphenyl triazoles via click chemistry as non-competitive hyaluronidase inhibitors.

Hyaluronidase is a promising target in drug discovery, given its overexpression in a range of physiological and pathological processes, including tumor migration, skin aging, sagging, and wrinkling, as well as inflammation and bacterial infections. In this study, to identify novel hyaluronidase inhibitors, we applied click chemistry for the modular synthesis of 370 triazoles in 96-well plates, starting with biphenyl azide. Utilizing an optimized turbidimetric screening assay in microplates, we identified Fmoc-containing triazoles 5 and 6, as well as quinoline-containing triazoles 15 and 16, as highly effective hyaluronidase inhibitors. Subsequent research indicated that these triazoles potentially interact with a novel binding site of hyaluronidase. Notably, these inhibitors displayed minimal cytotoxicity and showed promising anti-inflammatory effects in LPS-stimulated macrophages. Remarkably, compound 6 significantly reduced NO release by 74 % at a concentration of 20 µM.

Analysis of the main indicators and risk factors of ultrasonic shear wave elastography for the diagnosis of osteoarthritis among adults.

Objective: This study was conducted to explore the main indicators of ultrasonic shear wave elastography (SWE) for the diagnosis of osteoarthritis (OA) and its influencing factors. Methods: We collected 910 patients between January 2018 and November 2023 from the department of ultrasound, Third Hospital of Hebei Medical University. Logistic regression was used to analyze the effects of age, gender, body mass index (BMI), smoking, alcohol, hypertension and diabetes on the diagnosis of OA by SWE. Results: The results showed that medial meniscal projection distance (MMPD) and OA had a positively correlated dose-response relationship (OR = 2.12, 95%CI (1.53, 3.95), trend p < 0.05). Also, medial meniscus elastometry (MME) had a positive dose-response correlation with OA (OR = 8.98, 95%CI (3.89, 11.52), trend p < 0.05). In addition, regarding the analysis of factors influencing the diagnosis of OA, the risk of OA was significantly higher in the older age group [OR = 1.11, 95%CI (1.01, 1.25)], and the risk of diagnosis in OA was high in the high BMI group [OR = 1.8, 95%CI (1.23, 3.01)]. Conclusion: In diagnosing OA, MMPD and MME can be used as reliable indicators, while people of advanced age and high BMI have a high possibility diagnosed with OA.

Framework of compressive sensing and data compression for 4D-STEM.

Four-dimensional Scanning Transmission Electron Microscopy (4D-STEM) is a powerful technique for high-resolution and high-precision materials characterization at multiple length scales, including the characterization of beam-sensitive materials. However, the field of view of 4D-STEM is relatively small, which in absence of live processing is limited by the data size required for storage. Furthermore, the rectilinear scan approach currently employed in 4D-STEM places a resolution- and signal-dependent dose limit for the study of beam sensitive materials. Improving 4D-STEM data and dose efficiency, by keeping the data size manageable while limiting the amount of electron dose, is thus critical for broader applications. Here we introduce a general method for reconstructing 4D-STEM data with subsampling in both real and reciprocal spaces at high fidelity. The approach is first tested on the subsampled datasets created from a full 4D-STEM dataset, and then demonstrated experimentally using random scan in real-space. The same reconstruction algorithm can also be used for compression of 4D-STEM datasets, leading to a large reduction (100 times or more) in data size, while retaining the fine features of 4D-STEM imaging, for crystalline samples.