BACE1 inhibitors from the fruits of Alpinia oxyphylla have efficacy to treat T2DM-related cognitive disorder.

The fruits of Alpinia oxyphylla (Alpiniae Oxyphyllae Fructus, AOF) are one of the "Four Famous South Medicines" in China. In this study, beta-site amyloid protein precursor cleaving enzyme 1 (BACE1) was applied to explore the active components in AOF responsible for type 2 diabetes mellitus (T2DM)-related cognitive disorder. As a result, 24 compounds including three unreported ones (1, 3, 4) were isolated from AOF. Compound 1 is an unusual carbon­carbon linked diarylheptanoid dimer, and compound 4 is the first case of 3,4-seco-eudesmane sesquiterpenoid with a 5/6-bicyclic skeleton. Four diarylheptanoids (3, 5-7), one flavonoid (9) and two sesquiterpenoids (14 and 20) showed BACE1 inhibitory activity, of which the most active 6 was revealed to be a non-competitive and anti-competitive mixed inhibitor. Docking simulation suggested that OH-4' of 6 played important roles in maintaining activity by forming hydrogen bonds with Ser36 and Ile126 residues. Compounds 3, 5, 9 and 20 displayed neuroprotective effects against amyloid ß (Aß)-induced damage in BV2 cells. Mechanism study revealed that compounds 5 and 20 downregulated the expression of BACE1 and upregulated the expression of Lamp2 to exert effects. Thus, the characteristic diarylheptanoids and sesquiterpenoids in AOF had the efficacy to alleviate T2DM-related cognitive disorder by inhibiting BACE1 activity and reversing Aß-induced neuronal damage.

Xuanbi Yuyang Decoction Ameliorates DSS-Induced Colitis by Inhibiting Pyroptosis via Blocking of IL-17 Pathway Activation.

Background: Ulcerative colitis (UC), a highly relapsing non-specific disease, is difficult to cure completely. The investigation aims to determine the protective effect and potential action mechanism of Xuanbi yuyang decoction (XBD) on UC. Methods: The chemical composition of XBD was determined through non-targeted metabolomics analysis. Subsequently, experimental mice were orally given 3% DSS for 6 days, followed by XBD treatment (0.3 mL, 0.4 mL). In vitro, the human colon epithelial cells were co-treated with DSS and medicated serum. The therapeutic effects of XBD on UC were evaluated in vivo and vitro. The mechanisms of XBD against UC were determined by detecting hallmarks related to pyroptosis and Interleukin (IL)-17 pathways using Western blot and ELISA. The recombinant human interleukin 17A (rhIL17A) and was applied for further verifying the effect of XBD on IL-17 pathway in UC cells. Results: XBD supplementation restored DSS-induced weight loss, colon shortening and tissue damage, and reduced DAI. Moreover, XBD enhanced viability, repaired the intestinal mucosal barrier of colitis, decreased pro-inflammatory cytokines levels, and inhibited pyroptosis. Additionally, DSS increased the expression of IL-17 pathway was and cytokines (IL-17A, IL-6), which were blocked by XBD treatment. The rhIL17A treatment attenuated protective effect against DSS-induced colitis and could also enhance pyroptosis. Conclusion: XBD has a favorable protective effect against DSS-induced colitis through restraining pyroptosis via inhibition of IL-17 signaling pathway activation, suggesting XBD may be a new and effective treatment therapy for UC.

Association of proton-density fat fraction with osteoporosis: a systematic review and meta-analysis.

This study aimed to evaluate the correlation between measuring proton-density fat fraction (PDFF) in bone marrow using multi-echo chemical shift-encoded MRI and osteoporosis, assessing its effectiveness as a biomarker for osteoporosis. A systematic review was conducted by two independent researchers using Cochrane, PubMed, EMBASE, and Web of Science databases up to December 2023. Quality assessments were evaluated using the Cochrane risk of bias tool and the Agency for Healthcare Research and Quality (AHRQ) checklist. Fourteen studies involving 1495 patients were analyzed. The meta-analysis revealed a significant difference in PDFF values between the osteoporosis/osteopenia group and the normal control group, with a mean difference of 11.04 (95% CI: 9.17 to 12.92, Z=11.52, P < 0.00001). Measuring PDFF via MRI shows potential as an osteoporosis biomarker and may serve as a risk factor for osteoporosis. This insight opens new avenues for future diagnostic and therapeutic strategies, potentially improving osteoporosis management and patient care. OBJECTIVE: This study aims to assess the correlation between measuring proton-density fat fraction (PDFF) in bone marrow using multi-echo chemical shift-encoded MRI and osteoporosis, evaluating its effectiveness as a biomarker for osteoporosis. MATERIALS AND METHODS: This systematic review was carried out by two independent researchers using Cochrane, PubMed, EMBASE, and Web of Science databases up to December 2023. Quality assessments were evaluated using the Cochrane risk of bias tool and the Agency for Healthcare Research and Quality (AHRQ) checklist. RESULTS: Fourteen studies involving 1495 patients were analyzed. The meta-analysis revealed a significant difference in PDFF values between the osteoporosis/osteopenia group and the normal control group, with a (MD = 11.04, 95% CI: 9.17 to 12.92, Z = 11.52, P < 0.00001). Subgroup analyses indicated that diagnostic methods, gender, and echo length did not significantly impact the PDFF-osteoporosis association. CONCLUSION: PDFF measurement via MRI shows potential as an osteoporosis biomarker and may serve as a risk factor for osteoporosis. This insight opens new avenues for future diagnostic and therapeutic strategies, potentially improving osteoporosis management and patient care.

The Open Pediatric Cancer Project.

Background: In 2019, the Open Pediatric Brain Tumor Atlas (OpenPBTA) was created as a global, collaborative open-science initiative to genomically characterize 1,074 pediatric brain tumors and 22 patient-derived cell lines. Here, we extend the OpenPBTA to create the Open Pediatric Cancer (OpenPedCan) Project, a harmonized open-source multi-omic dataset from 6,112 pediatric cancer patients with 7,096 tumor events across more than 100 histologies. Combined with RNA-Seq from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA), OpenPedCan contains nearly 48,000 total biospecimens (24,002 tumor and 23,893 normal specimens). Findings: We utilized Gabriella Miller Kids First (GMKF) workflows to harmonize WGS, WXS, RNA-seq, and Targeted Sequencing datasets to include somatic SNVs, InDels, CNVs, SVs, RNA expression, fusions, and splice variants. We integrated summarized CPTAC whole cell proteomics and phospho-proteomics data, miRNA-Seq data, and have developed a methylation array harmonization workflow to include m-values, beta-vales, and copy number calls. OpenPedCan contains reproducible, dockerized workflows in GitHub, CAVATICA, and Amazon Web Services (AWS) to deliver harmonized and processed data from over 60 scalable modules which can be leveraged both locally and on AWS. The processed data are released in a versioned manner and accessible through CAVATICA or AWS S3 download (from GitHub), and queryable through PedcBioPortal and the NCI's pediatric Molecular Targets Platform. Notably, we have expanded PBTA molecular subtyping to include methylation information to align with the WHO 2021 Central Nervous System Tumor classifications, allowing us to create research- grade integrated diagnoses for these tumors. Conclusions: OpenPedCan data and its reproducible analysis module framework are openly available and can be utilized and/or adapted by researchers to accelerate discovery, validation, and clinical translation.

LncRNA SNHG12 suppresses adipocyte inflammation and insulin resistance by regulating the HDAC9/Nrf2 axis.

Obesity is often associated with low-grade inflammation. The incidence of obesity has increased annually worldwide, which seriously affects human health. A previous study indicated that long noncoding RNA SNHG12 was downregulated in obesity. Nevertheless, the role of SNHG12 in obesity remains to be elucidated. In this study, qRT-PCR, western blot, and ELISA were utilized to examine the gene and protein expression. Flow cytometry was employed to investigate the M2 macrophage markers. RNA pull-down assay and RIP were utilized to confirm the interactions of SNHG12, hnRNPA1, and HDAC9. Eventually, a high-fat diet-fed mouse model was established for in vivo studies. SNHG12 overexpression suppressed adipocyte inflammation and insulin resistance and promoted M2 polarization of macrophages that was caused by TNF-α treatment. SNHG12 interacted with hnRNPA1 to downregulate HDAC9 expression, which activated the Nrf2 signaling pathway. HDAC9 overexpression reversed the effect of SNHG12 overexpression on inflammatory response, insulin resistance, and M2 phenotype polarization. Overexpression of SNHG12 improved high-fat diet-fed mouse tissue inflammation. This study revealed the protective effect of SNHG12 against adipocyte inflammation and insulin resistance. This result further provides a new therapeutic target for preventing inflammation and insulin resistance in obesity.

Differentiating between benign and malignant breast lesions using dual-energy CT-based model: development and validation.

OBJECTIVES: To develop and validate a dual-energy CT (DECT)-based model for noninvasively differentiating between benign and malignant breast lesions detected on DECT. MATERIALS AND METHODS: This study prospectively enrolled patients with suspected breast cancer who underwent dual-phase contrast-enhanced DECT from July 2022 to July 2023. Breast lesions were randomly divided into the training and test cohorts at a ratio of 7:3. Clinical characteristics, DECT-based morphological features, and DECT quantitative parameters were collected. Univariate analyses and multivariate logistic regression were performed to determine independent predictors of benign and malignant breast lesions. An individualized model was constructed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic ability of the model, whose calibration and clinical usefulness were assessed by calibration curve and decision curve analysis. RESULTS: This study included 200 patients (mean age, 49.9 ± 11.9 years; age range, 22-83 years) with 222 breast lesions. Age, lesion shape, and the effective atomic number (Zeff) in the venous phase were significant independent predictors of breast lesions (all p < 0.05). The discriminative power of the model incorporating these three factors was high, with AUCs of 0.844 (95%CI 0.764-0.925) and 0.791 (95% CI 0.647-0.935) in the training and test cohorts, respectively. The constructed model showed a preferable fitting (all p > 0.05 by the Hosmer-Lemeshow test) and provided enhanced net benefits than simple default strategies within a wide range of threshold probabilities in both cohorts. CONCLUSION: The DECT-based model showed a favorable diagnostic performance for noninvasive differentiation between benign and malignant breast lesions detected on DECT. CRITICAL RELEVANCE STATEMENT: The combination of clinical and morphological characteristics and DECT-derived parameter have the potential to identify benign and malignant breast lesions and it may be useful for incidental breast lesions on DECT to decide if further work-up is needed. KEY POINTS: It is important to characterize incidental breast lesions on DECT for patient management. DECT-based model can differentiate benign and malignant breast lesions with good performance. DECT-based model is a potential tool for distinguishing breast lesions detected on DECT.

A novel method for highly linear gradient coil design based on stream function.

BACKGROUND: Magnetoencephalography (MEG) and magnetic resonance imaging (MRI) are non-invasive imaging techniques that offer effective means for disease diagnosis. A more straightforward and optimized method is presented for designing gradient coils which are pivotal parts of the above imaging systems. PURPOSE: A novel design method based on stream function combining an optimization algorithm is proposed to obtain highly linear gradient coil. METHODS: Two-dimensional Fourier expansion of the current field on the surface where the coil is located and the equipotential line of the expansion term superposition according to the number of turns of the coil are used to represent the coil shape. Particle swarm optimization is utilized to optimize the coil shape while linearity and field uniformity are used as parameters to evaluate the coil performance. Through this method, the main parameters such as input current distribution region, coil turns, desired magnetic field strength, expansion order and iteration times can be combined in a given solution space to optimize coil design. RESULTS: Simulation results show that the maximum linearity spatial deviation of the designed bi-planar x-gradient coil compared with that of target field method is reduced from 14% to 0.54%, and that of the bi-planar z-gradient coil is reduced from 8.98% to 0.52%. Similarly, that of the cylindrical x-gradient coil is reduced from 2% to 0.1%, and that of the cylindrical z-gradient coil is reduced from 0.87% to 0.45%. The similar results are found in the index of inhomogeneity error. Moreover, it has also been verified experimentally that the result of measured magnetic field is consist with simulated result. CONCLUSIONS: The proposed method provides a straightforward way that simplifies the design process and improves the linearity of designed gradient coil, which could be beneficial to realize better magnetic field in engineering applications.

Validation of an AI-Powered Automated X-ray Bone Age Analyzer in Chinese Children and Adolescents: A Comparison with the Tanner-Whitehouse 3 Method.

INTRODUCTION: Automated bone age assessment (BAA) is of growing interest because of its accuracy and time efficiency in daily practice. In this study, we validated the clinical applicability of a commercially available artificial intelligence (AI)-powered X-ray bone age analyzer equipped with a deep learning-based automated BAA system and compared its performance with that of the Tanner-Whitehouse 3 (TW-3) method. METHODS: Radiographs prospectively collected from 30 centers across various regions in China, including 900 Chinese children and adolescents, were assessed independently by six doctors (three experts and three residents) and an AI analyzer for TW3 radius, ulna, and short bones (RUS) and TW3 carpal bone age. The experts' mean estimates were accepted as the gold standard. The performance of the AI analyzer was compared with that of each resident. RESULTS: For the estimation of TW3-RUS, the AI analyzer had a mean absolute error (MAE) of 0.48 ± 0.42. The percentage of patients with an absolute error of < 1.0 years was 86.78%. The MAE was significantly lower than that of rater 1 (0.54 ± 0.49, P = 0.0068); however, it was not significant for rater 2 (0.48 ± 0.48) or rater 3 (0.49 ± 0.46). For TW3 carpal, the AI analyzer had an MAE of 0.48 ± 0.65. The percentage of patients with an absolute error of < 1.0 years was 88.78%. The MAE was significantly lower than that of rater 2 (0.58 ± 0.67, P = 0.0018) and numerically lower for rater 1 (0.54 ± 0.64) and rater 3 (0.50 ± 0.53). These results were consistent for the subgroups according to sex, and differences between the age groups were observed. CONCLUSION: In this comprehensive validation study conducted in China, an AI-powered X-ray bone age analyzer showed accuracies that matched or exceeded those of doctor raters. This method may improve the efficiency of clinical routines by reducing reading time without compromising accuracy.

Assessing bone age, or how developed a child's skeleton is, is important in medical care, but the standard method can be time-consuming. Using AI to automatically assess bone age from X-ray images may improve efficiency without reducing accuracy. In this study, we evaluated how well an AI-powered X-ray bone age analyzer performed compared to the established Tanner­Whitehouse 3 (TW-3) method. X-ray images from 900 Chinese children and adolescents were collected from 30 centers. Six doctors (three experts, three residents) and the AI system independently assessed the TW-3 radius, ulna, and short bones (RUS) and TW-3 carpal bone age. The experts' assessments were considered the gold standard. The AI analyzer had an average error of 0.48 years for TW3-RUS bone age, with 87% of assessments within 1 year of the experts. For TW3 carpal bone age, the AI had an average error of 0.48 years, with 89% within 1 year. These results were similar to or better than those of the resident raters. These findings show the AI-powered analyzer can assess bone age as accurately as human raters. This technology may improve clinical efficiency by reducing the time required for bone age assessments without compromising accuracy.

Alkaline Phosphatase Activated Near-Infrared Frequency Upconversion Photosensitizers for Tumor Photodynamic Therapy.

Photodynamic therapy (PDT) is a promising anticancer method due to its noninvasive features, high efficiency, and superior accuracy. The activated near-infrared upconversion photosensitizer has a high tissue penetration depth and could be explicitly released with minimal side effects. Therefore, we designed and synthesized a series of Br-substituted compounds (NFh-Br) based on the near-infrared upconversion hemicyanine dye. The heavy atomic effect improves the generation of 1O2 and upconversion luminous efficiency. Especially, NFh-Br11 exhibited an excellent 1O2 generation rate under 808 nm excitation and effectively killed tumor cells in vitro, and the alkaline phosphatase (ALP)-activatable photosensitizer (NFh-ALP) was obtained by modifying the NFh-Br11. NFh-ALP could be activated by ALP and release NFh-Br11, which induces apoptosis of tumor cells and has outstanding anticancer effects in vitro and in vivo. This work could provide a strategy for designing activatable upconversion photosensitizers.

Neoadjuvant anthracycline followed by toripalimab combined with nab-paclitaxel in patients with early triple-negative breast cancer (NeoTENNIS): a single-arm, phase II study.

Background: Toripalimab, a novel PD-1 antibody, is approved for treatment of multiple solid tumors; however, its neoadjuvant use with chemotherapy for triple-negative breast cancer (TNBC) remains unevaluated. Additionally, induction chemotherapy followed by de-escalation of neoadjuvant immunotherapy remains underexplored. Therefore, we conducted a phase II trial investigating a novel neoadjuvant chemoimmunotherapy regimen including de-escalation of immunotherapy for early-stage TNBC. Methods: Chemotherapy and anti-PD-1 therapy were sequentially administered in a neoadjuvant setting to female patients with histologically confirmed stage II-III TNBC between June 9, 2020, and March 24, 2022. Patients received neoadjuvant therapy with four cycles of epirubicin-cyclophosphamide every 2 weeks, followed by toripalimab (240 mg) every 3 weeks plus nab-paclitaxel weekly for 12 weeks. The primary endpoint was total pathological complete response (tpCR; ypT0/is ypN0). Key secondary endpoints included breast pCR (bpCR; ypT0/is), event-free survival and biomarker analysis. Safety was also assessed. This study was registered with ClinicalTrials.gov (NCT04418154). Findings: Among 70 enrolled patients (median age, 51 years; 62.9% stage III), 66 completed treatment without progression and subsequently underwent surgery. The percentages of patients with a tpCR and bpCR were 39 of 70 (55.7%, 95% confidence interval [CI]: 43.3-67.6) and 41 of 70 (58.6%, 95% CI 46.2-70.2), respectively. Sixteen (22.9%) patients experienced grade ≥3 adverse events (AEs), frequently neutropenia (12, 17.1%) and leukopenia (11, 15.7%). The most common immune-related AE was hypothyroidism (5, 7.1%, all grade 1-2). Interpretation: Including 12 weeks of toripalimab in neoadjuvant chemotherapy conferred encouraging activity and manageable toxicity in patients with early TNBC, and this regimen warrants further investigation. Funding: National Natural Science Foundation of China, Junshi Biosciences, and Jiangsu Hengrui Pharmaceuticals.

New labdane diterpenoids from Alpinia galanga: A new type of GLP-1 secretagogues targeting the PKA-CREB and PI3K-Akt signaling axes.

Glucagon-like peptide-1 (GLP-1) secretagogues are fascinating pharmacotherapies to overcome the defects of GLP-1 analogs and dipeptidyl peptidase-4 (DPP-4) inhibitors in treating diabetes and obesity. To discover new GLP-1 secretagogues from natural sources, alpigalangols A-Q (1-17), 17 new labdane diterpenoids including four unusual nor-labdane and N-containing ones, were isolated from the fruits of Alpinia galanga. Most of the isolates showed GLP-1 promotive effects in NCl-H716 cells, of which compounds 3, 4, 12, and 14-17 were revealed with high promoting rates of 246.0%-413.8% at 50 µM. A mechanistic study manifested that the most effective compound 12 upregulated the mRNA expression of Gcg and Pcsk1, and the protein phosphorylation of PKA, CREB, and GSK3ß, but was inactive on GPBAR and GPR119 receptors. Network pharmacology analysis indicated that the PI3K-Akt pathway was involved in the GLP-1 stimulation of 12, which was highly associated with AKT1, CASP3, PPARG, and ICAM1 proteins. This study suggests that A. galanga is rich in diverse labdane diterpenoids with GLP-1 promoting effects, representing a new type of antidiabetic candidates from natural sources.

Altered Brain Glymphatic Function at Diffusion-Tensor MRI in Pre-cirrhotic Metabolic Dysfunction-Associated Fatty Liver Disease.

RATIONALE AND OBJECTIVES: To evaluate glymphatic function changes and their relationships with clinical features in patients with metabolic dysfunction-associated fatty liver disease (MAFLD), thereby facilitating early intervention before this disease progresses to cirrhosis. MATERIALS AND METHODS: A cross-sectional cohort of 46 pre-cirrhotic MAFLD patients and 30 age-, sex-, and education-matched controls was enrolled, with diffusion-tensor imaging (DTI) data, laboratory and neurocognitive scores collected. The DTI analysis along the perivascular space (DTI-ALPS) index was computed for qualifying glymphatic function. Generalized linear model and partial correlation analyses were applied to evaluate relationships between the ALPS index and clinical variables. RESULTS: MAFLD group exhibited a decreased ALPS index and increased diffusivity along the y-axis in the projection fiber compared to the controls. The altered ALPS index was associated with clock drawing test (CDT) score (3.931 [0.914, 6.947], P = 0.011) and was correlated with diastolic pressure level (r = -0.315, P = 0.033) in MAFLD group. The relationships of ALPS index with CDT score (6.263 [2.069, 10.458], P = 0.003) and diastolic pressure level (r = -0.518, P = 0.014) remained in the MAFLD with metabolic syndrome (MetS) group. Furthermore, the ALPS index was even associated with Auditory Verbal Learning Test-Immediate recall score (-23.853 [-45.417, -2.289], P = 0.030) in MAFLD with MetS group. CONCLUSION: MAFLD patients may have a glymphatic dysfunction prior to cirrhosis, and this alteration may be related to cognition and diastolic pressure. Glymphatic dysfunction has a more severe impact on cognition when MAFLD patient is accompanied by MetS.

Predicting papillary thyroid microcarcinoma in American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 3 nodules: radiomics analysis based on intratumoral and peritumoral ultrasound images.

Background: A subset of patients undergoing thyroid surgery for presumed benign thyroid disease presented with papillary thyroid microcarcinoma (PTMC). A non-invasive and precise method for early recognition of PTMC are urgently needed. The aim of this study was to construct and validate a nomogram that combines intratumoral and peritumoral radiomics features as well as clinical features for predicting PTMC in the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 3 nodules using ultrasonography. Methods: A retrospective review was conducted on a cohort of 221 patients who presented with ACR TI-RADS 3 nodules. These patients were subsequently pathologically diagnosed with either PTMC or benign thyroid nodules. These patients were randomly divided into a training and test cohort with an 8:2 ratio for developing the clinical model, intratumor-region model, peritumor-region model and the combined-region model respectively. The radiomics features were extracted from ultrasound (US) images of each patient. We employed K-nearest neighbor (KNN) model as the base model for building the radiomics signature and clinical signature. Finally, a radiomics-clinical nomogram that combined intratumoral and peritumoral radiomics features as well as clinical features was developed. The prediction performance of each model was assessed by the area under the curve (AUC), sensitivity, specificity and calibration curve. Results: A total of 23 radiomics features were selected to develop radiomics models. The combined-region radiomics model showed favorable prediction efficiency in both the training dataset (AUC: 0.955) and the test dataset (AUC: 0.923). A radiomics-clinical nomogram was constructed and achieved excellent calibration and discrimination, which yielded an AUC value of 0.950, a sensitivity of 0.950 and a specificity of 0.920. Conclusions: This study proposed the nomogram that contributes to the accurate and intuitive identification of PTMC in ACR TI-RADS 3 nodules.

Anti-virus activity and mechanisms of natural polysaccharides from medicinal herbs.

There has been a sudden increase in viral diseases, such as coronavirus disease 2019 (COVID-19), causing significant harm to human and animal well-being, as well as economic development. Medicinal herbs, with a history of thousands of years in clinical use, contain versatile polysaccharides as one of their primary compounds. This review offers an overview of the antiviral effects of polysaccharides from medicinal herbs on viruses in humans, poultry, swine and aquaculture in recent years. The mechanism of these antiviral polysaccharides, involved in hindering various stages of the viral life cycle thereby blocking virus infection, is summarized. The review also explores other underlying mechanisms of antiviral effects, such as enhancing the immune response, regulating inflammatory reactions, balancing gut flora, reducing oxidative stress, and suppressing apoptosis through various corresponding signaling pathways. The structure-function relationships discussed in this article also aid in understanding the antiviral mechanism of natural polysaccharides, indicating the need for more in-depth research and analysis. Natural polysaccharides from medicinal herbs have emerged as valuable resources in the fight against viral infections, exhibiting high effectiveness. This review emphasizes the promising role of polysaccharides from medicinal herbs as potential candidates for blocking viral infections in humans and animals.

Integrative analysis of COL6A3 in lupus nephritis: insights from single-cell transcriptomics and proteomics.

Introduction: Lupus nephritis (LN), a severe complication of systemic lupus erythematosus (SLE), presents significant challenges in patient management and treatment outcomes. The identification of novel LN-related biomarkers and therapeutic targets is critical to enhancing treatment outcomes and prognosis for patients. Methods: In this study, we analyzed single-cell expression data from LN (n=21) and healthy controls (n=3). A total of 143 differentially expressed genes were identified between the LN and control groups. Then, proteomics analysis of LN patients (n=9) and control (SLE patients without LN, n=11) revealed 55 differentially expressed genes among patients with LN and control group. We further utilizes protein-protein interaction network and functional enrichment analyses to elucidate the pivotal role of COL6A3 in key signaling pathways. Its diagnostic value is evaluate through its correlation with disease progression and renal function metrics, as well as Receiver Operating Characteristic Curve (ROC) analysis. Additionally, immunohistochemistry and qPCR experiments were performed to validate the expression of COL6A3 in LN. Results: By comparison of single-cell and proteomics data, we discovered that COL6A3 is significantly upregulated, highlighting it as a critical biomarker of LN. Our findings emphasize the substantial involvement of COL6A3 in the pathogenesis of LN, particularly noting its expression in mesangial cells. Through comprehensive protein-protein interaction network and functional enrichment analyses, we uncovered the pivotal role of COL6A3 in key signaling pathways including integrin-mediated signaling pathways, collagen-activated signaling pathways, and ECM-receptor interaction, suggesting potential therapeutic targets. The diagnostic utility is confirmed by its correlation with disease progression and renal function metrics of the glomerular filtration rate. ROC analysis further validates the diagnostic value of COL6A3, with the area under the ROC values of 0.879 in the in-house cohort, and 0.802 and 0.915 in tubular and glomerular external cohort samples, respectively. Furthermore, immunohistochemistry and qPCR experiments were consistent with those obtained from the single-cell RNA sequencing and proteomics studies. Discussion: These results proved that COL6A3 is a promising biomarker and therapeutic target, advancing personalized medicine strategies for LN.

TET1-Lipid Nanoparticle Encapsulating Morphine for Specific Targeting of Peripheral Nerve for Pain Alleviation.

Background: Opioids are irreplaceable analgesics owing to the lack of alternative analgesics that offer opioid-like pain relief. However, opioids have many undesirable central side effects. Restricting opioids to peripheral opioid receptors could reduce those effects while maintaining analgesia. Methods: To achieve this goal, we developed Tet1-LNP (morphine), a neural-targeting lipid nanoparticle encapsulating morphine that could specifically activate the peripheral opioid receptor in the dorsal root ganglion (DRG) and significantly reduce the side effects caused by the activation of opioid receptors in the brain. Tet1-LNP (morphine) were successfully prepared using the thin-film hydration method. In vitro, Tet1-LNP (morphine) uptake was assessed in differentiated neuron-like PC-12 cells and dorsal root ganglion (DRG) primary cells. The uptake of Tet1-LNP (morphine) in the DRGs and the brain was assessed in vivo. Von Frey filament and Hargreaves tests were used to assess the antinociception of Tet1-LNP (morphine) in the chronic constriction injury (CCI) neuropathic pain model. Morphine concentration in blood and brain were evaluated using ELISA. Results: Tet1-LNP (morphine) had an average size of 131 nm. Tet1-LNP (morphine) showed high cellular uptake and targeted DRG in vitro. CCI mice treated with Tet1-LNP (morphine) experienced prolonged analgesia for nearly 32 h compared with 3 h with free morphine (p < 0.0001). Notably, the brain morphine concentration in the Tet1-LNP (morphine) group was eight-fold lower than that in the morphine group (p < 0.0001). Conclusion: Our study presents a targeted lipid nanoparticle system for peripheral neural delivery of morphine. We anticipate Tet1-LNP (morphine) will offer a safe formulation for chronic neuropathic pain treatment, and promise further development for clinical applications.

Association of podocyte ultrastructural changes with proteinuria and pathological classification in type 2 diabetic nephropathy.

AIMS: Podocyte injury plays an essential role in the progression of diabetic nephropathy (DN). The associations between the ultrastructural changes of podocyte with proteinuria and the pathological classification of DN proposed by Renal Pathology Society (RPS) have not been clarified in patients with type 2 diabetic nephropathy (T2DN). METHODS: We collected 110 patients with kidney biopsy-confirmed T2DN at Peking University First Hospital from 2017 to 2022. The morphometric analysis on the podocyte foot process width (FPW) and podocyte detachment (PD) as markers of podocyte injury was performed, and the correlations between the ultrastructural changes of podocytes with severity of proteinuria and the RPS pathological classification of DN were analyzed. RESULTS: Mean FPW was significantly broader in the group of T2DN patients with nephrotic proteinuria (565.1 nm) than those with microalbuminuria (437.4 nm) or overt proteinuria (494.6 nm). The cut-off value of FPW (> 506 nm) could differentiate nephrotic proteinuria from non-nephrotic proteinuria with a sensitivity of 75.3% and a specificity of 75.8%. Percentage of PD was significantly higher in group of nephrotic proteinuria (3.2%) than that in microalbuminuria (0%) or overt proteinuria (0.2%). FPW and PD significantly correlated with proteinuria in T2DN (r = 0.473, p < 0.001 and r = 0.656, P < 0.001). FPW and PD correlated with RPS pathological classification of T2DN (r = 0.179, P = 0.014 and r = 0.250, P = 0.001). FPW value was increased significantly with more severe DN classification (P for trend =0.007). The percentage of PD tended to increase with more severe DN classification (P for trend = 0.017). CONCLUSIONS: Podocyte injury, characterized by FPW broadening and PD, was associated with the severity of proteinuria and the pathological classification of DN.

Online monitoring lignocellulosic particles by focus beam reflectance measurement for efficient bioprocessing.

Lignocellulose presents a promising alternative to fossil fuels. Monitoring the mass and size changes of lignocellulosic particles without disrupting the process can assist in adjusting pretreatment and enzymatic hydrolysis, where conventional sieving methods fall short. A method utilizing focused beam reflectance measurement (FBRM) was developed to establish mathematical correlations between FBRM chord information (chord length and count) and particle characteristics (weight and size) quantified through sieving. Results indicate particle size exhibits a linear correlation with the square weighted median chord length (Lsqr) with R2 at 0.93. Further, real-time bulk particle mass can be predicted using Lsqr and chord count (R2 0.98). These correlations are applicable in range 53 µm to 358.5 µm. Real-time monitoring of enzymatic hydrolysis of corn stalks has demonstrated the practical applicability of FBRM. This study introduces a novel approach for online characterization of lignocellulosic particles, thereby enhancing lignocellulosic biorefineries.

GC/HRMS Analysis of E-Liquids Complements In Vivo Modeling Methods and can Help to Predict Toxicity.

Tobacco smoking is a major risk factor for disease development, with the user inhaling various chemicals known to be toxic. However, many of these chemicals are absent before tobacco is "burned". Similar, detailed data have only more recently being reported for the e-cigarette with regards to chemicals present before and after the e-liquid is "vaped." Here, zebrafish were dosed with vaped e-liquids, while C57-BL/6J mice were vaped using nose-cone only administration. Preliminary assessments were made using e-liquids and GC/HRMS to identify chemical signatures that differ between unvaped/vaped and flavored/unflavored samples. Oxidative stress and inflammatory immune cell response assays were then performed using our in vivo models. Chemical signatures differed, e.g., between unvaped/vaped samples and also between unflavored/flavored e-liquids, with known chemical irritants upregulated in vaped and unvaped flavored e-liquids compared with unflavored e-liquids. However, when possible respiratory irritants were evaluated, these agents were predominantly present in only the vaped e-liquid. Both oxidative stress and inflammatory responses were induced by a menthol-flavored but not a tobacco-flavored e-liquid. Thus, chemical signatures differ between unvaped versus vaped e-liquid samples and also between unflavored versus flavored e-liquids. These flavors also likely play a significant role in the variability of e-liquid characteristics, e.g., pro-inflammatory and/or cytotoxic responses.

E3 ligase FBXO22 is not significant for spermatogenesis and male fertility in mice.

BACKGROUND: F-box-only protein 22 (FBXO22), an important substrate receptor of the SKP1-Cullin-F-box (SCF) ubiquitin ligases, has been reported to be involved in many biological processes, including tumorigenesis, neurological disorders, cellular senescence, and DNA damage. However, the specific role of FBXO22 during spermatogenesis is poorly understood. METHODS: We produced Fbxo22 conditional knockout (cKO) and global knockout (KO) mice and assessed their sperm masurements using a computer-assisted sperm analysis (CASA) system. Additionally, we conducted histologic staining and immunostaining to examine the impact of Fbxo22 loss on spermatogenesis. RESULTS: Our results revealed that there were no notable differences in semen quality, fertility test results, or histologic findings in Fbxo22-KO and Fbxo22-cKO mice compared to the control group. CONCLUSIONS: Our study demonstrated that Fbxo22 is not significant for spermatogenesis or male fertility in mice. These findings will help researchers avoid redundant efforts and serve as a foundational resource for genetic studies on human fertility.