NT-proBNP point-of-care testing for predicting mortality in end-stage renal disease: A survival analysis.

This study examines the predictive value of elevated N-terminal-pro brain natriuretic peptide (NT-pro BNP) levels for mortality among patients with end-stage renal disease (ESRD). Data from 768 ESRD patients, excluding those with cancer or lost follow-up, were analyzed using Kaplan-Meier curves and Cox proportional hazards models over three years. Results indicated that patients with very high NT-pro BNP levels had shorter average survival times and a significantly higher risk of mortality (hazard ratio 1.43). Advanced age, ICU admission, and comorbidities like cerebrovascular diseases and chronic obstructive pulmonary disease also contributed to increased mortality risks. Thus, elevated NT-pro BNP is an independent risk factor for mortality in ESRD patients.

Optimizing ultrafast dynamic contrast-enhanced MRI scan duration in the differentiation of benign and malignant breast lesions.

OBJECTIVE: To determine the optimal scan duration for ultrafast DCE-MRI in effectively differentiating benign from malignant breast lesions. METHODS: The study prospectively recruited participants who underwent breast ultrafast DCE-MRI from September 2021 to March 2023. A 30-phase breast ultrafast DCE-MRI on a 3.0-T MRI system was conducted with a 4.5-s temporal resolution. Scan durations ranged from 40.5 s to 135.0 s, during which the analysis is performed at three-phase intervals, forming eight dynamic sets (scan duration [SD]40.5s: 40.5 s, SD54s: 54.0 s, SD67.5s: 67.5 s, SD81s: 81.0 s, SD94.5s: 94.5 s, SD108s: 108.0 s, SD121.5s: 121.5 s, and SD135s: 135.0 s). Two ultrafast DCE-MRI parameters, maximum slope (MS) and initial area under the curve in 60 s (iAUC), were calculated for each dynamic set and compared between benign and malignant lesions. Areas under the receiver operating characteristic curve (AUCs) were used to assess their diagnostic performance. RESULTS: A total of 140 women (mean age, 47 ± 11 years) with 151 lesions were included. MS and iAUC from eight dynamic sets exhibited significant differences between benign and malignant lesions (all p < 0.05), except iAUC at SD40.5s. The AUC of MS (AUC = 0.804) and iAUC (AUC = 0.659) at SD67.5s were significantly higher than their values at SD40.5s (AUC = 0.606 and 0.516; corrected p < 0.05). No significant differences in AUCs for MS and iAUC were observed from SD67.5s to SD135s (all corrected p > 0.05). CONCLUSIONS: Ultrafast DCE-MRI with a 67.5-s scan duration appears optimal for effectively differentiating malignant from benign breast lesions. CRITICAL RELEVANCE STATEMENT: By evaluating scan durations (40.5-135 s) and analyzing two ultrafast DCE-MRI parameters, we found a scan duration of 67.5 s optimal for discriminating between these lesions and offering a balance between acquisition time and diagnostic efficacy. KEY POINTS: Ultrafast DCE-MRI can effectively differentiate malignant from benign breast lesions. A minimum of 67.5-sec ultrafast DCE-MRI scan duration is required to differentiate benign and malignant lesions. Extending the scan duration beyond 67.5 s did not significantly improve diagnostic accuracy.

Clinical and pathological features of 52 patients with glomerulonephritis with dominant C3. / C3沉积为主的肾小球肾炎52ä¾‹ä¸´åºŠä¸Žç— ç†ç‰¹å¾.

OBJECTIVES: With the in-depth study of complement dysregulation, glomerulonephritis with dominant C3 has received increasing attention, with a variety of pathologic types and large differences in symptoms and prognosis between pathologic types. This study analyzes the clinical, pathological, and prognostic characteristics of different pathological types of glomerulonephritis with dominant C3, aiming to avoid misdiagnosis and missed diagnoses. METHODS: The clinical, pathological, and follow-up data of 52 patients diagnosed as glomerulonephritis with dominant C3 by renal biopsy from June 2013 to October 2022 were retrospectively analyzed. According to the clinical feature and results of pathology, 15 patients with post-infectious glomerulonephritis (PIGN) and 37 patients with of non-infectious glomerulonephritis (N-PIGN) were classified. N-PIGN subgroup analysis was performed, and 16 patients were assigned into a C3-alone-deposition group and 21 in a C3-dominant-deposition group, or 27 in a C3 glomerulopathy (C3G) group and 10 in a non-C3 nephropathy (N-C3G) group. RESULTS: The PIGN group had lower creatinine values (84.60 µmol/L vs179.62 µmol/L, P=0.001), lower complement C3 values (0.36 g/L vs0.74 g/L, P<0.001) at biopsy, and less severe pathological chronic lesions compared with the N-PIGN group. In the N-PIGN subgroup analysis, the C3-dominant-deposition group had higher creatinine values (235.30 µmol/L vs106.70 µmol/L, P=0.004) and higher 24-hour urine protein values (4 025.62 mg vs1 981.11 mg, P=0.037) than the C3-alone-deposition group. The prognosis of kidney in the PIGN group (P=0.049), the C3-alone-deposition group (P=0.017), and the C3G group (P=0.018) was better than that in the N-PIGN group, the C3-dominant-deposition group, and the N-C3G group, respectively. CONCLUSIONS: Glomerulonephritis with dominant C3 covers a variety of pathological types, and PIGN needs to be excluded before diagnosing C3G because of considerable overlap with atypical PIGN and C3G; in addition, the deposition of C1q complement under fluorescence microscope may indicate poor renal prognosis, and relevant diagnosis, treatment, and follow-up should be strengthened.

Predicting the risk of pulmonary infection in patients with chronic kidney failure: A-C2GH2S risk score-a retrospective study.

PURPOSE: The objective of this study is to investigate the associated risk factors of pulmonary infection in individuals diagnosed with chronic kidney disease (CKD). The primary goal is to develop a predictive model that can anticipate the likelihood of pulmonary infection during hospitalization among CKD patients. METHODS: This retrospective cohort study was conducted at two prominent tertiary teaching hospitals. Three distinct models were formulated employing three different approaches: (1) the statistics-driven model, (2) the clinical knowledge-driven model, and (3) the decision tree model. The simplest and most efficient model was obtained by comparing their predictive power, stability, and practicability. RESULTS: This study involved a total of 971 patients, with 388 individuals comprising the modeling group and 583 individuals comprising the validation group. Three different models, namely Models A, B, and C, were utilized, resulting in the identification of seven, four, and eleven predictors, respectively. Ultimately, a statistical knowledge-driven model was selected, which exhibited a C-statistic of 0.891 (0.855-0.927) and a Brier score of 0.012. Furthermore, the Hosmer-Lemeshow test indicated that the model demonstrated good calibration. Additionally, Model A displayed a satisfactory C-statistic of 0.883 (0.856-0.911) during external validation. The statistical-driven model, known as the A-C2GH2S risk score (which incorporates factors such as albumin, C2 [previous COPD history, blood calcium], random venous blood glucose, H2 [hemoglobin, high-density lipoprotein], and smoking), was utilized to determine the risk score for the incidence rate of lung infection in patients with CKD. The findings revealed a gradual increase in the occurrence of pulmonary infections, ranging from 1.84% for individuals with an A-C2GH2S Risk Score ≤ 6, to 93.96% for those with an A-C2GH2S Risk Score ≥ 18.5. CONCLUSION: A predictive model comprising seven predictors was developed to forecast pulmonary infection in patients with CKD. This model is characterized by its simplicity, practicality, and it also has good specificity and sensitivity after verification.

Huaier granule improves liver inflammation and fibrosis and prevents recurrence in hepatitis B virus related hepatocellular carcinoma.

Background: There is basic research suggesting that Huaier granule can inhibit liver cirrhosis and hepatocellular carcinoma (HCC), but this conclusion has not been clinically verified. We analyzed the distant cancer tissue of two groups of hepatitis B virus (HBV) related HCC with/without Huaier granule, to clarify the effect of Huaier granule on liver inflammation, liver fibrosis, and postoperative recurrence. Methods: We collected clinicopathological data of HCC patients who received two surgery procedures at Mengchao Hepatobiliary Hospital of Fujian Medical University in China from January 2014 to December 2020. Patients according to taking/not taking Huaier granule after the first hepatectomy were divided into two groups, 51 patients with Huaier granule for more than 6 months after operation (Group A); 56 patients without Huaier granule (Group B). The effects on liver inflammation, fibrosis grade, and postoperative recurrence were compared between two groups. Results: The results showed that liver inflammation improved significantly in the Group A [19 (37.3%) cases improved, 31 (60.8%) cases remained unchanged, and 1 (2.0%) case deteriorated] was significantly more than that in the Group B [7 (12.5%) cases improved, 32 (57.1%) cases remained unchanged, and 17 (30.4%) cases deteriorated] (P<0.001). The liver fibrosis in the Group A [17 (33.3%) cases improved, 32 (62.7%) cases remained unchanged, and 2 (3.9%) cases deteriorated] was significantly improved in the Group B [5 (8.9%) cases improved, 45 (80.4%) cases remained unchanged, and 6 (10.7%) cases deteriorated] (P=0.005). The recurrence interval (27.0±21.2 months) in the Group A was significantly longer than that in the Group B (19.0±14.2 months) (P=0.026). Conclusions: Huaier granule can improve liver inflammation, fibrosis, and liver function and prolong the time to recurrence in HBV-related HCC. Given the high rate of postoperative recurrence and poor prognosis of HBV-related HCC, our findings may have useful clinical significance in the prevention of tumor recurrence in these patients.

Genomic and transcriptomic profiling of peripheral T cell lymphoma reveals distinct molecular and microenvironment subtypes.

Peripheral T cell lymphoma (PTCL) is a heterogeneous group of non-Hodgkin's lymphomas varying in clinical, phenotypic, and genetic features. The molecular pathogenesis and the role of the tumor microenvironment in PTCL are poorly understood, with limited biomarkers available for genetic subtyping and targeted therapies. Through an integrated genomic and transcriptomic study of 221 PTCL patients, we delineate the genetic landscape of PTCL, enabling molecular and microenvironment classification. According to the mutational status of RHOA, TET2, histone-modifying, and immune-related genes, PTCL is divided into 4 molecular subtypes with discrete patterns of gene expression, biological aberrations, and vulnerabilities to targeted agents. We also perform an unsupervised clustering on the microenvironment transcriptional signatures and categorize PTCL into 4 lymphoma microenvironment subtypes based on characteristic activation of oncogenic pathways and composition of immune communities. Our findings highlight the potential clinical rationale of future precision medicine strategies that target both molecular and microenvironment alterations in PTCL.

[Preparation and evaluation of chitosan-based light source-loaded soluble microneedles].

The combination of photodynamic therapy and drug delivery microneedle (MN) provides a safe and effective way to treat tumors. In this paper, we designed a controlled and sustained-release drug-loaded microneedle patch (LED-losartan-HEMA/CS-MN, LLH-CSMN) based on chitosan loaded with high-energy photons, investigated its preparation process, and characterized the morphology and size of the microneedle array with losartan as the model drug. The mechanical properties of LLH-CSMN, skin puncture properties, slow release properties and the photothermal properties of high energy photons under long-term operation were investigated. The experimental results showed that the chitosan-based microneedle patch loaded with high-energy photons can effectively open channels on the skin surface for drug delivery and photodynamic therapy. At the same time, the in vitro percutaneous diffusion experiment showed that the microneedles prepared with losartan as the model drug released about 30% of the drug within 1 h, about 60% of the drug in total within 1 d, followed by slow release, and finally released 93% of the drug after 6 d. LLH-CSMN has controllable slow-release characteristics and good long-term photoassisted therapy effect. It provides a new safe and effective way for tumor treatment.

Type-II IFN inhibits SARS-CoV-2 replication in human lung epithelial cells and ex vivo human lung tissues through indoleamine 2,3-dioxygenase-mediated pathways.

Interferons (IFNs) are critical for immune defense against pathogens. While type-I and -III IFNs have been reported to inhibit SARS-CoV-2 replication, the antiviral effect and mechanism of type-II IFN against SARS-CoV-2 remain largely unknown. Here, we evaluate the antiviral activity of type-II IFN (IFNγ) using human lung epithelial cells (Calu3) and ex vivo human lung tissues. In this study, we found that IFNγ suppresses SARS-CoV-2 replication in both Calu3 cells and ex vivo human lung tissues. Moreover, IFNγ treatment does not significantly modulate the expression of SARS-CoV-2 entry-related factors and induces a similar level of pro-inflammatory response in human lung tissues when compared with IFNß treatment. Mechanistically, we show that overexpression of indoleamine 2,3-dioxygenase 1 (IDO1), which is most profoundly induced by IFNγ, substantially restricts the replication of ancestral SARS-CoV-2 and the Alpha and Delta variants. Meanwhile, loss-of-function study reveals that IDO1 knockdown restores SARS-CoV-2 replication restricted by IFNγ in Calu3 cells. We further found that the treatment of l-tryptophan, a substrate of IDO1, partially rescues the IFNγ-mediated inhibitory effect on SARS-CoV-2 replication in both Calu3 cells and ex vivo human lung tissues. Collectively, these results suggest that type-II IFN potently inhibits SARS-CoV-2 replication through IDO1-mediated antiviral response.

Opportunistic lung cancer screening with low-dose computed tomography in National Cancer Center of China: The first 14 years' experience.

BACKGROUND: In China, over 50% of lung cancer cases occur in nonsmokers. Thus, identifying high-risk individuals for targeted lung cancer screening is crucial. Beyond age and smoking, determining other risk factors for lung cancer in the Asian population has become a focal point of research. Using 30,000 participants in the prospectively enrolled cohort at China's National Cancer Center (NCC) over the past 14 years, we categorized participants by risk, with an emphasis on nonsmoking females. MATERIALS AND METHODS: Between November 2005 and December 2019, 31,431 individuals voluntarily underwent low-dose computed tomography (LDCT) scans for lung cancer screening at the NCC. We recorded details like smoking history, exposure to hazards, and family history of malignant tumors. Using the 2019 NCCN criteria, participants were categorized into high-, moderate-, and low-risk groups. Additionally, we separated non-high-risk groups into female never smokers (aged over 40) exposed to second-hand smoke (SHS) and others. Any positive results from initial scans were monitored per the I-ELCAP protocol (2006), and suspected malignancies were addressed through collaborative decisions between patients and physicians. We analyzed and compared the detection rates of positive results, confirmed lung cancers, and cancer stages across risk, age, and gender groups. RESULTS: Out of 31,431 participants (55.9% male, 44.1% female), 3695 (11.8%) showed positive baseline LDCT scans with 197 (0.6%; 106 females, 91 males) confirmed as lung cancer cases pathologically. Malignancy rate by age was 0.1% among those aged under 40 years, 0.4% among those aged 40-49 years, 0.8% among those aged 50-59 years, and 1.2% among those aged 60 years and older. From the 25,763 participants (56.9% male, 43.1% female) who completed questionnaires, 1877 (7.3%) were categorized as high risk, 6500 (25.2%) as moderate risk, and 17,386 (67.5%) as low risk. Of the 23,886 in the non-high-risk category, 8041 (33.7%) were females over 40 years old exposed to SHS. The high-risk group showed the highest lung cancer detection rate at 1.4%. However, females exposed to SHS had a notably higher detection rate than the rest of the non-high-risk group (1.1% vs. 0.5%; p < 0.0001). In this cohort, 84.8% of the detected lung cancers were at an early stage. CONCLUSIONS: In our study, using LDCT for lung cancer screening proved significant for high-risk individuals. For non-high-risk populations, LDCT screening could be considered for nonsmoking women with exposure to SHS.

Multiparametric MRI model to predict molecular subtypes of breast cancer using Shapley additive explanations interpretability analysis.

PURPOSE: The purpose of this study was to assess the predictive performance of multiparametric magnetic resonance imaging (MRI) for molecular subtypes and interpret features using SHapley Additive exPlanations (SHAP) analysis. MATERIAL AND METHODS: Patients with breast cancer who underwent pre-treatment MRI (including ultrafast dynamic contrast-enhanced MRI, magnetic resonance spectroscopy, diffusion kurtosis imaging and intravoxel incoherent motion) were recruited between February 2019 and January 2022. Thirteen semantic and thirteen multiparametric features were collected and the key features were selected to develop machine-learning models for predicting molecular subtypes of breast cancers (luminal A, luminal B, triple-negative and HER2-enriched) by using stepwise logistic regression. Semantic model and multiparametric model were built and compared based on five machine-learning classifiers. Model decision-making was interpreted using SHAP analysis. RESULTS: A total of 188 women (mean age, 53 ± 11 [standard deviation] years; age range: 25-75 years) were enrolled and further divided into training cohort (131 women) and validation cohort (57 women). XGBoost demonstrated good predictive performance among five machine-learning classifiers. Within the validation cohort, the areas under the receiver operating characteristic curves (AUCs) for the semantic models ranged from 0.693 (95% confidence interval [CI]: 0.478-0.839) for HER2-enriched subtype to 0.764 (95% CI: 0.681-0.908) for luminal A subtype, inferior to multiparametric models that yielded AUCs ranging from 0.771 (95% CI: 0.630-0.888) for HER2-enriched subtype to 0.857 (95% CI: 0.717-0.957) for triple-negative subtype. The AUCs between the semantic and the multiparametric models did not show significant differences (P range: 0.217-0.640). SHAP analysis revealed that lower iAUC, higher kurtosis, lower D*, and lower kurtosis were distinctive features for luminal A, luminal B, triple-negative breast cancer, and HER2-enriched subtypes, respectively. CONCLUSION: Multiparametric MRI is superior to semantic models to effectively predict the molecular subtypes of breast cancer.

Noninvasive detection of diabetes mellitus based on skin fluorescence and diffuse reflectance spectroscopy.

There is an urgent need for a mass population screening tool for diabetes. Skin tissue contains a large number of endogenous fluorophores and physiological parameter markers related to diabetes. We built an excitation-emission spectrum measurement system with the excited light sources of 365, 395, 415, 430, and 455 nm to extract skin characteristics. The modeling experiment was carried out to design and verify the accuracy of the recovery of tissue intrinsic discrete three-dimensional fluorescence spectrum. Blood oxygen modeling experiment results indicated the accuracy of the physiological parameter extraction algorithm based on the diffuse reflectance spectrum. A community population cohort study was carried out. The tissue-reduced scattering coefficient and scattering power of the diabetes were significantly higher than normal control groups. The Gaussian multi-peak fitting was performed on each excitation-emission spectrum of the subject. A total of 63 fluorescence features containing information such as Gaussian spectral curve intensity, central wavelength position, and variance were obtained from each person. Logistic regression was used to construct the diabetes screening model. The results showed that the area under the receiver operating characteristic curve of the model for predicting diabetes was 0.816, indicating a high diagnostic value. As a rapid and non-invasive detection method, it is expected to have high clinical value.

Early Identification of Pathologic Complete Response to Neoadjuvant Chemotherapy Using Multiphase DCE-MRI by Siamese Network in Breast Cancer: A Longitudinal Multicenter Study.

BACKGROUND: Siamese network (SN) using longitudinal DCE-MRI for pathologic complete response (pCR) identification lack a unified approach to phases selection. PURPOSE: To identify pCR in early-stage NAC, using SN with longitudinal DCE-MRI and introducing IPS for phases selection. STUDY TYPE: Multicenter, longitudinal. POPULATION: Center A: 162 female patients (50.63 ± 8.41 years) divided 7:3 into training and internal validation cohorts. Center B: 61 female patients (50.08 ± 7.82 years) were used as an external validation cohort. FIELD STRENGTH/SEQUENCE: Center A: single vendor 3.0 T with a compressed-sensing volume interpolated breath-hold examination sequence. Center B: single vendor 1.5 T with volume interpolated breath-hold examination sequence. ASSESSMENT: Patients underwent DCE-MRI before and after two NAC cycles, with tumor regions of interest (ROI) manually delineated. Histopathology was the reference for pCR identification. Models developed included a clinical one, four SN models based on IPS-selected phases, and integrated models combining clinical and SN features. STATISTICAL TESTS: Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). The DeLong test was used to compare AUCs. Net reclassification improvement and integrated discrimination improvement (IDI) tests were employed for performance comparison. P < 0.05 was considered significant. RESULTS: In internal and external validation cohorts, the clinical model showed AUCs of 0.760 and 0.718. SN and integrated models, with increasing phases via IPS, achieved AUCs ranging from 0.813 to 0.951 and 0.818 to 0.922. Notably, SN-3 and integrated-3 and integrated-4 outperformed the clinical model. However, input phases beyond 20% did not significantly enhance performance (IDI test: SN-4 vs. SN-3, P = 0.314 and 0.630; integrated-4 vs. integrated-3, P = 0.785 and 0.709). DATA CONCLUSION: The longitudinal multiphase DCE-MRI based on the SN demonstrates promise for identifying pCR in breast cancer. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 4.

Dyslipidemia in rheumatoid arthritis: the possible mechanisms.

Rheumatoid arthritis (RA) is an autoimmune inflammatory disease, of which the leading cause of death is cardiovascular disease (CVD). The levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), and high-density lipoprotein cholesterol (HDL-c) in RA decrease especially under hyperinflammatory conditions. It is conflictive with the increased risk of CVD in RA, which is called "lipid paradox". The systemic inflammation may explain this apparent contradiction. The increased systemic proinflammatory cytokines in RA mainly include interleukin-6(IL-6)、interleukin-1(IL-1)and tumor necrosis factor alpha(TNF-α). The inflammation of RA cause changes in the subcomponents and structure of HDL particles, leading to a weakened anti-atherosclerosis function and promoting LDL oxidation and plaque formation. Dysfunctional HDL can further worsen the abnormalities of LDL metabolism, increasing the risk of cardiovascular disease. However, the specific mechanisms underlying lipid changes in RA and increased CVD risk remain unclear. Therefore, this article comprehensively integrates the latest existing literature to describe the unique lipid profile of RA, explore the mechanisms of lipid changes, and investigate the impact of lipid changes on cardiovascular disease.

Clinical and pathological features of omicron variant of SARS-CoV-2-associated kidney injury.

Kidney injury is common in patients with Coronavirus Disease-19 (COVID-19), which is related to poor prognosis. We aim to summarize the clinical features, athological types, and prognosis of COVID-19 associated kidney injury caused by the Omicron strain. In this study, 46 patients with Omicron-associated kidney injury were included, 38 of whom performed renal biopsy. Patients were divided into two groups: group A for patients with onset of kidney injury after SARS-CoV-2 infection; group B for patients with pre-existing kidney disease who experienced aggravation of renal insufficiency after SARS-CoV-2 infection. The clinical, pathological, and prognostic characteristics of the patients were observed. Acute kidney injury (AKI) (35%) was the most common clinical manifestation in group A. Patients in group B mainly presented with chronic kidney disease (CKD) (55%) and nephrotic syndrome (NS) (40%). The pathological type was mainly IgA nephropathy (IgAN) (39% in group A and 45% in group B). Among all of them, one case presenting with thrombotic microangiopathy had worse kidney function at biopsy time. Mean serum C3 levels were 1.2 ± 0.5 and 1.0 ± 0.2 g/L in group A and group B, respectively. In renal tissues, C3 deposits were observed in 71.1% of patients. 11.8% (n = 2) patients experienced deterioration of renal function after treatment, but no patients developed to end-stage renal disease. In our single-center study in China, the main clinical manifestations were AKI, CKD, and NS, while the main pathological type was IgAN. Compared with previous strains of SARS-CoV-2, patients with the Omicron infection had a favorable prognosis.

Changes in spectrum of biopsy-proven kidney diseases within decade: an analysis based on 10 199 cases from South China.

PURPOSE: To assess the regional epidemiological trends of kidney diseases over time in the South China using renal biopsy-proven cases. METHODS: This retrospective observational cohort study was conducted at the Institute of Nephrology, Second Xiangya Hospital of Central South University, and encompasses all patients diagnosed with kidney disease via biopsy from 2012 to 2021. RESULTS: The study sample consisted of 10 199 native kidneys, with a male-to-female ratio of 0.91:1 and an average age of 38.74 (±14.53) years. Primary glomerular nephropathy, systemic glomerular nephropathy (SGN), tubulointerstitial disease, and hereditary renal diseases accounted for 66.92 (6825)%, 24.49 (2498)%, 8.06 (822)%, and 0.53 (54)%, respectively. The leading pathologies of primary glomerular nephropathy remained the IgA nephropathy. The frequencies of IgA nephropathy and membranous nephropathy increased significantly, whereas the frequencies of minimal change disease and focal segmental glomerulosclerosis decreased (P < .001) between 2017 and 2021 than in the years 2012 and 2016. An earlier onset of membranous nephropathy was observed in the age group of 45-59 years compared to previous studies. The leading pathologies of SGN were found to be lupus nephritis (758 cases, 30.45%) and hypertension nephropathy (527 cases, 21.17%). The frequencies of hypertension nephropathy and diabetic nephropathy increased between 2017 and 2021 compared to 2012 and 2016 (P < .001), gradually becoming the leading pathological types of SGN. In elderly patients diagnosed with nephrotic syndrome, the frequencies of amyloidosis significantly increased (P < .01). CONCLUSION: Our study may provide insights for kidney disease prevention and public health strategies. What is already known on this topic The pathological spectrum of kidney diseases has undergone significant transformations in the past decade, driven by the escalating incidence of chronic diseases. Although there are studies exploring the renal biopsy findings from various regions in China which present both similarities and differences in epidemiology, few large-scale reports from the South China in recent decades were published. What this study adds Our findings reveal the following key observations: (i) increased proportion of middle-aged patients leading to the increasing average age at the time of biopsy；(ii) the frequencies of IgA nephropathy and membranous nephropathy (MN) increased significantly, whereas the frequencies of minimal change disease and focal segmental glomerulosclerosis decreased (P < .001) between 2017 and 2021 than in the years 2012 and 2016; (iii) earlier onset of MN in the age group of 45-59 years old was found in our study; and (iv) a higher frequency of hypertension nephropathy and DN presented over time, and frequency of amyloidosis increased in elderly patients diagnosed with NS. How this study might affect research, practice, or policy This single-center yet a large-scale study of the kidney disease spectrum in South China may provide a reference point for the diagnosis, treatment, and prevention of chronic kidney disease.

LncRNA TIALD contributes to hepatocellular carcinoma metastasis via inducing AURKA lysosomal degradation.

The N6-methyladenosine (m6A) RNA methyltransferase METTL16 is an emerging player in RNA modification landscape and responsible for the deposition of m6A in a few transcripts. AURKA (aurora kinase A) has been confirmed as an oncogene in cancer development including hepatocellular carcinoma (HCC). Nevertheless, it remains unclear whether METTL16 mediated m6A modification of lncRNAs can regulate AURKA activation in cancer progression. Here we aimed to investigate the functional links between lncRNAs and the m6A modification in AURKA signaling and HCC progression. Here we show that LncRNA TIALD (transcript that induced AURKA Lysosomal degradation) was down-regulated in HCC tissues by METTL16 mediated m6A methylation to facilitate its RNA degradation, and correlates with poor prognosis. Functional assays reveal that TIALD inhibits HCC metastasis both in vitro and in vivo. Mechanistically, TIALD directly interacts with AURKA and facilitate its degradation through the lysosomal pathway to inhibited EMT and metastasis of HCC. AURKA's specific inhibitor alisertib exerts effective therapeutic effect on liver cancer with low TIALD expression, which might provide a new insight into HCC therapy. Our study uncovers a negative functional loop of METTL16-TIALD-AURKA axis, and identifies a new mechanism for METTL16 mediated m6A-induced decay of TIALD on AURKA signaling in HCC progression, which may provide potential prognostic and therapeutic targets for HCC.

Comparative Genomics Identified PenR E151V Substitution Associated with Carbapenem-Resistance Burkholderia cepacia Complex and a Novel Burkholderia cepacia Complex Specific OXA-1043 Subgroup.

Purpose: Burkholderia cepacia complex (Bcc) is a known significant opportunistic pathogen causing morbidity and mortality, particularly in those with cystic fibrosis, chronic granulomatous disease, or immunocompromising host. Mortality of Bcc bloodstream infections among non-cystic fibrosis patients remained high. The antibiotic treatment for Bcc infection is quite challenging due to its intrinsic resistance to most antibiotics, and the resistance to carbapenems was the biggest concern among them. We aimed to realize the mechanism of carbapenem resistance in Bcc. Patients and Methods: Ten strains of Bcc were identified by the MALDI-TOF MS, and the drug susceptibility test was using VITEK 2 system. The Burkholderia cepacia complex genomes were sequenced via Nanopore GridIon. We also downloaded another ninety-five strains of Bcc from the National Center for Biotechnology Information database to evaluate the divergence between carbapenem-resistance and carbapenem-sensitive strains. Results: The genetic organization between carbapenem-sensitive and carbapenem-resistant strains of Bcc showed no difference. However, in the carbapenem-sensitive strain, E151V substitution in PenR was detected. In addition, a novel specific OXA family subgroup, blaOXA-1043 in Burkholderia cenocepacia was discovered. Conclusion: The E151V substitution in PenR may be associated with carbapenem-sensitive in Bcc. Moreover, the V151E mutation in PenR may be related to the activation of PenB, leading to Bcc resistance to carbapenems. Besides, a novel OXA family subgroup, blaOXA-1043, was found in Burkholderia cenocepacia, which differs from the previous OXA family.

Ethanolic extract of Pereskia aculeata induces Anti-Inflammatory Responses through P38/MK2/TTP-mediated signaling pathway.

Pereskia aculeata Miller, a member of the Cactaceae family, is a plant with pharmacological potential due to its containing compounds with various biological activities, which include anti-inflammatory, anti-cancer and analgesic activities. In this study, we evaluated the anti-inflammatory effects of an ethanolic extract of P. aculeata Miller (EEPA) and the signalling pathways by which it exerts these effects. In vitro, EEPA inhibited the secretion of inflammatory factors NO, IL-6 and PGE2 in ipopolysaccharide-stimulated RAW264.7 macrophages (P<0.05). Treatment of RAW264.7 cells with EEPA also significantly decreased the levels of P-P38 and P-MK2, while upregulating the expression of TTP (P<0.05). In vivo anti-inflammatory activity assays revealed that EEPA reduced the degree of foot and joint swelling, the splenic index and the serum concentrations of TNF-α and IL-6 in in adjuvant-induced arthritis rats (P<0.05). Similarly, EEPA treatment of mice inhibited the acetic acid-induced exudation of Evans blue dye from peritoneal capillaries and significantly prolonged heat-stimulated pain response time (P<0.05). Taken together, these results suggest that EEPA exerts anti-inflammatory effects in vitro and in vivo. Thus, this study provides experimental and technical support for the development of a novel anti-inflammatory treatment based on P. aculeata Miller.

Stratifying High-Risk Thyroid Nodules Using a Novel Deep Learning System.

INTRODUCTION: The current ultrasound scan classification system for thyroid nodules is time-consuming, labor-intensive, and subjective. Artificial intelligence (AI) has been shown to increase the accuracy of predicting the malignancy rate of thyroid nodules. This study aims to demonstrate the state-of-the-art Swin Transformer to classify thyroid nodules. MATERIALS AND METHODS: Ultrasound images were collected prospectively from patients who received fine needle aspiration biopsy for thyroid nodules from January 2016 to June 2021. One hundred thirty-nine patients with malignant thyroid nodules were enrolled, while 235 patients with benign nodules served as controls. Images were fed to Swin-T and ResNeSt50 models to classify the thyroid nodules. RESULTS: Patients with malignant nodules were younger and more likely male compared to those with benign nodules. The average sensitivity and specificity of Swin-T were 82.46% and 84.29%, respectively. The average sensitivity and specificity of ResNeSt50 were 72.51% and 77.14%, respectively. Receiver operating characteristics analysis revealed that the area under the curve of Swin-T was higher (AUC=0.91) than that of ResNeSt50 (AUC=0.82). The McNemar test evaluating the performance of these models showed that Swin-T had significantly better performance than ResNeSt50.Swin-T classifier can be a useful tool in helping shared decision-making between physicians and patients with thyroid nodules, particularly in those with high-risk characteristics of sonographic patterns.

Early prediction of pathologic complete response of breast cancer after neoadjuvant chemotherapy using longitudinal ultrafast dynamic contrast-enhanced MRI.

PURPOSE: The purpose of this study was to evaluate the temporal trends of ultrafast dynamic contrast-enhanced (DCE)-MRI during neoadjuvant chemotherapy (NAC) and to investigate whether the changes in DCE-MRI parameters could early predict pathologic complete response (pCR) of breast cancer. MATERIALS AND METHODS: This longitudinal study prospectively recruited consecutive participants with breast cancer who underwent ultrafast DCE-MRI examinations before treatment and after two, four, and six NAC cycles between February 2021 and February 2022. Five ultrafast DCE-MRI parameters (maximum slope [MS], time-to-peak [TTP], time-to-enhancement [TTE], peak enhancement intensity [PEI], and initial area under the curve in 60 s [iAUC]) and tumor size were measured at each timepoint. The changes in parameters between each pair of adjacent timepoints were additionally measured and compared between the pCR and non-pCR groups. Longitudinal data were analyzed using generalized estimating equations. The performance for predicting pCR was assessed using area under the receiver operating characteristic curve (AUC). RESULTS: Sixty-seven women (mean age, 50 ± 8 [standard deviation] years; age range: 25-69 years) were included, 19 of whom achieved pCR. MS, PEI, iAUC, and tumor size decreased, while TTP increased during NAC (all P < 0.001). The AUC (0.92; 95% confidence interval [CI]: 0.83-0.97) of the model incorporating ultrafast DCE-MRI parameter change values (from timepoints 1 to 2) and clinicopathologic characteristics was greater than that of the clinical model (AUC, 0.79; 95% CI: 0.68-0.88) and ultrafast DCE-MRI parameter model at timepoint 2 when combined with clinicopathologic characteristics (AUC, 0.82; 95% CI: 0.71-0.90) (P = 0.01 and 0.02). CONCLUSION: Early changes in ultrafast DCE-MRI parameters after NAC combined with clinicopathologic characteristics could serve as predictive markers of pCR of breast cancer.