Structural basis of assembly and torque transmission of the bacterial flagellar motor.

The bacterial flagellar motor is a supramolecular protein machine that drives rotation of the flagellum for motility, which is essential for bacterial survival in different environments and a key determinant of pathogenicity. The detailed structure of the flagellar motor remains unknown. Here we present an atomic-resolution cryoelectron microscopy (cryo-EM) structure of the bacterial flagellar motor complexed with the hook, consisting of 175 subunits with a molecular mass of approximately 6.3 MDa. The structure reveals that 10 peptides protruding from the MS ring with the FlgB and FliE subunits mediate torque transmission from the MS ring to the rod and overcome the symmetry mismatch between the rotational and helical structures in the motor. The LP ring contacts the distal rod and applies electrostatic forces to support its rotation and torque transmission to the hook. This work provides detailed molecular insights into the structure, assembly, and torque transmission mechanisms of the flagellar motor.

Legionella effector LnaB is a phosphoryl AMPylase that impairs phosphosignalling.

AMPylation is a post-translational modification in which AMP is added to the amino acid side chains of proteins1,2. Here we show that, with ATP as the ligand and actin as the host activator, the effector protein LnaB of Legionella pneumophila exhibits AMPylase activity towards the phosphoryl group of phosphoribose on PRR42-Ub that is generated by the SidE family of effectors, and deubiquitinases DupA and DupB in an E1- and E2-independent ubiquitination process3-7. The product of LnaB is further hydrolysed by an ADP-ribosylhydrolase, MavL, to Ub, thereby preventing the accumulation of PRR42-Ub and ADPRR42-Ub and protecting canonical ubiquitination in host cells. LnaB represents a large family of AMPylases that adopt a common structural fold, distinct from those of the previously known AMPylases, and LnaB homologues are found in more than 20 species of bacterial pathogens. Moreover, LnaB also exhibits robust phosphoryl AMPylase activity towards phosphorylated residues and produces unique ADPylation modifications in proteins. During infection, LnaB AMPylates the conserved phosphorylated tyrosine residues in the activation loop of the Src family of kinases8,9, which dampens downstream phosphorylation signalling in the host. Structural studies reveal the actin-dependent activation and catalytic mechanisms of the LnaB family of AMPylases. This study identifies, to our knowledge, an unprecedented molecular regulation mechanism in bacterial pathogenesis and protein phosphorylation.

Threonine ADP-Ribosylation of Ubiquitin by a Bacterial Effector Family Blocks Host Ubiquitination.

Ubiquitination is essential for numerous eukaryotic cellular processes. Here, we show that the type III effector CteC from Chromobacterium violaceum functions as an adenosine diphosphate (ADP)-ribosyltransferase that specifically modifies ubiquitin via threonine ADP-ribosylation on residue T66. The covalent modification prevents the transfer of ubiquitin from ubiquitin-activating enzyme E1 to ubiquitin-conjugating enzyme E2, which inhibits subsequent ubiquitin activation by E2 and E3 enzymes in the ubiquitination cascade and leads to the shutdown of polyubiquitin synthesis in host cells. This unique modification also causes dysfunction of polyubiquitin chains in cells, thereby blocking host ubiquitin signaling. The disruption of host ubiquitination by CteC plays a crucial role in C. violaceum colonization in mice during infection. CteC represents a family of effector proteins in pathogens of hosts from different kingdoms. All the members of this family specifically ADP-ribosylate ubiquitin. The action of CteC reveals a new mechanism for interfering with host ubiquitination by pathogens.

Molecular basis of threonine ADP-ribosylation of ubiquitin by bacterial ARTs.

Ubiquitination plays essential roles in eukaryotic cellular processes. The effector protein CteC from Chromobacterium violaceum blocks host ubiquitination by mono-ADP-ribosylation of ubiquitin (Ub) at residue T66. However, the structural basis for this modification is unknown. Here we report three crystal structures of CteC in complexes with Ub, NAD+ or ADP-ribosylated Ub, which represent different catalytic states of CteC in the modification. CteC adopts a special 'D-E' catalytic motif for catalysis and binds NAD+ in a half-ligand binding mode. The specific recognition of Ub by CteC is determined by a relatively separate Ub-targeting domain and a long loop L6, not the classic ADP-ribosylating turn-turn loop. Structural analyses with biochemical results reveal that CteC represents a large family of poly (ADP-ribose) polymerase (PARP)-like ADP-ribosyltransferases, which harbors chimeric features from the R-S-E and H-Y-E classes of ADP-ribosyltransferases. The family of CteC-like ADP-ribosyltransferases has a common 'D-E' catalytic consensus and exists extensively in bacteria and eukaryotic microorganisms.

Potential lethality of organochlorine pesticides: Inducing fatality through inflammatory responses in the organism.

BACKGROUND: Organochlorine pesticides, with their environmental persistence and bioaccumulation potential, have gained significant attention. This study explores the impact of organochlorine pesticides on mortality and chronic diseases, investigates their link to inflammatory states, and examines the role of anti-inflammatory diets in mitigating adverse reactions to these pesticides. METHODS: This study, with 2,847 participants, used gas chromatography and mass spectrometry to measure organochlorine pesticide exposure in NHANES data. Conventional statistical methodologies, encompassing survival curves, Cox proportional hazards regression, regression analysis, and restricted quadratic spline analysis, were employed to investigate the association between pesticides and mortality, chronic ailments, and inflammation. Furthermore, machine learning techniques, comprising RF, AdaBoost, Extra-Trees, LightGBM, and BPNN, were leveraged to evaluate the impact of pesticides on chronic disease and mortality prognostication. RESULTS: Organochlorine pesticides were significantly and positively correlated with increased mortality (p<0.05). Additionally, these pollutants were linked to the incidence of chronic diseases such as chronic kidney disease, diabetes, and hypertension (p< 0.05). Our study, utilizing various machine learning models, also showed a notable increase in the Area Under the Curve when incorporating organochlorine pesticide indicators into the model as opposed to excluding them. Furthermore, strong correlations were observed between serum c-reactive protein (CRP) and CRP to serum albumin ratio (CAR) concentrations with these substances, demonstrating their pro-inflammatory effects at specific concentrations. Interestingly, cutting down on dietary inflammation through changes in diet effectively reduced the risk of death at high organochlorine pesticide exposure levels, but the effect was less noticeable at low to moderate exposure levels. CONCLUSIONS: Exposure to organochlorine pesticides was linked to a higher risk of mortality, likely due to an increased prevalence of chronic diseases. In this context, inflammation played a crucial role, and adopting an anti-inflammatory diet significantly reduced the mortality risk associated with these pesticides.

Uric acid-based ratios for predicting renal failure in Chinese IgA nephropathy patients.

Objective: The uric acid/albumin ratio (UAR), a novel, simple, and compositive laboratory biomarker, has recently attracted attention for predicting disease prediction and disease prognosis. However, whether uric acid-related biomarkers (especially UAR) could serve as prognostic indicator for IgAN is unclear. Methods: In this retrospective cohort study, biopsy-confirmed IgAN patients from 2009 to 2017 from West China Hospital were evaluated. The optimal cutoff value of UAR for renal outcome was defined using the Youden index by the area under receiver operating characteristic curve (AUC). The patients were then categorized into the high UAR group and the low UAR group. Renal endpoints were defined as progression to ESRD, eGFR decreased ≥50% of the baseline level, or initiation of renal replacement treatment. Kaplan‒Meier survival analysis and Cox regression analysis were used to identify factors influencing IgAN outcomes. Results: A total of 1143 patients with a median age of 33.0 (26.0-42.0) (44.2% men) were included in the study. The best cut-off UAR concerned with renal survival was determined to be 9.94 with a specificity of 77.5% and a sensitivity of 61.5% (J, 0.390; AUC, 0.750). Then, the patients were divided into two groups labelled as low and high UAR ratios (≥ 9.94 and <9.94, respectively). More severe clinical manifestations and pathological lesions were observed in the high UAR group. Multivariate Cox regression analysis after adjusted for important clinicopathological parameters manifested that a high UAR was an independent prognostic biomarker for IgAN. (p = 0.036, HR =2.56, 95% CI: 1.07-6.16). Conclusion: UAR might be a novel predictor for renal progression and contribute to targeted management.

Probiotics ameliorate IgA nephropathy by improving gut dysbiosis and blunting NLRP3 signaling.

BACKGROUND: Recently, a few studies have indicated a relationship between the gut microbiota and IgA nephropathy (IgAN). Whether the gut microbiota participates in the pathogenesis of IgAN and whether probiotics are effective in treating IgAN are still controversial. Therefore, this study aimed to identify the differences in the structure of the gut microbiota between IgAN and controls and to evaluate the efficacy and mechanism of probiotics in the treatment of IgAN. METHODS: To address this question, 35 IgAN patients and 25 healthy volunteers were enrolled, and a mouse IgAN model was also constructed. The stool microbes were analyzed by 16S rRNA high-throughput sequencing to identify the differential strains between IgAN and healthy controls. The impact of probiotics on the structure of the intestinal flora and the efficacy of the probiotics in the treatment of IgAN were evaluated. RESULTS: Although the microflora structure of mice and humans was not the same, both patients and mice with IgAN exhibited gut microbiota dysbiosis, with all subjects presenting an evident decrease in Bifidobacterium levels. The Bifidobacterium proportion was negatively correlated with proteinuria and hematuria levels, indicating that the decreased Bifidobacterium abundance could be related to IgAN severity. Probiotic treatment containing Bifidobacterium in IgAN mice could significantly alleviate gut dysbiosis, specifically by increasing the proportion of beneficial bacteria and reducing the abundance of potentially pathogenic bacteria. Moreover, both probiotics and their metabolites, short-chain fatty acids (SCFAs), could attenuate IgAN clinicopathological manifestations by inhibiting the NLRP3/ASC/Caspase 1 signaling pathway. CONCLUSIONS: Supplementation with probiotics mainly containing Bifidobacterium could markedly improve gut dysbiosis in IgAN. Moreover, both probiotics and their SCFA metabolites could attenuate the clinicopathological manifestations of IgAN by inhibiting the NLRP3/ASC/Caspase 1 signaling pathway. Therefore, probiotics have potential as an adjunctive therapy for IgAN.

Intestinal dysbiosis featuring abundance of Streptococcus associates with Henoch-Schönlein purpura nephritis (IgA vasculitis with nephritis) in adult.

BACKGROUND: The pathogenesis of Henoch-Schönlein purpura nephritis (HSPN) is closely associated with mucosal infection. But whether intestinal microbiota dysbiosis plays a role in it is not clear. METHODS: A total of 52 participants including 26 HSPN patients and 26 healthy controls were included. By using 16S ribosomal RNA gene sequencing, the intestinal microbiota composition between HSPN and healthy controls was compared. The diagnostic potency was evaluated by Receiver operating characteristic (ROC) with area under curves (AUC). Meanwhile, correlation analysis was also performed. RESULTS: The lower community richness and diversity of fecal microbiota was displayed in HSPN patients and the structure of gut microbiota was remarkedly different. A genus-level comparison indicated a significant increase in the proportions of g-Bacteroides, g-Escherichia-Shigella and g-Streptococcus, and a marked reduction of g-Prevotella_9 in HSPN patients, suggesting that the overrepresentation of potential pathogens and reduction of profitable strains were the main feature of the dysbiosis. The differential taxonomic abundance might make sense for distinguishing HSPN from healthy controls, with AUC of 0.86. The relative abundance of the differential bacteria was also concerned with clinical indices. Among them, Streptococcus spp. was positively associated with the severity of HSPN (P < 0.050). It was found that HSPN patients with higher level of Streptococcus spp. were more likely to suffering from hematuria and hypoalbuminemia (P < 0.050). CONCLUSIONS: The dysbiosis of gut microbiota was obvious in HSPN patients, and the intestinal mucosal streptococcal infection was distinctive, which was closely related to its severity.

Clinicopathological characteristics and risk factors in elderly patients with biopsy-proven IgA nephropathy.

BACKGROUND: Immunoglobulin A nephropathy (IgAN) has been well studied among young people, but few data on clinicopathological characteristics, treatment response and outcomes for elderly IgAN patients are available. METHODS: A cohort study of elderly IgAN patients was performed. The combined endpoints of renal outcome were a 50% decline in eGFR compared with the time of renal biopsy, end-stage kidney disease and/or death. Risk factors associated with poor renal outcomes were then determined. The benefits of immunosuppressant therapies were also evaluated by Kaplan-Meier survival curve analysis. RESULTS: This study ultimately included 126 elderly patients with IgAN. Comparison between the endpoint and non-endpoint groups indicated that patients with poor outcomes had more severe clinical features, such as worse kidney function, severe hematuria and lower albumin levels. Cox regression analysis indicated that age (HR 1.15, 95% CI 1.02-1.29, p = 0.021), male gender (HR 9.71, 95% CI 1.00-97.56, p = 0.050), and urine red blood cells (HR 1.003, 95% CI 1.000-1.006, p = 0.029) were independent risk factors for poor renal outcome in elderly IgAN patients. To explore possible reasons accounting for the predictive value of age and sex, patients were divided into two groups based on these two variables. Patients in the geriatric group had lower serum albumin, estimated glomerular filtration rate, hemoglobin and aspartate aminotransferase levels than those in the quinquagenarian group. Male patients tended to have higher hemoglobin, higher alanine aminotransferase, and lower triglycerides and cholesterol levels than female patients. To investigate different treatment responses, patients were classified into two groups depending on treatment strategies (renin-angiotensin system inhibitors and immunosuppressive therapy), and the survival analysis indicated no significant difference in kidney outcome between the two groups (p > 0.05). This result still holds after adjusting for age, sex, eGFR, hematuria, and proteinuria. CONCLUSION: Advanced age, male, and hematuria might be independently associated with poor kidney outcomes in elderly patients with IgAN. Immunosuppressive therapy might confer no overall benefit to older IgAN patients.

An Adaptive Learning Model for Multiscale Texture Features in Polyp Classification via Computed Tomographic Colonography.

Objective: As an effective lesion heterogeneity depiction, texture information extracted from computed tomography has become increasingly important in polyp classification. However, variation and redundancy among multiple texture descriptors render a challenging task of integrating them into a general characterization. Considering these two problems, this work proposes an adaptive learning model to integrate multi-scale texture features. Methods: To mitigate feature variation, the whole feature set is geometrically split into several independent subsets that are ranked by a learning evaluation measure after preliminary classifications. To reduce feature redundancy, a bottom-up hierarchical learning framework is proposed to ensure monotonic increase of classification performance while integrating these ranked sets selectively. Two types of classifiers, traditional (random forest + support vector machine)- and convolutional neural network (CNN)-based, are employed to perform the polyp classification under the proposed framework with extended Haralick measures and gray-level co-occurrence matrix (GLCM) as inputs, respectively. Experimental results are based on a retrospective dataset of 63 polyp masses (defined as greater than 3 cm in largest diameter), including 32 adenocarcinomas and 31 benign adenomas, from adult patients undergoing first-time computed tomography colonography and who had corresponding histopathology of the detected masses. Results: We evaluate the performance of the proposed models by the area under the curve (AUC) of the receiver operating characteristic curve. The proposed models show encouraging performances of an AUC score of 0.925 with the traditional classification method and an AUC score of 0.902 with CNN. The proposed adaptive learning framework significantly outperforms nine well-established classification methods, including six traditional methods and three deep learning ones with a large margin. Conclusions: The proposed adaptive learning model can combat the challenges of feature variation through a multiscale grouping of feature inputs, and the feature redundancy through a hierarchal sorting of these feature groups. The improved classification performance against comparative models demonstrated the feasibility and utility of this adaptive learning procedure for feature integration.

Higher-order sensorimotor circuit of the brain's global network supports human consciousness.

Consciousness is a mental characteristic of the human mind, whose exact neural features remain unclear. We aimed to identify the critical nodes within the brain's global functional network that support consciousness. To that end, we collected a large fMRI resting state dataset with subjects in at least one of the following three consciousness states: preserved (including the healthy awake state, and patients with a brain injury history (BI) that is fully conscious), reduced (including the N1-sleep state, and minimally conscious state), and lost (including the N3-sleep state, anesthesia, and unresponsive wakefulness state). We also included a unique dataset of subjects in rapid eye movement sleep state (REM-sleep) to test for the presence of consciousness with minimum movements and sensory input. To identify critical nodes, i.e., hubs, within the brain's global functional network, we used a graph-theoretical measure of degree centrality conjoined with ROI-based functional connectivity. Using these methods, we identified various higher-order sensory and motor regions including the supplementary motor area, bilateral supramarginal gyrus (part of inferior parietal lobule), supragenual/dorsal anterior cingulate cortex, and left middle temporal gyrus, that could be important hubs whose degree centrality was significantly reduced when consciousness was reduced or absent. Additionally, we identified a sensorimotor circuit, in which the functional connectivity among these regions was significantly correlated with levels of consciousness across the different groups, and remained present in the REM-sleep group. Taken together, we demonstrated that regions forming a higher-order sensorimotor integration circuit are involved in supporting consciousness within the brain's global functional network. That offers novel and more mechanism-guided treatment targets for disorders of consciousness.

Are intrinsic neural timescales related to sensory processing? Evidence from abnormal behavioral states.

The brain exhibits a complex temporal structure which translates into a hierarchy of distinct neural timescales. An open question is how these intrinsic timescales are related to sensory or motor information processing and whether these dynamics have common patterns in different behavioral states. We address these questions by investigating the brain's intrinsic timescales in healthy controls, motor (amyotrophic lateral sclerosis, locked-in syndrome), sensory (anesthesia, unresponsive wakefulness syndrome), and progressive reduction of sensory processing (from awake states over N1, N2, N3). We employed a combination of measures from EEG resting-state data: auto-correlation window (ACW), power spectral density (PSD), and power-law exponent (PLE). Prolonged neural timescales accompanied by a shift towards slower frequencies were observed in the conditions with sensory deficits, but not in conditions with motor deficits. Our results establish that the spontaneous activity's intrinsic neural timescale is related to the neural capacity that specifically supports sensory rather than motor information processing in the healthy brain.

Lower serum bilirubin is associated with poor renal outcome in IgA nephropathy patients.

Aims: IgA nephropathy (IgAN) is the most prevalent primary glomerulonephritis worldwide. We conducted this study to explore the relationship between serum bilirubin and renal outcome of patients with IgAN. Methods: A total of 1492 biopsy proven IgAN patients were recruited and divided into two groups according to their median serum bilirubin concentration: the low bilirubin group (serum bilirubin≤9.7umol/L, n=753) and high bilirubin group (serum bilirubin>9.7umol/L, n=739). Basic clinical characteristics were assessed at the time of renal biopsy and the relationships between serum bilirubin and the combined endpoints were analyzed. The combined endpoints were defined as a 50% decline in estimate glomerular filtration rate (e-GFR), end-stage kidney disease (ESKD), renal transplantation and/or death. In addition, propensity score matching (PSM) was then performed to improve balance and simulate randomization between patients in different groups. Kaplan-Meier survival analysis was applied to explore the role of serum bilirubin in the progression of IgAN. Three clinicopathological models of multivariate Cox regression analysis were established to evaluate the association of serum bilirubin and renal prognosis of IgAN. Results: During median 5-year follow-up period, significant differences were shown in Kaplan-Meier analysis. In the unmatched group, 189 (12.7%) patients progressed to the renal combined endpoints. Among this, 122 in 753 patients (16.2%) were in low bilirubin group and 67 in 739 patients (9.1%) were in high bilirubin group (p<0.001). After PSM, there were 134 (11.8%) patients reached the combined endpoints, which included 77 in 566 patients (14.6%) in low bilirubin group and 57 in 566 patients (10.1%) in high bilirubin group (p=0.039). The results of three models (including demographics, pathological, clinical indicators and serum bilirubin) demonstrated that a lower basic serum bilirubin level was significantly associated with a higher risk of reaching combined endpoints in IgAN patients both in unmatched and matched cohort. Conclusion: Serum bilirubin level may be negatively associated with the progression of IgAN.

Cigarette smoking may accelerate the progression of IgA nephropathy.

BACKGROUND: Whether cigarette smoking is associated with the progression of immunoglobulin A nephropathy (IgAN) remains uncertain; therefore, we aimed to evaluate the effect of cigarette smoking on the prognosis of IgAN. METHODS: We divided 1239 IgAN patients from West China Hospital of Sichuan University who met the inclusion criteria into smoker (current or former) and non-smoker groups. The endpoint was end-stage renal disease (ESRD: eGFR < 15 mL/min/1.73 m2 or undergoing renal replacement treatment) and/or eGFR decreased by > 50%. Kaplan-Meier, correlation, logistic regression and Cox proportional hazards analyses were performed. The association between cigarette smoking and IgAN was further verified by propensity-score-matched cohort analysis. RESULTS: During the mean follow-up period of 61 months, 19% (40/209) of the smoker group and 11% (110/1030) of the non-smoker group reached the study endpoint (p < 0.001). Multivariate Cox regression analysis revealed that cigarette smoking (hazard ratio (HR) = 1.58; p = 0.043) was an independent risk factor predicting poor renal progression in IgAN, and that IgAN patients with chronic kidney disease (CKD) stage 3-4 were more susceptible to cigarette smoking (p < 0.001). After propensity score matching (PSM), a significant correlation between cigarette smoking and renal outcomes in IgAN patients was seen. Furthermore, Spearman's correlation test revealed that smoking dose was negatively correlated with eGFR (r = 0.141; p < 0.001) and positively related with proteinuria (r = 0.096; p = 0.001). CONCLUSIONS: Cigarette smoking is an independent risk factor for IgAN progression, especially for advanced patients.

Pursuing Specific Chemotherapy of Orthotopic Breast Cancer with Lung Metastasis from Docking Nanoparticles Driven by Bioinspired Exosomes.

Breast cancer develops from local tissue but is characterized by a distinct metastatic pattern involving regional lymph nodes and distant organs, which is the primary cause of high mortality in breast cancer patients. Herein, optimal docking nanoparticles (NPs) composed of a laurate-functionalized Pt(IV) prodrug (Pt(lau)), human serum albumin (HSA), and lecithin were predicted by computational modeling, prepared by nanoprecipitation, and validated by fluorescence spectroscopy. As macrophages have been reported to be preferentially recruited by breast cancer, Rex, the exosome spontaneously secreted by murine RAW 264.7 cells, was isolated to encapsulate the NPs. This high-performance delivery system, called NPs/Rex, possessed the desired physicochemical properties, enhanced colloidal stability, and redox-triggered release profile. Investigations of cytodynamics proved that NPs/Rex was internalized through multiple pathways, avoided entrapment by bilayers, and successfully platinized nucleic acids after bioreduction in the cytosol. Intracellular activation of Pt(lau) was confirmed by observing the characteristic effects of cisplatin on cell proliferation and the cell cycle following treatment with NPs/Rex. During in vivo application, the bioinspired Rex coating endowed docking NPs with prolonged blood circulation, smart organ tropism, and enhanced biocompatibility, as well as robust platinum (Pt) chemotherapy for breast cancer cells in orthotopic tumors of fat pads and metastatic nodules of lungs. Therefore, this favorable nanoplatform might provide valuable insight into the derivatization and development of Pt anticancer drugs used currently in the clinic.

The Clinicopathological Characteristics of Henoch-Schönlein Purpura Nephritis with Presentation of Nephrotic Syndrome.

BACKGROUND: Henoch-Schönlein purpura nephritis (HSPN) is a common vasculitis involving the kidneys, with a lower incidence in adults. Meanwhile, nephrotic syndrome (NS) can appear in HSPN. However, the clinicopathological features and renal outcome of adult-onset HSPN presenting with NS (NS-HSPN) have not been well clarified. METHODS: A total of 191 HSPN patients were prospectively analyzed and comparisons were made between NS-HSPN and non-NS-HSPN. Multivariate Cox regression analysis was carried out to find the unfavorable factors of renal outcome of NS-HSPN. RESULTS: Among the 191 patients, 44 (23.0%) had NS-HSPN. Apart from edema and abdominal pain, patients with NS-HSPN tended to have lower levels of erythrocytes and hemoglobulin in blood as well as a greater number of erythrocytes in urine (p < 0.05). Mesangial proliferation was the most common pathological lesion in HSPN and the rates of crescent formation were significantly different, with 54.5% in NS-HSPN and 33.3% in non-NS-HSPN (p < 0.05). Notably, 18.2 and 4.8% of patients reached the composite endpoints in the NS-HSPN and non-NS-HSPN groups, respectively (p < 0.05), demonstrating that NS-HSPN patients were more likely to progress to end-stage renal disease and had a worse outcome. We also found that hypertension, estimated glomerular filtration rate (eGFR), cystatin, and tubular atrophy/interstitial fibrosis (HR > 1, p < 0.05) at onset were correlated with adverse outcome in NS-HSPN. CONCLUSION: NS-HSPN had more severe clinicopathological manifestations and poorer prognosis. The adverse predictors of NS-HSPN principally depend on clinicopathological presentation rather than on different therapies, and hypertension, eGFR, cystatin, and tubular atrophy/interstitial fibrosis can serve as independent risk factors in NS-HSPN.

Expert knowledge-infused deep learning for automatic lung nodule detection.

BACKGROUND: Computer aided detection (CADe) of pulmonary nodules from computed tomography (CT) is crucial for early diagnosis of lung cancer. Self-learned features obtained by training datasets via deep learning have facilitated CADe of the nodules. However, the complexity of CT lung images renders a challenge of extracting effective features by self-learning only. This condition is exacerbated for limited size of datasets. On the other hand, the engineered features have been widely studied. OBJECTIVE: We proposed a novel nodule CADe which aims to relieve the challenge by the use of available engineered features to prevent convolution neural networks (CNN) from overfitting under dataset limitation and reduce the running-time complexity of self-learning. METHODS: The CADe methodology infuses adequately the engineered features, particularly texture features, into the deep learning process. RESULTS: The methodology was validated on 208 patients with at least one juxta-pleural nodule from the public LIDC-IDRI database. Results demonstrated that the methodology achieves a sensitivity of 88% with 1.9 false positives per scan and a sensitivity of 94.01% with 4.01 false positives per scan. CONCLUSIONS: The methodology shows high performance compared with the state-of-the-art results, in terms of accuracy and efficiency, from both existing CNN-based approaches and engineered feature-based classifications.

miR-208-3p promotes hepatocellular carcinoma cell proliferation and invasion through regulating ARID2 expression.

MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression at post-transcriptional level. miRNA dysregulation plays a causal role in cancer progression. In this study, miR-208-3p was highly expressed and directly repressed ARID2 expression. As a result, ARID2 expression in hepatocellular carcinoma (HCC) was decreased. In vitro, miR-208-3p down-regulation and ARID2 over-expression elicited similar inhibitory effects on HCC cell proliferation and invasion. In vivo test results revealed that miR-208-3p down-regulation inhibited HCC tumorigenesis in Hep3B cells. Moreover, ARID2 was possibly a downstream element of transforming growth factor beta1 (TGFß1)/miR-208-3p/ARID2 regulatory pathway. These findings suggested that miR-208-3p up-regulation is associated with HCC cell progression and may provide a new target for liver cancer treatment.

Personalized decision support system for tailoring IgA nephropathy treatment strategies.

BACKGROUND: The ongoing debate surrounding the use of immunosuppressive treatments for IgA nephropathy (IgAN) underscores the demand for personalized and effective strategies. METHODS: Analyzed data from 807 IgAN patients over 5+ years using three methods: Random Forest with molecular biomarkers, network biomarkers with graph engineering, and an auto-encoder model. All models were trained using identical demographic, clinical, and pathological data, employing an 80-20 split for training and testing purposes. RESULTS: In the comprehensive assessment of IgAN prognosis, the Random Forest model, employing molecular biomarkers, demonstrated strong performance metrics (AUC = 0.83, sensitivity = 0.51, specificity = 0.96). However, traditional graph feature engineering on patient-specific networks outperformed these results with an AUC of 0.90, sensitivity of 0.64, and specificity of 0.94. The Auto-encoder model showed the best accuracy (AUC = 0.91, sensitivity = 0.46, specificity = 0.96). The findings highlighted the superior predictive capabilities of network biomarkers over molecular biomarkers for adverse renal outcome prediction in IgAN. Consequently, we integrated Auto-encoder-derived Network Biomarkers with Random Forest Models to enhance prognostic precision in diverse IgAN treatment scenarios. The prediction for the prognosis of patients receiving supportive care, glucocorticoid therapy, and immunosuppressant treatment yielded AUC values of 0.95, 0.96, and 1, respectively, indicating high specificity. Drawing from these insights, we pioneered the development of an innovative decision support model for IgAN treatment. This model demonstrated the ability to make medical decisions comparable to those by experienced nephrologists, enabling the customization of personalized disease management strategies. CONCLUSION: Our system accurately predicted IgAN prognosis and evaluated various treatment efficacies, aiding physicians in devising optimal therapeutic strategies for patients.

Association between the triglyceride-glucose index and chronic kidney disease in adults.

BACKGROUND: Chronic kidney disease (CKD) is characterized as a progressive dysfunction of the kidney, and it might have a close relationship with insulin resistance. We utilized the triglyceride-glucose (TyG) index, a reliable marker of insulin resistance, to evaluate the association between the TyG index and CKD in adults from the general population. METHODS: This was a cross-sectional study obtaining data from the 2015-2018 National Health and Nutrition Examination Survey. The estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) served as kidney function indicators. We defined CKD as the existence of either low eGFR (eGFR < 60 mL/min/1.73 m2 BSA) or albuminuria (UACR > 30 mg/g). Multivariate regressions, correlated subgroup analyses, and interaction terms were performed in this study. RESULTS: For 4361 recruited participants, the mean TyG index was 8.60 ± 0.68, and the prevalence of CKD was 13.35%. Participants with a higher TyG index showed a higher UACR level (ß = 25.10, 95% CI: 6.76, 43.44, P = 0.0074) and higher levels of CKD (OR = 1.34, 95% CI: 1.13, 1.59, P = 0.0006). The positive relationship between the TyG index and CKD became stronger and remained significant in the overweight (OR = 1.61, 95% CI: 1.18, 2.20, P = 0.0027) and obese (OR = 2.48, 95% CI: 1.95, 3.15, P < 0.0001) groups and in people with diabetes (OR = 1.94, 95% CI: 1.46, 2.56, P < 0.0001). CONCLUSIONS: Higher TyG index was strongly associated with a higher UACR level and higher values of albuminuria and CKD, which might be useful in kidney function screening especially among people in disadvantageous socioeconomic conditions with no availability for direct measurement of kidney function. However, more well-designed studies are still needed to validate this relationship.