Effect of Different Treatment Modalities for Condylar Fractures in Childhood on Mandibular Symmetry and Temporomandibular Joint Function: A Retrospective Study.

OBJECTIVE: In a retrospective study of the effects of different treatment modalities of condylar fractures in childhood on mandibular symmetry and temporomandibular function, the cases selected for this article were adult patients who had sustained a condylar fracture in childhood. The aim was to investigate the effects of condylar fractures in children on the development and function of the mandible and their specific manifestations after the completion of mandibular development. METHODS: According to the different treatment modalities, the patients were divided into the conservative treatment group and the open surgical treatment group, and the effects of the 2 treatment modalities on the patients' condylar healing, the difference in growth ability, and the symmetry of the jaws were evaluated. The effects of different treatment modalities of children's condylar fracture on the growth, development, and function of the mandible were investigated using the Ai and Di, the grading of the imaging results, and the 3-dimensional CT fixation measurements from the aspects of both clinical examination and imaging examination. RESULTS: The 2 groups had condylar malalignment and condylar morphology abnormality, and there was one case of joint ankylosis in the surgical treatment group. There was a statistical difference in the evaluation of condylar reconstruction between the 2 groups, and the condylar reconstruction in the surgical treatment group was better than that in the conservative treatment, and there was a statistical difference between the condylar length, condylar width, condylar height, and depth of TMJ fossa between the healthy side and the affected side in the closed treatment group. There was a statistical difference in the height of the mandibular ascending branch between the healthy side and the affected side, and the unilateral condylar fracture was treated conservatively; the difference in the bony chin point deviation between the 2 groups was not statistically significant. CONCLUSION: In children, after conservative treatment of condylar fracture, the growth of condylar process is poor, and the condylar shape and position are not as good as surgical repositioning, but through the proliferation of temporomandibular joint fossa, it can make up for the insufficient height of condylar process, which has no effect on the symmetry of the mandible, and the surgical treatment can achieve good anatomical repositioning, which has a greater effect on the symmetry of the mandible than the conservative treatment.

The role of macrophage-derived Exosomes in reversing peritoneal fibrosis: Insights from Astragaloside IV.

BACKGROUND: Peritoneal dialysis (PD) is a successful renal replacement therapy for end-stage renal disease. Long-term PD causes mesothelial-mesenchymal transition (MMT) of peritoneal mesothelial cells (PMCs), leading to peritoneal fibrosis (PF), which reduces the efficiency of PD. Macrophages are thought to play a role in the onset and perpetuation of peritoneal injury. However, the mechanisms by which macrophages-PMCs communication regulates peritoneal fibrosis are not fully understood resulting in a lack of disease-modifying drugs. Astragaloside IV (AS-IV) possessed anti-fibrotic effect towards PF in PD whereas the mechanistic effect of AS-IV in PD is unknown. METHODS: The primary macrophages were extracted and treated with LPS or AS-IV, then co-cultured with primary PMCs in transwell plates. The macrophage-derived exosomes were extracted and purified by differential centrifugation, then co-cultured with primary PMCs. Small RNA-seq was used to detect differential miRNAs in exosomes, and then KEGG analysis and q-PCR were performed for validation. In vivo PD rat models were established by inducing with high-glucose peritoneal dialysis fluid and different concentrations of AS-IV and exosomes were intraperitoneal injection. Through qRT-PCR, western blotting, and luciferase reporting, candidate proteins and pathways were validated in vivo and in vitro. The functions of the validated pathways were further investigated using the mimic or inhibition strategy. PF and inflammatory situations were assessed. RESULTS: We found AS-IV reversed the MMT of PMCs caused by LPS-stimulated macrophages and the improving effect was mediated by macrophage-derived exosomes in vitro. We also demonstrated that AS-IV significantly reduced the MMT of PMCs in vitro or PF in a rat PD model via regulating exosome-contained miR-204-5p which targets Foxc1/ß-catenin signaling pathway. CONCLUSION: AS-IV attenuates macrophage-derived exosomes induced fibrosis in PD through the miR-204-5p/Foxc1 pathway.

A non-image-forming visual circuit mediates the innate fear of heights in male mice.

The neural basis of fear of heights remains largely unknown. In this study, we investigated the fear response to heights in male mice and observed characteristic aversive behaviors resembling human height vertigo. We identified visual input as a critical factor in mouse reactions to heights, while peripheral vestibular input was found to be nonessential for fear of heights. Unexpectedly, we found that fear of heights in naïve mice does not rely on image-forming visual processing by the primary visual cortex. Instead, a subset of neurons in the ventral lateral geniculate nucleus (vLGN), which connects to the lateral/ventrolateral periaqueductal gray (l/vlPAG), drives the expression of fear associated with heights. Additionally, we observed that a subcortical visual pathway linking the superior colliculus to the lateral posterior thalamic nucleus inhibits the defensive response to height threats. These findings highlight a rapid fear response to height threats through a subcortical visual and defensive pathway from the vLGN to the l/vlPAG.

Green and Efficient Extraction of Phenolic Components from Plants with Supramolecular Solvents: Experimental and Theoretical Studies.

The supramolecular solvent (SUPRAS) has garnered significant attention as an innovative, efficient, and environmentally friendly solvent for the effective extraction and separation of bioactive compounds from natural resources. However, research on the use of a SUPRAS for the extraction of phenolic compounds from plants, which are highly valued in food products due to their exceptional antioxidant properties, remains scarce. The present study developed a green, ultra-sound-assisted SUPRAS method for the simultaneous determination of three phenolic acids in Prunella vulgaris using high-performance liquid chromatography (HPLC). The experimental parameters were meticulously optimized. The efficiency and antioxidant properties of the phenolic compounds obtained using different extraction methods were also compared. Under optimal conditions, the extraction efficiency of the SUPRAS, prepared with octanoic acid reverse micelles dispersed in ethanol-water, significantly exceeded that of conventional organic solvents. Moreover, the SUPRAS method demonstrated greater antioxidant capacity. Confocal laser scanning microscopy (CLSM) images revealed the spherical droplet structure of the SUPRAS, characterized by a well-defined circular fluorescence position, which coincided with the position of the phenolic acids. The phenolic acids were encapsulated within the SUPRAS droplets, indicating their efficient extraction capacity. Furthermore, molecular dynamics simulations combined with CLSM supported the proposed method's mechanism and theoretically demonstrated the superior extraction performance of the SUPRAS. In contrast to conventional methods, the higher extraction efficiency of the SUPRAS can be attributed to the larger solvent contact surface area, the formation of more types of hydrogen bonds between the extractants and the supramolecular solvents, and stronger, more stable interaction forces. The results of the theoretical studies corroborate the experimental outcomes.

Integrative Analyses of Bulk and Single-Cell RNA Seq Identified the Shared Genes in Acute Respiratory Distress Syndrome and Rheumatoid Arthritis.

Acute respiratory distress syndrome (ARDS), a progressive status of acute lung injury (ALI), is primarily caused by an immune-mediated inflammatory disorder, which can be an acute pulmonary complication of rheumatoid arthritis (RA). As a chronic inflammatory disease regulated by the immune system, RA is closely associated with the occurrence and progression of respiratory diseases. However, it remains elusive whether there are shared genes between the molecular mechanisms underlying RA and ARDS. The objective of this study is to identify potential shared genes for further clinical drug discovery through integrated analysis of bulk RNA sequencing datasets obtained from the Gene Expression Omnibus database, employing differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA). The hub genes were identified through the intersection of common DEGs and WGCNA-derived genes. The Random Forest (RF) and least absolute shrinkage and selection operator (LASSO) algorithms were subsequently employed to identify key shared target genes associated with two diseases. Additionally, RA immune infiltration analysis and COVID-19 single-cell transcriptome analysis revealed the correlation between these key genes and immune cells. A total of 59 shared genes were identified from the intersection of DEGs and gene clusters obtained through WGCNA, which analyzed the integrated gene matrix of ALI/ARDS and RA. The RF and LASSO algorithms were employed to screen for target genes specific to ALI/ARDS and RA, respectively. The final set of overlapping genes (FCMR, ADAM28, HK3, GRB10, UBE2J1, HPSE, DDX24, BATF, and CST7) all exhibited a strong predictive effect with an area under the curve (AUC) value greater than 0.8. Then, the immune infiltration analysis revealed a strong correlation between UBE2J1 and plasma cells in RA. Furthermore, scRNA-seq analysis demonstrated differential expression of these nine target genes primarily in T cells and NK cells, with CST7 showing a significant positive correlation specifically with NK cells. Beyond that, transcriptome sequencing was conducted on lung tissue collected from ALI mice, confirming the substantial differential expression of FCMR, HK3, UBE2J1, and BATF. This study provides unprecedented evidence linking the pathophysiological mechanisms of ALI/ARDS and RA to immune regulation, which offers novel understanding for future clinical treatment and experimental research.

Simulating short-term light responses of photosynthesis and water use efficiency in sweet sorghum under varying temperature and CO2 conditions.

Climate change, characterized by rising atmospheric CO2 levels and temperatures, poses significant challenges to global crop production. Sweet sorghum, a prominent C4 cereal extensively grown in arid areas, emerges as a promising candidate for sustainable bioenergy production. This study investigated the responses of photosynthesis and leaf-scale water use efficiency (WUE) to varying light intensity (I) in sweet sorghum under different temperature and CO2 conditions. Comparative analyses were conducted between the A n-I, g s-I, T r-I, WUEi-I, and WUEinst-I models proposed by Ye et al. and the widely utilized the non-rectangular hyperbolic (NRH) model for fitting light response curves. The Ye's models effectively replicated the light response curves of sweet sorghum, accurately capturing the diminishing intrinsic WUE (WUEi) and instantaneous WUE (WUEinst) trends with increasing I. The fitted maximum values of A n, g s, T r, WUEi, and WUEinst and their saturation light intensities closely matched observations, unlike the NRH model. Despite the NRH model demonstrating high R 2 values for A n-I, g s-I, and T r-I modelling, it returned the maximum values significantly deviating from observed values and failed to generate saturation light intensities. It also inadequately represented WUE responses to I, overestimating WUE. Across different leaf temperatures, A n, g s, and T r of sweet sorghum displayed comparable light response patterns. Elevated temperatures increased maximum A n, g s, and T r but consistently declined maximum WUEi and WUEinst. However, WUEinst declined more sharply due to the disproportionate transpiration increase over carbon assimilation. Critically, sweet sorghum A n saturated at current atmospheric CO2 levels, with no significant gains under 550 µmol mol-1. Instead, stomatal closure enhanced WUE under elevated CO2 by coordinated g s and T r reductions rather than improved carbon assimilation. Nonetheless, this response diminished under simultaneously high temperature, suggesting intricate interplay between CO2 and temperature in modulating plant responses. These findings provide valuable insights into photosynthetic dynamics of sweet sorghum, aiding predictions of yield and optimization of cultivation practices. Moreover, our methodology serves as a valuable reference for evaluating leaf photosynthesis and WUE dynamics in diverse plant species.

Clinical outcomes and clinico-pathological correlations in children with MPO-ANCA-associated glomerulonephritis showing renal arteritis.

The aim of this study was to evaluate the clinical features, pathological characteristics, and prognosis in myeloperoxidase (MPO)-antineutrophil cytoplasmic antibodies (ANCA)-associated glomerulonephritis (AAGN) with renal arteritis. The study involved 97 children from five pediatric clinical centers with MPO-AAGN who exhibited distinct clinical features. The patients were divided into AAGN-A+ and AAGN-A-, based on the presence or absence of arteritis, and the disparities in clinical, histopathological characteristics, and prognosis between the two groups was evaluated. In contrast to the AAGN-A- group, the children in the AAGN-A+ group exhibited more pronounced clinical symptoms and renal pathological injury. Arteritis positively moderately correlated with the serum creatinine, interleukin-6, urinary neutrophil gelatinase-associated lipocalin, negatively moderately correlated with serum complement C3. The renal survival rate in the AAGN-A+ group was significantly poorer than AAGN-A- group (χ2 = 4.278, p = 0.039). Arteritis showed a good predictive value for end-stage kidney disease (ESKD), and C3 deposition, ANCA renal risk score and arteritis were independent risk factors for the development of ESKD in children with MPO-AAGN. Arteritis is a significant pathological change observed in children with MPO-AAGN, and the formation of arteritis may be related to the inflammatory response and activation of the complement system.

On-device phase engineering.

In situ tailoring of two-dimensional materials' phases under external stimulus facilitates the manipulation of their properties for electronic, quantum and energy applications. However, current methods are mainly limited to the transitions among phases with unchanged chemical stoichiometry. Here we propose on-device phase engineering that allows us to realize various lattice phases with distinct chemical stoichiometries. Using palladium and selenide as a model system, we show that a PdSe2 channel with prepatterned Pd electrodes can be transformed into Pd17Se15 and Pd4Se by thermally tailoring the chemical composition ratio of the channel. Different phase configurations can be obtained by precisely controlling the thickness and spacing of the electrodes. The device can be thus engineered to implement versatile functions in situ, such as exhibiting superconducting behaviour and achieving ultralow-contact resistance, as well as customizing the synthesis of electrocatalysts. The proposed on-device phase engineering approach exhibits a universal mechanism and can be expanded to 29 element combinations between a metal and chalcogen. Our work highlights on-device phase engineering as a promising research approach through which to exploit fundamental properties as well as their applications.

Systemic immune-inflammation index and all-cause and cause-specific mortality in sarcopenia: a study from National Health and Nutrition Examination Survey 1999-2018.

Background: Sarcopenia, common in the elderly, often linked to chronic diseases, correlates with inflammation.The association between SII and mortality in sarcopenia patients is underexplored, this study investigates this relationship in a U.S. adult cohort. Methods: We analyzed 1999-2018 NHANES data, focusing on 2,974 adults with sarcopenia. Mortality outcomes were determined by linking to National Death Index (NDI) records up to December 31, 2019. Using a weighted sampling design, participants were grouped into three groups by the Systemic Immune-Inflammation Index (SII). We used Cox regression models, adjusting for demographic and clinical variables, to explore SII's association with all-cause and cause-specific mortality in sarcopenia, performing sensitivity analyses for robustness. Results: Over a median follow-up of 9.2 years, 829 deaths occurred. Kaplan-Meier analysis showed significant survival differences across SII groups. The highest SII group showed higher hazard ratios (HRs) for all-cause and cause-specific mortality in both crude and adjusted models. The highest SII group had a higher HR for all-cause(1.57, 1.25-1.98), cardiovascular(1.61, 1.00-2.58), cancer(2.13, 1.32-3.44), and respiratory disease mortality(3.21, 1.66-6.19) in fully adjusted models. Subgroup analyses revealed SII's association with all-cause mortality across various demographics, including age, gender, and presence of diabetes or cardiovascular disease. Sensitivity analyses, excluding participants with cardiovascular diseases, those who died within two years of follow-up, or those under 45 years of age, largely reflected these results, with the highest SII group consistently demonstrating higher HRs for all types of mortality in both unadjusted and adjusted models. Conclusion: Our study is the first to demonstrate a significant relationship between SII and increased mortality risks in a sarcopenia population.

Excitotoxic Storms of Ischemic Stroke: A Non-neuronal Perspective.

Numerous neurological disorders share a fatal pathologic process known as glutamate excitotoxicity. Among which, ischemic stroke is the major cause of mortality and disability worldwide. For a long time, the main idea of developing anti-excitotoxic neuroprotective agents was to block glutamate receptors. Despite this, there has been little successful clinical translation to date. After decades of "neuron-centered" views, a growing number of studies have recently revealed the importance of non-neuronal cells. Glial cells, cerebral microvascular endothelial cells, blood cells, and so forth are extensively engaged in glutamate synthesis, release, reuptake, and metabolism. They also express functional glutamate receptors and can listen and respond for fast synaptic transmission. This broadens the thoughts of developing excitotoxicity antagonists. In this review, the critical contribution of non-neuronal cells in glutamate excitotoxicity during ischemic stroke will be emphasized in detail, and the latest research progress as well as corresponding therapeutic strategies will be updated at length, aiming to reconceptualize glutamate excitotoxicity in a non-neuronal perspective.

Metabolomics distinguishes different grades of Scrophularia ningpoensis hemsl: Towards a biomarker discovery and quality evaluation.

In managing unique complexities associated with Chinese medicinal quality assessment, metabolomics serves as an innovative tool. This study proposes an analytical approach to assess differing qualities of Scrophularia ningpoensis （S. ningpoensis）Hemsl by identifying potential biomarker metabolites and their activity with the corresponding secondary metabolites. The methodology includes four steps; first, a GC-MS based metabolomics exploration of the Scrophularia ningpoensis Hemsl. Second, a multivariate statistical analysis (PCA, PLS-DA, OPLS-DA) for quality assessment and biomarker identification. Third, the application of ROC analysis and pathway analysis based on identified biomarkers. Finally, validation of the associated active ingredients by HPLC. The analysis showed distinct metabolite profiles across varying grades of S. ningpoensis Hemsl, establishing a grading dependency relationship. Select biomarkers (gluconic Acid, d-xylulose, sucrose, etc.) demonstrated robust grading performances. Further, the Pentose Phosphate Pathway, deemed as most influential in grading, was tied to the synthesis of key constituents (iridoids, phenylpropanoids). HPLC validation tests affirm a decreasing trend in harpagoside and cinnamic acid levels between first and third-grade samples. In conclusion, this GC-MS based metabolomics combined HPLC method offers a sound approach to assess and distinguish quality variations in S. ningpoensis Hemsl samples.

Radiomics model based on MRI to differentiate spinal multiple myeloma from metastases: A two-center study.

Purpose: Spinal multiple myeloma (MM) and metastases are two common cancer types with similar imaging characteristics, for which differential diagnosis is needed to ensure precision therapy. The aim of this study is to establish radiomics models for effective differentiation between them. Methods: Enrolled in this study were 263 patients from two medical institutions, including 127 with spinal MM and 136 with spinal metastases. Of them, 210 patients from institution I were used as the internal training cohort and 53 patients from Institution II were used as the external validation cohort. Contrast-enhanced T1-weighted imaging (CET1) and T2-weighted imaging (T2WI) sequences were collected and reviewed. Based on the 1037 radiomics features extracted from both CET1 and T2WI images, Logistic Regression (LR), AdaBoost (AB), Support Vector Machines (SVM), Random Forest (RF), and multiple kernel learning based SVM (MKL-SVM) were constructed. Hyper-parameters were tuned by five-fold cross-validation. The diagnostic efficiency among different radiomics models was compared by accuracy (ACC), sensitivity (SEN), specificity (SPE), area under the ROC curve (AUC), YI, positive predictive value (PPV), negative predictive value (NPY), and F1-score. Results: Based on single-sequence, the RF model outperformed all other models. All models based on T2WI images performed better than those based on CET1. The efficiency of all models was boosted by incorporating CET1 and T2WI sequences, and the MKL-SVM model achieved the best performance with ACC, AUC, and F1-score of 0.862, 0.870, and 0.874, respectively. Conclusions: The radiomics models constructed based on MRI achieved satisfactory diagnostic performance for differentiation of spinal MM and metastases, demonstrating broad application prospects for individualized diagnosis and treatment.

Involution Transformer based U-Net for Landmark Detection in Ultrasound Images for Diagnosis of Infantile DDH.

The B-mode ultrasound based computer-aided diagnosis (CAD) has demonstrated its effectiveness for diagnosis of Developmental Dysplasia of the Hip (DDH) in infants, which can conduct the Graf's method by detecting landmarks in hip ultrasound images. However, it is still necessary to explore more valuable information around these landmarks to enhance feature representation for improving detection performance in the detection model. To this end, a novel Involution Transformer based U-Net (IT-UNet) network is proposed for hip landmark detection. The IT-UNet integrates the efficient involution operation into Transformer to develop an Involution Transformer module (ITM), which consists of an involution attention block and a squeeze-and-excitation involution block. The ITM can capture both the spatial-related information and long-range dependencies from hip ultrasound images to effectively improve feature representation. Moreover, an Involution Downsampling block (IDB) is developed to alleviate the issue of feature loss in the encoder modules, which combines involution and convolution for the purpose of downsampling. The experimental results on two DDH ultrasound datasets indicate that the proposed IT-UNet achieves the best landmark detection performance, indicating its potential applications.

Mitochondrial tRNA pseudouridylation governs erythropoiesis.

Pseudouridine is the most prevalent RNA modification, and its aberrant function is implicated in various human diseases. However, the specific impact of pseudouridylation on hematopoiesis remains poorly understood. In this study, we investigated the role of tRNA pseudouridylation in erythropoiesis and its association with mitochondrial myopathy, lactic acidosis, and sideroblastic anemia syndrome (MLASA) pathogenesis. By utilizing patient-specific induced pluripotent stem cells (iPSCs) carrying a genetic PUS1 mutation and a corresponding mutant mouse model, we demonstrated impaired erythropoiesis in MLASA iPSCs and anemia in the MLASA mouse model. Both MLASA iPSCs and mouse erythroblasts exhibited compromised mitochondrial function and impaired protein synthesis. Mechanistically, we revealed that PUS1 deficiency resulted in reduced mitochondrial tRNA levels due to pseudouridylation loss, leading to aberrant mitochondrial translation. Screening of mitochondrial supplements aimed at enhancing respiration or heme synthesis showed limited effect in promoting erythroid differentiation. Interestingly, the mTOR inhibitor rapamycin facilitated erythroid differentiation in MLASA-iPSCs by suppressing mTOR signaling and protein synthesis, and consistent results were observed in the MLASA mouse model. Importantly, rapamycin treatment effectively ameliorated anemia phenotypes in the MLASA patient. Our findings provide novel insights into the crucial role of mitochondrial tRNA pseudouridylation in governing erythropoiesis and present potential therapeutic strategies for anemia patients facing challenges related to protein translation.

Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging.

Identifying the progression stages of Alzheimer's disease (AD) can be considered as an imbalanced multi-class classification problem in machine learning. It is challenging due to the class imbalance issue and the heterogeneity of the disease. Recently, graph convolutional networks (GCNs) have been successfully applied in AD classification. However, these works did not handle the class imbalance issue in classification. Besides, they ignore the heterogeneity of the disease. To this end, we propose a novel cost-sensitive weighted contrastive learning method based on graph convolutional networks (CSWCL-GCNs) for imbalanced AD staging using resting-state functional magnetic resonance imaging (rs-fMRI). The proposed method is developed on a multi-view graph constructed using the functional connectivity (FC) and high-order functional connectivity (HOFC) features of the subjects. A novel cost-sensitive weighted contrastive learning procedure is proposed to capture discriminative information from the minority classes, encouraging the samples in the minority class to provide adequate supervision. Considering the heterogeneity of the disease, the weights of the negative pairs are introduced into contrastive learning and they are computed based on the distance to class prototypes, which are automatically learned from the training data. Meanwhile, the cost-sensitive mechanism is further introduced into contrastive learning to handle the class imbalance issue. The proposed CSWCL-GCN is evaluated on 720 subjects (including 184 NCs, 40 SMC patients, 208 EMCI patients, 172 LMCI patients and 116 AD patients) from the ADNI (Alzheimer's Disease Neuroimaging Initiative). Experimental results show that the proposed CSWCL-GCN outperforms state-of-the-art methods on the ADNI database.

Histopathology language-image representation learning for fine-grained digital pathology cross-modal retrieval.

Large-scale digital whole slide image (WSI) datasets analysis have gained significant attention in computer-aided cancer diagnosis. Content-based histopathological image retrieval (CBHIR) is a technique that searches a large database for data samples matching input objects in both details and semantics, offering relevant diagnostic information to pathologists. However, the current methods are limited by the difficulty of gigapixels, the variable size of WSIs, and the dependence on manual annotations. In this work, we propose a novel histopathology language-image representation learning framework for fine-grained digital pathology cross-modal retrieval, which utilizes paired diagnosis reports to learn fine-grained semantics from the WSI. An anchor-based WSI encoder is built to extract hierarchical region features and a prompt-based text encoder is introduced to learn fine-grained semantics from the diagnosis reports. The proposed framework is trained with a multivariate cross-modal loss function to learn semantic information from the diagnosis report at both the instance level and region level. After training, it can perform four types of retrieval tasks based on the multi-modal database to support diagnostic requirements. We conducted experiments on an in-house dataset and a public dataset to evaluate the proposed method. Extensive experiments have demonstrated the effectiveness of the proposed method and its advantages to the present histopathology retrieval methods. The code is available at https://github.com/hudingyi/FGCR.

Analysis of related factors of CRA in lung cancer patients with different serum iron levels: A retrospective cohort study.

BACKGROUND: Serum iron, an essential component of hemoglobin (Hb) synthesis in vivo, is a crucial parameter for evaluating the body's iron storage and metabolism capacity. Iron deficiency leads to reduced Hb synthesis in red blood cells and smaller red blood cell volume, ultimately resulting in iron-deficiency anemia. Although serum iron cannot independently evaluate iron storage or metabolism ability, it can reflect iron concentration in vivo and serve as a good predictor of iron-deficiency anemia. Therefore, exploring the influence of different serum iron levels on anemia and diagnosing and treating iron deficiency in the early stages is of great significance for patients with lung cancer. AIM: This study aims to explore the related factors of cancer-related anemia (CRA) in lung cancer and construct a nomogram prediction model to evaluate the risk of CRA in patients with different serum iron levels. METHODS: A single-center retrospective cohort study was conducted, including 1610 patients with lung cancer, of whom 1040 had CRA. The relationship between CRA and its influencing factors was analyzed using multiple linear regression models. Lung cancer patients were divided into two groups according to their serum iron levels: decreased serum iron and normal serum iron. Each group was randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The influencing factors were screened by univariate and multivariate logistic regression analyses, and nomogram models were constructed. The area under the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the models. RESULTS: CRA in lung cancer is mainly related to surgery, chemotherapy, Karnofsky Performance Status (KPS) score, serum iron, C-reactive protein (CRP), albumin, and total cholesterol (p < 0.05). CRA in lung cancer patients with decreased serum iron is primarily associated with albumin, age, and cancer staging, while CRA in lung cancer patients with normal serum iron is mainly related to CRP, albumin, total cholesterol, and cancer staging. The area under the ROC curve of the training cohort and validation cohort for the prediction model of lung cancer patients with decreased serum iron was 0.758 and 0.760, respectively. Similarly, the area under the ROC curve of the training cohort and validation cohort for the prediction model of lung cancer patients with normal serum iron was 0.715 and 0.730, respectively. The calibration curves of both prediction models were around the ideal 45° line, suggesting good discrimination and calibration. DCA showed that the nomograms had good clinical utility. CONCLUSION: Both models have good reliability and validity and have significant clinical value. They can help doctors better assess the risk of developing CRA in lung cancer patients. CRP is a risk factor for CRA in lung cancer patients with normal serum iron but not in patients with decreased serum iron. Therefore, whether CRP and the inflammatory state represented by CRP will further aggravate the decrease in serum iron levels, thus contributing to anemia, warrants further study.

Exploring the effective compounds and potential mechanisms of Shengxian Decoction against coronary heart disease by UPLC-Q-TOF/MS and network pharmacology analysis.

As a well-known classical Chinese medicine prescription, Shengxian Decoction (SXD) has been applied for a century to treat cardiovascular diseases, especially coronary heart disease (CHD), but the potentially effective compounds and underlying mechanisms remain unclear. With ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF/MS) and network pharmacology analysis, the potential effective compounds of SXD and their pharmacological mechanisms against CHD were identified and revealed. 57 effective compounds with favorable pharmacokinetic characteristics and biological activities were screened through UPLC-Q-TOF/MS analysis, database and literature mining, interacting with 96 CHD-related targets to support potential synergistic therapeutic actions. Systematic analysis of the PPI network and microarray data further revealed six core targets, including TNF, IL-1ß, IL-6, TP53, VEGFA and PTGS2, which were mainly involved in fluid shear stress and atherosclerosis, lipid and atherosclerosis, PI3K-Akt signaling pathway et al. Moreover, the proposed contribution indexes of effective compounds indicated these compounds, including isoferulic acid, quercetin, calycosin, ferulic acid, kaempferol, calycosin 7-O-glycoside, formononetin, astragaloside IV and saikosaponin D, as the core compounds of SXD. The molecular docking results confirmed that those core compound-target pairs exhibited strong binding energy. Furthermore, we validated that SXD significantly alleviated myocardial tissue injury in CHD rats and reversed H/R-induced decreases in H9c2 cell viability by attenuating the production of TNF, IL-6 and IL-1ß, and reducing cardiomyocyte apoptosis via down-regulating the TP53, caspase3 and cytochrome C mRNA expression levels as well as caspase3, caspase9 and cytochrome C protein expression levels according to RT-qPCR and Western blot results. Our findings explained the pharmacological mechanisms underlying the effectiveness of SXD in the treatment of CHD, and laid a foundation for future basic and clinical research of SXD.

Systematic Optimization of Universal Real-Time Hypersensitive Fast Detection Method for HBsAg in Serum Based on SERS.

Hepatitis B virus (HBV) is a major cause of liver cirrhosis and hepatocellular carcinoma, with HBV surface antigen (HBsAg) being a crucial marker in the clinical detection of HBV. Due to the significant harm and ease of transmission associated with HBV, HBsAg testing has become an essential part of preoperative assessments, particularly for emergency surgeries where healthcare professionals face exposure risks. Therefore, a timely and accurate detection method for HBsAg is urgently needed. In this study, a surface-enhanced Raman scattering (SERS) sensor with a sandwich structure was developed for HBsAg detection. Leveraging the ultrasensitive and rapid detection capabilities of SERS, this sensor enables quick detection results, significantly reducing waiting times. By systematically optimizing critical factors in the detection process, such as the composition and concentration of the incubation solution as well as the modification conditions and amount of probe particles, the sensitivity of the SERS immune assay system was improved. Ultimately, the sensor achieved a sensitivity of 0.00576 IU/mL within 12 min, surpassing the clinical requirement of 0.05 IU/mL by an order of magnitude. In clinical serum assay validation, the issue of false positives was effectively addressed by adding a blocker. The final sensor demonstrated 100% specificity and sensitivity at the threshold of 0.05 IU/mL. Therefore, this study not only designed an ultrasensitive SERS sensor for detecting HBsAg in actual clinical serum samples but also provided theoretical support for similar systems, filling the knowledge gap in existing literature.

Interplay of IL-17A/IL-17RA signaling with microbial homeostasis in systemic anti-tumoral responses.

Enteric IL-17RA deficiency leads to gut dysbiosis, consequently initiating the proliferation of tumors at remote locations. The deficiency or blockade of enteric IL-17RA induces the secretion of IL-17A by B cells and Th17 cells in response to microbial signals, resulting in a systemic elevation of IL-17A and fostering the growth of remote tumors. This figure was created with BioRender.com.