Primed and ready: nanopore metabarcoding can now recover highly accurate consensus barcodes that are generally indel-free.

BACKGROUND: DNA metabarcoding applies high-throughput sequencing approaches to generate numerous DNA barcodes from mixed sample pools for mass species identification and community characterisation. To date, however, most metabarcoding studies employ second-generation sequencing platforms like Illumina, which are limited by short read lengths and longer turnaround times. While third-generation platforms such as the MinION (Oxford Nanopore Technologies) can sequence longer reads and even in real-time, application of these platforms for metabarcoding has remained limited possibly due to the relatively high read error rates as well as the paucity of specialised software for processing such reads. RESULTS: We show that this is no longer the case by performing nanopore-based, cytochrome c oxidase subunit I (COI) metabarcoding on 34 zooplankton bulk samples, and benchmarking the results against conventional Illumina MiSeq sequencing. Nanopore R10.3 sequencing chemistry and super accurate (SUP) basecalling model reduced raw read error rates to ~ 4%, and consensus calling with amplicon_sorter (without further error correction) generated metabarcodes that were ≤ 1% erroneous. Although Illumina recovered a higher number of molecular operational taxonomic units (MOTUs) than nanopore sequencing (589 vs. 471), we found no significant differences in the zooplankton communities inferred between the sequencing platforms. Importantly, 406 of 444 (91.4%) shared MOTUs between Illumina and nanopore were also found to be free of indel errors, and 85% of the zooplankton richness could be recovered after just 12-15 h of sequencing. CONCLUSION: Our results demonstrate that nanopore sequencing can generate metabarcodes with Illumina-like accuracy, and we are the first study to show that nanopore metabarcodes are almost always indel-free. We also show that nanopore metabarcoding is viable for characterising species-rich communities rapidly, and that the same ecological conclusions can be obtained regardless of the sequencing platform used. Collectively, our study inspires confidence in nanopore sequencing and paves the way for greater utilisation of nanopore technology in various metabarcoding applications.

Innovative biomarkers TCN2 and LY6E can significantly inhibit respiratory syncytial virus infection.

BACKGROUND: Respiratory syncytial virus (RSV) is a prominent etiological agent of lower respiratory tract infections in children, responsible for approximately 80% of cases of pediatric bronchiolitis and 50% of cases of infant pneumonia. Despite notable progress in the diagnosis and management of pediatric RSV infection, the current biomarkers for early-stage detection remain insufficient to meet clinical needs. Therefore, the development of more effective biomarkers for early-stage pediatric respiratory syncytial virus infection (EPR) is imperative. METHODS: The datasets used in this study were derived from the Gene Expression Omnibus (GEO) database. We used GSE188427 dataset as the training set to screen for biomarkers. Biomarkers of EPR were screened by Weighted Gene Co-expression Network Analysis (WGCNA), three machine-learning algorithms (LASSO regression, Random Forest, XGBoost), and other comprehensive bioinformatics analysis techniques. To evaluate the diagnostic value of these biomarkers, multiple external and internal datasets were employed as validation sets. Next, an examination was performed to investigate the relationship between the screened biomarkers and the infiltration of immune cells. Furthermore, an investigation was carried out to identify potential small molecule compounds that interact with selected diagnostic markers. Finally, we confirmed that the expression levels of the selected biomarkers exhibited a significant increase following RSV infection, and they were further identified as having antiviral properties. RESULTS: The study found that lymphocyte antigen 6E (LY6E) and Transcobalamin-2 (TCN2) are two biomarkers with diagnostic significance in EPR. Analysis of immune cell infiltration showed that they were associated with activation of multiple immune cells. Furthermore, our analysis demonstrated that small molecules, 3'-azido-3'-deoxythymine, methotrexate, and theophylline, have the potential to bind to TCN2 and exhibit antiviral properties. These compounds may serve as promising therapeutic agents for the management of pediatric RSV infections. Additionally, our data revealed an upregulation of LY6E and TCN2 expression in PBMCs from patients with RSV infection. ROC analysis indicated that LY6E and TCN2 possessed diagnostic value for RSV infection. Finally, we confirmed that LY6E and TCN2 expression increased after RSV infection and further inhibited RSV infection in A549 and BEAS-2B cell lines. Importantly, based on TCN2, our findings revealed the antiviral properties of a potentially efficacious compound, vitamin B12. CONCLUSION: LY6E and TCN2 are potential peripheral blood diagnostic biomarkers for pediatric RSV infection. LY6E and TCN2 inhibit RSV infection, indicating that LY6E and TCN2 are potential therapeutic target for RSV infection.

A physics-informed neural SDE network for learning cellular dynamics from time-series scRNA-seq data.

MOTIVATION: Learning cellular dynamics through reconstruction of the underlying cellular potential energy landscape (aka Waddington landscape) from time-series single-cell RNA sequencing (scRNA-seq) data is a current challenge. Prevailing data-driven computational methods can be hampered by the lack of physical principles to guide learning from complex data, resulting in reduced prediction accuracy and interpretability when applied to infer cell population dynamics. RESULTS: Here, we propose PI-SDE, a physics-informed neural stochastic differential equation (SDE) framework that combines the Hamilton-Jacobi (HJ) equation and neural SDE to learn cellular dynamics. Grounded in potential energy theory of biological systems, PI-SDE integrates the principle of least action by enforcing the HJ equation when reconstructing cellular potential energy function. This approach not only facilitates accurate predictions, but also improves interpretability, especially in the reconstructed potential energy landscape. Through benchmarking on two real scRNA-seq datasets, we demonstrate the importance of incorporating the HJ regularization term in dynamic inference, especially in predicting gene expression at held-out time points. Meanwhile, the learned potential energy landscape provides biologically interpretable insights into the process of cell differentiation. Our framework enhances model performance, while maintaining robustness and stability. AVAILABILITY: PI-SDE software is available at https://github.com/QiJiang-QJ/PI-SDE.

Graspot: a graph attention network for spatial transcriptomics data integration with optimal transport.

SUMMARY: Spatial transcriptomics (ST) technologies enable the measurement of mRNA expression while simultaneously capturing spot locations. By integrating ST data, the 3D structure of a tissue can be reconstructed, yielding a comprehensive understanding of the tissue's intricacies. Nevertheless, a computational challenge persists: how to remove batch effects while preserving genuine biological structure variations across ST data. To address this, we introduce Graspot, a graph attention network designed for spatial transcriptomics data integration with unbalanced optimal transport. Graspot adeptly harnesses both gene expression and spatial information to align common structures across multiple ST datasets. It embeds multiple ST datasets into a unified latent space, facilitating the partial alignment of spots from different slices. Demonstrating superior performance compared to existing methods on four real ST datasets, Graspot excels in ST data integration, including tasks that require partial alignment. In particular, Graspot efficiently integrates multiple ST slices and guides coordinate alignment. In addition, Graspot accurately aligns the spatio-temporal transcriptomics data to reconstruct human heart developmental processes. AVAILABILITY AND IMPLEMENTATION: Graspot software is available at https://github.com/zhan009/Graspot.

[Changes in Soil Organic Carbon Density and Its Response to Climate Change and Human Activities Before and After the Grain for Green Project on the Loess Plateau].

Accurately assessing the changes in soil organic carbon storage （SOCS） before and after the Grain for Green Project （GFG） in the Loess Plateau （LP） and exploring the relationship between its spatial and temporal distribution and the influencing factors were important references for the development of regional recycling as well as the formulation of ecological protection policies. Based on the data of climate, human activities, and SOCD in the surface （0-20 cm） and deep （0-100 cm） soil before and after GFG in the LP from 2001 to 2020, we investigated the changes in SOCD at different spatial and temporal scales by using the methods of trend analysis, the kriging method, and variance partitioning analysis. The results showed that： ① Before and after the GFG, the surface SOCS of the whole region increased by 8 338.7×104 t； the deep SOCS increased by 1 160.02×104 t. ② In each bioclimatic subregion, the whole-region average SOCD of Ⅰ （Semi-Humid Forest Region）, Ⅱ （Semi-Humid Semi-Arid Forest and Grassland Region）, and Ⅲ （Semi-Arid Typical Grassland Region） showed a significant increasing trend, with a decreasing trend in Ⅳ （arid semi-arid desert grassland area） and Ⅴ （arid desert area）. ③ The average surface SOCS increase in different ecosystems was ranked as follows： cropland > grassland > woodland > shrubs > bare land and sparse vegetation. The deep soil increase was ranked as follows： grassland > cropland > woodland > shrubs > bare land and sparse vegetation. ④ Climate factors were the most important driving factors for changes in SOCD； the annual average temperature and precipitation were significantly positively correlated with changes in SOCD. The results of the study could provide data support for regional ecological management and land use policy formulation to promote high quality development of the ecological environment in the LP.

Research progress on the effect of pyroptosis on the occurrence, development, invasion and metastasis of colorectal cancer.

Pyroptosis is a type of programmed cell death mediated by gasdermines (GSDMs). The N-terminal domain of GSDMs forms pores in the plasma membrane, causing cell membrane rupture and the release of cell contents, leading to an inflammatory response and mediating pyrodeath. Pyroptosis plays an important role in inflammatory diseases and malignant tumors. With the further study of pyroptosis, an increasing number of studies have shown that the pyroptosis pathway can regulate the tumor microenvironment and antitumor immunity of colorectal cancer and is closely related to the occurrence, development, treatment and prognosis of colorectal cancer. This review aimed to explore the molecular mechanism of pyroptosis and the role of pyroptosis in the occurrence, development, treatment and prognosis of colorectal cancer (CRC) and to provide ideas for the clinical diagnosis and treatment of CRC.

The partitioning of TCR repertoires by thymic selection.

αß T cells are critical components of the adaptive immune system; they maintain tissue and immune homeostasis during health, provide sterilizing immunity after pathogen infection, and are capable of eliminating transformed tumor cells. Fundamental to these distinct functions is the ligand specificity of the unique antigen receptor expressed on each mature T cell (TCR), which endows lymphocytes with the ability to behave in a cell-autonomous, disease context-specific manner. Clone-specific behavioral properties are initially established during T cell development when thymocytes use TCR recognition of major histocompatibility complex (MHC) and MHC-like ligands to instruct survival versus death and to differentiate into a plethora of inflammatory and regulatory T cell lineages. Here, we review the ligand specificity of the preselection thymocyte repertoire and argue that developmental stage-specific alterations in TCR signaling control cross-reactivity and foreign versus self-specificity of T cell sublineages.

Warthin tumor concomitant with mantle cell lymphoma: a case report and review of literature.

RATIONALE: Warthin tumor (WT) is the second most common benign tumor in salivary gland. It has a slow growth rate and most frequently occurs in the parotid gland. Most patients present with an incidental finding of a painless mass inferior/anterior to the ear. Besides the epithelial component of the tumor, WT is characteristically associated with lymphoid stroma that is considered benign. While there have been a few reports of malignant transformation of the lymphoid components in WT, cases of WT concomitant with mantle cell lymphoma (MCL) are extremely rare. To the best of our knowledge, two cases have been described in the English literature. Herein, we report a case of WT concomitant with MCL in a 70-year-old female patient, and emphasize the importance of careful examination of lymphoid stroma in WT so that concurrent lymphoma is not missed. PATIENT CONCERNS: A 70-year-old Chinese woman with a 40-year history of cigarette smoking presented with a one year history of a right submaxillary mass with recent enlargement. DIAGNOSIS: Cervical ultrasound (US) and computed tomography (CT) scans of the neck revealed a well-circumscribed mass in the right parotid with a maximum diameter of 3.1 cm. Surgical resection of the mass was performed. Histopathological examination revealed a characteristic double-layer of neoplastic epithelium with prominent lymphoid stroma, suggesting WT. In addition, morphology and immunohistochemistry studies confirmed the coexistence of MCL. Thereafter, the final diagnosis of this case was WT concomitant with MCL. INTERVENTIONS: The patient was staged as stage I after clinical assessment. Due to the slow growth of parotid lesions, close observation was decided with periodic clinical and radiological monitoring. OUTCOMES: Currently, the patient demonstrates a stable disease by clinical evaluation. LESSONS: To the best of our knowledge, reported cases of WT concomitant with MCL are very rare. This case highlights the importance of a comprehensive assessment of the lymphoid stroma of WT to avoid missed diagnosis of a lymphoma component in a collision tumor.

A liver immune rheostat regulates CD8 T cell immunity in chronic HBV infection.

Chronic hepatitis B virus (HBV) infection affects 300 million patients worldwide1,2, in whom virus-specific CD8 T cells by still ill-defined mechanisms lose their function and cannot eliminate HBV-infected hepatocytes3-7. Here we demonstrate that a liver immune rheostat renders virus-specific CD8 T cells refractory to activation and leads to their loss of effector functions. In preclinical models of persistent infection with hepatotropic viruses such as HBV, dysfunctional virus-specific CXCR6+ CD8 T cells accumulated in the liver and, as a characteristic hallmark, showed enhanced transcriptional activity of cAMP-responsive element modulator (CREM) distinct from T cell exhaustion. In patients with chronic hepatitis B, circulating and intrahepatic HBV-specific CXCR6+ CD8 T cells with enhanced CREM expression and transcriptional activity were detected at a frequency of 12-22% of HBV-specific CD8 T cells. Knocking out the inhibitory CREM/ICER isoform in T cells, however, failed to rescue T cell immunity. This indicates that CREM activity was a consequence, rather than the cause, of loss in T cell function, further supported by the observation of enhanced phosphorylation of protein kinase A (PKA) which is upstream of CREM. Indeed, we found that enhanced cAMP-PKA-signalling from increased T cell adenylyl cyclase activity augmented CREM activity and curbed T cell activation and effector function in persistent hepatic infection. Mechanistically, CD8 T cells recognizing their antigen on hepatocytes established close and extensive contact with liver sinusoidal endothelial cells, thereby enhancing adenylyl cyclase-cAMP-PKA signalling in T cells. In these hepatic CD8 T cells, which recognize their antigen on hepatocytes, phosphorylation of key signalling kinases of the T cell receptor signalling pathway was impaired, which rendered them refractory to activation. Thus, close contact with liver sinusoidal endothelial cells curbs the activation and effector function of HBV-specific CD8 T cells that target hepatocytes expressing viral antigens by means of the adenylyl cyclase-cAMP-PKA axis in an immune rheostat-like fashion.

Differential spatial working memory-related functional network reconfiguration in young and older adults.

Functional brain networks have preserved architectures in rest and task; nevertheless, previous work consistently demonstrated task-related brain functional reorganization. Efficient rest-to-task functional network reconfiguration is associated with better cognition in young adults. However, aging and cognitive load effects, as well as contributions of intra- and internetwork reconfiguration, remain unclear. We assessed age-related and load-dependent effects on global and network-specific functional reconfiguration between rest and a spatial working memory (SWM) task in young and older adults, then investigated associations between functional reconfiguration and SWM across loads and age groups. Overall, global and network-level functional reconfiguration between rest and task increased with age and load. Importantly, more efficient functional reconfiguration associated with better performance across age groups. However, older adults relied more on internetwork reconfiguration of higher cognitive and task-relevant networks. These reflect the consistent importance of efficient network updating despite recruitment of additional functional networks to offset reduction in neural resources and a change in brain functional topology in older adults. Our findings generalize the association between efficient functional reconfiguration and cognition to aging and demonstrate distinct brain functional reconfiguration patterns associated with SWM in aging, highlighting the importance of combining rest and task measures to study aging cognition.

Brain networks identified by functional connectivity (FC) have preserved architectures from rest to task and across task demands. Higher similarity, implying more efficient network reconfiguration, was associated with better cognition and task performance in young adults. To examine how it may be influenced by aging, we compared whole-brain and network-level FC similarities between resting-state and spatial working memory fMRI in young and older adults. At whole-brain level and higher order cognitive networks, older adults evidenced less efficient network reconfiguration from rest to task than young adults. Importantly, more efficient reconfiguration was associated with better accuracy. This relationship relied more on internetwork connections in older adults. Despite reduced neural resources compared to young, maintaining efficient network updating still contributes to better cognition at older age.

scVIC: deep generative modeling of heterogeneity for scRNA-seq data.

Motivation: Single-cell RNA sequencing (scRNA-seq) has become a valuable tool for studying cellular heterogeneity. However, the analysis of scRNA-seq data is challenging because of inherent noise and technical variability. Existing methods often struggle to simultaneously explore heterogeneity across cells, handle dropout events, and account for batch effects. These drawbacks call for a robust and comprehensive method that can address these challenges and provide accurate insights into heterogeneity at the single-cell level. Results: In this study, we introduce scVIC, an algorithm designed to account for variational inference, while simultaneously handling biological heterogeneity and batch effects at the single-cell level. scVIC explicitly models both biological heterogeneity and technical variability to learn cellular heterogeneity in a manner free from dropout events and the bias of batch effects. By leveraging variational inference, we provide a robust framework for inferring the parameters of scVIC. To test the performance of scVIC, we employed both simulated and biological scRNA-seq datasets, either including, or not, batch effects. scVIC was found to outperform other approaches because of its superior clustering ability and circumvention of the batch effects problem. Availability and implementation: The code of scVIC and replication for this study are available at https://github.com/HiBearME/scVIC/tree/v1.0.

Proton spot dose estimation based on positron activity distributions with neural network.

BACKGROUND: Positron emission tomography (PET) has been investigated for its ability to reconstruct proton-induced positron activity distributions in proton therapy. This technique holds potential for range verification in clinical practice. Recently, deep learning-based dose estimation from positron activity distributions shows promise for in vivo proton dose monitoring and guided proton therapy. PURPOSE: This study evaluates the effectiveness of three classical neural network models, recurrent neural network (RNN), U-Net, and Transformer, for proton dose estimating. It also investigates the characteristics of these models, providing valuable insights for selecting the appropriate model in clinical practice. METHODS: Proton dose calculations for spot beams were simulated using Geant4. Computed tomography (CT) images from four head cases were utilized, with three for training neural networks and the remaining one for testing. The neural networks were trained with one-dimensional (1D) positron activity distributions as inputs and generated 1D dose distributions as outputs. The impact of the number of training samples on the networks was examined, and their dose prediction performance in both homogeneous brain and heterogeneous nasopharynx sites was evaluated. Additionally, the effect of positron activity distribution uncertainty on dose prediction performance was investigated. To quantitatively evaluate the models, mean relative error (MRE) and absolute range error (ARE) were used as evaluation metrics. RESULTS: The U-Net exhibited a notable advantage in range verification with a smaller number of training samples, achieving approximately 75% of AREs below 0.5 mm using only 500 training samples. The networks performed better in the homogeneous brain site compared to the heterogeneous nasopharyngeal site. In the homogeneous brain site, all networks exhibited small AREs, with approximately 90% of the AREs below 0.5 mm. The Transformer exhibited the best overall dose distribution prediction, with approximately 92% of MREs below 3%. In the heterogeneous nasopharyngeal site, all networks demonstrated acceptable AREs, with approximately 88% of AREs below 3 mm. The Transformer maintained the best overall dose distribution prediction, with approximately 85% of MREs below 5%. The performance of all three networks in dose prediction declined as the uncertainty of positron activity distribution increased, and the Transformer consistently outperformed the other networks in all cases. CONCLUSIONS: Both the U-Net and the Transformer have certain advantages in the proton dose estimation task. The U-Net proves well suited for range verification with a small training sample size, while the Transformer outperforms others at dose-guided proton therapy.

Heart Rate Variability Biofeedback Training Reduces Early Maternal Stress, Anxiety, and Depression in Women Undergoing Cesarean Delivery: A Randomized Controlled Trial.

Women who undergo cesarean delivery have reported experiencing mood distress related to the surgery and postoperative pain. Heart rate variability biofeedback (HRVB) training is known to have positive effects on mental health, but its effects on women undergoing cesarean delivery have not yet been determined. This study evaluated the effects of an HRVB training intervention on stress, anxiety, and depression in women undergoing cesarean delivery. We hypothesized that 10 sessions of HRVB training could cumulatively improve emotion regulation in participants. This study was designed as a double-blinded randomized controlled trial involving a total of 86 enrolled women who were then divided into two groups: intervention and control. During their hospitalization, the intervention group underwent HRVB training daily, while both groups received standard perinatal care. Heart rate variability (HRV) was assessed using root mean square of successive differences (RMSSD), standard deviation of normal-to-normal intervals (SDNN), high-frequency power (HF) and low-frequency power (LF). HRV parameters, stress, anxiety, and depression were evaluated at baseline and on the fifth day after childbirth. Intention-to-treat (ITT) analyses examined change over time between groups. Although no significant effects were found for the RMSSD and HF, a significant increase was observed in SDNN (F = 13.43, p = < 0.001, ƞ2 = 0.14), and LF at post-assessment (F = 4.26, p = .04, ƞ2 = 0.05) compared to the control group. Except for the depression variable, stress (F = 6.11, p = .02, ƞ2 = 0.07) and anxiety (F = 8.78, p = .004, ƞ2 = 0.10) significantly decreased compared to the control group on the fifth postpartum day. Furthermore, post-hoc analysis showed that HRVB was more effective in decreasing mild to severe depressive symptoms (F = 7.60, p = .001, ƞ2 = 0.27). The intervention program successfully decreased self-perceived stress and anxiety in the postpartum period and relieved symptoms in more severely depressed participants. Our findings suggest that this program is suitable and beneficial for application in women during the early postpartum period following cesarean delivery.

The pathogenic T42A mutation in SHP2 rewires the interaction specificity of its N-terminal regulatory domain.

Mutations in the tyrosine phosphatase Src homology-2 domain-containing protein tyrosine phosphatase-2 (SHP2) are associated with a variety of human diseases. Most mutations in SHP2 increase its basal catalytic activity by disrupting autoinhibitory interactions between its phosphatase domain and N-terminal SH2 (phosphotyrosine recognition) domain. By contrast, some disease-associated mutations located in the ligand-binding pockets of the N- or C-terminal SH2 domains do not increase basal activity and likely exert their pathogenicity through alternative mechanisms. We lack a molecular understanding of how these SH2 mutations impact SHP2 structure, activity, and signaling. Here, we characterize five SHP2 SH2 domain ligand-binding pocket mutants through a combination of high-throughput biochemical screens, biophysical and biochemical measurements, and molecular dynamics simulations. We show that while some of these mutations alter binding affinity to phosphorylation sites, the T42A mutation in the N-SH2 domain is unique in that it also substantially alters ligand-binding specificity, despite being 8 to 10 Å from the specificity-determining region of the SH2 domain. This mutation exerts its effect on sequence specificity by remodeling the phosphotyrosine-binding pocket, altering the mode of engagement of both the phosphotyrosine and surrounding residues on the ligand. The functional consequence of this altered specificity is that the T42A mutant has biased sensitivity toward a subset of activating ligands and enhances downstream signaling. Our study highlights an example of a nuanced mechanism of action for a disease-associated mutation, characterized by a change in protein-protein interaction specificity that alters enzyme activation.

Design, synthesis and anti-Alzheimer's disease activity evaluation of C-3 arylated huperzine A derivatives.

A series of C-3 arylated huperzine A (HPA) derivatives (1-30) were designed and synthesized in good yields via palladium-catalyzed Suzuki cross-coupling reaction. Cholinesterase inhibitory and neuroprotective activities of all 30 derivatives were evaluated. Cholinesterase inhibition results revealed that derivatives 2 and 15 exhibited dual inhibitory activity against both acetylcholinesterase (AChE inhibition: 2, IC50 = 1.205 ± 0.395 µM; 15, IC50 = 0.225 ± 0.062 µM) and butyrylcholinesterase (BChE inhibition: 2, IC50 = 8.598 ± 3.605 µM; 15, IC50 = 4.013 ± 0.068 µM), a feature not observed in huperzine A. Molecular docking results indicated that the introduction of aryl groups enhanced the affinity of the derivatives for the acyl-binding pocket of BChE, thereby limiting the hydrolysis of acetyl choline. However, these derivatives exhibited poor performance in cytotoxicity and neuroprotection assays.

Mechanism of Lian Hua Qing Wen capsules regulates the inflammatory response caused by M1 macrophage based on cellular experiments and computer simulations.

PURPOSE: The polarization of macrophages with the resulting inflammatory response play a crucial part in tissue and organ damage due to inflammatory. Study has proved Lian Hua Qing Wen capsules (LHQW) can reduce activation of inflammatory response and damage of tissue derived from the inflammatory reactions. However, the mechanism of LHQW regulates the macrophage-induced inflammatory response is unclear. Therefore, we investigated the mechanism of LHQW regulated the inflammatory response of M1 macrophages by cellular experiments and computer simulations. METHODS: This study has analysed the targets and mechanisms of macrophage regulating inflammatory response at gene and protein levels through bioinformatics. The monomeric components of LHQW were analyzed by High Performance Liquid Chromatography (HPLC). We established the in vitro cell model by M1 macrophages (Induction of THP-1 cells into M1 macrophages). RT-qPCR and immunofluorescence were used to detect changes in gene and protein levels of key targets after LHQW treatment. Computer simulations were utilized to verify the binding stability of monomeric components and protein targets. RESULTS: Macrophages had 140,690 gene targets, inflammatory response had 12,192 gene targets, intersection gene targets were 11,772. Key monomeric components (including: Pinocembrin, Fargesone-A, Nodakenin and Bowdichione) of LHQW were screened by HPLC. The results of cellular experiments indicated that LHQW could significantly reduce the mRNA expression of CCR5, CSF2, IFNG and TNF, thereby alleviating the inflammatory response caused by M1 macrophage. The computer simulations further validated the binding stability and conformation of key monomeric components and key protein targets, and IFNG/Nodakenin was able to form the most stable binding conformation for its action. CONCLUSION: In this study, the mechanism of LHQW inhibits the polarization of macrophages and the resulting inflammatory response was investigated by computer simulations and cellular experiments. We found that LHQW may not only reduce cell damage and death by acting on TNF and CCR5, but also inhibit the immune recognition process and inflammatory response by regulating CSF2 and IFNG to prevent polarization of macrophages. Therefore, these results suggested that LHQW may act through multiple targets to inhibit the polarization of macrophages and the resulting inflammatory response.

Exhaustive clinical examination of etiology and initial response to first-line treatment in 577 children with infantile epileptic spasm syndrome children: A 5-year retrospective observational study.

OBJECTIVE: Employing whole-exome sequencing (WES) technology to investigate the etiology of infantile epileptic spasm syndrome (IESS), and determining whether different etiologies exhibit phenotypic variations, while elucidating the potential associated factors, might improve short-term responses to first-line treatment. METHODS: We retrospectively evaluated patients with IESS admitted for treatment between January 2018 and June 2023. Clinical phenotypic differences among etiological classifications and clinical manifestations were analyzed. Variable selection using the best subset method was performed, followed by logistic regression analysis to identify the factors influencing treatment response. RESULTS: A total of 577 patients were included; 412 completed trio-WES. Magnetic resonance imaging abnormalities were detected in 387 patients (67.1%). Patients with etiology as structural abnormalities were likelier to have non-spasms at the initial seizure onset. A total of 532 patients completed the first-line treatment; 273 patients received it for the first time at our hospital (initial response rates: 30.1% and 42.1%, respectively). The response group had a lower proportion of early-onset seizures (≤3 months) than the no-response group (11.3% vs. 23.7%, p < 0.01 and 11.3% vs. 21.5%, p = 0.03, respectively). Logistic regression analysis indicated that earlier initiation of first-line treatment was associated with a higher likelihood of an initial response. However, the etiological classification did not have a significant impact on the initial response. INTERPRETATION: IESS patients with structural abnormalities are more likely to present with non-spasm seizures at initial onset. Early initiation of first-line treatment is crucial; however, initial responses may be less favorable when seizures occur in early infancy.