A New Orthonairovirus Associated with Human Febrile Illness.

BACKGROUND: In June 2019, a patient presented with persistent fever and multiple organ dysfunction after a tick bite at a wetland park in Inner Mongolia. Next-generation sequencing in this patient revealed an infection with a previously unknown orthonairovirus, which we designated Wetland virus (WELV). METHODS: We conducted active hospital-based surveillance to determine the prevalence of WELV infection among febrile patients with a history of tick bites. Epidemiologic investigation was performed. The virus was isolated, and its infectivity and pathogenicity were investigated in animal models. RESULTS: WELV is a member of the orthonairovirus genus in the Nairoviridae family and is most closely related to the tickborne Hazara orthonairovirus genogroup. Acute WELV infection was identified in 17 patients from Inner Mongolia, Heilongjiang, Jilin, and Liaoning, China, by means of reverse-transcriptase-polymerase-chain-reaction assay. These patients presented with nonspecific symptoms, including fever, dizziness, headache, malaise, myalgia, arthritis, and back pain and less frequently with petechiae and localized lymphadenopathy. One patient had neurologic symptoms. Common laboratory findings were leukopenia, thrombocytopenia, and elevated d-dimer and lactate dehydrogenase levels. Serologic assessment of convalescent-stage samples obtained from 8 patients showed WELV-specific antibody titers that were 4 times as high as those in acute-phase samples. WELV RNA was detected in five tick species and in sheep, horses, pigs, and Transbaikal zokors (Myospalax psilurus) sampled in northeastern China. The virus that was isolated from the index patient and ticks showed cytopathic effects in human umbilical-vein endothelial cells. Intraperitoneal injection of the virus resulted in lethal infections in BALB/c, C57BL/6, and Kunming mice. The Haemaphysalis concinna tick is a possible vector that can transovarially transmit WELV. CONCLUSIONS: A newly discovered orthonairovirus was identified and shown to be associated with human febrile illnesses in northeastern China. (Funded by the National Natural Science Foundation of China and the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences.).

Predicting Human Subcutaneous Bioavailability of Therapeutic Monoclonal Antibodies from Systemic Clearance and Volume of Distribution.

Subcutaneous delivery of monoclonal antibody therapeutics is often preferred to intravenous delivery due to better patient compliance and overall lower cost to the healthcare system. However, the systemic absorption of biologics dosed subcutaneously is often incomplete. The aim of this work was to describe a human bioavailability prediction method for monoclonal antibodies delivered subcutaneously that utilizes intravenous pharmacokinetic parameters as input. A two-compartment pharmacokinetic model featuring a parallel-competitive absorption pathway and a presystemic metabolism pathway was employed. A training data set comprised 19 monoclonal antibodies (geometric mean bioavailability of 68%), with previously reported human pharmacokinetic parameters, while a validation set included data compiled from 5 commercial drug products (geometric mean bioavailability of 69%). A single fitted absorption rate constant, paired with compound-specific estimates of presystemic metabolism rate proportional to compound-specific systemic clearance parameters, resulted in calculations of human subcutaneous bioavailability closely mimicking clinical data in the training data set with a root-mean-square error of 5.5%. Application of the same approach to the validation data set resulted in predictions characterized by 12.6% root-mean-square error. Factors that may have impacted the prediction accuracy include a limited number of validation data set compounds and an uncertainty in the absorption rate, which were subsequently discussed. The predictive method described herein provides an initial estimate of the subcutaneous bioavailability based exclusively on pharmacokinetic parameters available from intravenous dosing.

Association between copper intake and essential hypertension: dual evidence from Mendelian randomization analysis and the NHANES database.

Background: Although previous studies have identified an association between trace elements and essential hypertension, the specific trace elements involved and the mechanisms of their association remain unclear. This study aimed to elucidate the relationship between various human trace elements and essential hypertension, thereby addressing existing gaps in the research. Methods: This study employed two-sample, multivariate, and inverse Mendelian randomization (MR) analyses to investigate the causal relationship between 15 human trace elements as exposure factors and essential hypertension as the outcome. The analysis revealed a statistically significant association between copper intake and essential hypertension. Further validation was conducted using logistic regression models based on data from the National Health and Nutrition Examination Survey (NHANES). Results: Eighteen trace elements were initially identified through searches in the GWAS database and PubMed. After screening, 15 trace elements were selected as potential exposure factors. MR analysis, utilizing the 2021 genome-wide dataset for essential hypertension, identified copper as a risk factor, showing a positive association with hypertension. Subsequent logistic regression analyses based on NHANES data further confirmed a significant association between dietary copper intake and the risk of essential hypertension, except for the 0.80-1.08 mg/d group in model 3 (p < 0.05). Restricted cubic spline (RCS) analysis indicated a nonlinear relationship between copper intake and the risk of developing essential hypertension. Conclusion: This study demonstrates a significant association between copper intake and the development of essential hypertension. The findings suggest that higher copper intake is linked to an increased risk of hypertension, underscoring the need to monitor copper intake levels in the prevention and management of this condition.

Clinical and epidemiological investigation of human infection with zoonotic parasite Trypanosoma dionisii in China.

BACKGROUND: Trypanosomiasis continues to pose a global threat to human health, with human infection mainly caused by Trypanosoma brucei and Trypanosoma cruzi. METHODS: We present a 30-year-old pregnant woman with persistent high fever from Shandong Province, China. High-throughput sequencing revealed the presence of Trypanosoma dionisii in blood. We conducted an analysis of the patient's clinical, epidemiological, and virological data. RESULTS: The patients exhibited fever, shortness of breath, chest tightness, accompanied by change in liver function and inflammatory response. She made a full recovery without any long-term effects. T. dionisii was detected in blood collected 23 days after onset of illness. The 18S rRNA gene sequence showed close similarity to T. dionisii found in bats from Japan, while the gGAPDH gene was closely related to T. dionisii from bats in Mengyin County, Shandong Province. Phylogenetic analysis demonstrated the current T. dionisii belongs to clade B within its species group. Positive anti-Trypanosoma IgG antibody was detected from the patient on Day 23, 66 and 122 after disease onset, as well as the cord blood and serum from the newborn. Retrospective screening of wild small mammals captured from Shandong Province revealed a prevalence rate of 0.54% (7/1304) for T. dionisii; specifically among 0.81% (5/620) of Apodemus agrarius, and 0.46% (2/438) of Mus musculus. CONCLUSIONS: The confirmation of human infection with T. dionisii underscores its potential as a zoonotic pathogen, while the widespread presence of this parasite in rodent and bat species emphasizes the emerging threat it poses to human health.

First Genomic Evidence of California Hare Coltivirus from Natural Populations of Ixodes persulcatus Ticks in Northeast China.

Background: California hare coltivirus (CHCV) was isolated in California in 1976 from a hare. Despite its long history, it remained unclear whether CHCV was exclusively distributed in California with limited host ranges. Main body: By next-generation sequencing (NGS), we obtained a complete sequence of CHCV from Ixodes persulcatus collected in 2019 in northeast China. An expanded epidemiological investigation was subsequently performed on ticks belonging to four species (Ix. persulcatus, Haemaphysalis concinna, Devmacentor silvarum, Haemaphysalis longicornis) collected in northeastern China by applying CHCV-specific RT-PCR and sequencing. CHCV RNA-positive results were found in 1.56% of the tick samples. Positive ticks were obtained in three of four sampled locations, with the highest rate observed in Inner Mongolia (2.69%), followed by Heilongjiang (1.94%) and Jilin provinces (0.55%). All positive results were derived from Ix. persulcatus ticks (2.33%), while no positive detection was found in the other tick species, even at the same location. Sequence analysis revealed that the current CHCV showed a high genetic identity (>80% amino acid identity) with the previously reported CHCV in all segments except segment seven (64.59% amino acid identity). Phylogenetic analysis based on RNA-dependent RNA polymerase (RdRp) amino acid sequences demonstrated that both the current and previously reported CHCV strains were grouped phylogenetically into the genus Coltivirus. Both CHCV strains formed a distinct clade, clustering with three human pathogenic coltiviruses (Colorado tick fever virus, Salmon River virus, and Eyach virus), and were distant from the other coltiviruses. Conclusions: We report the identification and characterization of CHCV for the first time in Ix. persulcatus ticks, expanding the currently known geographic scope, host, and genetic heterogeneity in CHCV.

Decoding the RNA viromes in shrew lungs along the eastern coast of China.

Shrews being insectivores, serve as natural reservoirs for a wide array of zoonotic viruses, including the recently discovered Langya henipavirus (LayV) in China in 2018. It is crucial to understand the shrew-associated virome, viral diversity, and new viruses. In the current study, we conducted high-throughput sequencing on lung samples obtained from 398 shrews captured along the eastern coast of China, and characterized the high-depth virome of 6 common shrew species (Anourosorex squamipes, Crocidura lasiura, Crocidura shantungensis, Crocidura tanakae, Sorex caecutiens, and Suncus murinus). Our analysis revealed numerous shrew-associated viruses comprising 54 known viruses and 72 new viruses that significantly enhance our understanding of mammalian viruses. Notably, 34 identified viruses possess spillover-risk potential and six were human pathogenic viruses: LayV, influenza A virus (H5N6), rotavirus A, rabies virus, avian paramyxovirus 1, and rat hepatitis E virus. Moreover, ten previously unreported viruses in China were discovered, six among them have spillover-risk potential. Additionally, all 54 known viruses and 12 new viruses had the ability to cross species boundaries. Our data underscore the diversity of shrew-associated viruses and provide a foundation for further studies into tracing and predicting emerging infectious diseases originated from shrews.

Causal associations between human gut microbiota and osteomyelitis: a Mendelian randomization study.

Background: Recent studies have emphasized the role of gut microbiota in the onset and progression of osteomyelitis. However, the exact types of gut microbiota and their mechanisms of action remain unclear. Additionally, there is a lack of theoretical support for treatments that improve osteomyelitis by altering the gut microbiota. Methods: In our study, we utilized the largest genome-wide association study (GWAS) meta-analysis to date from the MiBioGen consortium, involving 13,400 participants. The GWAS data for osteomyelitis were sourced from the UK Biobank, which included 4,836 osteomyelitis cases and 486,484 controls. We employed a two-sample Mendelian randomization framework for a detailed investigation into the causal relationship between gut microbiota and osteomyelitis. Our methods included inverse variance weighting, MR-Egger, weighted median, and weighted mode approaches. Additionally, we applied Cochran's Q statistic to assess the heterogeneity of the instrumental variable. Results: At the class level, Bacilli and Bacteroidia were positively correlated with the risk of osteomyelitis. At the order level, only Bacteroidales showed a positive association with osteomyelitis. At the genus level, an increased abundance of Butyricimonas, Coprococcus3, and Tyzzerella3 was positively associated with the risk of osteomyelitis, whereas Lachnospira was negatively associated. Sensitivity analyses showed no evidence of heterogeneity or pleiotropy. Conclusion: This study reveals that classes Bacilli and Bacteroidia, order Bacteroidales, and genera Butyricimonas, Coprococcus3, and Tyzzerella3 are implicated in increasing the risk of osteomyelitis, while the genus Lachnospira is associated with a reduced risk. Future investigations are warranted to elucidate the precise mechanisms through which these specific bacterial groups influence the pathophysiology of osteomyelitis.

Energy-Efficient Sleep Apnea Detection Using a Hyperdimensional Computing Framework Based on Wearable Bracelet Photoplethysmography.

OBJECTIVE: Sleep apnea syndrome (SAS) is a common sleep disorder, which has been shown to be an important contributor to major neurocognitive and cardiovascular sequelae. Considering current diagnostic strategies are limited with bulky medical devices and high examination expenses, a large number of cases go undiagnosed. To enable large-scale screening for SAS, wearable photoplethysmography (PPG) technologies have been used as an early detection tool. However, existing algorithms are energy-intensive and require large amounts of memory resources, which are believed to be the major drawbacks for further promotion of wearable devices for SAS detection. METHODS: In this paper, an energy-efficient method of SAS detection based on hyperdimensional computing (HDC) is proposed. Inspired by the phenomenon of chunking in cognitive psychology as a memory mechanism for improving working memory efficiency, we proposed a one-dimensional block local binary pattern (1D-BlockLBP) encoding scheme combined with HDC to preserve dominant dynamical and temporal characteristics of pulse rate signals from wearable PPG devices. RESULTS: Our method achieved 70.17 % accuracy in sleep apnea segment detection, which is comparable with traditional machine learning methods. Additionally, our method achieves up to 67× lower memory footprint, 68× latency reduction, and 93× energy saving on the ARM Cortex-M4 processor. CONCLUSION: The simplicity of hypervector operations in HDC and the novel 1D-BlockLBP encoding effectively preserve pulse rate signal characteristics with high computational efficiency. SIGNIFICANCE: This work provides a scalable solution for long-term home-based monitoring of sleep apnea, enhancing the feasibility of consistent patient care.

Analysis of alterations in serum vitamins and correlations with gut microbiome, microbial metabolomics in patients with sepsis.

BACKGROUND: Vitamins are essential micronutrients that play key roles in many biological pathways associated with sepsis. The gut microbiome plays a pivotal role in the progression of sepsis and may contribute to the onset of multi-organ dysfunction syndrome (MODS). The aim of this study was to investigate the changes in serum vitamins, and their correlation with intestinal flora and metabolomic profiles in patients with sepsis. METHODS: The serum levels of vitamins were determined by Ultra Performance Liquid Chromatography (UPLC). 16S rRNA gene sequencing and Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) targeted metabolomics were used for microbiome and metabolome analysis. RESULTS: In the training cohort: After univariate, multivariate (OPLS-DA) and Spearman analyses, it was concluded that vitamin levels of 25 (OH) VD3 and (VD2 + VD3), as well as vitamins A and B9, differed significantly among healthy controls (HC), non-septic critical patients (NS), and sepsis patients (SS) (P < 0.05). The validation cohort confirmed the differential vitamin findings from the training cohort. Moreover, analyses of gut flora and metabolites in septic patients and healthy individuals revealed differential flora, metabolites, and metabolic pathways that were linked to alterations in serum vitamin levels. We found for the first time that vitamin B9 was negatively correlated with g_Sellimonas. CONCLUSION: Sepsis patients exhibited significantly lower levels of 25 (OH) VD3 and (VD2 + VD3), vitamins A and B9, which hold potential as predictive markers for sepsis prognosis. The changes in these vitamins may be associated with inflammatory factors, oxidative stress, and changes in gut flora.

Establishment of transgenic fluorescent mice for labeling synapses and screening synaptogenic adhesion molecules.

Synapse is the fundamental structure for neurons to transmit information between cells. The proper synapse formation is crucial for developing neural circuits and cognitive functions of the brain. The aberrant synapse formation has been proved to cause many neurological disorders, including autism spectrum disorders and intellectual disability. Synaptic cell adhesion molecules (CAMs) are thought to play a major role in achieving mechanistic cell-cell recognition and initiating synapse formation via trans-synaptic interactions. Due to the diversity of synapses in different brain areas, circuits and neurons, although many synaptic CAMs, such as Neurexins (NRXNs), Neuroligins (NLGNs), Synaptic cell adhesion molecules (SynCAMs), Leucine-rich-repeat transmembrane neuronal proteins (LRRTMs), and SLIT and NTRK-like protein (SLITRKs) have been identified as synaptogenic molecules, how these molecules determine specific synapse formation and whether other molecules driving synapse formation remain undiscovered are unclear. Here, to provide a tool for synapse labeling and synaptic CAMs screening by artificial synapse formation (ASF) assay, we generated synaptotagmin-1-tdTomato (Syt1-tdTomato) transgenic mice by inserting the tdTomato-fused synaptotagmin-1 coding sequence into the genome of C57BL/6J mice. In the brain of Syt1-tdTomato transgenic mice, the tdTomato-fused synaptotagmin-1 (SYT1-tdTomato) signals were widely observed in different areas and overlapped with synapsin-1, a widely-used synaptic marker. In the olfactory bulb, the SYT1-tdTomato signals are highly enriched in the glomerulus. In the cultured hippocampal neurons, the SYT1-tdTomato signals showed colocalization with several synaptic markers. Compared to the wild-type (WT) mouse neurons, cultured hippocampal neurons from Syt1-tdTomato transgenic mice presented normal synaptic neurotransmission. In ASF assays, neurons from Syt1-tdTomato transgenic mice could form synaptic connections with HEK293T cells expressing NLGN2, LRRTM2, and SLITRK2 without immunostaining. Therefore, our work suggested that the Syt1-tdTomato transgenic mice with the ability to label synapses by tdTomato, and it will be a convenient tool for screening synaptogenic molecules.

Overexpression of SPP1 is a prognostic indicator of immune infiltration in lung adenocarcinoma.

OBJECTIVE: The extracellular phosphoprotein, secreted phosphoprotein 1 (SPP1), plays a crucial role in various tumors and regulating the immune system. This study aimed to evaluate its prognostic value and relationship to immune infiltration in lung adenocarcinoma (LUAD). METHODS: In the TCGA and GEO datasets, the information on clinic and transcriptome analysis of SPP1 in non-small-cell lung cancer (NSCLC) was examined accordingly. The association of SPP1 expression with overall survival and clinicopathologic characteristics was investigated by univariate and multivariate analysis. CancerSEA database was utilized to investigate the role of SPP1 at the cellular level by single-cell analysis. Additionally, the CIBERSORT algorithm was utilized to assess the correlation among the immune cells that infiltrated. RESULTS: NSCLC tissues exhibited a notable rise in SPP1 expression compared with that of normal tissues. Furthermore, the overexpression of SPP1 was substantially associated with clinicopathological features and unfavorable survival outcomes in individuals with LUAD, whereas no such correlation was observed in lung squamous cell carcinoma. Immune cells that infiltrate tumors and their corresponding genes were associated with SPP1 expression levels in LUAD. CONCLUSIONS: SPP1 is a reliable indicator for assessing LUAD immune infiltration status and prognosis. With this approach, SPP1 can help earlier LUAD diagnosis and act as a possible immunotherapy target.

Supervised and unsupervised machine learning approaches for monitoring subvisible particles within an aluminum-salt adjuvanted vaccine formulation.

Suspensions of protein antigens adsorbed to aluminum-salt adjuvants are used in many vaccines and require mixing during vial filling operations to prevent sedimentation. However, the mixing of vaccine formulations may generate undesirable particles that are difficult to detect against the background of suspended adjuvant particles. We simulated the mixing of a suspension containing a protein antigen adsorbed to an aluminum-salt adjuvant using a recirculating peristaltic pump and used flow imaging microscopy to record images of particles within the pumped suspensions. Supervised convolutional neural networks (CNNs) were used to analyze the images and create "fingerprints" of particle morphology distributions, allowing detection of new particles generated during pumping. These results were compared to those obtained from an unsupervised machine learning algorithm relying on variational autoencoders (VAEs) that were also used to detect new particles generated during pumping. Analyses of images conducted by applying both supervised CNNs and VAEs found that rates of generation of new particles were higher in aluminum-salt adjuvant suspensions containing protein antigen than placebo suspensions containing only adjuvant. Finally, front-face fluorescence measurements of the vaccine suspensions indicated changes in solvent exposure of tryptophan residues in the protein that occurred concomitantly with new particle generation during pumping.

Identification of Mudanjiang Phlebovirus in the Daxing'anling Region of China.

Mudanjiang phlebovirus (MJPV) is a newly discovered phlebovirus, initially detected from Ixodes persulcatus ticks in China in 2022. In this study, by next-generation sequencing (NGS) on a wide variety of ticks and wild small animals in China, we detected MJPV from I. persulcatus and Meriones meridianus. Additionally, we conducted RT-PCR and sequencing on 1815 adult ticks and 805 wild small mammals collected from eight provinces in China between 2017 and 2021. MJPV RNA-positive results were found in 0.22% (4/1815) of tick samples, as well as in 0.12% (1/805) of rodent samples. All positive detections were obtained from Heilongjiang and Inner Mongolia. Sequencing analysis revealed nucleotide similarities ranging from 98.23% to 99.11%, as well as amino acid similarities ranging from 99.12% to100%, between the current MJPV strain and previously reported strains of MJPV. Phylogenetic tree analysis demonstrated that the previously reported MJPV strain along with our two variants clustered together with other tick-borne phenuiviruses, indicating their close relationship within this viral group. This study represents the first detection of MJPV infection in wild rodents, expanding the known host range for this virus in the endemic regions.

Predicting Colloidal Stability of High-Concentration Monoclonal Antibody Formulations in Common Pharmaceutical Buffers Using Improved Polyethylene Glycol Induced Protein Precipitation Assay.

Colloidal stability is an important consideration when developing high concentration mAb formulations. PEG-induced protein precipitation is a commonly used assay to assess the colloidal stability of protein solutions. However, the practical usefulness and the current theoretical model for this assay have yet to be verified over a large formulation space across multiple mAbs and mAb-based modalities. In the present study, we used PEG-induced protein precipitation assays to evaluate colloidal stability of 3 mAbs in 24 common formulation buffers at 20 and 5 °C. These prediction assays were conducted at low protein concentration (1 mg/mL). We also directly characterized high concentration (100 mg/mL) formulations for cold-induced phase separation, turbidity, and concentratibility by ultrafiltration. This systematic study allowed analysis of the correlation between the results of low concentration assays and the high concentration attributes. The key findings of this study include the following: (1) verification of the usefulness of three different parameters (Cmid, µB, and Tcloud) from PEG-induced protein precipitation assays for ranking colloidal stability of high concentration mAb formulations; (2) a new method to implement PEG-induced protein precipitation assay suitable for high throughput screening with low sample consumption; (3) improvement in the theoretical model for calculating robust thermodynamic parameters of colloidal stability (µB and εB) that are independent of specific experimental settings; (4) systematic evaluation of the effects of pH and buffer salts on colloidal stability of mAbs in common formulation buffers. These findings provide improved theoretical and practical tools for assessing the colloidal stability of mAbs and mAb-based modalities during formulation development.

In Situ Observation of Cellular Structure Changes in and Chain Segregations of Anabaena sp. PCC 7120 on TiO2 Films under a Photocatalytic Device.

Cyanobacteria outbreaks are serious water pollution events, causing water crises around the world. Photocatalytic disinfection, as an effective approach, has been widely used to inhibit blue algae growth. In this study, a tiny reaction room containing a TiO2 film was designed to fulfill in situ optical observation of the destruction process of a one-dimensional multicellular microorganism, Anabaena sp. PCC 7120, which is also a typical bacterial strain causing water blooms. It was found that the fragment number increased exponentially with the activation time. The fracture mechanics of the algae chains were hypothesized to be the combining functions of increased local tensile stress originated from the cell contracting as well as the oxidative attacks coming from reactive oxygen species (ROSs). It was assumed that the oxidative species were the root cause of cellular structure changes in and chain fractures of Anabaena sp. PCC 7120 in the photocatalytic inactivation activity.

Facile Synthesis of Cu-Doped ZnO Nanoparticles for the Enhanced Photocatalytic Disinfection of Bacteria and Fungi.

In this study, Cu-doped ZnO was prepared via the facile one-pot solvothermal approach. The structure and composition of the synthesized samples were characterized by XRD (X-ray diffraction), TEM (transmission electron microscopy), and XPS (X-ray photoelectron spectroscopy) analyses, revealing that the synthesized samples consisted of Cu-doped ZnO nanoparticles. Ultraviolet-visible (UV-vis) spectroscopy analysis showed that Cu-doping significantly improves the visible light absorption properties of ZnO. The photocatalytic capacity of the synthesized samples was tested via the disinfection of Escherichia coli, with the Cu-ZnO presenting enhanced disinfection compared to pure ZnO. Of the synthesized materials, 7% Cu-ZnO exhibited the best photocatalytic performance, for which the size was ~9 nm. The photocurrent density of the 7% Cu-ZnO samples was also significantly higher than that of pure ZnO. The antifungal activity for 7% Cu-ZnO was also tested on the pathogenic fungi of Fusarium graminearum. The macroconidia of F. graminearum was treated with 7% Cu-ZnO photocatalyst for 5 h, resulting in a three order of magnitude reduction at a concentration of 105 CFU/mL. Fluorescence staining tests were used to verify the survival of macroconidia before and after photocatalytic treatment. ICP-MS was used to confirm that Cu-ZnO met national standards for cu ion precipitation, indicating that Cu-ZnO are environmentally friendly materials.

Machine learning-identified stemness features and constructed stemness-related subtype with prognosis, chemotherapy, and immunotherapy responses for non-small cell lung cancer patients.

AIM: This study aimed to explore a novel subtype classification method based on the stemness characteristics of patients with non-small cell lung cancer (NSCLC). METHODS: Based on the Cancer Genome Atlas database to calculate the stemness index (mRNAsi) of NSCLC patients, an unsupervised consensus clustering method was used to classify patients into two subtypes and analyze the survival differences, somatic mutational load, copy number variation, and immune characteristics differences between them. Subsequently, four machine learning methods were used to construct and validate a stemness subtype classification model, and cell function experiments were performed to verify the effect of the signature gene ARTN on NSCLC. RESULTS: Patients with Stemness Subtype I had better PFS and a higher somatic mutational burden and copy number alteration than patients with Stemness Subtype II. In addition, the two stemness subtypes have different patterns of tumor immune microenvironment. The immune score and stromal score and overall score of Stemness Subtype II were higher than those of Stemness Subtype I, suggesting a relatively small benefit to immune checkpoints. Four machine learning methods constructed and validated classification model for stemness subtypes and obtained multiple logistic regression equations for 22 characteristic genes. The results of cell function experiments showed that ARTN can promote the proliferation, invasion, and migration of NSCLC and is closely related to cancer stem cell properties. CONCLUSION: This new classification method based on stemness characteristics can effectively distinguish patients' characteristics and thus provide possible directions for the selection and optimization of clinical treatment plans.

Ze-Qi decoction inhibits non-small cell lung cancer growth and metastasis by modulating the PI3K/Akt/p53 signaling pathway.

Background: The Ze-Qi decoction (ZQD) is a traditional Chinese herbal formula commonly applied to treat lung cancer in China. This study aimed to assess the effective ingredients and molecular mechanisms of ZQD in treating non-small cell lung cancer (NSCLC) based on network pharmacology combined with experimental validation. Methods: Network pharmacology, bioinformatics, and molecular docking analyses were conducted to explore the mechanism of ZQD for treating NSCLC, which was further confirmed by animal experiments. Results: In total, 117 bioactive ingredients and 499 target proteins of ZQD were identified. Network pharmacology revealed 7 core active ingredients and 74 core target proteins. Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that the PI3K/Akt and p53 signaling pathways may be crucial in NSCLC treatment. Molecular docking analysis revealed that the seven crucial bioactive ingredients complexed with PI3K, Akt, and p53. The animal experiment results validated that ZQD treatment promoted cell apoptosis and cell cycle arrest, thereby inhibiting NSCLC growth and metastasis. Furthermore, ZQD treatment caused a significant increase in p53 and Bax, while leading to a distinct reduction in p-PI3K (Tyr317), p-Akt (Ser473), VEGFA, CD31, MMP2, MMP9, Bcl2, and CDK2. Conclusions: ZQD inhibited the growth and metastasis of NSCLC subcutaneous tumors in C57BL/6J mice via the PI3K/Akt/p53 signaling pathway.

An effective disease diagnostic model related to pyroptosis in ischemic cardiomyopathy.

Pyroptosis is involved in ischemic cardiomyopathy (ICM). The study aimed to investigate the pyroptosis-related genes and clarify their diagnostic value in ICM. The bioinformatics method identified the differential pyroptosis genes between the normal control and ICM samples from online datasets. Then, protein-protein interaction (PPI) and function analysis were carried out to explore the function of these genes. Following, subtype analysis was performed using ConsensusClusterPlus, functions, immune score, stromal score, immune cell proportion and human leukocyte antigen (HLA) genes between subtypes were investigated. Moreover, optimal pyroptosis genes were selected using the least absolute shrinkage and selection operator (LASSO) analysis to construct a diagnostic model and evaluate its effectiveness using receiver operator characteristic (ROC) analysis. Twenty-one differential expressed pyroptosis genes were identified, and these genes were related to immune and pyroptosis. Subtype analysis identified two obvious subtypes: sub-1 and sub-2. And LASSO identified 13 optimal genes used to construct the diagnostic model. The diagnostic model in ICM diagnosis with the area under ROC (AUC) was 0.965. Our results suggested that pyroptosis was tightly associated with ICM.