Custom-Designed Probes for the Accurate Determination of Epidermal Growth Factor Receptor Mutations and Their Allelic Configuration.

The identification of single nucleotide polymorphisms (SNPs) is of paramount importance for disease diagnosis and clinical prognostication. In the context of nonsmall cell lung cancer (NSCLC), the emergence of resistance mutations, exemplified by the epidermal growth factor receptor (EGFR) T790 M and C797S, is intricately linked to the therapeutic efficacy of EGFR tyrosine kinase inhibitors (EGFR-TKIs). Herein, a highly efficient and specific SNP detection platform for T790 M and C797S mutations has been engineered through the integration of an asymmetric polymerase chain reaction (PCR) and an ingeniously tailored four-way junction (4WJ) probe. Notably, a molecular beacon (MB) probe was judiciously designed to discern the allelic configuration of these mutations. The administration of first- and third-generation EGFR-TKIs demonstrates therapeutic efficacy solely when the mutations are in the trans configuration, characterized by a low fluorescence signal. In contrast, significant fluorescence by the MB probe is indicative of the C797S mutation being in a cis arrangement with T790M, thereby rendering the cells refractory to the therapeutic interventions of both first- and third-generation EGFR-TKIs. The assay is capable of concurrently detecting two point-mutations and ascertaining their allelic positions in a single test within 1.5 h, enhancing both efficiency and simplicity. It also exhibits high accuracy in the identification of clinical samples, offering promising implications for therapeutic guidelines. By enabling tailored treatment plans based on specific genetic profiles, our approach not only advances the precision of NSCLC treatment strategies but also marks a significant contribution to personalized medicine.

Assembly of Functional Co(II) Metal-Organic Frameworks through a Mixed Ligand Strategy: Structure and Photocatalytic Degradation Properties.

Four Co(II)-based metal-organic frameworks (MOFs) were constructed by a mixed ligand strategy under solvothermal conditions. The controllable modification of the bridging groups in the secondary building units was realized by changing the anions in MOFs 1-3. The MOF 4 with 3D framework structure was obtained by regulating the solvent ratio following the synthesis process of MOF 3. Furthermore, the MOFs 1-4 exhibited efficient photocatalytic activity for the degradation of malachite green (MG) dye without any photosensitizer or cocatalyst under a low-energy light source, the decolorization ratio of MG all reached more than 96.0% within 60 min, and maximal degradation was obtained to be 99.4% (MOF 4). The recycling experiments showed that the degradation rate of MG was still higher than 91% after 10 cycles. In the MOF 4 as representation, the photocatalytic process was explored systematically. The possible mechanism of catalytic degradation was discussed, which proved the existence of efficient oxidation active factors (•O2-, •OH, and h+). The possible intermediates and degradation pathways were investigated based on high-performance liquid chromatography tandem mass spectrometry. Additionally, MOFs 1-4 also exhibited excellent photocatalytic activity for the degradation of methylene blue, methyl violet, rhodamine B, and basic red 9.

Two 2D Metal-Organic Frameworks Based on Purine Carboxylic Acid Ligands for Photocatalytic Oxidation of Sulfides and CO2 Chemical Fixation.

Two two-dimensional (2D) layered metal-organic frameworks (MOFs), namely, {[Yb(L)(H2O)2NO3]·2H2O}n (Yb-MOF) and [Er(L)(H2O)3Cl]n (Er-MOF) (H2L = 5-((6H-purin-6-yl)amino)isophthalic acid), were constructed by a solvothermal method and characterized. The catalytic performance study showed that the Yb-MOF could efficiently catalyze the oxidation of sulfides to sulfoxides under 15 W light-emitting diode (LED) blue light irradiation. Electron paramagnetic resonance spectroscopy and free-radical trapping experiments demonstrated that the photocatalytic reaction process involved •O2-, and the corresponding mechanism was proposed. Moreover, Er-MOF exhibited good catalytic efficiency and excellent substrate tolerance in the cycloaddition reaction of CO2, and the reaction conditions were mild. After 5 cycles, the catalytic activities of two MOFs did not significantly decrease, and the framework structures remained unchanged. Therefore, the Yb-MOF and Er-MOF were considered efficient and stable heterogeneous catalysts.

A Region-Monitoring-Type Slitless Imaging Spectrometer.

In modern scientific practice, it is necessary to consistently observe predetermined zones, with the expectation of detecting and identifying emerging targets or events inside such areas. This research presents an innovative imaging spectrometer system for the continuous monitoring of specific areas. This study begins by providing detailed information on the features and optical structure of the constructed instrument. This is then followed by simulations using optical design tools. The device has an F-number of 5, a focal length of 100 mm, a field of view of 3 × 7, and a wavelength range spanning from 400 nm to 600 nm. The optical path diagram demonstrates that the system's dispersion and imaging pictures can be distinguished, hence fulfilling the system's specifications. Furthermore, the utilization of a Modulation Transfer Function (MTF) graph has substantiated that the image quality indeed satisfies the specified criteria. To evaluate the instrument's performance in the spectrum observation of fixed regions, a region-monitoring-type slitless imaging spectrometer was built. The equipment has the capability to identify a specific region and rapidly capture the spectra of objects or events that are present inside that region. The spectral data were collected effectively by the implementation of image processing techniques on the captured photos. The correlation coefficient between these data and the reference data was 0.9226, showing that the device successfully measured the target's spectrum. Therefore, the instrument that was created successfully demonstrated its ability to capture images of the observed areas and collect spectral data from the targets located within those regions.

[Ligusticum cycloprolactam inhibits IL-1ß-induced apoptosis and inflammation of rat chondrocytes via HMGB1/TLR4/NF-κB signaling pathway].

Chondrocytes are unique resident cells in the articular cartilage, and the pathological changes of them can lead to the occurrence of osteoarthritis(OA). Ligusticum cycloprolactam(LIGc) are derivatives of Z-ligustilide(LIG), a pharmacodynamic marker of Angelica sinensis, which has various biological functions such as anti-inflammation and inhibition of cell apoptosis. However, its protective effect on chondrocytes in the case of OA and the underlying mechanism remain unclear. This study conducted in vitro experiments to explore the molecular mechanism of LIGc in protecting chondrocytes from OA. The inflammation model of rat OA chondrocyte model was established by using interleukin-1ß(IL-1ß) to induce. LIGc alone and combined with glycyrrhizic acid(GA), a blocker of the high mobility group box-1 protein(HMGB1)/Toll-like receptor 4(TLR4)/nuclear factor-kappa B(NF-κB) signaling pathway, were used to intervene in the model, and the therapeutic effects were systematically evaluated. The viability of chondrocytes treated with different concentrations of LIGc was measured by the cell counting kit-8(CCK-8), and the optimal LIGc concentration was screened out. Annexin V-FITC/PI apoptosis detection kit was employed to examine the apoptosis of chondrocytes in each group. The enzyme-linked immunosorbent assay(ELISA) was employed to measure the expression of cyclooxygenase-2(COX-2), prostaglandin-2(PGE2), and tumor necrosis factor-alpha(TNF-α) in the supernatant of chondrocytes in each group. Western blot was employed to determine the protein levels of B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), caspase-3, HMGB1, TLR4, and NF-κB p65. The mRNA levels of HMGB1, TLR4, NF-κB p65, and myeloid differentiation factor 88(MyD88) in chondrocytes were determined by real-time fluorescent quantitative PCR(RT-qPCR). The safe concentration range of LIGc on chondrocytes was determined by CCK-8, and then the optimal concentration of LIGc for exerting the effect was clarified. Under the intervention of IL-1ß, the rat chondrocyte model of OA was successfully established. The modeled chondrocytes showed increased apoptosis rate, promoted expression of COX-2, PGE2, and TNF-α, up-regulated protein levels of Bax, caspase-3, HMGB1, TLR4, and NF-κB p65 and mRNA levels of HMGB1, TLR4, NF-κB p65, and MyD88, and down-regulated protein level of Bcl-2. However, LIGc reversed the IL-1ß-induced changes of the above factors. Moreover, LIGc combined with GA showed more significant reversal effect than LIGc alone. These fin-dings indicate that LIGc extracted and derived from the traditional Chinese medicine A. sinensis can inhibit the inflammatory response of chondrocytes and reduce the apoptosis of chondrocytes, and this effect may be related to the HMGB1/TLR4/NF-κB signaling pathway. The pharmacological effect of LIGc on protecting chondrocytes has potential value in delaying the progression of OA and improving the clinical symptoms of patients, and deserves further study.

Long noncoding RNA MALAT-1: A versatile regulator in cancer progression, metastasis, immunity, and therapeutic resistance.

Long noncoding RNAs (lncRNAs) are RNA transcripts longer than 200 nucleotides that do not code for proteins but have been linked to cancer development and metastasis. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT-1) influences crucial cancer hallmarks through intricate molecular mechanisms, including proliferation, invasion, angiogenesis, apoptosis, and the epithelial-mesenchymal transition (EMT). The current article highlights the involvement of MALAT-1 in drug resistance, making it a potential target to overcome chemotherapy refractoriness. It discusses the impact of MALAT-1 on immunomodulatory molecules, such as major histocompatibility complex (MHC) proteins and PD-L1, leading to immune evasion and hindering anti-tumor immune responses. MALAT-1 also plays a significant role in cancer immunology by regulating diverse immune cell populations. In summary, MALAT-1 is a versatile cancer regulator, influencing tumorigenesis, chemoresistance, and immunotherapy responses. Understanding its precise molecular mechanisms is crucial for developing targeted therapies, and therapeutic strategies targeting MALAT-1 show promise for improving cancer treatment outcomes. However, further research is needed to fully uncover the role of MALAT-1 in cancer biology and translate these findings into clinical applications.

Harmonizing tumor mutational burden analysis: Insights from a multicenter study using in silico reference data sets in clinical whole-exome sequencing (WES).

OBJECTIVES: Tumor mutational burden (TMB) is a significant biomarker for predicting immune checkpoint inhibitor response, but the clinical performance of whole-exome sequencing (WES)-based TMB estimation has received less attention compared to panel-based methods. This study aimed to assess the reliability and comparability of WES-based TMB analysis among laboratories under routine testing conditions. METHODS: A multicenter study was conducted involving 24 laboratories in China using in silico reference data sets. The accuracy and comparability of TMB estimation were evaluated using matched tumor-normal data sets. Factors such as accuracy of variant calls, limit of detection (LOD) of WES test, size of regions of interest (ROIs) used for TMB calculation, and TMB cutoff points were analyzed. RESULTS: The laboratories consistently underestimated the expected TMB scores in matched tumor-normal samples, with only 50% falling within the ±30% TMB interval. Samples with low TMB score (<2.5) received the consensus interpretation. Accuracy of variant calls, LOD of the WES test, ROI, and TMB cutoff points were important factors causing interlaboratory deviations. CONCLUSIONS: This study highlights real-world challenges in WES-based TMB analysis that need to be improved and optimized. This research will aid in the selection of more reasonable analytical procedures to minimize potential methodologic biases in estimating TMB in clinical exome sequencing tests. Harmonizing TMB estimation in clinical testing conditions is crucial for accurately evaluating patients' response to immunotherapy.

New Mode of Asymmetric Induction for Enantioselective Radical N-Heterobicyclization via Kinetically Stable Chiral Radical Center.

Enantioselective radical N-heterobicyclization of N-allylsulfamoyl azides have been developed via metalloradical catalysis (MRC). The Co(II)-based catalytic system can homolytically activate the organic azides with varied electronic and steric properties for asymmetric radical N-heterobicyclization under mild conditions without the need of oxidants, allowing for stereoselective construction of chiral [3.1.0]-bicyclic sulfamoyl aziridines in excellent yields with high diastereoselectivities and enantioselectivities. The key to achieving the enantioselective radical process relies on catalyst development through ligand design. We demonstrate that the use of new-generation D2-symmetric chiral bridged amidoporphyrin ligand HuPhyrin with judicious variation of the alkyl bridge length can dictate both reactivity and selectivity of Co(II)-based MRC. We present both experimental and computational studies that shed light on the working details of the unprecedented mode of asymmetric induction consisting of enantioface-selective radical addition and stereospecific radical substitution. We showcase the synthetic applications of the resulting enantioenriched bicyclic aziridines through a number of stereospecific transformations.

Study on the Biological Characteristics of Dark Septate Endophytes under Drought and Cadmium Stress and Their Effects on Regulating the Stress Resistance of Astragalus membranaceus.

Astragalus membranaceus is a famous traditional medicinal plant. However, drought and cadmium (Cd) pollution are the main abiotic stress factors that affect plant growth and yield and the ability to improve the host's stress resistance through the use of beneficial endophytic fungi. To evaluate the tolerance of dark septate endophytes (DSE) to various abiotic stresses, 10 DSE strains [Microsphaeropsis cytisi (Mc), Alternaria alstroemeriae (Aa), Stagonosporopsis lupini (Sl), Neocamarosporium phragmitis (Np), Paraphoma chlamydocopiosa (Pc), Macrophomina phaseolina (Mp'), Papulaspora equi (Pe), Alternaria tellustris (At), Macrophomina pseudophaseolina (Mp), and Paraphoma radicina (Pr)] were investigated under different drought and Cd stressors in vitro by using solid-plate cultures and liquid-shaker cultures in the current study. The experiments involved using varying concentrations of PEG (0, 9, 18, and 27%) and Cd2+ (0, 25, 50, and 100 mg/L) to simulate different stress conditions on DSE. Additionally, the effect of DSE (Np and At) on the growth of A. membranaceus at different field water capacities (70% and 40%) and at different CdCl2 concentrations (0, 5, 10, and 15 mg Cd/kg) in soil was studied. The results demonstrated that the colony growth rates of Aa, Np, Pc, Mp', and Mp were the first to reach the maximum diameter at a PEG concentration of 18%. Aa, Np, and At remained growth-active at 100 mg Cd/L. In addition, Aa, Np, and At were selected for drought and Cd stress tests. The results of the drought-combined-with-Cd-stress solid culture indicated that the growth rate of Np was significantly superior to that of the other strains. In the liquid culture condition, the biomasses of Np and Aa were the highest, with biomasses of 1.39 g and 1.23 g under the concentration of 18% + 25 mg Cd/L, and At had the highest biomass of 1.71 g at 18% + 50 mg Cd/L concentration, respectively. The CAT and POD activities of Np reached their peak levels at concentrations of 27% + 50 mg Cd/L and 27% + 25 mg Cd/L, respectively. Compared to the control, these levels indicated increases of 416.97% and 573.12%, respectively. Aa, Np, and At positively influenced SOD activity. The glutathione (GSH) contents of Aa, Np, and At were increased under different combined stressors of drought and Cd. The structural-equation-modeling (SEM) analysis revealed that Aa positively influenced biomass and negatively affected Cd content, while Np and At positively influenced Cd content. Under the stress of 40% field-water capacity and the synergistic stress of 40% field-water capacity and 5 mg Cd/kg soil, Np and At significantly increased root weight of A. membranaceus. This study provides guidance for the establishment of agricultural planting systems and has good development and utilization value.

Understanding key contributing factors on the severity of traffic violations by elderly drivers: a hybrid approach of latent class analysis and XGBoost based SHAP.

Traffic violation is one of the leading causes of traffic crashes. In the context of global aging, it is important to study traffic violations by elderly drivers for improving traffic safety in preparation for a worldwide aging population. In this study, a hybrid approach of Latent Class Analysis (LCA) and XGBoost based SHAP is proposed to identify hidden clusters and to understand the key contributing factors on the severity of traffic violations by elderly drivers, based on the police-reported traffic violation dataset of Beijing (China). First, LCA is applied to segment the dataset into several latent homogeneous clusters, then XGBoost based SHAP is established on each cluster to identify feature contributions and the interaction effects of the key contributing factors on the severity of traffic violations by elderly drivers. Two comparison groups were set up to analyze factors, which are responsible for the different severities of traffic violations. The results show that elderly drivers can be classified into four groups by age, urban or not, license, and season; factors such as less annual number of traffic violations, national & provincial highway, night and winter are key contributing factors for higher severity of traffic violations, which are consistent with common cognition; key contributing factors for all clusters are similar but not identical, for example, more annual number of traffic violations contribute to more severe violation for all clusters except for Cluster 2; some factors which are not key contributing factors may affect the severity of traffic violations when they are combined with other factors, for example, the combination of lower annual number of traffic violations and county & township highway contributes to more severe violation for Cluster 1. These findings can help government to formulate targeted countermeasures to decrease the severity of traffic violations by specific elderly groups and improve road service for the driving population.

Inflammatory Cytokines and Chemokines Are Synergistically Induced in a ROS-Dependent Manner by a Co-Culture of Corneal Epithelial Cells and Neutrophil-like Cells in the Presence of Particulate Matter.

Ocular exposure to particulate matter (PM) causes local inflammation; however, the influence of neutrophils on PM-induced ocular inflammation is still not fully understood. In this study, we constructed a system to investigate the role of PM in ocular inflammation using a co-culture of human corneal epithelial cells (HCE-T) and differentiation-induced neutrophils (dHL-60). To investigate whether HCE-T directly endocytosed PM, we performed a holographic analysis, which showed the endocytosis of PM in HCE-T. The cytokines and chemokines produced by HCE-T were measured using an ELISA. HCE-T treated with PM produced IL-6 and IL-8, which were inhibited by N-Acetyl-L-cysteine (NAC), suggesting the involvement of ROS. Their co-culture with dHL-60 enhanced their production of IL-6, IL-8, and MCP-1. This suggests an inflammatory loop involving intraocular corneal epithelial cells and neutrophils. These cytokines and chemokines are mainly regulated by NF-κB. Therefore, this co-culture system was examined in the presence of an IKK inhibitor known to downregulate NF-κB activity. The IKK inhibitor dramatically suppressed the production of these factors in co-culture supernatants. The results suggest that the inflammatory loop observed in the co-culture is mediated through ROS and the transcription factor NF-κB. Thus, the co-culture system is considered a valuable tool for analyzing complex inflammations.

Overexpression of LINC00853 enhances tumorigenesis and metastasis of gastric cancer.

Gastric cancer (GC) is a rising global health issue, with increasing incidence and mortality rates. The pathogenesis of GC is highly complex and involves a combination of genetic and environmental factors. Therefore, identifying new genes and pathways that contribute to the development and progression of GC is essential for improving diagnosis and treatment outcomes. Long noncoding RNAs (lncRNAs) have recently emerged as a promising area of research in understanding the molecular mechanisms underlying various cancers, including GC. These RNA molecules are longer than 200 nucleotides and do not code proteins. Although initially considered "junk DNA", lncRNAs have been demonstrated to play significant roles in various biological processes, including cell proliferation, differentiation, and apoptosis, as well as in the pathogenesis of various cancers. In this study, we screened clinical specimens for a novel lncRNA, LINC00853, which showed high expression in GC tissues and promoted the proliferation, migration, and invasion of GC cells. Furthermore, in vivo experiments confirmed its ability to facilitate the growth and metastasis of GC. These results suggest that LINC00853 plays a crucial role in the development and progression of GC.

Enhancing the quality of panel-based tumor mutation burden assessment: a comprehensive study of real-world and in-silico outcomes.

Targeted panel-based tumor mutation burden (TMB) assays are widely employed to guide immunotherapy for patients with solid tumors. However, the accuracy and consistency of this method can be compromised due to the variability in technical details across different laboratories, particularly in terms of panel size, somatic mutation detection and TMB calculation rules. Currently, systematic evaluations of the impact of these technical factors on existing assays and best practice recommendations remain lacking. We assessed the performance of 50 participating panel-based TMB assays involving 38 unique methods using cell line samples. In silico experiments utilizing TCGA MC3 datasets were performed to further dissect the impact of technical factors. Here we show that the panel sizes beyond 1.04 Mb and 389 genes are necessary for the basic discrete accuracy, as determined by over 40,000 synthetic panels. The somatic mutation detection should maintain a reciprocal gap of recall and precision less than 0.179 for reliable psTMB calculation results. The inclusion of synonymous, nonsense and hotspot mutations could enhance the accuracy of panel-based TMB assay. A 5% variant allele frequency cut-off is suitable for TMB assays using tumor samples with at least 20% tumor purity. In conclusion, this multicenter study elucidates the major technical factors as sources of variability in panel-based TMB assays and proposed comprehensive recommendations for the enhancement of accuracy and consistency. These findings will assist clinical laboratories in optimizing the methodological details through bioinformatic experiments to enhance the reliability of panel-based methods.

Considering multi-scale built environment in modeling severity of traffic violations by elderly drivers: An interpretable machine learning framework.

The causes of traffic violations by elderly drivers are different from those of other age groups. To reduce serious traffic violations that are more likely to cause serious traffic crashes, this study divided the severity of traffic violations into three levels (i.e., slight, ordinary, severe) based on point deduction, and explore the patterns of serious traffic violations (i.e., ordinary, severe) using multi-source data. This paper designed an interpretable machine learning framework, in which four popular machine learning models were enhanced and compared. Specifically, adaptive synthetic sampling method was applied to overcome the effects of imbalanced data and improve the prediction accuracy of minority classes (i.e., ordinary, severe); multi-objective feature selection based on NSGA-II was used to remove the redundant factors to increase the computational efficiency and make the patterns discovered by the explainer more effective; Bayesian hyperparameter optimization aimed to obtain more effective hyperparameters combination with fewer iterations and boost the model adaptability. Results show that the proposed interpretable machine learning framework can significantly improve and distinguish the performance of four popular machine learning models and two post-hoc interpretation methods. It is found that six of the top ten important factors belong to multi-scale built environment attributes. By comparing the results of feature contribution and interaction effects, some findings can be summarized: ordinary and severe traffic violations have some identical influencing factors and interactive effects; have the same influencing factors or the same combinations of influencing factors, but the values of the factors are different; have some unique influencing factors and unique combinations of influencing factors.

Causal relationships between gut microbiota and dementia: A two-sample, bidirectional, Mendelian randomization study.

BACKGROUND: Existing evidence suggests that gut microbiota represent a significant environmental risk factor for various forms of dementia, including Alzheimer's dementia, vascular dementia, and dementia in other diseases classified elsewhere. However, the exact causal relationships between gut microbiota and the different forms of dementia or their subtypes remain unclear. AIM: To investigate putative causal relationships between gut microbiota and dementia or its subtypes using Mendelian randomization (MR) analysis. METHODS: A bidirectional, two-sample, MR analysis was conducted utilizing publicly available gut microbiota-related genome-wide association study (GWAS) summary data from the MiBioGen consortium alongside GWAS summary statistics for dementia and its subtypes from the FinnGen consortium. Instrumental variables were selected according to the fundamental tenets of MR and their strengths were evaluated using the F-statistic. Five MR methods were employed, and the robustness of our findings was validated. To account for multiple comparisons, we applied the Bonferroni method for P-value adjustment. RESULTS: We identified several gut microbiota taxa exhibiting putative causal relationships with dementia or its subtypes, potentially serving as risk or protective factors for the disease. In addition, reverse MR analysis indicated that the relative abundance of several gut microbiota taxa might be influenced by dementia or its subtypes. An exhaustive sensitivity analysis confirmed the absence of heterogeneity and horizontal pleiotropy. After applying correction for multiple testing, we observed that the order Bacillales (odds ratio: 0.830, 95% confidence interval: 0.740-0.932, P = 0.00155, Padjust = 0.0311) exhibited a strong association with Alzheimer's disease-related dementia. CONCLUSION: The results suggest that gut microbiota is causally associated with dementia. Our findings provide novel insights into the pathophysiology of dementia and have important implications for its treatment and prevention.

Single-cell transcriptomic analysis identifies downregulated phosphodiesterase 8B as a novel oncogene in IDH-mutant glioma.

Introduction: Glioma, a prevalent and deadly brain tumor, is marked by significant cellular heterogeneity and metabolic alterations. However, the comprehensive cell-of-origin and metabolic landscape in high-grade (Glioblastoma Multiforme, WHO grade IV) and low-grade (Oligoastrocytoma, WHO grade II) gliomas remains elusive. Methods: In this study, we undertook single-cell transcriptome sequencing of these glioma grades to elucidate their cellular and metabolic distinctions. Following the identification of cell types, we compared metabolic pathway activities and gene expressions between high-grade and low-grade gliomas. Results: Notably, astrocytes and oligodendrocyte progenitor cells (OPCs) exhibited the most substantial differences in both metabolic pathways and gene expression, indicative of their distinct origins. The comprehensive analysis identified the most altered metabolic pathways (MCPs) and genes across all cell types, which were further validated against TCGA and CGGA datasets for clinical relevance. Discussion: Crucially, the metabolic enzyme phosphodiesterase 8B (PDE8B) was found to be exclusively expressed and progressively downregulated in astrocytes and OPCs in higher-grade gliomas. This decreased expression identifies PDE8B as a metabolism-related oncogene in IDH-mutant glioma, marking its dual role as both a protective marker for glioma grading and prognosis and as a facilitator in glioma progression.

RLP system: A single-tube two-step approach with dual amplification cascades for rapid identification of EGFR T790M.

BACKGROUND: The detection of cancer gene mutations in biofluids plays a pivotal role in revolutionizing disease diagnosis. The presence of a large background of wild-type sequences poses a challenge to liquid biopsy of tumor mutation genes. Suppressing the detection of wild-type sequences can reduce their interference, however, due to the minimal difference between mutant and wild-type sequences (such as single nucleotide variants differing by only one nucleotide), how to suppress the detection of wild-type sequences to the greatest extent without compromising the sensitivity of mutant sequence detection remains to be explored. SIGNIFICANCE: The RLP system addresses the incompatibility between RPA and RT-PCR reactions through a physical separation strategy. Besides, due to the remarkable flexibility of locked nucleic acid probes, the RLP system emerges as a potent tool for detecting mutations across diverse genes. It excels in sensitivity and speed, tolerates plasma matrix, and is cost-effective. This bodes well for advancing the field of precision medicine. RESULTS: The recombinase-assisted locked nucleic acid (LNA) probe-mediated dual amplification biosensing platform (namely RLP), which combines recombinase polymerase amplification (RPA) and LNA clamp PCR method in one tube, enabling highly sensitive and selective detection of EGFR T790M mutation under the help of well-designed LNA probes. This technique can quantify DNA targets with a limit of detection (LoD) at the single copy level and identify point mutation with mutant allelic fractions as low as 0.007 % in 45 min. Moreover, RLP has the potential for the direct detection of plasma samples without the need for nucleic acid extraction and the cost of a single test is less than 1USD. Furthermore, the RLP system is a cascading dual amplification reaction conducted in a single tube, which eliminates the risk of cross-contamination associated with opening multiple tubes and ensures the reliability of the results.

Exosome secretion related gene signature predicts chemoresistance in patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a highly heterogeneous malignancy, and patients often have different responses to treatment. In this study, the genetic characteristics related to exosome formation and secretion procedure were used to predict chemoresistance and guide the individualized treatment of patients. METHODS: Firstly, seven microarray datasets in Gene Expression Omnibus (GEO) and RNA-Seq dataset from the Cancer Genome Atlas (TCGA) were used to analysis the transcriptome profiles and associated characteristics of CRC patients. Then, a predictive model based on gene features linked to exosome formation and secretion was created and validated using Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) machine learning. Finally, we evaluated the model using chemoresistant/chemosensitive cells and tissues by immunofluorescence (IF), western blot (WB), quantitative real-time PCR (qRT-PCR) and immunocytochemistry (IHC) experiments, and the predictive value of integrated model in the clinical validation cohort were performed by Receiver Operating Characteristic (ROC) and Kaplan-Meier (K-M) curves analyses. RESULTS: We established a risk score signature based on three genes related to exosome secretion in CRC. Better Overall Survival (OS) and greater chemosensitivity were seen in the low-risk group, whereas the high-risk group exhibited chemoresistance and a subpar response to immune checkpoint blockade (ICB) therapy. Higher expression of the model genes EXOC2, EXOC3 and STX4 were observed in chemoresistant cells and specimens. The AUC of 5-year disease-free survival (DFS) was 0.804. Compared with that in the low-risk group, patients' DFS was found to be significantly worse in the high-risk group. CONCLUSIONS: In summary, the gene signature related to exosome formation and secretion could reliably predict patients' chemosensitivity and ICB treatment response, which providing new independent biomarkers for the treatment of CRC.

Diabetes mellitus as a risk factor for severe dengue fever and West Nile fever: A meta-analysis.

BACKGROUND: Dengue fever (DF) and West Nile fever (WNF) have become endemic worldwide in the last two decades. Studies suggest that individuals with diabetes mellitus (DM) are at a higher risk of developing severe complications from these diseases. Identifying the factors associated with a severe clinical presentation is crucial, as prompt treatment is essential to prevent complications and fatalities. This article aims to summarize and assess the published evidence regarding the link between DM and the risk of severe clinical manifestations in cases of DF and WNF. METHODOLOGY/PRINCIPAL FINDINGS: A systematic search was conducted using the PubMed and Web of Science databases. 27 studies (19 on DF, 8 on WNF) involving 342,873 laboratory-confirmed patients were included in the analysis. The analysis showed that a diagnosis of DM was associated with an increased risk for severe clinical presentations of both DF (OR 3.39; 95% CI: 2.46, 4.68) and WNF (OR 2.89; 95% CI: 1.89, 4.41). DM also significantly increased the risk of death from both diseases (DF: OR 1.95; 95% CI: 1.09, 3.52; WNF: OR 1.74; 95% CI: 1.40, 2.17). CONCLUSIONS/SIGNIFICANCE: This study provides strong evidence supporting the association between DM and an increased risk of severe clinical manifestations in cases of DF and WNF. Diabetic individuals in DF or WNF endemic areas should be closely monitored when presenting with febrile symptoms due to their higher susceptibility to severe disease. Early detection and appropriate management strategies are crucial in reducing the morbidity and mortality rates associated with DF and WNF in diabetic patients. Tailored care and targeted public health interventions are needed to address this at-risk population. Further research is required to understand the underlying mechanisms and develop effective preventive and therapeutic approaches.