Characteristics and comparative study of medicinal materials between China and India based on data mining from literatures.

ETHNOPHARMACOLOGICAL RELEVANCE: China and India have unique traditional medicine systems with vast territory and rich medical resources. Traditional medicines in China include traditional Chinese medicine, Tibetan medicine, Mongolian medicine, Uyghur medicine, Dai medicine, etc. In the third national survey of Chinese medicine resources, 12694 medicinal materials were identified. Traditional medicines in India include Ayurveda, Unani, Siddha, Homoeopathy, etc. There are 7263 medicinal materials in India. AIM OF THE STUDY: To reveal the characteristics of medicinal materials between China and India respectively, and to compare the similarities and differences in terms of properties, tastes, medicinal parts and therapeutic uses and to promote the exchange of traditional medicine between China and India and the international trade of traditional medicine industry. METHODS: The information of medicinal materials between China and India was extracted from The Chinese Traditional Medicine Resource Records and Pharmacopoeia of the People's Republic of China, as well as from 71 Indian herbal monographs. The information of each medicinal material, such as types, families, genera, properties, distribution, medicinal parts, efficacy, therapeutic uses, dosage form and dosage, was recorded in Excel for statistical analysis and visual comparison. RESULTS: A total of 12694 medicinal materials in China and 5362 medicinal materials in India were identified. The medicinal materials were mostly distributed in Southwest China and northern India. Plants were the main sources of medicinal materials. The common medicinal parts in China were whole medicinal materials, roots and rhizomes, and India used more renewable fruits, seeds and leaves. They are commonly used in the treatment of digestive system diseases. There were 1048 medicinal materials used by both China and India, which were distributed in 188 families and 685 genera. The Chinese and Indian pharmacopoeias had a total of 80 species of medicinal materials used by both China and India. CONCLUSIONS: The characteristics of medicinal materials between China and India were somewhat different, which was conducive to provide a reference basis for traditional medicine in China or India to increase the medicinal parts and indications when using a certain medicinal material, as well as to expand the source of medicine and introduce new resources. However, there were certain similarities and shared medicinal materials, which can tap the potential of bilateral trade of medicinal materials between China and India, so as to promote the medical cultural exchange and economic and trade cooperation between the two countries.

Activating innate immune responses repolarizes hPSC-derived CAR macrophages to improve anti-tumor activity.

Generation of chimeric antigen receptor macrophages (CAR-Ms) from human pluripotent stem cells (hPSCs) offers new prospects for cancer immunotherapy but is currently challenged by low differentiation efficiency and limited function. Here, we develop a highly efficient monolayer-based system that can produce around 6,000 macrophages from a single hPSC within 3 weeks. Based on CAR structure screening, we generate hPSC-CAR-Ms with stable CAR expression and potent tumoricidal activity in vitro. To overcome the loss of tumoricidal activity of hPSC-CAR-Ms in vivo, we use interferon-γ and monophosphoryl lipid A to activate an innate immune response that repolarizes the hPSC-CAR-Ms to tumoricidal macrophages. Moreover, through combined activation of T cells by hPSC-CAR-Ms, we demonstrate that activating a collaborative innate-adaptive immune response can further enhance the anti-tumor effect of hPSC-CAR-Ms in vivo. Collectively, our study provides feasible methodologies that significantly improve the production and function of hPSC-CAR-Ms to support their translation into clinical applications.

Artificial intelligence enhances whole-slide interpretation of PD-L1 CPS in triple-negative breast cancer: A multi-institutional ring study.

BACKGROUND AND AIMS: Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability in the consistency and accuracy of the interpretation. It is of great importance to establish an objective and effective method which is highly repeatable. METHODS: We proposed a model in a deep learning-based framework, which at the patch level incorporated cell analysis and tissue region analysis, followed by the whole-slide level fusion of patch results. Three rounds of ring studies (RSs) were conducted. Twenty-one pathologists of different levels from four institutions evaluated the PD-L1 CPS in TNBC specimens as continuous scores by visual assessment and our artificial intelligence (AI)-assisted method. RESULTS: In the visual assessment, the interpretation results of PD-L1 (Dako 22C3) CPS by different levels of pathologists have significant differences and showed weak consistency. Using AI-assisted interpretation, there were no significant differences between all pathologists (P = 0.43), and the intraclass correlation coefficient (ICC) value was increased from 0.618 [95% confidence interval (CI) = 0.524-0.719] to 0.931 (95% CI = 0.902-0.955). The accuracy of interpretation result is further improved to 0.919 (95% CI = 0.886-0.947). Acceptance of AI results by junior pathologists was the highest among all levels, and 80% of the AI results were accepted overall. CONCLUSION: With the help of the AI-assisted diagnostic method, different levels of pathologists achieved excellent consistency and repeatability in the interpretation of PD-L1 (Dako 22C3) CPS. Our AI-assisted diagnostic approach was proved to strengthen the consistency and repeatability in clinical practice.

Isolation, characterization and functional analysis of a bacteriophage targeting Culex pipiens pallens resistance-associated Aeromonas hydrophila.

BACKGROUND: Culex pipiens pallens is a well-known mosquito vector for several diseases. Deltamethrin, a commonly used pyrethroid insecticide, has been frequently applied to manage adult Cx. pipiens pallens. However, mosquitoes can develop resistance to these insecticides as a result of insecticide misuse and, therefore, it is crucial to identify novel methods to control insecticide resistance. The relationship between commensal bacteria and vector resistance has been recently recognized. Bacteriophages (= phages) are effective tools by which to control insect commensal bacteria, but there have as yet been no studies using phages on adult mosquitoes. In this study, we isolated an Aeromonas phage vB AhM-LH that specifically targets resistance-associated symbiotic bacteria in mosquitoes. We investigated the impact of Aeromonas phage vB AhM-LH in an abundance of Aeromonas hydrophila in the gut of Cx. pipiens pallens and its effect on the status of deltamethrin resistance. METHODS: Phages were isolated on double-layer agar plates and their biological properties analyzed. Phage morphology was observed by transmission electron microscopy (TEM) after negative staining. The phage was then introduced into the mosquito intestines via oral feeding. The inhibitory effect of Aeromonas phage vB AhM-LH on Aeromonas hydrophila in mosquito intestines was assessed through quantitative real-time PCR analysis. Deltamethrin resistance of mosquitoes was assessed using WHO bottle bioassays. RESULTS: An Aeromonas phage vB AhM-LH was isolated from sewage and identified as belonging to the Myoviridae family in the order Caudovirales using TEM. Based on biological characteristics analysis and in vitro antibacterial experiments, Aeromonas phage vB AhM-LH was observed to exhibit excellent stability and effective bactericidal activity. Sequencing revealed that the Aeromonas phage vB AhM-LH genome comprises 43,663 bp (51.6% CG content) with 81 predicted open reading frames. No integrase-related gene was detected in the vB AH-LH genome, which marked it as a potential biological antibacterial. Finally, we found that Aeromonas phage vB AhM-LH could significantly reduce deltamethrin resistance in Cx. pipiens pallens, in both the laboratory and field settings, by decreasing the abundance of Aeromonas hydrophila in their midgut. CONCLUSIONS: Our findings demonstrate that Aeromonas phage vB AhM-LH could effectively modulate commensal bacteria Aeromonas hydrophila in adult mosquitoes, thus representing a promising strategy to mitigate mosquito vector resistance.

Facile synthesis of MOF-808/RGO-based 3D macroscopic aerogel for enhanced photoreduction CO2.

Three-dimensional (3D) macroscopic aerogels have emerged as a critical component in the realm of photocatalysis. Maximizing the integration of materials can result in enhanced efficiency and selectivity in photocatalytic processes. In this investigation, we fabricated MOF-808/reduced graphene oxide (RGO) 3D macroscopic aerogel composite materials employing the techniques of hydrothermal synthesis and freeze-drying. The results revealed that the macroscopic aerogel material exhibited the highest performance in CO2 reduction to CO, particularly when the concentration of RGO was maintained at 5 mg mL-1. In addition, we synthesized powder materials of MR-5 composite photocatalysts and conducted a comparative analysis in terms of photocatalytic CO2 reduction performance and electron transfer efficiency. The results showthat the macroscopic aerogel material boasts a high specific surface area, an abundant internal pore structure, and increased active sites. These attributes collectively enhance light energy utilization, and electron transfer rates, thereby, improving photothermal and photoelectric conversion efficiencies. Furthermore, we conducted in-situ FT-IR measurements and found that the M/R-5 aerogel exhibited the best CO2 adsorption capacity under a CO2 flow rate of 10 mL min-1. The density functional theory results demonstrate the correlation between the formation pathway of the product and the charge transfer pathway. This study provides useful ideas for realizing photocatalytic CO2 reduction of macroscopic aerogel materials in gas-solid reaction mode.

Single Effective Complex Loading into Zero-Mode Waveguides Optimized with Fluorescence Evaluation at Quenching and Accumulation Checkpoints.

Single-molecule detection with high accuracy and specialty plays an important role in biomedical diagnosis and screening. Zero-mode waveguides (ZMWs) enable the possibility of single biological molecule detection in real time. Nevertheless, the absence of a reliable assessment for single effective complex loading has constrained further applications of ZMWs in complex interaction. Both the quantity and activity of the complex loaded into ZMWs have a critical effect on the efficiency of detection. Herein, a fluorescence evaluation at quenching and accumulation checkpoints was established to assess and optimize single effective complex loading into ZMWs. A primer-template-enzyme ternary complex was designed, and then an evaluation for quantity statistics at the quenching checkpoint and functional activity at the accumulation checkpoint was used to validate the effectiveness of complexes loaded into ZMWs. By optimizing the parameters such as loading time, procedures, and enzyme amount, the single-molecule effective occupancy was increased to 25.48%, achieving 68.86% of the theoretical maximum value (37%) according to Poisson statistics. It is of great significance to provide effective complex-loading validation for improving the sample-loading efficiency of single-molecule assays or sequencing in the future.

High-resolution vasomotion analysis reveals novel arteriole physiological features and progressive modulation of cerebral vascular networks by stroke.

Spontaneous cerebral vasomotion, characterized by ∼0.1 Hz rhythmic contractility, is crucial for brain homeostasis. However, our understanding of vasomotion is limited due to a lack of high-precision analytical methods to determine single vasomotion events at basal levels. Here, we developed a novel strategy that integrates a baseline smoothing algorithm, allowing precise measurements of vasodynamics and concomitant Ca2+ dynamics in mouse cerebral vasculature imaged by two-photon microscopy. We identified several previously unrecognized vasomotion properties under different physiological and pathological conditions, especially in ischemic stroke, which is a highly harmful brain disease that results from vessel occlusion. First, the dynamic characteristics between SMCs Ca2+ and corresponding arteriolar vasomotion are correlated. Second, compared to previous diameter-based estimations, our radius-based measurements reveal anisotropic vascular movements, enabling a more precise determination of the latency between smooth muscle cell (SMC) Ca2+ activity and vasoconstriction. Third, we characterized single vasomotion event kinetics at scales of less than 4 seconds. Finally, following pathological vasoconstrictions induced by ischemic stroke, vasoactive arterioles entered an inert state and persisted despite recanalization. In summary, we developed a highly accurate technique for analyzing spontaneous vasomotion, and our data suggested a potential strategy to reduce stroke damage by promoting vasomotion recovery.

Disulfidptosis-related lncRNA signature reveals immune microenvironment and novel molecular subtyping of stomach adenocarcinoma.

The main challenge in treating stomach adenocarcinoma (STAD) is chemotherapy resistance, which is characterized by changes in the immune microenvironment. Disulfidptosis, a novel form of programmed cell death, is involved in STAD but its mechanism is not fully understood. Long non-coding RNAs (LncRNAs) may play a role in regulating disulfidptosis and influencing the immune microenvironment and chemotherapy resistance in STAD. This study aims to establish disulfidptosis-related lncRNA (DRL) features and explore their significance in the immune microenvironment and chemotherapy resistance in STAD patients. By analyzing RNA sequencing and clinical data from STAD patients and extracting disulfidptosis-related genes, we identified DRLs through co-expression, single-factor and multi-factor Cox regression, and Lasso regression analyses. We also investigated differences in the immune microenvironment, immune function, immune checkpoint gene expression, and chemotherapy resistance between different risk groups using various algorithms. A prognostic risk model consisting of 2 DRLs was constructed, with a strong predictive value for patient survival, outperforming other clinical-pathological factors in predicting 3-year and 5-year survival. Immune-related analysis revealed a strong positive correlation between T cell CD4+ cells and risk score across all algorithms, and higher expression of immune checkpoint genes in the high-risk group. In addition, high-risk patients showed better sensitivity to Erlotinib, Oxaliplatin, and Gefitinib. Furthermore, three novel molecular subtypes of STAD were identified based on the 2-DRLs features, with evaluation of the immune microenvironment and chemotherapy drug sensitivity for each subgroup, which holds significant implications for achieving precise treatment in STAD. Overall, our 2-DRLs prognostic model demonstrates high predictive value for patient survival in STAD, potentially providing new targets for individualized immune and chemical therapy.

A PCF Sensor Design Using Biocompatible PDMS for Biosensing.

A novel photonic crystal fiber (PCF) sensor for refractive index detection based on polydimethylsiloxane (PDMS) is presented in this research, as well as designs for single-channel and dual-channel structures for this PDMS-PCF sensor. The proposed structures can be used to develop sensors with biocompatible polymers. The performance of the single-channel PDMS-PCF sensor was studied, and it was found that adjusting parameters such as pore diameter, lattice constant, distance between the D-shaped structure and the fiber core, and the radius of gold nanoparticles can optimize the sensor's performance. The findings indicate that the detection range of the single-channel photonic crystal is 1.21-1.27. The maximum wavelength sensitivity is 10,000 nm/RIU with a resolution of 1×10-5 RIU, which is gained when the refractive index is set to 1.27. Based on the results of the single-channel PCF, a dual-channel PDMS-PCF sensor is designed. The refractive index detection range of the proposed sensor is 1.2-1.28. The proposed sensor has a maximum wavelength sensitivity of 13,000 nm/RIU and a maximum resolution of 7.69×10-6 RIU at a refractive index of 1.28. The designed PDMS-PCF holds tremendous potential for applications in the analysis and detection of substances in the human body in the future.

A New Method for In-Situ Characterization of Solid-State Batteries Based on Optical Coherence Tomography.

With the in-depth study of solid-state batteries (SSBs), various in situ and ex situ characterization technologies have been widely used to study them. The performance and reliability of SSBs are limited by the formation and evolution of lithium dendrites at the interfaces between solid electrodes and solid electrolytes. We propose a new method based on optical coherence tomography (OCT) for in situ characterization of the internal state of solid-state batteries. OCT is a low-loss, high-resolution, non-invasive imaging technique that can provide real-time monitoring of cross-sectional images of internal structures of SSBs. The morphology, growth, and evolution of lithium dendrites at different stages of cycling under various conditions can be visualized and quantified by OCT. Furthermore, we validate and correlate the OCT results with scanning electron microscopy (SEM) and XPS, proving the accuracy and effectiveness of the OCT characterization method. We reveal the interfacial phenomena and challenges in SSBs and demonstrate the feasibility and advantages of OCT as a powerful tool for in situ and operando imaging of battery interfaces. This study provides new insights into the mechanisms and factors that affect SSB performance, safety, and lifetime, and suggests possible solutions for improvement and application in the field of applied energy.

Effect of Pulping Waste Liquid on the Physicochemical Properties and the Prediction Model of Wheat Straw Residue Granular Fuels.

Herein, wheat straw residue and pulping waste liquid were collected from pulping mill and mixed to prepare bio-based granular fuels by using compression molding technology, and to explore the comprehensive utilization of the industrial waste of pulping and papermaking. The effects of pulping waste liquid on granular fuel properties were analyzed systemically. Further study of the function of pulping waste liquid, cellulose and hemicellulose was used to replace wheat straw residue and avoid the interference factors. Therefore, the prediction models of granular fuels were established with influencing factors that included cellulose, hemicellulose and pulping waste liquid. The granular fuels had the best performance with 18.30% solid content of pulping waste liquid. The highest transverse compressive strength of granular fuel was 102.61 MPa, and the activation energy was 81.71 KJ·mol-1. A series of curve fitting prediction models were established to clarify the forming process of granular fuel, and it turned out that the pulping waste liquid could improve the adhesion between solid particles and increase their compression resistance.

Lipid metabolism-related long noncoding RNA RP11-817I4.1 promotes fatty acid synthesis and tumor progression in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common types of tumors. The influence of lipid metabolism disruption on the development of HCC has been demonstrated in published studies. AIM: To establish an HCC prognostic model for lipid metabolism-related long non-coding RNAs (LMR-lncRNAs) and conduct in-depth research on the specific role of novel LMR-lncRNAs in HCC. METHODS: Correlation and differential expression analyses of The Cancer Genome Atlas data were used to identify differentially expressed LMR-lncRNAs. Quantitative real-time polymerase chain reaction analysis was used to evaluate the expression of LMR-lncRNAs. Nile red staining was employed to observe intracellular lipid levels. The interaction between RP11-817I4.1, miR-3120-3p, and ATP citrate lyase (ACLY) was validated through the performance of dual-luciferase reporter gene and RIP assays. RESULTS: Three LMR-lncRNAs (negative regulator of antiviral response, RNA transmembrane and coiled-coil domain family 1 antisense RNA 1, and RP11-817I4.1) were identified as predictive markers for HCC patients and were utilized in the construction of risk models. Additionally, proliferation, migration, and invasion were reduced by RP11-817I4.1 knockdown. An increase in lipid levels in HCC cells was significantly induced by RP11-817I4.1 through the miR-3120-3p/ACLY axis. CONCLUSION: LMR-lncRNAs have the capacity to predict the clinical characteristics and prognoses of HCC patients, and the discovery of a novel LMR-lncRNAs, RP11-817I4.1, revealed its role in promoting lipid accumulation, thereby accelerating the onset and progression of HCC.

Lactobacillus rhamnosus GG ameliorates hyperuricemia in a novel model.

Hyperuricemia (HUA) is a metabolic syndrome caused by abnormal purine metabolism. Although recent studies have noted a relationship between the gut microbiota and gout, whether the microbiota could ameliorate HUA-associated systemic purine metabolism remains unclear. In this study, we constructed a novel model of HUA in geese and investigated the mechanism by which Lactobacillus rhamnosus GG (LGG) could have beneficial effects on HUA. The administration of antibiotics and fecal microbiota transplantation (FMT) experiments were used in this HUA goose model. The effects of LGG and its metabolites on HUA were evaluated in vivo and in vitro. Heterogeneous expression and gene knockout of LGG revealed the mechanism of LGG. Multi-omics analysis revealed that the Lactobacillus genus is associated with changes in purine metabolism in HUA. This study showed that LGG and its metabolites could alleviate HUA through the gut-liver-kidney axis. Whole-genome analysis, heterogeneous expression, and gene knockout of LGG enzymes ABC-type multidrug transport system (ABCT), inosine-uridine nucleoside N-ribohydrolase (iunH), and xanthine permease (pbuX) demonstrated the function of nucleoside degradation in LGG. Multi-omics and a correlation analysis in HUA patients and this goose model revealed that a serum proline deficiency, as well as changes in Collinsella and Lactobacillus, may be associated with the occurrence of HUA. Our findings demonstrated the potential of a goose model of diet-induced HUA, and LGG and proline could be promising therapies for HUA.

Precise large-fragment deletions in mammalian cells and mice generated by dCas9-controlled CRISPR/Cas3.

Currently, the Cas9 and Cas12a systems are widely used for genome editing, but their ability to precisely generate large chromosome fragment deletions is limited. Type I-E CRISPR mediates broad and unidirectional DNA degradation, but controlling the size of Cas3-mediated DNA deletions has proven elusive thus far. Here, we demonstrate that the endonuclease deactivation of Cas9 (dCas9) can precisely control Cas3-mediated large-fragment deletions in mammalian cells. In addition, we report the elimination of the Y chromosome and precise retention of the Sry gene in mice using CRISPR/Cas3 and dCas9-controlled CRISPR/Cas3, respectively. In conclusion, dCas9-controlled CRISPR/Cas3-mediated precise large-fragment deletion provides an approach for establishing animal models by chromosome elimination. This method also holds promise as a potential therapeutic strategy for treating fragment mutations or human aneuploidy diseases that involve additional chromosomes.

Ca2+ oscillation in vascular smooth muscle cells control myogenic spontaneous vasomotion and counteract post-ischemic no-reflow.

Ischemic stroke produces the highest adult disability. Despite successful recanalization, no-reflow, or the futile restoration of the cerebral perfusion after ischemia, is a major cause of brain lesion expansion. However, the vascular mechanism underlying this hypoperfusion is largely unknown, and no approach is available to actively promote optimal reperfusion to treat no-reflow. Here, by combining two-photon laser scanning microscopy (2PLSM) and a mouse middle cerebral arteriolar occlusion (MCAO) model, we find myogenic vasomotion deficits correlated with post-ischemic cerebral circulation interruptions and no-reflow. Transient occlusion-induced transient loss of mitochondrial membrane potential (ΔΨm) permanently impairs mitochondria-endoplasmic reticulum (ER) contacts and abolish Ca2+ oscillation in smooth muscle cells (SMCs), the driving force of myogenic spontaneous vasomotion. Furthermore, tethering mitochondria and ER by specific overexpression of ME-Linker in SMCs restores cytosolic Ca2+ homeostasis, remotivates myogenic spontaneous vasomotion, achieves optimal reperfusion, and ameliorates neurological injury. Collectively, the maintaining of arteriolar myogenic vasomotion and mitochondria-ER contacts in SMCs, are of critical importance in preventing post-ischemic no-reflow.

Self-correction of cycle threshold values by a normal distribution-based process to improve accuracy of quantification in real-time digital PCR.

The digital polymerase chain reaction (dPCR) is a new and developing nucleic acid detection technology with high sensitivity that can realize the absolute quantitative analysis of samples. In order to improve the accuracy of quantitative results, real-time digital PCR emphasizes the kinetic information during amplification to identify prominent abnormal data. However, it is challenging to use a unified standard to accurately classify the amplification curve of each well as negative and positive, due to the interference caused by various factors in the experiment. In this work, a normal distribution-based cycle threshold value self-correcting model (NCSM) was established, which focused on the feature of the cycle threshold values in amplification curves and conducted continuous detection and correction on the whole. The cycle threshold value distribution was closer to the ideal normal distribution to avoid the influence of interference. Thus, the model achieves a more accurate classification between positive and negative results. The corrective process was applied to plasmid samples and resulted in an accuracy improvement from 92 to 99%. The coefficient of variation was below 5% when considering the quantitation of a range between 100 and 10,000 copies. At the same time, by utilizing this model, the distribution of cycle threshold values at the endpoint can be predicted with fewer thermal cycles, which can reduce the cycling time by around 25% while maintaining a consistency of more than 98%. Therefore, using the NCSM can effectively enhance the quantitative accuracy and increase the detection efficiency based on the real-time dPCR platform.

Programmable RNA 5-methylcytosine (m5C) modification of cellular RNAs by dCasRx conjugated methyltransferase and demethylase.

5-Methylcytosine (m5C), an abundant RNA modification, plays a crucial role in regulating RNA fate and gene expression. While recent progress has been made in understanding the biological roles of m5C, the inability to introduce m5C at specific sites within transcripts has hindered efforts to elucidate direct links between specific m5C and phenotypic outcomes. Here, we developed a CRISPR-Cas13d-based tool, named reengineered m5C modification system (termed 'RCMS'), for targeted m5C methylation and demethylation in specific transcripts. The RCMS editors consist of a nuclear-localized dCasRx conjugated to either a methyltransferase, NSUN2/NSUN6, or a demethylase, the catalytic domain of mouse Tet2 (ten-eleven translocation 2), enabling the manipulation of methylation events at precise m5C sites. We demonstrate that the RCMS editors can direct site-specific m5C incorporation and demethylation. Furthermore, we confirm their effectiveness in modulating m5C levels within transfer RNAs and their ability to induce changes in transcript abundance and cell proliferation through m5C-mediated mechanisms. These findings collectively establish RCMS editors as a focused epitranscriptome engineering tool, facilitating the identification of individual m5C alterations and their consequential effects.

Potential molecular biomarkers for the diagnosis and prognosis of bladder cancer.

Bladder cancer (BC) is a common malignant tumor of urinary system, which can be divided into muscle-invasive BC (MIBC) and nonmuscle-invasive BC (NMIBC). The number of BC patients has been gradually increasing currently. At present, bladder tumours are diagnosed and followed-up using a combination of cystoscopic examination, cytology and histology. However, the detection of early grade tumors, which is much easier to treat effectively than advanced stage disease, is still insufficient. It frequently recurs and can progress when not expeditiously diagnosed and monitored following initial therapy for NMIBC. Treatment strategies are totally different for different stage diseases. Therefore, it is of great practical significance to study new biomarkers for diagnosis and prognosis. In this review, we summarize the current state of biomarker development in BC diagnosis and prognosis prediction. We retrospectively analyse eight diagnostic biomarkers and eight prognostic biomarkers, in which CK, P53, PPARγ, PTEN and ncRNA are emphasized for discussion. Eight molecular subtype systems are also identified. Clinical translation of biomarkers for diagnosis, prognosis, monitoring and treatment will hopefully improve outcomes for patients. These potential biomarkers provide an opportunity to diagnose tumors earlier and with greater accuracy, and help identify those patients most at risk of disease recurrence.

The relationship between nonsteroidal anti-inflammatory drugs and cancer incidence: An umbrella review.

Several clinical and preclinical studies have shown that nonsteroidal anti-inflammatory drugs (NSAIDs), particularly aspirin, reduce the incidence of various cancer types. However, there is still a lack of literature evaluating the overall association between multiple cancer morbidities and NSAIDs. Thus, we conducted an umbrella review to evaluate the quality of evidence, validity, and biases of the existing systematic reviews and meta-analyses on the relationships between NSAIDS and multiple tumor incidence outcomes. We found that NSAIDs might be associated with a decreased risk of several cancers, including the central nervous system, breast, esophageal, gastric, head and neck, hepatocellular, cholangiocarcinoma, colorectal, endometrial, lung, ovary, prostate, and pancreatic cancers, but regular intake of any dose of non-aspirin NSAIDs (NA-NSAIDs) could increase the incidence of kidney cancer. However, most of included studies are evaluated as low quality according to our evidence assessment. Furthermore, due to the potential side effects, such as hemorrhage, digestive symptoms and peptic ulcer, it is still not recommend to use NSAIDs regularly to prevent cancers.