Plasma-based near-infrared spectroscopy for early diagnosis of lung cancer.

Lung cancer (LC) continues to be a leading death cause in China, primarily due to late diagnosis. This study aimed to evaluate the effectiveness of using plasma-based near-infrared spectroscopy (NIRS) for LC early diagnosis. A total of 171 plasma samples were collected, including 73 healthy controls (HC), 73 LC, and 25 benign lung tumors (B). NIRS was utilized to measure the spectra of samples. Pre-processing methods, including centering and scaling, standard normal variate, multiplicative scatter correction, Savitzky-Golay smoothing, Savitzky-Golay first derivative, and baseline correction were applied. Subsequently, 4 machine learning (ML) algorithms, including partial least squares (PLS), support vector machines (SVM), gradient boosting machine, and random forest, were utilized to develop diagnostic models using train set data. Then, the predictive performance of each model was evaluated using test set samples. The study was conducted in 5 comparisons as follows: LC and HC, LC and B, B and HC, the diseased group (D) and HC, as well as LC, B and HC. Among the 5 comparisons, SVM consistently generated the best performance with a certain pre-processing method, achieving overall accuracy of 1.0 (kappa: 1.0) in the comparisons of LC and HC, B and HC, as well as D and HC. Pre-processing was identified as a crucial step in developing ML models. Interestingly, PLS demonstrated remarkable stability and relatively high predictive performance across the 5 comparisons, even though it did not achieve the top results like SVM. However, none of these algorithms were able to effectively distinguish B from LC. These findings indicate that the combination of plasma-based NIRS with ML algorithms is a rapid, non-invasive, effective, and economical method for LC early diagnosis.

ROS-responsive MSC-derived Exosome Mimetics Carrying MHY1485 Alleviate Renal Ischemia Reperfusion Injury through Multiple Mechanisms.

Renal ischemia reperfusion (IR) injury is a prevalent inflammatory nephropathy in surgeries such as renal transplantation or partial nephrectomy, damaging renal function through inducing inflammation and cell death in renal tubules. Mesenchymal stromal/stem cell (MSC)-based therapies, common treatments to attenuate inflammation in IR diseases, fail to exhibit satisfying effects on cell death in renal IR. In this study, we prepared MSC-derived exosome mimetics (EMs) carrying the mammalian target of the rapamycin (mTOR) agonist to protect kidneys in proinflammatory environments under IR conditions. The thioketal-modified EMs carried the mTOR agonist and bioactive molecules in MSCs and responsively released them in kidney IR areas. MSC-derived EMs and mTOR agonists protected kidneys synergistically from IR through alleviating inflammation, apoptosis, and ferroptosis. The current study indicates that MSC-TK-MHY1485 EMs (MTM-EM) are promising therapeutic biomaterials for renal IR injury.

Bioinformatics Analysis Reveals a Novel Prognostic Model for Esophageal Squamous Cell Carcinoma.

Background: Esophageal squamous cell carcinoma (ESCC), a gastrointestinal cancer, is associated with poor prognosis. Prognostic models predict the likelihood of disease progression and are important for the management of patients with ESCC. The objective of this study was to develop a prognostic model for ESCC using bioinformatics analysis. Methods: Two transcriptome microarray Gene Expression Omnibus ESCC datasets (GSE53624 and GSE53622) were analyzed using bioinformatics methods. Differentially expressed genes (DEGs) were identified using the R package limma, and genes associated with survival outcomes in both datasets were identified by Kaplan-Meier analysis. Genes with diagnostic or prognostic value were selected for further analysis, and hazard ratios and their relationship with pathological TNM (pTNM) staging were investigated using univariate and multivariate Cox analysis. After selecting the independent factors from pTNM staging, Cox analysis and nomogram plotting were performed. The ability of the model to stratify risk and predict survival was evaluated and compared with the pTNM staging system to determine its potential clinical value. Key genes were analyzed by immunohistochemistry and RT-PCR. Results: Four candidate genes (B3GNT3, MACC1, NELL2, and USH1G) with prognostic value were identified from the two transcriptome microarray datasets. Age, pTNM stage, and B3GNT3, MACC1, and NELL2 were identified as independent factors associated with survival in the multivariate Cox analysis and used to establish a prognostic model. The model demonstrated significantly higher accuracy in predicting 3-year survival than the pTNM staging system and was useful for further risk stratification in patients with ESCC. B3GNT3 was significantly downregulated in ESCC tumor tissues and negatively associated with lymph node metastasis. Bioinformatics analysis indicated that B3GNT3 may play a role in immune regulation by regulating M2 macrophages. Conclusion: This study developed a new prognostic model for ESCC and identified B3GNT3 as a potential biomarker negatively associated with lymph node metastasis, which warrants further validation.

Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study.

Background: Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms. Methods: Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software. Results: A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.

Dissolving Microneedle-Based Cascade-Activation Nanoplatform for Enhanced Photodynamic Therapy of Skin Cancer.

Purpose: Photodynamic therapy (PDT) has been an attractive strategy for skin tumor treatment. However, the hypoxic microenvironment of solid tumors and further O2 consumption during PDT would diminish its therapeutic effect. Herein, we developed a strategy using the combination of PDT and hypoxia-activated bioreductive drug tirapazamine (TPZ). Methods: TPZ was linked to DSPE-PEG-NHS forming DSPE-PEG-TPZ to solve leakage of water-soluble TPZ and serve as an antitumor agent and monomer molecule further forming the micellar. Chlorin e6 (Ce6) was loaded in DSPE-PEG-TPZ forming DSPE-PEG-TPZ@Ce6 (DPTC). To further improve tumor infiltration and accumulation, hyaluronic acid was adopted to make DPTC-containing microneedles (DPTC-MNs). Results: Both in vitro and in vivo studies consistently demonstrated the synergistic antitumor effect of photodynamic therapy and TPZ achieved by DPTC-MNs. With laser irradiation, overexpressions of PDT tolerance factors NQO1 and HIF-1α were inhibited by this PDT process. Conclusion: The synergistic effect of PDT and TPZ significantly improved the performance of DPTC-MNs in the treatment of melanoma and cutaneous squamous cell carcinoma and has good biocompatibility.

Adoptive cell therapy for solid tumors beyond CAR-T: Current challenges and emerging therapeutic advances.

Adoptive cellular immunotherapy using immune cells expressing chimeric antigen receptors (CARs) is a highly specific anti-tumor immunotherapy that has shown promise in the treatment of hematological malignancies. However, there has been a slow progress toward the treatment of solid tumors owing to the complex tumor microenvironment that affects the localization and killing ability of the CAR cells. Solid tumors with a strong immunosuppressive microenvironment and complex vascular system are unaffected by CAR cell infiltration and attack. To improve their efficacy toward solid tumors, CAR cells have been modified and upgraded by "decorating" and "pruning". This review focuses on the structure and function of CARs, the immune cells that can be engineered by CARs and the transformation strategies to overcome solid tumors, with a view to broadening ideas for the better application of CAR cell therapy for the treatment of solid tumors.

Targeting tumor-associated macrophages: Novel insights into immunotherapy of skin cancer.

BACKGROUND: The incidence of skin cancer is currently increasing, and conventional treatment options inadequately address the demands of disease management. Fortunately, the recent rapid advancement of immunotherapy, particularly immune checkpoint inhibitors (ICIs), has ushered in a new era for numerous cancer patients. However, the efficacy of immunotherapy remains suboptimal due to the impact of the tumor microenvironment (TME). Tumor-associated macrophages (TAMs), a major component of the TME, play crucial roles in tumor invasion, metastasis, angiogenesis, and immune evasion, significantly impacting tumor development. Consequently, TAMs have gained considerable attention in recent years, and their roles have been extensively studied in various tumors. However, the specific roles of TAMs and their regulatory mechanisms in skin cancer remain unclear. AIM OF REVIEW: This paper aims to elucidate the origin and classification of TAMs, investigate the interactions between TAMs and various immune cells, comprehensively understand the precise mechanisms by which TAMs contribute to the pathogenesis of different types of skin cancer, and finally discuss current strategies for targeting TAMs in the treatment of skin cancer. KEY SCIENTIFIC CONCEPTS OF OVERVIEW: With a specific emphasis on the interrelationship between TAMs and skin cancer, this paper posits that therapeutic modalities centered on TAMs hold promise in augmenting and harmonizing with prevailing clinical interventions for skin cancer, thereby charting a novel trajectory for advancing the landscape of immunotherapeutic approaches for skin cancer.

Nanocarrier-Mediated Immunogenic Cell Death for Melanoma Treatment.

Melanoma, a highly aggressive skin tumor, exhibits notable features including heterogeneity, a high mutational load, and innate immune escape. Despite advancements in melanoma treatment, current immunotherapies fail to fully exploit the immune system's maximum potential. Activating immunogenic cell death (ICD) holds promise in enhancing tumor cell immunogenicity, stimulating immune amplification response, improving drug sensitivity, and eliminating tumors. Nanotechnology-enabled ICD has emerged as a compelling therapeutic strategy for augmenting cancer immunotherapy. Nanoparticles possess versatile attributes, such as prolonged blood circulation, stability, and tumor-targeting capabilities, rendering them ideal for drug delivery. In this review, we elucidate the mechanisms underlying ICD induction and associated therapeutic strategies. Additionally, we provide a concise overview of the immune stress response associated with ICD and explore the potential synergistic benefits of combining ICD induction methods with the utilization of nanocarriers.

Synergism and attenuation of triptolide through prodrug engineering combined with liposomal scaffold strategy to enhance inhibition in pancreatic cancer.

The prognosis of pancreatic cancer (PCa) is extremely poor because of its resistance to conventional therapies. Many previous studies have demonstrated that triptolide (TPL) has a potent tumoricidal activity on PCa. However, the clinical application of TPL in tumor therapy has been greatly limited by its poor aqueous solubility, short half-time, high toxicity and inefficient delivery. Here, through the engineering of prodrug technology combined with the nanodrug-delivery system (NDDS) strategy, we modified the main active site of TPL C14-OH by esterification reaction to obtain a highly lipophilic prodrug, and then encapsulated the drug in a phospholipid bilayer in liposomal vehicles through the thin-film hydration method for efficient delivery. A delivery system based on TPL lignocerate liposomes (TPL-LA-lip) for drug loading for targeted therapy against PCa was established. Our results showed that TPL-LA demonstrates exceptional compatibility with the phospholipid layer of liposomes, thereby enhancing drug retention in liposomal vehicle and improving tumor targeting and cellular uptake. Moreover, The system of TPL-LA-lip exhibited a sustained drug release profile in vitro, and intravenous administration significantly impedes tumor progression while reducing the toxicity of TPL in the PCa mouse model. These results demonstrated that the prodrug-loaded liposomes could significantly reduce the toxicity of TPL and enhance the biosafety. Overall, this prodrug approach is a simple and effective method to transform the highly toxic TPL into a safe and efficacious nanomedicine with excellent in vivo tolerability for PCa treatment.

Lipid carriers for mRNA delivery.

Messenger RNA (mRNA) is the template for protein biosynthesis and is emerging as an essential active molecule to combat various diseases, including viral infection and cancer. Especially, mRNA-based vaccines, as a new type of vaccine, have played a leading role in fighting against the current global pandemic of COVID-19. However, the inherent drawbacks, including large size, negative charge, and instability, hinder its use as a therapeutic agent. Lipid carriers are distinguishable and promising vehicles for mRNA delivery, owning the capacity to encapsulate and deliver negatively charged drugs to the targeted tissues and release cargoes at the desired time. Here, we first summarized the structure and properties of different lipid carriers, such as liposomes, liposome-like nanoparticles, solid lipid nanoparticles, lipid-polymer hybrid nanoparticles, nanoemulsions, exosomes and lipoprotein particles, and their applications in delivering mRNA. Then, the development of lipid-based formulations as vaccine delivery systems was discussed and highlighted. Recent advancements in the mRNA vaccine of COVID-19 were emphasized. Finally, we described our future vision and perspectives in this field.

Nanomedicine-induced programmed cell death enhances tumor immunotherapy.

BACKGROUND: There has been widespread concern about the high cancer mortality rate and the shortcomings of conventional cancer treatments. Immunotherapy is a novel oncology therapy with high efficiency and low side effects, which is a revolutionary direction for clinical oncology treatment. However, its clinical effectiveness is uneven. Based on the redefinition and reclassification of programmed cell death (PCD) (divided into necroptosis, ferroptosis, pyroptosis, and autophagy), the role of nanomedicine-induced PCD in cancer therapy has also received significant attention. Clinical and preclinical studies have begun to combine PCD with immunotherapy. AIM OF REVIEW: In this article, we present recent research in tumor immunotherapy, provide an overview of how nanomedicine-induced PCD is involved in tumor therapy, and review how nanomedicine-induced PCD can improve the limitations of immunotherapy to enhance tumor immunotherapy. The future development of nanomedicine-mediated PCD tumor therapy and tumor immunotherapy is also proposed Key scientific concepts of overview Nanomedicine-induced PCD is a prospective method of tumor immunotherapy. Nanomedicines increase tumor site penetration and targeting ability, and nanomedicine-mediated PCD activation can stimulate powerful anti-tumor immune effects, which has a good contribution to immunotherapy of tumors.

Urine based near-infrared spectroscopy analysis reveals a noninvasive and convenient diagnosis method for cancers: a pilot study.

Background: The challenges in cancer diagnosis underline the need for continued research and development of new diagnostic tools and methods. This study aims to explore an effective, noninvasive, and convenient diagnostic tool using urine based near-infrared spectroscopy (NIRS) analysis combined with machine learning algorithm. Methods: Urine samples were collected from a total of 327 participants, including 181 cancer cases and 146 healthy controls. These participants were randomly spit into train set (n = 218) and test set (n = 109). NIRS analysis (4,000 ∼10,000 cm-1) was performed for each sample in both train and test sets. Five pretreatment methods, including Savitzky-Golay (SG) smoothing, multiplicative scatter correction (MSC), baseline removal (BSL) with fitting polynomials to be used as baselines, the first derivative (DERIV1), and the second derivative (DERIV2), and combination with "scaling" and "center", were investigated. Then partial least-squares (PLS) and linear support-vector machine (SVM) classification models were established, and prediction performance was evaluated in test set. Results: NIRS had greatly overlapping in peaks, and PCA analysis failed in separation between cancers and healthy controls. In modeling with urine based NIRS data, PLS model showed its highest prediction accuracy of 0.780, with DERIV2, "scaling" and "center" pretreatment, while linear SVM displayed its best prediction accuracy of 0.844, with raw NIRS. With optimization in SVM, the prediction accuracy could improve to 0.862, when the top 262 features were involved as variables. Discussion: This pilot study combining urine based NIRS analysis and machine learning is effective and convenient that might facilitate in cancer diagnosis, encouraging further evaluation with a large-size multi-center study.

Preoperative serum bilirubin is an independent prognostic factor for curatively resected esophageal squamous cell carcinoma.

PURPOSE: This study examines prognostic value of preoperative serum bilirubin, including unconjugated bilirubin (UCB), conjugated bilirubin (CB), and total bilirubin (TB), in esophageal squamous cell carcinoma (ESCC) patients who underwent curative resection. METHODS: Between May 2010 and December 2012, a total of 351 ESCC patients were retrospectively reviewed. All the patients underwent curative resection as their primary treatment. Clinicopathological features and overall survival (OS) rate were investigated. Kaplan-Meier curves were used to calculate the OS rate, and the prognostic factors were identified by Cox regression model. Besides, the potential inhibition effect of UCB on ESCC was investigated with both in vitro and in vivo models. RESULTS: The higher-level groups of UCB, CB, and TB demonstrated longer OS than their low counterparts, with hazard ratio (HR) values of 0.567 (95% CI: 0.424-0.759), 0.698 (95% CI: 0.522-0.933), and 0.602 (95% CI: 0.449-0.807), respectively. All three forms of bilirubin were identified as independent prognostic factors for patients with ESCC, and they were found to effectively stratify the survival risk of patients at TNM stage III. In vivo and in vitro models further confirmed the inhibitory effect of unconjugated bilirubin (UCB) on the proliferation of ESCC. CONCLUSION: The findings of our study have shed new light on the prognostic value and biological functions of bilirubin in relation to ESCC. These results may contribute to a better understanding of the underlying mechanisms involved in ESCC tumorigenesis and provide potential therapeutic pathways for treating ESCC.

A traditional gynecological medicine inhibits ovarian cancer progression and eliminates cancer stem cells via the LRPPRC-OXPHOS axis.

BACKGROUND: Ovarian cancer (OC) is the most lethal malignant gynecological tumor type for which limited therapeutic targets and drugs are available. Enhanced mitochondrial oxidative phosphorylation (OXPHOS), which enables cell growth, migration, and cancer stem cell maintenance, is a critical driver of disease progression and a potential intervention target of OC. However, the current OXPHOS intervention strategy mainly suppresses the activity of the electron transport chain directly and cannot effectively distinguish normal tissues from cancer tissues, resulting in serious side effects and limited efficacy. METHODS: We screened natural product libraries to investigate potential anti-OC drugs that target OXPHOS. Additionally, LC-MS, qRT-PCR, western-blot, clonogenic assay, Immunohistochemistry, wound scratch assay, and xenograft model was applied to evaluate the anti-tumor mechanism of small molecules obtained by screening in OC. RESULTS: Gossypol acetic acid (GAA), a widely used gynecological medicine, was screened out from the drug library with the function of suppressing OXPHOS and OC progression by targeting the leucine-rich pentatricopeptide repeat containing (LRPPRC) protein. Mechanically, LRPPRC promotes the synthesis of OXPHOS subunits by binding to RNAs encoded by mitochondrial DNA. GAA binds to LRPPRC directly and induces LRPPRC rapid degradation in a ubiquitin-independent manner. LRPPRC was overexpressed in OC, which is highly correlated with the poor outcomes of OC and could promote the malignant phenotype of OC cells in vitro and in vivo. GAA management inhibits cell growth, clonal formation, and cancer stem cell maintenance in vitro, and suppresses subcutaneous graft tumor growth in vivo. CONCLUSIONS: Our study identified a therapeutic target and provided a corresponding inhibitor for OXPHOS-based OC therapy. GAA inhibits OC progression by suppressing OXPHOS complex synthesis via targeting LRPPRC protein, supporting its potential utility as a natural therapeutic agent for ovarian cancer.

Pickering Emulsions Enhance Oral Bioavailability of Curcumin Nanocrystals: The Effect of Oil Types.

Nanocrystals (NCs) have the potential to enhance the oral bioavailability of Class IV drugs in the Biopharmaceutical Classification System (BCS) due to the absorption of the intact crystals. The performance is compromised by the dissolution of NCs. Drug NCs have recently been adopted as solid emulsifiers to prepare nanocrystal self-stabilized Pickering emulsions (NCSSPEs). They are advantageous in high drug loading and low side effects due to the specific drug loading mode and the absence of chemical surfactants. More importantly, NCSSPEs may further enhance the oral bioavailability of drug NCs by impeding their dissolution. This is especially true for BCS IV drugs. In this study, curcumin (CUR), a typical BCS IV drug, was adopted to prepare CUR-NCs stabilized Pickering emulsions using either indigestible (isopropyl palmitate, IPP) or digestible (soybean oil, SO) oils, i.e., IPP-PEs and SO-PEs. The optimized formulations were spheric with CUR-NCs adsorbed on the water/oil interface. The CUR concentration in the formulation reached 20 mg/mL, which was far beyond the solubility of CUR in IPP (158.06 ± 3.44 µg/g) or SO (124.19 ± 2.40 µg/g). Moreover, the Pickering emulsions enhanced the oral bioavailability of CUR-NCs, being 172.85% for IPP-PEs and 152.07% for SO-PEs. The digestibility of the oil phase affected the amounts of CUR-NCs that remained intact in lipolysis and, thus, the oral bioavailability. In conclusion, converting NCs into Pickering emulsions provides a novel strategy to enhance the oral bioavailability of CUR and BCS IV drugs.

GC-MS-based untargeted metabolic profiling of malignant mesothelioma plasma.

Background: Malignant mesothelioma (MM) is a cancer caused mainly by asbestos exposure, and is aggressive and incurable. This study aimed to identify differential metabolites and metabolic pathways involved in the pathogenesis and diagnosis of malignant mesothelioma. Methods: By using gas chromatography-mass spectrometry (GC-MS), this study examined the plasma metabolic profile of human malignant mesothelioma. We performed univariate and multivariate analyses and pathway analyses to identify differential metabolites, enriched metabolism pathways, and potential metabolic targets. The area under the receiver-operating curve (AUC) criterion was used to identify possible plasma biomarkers. Results: Using samples from MM (n = 19) and healthy control (n = 22) participants, 20 metabolites were annotated. Seven metabolic pathways were disrupted, involving alanine, aspartate, and glutamate metabolism; glyoxylate and dicarboxylate metabolism; arginine and proline metabolism; butanoate and histidine metabolism; beta-alanine metabolism; and pentose phosphate metabolic pathway. The AUC was used to identify potential plasma biomarkers. Using a threshold of AUC = 0.9, five metabolites were identified, including xanthurenic acid, (s)-3,4-hydroxybutyric acid, D-arabinose, gluconic acid, and beta-d-glucopyranuronic acid. Conclusions: To the best of our knowledge, this is the first report of a plasma metabolomics analysis using GC-MS analyses of Asian MM patients. Our identification of these metabolic abnormalities is critical for identifying plasma biomarkers in patients with MM. However, additional research using a larger population is needed to validate our findings.

Lycorine transfersomes modified with cell-penetrating peptides for topical treatment of cutaneous squamous cell carcinoma.

BACKGROUND: Topical anticancer drugs offer a potential therapeutic modality with high compliance for treating cutaneous squamous cell carcinoma (cSCC). However, the existing topical treatments for cSCC are associated with limited penetrating ability to achieve the desired outcome. Therefore, there remains an urgent requirement to develop drugs with efficient anticancer activity suitable for treating cSCC and to overcome the skin physiological barrier to improve the efficiency of drug delivery to the tumor. RESULTS: We introduced lycorine (LR) into the topical treatment for cSCC and developed a cell-penetrating peptide (CPP)-modified cationic transfersome gel loaded with lycorine-oleic acid ionic complex (LR-OA) (LR@DTFs-CPP Gel) and investigated its topical therapeutic effects on cSCC. The anti-cSCC effects of LR and skin penetration of LR-OA transfersomes were confirmed. Simultaneously, cationic lipids and modification of R5H3 peptide of the transfersomes further enhanced the permeability of the skin and tumor as well as the effective delivery of LR to tumor cells. CONCLUSIONS: Topical treatment of cSCC-xenografted nude mice with LR@DTFs-CPP Gel showed effective anticancer properties with high safety. This novel formulation provides novel insights into the treatment and pathogenesis of cSCC.

Classification of multiple cancer types by combination of plasma-based near-infrared spectroscopy analysis and machine learning modeling.

BACKGROUND AND AIM: Near-infrared spectroscopy (NIRS) is a non-invasive and convenient tool, which gains features related to chemical components in biological samples. Machine learning (ML) has been popularized in medical diagnosis. This study aimed at investigating a novel cancer diagnosis strategy using NIRS data based ML modeling. METHODS: Plasma samples were collected from a total of 247 participants, including lung cancer, cervical cancer, nasopharyngeal cancer, and healthy control, and were randomly split into train set and test set. After performing NIRS analysis, the train dataset was utilized to train ML models, including partial least-squares (PLS), random forest (RF), gradient boosting machine (GBM), and support-vector machine (SVM). Subsequently, these models were tested for their prediction performance by the test set. RESULTS: All ML models demonstrated high prediction performance in differentiating cancers from controls, and SVM had high prediction accuracy for different types of cancers. SVM was considered as the most suitable model for its minimal computational cost and high accuracies for both binary and quaternary classification. CONCLUSIONS: This strategy coupling NIRS with ML is insightful that may aid in clinic cancer diagnosis, while further studies should test our results in a larger cohort with better representativeness.

Effect and mechanism of longkui yinxiao soup in treating psoriasis in mice.

Objective: Longkui Yinxiao Soup is a traditional Chinese medicine formula used to treat psoriasis for decades. Although Longkui Yinxiao Soup showed promising efficacy in clinical practice, the regulatory mechanisms of Longkui Yinxiao Soup remain elusive. This study aimed to explore the underlying mechanisms of Longkui Yinxiao Soup in a psoriasis-like mouse model. Methods: Longkui Yinxiao Soup was quality controlled by determining the contents of imperatorin and rhoifolin using high-performance liquid chromatography. The imiquimod-induced psoriasis-like mouse model was used to study the therapeutic effect and mechanism of Longkui Yinxiao Soup. The histopathological skin changes were observed by hematoxylin and eosin staining; the infiltration of proliferating proteins, proliferating cell nuclear antigen and Ki67, in skin tissues were observed by immunohistochemical analysis; and the inflammatory factors such as interleukin (IL)-6, tumor necrosis factor (TNF)-α, IL-23, and IL-17 in serum were detected using enzyme-linked immunosorbent assay. RNA sequencing and bioinformatic analysis were used to predict the mechanism of LYS against psoriasis. mRNA expressions of p38, extracellular regulated protein kinases (ERK), mitogen-activated protein kinase 3 (MEK3), mitogen-activated protein kinase 6 (MEK6), RAP1 GTPase activating protein (Rap1gap), and Rap1 were determined using real-time quantitative polymerase chain reaction. The expression levels of proteins related to Rap1-mitogen-activated protein kinase signaling pathways were measured by Western blotting. Results: A quality-control method for Longkui Yinxiao Soup was successfully established using imperatorin and rhoifolin as content determination indexes. Longkui Yinxiao Soup significantly ameliorated the psoriatic symptoms in mice. The serum levels of inflammatory cytokines such as IL-6, TNF-α, IL-23, and IL-17 were decreased, and the expression levels of antigen identified by monoclonal antibody Ki67 (Ki67) and PCNA in skin tissues were downregulated. Moreover, the inhibition of Rap1-MAPK signaling pathways by Longkui Yinxiao Soup was detected. Conclusion: This study confirmed the antipsoriatic activity of Longkui Yinxiao Soup in psoriasis-like mice. This might be due to the inhibition of inflammatory factor secretion, keratinocyte proliferation, and the Rap1-MAPK signal pathway.