Preoperative magnetic resonance imaging identify feasibility of breast-conserving surgery for breast cancer patients.

Background: Breast-conserving surgery (BCS) stands as the favored modality for treating early-stage breast cancer. Accurately forecasting the feasibility of BCS preoperatively can aid in surgical planning and reduce the rate of switching of surgical methods and reoperation. The objective of this study is to identify the radiomics features and preoperative breast magnetic resonance imaging (MRI) characteristics that are linked with positive margins following BCS in patients with breast cancer, with the ultimate aim of creating a predictive model for the feasibility of BCS. Methods: This study included a cohort of 221 pretreatment MRI images obtained from patients with breast cancer. A total of seven MRI semantic features and 1,561 radiomics features of lesions were extracted. The feature subset was determined by eliminating redundancy and correlation based on the features of the training set. The least absolute shrinkage and selection operator (LASSO) logistic regression was then trained with this subset to classify the final BCS positive and negative margins and subsequently validated using the test set. Results: Seven features were significant in the discrimination of cases achieving positive and negative margins. The radiomics signature achieved area under the curve (AUC), accuracy, sensitivity, and specificity of 0.760 [95% confidence interval (CI): 0.630, 0.891], 0.712 (95% CI: 0.569, 0.829), 0.882 (95% CI: 0.623, 0.979) and 0.629 (95% CI: 0.449, 0.780) in the test set, respectively. The combined model of radiomics signature and background parenchymal enhancement (BPE) demonstrated an AUC, accuracy, sensitivity, and specificity of 0.759 (95% CI: 0.628, 0.890), 0.654 (95% CI: 0.509, 0.780), 0.679 (95% CI: 0.476, 0.834) and 0.625 (95% CI: 0.408, 0.804). Conclusions: The combination of preoperative MRI radiomics features can well predict the success of breast conserving surgery.

Preoperative CECT-Based Multitask Model Predicts Peritoneal Recurrence and Disease-Free Survival in Advanced Ovarian Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: Peritoneal recurrence is the predominant pattern of recurrence in advanced ovarian cancer (AOC) and portends a dismal prognosis. Accurate prediction of peritoneal recurrence and disease-free survival (DFS) is crucial to identify patients who might benefit from intensive treatment. We aimed to develop a predictive model for peritoneal recurrence and prognosis in AOC. METHODS: In this retrospective multi-institution study of 515 patients, an end-to-end multi-task convolutional neural network (MCNN) comprising a segmentation convolutional neural network (CNN) and a classification CNN was developed and tested using preoperative CT images, and MCNN-score was generated to indicate the peritoneal recurrence and DFS status in patients with AOC. We evaluated the accuracy of the model for automatic segmentation and predict prognosis. RESULTS: The MCNN achieved promising segmentation performances with a mean Dice coefficient of 84.3% (range: 78.8%-87.0%). The MCNN was able to predict peritoneal recurrence in the training (AUC 0.87; 95% CI 0.82-0.90), internal test (0.88; 0.85-0.92), and external test set (0.82; 0.78-0.86). Similarly, MCNN demonstrated consistently high accuracy in predicting recurrence, with an AUC of 0.85; 95% CI 0.82-0.88, 0.83; 95% CI 0.80-0.86, and 0.85; 95% CI 0.83-0.88. For patients with a high MCNN-score of recurrence, it was associated with poorer DFS with P < 0.0001 and hazard ratios of 0.1964 (95% CI: 0.1439-0.2680), 0.3249 (95% CI: 0.1896-0.5565), and 0.3458 (95% CI: 0.2582-0.4632). CONCLUSION: The MCNN approach demonstrated high performance in predicting peritoneal recurrence and DFS in patients with AOC.

Prediction of all-cause death and specific causes of death in patients with gastric cancer with liver metastasis: a Surveillance, Epidemiology, and End Results-based study.

BACKGROUND: Gastric cancer (GC), considered the fifth most prevalent malignancy, is the fourth leading cause of cancer death worldwide. This cancer is heterogeneous and invasive and often metastasizes to the liver. The survival of patients with GC, especially cancer-specific survival (CSS), is a matter of concern to their families and medical workers in clinical practice. However, efficient tools for early risk prediction are lacking. Thus, this study aimed to develop a nomogram for forecasting the overall survival (OS) and CSS of patients with GC with liver metastasis (GCLM) based on the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: Information on individuals with GCLM was acquired from the SEER database from January 2000 to December 2015. Patients' data were randomized into the train cohort and the test cohort. The independent factors for CSS and OS were determined by univariate and multivariate competing risk analyses and Cox proportional hazards analysis, and the nomograms for predicting CSS and OS were constructed. The receiver operating characteristic curve and calibration curve were used to measure the accuracy and calibration of nomograms. RESULTS: Our study included 4372 patients with GCLM, with 3060 patients in the train set and 1312 in the test set. The mean follow-up period was 12.31 months. The independent factors influencing the OS of patients with GCLM were age, bone metastasis, chemotherapy, grade, lung metastasis, stage, primary site, radiotherapy, surgical primary site, T stage, and tumor size. The concordance Index (C-index) of the constructed nomogram for OS were 0.718 (SE, 0.004) in the train set and 0.0.680 (SE, 0.006) in the test set. The independent factors affecting the CSS of patients with GCLM were age, chemotherapy, grade, lung metastasis, stage, radiotherapy, regional lymph node positive, surgical primary site, and total number of tumors. The C-index for the constructed nomogram for CSS were 0.696 (SE, 0.005) in the train set and 0.696 (SE, 0.008) in the test set. CONCLUSION: The constructed nomograms showed satisfactory performance in predicting the OS and CSS of patients with GCLM, which can help clinicians formulate follow-up and rehabilitation strategies conducive to survival. At the same time, it can provide more family and social support for high-risk groups.

Liposome encapsulated polydopamine nanoparticles: Enhancing ferroptosis and activating hypoxia prodrug activity.

The short lifespan of active oxygen species and depressed O2 level during ferroptosis treatment in tumor cells weaken ferroptosis therapy. How to improve the utilization efficiency of active oxygen species generated in real time is pivotal for anticancer treatment. Herein, the tirapazamine (TPZ) loaded polydopamine-Fe nanoparticles (PDA-Fe-TPZ) was modified with unsaturated liposome (Lip), which was constructed to overcome the drawbacks of traditional ferroptosis therapy. The Lip@PDA-Fe-TPZ nanoliposomes can react with H2O2 to produce •OH by Fenton reaction, which then attacks Lip and transforms into radical intermediate (L•) and phospholipid peroxide radical (LOO•) to avoid the annihilation of •OH. The introduced Lip enhances lipid peroxidation and promotes oxygen consumption, resulting in increased hypoxia at tumor site. The introduced TPZ can be triggered by reductase in tumor cells under hypoxia, which can reduce to transient oxidative free radicals by reductase enzymes and destroy the structure of the surrounding biomacromolecules, thus achieving the synergistic treatment of ferroptosis and chemotherapy. In this work, we organically combined enhanced ferrroptosis with hypoxic activated chemotherapy to achieve efficient and specific tumor killing effect, which can sever as a promising treatment of cancer in the future.

MRI-Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN-RNN Model.

BACKGROUND: Accurate evaluation of the axillary lymph node (ALN) status is needed for determining the treatment protocol for breast cancer (BC). The value of magnetic resonance imaging (MRI)-based tumor heterogeneity in assessing ALN metastasis in BC is unclear. PURPOSE: To assess the value of deep learning (DL)-derived kinetic heterogeneity parameters based on BC dynamic contrast-enhanced (DCE)-MRI to infer the ALN status. STUDY TYPE: Retrospective. SUBJECTS: 1256/539/153/115 patients in the training cohort, internal validation cohort, and external validation cohorts I and II, respectively. FIELD STRENGTH/SEQUENCE: 1.5 T/3.0 T, non-contrast T1-weighted spin-echo sequence imaging (T1WI), DCE-T1WI, and diffusion-weighted imaging. ASSESSMENT: Clinical pathological and MRI semantic features were obtained by reviewing histopathology and MRI reports. The segmentation of the tumor lesion on the first phase of T1WI DCE-MRI images was applied to other phases after registration. A DL architecture termed convolutional recurrent neural network (ConvRNN) was developed to generate the KHimage (kinetic heterogeneity of DCE-MRI image) score that indicated the ALN status in patients with BC. The model was trained and optimized on training and internal validation cohorts, tested on two external validation cohorts. We compared ConvRNN model with other 10 models and the subgroup analyses of tumor size, magnetic field strength, and molecular subtype were also evaluated. STATISTICAL TESTS: Chi-squared, Fisher's exact, Student's t, Mann-Whitney U tests, and receiver operating characteristics (ROC) analysis were performed. P < 0.05 was considered significant. RESULTS: The ConvRNN model achieved area under the curve (AUC) of 0.802 in the internal validation cohort and 0.785-0.806 in the external validation cohorts. The ConvRNN model could well evaluate the ALN status of the four molecular subtypes (AUC = 0.685-0.868). The patients with larger tumor sizes (>5 cm) were more susceptible to ALN metastasis with KHimage scores of 0.527-0.827. DATA CONCLUSION: A ConvRNN model outperformed traditional models for determining the ALN status in patients with BC. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Prediction of Disease-Free Survival in Breast Cancer using Deep Learning with Ultrasound and Mammography: A Multicenter Study.

BACKGROUND: Breast cancer is a leading cause of cancer morbility and mortality in women. The possibility of overtreatment or inappropriate treatment exists, and methods for evaluating prognosis need to be improved. MATERIALS AND METHODS: Patients (from January 2013 to December 2018) were recruited and divided into a training group and a testing group. All patients were followed for more than 3 years. Patients were divided into a disease-free group and a recurrence group based on follow up results at 3 years. Ultrasound (US) and mammography (MG) images were collected to establish deep learning models (DLMs) using ResNet50. Clinical data, MG, and US characteristics were collected to select independent prognostic factors using a cox proportional hazards model to establish a clinical model. DLM and independent prognostic factors were combined to establish a combined model. RESULTS: In total, 1242 patients were included. Independent prognostic factors included age, neoadjuvant chemotherapy, HER2, orientation, blood flow, dubious calcification, and size. We established 5 models: the US DLM, MG DLM, US + MG DLM, clinical and combined model. The combined model using US images, MG images, and pathological, clinical, and radiographic characteristics had the highest predictive performance (AUC = 0.882 in the training group, AUC = 0.739 in the testing group). CONCLUSION: DLMs based on the combination of US, MG, and clinical data have potential as predictive tools for breast cancer prognosis.

Direct Laser Writing Photonic Crystal Hydrogels with a Supramolecular Sacrificial Scaffold.

Photonic crystal hydrogels (PCHs), with smart stimulus-responsive abilities, have been widely exploited as colorimetric sensors for years. However, the current fabrication technologies are mostly applicable to produce PCHs with simple geometries at the sub-millimeter scale, limiting the introduction of structural design into PCH sensors as well as the accompanied advanced applications. This paper reports the microfabrication of three-dimensional (3D) PCHs with the help of supramolecular agarose PCH as a sacrificial scaffold by two-photon lithography (TPL). The supramolecular PCHs, formulated with SiO2 colloidal nanoparticles and agarose aqueous solutions, show bright structural color and are degradable upon short-time dimethyl sulfoxide treatment. Leveraging the supramolecular PCH as a sacrificial scaffold, PCHs with precise 3D geometries can be fabricated in an economical and efficient way. This work demonstrates the application of such a strategy in the creation of structural-designed PCH mechanical microsensors that have not been explored before.

Perioperative tislelizumab plus chemotherapy for locally advanced resectable thoracic esophageal squamous cell carcinoma trial: a prospective single-arm, phase II study (PILOT trial).

BACKGROUND: The promising therapeutic outcomes of neoadjuvant immunotherapy combined with chemotherapy in the treatment of locally advanced esophageal squamous cell carcinoma (ESCC) have been confirmed by several phase II clinical trials and have been widely demonstrated in clinical work. Theoretically, postoperative adjuvant immunotherapy may further improve the therapeutic effect, but there is still lack of evidence. The aim of this study was to analyse the safety and efficacy of perioperative immunotherapy (tislelizumab) in locally advanced resectable thoracic ESCC (PILOT trial). METHODS: Seventy-three eligible patients with pathologically confirmed thoracic ESCC of clinical T1b-3N1-3M0 or T3N0M0 stage were allocated to receive neoadjuvant immunotherapy (tislelizumab 200 mg d1, q3w × 2 cycles) plus chemotherapy (nad-paclitaxel 260 mg/m2 d1 + carboplatin AUC = 5 d1, q3w × 2 cycles) treatment. Patients with pathologic complete response (pCR) after esophagectomy received adjuvant tislelizumab (200 mg every 3 weeks for up to one year), and patients with non-pCR were assigned adjuvant tislelizumab plus chemotherapy for two cycles and then maintenance tislelizumab (200 mg every 3 weeks for up to 15 cycles). The primary endpoint of this study is 2-year disease-free survival (DFS) in non-pCR patients. The secondary endpoints include pCR rate, major pathological response rate, 2-year DFS in pCR patients, R0 resection rate, adverse events, and overall survival. DISCUSSION: This protocol was reviewed and approved by the Ethics Committee of Shanghai Chest Hospital (IS23059). This is the first prospective clinical trial to investigate the safety and efficacy of perioperative immunotherapy for locally advanced resectable thoracic ESCC. We hypothesize that perioperative immunotherapy could be a promising therapeutic strategy that can provide better 2-year DFS in non-pCR patients. TRIAL REGISTRATION: ClinicalTrial.gov: NCT0605633.

Feasibility analysis of magnetic resonance imaging-based radiomics features for preoperative prediction of nuclear grading of ductal carcinoma in situ.

Background: The nuclear grading of ductal carcinoma in situ (DCIS) affects its clinical risk. The aim of this study was to investigate the possibility of predicting the nuclear grading of DCIS, by magnetic resonance imaging (MRI)-based radiomics features. And to develop a nomogram combining radiomics features and MRI semantic features to explore the potential role of MRI radiomic features in the assessment of DCIS nuclear grading. Methods: A total of 156 patients (159 lesions) with DCIS and DCIS with microinvasive (DCIS-MI) were enrolled in this retrospective study, with 112 lesions included in the training cohort and 47 lesions included in the validation cohort. Radiomics features were extracted from Dynamic contrast-enhanced MRI (DCE-MRI) phases 1st and 5th. After feature selection, radiomics signature was constructed and radiomics score (Rad-score) was calculated. Multivariate analysis was used to identify MRI semantic features that were significantly associated with DCIS nuclear grading and combined with Rad-score to construct a Nomogram. Receiver operating characteristic curves were used to evaluate the predictive performance of Rad-score and Nomogram, and decision curve analysis (DCA) was used to evaluate the clinical utility. Results: In multivariate analyses of MRI semantic features, larger tumor size and heterogeneous enhancement pattern were significantly associated with high-nuclear grade DCIS (HNG DCIS). In the training cohort, Nomogram had an area under curve (AUC) of 0.879 and Rad-score had an AUC of 0.828. Similarly, in the independent validation cohort, Nomogram had an AUC value of 0.828 and Rad-score had an AUC of 0.772. In both the training and validation cohorts, Nomogram had a significantly higher AUC value than Rad-score (P<0.05). DCA confirmed that Nomogram had a higher net clinical benefit. Conclusions: MRI-based radiomic features can be used as potential biomarkers for assessing nuclear grading of DCIS. The nomogram constructed by radiomic features combined with semantic features is feasible in discriminating non-HNG and HNG DCIS.

Predicting Neoadjuvant Chemotherapy Response and High-Grade Serous Ovarian Cancer From CT Images in Ovarian Cancer with Multitask Deep Learning: A Multicenter Study.

RATIONALE AND OBJECTIVES: Accurate prediction neoadjuvant chemotherapy (NACT) response in ovarian cancer (OC) is essential for personalized medicine. We aimed to develop and validate a deep learning (DL) model based on pretreatment contrast-enhanced CT (CECT) images for predicting NACT responses and classifying high-grade serous ovarian cancer (HGSOC) to identify patients who may benefit from NACT. MATERIALS AND METHODS: This multicenter study, which contained both retrospective and prospective studies, included consecutive OC patients (n = 757) from three hospitals. Using WHO RECIST 1.1 for the reference standard, a total of 587 women with 1761 images were included in the training and validation sets, 67 women with 201 images were included in the prospective sets, and 103 women with 309 images were included in the external sets. A multitask DL model based on the multiperiod CT image was developed to predict NACT response and HGSOC. RESULTS: Logistic regression analysis showed that peritoneal invasion, retinal invasion, and inguinal lymph node metastasis were independent predictors. The DL achieved promising segmentation performances with DICEmean= 0.83 (range: 0.78-0.87). For predicting NACT response, the DL model combined with clinical risk factors obtained area under the receiver operating characteristic curve (AUCs) of 0.87 (0.83-0.89), 0.88 (0.86-0.91), 0.86 (0.82-0.89), and 0.79 (0.75-0.82) in the training, validation, prospective, and external sets, respectively. The AUCs were 0.91 (0.87-0.94), 0.89 (0.86-0.91), 0.80 (0.76-0.84), and 0.80 (0.75-0.85) in four sets in HGSOC classification. CONCLUSION: The multitask DL model developed using multiperiod CT images exhibited a promising performance for predicting NACT response and HGSOC with OC, which could provide valuable information for individualized treatment.

Association between TH/MAOB gene single nucleotide polymorphisms and excitability in Labrador Retrievers.

Excitability is a pivotal quality in guide dogs because moderately active dogs are more trainable. Excessive activity is associated with behavioral problems and pet surrender. Excitability is a highly heritable trait, yet the relevant genetic factors and markers associated with this condition are poorly characterized. In the present study, we selected six single nucleotide polymorphisms (SNPs) of two genes that are possibly related to excitability in dogs (TH c.264G > A, TH c.1208A > T, TH c.415C > G, TH c.168C > T, TH c.180C > T and MAOB c.199 T > C). We measured the excitability of dogs using seven variables from three behavioral tests: the play test (interest in play, grabbing in throw and tug-of-war), the chase test (following and forward grabbing) and the passive test (moving range and moving time). These behavioral tests are part of the Dog Mentality Assessment developed by Svartberg & Forkman. The activity scores in the guide dog group were higher than in the temperament withdrawal group, and significant differences were detected in the aggregate score (p = 0.02), passive activity score (p = 0.007) and moving range score (p = 0.04). Analysis using the Kruskal-Wallis test and non-parametric Steel-Dwass test to evaluate the relationship between these SNPs and behavioral variable scores revealed that TH c.264G > A was associated with aggregate scores of excitability-related behavioral variables (adj. p = 0.03), object-interaction activity scores (adj. p = 0.03), following scores (adj. p = 0.03) and forward grabbing scores (adj. p = 0.03) in Labrador dogs and MAOB c.199 T > C was associated with moving range scores in these dogs (adj. p = 0.004). However, these results had low power. To explain the behavioral traits, further genetic studies more reliable than candidate gene studies are needed.

Efficient precise integration of large DNA sequences with 3'-overhang dsDNA donors using CRISPR/Cas9.

CRISPR/Cas9 genome-editing tools have tremendously boosted our capability of manipulating the eukaryotic genomes in biomedical research and innovative biotechnologies. However, the current approaches that allow precise integration of gene-sized large DNA fragments generally suffer from low efficiency and high cost. Herein, we developed a versatile and efficient approach, termed LOCK (Long dsDNA with 3'-Overhangs mediated CRISPR Knock-in), by utilizing specially designed 3'-overhang double-stranded DNA (odsDNA) donors harboring 50-nt homology arm. The length of the 3'-overhangs of odsDNA is specified by the five consecutive phosphorothioate modifications. Compared with existing methods, LOCK allows highly efficient targeted insertion of kilobase-sized DNA fragments into the mammalian genomes with low cost and low off-target effects, yielding >fivefold higher knock-in frequencies than conventional homologous recombination-based approaches. This newly designed LOCK approach based on homology-directed repair is a powerful tool suitable for gene-sized fragment integration that is urgently needed for genetic engineering, gene therapies, and synthetic biology.

Unsaturated phospholipid modified FeOCl nanosheets for enhancing tumor ferroptosis.

Iron-dependent accumulation of reactive oxygen species (ROS) and lipid peroxidation play key roles in ferroptosis, which has been an attractive strategy to kill tumor cells. However, the rapid annihilation of hydroxyl radicals (˙OH) produced from the Fenton reaction has become a major obstacle in inducing lipid peroxidation in cells. In this study, we develop a nano-delivery system of unsaturated phospholipid (Lip) and polyacrylic acid (PAA) functionalized FeOCl nanosheets (FeOCl@PAA-Lip). In this system, the ˙OH radicals produced from the Fenton reaction between FeOCl nanosheets and endogenous H2O2 of tumor cells attack Lip on the nanosheets in situ to initiate the lipid peroxidation chain reaction, which not only realizes free radical conversion but also leads to the amplification of ROS and lipid peroxides, thus enhancing tumor ferroptosis. The in vitro and in vivo results confirmed that FeOCl@PAA-Lip nanosheets exhibited specific tumor cell-killing effects, good biocompatibility, long circulation time, low side effects, high tumor targeting and an excellent tumor inhibition rate (73%). The Lip functionalization strategy offers a paradigm of enhancing ferroptosis treatment by conversion of ˙OH/phospholipid radicals/lipid peroxyl radicals and strengthening lipid peroxidation.

The ALFF Alterations of Spontaneous Pelvic Pain in the Patients of Chronic Prostatitis/Chronic Pelvic Pain Syndrome Evaluated by fMRI.

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a challenging entity with complicated symptoms for treatment in the male crowd. Accumulating evidence revealed the dysfunction in the central system should be a critical factor for the pathogenesis and development in the CP/CPPS. Therefore, we recruited 20 patients of CP/CPPS and 20 healthy male volunteers, aged 20 to 50 years. Through resting-state functional magnetic resonance imaging (fMRI), we analyzed the mean amplitude of low-frequency fluctuations (mALFF) and the mean fractional amplitude of low-frequency fluctuations (mfALFF) to reflect the spontaneous abnormal activated regions in the brains of CP/CPPS patients. Compared to the healthy controls, the group with CP/CPPS had significantly increased mALFF values in the thalamus and augmented fALFF values in the inferior parietal lobule and cingulate gyrus. Significant positive correlations were observed in the extracted mALFF values in the midbrain periaqueductal gray matter (PAG) and the pain intensity (r = 0.2712, p = 0.0019), mALFF values in the thalamus and the scores of Hospital Anxiety and Depression Scale (HADS) anxiety subscale (r = 0.08477, p = 0.0461), and mfALFF values in the superior frontal gyrus (SFG) and the scores of the HADS anxiety subscale (r = 0.07102, p = 0.0282). Therefore, we delineated the clinical alterations in patients of CP/CPPS that might be attributed to the functional abnormality of the thalamus, inferior parietal lobule, and cingulate gyrus. Among these regions, the PAG, thalamus, and SFG may further play an important role in the pathogenesis, with their regulating effect on pain or emotion.

The Core Mechanism of Yiqi Yangjing Decoction Inhibiting Nonsmall-Cell Lung Cancer.

Background: Yiqi Yangjing prescription (YQYJ) is a traditional Chinese medicine prescription used for treating lung cancer. It has a significant effect on enhancing efficacy, reducing toxic symptoms, and improving patients' physical well-being. The effective inhibitory effect on nonsmall-cell lung cancer (NSCLC) has been demonstrated in vitro and in vivo. However, the mechanism of action and the material basis still remain unclear. Methods: In this study, we explored this mechanism using network pharmacology, after which we explored the pharmacodynamics and the action mechanism of YQYJ using cell viability evaluation, plate clone formation assay, flow cytometry, real-time quantitative PCR, and Western blot. Results: The enrichment results showed that there were 50 active components and 68 core targets related to YQYJ inhibiting NSCLC, including quercetin, luteolin, gamatin, kaempferol, heat shock protein HSP 90-alpha (HSP90AA1), cyclin-dependent kinase 2 (CDK2), epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 3 (STAT3), and others. Among them, quercetin and kaempferol revealed the best binding effect with core targets. Most importantly, YQYJ promoted A549 cells from the quiescent phase into the proliferative phase to enhance the sensitivity of A549 cells to YQYJ and inhibited the proliferation of A549 cells significantly (P < 0.05). The A549 cells were blocked in both S and G2/M phases while the apoptosis ratio was increased. The proliferation score of A549 cells treated with YQYJ was significantly reduced compared to A549 cells in the proliferative phase (P < 0.05). This regulatory effect was related to the expression regulation of HSP90AA1, CDK2, STAT3, and phosphor-STAT3 (p-STAT3) by YQYJ, kaempferol, and quercetin. Conclusion: Our results suggested that the inhibition of NSCLC via YQYJ had multicomponent and multitarget characteristics. Its core mechanism is related to the regulation of the cell cycle, proliferation, and apoptosis of NSCLC. This study provides a direction and scientific basis for exploring the future mechanism of YQYJ for the treatment of NSCLC.

6-acrylic phenethyl ester-2-pyranone derivative induces apoptosis and G2/M arrest by targeting GRP94 in colorectal cancer.

Colorectal cancer (CRC) is ranked the third driving reason for cancer death in the world. Surgery and chemotherapy have long been the first choices for cancer patients. However, the prognosis of CRC has never been satisfying, necessitating new effective treatment strategies. In our previous study, we synthesized compound5othat showed high anticancer potential with a 6-acrylic phenethyl ester-2-pyranone backbone, but its mechanism of action (MOA) is not understood. To articulate the MOA of 5o against colon cancer, we evaluated the anti-cancer effect of compound5oon CRC cells by cell proliferation assays. The MOA of5owas explored through cell cycle assays and apoptosis assays. The target of 5o was identified by molecular dynamic assays, ATPase assays, and surface plasmon resonance (SPR) analysis. We discovered 5o, a compound capable of inhibiting CRC cell proliferation with 1/25 folds in IC50 values compared with NCM460 cells (normal human colonic epithelial cell line). 5o induces cell apoptosis in a dose-dependent manner through PI3K/Akt/FoxO1 and NF-κB signaling pathways. In addition, 5o arrests cell cycle at G2/M by regulating MAPKs (ERK1/2 and p38) pathway. We further confirmed that 5o inhibits ATPase activity of GRP94 (Glucose-regulated protein 94) with the IC50 1.45 ± 0.06 µM. Compound 5o inhibits GRP94 to trigger regulation of PI3K/Akt and MAPKs pathways. This study reveals that 5o is a promising therapeutic agent against CRC as a novel GRP94 inhibition.

Combined treatment with dihydrotestosterone and lipopolysaccharide modulates prostate homeostasis by upregulating TNF-α from M1 macrophages and promotes proliferation of prostate stromal cells.

Androgens and chronic inflammation, which play essential roles in the development of benign prostatic hyperplasia (BPH), are considered to be important factors in disorders of prostate homeostasis. These two factors may lead to pathological hyperplasia in the prostate transition zone of patients with BPH. However, few studies have examined the mechanism of how dihydrotestosterone (DHT) affects chronic inflammation in prostate tissue during the progression of BPH. This study examined the performance of DHT in lipopolysaccharide-treated M1 macrophages and the subsequent effects on the proliferation of prostate stromal and epithelial cells. We found that DHT increased secretion of the pro-inflammatory factor tumor necrosis factor (TNF)-α from M1 macrophages differentiated from THP-1 cells. The supernatant of M1 macrophages promoted the proliferation of WPMY-1 prostate stromal cells by upregulating B-cell lymphoma-extra large (Bcl-xL) and cellular Myc (c-Myc) levels by activating TNF-α-mediated nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinase (MAPK) pathways. Moreover, this supernatant increased the expression of androgen receptor in WPMY-1 cells, which was TNF-α-independent. Additionally, TNF-α protein expression was significantly higher in patients with BPH and a large prostate volume than that in those with a small prostate volume. Further analysis showed that higher serum testosterone combined with prostate-specific androgen concentrations was related to TNF-α expression. This study suggests that DHT modulates the inflammatory environment of BPH by increasing TNF-α expression from lipopolysaccharide-treated M1 macrophages and promotes the proliferation of prostate stromal cells. Targeting TNF-α, but not DHT, may be a promising strategy for patients with BPH.

Rubidium Chloride Increases Life Span Through an AMPK/FOXO-Dependent Pathway in Caenorhabditis elegans.

AMP-activated protein kinase (AMPK) is involved in life-span maintenance, stress responses, and germ cell cycle arrest upon dauer entry. AMPK is currently considered a promising target for preventing age-related diseases. Rubidium is one of the trace elements in the human body. As early as the 1970s, rubidium chloride (RbCl) was reported to have neuroprotective effects. In this work, we report the antiaging effect of RbCl in Caenorhabditis elegans. Specifically, we reveal that (a) RbCl does increase the life span and enhance stress resistance in C. elegans without disturbing their fecundity. (b) RbCl induces superoxide dismutase expression, which is essential for its antiaging and antistress effect. (c) AAK-2 and DAF-16 are essential to the antiaging efficacy of RbCl, and RbCl can promote DAF-16 translocating into the nucleus, suggesting that RbCl delays aging by regulating the AMPK/FOXO pathway. RbCl can be a promising agent against aging-related diseases.

Metabolizable pH/H2O2 dual-responsive conductive polymer nanoparticles for safe and precise chemo-photothermal therapy.

Conductive polymers with high near-infrared absorbance, have attracted considerable attention in the design of intelligent nanomedicines for cancer therapy, especially chemo-photothermal therapy. However, the unknown long-term biosafety of conductive polymers in vivo due to non-degradability hinders their clinic application. Herein, a H2O2-triggered degradable conductive polymer, polyacrylic acid (PAA) stabilized poly(pyrrole-3-COOH) (PAA@PPyCOOH), is fabricated to form nanoparticles with doxorubicin (DOX) for safe and precise chemo-phototherapy. The PAA@PPyCOOH was found to be an ideal photothermal nano-agent with good dispersity, excellent biocompatibility and high photothermal conversion efficiency (56%). After further loading of doxorubicin (DOX), PAA@PPyCOOH@DOX demonstrates outstanding photothermal performance, as well as pH/H2O2 dual-responsive release of DOX in tumors with an acidic and overexpressed H2O2 microenvironment, resulting in superior chemo-photothermal therapeutic effects. The degradation mechanism of PAA@PPyCOOH is proposed to be the ring-opening reaction between the pyrrole-3-COOH unit and H2O2. More importantly, the nanoparticles can be specifically degraded by excess H2O2 in tumor, and the degradation products were confirmed to be excreted via urine and feces. In vivo therapeutic evaluation of chemo-photothermal therapy reveals tumor growth of 4T1 breast cancer model is drastically inhibited and no apparent side-effect is detected, thus indicating substantial potential in clinic application.

Zhengyuan capsule for the treatment of cancer-related fatigue in lung cancer patients undergoing operation: a study protocol for a randomized controlled trial.

OBJECTIVE: To evaluate the efficacy and safety of Zhengyuan capsule () when treating Cancer-related fatigue (CRF) in lung cancer patients undergoing surgical operation. METHODS/DESIGN: This is a single-center, double-blinded, prospective, and randomized controlled trial in the Department of Integrated Chinese and Western Medicine, Shanghai Chest Hospital Shanghai JiaoTong University, Shanghai. Eligible participants will be randomly allocated into two groups: a treatment group receiving an 8-week Zhengyuan capsule regimen therapy and a control group receiving an 8-week placebo capsule regimen therapy. Evaluation will be carried out at four timelines: the participants' screening period, baseline period, the middle of the intervention period, and the end of the intervention period. The primary outcome assessment is fatigue scoring using the Cancer Fatigue Scale (CFS) measurement system. Secondary measurements include fatigue severity assessment using the Multidimensional Fatigue Symptom Inventory-Short Form (MFSI-SF) measurement system, Traditional Chinese Medicine syndrome pattern differentiation, levels of immunologic indicators (TNF-α, IL-6, IL-1, T lymphocytes subsets and B lymphocyte subsets), patient's pulmonary function, performance status scale (PS), self-rating scale of sleep (SRSS), and adverse events (AEs). DISCUSSION: The trial results can provide efficacy and safety data of Zhengyuan capsule when treating CRF in clinic. The data can also be imported into the management and treatment guidelines for CRF in lung cancer patients undergoing operation throughout China.