A retrospective clinical analysis of 11 cases of PEComa from different sites.

PURPOSE: The objective of this paper is to offer a thorough examination of the clinical presentations, etiology, and treatment strategies associated with perivascular epithelioid cell tumors (PEComas). METHODS: This retrospective study examined the comprehensive archival data of PEComa cases diagnosed at Beijing Hospital from 2015 to 2023. The pathology slides of all patients were thoroughly reassessed by two experienced pathologists. A thorough retrospective analysis was undertaken, incorporating clinicopathological data including gender, age at diagnosis, initial clinical manifestations, signs, disease onset site, tumor markers, imaging findings, therapeutic modalities, pathological features, immunohistochemical profiles, treatment responses, and prognostic indicators. Patients were evaluated for disease severity according to established pathological classification criteria and were followed up until the designated analysis cut-off date. In instances where patients were unable to be monitored on-site, they were contacted via telephone for postoperative follow-up inquiries. RESULTS: This study included 11 patients with ages ranging from 17 to 66 years old, presenting with the disease in multiple anatomical sites, including the retroperitoneum (2/11), liver (4/11), kidney (4/11), lung (1/11), and broad ligament of the uterus (1/11). Most patients presented with non-specific clinical symptoms and were subsequently diagnosed with space-occupying lesions upon physical examination. The tumor demonstrated progressive growth and enlargement, which could result in compression of neighboring organs. Preoperative imaging alone is insufficient for a definitive diagnosis of PEComa, but MRI can provide an initial evaluation of the tumor's potential malignancy. Molecular marker testing specific to PEComa, such as HMB-45 (90.0%), SMA (81.8%), Melan-A (90.9%), vimentin (90.9%), and Desmin (36.3%), was conducted on all patients. No adjuvant therapies were administered postoperatively. Upon analysis, no instances of relapse at the primary site or the development of new tumors at other sites were observed. Regular imaging reviews of three patients with malignant PEComa post-surgery showed no evidence of recurrence. CONCLUSIONS: The clinical presentation, tumor biomarkers, and imaging characteristics of PEComa lack specificity, necessitating dependence on pathology and immunohistochemistry for precise diagnosis. The mainstay of treatment consists of surgical resection, with patients typically experiencing a favorable prognosis.

Multi-omics analyses based on genes associated with oxidative stress and phospholipid metabolism revealed the intrinsic molecular characteristics of pancreatic cancer.

Oxidative stress (OS), which impacts lipid metabolic reprogramming, can affect the biological activities of cancer cells. How oxidative stress and phospholipid metabolism (OSPM) influence the prognosis of pancreatic cancer (PC) needs to be elucidated. The metabolic data of 35 pancreatic tumor samples, 34 para-carcinoma samples, and 31 normal pancreatic tissues were obtained from the previously published literature. Pan-cancer samples were obtained from The Cancer Genome Atlas (TCGA). And the Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), ArrayExpress, and the Genotype-Tissue Expression (GTEx) databases were searched for more PC and normal pancreatic samples. The metabolites in PC were compared with normal and para-carcinoma tissues. The characteristics of the key OSPM genes were summarized in pan-cancer. The random survival forest analysis and multivariate Cox regression analysis were utilized to construct an OSPM-related signature. Based on this signature, PC samples were divided into high- and low-risk subgroups. The dysregulations of the tumor immune microenvironment were further investigated. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was conducted to investigate the expression of genes in the signature in PC and normal tissues. The protein levels of these genes were further demonstrated. In PC, metabolomic studies revealed the alteration of PM, while transcriptomic studies showed different expressions of OSPM-related genes. Then 930 PC samples were divided into three subtypes with different prognoses, and an OSPM-related signature including eight OSPM-related genes (i.e., SLC2A1, MMP14, TOP2A, MBOAT2, ANLN, ECT2, SLC22A3, and FGD6) was developed. High- and low-risk subgroups divided by the signature showed different prognoses, expression levels of immune checkpoint genes, immune cell infiltration, and tumor microenvironment. The risk score was negatively correlated with the proportion of TIL, pDC, Mast cell, and T cell co-stimulation. The expression levels of genes in the signature were verified in PC and normal samples. The protein levels of SLC2A1, MMP14, TOP2A, MBOAT2, ANLN, and SLC22A3 showed up-regulation in PC samples compared with normal tissues. After integrating metabolomics and transcriptomics data, the alterations in OSPM in PC were investigated, and an OSPM-related signature was developed, which was helpful for the prognostic assessment and individualized treatment for PC.

Bait-trap chip for accurate and ultrasensitive capture of living circulating tumor cells.

Accurate analysis of living circulating tumor cells (CTCs) plays a crucial role in cancer diagnosis and prognosis evaluation. However, it is still challenging to develop a facile method for accurate, sensitive, and broad-spectrum isolation of living CTCs. Herein, inspired by the filopodia-extending behavior and clustered surface-biomarker of living CTCs, we present a unique bait-trap chip to achieve accurate and ultrasensitive capture of living CTCs from peripheral blood. The bait-trap chip is designed with the integration of nanocage (NCage) structure and branched aptamers. The NCage structure could "trap" the extended filopodia of living CTCs and resist the adhesion of filopodia-inhibited apoptotic cells, thus realizing the accurate capture (∼95% accuracy) of living CTCs independent of complex instruments. Using an in-situ rolling circle amplification (RCA) method, branched aptamers were easily modified onto the NCage structure, and served as "baits" to enhance the multi-interactions between CTC biomarker and chips, leading to ultrasensitive (99%) and reversible cell capture performance. The bait-trap chip successfully detects living CTCs in broad-spectrum cancer patients and achieves high diagnostic sensitivity (100%) and specificity (86%) of early prostate cancer. Therefore, our bait-trap chip provides a facile, accurate, and ultrasensitive strategy for living CTC isolation in clinical. STATEMENT OF SIGNIFICANCE: A unique bait-trap chip integrated with precise nanocage structure and branched aptamers was developed for the accurate and ultrasensitive capture of living CTCs. Compared with the current CTC isolation methods that are unable to distinguish CTC viability, the nanocage structure could not only "trap" the extended-filopodia of living CTCs, but also resist the adhesion of filopodia-inhibited apoptotic cells, thus realizing the accurate capture of living CTCs. Additionally, benefiting from the "bait-trap" synergistic effects generated by aptamer modification and nanocage structure, our chip achieved ultrasensitive, reversible capture of living CTCs. Moreover, this work provided a facile strategy for living CTC isolation from the blood of patients with early-stage and advanced cancer, exhibiting high consistency with the pathological diagnosis.

Predicting future cancer incidence by age, race, ethnicity, and sex.

INTRODUCTION: Cancer remains a substantial burden on society. Our objective was to update projections on the number of new cancer diagnoses in the United States by age, race, ethnicity, and sex through 2040. MATERIALS AND METHODS: Population-based cancer incidence data were obtained using Surveillance, Epidemiology, and End Results (SEER) data. Population estimates were made using the 2010 US Census data population projections to calculate future cancer incidence. Trends in age-adjusted incidence rates for 23 cancer types along with total cancers were calculated and incorporated into a second projection model. RESULTS: If cancer incidence remains stable, annual cancer diagnoses are projected to increase by 29.5% from 1.86 million to 2.4 million between 2020 and 2040. This increase outpaces the projected US population growth of 12.3% over the same period. The population of older adults is projected to represent an increasing proportion of total cancer diagnoses with patients ≥65 years old comprising 69% of all new cancer diagnoses and patients ≥85 years old representing 13% of new diagnoses by 2040. Cancer diagnoses are projected to increase in racial minority groups, with a projected 44% increase in Black Americans (from 222,000 to 320,000 annually), and 86% in Hispanic Americans (from 175,000 to 326,000 annually). DISCUSSION: The landscape of cancer care will continue to change over the next several decades. The burden of disease will remain substantial, and the growing proportion of older and minority patients with cancer remains of particular interest. These projections should help guide future health policy and research priorities.

Comparison of immunohistochemistry and RT-qPCR for assessing ER, PR, HER2, and Ki67 and evaluating subtypes in patients with breast cancer.

PURPOSE: Currently, the most commonly applied method for the determination of breast cancer subtypes is to test estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki67 by immunohistochemistry (IHC). However, the IHC method has substantial intraobserver and interobserver variability. ESR1, PGR, ERBB2, and MKi67 mRNA tests by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay may improve the diagnostic objectivity and efficiency. Here, we compared the concordance between RT-qPCR and IHC for assessment of the same biomarkers and evaluated the subtypes. METHODS: A total of 265 eligible cases were divided into a training cohort and a validation cohort, and the expressions of ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 were tested by IHC and RT-qPCR. Then, the appropriate cutoff of RT-qPCR was calculated in the training cohort. The concordance between RT-qPCR and IHC was calculated for individual marker. In addition, we investigated the subtypes based on the RT-qPCR results. RESULTS: The Spearman correlation coefficients between ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 by IHC and RT-qPCR were 0.768, 0.699, 0.762, and 0.387, respectively. The cutoff values for the RT-qPCR assay of ESR1 (1%), PGR (1%), ERBB2, and MKi67 (14%) were 35.539, 32.139, 36.398, and 29.176, respectively. The overall percent agreement (OPA) between ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 by IHC and RT-qPCR was 92.48%, 73.68%, 92.80%, and 74.44%, respectively. A total of 224 (84.53%) specimens were concordant for the breast cancer subtypes (IHC-based type) by RT-qPCR. CONCLUSION: Evaluation of breast cancer biomarker status by RT-qPCR was highly concordant with IHC. RT-qPCR can be used as a supplementary method to detect molecular markers of breast cancer.

CNST is Characteristic of Leukemia Stem Cells and is Associated With Poor Prognosis in AML.

Consortin (CNST) is a protein located on the trans-Golgi network that can target transmembrane proteins to the plasma membrane. Although CNST was discovered more than 10 years ago, there are still not enough studies on its function. During our search for possible new acute myeloid leukemia (AML) markers, we found that CNST was overexpressed in almost all patients with AML. By analyzing profiling data from public databases, we found that CNST expression inversely correlated with overall survival among AML patients. There was a great variation in CNST expression among different subtypes of AML, and the expression was the highest in the t(8,21) subtype, which was probably due to the direct regulation of CNST transcription by RUNX1-RUNX1T1. In addition, we analyzed the expression of CNST in different cells of the hematopoietic system. We found that CNST was associated with the low differentiation degrees of hematopoietic cells and had the highest expression level in leukemia stem cells (LSCs). Finally, we analyzed the CNST-related gene network and found that the genes negatively correlated with CNST are involved in various immune-related pathways, which indicates that CNST is likely related to immune evasion, LSC niche retention, and assembly of stress granules. In conclusion, our study suggests that CNST has the potential to be a diagnostic and prognostic biomarker for AML.

Prospero homeobox 1 promotes proliferation, migration, and invasion of osteosarcoma cells and its clinical significance.

Osteosarcoma (OS) is the most common primary malignant bone tumor. Prospero homeobox 1 (PROX1) is a key transcription factor involved in some cancers, but the role of PROX1 in OS is unclear. This study aimed to explore the clinical and biology significance of PROX1 in OS. Fifty-four OS tissues and matched nontumor tissues were collected to explore the relationship between PROX1 expression and clinical characteristics and prognosis. qRT-PCR and immunohistochemistry were used to investigate the expression patterns of PROX1 in OS tissues and cells. CCK-8, wound healing, and transwell assays were used to detect the effects of PROX1 on the proliferation, migration, and invasion of OS cells. Transcriptome sequencing, bioinformatics analysis and qRT-PCR were used to explore the regulatory network of PROX1. PROX1 was significantly higher in OS tissues and cells compared to normal tissues and cell lines. In OS patients, high expression of PROX1 was associated with Enneking stage (P < 0.001) and M classification (P < 0.001). High PROX1 expression predicted a poorer overall survival (P = 0.0047). Compared with untreated cells, OS cells overexpressing PROX1 showed higher proliferation, migration, and invasion abilities, while knockdown of PROX1 suppressed these abilities. The results of Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that the down regulated genes were mainly enriched in TNF signaling pathway, MAPK signaling pathway, and neuroactive ligand-receptor interaction. High PROX1 expression was significantly associated with poor overall survival in OS patients. PROX1 may be a promising prognostic marker and therapeutic target for OS patients.

A whole-slide image (WSI)-based immunohistochemical feature prediction system improves the subtyping of lung cancer.

BACKGROUND: Clinically, accurate pathological diagnosis is often challenged by insufficient tissue amounts and the unaffordability of additional immunohistochemical or genetic tests; thus, there is an urgent need for a universal approach to improve the subtyping of lung cancer without the above limitations. Here we aimed to develop a deep learning system to predict the immunohistochemistry (IHC) phenotype directly from whole-slide images (WSIs) to improve the subtyping of lung cancer from surgical resection and biopsy specimens. METHODS: A total of 1914 patients with lung cancer from three independent hospitals in China were enrolled for WSI-based immunohistochemical feature prediction system (WIFPS) development and validation. RESULTS: The WIFPS could directly predict the IHC status of nine subtype-specific biomarkers, including CK7, TTF-1, Napsin A, CK5/6, P63, P40, CD56, Synaptophysin, and Chromogranin A, achieving average areas under the curve (AUCs) of 0.912, 0.906, and 0.888 and overall diagnostic accuracies of 0.925, 0.941, and 0.887 in the validation datasets of total, external surgical resection specimens and biopsy specimens, respectively. The histological subtyping performance of the WIFPS remained comparable with that of general pathologists (GPs), with Cohen's kappa values ranging from 0.7646 to 0.8282. Furthermore, the WIFPS could be trained to not only predict the IHC status of anaplastic lymphoma kinase (ALK), programmed death-1 (PD-1), and programmed death ligand 1 (PD-L1), but also predict EGFR and KRAS mutation status, with AUCs from 0.525 to 0.917, as detected in separate populations. CONCLUSIONS: In this study, the WIFPS showed its proficiency as a useful complement to traditional histologic subtyping for integrated immunohistochemical spectrum prediction as well as potential in the detection of gene mutations.

Innovative Synoptic Reporting With Seven-Point Sampling Protocol to Improve Detection Rate of Microvascular Invasion in Hepatocellular Carcinoma.

Pathological MVI diagnosis could help to determine the prognosis and need for adjuvant therapy in hepatocellular carcinoma (HCC). However, narrative reporting (NR) would miss relevant clinical information and non-standardized sampling would underestimate MVI detection. Our objective was to explore the impact of innovative synoptic reporting (SR) and seven-point sampling (SPRING) protocol on microvascular invasion (MVI) rate and patient outcomes. In retrospective cohort, we extracted MVI status from NR in three centers and re-reviewed specimen sections by SR recommended by the College of American Pathologists (CAP) in our center. In prospective cohort, our center implemented the SPRING protocol, and external centers remained traditional pathological examination. MVI rate was compared between our center and external centers in both cohorts. Recurrence-free survival (RFS) before and after implementation was calculated by Kaplan-Meier method and compared by the log-rank test. In retrospective study, we found there was no significant difference in MVI rate between our center and external centers [10.3% (115/1112) vs. 12.4% (35/282), P=0.316]. In our center, SR recommended by CAP improved the MVI detection rate from 10.3 to 38.6% (P<0.001). In prospective study, the MVI rate in our center under SPRING was significantly higher than external centers (53.2 vs. 17%, P<0.001). RFS of MVI (-) patients improved after SPRING in our center (P=0.010), but it remained unchanged in MVI (+) patients (P=0.200). We conclude that the SR recommended by CAP could help to improve MVI detection rate. Our SPRING protocol could help to further improve the MVI rate and optimize prognostic stratification for HCC patients.

Neoadjuvant camrelizumab plus chemotherapy in treating locally advanced esophageal squamous cell carcinoma patients: a pilot study.

BACKGROUND: Camrelizumab (a PD-1 inhibitor) has been used as a potential therapy in unresectable advanced esophageal squamous cell carcinoma (ESCC) along with adjuvant treatment in locally advanced ESCC, exhibiting an acceptable efficacy and safety profile. This pilot study was designed to further investigate the clinical value and tolerance of neoadjuvant camrelizumab plus chemotherapy in locally advanced ESCC. METHODS: A total of 16 patients with locally advanced ESCC were recruited. Patients received 2 cycles of neoadjuvant therapy including 2 doses of camrelizumab concurrent with 2 cycles of paclitaxel plus carboplatin followed by surgery 4 weeks afterward. Then, the treatment response after neoadjuvant therapy, R0 resection rate, tumor regression grade (TRG), and pathological complete remission (pCR) rate were measured. Besides, adverse events were documented. At last, progression-free survival (PFS) and overall survival (OS) were assessed. RESULTS: Generally, objective remission rate (ORR) was 81.3% whereas disease control rate (DCR) was 100% after neoadjuvant therapy. Concerning TRG grade, 31.3, 37.5, 18.8, and 12.5% patients reached TRG0, TRG1, TRG2, and TRG3, respectively. Then, pCR rate and R0 resection rate were 31.3 and 93.8%, respectively. Besides, mean PFS and OS were 18.3 months (95%CI: (16.2-20.5) months) and 19.2 months (95%CI: (17.7-20.7) months), respectively, with a 1-year PFS of 83% and OS of 90.9%. Adverse events included white blood cell decrease (37.5%), neutrophil decrease (31.3%), reactive cutaneous capillary endothelial proliferation (37.5%), and nausea or vomiting (25.0%), which were relatively mild and manageable. CONCLUSION: Neoadjuvant camrelizumab plus chemotherapy exhibits good efficacy and acceptable tolerance in patients with locally advanced ESCC.

Histopathological Diagnosis System for Gastritis Using Deep Learning Algorithm.

Objective To develope a deep learning algorithm for pathological classification of chronic gastritis and assess its performance using whole-slide images (WSIs). Methods We retrospectively collected 1,250 gastric biopsy specimens (1,128 gastritis, 122 normal mucosa) from PLA General Hospital. The deep learning algorithm based on DeepLab v3 (ResNet-50) architecture was trained and validated using 1,008 WSIs and 100 WSIs, respectively. The diagnostic performance of the algorithm was tested on an independent test set of 142 WSIs, with the pathologists' consensus diagnosis as the gold standard. Results The receiver operating characteristic (ROC) curves were generated for chronic superficial gastritis (CSuG), chronic active gastritis (CAcG), and chronic atrophic gastritis (CAtG) in the test set, respectively.The areas under the ROC curves (AUCs) of the algorithm for CSuG, CAcG, and CAtG were 0.882, 0.905 and 0.910, respectively. The sensitivity and specificity of the deep learning algorithm for the classification of CSuG, CAcG, and CAtG were 0.790 and 1.000 (accuracy 0.880), 0.985 and 0.829 (accuracy 0.901), 0.952 and 0.992 (accuracy 0.986), respectively. The overall predicted accuracy for three different types of gastritis was 0.867. By flagging the suspicious regions identified by the algorithm in WSI, a more transparent and interpretable diagnosis can be generated. Conclusion The deep learning algorithm achieved high accuracy for chronic gastritis classification using WSIs. By pre-highlighting the different gastritis regions, it might be used as an auxiliary diagnostic tool to improve the work efficiency of pathologists.

Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study.

BACKGROUND: Targeted therapy and immunotherapy put forward higher demands for accurate lung cancer classification, as well as benign versus malignant disease discrimination. Digital whole slide images (WSIs) witnessed the transition from traditional histopathology to computational approaches, arousing a hype of deep learning methods for histopathological analysis. We aimed at exploring the potential of deep learning models in the identification of lung cancer subtypes and cancer mimics from WSIs. METHODS: We initially obtained 741 WSIs from the First Affiliated Hospital of Sun Yat-sen University (SYSUFH) for the deep learning model development, optimization, and verification. Additional 318 WSIs from SYSUFH, 212 from Shenzhen People's Hospital, and 422 from The Cancer Genome Atlas were further collected for multi-centre verification. EfficientNet-B5- and ResNet-50-based deep learning methods were developed and compared using the metrics of recall, precision, F1-score, and areas under the curve (AUCs). A threshold-based tumour-first aggregation approach was proposed and implemented for the label inferencing of WSIs with complex tissue components. Four pathologists of different levels from SYSUFH reviewed all the testing slides blindly, and the diagnosing results were used for quantitative comparisons with the best performing deep learning model. RESULTS: We developed the first deep learning-based six-type classifier for histopathological WSI classification of lung adenocarcinoma, lung squamous cell carcinoma, small cell lung carcinoma, pulmonary tuberculosis, organizing pneumonia, and normal lung. The EfficientNet-B5-based model outperformed ResNet-50 and was selected as the backbone in the classifier. Tested on 1067 slides from four cohorts of different medical centres, AUCs of 0.970, 0.918, 0.963, and 0.978 were achieved, respectively. The classifier achieved high consistence to the ground truth and attending pathologists with high intraclass correlation coefficients over 0.873. CONCLUSIONS: Multi-cohort testing demonstrated our six-type classifier achieved consistent and comparable performance to experienced pathologists and gained advantages over other existing computational methods. The visualization of prediction heatmap improved the model interpretability intuitively. The classifier with the threshold-based tumour-first label inferencing method exhibited excellent accuracy and feasibility in classifying lung cancers and confused nonneoplastic tissues, indicating that deep learning can resolve complex multi-class tissue classification that conforms to real-world histopathological scenarios.

Survival After Robotic-assisted Prostatectomy for Localized Prostate Cancer: An Epidemiologic Study.

BACKGROUNDS: To determine the potential survival benefit associated with robotic-assisted laparoscopic prostatectomy (RALP) compared to open radical prostatectomy (ORP) for prostate cancer. SUMMARY OF BACKGROUND DATA: RALP has become the dominant surgical approach for localized disease in the absence of randomized clinical evidence and despite of the factor that RALP is more expensive than ORP. METHODS: We performed a cohort study involving patients who underwent RALP and ORP for localized prostate cancer at the Commission on Cancer- accredited hospitals in the United States. Overall survival was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards models, and propensity score-matched analyses. An interrupted time-series analysis using the surveillance, epidemiology, and end results program database was also performed. RESULTS: From 2010 to 2011, 37,645 patients received RALP and 12,655 patients received ORP. At a median follow-up of 60.7 months, RALP was associated with improved overall survival by both univariate [hazard ratio (HR), 0.69; P < 0.001] and multivariate analysis (HR, 0.76; P < 0.001) compared with ORP. Propensity score-matched analysis demonstrated improved 5-year all-cause mortality (3.9% vs 5.5%, HR, 0.73; P < 0.001) for RALP. The interrupted time-series analysis demonstrated the adoption of robotic surgery coincided with a systematic improvement in the 5-year cancer-specific survival rate of 0.17% (95% confidence interval, 0.06-0.25) per year after 2003 (P = 0.004 for change of trend), as compared to the time before adoption of RALP (1998-2003, annual percentage change, 0.01%; 95% confidence interval, -0.06 to 0.08). Sensitivity analysis suggested that the results from the interrupted time-series analysis were consistent with the improvement in the all-cause mortality demonstrated in the survival analysis (P = 0.87). CONCLUSIONS: In this epidemiologic analysis, RALP was associated with a small but statistically significant improvement in 5-year all-cause mortality compared to ORP for localized prostate cancer. This is the first time in the literature to report a survival benefit with RALP. Our findings have significant quality and cost implications, and provide assurance regarding a dominant adoption of more expensive technology in the absence of randomized controlled trials.

Research on the effect of health care integration on patients' negative emotions and satisfaction with lung cancer nursing activities.

BACKGROUND: Lung cancer is a clinical disease with multiple malignant tumors. Currently, it is difficult for patients to benefit from routine clinical nursing due to the lack of a pertinent and systematic approach. AIM: To investigate the effect of integrated nursing care on the negative emotions and satisfaction of lung cancer patients. METHODS: From January 2018 to December 2019, 92 patients with lung cancer were selected and divided into the study group and the control group; there were 46 patients in each group. The control group received routine nursing, and the study group received integrated medical care in addition to the care received by the control group. Negative emotions before and after the intervention, the self-management ability score after the intervention, family care burden after the intervention and nursing satisfaction after the intervention were measured in the two groups. RESULTS: After the intervention, the self-rating anxiety scale and self-rating depression scale scores in the study group were lower than those in the control group (P < 0.05); the scores for health knowledge, self-concept, self-responsibility and self-care skills in the study group were higher than those in the control group (P < 0.05); the scores for individual burden and responsibility burden in the study group were lower than those before the intervention (P < 0.05); and the nursing satisfaction in the study group (93.48%) was higher than that in the control group (78.26%, P < 0.05). CONCLUSION: An integrated nursing care approach for lung cancer patients can effectively relieve the patient's negative feelings, improve their self-management ability, help to reduce the burden of family care and improve patient satisfaction with nursing activities.

Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning.

The early detection and accurate histopathological diagnosis of gastric cancer increase the chances of successful treatment. The worldwide shortage of pathologists offers a unique opportunity for the use of artificial intelligence assistance systems to alleviate the workload and increase diagnostic accuracy. Here, we report a clinically applicable system developed at the Chinese PLA General Hospital, China, using a deep convolutional neural network trained with 2,123 pixel-level annotated H&E-stained whole slide images. The model achieves a sensitivity near 100% and an average specificity of 80.6% on a real-world test dataset with 3,212 whole slide images digitalized by three scanners. We show that the system could aid pathologists in improving diagnostic accuracy and preventing misdiagnoses. Moreover, we demonstrate that our system performs robustly with 1,582 whole slide images from two other medical centres. Our study suggests the feasibility and benefits of using histopathological artificial intelligence assistance systems in routine practice scenarios.

Compatible Ag+ Complex-Assisted Ultrafine Copper Pattern Deposition on Poly(ethylene terephtalate) Film with Micro Inkjet Printing.

Firm immobilization of catalysts on the predesigned position over substrates is an essential process for producing flexible circuits by the electroless deposition (ELD) process. In this work, a compatible Ag+ complex was developed and directly printed on the poly(ethylene terephtalate) (PET) film through a micro inkjet printing instrument to trigger the deposition of ultrafine copper patterns with approximately 20 µm in width. Morphological and elementary characterization verified that the nanosized silver catalyst was uniformly distributed in the bridge layer, which could enhance the adhesion between the PET film and deposited copper patterns. Moreover, after 30 min of ELD, the copper patterns exhibited a low resistivity of 2.68 × 10-6 Ω·cm and maintained considerable conductivity even after 2000 times of cyclical bending. These interesting conductive and mechanical features demonstrate the tremendous potential of this Ag+ complex-assisted copper deposition in the interconnection of high-density integrated flexible electronics.

Integration of Tumor-Treating Fields into the Multidisciplinary Management of Patients with Solid Malignancies.

Tumor-treating fields (TTFields) are a noninvasive antimitotic cancer treatment consisting of low-intensity alternating electric fields delivered to the tumor or tumor bed via externally applied transducer arrays. In multiple in vitro and in vivo cancer cell lines, TTFields therapy inhibits cell proliferation, disrupts cell division, interferes with cell migration and invasion, and reduces DNA repair. Human trials in patients with primary glioblastoma showed an improvement in overall survival, and trials in patients with unresectable malignant pleural mesothelioma showed favorable outcomes compared with historical control. This led to U.S. Food and Drug Administration approval in both clinical situations, paving the way for development of trials investigating TTFields in other malignancies. Although these trials are ongoing, the existing evidence suggests that TTFields have activity outside of neuro-oncology, and further study into the mechanism of action and clinical activity is required. In addition, because TTFields are a previously unrecognized antimitotic therapy with a unique mode of delivery, the oncological community must address obstacles to widespread patient and provider acceptance. TTFields will likely join surgery, systemic therapy, and radiation therapy as a component of multimodality management of patients with solid malignancies. IMPLICATIONS FOR PRACTICE: Tumor-treating fields (TTFields) exhibit a broad range of antitumor activities. Clinically, they improve overall survival for patients with newly diagnosed glioblastoma. The emergence of TTFields has changed the treatment regimen for glioblastoma. Clinicians need to understand the practical issues surrounding its use in the multidisciplinary management of patients with glioblastoma. With ongoing clinical trials, TTFields likely will become another treatment modality for solid malignancies.

Surgical outcomes in patients with epilepsy after viral encephalitis: contribution of SEEG study.

BACKGROUND: Nowadays, few surgery analysis has been reported in cases of epilepsy after viral encephalitis(VE). Herein, this study was to evaluate the efficacy of surgery and capability of stereoelectroencephalography (SEEG) in the definition of the epileptogenic zone (EZ) after VE, and also to explore the relationship between the SEEG features and the surgical outcomes. METHODS: We retrospectively analyzed 10 surgically treated patients that identified to suffer from epilepsy secondary to VE using SEEG, and investigated the SEEG features associated with surgical outcomes in these patients. Besides visual analysis, we used the epileptogenicity index (EI), a semi-quantitative and supplementary tool to evaluate the validity of SEEG in the context of VE. RESULTS: Among the 10 operated patients, 3 of them became completely seizure-free. The patients who got totally seizure free or significant improvement, the seizure onset was located either in the antero-mesial temporal structures or focal gyrus; patients who got worthwhile improvement or no improvement, the seizure started from multiple brain lobes. The number of electrodes classified as epileptogenic visually involved were closely correlated with EI positive onses.Anatomic areas defined and shown as EZ on MRI by visual assessment were also defined as epileptogenic by the EI in these cases. CONCLUSION: Apart from exploring the surgical outcome related to epilepsy after VE, we also bring insight into the relationship between the SEEG features and surgical outcome with the application of the supplementary methods.

Oxygenation impairment in patients with acute aortic dissection is associated with disorders of coagulation and fibrinolysis: a prospective observational study.

BACKGROUND: Stanford type-A acute aortic dissection (AAD) is typically accompanied by oxygenation impairment before surgery. In addition, inflammation, coagulation and fibrinolysis also impair blood oxygenation. However, our understanding of the concentration of these factors in bronchoalveolar lavage fluid (BALF) has not been reported. The objective of the study was to investigate the impact of preoperative acute lung injury (ALI) on postoperative oxygenation impairment and to explore the effect of coagulation and fibrinolysis in blood and BALF. METHODS: This investigation utilized a prospective observational study design, which was registered at www.clinicaltrials.gov (identifier NCT01894334). The study included 53 patients undergoing surgery for Stanford type-A AAD at an academic hospital in China between October 2013 and July 2014. Preoperative ALI was identified according to the oxygenation index calculated by the PaO2/FiO2 ratio. The subjects were divided into the ALI group (oxygenation index ≤300 mmHg) or the control group (oxygenation index >300 mmHg). The primary outcome was patient oxygenation index, while secondary outcomes were concentrations of tissue factor (TF), tissue factor pathway inhibitor (TFPI), and plasminogen activator inhibitor-1 (PAI-1) in serum and BALF. RESULTS: The incidence of preoperative ALI for Stanford type-A AAD patients was 41.5%. Stanford type-A AAD patients with preoperative ALI had a lower postoperative oxygenation index (104.6±31.7 vs. 248.7±48.0 mmHg, P<0.001), higher concentrations of TF in serum and BALF (F=133.67, P<0.001; F=68.14, P<0.001), higher concentrations of TFPI in serum and BALF (F=31.98, P<0.001; F=45.58, P<0.001), and higher concentrations of PAI-1 in serum and BALF (F=213.88, P<0.001; F=107.95, P<0.001) when compared with those without preoperative ALI. Type-A AAD patients also showed a greater loss of blood (1,524±458 vs. 1,175±327 mL, P=0.040), longer mechanical ventilation time in the ICU (27.24±8.37 vs. 17.33±7.36 h, P<0.001), longer total stay in the ICU (42.27±10.85 vs. 33.45±9.05 h, P=0.002), and longer total hospital stay (17.77±5.00 vs. 13.48±3.97 days, P=0.001). Multivariate linear regression analysis indicated that preoperative PAI-1 in BALF, and TF in both serum and BALF were significantly associated with preoperative oxygenation impairment in patients with Stanford type-A AAD. CONCLUSIONS: Preoperative ALI caused more serious postoperative oxygenation impairment for Stanford type-A AAD, and coagulation and fibrinolysis appear to play critical roles in this process. Preoperative PAI-1 in BALF and TF in both serum and BALF were significant factors related to the occurrence of preoperative oxygenation impairment for Stanford type-A AAD.