When surface-enhanced Raman spectroscopy meets complex biofluids: A new representation strategy for reliable and comprehensive characterization.

BACKGROUND: Surface-enhanced Raman spectroscopy (SERS) has gained increasing importance in molecular detection due to its high specificity and sensitivity. Complex biofluids (e.g., cell lysates and serums) typically contain large numbers of different bio-molecules with various concentrations, making it extremely challenging to be reliably and comprehensively characterized via conventional single SERS spectra due to uncontrollable electromagnetic hot spots and irregular molecular motions. The traditional approach of directly reading out the single SERS spectra or calculating the average of multiple spectra is less likely to take advantage of the full information of complex biofluid systems. RESULTS: Herein, we propose to construct a spectral set with unordered multiple SERS spectra as a novel representation strategy to characterize full molecular information of complex biofluids. This new SERS representation not only contains details from each single spectra but captures the temporal/spatial distribution characteristics. To address the ordering-independent property of traditional chemometric methods (e.g., the Euclidean distance and the Pearson correlation coefficient), we introduce Wasserstein distance (WD) to quantitatively and comprehensively assess the quality of spectral sets on biofluids. WD performs its superiority for the quantitative assessment of the spectral sets. Additionally, WD benefits from its independence of the ordering of spectra in a spectral set, which is undesirable for traditional chemometric methods. With experiments on cell lysates and human serums, we successfully achieve the verification for the reproducibility between parallel samples, the uniformity at different positions in the same sample, the repeatability from multiple tests at one location of the same sample, and the cardinality effect of the spectral set. SERS spectral sets also manage to distinguish different classes of human serums and achieve higher accuracy than the traditional prostate-specific antigen in prostate cancer classification. SIGNIFICANCE: The proposed SERS spectral set is a robust representation approach in accessing full information of biological samples compared to relying on a single or averaged spectra in terms of reproducibility, uniformity, repeatability, and cardinality effect. The application of WD further demonstrates the effectiveness and robustness of spectral sets in characterizing complex biofluid samples, which extends and consolidates the role of SERS.

SERSomes for metabolic phenotyping and prostate cancer diagnosis.

Molecular phenotypic variations in metabolites offer the promise of rapid profiling of physiological and pathological states for diagnosis, monitoring, and prognosis. Since present methods are expensive, time-consuming, and still not sensitive enough, there is an urgent need for approaches that can interrogate complex biological fluids at a system-wide level. Here, we introduce hyperspectral surface-enhanced Raman spectroscopy (SERS) to profile microliters of biofluidic metabolite extraction in 15 min with a spectral set, SERSome, that can be used to describe the structures and functions of various molecules produced in the biofluid at a specific time via SERS characteristics. The metabolite differences of various biofluids, including cell culture medium and human serum, are successfully profiled, showing a diagnosis accuracy of 80.8% on the internal test set and 73% on the external validation set for prostate cancer, discovering potential biomarkers, and predicting the tissue-level pathological aggressiveness. SERSomes offer a promising methodology for metabolic phenotyping.

A Prospective Randomized Trial of Neoadjuvant Chemohormonal Therapy vs Hormonal Therapy in Locally Advanced Prostate Cancer Treated by Radical Prostatectomy.

PURPOSE: Benefits of docetaxel-based neoadjuvant chemohormonal therapy (NCHT) before radical prostatectomy (RP) remain largely unknown. We explored whether docetaxel-based NCHT would bring pathological benefits and improve biochemical progression-free survival (bPFS) over neoadjuvant hormonal therapy (NHT) in locally advanced prostate cancer. MATERIALS AND METHODS: A randomized trial was designed recruiting 141 locally advanced, high-risk prostate cancer patients who were randomly assigned at the ratio of 2:1 to the NCHT group (75 mg/m2 body surface area every 3 weeks plus androgen deprivation therapy for 6 cycles) and the NHT group (androgen deprivation therapy for 24 weeks). The primary end point was 3-year bPFS. Secondary end points were pathological response including pathological downstaging and minimal residual disease rates. RESULTS: The NCHT group showed significant benefits in 3-year bPFS compared to the NHT group (29% vs 9.5%, P = .002). At a median follow-up of 53 months, the NCHT group achieved a significantly longer median bPFS time than the NHT group (17 months vs 14 months). No significant differences were found between the 2 groups in pathological downstaging and minimal residual disease rates. CONCLUSIONS: NCHT plus RP achieved significant bPFS benefits when compared with NHT plus RP in high-risk, locally advanced prostate cancer. A larger cohort with longer follow-up duration is essential in further investigation.

Harnessing artificial intelligence for prostate cancer management.

Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is crucial for clinical decision-making, but traditional pathology review is labor intensive and subjective to some extent. Digital pathology and whole-slide imaging enable the application of artificial intelligence (AI) in pathology. This review highlights the success of AI in detecting and grading PCa, predicting patient outcomes, and identifying molecular subtypes. We propose that AI-based methods could collaborate with pathologists to reduce workload and assist clinicians in formulating treatment recommendations. We also introduce the general process and challenges in developing AI pathology models for PCa. Importantly, we summarize publicly available datasets and open-source codes to facilitate the utilization of existing data and the comparison of the performance of different models to improve future studies.

Precise diagnosis and risk stratification of prostate cancer by comprehensive serum metabolic fingerprints: a prediction model study.

OBJECTIVES: Prostate cancer (PCa) is one of the most common malignancies in men worldwide and has caused increasing clinical morbidity and mortality, making timely diagnosis and accurate staging crucial. The authors introduced a novel approach based on mass spectrometry for precise diagnosis and stratification of PCa to facilitate clinical decision-making. METHODS: Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry analysis of trace blood samples was combined with machine learning algorithms to construct diagnostic and stratification models. A total of 367 subjects, comprising 181 with PCa and 186 with non-PCa were enrolled. Additional 60 subjects, comprising 30 with PCa and 30 with non-PCa were enrolled as an external cohort for validation. Subsequent metabolomic analysis was carried out using Autoflex MALDI-TOF, and the mass spectra were introduced into various algorithms to construct different models. RESULTS: Serum metabolic fingerprints were successfully obtained from 181 patients with PCa and 186 patients with non-PCa. The diagnostic model based on the eight signals demonstrated a remarkable area under curve of 100% and was validated in the external cohort with the area under curve of 87.3%. Fifteen signals were selected for enrichment analysis, revealing the potential metabolic pathways that facilitate tumorigenesis. Furthermore, the stage prediction model with an overall accuracy of 85.9% precisely classified subjects with localized disease and those with metastasis. The risk stratification model, with an overall accuracy of 89.6%, precisely classified the subjects as low-risk and high-risk. CONCLUSIONS: Our study facilitated the timely diagnosis and risk stratification of PCa and provided new insights into the underlying mechanisms of metabolic alterations in PCa.

Identifying High Gleason Score Prostate Cancer by Prostate Fluid Metabolic Fingerprint-Based Multi-Modal Recognition.

Prostate cancer (PCa) is the second most common cancer in males worldwide. The Gleason scoring system, which classifies the pathological growth pattern of cancer, is considered one of the most important prognostic factors for PCa. Compared to indolent PCa, PCa with high Gleason score (h-GS PCa, GS ≥ 8) has greater clinical significance due to its high aggressiveness and poor prognosis. It is crucial to establish a rapid, non-invasive diagnostic modality to decipher patients with h-GS PCa as early as possible. In this study, ferric nanoparticle-assisted laser desorption/ionization mass spectrometry (FeNPALDI-MS) to extract prostate fluid metabolic fingerprint (PSF-MF) is employed and combined with the clinical features of patients, such as prostate-specific antigen (PSA), to establish a multi-modal diagnosis assisted by machine learning. This approach yields an impressive area under the curve (AUC) of 0.87 to diagnose patients with h-GS, surpassing the results of single-modal diagnosis using only PSF-MF or PSA, respectively. Additionally, using various screening methods, six key metabolites that exhibit greater diagnostic efficacy (AUC = 0.96) are identified. These findings also provide insights into related metabolic pathways, which may provide valuable information for further elucidation of the pathological mechanisms underlying h-GS PCa.

Extracellular vesicles related gene HSPH1 exerts anti-tumor effects in prostate cancer via promoting the stress response of CD8 + T cells.

BACKGROUND: T cell stress response state (TSTR), as a novel immune concept previous studies have proposed, has not yet been explored in prostate cancer (PC). As a type of cellular efflux, exosomes play important roles in the occurrence and development of PC. METHOD: Here, we conducted a combined analysis on extracellular vesicle related genes (EVRGs) in PC using data from single-cell RNA (scRNA), spatial transcriptome (ST), and bulk RNA sequencing. RESULT: Preliminary findings have revealed that heat shock protein family H (Hsp110) member 1 (HSPH1) possesses two identities, one being EVRGs and the other being a member of the heat shock protein family involved in TSTR, which may promote the differentiation of conventional T cells towards Th1 or Th2 cells through the pathway of IL2-MYC-IL2RA, thereby promoting the increase of CD8 + T cells in the tumor area, especially in the invasive zone, and inhibiting the invasion of PCs. We also notice the negative response of HSPH1 + CD8 + T cell related genes in immune checkpoint blockade (ICB). Western blot (WB) and droplet digital Polymerase Chain Reaction (ddPCR) demonstrated that the mRNA and protein levels of HSPH1 in EVs of PCs were significantly higher than those in adjacent tissues. CONCLUSION: Results above indicate the potential of HSPH1 as a critical therapeutic target in PC.

Advances of hafnium based nanomaterials for cancer theranostics.

Hafnium-based nanomaterials (Hf-NMs) have attracted the interest of numerous biomedical researchers by their unique properties. Recent years have witnessed significant advancements in the field of Hafnium-based nanomaterials, particularly in the context of cancer diagnosis and treatment. However, research in this area, especially concerning the clinical application of Hafnium-based nanomaterials, has not been thoroughly reviewed. This review will cover: 1) Classification and synthesis of Hafnium-based nanomaterials including Hafnium oxide nanomaterials, Hafnium Metal-Organic Frameworks/nanoscale coordination polymers (MOFs/NCPs); 2) Hafnium-based nanomaterials act as contrast enhancement agent for cancer imaging, and hafnium-based nanomaterials used for diagnosis in cancer liquid biopsy; 3) hafnium-based nanomaterials for cancer therapy, including hafnium-based nanomaterials for radiotherapy, hafnium-based nanomaterials for photodynamic therapy, hafnium-based nanomaterials for various combined therapy; and 4) Translation, toxicity, and safety for Hf-NMs in human and preclinical animal models. More attention will be given to the clinical translation of Hf-NMs in cancer.

The ELAVL3/MYCN positive feedback loop provides a therapeutic target for neuroendocrine prostate cancer.

Neuroendocrine prostate cancer is a rapidly progressive and lethal disease characterized by early visceral metastasis, poor prognosis, and limited treatment options. Uncovering the oncogenic mechanisms could lead to the discovery of potential therapeutic avenues. Here, we demonstrate that the RNA-binding protein ELAVL3 is specifically upregulated in neuroendocrine prostate cancer and that overexpression of ELAVL3 alone is sufficient to induce the neuroendocrine phenotype in prostate adenocarcinoma. Mechanistically, ELAVL3 is transcriptionally regulated by MYCN and subsequently binds to and stabilizes MYCN and RICTOR mRNA. Moreover, ELAVL3 is shown to be released in extracellular vesicles and induce neuroendocrine differentiation of adenocarcinoma cells via an intercellular mechanism. Pharmacological inhibition of ELAVL3 with pyrvinium pamoate, an FDA-approved drug, effectively suppresses tumor growth, reduces metastatic risk, and improves survival in neuroendocrine prostate cancer mouse models. Our results identify ELAVL3 as a critical regulator of neuroendocrine differentiation in prostate cancer and propose a drug repurposing strategy for targeted therapies.

Transcriptomic signature defines two subtypes of locally advanced PCa with distinct neoadjuvant therapy benefits.

Background: Patients with locally advanced prostate cancer (LAPCa) received docetaxel-based neoadjuvant chemo-hormonal therapy (NCHT) had better clinical outcomes after surgery compared to neoadjuvant hormonal therapy (NHT) groups, but not all patients experienced favorable clinical outcomes with NCHT, raising the necessity for potential biomarker assessment. The transcriptomic profiling offers a unique opportunity to interrogate the accurate response to NCHT and NHT treatment and to identify the predictive biomarkers for neoadjuvant therapy. Methods: The whole transcriptomic profiling was performed on baseline biopsies and surgical tissue specimens from 64 patients with LAPCa at Renji Hospital between 2014 and 2018. Biochemical progression-free survival (bPFS)-based gene-by-treatment interaction effects were used to identify predictive biomarkers for guiding treatment selection. Results: Comparing the transcriptome profiling of pre- and post-treatment LAPCa specimens, NHT and NCHT shared 1917 up- and 670 down-regulated DEGs at least 2-fold. Pathway enrichment analysis showed up-regulated pathways in response to NHT and NCHT were both enriched in cytokine receptor interaction pathways, and down-regulated pathways in response to NCHT were enriched in cell cycle pathways. By comprehensive transcriptome profiling of 64 baseline specimens, ten predictive markers were identified. We integrated them into the signature to evaluate the relative benefits of neoadjuvant therapy, which categorizes patients into two subgroups with relative bPFS benefits from either NHCT or NHT. In the high-score (≥ -95.798) group (n = 37), NCHT treatment led to significantly longer bPFS (P< 0.0001), with a clear and early separation of the Kaplan-Meier curves. In the low-score (< -95.798) group (n = 27), NHT also led to significantly longer bPFS (P=0.0025). Conclusions: In this study, we proposed the first predictive transcriptomic signature might potentially guide the effective selection of neoadjuvant therapy in LAPCa and might provide precise guidance toward future personalized adjuvant therapy. Trial registration: The study was approved by the Ethics Committee of Renji Hospital affiliated to Shanghai Jiao Tong University (Ky2019-087).

Early serial circulating tumor DNA sequencing predicts the efficacy of chemohormonal therapy in patients with metastatic hormone-sensitive prostate cancer.

Chemohormonal therapy is a standard treatment for metastatic hormone-sensitive prostate cancer (mHSPC); however, there are no biomarkers to guide clinical decisions regarding therapeutic options. We aimed to evaluate the clinical utility of serial circulating tumor DNA (ctDNA) sequencing in early prediction of the efficacy of chemohormonal therapy in patients with mHSPC. We conducted a retrospective observational study of 66 patients with mHSPC receiving chemohormonal therapy who underwent serial targeted gene-panel ctDNA sequencing. Peripheral blood samples were collected before treatment and after one cycle of chemotherapy. Kaplan-Meier and log-rank analyses were used to analyze the association between ctDNA status and disease progression-free survival. Serial changes in the ctDNA fraction and genetic alterations were also observed. After one cycle of chemotherapy, 23 (34.8%) patients displayed elevated ctDNA levels, whereas the other patients (65.2%, n = 43) did not. The median time to castration resistance in the group with reduced ctDNA levels was significantly longer than that in the group with increased ctDNA levels (17.70 vs. 8.43 months [mo], p < 0.001). Interestingly, patients with de novo alterations in homologous recombination pathway genes after treatment experienced a shorter time to castration resistance than that experienced by the remaining patients (8.02 vs. 13.20 mo, p = 0.011). The increased ctDNA levels or de novo alterations detected in homologous recombination pathway genes are a harbinger of disease progression. Early serial ctDNA sequencing could aid clinicians in making accurate treatment decisions.

Baseline PSMA-PET/CT as a predictor of PSA persistence following radical prostatectomy in high-risk nonmetastatic prostate cancer patients receiving neoadjuvant therapy.

BACKGROUND: The precise staging and proper management of high-risk prostate cancer (PCa) continues to be a challenge. We aimed to demonstrate the prognostic value of baseline prostate-specific membrane antigen-ligand positron emission tomography/computed tomography (PSMA-PET/CT) in high-risk, nonmetastatic PCa patients who received neoadjuvant hormonal or chemohormonal treatment followed by radical prostatectomy (RP). METHODS: We performed retrospective analyses of 70 patients with high-risk, nonmetastatic PCa confirmed by biopsy between 2018 and 2021. All patients underwent neoadjuvant therapy followed by RP and pelvic lymph node dissection (PLND); PSMA-PET/CT was performed before initiation of neoadjuvant therapy. Acquired image information and clinical characteristics/outcomes were examined for possible associations. RESULTS: Among 70 high-risk PCa patients, median age was 69 years old and median prostate specific antigen (PSA) at presentation was 58.5 ng/mL. Thirty (42.9%) patients had uptake of the PSMA tracer only in the primary PCa lesions and 40 (57.1%) patients had PSMA-positive lesions in regional or distant sites. Sixteen (32%) localized PCa patients defined by pre-PET magnetic resonance imaging were found to have locally advanced PCa based on PSMA-PET/CT. Fifteen (30%) localized PCa patients and 7 (35%) locally advanced PCa patients were upstaged to metastatic PCa. The sensitivity and specificity of PSMA-PET/CT for the detection of lymph node involvement were 90.9% and 69.5%, respectively, with a positive prediction value of 35.7% and negative prediction value of 97.6%. The diagnostic accuracy was 72.9%. Univariate analysis showed upstaging, tumor stage, and metastasis location based on PSMA-PET/CT are predictors to PSA persistence after surgery, while multivariate logistic regression analysis showed only the tumor stage based on PSMA-PET/CT remained an independent predictor of the outcome. CONCLUSIONS: This study further highlights the accuracy and necessity of PSMA-PET/CT in newly diagnosed, high-risk, nonmetastatic PCa patients.

Identification of cancer-associated fibroblasts subtypes in prostate cancer.

Introduction: Cancer-associated fibroblasts (CAFs) are one of the most abundant cell types in tumor microenvironment. However, the phenotypic and functional heterogeneities among CAFs have not been sufficiently investigated in prostate cancer. Methods: We obtained and analyzed the single-cell RNA-sequencing data from 26 hormone-sensitive prostate cancer samples and 8 castration-resistant prostate cancer samples, along with the analysis of bulk-sequencing datasets. Furthermore, we performed multicolor immunofluorescence staining to verify the findings from the data analysis. Results: We identified two major CAFs subtypes with distinct molecular characteristics and biological functions in prostate cancer microenvironment, namely αSMA+ CAV1+ CAFs-C0 and FN1+ FAP+ CAFs-C1. Another single-cell RNA-sequencing dataset containing 7 bone metastatic prostate cancer samples demonstrated that osteoblasts in the bone metastatic lesions comprised two subtypes with molecular characteristics and biological functions similar to CAFs-C0 and CAFs-C1 in the primary tumor sites. In addition, we discovered a transcriptional factor regulatory network depending on CAFs-C1. CAFs-C1, but not CAFs-C0, was associated with castration resistance and poor prognosis. We also found that CAFs-C1 signature was involved in treatment resistance to immune checkpoint inhibitors. Discussion: In summary, our results identified the presence of heterogeneous CAFs subtypes in prostate cancer microenvironment and the potential of specific CAFs subtype as therapeutic target for castration-resistant prostate cancer.

The prognostic nomogram for PSA-incongruent low-risk prostate cancer treated by radical prostatectomy.

OBJECTIVE: To establish a prognostic nomogram for PSA-incongruent low-risk prostate cancer (PCa) patients (Gleason score 6 and clinical stage T2a) at diagnosis and treated with radical prostatectomy (RP), based on clinical and pathological metrics. METHODS: In total, 217 patients diagnosed with PCa were included in this study. All patients had a Gleason score of 6 (GS6) in biopsy, had clinical T2a before surgery and were treated with RP. Biochemical progression-free survival (bPFS) was analyzed using the Kaplan-Meier method. Univariate and multivariate analyses were used to determine prognostic factors related to bPFS. A prognostic nomogram was established based on factors that were significant in the multivariate analyses. RESULTS: The median bPFS had a significant difference in the subgroup of PSA at diagnosis (' < 10 ng/mL': 71.698 [67.549-75.847] vs '10-20 ng/mL': 71.038 [66.220-75.857] vs ' ≥ 20 ng/mL': 26.746 [12.384-41.108] months [Log Rank P < 0.001]), the subgroup of T stage upgrade (Negative: 70.016 [65.846-74.187] vs 'T2b/c': 69.183 [63.544-74.822] vs 'T3/4': 32.235 [11.877-52.593] months [Log Rank P < 0.001]) and the subgroup of Gleason score upgrade (Negative: 72.63 [69.096-76.163] vs '3 + 4': 68.393 [62.243-74.543] vs '4 + 3': 41.427 [27.517-55.336] vs ' ≥ 8': 28.291 [7.527-49.055] [Log Rank P < 0.001]). PSA at diagnoses (Hazard Ratio (HR) 1.027, 95% CI 1.015-1.039, P < 0.001), T stage upgrade (HR 2.116, 95% CI 1.083-4.133, P = 0.028), and Gleason score upgrade (HR 2.831, 95% CI 1.892-4.237, P < 0.001) were identified as independent predictors with significance in multivariable Cox regression analysis. A nomogram was established based on these three factors. CONCLUSIONS: Our study indicated that PSA-incongruent low-risk PCa patients (PSA with 10-20 ng/mL) had a similar prognosis to those with real low-risk PCa (PSA < 10 ng/mL) in the D' Amico criteria. We also established a nomogram based on three significant prognostic factors, including PSA at diagnosis, T stage upgrade, and Gleason score upgrade, which were associated with clinical outcomes in prostate cancer patients with GS6 and T2a after surgery.

Engineering the MoS2 /MXene Heterostructure for Precise and Noninvasive Diagnosis of Prostate Cancer with Clinical Specimens.

High-throughput metabolic fingerprinting has been deemed one of the most promising strategies for addressing the high false positive rate of prostate cancer (PCa) diagnosis in the prostate-specific antigen (PSA) gray zone. However, the current metabolic fingerprinting remains challenging in achieving high-precision metabolite detection in complex biological samples (e.g., serum and urine). Herein, a novel self-assembly MoS2 /MXene heterostructure nanocomposite with a tailored doping ratio of 10% is presented as a matrix for laser desorption ionization mass spectrometry analysis in clinical biosamples. Notably, owing to the two-dimensional architecture and doping effect, MoS2 /MXene demonstrates favorable laser desorption ionization performance with low adsorption energy, which is evidenced by efficient urinary metabolic fingerprinting with an enhanced area under curve (AUC) diagnosis capability of 0.959 relative to that of serum metabolic fingerprinting (AUC = 0.902) for the diagnosis of PCa in the PSA gray zone. Thus, this MoS2 /MXene heterostructure is anticipated to offer a novel strategy to precisely and noninvasively diagnose PCa in the PSA gray zone.

Early Plasma Circulating Tumor DNA as a Potential Biomarker of Disease Recurrence in Non-metastatic Prostate Cancer.

PURPOSE: In non-metastatic prostate cancer (nmPCa) setting, it is important to early identify the patients at risk of biochemical recurrence (BCR) for immediate postoperative intervention. Our study aimed to evaluate the potential clinical utility of circulating tumor DNA (ctDNA) for predicting disease recurrence. Materials and Methods: This real-world observational study evaluated 161 cases of nmPCa undergoing next-generation sequencing at our institution. A total of 139 ctDNA samples and 31 biopsied tumor tissue underwent genomic profiling. The study endpoint was BCR after radical prostatectomy. Relationships between the ctDNA status and the biochemical progression-free survival (bPFS) were analyzed by log-rank test and multivariate Cox regression. RESULTS: Of 161 enrolled patients, 19 (11.8%) harbored deleterious alterations in NCOR2, followed by BRCA2 (3.7%), ATR (2.5%), and CDK12 (2.5%). Of available pre-operative blood samples (n=139), ctDNA was detectable in 91 (65.5%). Until last follow-up, 56 of 68 patients (85.3%) with detectable ctDNA had achieved BCR, whereas only eight of 39 patients (20.5%) with undetectable ctDNA had achieved BCR. Patients who had undetectable ctDNA experienced significantly longer bPFS compared with those who had detectable ctDNA (not available vs. 8.2 months; hazard ratio, 0.14; p < 0.01). Pre-operative ctDNA status was a significant prognostic factor of disease recurrence. CONCLUSION: Pre-operative ctDNA detection could identify patients at high risk of recurrence and has the potential to inform immediate postoperative interventions, but these approaches remain to be validated in prospective studies. ctDNA studies can provide insights into accurate monitoring and precise treatment rather than simply following routine clinical care.

Multimodal convolutional neural networks based on the Raman spectra of serum and clinical features for the early diagnosis of prostate cancer.

We collected surface-enhanced Raman spectroscopy (SERS) data from the serum of 729 patients with prostate cancer or benign prostatic hyperplasia (BPH), corresponding to their pathological results, and built an artificial intelligence-assisted diagnosis model based on a convolutional neural network (CNN). We then evaluated its value in diagnosing prostate cancer and predicting the Gleason score (GS) using a simple cross-validation method. Our CNN model based on the spectral data for prostate cancer diagnosis revealed an accuracy of 85.14 ± 0.39%. After adjusting the model with patient age and prostate specific antigen (PSA), the accuracy of the multimodal CNN was up to 88.55 ± 0.66%. Our multimodal CNN for distinguishing low-GS/high-GS and GS = 3 + 3/GS = 3 + 4 revealed accuracies of 68 ± 0.58% and 77 ± 0.52%, respectively.

Less Invasive Surfactant Administration for the Treatment of Neonatal Respiratory Distress Syndrome Combined With Noninvasive Ventilation in Anhui Province, China: A Retrospective Cohort Study.

The less invasive surfactant application (LISA) technology has been widely used to manage breathing in premature infants. Premature infants with respiratory distress syndrome (RDS) were retrospectively analyzed and divided into 2 groups according to the drug delivery methods used: LISA versus traditional pulmonary surfactant injection (INSURE). The decrease of transcutaneous saturation (TcSO2) and heart rate during surfactant delivery in the LISA group was higher than that in the INSURE group (P < .05). Between the 2 groups, there was no significant difference in the change in partial pressure of oxygen/fraction of inspired oxygen value before and after drug delivery; second-use pulmonary surfactant; noninvasive ventilation (NIV) failure rate; incidence of some complications; duration of NIV use; hospitalization time; and mortality (P > .05). However, the incidence of bronchopulmonary dysplasia (BPD) in the LISA group was lower than that in the INSURE group (P < .05). The clinical efficacy of LISA combined with the NIV treatment in premature infants with RDS was clear, and this treatment could reduce the incidence of BPD.

Stimulated Raman Scattering Microscopy Enables Gleason Scoring of Prostate Core Needle Biopsy by a Convolutional Neural Network.

Focal therapy (FT) has been proposed as an approach to eradicate clinically significant prostate cancer while preserving the normal surrounding tissues to minimize treatment-related toxicity. Rapid histology of core needle biopsies is essential to ensure the precise FT for localized lesions and to determine tumor grades. However, it is difficult to achieve both high accuracy and speed with currently available histopathology methods. Here, we demonstrated that stimulated Raman scattering (SRS) microscopy could reveal the largely heterogeneous histologic features of fresh prostatic biopsy tissues in a label-free and near real-time manner. A diagnostic convolutional neural network (CNN) built based on images from 61 patients could classify Gleason patterns of prostate cancer with an accuracy of 85.7%. An additional 22 independent cases introduced as external test dataset validated the CNN performance with 84.4% accuracy. Gleason scores of core needle biopsies from 21 cases were calculated using the deep learning SRS system and showed a 71% diagnostic consistency with grading from three pathologists. This study demonstrates the potential of a deep learning-assisted SRS platform in evaluating the tumor grade of prostate cancer, which could help simplify the diagnostic workflow and provide timely histopathology compatible with FT treatment. SIGNIFICANCE: A platform combining stimulated Raman scattering microscopy and a convolutional neural network provides rapid histopathology and automated Gleason scoring on fresh prostate core needle biopsies without complex tissue processing.

The application of "S.I.S" technique improves long-term continence after robotic radical prostatectomy.

AIMS: To propose a novel S.I.S technique during the robotic-assisted radical prostatectomy (RARP), encompassing pubourethral suspension, posterior wall intensification, and bladder neck stripping, and to present functional and oncological outcomes with a special focus on long-term continence. METHODS: From January 1, 2018, to December 31, 2019, consecutive patients who underwent RARP were retrospectively investigated and separated into the S.I.S group and the conventional group. Preoperative patient characteristics, tumor status, and perioperative parameters were collected, followed by the assessment of self-reported status on continence, using an International Consultation on Incontinence Modular Questionnaire-urinary incontinence short form (ICIQ-UI-SF). Statistical comparisons were performed on variables between the two surgery groups, and multivariate logistic regression analysis was used to determine predictive factors for postoperative incontinence severity. RESULTS: A total of 602 subjects were analyzed with a median follow-up of 24 months. There was no significant difference regarding baseline characteristics and perioperative parameters, except for a more advanced tumor stage in the S.I.S group. The application of the S.I.S technique did not jeopardize the positive surgical margin rate at the bladder neck or long-term tumor control. Notably, the patient-reported degree of incontinence was significantly reduced with the assistance of S.I.S technique, as evidenced by the diminished severe-to-very severe cases. On multivariate analysis, both preoperative body mass index and use of S.I.S modification were independent predictive factors for the long-term incontinence severity. CONCLUSIONS: The application of S.I.S technique during RARP is feasible and superior compare with the conventional approach, with a significantly alleviated long-term incontinence severity, without compromising cancer control.