Search

Broad-area lasers (BALs) have found applications in a variety of crucial fields on account of their high output power and high energy transfer efficiency. However, they suffer from poor spatial beam quality due to multi-mode behavior along the waveguide transverse direction. In this paper, we propose a novel metasurface waveguide structure acting as a transverse mode selective back-reflector for BALs. In order to effectively inverse design such a structure, a digital adjoint algorithm is introduced to adapt the considerably large design area and the high degree of freedom. As a proof of the concept, a device structure with a design area of 40 × 20 μm2 is investigated. The simulation results exhibit high fundamental mode reflection (above 90%), while higher-order transverse mode reflections are suppressed below 0.2%. This is, to our knowledge, the largest device structure designed based on the inverse method. We exploited such a device and the method and further investigated the device's robustness and feasibility of the inverse method. The results are elaborately discussed. [ABSTRACT FROM AUTHOR]

Photonic devices based on silicon waveguides are essential to versatile high‐performance and low‐cost photonic integrated systems. Extremely complex silicon photonic devices with hundreds or even thousands of degrees of freedom (DOF) are successfully designed and manufactured based on recent advances in data science and nanofabrication technology. At this level, conventional forward‐reasoning may no longer be suitable for designing high‐performance silicon photonic devices with novel functionalities since the light‐matter interaction is complex and non‐intuitive. Therefore, the timely development of sub‐wavelength silicon photonic devices that can precisely mold the flow of light is a critical and urgent issue requiring joint engineering and scientific efforts. In this paper, an inverse design strategy based on heuristic and gradient descendant algorithms, enabling the realization of large‐scale integrated devices is first introduced. Subsequently, the burgeoning deep learning technology, which offers a promising direction for the automation design of silicon photonics with a data‐driven approach, is discussed. Finally, the obstacles and prospects in this emerging research direction are revealed. Detail discussions from multiple perspectives are provided. This review aims to provide general guidance and a comprehensive reference for scientists developing photonic integrated systems. [ABSTRACT FROM AUTHOR]

In this article, we investigate a new estimation approach for the partially linear single-index model based on modal regression method, where the non parametric function is estimated by penalized spline method. Moreover, we develop an expection maximum (EM)-type algorithm and establish the large sample properties of the proposed estimation method. A distinguishing characteristic of the newly proposed estimation is robust against outliers through introducing an additional tuning parameter which can be automatically selected using the observed data. Simulation studies and real data example are used to evaluate the finite-sample performance, and the results show that the newly proposed method works very well. [ABSTRACT FROM AUTHOR]

The t distribution is a useful extension of the normal distribution, which can be used for statistical modeling of data sets with heavy tails, and provides robust estimation. In this paper, in view of the advantages of Bayesian analysis, we propose a new robust coefficient estimation and variable selection method based on Bayesian adaptive Lasso t regression. A Gibbs sampler is developed based on the Bayesian hierarchical model framework, where we treat the t distribution as a mixture of normal and gamma distributions and put different penalization parameters for different regression coefficients. We also consider the Bayesian t regression with adaptive group Lasso and obtain the Gibbs sampler from the posterior distributions. Both simulation studies and real data example show that our method performs well compared with other existing methods when the error distribution has heavy tails and/or outliers. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to investigate the associations of serine proteinase inhibitor family G1 (SERPING1) down-regulation with poor prognosis in patients with prostate cancer (PCa). Furthermore, we aim to find more novel and effective PCa molecular markers to provide an early screening of PCa, distinguish patients with aggressive PCa, predict the prognosis, or reduce the economic burden of PCa.Methods: SERPING1 protein expression in both human PCa and normal prostate tissues was detected by immunohistochemical staining, which intensity was analyzed in association with clinical pathological parameters such Gleason score, pathological grade, clinical stage, tumor stage, lymph node metastasis, and distant metastasis. Moreover, we used The Cancer Genome Atlas (TCGA) Database, Taylor Database, and Oncomine dataset to validate our immunohistochemical results and investigated the value of SERPING1 in PCa at mRNA level. Kaplan-Meier analysis and Cox regression analysis were performed to evaluate the relationship between SERPING1 and prognosis of patients with PCa.Results: The outcome showed that SERPING1 was expressed mainly in cytoplasm of grand cells of prostate tissue and was significantly expressed less in PCa (P<0.001). Furthermore, in the tissue microarray of our samples, decreasing expression of SERPING1 was correlated with the higher Gleason score (P = 0.004), the higher pathological grade (P = 0.01) and the advanced tumor stage (P = 0.005) at protein level. In TCGA dataset and Taylor Dataset, low-expressed SERPING1 was correlated with the younger patient (P = 0.02 in TCGA, P = 0.044 in Taylor) and the higher Gleason score (P = 0.019 in TCGA, P<0.001 in Taylor) at mRNA level. Kaplan-Meier analysis revealed that the lower mRNA of SERPING1 predicted lower overall survivals (P = 0.027 in TCGA), lower disease-free survival (P = 0.029) and lower biochemical recurrence-free survival (P = 0.011 in Taylor). Data from Oncomine database shown that SERPING1 low expression implying higher malignancy of prostate lesions. Using multivariate analysis, we also found that SERPING1 expression was independent prognostic marker of poor disease-free survival and biochemical recurrence-free survival.Conclusion: SERPING1 may play an important role in PCa and can be serve as a novel marker in diagnosis and prognostic prediction in PCa. In addition, levels of SERPING1 can help identify low-risk prostate to provide reference for patients with PCa to accept active surveillance and reduce overtreatment. [ABSTRACT FROM AUTHOR]

Background: Oligometastatic prostate cancer (OmPCa) is characterized by a restricted number of metastatic lesions confined to a limited organ range, presenting a distinct clinical challenge. The role of cytoreductive prostatectomy (CRP) in managing this specific metastatic stage has gained attention but remains controversial. This study aims to assess the effectiveness of CRP in OmPCa by synthesizing outcomes from previous studies and analyzing data from a multicenter, retrospective cohort., Methods: We focused on evaluating overall survival (OS), progression-free survival (PFS), cancer-specific survival (CSS), and castration-resistant prostate cancer-free survival (CRPCFS) as primary outcomes. A multicenter comparative retrospective analysis was also conducted on OmPCa patients treated with CRP versus those receiving androgen deprivation therapy (ADT) alone from January 2008 to June 2018. We gathered and analyzed data on patient demographics, tumor characteristics, surgical outcomes, and survival metrics., Results: The quantitative analysis included 18 studies(2 randomized controlled trial (RCT) and 16 non-RCT studies),comprising a total of 1733 patients with oligometastatic prostate cancer,this is the largest number of samples included in the same subject research at present.The pooled analysis demonstrated that cytoreductive surgery was associated with significantly improved OS (hazard ratio [HR]: 0.50, 95% confidence interval[CI]: 0.40-0.60) ,PFS (HR: 0.39, 95%[CI]: 0.27-0.51) ,CSS (HR: 0.44, 95%[CI]: 0.23-0.65) and CRPCFS (HR: 0.48, 95%[CI]: 0.36-0.59) compared to non-surgical management.In addition,OS ,PFS and CRPCFS showed better results in the CRP group in all analyses(RCT and non-RCT).Additionally,in our multicenter retrospective research analysis, 64 patients with oligometastatic prostate cancer were included ,32 underwent CRP (50%), and 32 underwent ADT alone (50%).The median follow-up time was 40.1 (18.9-51.3) months.The OS (P=0.0182), PFS (P=0.0297), and CRPCFS (P=0.0125) had statistical difference between the two matched cohorts.Moreover,we observed 8(25%) cases of perioperative complications, with the most common being urinary incontinence(9.4%)., Conclusions: Incorporating CRP alongside ADT in the treatment protocol for OmPCa significantly enhances patient outcomes in terms of OS, PFS, and CRPC-free survival, underscoring the potential benefit of this surgical approach in the specified patient population., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Chronic subdural hematoma (CSDH) is a common neurological disease, and the surgical evacuation of subdural collection remains the primary treatment approach for symptomatic patients. Postoperative recurrence is a serious complication, and several factors are correlated with postoperative recurrence., Methods: We searched Embase, Web of Science, PubMed, and Cochrane Library from their establishment to September 2020. Reports on randomized, prospective, retrospective, and overall observational studies on the management of surgical patients with CSDH were searched, and an independent reviewer performed research quality assessment. Factors that affect the postoperative recurrence of CSDH were extracted: social demographics, drugs (as the main or auxiliary treatment), surgical management, imaging, and other risk factors. We evaluated the recurrence rate of each risk factor. A random effect model was used to perform a meta-analysis, and each risk factor affecting the postoperative recurrence of CSDH was then evaluated and graded., Findings: In total, 402 studies were included in this analysis and 32 potential risk factors were evaluated. Among these, 21 were significantly associated with the postoperative recurrence of CSDH. Three risk factors (male, bilateral hematoma, and no drainage) had convincing evidence. The classification of evidence can help clinicians identify significant risk factors for the postoperative recurrence of CSDH., Interpretation: Only few associations were supported by high-quality evidence. Factors with high-quality evidence may be important for treating and preventing CSDH recurrence. Our results can be used as a basis for improving clinical treatment strategies and designing preventive methods., Funding: No funding was received., Competing Interests: The authors declare no conflicts of interest related to this study., (© 2021 The Authors.)

Objective: To explore the genetic changes in the progression of castration-resistant prostate cancer (CRPC) and neuroendocrine prostate cancer (NEPC) and the reason why these cancers resist existing therapies., Methods: We employed our CRPC cell line microarray and other CRPC or NEPC datasets to screen the target gene NEIL3. Lentiviral transfection and RNA interference were used to construct overexpression and knockdown cell lines. Cell and animal models of radiotherapy were established by using a medical electron linear accelerator. Flow cytometry was used to detect apoptosis or cell cycle progression. Western blot and qPCR were used to detect changes in the protein and RNA levels., Results: TCGA and clinical patient datasets indicated that NEIL3 was downregulated in CRPC and NEPC cell lines, and NEIL3 was correlated with a high Gleason score but a good prognosis. Further functional studies demonstrated that NEIL3 had no effect on the proliferation and migration of PCa cells. However, cell and animal radiotherapy models revealed that NEIL3 could facilitate the radiotherapy sensitivity of PCa cells, while loss of NEIL3 activated radiotherapy resistance. Mechanistically, we found that NEIL3 negatively regulated the expression of ATR, and higher NEIL3 expression repressed the ATR/CHK1 pathway, thus regulating the cell cycle., Conclusions: We demonstrated that NEIL3 may serve as a diagnostic or therapeutic target for therapy-resistant patients., Competing Interests: No potential conflicts of interest are disclosed., (Copyright © 2022 Cancer Biology & Medicine.)