Cooled infrared coaxial four-mirror system design with a low F-number.

A low F-number and 100% cold stop efficiency are beneficial for improving the performance of optical systems and have a wide range of applications in various thermal imaging scenarios. The cooled infrared coaxial four-mirror system can meet these two requirements, improve system integration, and reduce adjustment costs and difficulties. However, the secondary obstruction caused by the central hole of the third mirror will generate potential stray light. A structure model is proposed in which the primary mirror and the quaternary mirror are processed on the same mirror blank. In this model, a method is given to calculate system parameters using the obstruction ratio and magnification of each mirror. To evaluate the performance of the method, two design examples with different F-numbers (1.4, 1.0) were constructed. The influence of initial structural constraints on the exit pupil position and secondary obstruction was analyzed based on the design objectives of the examples. The aberrations were optimized by targeting the spot. In the optimization process, the incident coordinates and directions of the restricted edge field rays in the tertiary mirror and the quaternary mirror were limited to achieve control of the obstruction caused by the holes in the center of the mirrors. In the results, the RMS spot radius of the two design examples is smaller than the Airy disk radius, and the axial beam wavefront deviation RMS values are 0.026λ and 0.024λ, respectively. Moreover, the obstruction caused by the central holes of the mirrors is controlled within the given field of view. The results show that the proposed model and method can be used to design a low F-number cooled infrared coaxial four-mirror system and have good application prospects.

Surgical strategies for patients with second primary non-small cell lung cancer lesions 2 cm or less in diameter.

BACKGROUND AND PURPOSE: The wide application of low-dose computed tomography (CT) has led to an increase in the detection of small lung cancer lesions. Moreover, surgical recommendations for second primary non-small cell lung cancer (NSCLC) lesions ≤ 2 cm are obscure. This study compares the efficacy of wedge resection, lobectomy, and segmentectomy for small second primary NSCLC lesions. METHODS: The cohort was established based on the SEER database. Univariate and multivariate cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, and restricted mean survival time (RMST) values were applied to identify prognostic factors. We used the Kaplan-Meier method to plot the survival curves of the different subgroups according to propensity score matching (PSM) analysis to then compare the therapeutic efficacy of the surgical procedures. RESULTS: A total of 568 patients were enrolled in this study. Age, sex, grade, and lymph node ratio were selected as independent prognostic factors (p < 0.05). No significant differences were observed in survival probabilities among the groups of patients who underwent segmentectomy, wedge resection, or lobectomy (p > 0.05). We also established a nomogram model based on the four prognostic factors to guide clinical treatment. CONCLUSIONS: Based on the findings of our study, segmentectomy was more appropriate than lobectomy for patients with a second primary NSCLC lesion ≤ 2 cm in diameter. The evidence to support other recommendations is insufficient.

Simultaneous detection of multiple exosomal microRNAs for exosome screening based on rolling circle amplification.

Exosomal microRNAs (miRNAs) have attracted great attention as predictive and prognostic biomarkers of cancer. Profiling of miRNAs plays a key role in the effective diagnosis of cancers. However, simultaneous quantification of multiple miRNAs is challenging due to their homology and low abundance especially in exosomes. Here, we developed a sensitive detection method for multiple exosomal miRNAs with the help of rolling circle amplification (RCA). In contrast of the traditional ways, this method takes the advantages of both the multiplex sensing ability and the simplicity of RCA. Specifically, multiple exosomal miRNAs from different cell lines were replicated simultaneously through RCA and detected using designed molecular beacons (MBs). miRNA-21, miRNA-122 and miRNA-155 were chosen as the targets, which are overexpressed in cancers. Normalized fluorescence intensities of MB were used to imply the relative concentrations of these miRNAs. The obtained relative miRNAs expression levels could be used to distinguish the breast cancer exosome from normal one. If the varieties of the detected exosomal miRNAs are abundant enough, the concentration ratios of miRNAs could basically indicate the corresponding exosome and exosome screening could be realized. Such exosomal miRNA profiling and exosome screening can assist cancer diagnosis, which is promising in clinical application.

Predicting occult lymph node metastasis by nomogram in patients with lung adenocarcinoma ≤2 cm.

Background: Previous researches had not proposed any prediction models for occult lymph node metastasis (OLNM). Considering the occurrence of OLNM and the importance of OLNM management, we aimed to develop a nomogram to predict OLNM of patients with lung adenocarcinoma ≤2 cm. Methods: Characteristics of patients with lung adenocarcinoma of ≤2 cm diameter at the Peking Union Medical College Hospital were retrospectively reviewed. Univariate and multivariate logistic regressions were performed. A nomogram model was developed. The concordance index (C-index) and calibration and decision curves were used to evaluate the predictive ability. Results: A total of 473 patients were enrolled, with an OLNM incidence of 7.4%. Four factors were selected as risk factors. The model had a C-index of 0.932. Calibration and decision curves were determined. Conclusion: Patients with pure ground-glass opacity (pGGO) or noninvasive adenocarcinoma have significantly lower risk of OLNM. SUVmax, CEA, micropapillary and solid component were identified as independent risk factors. The nomogram model was effective in predicting OLNM preoperatively.

Lay abstract Lung cancer was once the leading cause of death among tumors. Today, as routine examination has become more common, the incidence of lung cancers ≤2 cm diameter has been increasing. Much research had explored treatment for these patients. Lobectomy and lymph node dissection in particular were recommended. Furthermore, lymph node dissection was strongly recommended for lymph-node-positive patients. During treatment, occult lymph node metastasis (OLNM) had been observed in some cases. And OLNM referred to a postoperative positive pathological result among preoperative imaging-negative cases. The study was designed to establish a model for predicting OLNM. In a cohort of 473 patients, we found certain risk factors for OLNM and established a predictive model. Relevant findings were shown in the 'Conclusion' section.

Quaternary-Ammonium-Modulated Surface-Enhanced Raman Spectroscopy Effect: Discovery, Mechanism, and Application for Highly Sensitive In Vitro Sensing of Acetylcholine.

Quaternary ammonium (QA) plays multiple roles in biological functions, whose dysregulation may result in multiple diseases. However, how to efficiently detect QA-based materials such as acetylcholine (ACh) still remains a great challenge, especially in complex biological environments. Here, a new effect [called quaternary-ammonium-modulated surface-enhanced Raman spectroscopy (QAM-SERS) effect] is discovered, showing that the existence of QA will modulate the intensity of SERS signals in a concentration-dependent manner. When the QAM-SERS effect is used, a new method is easily developed for in vitro detection of ACh with an extremely high sensitivity and an ultrawide dynamic range. Particularly, the linear dynamic range can be freely tuned to adapt for various physiological samples. As a proof-of-concept experiment, the time-dependent secretion of ACh from PC12 cells was successfully monitored using the QAM-SERS method, which were under either the stimulation of potassium ions or the incubation of drugs. The discovery of the QAM-SERS effect provides an easy and universal strategy for detecting ACh as well as other QA-contained molecules, which can also inspire new insights into the roles that QA could play in biology and chemistry.

A SERS-colorimetric dual-mode aptasensor for the detection of cancer biomarker MUC1.

Human mucin-1 (MUC1) has attracted considerable attention owing to its overexpression in diverse malignancies. Here, for the rapid and efficient detection of MUC1, we present a SERS-colorimetric dual-mode aptasensor, by integrating SERS probes with magnetic separation, which has several distinctive advantages. Using such a dual-mode aptasensor, the colorimetric functionality is distinguishable by the naked eye, providing a fast and straightforward screening ability for the detection of MUC1. Moreover, SERS-based detection greatly improves the detection sensitivity, reaching a limit of detection of 0.1 U/mL. In addition, the combination of SERS and colorimetric method holds the advantages of these two techniques and thereby increases the reliability and efficiency of MUC1 detection. On the one hand, the magnetic nanobeads functionalized with MUC1-specific aptamer were utilized as an efficient capturing substrate for separating MUC1 from biological complex medium. On the other hand, the gold-silver core-shell nanoparticles modified with Raman reporters and the complementary sequences of MUC1 were used as the signal indicator, which could simultaneously report the SERS signal and colorimetric change. This strategy can achieve a good detection range and realize MUC1 analysis in real patients' samples. Thus, we anticipate that this kind of aptasensor would provide promising potential applications in the diagnosis and prognosis of cancers. Graphical abstract.

A SERS fiber probe fabricated by layer-by-layer assembly of silver sphere nanoparticles and nanorods with a greatly enhanced sensitivity for remote sensing.

Remote sensing remains a challenge due to its demand for high sensitivity, convenient sampling and rapid response time. Surface enhanced Raman scattering (SERS) spectroscopy is a powerful analytical method for the detection of various samples. Here, aiming at increasing the sensitivity, a novel strategy for the preparation of a SERS probe is demonstrated by using hollow optical fiber tips decorated by layer-by-layer assembly of two kinds of nanoparticles. Specifically, Au@Ag core-shell nanorods and Ag nanospheres with opposite surface charge were assembled layer-by-layer on the tip of hollow optical fibers through electrostatic interaction. Then, much more hotspots are generated due to the close gap between the nanorods and nanospheres in the resultant 3D structure, which can lead to a dramatically enhanced SERS activity of the probe compared with that fabricated by pure silver sphere nanoparticles or nanorods. On the other hand, taking the advantages of the vibration spectroscopic fingerprints property of SERS spectra and the long-distance communication capacity of optical fibers, the remote online detection of biological species including proteins, funguses and cells can be easily achieved within a few minutes. Therefore, such a novel kind of optical fiber-SERS sensor holds great potential for the rapid detection of a wide range of samples due to its superiority of simplicity and high sensitivity.

Mid-frequency MTF compensation of optical sparse aperture system.

Optical sparse aperture (OSA) can greatly improve the spatial resolution of optical system. However, because of its aperture dispersion and sparse, its mid-frequency modulation transfer function (MTF) are significantly lower than that of a single aperture system. The main focus of this paper is on the mid-frequency MTF compensation of the optical sparse aperture system. Firstly, the principle of the mid-frequency MTF decreasing and missing of optical sparse aperture are analyzed. This paper takes the filling factor as a clue. The method of processing the mid-frequency MTF decreasing with large filling factor and method of compensation mid-frequency MTF with small filling factor are given respectively. For the MTF mid-frequency decreasing, the image spatial-variant restoration method is proposed to restore the mid-frequency information in the image; for the mid-frequency MTF missing, two images obtained by two system respectively are fused to compensate the mid-frequency information in optical sparse aperture image. The feasibility of the two method are analyzed in this paper. The numerical simulation of the system and algorithm of the two cases are presented using Zemax and Matlab. The results demonstrate that by these two methods the mid-frequency MTF of OSA system can be compensated effectively.

Microfluidic chip based micro RNA detection through the combination of fluorescence and surface enhanced Raman scattering techniques.

We present a novel microfluidic chip based method for the detection of micro RNA (miRNA) via the combination of fluorescence and surface enhanced Raman scattering (SERS) spectroscopies. First, silver nanoparticles (Ag NPs) are immobilized onto a glass slide, forming a SERS enhancing substrate. Then a specificially designed molecular beacon (MB) is attached to the SERS substrate. The 3' end of the MB is decorated with a thiol group to facilitate the attachment of the MB, while the 5' end of the MB is labeled with an organic dye 6-FAM, which is used both as the fluorophore and SERS reporter. In the absence of target miRNA, the MB will form a hairpin structure, making 6-FAM close to the Ag NPs. Hence, the fluorescence of 6-FAM will be quenched and the Raman signal of 6-FAM will be enhanced. On the contrary, with target miRNA present, hybridization between the miRNA and MB will unfold the MB and increase the distance between 6-FAM and the Ag NPs. Thus the fluorescence of 6-FAM will recover and the SERS signal of 6-FAM will decrease. So the target miRNA will simultaneously introduce opposite changing trends in the intensities of the fluorescence and SERS signals. By combining the opposite changes in the two optical spectra, an improved sensitivity and linearity toward the target miRNA is achieved as compared with using solely fluorescence or SERS. Moreover, introducing the microfluidic chip can reduce the reaction time, reagent dosage and complexity of detection. With the improved sensitivity and simplicity, we anticipate that the presented method can have great potential in the investigation of miRNA related diseases.

Context-aware SAR image ship detection and recognition network.

With the development of deep learning, synthetic aperture radar (SAR) ship detection and recognition based on deep learning have gained widespread application and advancement. However, there are still challenging issues, manifesting in two primary facets: firstly, the imaging mechanism of SAR results in significant noise interference, making it difficult to separate background noise from ship target features in complex backgrounds such as ports and urban areas; secondly, the heterogeneous scales of ship target features result in the susceptibility of smaller targets to information loss, rendering them elusive to detection. In this article, we propose a context-aware one-stage ship detection network that exhibits heightened sensitivity to scale variations and robust resistance to noise interference. Then we introduce a Local feature refinement module (LFRM), which utilizes multiple receptive fields of different sizes to extract local multi-scale information, followed by a two-branch channel-wise attention approach to obtain local cross-channel interactions. To minimize the effect of a complex background on the target, we design the global context aggregation module (GCAM) to enhance the feature representation of the target and suppress the interference of noise by acquiring long-range dependencies. Finally, we validate the effectiveness of our method on three publicly available SAR ship detection datasets, SAR-Ship-Dataset, high-resolution SAR images dataset (HRSID), and SAR ship detection dataset (SSDD). The experimental results show that our method is more competitive, with AP50s of 96.3, 93.3, and 96.2% on the three publicly available datasets, respectively.

Performance evaluation of influenza a rapid antigen test and PCR among nasopharyngeal and oropharyngeal samples.

Objectives: Rapid antigen test (RAT) and polymerase chain reaction (PCR) using nasopharyngeal (NP) or oropharyngeal (OP) swab specimens are the two main testing techniques used for laboratory diagnosis of influenza in clinical practice. However, performance variations have been observed not only between techniques, but also between different specimens. This study evaluated the differences in performance between specimens and testing techniques to identify the best combination in clinical practice. Methods: Both NP and OP samples from suspected influenza patients collected in the 2023/4-2023/5 Flu-season in Xiamen, China, were tested for RAT and quantitative PCR. The testing performance of the different specimens and testing techniques were recorded and evaluated. Results: Compared to PCR, RAT showed 58.9 % and 10.3 % sensitivity for NP and OP swabs, respectively. The Limit of Detection (LoD) was 28.71 the Median Tissue Culture Infectious Dose (TCID50)/mL. Compared with PCR using NP swabs, PCR with OP swabs showed 89.5 % sensitivity and 95.4 % specificity. Conclusions: There were no significant differences in performance between the specimens when PCR was used to test for influenza. However, a decrease in sensitivity was observed when the RAT was used, regardless of the specimen type. Therefore, to avoid false-negative results, PCR may be a better choice when OP swabs are used as specimens. In contrast, NP swabs should be the recommended specimens for RAT.

Single-Cell Profiling Comparisons of Tumor Microenvironment between Primary Advanced Lung Adenocarcinomas and Brain Metastases and Machine Learning Algorithms in Predicting Immunotherapeutic Responses.

Brain metastasis (BM) occurs commonly in patients with lung adenocarcinomas. Limited evidence indicates safety and efficacy of immunotherapy for this metastatic tumor, though immune checkpoint blockade has become the front-line treatment for primary advanced non-small cell lung cancer. We aim to comprehensively compare tumor microenvironments (TME) between primary tumors (PT) and BM at single-cell resolution. Single-cell RNA transcriptomics from tumor samples of PT (N = 23) and BM (N = 16) and bulk sequencing data were analyzed to explore potential differences in immunotherapeutic efficacy between PT and BM of lung adenocarcinomas. Multiple machine learning algorithms were used to develop and validate models that predict responses to immunotherapy using the external cohorts. We found obviously less infiltration of immune cells in BM than PT, characterized specifically by deletion of anti-cancer CD8+ Trm cells and more dysfunctional CD8+ Tem cells in BM tumors. Meanwhile, macrophages and dendritic cells within BM demonstrated more pro-tumoral and anti-inflammatory effects, represented by distinct distribution and function of SPP1+ and C1Qs+ tumor-associated microphages, and inhibited antigen presentation capacity and HLA-I gene expression, respectively. Besides, we also found the lack of inflammatory-like CAFs and enrichment of pericytes within BM tumors, which may be critical factors in shaping inhibitory TME. Cell communication analysis further revealed mechanisms of the immunosuppressive effects associated with the activation of some unfavorable pathways, such as TGFß signaling, highlighting the important roles of stromal cells in the anti-inflammatory microenvironment, especially specific pericytes. Furthermore, pericyte-related genes were identified to optimally predict immunotherapeutic responses by machine learning models with great predictive performance. Overall, various factors contribute to the immunosuppressive TME within BM tumors, represented by the lack of critical anti-cancer immune cells. Meanwhile, pericytes may help shape the TME and targeting the associated mechanisms may enhance immunotherapy efficacy for BM tumors in patients with lung adenocarcinomas.

Nonstationary feature extraction based on stochastic resonance and its application in rolling bearing fault diagnosis under strong noise background.

When the load and speed of rotating machinery change, the vibration signal of rolling bearing presents an obvious nonstationary characteristic. Stochastic resonance (SR) mainly is convenient to analyze the stationary feature of vibration signals with high signal-to-noise ratio. However, it is difficult for SR to extract the nonstationary feature of rolling bearings under strong noise background. For one thing, the frequency change of nonstationary signals makes the occurrence of SR very difficult. For another, the features of rolling bearings are large parameters and further prevent the SR method from performing well. Therefore, combined with order analysis (OA), adaptive frequency-shift SR is presented in this paper. To solve the problem of frequency change, OA is used to convert the nonstationary feature into stationary feature, which resamples the nonstationary signal in the time domain to stationary signal in the angular domain. To solve the other problem, the frequency-shift method based on Fourier transform is adopted to move the fault feature frequency to low frequency, and thus SR is more likely to occur under small parameter conditions. The simulated and experimental results indicate that not only the amplitude of fault feature but also the signal-to-noise ratio is significantly improved. These demonstrate that the fault features of rolling bearing in variable speed conditions are extracted successfully.

Homologous recombination deficiency in triple-negative breast cancer: Multi-scale transcriptomics reveals distinct tumor microenvironments and limitations in predicting immunotherapy response.

BACKGROUND: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and has the highest proportion of homologous recombination deficiency (HRD). HRD has been considered a biomarker of response to immune checkpoint inhibitors (ICIs), but the reality is more complicated. A comprehensive comparison of the tumor microenvironment (TME) in HRD and non-HRD TNBC samples may be helpful. METHODS: Datasets from single-cell, spatial, and bulk RNA-sequencing were collected to explore the role of HRD in the development of TME at multiple scales. Based on the findings in the TME, machine learning algorithms were used to construct a response prediction model in eleven ICI therapy cohorts. RESULTS: A more exhausted phenotype of T cells and a more tolerogenic phenotype of dendritic cells were found in the non-HRD group. HRD reprograms the predominant phenotype of cancer-associated fibroblasts (CAFs) from myofibroblastic CAFs to inflammatory-like CAFs. As interactions between myofibroblastic CAFs and other cells, DPP4-chemokines associated with reduced immune cell recruitment were unique in the non-HRD group. The prediction model based on DPP4-related genes had acceptable performance in predicting response, prognosis, and immune cell content. Higher HRD scores in bulk RNA-sequencing samples indicated more activated immune cell function, but not higher immune cell content, which may be affected by factors such as antigen-presenting capacity. CONCLUSIONS: Based on multi-scale transcriptomics, our findings comprehensively reveal differences in the TME between HRD and non-HRD samples. Combining HRD with the prediction model or other methods for assessing immune cell content, may better predict response to ICIs in TNBC.

Exploration of potential novel drug targets and biomarkers for small cell lung cancer by plasma proteome screening.

Background: Small cell lung cancer (SCLC) is characterized by extreme invasiveness and lethality. There have been very few developments in its diagnosis and treatment over the past decades. It is urgently needed to explore potential novel biomarkers and drug targets for SCLC. Methods: Two-sample Mendelian Randomization (MR) was performed to investigate causal associations between SCLC and plasma proteins using genome-wide association studies (GWAS) summary statistics of SCLC from Transdisciplinary Research Into Cancer of the Lung Consortium (nCase = 2,791 vs. nControl = 20,580), and was validated in another cohort (nCase = 2,664 vs. nControl = 21,444). 734 plasma proteins and their genetic instruments of cis-acting protein quantitative trait loci (pQTL) were used, whereas external plasma proteome data was retrieved from deCODE database. Bidirectional MR, Steiger filtering and phenotype scanning were applied to further verify the associations. Results: Seven significant (p < 6.81 × 10-5) plasma protein-SCLC pairs were identified by MR analysis, including ACP5 (OR = 0.76, 95% CI: 0.67-0.86), CPB2 (OR = 0.90, 95% CI: 0.86-0.95), GSTM3 (OR = 0.45, 95% CI: 0.33-0.63), SHMT1 (OR = 0.74, 95% CI: 0.64-0.86), CTSB (OR = 0.79, 95% CI: 0.71-0.88), NTNG1 (OR = 0.81, 95% CI: 0.74-0.90) and FAM171B (OR = 1.40, 95% CI: 1.21-1.62). The external validation confirmed that CPB2, GSTM3 and NTNG1 had protective effects against SCLC, while FAM171B increased SCLC risk. However, the reverse causality analysis revealed that SCLC caused significant changes in plasma levels of most of these proteins, including decreases of ACP5, CPB2, GSTM3 and NTNG1, and the increase of FAM171B. Conclusion: This integrative analysis firstly suggested the causal associations between SCLC and plasma proteins, and the identified several proteins may be promising novel drug targets or biomarkers for SCLC.

Multifaceted roles of WRKY transcription factors in abiotic stress and flavonoid biosynthesis.

Increasing biotic and abiotic stresses are seriously impeding the growth and yield of staple crops and threatening global food security. As one of the largest classes of regulators in vascular plants, WRKY transcription factors play critical roles governing flavonoid biosynthesis during stress responses. By binding major W-box cis-elements (TGACCA/T) in target promoters, WRKYs modulate diverse signaling pathways. In this review, we optimized existing WRKY phylogenetic trees by incorporating additional plant species with WRKY proteins implicated in stress tolerance and flavonoid regulation. Based on the improved frameworks and documented results, we aim to deduce unifying themes of distinct WRKY subfamilies governing specific stress responses and flavonoid metabolism. These analyses will generate experimentally testable hypotheses regarding the putative functions of uncharacterized WRKY homologs in tuning flavonoid accumulation to enhance stress resilience.

Band Gap and Defect Engineering Enhanced Scintillation from Ce3+-Doped Nanoglass Containing Mixed-Type Fluoride Nanocrystals.

Much can be learned from the research and development of scintillator crystals for improving the scintillation performance of glasses. Relying on the concept of "embedding crystalline order in glass", we have demonstrated that the scintillation properties of Ce3+-doped nanoglass composites (nano-GCs) can be optimized via the synergistic effects of Gd3+-sublattice sensitization and band-gap engineering. The nano-GCs host a large volume fraction of KYxGd1-xF4 mixed-type fluoride nanocrystals (NCs) and still retain reasonably good transparency at Ce3+-emitting wavelengths. The light yield of 3455 ± 20 ph/MeV is found, which is the largest value ever reported in fluoride NC-embedded nano-GCs. A comprehensive study is given on the highly selective doping of Ce3+ in the NCs and its positive effect on the scintillation properties. The favorable influence of the Y3+/Gd3+ mixing on the suppression of defects is accounted for by density functional theory and borne out experimentally. As a proof-of-concept, X-ray imaging with a good spatial resolution (7.9 lp/mm) is demonstrated by employing Ce3+-doped nano-GCs. The superior radiation hardness, repeatability, and thermal stability of the designed scintillators bode well for their long-term practical applications.

Optical distortion evaluation of an aerodynamically heated window, based on the higher-order singular value decomposition with the influence of elasto-optical effect excluded.

The higher-order singular value decomposition (HOSVD) was used to reconstruct the three-dimensional (3D) refractive index field of an aerodynamically heated window. The numerical 3D optical distortion was evaluated for both the reconstructed and the exact refractive index fields of the window, excluding the influence of the elasto-optical effect. The method based on the HOSVD truncation was shown to reduce the refractive index information required to capture the major optical distortion of the window. The refractive index information was reduced by reconstructing the refractive index field of the window using the truncated n-mode singular matrices. The method can also be used to evaluate the optical distortion of the window.

Improved infrared target-tracking algorithm based on mean shift.

An improved IR target-tracking algorithm based on mean shift is proposed herein, which combines the mean-shift-based gradient-matched searching strategy with a feature-classification-based tracking algorithm. An improved target representation model is constructed by considering the likelihood ratio of the gray-level features of the target and local background as a weighted value of the original kernel histogram of the target region. An expression for the mean-shift vector in this model is derived, and a criterion for updating the model is presented. Experimental results show that the algorithm improves the shift weight of the target pixel gray level and suppresses background disturbance.

Incidence, mortality, and survival analyses of patients with thymic lymphoma.

Objectives: To explore the clinical and prognostic characteristics of thymic lymphoma and the effects of current treatments on the prognosis. Methods: Patients diagnosed as primary thymic lymphoma between 1975 and 2018 from the nine states of the US were identified, including Atlanta, Connecticut, Detroit, Hawaii, Iowa, New Mexico, San Francisco-Oakland, Seattle-Puget Sound, and Utah. Incidence and mortality rates were analyzed using SEER*Stat 8.3.9 software. Univariate and multivariate Cox regressions were performed to identify prognostic factors. The Kaplan-Meier curve and log-rank test were used to compare overall survival (OS) among different treatments. Results: A total of 233 patients diagnosed as thymic lymphoma were identified, and eight of them were lost to follow-up or died upon diagnosis. The incidence of thymic lymphoma was 2.032 per ten million (95% CI: 1.777-2.312), and the mortality rate was 0.649 per ten million (95% CI: 0.508-0.817). Among the 225 patients with definite follow-up, 98 were males and 127 were females, with a median age of 33 years. The Cox regression results showed that age and pathological type were independent risk prognostic factors. The 5-, 10-, and 20-year OS were 80.0%, 77.5%, and 70.9%, respectively. For Ann Arbor stage I and II patients, there was no significant difference between the surgical group (N = 78) and the non-operative group (N = 65; P = 0.270). The radiotherapy group (N = 79) had better OS than the non-radiotherapy group (N = 64) in the first 25 years, and the prognosis in the later years was not significantly different (P = 0.051). The chemotherapy group (N = 37) had a significantly better prognosis than the non-chemotherapy group (N = 37; P = 0.020). Patients who received postoperative radiotherapy (N = 45) or who only received radiotherapy (N = 34) seemed to have better OS than that of patients who only received surgery (N = 33), although the difference was not significant (P = 0.063). Conclusions: Age and pathological type were independent prognostic factors for thymic lymphoma. Surgical treatment had limited effects on OS, while both radiotherapy and chemotherapy could significantly improve the survival outcome.