Decoding Bilingual EEG Signals With Complex Semantics Using Adaptive Graph Attention Convolutional Network.

Decoding neural signals of silent reading with Brain-Computer Interface (BCI) techniques presents a fast and intuitive communication method for severely aphasia patients. Electroencephalogram (EEG) acquisition is convenient and easily wearable with high temporal resolution. However, existing EEG-based decoding units primarily concentrate on individual words due to their low signal-to-noise ratio, rendering them insufficient for facilitating daily communication. Decoding at the word level is less efficient than decoding at the phrase or sentence level. Furthermore, with the popularity of multilingualism, decoding EEG signals with complex semantics under multiple languages is highly urgent and necessary. To the best of our knowledge, there is currently no research on decoding EEG signals during silent reading of complex semantics, let alone decoding silent reading EEG signals with complex semantics for bilingualism. Moreover, the feasibility of decoding such signals remains to be investigated. In this work, we collect silent reading EEG signals of 9 English Phrases (EP), 7 English Sentences (ES), 10 Chinese Phrases (CP), and 7 Chinese Sentences (CS) from the subject within 26 days. We propose a novel Adaptive Graph Attention Convolution Network (AGACN) for classification. Experimental results demonstrate that our proposed method outperforms state-of-the-art methods, achieving the highest classification accuracy of 54.70%, 62.26%, 44.55%, and 57.14% for silent reading EEG signals of EP, ES, CP, and CS, respectively. Moreover, our results prove the feasibility of complex semantics EEG signal decoding. This work will aid aphasic patients in achieving regular communication while providing novel ideas for neural signal decoding research.

PD-L1 expression in recurrent or metastatic head and neck squamous cell carcinoma in China (EXCEED study): a multicentre retrospective study.

AIMS: Programmed death-ligand 1 (PD-L1) is known to be highly expressed in various malignancies, including head and neck squamous cell carcinoma (HNSCC). We aimed to determine the prevalence of PD-L1 expression in recurrent or metastatic HNSCC (R/M HNSCC) among Chinese patients. METHODS: This multicentre, retrospective analysis of data from six centres in China included patients with R/M HNSCC treated from 9 August 2021 to 28 February 2022. PD-L1 expression in tumour tissue was assessed and represented using a combined positive score (CPS). The χ2 and Cochran-Mantel-Haenszel χ2 tests were used to compare the prevalence of different PD-L1 expression statuses according to related co-variables. RESULTS: For all 402 examined patients with R/M HNSCC, 168 cases (41.8%) had PD-L1 expression with a CPS ≥20, and 337 cases (83.8%) had PD-L1 expression with a CPS ≥1. Between the PD-L1 CPS ≥20 group and PD-L1 CPS <20 group, statistically significant differences were observed for variables of sex (p<0.001), smoking habit (p=0.0138 for non-smokers vs current smokers) and primary tumour site (p<0.001 for hypopharynx vs oral cavity and p=0.0304 for larynx vs oral cavity, respectively). CONCLUSION: PD-L1 with CPS ≥20 was expressed in about 41.8% of cases with R/M HNSCC among Chinese patients, and PD-L1 expression was significantly associated with sex, smoking history and primary tumour site. Our findings regarding the variables related to PD-L1 expression level provide insight for clinical practice and a solid basis for future research on immunotherapy in HNSCC. TRIAL REGISTRATION NUMBER: ISRCTN10570964.

A Survey of Deep Learning-Based Low-Light Image Enhancement.

Images captured under poor lighting conditions often suffer from low brightness, low contrast, color distortion, and noise. The function of low-light image enhancement is to improve the visual effect of such images for subsequent processing. Recently, deep learning has been used more and more widely in image processing with the development of artificial intelligence technology, and we provide a comprehensive review of the field of low-light image enhancement in terms of network structure, training data, and evaluation metrics. In this paper, we systematically introduce low-light image enhancement based on deep learning in four aspects. First, we introduce the related methods of low-light image enhancement based on deep learning. We then describe the low-light image quality evaluation methods, organize the low-light image dataset, and finally compare and analyze the advantages and disadvantages of the related methods and give an outlook on the future development direction.

Using machine learning to realize genetic site screening and genomic prediction of productive traits in pigs.

Genomic prediction, which is based on solving linear mixed-model (LMM) equations, is the most popular method for predicting breeding values or phenotypic performance for economic traits in livestock. With the need to further improve the performance of genomic prediction, nonlinear methods have been considered as an alternative and promising approach. The excellent ability to predict phenotypes in animal husbandry has been demonstrated by machine learning (ML) approaches, which have been rapidly developed. To investigate the feasibility and reliability of implementing genomic prediction using nonlinear models, the performances of genomic predictions for pig productive traits using the linear genomic selection model and nonlinear machine learning models were compared. Then, to reduce the high-dimensional features of genome sequence data, different machine learning algorithms, including the random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost) and convolutional neural network (CNN) algorithms, were used to perform genomic feature selection as well as genomic prediction on reduced feature genome data. All of the analyses were processed on two real pig datasets: the published PIC pig dataset and a dataset comprising data from a national pig nucleus herd in Chifeng, North China. Overall, the accuracies of predicted phenotypic performance for traits T1, T2, T3 and T5 in the PIC dataset and average daily gain (ADG) in the Chifeng dataset were higher using the ML methods than the LMM method, while those for trait T4 in the PIC dataset and total number of piglets born (TNB) in the Chifeng dataset were slightly lower using the ML methods than the LMM method. Among all the different ML algorithms, SVM was the most appropriate for genomic prediction. For the genomic feature selection experiment, the most stable and most accurate results across different algorithms were achieved using XGBoost in combination with the SVM algorithm. Through feature selection, the number of genomic markers can be reduced to 1 in 20, while the predictive performance on some traits can even be improved compared to using the full genome data. Finally, we developed a new tool that can be used to execute combined XGBoost and SVM algorithms to realize genomic feature selection and phenotypic prediction.

Identification of nine mutant genes and establishment of three prediction models of organ tropism metastases of non-small cell lung cancer.

BACKGROUND: Most Non-small cell lung cancer (NSCLC) patients tend to have metastases at the initial diagnosis. However, limited knowledge has been established regarding which factors, are associated with its metastases. This study aims to identify more biomarkers associated with its organ tropism metastasis and to establish models for prediction of its metastatic organs. METHODS: We performed targeted next-generation sequencing (NGS) to detect genes related to lung cancer in 272 patients with primary advanced NSCLC from Northeast China. We adopted Fisher test, multivariate logistic regression analysis to identify metastasis-related gene mutations and to establish prediction models. RESULTS: Mutations of EGFR (p = 0.0003, OR = 2.554) (especially EGFR L858R [p = 0.02, OR = 2.009]), ATM (p = 0.008, OR = 11.032), and JAK2 (p = 0.009, OR = Inf) were positively and of TP53 exon4mut (p = 0.001, OR = 0.173) was negatively correlated with lung metastasis, and those of CSF1R (p = 0.01, OR = Inf), KIT (p = 0.03, OR = 4.746), MYC (p = 0.05, OR = 7.938), and ERBB2 (p = 0.02, OR = 2.666) were positively correlated with pleural dissemination; those of TP53 (p = 0.01, OR = 0.417) was negatively, while of SMAD4 (p = 0.03, OR = 4.957) was positively correlated with brain metastasis of NSCLC. Additionally, smoking history (p = 0.004, OR = 0.004) was negatively correlated with pleural dissemination of NSCLC. Furthermore, models for prediction of lung metastasis (AUC = 0.706), pleural dissemination (AUC = 0.651), and brane metastasis (AUC = 0.629) were established. CONCLUSION: Taken together, this study revealed nine mutant genes and smoking history associated with organ tropism metastases of NSCLC and provided three models for the prediction of metastatic organs. This study enables us to predict the organs to which non-small cell lung cancer metastasizes before it does develop.

Impacts of additive, dominance, and inbreeding depression effects on genomic evaluation by combining two SNP chips in Canadian Yorkshire pigs bred in China.

BACKGROUND: At the beginning of genomic selection, some Chinese companies genotyped pigs with different single nucleotide polymorphism (SNP) arrays. The obtained genomic data are then combined and to do this, several imputation strategies have been developed. Usually, only additive genetic effects are considered in genetic evaluations. However, dominance effects that may be important for some traits can be fitted in a mixed linear model as either 'classical' or 'genotypic' dominance effects. Their influence on genomic evaluation has rarely been studied. Thus, the objectives of this study were to use a dataset from Canadian Yorkshire pigs to (1) compare different strategies to combine data from two SNP arrays (Affymetrix 55K and Illumina 42K) and identify the most appropriate strategy for genomic evaluation and (2) evaluate the impact of dominance effects (classical' and 'genotypic') and inbreeding depression effects on genomic predictive abilities for average daily gain (ADG), backfat thickness (BF), loin muscle depth (LMD), days to 100 kg (AGE100), and the total number of piglets born (TNB) at first parity. RESULTS: The reliabilities obtained with the additive genomic models showed that the strategy used to combine data from two SNP arrays had little impact on genomic evaluations. Models with classical or genotypic dominance effect showed similar predictive abilities for all traits. For ADG, BF, LMD, and AGE100, dominance effects accounted for a small proportion (2 to 11%) of the total genetic variance, whereas for TNB, dominance effects accounted for 11 to 20%. For all traits, the predictive abilities of the models increased significantly when genomic inbreeding depression effects were included in the model. However, the inclusion of dominance effects did not change the predictive ability for any trait except for TNB. CONCLUSIONS: Our study shows that it is feasible to combine data from different SNP arrays for genomic evaluation, and that all combination methods result in similar accuracies. Regardless of how dominance effects are fitted in the genomic model, there is no impact on genetic evaluation. Models including inbreeding depression effects outperform a model with only additive effects, even if the trait is not strongly affected by dominant genes.

Analysis of risk factors associated with endoscopic retrograde cholangiopancreatography for patients with liver cirrhosis: a multicenter, retrospective, clinical study.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is the endoscopic modality of choice for the treatment of biliary and pancreatic diseases. However, patients with cirrhosis, particularly those with decompensated cirrhosis, are believed to be at increased risk for complications associated with ERCP. There is a paucity of literature describing the outcomes of ERCP for patients with cirrhosis. This study aimed to investigate the outcomes of ERCP for cirrhosis patients, especially adverse events, and evaluated its safety and efficacy. METHODS: We performed a multicenter, retrospective study of all patients at Beijing Friendship Hospital affiliated to Capital Medical University, Xijing Hospital affiliated to Air Force Military Medical University, Beijing Youan Hospital affiliated to Capital Medical University, and the Fifth Medical Center of the People's Liberation Army General Hospital from June 2003 to August 2019. The adverse events of inpatient ERCP for patients with ( n  = 182) and without liver cirrhosis (controls; n  = 385) were compared. RESULTS: A total of 567 patients underwent ERCP between January 2003 and December 2019 were enrolled in this study. Compared to patients without cirrhosis, patients with cirrhosis were at higher risk for postoperative complications (odds ratio [OR], 4.172; 95% confidence interval [CI], 1.232-7.031; P  < 0.001) such as postoperative pancreatitis (OR, 2.026; 95% CI, 1.002-4.378; P  = 0.001) and cholangitis (OR, 3.903; 95% CI, 1.001-10.038; P  = 0.036). The main indications for ERCP for patients with cirrhosis in this study included choledocholithiasis (101 cases; 55.5%), benign bile duct strictures (46 cases; 25.3%), and malignant bile duct strictures (28 cases; 15.4%). Among them, 23 patients (12.6%) underwent balloon dilation and 79 patients (43.4%) underwent sphincterotomy. Of the patients with cirrhosis, delayed bleeding occurred in ten patients (5.5%), postoperative pancreatitis occurred in 80 patients (44.0%), and postoperative cholangitis occurred in 25 patients (13.7%). An additional multivariate analysis showed that the total bilirubin (TBIL) level (OR, 4.58; 95% CI, 2.37-6.70) and Child-Pugh score of C (OR, 3.11; 95% CI, 1.04-5.37) were risk factors for postoperative complications in patients with cirrhosis. CONCLUSIONS: Compared with the general population of patients undergoing ERCP, patients with cirrhosis were more prone to postoperative pancreatitis and cholangitis. TBIL levels and Child-Pugh scores were risk factors for postoperative complications in patients with cirrhosis.

Genomic evaluation and genome-wide association studies for total number of teats in a combined American and Danish Yorkshire pig populations selected in China.

Joint genomic evaluation by combining data recordings and genomic information from different pig herds and populations is of interest for pig breeding companies because the efficiency of genomic selection (GS) could be further improved. In this work, an efficient strategy of joint genomic evaluation combining data from multiple pig populations is investigated. Total teat number (TTN), a trait that is equally recorded on 13,060 American Yorkshire (AY) populations (~14.68 teats) and 10,060 Danish Yorkshire (DY) pigs (~14.29 teats), was used to explore the feasibility and accuracy of GS combining datasets from different populations. We first estimated the genetic correlation (rg) of TTN between AY and DY pig populations (rg = 0.79, se = 0.23). Then we employed the genome-wide association study to identify quantitative trait locus (QTL) regions that are significantly associated with TTN and investigate the genetic architecture of TTN in different populations. Our results suggested that the genomic regions controlling TTN are slightly different in the two Yorkshire populations, where the candidate QTL regions were on SSC 7 and SSC 8 for the AY population and on SSC 7 for the DY population. Finally, we explored an optimal way of genomic prediction for TTN via three different genomic best linear unbiased prediction models and we concluded that when TTN across populations are regarded as different, but correlated, traits in a multitrait model, predictive abilities for both Yorkshire populations improve. As a conclusion, joint genomic evaluation for target traits in multiple pig populations is feasible in practice and more accurate, provided a proper model is used.

This study aimed at investigating joint genomic evaluation by combining data from multiple pig populations. Genomic evaluation is commonly applied in the pig industry to select the best animals to be the parents for the next generation. A bottleneck of genomic evaluation is that the selection accuracy is not high enough. To increase the selection accuracy, in theory, larger datasets are needed. In this article, multiple pig populations were considered together and we explored the feasibility and accuracy of genomic evaluation combining datasets from different populations. To realize the objective, total teat number (TTN), a trait that is equally recorded across different populations, was chosen. We first estimated the genetic correlation of TTN between American and Danish Yorkshire pig populations. Then to interpret why such genetic correlation was obtained, we employed the genome-wide association study to identify quantitative trait locus regions that are significantly associated with TTN and investigated the genetic architecture of TTN in different populations. Finally, we explored an optimal way of genomic prediction for TTN via three different genomic models and we concluded that when TTN across populations are regarded as different, but correlated, traits in a multitrait model, predictive abilities for both Yorkshire populations improve.

Molecular and clinical characteristics of IDH mutations in Chinese NSCLC patients and potential treatment strategies.

BACKGROUND: Isocitrate dehydrogenase (IDH) is an appealing target for anticancer therapy, and IDH (IDH1/2) inhibitors have been approved for targeted therapy of acute myeloid leukemia (AML) and Cholangiocarcinoma. The therapeutic potential of IDH inhibitors for non-small-cell lung cancer (NSCLC) patients is under active clinical investigation. Thus, it would be necessary and meaningful to study the molecular and clinical characteristics of IDH mutation in NSCLC patients, especially in the Chinese population. METHODS: A total of 17,978 Chinese patients with NSCLC who underwent next -generation sequencing (NGS) testing were retrospectively reviewed. RESULTS: We identified 161 unique IDH mutations in 361 of 17,978 patients (2.01%). Common active-site mutations, including IDH1R100 , IDH1R132 , IDH2R140 , and IDH2R172 , were detected in 154 patients (0.86%) and were associated with male sex (p = 0.004) and older age (p = 0.02). The IDH mutation spectra observed in NSCLC were quite different from those in glioma or AML. Patients with IDH active-site mutations exhibited significantly higher coalterations in KRAS (p. G12/13/61, 22.1% vs. 8.2%, p < 0.001) or BRAF (p. V600E, 6.5% vs. 1.0%, p < 0.001), but significantly lower coalterations in activating EGFR (e18-e20, 22.7 vs. 37.9%, p < 0.001) than IDH wild-type patients. Furthermore, we found that active-site IDH mutations were correlated with a short PFS (2-5.6 months) and short OS (2-9.5 months), which may arise as a resistance mechanism against common targeted drugs. In vitro, we experimentally observed that the combination of an IDH inhibitor and EGFR TKI could better inhibit lung cancer cell proliferation than an EGFR TKI alone. CONCLUSIONS: Taken together, this study reveals the molecular and clinical characteristics of IDH mutations in Chinese NSCLC patients and provides a theoretical basis for IDH-directed treatment. The potential of IDH mutations as response markers for targeted therapy warrants further investigation.

Expression of heat-resistant ß-glucosidase in Escherichia coli and its application in the production of gardenia blue.

Gardenia blue is a natural blue pigment that is environmentally friendly, non-toxic, and stable. The hydrolysis of geniposide, catalyzed by ß-glucosidase, is a critical step in the production process of gardenia blue. However, ß-glucosidase is not resistant to high temperatures, limiting the production of gardenia blue. In this study, we investigated the effectiveness of a heat-resistant glucosidase obtained from Thermotoga maritima in the production of gardenia blue. The enzyme exhibited a maximum activity of 10.60 U/mL at 90 °C. Single-factor and orthogonal analyses showed that exogenously expressed heat-resistant glucosidase reacted with 470.3 µg/mL geniposide and 13.5 µg/mL glycine at 94.2 °C, producing a maximum yield of 26.2857 µg/mL of gardenia blue after 156.6 min. When applied to the dyeing of denim, gardenia blue produced by this method yielded excellent results; the best color-fastness was achieved when an iron ion mordant was used. This study revealed the feasibility and application potential of microbial production of gardenia blue.

Difficult endoscopic resection of a giant esophageal fibrovascular polyp: case report and literature review.

Esophageal fibrovascular polyp is rare in esophageal neoplasms and usually very large. Here, we present a case of giant esophageal fibrovascular polyp. The patient had dysphagia and choking sensation at presentation. She underwent positron emission-computed tomography (PET-CT), endoscopy, endoscopic ultrasonography, and fine needle aspiration. She was clinically diagnosed as having an esophageal benign tumor and underwent endoscopic submucosal dissection. The polyp was successfully resected; however, the process was very difficult, and the lesion was too large to pass through the upper esophagus. Finally, we removed the lesion surgically. Fibrovascular polyps are often large, and if endoscopic resection is chosen, it is necessary to consider the difficulties that may be encountered during resection, before initiating treatment.

Esophagomediastinal fistula due to secondary esophageal tuberculosis: report of two cases.

Esophageal tuberculosis is rare among digestive system diseases. We herein present two cases of esophageal tuberculosis. One patient presented with a choking sensation and pain in the chest, and the other presented with loss of appetite and emaciation. Both patients had an esophagomediastinal fistula, underwent endoscopic ultrasonography and fine-needle aspiration, were clinically diagnosed with esophageal tuberculosis, received antituberculosis treatment, and exhibited clinical improvement. These two rare cases suggest that the possibility of esophageal tuberculosis should be considered in patients with an esophagomediastinal fistula. Endoscopic ultrasonography and fine-needle aspiration can be performed to assist the diagnosis. Good clinical results can often be achieved with timely antituberculosis treatment.

Targeting the Proteasome in Advanced Renal Cell Carcinoma: Complexity and Limitations of Patient-Individualized Preclinical Drug Discovery.

BACKGROUND: Systemic treatment options for metastatic renal cell carcinoma (RCC) have significantly expanded in recent years. However, patients refractory to tyrosine kinase and immune checkpoint inhibitors still have limited treatment options and patient-individualized approaches are largely missing. PATIENTS AND METHODS: In vitro drug screening of tumor-derived short-term cultures obtained from seven patients with clear cell RCC was performed. For one patient, a patient-derived xenograft (PDX) mouse model was established for in vivo validation experiments. Drug effects were further investigated in established RCC cell lines. RESULTS: The proteasome inhibitor carfilzomib was among the top hits identified in three of four patients in which an in vitro drug screening could be performed successfully. Carfilzomib also showed significant acute and long-term cytotoxicity in established RCC cell lines. The in vivo antitumoral activity of carfilzomib was confirmed in a same-patient PDX model. The cytotoxicity of carfilzomib was found to correlate with the level of accumulation of ubiquitinated proteins. CONCLUSIONS: In this proof-of-concept study, we show that patient-individualized in vitro drug screening and preclinical validation is feasible. However, the fact that carfilzomib failed to deliver a clinical benefit in RCC patients in a recent phase II trial unrelated to the present study underscores the complexities and limitations of this strategy.

Enhanced protective immune response of foot-and-mouth disease vaccine through DNA-loaded virus-like particles.

Foot-and-mouth disease virus (FMDV) is the etiological agent of a highly contagious disease that affects cloven-hoofed animals. Virus-like particles (VLPs) can induce a robust immune response and deliver DNA and small molecules. In this study, a VLP-harboring pcDNA3.1/P12A3C plasmid was generated, and the protective immune response was characterized. Guinea pigs were injected with VLPs, naked DNA vaccine, DNA-loaded VLPs, or phosphate-buffered saline twice subcutaneously at four-week intervals. Results demonstrated that the VLPs protected the naked DNA from DNase degeneration and delivered the DNA into the cells in vitro. The DNA-loaded VLPs and the VLPs alone induced a similar level of specific antibodies (P > 0.05) except at 49 dpv (P < 0.05). The difference in interferon-γ was consistent with that in specific antibodies. The levels of neutralizing antibodies induced by the DNA-loaded VLPs were significantly higher than those of other samples (P < 0.01). Similarly, the lymphocyte proliferation by using DNA-loaded VLPs was significantly higher than those using other formulas after booster immunization. Vaccination with DNA-loaded VLPs provided higher protection (100%) against viral challenge compared with vaccination with VLPs (75%) and DNA vaccine (25%). This study suggested that VLPs can be used as a delivery carrier for DNA vaccine. In turn, the DNA vaccine can enhance the immune response and prolong the serological duration of the VLP vaccine. This phenomenon contributes in providing complete protection against the FMDV challenge in guinea pigs and can be valuable in exploring novel nonreplicating vaccines and controlling FMD in endemic countries worldwide.

Molecular complexity of taxane-induced cytotoxicity in prostate cancer cells.

BACKGROUND: Taxanes are routinely used to treat men with advanced prostate cancer, yet their molecular mode of action is poorly characterized. Taxanes stabilize microtubules and may hence interfere with a plethora of cellular processes, most notably mitosis. However, prostate cancer is typically a slowly growing tumor suggesting that additional processes play a role in the response to taxanes. METHODS: Here, we analyzed the potential effect of taxanes on microtubuli-dependent intracellular transport and signaling processes, specifically, nuclear translocation of the androgen receptor and modulation of the RAS-RAF-MEK-ERK signaling cascade. RESULTS: We show that the androgen-driven nuclear translocation of the androgen receptor remains virtually undisturbed by docetaxel in prostate cancer cells. However, we found a striking down-regulation of activated ERK1/2 together with enhanced cytotoxicity in both docetaxel or cabazitaxel-treated cells that was comparable to direct MEK kinase inhibition. Remarkably, MEK inhibition alone was less effective in inducing cytotoxicity than taxanes indicating that a down-regulation of activated ERK1/2 may be necessary but is not sufficient for taxane-induced antitumoral effects. In line with this notion, we show in a xenograft mouse model that prostate cancer cells that are resistant to docetaxel overexpress activated ERK1/2. Taken together, our findings underscore that the modulation of ERK1/2 activation, in concert with other mechanisms, plays an important role in taxane-induced antineoplastic effects on prostate cancer cells. CONCLUSIONS: These results suggest at least partially nonoverlapping effects of docetaxel and androgen deprivation therapy and hence help to understand recent clinical findings. A further elucidation of the mode of action of docetaxel would have important implications to optimize current treatment strategies and biomarker development for men with metastatic prostate cancer.

Uncoupling of PUMA Expression and Apoptosis Contributes to Functional Heterogeneity in Renal Cell Carcinoma - Prognostic and Translational Implications.

Renal cell carcinoma (RCC) is characterized by a profound disruption of proapoptotic signaling networks leading to chemo- and radioresistance. A key mediator of DNA damage-induced apoptosis is the BH3-only protein PUMA. Given its central role in proapoptotic signaling, we analyzed a series of more than 600 precision-annotated primary RCC specimens for PUMA protein expression. We found a reduced expression of PUMA in 22.6% of RCCs analyzed. Unexpectedly, however, PUMA deficiency was not associated with more aggressive tumor characteristic as expected. Instead, a reduced PUMA expression was associated with a lower TNM stage, lower histopathologic grade, and more favorable cancer-specific patient survival. A direct correlation in a separate patient cohort revealed a profound disconnection between PUMA expression and apoptosis as exemplified by the fact that the tumor with the highest level of apoptotic cells was PUMA deficient. In a series of in vitro studies, we corroborated these results and discovered the highest propensity to undergo apoptosis in an RCC cell line with virtually undetectable PUMA expression. At the same time, PUMA expression was not necessarily associated with stronger apoptosis induction, which underscores the striking functional heterogeneity of PUMA expression and apoptosis in RCC. Collectively, our findings suggest that PUMA-independent mechanisms of cell death exist and may play an important role in suppressing malignant progression. They underscore the functional heterogeneity of RCCs and suggest that PUMA expression alone may not be a suitable predictive biomarker. A better understanding of alternative proapoptotic pathways, however, may help to design novel therapeutic strategies for patients with advanced RCC.

Systematic review and meta-analysis of comparative studies reporting early outcomes after robot-assisted radical cystectomy versus open radical cystectomy.

BACKGROUND: Robot-assisted radical cystectomy (RARC) is increasingly being used in the management of bladder cancer. Studies comparing RARC and open radical cystectomy (ORC) have reported conflicting results. We conducted a systematic review and meta-analysis of the literature on the efficacy and advantages of RARC compared with ORC. METHODS: An electronic database search of PubMed, Scopus, and the Cochrane Library was performed up to July 8, 2012. This systematic review and meta-analysis was performed based on all randomized controlled trials (RCTs) and observational comparative studies assessing the two techniques. RESULTS: One RCT, eight studies with prospectively collected data, and four retrospective studies were identified, including 962 cases. Although RARC was associated with longer operative time (p<0.001), patients in this group might benefit from less overall perioperative complications (p=0.04), more lymph node yield (p=0.009), less estimated blood loss (p<0.001), a lower need for perioperative transfusion (p<0.001), and shorter length of hospital stay (p<0.001). Positive surgical margins did not differ significantly between techniques. Sensitivity analysis with prospective studies showed similar results to the original analysis, but no significant difference of lymph node yield and length of stay between two techniques. CONCLUSIONS: RARC is a mini-invasive alternative to ORC with less overall perioperative complications, more lymph node yields, less estimated blood loss, less need for a perioperative transfusion, and shorter length of stay.

Optimized two-frequency phase-measuring-profilometry light-sensor temporal-noise sensitivity.

Temporal frame-to-frame noise in multipattern structured light projection can significantly corrupt depth measurement repeatability. We present a rigorous stochastic analysis of phase-measuring-profilometry temporal noise as a function of the pattern parameters and the reconstruction coefficients. The analysis is used to optimize the two-frequency phase measurement technique. In phase-measuring profilometry, a sequence of phase-shifted sine-wave patterns is projected onto a surface. In two-frequency phase measurement, two sets of pattern sequences are used. The first, low-frequency set establishes a nonambiguous depth estimate, and the second, high-frequency set is unwrapped, based on the low-frequency estimate, to obtain an accurate depth estimate. If the second frequency is too low, then depth error is caused directly by temporal noise in the phase measurement. If the second frequency is too high, temporal noise triggers ambiguous unwrapping, resulting in depth measurement error. We present a solution for finding the second frequency, where intensity noise variance is at its minimum.