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A trademark's image is usually the first type of indirect contact between a consumer and a product or a service. Companies rely on graphical trademarks as a symbol of quality and instant recognition, seeking to protect them from copyright infringements. A popular defense mechanism is graphical searching, where an image is compared to a large database to find potential conflicts with similar trademarks. Despite not being a new subject, image retrieval state-of-the-art lacks reliable solutions in the Industrial Property (IP) sector, where datasets are practically unrestricted in content, with abstract images for which modeling human perception is a challenging task. Existing Content-based Image Retrieval (CBIR) systems still present several problems, particularly in terms of efficiency and reliability. In this paper, we propose a new CBIR system that overcomes these major limitations. It follows a modular methodology, composed of a set of individual components tasked with the retrieval, maintenance and gradual optimization of trademark image searching, working on large-scale, unlabeled datasets. Its generalization capacity is achieved using multiple feature descriptions, weighted separately, and combined to represent a single similarity score. Images are evaluated for general features, edge maps, and regions of interest, using a method based on Watershedding K-Means segments. We propose an image recovery process that relies on a new similarity measure between all feature descriptions. New trademark images are added every day to ensure up-to-date results. The proposed system showcases a timely retrieval speed, with 95% of searches having a 10 second presentation speed and a mean average precision of 93.7%, supporting its applicability to real-word IP protection scenarios.

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Ferroptosis is an iron-dependent lipid-peroxidation-driven mechanism of cell death and a promising therapeutic target to eradicate cancer cells. In this study, we discovered that boronic acid-derived salicylidenehydrazone (BASHY) dyes are highly efficient singlet-oxygen photosensitizers (PSs; ΦΔ up to 0.8) that induce ferroptosis triggered by photodynamic therapy. The best-performing BASHY dye displayed a high phototoxicity against the human glioblastoma multiform U87 cell line, with an IC50 value in the low nanomolar range (4.40 nM) and a remarkable phototoxicity index (PI > 22,700). Importantly, BASHY dyes were shown to accumulate in lipid droplets (LDs) and this intracellular partition was found to be essential for the enhanced phototoxicity and the induction of ferroptosis through lipid peroxidation. The safety and phototoxicity of this platform were validated using an in vivo zebrafish model (Danio rerio).

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The growth in the volume of data generated, consumed, and stored, which is estimated to exceed 180 zettabytes in 2025, represents a major challenge both for organizations and for society in general. In addition to being larger, datasets are increasingly complex, bringing new theoretical and computational challenges. Alongside this evolution, data science tools have exploded in popularity over the past two decades due to their myriad of applications when dealing with complex data, their high accuracy, flexible customization, and excellent adaptability. When it comes to images, data analysis presents additional challenges because as the quality of an image increases, which is desirable, so does the volume of data to be processed. Although classic machine learning (ML) techniques are still widely used in different research fields and industries, there has been great interest from the scientific community in the development of new artificial intelligence (AI) techniques. The resurgence of neural networks has boosted remarkable advances in areas such as the understanding and processing of images. In this study, we conducted a comprehensive survey regarding advances in AI design and the optimization solutions proposed to deal with image processing challenges. Despite the good results that have been achieved, there are still many challenges to face in this field of study. In this work, we discuss the main and more recent improvements, applications, and developments when targeting image processing applications, and we propose future research directions in this field of constant and fast evolution.

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Benzodiazaborines (BDABs) have emerged as a valuable tool to produce stable and functional bioconjugates via a click-type transformation. However, the current available methods to install them on peptides lack bioorthogonality, limiting their applications. Here, we report a strategy to install BDABs directly on peptide chains using (2-cyanamidophenyl)boronic acids (2CyPBAs). The resulting BDAB is stabilized through the formation of a key intramolecular B-N bond. This technology was applied in the selective modification of N-terminal cysteine-containing functional peptides.

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Four new Cu(I) complexes of the general formula [Cu(PP)(LL)][BF4 ], in which PP is a phosphane ligand (triphenylphosphane or 1,2-bis(diphenylphosphano)ethane (dppe)) and LL is a bioactive thiosemicarbazone ligand (4-(methyl)-1-(5-nitrofurfurylidene)thiosemicarbazone) or 4-(ethyl)-1-(5-nitrofurfurylidene)thiosemicarbazone) were synthesized and fully characterized by classical analytical and spectroscopic methods. The anti-trypanosome and anticancer activities were investigated in vitro on Trypanosoma cruzi and in two human cancer cell lines (ovarian OVCAR3 and prostate PC3). To test the selectivity toward parasites and cancer cells, the cytotoxicity on normal monkey kidney VERO and human dermal fibroblasts HDF cells was also evaluated. The new heteroleptic complexes were more cytotoxic on T. cruzi and chemoresistant prostate PC3 cells than the benchmark drugs nifurtimox and cisplatin. The compounds also showed a high level of cellular internalization by the OVCAR3 cells and, in particular, those containing the dppe phosphane showed activation of the cell death mechanism via apoptosis. On the other hand, the production of reactive oxygen species induced by these complexes was not evident.

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WHAT IS THIS SUMMARY ABOUT?: This is a summary of a paper published in a medical journal that describes the results of a study called CheckMate 274. This study looked at a new treatment for muscle-invasive urothelial cancer, a type of cancer found in the urinary tract that has spread from the inner lining of the urinary tract or bladder and into the surrounding muscle wall where it can then spread to other parts of the body. The standard treatment for muscle-invasive urothelial cancer is surgery to remove affected parts of the urinary tract. However, cancer returns in more than half of people after this surgery. Adjuvant therapy is given to people after surgery with muscle-invasive urothelial cancer with a goal to reduce the risk of the cancer coming back; however, at the time this study started, there was no standard adjuvant treatment. WHAT HAPPENED IN THE STUDY?: In the CheckMate 274 study, researchers compared nivolumab with a placebo as an adjuvant treatment for people with muscle-invasive urothelial cancer. The aim of the study was to understand how well nivolumab worked to reduce the chance of the cancer returning after surgery. The study also looked at what side effects (unwanted or unexpected results or conditions that are possibly related to the use of a medication) people had with treatment. WHAT DO THE RESULTS MEAN?: The results showed that people who received nivolumab versus placebo: Survived longer before the cancer was detected again, including people who had programmed death ligand-1 (shortened to PD-L1) on their cancer cells. Survived longer before a secondary cancer outside of the urinary tract was detected. Experienced no differences in health-related quality of life (the impact of the treatment on a person's mental and physical health). Had similar side effects to the people who received nivolumab in other studies. Clinical Trial Registration: NCT02632409 (ClinicalTrials.gov).

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Antibody-drug conjugates (ADCs) are among the fastest-growing classes of therapeutics in oncology. Although ADCs are in the spotlight, they still present significant engineering challenges. Therefore, there is an urgent need to develop more stable and effective ADCs. Most rabbit light chains have an extra disulfide bridge, that links the variable and constant domains, between Cys80 and Cys171, which is not found in the human or mouse. Thus, to develop a new generation of ADCs, we explored the potential of rabbit-derived VL-single-domain antibody scaffolds (sdAbs) to selectively conjugate a payload to Cys80. Hence, a rabbit sdAb library directed towards canine non-Hodgkin lymphoma (cNHL) was subjected to in vitro and in vivo phage display. This allowed the identification of several highly specific VL-sdAbs, including C5, which specifically target cNHL cells in vitro and present promising in vivo tumor uptake. C5 was selected for SN-38 site-selective payload conjugation through its exposed free Cys80 to generate a stable and homogenous C5-DAB-SN-38. C5-DAB-SN-38 exhibited potent cytotoxicity activity against cNHL cells while inhibiting DNA-TopoI activity. Overall, our strategy validates a platform to develop a novel class of ADCs that combines the benefits of rabbit VL-sdAb scaffolds and the canine lymphoma model as a powerful framework for clinically translation of novel therapeutics for cancer.

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The in vitro to in vivo translation of metal-based cytotoxic drugs has proven to be a significant hurdle in their establishment as effective anti-cancer alternatives. Various nano-delivery systems, such as polymeric nanoparticles, have been explored to address the pharmacokinetic limitations associated with the use of these complexes. However, these systems often suffer from poor stability or involve complex synthetic procedures. To circumvent these problems, we report here a simple, one-pot procedure for the preparation of covalently-attached Ru-polylactide nanoparticles. This methodology relies on the ring-opening polymerization of lactide initiated by a calcium alkoxide derivative formed from calcium bis(trimethylsilyl amide) and a hydroxyl-bearing ruthenium complex. This procedure proceeds with high efficiency (near-quantitative incorporation of Ru in the polymer) and enables the preparation of polymers with varying molecular weights (2000-11000 Da) and high drug loadings (up to 68% w/w). These polymers were formulated as narrowly dispersed nanoparticles (110 nm) that exhibited a slow and predictable release of the ruthenium payload. Unlike standard encapsulation methods routinely used, the release kinetics of these nanoparticles is controlled and may be adjusted on demand, by tuning the size of the polymer chain. In terms of cytotoxicity, the nanoparticles were assessed in the ovarian cancer cell line A2780 and displayed potency comparable to cisplatin and the free drug, in the low micromolar range. Interestingly, the activity was maintained when tested in a cisplatin-resistant cell line, suggesting a possible orthogonal mechanism of action. Additionally, the internalization in tumour cells was found to be significantly higher than the free ruthenium complex (>200 times in some cases), clearly showcasing the added benefit in the drug's cellular permeation and accumulation of the drug. Finally, the in vivo performance was evaluated for the first time in mice. The experiments showed that the intravenously injected nanoparticles were well tolerated and were able to significantly improve the pharmacokinetics and biodistribution of the parent drug. Not only was the nanosystem able to promote an 18-fold increase in tumour accumulation, but it also allowed a considerable reduction of drug accumulation in vital organs, achieving, for example, reduction levels of 90% and 97% in the brain and lungs respectively. In summary, this simple and efficient one-pot procedure enables the generation of stable and predictable nanoparticles capable of improving the cellular penetration and systemic accumulation of the Ru drug in the tumour. Altogether, these results showcase the potential of covalently-loaded ruthenium polylactide nanoparticles and pave the way for its exploitation and application as a viable tool in the treatment of ovarian cancer.

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In semi-arid regions, agricultural production is often limited due to scarcity and rainfall irregularities, and, therefore, the production system depends on irrigation. In this direction, the research aimed to evaluate the influence of the reduction of water losses in the soil through the coating of the lateral faces of the planting furrows with plastic film, by lateral infiltration of water and bovine biofertilizers for growth in height, production, and chlorophyll responses of tomato cv. Fascínio F1 irrigated with moderately saline water. The experiment was carried out in randomized blocks, in a 2 × 3 factorial scheme, with 4 replicates and 21 plants per plot. Different conditions were used and compared with each other: the furrow had side coating or not, and the soil received a common biofertilizer (fresh lactating bovine manure), chemically enriched fertilizer (common biofertilizer, milk, molasses, and gypsum), or no fertilizer at all. The variables evaluated were soil moisture, plant height, a, b, and total chlorophyll content, number and average fruit mass, tomato production, and productivity. The enriched bovine biofertilizer associated with the lateral furrow coating increased the synthesis of chlorophyll pigments, the number of fruits per plant, and the productivity of tomato cv. Fascínio F1. Protecting the faces of the furrows against water losses from the root environment of plants keeps the soil moist, stimulates the synthesis of chlorophyll, and increases the average mass of the fruits. The common bovine biofertilizer promotes greater growth in plant height, and the chemically enriched biofertilizer increases the average weight of tomato fruits.

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Graphical Search Engines are conceptually used in many development areas surrounding information retrieval systems that aim to provide a visual representation of results, typically associated with retrieving images relevant to one or more input images. Since the 1990s, efforts have been made to improve the result quality, be it through improved processing speeds or more efficient graphical processing techniques that generate accurate representations of images for comparison. While many systems achieve timely results by combining high-level features, they still struggle when dealing with large datasets and abstract images. Image datasets regarding industrial property are an example of an hurdle for typical image retrieval systems where the dimensions and characteristics of images make adequate comparison a difficult task. In this paper, we introduce an image retrieval system based on a multi-phase implementation of different deep learning and image processing techniques, designed to deliver highly accurate results regardless of dataset complexity and size. The proposed approach uses image signatures to provide a near exact representation of an image, with abstraction levels that allow the comparison with other signatures as a means to achieve a fully capable image comparison process. To overcome performance disadvantages related to multiple image searches due to the high complexity of image signatures, the proposed system incorporates a parallel processing block responsible for dealing with multi-image search scenarios. The system achieves the image retrieval through the use of a new similarity compound formula that accounts for all components of an image signature. The results shows that the developed approach performs image retrieval with high accuracy, showing that combining multiple image assets allows for more accurate comparisons across a broad spectrum of image typologies. The use of deep convolutional networks for feature extraction as a means of semantically describing more commonly encountered objects allows for the system to perform research with a degree of abstraction.

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Post-translational modifications of histones are essential in the regulation of chromatin structure and function. Among these modifications, lysine acetylation is one of the most established. Earlier studies relied on the use of chromatin containing heterogeneous mixtures of histones acetylated at multiple sites. Differentiating the individual contribution of single acetylation events towards chromatin regulation is thus of great relevance. However, it is difficult to access homogeneous samples of histones, with a single acetylation, in sufficient quantities for such studies. By engineering histone H3 with a cysteine in proximity of the lysine of interest, we demonstrate that conjugation with maleimide-DBCO followed by a strain-promoted alkyne-azide cycloaddition reaction results in the acetylation of a single lysine in a controlled, site-specific manner. The chemical precision offered by our click-to-acetylate approach will facilitate access to and the study of acetylated histones.

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Na prática clínica da dermatologia não é incomum nos depararmos com situações desafiadoras, de difícil caracterização e que podem nos induzir ao erro diagnóstico. Quadros cutâneos com apresentações semelhantes entre si estão aqui inclusas e, neste caso, é de suma importância a atuação do médico dermatologista de forma a unir as informações da anamnese, exame físico e exames complementares, a fim de excluir condições de pior prognóstico e que requerem atuação mais agressiva de outras condições benignas e/ou com menor impacto negativo. Apresentamos abaixo uma dessas situações de desafio diagnóstico em que uma lesão cutânea secundária à osteomielite crônica foi inicialmente atribuída à causa inflamatória ou neoplásica (AU)

In the clinical practice of Dermatology, it is not uncommon to encounter challenging situations that are difficult to characterize and may lead to misdiagnosis. Skin conditions with similar presentations are included here and, in this case, it is of utmost importance that the dermatologist combines information from the medical history, physical examination and complementary tests in order to exclude conditions with worse prognosis and that require more aggressive action than other benign conditions and/or with less negative impac (AU)

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With a wide range of applications, image segmentation is a complex and difficult preprocessing step that plays an important role in automatic visual systems, which accuracy impacts, not only on segmentation results, but directly affects the effectiveness of the follow-up tasks. Despite the many advances achieved in the last decades, image segmentation remains a challenging problem, particularly, the segmenting of color images due to the diverse inhomogeneities of color, textures and shapes present in the descriptive features of the images. In trademark graphic images segmentation, beyond these difficulties, we must also take into account the high noise and low resolution, which are often present. Trademark graphic images can also be very heterogeneous with regard to the elements that make them up, which can be overlapping and with varying lighting conditions. Due to the immense variation encountered in corporate logos and trademark graphic images, it is often difficult to select a single method for extracting relevant image regions in a way that produces satisfactory results. Many of the hybrid approaches that integrate the Watershed and K-Means algorithms involve processing very high quality and visually similar images, such as medical images, meaning that either approach can be tweaked to work on images that follow a certain pattern. Trademark images are totally different from each other and are usually fully colored. Our system solves this difficulty given it is a generalized implementation designed to work in most scenarios, through the use of customizable parameters and completely unbiased for an image type. In this paper, we propose a hybrid approach to Image Region Extraction that focuses on automated region proposal and segmentation techniques. In particular, we analyze popular techniques such as K-Means Clustering and Watershedding and their effectiveness when deployed in a hybrid environment to be applied to a highly variable dataset. The proposed system consists of a multi-stage algorithm that takes as input an RGB image and produces multiple outputs, corresponding to the extracted regions. After preprocessing steps, a K-Means function with random initial centroids and a user-defined value for k is executed over the RGB image, generating a gray-scale segmented image, to which a threshold method is applied to generate a binary mask, containing the necessary information to generate a distance map. Then, the Watershed function is performed over the distance map, using the markers defined by the Connected Component Analysis function that labels regions on 8-way pixel connectivity, ensuring that all regions are correctly found. Finally, individual objects are labelled for extraction through a contour method, based on border following. The achieved results show adequate region extraction capabilities when processing graphical images from different datasets, where the system correctly distinguishes the most relevant visual elements of images with minimal tweaking.

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People differ in their general tendency to endorse conspiracy theories (that is, conspiracy mentality). Previous research yielded inconsistent findings on the relationship between conspiracy mentality and political orientation, showing a greater conspiracy mentality either among the political right (a linear relation) or amongst both the left and right extremes (a curvilinear relation). We revisited this relationship across two studies spanning 26 countries (combined N = 104,253) and found overall evidence for both linear and quadratic relations, albeit small and heterogeneous across countries. We also observed stronger support for conspiracy mentality among voters of opposition parties (that is, those deprived of political control). Nonetheless, the quadratic effect of political orientation remained significant when adjusting for political control deprivation. We conclude that conspiracy mentality is associated with extreme left- and especially extreme right-wing beliefs, and that this non-linear relation may be strengthened by, but is not reducible to, deprivation of political control.

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This study evaluated the effect of soybean meal (SBM) particle size on nutrient digestibility and the growth performance of nursery piglets. Sixty-three piglets (BW = 6.86 kg ± 0.56; 23 d of age) were distributed in a randomized block design (by initial weight and sex) with 3 dietary treatments: diets with 1,017 µm (unground); 585 µm; and 411µm SBM, with 7 replicates of 3 piglets each. All diets were offered ad libitum in mash form, formulated differently according to three growing phases: (1) with 20% of SBM, from 23 to 32 d of age; (2) with 25% of SBM, from 32 to 44 d of age, and (3) with 30% of SBM, from 44 to 63 d of age. For the first 21 d, pigs fed diets with a medium particle size of SBM (585mm) had better average weight gain and feed/gain ratio (P<0.05). The average feed intake, average body weight gain, and feed/gain ratio from 44 to 63 d improved (P<0.05) with increasing SBM particle sizes, and the average live weight for the overall period increased with coarser SBM (P<0.05). There was a marginally improvement (P < 0.1) on digestible energy as particle size of SBM decreased; although, no differences (P > 0.05) in the coefficients of apparent digestibility of dry matter and crude protein for the assessed SBM particle sizes were observed. It was concluded that the grinding of dietary SBM is not required for piglets during the nursery phase.

O objetivo deste estudo foi avaliar o efeito do tamanho da partícula do farelo de soja (FS) sobre o desempenho e digestibilidade de leitões no período de creche. 63 leitões (6,86 kg ± 0,56; 23 dias de idade) foram distribuídos aleatoriamente em um delineamento de blocos casualizados (peso inicial e sexo) entre os tratamentos. As dietas experimentais foram produzidas a partir de diferentes tamanhos médios de partículas do FS moídos ou não: 1,017 µm (sem moer), 585 µm (moído em peneira de 10 mm), e 411µm (moído em peneira de 3 mm), totalizando três tratamentos com sete repetições de três animais cada. Todas as dietas foram fornecidas na forma farelada e ad libitum, sendo divididas em três fases: 1) com 20% de FS, dos 23 a 32 dias de idade; 2) com 25% de FS, dos 32 a 44 dias de idade; e 3) com 30% de FS, dos 44 a 62 dias de idade. Nos primeiros 21 dias de experimento, os animais consumindo a dieta com o tamanho médio (585 µm) das partículas do FS apresentaram melhores resultados para o ganho de peso médio e conversão alimentar. No período seguinte (44 a 63 d), houve (P<0.05) aumento do consumo de ração médio, do ganho do peso médio e melhor conversão alimentar dos leitões conforme o aumento do tamanho da partícula de FS incluída na ração. Consequentemente, ao final do experimento houve melhora linear do peso vivo médio dos animais com o aumento do tamanho do FS consumido. Foi observado melhora marginalmente significativa (P < 0.1) da energia digestível conforme a redução no tamanho do FS, entretanto, não houve diferença (P > 0.05) no coeficiente de digestibilidade aparente da matéria seca e da proteína bruta dos animais entre os diferentes tamanhos do FS. Em conclusão, de acordo com as condições deste estudo, não se faz necessária a moagem do farelo de soja para leitões no período de creche.

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Antibody-drug conjugates (ADCs) are a new class of therapeutics that combine the lethality of potent cytotoxic drugs with the targeting ability of antibodies to selectively deliver drugs to cancer cells. In this study we show for the first time the synthesis of a reactive-oxygen-species (ROS)-responsive ADC (VL-DAB31-SN-38) that is highly selective and cytotoxic to B-cell lymphoma (CLBL-1 cell line, IC50 value of 54.1 nM). The synthesis of this ADC was possible due to the discovery that diazaborines (DABs) are a very effective ROS-responsive unit that are also very stable in buffer and in plasma. DFT calculations performed on this system revealed a favorable energetic profile (ΔGR=-74.3 kcal mol-1 ) similar to the oxidation mechanism of aromatic boronic acids. DABs' very fast formation rate and modularity enabled the construction of different ROS-responsive linkers featuring self-immolative modules, bioorthogonal functions, and bioconjugation handles. These structures were used in the site-selective functionalization of a VL antibody domain and in the construction of the homogeneous ADC.

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Correction for 'A 2-formylphenylboronic acid (2FPBA)-maleimide crosslinker: a versatile platform for Cys-peptide-hydrazine conjugation and interplay' by João P. M. António et al., Org. Biomol. Chem., 2021, 19, 6221-6226, DOI: 10.1039/D1OB00917F.

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In this work, we describe the preparation of a heterobifunctional 2-formylphenylboronic acid (2-FPBA)-maleimide crosslinker and explore its versatility in the preparation of various bioconjugates. We demonstrate the straightforward attachment of hydrazine payloads to cysteine residues in peptides, as well as the crosslinking of different thiol-bearing peptides or payloads with N-terminal cysteine peptides. Importantly, the dynamic nature of the 2-FPBA handle enables an interplay between the thiazolidine and diazaborine forms, which allows obtaining various products controlled by (and in some cases independent of) the order of addition of the components.

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BACKGROUND: The role of adjuvant treatment in high-risk muscle-invasive urothelial carcinoma after radical surgery is not clear. METHODS: In a phase 3, multicenter, double-blind, randomized, controlled trial, we assigned patients with muscle-invasive urothelial carcinoma who had undergone radical surgery to receive, in a 1:1 ratio, either nivolumab (240 mg intravenously) or placebo every 2 weeks for up to 1 year. Neoadjuvant cisplatin-based chemotherapy before trial entry was allowed. The primary end points were disease-free survival among all the patients (intention-to-treat population) and among patients with a tumor programmed death ligand 1 (PD-L1) expression level of 1% or more. Survival free from recurrence outside the urothelial tract was a secondary end point. RESULTS: A total of 353 patients were assigned to receive nivolumab and 356 to receive placebo. The median disease-free survival in the intention-to-treat population was 20.8 months (95% confidence interval [CI], 16.5 to 27.6) with nivolumab and 10.8 months (95% CI, 8.3 to 13.9) with placebo. The percentage of patients who were alive and disease-free at 6 months was 74.9% with nivolumab and 60.3% with placebo (hazard ratio for disease recurrence or death, 0.70; 98.22% CI, 0.55 to 0.90; P<0.001). Among patients with a PD-L1 expression level of 1% or more, the percentage of patients was 74.5% and 55.7%, respectively (hazard ratio, 0.55; 98.72% CI, 0.35 to 0.85; P<0.001). The median survival free from recurrence outside the urothelial tract in the intention-to-treat population was 22.9 months (95% CI, 19.2 to 33.4) with nivolumab and 13.7 months (95% CI, 8.4 to 20.3) with placebo. The percentage of patients who were alive and free from recurrence outside the urothelial tract at 6 months was 77.0% with nivolumab and 62.7% with placebo (hazard ratio for recurrence outside the urothelial tract or death, 0.72; 95% CI, 0.59 to 0.89). Among patients with a PD-L1 expression level of 1% or more, the percentage of patients was 75.3% and 56.7%, respectively (hazard ratio, 0.55; 95% CI, 0.39 to 0.79). Treatment-related adverse events of grade 3 or higher occurred in 17.9% of the nivolumab group and 7.2% of the placebo group. Two treatment-related deaths due to pneumonitis were noted in the nivolumab group. CONCLUSIONS: In this trial involving patients with high-risk muscle-invasive urothelial carcinoma who had undergone radical surgery, disease-free survival was longer with adjuvant nivolumab than with placebo in the intention-to-treat population and among patients with a PD-L1 expression level of 1% or more. (Funded by Bristol Myers Squibb and Ono Pharmaceutical; CheckMate 274 ClinicalTrials.gov number, NCT02632409.).

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Fertigation management of banana plantations at a plot scale is expanding rapidly in Brazil. To guide nutrient management at such a small scale, genetic, environmental and managerial features should be well understood. Machine learning and compositional data analysis (CoDa) methods can measure the effects of feature combinations on banana yield and rank nutrients in the order of their limitation. Our objectives are to review ML and CoDa models for application at regional and local scales, and to customize nutrient diagnoses of fertigated banana at the plot scale. We documented 940 "Prata" and "Cavendish" plot units for tissue and soil tests, environmental and managerial features, and fruit yield. A Neural Network informed by soil tests, tissue tests and other features was the most proficient learner (AUC up to 0.827). Tissue nutrients were shown to have the greatest impact on model accuracy. Regional nutrient standards were elaborated as centered log ratio means and standard deviations of high-yield and nutritionally balanced specimens. Plot-scale diagnosis was customized using the closest successful factor-specific tissue compositions identified by the smallest Euclidean distance from the diagnosed composition using centered or isometric log ratios. Nutrient imbalance differed between regional and plot-scale diagnoses, indicating the profound influence of local factors on plant nutrition. However, plot-scale diagnoses require large, reliable datasets to customize nutrient management using ML and CoDa models.