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Abstract Immune checkpoint inhibitors (ICI) are highly effective in specific cancers where canonical markers of antitumor immunity are used for patient selection. Improved predictors of T cell-inflammation are needed to identify ICI-responsive tumor subsets in additional cancer types. We investigated associations of a 4-chemokine expression signature (c-Score: CCL4, CCL5, CXCL9, CXCL10) with metrics of antitumor immunity across tumor types. Across cancer entities from The Cancer Genome Atlas, subgroups of tumors displayed high expression of the c-Score (c-Scorehi) with increased expression of immune checkpoint (IC) genes and transcriptional hallmarks of the cancer-immunity cycle. There was an incomplete association of the c-Score with high tumor mutation burden (TMB), with only 15% of c-Scorehi tumors displaying ≥10 mutations per megabase. In a heterogeneous pan-cancer cohort of 82 patients, with advanced and previously treated solid cancers, c-Scorehi tumors had a longer median time to progression (103 versus 72 days, P = 0.012) and overall survival (382 versus 196 days, P = 0.038) following ICI therapy initiation, compared to patients with low c-Score expression. We also found c-Score stratification to outperform TMB assignment for overall survival prediction (HR = 0.42 [0.22–0.79], P = 0.008 versus HR = 0.60 [0.29-1.27], P = 0.18, respectively). Assessment of the c-Score using the TIDE and PredictIO databases, which include ICI treatment outcomes from 10 tumor types, provided further support for the c-Score as a predictive ICI therapeutic biomarker. In summary, the c-Score identifies patients with hallmarks of T cell-inflammation and potential response to ICI treatment across cancer types, which is missed by TMB assignment.

A Scientific Integrity Consortium developed a set of recommended principles and best practices that can be used broadly across scientific disciplines as a mechanism for consensus on scientific integrity standards and to better equip scientists to operate in a rapidly changing research environment. The two principles that represent the umbrella under which scientific processes should operate are as follows: (1) Foster a culture of integrity in the scientific process. (2) Evidence-based policy interests may have legitimate roles to play in influencing aspects of the research process, but those roles should not interfere with scientific integrity. The nine best practices for instilling scientific integrity in the implementation of these two overarching principles are (1) Require universal training in robust scientific methods, in the use of appropriate experimental design and statistics, and in responsible research practices for scientists at all levels, with the training content regularly updated and presented by qualified scientists. (2) Strengthen scientific integrity oversight and processes throughout the research continuum with a focus on training in ethics and conduct. (3) Encourage reproducibility of research through transparency. (4) Strive to establish open science as the standard operating procedure throughout the scientific enterprise. (5) Develop and implement educational tools to teach communication skills that uphold scientific integrity. (6) Strive to identify ways to further strengthen the peer review process. (7) Encourage scientific journals to publish unanticipated findings that meet standards of quality and scientific integrity. (8) Seek harmonization and implementation among journals of rapid, consistent, and transparent processes for correction and/or retraction of published papers. (9) Design rigorous and comprehensive evaluation criteria that recognize and reward the highest standards of integrity in scientific research.

Cardiovascular disease risk factor control as primary prevention in patients with type 2 diabetes mellitus has changed substantially in the past few years. The purpose of this scientific statement is to review the current literature and key clinical trials pertaining to blood pressure and blood glucose control, cholesterol management, aspirin therapy, and lifestyle modification. We present a synthesis of the recent literature, new guidelines, and clinical targets, including screening for kidney and subclinical cardiovascular disease for the contemporary management of patients with type 2 diabetes mellitus.

One of the essential layers in most Convolutional Neural Networks (CNNs) is the pooling layer, which is placed right after the convolution layer, effectively downsampling the input and reducing the computational power required. Different pooling methods have been proposed over the years, each with its own advantages and disadvantages, rendering them a better fit for different applications. We introduce a benchmark between many of these methods that highlights an optimal choice for different scenarios depending on each project’s individual needs, whether it is detail retention, performance, or overall computational speed requirements.

The paper presents a design and operation analysis of an Integrated Collector Storage (ICS) solar water heater, which consists of an asymmetric Compound Parabolic Concentrating (CPC) reflector trough, while the water tank comprises two concentric cylinders. The annulus between these vessels is partially depressurized and contains a small amount of water in the bottom of the outer vessel which dominantly contributes to the heat transfer from the outer to the inner cylinder. A multi-criteria optimization algorithm is applied to re-evaluate the design specifications of the parabolic surface, thus modifying the design of the entire ICS system and predict the necessary number of units for achieving the highest possible effectiveness with minimized fabrication costs and environmental impacts. The environmental footprint of the device is assessed through Life Cycle Assessment (LCA). The produced thermal energy in conjunction with the environmental and economic results are evaluated as a function of different configuration parameters regarding the water storage conditions, the solar radiation and the total pressure inside the annulus. The ultimate aim of the evaluation process is to offer new perspectives on the design principles of environmentally friendly and cost-effective devices with improved thermal performance.

The production cost of greenhouse cultivation depends mainly upon significant amounts of energy consumption in order to keep the optimum environmental condition for plant growth. Τhe expenditure on energy, either for heating or cooling, ranges between 30% to 60% of the total production costs, and any attempt to save energy will result in a positive effect on the potentiality of production accordingly, affecting the greenhouse product prices. Research has shown that CO2 enrichment in greenhouses significantly increases the yield of most indoor cultivation of plants of the C3 category. For these plants, when the CO2 concentration increases by three times above that of the atmosphere (380 ppm), the optimum plant growth temperature shifts higher by 5 °C to 10 °C reaching up to 30 °C to 32 °C. Therefore, huge amounts of solar energy can be captured inside the greenhouses, as the ventilation can be decreased. Alongside this, the use of a simple passive solar system consisting of plastic sleeves filled with water is considered to be an improved way to increase the energy inside greenhouses. In this work, three experimental trials were conducted to examine the benefit of the solar energy captured inside a greenhouse during CO2 enrichment at high temperatures. Finally, a modeling approach based on the heat loss equation was developed in order to establish the energy saving inside the greenhouses under the circumstances mentioned.