Notes

AQU-019 reveals protecting impact on infection induced gastroenteritis in rat model.
Depressed patients demonstrated greater inhibitory connectivity from the rACC to the dlPFC, AIC, dACC and left amygdala. Moreover, treatment responders illustrated greater inhibitory connectivity from the rACC to dACC, greater excitatory connectivity from the dACC to sgACC and reduced inhibitory connectivity from the sgACC to amygdalae at baseline. The inhibitory hyperconnectivity of the rACC in depressed patients aligns with hypotheses concerning the dominance of the default mode network over other intrinsic brain networks. Surprisingly, treatment responders did not demonstrate connectivity which was more similar to healthy controls, but rather distinct alterations that may have predicated their enhanced treatment response.Cabazitaxel (CBZ) is approved for the treatment of docetaxel-resistant castration-resistant prostate cancer (CRPC). However, its efficacy against CRPC is limited, and there are no effective treatments for CBZ-resistant CRPC. This study explored the optimal treatment for CRPC in the post-cabazitaxel setting. PC3 (CBZ-sensitive) and PC3CR cells (CBZ-resistant) were used in this study. We performed in silico drug screening for candidate drugs that could reprogram the gene expression signature of PC3CR cells. The in vivo effect of the drug combination was tested in xenograft mice models. We identified etoposide (VP16) as a promising treatment candidate for CBZ-resistant CRPC. The WST assay revealed that VP16 had a significant antitumor effect on PC3CR cells. PC3CR cells exhibited significantly higher topoisomerase II alpha (TOP2A) expression than PC3 cells. Higher TOP2A expression was a poor prognostic factor in The Cancer Genome Atlas prostate cancer cohort. In the Fred Hutchinson Cancer Research Center dataset, docetaxel-exposed tissues and metastatic tumors had higher TOP2A expression. In addition, VP16 significantly inhibited the growth of tumors generated from both cell lines. Based on these findings, VP16-based chemotherapy may be an optimal treatment for CPRC in the post-CBZ setting.Contrast-enhanced mammography (CEM) has shown to be superior to full-field digital mammography (FFDM), but current results are dominated by studies performed on systems by one vendor. Information on diagnostic accuracy of other CEM systems is limited. Therefore, we aimed to evaluate the diagnostic performance of CEM on an alternative vendor's system. We included all patients who underwent CEM in one hospital in 2019, except those with missing data or in whom CEM was used as response monitoring tool. Three experienced breast radiologists scored the low-energy images using the BI-RADS classification. Next, the complete CEM exams were scored similarly. Histopathological results or a minimum of one year follow-up were used as reference standard. Diagnostic performance and AUC were calculated and compared between low-energy images and the complete CEM examination, for all readers independently as well as combined. Breast cancer was diagnosed in 23.0% of the patients (35/152). Compared to low-energy images, overall CEM sensitivity increased from 74.3 to 87.6% (p  less then  0.0001), specificity from 87.8 to 94.6% (p = 0.0146). AUC increased from 0.872 to 0.957 (p = 0.0001). see more Performing CEM on the system tested, showed that, similar to earlier studies mainly performed on another vendor's systems, both sensitivity and specificity improved when compared to FFDM.Operant boxes enable the application of complex behavioural paradigms to support circuit neuroscience and drug discovery research. However, commercial operant box systems are expensive and often not optimised for combining behaviour with neurophysiology. Here we introduce a fully open-source Python-based operant-box system in a 5-choice design (pyOS-5) that enables assessment of multiple cognitive and affective functions. It is optimized for fast turn-over between animals, and for testing of tethered mice for simultaneous physiological recordings or optogenetic manipulation. For reward delivery, we developed peristaltic and syringe pumps based on a stepper motor and 3D-printed parts. Tasks are specified using a Python-based syntax implemented on custom-designed printed circuit boards that are commercially available at low cost. We developed an open-source graphical user interface (GUI) and task definition scripts to conduct assays assessing operant learning, attention, impulsivity, working memory, or cognitive flexibility, alleviating the need for programming skills of the end user. All behavioural events are recorded with millisecond resolution, and TTL-outputs and -inputs allow straightforward integration with physiological recordings and closed-loop manipulations. This combination of features realizes a cost-effective, nose-poke-based operant box system that allows reliable circuit-neuroscience experiments investigating correlates of cognition and emotion in large cohorts of subjects.Problem framing is critical to developing risk prediction models because all subsequent development work and evaluation takes place within the context of how a problem has been framed and explicit documentation of framing choices makes it easier to compare evaluation metrics between published studies. In this work, we introduce the basic concepts of framing, including prediction windows, observation windows, window shifts and event-triggers for a prediction that strongly affects the risk of clinician fatigue caused by false positives. Building on this, we apply four different framing structures to the same generic dataset, using a sepsis risk prediction model as an example, and evaluate how framing affects model performance and learning. Our results show that an apparently good model with strong evaluation results in both discrimination and calibration is not necessarily clinically usable. Therefore, it is important to assess the results of objective evaluations within the context of more subjective evaluations of how a model is framed.Space information networks is network systems that can receive, transmit, and process spatial information lively. It uses satellites, stratosphere airships, Unmanned Aerial Vehicles, and other platforms as the carrier. It supports high-dynamic, real-time broadband transmission of earth observations and ultra-long-distance, long-delay reliable transmission of deep space exploration. The deeper the network integration, the higher the system's security concerns and the more likely SINs will be controlled and destroyed in terms of cybersecurity. How to integrate new IT technologies such as artificial intelligence, digital twins, and blockchain to diverse application scenarios of SINs while maintaining SIN cybersecurity will be a long-term critical technical issue. link2 This study is a review of the security issues for space information networks. First, this paper examines space information networks' security issues and figures out the relationship between the main security threats, services, and mechanisms. Then, this article selects secure routing and anomaly detection from many security technologies to conduct a detailed overview from two perspectives of traditional methods and artificial intelligence. Subsequently, this paper investigates anomaly detection schemes for spatial information networks and proposes a deep learning-based anomaly detection scheme. Finally, we suggest the potential research directions and opening problems of space information network security. link3 Overall, this paper aims to give readers an overview of the newly emerging technologies in space information networks' security issues and provide inspiration for future exploration.The plague of 1630-1632 was one of the deadliest plague epidemics to ever hit Northern Italy, and for many of the affected regions, it was also the last. While accounts on plague during the early 1630s in Florence and Milan are frequent, much less is known about the city of Imola. We analyzed the full skeletal assemblage of four mass graves (n = 133 individuals) at the Lazaretto dell'Osservanza, which date back to the outbreak of 1630-1632 in Imola and evaluated our results by integrating new archival sources. The skeletons showed little evidence of physical trauma and were covered by multiple layers of lime, which is characteristic for epidemic mass mortality sites. We screened 15 teeth for Yersinia pestis aDNA and were able to confirm the presence of plague in Imola via metagenomic analysis. Additionally, we studied a contemporaneous register, in which a friar recorded patient outcomes at the lazaretto during the last year of the epidemic. Our multidisciplinary approach combining historical, osteological and genomic data provided a unique opportunity to reconstruct an in-depth picture of the last plague of Imola through the city's main lazaretto.Lung function reflects the ability of the respiratory system and is utilized for the assessment of respiratory diseases. Because type 2 airway inflammation influences lung function, genome wide association studies (GWAS) for lung function would be improved by adjustment with an indicator of the inflammation. Here, we performed a GWAS for lung function with adjustment for exhaled nitric oxide (FeNO) levels in two independent Japanese populations. Our GWAS with genotype imputations revealed that the RNF5/AGER locus including AGER rs2070600 SNP, which introduces a G82S substitution of AGER, was the most significantly associated with FEV1/FVC. Three other rare missense variants of AGER were further identified. We also found genetic loci with three candidate genes (NOS2, SPSB2 and RIPOR2) associated with FeNO levels. Analyses with the BioBank-Japan GWAS resource revealed genetic links of FeNO and asthma-related traits, and existence of common genetic background for allergic diseases and their biomarkers. Our study identified the genetic locus most strongly associated with airway obstruction in the Japanese population and three genetic loci associated with FeNO, an indicator of type 2 airway inflammation in adults.Traditionally, topographic surveying in earth sciences requires high financial investments, elaborate logistics, complicated training of staff and extensive data processing. Recently, off-the-shelf drones with optical sensors already reduced the costs for obtaining a high-resolution dataset of an Earth surface considerably. Nevertheless, costs and complexity associated with topographic surveying are still high. In 2020, Apple Inc. released the iPad Pro 2020 and the iPhone 12 Pro with novel build-in LiDAR sensors. Here we investigate the basic technical capabilities of the LiDAR sensors and we test the application at a coastal cliff in Denmark. The results are compared to state-of-the-art Structure from Motion Multi-View Stereo (SfM MVS) point clouds. The LiDAR sensors create accurate high-resolution models of small objects with a side length > 10 cm with an absolute accuracy of ± 1 cm. 3D models with the dimensions of up to 130 × 15 × 10 m of a coastal cliff with an absolute accuracy of ± 10 cm are compiled. Overall, the versatility in handling outweighs the range limitations, making the Apple LiDAR devices cost-effective alternatives to established techniques in remote sensing with possible fields of application for a wide range of geo-scientific areas and teaching.
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