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Cancer is a disease characterised by uncontrolled cell growth, that affects not only humans but also a wide range of animal species, and even plants. In this review, we explore and discuss the published literature about cancer across domestic animals. Most existing cancer across species studies have been conducted by researchers who are not familiar with the diagnosis and treatment of cancer in domestic animals, and the veterinary perspective is rarely included. Moreover, many scientists remain unaware of the value of clinical data obtained from spontaneous cancer in domestic animals. In this review, we examine, summarise, and comment on the available literature investigating cancer across different species, with a focus on domestic animals, including herbivores, carnivores, and omnivores. We also analyse the potential influence of body size, metabolism, environment, and genetic background on cancer risk across species. Understanding both cancer sensitivity and resistance mechanisms in different animals may help bridge current knowledge gaps between veterinarians, researchers, and human oncologists. Ultimately, these insights may support the development of more effective cancer prevention and treatment strategies in animals and humans, emphasising the One Health–One Cancer approach.

As large language models (LLMs) converge towards similar capabilities, the key to advancing their performance lies in identifying and incorporating valuable new information sources. However, evaluating which text collections are worth the substantial investment required for digitization, preprocessing, and integration into LLM systems remains a significant challenge. We present a novel approach to this challenge: an automated pipeline that evaluates the potential information gain from text collections without requiring model training or fine-tuning. Our method generates multiple choice questions (MCQs) from texts and measures an LLM's performance both with and without access to the source material. The performance gap between these conditions serves as a proxy for the collection's information potential. We validate our approach using five strategically selected datasets: EPFL PhD manuscripts, a private collection of Venetian historical records, two sets of Wikipedia articles on related topics, and a synthetic baseline dataset. Our results demonstrate that this method effectively identifies collections containing valuable novel information, providing a practical tool for prioritizing data acquisition and integration efforts.

Clathrin-mediated endocytosis (CME) is one of the best studied cellular uptake pathways and its contributions to nutrient uptake, receptor signaling, and maintenance of the lipid membrane homeostasis have been already elucidated. Today, we still have a lack of understanding how the different components of this pathway cooperate dynamically in vivo . Therefore, we generated a reporter mouse model for CME by fusing eGFP endogenously in frame to clathrin light chain a (Clta) to track endocytosis in living mice. The fusion protein is expressed in all tissues, but in a cell specific manner, and can be visualized using fluorescence microscopy. Recruitment to nanobeads recorded by TIRF microscopy validated the functionality of the Clta-eGFP reporter. With this reporter model we were able to track the dynamics of Alexa594-BSA uptake in kidneys of anesthetized mice using intravital 2-photon microscopy. This reporter mouse model is not only a suitable and powerful tool to track CME in vivo in genetic or disease mouse models it can also help to shed light into the differential roles of the two clathrin light chain isoforms in health and disease.

Light manipulation at the nanoscale is essential both for fundamental science and modern technology. The quest to shorter lengthscales, however, requires the use of light wavelengths beyond the visible. In particular, in the extreme ultraviolet regime these manipulation capabilities are hampered by the lack of efficient optics, especially for polarization control. Here, we present a method to create periodic, polarization modulations at the nanoscale using a tailored configuration of the FERMI free electron laser and demonstrate its capabilities by comparing the dynamics induced by this polarization transient grating with those driven by a conventional intensity grating on a thin ferrimagnetic alloy. While the intensity grating signal is dominated by the thermoelastic response, the polarization grating excitation minimizes it, uncovering helicity-dependent responses previously undetected. We anticipate nanoscale polarization transient gratings to become useful for the study of physical, chemical and biological systems possessing chiral symmetry. This study presents a method to create nanoscale polarization transient gratings in the EUV range. Unlike intensity gratings, it reduces thermal effects, revealing hidden material dynamics. This enables new insights in chiral materials and ultrafast magnetism.

For about 100 years, the shake flask has been established for biotechnological cultivations as one of the most important cultivation systems in early process development. Its appeal lies in its simple handling and highly versatile application for a wide range of cell types—from bacteria to mammalian cells. In recent decades, extensive research has been conducted on the shake flask, to not perform processes blindly but to gain a deeper understanding of the various process parameters, phenomena, and their impact on the process. Although the characterization of the shake flask is now well‐established in literature, many publications show that this knowledge is often inadequately applied. Therefore, this review provides an overview of the current state of knowledge on various topics related to the shake flask. We first present the key process parameters and their influence on different physical phenomena, such as power input, the largely unknown in‐phase/out‐of‐phase phenomenon, as well as temperature and mass transfer. Then, the most common online monitoring systems that have been established for shake flasks are discussed. Finally, various pitfalls that often arise from inadequate knowledge of handling shake flask cultivations are discussed and guidance on how to avoid them is provided.

Background High sensitivity cardiac troponin T (hs-cTnT) and NT-pro-brain natriuretic peptide (NT-pro BNP) are often elevated in chronic kidney disease (CKD) and associated with both cardiovascular remodeling and outcome. Relationship between these biomarkers and quantitative imaging measures of myocardial fibrosis and edema by T1 and T2 mapping remains unknown. Methods Consecutive patients with established CKD and estimated glomerular filtration rate (eGFR) < 59 ml/min/1.73 m 2 (n = 276) were compared to age/sex matched patients with eGFR ≥ 60 ml/min/1.73 m 2 (n = 242) and healthy controls (n = 38). Comprehensive cardiovascular magnetic resonance (CMR) with native T1 and T2 mapping, myocardial ischemia and scar imaging was performed with venous sampling immediately prior to CMR. Results Patients with CKD showed significant cardiac remodeling in comparison with both healthy individuals and non-CKD patients, including a stepwise increase of native T1 and T2 (p < 0.001 between all CKD stages). Native T1 and T2 were the sole imaging markers independently associated with worsening CKD in patients [B = 0.125 (95% CI 0.022–0.235) and B = 0.272 (95% CI 0.164–0.374) with p = 0.019 and < 0.001 respectively]. At univariable analysis, both hs-cTnT and NT-pro BNP significantly correlated with native T1 and T2 in groups with eGFR 30–59 ml/min/1.73 m 2 and eGFR < 29 ml/min/1.73 m 2 groups, with associations being stronger at lower eGFR (NT-pro BNP (log transformed, lg10): native T1 r = 0.43 and r = 0.57, native T2 r = 0.39 and r = 0.48 respectively; log-transformed hs-cTnT(lg10): native T1 r = 0.23 and r = 0.43, native T2 r = 0.38 and r = 0.58 respectively, p < 0.001 for all, p < 0.05 for interaction). On multivariable analyses, we found independent associations of native T1 with NT-pro BNP [(B = 0.308 (95% CI 0.129–0.407), p < 0.001 and B = 0.334 (95% CI 0.154–0.660), p = 0.002 for eGFR 30–59 ml/min/1.73 m 2 and eGFR < 29 ml/min/1.73 m 2 , respectively] and of T2 with hs-cTnT [B = 0.417 (95% CI 0.219–0.650), p < 0.001 for eGFR < 29 ml/min/1.73 m 2 ]. Conclusions We demonstrate independent associations between cardiac biomarkers with imaging markers of interstitial expansion, which are CKD-group specific. Our findings indicate the role of diffuse non-ischemic tissue processes, including excess of myocardial fluid in addition to diffuse fibrosis in CKD-related adverse remodeling.

The demand for safe and secure journeys over roads and highways has been growing at a tremendous pace over recent decades. At the same time, the smart city paradigm has emerged to improve citizens’ quality of life by developing the smart mobility concept. Vehicular Ad hoc NETworks (VANETs) are widely recognized to be instrumental in realizing such concept, by enabling appealing safety and infotainment services. Such networks come with their own set of challenges, which range from managing high node mobility to securing data and user privacy. The Software Defined Networking (SDN) paradigm has been identified as a suitable solution for dealing with the dynamic network environment, the increased number of connected devices, and the heterogeneity of applications. While some preliminary investigations have been already conducted to check the applicability of the SDN paradigm to VANETs, and its presumed benefits for managing resources and mobility, it is still unclear what impact SDN will have on security and privacy. Security is a relevant issue in VANETs, because of the impact that threats can have on drivers’ behavior and quality of life. This paper opens a discussion on the security threats that future SDN-enabled VANETs will have to face, and investigates how SDN could be beneficial in building new countermeasures. The analysis is conducted in real use cases (smart parking, smart grid of electric vehicles, platooning, and emergency services), which are expected to be among the vehicular applications that will most benefit from introducing an SDN architecture.

Leukemia relapse is a major cause of death after allogeneic hematopoietic cell transplantation (allo-HCT). We tested the potential of targeting T cell (Tc) immunoglobulin and mucin-containing molecule 3 (TIM-3) for improving graft-versus-leukemia (GVL) effects. We observed differential expression of TIM-3 ligands when hematopoietic stem cells overexpressed certain oncogenic-driver mutations. Anti–TIM-3 Ab treatment improved survival of mice bearing leukemia with oncogene-induced TIM-3 ligand expression. Conversely, leukemia cells with low ligand expression were anti–TIM-3 treatment resistant. In vitro, TIM-3 blockade or genetic deletion in CD8 + Tc enhanced Tc activation, proliferation, and IFN-γ production while enhancing GVL effects, preventing Tc exhaustion, and improving Tc cytotoxicity and glycolysis in vivo. Conversely, TIM-3 deletion in myeloid cells did not affect allogeneic Tc proliferation and activation in vitro, suggesting that anti–TIM-3 treatment–mediated GVL effects are Tc induced. In contrast to anti–programmed cell death protein 1 (anti–PD-1) and anti–cytotoxic T lymphocyte–associated protein 4 (anti–CTLA-4) treatment, anti–TIM-3-treatment did not enhance acute graft-versus-host disease (aGVHD). TIM-3 and its ligands were frequently expressed in acute myeloid leukemia (AML) cells of patients with post–allo-HCT relapse. We decipher the connections between oncogenic mutations found in AML and TIM-3 ligand expression and identify anti–TIM-3 treatment as a strategy for enhancing GVL effects via metabolic and transcriptional Tc reprogramming without exacerbation of aGVHD. Our findings support clinical testing of anti–TIM-3 Ab in patients with AML relapse after allo-HCT.

Background Triple negative breast cancer (TNBC) is a distinct subtype of breast cancer burdened with a dismal prognosis due to the lack of effective therapeutic agents. Receptors for LHRH (luteinizing hormone-releasing hormone) can be successfully targeted with AEZS-108 [AN-152], an analog of LHRH conjugated to doxorubicin. Our study evaluates the presence of this target LHRH receptor in human specimens of TNBC and investigates the efficacy and toxicity of AEZS-108 in vivo. We also studied in vitro activity of AEZS-125, a new LHRH analog conjugated with the highly potent natural compound, Disorazol Z. Methods 69 human surgical specimens of TNBC were investigated for LHRH-R expression by immunohistochemistry. Expression of LHRH-R in two TNBC cell lines was evaluated by real time RT-PCR. Cytotoxicity of AEZS-125 was evaluated by Cell Titer Blue cytoxicity assay. LHRH- receptor expression was silenced with an siRNA in both cell lines. For the in vivo experiments an athymic nude mice model xenotransplanted with the cell lines, MDA-MB-231 and HCC 1806, was used. The animals were randomised to three groups receiving solvent only (d 1, 7, 14, i.v.) for control, AEZS-108 (d 1, 7, 14, i.v.) or doxorubicin at an equimolar dose (d 1, 7, 14, i.v.). Results In human clinical specimens of TNBC, expression of the LHRH-receptor was present in 49% (n = 69). HCC 1806 and MDA-MB-231 TNBC cells expressed mRNA for the LHRH-receptor. Silencing of the LHRH-receptor significantly decreased the cytotoxic effect of AEZS-108. MDA-MB-231 and HCC 1806 tumors xenografted into nude mice were significantly inhibited by treatment with AEZS-108; doxorubicin at equimolar doses was ineffective. As compared to AEZS 108, the Disorazol Z – LHRH conjugate, AEZS-125, demonstrated an increased cytotoxicity in vitro in HCC 1806 and MDA-MB-231 TNBC; this was diminished by receptor blockade with synthetic LHRH agonist (triptorelin) pretreatment. Conclusion The current study confirms that LHRH-receptors are expressed by a significant proportion of TNBC and can be successfully used as homing sites for cytotoxic analogs of LHRH, such as AEZS-108 and AEZS-125.

Load-forecasting problems have already been widely addressed with different approaches, granularities and objectives. Recent studies focused not only on deep learning methods but also on forecasting loads on single building level. This study aims to research problems and possibilities arising by using different load-forecasting techniques to manage loads. For that behavior of two neural networks, Long Short-Term Memory and Feed-Forward Neural Network as well as two statistical methods, standardized load profiles and personalized standardized load profiles are analyzed and assessed by using a sliding-window forecast approach. The results show that personalized standardized load profiles (MAE: 3.99) can perform similar to deep learning methods (for example, LSTM MAE: 4.47). However, because of the simplistic approach, load profiles are not able to adapt to new patterns. As a case study for evaluating the support of load-forecasting for applications in energy management systems, the integration of charging stations into an existing building is simulated by using load-forecasts to schedule the charging procedures. It is shown that forecast- based controlled charging can have a significant impact by lowering overload peaks exceeding the house connection point power limit (controlled charging 20.24 kW; uncontrolled charging: 65.15 kW) while slightly increasing average charging duration. It is concluded that integration of high flexible loads can be supported by using forecast-based energy management systems with regards to their limitations.