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Origami art has found numerous engineering applications. Many studies show that folding structures are the source of the desired system characteristics. In this article, we discuss the design of a beach umbrella based on the principles of origami and the study of its optical and mechanical properties. The main requirements for the designed model are that it should reduce the harmful effects of solar radiation on human health, should be compact for storage, and not collapse in the wind. To demonstrate the optical and mechanical properties of the designed model, the developed recursive ray tracing algorithm is used to simulate the propagation of light rays through the designed paper origami-based structure and the numerical simulations are performed using the commercial software ANSYS and LS-DYNA to study the behavior of the designed origami-based structure under lateral forces as well as its folding behavior. A combination of ray tracing approach and an optimization technique based on the genetic algorithm for modifying the developed model is also discussed. Simulation results are presented in the illustrations.

BackgroundPredicting the risk of immune-related adverse events (IrAEs) in patients receiving immune checkpoint blockade (ICB) therapy is crucial for optimizing safety and treatment outcomes. While single biomarkers have been implicated in risk stratification, multi-modal data integration can greatly enhance prediction accuracy.1–3 Here, we developed a blood-based, multi-modal predictor for estimating severe irAE risk prior to ICB initiation.MethodsClinical annotations, HLA genotyping, and bulk RNA-sequencing data from peripheral blood were analyzed across three cohorts: cancer patients prior to ICB therapy (Cohorts 1 and 2) and individuals with inflammatory bowel disease (IBD) or healthy controls (Cohort 3) (table 1). Events with grades ≥3 were defined as severe IrAEs. RNA-seq data were preprocessed to evaluate features such as immune signatures,4 cell composition,5 immunotypes,6 and TCR diversity. For overall IrAE risk estimation, the CatBoost classifier was used to train predictors on clinical data,7 while a logistic regression model was trained on integrated clinical and transcriptomic data. A genetic-based model based on HLA alleles was also developed to predict specific IrAE types.ResultsA CatBoost classifier trained to assess IrAE risk based on clinical data from Train Set 1 predicted severe irAEs in Test Sets 1 (AUC=0.72) and 2 (AUC=0.59). Age, therapy type, and diagnosis were the major risk determinants. We improved the model’s predictive capacity by combining its output with transcriptomic data (12 preprocessed features) and training a logistic regression classifier on Train Set 1, subsequently achieving AUC=0.79 in Test Set 1 and AUC=0.63 in Test Set 2. Features related to immune regulation (such as CD4+ T-cell activation, myeloid-cell-mediated suppression, and Treg activity) were strongly associated with severe IrAEs. Finally, using train and test sets from Cohort 3, we developed a CatBoost classifier based on 46 HLA alleles associated with risk of and protection against autoimmune colitis. This genetic-based model predicted the likelihood of colitis with AUC=0.68 in patients with severe IrAEs from Cohort 1, revealing a threefold HLA-driven increase in colitis risk (OR=2.8).ConclusionsOur multi-modal, machine-learning approach provides a robust framework for assessing severe IrAE risk before ICB initiation. Early identification and monitoring of high-risk patients will enable physicians to mitigate IrAEs in a timely manner, thus improving patient outcomes.ReferencesAli O, Berner F, Bomze D, Fässler M, Diem S, Cozzio A, Jörger M, Früh M, Driessen C, Lenz TL, Flatz L. Human leukocyte antigen variation is associated with adverse events of checkpoint inhibitors. Eur J Cancer. 2019;107:8–14.Ye W, Olsson-Brown A, Watson R, Cheung V, Morgan R, Nassiri I, Cooper R, Taylor C, Akbani U, Brain O, Matin R, Coupe N, Middleton M, Coles M, Sacco J, Payne M, Fairfax B. Checkpoint-blocker-induced autoimmunity is associated with favourable outcome in metastatic melanoma and distinct T-cell expression profiles. Br J Cancer. 2021;124(11):1661–1669.Kim KH, Hur JY, Cho J, Ku BM, Koh J, Koh JY, Sun JM, Lee SH, Ahn JS, Park K, Ahn MJ, Shin EC. Immune-related adverse events are clustered into distinct subtypes by T-cell profiling before and early after anti-PD-1 treatment. Oncoimmunology. 2020;9(1):1722023.1–12.Bolshakov E, Vasileva T, Kust S, Frank A, Savchenko M, Wang I, Conroy T, Merriam NR, Markova K, Brunovlenskaia-Bogoiavlenskaia A, Ushakova E, Ambarian S, Mulyukina A, Shilov E, Arutyunyan N, Shchetsova A, Shulga P, Spirin D, Terenteva A, Goldberg MF, Lawless A, Boland GM, Sullivan RJ, Zaytcev A. Identifying a composite signature for predicting immune-related adverse events in advanced melanoma patients treated with immune checkpoint blockade. J Immunother Cancer. 2024;12:e144.Zaitsev A, Chelushkin M, Dyikanov D, Cheremushkin I, Shpak B, Nomie K, Zyrin V, Nuzhdina E, Lozinsky Y, Zotova A, Degryse S, Kotlov N, Baisangurov A, Shatsky V, Afenteva D, Kuznetsov A, Paul SR, Davies DL, Reeves PM, Lanuti M, Goldberg MF, Tazearslan C, Chasse M, Wang I, Abdou M, Aslanian SM, Andrewes S, Hsieh JJ, Ramachandran A, Lyu Y, Galkin I, Svekolkin V, Cerchietti L, Poznansky MC, Ataullakhanov RI, Fowler N, Bagaev A. Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial transcriptomes. Cancer Cell. 2022;40(8):879–894.e16.Dyikanov D, Zaitsev A, Vasileva T, Wang I, Sokolov A, Bolshakov E, Frank A, Turova P, Golubeva O, Gantseva A, Kamysheva A, Shpudeiko P, Krauz I, Abdou M, Chasse M, Conroy T, Merriam NR, Alesse JE, English N, Shpak B, Shchetsova A, Tikhonov E, Filatov I, Radko A, Bolshakova A, Kachalova A, Lugovykh N, Bulahov A, Kilina A, Asanbekov S, Zheleznyak I, Skoptsov P, Alekseeva E, Johnson JM, Curry JM, Linnenbach AJ, South AP, Yang EJ, Morozov K, Terenteva A, Nigmatullina L, Fastovetz D, Bobe A, Balabanian L, Nomie K, Yong ST, Davitt CJH, Ryabykh A, Kudryashova O, Tazearslan C, Bagaev A, Fowler N, Luginbuhl AJ, Ataullakhanov R, Goldberg MF. Comprehensive peripheral blood immunoprofiling reveals five immunotypes with immunotherapy response characteristics in patients with cancer. Cancer Cell. 2024;42(5):759–779.e12.Quandt Z, Lucas A, Liang SI, Yang E, Stone S, Fadlullah MZH, Bayless NL, Marr SS, Thompson MA, Padron LJ, Bucktrout S, Butterfield LH, Tan AC, Herold KC, Bluestone JA, Anderson MS, Spencer CN, Young A, Connolly JE. Associations between immune checkpoint inhibitor response, immune-related adverse events, and steroid use in RADIOHEAD: a prospective pan-tumor cohort study. J Immunother Cancer. 2025 May 12;13(5):e011545.Ethics ApprovalThis study involves human participants and was approved by WCG IRB Protocol #20182579. Participants gave informed consent to participate in the study before taking part.Abstract 1094 Table 1Cohort description

A novel quasi-statistical approach to improve the quality of triangular meshes is presented. The present method is based on modeling of an event of the mesh improvement. This event is modeled via modeling of a discrete random variable. The random variable is modeled in a tangent plane of each local domain of the mesh. One domain collects several elements with a common point. Values of random variable are calculated by modeling formula according to the initial sampling data of the projected elements with respect to all neighbors of the domain. Geometrical equivalent called potential form is constructed for each element of the domain with a mesh quality parameter value equal to the modeled numerical value. Such potential forms create potential centers of the domain. Averaging the coordinates of potential centers of the domain gives a new central point position. After geometrical realization over the entire mesh, the shapes of triangular elements are changed according to the normal distribution. It is shown experimentally that the mean of the final mesh is better than the initial one in most cases, so the event of the mesh improvement is likely occurred. Moreover, projection onto a local tangent plane included in the algorithm allows preservation of the model volume enclosed by the surface mesh. The implementation results are presented to demonstrate the functionality of the method. Our approach can provide a flexible tool for the development of mesh improvement algorithms, creating better-input parameters for the triangular meshes and other kinds of meshes intended to be applied in finite element analysis or computer graphics.[PUBLICATION ABSTRACT]

We study the qualitative properties of functions belonging to the corresponding De Giorgi classes \\begin{equation*} \\int\\limits_{B_{r(1-\\sigma)}(x_{0})}\\,\\varPhi(x, |\\nabla(u-k)_{\\pm}|)\\,dx \\leqslant \\gamma\\,\\int\\limits_{B_{r}(x_{0})}\\,\\varPhi\\bigg(x, \\frac{(u-k)_{\\pm}}{\\sigma r}\\bigg)\\,dx, \\end{equation*} where \\(\\sigma\\), \\(r \\in (0,1)\\), \\(k\\in \\mathbb{R}\\) and the function \\(\\varPhi\\) satisfies the non-logarithmic condition \\begin{equation*} \\bigg(r^{-n}\\int\\limits_{B_{r}(x_{0})}[\\varPhi\\big(x,\\frac{v}{r}\\big)]^{s}\\,dx\\bigg)^{\\frac{1}{s}}\\bigg(r^{-n}\\int\\limits_{B_{r}(x_{0})}[\\varPhi\\big(x,\\frac{v}{r}\\big)]^{-t}\\,dx\\bigg)^{\\frac{1}{t}}\\leqslant c(K) \\Lambda(x_{0},r),\\quad r\\leqslant v\\leqslant K\\,\\lambda(r), \\end{equation*} under some assumptions on the functions \\(\\lambda(r)\\) and \\(\\Lambda(x_{0}, r)\\) and the numbers \\(s\\), \\(t >1\\). These conditions generalize the known logarithmic, non-logarithmic and non uniformly elliptic conditions. In particular, our results cover new cases of non uniformly elliptic double-phase, degenerate double-phase functionals and functionals with variable exponents.

The arms race among microorganisms is a key driver in the evolution of not only the weapons but also defence mechanisms. Many Gram-negative bacteria use the type six secretion system (T6SS) to deliver toxic effectors directly into neighbouring cells. Defence against effectors requires cognate immunity proteins. However, here we show immunity-independent protection mediated by envelope stress responses in Escherichia coli and Vibrio cholerae against a V. cholerae T6SS effector, TseH. We demonstrate that TseH is a PAAR-dependent species-specific effector highly potent against Aeromonas species but not against its V. cholerae immunity mutant or E. coli . A structural analysis reveals TseH is probably a NlpC/P60-family cysteine endopeptidase. We determine that two envelope stress-response pathways, Rcs and BaeSR, protect E. coli from TseH toxicity by mechanisms including capsule synthesis. The two-component system WigKR (VxrAB) is critical for protecting V. cholerae from its own T6SS despite expressing immunity genes. WigR also regulates T6SS expression, suggesting a dual role in attack and defence. This deepens our understanding of how bacteria survive T6SS attacks and suggests that defence against the T6SS represents a major selective pressure driving the evolution of species-specific effectors and protective mechanisms mediated by envelope stress responses and capsule synthesis. Defence against type six secretion system (T6SS) effectors is thought to be mostly mediated by dedicated immunity proteins that antagonize specific effector proteins. Here, two envelope stress-response pathways, Rcs and BaeSR, are shown to regulate protection against the T6SS effector TseH by modulating the integrity of the bacterial envelope in a manner independent of immunity proteins.

High-quality, 25 nm octahedral-shaped Fe 3 O 4 magnetite nanocrystals are epitaxially grown on 9 nm Au seed nanoparticles using a modified wet-chemical synthesis. These Fe 3 O 4 -Au Janus nanoparticles exhibit bulk-like magnetic properties. Due to their high magnetization and octahedral shape, the hybrids show superior in vitro and in vivo T 2 relaxivity for magnetic resonance imaging as compared to other types of Fe 3 O 4 -Au hybrids and commercial contrast agents. The nanoparticles provide two functional surfaces for theranostic applications. For the first time, Fe 3 O 4 -Au hybrids are conjugated with two fluorescent dyes or the combination of drug and dye allowing the simultaneous tracking of the nanoparticle vehicle and the drug cargo in vitro and in vivo . The delivery to tumors and payload release are demonstrated in real time by intravital microscopy. Replacing the dyes by cell-specific molecules and drugs makes the Fe 3 O 4 -Au hybrids a unique all-in-one platform for theranostics.

The grey wolf ( Canis lupus ) is a pivotal species for ecological studies. As a key participant in ecosystem processes, it also serves as a model for investigating social structure formation and ecological adaptation. However, the species’ complex social behavior, spatial dynamics, and expansive habitats make monitoring and population assessments across large areas particularly challenging. In recent years, audio traps have been used to collect extensive datasets of wolf vocalizations, particularly howls. Yet, manually detecting wolf howls in lengthy recordings remains a labor-intensive and inefficient task. We propose an approach leveraging modern machine-learning techniques to address this challenge. Following a comprehensive analysis of sound processing methods, we developed two state-of-the-art deep learning models based on the Audio Spectrogram Transformer architecture. The first model classifies audio for the presence of animal sounds with a precision of 98.3% and a recall of 99.3%. The second model distinguishes wolf howls from other animal sounds with a precision of 89.6% and a recall of 93.4%. These models significantly enhance the efficiency and accuracy of wolf vocalization detection, supporting ecological monitoring and research efforts.

Size-selected Fe3O4–Au hybrid nanoparticles with diameters of 6–44 nm (Fe3O4) and 3–11 nm (Au) were prepared by high temperature, wet chemical synthesis. High-quality Fe3O4 nanocrystals with bulk-like magnetic behavior were obtained as confirmed by the presence of the Verwey transition. The 25 nm diameter Fe3O4–Au hybrid nanomaterial sample (in aqueous and agarose phantom systems) showed the best characteristics for application as contrast agents in magnetic resonance imaging and for local heating using magnetic particle hyperthermia. Due to the octahedral shape and the large saturation magnetization of the magnetite particles, we obtained an extraordinarily high r 2-relaxivity of 495 mM−1·s−1 along with a specific loss power of 617 W·gFe −1 and 327 W·gFe −1 for hyperthermia in aqueous and agarose systems, respectively. The functional in vitro hyperthermia test for the 4T1 mouse breast cancer cell line demonstrated 80% and 100% cell death for immediate exposure and after precultivation of the cells for 6 h with 25 nm Fe3O4–Au hybrid nanomaterials, respectively. This confirms that the improved magnetic properties of the bifunctional particles present a next step in magnetic-particle-based theranostics.

Background/Objectives: Indolo[2,3-a]pyrrolo[3,4-c]carbazole scaffold is successfully used as an efficient structural motif for the design and development of different antitumor agents. In this study, we investigated the anti-glioblastoma therapeutic potential of glycosylated indolocarbazole analog LCS1269 utilizing in vitro, in vivo, and in silico approaches. Methods: Cell viability was estimated by an MTT assay. The distribution of cell cycle phases was monitored using flow cytometry. Mitotic figures were visualized by fluorescence microscopy. Quantitative RT-PCR was used to evaluate the gene expression. The protein expression was assessed by Western blotting. Molecular docking and computational ADMET were approved for the probable protein target simulations and predicted pharmacological assessments, respectively. Results: Our findings clearly suggest that LCS1269 displayed a significant cytotoxic effect against diverse glioblastoma cell lines and patient-derived glioblastoma cultures as well as strongly suppressed xenograft growth in nude mice. LCS1269 exhibited more potent anti-proliferative activity toward glioblastoma cell lines and patient-derived glioblastoma cultures compared to conventional drug temozolomide. We further demonstrated that LCS1269 treatment caused the severe G2 phase arrest of cell cycle in a dose-dependent manner. Mechanistically, we proposed that LCS1269 could affect the CDK1 activity both by targeting active site of this enzyme and indirectly, in particular through the modulation of the Wee1/Myt1 and FOXM1/Plk1 signaling pathways, and via p21 up-regulation. LCS1269 also showed favorable pharmacological characteristics in in silico ADME prediction in comparison with staurosporine, rebeccamycin, and becatecarin as reference drugs. Conclusions: Further investigations of LCS1269 as an anti-glioblastoma medicinal agent could be very promising.