Signal Signature Research Articles

Investigating the Response of Vegetation to Flash Droughts by Using Cross-Spectral Analysis and an Evapotranspiration-Based Drought Index

Flash droughts tend to cause severe damage to agriculture due to their characteristics of sudden onset and rapid intensification. Early detection of the response of vegetation to flash droughts is of utmost importance in mitigating the effects of flash droughts, as it can provide a scientific basis for establishing an early warning system. The commonly used method of determining the response time of vegetation to flash drought, based on the response time index or the correlation between the precipitation anomaly and vegetation growth anomaly, leads to the late detection of irreversible drought effects on vegetation, which may not be sufficient for use in analyzing the response of vegetation to flash drought for early earning. The evapotranspiration-based (ET-based) drought indices are an effective indicator for identifying and monitoring flash drought. This study proposes a novel approach that applies cross-spectral analysis to an ET-based drought index, i.e., Evaporative Stress Anomaly Index (ESAI), as the forcing and a vegetation-based drought index, i.e., Normalized Vegetation Anomaly Index (NVAI), as the response, both from medium-resolution remote sensing data, to estimate the time lag of the response of vegetation vitality status to flash drought. An experiment on the novel method was carried out in North China during March–September for the period of 2001–2020 using remote sensing products at 1 km spatial resolution. The results show that the average time lag of the response of vegetation to water availability during flash droughts estimated by the cross-spectral analysis over North China in 2001–2020 was 5.9 days, which is shorter than the results measured by the widely used response time index (26.5 days). The main difference between the phase lag from the cross-spectral analysis method and the response time from the response time index method lies in the fundamental processes behind the definitions of the vegetation response in the two methods, i.e., a subtle and dynamic fluctuation signature in the response signal (vegetation-based drought index) that correlates with the fluctuation in the forcing signal (ET-based drought index) versus an irreversible impact indicated by a negative NDVI anomaly. The time lag of the response of vegetation to flash droughts varied with vegetation types and irrigation conditions. The average time lag for rainfed cropland, irrigated cropland, grassland, and forest in North China was 5.4, 5.8, 6.1, and 6.9 days, respectively. Forests have a longer response time to flash droughts than grasses and crops due to their deeper root systems, and irrigation can mitigate the impacts of flash droughts. Our method, based on cross-spectral analysis and the ET-based drought index, is innovative and can provide an earlier warning of impending drought impacts, rather than waiting for the irreversible impacts to occur. The information detected at an earlier stage of flash droughts can help decision makers in developing more effective and timely strategies to mitigate the impact of flash droughts on ecosystems.

GWAK: gravitational-wave anomalous knowledge with recurrent autoencoders

Matched-filtering detection techniques for gravitational-wave (GW) signals in ground-based interferometers rely on having well-modeled templates of the GW emission. Such techniques have been traditionally used in searches for compact binary coalescences (CBCs), and have been employed in all known GW detections so far. However, interesting science cases aside from compact mergers do not yet have accurate enough modeling to make matched filtering possible, including core-collapse supernovae and sources where stochasticity may be involved. Therefore the development of techniques to identify sources of these types is of significant interest. In this paper, we present a method of anomaly detection based on deep recurrent autoencoders to enhance the search region to unmodeled transients. We use a semi-supervised strategy that we name ‘Gravitational Wave Anomalous Knowledge’ (GWAK). While the semi-supervised approach to this problem entails a potential reduction in accuracy compared to fully supervised methods, it offers a generalizability advantage by enhancing the reach of experimental sensitivity beyond the constraints of pre-defined signal templates. We construct a low-dimensional embedded space using the GWAK method, capturing the physical signatures of distinct signals on each axis of the space. By introducing signal priors that capture some of the salient features of GW signals, we allow for the recovery of sensitivity even when an unmodeled anomaly is encountered. We show that regions of the GWAK space can identify CBCs, detector glitches and also a variety of unmodeled astrophysical sources.

PhuEGO: A Network-Based Method to Reconstruct Active Signaling Pathways From Phosphoproteomics Datasets

Signaling networks are critical for virtually all cell functions. Our current knowledge of cell signaling has been summarized in signaling pathway databases, which, while useful, are highly biased toward well-studied processes, and do not capture context specific network wiring or pathway cross-talk. Mass spectrometry-based phosphoproteomics data can provide a more unbiased view of active cell signaling processes in a given context, however, it suffers from low signal-to-noise ratio and poor reproducibility across experiments. While progress in methods to extract active signaling signatures from such data has been made, there are still limitations with respect to balancing bias and interpretability. Here we present phuEGO, which combines up-to-three-layer network propagation with ego network decomposition to provide small networks comprising active functional signaling modules. PhuEGO boosts the signal-to-noise ratio from global phosphoproteomics datasets, enriches the resulting networks for functional phosphosites and allows the improved comparison and integration across datasets. We applied phuEGO to five phosphoproteomics data sets from cell lines collected upon infection with SARS CoV2. PhuEGO was better able to identify common active functions across datasets and to point to a subnetwork enriched for known COVID-19 targets. Overall, phuEGO provides a flexible tool to the community for the improved functional interpretation of global phosphoproteomics datasets.

Experimental Identification of a Coupled-Circuit Model for the Digital Twin of a Wound-Rotor Induction Machine

The development of monitoring and diagnostic methods for electrical machines requires the use of transient models capable of operating in real time and producing signal signatures with high precision. In this context, coupled-circuit models offer numerous advantages due to their speed of execution and accuracy. They have been successfully employed to create real-time digital twins of electrical machines. The main challenge of this modeling method lies in the preparation of the model, which involves numerous preliminary calculations and takes time to identify all its parameters. This is particularly due to the variation in inductances based on the rotor position. To determine these inductance values with great precision, the classical approach involves using finite-element field calculation software. However, the computation time quickly becomes an issue due to the large number of values to calculate and simulations to perform. This article introduces an innovative experimental approach to identify a coupled-circuit model and develop a digital twin of a wound-rotor induction machine. This method relies solely on simple electrical measurements and tests conducted at extremely low rotation speeds (1 rpm) to obtain inductance variations as a function of the rotor position. By employing this technique, the need for analytical models or finite-element field calculation simulations, which typically require precise knowledge of the machine’s geometry and materials, is circumvented. The measurement processing employs optimization methods to extract the inductances as a function of the rotor position, which are then used as input data for the coupled-circuit model. The final parameters are specific to each machine and replicate all its manufacturing imperfections such as eccentricity and geometric or winding defects. This experimental identification method significantly enhances the model’s accuracy and reduces the usually required preliminary calculation time in a finite-element-based identification process.

Abstract LB037: E3 pairing and structural mechanisms underlying anti-tumor activity of clinical STAT3 degrader KT-333

Abstract To elucidate the underlying mechanisms of STAT3 degradation and the suitability of VHL as an E3 ligase partner for targeting STAT3 in cancer using our clinical degrader, KT-333. Signal transducer and activator of transcription 3 (STAT3) is an undrugged oncogenic transcription factor and its role as cancer driver and tumor microenvironment modulator has been validated in a multitude of studies. Based on it’s potential as a target for cancer therapeutics and limitations of prior approaches, we developed KT-333, a first-in-class, potent, highly selective, heterobifunctional STAT3 degrader currently in Phase 1 clinical trials. Here, based on STAT3 degradation by multiple E3s based degraders, structure of STAT3-KT333-VHL and a lysine site-resolved target ubiquitination model, we provide evidence for VHL as the ideal partner E3 for targeting STAT3 in cancer. We successfully identified potent and selective STAT3 degraders using either CRBN or VHL as the E3 ligase, but ultimately preferred VHL based degraders for their increased potency, and consistent STAT3 degradation across multiple cancer lines. KT-333, our VHL based clinical STAT3 degrader, induces a strong ternary complex between STAT3 and VHL. We present a high resolution cryo-electron microscopy based ternary complex structure of STAT3-KT333-VHL which provides mechanistic insights further validating VHL as the E3 of choice for deep, selective and fast STAT3 degradation. Specifically, KT-333 enables favorable protein-protein interactions between STAT3 and VHL, burying a large protein interface in the ternary complex to the extent typically observed only in native protein complexes. Additionally, the residues forming the STAT3-VHL interface are not conserved in other STAT family members corroborating with degradation selectivity observed with KT-333. Next, we leveraged this structure and generated a ubiquitination super-complex model by deploying a combination of biochemical and proteomics techniques and reveal that KT-333-induced ubiquitination occurs by precise targeting of specific lysine resides on STAT3. Furthermore, to decode the mechanism for KT-333 activity against SUDHL1 cell line both in vitro and in a mouse xenograft model, we measured temporal changes at protein level by discovery proteomics. Reduced expression of canonical STAT3 targets and down-regulation of cytokine-mediated signaling and cell cycle signature genes indicated that cell cycle arrest and subsequent apoptosis are the main drivers of efficacy in vitro and in vivo. In summary, we show that our clinical STAT3 degrader, KT-333, is designed and optimally paired with VHL resulting in a very stable ternary complex exhibiting properties of native protein complexes. Our data provides precise structural and molecular mechanisms behind potent, selective, consistent, and fast degradation of STAT3, and downstream mechanism of action observed in vitro and in vivo. Citation Format: Kirti Sharma, Xue Fei, Yatao Shi, Christopher Browne, Dirk Walther, Caroline Daigle, Anand Ramanathan, Richard Miller, Karen Yuan, Kiran Mahasenan, Sean Zhu, Xin Huang, Bin Yang. E3 pairing and structural mechanisms underlying anti-tumor activity of clinical STAT3 degrader KT-333 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB037.

Pharmacological fingerprint of antipsychotic drugs at the serotonin 5-HT2A receptor.

The intricate involvement of the serotonin 5-HT2A receptor (5-HT2AR) both in schizophrenia and in the activity of antipsychotic drugs is widely acknowledged. The currently marketed antipsychotic drugs, although effective in managing the symptoms of schizophrenia to a certain extent, are not without their repertoire of serious side effects. There is a need for better therapeutics to treat schizophrenia for which understanding the mechanism of action of the current antipsychotic drugs is imperative. With bioluminescence resonance energy transfer (BRET) assays, we trace the signaling signature of six antipsychotic drugs belonging to three generations at the 5-HT2AR for the entire spectrum of signaling pathways activated by serotonin (5-HT). The antipsychotic drugs display previously unidentified pathway preference at the level of the individual Gα subunits and β-arrestins. In particular, risperidone, clozapine, olanzapine and haloperidol showed G protein-selective inverse agonist activity. In addition, G protein-selective partial agonism was found for aripiprazole and cariprazine. Pathway-specific apparent dissociation constants determined from functional analyses revealed distinct coupling-modulating capacities of the tested antipsychotics at the different 5-HT-activated pathways. Computational analyses of the pharmacological and structural fingerprints support a mechanistically based clustering that recapitulate the clinical classification (typical/first generation, atypical/second generation, third generation) of the antipsychotic drugs. The study provides a new framework to functionally classify antipsychotics that should represent a useful tool for the identification of better and safer neuropsychiatric drugs and allows formulating hypotheses on the links between specific signaling cascades and in the clinical outcomes of the existing drugs.

Vocalization Pattern and Echolocation Signal Characteristics of Yangtze Finless Porpoise (Neophocaena asiaeorientalis asiaeorientalis) in Captivity

The Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis, YFP) possesses the ability to detect distance through echolocation signals, and its sonar signal signature is adjusted to detect different targets. In order to understand the vocal characteristics of YFPs in different behavioral states and their differential performance, we recorded the vocal activities of YFPs in captivity during free-swimming, feeding, and nighttime resting and quantified their signal characteristic parameters for statistical analysis and comparison. The results showed that the number of vocalizations of the YFPs in the daytime free-swimming state was lower than that in the feeding and nighttime resting states, and the echolocation signals emitted in these three states showed significant differences in the −10 dB duration, −3 dB bandwidth, −10 dB bandwidth, and root-mean-square (RMS) bandwidth. Analysis of the resolution of the echolocation signals of the YFPs using the ambiguity function indicated that their distance resolution could reach the millimeter level. These results indicate that the echolocation signal characteristics of YFPs present diurnal differences and that they can be adjusted with changes in their detection targets. The results of this study can provide certain scientific references and foundations for the studies of tooth whale behavioral acoustics, and provide relevant scientific guidance for the conservation and management of YFPs.

Constraining the Onset Density for the QCD Phase Transition with the Neutrino Signal from Core-collapse Supernovae

The occurrence of a first-order hadron–quark matter phase transition at high baryon densities is investigated in astrophysical simulations of core-collapse supernovae, to decipher yet incompletely understood properties of the dense matter equation of state (EOS) using neutrinos from such cosmic events. It is found that the emission of a nonstandard second neutrino burst, dominated by electron antineutrinos, is not only a measurable signal for the appearance of deconfined quark matter but also reveals information about the state of matter at extreme conditions encountered at the supernova (SN) interior. To this end, a large set of spherically symmetric SN models is investigated, studying the dependence on the EOS and the stellar progenitor. General relativistic neutrino-radiation hydrodynamics is employed featuring three-flavor Boltzmann neutrino transport and a microscopic hadron-quark hybrid matter EOS class. Therefore, the DD2 relativistic mean-field hadronic model is employed, and several variations of it, and the string-flip model for the description of deconfined quark matter. The resulting hybrid model covers a representative range of onset densities for the phase transition and latent heats. This facilitates the direct connection between intrinsic signatures of the neutrino signal and properties of the EOS. In particular, a set of linear relations has been found empirically. These potentially provide a constraint for the onset density of a possible QCD phase transition from the future neutrino observation of the next galactic core-collapse SN, if a millisecond electron anti-neutrino burst is present around or less than 1 s.

Dual-Encoded Affinity Microbead Signature Combinatorial Profiling for Acute Myocardial Infarction High-Sensitivity Diagnosis.

The early diagnosis of acute myocardial infarction (AMI) is dependent on the combined feedback of multiple cardiac biomarkers. However, it remains challenging to precisely detect multicardiac biomarkers in complex blood early due to the lack of sensitive and specific diagnostic indicators and the low abundance and small size of associated biomarkers with high specificity (such as microRNAs). To make matters worse, spectral overlap significantly limits the multiplex analysis of cardiac biomarkers by fluorescent probes, leading to bias in the diagnosis of myocardial infarction. Herein, we developed a method for simultaneous detection of miRNAs and protein biomarkers using size- and color-coded microbeads that carry signature for target capture. We also constructed a microfluidic chip with different spacer arrays that segregate these microbeads in different chip regions according to their size to produce signature signals, indicating the level of different biomarkers. The signals on the microbeads were hugely amplified by catalytic hairpin assembly and rolling circle amplification. Notably, this strategy enables the simultaneous and in situ sensitive profiling of six kinds of biomarkers via adding two different fluorescent labels, removing the limitations of spectral overlap. We envision that the strategy has great potential for application in clinical diagnosis for AMI.

Abstract 5088: Evaluating TNF-receptor associated factor 2 (TRAF2) as a targetable driver of immune resistance in LKB1 deficient non-small cell lung cancer

Abstract STK11 is a serine-threonine kinase and tumor suppressor lost in about 25% of NSCLC. It potently regulates a network of downstream effector kinases in the AMPK family, thereby exerting major effects on cell signaling, metabolic activity, and epigenetic patterning. Clinically loss of STK11 in NSCLC is associated with poor response to immune checkpoint blockade. Several mechanisms of immune resistance have been identified involving both tumor intrinsic pathways as well as changes in the immune microenvironment. Dysregulation of cellular inhibitor of apoptosis proteins, specifically cIAP1 has been identified as a specific resistance mechanism, which was shown to also influence the STING pathway in the context of STK11 loss. However, there is a gap in understanding how loss of STK11 influences cIAP1 signaling.We evaluated cIAP1, its TRAF family member binding partners, and downstream NF-kB and immune signaling using a multiomic approach. Using CPTAC multiomic data of 110 lung adenocarcinomas, we observe discordance between protein vs mRNA expression for cIAP1, which shows no significant association with STK11 loss in mRNA, but is significantly over-expressed at the protein level (P<1e-4). Conversely, we identify TRAF2 as the only TRAF member whose expression is increased in STK11-deficient NSCLC, with concordant increase in both mRNA (P<1e-8) and protein (P<1e-10). Further, on the protein level TRAF2 and cIAP1 levels were highly correlated (P<1e-12), strongly suggesting that TRAF2 is the proximal factor driving dysregulation of cIAP1 signaling in these tumors. We also observe a correlated pattern of phosphorylation sites within cIAP1, TRAF2, and other NF-kB signaling members that we putatively link to STK11 loss. We confirm that TRAF2 mRNA is consistently over-expressed in STK11 deficient NSCLC across multiple additional transcriptomic datasets together comprising >2000 tumors. Across this large dataset we observe that among STK11-deficient tumors, TRAF2 is anti-correlated with NF-kB signaling and immune infiltration signatures, a relationship that is strikingly absent among the STK11-WT subset. Using GEMM cell lines (KRAS, TP53, STK11 GEMM; Winslow lab, Stanford), we derived STK11 mutant vs WT isogenic pairs and performed T-cell co-culture experiments using ovalbumin antigen and OT-I CD8 T-cells. This showed that inhibition of cIAP1 using birinapant was synergistic to CD8 cytotoxicity, as previously known, but the synergy was much more pronounced in STK11 mutant vs STK11-WT context (Bliss index 38, P<1e-10). Together, these data demonstrate that the link between STK11-loss and cIAP1 dysregulation is likely through over-expression of TRAF2, and support the strategy of targeting TRAF2/cIAP1 to overcome immune resistance STK11-deficient NSCLC. Citation Format: Bahareh Nourmohammadi, Joseph M. Amann, Rahul Shivahare, Qin Ma, Zihai Li, David P. Carbone, Jacob Kaufman. Evaluating TNF-receptor associated factor 2 (TRAF2) as a targetable driver of immune resistance in LKB1 deficient non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5088.

Abstract 2006: Deciphering the interplay of β-catenin/YAP signaling and alveolar lineage plasticity during targeted therapy in non-small cell lung cancer

Abstract Molecularly targeted therapies have significantly enhanced clinical outcomes by directly addressing oncogenic driver mutations in genes such as EGFR. However, despite the success of treatments targeting these mutations, long-term patient survival remains limited. This study investigates the molecular mechanisms underlying drug-tolerance in response to targeted therapies in non-small cell lung cancer (NSCLC). Using single-cell RNA sequencing of oncogene-driven human NSCLCs at the residual disease (RD) state during active targeted therapy, our investigation reveals an increase of an alveolar type I/II (AT1/2) mixed lineage program in surviving cancer cells, resembling an alveolar cell-like state. We observed increased WNT3A/4 ligands, FZD2 receptors, β-catenin signaling, and AT1/2 signatures at the RD stage. Consistent with clinical results, AT1/2 signatures and target genes of β-catenin and YAP are increased in drug-tolerant persister (DTP) cells in preclinical models. Additionally, we discovered that β-catenin and YAP form a stable nuclear protein complex in DTP cells. Disrupting β-catenin/YAP protein expression and stability in DTP cells by knocking down FZD2 or interrupting the destruction complex of β-catenin/YAP leads to re-sensitization to the EGFR inhibitor Osimertinib, suggesting a potential therapeutic approach. Furthermore, this therapeutic strategy decreased AT1/2 gene signatures. Our results highlight an interdependence between β-catenin and YAP, with both proteins playing crucial roles in sustaining DTP cells and promoting the alveolar cell like lineage plasticity. These findings shed light on the complex interplay between β-catenin/YAP signaling and alveolar signatures in the residual cancer state, offering mechanistic insights and potential therapeutic strategies to address drug tolerance and improve clinical outcomes. Citation Format: Yu-Ting Chou, Wei Wu, Daniel Kerr, Macey Slota, Trever Bivona. Deciphering the interplay of β-catenin/YAP signaling and alveolar lineage plasticity during targeted therapy in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2006.

Abstract 3696: Liquid biopsy biomarker analysis during treatment with 177Lu-PSMA-617 in castrate resistant prostate cancer

Abstract Background: Prostate-Specific Membrane Antigen (PSMA) is a highly expressed prostate cancer (PCa) cell surface protein regulated by androgen receptor signaling and the target of the recently approved radioligand therapy 177Lu-PSMA-617. While some patients have dramatic responses to this therapy, rates of upfront or acquired resistance are high even in patients with PSMA-PET-avid disease, and better biomarkers of 177Lu PSMA-617 response and resistance are needed to select patients more effectively for this therapy. To address this need, we evaluated the relationship between longitudinal circulating tumor cell (CTC) androgen signaling and PSMA expression to 177Lu-PSMA-617 response or resistance in patients with metastatic prostate cancer. We leveraged a CTC androgen signaling signature that we have previously shown is prognostic for patients with metastatic prostate cancer treated with AR signaling inhibitors. Methods: Longitudinal blood samples were collected from 20 patients for circulating tumor cell (CTC) analysis at C1D1, C2D1, C4D1, and C6D1. CTCs were isolated with antibodies to EpCAM followed by parallel enumeration, analysis of cell surface expression of PSMA and RNA extraction for AR or neuroendocrine marker transcriptional profiling. Results: CTC samples were assessed for PSMA cell surface protein expression prior to treatment and on treatment. FOLH1 (PSMA) gene expression was detected from CTCs at baseline that persisted through treatment. Gene expression representative of AR pathway activation was present in 70% of the cohort at baseline and 50% of patients at C2D1. Concordant with these observations, no significant decrease in CTC number or PSMA protein expression was seen from baseline to C2D1. However, increased CTC AR pathway activation at C2D1 was associated with increased mean serum PSA (155 vs 21.93 ng/ml) and was associated with decreased duration of response. Conclusions: Improved tools to predict who will respond to 177Lu-PSMA-617 and detect early treatment resistance and disease progression are needed. Here, we show that persistent CTC burden, CTC AR signaling, and CTC PSMA expression are common early in treatment with 177Lu-PSMA-617 and may be associated with lower likelihood of clinical response. Further ongoing studies are needed to elucidate the relationship between these liquid biopsy results and clinical outcomes. Citation Format: Jamie M. Sperger, Marina N. Sharifi, Luke Nunamaker, Viridiana Carreno, Alex H. Chang, Shannon R. Reese, Charlotte Linebarger, Amy K. Taylor, Grace C. Bliitzer, John Floberg, Shuang G. Zhao, Joshua M. Lang. Liquid biopsy biomarker analysis during treatment with 177Lu-PSMA-617 in castrate resistant prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3696.

Retinoid orphan receptor gamma t (rorγt) promotes inflammatory eosinophilia but is dispensable for innate immune-mediated colitis.

Inflammatory bowel diseases (IBD) result from uncontrolled inflammation in the intestinal mucosa leading to damage and loss of function. Both innate and adaptive immunity contribute to the inflammation of IBD and innate and adaptive immune cells reciprocally activate each other in a forward feedback loop. In order to better understand innate immune contributions to IBD, we developed a model of spontaneous 100% penetrant, early onset colitis that occurs in the absence of adaptive immunity by crossing villin-TNFAIP3 mice to RAG1-/- mice (TRAG mice). This model is driven by microbes and features increased levels of innate lymphoid cells in the intestinal mucosa. To investigate the role of type 3 innate lymphoid cells (ILC3) in the innate colitis of TRAG mice, we crossed them to retinoid orphan receptor gamma t deficient (Rorγt-/-) mice. Rorγt-/- x TRAG mice exhibited markedly reduced eosinophilia in the colonic mucosa, but colitis persisted in these mice. Colitis in Rorγt-/- x TRAG mice was characterized by increased infiltration of the intestinal mucosa by neutrophils, inflammatory monocytes, macrophages and other innate cells. RNA and cellular profiles of Rorγt-/- x TRAG mice were consistent with a lack of ILC3 and ILC3 derived cytokines, reduced antimicrobial factors, increased activation oof epithelial repair processes and reduced activation of epithelial cell STAT3. The colitis in Rorγt-/- x TRAG mice was ameliorated by antibiotic treatment indicating that microbes contribute to the ILC3-independent colitis of these mice. Together, these gene expression and cell signaling signatures reflect the double-edged sword of ILC3 in the intestine, inducing both proinflammatory and antimicrobial protective responses. Thus, Rorγt promotes eosinophilia but Rorγt and Rorγt-dependent ILC3 are dispensable for the innate colitis in TRAG mice.

EGFR signaling and pharmacology in oncology revealed with innovative BRET-based biosensors

Mutations of receptor tyrosine kinases (RTKs) are associated with the development of many cancers by modifying receptor signaling and contributing to drug resistance in clinical settings. We present enhanced bystander bioluminescence resonance energy transfer-based biosensors providing new insights into RTK biology and pharmacology critical for the development of more effective RTK-targeting drugs. Distinct SH2-specific effector biosensors allow for real-time and spatiotemporal monitoring of signal transduction pathways engaged upon RTK activation. Using EGFR as a model, we demonstrate the capacity of these biosensors to differentiate unique signaling signatures, with EGF and Epiregulin ligands displaying differences in efficacy, potency, and responses within different cellular compartments. We further demonstrate that EGFR single point mutations found in Glioblastoma or non-small cell lung cancer, impact the constitutive activity of EGFR and response to tyrosine kinase inhibitor. The BRET-based biosensors are compatible with microscopy, and more importantly characterize the next generation of therapeutics directed against RTKs.

Heterogeneous fusion of biometric and deep physiological features for accurate porcine cough recognition.

Accurate identification of porcine cough plays a vital role in comprehensive respiratory health monitoring and diagnosis of pigs. It serves as a fundamental prerequisite for stress-free animal health management, reducing pig mortality rates, and improving the economic efficiency of the farming industry. Creating a representative multi-source signal signature for porcine cough is a crucial step toward automating its identification. To this end, a feature fusion method that combines the biological features extracted from the acoustic source segment with the deep physiological features derived from thermal source images is proposed in the paper. First, acoustic features from various domains are extracted from the sound source signals. To determine the most effective combination of sound source features, an SVM-based recursive feature elimination cross-validation algorithm (SVM-RFECV) is employed. Second, a shallow convolutional neural network (named ThermographicNet) is constructed to extract deep physiological features from the thermal source images. Finally, the two heterogeneous features are integrated at an early stage and input into a support vector machine (SVM) for porcine cough recognition. Through rigorous experimentation, the performance of the proposed fusion approach is evaluated, achieving an impressive accuracy of 98.79% in recognizing porcine cough. These results further underscore the effectiveness of combining acoustic source features with heterogeneous deep thermal source features, thereby establishing a robust feature representation for porcine cough recognition.

TESTING OF PSEUDORANDOM SIGNAL GENERATORS BASED ON THE LORENTZ SYSTEM

This work presents results of the testing of modified pseudorandom signal generators. Two generators developed on the basis of the Lorentz system with chaotic dynamics are considered. The first generator is described by the Lorentz system implemented over a Galois field, and the second is described by the Lorentz system in which digital sequence formation occurs by periodic sampling from signal signatures. As an additional confirmation of the relevance of the results obtained, the article valuates a generator developed on the basis of the standard Matlab function for binary random sequence generating. Generator testing was carried out using a test battery developed by the National Institute of Standards and Technology, which includes 15 different tests. The results obtained are compared with the results obtained by testing reference generators. The results of this research can be applied in the development of cryptographic and data transmission systems.

Evidence for heterodimerization and functional interaction of the urotensin II and the angiotensin II type 1 receptors

Despite the observation of synergistic interactions between the urotensinergic and angiotensinergic systems, the interplay between the urotensin II receptor (hUT) and the angiotensin II type 1 receptor (hAT1R) in regulating cellular signaling remains incompletely understood. Notably, the putative interaction between hUT and hAT1R could engender reciprocal allosteric modulation of their signaling signatures, defining a unique role for these complexes in cardiovascular physiology and pathophysiology. Using a combination of co-immunoprecipitation, bioluminescence resonance energy transfer (BRET) and FlAsH BRET-based conformational biosensors, we first demonstrated the physical interaction between hUT and hAT1R. Next, to analyze how this functional interaction regulated proximal and distal hUT- and hAT1R-associated signaling pathways, we used BRET-based signaling biosensors and western blots to profile pathway-specific signaling in HEK 293 cells expressing hUT, hAT1R or both. We observed that hUT-hAT1R heterodimers triggered distinct signaling outcomes compared to their respective parent receptors alone. Notably, co-transfection of hUT and hAT1R has no impact on hUII-induced Gq activation but significantly reduced the potency and efficacy of Ang II to mediate Gq activation. Interestingly, URP, the second hUT endogenous ligand, produce a distinct signaling signature compared to hUII at hUT-hAT1R. Our results therefore suggest that assembly of hUT with hAT1R might be important for allosteric modulation of outcomes associated with specific hardwired signaling complexes in healthy and disease states. Altogether, our work, which potentially explains the interplay observed in native cells and tissues, validates such complexes as potential targets to promote the design of compounds that can modulate heterodimer function selectively.

Analysis of tumor biomarkers in patients (pts) with advanced hepatocellular carcinoma (HCC) from a phase 1b study of E7386, a CREB-binding protein/β-catenin interaction inhibitor, in combination with lenvatinib.

535 Background: E7386, a novel oral anticancer agent, inhibits β-catenin binding to its transcriptional co-activator CREB-binding protein, thus modulating Wnt/β-catenin signaling. Lenvatinib is a multikinase inhibitor that targets VEGFR 1–3, FGFR 1–4, PDGFRα, RET, and KIT. We previously reported the safety/tolerability, pharmacokinetics, biomarkers, and preliminary efficacy of E7386 plus lenvatinib in 25 pts with HCC in the dose escalation part of a phase 1b study1 (NCT04008797). Here, we present the results of exploratory tumor biomarker analyses from this study. Methods: Pts with HCC were treated with E7386 10–80 mg QD and 60–120 mg BID plus lenvatinib (bodyweight < 60 kg: 8 mg QD; ≥ 60 kg: 12 mg QD). Archival or fresh tumor samples were collected at baseline and post-treatment; tumor tissue was assessed for genetic alteration, immunohistochemistry (IHC), and gene expression. Gene signature scores of interest were calculated using obtained gene expression data. The preliminary association between biomarker status and efficacy was investigated. Results: Of the 25 pts enrolled, 22 had baseline tumor samples available for the gene mutation analysis. TERT (6 pts: 27%), CTNNB1 (5 pts: 23%), and TP53 (4 pts: 18%) mutations were detected. CTNNB1 mutation was confirmed in 3 of 7 responders and 2 of 13 non-responders. Nuclear β-catenin expression was confirmed by IHC analysis in 5 of 16 pts; it was expressed in 3 of 5 pts with CTNNB1 MUT and 2 of 11 pts with CTNNB1 WT. Pts with expression of nuclear β-catenin had 2 partial responses (PRs) among 5 pts; those without β-catenin expression had 2 PRs among 11 pts. Additionally, IHC analysis of tumor microvessel density (MVD; number of CD31+ vessels) at baseline suggested that greater maximum tumor shrinkage (MTS) tended to be observed in the MVD-high population compared to the MVD-low population. 7 Pts had evaluable baseline and post-baseline tumor samples and were included in the gene signature analysis. Despite the small sample size, preliminary results indicated that MTS may be associated with a decrease in Wnt signaling and angiogenesis gene signature scores (spearman r [r]=0.61 for both) and attenuation of hypoxic induction and glycolysis gene signature scores (r=0.79 and 0.68, respectively). Conclusions: These exploratory tumor biomarker analyses suggest that E7386 in combination with lenvatinib may affect the tumor microenvironment in HCC pts through effects on Wnt signaling, angiogenesis, hypoxic response, and glycolysis pathways. This concept is the basis for treatment with this combination. However, given the small sample size, further investigation is needed to confirm these effects on the tumor microenvironment. Enrollment of pts with HCC to the expansion part of Study 102 is ongoing. 1. Ikeda et al. ASCO 2023. Clinical trial information: NCT04008797 .

Seismic Station Monitoring Using Deviation from the Gaussianity

Abstract Degradation of the seismic signal quality sometimes occurs at permanent and temporary stations. Although the most likely cause is a high level of humidity, leading to corrosion of the connectors, environmental changes can also alter recording conditions in different frequency ranges and not necessarily for all three components in the same way. Assuming that the continuous seismic signal can be described by a normal distribution, we present a new approach to quantify the seismogram quality and to point out any time sample that deviates from this Gaussian assumption. We introduce the notion of background Gaussian signal (BGS) to characterize a set of samples that follows a normal distribution. The discrete function obtained by sorting the samples in ascending order of amplitudes is compared with a modified Probit function to retrieve the elements composing the BGS, and its statistical properties (mostly its standard deviation σG). As soon as there is any amplitude perturbation, σG deviates from the standard deviation of all samples composing the time window (σ). Hence, the parameter log(σσG) directly quantifies the alteration level. For a single day, a given frequency range and a given component, the median of all log(σσG) that can be computed using short-time windows, reflects the overall gaussianity of the continuous seismic signal. We demonstrate that it can be used to efficiently monitor the quality of seismic traces using this approach at four broadband permanent stations. We show that the daily log(σσG) is sensitive to both subtle changes on one or two components as well as the signal signature of a sensor’s degradation. Finally, we suggest that log(σσG) and other parameters that are computed from the BGS bring useful information for station monitoring in addition to existing methods.

Gpcpd1-GPC metabolic pathway is dysfunctional in aging and its deficiency severely perturbs glucose metabolism.

Skeletal muscle plays a central role in the regulation of systemic metabolism during lifespan. With aging, this function is perturbed, initiating multiple chronic diseases. Our knowledge of mechanisms responsible for this decline is limited. Glycerophosphocholine phosphodiesterase 1 (Gpcpd1) is a highly abundant muscle enzyme that hydrolyzes glycerophosphocholine (GPC). The physiological functions of Gpcpd1 remain largely unknown. Here we show, in mice, that the Gpcpd1-GPC metabolic pathway is perturbed in aged muscles. Further, muscle-specific, but not liver- or fat-specific, inactivation of Gpcpd1 resulted in severely impaired glucose metabolism. Western-type diets markedly worsened this condition. Mechanistically, Gpcpd1 muscle deficiency resulted in accumulation of GPC, causing an 'aged-like' transcriptomic signature and impaired insulin signaling in young Gpcpd1-deficient muscles. Finally, we report that the muscle GPC levels are markedly altered in both aged humans and patients with type 2 diabetes, displaying a high positive correlation between GPC levels and chronological age. Our findings reveal that the muscle GPCPD1-GPC metabolic pathway has an important role in the regulation of glucose homeostasis and that it is impaired during aging, which may contribute to glucose intolerance in aging.