A novel AIE-based mitochondria-targeting fluorescent probe for monitoring of the fluctuation of endogenous hypochlorous acid in ferroptosis models.

Ferroptosis is a way of cell death mainly due to the imbalance between the production and degradation of lipid reactive oxygen species, which is closely associated with various diseases. Endogenous hypochlorous acid (HOCl) mainly produced in mitochondria is regarded as an important signal molecule of ferroptosis. Therefore, monitoring the fluctuation of endogenous HOCl is beneficial to better understand and treat ferroptosis-related diseases. Inspired by the promising aggregation-induced emission (AIE) properties of tetraphenylethene (TPE), herein, we rationally constructed a novel AIE-based fluorescent probe, namely QTrPEP, for HOCl with nice mitochondria-targeting ability and high sensitivity and selectivity. Probe QTrPEP consisted of phenylborate ester and the AIE fluorophore of quinoline-conjugated triphenylethylene (QTrPE). HOCl can brighten the strong fluorescence through a specific HOCl-triggered cleavage of the phenylborate ester bond and release of QTrPE, which has been demonstrated by MS, HPLC, and DLS experiments. In addition, combining QTrPE-doped test strips with a smartphone-based measurement demonstrated the excellent performance of the probe to sense HOCl. The obtained favorable optical properties and negligible cytotoxicity allowed the use of this probe for tracking of HOCl in three different cells. In particular, this work represents the first AIE-based mitochondria-targeting fluorescent probe for monitoring the fluctuation of HOCl in ferroptosis.

Efficient and scalable prediction of stochastic reaction-diffusion processes using graph neural networks.

The dynamics of locally interacting particles that are distributed in space give rise to a multitude of complex behaviours. However the simulation of reaction-diffusion processes which model such systems is highly computationally expensive, the cost increasing rapidly with the size of space. Here, we devise a graph neural network based approach that uses cheap Monte Carlo simulations of reaction-diffusion processes in a small space to cast predictions of the dynamics of the same processes in a much larger and complex space, including spaces modelled by networks with heterogeneous topology. By applying the method to two biological examples, we show that it leads to accurate results in a small fraction of the computation time of standard stochastic simulation methods. The scalability and accuracy of the method suggest it is a promising approach for studying reaction-diffusion processes in complex spatial domains such as those modelling biochemical reactions, population evolution and epidemic spreading.

A novel LD-targeting cysteine-activated fluorescent probe for diagnosis of APAP-induced liver injury and its application in food analysis.

Cysteine (Cys) not only plays an indispensable role in maintaining the redox balance in organisms, but is also an important nutrient in the food industry. Fluorescence-based detection systems have emerged as an effective method to track the locations and concentrations of different species. To achieve efficient monitoring of Cys in both food samples and biological systems, a novel lipid droplet (LD) targeted fluorescent probe (namely NIT-Cys) was constructed for the turn-on detection of Cys, characterized by a large Stokes shift (142 nm), a short response time (<8 min), and a low Cys detection limit (39 nM). Furthermore, the NIT-Cys probe has been successfully used not only to quantify the amounts of Cys in selected food samples, but also to enable the visualization of endogenous Cys in acetaminophen (APAP)-induced drug-induced liver injury cells, zebrafish larvae and mice models. Consequently, the work presented here provides an efficient tool for monitoring Cys.

A generative benchmark for evaluating the performance of fluorescent cell image segmentation.

Fluorescent cell imaging technology is fundamental in life science research, offering a rich source of image data crucial for understanding cell spatial positioning, differentiation, and decision-making mechanisms. As the volume of this data expands, precise image analysis becomes increasingly critical. Cell segmentation, a key analysis step, significantly influences quantitative analysis outcomes. However, selecting the most effective segmentation method is challenging, hindered by existing evaluation methods' inaccuracies, lack of graded evaluation, and narrow assessment scope. Addressing this, we developed a novel framework with two modules: StyleGAN2-based contour generation and Pix2PixHD-based image rendering, producing diverse, graded-density cell images. Using this dataset, we evaluated three leading cell segmentation methods: DeepCell, CellProfiler, and CellPose. Our comprehensive comparison revealed CellProfiler's superior accuracy in segmenting cytoplasm and nuclei. Our framework diversifies cell image data generation and systematically addresses evaluation challenges in cell segmentation technologies, establishing a solid foundation for advancing research and applications in cell image analysis.

Polyphyllin I induces rapid ferroptosis in acute myeloid leukemia through simultaneous targeting PI3K/SREBP-1/SCD1 axis and triggering of lipid peroxidation.

Acute myeloid leukemia (AML) is a malignant disease that is difficult to completely cure. Polyphyllin I (PPI), a steroidal saponin isolated from Paris polyphylla, has exhibited multiple biological activities. Here, we discovered the superior cytotoxicity of PPI on AML cells MOLM-13 with an IC50 values of 0.44 ± 0.09 µM. Mechanically, PPI could cause ferroptosis via the accumulation of intracellular iron concentration and triggering lipid peroxidation. Interestingly, PPI could induced stronger ferroptosis in a short time of about 6 h compared to erastin. Furthermore, we demonstrate that PPI-induced rapid ferroptosis is due to the simultaneous targeting PI3K/SREBP-1/SCD1 axis and triggering lipid peroxidation, and PI3K inhibitor Alpelisib can enhance the activity of erastin-induced ferroptosis. Molecular docking simulations and kinase inhibition assays demonstrated that PPI is a PI3K inhibitor. In addition, PPI significantly inhibited tumor progression and prolonged mouse survival at 4 mg/kg with well tolerance. In summary, our study highlights the therapeutic potential of PPI for AML and shows its unique dual mechanism.

In Vivo Pharmacokinetic Study of Polygonatum cyrtonema Polysaccharide DPC1 after Oral and Intraperitoneal Administration.

(1) Background: Polygonatum cyrtonema is a medicinal plant, and its polysaccharides are used for immunomodulation and the treatment of hyperglycemia. Investigation of the tissue distribution and pharmacokinetics of P. cyrtonema polysaccharide can further elucidate its pharmacological mechanisms. (2) Methods: A fluorescence-labeling approach using rhodamine B (RhB) as a fluorescent molecular probe was used for the quantitative assessment of the polysaccharide from dried P. cyrtonema (DPC1) samples, and the pharmacokinetics and tissue distribution of DPC1 were evaluated in mice after intraperitoneal or oral administration. (3) Results: DPC1 was successfully labeled with RhB, showing degrees of fluorescence labeling at 0.453% and 0.568% as determined by the ultraviolet and enzyme marker methods, respectively. DPC1-RhB was rapidly absorbed into the bloodstream after oral and intraperitoneal administration. Pharmacokinetic characteristics showed that oral administration and intraperitoneal administration were consistent with the features of a two-compartment model. (4) Conclusion: After administration, DPC1-RhB was primarily distributed in the tissues of the heart, spleen, and lung, indicating that the drug has a targeted effect on these tissues. Overall, the findings provide a comprehensive reference for the in vivo distribution of DPC1, together with a foundation for further elucidation of its pharmacological mechanisms and the development and application of DPC1 formulations.

Isobavachalcone, a natural sirtuin 2 inhibitor, exhibits anti-triple-negative breast cancer efficacy in vitro and in vivo.

Triple-negative breast cancer (TNBC) is the most aggressive and lethal clinical subtype and lacks effective targeted therapies at present. Isobavachalcone (IBC), the main active component of Psoralea corylifolia L., has potential anticancer effects. Herein, we identified IBC as a natural sirtuin 2 (SIRT2) inhibitor and characterized the potential mechanisms underlying the inhibition of TNBC. Molecular dynamics analysis, enzyme activity assay, and cellular thermal shift assay were performed to evaluate the combination of IBC and SIRT2. The therapeutic effects, mechanism, and safety of IBC were analyzed in vitro and in vivo using cellular and xenograft models. IBC effectively inhibited SIRT2 enzyme activity with an IC50 value of 0.84 ± 0.22 µM by forming hydrogen bonds with VAL233 and ALA135 within its catalytic domain. In the cellular environment, IBC bound to and stabilized SIRT2, consequently inhibiting cellular proliferation and migration, and inducing apoptosis and cell cycle arrest by disrupting the SIRT2/α-tubulin interaction and inhibiting the downstream Snail/MMP and STAT3/c-Myc pathways. In the in vivo model, 30 mg/kg IBC markedly inhibited tumor growth by targeting the SIRT2/α-tubulin interaction. Furthermore, IBC exerted its effects by inducing apoptosis in tumor tissues and was well-tolerated. IBC alleviated TNBC by targeting SIRT2 and triggering the reactive oxygen species ROS/ß-catenin/CDK2 axis. It is a promising natural lead compound for future development of SIRT2-targeting drugs.

A rationally designed fluorescent probe for sulfur dioxide and its derivatives: applications in food analysis and bioimaging.

Exogenous sulfur dioxide (SO2) and its derivatives (SO32-/HSO3-) have been extensively utilized in food preservation and endogenous SO2 is recognized as a significant gaseous signaling molecule that can mediate various physiological processes. Overproduction and/or extensive intake of these species can trigger allergic reactions and even tissue damage. Therefore, it is highly desirable to monitor SO2 and its derivatives effectively and quantitatively both in vitro and in vivo. Herein, a new mitochondria-targeted fluorescent probe (PIB) had been constructed, which could ratiometrically recognize SO2 and its derivatives with excellent sensitivity (DL = 15.9 nM) and a fast response time (200 s). The obtained high selectivity and good adaptability of this SO2-specific probe in a wide pH range (6.5-10.0) allowed for quantitatively tracking of SO2 and its derivatives in real food samples (granulated sugar, crystal sugar, and white wine). In addition, PIB could locate at mitochondrion and was capable of imaging exogenous/endogenous SO2 in the cells and zebrafish. In particular, our findings represented one of the rare examples that have demonstrated endogenous SO2 is closely related with the apoptosis of cells. Importantly, probe PIB was successfully employed for in situ metabolic localization in mouse organs, implying the potential applications of our probe in further exploration on SO2-releated pathological and physiological processes.

Exact solution of a three-stage model of stochastic gene expression including cell-cycle dynamics.

The classical three-stage model of stochastic gene expression predicts the statistics of single cell mRNA and protein number fluctuations as a function of the rates of promoter switching, transcription, translation, degradation and dilution. While this model is easily simulated, its analytical solution remains an unsolved problem. Here we modify this model to explicitly include cell-cycle dynamics and then derive an exact solution for the time-dependent joint distribution of mRNA and protein numbers. We show large differences between this model and the classical model which captures cell-cycle effects implicitly via effective first-order dilution reactions. In particular we find that the Fano factor of protein numbers calculated from a population snapshot measurement are underestimated by the classical model whereas the correlation between mRNA and protein can be either over- or underestimated, depending on the timescales of mRNA degradation and promoter switching relative to the mean cell-cycle duration time.

Artificial intelligence-aided detection for prostate cancer with multimodal routine health check-up data: an Asian multi-center study.

BACKGROUND: The early detection of high-grade prostate cancer (HGPCa) is of great importance. However, the current detection strategies result in a high rate of negative biopsies and high medical costs. In this study, the authors aimed to establish an Asian Prostate Cancer Artificial intelligence (APCA) score with no extra cost other than routine health check-ups to predict the risk of HGPCa. PATIENTS AND METHODS: A total of 7476 patients with routine health check-up data who underwent prostate biopsies from January 2008 to December 2021 in eight referral centres in Asia were screened. After data pre-processing and cleaning, 5037 patients and 117 features were analyzed. Seven AI-based algorithms were tested for feature selection and seven AI-based algorithms were tested for classification, with the best combination applied for model construction. The APAC score was established in the CH cohort and validated in a multi-centre cohort and in each validation cohort to evaluate its generalizability in different Asian regions. The performance of the models was evaluated using area under the receiver operating characteristic curve (ROC), calibration plot, and decision curve analyses. RESULTS: Eighteen features were involved in the APCA score predicting HGPCa, with some of these markers not previously used in prostate cancer diagnosis. The area under the curve (AUC) was 0.76 (95% CI:0.74-0.78) in the multi-centre validation cohort and the increment of AUC (APCA vs. PSA) was 0.16 (95% CI:0.13-0.20). The calibration plots yielded a high degree of coherence and the decision curve analysis yielded a higher net clinical benefit. Applying the APCA score could reduce unnecessary biopsies by 20.2% and 38.4%, at the risk of missing 5.0% and 10.0% of HGPCa cases in the multi-centre validation cohort, respectively. CONCLUSIONS: The APCA score based on routine health check-ups could reduce unnecessary prostate biopsies without additional examinations in Asian populations. Further prospective population-based studies are warranted to confirm these results.

Real-time monitoring of endogenous cysteine in LPS-induced oxidative stress process with a novel lysosome-targeted fluorescent probe.

Cysteine (Cys), one of essential small-molecule-based biothiols in the human body, contributes to the regulation of redox reactions and is closely associated with many physiological and pathological metabolic processes. Herein, a novel fluorescent probe, hydroxyphenyl-conjugated benzothiazole (HBT-Cys) capable of detecting Cys was constructed, where acrylate served as the recognition group and hydroxyphenyl-linked benzothiazole acted as the fluorophore. The fluorescence of the probe was negligible in the absence of Cys, and an intense blue fluorescence was observed upon addition of Cys. The Cys-sensing mechanism could be ascribed to the Cys-involved hydrolysis reaction with acrylate, leading to light up the emission at 430 nm with about 80-fold enhancement. In addition, HBT-Cys exhibited a fast response time, remarkable selectivity and low detection limit. HBT-Cys also worked well in real-time monitoring of Cys in three different food samples (wolfberry, hawthorn, and red dates). Importantly, our probe had an excellent lysosomes-targeted ability, which was successfully employed to real-time visualize the fluctuation of both exogenous and endogenous Cys in living cells and zebrafish under lipopolysaccharide (LPS)-induced oxidative stress. Hopefully, the work shown here provides a potent candidate for the real-time tracking of Cys fluctuations in various biological samples.

Dynamic Growth of Macroscopically Structured Supramolecular Hydrogels through Orchestrated Reaction-Diffusion.

Living organisms are capable of dynamically changing their structures for adaptive functions through sophisticated reaction-diffusion processes. Here we show how active supramolecular hydrogels with programmable lifetimes and macroscopic structures can be created by relying on a simple reaction-diffusion strategy. Two hydrogel precursors (poly(acrylic acid) PAA/CaCl2 and Na2 CO3 ) diffuse from different locations and generate amorphous calcium carbonate (ACC) nanoparticles at the diffusional fronts, leading to the formation of hydrogel structures driven by electrostatic interactions between PAA and ACC nanoparticles. Interestingly, the formed hydrogels are capable of autonomously disintegrating over time because of a delayed influx of electrostatic-interaction inhibitors (NaCl). The hydrogel growth process is well explained by a reaction-diffusion model which offers a theoretical means to program the dynamic growth of structured hydrogels. Furthermore, we demonstrate a conceptual access to dynamic information storage in soft materials using the developed reaction-diffusion strategy. This work may serve as a starting point for the development of life-like materials with adaptive structures and functionalities.

Non-ossifying fibroma of the mandible in a 4-year-old child: A rare case and review of the literature.

Non-ossifying fibromas usually occur in the metaphysis of the long bones in children, and are extremely rare in the mandible. Here, we present a case of non-ossifying fibromas which occurred in the mandible of a 4-year-old boy. The patient had no complaint of ache. Laboratory blood examination of serum calcium, phosphorus, and parathormone levels was normal. Computed tomography of the maxillofacial region showed a well-defined osteolytic lesion affecting the right mandible. Microscopically, the lesion showed whorled bundles of spindle-shaped fibroblasts, as well as foam cells, mingled with scant multinucleated giant cells, without any bone formation. It is necessary to distinguish non-ossifying fibromas from other giant cell-containing lesions because of the extremely infrequent occurrence of this lesion in the mandible. We reviewed the histologic features of 14 cases of non-ossifying fibromas involved in the jaw.

Neoprzewaquinone A Inhibits Breast Cancer Cell Migration and Promotes Smooth Muscle Relaxation by Targeting PIM1 to Block ROCK2/STAT3 Pathway.

Salvia miltiorrhiza Bunge (Danshen) has been widely used to treat cancer and cardiovascular diseases in Chinese traditional medicine. Here, we found that Neoprzewaquinone A (NEO), an active component of S. miltiorrhiza, selectively inhibits PIM1. We showed that NEO potently inhibits PIM1 kinase at nanomolar concentrations and significantly suppresses the growth, migration, and Epithelial-Mesenchymal Transition (EMT) in the triple-negative breast cancer cell line, MDA-MB-231 in vitro. Molecular docking simulations revealed that NEO enters the PIM1 pocket, thereby triggering multiple interaction effects. Western blot analysis revealed that both NEO and SGI-1776 (a specific PIM1 inhibitor), inhibited ROCK2/STAT3 signaling in MDA-MB-231 cells, indicating that PIM1 kinase modulates cell migration and EMT via ROCK2 signaling. Recent studies indicated that ROCK2 plays a key role in smooth muscle contraction, and that ROCK2 inhibitors effectively control the symptoms of high intraocular pressure (IOP) in glaucoma patients. Here, we showed that NEO and SGI-1776 significantly reduce IOP in normal rabbits and relax pre-restrained thoracic aortic rings in rats. Taken together, our findings indicated that NEO inhibits TNBC cell migration and relaxes smooth muscles mainly by targeting PIM1 and inhibiting ROCK2/STAT3 signaling, and that PIM1 may be an effective target for IOP and other circulatory diseases.

Diverse alkaloids from the aerial parts of Aconitum carmichaelii and antiproliferative activity of costemline via inhibiting SIRT1/ROCK1/P-STAT3 pathways.

Six undescribed alkaloids together with 15 known alkaloids were isolated from the aerial parts of Aconitum carmichaelii. Their structures were elucidated extensively by NMR and HRESIMS spectroscopy. The absolute configurations of N-formyllaurotetanine, and the known compounds glaucine-ß-N-oxide and glaucine-α-N-oxide were established by electronic circular dichroism (ECD) spectra. Notably, it was the discovery of rare indole alkaloids from the genus Aconitum, and biosynthetic pathway of compounds 1 and 6 was deduced. Evaluation of the antiproliferative activity of these alkaloids demonstrated that costemline exhibited significant anti-proliferation effects against HCT116, SKOV3, and A549 cells with IC50 values of 5.6, 14.2, and 6.8 µM, respectively. Costemline could also inhibit the cell invasion activity of HCT116 cells. Mechanistic studies in HCT116 cells suggested that the antiproliferative activity of costemline was attributable to SIRT1/ROCK1/P-STAT3 pathways regulation. This study revealed the potential for developing and utilizing the aerial parts of Aconitum carmichaelii.

Ibrutinib Prevents Acute Lung Injury via Multi-Targeting BTK, FLT3 and EGFR in Mice.

Ibrutinib has potential therapeutic or protective effects against viral- and bacterial-induced acute lung injury (ALI), likely by modulating the Bruton tyrosine kinase (BTK) signaling pathway. However, ibrutinib has multi-target effects. Moreover, immunity and inflammation targets in ALI treatment are poorly defined. We investigated whether the BTK-, FLT3-, and EGFR-related signaling pathways mediated the protective effects of ibrutinib on ALI. The intratracheal administration of poly I:C or LPS after ibrutinib administration in mice was performed by gavage. The pathological conditions of the lungs were assessed by micro-CT and HE staining. The levels of neutrophils, lymphocytes, and related inflammatory factors in the lungs were evaluated by ELISA, flow cytometry, immunohistochemistry, and immunofluorescence. Finally, the expression of proteins associated with the BTK-, FLT3-, and EGFR-related signaling pathways were evaluated by Western blotting. Ibrutinib (10 mg/kg) protected against poly I:C-induced (5 mg/kg) and LPS-induced (5 mg/kg) lung inflammation. The wet/dry weight ratio (W/D) and total proteins in the bronchoalveolar lavage fluid (BALF) were markedly reduced after ibrutinib (10 mg/kg) treatment, relative to the poly I:C- and LPS-treated groups. The levels of ALI indicators (NFκB, IL-1ß, IL-6, TNF-α, IFN-γ, neutrophils, and lymphocytes) were significantly reduced after treatment. Accordingly, ibrutinib inhibited the poly I:C- and LPS-induced BTK-, FLT3-, and EGFR-related pathway activations. Ibrutinib inhibited poly I:C- and LPS-induced acute lung injury, and this may be due to its ability to suppress the BTK-, FLT3-, and EGFR-related signaling pathways. Therefore, ibrutinib is a potential protective agent for regulating immunity and inflammation in poly I:C- and LPS-induced ALI.

Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions.

Transcriptional rates are often estimated by fitting the distribution of mature mRNA numbers measured using smFISH (single molecule fluorescence in situ hybridization) with the distribution predicted by the telegraph model of gene expression, which defines two promoter states of activity and inactivity. However, fluctuations in mature mRNA numbers are strongly affected by processes downstream of transcription. In addition, the telegraph model assumes one gene copy but in experiments, cells may have two gene copies as cells replicate their genome during the cell cycle. While it is often presumed that post-transcriptional noise and gene copy number variation affect transcriptional parameter estimation, the size of the error introduced remains unclear. To address this issue, here we measure both mature and nascent mRNA distributions of GAL10 in yeast cells using smFISH and classify each cell according to its cell cycle phase. We infer transcriptional parameters from mature and nascent mRNA distributions, with and without accounting for cell cycle phase and compare the results to live-cell transcription measurements of the same gene. We find that: (i) correcting for cell cycle dynamics decreases the promoter switching rates and the initiation rate, and increases the fraction of time spent in the active state, as well as the burst size; (ii) additional correction for post-transcriptional noise leads to further increases in the burst size and to a large reduction in the errors in parameter estimation. Furthermore, we outline how to correctly adjust for measurement noise in smFISH due to uncertainty in transcription site localisation when introns cannot be labelled. Simulations with parameters estimated from nascent smFISH data, which is corrected for cell cycle phases and measurement noise, leads to autocorrelation functions that agree with those obtained from live-cell imaging.

Identification of cuproptosis-related subtypes, cuproptosis-related gene prognostic index in hepatocellular carcinoma.

Cuproptosis is a novel form of cell death, correlated with the tricarboxylic acid (TCA) cycle. However, the metabolic features and the benefit of immune checkpoint inhibitor (ICI) therapy based on cuproptosis have not yet been elucidated in Hepatocellular carcinoma (HCC). First, we identified and validated three cuproptosis subtypes based on 10 cuproptosis-related genes (CRGs) in HCC patients. We explored the correlation between three cuproptosis subtypes and metabolism-related pathways. Besides, a comprehensive immune analysis of three cuproptosis subtypes was performed. Then, we calculated the cuproptosis-related gene prognostic index (CRGPI) score for predicting prognosis and validated its predictive capability by Decision curve analysis (DCA). We as well explored the benefit of ICI therapy of different CRGPI subgroups in two anti-PD1/PD-L1 therapy cohorts (IMvigor210 cohort and GSE176307). Finally, we performed the ridge regression algorithm to calculate the IC50 value for drug sensitivity and Gene set enrichment analysis (GSEA) analysis to explore the potential mechanism. We found that cluster A presented a higher expression of FDX1 and was correlated with metabolism, glycolysis, and TCA cycle pathways, compared with the other two clusters. HCC patients with high CRGPI scores had a worse OS probability, and we further found that the CRGPI-high group had high expression of PD1/PDL1, TMB, and better response (PR/CR) to immunotherapy in the IMvigor210 cohort and GSE176307. These findings highlight the importance of CRGPI serving as a potential biomarker for both prognostic and immunotherapy for HCC patients. Generally, our results provide novel insights about cuproptosis into immune therapeutic strategies.

DelaySSAToolkit.jl: stochastic simulation of reaction systems with time delays in Julia.

SUMMARY: DelaySSAToolkit.jl is a Julia package for modelling reaction systems with non-Markovian dynamics, specifically those with time delays. These delays implicitly capture multiple intermediate reaction steps and hence serve as an effective model reduction technique for complex systems in biology, chemistry, ecology and genetics. The package implements a variety of exact formulations of the delay stochastic simulation algorithm. AVAILABILITY AND IMPLEMENTATION: The source code and documentation of DelaySSAToolkit.jl are available at https://github.com/palmtree2013/DelaySSAToolkit.jl.

Learning of Iterative Learning Control for Flexible Manufacturing of Batch Processes.

Flexible manufacturing as an essential component of smart manufacturing implements the customized production mode, thereby requesting fast controller adaptation for producing different goods but still with high precision. This problem becomes even more acute for batch processes. Here we present a solution called learning of iterative learning control (ILC) based on neural networks. It is able to recommend control parameters for ILC controllers accordingly, so as to yield fast tracking error convergence and smaller steady-state error for disparate set-point profiles, which is deemed an abstraction of different production needs. The method substantially outperforms a benchmark ILC on a variety of systems and cases, thereby showing its potential for deployment in the industrial Internet of Things.