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The variation in the fitting accuracy of neural networks (NNs) when used to fit databases comprising potential energies obtained from ab initio electronic structure calculations is investigated as a function of the number and nature of the elements employed in the input vector to the NN. Ab initio databases for H2O2, HONO, Si5, and H2C==CHBr were employed in the investigations. These systems were chosen so as to include four-, five-, and six-body systems containing first, second, third, and fourth row elements with a wide variety of chemical bonding and whose conformations cover a wide range of structures that occur under high-energy machining conditions and in chemical reactions involving cis-trans isomerizations, six different types of two-center bond ruptures, and two different three-center dissociation reactions. The ab initio databases for these systems were obtained using density functional theory/B3LYP, MP2, and MP4 methods with extended basis sets. A total of 31 input vectors were investigated. In each case, the elements of the input vector were chosen from interatomic distances, inverse powers of the interatomic distance, three-body angles, and dihedral angles. Both redundant and nonredundant input vectors were investigated. The results show that among all the input vectors investigated, the set employed in the Z-matrix specification of the molecular configurations in the electronic structure calculations gave the lowest NN fitting accuracy for both Si5 and vinyl bromide. The underlying reason for this result appears to be the discontinuity present in the dihedral angle for planar geometries. The use of trigometric functions of the angles as input elements produced significantly improved fitting accuracy as this choice eliminates the discontinuity. The most accurate fitting was obtained when the elements of the input vector were taken to have the form Rij-n, where the Rij are the interatomic distances. When the Levenberg–Marquardt procedure was modified to permit error minimization with respect to n as well as the weights and biases of the NN, the optimum powers were all found to lie in the range of 1.625–2.38 for the four systems studied. No statistically significant increase in fitting accuracy was achieved for vinyl bromide when a different value of n was employed and optimized for each bond type. The rate of change in the fitting error with n is found to be very small when n is near its optimum value. Consequently, good fitting accuracy can be achieved by employing a value of n in the middle of the above range. The use of interparticle distances as elements of the input vector rather than the Z-matrix variables employed in the electronic structure calculations is found to reduce the rms fitting errors by factors of 8.86 and 1.67 for Si5 and vinyl bromide, respectively. If the interparticle distances are replaced with input elements of the form Rij-n with n optimized, further reductions in the rms error by a factor of 1.31 to 2.83 for the four systems investigated are obtained. A major advantage of using this procedure to increase NN fitting accuracy rather than increasing the number of neurons or the size of the database is that the required increase in computational effort is very small. [ABSTRACT FROM AUTHOR]

A novel method is presented that significantly reduces the computational bottleneck of executing high-level, electronic structure calculations of the energies and their gradients for a large database that adequately samples the configuration space of importance for systems containing more than four atoms that are undergoing multiple, simultaneous reactions in several energetically open channels. The basis of the method is the high-degree of correlation that generally exists between the Hartree–Fock (HF) and higher-level electronic structure energies. It is shown that if the input vector to a neural network (NN) includes both the configuration coordinates and the HF energies of a small subset of the database, MP4(SDQ) energies with the same basis set can be predicted for the entire database using only the HF and MP4(SDQ) energies for the small subset and the HF energies for the remainder of the database. The predictive error is shown to be less than or equal to the NN fitting error if a NN is fitted to the entire database of higher-level electronic structure energies. The general method is applied to the computation of MP4(SDQ) energies of 68 308 configurations that comprise the database for the simultaneous, unimolecular decomposition of vinyl bromide into six different reaction channels. The predictive accuracy of the method is investigated by employing successively smaller subsets of the database to train the NN to predict the MP4(SDQ) energies of the remaining configurations of the database. The results indicate that for this system, the subset can be as small as 8% of the total number of configurations in the database without loss of accuracy beyond that expected if a NN is employed to fit the higher-level energies for the entire database. The utilization of this procedure is shown to save about 78% of the total computational time required for the execution of the MP4(SDQ) calculations. The sampling error involved with selection of the subset is shown to be about 10% of the predictive error for the higher-level energies. A practical procedure for utilization of the method is outlined. It is suggested that the method will be equally applicable to the prediction of electronic structure energies computed using even higher-level methods than MP4(SDQ). [ABSTRACT FROM AUTHOR]

A general method for the development of potential-energy hypersurfaces is presented. The method combines a many-body expansion to represent the potential-energy surface with two-layer neural networks (NN) for each M-body term in the summations. The total number of NNs required is significantly reduced by employing a moiety energy approximation. An algorithm is presented that efficiently adjusts all the coupled NN parameters to the database for the surface. Application of the method to four different systems of increasing complexity shows that the fitting accuracy of the method is good to excellent. For some cases, it exceeds that available by other methods currently in literature. The method is illustrated by fitting large databases of ab initio energies for Sin (n=3,4,...,7) clusters obtained from density functional theory calculations and for vinyl bromide (C2H3Br) and all products for dissociation into six open reaction channels (12 if the reverse reactions are counted as separate open channels) that include C–H and C–Br bond scissions, three-center HBr dissociation, and three-center H2 dissociation. The vinyl bromide database comprises the ab initio energies of 71 969 configurations computed at MP4(SDQ) level with a 6-31G(d,p) basis set for the carbon and hydrogen atoms and Huzinaga’s (4333/433/4) basis set augmented with split outer s and p orbitals (43321/4321/4) and a polarization f orbital with an exponent of 0.5 for the bromine atom. It is found that an expansion truncated after the three-body terms is sufficient to fit the Si5 system with a mean absolute testing set error of 5.693×10-4 eV. Expansions truncated after the four-body terms for Sin (n=3,4,5) and Sin (n=3,4,...,7) provide fits whose mean absolute testing set errors are 0.0056 and 0.0212 eV, respectively. For vinyl bromide, a many-body expansion truncated after the four-body terms provides fitting accuracy with mean absolute testing set errors that range between 0.0782 and 0.0808 eV. These errors correspond to mean percent errors that fall in the range 0.98%–1.01%. Our best result using the present method truncated after the four-body summation with 16 NNs yields a testing set error that is 20.3% higher than that obtained using a 15-dimensional (15-140-1) NN to fit the vinyl bromide database. This appears to be the price of the added simplicity of the many-body expansion procedure. [ABSTRACT FROM AUTHOR]

A generalized method that permits the parameters of an arbitrary empirical potential to be efficiently and accurately fitted to a database is presented. The method permits the values of a subset of the potential parameters to be considered as general functions of the internal coordinates that define the instantaneous configuration of the system. The parameters in this subset are computed by a generalized neural network (NN) with one or more hidden layers and an input vector with at least 3n-6 elements, where n is the number of atoms in the system. The Levenberg–Marquardt algorithm is employed to efficiently affect the optimization of the weights and biases of the NN as well as all other potential parameters being treated as constants rather than as functions of the input coordinates. In order to effect this minimization, the usual Jacobian employed in NN operations is modified to include the Jacobian of the computed errors with respect to the parameters of the potential function. The total Jacobian employed in each epoch of minimization is the concatenation of two Jacobians, one containing derivatives of the errors with respect to the weights and biases of the network, and the other with respect to the constant parameters of the potential function. The method provides three principal advantages. First, it obviates the problem of selecting the form of the functional dependence of the parameters upon the system’s coordinates by employing a NN. If this network contains a sufficient number of neurons, it will automatically find something close to the best functional form. This is the case since Hornik et al., [Neural Networks 2, 359 (1989)] have shown that two-layer NNs with sigmoid transfer functions in the first hidden layer and linear functions in the output layer are universal approximators for analytic functions. Second, the entire fitting procedure is automated so that excellent fits are obtained rapidly with little human effort. Third, the method provides a procedure to avoid local minima in the multidimensional parameter hyperspace. As an illustrative example, the general method has been applied to the specific case of fitting the ab initio energies of Si5 clusters that are observed in a molecular dynamics (MD) simulation of the machining of a silicon workpiece. The energies of the Si5 configurations obtained in the MD calculations are computed using the B3LYP procedure with a 6-31G** basis set. The final ab initio database, which comprises the density functional theory energies of 10 202 Si5 clusters, is fitted to an empirical Tersoff potential containing nine adjustable parameters, two of which are allowed to be the functions of the Si5 configuration. The fitting error averaged over all 10 202 points is 0.0148 eV (1.43 kJ mol-1). This result is comparable to the accuracy achieved by more general fitting methods that do not rely on an assumed functional form for the potential surface. [ABSTRACT FROM AUTHOR]

In this paper, we present the analytical foundations for modelling the staircase traversal of convex polygonal surfaces by a tool in the form of a circular disk. Based on these foundations, we next develop a mathematical model and an algorithm for a near optimal tool path in a staircase traversal of convex polygonal surfaces. We compare this algorithm---which is called OPTPATH--with two existing algorithms. This comparison confirms that OPTPATH performs better than the other two test algorithms. The OPTPATH algorithm can be used for staircase traversal with or without overlap between successive sweep passes and with or without rapid traversal in edge passes. This generality of OPTPATH allows its application to several manufacturing problems such as face and pocket milling, robotic deburring, rapid prototyping, and robotic spray painting. The results of the theorems presented in the paper can be helpful in designing new algorithms as well as in improving some of the existing algorithms for optimizing tool path in staircase traversal of convex polygonal surfaces. [ABSTRACT FROM AUTHOR]

Acoustic emission (AE) signals are emerging as promising means for monitoring machining processes, but understanding their generation is presently a topic of active research; hence techniques to analyze them are not completely developed. In this paper, we present a novel methodology based on chaos theory, wavelets and neural networks, for analyzing AE signals. Our methodology involves a thorough signal characterization, followed by signal representation using wavelet packets, and state estimation using multilayer neural networks. Our methodology has yielded a compact signal representation, facilitating the extraction of a tight set of features for flank wear estimation.

A distributed control approach based on multiagent negotiation is presented, wherein stops and buses act as agents that communicate in real-time to achieve dynamic coordination of bus dispatching at various stops. The negotiation between a Bus Agent and a Stop Agent is conducted based on marginal cost calculations. We present optimality conditions for the formulated problem, using a negotiation algorithm, which we derive, to coordinate bus holding at various stops. A comparison between the negotiation algorithm and other simple bus control strategies such as on-schedule and even-headway strategies made through simulations verifies the robustness and efficiency of our negotiation strategy to different transit environments, involving both stationary passenger arrivals as well as a variety of nonstationary passenger arrivals. [ABSTRACT FROM PUBLISHER]

Background: Perineural invasion (PNI) and nerve density within the tumor microenvironment (TME) have long been associated with worse outcomes in head and neck squamous cell carcinoma (HNSCC). This prompted an investigation into how nerves within the tumor microenvironment affect the adaptive immune system and tumor growth., Methods: We used RNA sequencing analysis of human tumor tissue from a recent HNSCC clinical trial, proteomics of human nerves from HNSCC patients, and syngeneic orthotopic murine models of HPV-unrelated HNSCC to investigate how sensory nerves modulate the adaptive immune system., Findings: Calcitonin gene-related peptide (CGRP) directly inhibited CD8 T cell activity in vitro, and blocking sensory nerve function surgically, pharmacologically, or genetically increased CD8 and CD4 T cell activity in vivo., Conclusions: Our data support sensory nerves playing a role in accelerating tumor growth by directly acting on the adaptive immune system to decrease Th1 CD4 T cells and activated CD8 T cells in the TME. These data support further investigation into the role of sensory nerves in the TME of HNSCC and points toward the possible treatment efficacy of blocking sensory nerve function or specifically inhibiting CGRP release or activity within the TME to improve outcomes., Funding: 1R01DE028282-01, 1R01DE028529-01, 1P50CA261605-01 (to S.D.K.), 1R01CA284651-01 (to S.D.K.), and F31 DE029997 (to L.B.D.)., Competing Interests: Declaration of interests S.D.K. receives clinical funding from Genentech that does not relate to this work. She receives clinical trial funding from AstraZeneca, a part of which is included in this manuscript. She also receives preclinical research funding from Roche and Amgen unrelated to this manuscript. R.W. serves in an advisory role for AstraZeneca., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objectives: To compare and evaluate the occlusal variability/discrepancy recorded using qualitative (articulating paper) and quantitative (T-scan) techniques in partially edentulous implant-supported restorations., Materials and Methods: A total of 20 patients in the age group of 25-61 yrs participated in this study. All the patients had more than one tooth replaced with implant-supported prosthesis. After three months of restoration, occlusion reevaluated was carried out using qualitative (articulating paper) and quantitative (T-scan). T-scan data were used to measure implant occlusion time, occlusion time, and the relative occlusal force (ROFs) on implant prosthesis. And the data were statistically evaluated., Results: The T-scan values showed high points on the implants in most of the patients, which could not be evaluated by that of articulating paper outcomes., Conclusion: The occlusal harmony achieved from using qualitative analysis of articulating paper was not supported by the finding of the quantitative analysis (T-scan). Also the T-scan provided the time interval of occlusion of the implant-supported restorations, which would help in better defining the implant-protected occlusal., Clinical Relevance: The T-scan occlusal analysis system provides ROF and time intervals of occlusal contact. This allows accurate occlusal equilibration of implant-supported restoration according to implant protected occlusal concept., (Copyright © 2024 Copyright: © 2024 Indian Journal of Dental Research.)

The implementation of cancer immunotherapies has seen limited clinical success in head and neck squamous cell carcinoma (HNSCC). Interleukin-2 (IL-2), which modulates the survival and functionality of lymphocytes, is an attractive target for new immunotherapies but one that is limited by presence of regulatory T cells (Tregs) expressing the high-affinity IL-2Rα. The bispecific immunocytokine PD1-IL2v preferentially delivers IL-2 signaling through IL-2Rβγ on PD-1-expressing cells. Selectively targeting the intermediate-affinity IL-2Rβγ can be leveraged to induce anti-tumor immune responses in effector T cells and natural killer (NK) cells while limiting the negative regulation of IL-2Rα activation on Tregs. Using radiation therapy (RT) in combination with PD1-IL2v improves local tumor control and survival, and controls metastatic spread in orthotopic HNSCC tumor models. PD1-IL2v drives systemic activation and expansion of circulating and tumor-infiltrating cytotoxic T cells and NK cells while limiting Treg-mediated immunosuppression. These data show that PD1-L2v induces durable systemic tumor control in HNSCC., Competing Interests: Declaration of interests M.A., L.C.D., P.U., and C.K. are employed by Roche Innovation Center Zurich and declare ownership of stock and patents with Roche. S.D.K. receives funding from NIDCR/NCI in addition to clinical trial funding from AstraZeneca, Genentech, and Ionis outside the submitted work. S.D.K. reports no personal payment in consulting, advisory boards, clinical trials, or any other relevant financial disclosures. A.D. is a founder of Omix Technologies Inc. and Altis Biosciences. A.D. is a scientific advisory board member for Hemanext Inc., Macopharma Inc., and Forma Therapeutics., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Differential outcomes of EphB4-ephrinB2 signaling offers formidable challenge for the development of cancer therapeutics. Here, we interrogate the effects of targeting EphB4 and ephrinB2 in head and neck squamous cell carcinoma (HNSCC) and within its microenvironment using genetically engineered mice, recombinant constructs, pharmacologic agonists and antagonists. We observe that manipulating the EphB4 intracellular domain on cancer cells accelerates tumor growth and angiogenesis. EphB4 cancer cell loss also triggers compensatory upregulation of EphA4 and T regulatory cells (Tregs) influx and their targeting results in reversal of accelerated tumor growth mediated by EphB4 knockdown. EphrinB2 knockout on cancer cells and vasculature, on the other hand, results in maximal tumor reduction and vascular normalization. We report that EphB4 agonism provides no additional anti-tumoral benefit in the absence of ephrinB2. These results identify ephrinB2 as a tumor promoter and its receptor, EphB4, as a tumor suppressor in HNSCC, presenting opportunities for rational drug design., (© 2022. The Author(s).)

Resistance to radiation therapy (RT) remains an obstacle in HPV-negative head and neck squamous cell carcinomas (HNSCCs)-even with a combined RT-immunotherapy approach. Jak-Stat proteins have long been studied for both their immune regulatory role in the host immune response as well as their cancer cell signaling role in shaping the tumor microenvironment (TME). Here, we identify STAT1 as a mediator of radioresistance in HPV-negative preclinical mouse models of HNSCC, by which knockout of STAT1 in the cancer cell (STAT1 KO)-but not in the host-resulted in decreased tumor growth alongside increased immune activation. We show that RT increases STAT1/pSTAT1 expression, which may act as a marker of radioresistance. Whereas RT increased JAK-STAT and interferon (IFN) signaling, transcriptomic analysis revealed that STAT1 KO in the cancer cell resulted in decreased expression of IFN-associated genes of resistance. In vitro experiments showed that STAT1 KO increased T cell chemoattraction and decreased baseline growth. These results indicate that STAT1 may serve a tumor-promoting role in the cancer cell and will inform biomarker development and treatment regimens for HNSCC incorporating RT., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Advances in the image-based diagnostics of complex biological and manufacturing processes have brought unsupervised image segmentation to the forefront of enabling automated, on the fly decision making. However, most existing unsupervised segmentation approaches are either computationally complex or require manual parameter selection (e.g., flow capacities in max-flow/min-cut segmentation). In this work, we present a fully unsupervised segmentation approach using a continuous max-flow formulation over the image domain while optimally estimating the flow parameters from the image characteristics. More specifically, we show that the maximum a posteriori estimate of the image labels can be formulated as a continuous max-flow problem given the flow capacities are known. The flow capacities are then iteratively obtained by employing a novel Markov random field prior over the image domain. We present theoretical results to establish the posterior consistency of the flow capacities. We compare the performance of our approach using brain tumor image segmentation, defect identification in additively manufactured components using electron microscopic images, and segmentation of multiple real-world images. Comparative results with several state-of-the-art supervised as well as unsupervised methods suggest that the present method performs statistically similar to the supervised methods, but results in more than 90 percent improvement in the Dice score when compared to the state-of-the-art unsupervised methods.

The aggressive nature of glioblastoma multiforme (GBM) may be attributed to the dysregulation of pathways driving both proliferation and invasion. EphrinB2, a membrane-bound ligand for some of the Eph receptors, has emerged as a critical target regulating these pathways. In this study, we investigated the role of ephrinB2 in regulating proliferation and invasion in GBM using intracranial and subcutaneous xenograft models. The Cancer Genome Atlas analysis suggested high transcript and low methylation levels of ephrinB2 as poor prognostic indicators in GBM, consistent with its role as an oncogene. EphrinB2 knockdown, however, increased tumor growth, an effect that was reversed by ephrinB2 Fc protein. This was associated with EphB4 receptor activation, consistent with the data showing a significant decrease in tumor growth with ephrinB2 overexpression. Mechanistic analyses showed that ephrinB2 knockdown has anti-invasive but pro-proliferative effects in GBM. EphB4 stimulation following ephrinB2 Fc treatment in ephrinB2 knockdown tumors was shown to impart strong anti-proliferative and anti-invasive effects, which correlated with decrease in PCNA, p-ERK, vimentin, Snail, Fak, and increase in the E-cadherin levels. Overall, our study suggests that ephrinB2 cannot be used as a sole therapeutic target. Concomitant inhibition of ephrinB2 signaling with EphB4 activation is required to achieve maximal therapeutic benefit in GBM., (© 2020 Wiley Periodicals LLC.)

Timely evaluation and reperfusion have improved the myocardial salvage and the subsequent recovery rate of the patients hospitalized with acute myocardial infarction (MI). Long waiting time and time-consuming procedures of in-hospital diagnostic testing severely affect the timeliness. We present a Poincare pattern ensemble-based method with the consideration of multi-correlated non-stationary stochastic system dynamics to localize the infarct-related artery (IRA) in acute MI by fully harnessing information from paper-based Electrocardiogram (ECG). The vectorcardiogram (VCG) diagnostic features extracted from only 2.5-s long paper ECG recordings were used to hierarchically localize the IRA-not mere localization of the infarcted cardiac tissues-in acute MI. Paper ECG records and angiograms of 106 acute MI patients collected at the Heart Artery and Vein Center at Fresno California and the 12-lead ECG signals from the Physionet PTB online database were employed to validate the proposed approach. We reported the overall accuracies of 97.41% for healthy control (HC) vs. MI, 89.41 ± 9.89 for left and right culprit arteries vs. others, 88.2 ± 11.6 for left main arteries vs. right-coronary-ascending (RCA) and 93.67 ± 4.89 for left-anterior-descending (LAD) vs. left-circumflex (LCX). The IRA localization from paper ECG can be used to timely triage the patients with acute coronary syndromes to the percutaneous coronary intervention facilities.

Purpose: Radiotherapy (RT) can transform the immune landscape and render poorly immunogenic tumors sensitive to PD-L1 inhibition. Here, we established that the response to combined RT and PD-L1 inhibition is transient and investigated mechanisms of resistance. Experimental Design: Mechanisms of resistance to RT and PD-L1 blockade were investigated in orthotopic murine head and neck squamous cell carcinoma (HNSCC) tumors using mass cytometry and whole-genome sequencing. Mice were treated with anti-PD-L1 or anti-TIM-3 alone and in combination with and without RT. Tumor growth and survival were assessed. Flow cytometry was used to assess phenotypic and functional changes in intratumoral T-cell populations. Depletion of regulatory T cells (Treg) was performed using anti-CD25 antibody. Results: We show that the immune checkpoint receptor, TIM-3, is upregulated on CD8 T cells and Tregs in tumors treated with RT and PD-L1 blockade. Treatment with anti-TIM-3 concurrently with anti-PD-L1 and RT led to significant tumor growth delay, enhanced T-cell cytotoxicity, decreased Tregs, and improved survival in orthotopic models of HNSCC. Despite this treatment combination, the response was not durable, and analysis of relapsed tumors revealed resurgence of Tregs. Targeted Treg depletion, however, restored antitumor immunity in mice treated with RT and dual immune checkpoint blockade and resulted in tumor rejection and induction of immunologic memory. Conclusions: These data reveal multiple layers of immune regulation that can promote tumorigenesis and the therapeutic potential of sequential targeting to overcome tumor resistance mechanisms. We propose that targeted Treg inhibitors may be critical for achieving durable tumor response with combined radiotherapy and immunotherapy. Clin Cancer Res; 24(21); 5368-80. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Purpose: The clinical success of targeted therapies such as cetuximab and radiotherapy (RT) is hampered by the low response rates and development of therapeutic resistance. In the current study, we investigated the involvement of EphB4-ephrin-B2 protumorigenic signaling in mediating resistance to EGFR inhibition and RT in head and neck cancers. Experimental Design: We used patient-derived xenograft (PDX) models of head and neck squamous cell carcinoma (HNSCC) and HNSCC cell lines to test our hypothesis. Tumor tissues were subjected to PhosphoRTK array, and Western blotting to detect changes in EphB4-ephrin-B2 targets. mRNA sequencing and microarray data analysis were performed on PDX tumors and HNSCC cell lines, respectively, to determine differences in gene expression of molecules involved in tumor cell growth, proliferation, and survival pathways. Effects on cell growth were determined by MTT assay on HNSCC cells downregulated for EphB4/ephrin-B2 expression, with and without EGFR inhibitor and radiation. Results: Our data from locally advanced HNSCC patients treated with standard-of-care definitive chemo-RT show elevated EphB4 and ephrin-B2 levels after failure of treatment. We observed significant response toward cetuximab and RT following EphB4-ephrin-B2 inhibition, resulting in improved survival in tumor-bearing mice. Tumor growth inhibition was accompanied by a decrease in the levels of proliferation and prosurvival molecules and increased apoptosis. Conclusions: Our findings underscore the importance of adopting rational drug combinations to enhance therapeutic effect. Our study documenting enhanced response of HNSCC to cetuximab-RT with EphB4-ephrin-B2 blockade has the potential to translate into the clinic to benefit this patient population. Clin Cancer Res; 24(18); 4539-50. ©2018 AACR ., (©2018 American Association for Cancer Research.)