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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Skeletal unloading inhibits the in vitro proliferation and differentiation of rat osteoprogenitor cells

Loss of weight bearing in the growing rat decreases bone formation, osteoblast numbers, and bone maturation in unloaded bones. These responses suggest an impairment of osteoblast proliferation and differentiation. To test this assumption, we assessed the effects of skeletal unloading using an in vitro model of osteoprogenitor cell differentiation. Rats were hindlimb elevated for 0 (control), 2, or 5 days, after which their tibial bone marrow stromal cells (BMSCs) were harvested and cultured. Five days of hindlimb elevation led to significant decreases in proliferation, alkaline phosphatase (AP) enzyme activity, and mineralization of BMSC cultures. Differentiation of BMSCs was analyzed by quantitative competitive polymerase chain reaction of cDNA after 10, 15, 20, and 28 days of culture. cDNA pools were analyzed for the expression of c-fos (an index of proliferation), AP (an index of early osteoblast differentiation), and osteocalcin (a marker of late differentiation). BMSCs from 5-day unloaded rats expressed 50% less c-fos, 61% more AP, and 35% less osteocalcin mRNA compared with controls. These data demonstrate that cultured osteoprogenitor cells retain a memory of their in vivo loading history and indicate that skeletal unloading inhibits proliferation and differentiation of osteoprogenitor cells in vitro.

NASA Discipline Musculoskeletal↗
DOE OSTI2022

Surface analysis insight note: Differentiation methods applicable to noisy data for determination of sp2‐ versus sp3‐hybridization of carbon allotropes and AES signal strengths

The derivatives of the spectra are commonly used for quantification in Auger Electron Spectroscopy (AES) spectra, while the derivative of the KLL C Auger line has proven to be valuable in obtaining a measure of the relative proportions of sp 2 ‐ and sp 3 ‐hybridization using the D‐parameter in both AES and X‐ray Photoelectron Spectroscopy (XPS). Differentiation of X‐ray Photoelectron Spectroscopy (XPS) and Auger Electron Spectroscopy (AES) spectra by numerical means is presented and illustrated for polymeric, such as PEEK and Nylon, as well as for graphitic materials including highly ordered pyrolytic graphite and graphene oxide. The most commonly available Savitzky–Golay method is explained mathematically and developed through the case of constructing a 5‐point quadratic polynomial convolution kernel suitable for differentiating spectra of adequate signal to noise. The concept of differentiation of spectra where signal to noise is less than adequate is also developed. Two alternative strategies to Savitzky–Golay differentiation are presented, which fit curves to data that allow derivatives to be obtained where Savitzky–Golay would otherwise fail. These alternative methods involve constructing a parametric curve that fits data over the entire energy interval of interest. Derivatives of spectra are then obtained by differentiating these parametric curves directly. A comparison of results for different materials for which specific sp 2 ‐ vs sp 3 ‐hybridized carbon proportions are of interest is used to emphasize the importance of characterizing methods used to differentiate spectra and understanding the characteristics of instrumentation used to measure spectra. The case for using Principal Component Analysis noise reduction with C KLL spectra is made for spectra collected from a heterogeneous graphene oxide sample.

Fairley, Neal↗
DOE OSTI2019

Predictive role of PI-RADSv2 and ADC parameters in differentiating Gleason pattern 3 + 4 and 4 + 3 prostate cancer

Purpose: To compare the predictive roles of qualitative (PI-RADSv2) and quantitative assessment (ADC metrics), in differentiating Gleason pattern (GP) 3 + 4 from the more aggressive GP 4 + 3 prostate cancer (PCa) using radical prostatectomy (RP) specimen as the reference standard. Methods: We retrospectively identified treatment-naïve peripheral (PZ) and transitional zone (TZ) Gleason Score 7 PCa patients who underwent multiparametric 3T prostate MRI (DWI with b value of 0,1400 and where unavailable, 0,500) and subsequent RP from 2011 to 2015. For each lesion identified on MRI, a PI-RADSv2 score was assigned by a radiologist blinded to pathology data. A PI-RADSv2 score ≤ 3 was defined as “low risk,” a PI-RADSv2 score ≥ 4 as “high risk” for clinically significant PCa. Mean tumor ADC (ADC{sub T}), ADC of adjacent normal tissue (ADC{sub N}), and ADC{sub ratio} (ADC{sub T}/ADC{sub N}) were calculated. Stepwise regression analysis using tumor location, ADC{sub T} and ADC{sub ratio}, b value, low vs. high PI-RADSv2 score was performed to differentiate GP 3 + 4 from 4 + 3. Results: 119 out of 645 cases initially identified met eligibility requirements. 76 lesions were GP 3 + 4, 43 were 4 + 3. ADC{sub ratio} was significantly different between the two GP groups (p = 0.001). PI-RADSv2 score (“low” vs. “high”) was not significantly different between the two GP groups (p = 0.17). Regression analysis selected ADC{sub T} (p = 0.03) and ADC{sub ratio} (p = 0.0007) as best predictors to differentiate GP 4 + 3 from 3 + 4. Estimated sensitivity, specificity, and accuracy of the predictive model in differentiating GP 4 + 3 from 3 + 4 were 37, 82, and 66%, respectively. Conclusions: ADC metrics could differentiate GP 3 + 4 from 4 + 3 PCa with high specificity and moderate accuracy while PI-RADSv2, did not differentiate between these patterns.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

A feasible order-arbitrarily-tunable optical differentiator

We propose a feasible temporal filtering (or spectrum weighting) system to implement optical differentiation with arbitrarily-tunable order. Differentiation order is tuned by programming the temporal weighting mask (TWM) as power function of different exponents, not limited by the structure of the system. Assembly of the system is feasible, since the active parts are implemented by electro-optic elements and some key elements are reused between sub-systems involved in the scheme. Tuning of the system is simple, since electronically pre-stored TWMs are easy to switch among each other. The order-tunable functionality is verified by numerically testing the differentiation cases of normalized input pulse duration ranging from 0.1 to 0.4, and of differentiation order tuned from 1 to 10. Good accuracy is achieved, and measured by root mean square error lower than 0.1. Feasibilities of the system are also verified in terms of accuracy maintaining and distortion avoiding. Compared with existing methods, apart from the arbitrary order-tunable capacity and good accuracy, our proposed optical differentiator also possesses properties of good compactness and constant complexity. The proposed differentiator has unique applications on multi-peak waveform generation for optical communications and photonics-aided Radars with enhanced agility and feasibility.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Taxifolin enhances osteogenic differentiation of human bone marrow mesenchymal stem cells partially via NF-κB pathway

Taxifolin, a flavonoid compound, has been reported to stimulate osteogenic differentiation in osteoblasts. The present study investigated whether taxifolin affects the osteogenic differentiation of human bone marrow mesenchymal stem cells (hBMSCs) and the molecular mechanisms involved. The proliferation and osteogenic differentiation of hBMSCs in the presence of taxifolin were examined by CCK-8 assay, alkaline phosphatase (ALP) activity, ALP staining and Alizarin red staining. The expression of osteogenic differentiation markers were detected by real-time quantitative PCR (RT-PCR) analysis and western blot assay. The activation of potential related pathways was examined by luciferase reporter assay, immunofluorescence and western blot analysis. Taxifolin treatment increased osteogenic differentiation of hBMSCs without cytotoxicity. Luciferase reporter assay showed that taxifolin could not activate estrogen receptor pathway, but inhibit TNF-α-induced NF-κB signaling pathway activation in osteogenic induction condition. Moreover, the nucleus translocation of NF-κB under TNF-α treatment was inhibited by taxifolin treatment. The taxifolin-induced osteogenic differentiation effects of hBMSCs were abolished by TNF-α treatment. In conclusion, our results suggested that taxifolin could promote osteogenesis of hBMSCs, partially through antagonism of NF-κB signaling pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Pilose antler peptide potentiates osteoblast differentiation and inhibits osteoclastogenesis via manipulating the NF-κB pathway

Bones are inflexible yet ever-changing metabolic organs, and bone homeostasis is maintained through two delicately regulated processes: bone construction and bone reabsorption. An imbalance in bone metabolism is linked to most orthopedic diseases, including osteoporosis and rheumatoid arthritis. Importantly, tumor necrosis factor-α (TNF-α) blocks osteoblast differentiation and stimulates osteoclast formation, resulting in delayed deposition of new bone and accelerated bone resorption, especially in rheumatoid arthritis patients with inflammatory conditions. Pilose antler peptide (PAP) isolated and purified from deer antlers has been shown to have beneficial effects on chronic inflammation. In the present study, we studied the impact of PAP on osteoblast differentiation and evaluated the regulatory mechanism, with particular emphasis on the effect of PAP on TNF-α-mediated NF-κB signaling. Mouse primary osteoblast cells were activated with bone morphogenetic protein-2 (BMP-2) for osteoblast differentiation. A significant stimulatory effect of PAP in osteoblastogenesis was observed using ALP activity and Alizarin Red S staining assays. Meanwhile, PAP significantly rescued TNF-α-induced impairment of osteoblast formation as well as mineralization. Furthermore, we found a similar trend upon analyzing osteoblast-specific gene expression. PAP significantly rescued TNF-α-mediated decrease in expression of osteoblast-specific genes. A molecular mechanism assay indicated that PAP significantly inhibited TNF-α-mediated stimulation of NF-κB signaling activity, as well as nuclear translocation of its subunit p65. Moreover, over-expression of p65 reversed the stimulatory effects of PAP on osteoblast differentiation. Furthermore, we also identified that PAP dose dependently inhibit osteoclastogenesis, and this effect might be achieved via suppressing NF-κB activity. In summary, this study shows that PAP promotes osteoblast differentiation and blocks TNF-α-mediated suppression of osteoblastogenesis in vitro via the NF-κB/p65 pathway, as well as inhibits osteoclastsogenesis in vitro. Therefore, PAP, a novel drug with both antiresorptive and osteoanabolic activity, shows therapeutic potential as an alternative treatment for osteolytic diseases, including rheumatoid arthritis and osteoporosis. - Highlights: • PAP promotes osteoblasts differentiation and inhibits osteoclastogenesis. • PAP blocks TNFα-mediated suppression of osteoblastogenesis via NF-κB pathway. • PAP shows both antiresorptive and osteoanabolic activity, and is promising in the treatment of inflammatory bone loss.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

ATP6V1H regulates the growth and differentiation of bone marrow stromal cells

Highlights: • Lack of ATP6V1H inhibits the proliferation of bone marrow stromal cells (BMSCs). • Partial loss of ATP6V1H inhibits osteogenic differentiation and promotes adipogenic differentiation of BMSCs. • ATP6V1H interacts with TGF-β receptor I and AP-2 complex to regulate the proliferation and differentiation of BMSCs. ATP6V1H encodes subunit H of vacuolar ATPase (V-ATPase) and may regulate osteoclastic function. The deficiency of ATP6V1H caused bone loss in human, mouse and zebrafish. In this report, we identified the mechanisms by which ATP6V1H regulates proliferation and differentiation of bone marrow stromal cells (BMSCs). We found that ATP6V1H was expressed in BMSCs, and Atp6v1h{sup +/-} BMSCs exhibited the lower proliferation rate, cell cycle arrest and reduced osteogenic differentiation capacity, as well as the increased adipogenic potentials. Histologic analysis confirmed less bone formation and more fatty degeneration in Atp6v1h{sup +/-} mice in the different age groups. Q-PCR analysis revealed that loss of ATP6V1H function downregulated the mRNA level of TGF-β1 receptor, and its binding molecule, subunit β of adaptor protein complex 2 (AP-2), suggesting ATP6V1H regulates the proliferation and differentiation of BMSCs by interacting with TGF-β receptor I and AP-2 complex.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Methylmercury causes epigenetic suppression of the tyrosine hydroxylase gene in an in vitro neuronal differentiation model

Highlights: • The low level of methylmercury induces inhibitory epigenetic changes in LUHMES cells. • Tyrosine hydroxylase is decreased by methylmercury in neuronal differentiation model. • HistoneH3 lysine27 tri-methylation is increased in promoter of tyrosine hydroxylase. Methylmercury (MeHg) is the causative substance of Minamata disease, which is associated with various neurological disorders such as sensory disturbance and ataxia. It has been suggested low-level dietary intake of MeHg from MeHg-containing fish during gestation adversely affects the fetus. In our study, we investigated the toxicological effects of MeHg exposure on neuronal differentiation focusing on epigenetics. We used human fetal brain-derived immortalized cells (LUHMES cells) as a human neuronal differentiation model. Cell viability, neuronal, and catecholamine markers in LUHMES cells were assessed after exposure to MeHg (0–1000 nM) for 6 days (from day 2 to day 8 of neuronal differentiation). Cell viability on day 8 was not affected by exposure to 1 nM MeHg for 6 days. mRNA levels of AADC, DBH, TUJ1, and SYN1 also were unaffected by MeHg exposure. In contrast, levels of TH, the rate-limiting enzyme for dopamine synthesis, were significantly decreased after MeHg exposure. Acetylated histone H3, acetylated histone H3 lysine 9, and tri-methyl histone H3 lysine 9 levels at the TH gene promoter were not altered by MeHg exposure. However, tri-methylation of histone H3 lysine 27 levels, related to transcriptional repression, were significantly increased at the TH gene promotor after MeHg exposure. In summary, MeHg exposure during neuronal differentiation led to epigenetic changes that repressed TH gene expression. This study provides useful insights into the toxicological mechanisms underlying the effects of developmental MeHg exposure during neuronal differentiation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Valproic acid promotes the neuronal differentiation of spiral ganglion neural stem cells with robust axonal growth

Highlights: • Hearing loss occurs with loss of both hair cells and spiral ganglion neurons (SGNs). • SGN-neural stem cells (NSCs) may be a source of SGN regeneration. • Valproic acid (VPA) induces neural differentiation of SGNs and inhibits their proliferation. • VPA-treated SGN-NSCs show longer neurite outgrowths than those cultured without bFGF. • The effects of VPA are related to Wnt/β-catenin signaling activation. Hearing loss occurs with the loss of hair cells of the cochlea and subsequent degeneration of spiral ganglion neurons (SGNs). Regeneration of SGNs is a potentially promising therapeutic approach to hearing loss in addition to the use of a cochlear implant (CI), because this device stimulates SGNs directly to restore hearing bypassing the missing hair cells. The presence of SGN-neural stem cells (NSCs) has been reported in adult human and mice. These cells have the potential to become SGNs and thus represent a cellular foundation for regeneration therapies for hearing loss. Valproic acid (VPA) has been shown to influence the neural differentiation of NSCs through multiple signaling pathways involving glycogen synthase kinase3β (GSK3β). Our present study therefore aimed to modulate the neural differentiation potential of SGN-NSCs by treatment with VPA. We here report that a clinically relevant concentration of 1 mM VPA induced the differentiation of basic fibroblast growth factor (bFGF)-treated P1- and P14-SGN-NSCs into neuronal and glial cells, confirmed by neuronal marker (Tuj1 and MAP2) and glial cell marker (GFAP and S100β) detection. VPA-treated cells also promoted much longer neurite outgrowth compared to differentiated cells cultured without bFGF. The effects of VPA on the regulation of differentiation may be related to the activation of the Wnt/β-catenin signaling pathway, but not the inhibition of histone deacetylases (HDACs). We propose that VPA has the potential to convert SGN-NSCs into SGNs and thereby restore hearing when combined with a CI.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Berberine derivative, Q8, stimulates osteogenic differentiation

Highlights: • Q8 increases BMP4-induced osteoblast differentiation of C2C12 cells. • Q8 induced β-catenin nuclear accumulation by enhancing GSK3β phosphorylation via inactivation of PPARγ. • Q8 ameliorated the inhibitory effects of rosiglitazone during osteoblast differentiation. Berberine has been implicated to be involved in maintaining bone health due to its anti-oxidative and osteogenic properties. However, low potency and low bioavailability limit the clinical development of the drug. To overcome these obstacles, we previously synthesized a compound, Q8, which is a structural homolog of berberine. The present study examined the pharmacological functions of Q8 to evaluate its potential use in bone regeneration with respect to osteoblast differentiation. Here, we report that Q8 enhanced BMP4-induced alkaline phosphatase (ALP) activity and transcription from the ALP promoter. In addition, Q8 suppressed the expression and activity of PPARγ (a known negative regulator of osteogenesis due to its stimulatory effects on adipogenesis and its role as an adipogenic transcription factor), which in turn increases β-catenin expression in the nucleus, and ultimately promotes osteoblast differentiation. Meanwhile, Q8 reversed the inhibitory effects of the PPARγ agonist, rosiglitazone, on osteoblast differentiation. This study demonstrated that Q8 promotes osteoblast differentiation via inhibition of PPARγ and the enhancement of osteoblast function by Q8 may contribute to the prevention for osteoporosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

PTEN silencing enhances neuronal proliferation and differentiation by activating PI3K/Akt/GSK3β pathway in vitro

Highlights: • PTEN had a dual effect on the neuronal cells in vitro. • PTEN knockdown significantly promoted neuronal cell proliferation and differentiation. • PTEN knockdown activated Akt/GSK3β and Wnt/β-catenin pathways in vitro. • GSK3β as a key node involved in PTEN controlling cell proliferation and differentiation in PC12 cells. • PTEN-GSK3β pathway modulated neuronal proliferation via β-catenin. The failure of neuronal proliferation and differentiation is a major obstacle for neural repair and regeneration after traumatic central nervous system (CNS) injury. PTEN acts as an intrinsic brake on the neuronal cells, but its roles and mechanism still remain to be clarified. Herein, for the first time we confirmed that PTEN had a dual effect on the neuronal cells in vitro. Firstly, we found that PTEN knockdown significantly promoted cell proliferation and differentiation. Then, PTEN knockdown activated PI3K/Akt and Wnt/β-catenin pathways in vitro. Further evidence revealed that GSK3β as a key node involved in PTEN controlling cell proliferation and differentiation in PC12 cells. In addition, we identified that PTEN-GSK3β pathway modulated neuronal proliferation via β-catenin. Taken together, these results suggest that PTEN silencing enhances neuronal proliferation and differentiation by activating PI3K/Akt/GSK3β pathway that it may be a promising therapeutic approach for CNS injury.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Validation of reference genes for real-time PCR of cord blood mononuclear cells, differentiating endothelial progenitor cells, and mature endothelial cells

Highlights: • RT-qPCR was used to assess and follow the differentiation of EPCs. • A set of reliable and non-variable genes is key to obtain accurate RT-qPCR results. • The relative gene expression of CD34+ and differentiating endothelial progenitor cells was determined. • The optimal set of reference for the gene expression studies performed by RT-qPCR was determined. In the last ten years, endothelial progenitor cells (EPCs) have gained interest as an attractive cell population in regenerative medicine for vascular applications. This population is defined as the precursor of endothelial mature cells (ECs) through a process of differentiation. To our knowledge, no single marker can be used to discriminate them from mature ECs. To effectively study their differentiation kinetics, gene expression must be assessed. Quantitative real-time PCR (RT-qPCR) is widely used to analyze gene expression. To minimize the impact of variances from RT-qPCR, a rigorous selection of reference genes must be performed prior to any experiments due to variations in experimental conditions. In this study, CD34+ mononuclear cells were extracted from human cord blood and differentiated into EPCs after seeding for a maximum period of 21 days. To choose the best combinations of reference genes, we compared the results of EPCs, CD34+ mononuclear cells, and mature endothelial cells to ensure that the differentiation kinetics did not affect the expression of our selected reference genes. The expression levels of seven genes, namely, YWHAZ, GAPDH, HPRT1, RPLP0, UBC, B2M, and TBP were thus compared. The algorithms geNorm, NormFinder, BestKeeper, and the Comparative ΔCt method were employed to assess the expression of each candidate gene. Overall results reveal that the expression stability of reference genes may differ depending on the statistical program used. YWHAZ, GAPDH, and UBC composed the optimal set of reference genes for the gene expression studies performed by RT-qPCR in our experimental conditions. This work can thus serve as a starting point for the selection of candidate reference genes to normalize the levels of gene expression in endothelial progenitor cell populations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Extracellular IL-37 promotes osteogenic and odontogenic differentiation of human dental pulp stem cells via autophagy

The osteogenic and odontogenic differentiation of dental pulp stem cells (DPSCs) contribute to restoration and regeneration of dental tissue. Previous study indicated that interleukin-37 (IL-37) was an anti-inflammatory factor that affected other pro-inflammatory signals. The aim of this study was to explore the effects of IL-37 on the differentiation of DPSCs. DPSCs were cultured in growth medium with different concentrations of IL-37. We selected the optimal concentration for the following experiments by alkaline phosphatase (ALP) activity analysis, quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and Western blot. Cell counting kit assay (CCK-8) and 5-Ethynyl-2-Deoxyuridine (EdU) assay were conducted to assess the effects of IL-37 on the proliferation of DPSCs. ALP activity assay and staining, alizarin red S (ARS) staining, qRT‐PCR, Western blot as well as immunofluorescence staining were conducted to assess differentiation ability of DPSCs. Western blot, immunofluorescence staining and transmission electron microscopy (TEM) were utilized to examine cell autophagy. Results showed that IL-37 enhanced the osteogenic and odontogenic differentiation ability of DPSCs with no significant influence on the proliferation of DPSCs. Autophagy in DPSCs was activated by IL-37. Activation of autophagy enhanced osteogenesis and odontogenesis of DPSCs, whereas inhibition of autophagy suppressed DPSCs osteogenic and odontogenic differentiation. In conclusion, IL-37 increased osteogenic and odontogenic differentiation via autophagy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Paleomagnetic Evidence for a Partially Differentiated Ordinary Chondrite Parent Asteroid

Abstract The textures and accretion ages of chondrites have been used to argue that their parent asteroids never differentiated. Without a core, undifferentiated planetesimals could not have generated magnetic fields through dynamo activity, so chondrites are not expected to have experienced such fields. However, the magnetic remanence carried by the CV chondrites is consistent with dynamo‐generated fields, hinting that partially differentiated asteroids consisting of an unmelted crust atop a differentiated interior may exist. Here, we test this hypothesis by applying synchrotron X‐ray microscopy to metallic veins in the slowly cooled H6 chondrite Portales Valley. The magnetic remanence carried by nanostructures in these veins indicates that this meteorite recorded a magnetic field over a period of tens to hundreds of years at ∼100 Myr after solar system formation. These properties are inconsistent with external field sources such as the nebula, solar wind, or impacts, but are consistent with dynamo‐generated fields, indicating that the H chondrite parent body contained an advecting metallic core and was therefore partially differentiated. We calculate the thermal evolution of the chondritic portions of partially differentiated asteroids that form through incremental accretion across 10 5 to 10 6 years, finding this can agree with the measured ages and cooling rates of multiple H chondrites. We also predict that the cores of these bodies could have been partially liquid and feasibly generating a dynamo at 100 Myr after solar system formation. These observations contribute to a growing body of evidence supporting a spectrum of internal differentiation within some asteroids with primitive surfaces.

Bryson, J. F. J.↗
DOE OSTI2023

Differentiable modelling to unify machine learning and physical models for geosciences

Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. Here, in this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.

58 GEOSCIENCES↗
DOE OSTI2026

Study of fully coupled three-dimensional envelope instability using automatic differentiation

Automatic differentiation is a powerful tool for computing derivatives of simulation results with respect to given parameters. In this Letter, we have applied this tool to investigate the instability of a dynamical system governed by 21 ordinary differential equations. This second-order instability (named envelope instability) is driven by space-charge effects and has a significant impact on the operational regimes of particle accelerators. Our study delves into the three-dimensional envelope instability, incorporating both transverse and longitudinal coupling. Conventionally, analyzing this complex system would necessitate solving 441 ordinary differential equations, which is computationally intractable. However, by employing automatic differentiation, we were able to track only 21 equations. This approach allowed us to uncover an additional instability stopband, which arises from space-charge-induced coupling and has not been reported in previous studies. This research highlights the significant advantages of automatic differentiation in analyzing complicated dynamical systems involving a large number of ordinary differential equations.

Qiang, Ji [Lawrence Berkeley National Laboratory (↗
DOE OSTI2021

Informing nuclear physics via machine learning methods with differential and integral experiments

Information from differential nuclear-physics experiments and theory is often too uncertain to accurately define nuclear-physics observables such as cross sections or energy spectra. Integral experimental data, representing the applications of these observables, are often more precise but depend simultaneously on too many of them to unambiguously identify issues in the observable with human expert analysis alone. Here, we explore how we can leverage physics knowledge gained from differential experimental data, nuclear theory, integral experiments, and neutron-transport calculations to better understand nuclear-physics observables in the context of the application area represented by integral experiments. We support this task with machine-learning methods to discern trends in a large amount of convoluted data. Differential and integral information was used in an analysis augmented by the random forest and the Shapley additive explanations metric. We chose as an application area one that is represented by criticality measurements and pulsed-sphere neutron-leakage spectra. We show one representative example ( 241 Pu fission observables) where the combination of differential and integral information allowed to resolve issues in data representing these observables. As a starting point, the machine learning (ML) algorithms highlighted several observables as leading potentially to bias in simulating integral experiments. Differential information, paired with sensitivity to integral quantities, allowed us then to pinpoint one specific observable ( 241 Pu fission cross section) as the main driver of bias. The comparison to integral experiments, on the other hand, allowed us to indicate a likely reliable experiment among several discrepant ones for this observables. In other cases (e.g., 239 Pu observables), we were not able to resolve the confounding introduced by integral experiments but instead highlighted the need for targeted new experiments and theory developments to better constrain the nuclear-physics space for the application area represented by integral experiments. We were able to combine information from differential experimental data, nuclear-physics theory, integral experiments, and neutron-transport simulations of the latter experiments with the help of the random forest algorithm and expert judgment. This combination of knowledge allows to improve our description of nuclear-physics observables as applied to a particular application area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

The Memory Scaling of Reverse-Mode Differentiation in Particle Accelerator Simulations with Space Charge

The recent development of differentiable simulation codes for particle accelerators has enabled gradient-based workflows that promise finer control and more realistic modeling of accelerator facilities. However, when using reverse-mode automatic differentiation, the memory usage continuously increases during the simulation, and can potentially exceed the available hardware memory - especially when costly space charge computation is included. To study the memory requirements for differentiable simulations, we have implemented space charge in Cheetah, a PyTorch-based beam tracking code that supports reverse-mode differentiation. We find that the memory usage for reverse-mode differentiation grows linearly with the number of macroparticles and cells, and that it is proportional to the number of space charge kicks involved in the simulation. This general scaling can be used to evaluate whether a given differentiable simulation is feasible given hardware memory constraints.

Dhamrait, Arjun↗