Targeting the TCA cycle can ameliorate widespread axonal energy deficiency in neuroinflammatory lesions

Inflammation in the central nervous system can impair the function of neuronal mitochondria and contributes to axon degeneration in the common neuroinflammatory disease multiple sclerosis (MS). Here we combine cell-type-specific mitochondrial proteomics with in vivo biosensor imaging to dissect how inflammation alters the molecular composition and functional capacity of neuronal mitochondria. We show that neuroinflammatory lesions in the mouse spinal cord cause widespread and persisting axonal ATP deficiency, which precedes mitochondrial oxidation and calcium overload. This axonal energy deficiency is associated with impaired electron transport chain function, but also an upstream imbalance of tricarboxylic acid (TCA) cycle enzymes, with several, including key rate-limiting, enzymes being depleted in neuronal mitochondria in experimental models and in MS lesions. Notably, viral overexpression of individual TCA enzymes can ameliorate the axonal energy deficits in neuroinflammatory lesions, suggesting that TCA cycle dysfunction in MS may be amendable to therapy

Nanoscale transient polarization gratings

We present the generation of transient polarization gratings at the nanoscale, achieved using a tailored accelerator configuration of the FERMI free electron laser. We demonstrate the capabilities of such a transient polarization grating by comparing its induced dynamics with the ones triggered by a more conventional intensity grating on a thin film ferrimagnetic alloy. While the signal of the intensity grating is dominated by the thermoelastic response of the system, such a contribution is suppressed in the case of the polarization grating. This exposes helicity-dependent magnetization dynamics that have so-far remained hidden under the large thermally driven response. We anticipate nanoscale transient polarization gratings to become useful for the study of any physical, chemical and biological systems possessing chiral symmetry

A new method for measuring angle-resolved phases in photoemission

Quantum mechanically, photoionization can be fully described by the complex photoionization amplitudes that describe the transition between the ground state and the continuum state. Knowledge of the value of the phase of these amplitudes has been a central interest in photoionization studies and newly developing attosecond science, since the phase can reveal important information about phenomena such as electron correlation. We present a new attosecond-precision interferometric method of angle-resolved measurement for the phase of the photoionization amplitudes, using two phase-locked Extreme Ultraviolet pulses of frequency $\omega$ and $2\omega$, from a Free-Electron Laser. Phase differences $\Delta \tilde \eta$ between one- and two-photon ionization channels, averaged over multiple wave packets, are extracted for neon $2p$ electrons as a function of emission angle at photoelectron energies 7.9, 10.2, and 16.6 eV. $\Delta \tilde \eta$ is nearly constant for emission parallel to the electric vector but increases at 10.2 eV for emission perpendicular to the electric vector. We model our observations with both perturbation and \textit{ab initio} theory, and find excellent agreement. In the existing method for attosecond measurement, Reconstruction of Attosecond Beating By Interference of Two-photon Transitions (RABBITT), a phase difference between two-photon pathways involving absorption and emission of an infrared photon is extracted. Our method can be used for extraction of a phase difference between single-photon and two-photon pathways and provides a new tool for attosecond science, which is complementary to RABBITT

COMMISIONING OF THE FERMI@ELETTRA LASER HEATER*

Abstract The linac of the FERMI seeded free electron laser includes a laser heater to control the longitudinal microbunching instability, which otherwise is expected to degrade the quality of high brightness electron beam sufficiently to reduce the FEL power. The laser heater consists of a short undulator located in a small magnetic chicane through which an external laser pulse enters to modulate the electron beam energy both temporally and spatially. This modulation, which varies on the scale of the laser wavelength, together with the effective R52 transport term of the chicane increases the incoherent energy spread (i.e., e-beam heating). We present the first commissioning results of this system, and its impact both upon the electron beam phase space, and upon the FEL output intensity and quality

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research

Introduction: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). Methods and objectives: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. Conclusion: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

IntroductionArtificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods.MethodsWe prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions.ResultsOf 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models’ prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR.ConclusionsIn this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients

A detailed investigation of single-photon laser enabled Auger decay in neon

Single-photon laser enabled Auger decay (spLEAD) is an electronic de-excitation process which was recently predicted and observed in Ne. We have investigated it using bichromatic phase-locked free electron laser radiation and extensive angle-resolved photoelectron measurements, supported by a detailed theoretical model. We first used separately the fundamental wavelength resonant with the Ne+ 2s?2p transition, 46.17 nm, and its second harmonic, 23.08 nm, then their phase-locked bichromatic combination. In the latter case the phase difference between the two wavelengths was scanned, and interference effects were observed, confirming that the spLEAD process was occurring. The detailed theoretical model we developed qualitatively predicts all observations: branching ratios between the final Auger states, their amplitudes of oscillation as a function of phase, the phase lag between the oscillations of different final states, and partial cancellation of the oscillations under certain conditions

Evaluation of tumor-infiltrating lymphocytes in HER2-positive breast cancer patients treated with neoadjuvant therapy

openBackground: La valutazione morfologica dei linfociti infiltranti il tumore (TILs) nel carcinoma mammario sta acquisendo sempre più rilievo come marcatore prognostico e predittivo di risposta al trattamento, in particolare nel contesto della malattia residua (RD) post chemioterapia neoadiuvante (NACT) in pazienti che non ottengono l’eradicazione completa della malattia residua (=risposta patologica completa, pCR). Tuttavia, l’impatto dei TILs è eterogeneo tra i diversi sottotipi di carcinoma mammario ed il ruolo non è ben chiaro nel sottotipo HER2+. Scopo dello studio: Lo scopo principale del presente studio è rappresentato dalla valutazione del ruolo prognostico dei TILs, analizzati sul residuo tumorale (RD-TILs) in pazienti affette da carcinoma mammario HER2+ sottoposte a trattamento neoadiuvante, a base di chemioterapia e targeted therapy anti-HER2. È stato inoltre elaborato uno score composito RCB + TILs che integra le informazioni prognostiche fornite dal “residual cancer burden” (RCB) e dall’infiltrato linfocitario RD-TILs. Materiali e metodi: È stata inclusa retrospettivamente una coorte multicentrica di pazienti con carcinoma mammario HER2+ sottoposte a trattamento neoadiuvante. Per ogni paziente sono state recuperate le sezioni colorate in ematossilina/eosina del materiale istologico relativo alla biopsia basale, e, per coloro che non hanno raggiunto la pCR, del materiale istologico relativo al residuo di malattia. Per ogni paziente è stato calcolato il RCB tramite tool online. I TILs stromali sono stati valutati adottando le raccomandazioni del Working Group Internazionale sui Biomarcatori Immunologici. Le analisi statistiche sono state condotte con software IBM SPSS Statistics v24. Per le analisi di sopravvivenza è stato adottato l’endpoint overall survival (OS) e applicato il metodo di Kaplan-Meier per stimare le curve di sopravvivenza. L’indice di Harrell (C-index) è stato applicato per determinare il cut-off dei RD-TILs che meglio correla con la prognosi e per eseguire confronti di performance prognostica dei diversi biomarcatori. Risultati: Abbiamo incluso 295 pazienti, di cui 195 presentavano RD dopo NACT. Abbiamo osservato una relazione positiva statisticamente significativa tra i livelli di TILs basali e la probabilità di raggiungimento della pCR dopo NACT (tassi di pCR in high TILs [ 10%] vs low TILs [ 10%]: 64% vs 33%, p0,001). Nel sottogruppo di pazienti che non ha raggiunto la pCR, abbiamo osservato una relazione significativa tra RCB e OS (HR 1,97; 95% CI 1,415-2,744; p0,001) e RD-TILs e OS (HR 2.32; 95% CI 1.07-5.03; p=0,028). In analisi multivariata, sia RCB sia RD-TILs hanno conservato una relazione significativa indipendente con l’outcome (RCB: HR 1,90; 95% CI 1,35-2,67; p0,001; RD-TIL: HR 2,30; 95% CI 1,06-5,01; p=0,036). Lo score composito RCB + TILs è risultato essere significativamente associato all’OS sia come variabile continua (HR 2,72; 95% CI 1,72-4,31; p0,001), sia dicotomizzato, adottando come cut-off 1,72. La performance prognostica dello score RCB + RD-TILs è risultata essere significativamente superiore a quella del RCB (0,73 vs 0,68 p=0,08) e a quella dei RD-TILs (0,73 vs 0,58 p=0,07). Conclusioni: Abbiamo riportato un impatto prognostico negativo dei RD-TILs in pazienti con carcinoma mammario HER2+ che hanno fallito il raggiungimento della pCR dopo NACT a base di chemioterapia + terapia targeted anti-HER2. Tale osservazione potrebbe sottendere uno squilibrio del microambiente immunitario della RD verso caratteristiche immunosoppressive. Abbiamo inoltre generato un nuovo score prognostico composito RCB + TILs, che si è rivelato essere più informativo rispetto alla valutazione isolata di RCB e RD-TILs nel predire l'OS. Questo modello composito potrebbe agevolare l’identificazione di pazienti ad alto rischio di recidiva che potrebbero beneficiare di trattamenti aggiuntivi nel setting post-neoadiuvante.Background: TILs’ morphological evaluation in breast cancer is achieving increasing importance as a prognostic and predictor marker of response to treatment, especially in residual disease (RD) after neoadjuvant chemotherapy (NACT) in patients who not obtain the complete eradication of residual disease (= pathologic-complete response, pCR). However, TILs’ impact is heterogeneous between different breast cancers and their role isn’t clear in HER2+ subtype. Purpose: We aim to evaluate the prognostic significance of tumor-infiltrating lymphocyte on residual disease (RD-TIL) in HER2+ breast cancer (BC) patients who failed to achieve pathologic-complete response (pCR) after neoadjuvant treatment, based on chemotherapy and targeted therapy anti-HER2. Also, we elaborated a composite score (RCB + TILs) that combining the prognostic information provided by residual cancer burden (RCB) and RD-TILs. Methods: We retrospectively included a multicenter cohort of patients with HER2+ breast cancer treated with neoadjuvant therapy. We recovered for each patient the hematoxylin/eosin stained slides of the histological material to the baseline biopsy, and, for patients who did not achieve pCR, of the histological material to the residual disease. RCB was evaluated through a tool online. Stromal TILs were evaluated according to recommendations of Working International Group on Immunological Biomarkers. Statistical analyses were produced through software IBM SPSS Statistics v24. Endpoint overall survival (OS) was used as an outcome measure and Kaplan-Meier analysis was used to estimate survival. Harrell’s index (C-index) was applied to define RD-TILs cut-off that better was associated with survival and to realize comparisons of prognostic performance of markers. Results: we included 295 patients, 195 of them showed RD after NACT. We observed a statistically positive relationship between basal TILs and pCR rates after NACT (pCR in high TILs [ 10%] vs low TILs [ 10%]: 64% vs 33%, p0,001). In patients who not achieve pCR, we observed a significant relationship between RCB and OS (HR 1,97; 95% CI 1,415-2,744; p0,001) and RD-TILs and OS (HR 2.32; 95% CI 1.07-5.03; p=0,028). In multivariate analysis, both RCB and RD-TILs have maintained a independent relationship with outcome (RCB: HR 1,90; 95% CI 1,35-2,67; p0,001; RD-TIL: HR 2,30; 95% CI 1,06-5,01; p=0,036). Composite score RCB + TILs were significantly associated with OS, both as continuous variable (HR 2,72; 95% CI 1,72-4,31; p0,001), both dichotomized variable (cut-off 1,72). The C-index for OS of the RCB+TIL score was numerically higher than that of RCB (0,73 vs 0,68 p=0,08) and significantly higher than that of RD-TILs (0,73 vs 0,58 p=0,07)

In vitro assessment of dietary bioactives for TFEB activation as a possible target to support cognitive and emotional wellbeing

Aging and chronic stress are associated with altered brain plasticity and an increased risk of developing cognitive and emotional health problems. A key cellular mechanism involved is autophagy, which is known to be important for memory encoding and information processing, and is also thought to be important for psychiatric and emotional health. Activation of the autophagic system can be established by the transcription factor EB (TFEB), which regulates both autophagosome formation and lysosomal biogenesis and function. As well-known activators of autophagy like caloric restriction, fasting, or regular exercise require intervention programs that are hard to adhere to, the search for nutritional solutions with similar effects, is increasing. We therefore evaluated pro-autophagic dietary bioactives for effects specifically through TFEB activation and assessed whether combining bioactives can lead to synergistic or additive effects. We also discuss current evidence supporting the use of these natural dietary compounds to promote cognitive and emotional wellbeing. Methods: Primary cortical astrocytes were treated with 13 different ingredients and analyzed for their effect on TFEB nuclear translocation by high content imaging. Effective ingredients were then evaluated at different concentrations for their effect on TFEB downstream signaling by analyzing mRNA levels of Beclin1, LC3, Lamp-1 and Cathepsin D. Furthermore, the synergistic effects of sub-optimal concentrations of different ingredient combinations were evaluated on the same TFEB downstream signaling markers. Potential signs of toxicity of all ingredients and their combinations were evaluated by analysis of ATP production and nuclear counts. Results: DHA, EPA, 7,8-DHF, ellagic acid, curcumin and spermidine increased TFEB nuclear localization. DHA and spermidine exhibited the strongest effects when measuring mRNA levels of TFEB downstream signaling markers. The most significant synergies were observed when combining spermidine with ellagic acid or when combining DHA with curcumin. None of the ingredients alone or in combination presented any sign of toxicity at the concentrations tested. Discussion/Conclusion: The results of our study show for the first time a synergistic effect of spermidine and ellagic acid and of DHA and curcumin on TFEB signaling and thus its ability to act on the autophagic system in brain cells. These combinations may hold potential as dietary promoters of cognitive and emotional wellbeing