Commodity futures market conditions and climate policy risk:Evidence from energy and metals markets

This study investigates the impact of climate policy uncertainty (CPU) on energy and metal commodity futures markets by employing quantile regression, which accounts for various (bearish, normal, and bullish) markets. Our results reveal that the impact of CPU shocks is heterogeneous and market condition-specific. Particularly, CPU exerts a significantly negative effect on all commodities, except natural gas, in a bearish market. Under a normal market, the impact of CPU on energy returns varies across commodities whereas for a bullish market, the CPU effect is mixed. The results also reveal natural gas to be a good hedge instrument for climate policy risk. We further conducted channel analysis using the theory of storage and hedging pressure hypothesis. The key finding reveals inventory level as the transmission channel of climate policy risk. Our findings have implications for the inventory management strategies of producers and suggest that regulators should consider market-based policies in their decarbonization efforts.</p

Impact of the inversion time on regional brain perfusion estimation with clinical arterial spin labeling protocols

Objective: Evaluating the impact of the Inversion Time (TI) on regional perfusion estimation in a pediatric cohort using Arterial Spin Labeling (ASL). Materials and methods: Pulsed ASL (PASL) was acquired at 3 T both at TI 1500 ms and 2020 ms from twelve MRI-negative patients (age range 9–17 years). A volume of interest (VOIs) and a voxel-wise approach were employed to evaluate subject-specific TI-dependent Cerebral Blood Flow (CBF) differences, and grey matter CBF Z-score differences. A visual evaluation was also performed. Results: CBF was higher for TI 1500 ms in the proximal territories of the arteries (PTAs) (e.g. insular cortex and basal ganglia — P < 0.01 and P < 0.05 from the VOI analysis, respectively), and for TI 2020 ms in the distal territories of the arteries (DTAs), including the watershed areas (e.g. posterior parietal and occipital cortex — P < 0.001 and P < 0.01 from the VOI analysis, respectively). Similar differences were also evident when analyzing patient-specific CBF Z-scores and at a visual inspection. Conclusions: TI influences ASL perfusion estimates with a region-dependent effect. The presence of intraluminal arterial signal in PTAs and the longer arterial transit time in the DTAs (including watershed areas) may account for the TI-dependent differences. Watershed areas exhibiting a lower perfusion signal at short TIs (~ 1500 ms) should not be misinterpreted as focal hypoperfused areas

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN–Neuroimaging Network

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures

Area under the curve of methotrexate and creatinine clearance are outcome-determining factors in primary CNS lymphomas

Although high-dose methotrexate (HD-MTX) is the most effective drug against primary CNS lymphomas (PCNSL), outcome-determining variables related to its administration schedule have not been defined. The impact on toxicity and outcome of the area under the curve (AUC(MTX)), dose intensity (DI(MTX)) and infusion rate (IR(MTX)) of MTX and plasmatic creatinine clearance (CL(crea)) was investigated in a retrospective series of 45 PCNSL patients treated with three different HD-MTX-based combinations. Anticonvulsants were administered in 31 pts (69%). Age >60 years, anticonvulsant therapy, slow IR(MTX) (1100 micromol hl(-1) were independently associated with a better survival. Slow CL(crea) and high AUC(MTX) are favourable outcome-determining factors in PCNSL, while slow CL(crea) is significantly related to higher toxicity. AUC(MTX) significantly correlates with age, anticonvulsant therapy, IR(MTX), and DI(MTX). These findings, which seem to support the choice of an MTX dose >/=3 gm(-2) in a 4-6-h infusion, every 3-4 weeks, deserve to be assessed prospectively in future trials. MTX dose adjustments in patients with fast CL(crea) should be investigated

The Italian Rare Biliary tract Cancer initiative (IRaBiCa): A multicentric observational study of Gruppo Oncologico dell’Italia Meridionale (GOIM) in collaboration with Gruppo Italiano Colangiocarcinoma (GICO)

Introduction: About 90% of cholangiocarcinomas are adenocarcinomas with glandular or tubular structures lined by epithelial cells, with no bile production and with a variable degree of differentiation, arising in the background of desmoplastic stroma. The remaining 10% is represented by rarer histological variants of which there is little knowledge regarding the biological behavior, molecular characterization, and sensitivity to the various possible therapies, including molecular-based treatments. Such rare tumors are described only in case reports or small retrospective series because of their exclusion from clinical trials. This national initiative, here presented, aims to address the following knowledge gap: a) how much does histological diversity translate into clinical manifestation variety? b) are those chemotherapy regimens, recommended for conventional biliary tract cancers, potentially active in rare variants? Therefore, epidemiological, pathological, and clinical characterization of series of rare biliary histotypes/variants, for which therapeutic and follow-up data are available, will be collected. Methods: An Italian task force on rare tumors of the biliary tract (IRaBiCa) has been created, whose initiative is a multicenter retrospective study involving 34 Italian cancer centers. Clinical data from approximately 100 patients will be collected and analyzed. Continuous variables will be presented as median ± standard deviation, while categorical variables will be expressed in terms of frequency. Kaplan-Maier analyses will be used to compare disease free, progression free and overall survival, according to the different histotypes. Conclusions: We expect to gather novel data on rare histotypes of biliary tract cancer that will be useful to support their molecular and immunological characterization

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer’s dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Persistent trigeminal artery causing double neurovascular conflict

We report the case of a 73-year-old woman who presented with right VI nerve palsy and homolateral atypical trigeminal neuralgia; standard neuroradiological investigation of orbital/retroorbital regions and intracranial arteries excluded the most commonly demonstrable underlying causes while brain magnetic resonance (T1-weighted fat suppression; T2-weighted thin-section) and magnetic resonance angiography disclosed the evidence of "double" neurovascular conflict because of persistent trigeminal artery with aneurysmal dilation