How multisensory neurons solve causal inference.

Sitting in a static railway carriage can produce illusory self-motion if the train on an adjoining track moves off. While our visual system registers motion, vestibular signals indicate that we are stationary. The brain is faced with a difficult challenge: is there a single cause of sensations (I am moving) or two causes (I am static, another train is moving)? If a single cause, integrating signals produces a more precise estimate of self-motion, but if not, one cue should be ignored. In many cases, this process of causal inference works without error, but how does the brain achieve it? Electrophysiological recordings show that the macaque medial superior temporal area contains many neurons that encode combinations of vestibular and visual motion cues. Some respond best to vestibular and visual motion in the same direction ("congruent" neurons), while others prefer opposing directions ("opposite" neurons). Congruent neurons could underlie cue integration, but the function of opposite neurons remains a puzzle. Here, we seek to explain this computational arrangement by training a neural network model to solve causal inference for motion estimation. Like biological systems, the model develops congruent and opposite units and recapitulates known behavioral and neurophysiological observations. We show that all units (both congruent and opposite) contribute to motion estimation. Importantly, however, it is the balance between their activity that distinguishes whether visual and vestibular cues should be integrated or separated. This explains the computational purpose of puzzling neural representations and shows how a relatively simple feedforward network can solve causal inference

High-dose chemotherapy as initial salvage treatment in relapsed testicular cancer patients

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Reflectivity and velocity radar data assimilation for two flash flood events in central Italy: A comparison between 3D and 4D variational methods

The aim of this study is to provide an evaluation of the impact of two largely used data assimilation techniques, namely three- and four-dimensional variational data assimilation systems (3D-Var and 4D-Var), on the forecasting of heavy precipitation events using the Weather Research and Forecasting (WRF) model. For this purpose, two flash flood events in central Italy are analysed. The first occurred on September 14, 2012 during an Intensive Observation Period of the Hydrological cycle in the Mediterranean experiment (HyMeX) campaign, while the other occurred on May 3, 2018. Radial velocity and reflectivity acquired by C-band weather radars at Mt. Midia (central Italy) and San Pietro Capofiume (northern Italy), as well as conventional observations (SYNOP and TEMP), are assimilated into the WRF model to simulate these damaging flash flood events. In order to evaluate the impact of the 3D-Var and 4D-Var assimilation systems on the estimation of short-term quantitative precipitation forecasts, several experiments are carried out using conventional observations with and without radar data. Rainfall evaluation is performed by means of point-by-point and filtering methodologies. The results point to a positive impact of the 4D-Var technique compared to results without assimilation and with 3D-Var experiments. More specifically, the 4D-Var system produces an increase of up to 22% in terms of the Fractions Skill Score compared to 3D-Var for the first flash flood event, while an increase of about 5% is achieved for the second event. The use of a warm start initialization results in a considerable reduction in the spin-up time and a significant improvement in the rainfall forecast, suggesting that the initial precipitation spin-up problem still occurs when using 4D-Var

Pharmacokinetic and metabolism determinants of fluoropyrimidines and oxaliplatin activity in treatment of colorectal patients

Fluoropyrimidines and oxaliplatin continued to be the mainstay of therapeutic regimens in the treatment of colorectal cancer (CRC). For this reason, pharmacokinetic and metabolism of these drugs were analyzed and the identification of accurate and validated predictive, prognostic and toxicity markers became necessary to develop an effective therapy adapted to the patient's molecular profile, while minimizing life-threatening toxicities. In this review, we discuss literature data, defining predictive and prognostic markers actually identified in the treatment of CRC. We analyzed predictive markers of fluoropyrimidines effectiveness, principally for 5-Fluorouracil (5-FU) and also for oral fluoropyrimidines, as thymidylate Synthase (TS), dihydropyrimidine dehydrogenase (DPD), orotate phosphoribosyl transferase (OPRT), methylenetetrahydrofolate reductase (MTHFR), deoxyuridine triphosphate nucleotidohydrolase (dUTPase), micro-satellite instability. DPD represent the more studied 5-FU toxicity marker, followed by TS and OPRT. Oxaliplatin effectiveness is principally regulated by nucleotide excision repair (NER) pathway, including excision repair cross-complementation group 1 (ERCC1), X-ray cross-complementing group 1 (XRCC1) and xeroderma pigmentosum group D (XDP). The major oxaliplatin toxicity marker is represented by glutathione S-transferase (GST). All these results are based principally on retrospective studies. The future challenge became to validate molecular markers and their association with clinical outcomes in prospective trials, refining technologic platforms and bioin-formatics to accommodate the complexity of the multifaceted molecular map that may determine outcome, and determining CRC patients most likely to benefit from therapeutic interventions tailored specifically for them

Implementing anti-epidermal growth factor receptor (EGFR) therapy in metastatic colorectal cancer: challenges and future perspectives

Epidermal growth factor receptor (EGFR) inhibitors are valuable therapeutics in metastatic colorectal cancer (mCRC). Anti-EGFR monoclonal antibodies (MoAbs), such as cetuximab or panitumumab, in combination with chemotherapy are effective treatment options for patients with RAS and BRAF wild-type mCRC. Nevertheless, several issues are still open concerning the optimal use of anti-EGFR drugs in the continuum of care of mCRC. Novel approaches for increasing the efficacy of anti-EGFR therapies include better molecular selection of EGFR-dependent mCRC, intensification of chemotherapy, combination of anti-EGFR MoAbs and immune checkpoint inhibitors, and reintroduction of EGFR blockade or 'rechallenge' in selected patients who have previously responded to anti-EGFR MoAb therapy. An extensive translational research program was conducted in the Cetuximab After Progression in KRAS wIld-type colorectal cancer patients-Gruppo Oncologico dell' Italia Meridionale (CAPRI-GOIM) study with the aims of determining which subgroups of patients could benefit from the continuous inhibition of EGFR, from evaluating the role of liquid biopsy-based and its concordance with tissue-based molecular testing, and from investigating novel potential mechanisms of resistance to anti-EGFR therapies. In this review, we summarize the translational and clinical findings of the CAPRI-GOIM program in the context of the current knowledge of therapeutic strategies and of ongoing research on more appropriate uses of anti-EGFR therapies in RAS and BRAF wild-type mCRC patients

Experience of 170 cases of ductal carcinoma in ' (DCIS)

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