Vector-based navigation using grid-like representations in artificial agents.

Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go1,2. Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space7,8 and is critical for integrating self-motion (path integration)6,7,9 and planning direct trajectories to goals (vector-based navigation)7,10,11. Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation7,10,11, demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments.

Kidney transplant patients with SARS-CoV-2 infection: The Brescia Renal COVID task force experience.

The outcome of kidney transplant patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still unclear. Here we describe the clinical characteristics, disease outcome, and risk factors for acute respiratory distress syndrome (ARDS) and death of a cohort of 53 kidney transplant patients with coronavirus disease 2019 (COVID-19). Eight of 53 have been handled as outpatients because of mild disease, on average with immunosuppression reduction and the addition of hydroxychloroquine and azithromycin; no patients required admission, developed ARDS, or died. Because of severe symptoms, 45/53 required admission: this cohort has been managed with immunosuppression withdrawal, methylprednisolone 16 mg/d, hydroxychloroquine, and antiviral drugs. Dexamethasone and tocilizumab were considered in case of ARDS. About 33% of the patients developed acute kidney injury, 60% ARDS, and 33% died. In this group, thrombocytopenia was associated to ARDS whereas lymphopenia at the baseline, higher D-dimer, and lack of C-reactive protein reduction were associated with risk of death. In the overall population, dyspnea was associated with the risk of ARDS and age older than 60 years and dyspnea were associated with the risk of death with only a trend toward an increased risk of death for patients on tacrolimus. In conclusion, SARS-CoV-2 infection may have a variable outcome in renal transplant patients, with higher risk of ARDS and death in the ones requiring admission.

Energy Harvester Sensing.

Our existence is immersed in a solution of energy, which is often left to degrade because we perceive this energy as expendable [...].

SARS-CoV-2 infection in dialysis and kidney transplant patients: immunological and serological response.

BACKGROUND: Dialysis and kidney transplant patients with moderate-severe COVID-19 have a high mortality rate, around 30%, that is similar in the two populations, despite differences in their baseline characteristics. In these groups, the immunology of the disease has been poorly explored. METHODS: Thirty-two patients on dialysis or with kidney transplant and SARS-CoV-2 infection requiring hospitalization (COV group) were included in our study. Lymphocyte subsets, dendritic cell (DC) counts and monocyte activation were studied. SARS-CoV-2 anti-spike/anti-nucleocapsid were monitored, and baseline cytokines and chemokines were measured in 10 patients. RESULTS: The COV group, compared to healthy subjects and uninfected dialysis/kidney transplant controls, showed lower numbers of CD4 + and CD8 + T cells, Natural-Killer (NK), B cells, plasmacytoid and myeloid DCs, while the proportion of terminally differentiated B-cells was increased. IL6, IL10, IFN-α and chemokines involved in monocyte and neutrophil recruitment were higher in the COV group, compared to uninfected dialysis/kidney transplant controls. Patients with severe disease had lower CD4 + , CD8 + and B-cell counts and lower monocyte HLA-DR expression. Of note, when comparing dialysis and kidney transplant patients with COVID-19, the latter group presented lower NK and pDC counts and monocyte HLA-DR expression. Up to 60 days after symptom onset, kidney transplant recipients showed lower levels of anti-spike antibodies compared to dialysis patients. CONCLUSIONS: During SARS-CoV-2 infection, dialysis and kidney transplant patients manifest immunophenotype abnormalities; these are similar in the two groups, however kidney transplant recipients show more profound alterations of the innate immune system and lower anti-spike antibody response.

Neural scene representation and rendering.

Scene representation-the process of converting visual sensory data into concise descriptions-is a requirement for intelligent behavior. Recent work has shown that neural networks excel at this task when provided with large, labeled datasets. However, removing the reliance on human labeling remains an important open problem. To this end, we introduce the Generative Query Network (GQN), a framework within which machines learn to represent scenes using only their own sensors. The GQN takes as input images of a scene taken from different viewpoints, constructs an internal representation, and uses this representation to predict the appearance of that scene from previously unobserved viewpoints. The GQN demonstrates representation learning without human labels or domain knowledge, paving the way toward machines that autonomously learn to understand the world around them.

Apolipoprotein E in idiopathic nephrotic syndrome and focal segmental glomerulosclerosis.

BACKGROUND: Hyperlipemia characterizes nephrotic syndrome (NS) and contributes to the progression of the underlying nephropathy. The data in the literature support an implication of apolipoprotein E (apoE) in both hyperlipemia and focal segmental glomerulosclerosis (FSGS), a malignant condition associated with NS. METHODS: The apoE genotype was determined in 209 nephrotic patients, who were classified according to age and their response to steroids as resistant children (N = 96) and adults (43), and steroid dependent (33) and steroid responder (37) children. A total of 123 presented the histological features of FSGS. In a subgroup of 28 patients, serum and urinary levels of apoE and renal deposits were evaluated by immunofluorescence. RESULTS: The allelic frequencies of the three major haplotypes epsilon2, epsilon3, and epsilon4 were the same in nephrotic patients versus controls, and homozygosity for epsilon3epsilon3 was comparably the most frequent genotype (70 vs. 71%) followed by epsilon3epsilon4, epsilon2epsilon3, epsilon2epsilon4, epsilon4epsilon4. Serum levels of apoE were fivefold higher in NS and in FSGS patients than in controls, with a direct correlation with hypercholesterolemia and proteinuria. ApoE genotypes did not influence serum levels. Urinary levels were 1/10,000 of serum with an increment in nephrotic urines. Finally, immunofluorescence demonstrated the absence of apoE in sclerotic glomeruli, while comparably nephrotic patients with membranous nephropathy had an increased glomerular expression of apoE. CONCLUSIONS: ApoE is dysregulated in NS with a marked increment in serum, which is a part of the complex lipid metabolism. Down-regulation of glomerular apoE instead is a peculiarity of FSGS and may contribute to the pathogenesis of the disease. The normal distribution of apoE genotypes in nephrotic patients with FSGS excludes a pathogenetic role of genetic variants.