Multi-Domain Norm-referenced Encoding Enables Data Efficient Transfer Learning of Facial Expression Recognition

People can innately recognize human facial expressions in unnatural forms, such as when depicted on the unusual faces drawn in cartoons or when applied to an animal's features. However, current machine learning algorithms struggle with out-of-domain transfer in facial expression recognition (FER). We propose a biologically-inspired mechanism for such transfer learning, which is based on norm-referenced encoding, where patterns are encoded in terms of difference vectors relative to a domain-specific reference vector. By incorporating domain-specific reference frames, we demonstrate high data efficiency in transfer learning across multiple domains. Our proposed architecture provides an explanation for how the human brain might innately recognize facial expressions on varying head shapes (humans, monkeys, and cartoon avatars) without extensive training. Norm-referenced encoding also allows the intensity of the expression to be read out directly from neural unit activity, similar to face-selective neurons in the brain. Our model achieves a classification accuracy of 92.15\% on the FERG dataset with extreme data efficiency. We train our proposed mechanism with only 12 images, including a single image of each class (facial expression) and one image per domain (avatar). In comparison, the authors of the FERG dataset achieved a classification accuracy of 89.02\% with their FaceExpr model, which was trained on 43,000 images

Insights into Autotrophic Activities and Carbon Flow in Iron-Rich Pelagic Aggregates (Iron Snow)

Pelagic aggregates function as biological carbon pumps for transporting fixed organic carbon to sediments. In iron-rich (ferruginous) lakes, photoferrotrophic and chemolithoautotrophic bacteria contribute to CO2 fixation by oxidizing reduced iron, leading to the formation of iron-rich pelagic aggregates (iron snow). The significance of iron oxidizers in carbon fixation, their general role in iron snow functioning and the flow of carbon within iron snow is still unclear. Here, we combined a two-year metatranscriptome analysis of iron snow collected from an acidic lake with protein-based stable isotope probing to determine general metabolic activities and to trace 13CO2 incorporation in iron snow over time under oxic and anoxic conditions. mRNA-derived metatranscriptome of iron snow identified four key players (Leptospirillum, Ferrovum, Acidithrix, Acidiphilium) with relative abundances (59.6–85.7%) encoding ecologically relevant pathways, including carbon fixation and polysaccharide biosynthesis. No transcriptional activity for carbon fixation from archaea or eukaryotes was detected. 13CO2 incorporation studies identified active chemolithoautotroph Ferrovum under both conditions. Only 1.0–5.3% relative 13C abundances were found in heterotrophic Acidiphilium and Acidocella under oxic conditions. These data show that iron oxidizers play an important role in CO2 fixation, but the majority of fixed C will be directly transported to the sediment without feeding heterotrophs in the water column in acidic ferruginous lakes

Bidirectional gray matter changes after complex motor skill learning

Long-term motor skill learning has been consistently shown to result in functional as well as structural changes in the adult human brain. However, the effect of short learning periods on brain structure is not well understood. In the present study, subjects performed a sequential pinch force task (SPFT) for 20 min on 5 consecutive days. Changes in brain structure were evaluated with anatomical magnetic resonance imaging (MRI) scans acquired on the first and last day of motor skill learning. Behaviorally, the SPFT resulted in sequence-specific learning with the trained (right) hand. Structural gray matter (GM) alterations in left M1, right ventral premotor cortex (PMC) and right dorsolateral prefrontal cortex (DLPFC) correlated with performance improvements in the SPFT. More specifically we found that subjects with strong sequence-specific performance improvements in the SPFT also had larger increases in GM volume in the respective brain areas. On the other hand, subjects with small behavioral gains either showed no change or even a decrease in GM volume during the time course of learning. Furthermore, cerebellar GM volume before motor skill learning predicted (A) individual learning-related changes in the SPFT and (B) the amount of structural changes in left M1, right ventral PMC and DLPFC. In summary, we provide novel evidence that short-term motor skill learning is associated with learning-related structural brain alterations. Additionally, we showed that practicing a motor skill is not exclusively accompanied by increased GM volume. Instead, bidirectional structural alterations explained the variability of the individual learning success

Enhanced activation of an amino-terminally truncated isoform of the voltage-gated proton channel HVCN1 enriched in malignant B cells

The final published version can be found here: http://dx.doi.org/10.1073/pnas.1411390111M.C. is the recipient of a Bennett Fellowship from Leukaemia and Lymphoma Research (ref. 12002). M.A.B. is supported by a GlaxoSmithKline Oncology–Biotechnology and Biological Sciences Research Council Collaborative Awards in Science and Engineering PhD studentship. This work was supported by National Institutes of Health Grants GM087507 and GM102336 (to T.E.D.)

Combining metagenomics with metaproteomics and stable isotope probing reveals metabolic pathways used by a naturally occurring marine methylotroph

A variety of culture-independent techniques have been developed that can be used in conjunction with culture-dependent physiological and metabolic studies of key microbial organisms, in order to better understand how the activity of natural populations influences and regulates all major biogeochemical cycles. In this study, we combined DNA-stable isotope probing with metagenomics and metaproteomics to characterize an as yet uncultivated marine methylotroph that actively incorporated carbon from 13C-labeled methanol into biomass. By metagenomic sequencing of the heavy DNA, we retrieved virtually the whole genome of this bacterium and determined its metabolic potential. Through protein-stable isotope probing, the RuMP cycle was established as the main carbon assimilation pathway, and the classical methanol dehydrogenase-encoding gene mxaF, as well as three out of four identified xoxF homologues were found to be expressed. This proof-of-concept study is the first in which theculture-independent techniques of DNA- and protein-stable isotope probing have been used to characterize the metabolism of a naturally-ocurring Methylophaga-like bacterium in the marine environment (i.e. M. thiooxydans L4) and thus provides a powerful approach to access the genome and proteome of uncultivated microbes involved in key processes in the environment

Comparative Genomics and Mutational Analysis Reveals a Novel XoxF-Utilizing Methylotroph in the Roseobacter Group Isolated From the Marine Environment

The Roseobacter group comprises a significant group of marine bacteria which are involved in global carbon and sulfur cycles. Some members are methylotrophs, using one-carbon compounds as a carbon and energy source. It has recently been shown that methylotrophs generally require a rare earth element when using the methanol dehydrogenase enzyme XoxF for growth on methanol. Addition of lanthanum to methanol enrichments of coastal seawater facilitated the isolation of a novel methylotroph in the Roseobacter group: Marinibacterium anthonyi strain La 6. Mutation of xoxF5 revealed the essential nature of this gene during growth on methanol and ethanol. Physiological characterization demonstrated the metabolic versatility of this strain. Genome sequencing revealed that strain La 6 has the largest genome of all Roseobacter group members sequenced to date, at 7.18 Mbp. Multilocus sequence analysis (MLSA) showed that whilst it displays the highest core gene sequence similarity with subgroup 1 of the Roseobacter group, it shares very little of its pangenome, suggesting unique genetic adaptations. This research revealed that the addition of lanthanides to isolation procedures was key to cultivating novel XoxF-utilizing methylotrophs from the marine environment, whilst genome sequencing and MLSA provided insights into their potential genetic adaptations and relationship to the wider community

Communal metabolism by Methylococcaceae and Methylophilaceae is driving rapid aerobic methane oxidation in sediments of a shallow seep near Elba, Italy

Release of abiotic methane from marine seeps into the atmosphere is a major source of this potent greenhouse gas. Methanotrophic microorganisms in methane seeps use methane as carbon and energy source, thus significantly mitigating global methane emissions. Here we investigated microbial methane oxidation at the sediment-water interface of a shallow marine methane seep. Metagenomics and metaproteomics, combined with 13C-methane stable isotope probing, demonstrated that various members of the gammaproteobacterial family Methylococcaceae were the key players for methane oxidation, catalyzing the first reaction step to methanol. We observed a transfer of carbon to methanol-oxidizing methylotrophs of the betaproteobacterial family Methylophilaceae, suggesting an interaction between methanotrophic and methylotrophic microorganisms that allowed for rapid methane oxidation. From our microcosms, we estimated methane oxidation rates of up to 871 nmol of methane per gram sediment and day. This implies that more than 50% of methane at the seep is removed by microbial oxidation at the sediment-water interface, based on previously reported in situ methane fluxes. The organic carbon produced was further assimilated by different heterotrophic microbes, demonstrating that the methane-oxidizing community supported a complex trophic network. Our results provide valuable eco-physiological insights into this specialized microbial community performing an ecosystem function of global relevance

Causes and Consequences of A Glutamine Induced Normoxic HIF1 Activity for the Tumor Metabolism

The transcription factor hypoxia-inducible factor 1 (HIF1) is the crucial regulator of genes that are involved in metabolism under hypoxic conditions, but information regarding the transcriptional activity of HIF1 in normoxic metabolism is limited. Different tumor cells were treated under normoxic and hypoxic conditions with various drugs that affect cellular metabolism. HIF1ff was silenced by siRNA in normoxic/hypoxic tumor cells, before RNA sequencing and bioinformatics analyses were performed while using the breast cancer cell line MDA-MB-231 as a model. Differentially expressed genes were further analyzed and validated by qPCR, while the activity of the metabolites was determined by enzyme assays. Under normoxic conditions, HIF1 activity was significantly increased by (i) glutamine metabolism, which was associated with the release of ammonium, and it was decreased by (ii) acetylation via acetyl CoA synthetase (ACSS2) or ATP citrate lyase (ACLY), respectively, and (iii) the presence of L-ascorbic acid, citrate, or acetyl-CoA. Interestingly, acetylsalicylic acid, ibuprofen, L-ascorbic acid, and citrate each significantly destabilized HIF1ff only under normoxia. The results from the deep sequence analyses indicated that, in HIF1-siRNA silenced MDA-MB-231 cells, 231 genes under normoxia and 1384 genes under hypoxia were transcriptionally significant deregulated in a HIF1-dependent manner. Focusing on glycolysis genes, it was confirmed that HIF1 significantly regulated six normoxic and 16 hypoxic glycolysis-associated gene transcripts. However, the results from the targeted metabolome analyses revealed that HIF1 activity affected neither the consumption of glucose nor the release of ammonium or lactate; however, it significantly inhibited the release of the amino acid alanine. This study comprehensively investigated, for the first time, how normoxic HIF1 is stabilized, and it analyzed the possible function of normoxic HIF1 in the transcriptome and metabolic processes of tumor cells in a breast cancer cell model. Furthermore, these data imply that HIF1 compensates for the metabolic outcomes of glutaminolysis and, subsequently, theWarburg effect might be a direct consequence of the altered amino acid metabolism in tumor cells

Empfehlungen zur Zukunft des wissenschaftlichen Publikationssystems

Ash M, Carrier M, Dössel O, et al. Empfehlungen zur Zukunft des wissenschaftlichen Publikationssystems. Berlin: Berlin-Brandenburgische Akademie der Wissenschaften; 2015