Biology subjects

Necula, D.

Publications and source records attributed to Necula, D..

3 recordsLinked to original sources

bioRxiv2023

Mapping general anesthesia states based on electro-encephalogram transition phases

Cortical electro-encephalography (EEG) has become the clinical reference for monitoring unconsciousness during general anesthesia. The current EEG-based monitors classify general anesthesia states simply as underdosed, adequate, or overdosed, with no transition phases among these states, and therefore no predictive power. To address the issue of transition phases, we analyzed EEG signal of isoflurane-induced general anesthesia in mice. We adopted a data-driven approach and utilized signal processing to track{theta} - and{delta} - band dynamics as well as iso-electric suppressions. By combining this approach with machine learning, we developed a fully-automated algorithm. We found that the dampening of the{delta} -band occurred several minutes before significant iso-electric suppression episodes. Additionally, we observed a distinct{gamma} -frequency oscillation that persisted for several minutes during the recovery phase following isoflurane-induced overdose. Finally, we constructed a map summarizing multiple states and their transitions which can be utilized to predict and prevent overdose during general anesthesia. The transition phases we identified and algorithm we developed may allow clinicians to prevent inadequate anesthesia, and thus individually tailor anesthetic regimens. 1 Significance statementIn human patients, overdosing during general anesthesia can lead to cognitive impairment. Cortical electro-encephalograms are used to measure the depth of anesthesia. They allow for correction, but not prevention, of overdose. However, data-driven approaches open new possibilities to predict the depth of anesthesia. We established an electro-encephalogram signalprocessing pipeline, and constructed a predictive map representing an ensemble of gradual sedation states during general anesthesia in mice. In particular, we identified key electroencephalogram patterns which anticipate signs of overdose several minutes before they occur. Our results bring a novel paradigm to the medical community, allowing for the development of individually tailored and predictive anesthetic regimens.

neuroscience↗

bioRxiv2021

CCR5 closes the temporal window for memory linking

Real world memories are formed in a particular context and are not acquired or recalled in isolation 1-5. Time is a key variable in the organization of memories, since events experienced close in time are more likely to be meaningfully associated, while those experienced with a longer interval are not1-4. How does the brain segregate events that are temporally distinct? Here, we report that a delayed (12-24h) increase in the expression of the C-C chemokine receptor type 5 (CCR5), an immune receptor well known as a co-receptor for HIV infection6,7, following the formation of a contextual memory, determines the duration of the temporal window for associating or linking that memory with subsequent memories. This delayed CCR5 expression in mouse dorsal CA1 (dCA1) neurons results in a decrease in neuronal excitability, which in turn negatively regulates neuronal memory allocation, thus reducing the overlap between dCA1 memory ensembles. Lowering this overlap affects the ability of one memory to trigger the recall of the other, thus closing the temporal window for memory linking. Remarkably, our findings also show that an age-related increase in CCL5/CCR5 expression leads to impairments in memory linking in aged mice, which could be reversed with a CCR5 knockout and an FDA approved drug that inhibits this receptor, a result with significant clinical implications. All together the findings reported here provide the first insights into the molecular and cellular mechanisms that shape the temporal window for memory linking.

neuroscience↗

bioRxiv2021

Proteomic landscape of multi-layered breast cancer internal tumor heterogeneity

Despite extensive research, internal tumor heterogeneity presents enormous challenges to achieve complete therapeutic responses. Changes in protein expression are central determinants of cancer phenotypes that reflect potential therapeutic targets. However, previous proteomic studies did not address internal heterogeneity, therefore, masked the necessary spatial resolution to achieve a comprehensive understanding of cancer complexity. Here we present the first large-scale multi-focal breast cancer proteomic study of 330 tumor regions which associated cancer cell function, pathological parameters, and spatial localization of each tumor region. We found marked internal proteomic heterogeneity even within tumors presenting homogeneous receptor expression. Additionally, analysis of the internal heterogeneity, based on coexisting receptor expression or histological patterns in single tumors, showed significant functional differences between homogeneous and heterogeneous tumors related to cancer metabolism, immunogenicity, and proliferation. We anticipate that this study will serve as a starting point towards the development of improved cancer therapy and diagnostics.

cancer biology↗