Tuesday, January 21, 2020

Neurologists Identify a Genetic ‘Switch’ That Could Improve Memory

A neural circuit mechanism involved in preserving the specificity of memories has been identified by investigators from the Massachusetts General Hospital (MGH) Center for Regenerative Medicine and the Harvard Stem Cell Institute (HSCI).

They also identified a genetic “switch” that can slow down memory generalization — the loss of specific details over time that occurs in both age-related memory impairment and in post-traumatic stress disorder (PTSD), in which emotions originally produced by traumatic experiences are elicited in response to innocuous cues that have little resemblance to the traumatic memory.

“The circuit mechanism we identified in mice allows us to preserve the precision or the details of memories over the passage of time in adult as well as aged animals,” says Amar Sahay of the MGH Center for Regenerative Medicine and HSCI, corresponding author of a paper appearing in Nature Medicine. “These findings have implications for the generalization of traumatic memories in PTSD and for memory imprecision in aging.”

Memories are generated in the seahorse-shaped brain structure called the hippocampus and stored in the prefrontal cortex at the front of the brain. Memory formation involves cells in a portion of the hippocampus called the dentate gyrus, and memories are thought to be conveyed to the prefrontal cortex via the CA subregions of the hippocampus, specifically subregions CA3 and CA1. The hippocampus also is believed to play a continuing role in the stabilization of memories in the cortex — maintaining the precise details that keep one memory from being confused with another and preventing issues ranging from not being able to remember last week’s dinner selections to age-related memory loss.

Hyperactivity of this hippocampal circuitry has been observed in aged animals — rodents, non-human primates, and humans — and alterations in hippocampal structure are seen in patients with PTSD. The current study was designed to investigate the hypothesis that inhibitory signals passing from dentate gyrus cells (DGCs) to the CA3 subregion help constrain hyperactivity and maintain the stability and precision of memories over time.

A key finding by Sahay’s team was identification of a protein called abLIM3 — highly expressed in DGCs but absent in the CA field of mouse brains. The protein acts as a molecular brake on the inhibitory signals DGCs exert onto the CA3 subregion. Experimental manipulation of abLIM3 levels in DGCs in adult mice revealed that decreasing abLIM3 levels increased the delivery of inhibitory signals to CA3 neurons. A series of experiments with mouse models showed that manipulation of abLIM3 levels within DGCs could slow down the process of memory generalization.

Using a classical behavioral-conditioning protocol, the investigators first trained the animals to expect an unpleasant sensation, a mild but not painful foot shock, in a particular context, such as being placed into a box with dark walls. Typically, when animals are placed in the same context, they will “freeze” in expectation of the shock but will not react to a context not associated with the shock, such as a box with light walls. But after two weeks, the memory will generalize and the animals will “freeze” when placed in any context, even one with little resemblance to that in which they received the foot shock.

In contrast, decreasing abLIM3 levels within DGCs maintained the specificity of the memory over time so that, even two weeks later, the mice would only freeze when placed into the foot-shock-associated context. The investigators also found that decreasing abLIM3 levels in aged mice reversed age-related alterations in DGC-CA3 circuitry and improved memory precision. A recent study by another group found significantly increased abLIM3 levels in the circulation of aged humans who are beginning to show signs of memory impairment.

“Our ability to improve memory precision in both adult and aged mice by essentially ‘flipping a genetic switch’ suggests that targeting abLIM3 expression in DGCs may lead to similar improvement in aged humans, a strategy we are actively pursuing,” says Sahay, who is an associate professor of psychiatry at Harvard Medical School and principal faculty of the Harvard Stem Cell Institute. “Since overgeneralization of traumatic memories is a hallmark of PTSD, we are also keen to assess abLIM3 levels in patients with PTSD and investigate whether reducing abLIM3 expression could prevent the activation of traumatic memories.”


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Monday, November 25, 2019

Artificial Intelligence to determine whether immunotherapy is working or not

Researchers working on Artificial Intelligence has hit another milestone as they have found a way to predict if a lung cancer patients can be benefited from expensive immunotherapy.

And, once again, they’re doing it by teaching a computer to find previously unseen changes in patterns in CT scans taken when the lung cancer is 1st diagnosed compared to scans taken after the first 2-3 cycles of immunotherapy treatment.

Madabhushi said the recent work by his lab would help oncologists know which patients would actually benefit from the therapy, and who would not.

“Even though immunotherapy has changed the entire ecosystem of cancer, it also remains extremely expensive — about $200,000 per patient, per year,” Madabhushi said.

“That’s part of the financial toxicity that comes along with cancer and results in about 42% of all newly diagnosed cancer patients losing their life savings within a year of diagnosis,” added Madabhushi.

Having a tool based on the research being done now by his lab would go a long way toward “doing a better job of matching up which patients will respond to immunotherapy instead of throwing $800,000 down the drain,” he added, referencing the four patients out of five who will not benefit, multiplied by annual estimated cost.
 Khorrami, a graduate student working at the CCIPD, said one of the more significant advances in the research was the ability of the computer program to note the changes in texture, volume and shape of a given lesion, not just its size.

“This is important because when a doctor decides based on CT images alone whether a patient has responded to therapy, it is often based on the size of the lesion,” Khorrami said. “We have found that textural change is a better predictor of whether the therapy is working.

“Sometimes, for example, the nodule may appear larger after therapy because of another reason, say a broken vessel inside the tumour — but the therapy is actually working. Now, we have a way of knowing that,” added Khorrami.

Prasanna, a postdoctoral research associate in Madabhushi’s lab, said the study also showed that the results were consistent across scans of patients treated at two different sites and with three different types of immunotherapy agents.

Prasanna added the initial study used CT scans from 50 patients to train the computer and create a mathematical algorithm to identify the changes in the lesion.

Additionally, Madabhushi said, researchers were able to show that the patterns on the CT scans which were most associated with a positive response to treatment and with overall patient survival were also later found to be closely associated with the arrangement of immune cells on the original diagnostic biopsies of those patients.

This suggests that those CT scans actually appear to capture the immune response elicited by the tumours against the invasion of cancer — and that the ones with the strongest immune response were showing the most significant textural change and most importantly, would best respond to the immunotherapy, he said.

this is only for your information, kindly take the advice of your doctor for medicines, exercises and so on.     
https://gscrochetdesigns.blogspot.com. one can see my crochet creations  
https://gseasyrecipes.blogspot.com. feel free to view for easy, simple and healthy recipes    
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