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Biology subjects

Haliyo, S.

Publications and source records attributed to Haliyo, S..

2 recordsLinked to original sources

Cardiolipin increases the peak of reversible traveling H+ fronts at the membrane surface

Cardiolipin (CL) is a phospholipid found in the inner mitochondrial membrane (IMM) where it increases the efficiency of ATP regeneration. We have investigated the hypothesis that this increase may result in part from CL concentrating H+ at the IMM surface through electrostatic interactions as the CL polar head is a dianion at physiological pH. To this aim, we compared the concentrations and movements of H+ at the surface of giant planar phosphatidylcholine (PC) membranes and 20% CL enriched PC membranes by recording their surface pH with the membrane-grafted pH probe fluorescein DHPE. CL enrichment of the membranes increased their surface H+ activity by a ~4 factor. Moreover, we observed non-gaussian spatial H+ concentration profiles with distance from a point H+ source with both PC and CL membranes suggesting that both lipids also induce interactions between probe molecules. A whole bath pH variation revealed that these interactions allow the traveling of reversible acidification fronts with constant speed over the membrane between high and low pH states. A reaction-diffusion model of these observations suggests that membranes support these fronts through a mechanism of autocatalytic (de)protonation of the membrane surface. In mitochondria, these fronts would result in transitions between high and low pH states, the low one having a larger H+ concentration in CL-enriched regions of the IMM. Such an increase at the inner leaflet of the IMM may increase efficiency of the respiratory chain whereas the increase at the outer leaflet may boost the ATP synthase rate.

biophysics↗

Rotiferometer: an automated system for quantification of rotifer cultures

Accurate quantification and continuous monitoring of Brachionus plicatilis L. rotifer cultures are essential for aquaculture and aquatic animal research laboratories. Manual counting methods are labor-intensive, error-prone, and inefficient for large-scale operations, necessitating automated solutions. This study presents the Rotiferometer, an automated and cost-effective system that integrates mechanical design, deep learning, and automation for precise rotifer detection, classification and counting. Using a YOLOv8 model, the system achieves a mean average precision (mAP@0.5) of 94.7% in distinguishing gravid and non-gravid rotifers. It proceeds by scanning a 1 mL Sedgewick Rafter slide under 3 minutes, ensuring rapid and accurate enumeration. A strong correlation was observed between manual and Rotiferometer counts, (with R2 values of 0.9729 and 0.9868 for gravid and non-gravid rotifers, respectively), confirming the system s accuracy. Additionally, the analysis of operator variability using the Rotiferometer delivered consistent results regardless of the user, minimizing the need for specialized expertise. Finally, a 45-day monitoring experiment with the Rotiferometer effectively tracked rotifer population changes, identifying key phases of growth, decline, and recovery. These results highlight the device s potential to enhance rotifer culture management by providing real-time, reliable, and automated monitoring, thereby optimizing aquaculture productivity and research efficiency.

bioengineering↗