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A postdoc explains how being medicated for bipolar changed her life and the way she conducts research.

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The release of Ca2+ ions from intracellular stores plays a crucial role in many cellular processes, acting as a secondary messenger in various cell types, including cardiomyocytes, smooth muscle cells, hepatocytes, and many others. Detecting and classifying associated local Ca2+ release events is particularly important, as these events provide insight into the mechanisms, interplay, and interdependencies of local Ca2+release events underlying global intracellular Ca2+signaling. However, time-consuming and labor-intensive procedures often complicate analysis, especially with low signal-to-noise ratio imaging data. Here, we present an innovative deep learning-based approach for automatically detecting and classifying local Ca2+ release events. This approach is exemplified with rapid full-frame confocal imaging data recorded in isolated cardiomyocytes. To demonstrate the robustness and accuracy of our method, we first use conventional evaluation methods by comparing the intersection between manual annotations and the segmentation of Ca2+ release events provided by the deep learning method, as well as the annotated and recognized instances of individual events. In addition to these methods, we compare the performance of the proposed model with the annotation of six experts in the field. Our model can recognize more than 75 % of the annotated Ca2+ release events and correctly classify more than 75 %. A key result was that there were no significant differences between the annotations produced by human experts and the result of the proposed deep learning model. We conclude that the proposed approach is a robust and time-saving alternative to conventional full-frame confocal imaging analysis of local intracellular Ca2+ events.

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From diagnosis and disclosure to leading change, two neurodivergent researchers recount their experiences setting up peer support networks at their universities.

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An AuDHD researcher recounts the highs and lows of relocating from the United States to Germany for his postdoc.

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A fraught exchange on social media leads a PhD student to reconsider how she conducts research on neuroinclusivity while being neurodivergent herself.

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After hitting rock bottom a few months into a prestigious fellowship, a postdoc recounts how they found their way to ADHD medication, therapy, and better mental health.

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In heart muscle, the physiological function of IP3-induced Ca2+ release (IP3ICR) from the sarcoplasmic reticulum (SR) is still the subject of intense study. A role of IP3ICR may reside in modulating Ca2+-dependent cardiac arrhythmogenicity. Here we observe the propensity of spontaneous intracellular Ca2+ waves (SCaW) driven by Ca2+-induced Ca2+ release (CICR) in ventricular myocytes as a correlate of arrhythmogenicity on the organ level. We observe a dual mode of action of IP3ICR on SCaW generation in an IP3R overexpression model. This model shows a mild cardiac phenotype and mimics pathophysiological conditions of increased IP3R activity. In this model, IP3ICR was able to increase or decrease the occurrence of SCaW depending on global Ca2+ activity. This IP3ICR-based regulatory mechanism can operate in two "modes" depending on the intracellular CICR activity and efficiency (e.g. SCaW and/or local Ryanodine Receptor (RyR) Ca2+ release events, respectively): a) in a mode that augments the CICR mechanism at the cellular level, resulting in improved excitation-contraction coupling (ECC) and ultimately better contraction of the myocardium, and b) in a protective mode in which the CICR activity is curtailed to prevent the occurrence of Ca2+ waves at the cellular level and thus reduce the probability of arrhythmogenicity at the organ level.

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When attempts to capitalize on her undiagnosed ADHD traits led to repeated cycles of overwork and burnout, a postdoc re-evaluated how she faces the daily challenges of being a neurodivergent scientist.

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A PhD student recounts what she has learned from managing her ADHD between the office and the rainforest.

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A research technician describes how receiving an ADHD diagnosis allowed her to re-examine how she sees herself and her work.

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An assistant professor and group leader explains how being diagnosed with autism in her early 40s changed her approach to being a scientist.

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Aging is a major risk factor for cardiovascular diseases. Our previous studies demonstrate that aging impairs the caveolar T-type CaV 3.2-RyR axis for extracellular Ca2+ influx to trigger Ca2+ sparks in vascular smooth muscle cells (VSMCs). We hypothesize that the administration of senolytics, which can selectively clear senescent cells, could preserve the caveolar CaV 3.2-RyR axis in aging VSMCs. In this study, 10-month-old mice were administered the senolytics cocktail consisting of dasatinib (5 mg/kg) and quercetin (50 mg/kg) or vehicle bi-weekly for 4 months. Using VSMCs from mouse mesenteric arteries, we found that Ca2+ sparks were diminished after caveolae disruption by methyl-ß-cyclodextrin (10 mM) in cells from D + Q treated but not vehicle-treated 14-month-old mice. D + Q treatment promoted the expression of CaV 3.2 in 14-month-old mesenteric arteries. Structural analysis using electron tomography and immunofluorescence staining revealed the remodeling of caveolae and co-localization of CaV 3.2-Cav-1 in D + Q treatment aged mesenteric arteries. In keeping with theoretical observations, Cav 3.2 channel inhibition by Ni2+ (50 µM) suppressed Ca2+ in VSMCs from the D + Q group, with no effect observed in vehicle-treated arteries. Our study provides evidence that age-related caveolar CaV 3.2-RyR axis malfunction can be alleviated by pharmaceutical intervention targeting cellular senescence. Our findings support the potential of senolytics for ameliorating age-associated cardiovascular disease.

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Studying abroad helped a Panamanian student to accept who he is, but it meant him letting go of his dream.

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Between honoring her immigrant family and making her children proud, a first-generation PhD student fights for her place in academia.

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Creating a writing club allowed a Brazilian PhD student to confront her fears, improve her English and, ultimately, change the way she sees research.

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Calcium (Ca2+) sparks are the elementary events of excitation-contraction coupling, yet they are not explicitly represented in human ventricular myocyte models. A stochastic ventricular cardiomyocyte human model that adapts to intracellular Ca2+ ([Ca2+]i) dynamics, spark regulation, and frequency-dependent changes in the form of locally controlled Ca2+ release was developed. The 20,000 CRUs in this model are composed of 9 individual LCCs and 49 RyRs that function as couplons. The simulated action potential duration at 1 Hz steady-state pacing is ~0.280 s similar to human ventricular cell recordings. Rate-dependence experiments reveal that APD shortening mechanisms are largely contributed by the L-type calcium channel inactivation, RyR open fraction, and [Ca2+]myo concentrations. The dynamic slow-rapid-slow pacing protocol shows that RyR open probability during high pacing frequency (2.5 Hz) switches to an adapted "nonconducting" form of Ca2+-dependent transition state. The predicted force was also observed to be increased in high pacing, but the SR Ca2+ fractional release was lower due to the smaller difference between diastolic and systolic [Ca2+]SR. Restitution analysis through the S1S2 protocol and increased LCC Ca2+-dependent activation rate show that the duration of LCC opening helps modulate its effects on the APD restitution at different diastolic intervals. Ultimately, a longer duration of calcium sparks was observed in relation to the SR Ca2+ loading at high pacing rates. Overall, this study demonstrates the spontaneous Ca2+ release events and ion channel responses throughout various stimuli.

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One of the primary causes of fires at construction sites is welding sparks. Fire detection systems utilizing computer vision technology offer a unique opportunity to monitor fires in construction sites. However, little effort has been made to date in regard to real-time tracking of small sparks that can lead to major fires at construction sites. In this study, a novel method is proposed to detect welding sparks in real-time contour detection with deep learning parameter tuning. An automatic parameter tuning algorithm employing a convolutional neural network was developed to identify the optimum hue saturation value. Additional filtering methods regarding the non-welding zone and a contour area-based filter were also newly developed to enhance the accuracy of welding spark prediction. The method was evaluated using 230 welding spark images and 104 videos. The results obtained from the welding images indicate that the suggested model for detecting welding sparks achieves a precision of 74.45% and a recall of 63.50% when noise images, such as flashing and reflection light, were removed from the dataset. Furthermore, our findings demonstrate that the proposed model is effective in capturing the number of welding sparks in the video dataset, with a 95.2% accuracy in detecting the moment when the number of welding sparks reaches its peak. These results highlight the potential of automated welding spark detection to enhance fire surveillance at construction sites.

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Cardiac excitation-contraction coupling (ECC) depends on Ca2+ release from intracellular stores via ryanodine receptors (RyRs) triggered by L-type Ca2+ channels (LCCs). Uncertain numbers of RyRs and LCCs form 'couplons' whose activation produces Ca2+ sparks, which summate to form a cell-wide Ca2+ transient that switches on contraction. Voltage (Vm) changes during the action potential (AP) and stochasticity in channel gating should create variability in Ca2+ spark timing, but Ca2+ transient wavefronts have remarkable uniformity. To examine how this is achieved, we measured the Vm-dependence of evoked Ca2+ spark probability (Pspark) and latency over a wide voltage range in rat ventricular cells. With depolarising steps, Ca2+ spark latency showed a U-shaped Vm-dependence, while repolarising steps from 50 mV produced Ca2+ spark latencies that increased monotonically with Vm. A computer model based on reported channel gating and geometry reproduced our experimental data and revealed a likely RyR:LCC stoichiometry of âˆ¼ 5:1 for the Ca2+ spark initiating complex (IC). Using the experimental AP waveform, the model revealed a high coupling fidelity (Pcpl âˆ¼ 0.5) between each LCC opening and IC activation. The presence of âˆ¼ 4 ICs per couplon reduced Ca2+ spark latency and increased Pspark to match experimental data. Variability in AP release timing is less than that seen with voltage steps because the AP overshoot and later repolarization decrease Pspark due to effects on LCC flux and LCC deactivation respectively. This work provides a framework for explaining the Vm- and time-dependence of Pspark, and indicates how ion channel dispersion in disease can contribute to dyssynchrony in Ca2+ release.

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Facing the harsh realities of life as a refugee in Jordan and the United States, an ambitious young man holds to a conviction: that he will, one day, get a PhD.

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Intracellular Ca2+ signals are key for the regulation of cellular processes ranging from myocyte contraction, hormonal secretion, neural transmission, cellular metabolism, transcriptional regulation, and cell proliferation. Measurement of cellular Ca2+ is routinely performed using fluorescence microscopy with biological indicators. Analysis of deterministic signals is reasonably straightforward as relevant data can be discriminated based on the timing of cellular responses. However, analysis of stochastic, slower oscillatory events, as well as rapid subcellular Ca2+ responses, takes considerable time and effort which often includes visual analysis by trained investigators, especially when studying signals arising from cells embedded in complex tissues. The purpose of the current study was to determine if full-frame time-series and line-scan image analysis workflow of Fluo-4 generated Ca2+ fluorescence data from vascular myocytes could be automated without introducing errors. This evaluation was addressed by re-analyzing a published "gold standard" full-frame time-series dataset through visual analysis of Ca2+ signals from recordings made in pulmonary arterial myocytes of en face arterial preparations. We applied a combination of data driven and statistical approaches with comparisons to our published data to assess the fidelity of the various approaches. Regions of interest with Ca2+ oscillations were detected automatically post hoc using the LCPro plug-in for ImageJ. Oscillatory signals were separated based on event durations between 4 and 40 s. These data were filtered based on cutoffs obtained from multiple methods and compared to the published manually curated "gold standard" dataset. Subcellular focal and rapid Ca2+ "spark" events from line-scan recordings were examined using SparkLab 5.8, which is a custom automated detection and analysis program. After filtering, the number of true positives, false positives, and false negatives were calculated through comparisons to visually derived "gold standard" datasets. Positive predictive value, sensitivity, and false discovery rates were calculated. There were very few significant differences between the automated and manually curated results with respect to quality of the oscillatory and Ca2+ spark events, and there were no systematic biases in the data curation or filtering techniques. The lack of statistical difference in event quality between manual data curation and statistically derived critical cutoff techniques leads us to believe that automated analysis techniques can be reliably used to analyze spatial and temporal aspects to Ca2+ imaging data, which will improve experiment workflow.

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