Biology subjects

Recoder, N.

Publications and source records attributed to Recoder, N..

3 recordsLinked to original sources

bioRxiv2024

Intratumoral CXCL12 Gradients Contextualize Tumor Cell Invasion, Migration and Immune Suppression in Breast Cancer

Although the CXCL12/CXCR4 pathway has been prior investigated for its prometastatic and immuno- suppressive roles in the tumor microenvironment, evidence on the spatiotemporal regulation of these hallmarks has been lacking. Here, we demonstrate that CXCL12 forms a gradient specifically around cancer cell intravasation doorways, also known as Tumor Microenvironment of Metastasis (TMEM) doorways, thus facilitating the chemotactic translocation of prometastatic tumor cells expressing CXCR4 toward the perivascular TMEM doorways for subsequent entry into peripheral circulation. Fur- thermore, we demonstrate that the CXCL12-rich micro-environment around TMEM doorways may cre- ate immunosuppressive niches, whereby CD8+ T cells, despite being attracted to these regions, often exhibit reduced effector functions, limiting their efficacy. While the CXCL12/CXCR4 pathway can mini- mally influence the overall composition of immune cell populations, it biases the distribution of CD8+ T cells away from TMEM doorways, justifying its prior-established role as immunosuppressive factor for CD8+ T cells. Our research suggests that the complex interactions between CXCL12 and the various tumor and immune cell types contributes not only to the completion of the initial steps of the metastatic cascade, but also offers an immunological "sanctuary" to prometastatic tumor cells homed around TMEM doorways. Overall, our study enhances our current understanding on the mechanisms, via which CXCL12 orchestrates tumor cell behavior and immune dynamics, potentially guiding future thera- peutic strategies to combat breast cancer metastasis and improve anti-tumor immunity.

cancer biology↗

bioRxiv2024

Heart rate variability impairment during sleep in Veterans with REM sleep behavior disorder, traumatic brain injury, and posttraumatic stress disorder: An early potential window into autonomic dysfunction?

Individuals with comorbid REM sleep behavior disorder (RBD) and neurotrauma (defined by traumatic brain injury and post-traumatic stress disorder) have an earlier age of RBD symptom onset, increased RBD-related symptom severity and more neurological features indicative of prodromal synucleinopathy compared to RBD only. An early sign of neurodegenerative condition is autonomic dysfunction, which we sought to evaluate by examining heart rate variability during sleep. Participants with overnight polysomnography were recruited from the VA Portland Health Care System. Veterans without neurotrauma or RBD (controls; n=19), with RBD only (RBD, n=14), and with RBD and neurotrauma (RBD+NT, n=19) were evaluated. Eligible 5-minute NREM and REM epochs without apneas/hypopneas, microarousals, and ectopic beats were analyzed for frequency and time domain (e.g. low frequency power, LF; high frequency power, HF; root mean square of successive RR intervals, RMSSD; % of RR intervals that vary [≥]50 ms, pNN50) heart rate variability outcomes. Heart rate did not significantly differ between groups in any sleep stage. Time domain and frequency domain variables (e.g., LF power, HF power, RMSSD, and pNN50) were significantly reduced in the RBD and RBD+NT groups compared to controls and RBD only during NREM sleep. There were no group differences detected during REM sleep. These data suggest significant reductions in heart rate variability during NREM sleep in RBD+NT participants, suggesting greater autonomic dysfunction compared to controls or RBD alone. Heart rate variability during sleep may be an early, promising biomarker, yielding mechanistic insight for diagnosis and prognosis of early neurodegeneration in this vulnerable population. STATEMENT OF SIGNIFICANCEComorbid REM sleep behavior disorder (RBD) and neurotrauma (NT, traumatic brain injury + post-traumatic stress disorder; RBD+NT) is associated with increased neurodegenerative symptom burden and worsened health. Sleep and autonomic function are integrally and bidirectionally related to neurodegenerative processes. In the current study, we sought to determine if early signs of autonomic dysfunction, measured via heart rate variability (HRV), were present during sleep in comorbid RBD+NT compared to RBD only and controls. Our data show reduced time and frequency domain HRV during NREM sleep in RBD+NT Veterans compared to RBD only and controls. These data contribute evidence that participants with RBD and comorbid NT demonstrate significantly worse autonomic dysfunction compared to age/sex matched participants with RBD alone.

physiology↗

bioRxiv2020

CardioPy: An open-source heart rate variabilitytoolkit for single-lead EKG

Background and ObjectiveHeart rate variability (HRV) is a promising clinical marker of health and disease. Although HRV methodology is relatively straightforward, accurate detection of R-peaks remains a significant methodological challenge; this is especially true for single-lead EKG signals, which are routinely collected alongside EEG monitoring and for which few software options exist. Most developed algorithms with favorable R-peak detection profiles require significant mathematical and computational proficiency for implementation, providing a significant barrier for clinical research. Our objective was to address these challenges by developing a simple, free, and open-source software package for HRV analysis of single-lead EKG signals. MethodsCardioPy was developed in python and optimized for short-term (5-minute) single-lead EKG recordings. CardioPys R-peak detection trades full automation and algorithmic complexity for an adaptive thresholding mechanism, manual artifact removal and parameter adjustment. Standard time and frequency domain analyses are included, such that CardioPy may be used as a stand-alone HRV analysis package. An example use-case of HRV across wakefulness and sleep is presented and results validated against the widely used Kubios HRV software. ResultsHRV analyses were conducted in 66 EKG segments collected from five healthy individuals. Parameter optimization was conducted or each segment, requiring ~1-3 minutes of manual inspection time. With optimization, CardioPys R-peak detection algorithm achieved a mean sensitivity of 100.0% (SD 0.05%) and positive predictive value of 99.8% (SD 0.20%). HRV results closely matched those produced by Kubios HRV, both by eye and by quantitative comparison; CardioPy power spectra explained an average of 99.7% (SD 0.50%) of the variance present in Kubios spectra. HRV analyses showed significant group differences between brain states; SDNN, low frequency power, and low frequency-to-high frequency ratio were reduced in slow wave sleep compared to wakefulness. ConclusionsCardioPy provides an accessible and transparent tool for HRV analyses. Manual parameter optimization and artifact removal allow granular control over data quality and a highly reproducible analytic pipeline, despite additional time requirements. Future versions are slated to include automatic parameter optimization and a graphical user interface, further reducing analysis time and improving accessibility.

physiology↗