Nocturnal peripheral vasoconstriction predicts the frequency of severe acute pain episodes in children with sickle cell disease.

The basic model of SCD physiology states that vaso-occlusion occurs when hemoglobin S-containing red blood cells (RBC) undergo sickling before they escape the capillary into a larger vessel. We have shown that mental stress, pain and cold, and events reported by patients to trigger SCD vaso-occlusive crisis (VOC), cause rapid and significant decrease in blood flow, reducing the likelihood that RBC could transit the microvasculature before sickling occurs. However, the critical link between decrease in microvascular blood flow and the incidence of future sickle VOC has never been established experimentally in humans. Using data from centrally adjudicated, overnight polysomnograms (PSG), previously collected in a prospective multi-center cohort sleep study, we analyzed the beat-to-beat amplitudes of vasoconstriction reported by the fingertip photoplethysmogram in 212 children and adolescents with SCD and developed an algorithm that detects vasoconstriction events and quantifies the magnitude (Mvasoc ), duration, and frequency of vasoconstriction that reflect the individual's inherent peripheral vasoreactivity. The propensity to vasoconstrict, quantified by median Mvasoc , predicted the incidence rate of post-PSG severe acute vaso-occlusive pain events (P = .006) after accounting for age and hemoglobin. Indices of sleep-disordered breathing contributed to median Mvasoc but did not predict future pain rate. Median Mvasoc was not associated with vaso-occlusive pain events that occurred prior to each PSG. These results show that SCD individuals with high inherent propensity to vasoconstrict have more frequent severe acute pain events. Our empirical findings are consistent with the fundamental SCD hypothesis that decreased microvascular flow promotes microvascular occlusion.

Feasibility of through-time spiral generalized autocalibrating partial parallel acquisition for low latency accelerated real-time MRI of speech.

PURPOSE: To evaluate the feasibility of through-time spiral generalized autocalibrating partial parallel acquisition (GRAPPA) for low-latency accelerated real-time MRI of speech. METHODS: Through-time spiral GRAPPA (spiral GRAPPA), a fast linear reconstruction method, is applied to spiral (k-t) data acquired from an eight-channel custom upper-airway coil. Fully sampled data were retrospectively down-sampled to evaluate spiral GRAPPA at undersampling factors R = 2 to 6. Pseudo-golden-angle spiral acquisitions were used for prospective studies. Three subjects were imaged while performing a range of speech tasks that involved rapid articulator movements, including fluent speech and beat-boxing. Spiral GRAPPA was compared with view sharing, and a parallel imaging and compressed sensing (PI-CS) method. RESULTS: Spiral GRAPPA captured spatiotemporal dynamics of vocal tract articulators at undersampling factors ≤4. Spiral GRAPPA at 18 ms/frame and 2.4 mm2 /pixel outperformed view sharing in depicting rapidly moving articulators. Spiral GRAPPA and PI-CS provided equivalent temporal fidelity. Reconstruction latency per frame was 14 ms for view sharing and 116 ms for spiral GRAPPA, using a single processor. Spiral GRAPPA kept up with the MRI data rate of 18ms/frame with eight processors. PI-CS required 17 minutes to reconstruct 5 seconds of dynamic data. CONCLUSION: Spiral GRAPPA enabled 4-fold accelerated real-time MRI of speech with a low reconstruction latency. This approach is applicable to wide range of speech RT-MRI experiments that benefit from real-time feedback while visualizing rapid articulator movement. Magn Reson Med 78:2275-2282, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Genetic Insights into Intestinal Microbiota and Risk of Infertility: A Mendelian Randomization Study.

BACKGROUND: The interaction between intestinal microbiota and infertility is less researched. This study was performed to investigate the causal association between gut microbiota and infertility. METHODS: In this two-sample Mendelian randomization (MR) study, genetic variants of intestinal microbiota were obtained from the MiBioGen consortium, which included 18,340 individuals. Inverse variance weighting (IVW), MR-Egger, weighted median, maximum likelihood, MR Robust adjusted profile score, MR Pleiotropy residual sum, and outlier (MR-PRESSO) methods were used to explore the causal links between intestinal microbiota and infertility. The MR-Egger intercept term and the global test from the MR-PRESSO estimator were used to assess the horizontal pleiotropy. The Cochran Q test was applied to evaluate the heterogeneity of instrumental variables (IVs). RESULTS: As indicated by the IVW estimator, significantly protective effects of the Family XIII AD3011 group (OR = 0.87) and Ruminococcaceae NK4A214 group (OR = 0.85) were identified for female fertility, while Betaproteobacteria (OR = 1.18), Burkholderiales (OR = 1.18), Candidatus Soleaferrea (OR = 1.12), and Lentisphaerae (OR = 1.11) showed adverse effects on female fertility. Meanwhile, Bacteroidaceae (OR = 0.57), Bacteroides (OR = 0.57), and Ruminococcaceae NK4A214 group (OR = 0.61) revealed protective effects on male fertility, and a causal association between Anaerotruncus (OR = 1.81) and male infertility was detected. The effect sizes and directions remained consistent in the other five methods except for Candidatus Soleaferrea. No heterogeneity or pleiotropy were identified by Cochran's Q test, MR-Egger, and global test (all p > 0.05). CONCLUSIONS: This two-sample MR study revealed that genetically proxied intestinal microbiota had potentially causal effects on infertility. In all, the Ruminococcaceae NK4A214 group displayed protective effects against both male and female infertility. Further investigations are needed to establish the biological mechanisms linking gut microbiota and infertility.

Cascading effects of hypobaric hypoxia on the testis: insights from a single-cell RNA sequencing analysis.

Most mammals tolerate exposure to hypobaric hypoxia poorly as it may affect multiple regulatory mechanisms and inhibit cell proliferation, promote apoptosis, limit tissue vascularization, and disrupt the acid-base equilibrium. Here, we quantified the functional state of germ cell development and demonstrated the interaction between the germ and somatic cells via single-cell RNA sequencing (scRNA-seq). The present study elucidated the regulatory effects of hypobaric hypoxia exposure on germ cell formation and sperm differentiation by applying enrichment analysis to genomic regions. Hypobaric hypoxia downregulates the genes controlling granule secretion and organic matter biosynthesis, upregulates tektin 1 (TEKT1) and kinesin family member 2C (KIF2C), and downregulates 60S ribosomal protein 11 (RPL11) and cilia- and flagella-associated protein 206 (CFAP206). Our research indicated that prosaposin-G protein-coupled receptor 37 (PSAP-GPR37) ligands mediate the damage to supporting cells caused by hypobaric hypoxic exposure. The present work revealed that hypoxia injures peritubular myoid (PTM) cells and spermatocytes in the S phase. It also showed that elongating spermatids promote maturation toward the G2 phase and increase their functional reserve for sperm-egg binding. The results of this study provide a theoretical basis for future investigations on prophylactic and therapeutic approaches toward protecting the reproductive system against the harmful effects of hypobaric hypoxic exposure.

Identifying elevated risk for future pain crises in sickle-cell disease using photoplethysmogram patterns measured during sleep: A machine learning approach.

Transient increases in peripheral vasoconstriction frequently occur in obstructive sleep apnea and periodic leg movement disorder, both of which are common in sickle cell disease (SCD). These events reduce microvascular blood flow and increase the likelihood of triggering painful vaso-occlusive crises (VOC) that are the hallmark of SCD. We recently reported a significant association between the magnitude of vasoconstriction, inferred from the finger photoplethysmogram (PPG) during sleep, and the frequency of future VOC in 212 children with SCD. In this study, we present an improved predictive model of VOC frequency by employing a two-level stacking machine learning (ML) model that incorporates detailed features extracted from the PPG signals in the same database. The first level contains seven different base ML algorithms predicting each subject's pain category based on the input PPG characteristics and other clinical information, while the second level is a meta model which uses the inputs to the first-level model along with the outputs of the base models to produce the final prediction. Model performance in predicting future VOC was significantly higher than in predicting VOC prior to each sleep study (F1-score of 0.43 vs 0.35, p-value < 0.0001), consistent with our hypothesis of a causal relationship between vasoconstriction and future pain incidence, rather than past pain leading to greater propensity for vasoconstriction. The model also performed much better than our previous conventional statistical model (F1=0.33), as well as all other algorithms that used only the base-models for predicting VOC without the second tier meta model. The modest F1 score of the present predictive model was due in part to the relatively small database with substantial imbalance (176:36) between low-pain and high-pain subjects, as well as other factors not captured by the sleep data alone. This report represents the first attempt ever to use noninvasive finger PPG measurements during sleep and a ML-based approach to predict increased propensity for VOC crises in SCD. The promising results suggest the future possibility of embedding an improved version of this model in a low-cost wearable system to assist clinicians in managing long-term therapy for SCD patients.