Ketomimetic Medium Promotes Metastatic Disposition and Chemoresistance in Breast Cancer Cells through Hypersialylation and Lipid Synthesis.

Although metastasis accounts for the vast majority of cancer-related fatalities, the triggers for the metastatic transformation of breast cancer (BC) cells remain unknown. Recent evidence suggests that a common feature of invasive and resistant cells could be their metabolic state. However, attempts to control metabolic state via nutrient intake, e.g., ketogenic or low carbohydrate diets, have shown inconsistent results with respect to improving chemotherapy efficacy and curbing metastasis. Aiming to decode the molecular mechanisms that alter cell phenotype upon nutrient alteration, we study how a ketomimetic (ketone body-rich, low glucose) medium affects Doxorubicin (DOX) susceptibility and invasive disposition of BC cells. We quantified glycocalyx sialylation and found an inverse correlation with DOX-induced cytotoxicity and DOX internalization. These measurements were coupled with single-cell metabolic imaging, bulk migration studies, and transcriptomic and metabolomic analyses to map the mechanisms involved in ketone body-driven BC cell metabolic maneuvering. Our findings revealed that a ketomimetic medium enhances chemoresistance and invasive disposition of BC cells via two main oncogenic pathways: hypersialylation and lipid accumulation. We propose that the crosstalk between these pathways leads to synthesis of the glycan precursor UDP-GlcNAc, which leads to advancement of a metastatic phenotype in BC cells under ketomimetic conditions.

Andrographolide suppresses the malignancy of pancreatic cancer via alleviating DNMT3B-dependent repression of tumor suppressor gene ZNF382.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer type that urgently requires effective therapeutic strategies. Andrographolide, a labdane diterpenoid compound abundant in Andrographis paniculata, has anticancer effects against various cancer types, but its anticancer activity and mechanism against PDAC remain largely uncharacterized. PURPOSE: This study explores novel drug target(s) and underlying molecular mechanism of andrographolide against PDAC. STUDY DESIGN AND METHODS: The malignant phenotypes of PDAC cells, PANC-1 and MIA PaCa-2 cells, were measured using MTT, clonogenic assays, and Transwell migration assays. A PDAC xenograft animal model was used to evaluate tumor growth in vivo. Western blot, immunofluorescence and immunohistochemistry were used for measuring protein expression. The TCGA database was analyzed to evaluate promoter methylation status, gene expression, and their relationship with patient survival rates. RT-qPCR was used for detecting mRNA expression. Reporter assays were used for detecting signal transduction pathways. Promoter DNA methylation was determined by sodium bisulfite treatment and methylation-specific PCR (MSP). The biological function and role of specific genes involved in drug effects were measured through gene overexpression. RESULTS: Andrographolide treatment suppressed the proliferation and migration of PDAC cells and impaired tumor growth in vivo. Furthermore, andrographolide induced the mRNA and protein expression of zinc finger protein 382 (ZNF382) in PDAC cells. Overexpression of ZNF382 inhibited malignant phenotypes and cancer-associated signaling pathways (AP-1, NF-κB and ß-catenin) and oncogenes (ZEB-1, STAT-3, STAT-5, and HIF-1α). Overexpression of ZNF382 delayed growth of PANC-1 cells in vivo. ZNF382 mRNA and protein expression was lower in tumor tissues than in adjacent normal tissues of pancreatic cancer patients. Analysis of the TCGA database found the ZNF382 promoter is hypermethylated in primary pancreatic tumors which correlates with its low expression. Furthermore, andrographolide inhibited the expression of DNA methyltransferase 3 beta (DNMT3B) and increased the demethylation of the ZNF382 promoter in PDAC cells. Overexpression of DNMT3B attenuated the andrographolide-suppressed proliferation and migration of PDAC cells. CONCLUSION: Our finding revealed that ZNF382 acts as a tumor suppressor gene in pancreatic cancer and andrographolide restores ZNF382 expression to suppress pancreatic cancer, providing a novel molecular target and a promising therapeutic approach for treating pancreatic cancer.

Two-photon autofluorescence lifetime assay of rabbit photoreceptors and retinal pigment epithelium during light-dark visual cycles in rabbit retina.

Two-photon excited fluorescence (TPEF) is a powerful technique that enables the examination of intrinsic retinal fluorophores involved in cellular metabolism and the visual cycle. Although previous intensity-based TPEF studies in non-human primates have successfully imaged several classes of retinal cells and elucidated aspects of both rod and cone photoreceptor function, fluorescence lifetime imaging (FLIM) of the retinal cells under light-dark visual cycle has yet to be fully exploited. Here we demonstrate a FLIM assay of photoreceptors and retinal pigment epithelium (RPE) that reveals key insights into retinal physiology and adaptation. We found that photoreceptor fluorescence lifetimes increase and decrease in sync with light and dark exposure, respectively. This is likely due to changes in all-trans-retinol and all-trans-retinal levels in the outer segments, mediated by phototransduction and visual cycle activity. During light exposure, RPE fluorescence lifetime was observed to increase steadily over time, as a result of all-trans-retinol accumulation during the visual cycle and decreasing metabolism caused by the lack of normal perfusion of the sample. Our system can measure the fluorescence lifetime of intrinsic retinal fluorophores on a cellular scale, revealing differences in lifetime between retinal cell classes under different conditions of light and dark exposure.

Epidemiologic Features of Recovery From SARS-CoV-2 Infection.

Importance: Persistent symptoms and disability following SARS-CoV-2 infection, known as post-COVID-19 condition or "long COVID," are frequently reported and pose a substantial personal and societal burden. Objective: To determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days. Design, Setting, and Participants: For this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health-funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection. Exposure: Preinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires. Main Outcomes and Measures: Probability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days. Results: Of 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections. Conclusions and Relevance: In this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Assessing the impact of extracellular matrix fiber orientation on breast cancer cellular metabolism.

The extracellular matrix (ECM) is a dynamic and complex microenvironment that modulates cell behavior and cell fate. Changes in ECM composition and architecture have been correlated with development, differentiation, and disease progression in various pathologies, including breast cancer [1]. Studies have shown that aligned fibers drive a pro-metastatic microenvironment, promoting the transformation of mammary epithelial cells into invasive ductal carcinoma via the epithelial-to-mesenchymal transition (EMT) [2]. The impact of ECM orientation on breast cancer metabolism, however, is largely unknown. Here, we employ two non-invasive imaging techniques, fluorescence-lifetime imaging microscopy (FLIM) and intensity-based multiphoton microscopy, to assess the metabolic states of cancer cells cultured on ECM-mimicking nanofibers in a random and aligned orientation. By tracking the changes in the intrinsic fluorescence of nicotinamide adenine dinucleotide and flavin adenine dinucleotide, as well as expression levels of metastatic markers, we reveal how ECM fiber orientation alters cancer metabolism and EMT progression. Our study indicates that aligned cellular microenvironments play a key role in promoting metastatic phenotypes of breast cancer as evidenced by a more glycolytic metabolic signature on nanofiber scaffolds of aligned orientation compared to scaffolds of random orientation. This finding is particularly relevant for subsets of breast cancer marked by high levels of collagen remodeling (e.g. pregnancy associated breast cancer), and may serve as a platform for predicting clinical outcomes within these subsets [3-6].

MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric.

Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.

Neurobiologically realistic neural network enables cross-scale modeling of neural dynamics.

Fundamental principles underlying computation in multi-scale brain networks illustrate how multiple brain areas and their coordinated activity give rise to complex cognitive functions. Whereas brain activity has been studied at the micro- to meso-scale to reveal the connections between the dynamical patterns and the behaviors, investigations of neural population dynamics are mainly limited to single-scale analysis. Our goal is to develop a cross-scale dynamical model for the collective activity of neuronal populations. Here we introduce a bio-inspired deep learning approach, termed NeuroBondGraph Network (NBGNet), to capture cross-scale dynamics that can infer and map the neural data from multiple scales. Our model not only exhibits more than an 11-fold improvement in reconstruction accuracy, but also predicts synchronous neural activity and preserves correlated low-dimensional latent dynamics. We also show that the NBGNet robustly predicts held-out data across a long time scale (2 weeks) without retraining. We further validate the effective connectivity defined from our model by demonstrating that neural connectivity during motor behaviour agrees with the established neuroanatomical hierarchy of motor control in the literature. The NBGNet approach opens the door to revealing a comprehensive understanding of brain computation, where network mechanisms of multi-scale activity are critical.

A non-FRET DNA reporter that changes fluorescence colour upon nuclease digestion.

Fluorescence resonance energy transfer (FRET) reporters are commonly used in the final stages of nucleic acid amplification tests to indicate the presence of nucleic acid targets, where fluorescence is restored by nucleases that cleave the FRET reporters. However, the need for dual labelling and purification during manufacturing contributes to the high cost of FRET reporters. Here we demonstrate a low-cost silver nanocluster reporter that does not rely on FRET as the on/off switching mechanism, but rather on a cluster transformation process that leads to fluorescence color change upon nuclease digestion. Notably, a 90 nm red shift in emission is observed upon reporter cleavage, a result unattainable by a simple donor-quencher FRET reporter. Electrospray ionization-mass spectrometry results suggest that the stoichiometric change of the silver nanoclusters from Ag13 (in the intact DNA host) to Ag10 (in the fragments) is probably responsible for the emission colour change observed after reporter digestion. Our results demonstrate that DNA-templated silver nanocluster probes can be versatile reporters for detecting nuclease activities and provide insights into the interactions between nucleases and metallo-DNA nanomaterials.

Multiplexed imaging in live cells using pulsed interleaved excitation spectral FLIM.

Multiplexed fluorescence detection has become increasingly important in the fields of biosensing and bioimaging. Although a variety of excitation/detection optical designs and fluorescence unmixing schemes have been proposed to allow for multiplexed imaging, rapid and reliable differentiation and quantification of multiple fluorescent species at each imaging pixel is still challenging. Here we present a pulsed interleaved excitation spectral fluorescence lifetime microscopic (PIE-sFLIM) system that can simultaneously image six fluorescent tags in live cells in a single hyperspectral snapshot. Using an alternating pulsed laser excitation scheme at two different wavelengths and a synchronized 16-channel time-resolved spectral detector, our PIE-sFLIM system can effectively excite multiple fluorophores and collect their emission over a broad spectrum for analysis. Combining our system with the advanced live-cell labeling techniques and the lifetime/spectral phasor analysis, our PIE-sFLIM approach can well unmix the fluorescence of six fluorophores acquired in a single measurement, thus improving the imaging speed in live-specimen investigation.

Visualizing molecular deformation in fibrin networks under tensile loading via FLIM-FRET.

Mapping molecular deformation and forces in protein biomaterials is critical to understanding mechanochemistry. Here we use intramolecular Förster resonance energy transfer (FRET) of dual-labeled fibrin to distinguish molecular conformations of proteins in situ during mechanical loading. The FRET approach offers increased spatial resolution compared to our previous vibrational imaging. By using fluorescence lifetime microscopy (FLIM), we demonstrate that the combination of FRET and FLIM can probe the molecular changes in fibrin with high spatial (nanometer) and temporal (nanosecond) resolution. Our results map changes in fibrin monomer deformation during the macroscopic loading of the fibrin network, paving the way to directly visualizing the biomaterial mechanics and structure in cell-ECM scaffolds for the first time.

Cross-sectional and longitudinal analyses of variations of anthropometric measures of obesity with age in the Jackson Heart Study.

OBJECTIVE: To explore how anthropometric measures of obesity vary with age among African American (AA) adults. PARTICIPANTS AND SETTING: 3634 AA adults participated in the Jackson Heart Study (Jackson, Mississippi, USA) from 2004 to 2013. OUTCOME MEASURES: Body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and waist-to-hip ratio (WHR). METHODS: Linear regression models were used to estimate the mean differences in anthropometric measures cross-sectionally by age group. Longitudinal changes in anthropometric measures over time (ie, the ageing effect) within each sex and age group were analysed using mixed effects models. All regression models were adjusted for education and lifestyle factors. RESULTS: In cross-sectional analysis, older age was associated with lower BMI, WC and WHtR, but higher WHR in both sexes. Compared with 25 to <44 years age group, the mean (95% CI) BMI, WC and WHtR was 0.80 (0.66 to 0.94), 0.27 (0.13 to 0.42) and 0.18 (0.03 to 0.32) standardised (SD) unit lower, while WHR was 0.48 (0.33 to 0.62) SD unit higher in the 75+ years age group. In longitudinal analysis, ageing was associated with increased BMI, WC and WHtR, among younger age groups but not in older age groups. However, WHR tended to increase with ageing across all age groups in both sexes. Among men 75+ years old, the mean change (95% CI) in BMI, WC and WHtR for every 5 years increase in age, was -0.20 (-0.29 to -0.11), -0.19 (-0.31 to -0.07), -0.15 (-0.27 to -0.02) SD unit, respectively, while it was 0.24 (0.05 to 0.44) SD unit for WHR. CONCLUSIONS: Among middle-aged AA adults, all four anthropometric measures of obesity examined increased with ageing. However, among elderly AA adults, only WHR showed continued increase with ageing. WHR may be a better anthropometric measure for monitoring obesity in older AA adults.

Cysteine-cysteine Chemokine Receptor Type 5 Plays a Critical Role in Exercise Performance by Regulating Mitochondrial Content in Skeletal Muscle.

Cysteine-cysteine chemokine receptor type 5 (CCR5) is thought to play an important role in the trafficking of lymphoid cells but has recently also been associated with AMPK signaling pathways that are implicated in energy metabolism in skeletal muscle. We hypothesized that genetic deletions of CCR5 would alter mitochondria content and exercise performance in mice. CCR5-/- and wild-type mice with the same genetic background were subjected to endurance exercise and grip strength tests. The soleus muscle was stained with immunofluorescence for myosin heavy chain 7 (MYH7) and succinate dehydrogenase (SDH) analysis as well as the expression of genes associated with muscle atrophy and mitochondrial oxidative phosphorylation were measured using qPCR. Although there were no differences in the weight of the soleus muscle between the CCR5-/- group and the wild-type mice, the CCR5-/- mice showed the following muscular dysfunctions: (i) decreased MYH7 percentage and cross-section area, (ii) higher myostatin and atrogin-1 mRNA levels, (iii) dropped expression of mitochondrial DNA-encoded electron respiratory chain genes (cytochrome B, cytochrome c oxidase subunit III, and ATP synthase subunit 6) as well as mitochondrial generation genes (PPARγ and PGC-1α), and (iv) lower SDH activity and exercise performance when compared with wild-type mice. In addition, genes associated with mitochondrial biogenesis (PGC-1α, PPARγ, and MFN2) and mitochondrial complex (ND4 and Cytb) were upregulated when the skeletal muscle cell line C2C12 was exposed to cysteine-cysteine chemokine ligand 4 (a ligand of CCR5) in vitro. These findings suggested that attenuation of endurance exercise performance is related to the loss of mitochondrial content and lower SDH activity of soleus muscle in CCR5 knockout mice. The present study provides evidence indicating that the chemokine receptor CCR5 might modulate the skeletal muscle metabolic energy system during exercise.

Recent Advances in Single-Molecule Tracking and Imaging Techniques.

Since the early 1990s, single-molecule detection in solution at room temperature has enabled direct observation of single biomolecules at work in real time and under physiological conditions, providing insights into complex biological systems that the traditional ensemble methods cannot offer. In particular, recent advances in single-molecule tracking techniques allow researchers to follow individual biomolecules in their native environments for a timescale of seconds to minutes, revealing not only the distinct pathways these biomolecules take for downstream signaling but also their roles in supporting life. In this review, we discuss various single-molecule tracking and imaging techniques developed to date, with an emphasis on advanced three-dimensional (3D) tracking systems that not only achieve ultrahigh spatiotemporal resolution but also provide sufficient working depths suitable for tracking single molecules in 3D tissue models. We then summarize the observables that can be extracted from the trajectory data. Methods to perform single-molecule clustering analysis and future directions are also discussed.

Spatial resolution enhancement in photon-starved STED imaging using deep learning-based fluorescence lifetime analysis.

As a super-resolution imaging method, stimulated emission depletion (STED) microscopy has unraveled fine intracellular structures and provided insights into nanoscale organizations in cells. Although image resolution can be further enhanced by continuously increasing the STED-beam power, the resulting photodamage and phototoxicity are major issues for real-world applications of STED microscopy. Here we demonstrate that, with 50% less STED-beam power, the STED image resolution can be improved up to 1.45-fold using the separation of photons by a lifetime tuning (SPLIT) scheme combined with a deep learning-based phasor analysis algorithm termed flimGANE (fluorescence lifetime imaging based on a generative adversarial network). This work offers a new approach for STED imaging in situations where only a limited photon budget is available.

Impact of Diabetes and Hypertension on Left Ventricular Structure and Function: The Jackson Heart Study.

Background Diabetes and hypertension have been associated with adverse left ventricular (LV) remodeling. While they often occur concurrently, their individual effects are understudied. We aimed to assess the independent effects of diabetes and hypertension on LV remodeling in Black adults. Methods and Results The JHS (Jackson Heart Study) participants (n=4143 Black adults) with echocardiographic measures from baseline exam were stratified into 4 groups: neither diabetes nor hypertension (n=1643), only diabetes (n=152), only hypertension (n=1669), or both diabetes and hypertension (n=679). Echocardiographic measures of LV structure and function among these groups were evaluated by multivariable regression adjusting for covariates. Mean age of the participants was 52±1 years, and 63.7% were women. LV mass index was not different in participants with only diabetes compared with participants with neither diabetes nor hypertension (P=0.8). LV mass index was 7.9% (6.0 g/m2) higher in participants with only hypertension and 10.8% (8.1 g/m2) higher in participants with both diabetes and hypertension compared with those with neither (P<0.001). LV wall thickness (relative, posterior, and septal) and brain natriuretic peptide levels in participants with only diabetes were not significantly higher than participants with neither (P>0.05). However, participants with both diabetes and hypertension demonstrated higher LV wall thickness and brain natriuretic peptide levels than participants with neither (P<0.05). Conclusions In this cross-sectional analysis, diabetes was not associated with altered LV structure or function in Black adults unless participants also had hypertension. Our findings suggest hypertension is the main contributor to cardiac structural and functional changes in Black adults with diabetes.

Effect of ultramarathon running on iron metabolism.

BACKGROUND: Iron is a vital trace element for energy production and oxygen transportation; importantly, it is essential to athletic performance. Maintaining iron balance is tightly controlled at systemic and cellular levels. This study aimed to determine serum iron tests, hepcidin levels, and cellular iron import and export activities in peripheral blood mononuclear cells (PBMCs) in ultramarathon runners to elucidate the association of systemic inflammation response and iron metabolism. METHODS: Sixteen amateur runners were enrolled. Blood samples were taken 1 week before, immediately, and 24 h after the run. Plasma hepcidin levels were measured by enzyme-linked immunosorbent assay. The expression levels of divalent metal iron transporter 1 (DMT1), ZRT/IRT-like protein 14 (ZIP14), transferrin receptor 1 (TfR1), and ferroportin (FPN) in PBMCs were measured using real-time quantitative reverse transcription-polymerase chain reaction. RESULTS: Serum iron concentrations and transferrin saturation significantly decreased immediately after the race and dramatically recovered 24 h post-race. Serum ferritin levels had a statistically significant rise immediately after the race and remained high 24 h after the completion of the race. Ultramarathons were associated with increased plasma interleukin-6 concentrations corresponding to the state of severe systemic inflammation and therefore boosted plasma hepcidin levels. The expression levels of DMT1 and FPN mRNA were markedly decreased immediately and 24 h after the race. The ZIP14 and TfR1 mRNA expression in PBMCs significantly decreased immediately after the race and returned to the baseline level at 24 h post-race. Positive significant correlations were observed between plasma hepcidin and ferritin levels. CONCLUSION: Iron homeostasis and systemic inflammatory response are closely interconnected. Cellular iron import and export mRNA activities in PBMCs were acutely inhibited during an ultramarathon.

Digital Connectedness in the Jackson Heart Study: Cross-sectional Study.

BACKGROUND: Although new approaches for data collection, such as mobile technology and teleresearch, have demonstrated new opportunities for the conduct of more timely and less costly surveys in community-based studies, literature on the feasibility of conducing cardiovascular disease research using mobile health (mHealth) platforms among middle-aged and older African Americans has been limited. OBJECTIVE: The purpose of this study was to contribute to the knowledge regarding the penetrance of internet and mobile technologies, such as cellphones or smartphones in existing large cohort studies of cardiovascular disease. METHODS: A digital connectedness survey was conducted in the Jackson Heart Study (JHS), a Mississippi-based African American cohort study, as part of the annual follow-up calls with participants from July 2017 to February 2019. RESULTS: Of the 4024 participants contacted, 2564 (63.7%) completed the survey. Among survey respondents, 2262 (88.2%) reported use of internet or cellphone, and 1593 (62.1%) had a smartphone. Compared to nonusers (n=302), internet or cellphone users (n=2262) were younger (mean age 80.1, SD 8.0 vs 68.2, SD 11.3 years), more likely to be affluent (n=778, 40.1% vs n=39, 15.4%), and had greater than high school education (n=1636, 72.5% vs n=85, 28.1%). Internet or cellphone users were less likely to have cardiovascular disease history compared to nonusers (136/2262, 6.6% vs 41/302, 15.8%). The prevalence of current smoking and average BMI were similar between internet or cellphone users and nonusers. Among internet or cellphone users, 1316 (58.3%) reported use of email, 504 (22.3%) reported use of apps to track or manage health, and 1269 (56.1%) expressed interest in using JHS-developed apps. CONCLUSIONS: Our findings suggest that it is feasible to use mHealth technologies to collect survey data among African Americans already enrolled in a longitudinal study. Our findings also highlight the need for more efforts to reduce the age and education divide in access and use of internet and smartphones for tracking health and research in African American communities.

Therapeutic effects of herbal-medicine combined therapy for COVID-19: A systematic review and meta-analysis of randomized controlled trials.

Background/Aim: Since 2019, the COVID-19 pandemic has been a devastating disease affecting global health to a great extent. Some countries have added on herbal medicines as a complementary treatment for combating COVID-19 due to the urgency of stopping the spread of this viral disease. However, whether these herbal medicines are effective is uncertain. This systematic review and meta-analysis aimed to evaluate the effects of herbal medicine combined therapy in the treatment of COVID-19. Methods: A literature search was performed following the PRISMA Statement and without language restrictions. Seven databases were searched from inception through December 2021. All selected studies were randomized clinical trials (RCTs). Comparing the effects of herbal medicine combined therapy with conventional western medicine, including improvement of clinical symptoms, chest CT images, viral conversion rate, C-reactive protein (CRP) and interleukin 6. Cochrane criteria were applied to examine the methodological quality of the enrolled trials; and meta-analysis software (RevMan 5.4.1) was used for data analysis. Results: In total, the data of 5,417 participants from 40 trials were included in this systematic review; and 28 trials were qualified for meta-analysis. The trials had medium-to-high quality based on GRADE system. Meta-analysis showed that combining herbal medicine vs conventional treatment in 1) coughing (1.43 95% CI:1.21, 1.71, p = 0.0001), 2) fever (1.09 95% CI:1.00, 1.19, p = 0.06), 3) fatigue (1.21 95% CI:1.10, 1.33, p = 0.0001); 4) CT images (1.26 95% CI:1.19, 1.34, P ≤ 0.00001), 5) viral conversion rates (1.22 95% CI:1.06, 1.40, p = 0.005) and 6) viral conversion times (-3.72 95% CI: -6.05, -1.40, p = 0.002), 7) IL6 change (1.97 95% CI: -0.72, 4.66, p = 0.15) and 8) CRP change (-7.92 95% CI: -11.30, -4.53, P ≤ 0.00001). Conclusion: Herbal medicine combined therapy significantly reduces COVID-19 clinical symptoms, improving CT images and viral conversion rates. Reported adverse events are mild. However, for certain biases in the included studies, and the need for further study on effective components of herbal medicine. Further large trials with better randomized design are warranted to definite a more definite role of herbal medicine.

Massively Parallel Selection of NanoCluster Beacons.

NanoCluster Beacons (NCBs) are multicolor silver nanocluster probes whose fluorescence can be activated or tuned by a proximal DNA strand called the activator. While a single-nucleotide difference in a pair of activators can lead to drastically different activation outcomes, termed polar opposite twins (POTs), it is difficult to discover new POT-NCBs using the conventional low-throughput characterization approaches. Here, a high-throughput selection method is reported that takes advantage of repurposed next-generation-sequencing chips to screen the activation fluorescence of ≈40 000 activator sequences. It is found that the nucleobases at positions 7-12 of the 18-nucleotide-long activator are critical to creating bright NCBs and positions 4-6 and 2-4 are hotspots to generate yellow-orange and red POTs, respectively. Based on these findings, a "zipper-bag" model is proposed that can explain how these hotspots facilitate the formation of distinct silver cluster chromophores and alter their chemical yields. Combining high-throughput screening with machine-learning algorithms, a pipeline is established to design bright and multicolor NCBs in silico.

TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data.

Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.