Genome-wide polygenic risk score for rheumatoid arthritis prediction in postmenopausal women.

BACKGROUND: Rheumatoid arthritis (RA), a common autoimmune disease, exhibits a vital genetic component. Polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) offer potential utility in predicting disease susceptibility. The present study aimed to develop and validate a PRS for predicting RA risk in postmenopausal women. METHODS: The study developed a novel PRS using 225,000 genetic variants from a GWAS dataset. The PRS was developed in a cohort of 8967 postmenopausal women and validated in an independent cohort of 6269 postmenopausal women. Among the development cohort, approximately 70% were Hispanic and approximately 30% were African American. The testing cohort comprised approximately 50% Hispanic and 50% Caucasian individuals. Stratification according to PRS quintiles revealed a pronounced gradient in RA prevalence and odds ratios. RESULTS: High PRS was significantly associated with increased RA risk in individuals aged 60-70 years, ≥ 70 years, and overweight and obese participants. Furthermore, at age 65 years, individuals in the bottom 5% of the PRS distribution have an absolute risk of RA at 30.6% (95% confidence interval = 18.5%-42.6%). The risk increased to 53.8% (95% confidence interval = 42.8%-64.9%) for those in the top 5% of the PRS distribution. CONCLUSIONS: The PRS developed in the present study is significantly associated with RA risk, showing the potential for early screening of RA in postmenopausal women. This work demonstrates the feasibility of personalized medicine in identifying high-risk individuals for RA, indicating the need for further studies to test the utility of PRS in other populations.

A deep learning based method for automatic analysis of high-throughput droplet digital PCR images.

Droplet digital PCR (ddPCR) is a technique for absolute quantification of nucleic acid molecules and is widely used in biomedical research and clinical diagnosis. ddPCR partitions the reaction solution containing target molecules into a large number of independent microdroplets for amplification and performs quantitative analysis of target molecules by calculating the proportion of positive droplets by the principle of Poisson distribution. Accurate recognition of positive droplets in ddPCR images is of great importance to guarantee the accuracy of target nucleic acid quantitative analysis. However, hand-designed operators are sensitive to interference and have disadvantages such as low contrast, uneven illumination, low sample copy number, and noise, and their accuracy and robustness still need to be improved. Herein, we developed a deep learning-based high-throughput ddPCR droplet detection framework for robust and accurate ddPCR image analysis, and the experimental results show that our method achieves excellent performance in the recognition of positive droplets (99.71%) within a limited time. By combining the Hough transform and a convolutional neural network (CNN), our novel method can automatically filter out invalid droplets that are difficult to be identified by local or global encoding methods and realize high-precision localization and classification of droplets in ddPCR images under variable exposure, contrast, and uneven illumination conditions without the need for image pre-processing and normalization processes.

Proximity proteomics identifies novel function of Rab14 in trafficking of Ebola virus matrix protein VP40.

Ebola virus is a member of Filoviridae family of viruses that causes fetal hemorrhagic fever in human. Matrix protein VP40 of the Ebola virus is involved in multiple stages of viral maturation processes. In order to fully understand the interacting partners of VP40 in host cells, we applied proximity-dependent biotin-identification (BioID) approach to systematically screen for potential proteins at different time points of VP40 expression. By immunoprecipitation and subsequent proteomics analysis, we found over 100 candidate proteins with various cellular components and molecular functions. Among them, we identified Rab14 GTPase that appears to function at the late stage of VP40 expression. Imaging studies demonstrated that VP40 and Rab14 have substantial colocalization when expressed in HeLa cells. Overexpression of the dominant-negative Rab14(S25N) diminished the plasma membrane (PM) localization of VP40. In addition, we found that secreted VP40 protein can be endocytosed into Rab14 positive compartments. In summary, our study provides evidence that Rab14 is a novel regulator of the intracellular trafficking of Ebola virus matrix protein VP40 in HeLa cells.

Sec3 knockdown inhibits TGF-ß induced epithelial-mesenchymal transition through the down-regulation of Akt phosphorylation in A549 cells.

The exocyst, an evolutionarily conserved octomeric protein complex, has been demonstrated as an essential component for vesicle tethering during cell exocytosis, and participates in various physiological processes in the cell. Although subunits of the exocyst complex have been reported to be involved in the regulation of TGF-ß induced cancer cell migration and epithelial-mesenchymal transition (EMT), the potential function of Sec3 in these regulated processes remains unclear. Here, we show that Sec3 knockdown abolishes TGF-ß stimulated A549 lung cancer cell migration in vitro and causes defects in the regulated EMT process. In addition, we find that depletion of Sec3 significantly inhibits TGF-ß stimulated Akt phosphorylation in A549 cells, whereas the increase of Smad2 phosphorylation is unaffected. Furthermore, replenishment of an RNAi-resistant form of Sec3 is shown to restore the defects of TGF-ß induced cell migration, EMT and Akt signaling activation. In summary, our study provides evidence that Sec3 is involved in TGF-ß induced cell migration and EMT processes, presumably through the regulation of PI3K/Akt signaling activation in A549 cancer cells.

Optogenetic activation reveals distinct roles of PIP3 and Akt in adipocyte insulin action.

Glucose transporter 4 (GLUT4; also known as SLC2A4) resides on intracellular vesicles in muscle and adipose cells, and translocates to the plasma membrane in response to insulin. The phosphoinositide 3-kinase (PI3K)-Akt signaling pathway plays a major role in GLUT4 translocation; however, a challenge has been to unravel the potentially distinct contributions of PI3K and Akt (of which there are three isoforms, Akt1-Akt3) to overall insulin action. Here, we describe new optogenetic tools based on CRY2 and the N-terminus of CIB1 (CIBN). We used these 'Opto' modules to activate PI3K and Akt selectively in time and space in 3T3-L1 adipocytes. We validated these tools using biochemical assays and performed live-cell kinetic analyses of IRAP-pHluorin translocation (IRAP is also known as LNPEP and acts as a surrogate marker for GLUT4 here). Strikingly, Opto-PIP3 largely mimicked the maximal effects of insulin stimulation, whereas Opto-Akt only partially triggered translocation. Conversely, drug-mediated inhibition of Akt only partially dampened the translocation response of Opto-PIP3 In spatial optogenetic studies, focal targeting of Akt to a region of the cell marked the sites where IRAP-pHluorin vesicles fused, supporting the idea that local Akt-mediated signaling regulates exocytosis. Taken together, these results indicate that PI3K and Akt play distinct roles, and that PI3K stimulates Akt-independent pathways that are important for GLUT4 translocation.

Three-dimensional super-resolved live cell imaging through polarized multi-angle TIRF.

Measuring three-dimensional nanoscale cellular structures is challenging, especially when the structure is dynamic. Owing to the informative total internal reflection fluorescence (TIRF) imaging under varied illumination angles, multi-angle (MA) TIRF has been examined to offer a nanoscale axial and a subsecond temporal resolution. However, conventional MA-TIRF still performs badly in lateral resolution and fails to characterize the depth image in densely distributed regions. Here, we emphasize the lateral super-resolution in the MA-TIRF, exampled by simply introducing polarization modulation into the illumination procedure. Equipped with a sparsity and accelerated proximal algorithm, we examine a more precise 3D sample structure compared with previous methods, enabling live cell imaging with a temporal resolution of 2 s and recovering high-resolution mitochondria fission and fusion processes. We also shared the recovery program, which is the first open-source recovery code for MA-TIRF, to the best of our knowledge.

Excess cholesterol inhibits glucose-stimulated fusion pore dynamics in insulin exocytosis.

Type 2 diabetes is caused by defects in both insulin sensitivity and insulin secretion. Glucose triggers insulin secretion by causing exocytosis of insulin granules from pancreatic ß-cells. High circulating cholesterol levels and a diminished capacity of serum to remove cholesterol from ß-cells are observed in diabetic individuals. Both of these effects can lead to cholesterol accumulation in ß-cells and contribute to ß-cell dysfunction. However, the molecular mechanisms by which cholesterol accumulation impairs ß-cell function remain largely unknown. Here, we used total internal reflection fluorescence microscopy to address, at the single-granule level, the role of cholesterol in regulating fusion pore dynamics during insulin exocytosis. We focused particularly on the effects of cholesterol overload, which is relevant to type 2 diabetes. We show that excess cholesterol reduced the number of glucose-stimulated fusion events, and modulated the proportion of full fusion and kiss-and-run fusion events. Analysis of single exocytic events revealed distinct fusion kinetics, with more clustered and compound exocytosis observed in cholesterol-overloaded ß-cells. We provide evidence for the involvement of the GTPase dynamin, which is regulated in part by cholesterol-induced phosphatidylinositol 4,5-bisphosphate enrichment in the plasma membrane, in the switch between full fusion and kiss-and-run fusion. Characterization of insulin exocytosis offers insights into the role that elevated cholesterol may play in the development of type 2 diabetes.

Objective comparison of particle tracking methods.

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.

Fluorescent Nanowire Ring Illumination for Wide-Field Far-Field Subdiffraction Imaging.

Here we demonstrate an active method which pioneers in utilizing a combination of a spatial frequency shift and a Stokes frequency shift to enable wide-field far-field subdiffraction imaging. A fluorescent nanowire ring acts as a localized source and is combined with a film waveguide to produce omnidirectional illuminating evanescent waves. Benefitting from the high wave vector of illumination, the high spatial frequencies of an object can be shifted to the passband of a conventional imaging system, contributing subwavelength spatial information to the far-field image. A structure featuring 70-nm-wide slots spaced 70 nm apart has been resolved at a wavelength of 520 nm with a 0.85 numerical aperture standard objective based on this method. The versatility of this approach has been demonstrated by imaging integrated chips, Blu-ray DVDs, biological cells, and various subwavelength 2D patterns, with a viewing area of up to 1000 µm^{2}, which is one order of magnitude larger than the previous far-field and full-field nanoscopy methods. This new resolving technique is label-free, is conveniently integrated with conventional microscopes, and can potentially become an important tool in cellular biology, the on-chip industry, as well as other fields requiring wide-field nanoscale visualization.

Establishment of rat ankle post-traumatic osteoarthritis model induced by malleolus fracture.

BACKGROUND: Malleolar fracture, which is present in 37-53% of human ankle osteoarthritis (OA), is the most common type of fracture in the ankle joint. In spite of this, no rat animal model has been developed for this type of injury to date. Here, we established a rat ankle post-traumatic OA (PTOA) model induced by malleolar fracture; this model will be useful in ankle OA research. METHODS: Two-month-old male Sprague Dawley (SD) rats were randomized into 2 groups (n = 19 per group): 1) malleolus articular fracture, dislocation, and immediate reduction on the right joints and 2) malleolus articular fracture on the right ankle. The contralateral ankle joints were used as controls. The fracture and healing processes were confirmed and monitored by radiography. Changes in inflammation were monitored in vivo by fluorescence molecular tomography (FMT). Cartilage damage and changes in expression of OA-related genes were analyzed by histology, immunohistochemistry, Real-time quantitative PCR (qPCR) and enzyme-linked immunosorbent assay (ELISA) at 8 weeks post-surgery. RESULTS: X-rays showed that all fractures were healed at 8 weeks post-surgery. A reproducible, mild to moderate degree of OA cartilage damage with reduced aggrecan was detected by histology in all animals in both groups but there was no significant difference between the two groups. Decreased Col-II and increased Col-X and MMP-13 levels were detected by qPCR, immunohistochemistry, ELISA and FMT from both groups cartilage. CONCLUSIONS: Malleolus articular fracture alone induces ankle OA with lesions on the central weight bearing area of the tibiotalar joint in rats. This model will provide a reproducible and useful tool for researchers to study ankle OA.

Virtual k-Space Modulation Optical Microscopy.

We report a novel superresolution microscopy approach for imaging fluorescence samples. The reported approach, termed virtual k-space modulation optical microscopy (VIKMOM), is able to improve the lateral resolution by a factor of 2, reduce the background level, improve the optical sectioning effect and correct for unknown optical aberrations. In the acquisition process of VIKMOM, we used a scanning confocal microscope setup with a 2D detector array to capture sample information at each scanned x-y position. In the recovery process of VIKMOM, we first modulated the captured data by virtual k-space coding and then employed a ptychography-inspired procedure to recover the sample information and correct for unknown optical aberrations. We demonstrated the performance of the reported approach by imaging fluorescent beads, fixed bovine pulmonary artery endothelial (BPAE) cells, and living human astrocytes (HA). As the VIKMOM approach is fully compatible with conventional confocal microscope setups, it may provide a turn-key solution for imaging biological samples with ∼100 nm lateral resolution, in two or three dimensions, with improved optical sectioning capabilities and aberration correcting.

Dual-mode super-resolution imaging with stimulated emission depletion microscopy and fluorescence emission difference microscopy.

Dual-mode super-resolution imaging system with two different super-resolution imaging methods, STED and FED, is presented. Electrical shutters controlled by the host computer are introduced to switch the two imaging modes. Principles of both methods are analyzed theoretically, and enhancements in the lateral resolution and SNR are demonstrated theoretically and experimentally. Results show that both imaging methods offered by the proposed system can break the diffraction barrier. Furthermore, the presented system provides a meaningful way to image fluorescent samples by a corresponding imaging mode according to the specific characteristics of samples analyzed for study. For samples that can endure high-power illumination, it is appropriate to use the STED mode to achieve a better resolution, while for samples that are vulnerable to high intensity, the FED method is a better choice because no high-power beam is needed, and the FED method can provide better resolution than STED when no high-power beam is allowed. The flexible switching of the two super-resolution imaging modes can help researchers to make most of the advantages of each imaging method. It is believed that the presented system has the potential to be widely used in future nanoscale investigations.

Cholesterol accumulation increases insulin granule size and impairs membrane trafficking.

The formation of mature secretory granules is essential for proper storage and regulated release of hormones and neuropeptides. In pancreatic ß cells, cholesterol accumulation causes defects in insulin secretion and may participate in the pathogenesis of type 2 diabetes. Using a novel cholesterol analog, we show for the first time that insulin granules are the major sites of intracellular cholesterol accumulation in live ß cells. This is distinct from other, non-secretory cell types, in which cholesterol is concentrated in the recycling endosomes and the trans-Golgi network. Excess cholesterol was delivered specifically to insulin granules, which caused granule enlargement and retention of syntaxin 6 and VAMP4 in granule membranes, with concurrent depletion of these proteins from the trans-Golgi network. Clathrin also accumulated in the granules of cholesterol-overloaded cells, consistent with a possible defect in the last stage of granule maturation, during which clathrin-coated vesicles bud from the immature granules. Excess cholesterol also reduced the docking and fusion of insulin granules at the plasma membrane. Together, the data support a model in which cholesterol accumulation in insulin secretory granules impairs the ability of these vesicles to respond to stimuli, and thus reduces insulin secretion.

Optogenetic therapeutic strategies for diabetes mellitus.

Diabetes mellitus (DM) is a common chronic disease affecting humans globally. It is characterized by abnormally elevated blood glucose levels due to the failure of insulin production or reduction of insulin sensitivity and functionality. Insulin and glucagon-like peptide (GLP)-1 replenishment or improvement of insulin resistance are the two major strategies to treat diabetes. Recently, optogenetics that uses genetically encoded light-sensitive proteins to precisely control cell functions has been regarded as a novel therapeutic strategy for diabetes. Here, we summarize the latest development of optogenetics and its integration with synthetic biology approaches to produce light-responsive cells for insulin/GLP-1 production, amelioration of insulin resistance and neuromodulation of insulin secretion. In addition, we introduce the development of cell encapsulation and delivery methods and smart bioelectronic devices for the in vivo application of optogenetics-based cell therapy in diabetes. The remaining challenges for optogenetics-based cell therapy in the clinical translational study are also discussed.

Awareness, understanding, and interest in personalized medicine: A cross-sectional survey study of college students.

INTRODUCTION: Personalized Medicine (PM) holds great potential in healthcare. A few existing surveys have investigated awareness, understanding, and interest regarding PM in the general public; however, studies investigating college students' opinions about PM are lacking. This study aimed to evaluate the college student's awareness, understanding, and interest in PM, and their opinion was also analyzed by their gender and major. METHODS: The study samples were undergraduate students enrolled at the University of Nevada, Las Vegas (UNLV). A web-based survey with 42 questions was emailed to all UNLV undergraduate students. Overall survey results were analyzed by gender and each student's major. A chi-square test evaluated the significant association between responses to questions with regard to gender or major. RESULTS: Among the participants, 1225 students completed the survey. This survey found that most college students had a neutral attitude to PM and were not entirely familiar with this field. For example, most students (57.6%) had a "neutral" attitude toward PM. In addition, 77.6% of students never received any personal genetic testing. More than 80% of students thought "interests" was the most important factor in using PM, and 50% of respondents chose "somewhat likely" to the recommendation about PM from the doctor. Also of importance was the finding that a significant association between the most important factor of using PM and gender was observed (p = 0.04), and the associations between a student's major affected his or her reaction to PM, how well informed she or he was about PM, his or her attitude toward a doctor's recommendation about using PM were all significant (all participant's p<0.004). CONCLUSION: UNLV undergraduate students had a neutral attitude to PM and were not entirely familiar with this field.

Racial and ethnic difference in the risk of fractures in the United States: a systematic review and meta-analysis.

This systematic review and meta-analysis examined the association between race and ethnicity and fracture risk in the United States. We identified relevant studies by searching PubMed and EMBASE for studies published from the databases' inception date to December 23, 2022. Only observational studies conducted in the US population that reported the effect size of racial-ethnic minority groups versus white people were included. Two investigators independently conducted literature searches, study selection, risk of bias assessment, and data abstraction; discrepancies were resolved by consensus or consultation of a third investigator. Twenty-five studies met the inclusion criteria, and the random-effects model was used to calculate the pooled effect size due to heterogeneity between the studies. Using white people as the reference group, we found that people of other races and ethnic groups had a significantly lower fracture risk. In Black people, the pooled relative risk (RR) was 0.46 (95% confidence interval (CI), 0.43-0.48, p < 0.0001). In Hispanics, the pooled RR was 0.66 (95% CI, 0.55-0.79, p < 0.0001). In Asian Americans, the pooled RR was 0.55 (95% CI, 0.45-0.66, p < 0.0001). In American Indians, the pooled RR was 0.80 (95% CI, 0.41-1.58, p = 0.3436). Subgroup analysis by sex in Black people revealed the strength of association was greater in men (RR = 0.57, 95% CI = 0.51-0.63, p < 0.0001) than in women (RR = 0.43, 95% CI = 0.39-0.47, p < 0.0001). Our findings suggest that people of other races and ethnic groups have a lower fracture risk than white people.

Coordinated Approach: Comprehensive Policy and Action Planning.

BACKGROUND: Schools play a vital role in student health, and a collaborative approach may affect health factors such as physical activity (PA) and nutrition. There is a lack of recent literature synthesizing collaborative approaches in K-12 settings. We present updated evidence about interventions that used a coordinated school health approach to support K-12 student PA and nutrition in the United States. METHODS: A 2-phase literature review search included a search of systematic reviews for individual qualifying studies (2010-2018), followed by a search for individual articles (2010-2020) that evaluated a coordinated approach or use of school wellness councils, committees, or teams to address PA and/or nutrition. RESULTS: We identified 35 articles describing 30 studies and grouped them by intervention type. Interventions demonstrated promising findings for environmental changes and student dietary and PA behaviors. IMPLICATIONS: Coordinated and multicomponent interventions demonstrated significant improvements or null results, indicating that implementation of programs and/or policies to promote healthier eating and PA practices may support and do not appear to hinder environmental or behavioral outcomes. CONCLUSIONS: Schools can use a coordinated approach to implement opportunities for PA and nutrition; this may influence students' PA and dietary behaviors.

Local-to-global spatial learning for whole-slide image representation and classification.

Whole-slide image (WSI) provides an important reference for clinical diagnosis. Classification with only WSI-level labels can be recognized for multi-instance learning (MIL) tasks. However, most existing MIL-based WSI classification methods have moderate performance on correlation mining between instances limited by their instance- level classification strategy. Herein, we propose a novel local-to-global spatial learning method to mine global position and local morphological information by redefining the MIL-based WSI classification strategy, better at learning WSI-level representation, called Global-Local Attentional Multi-Instance Learning (GLAMIL). GLAMIL can focus on regional relationships rather than single instances. It first learns relationships between patches in the local pool to aggregate region correlation (tissue types of a WSI). These correlations then can be further mined to fulfill WSI-level representation, where position correlation between different regions can be modeled. Furthermore, Transformer layers are employed to model global and local spatial information rather than being simply used as feature extractors, and the corresponding structure improvements are present. In addition, we evaluate GIAMIL on three benchmarks considering various challenging factors and achieve satisfactory results. GLAMIL outperforms state-of-the-art methods and baselines by about 1 % and 10 %, respectively.

Boosting microscopic object detection via feature activation map guided poisson blending.

Microscopic examination of visible components based on micrographs is the gold standard for testing in biomedical research and clinical diagnosis. The application of object detection technology in bioimages not only improves the efficiency of the analyst but also provides decision support to ensure the objectivity and consistency of diagnosis. However, the lack of large annotated datasets is a significant impediment in rapidly deploying object detection models for microscopic formed elements detection. Standard augmentation methods used in object detection are not appropriate because they are prone to destroy the original micro-morphological information to produce counterintuitive micrographs, which is not conducive to build the trust of analysts in the intelligent system. Here, we propose a feature activation map-guided boosting mechanism dedicated to microscopic object detection to improve data efficiency. Our results show that the boosting mechanism provides solid gains in the object detection model deployed for microscopic formed elements detection. After image augmentation, the mean Average Precision (mAP) of baseline and strong baseline of the Chinese herbal medicine micrograph dataset are increased by 16.3% and 5.8% respectively. Similarly, on the urine sediment dataset, the boosting mechanism resulted in an improvement of 8.0% and 2.6% in mAP of the baseline and strong baseline maps respectively. Moreover, the method shows strong generalizability and can be easily integrated into any main-stream object detection model. The performance enhancement is interpretable, making it more suitable for microscopic biomedical applications.

Deep learning-enabled fast DNA-PAINT imaging in cells.

DNA-based point accumulation in nanoscale topography (DNA-PAINT) is a well-established technique for single-molecule localization microscopy (SMLM), enabling resolution of up to a few nanometers. Traditionally, DNA-PAINT involves the utilization of tens of thousands of single-molecule fluorescent images to generate a single super-resolution image. This process can be time-consuming, which makes it unfeasible for many researchers. Here, we propose a simplified DNA-PAINT labeling method and a deep learning-enabled fast DNA-PAINT imaging strategy for subcellular structures, such as microtubules. By employing our method, super-resolution reconstruction can be achieved with only one-tenth of the raw data previously needed, along with the option of acquiring the widefield image. As a result, DNA-PAINT imaging is significantly accelerated, making it more accessible to a wider range of biological researchers.