Examining individual and contextual predictors of disability in Chinese older adults: A machine learning approach.

BACKGROUND: There is a large gap of understanding the determinants of disability, especially the contextual characteristics. Therefore, this study aimed to examine the important predictors of disability in Chinese older adults based on the social ecological framework. METHODS: We used the China Health and Retirement Longitudinal Study to examine predictors of disability, defined as self-report of any difficulty for six activity of daily living items. We restricted analytical sample to older adults aged 65 or above (N=1816). We considered 44 predictors, including personal-, behavioral-, interpersonal-, community-, and policy-level characteristics. The built-in variable importance measure (VIM) of random forest and SHapley Additive exPlanations (SHAP) were applied to assess key predictors of disability. A multilevel logit regression was further used to examine the associations of individual and contextual characteristics with disability. RESULTS: The mean age of study sample was 72.62 years old (standard deviation: 5.77). During a 2-year of follow-up, 518 (28.52 %) of them developed into disability. Walking speed, age, and peak expiratory flow were the top important predictors in both VIM and SHAP. Contextual characteristics such as humidity, PM2.5, temperature, normalized difference vegetation index, and landscape also showed promise in predicting disability. Multilevel logit regression showed that people with male gender, arthritis, vision impairment, unable to finish semi tandem, no social activity, lower grip strength, and higher waist circumference, had much higher risk of disability. CONCLUSION: Disability prevention strategies should specifically focus on multilevel factors such as individual and contextual characteristics, although the latter is warranted to be verified in future studies.

Spiky Gold Nanoparticles, a Nanoscale Approach to Enhanced Ex Vivo T-Cell Activation.

While existing synthetic technologies for ex vivo T-cell activation face challenges like suboptimal expansion rates and low effectiveness, artificial antigen-presenting cells (aAPCs) hold great promise for enhanced T-cell based therapies. In particular, gold nanoparticles (AuNPs), known for their biocompatibility, ease of synthesis, and versatile surface chemistry, are strong candidates for use as nanoscale aAPCs. In this study, we developed spiky AuNPs with branched geometries to present activating ligands to primary human T-cells. The special structure of spiky AuNPs enhances biomolecule loading capacity and significantly improves T-cell activation through multivalent binding of costimulatory ligands and receptors. Our spiky AuNPs outperform existing systems including Dynabeads and soluble activators by promoting greater polyclonal expansion of T-cells, boosting sustained cytokine production, and generating highly functional T-cells with reduced exhaustion. In addition, spiky AuNPs effectively activate and expand CD19 CAR-T cells while demonstrating increased in vitro cytotoxicity against target cells using fewer effector cells than Dynabeads. This study underscores the potential of spiky AuNPs as a powerful tool, bringing new opportunities to adoptive cell therapy applications.

Miconazole induces aneuploidy-mediated tolerance in Candida albicans that is dependent on Hsp90 and calcineurin.

Antifungal resistance and antifungal tolerance are two distinct terms that describe different cellular responses to drugs. Antifungal resistance describes the ability of a fungus to grow above the minimal inhibitory concentration (MIC) of a drug. Antifungal tolerance describes the ability of drug susceptible strains to grow slowly at inhibitory drug concentrations. Recent studies indicate antifungal resistance and tolerance have distinct evolutionary trajectories. Superficial candidiasis bothers millions of people yearly. Miconazole has been used for topical treatment of yeast infections for over 40 years. Yet, fungal resistance to miconazole remains relatively low. Here we found different clinical isolates of Candida albicans had different profile of tolerance to miconazole, and the tolerance was modulated by physiological factors including temperature and medium composition. Exposure of non-tolerant strains with different genetic backgrounds to miconazole mainly induced development of tolerance, not resistance, and the tolerance was mainly due to whole chromosomal or segmental amplification of chromosome R. The efflux gene CDR1 was required for maintenance of tolerance in wild type strains but not required for gain of aneuploidy-mediated tolerance. Heat shock protein Hsp90 and calcineurin were essential for maintenance as well as gain of tolerance. Our study indicates development of aneuploidy-mediated tolerance, not resistance, is the predominant mechanism of rapid adaptation to miconazole in C. albicans, and the clinical relevance of tolerance deserves further investigations.

Self-Healing Materials for Bioelectronic Devices.

Though the history of self-healing materials stretches far back to the mid-20th century, it is only in recent years where such unique classes of materials have begun to find use in bioelectronics-itself a burgeoning area of research. Inspired by the natural ability of biological tissue to self-repair, self-healing materials play a multifaceted role in the context of soft, wireless bioelectronic systems, in that they can not only serve as a protective outer shell or substrate for the internal electronic circuitry-analogous to the mechanical barrier that skin provides for the human body-but also, and most importantly, act as an active sensing safeguard against mechanical damage to preserve device functionality and enhance overall durability. This perspective presents the historical overview, general design principles, recent developments, and future outlook of self-healing materials for bioelectronic devices, which integrates topics in many research disciplines-from materials science and chemistry to electronics and bioengineering-together.

Phenotypic targeting using magnetic nanoparticles for rapid characterization of cellular proliferation regulators.

Genome-wide CRISPR screens have provided a systematic way to identify essential genetic regulators of a phenotype of interest with single-cell resolution. However, most screens use live/dead readout of viability to identify factors of interest. Here, we describe an approach that converts cell proliferation into the degree of magnetization, enabling downstream microfluidic magnetic sorting to be performed. We performed a head-to-head comparison and verified that the magnetic workflow can identify the same hits from a traditional screen while reducing the screening period from 4 weeks to 1 week. Taking advantage of parallelization and performance, we screened multiple mesenchymal cancer cell lines for their dependency on cell proliferation. We found and validated pan- and cell-specific potential therapeutic targets. The method presented provides a nanoparticle-enabled approach means to increase the breadth of data collected in CRISPR screens, enabling the rapid discovery of drug targets for treatment.

Association of Performance on Multiple Cognitive Domains with Sarcopenia among Middle-Aged and Older Adults.

INTRODUCTION: The relationship between cognitive function and subsequent sarcopenia remains unclear. Therefore, this study aimed to examine the associations of performance on multiple cognitive domains with sarcopenia in the middle-aged and older adults. METHODS: This longitudinal analysis (wave 2011-2013) included 2,934 participants from the CHARLS study. Sarcopenia was defined by the Asian Sarcopenia Working Group 2019 criteria. Cognitive function was measured by the Chinese version of the Mini-Mental State Examination (MMSE). Three interpretable techniques, namely SHapley Additive exPlanations (SHAP) and two built-in methods (coefficients of logistic regression and Gini importance of random forest), were used to assess the relationship between MMSE, its components (orientation, attention, episodic memory, and visuospatial ability) and sarcopenia. In addition, the association of MMSE score and its components with sarcopenia was further validated using stepwise regression. RESULTS: All interpretable methods showed that MMSE score was important predictors of sarcopenia, especially the SHAP (MMSE score ranked top one). For its components, episodic memory, visuospatial ability, and attention showed high predictive value compared with orientation. Stepwise regression analyses showed that MMSE score and its components of episodic memory and visuospatial ability were correlated with sarcopenia, with their odds ratios of 0.93 (95% CI: 0.91-0.96, p < 0.001), 0.87 (95% CI: 0.82-0.93, p < 0.001), and 1.32 (95% CI: 1.05-1.65, p = 0.016), respectively. CONCLUSIONS: Better cognitive function especially episodic memory and visuospatial ability was negatively associated with incident sarcopenia among community middle-aged and older adults.

Interpretable prediction models for disability in older adults with hypertension: the Chinese Longitudinal Healthy Longevity and Happy Family Study.

BACKGROUND: Older adults with hypertension have a high risk of disability, while an accurate risk prediction model is still lacking. This study aimed to construct interpretable disability prediction models for older Chinese with hypertension based on multiple time intervals. METHODS: Data were collected from the Chinese Longitudinal Healthy Longevity and Happy Family Study for 2008-2018. A total of 1602, 1108, and 537 older adults were included for the periods of 2008-2012, 2008-2014, and 2008-2018, respectively. Disability was measured by basic activities of daily living. Least absolute shrinkage and selection operator (LASSO) was applied for feature selection. Five machine learning algorithms combined with LASSO set and full-variable set were used to predict 4-, 6-, and 10-year disability risk, respectively. Area under the receiver operating characteristic curve was used as the main metric for selection of the optimal model. SHapley Additive exPlanations (SHAP) was used to explore important predictors of the optimal model. RESULTS: Random forest in full-variable set and XGBoost in LASSO set were the optimal models for 4-year prediction. Support vector machine was the optimal model for 6-year prediction on both sets. For 10-year prediction, deep neural network in full variable set and logistic regression in LASSO set were optimal models. Age ranked the most important predictor. Marital status, body mass index, score of Mini-Mental State Examination, and psychological well-being score were also important predictors. CONCLUSIONS: Machine learning shows promise in screening out older adults at high risk of disability. Disability prevention strategies should specifically focus on older patients with unfortunate marriage, high BMI, and poor cognitive and psychological conditions.

Identification of druggable regulators of cell secretion via a kinome-wide screen and high-throughput immunomagnetic cell sorting.

The identification of genetic regulators of cell secretions is challenging because it requires the sorting of a large number of cells according to their secretion patterns. Here we report the development and applicability of a high-throughput microfluidic method for the analysis of the secretion levels of large populations of immune cells. The method is linked with a kinome-wide loss-of-function CRISPR screen, immunomagnetically sorting the cells according to their secretion levels, and the sequencing of their genomes to identify key genetic modifiers of cell secretion. We used the method, which we validated against flow cytometry for cytokines secreted from primary mouse CD4+ (cluster of differentiation 4-positive) T cells, to discover a subgroup of highly co-expressed kinase-coding genes that regulate interferon-gamma secretion by these cells. We validated the function of the kinases identified using RNA interference, CRISPR knockouts and kinase inhibitors and confirmed the druggability of selected kinases via the administration of a kinase inhibitor in an animal model of colitis. The technique may facilitate the discovery of regulatory mechanisms for immune-cell activation and of therapeutic targets for autoimmune diseases.

Apta FastZ: An Algorithm for the Rapid Identification of Aptamers with Defined Binding Affinities.

Real-time biomolecular monitoring requires biosensors based on affinity reagents, such as aptamers, with moderate to low affinities for the best binding dynamics and signal gain. We recently reported Pro-SELEX, an approach that utilizes parallelized SELEX and high-content bioinformatics for the selection of aptamers with predefined binding affinities. The Pro-SELEX pipeline relies on an algorithm, termed AptaZ, that can predict the binding affinities of selected aptamers. The original AptaZ algorithm is computationally complex and slows the overall throughput of Pro-SELEX. Here, we present Apta FastZ, a rapid equivalent of AptaZ. The Apta FastZ algorithm considers the spare nature of the sequences from SELEX and is coded to avoid unnecessary comparison between sequences. As a result, Apta FastZ achieved a 10 to 40-fold faster computing speed compared to the original AptaZ algorithm while maintaining identical outcomes, allowing the bioinformatics to be completed within 1-10 h for large-scale data sets. We further validated the affinity of myeloperoxidase aptamers predicted by Apta FastZ by experiments and observed a high level of linear correlation between predicted scores and measured affinities. Taken together, the implementation of Apta FastZ could greatly accelerate the current Pro-SELEX workflow, allowing customized aptamers to be discovered within 3 days using preselected DNA libraries.

A Micropillar Array Based Microfluidic Device for Rare Cell Detection and Single-Cell Proteomics.

Advancements in single-cell-related technologies have opened new possibilities for analyzing rare cells, such as circulating tumor cells (CTCs) and rare immune cells. Among these techniques, single-cell proteomics, particularly single-cell mass spectrometric analysis (scMS), has gained significant attention due to its ability to directly measure transcripts without the need for specific reagents. However, the success of single-cell proteomics relies heavily on efficient sample preparation, as protein loss in low-concentration samples can profoundly impact the analysis. To address this challenge, an effective handling system for rare cells is essential for single-cell proteomic analysis. Herein, we propose a microfluidics-based method that offers highly efficient isolation, detection, and collection of rare cells (e.g., CTCs). The detailed fabrication process of the micropillar array-based microfluidic device is presented, along with its application for CTC isolation, identification, and collection for subsequent proteomic analysis.

A magneto-activated nanoscale cytometry platform for molecular profiling of small extracellular vesicles.

Exosomal PD-L1 (exoPD-L1) has recently received significant attention as a biomarker predicting immunotherapeutic responses involving the PD1/PD-L1 pathway. However, current technologies for exosomal analysis rely primarily on bulk measurements that do not consider the heterogeneity found within exosomal subpopulations. Here, we present a nanoscale cytometry platform NanoEPIC, enabling phenotypic sorting and exoPD-L1 profiling from blood plasma. We highlight the efficacy of NanoEPIC in monitoring anti-PD-1 immunotherapy through the interrogation of exoPD-L1. NanoEPIC generates signature exoPD-L1 patterns in responders and non-responders. In mice treated with PD1-targeted immunotherapy, exoPD-L1 is correlated with tumor growth, PD-L1 burden in tumors, and the immune suppression of CD8+ tumor-infiltrating lymphocytes. Small extracellular vesicles (sEVs) with different PD-L1 expression levels display distinctive inhibitory effects on CD8 + T cells. NanoEPIC offers robust, high-throughput profiling of exosomal markers, enabling sEV subpopulation analysis. This platform holds the potential for enhanced cancer screening, personalized treatment, and therapeutic response monitoring.

Assessing Tumorigenicity in Stem Cell-Derived Therapeutic Products: A Critical Step in Safeguarding Regenerative Medicine.

Stem cells hold promise in regenerative medicine due to their ability to proliferate and differentiate into various cell types. However, their self-renewal and multipotency also raise concerns about their tumorigenicity during and post-therapy. Indeed, multiple studies have reported the presence of stem cell-derived tumors in animal models and clinical administrations. Therefore, the assessment of tumorigenicity is crucial in evaluating the safety of stem cell-derived therapeutic products. Ideally, the assessment needs to be performed rapidly, sensitively, cost-effectively, and scalable. This article reviews various approaches for assessing tumorigenicity, including animal models, soft agar culture, PCR, flow cytometry, and microfluidics. Each method has its advantages and limitations. The selection of the assay depends on the specific needs of the study and the stage of development of the stem cell-derived therapeutic product. Combining multiple assays may provide a more comprehensive evaluation of tumorigenicity. Future developments should focus on the optimization and standardization of microfluidics-based methods, as well as the integration of multiple assays into a single platform for efficient and comprehensive evaluation of tumorigenicity.

Downregulation of XBP1s aggravates lipopolysaccharide-induced inflammation by promoting NF-κB and NLRP3 pathways' activation in goat endometrial epithelial cells.

After delivery, bacterial contamination and uterine tissue degeneration in animals can lead to the development of uterine diseases, such as endometritis, accompanied by endoplasmic reticulum stress (ERS). Increasing evidence suggests that spliced X-box binding protein 1 (XBP1s), a critical component of ERS, is involved in several pathological processes in various organisms. However, the specific molecular mechanisms by which XBP1s mediates the inflammatory response in goat endometrial epithelial cells (gEECs) remain largely unknown. In the present study, XBP1s protein was induced into the nucleus in the lipopolysaccharide (LPS, 5 µg/mL)-induced inflammatory response of gEECs. Lipopolysaccharide-induced expression and nucleation of XBP1s were reduced by the inhibition of Toll-like receptor 4 (TLR4) using TAK-242 (1 µM; a TLR4 inhibitor). Expression and nucleation of XBP1s were similarly reduced when the activity of inositol-requiring enzyme 1α (IRE1α) was inhibited using 4µ8C (10 µM; an IRE1α inhibitor). In addition, inhibition of IRE1a increased IL-1ß, TNF-α, and IL-8 levels and secretion of IL-6 induced by LPS. Notably, phosphorylation of nuclear factor kappa-B (NF-κB) P65 protein and expression of NOD-like receptor thermal protein domain associated protein 3 (NLRP3) were similarly increased. Furthermore, knockdown of XBP1s in gEECs consistently promoted NF-κB P65 protein phosphorylation, NLRP3 protein expression, and inflammatory cytokine secretion. In summary, the current results suggest that in the LPS-induced inflammatory response in gEECs, LPS generates intracellular signaling cascades in gEECs via TLR4, which may promote XBP1s protein expression and nucleation by activating IRE1a. However, downregulation of XBP1s expression exacerbates inflammation by promoting activation of the NF-κB and NLRP3 inflammatory vesicle pathways. These results will potentially contribute to the treatment and prevention of endometritis in ruminants.

Discovery and Characterization of a Myxobacterial Lanthipeptide with Unique Biosynthetic Features and Anti-inflammatory Activity.

The genomes of myxobacteria harbor a variety of biosynthetic gene clusters encoding numerous secondary metabolites, including ribosomally synthesized and post-translationally modified peptides (RiPPs) with diverse chemical structures and biological activities. However, the biosynthetic potential of RiPPs from myxobacteria remains barely explored. Herein, we report a novel myxobacteria lanthipeptide myxococin identified from Myxococcus fulvus. Myxococins represent the first example of lanthipeptides, of which the characteristic multiple thioether rings are installed by employing a Class II lanthipeptide synthetase MfuM and a Class I lanthipeptide cyclase MfuC in a cascaded way. Unprecedentedly, we biochemically characterized the first M61 family aminopeptidase MfuP involved in RiPP biosynthesis, demonstrating that MfuP showed the activity of an endopeptidase activity. MfuP is leader-independent but strictly selective for the multibridge structure of myxococin A and responsible for unwrapping two rings via amide bond hydrolysis, yielding myxococin B. Furthermore, the X-ray crystal structure of MfuP and structural analysis, including active-site mutations, are reported. Finally, myxococins are evaluated to exhibit anti-inflammatory activity in lipopolysaccharide-induced macrophages without detectable cytotoxicity.

A high-dimensional microfluidic approach for selection of aptamers with programmable binding affinities.

Aptamers are being applied as affinity reagents in analytical applications owing to their high stability, compact size and amenability to chemical modification. Generating aptamers with different binding affinities is desirable, but systematic evolution of ligands by exponential enrichment (SELEX), the standard for aptamer generation, is unable to quantitatively produce aptamers with desired binding affinities and requires multiple rounds of selection to eliminate false-positive hits. Here we introduce Pro-SELEX, an approach for the rapid discovery of aptamers with precisely defined binding affinities that combines efficient particle display, high-performance microfluidic sorting and high-content bioinformatics. Using the Pro-SELEX workflow, we were able to investigate the binding performance of individual aptamer candidates under different selective pressures in a single round of selection. Using human myeloperoxidase as a target, we demonstrate that aptamers with dissociation constants spanning a 20-fold range of affinities can be identified within one round of Pro-SELEX.

Deciphering the Biosynthesis of Novel Class I Lanthipeptides from Marine Pseudoalteromonas Reveals a Dehydratase PsfB with Dethiolation Activity.

Lanthipeptides are a representative class of RiPPs that possess characteristic lanthionine and/or methyllanthionine thioether cross-links. The biosynthetic potentials of marine-derived lanthipeptides remain largely unexplored. In this study, we characterized three novel lanthipeptides pseudorosin A-C by heterologous expression of a class I lanthipeptide biosynthetic gene cluster from marine Pseudoalteromonas flavipulchra S16. Interestingly, pseudorosin C contains a large loop spanning 18 amino acid residues, which is rare in lanthipeptides. Unexpectedly, the dehydratase PsfB could catalyze the dethiolation of specific Cys residues in all three core peptides, thereby generating dehydroalanines in the absence of LanC cyclase. To the best of our knowledge, we identified the first member of the LanB dehydratase family to perform glutamylation and subsequent elimination on Cys thiol groups, which likely represents a new bypass for class I lanthipeptide biosynthesis. Furthermore, we employed mutagenesis to determine the important motif of the core peptide for dethiolation activity. Moreover, sequence analysis revealed that PsfB exhibited a distinct phylogenetic distance from the characterized LanBs from Gram-positive bacteria. Our findings, therefore, pave the way for further genome mining of lanthipeptides, novel post-translational modification enzymes from marine Gram-negative bacteria, and bioengineering applications.

Recent Advances in Discovery, Bioengineering, and Bioactivity-Evaluation of Ribosomally Synthesized and Post-translationally Modified Peptides.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are of increasing interest in natural products as well as drug discovery. This empowers not only the unique chemical structures and topologies in natural products but also the excellent bioactivities such as antibacteria, antifungi, antiviruses, and so on. Advances in genomics, bioinformatics, and chemical analytics have promoted the exponential increase of RiPPs as well as the evaluation of biological activities thereof. Furthermore, benefiting from their relatively simple and conserved biosynthetic logic, RiPPs are prone to be engineered to obtain diverse analogues that exhibit distinct physiological activities and are difficult to synthesize. This Review aims to systematically address the variety of biological activities and/or the mode of mechanisms of novel RiPPs discovered in the past decade, albeit the characteristics of selective structures and biosynthetic mechanisms are briefly covered as well. Almost one-half of the cases are involved in anti-Gram-positive bacteria. Meanwhile, an increasing number of RiPPs related to anti-Gram-negative bacteria, antitumor, antivirus, etc., are also discussed in detail. Last but not least, we sum up some disciplines of the RiPPs' biological activities to guide genome mining as well as drug discovery and optimization in the future.

3D Bioprinting for Next-Generation Personalized Medicine.

In the past decade, immense progress has been made in advancing personalized medicine to effectively address patient-specific disease complexities in order to develop individualized treatment strategies. In particular, the emergence of 3D bioprinting for in vitro models of tissue and organ engineering presents novel opportunities to improve personalized medicine. However, the existing bioprinted constructs are not yet able to fulfill the ultimate goal: an anatomically realistic organ with mature biological functions. Current bioprinting approaches have technical challenges in terms of precise cell deposition, effective differentiation, proper vascularization, and innervation. This review introduces the principles and realizations of bioprinting with a strong focus on the predominant techniques, including extrusion printing and digital light processing (DLP). We further discussed the applications of bioprinted constructs, including the engraftment of stem cells as personalized implants for regenerative medicine and in vitro high-throughput drug development models for drug discovery. While no one-size-fits-all approach to bioprinting has emerged, the rapid progress and promising results of preliminary studies have demonstrated that bioprinting could serve as an empowering technology to resolve critical challenges in personalized medicine.

Efficient Delivery of Biological Cargos into Primary Cells by Electrodeposited Nanoneedles via Cell-Cycle-Dependent Endocytosis.

Nanoneedles are a useful tool for delivering exogenous biomolecules to cells. Although therapeutic applications have been explored, the mechanism regarding how cells interact with nanoneedles remains poorly studied. Here, we present a new approach for the generation of nanoneedles, validated their usefulness in cargo delivery, and studied the underlying genetic modulators during delivery. We fabricated arrays of nanoneedles based on electrodeposition and quantified its efficacy of delivery using fluorescently labeled proteins and siRNAs. Notably, we revealed that our nanoneedles caused the disruption of cell membranes, enhanced the expression of cell-cell junction proteins, and downregulated the expression of transcriptional factors of NFκB pathways. This perturbation trapped most of the cells in G2 phase, in which the cells have the highest endocytosis activities. Taken together, this system provides a new model for the study of interactions between cells and high-aspect-ratio materials.

Isolation of tumour-reactive lymphocytes from peripheral blood via microfluidic immunomagnetic cell sorting.

The clinical use of tumour-infiltrating lymphocytes for the treatment of solid tumours is hindered by the need to obtain large and fresh tumour fractions, which is often not feasible in patients with unresectable tumours or recurrent metastases. Here we show that circulating tumour-reactive lymphocytes (cTRLs) can be isolated from peripheral blood at high yield and purity via microfluidic immunomagnetic cell sorting, allowing for comprehensive downstream analyses of these rare cells. We observed that CD103 is strongly expressed by the isolated cTRLs, and that in mice with subcutaneous tumours, tumour-infiltrating lymphocytes isolated from the tumours and rapidly expanded CD8+CD103+ cTRLs isolated from blood are comparably potent and respond similarly to immune checkpoint blockade. We also show that CD8+CD103+ cTRLs isolated from the peripheral blood of patients and co-cultured with tumour cells dissociated from their resected tumours resulted in the enrichment of interferon-γ-secreting cell populations with T-cell-receptor clonotypes substantially overlapping those of the patients' tumour-infiltrating lymphocytes. Therapeutically potent cTRLs isolated from peripheral blood may advance the clinical development of adoptive cell therapies.