Effect of transitioning from conventional cardiac troponin to high-sensitivity cardiac troponin on resource utilization- a single center experience.

BACKGROUND: Compared to conventional cardiac troponin (cTn), the high-sensitivity cardiac troponin (hs-cTn) assay is associated with improved detection of myocardial infarction (MI). METHODS: We performed a descriptive retrospective analysis of resource utilization at Rush University Medical Center over the transition period (July 1, 2021) from a cTn to a hs-cTn assay. Inclusion criteria included emergency department (ED) encounters between January 1 to December 31, 2021, with chief complaints of "chest pain" or "dyspnea" with associated troponin orders. The primary endpoint was the percentage of ED discharges. Secondary endpoints included the number of cardiac studies ordered. Univariable comparisons of these endpoints were performed using Student's t-test for continuous variables and Chi-square tests for binary/categorical variables. RESULTS: A total of 5113 encounters were analyzed. Hs-cTn was associated with an overall increase in ED patient discharges with negative troponin tests (44.1% vs. 29.9%, P < 0.01). In terms of cardiac testing per encounter, hs-cTn was associated with significant increases in the number of troponin tests (1.9 vs. 1.6, P < 0.01), electrocardiograms (3.0 vs. 2.9, P = 0.01), and echocardiograms (0.5 vs. 0.4, P < 0.01). There was a significant decrease in the utilization of stress testing (0.21 vs. 0.26, P < 0.01). There was a significant increase in total coronary angiography use during the hs-cTn period compared to cTn (227/2471 (9.2%) vs. 195/2642 (7.4%), P = 0.02). CONCLUSION: Transitioning from cTn to hs-cTn was associated with significantly increased ED discharges and an increase in troponin tests, ECG, echocardiograms, and coronary angiograms. There was a decrease in the number of stress tests.

Aging Gut Microbiome in Healthy and Unhealthy Aging.

The characteristics of human aging manifest in tissue and organ function decline, heightening susceptibility to age-related ailments, thereby presenting novel challenges to fostering and sustaining healthy longevity. In recent years, an abundance of research on human aging has surfaced. Intriguingly, evidence suggests a pervasive correlation among gut microbiota, bodily functions, and chronic diseases. From infancy to later stages of adulthood, healthy individuals witness dynamic shifts in gut microbiota composition. This microbial community is associated with tissue and organ function deterioration (e.g., brain, bones, muscles, immune system, vascular system) and heightened risk of age-related diseases. Thus, we present a narrative review of the aging gut microbiome in both healthy and unhealthy aging contexts. Additionally, we explore the potential for adjustments to physical health based on gut microbiome analysis and how targeting the gut microbiome can potentially slow down the aging process.

Injectable isoniazid-loaded bone cement based on hydrazone bonds achieving long-term release and decent mechanical properties.

A robust and easily manufactured high-strength and long-term release hydrazone-based isoniazid acrylic (HIA) bone cement is reported. The mechanical strength of HIA bone cement is similar to that of normal polymethyl methacrylate (PMMA) bone cement, far surpassing that of traditional isoniazid-containing antibiotic-loaded bone cement (INH bone cement). Isoniazid is connected to the bone cement through bioorthogonal hydrazone chemistry, and it possesses release properties superior to those of INH bone cement, allowing for the sustained release of isoniazid for up to 12 weeks. In vivo and in vitro studies also indicate that HIA cement exhibits better biocompatibility than INH bone cement. The results of this study not only signify progress in the realm of antimicrobial bone cement for addressing bone tuberculosis but also enhance our capacity to create and comprehend high-performing antimicrobial bone cement.

Transcriptional profile and immune infiltration in colorectal cancer reveal the significance of inducible T-cell costimulator as a crucial immune checkpoint molecule.

BACKGROUND: Emergence of novel immuno-therapeutics has shown promising improvement in the clinical outcome of colorectal cancer (CRC). OBJECTIVE: To identify robust immune checkpoints based on expression and immune infiltration profiles of clinical CRC samples. METHODS: One dataset from The Cancer Genome Atlas database and two from Gene Expression Omnibus were independently employed for the analysis. Genes associated with overall survival were identified, and distribution of each immune checkpoint with respect to different clinical features was determined to explore key immune checkpoints. Multiple staining methods were used to verify the correlation between key immune checkpoint ICOS and clinical pathological features. Differentially expressed mRNA and long non-coding RNA (lncRNA) were then detected for gene set enrichment analysis and gene set variation analysis to investigate the differentially enriched biological processes between low- and high-expression groups. Significant immune-related mRNAs and lncRNA were subjected to competing endogenous RNA (ceRNA) network analysis. Correlation of inducible T-cell costimulator (ICOS) and top 10 genes in ceRNA network were further considered for validation. RESULTS: ICOS was identified from 14 immune checkpoints as the most highly correlated gene with survival and clinical features in CRC. The expression of ICOS protein in the poorly differentiated group was lower than that in the moderately differentiated group, and the expression in different pathological stages was significant. In addition, the expressions of ICOS were negatively correlated with Ki67. A conspicuous number of immune-related pathways were enriched in differentially expressed genes in the ICOS high- and low-expression groups. Integration with immune infiltration data revealed a multitude of differentially expressed immune-related genes enriched for ceRNA network. Furthermore, expression of top 10 genes investigated from ceRNA network showed high correlation with ICOS. CONCLUSION: ICOS might serve as a robust immune checkpoint for prognosis with several genes being potential targets of ICOS-directed immunotherapy in CRC.

Advances in single-cell sequencing technology in microbiome research.

With the rapid development of histological techniques and the widespread application of single-cell sequencing in eukaryotes, researchers desire to explore individual microbial genotypes and functional expression, which deepens our understanding of microorganisms. In this review, the history of the development of microbial detection technologies was revealed and the difficulties in the application of single-cell sequencing in microorganisms were dissected as well. Moreover, the characteristics of the currently emerging microbial single-cell sequencing (Microbe-seq) technology were summarized, and the prospects of the application of Microbe-seq in microorganisms were distilled based on the current development status. Despite its mature development, the Microbe-seq technology was still in the optimization stage. A retrospective study was conducted, aiming to promote the widespread application of single-cell sequencing in microorganisms and facilitate further improvement in the technology.

Investigating the in vitro antibacterial efficacy of composite bone cement incorporating natural product-based monomers and gentamicin.

OBJECTIVE: The objective of this study is to investigate the impact of four natural product extracts, namely, aloe-emodin, quercetin, curcumin, and tannic acid, on the in vitro bacteriostatic properties and biocompatibility of gentamicin-loaded bone cement and to establish an experimental groundwork supporting the clinical utility of antibiotic-loaded bone cements (ALBC). METHODS: Based on the components, the bone cement samples were categorized as follows: the gentamicin combined with aloe-emodin group, the gentamicin combined with quercetin group, the gentamicin combined with curcumin group, the gentamicin combined with tannic acid group, the gentamicin group, the aloe-emodin group, the quercetin group, the curcumin group, and the tannic acid group. Using the disk diffusion test, we investigated the antibacterial properties of the bone cement material against Staphylococcus aureus (n = 4). We tested cell toxicity and proliferation using the cell counting kit-8 (CCK-8) and examined the biocompatibility of bone cement materials. RESULTS: The combination of gentamicin with the four natural product extracts resulted in significantly larger diameters of inhibition zones compared to gentamicin alone, and the difference was statistically significant (P < 0.05). Except for the groups containing tannic acid, cells in all other groups showed good proliferation across varying time intervals without displaying significant cytotoxicity (P < 0.05). CONCLUSION: In this study, aloe-emodin, quercetin, curcumin, and tannic acid were capable of enhancing the in vitro antibacterial performance of gentamicin-loaded bone cement against S. aureus. While the groups containing tannic acid displayed moderate cytotoxicity in in vitro cell culture, all other groups showed no discernible cytotoxic effects.

The application of impantable sensors in the musculoskeletal system: a review.

As the population ages and the incidence of traumatic events rises, there is a growing trend toward the implantation of devices to replace damaged or degenerated tissues in the body. In orthopedic applications, some implants are equipped with sensors to measure internal data and monitor the status of the implant. In recent years, several multi-functional implants have been developed that the clinician can externally control using a smart device. Experts anticipate that these versatile implants could pave the way for the next-generation of technological advancements. This paper provides an introduction to implantable sensors and is structured into three parts. The first section categorizes existing implantable sensors based on their working principles and provides detailed illustrations with examples. The second section introduces the most common materials used in implantable sensors, divided into rigid and flexible materials according to their properties. The third section is the focal point of this article, with implantable orthopedic sensors being classified as joint, spine, or fracture, based on different practical scenarios. The aim of this review is to introduce various implantable orthopedic sensors, compare their different characteristics, and outline the future direction of their development and application.

The Role of CD8A in the Immune Microenvironment of Breast Cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer (BC), and it is often associated with a high tumor grade, a younger age at diagnosis, and a low survival rate. Conventional endocrine and anti-HER-2 therapies are usually ineffective against TNBC, creating treatment challenges and resulting in a poor prognosis. Hence, new targets and treatment strategies for TNBC are urgently required. METHODS: The GSE102818 dataset was used to identify differentially expressed genes (DEGs) between primary BC and metastatic BC lesions. The Cancer Genome Atlas and the cBioPortal platform were employed to explore mutations in candidate genes. Utilizing the Tumor IMmune Estimation Resource (TIMER), the relationship between the expression of candidate genes and immune cell infiltration was assessed. Additionally, the cell-specific expression of the candidate genes was examined in the immune microenvironment of primary BC and metastatic BC lesions using the single-cell RNA sequencing (scRNA-seq) datasets GSE118389 and GSE202695. Finally, the protein expression of the candidate genes in clinical TNBC samples was evaluated. RESULTS: CD8A was identified as a hub gene in the DEG network and was found to be down-regulated in metastatic BC lesions. CD8A expression was highly correlated with the infiltration of CD8+ T cells, and elevated CD8A expression was correlated with improved survival. Interestingly, scRNA-seq data revealed that CD8A was down-regulated in CD8+ T cells in the immune microenvironment of metastatic BC lesions. Finally, the evaluation of clinical samples confirmed the down-regulation of CD8A in the immune microenvironment of BC lung metastases. CONCLUSIONS: In patients with metastatic TNBC, high levels of CD8A (especially in the immune microenvironment) are associated with a good prognosis.

GraphCL-DTA: A Graph Contrastive Learning With Molecular Semantics for Drug-Target Binding Affinity Prediction.

Drug-target binding affinity prediction plays an important role in the early stages of drug discovery, which can infer the strength of interactions between new drugs and new targets. However, the performance of previous computational models is limited by the following drawbacks. The learning of drug representation relies only on supervised data without considering the information in the molecular graph itself. Moreover, most previous studies tended to design complicated representation learning modules, while uniformity used to measure representation quality is ignored. In this study, we propose GraphCL-DTA, a graph contrastive learning with molecular semantics for drug-target binding affinity prediction. This graph contrastive learning framework replaces the dropout-based data augmentation strategy by performing data augmentation in the embedding space, thereby better preserving the semantic information of the molecular graph. A more essential and effective drug representation can be learned through this graph contrastive framework without additional supervised data. Next, we design a new loss function that can be directly used to adjust the uniformity of drug and target representations. By directly optimizing the uniformity of representations, the representation quality of drugs and targets can be improved. The effectiveness of the above innovative elements is verified on two real datasets, KIBA and Davis. Compared with the GraphDTA model, the relative improvement of the GraphCL-DTA model on the two datasets is 2.7% and 4.5%. The graph contrastive learning framework and uniformity function in the GraphCL-DTA model can be embedded into other computational models as independent modules to improve their generalization capability.

Integration analysis of PLAUR as a sunitinib resistance and macrophage related biomarker in ccRCC, an in silicon and experimental study.

Sunitinib remains the preferred systemic treatment option for specific patients with advanced RCC who are ineligible for immune therapy. However, it's essential to recognize that Sunitinib fails to elicit a favourable response in all patients. Moreover, most patients eventually develop resistance to Sunitinib. Therefore, identifying new targets associated with Sunitinib resistance is crucial. Utilizing multiple datasets from public cohorts, we conducted an exhaustive analysis and identified a total of 8 microRNAs and 112 mRNAs displaying significant expression differences between Sunitinib responsive and resistant groups. A particular set of six genes, specifically NIPSNAP1, STK40, SDC4, NEU1, TBC1D9, and PLAUR, were identified as highly significant via WGCNA. To delve deeper into the resistance mechanisms, we performed additional investigations using cell, molecular, and flow cytometry tests. These studies confirmed PLAUR's pivotal role in fostering Sunitinib resistance, both in vitro and in vivo. Our findings suggest that PLAUR could be a promising therapeutic target across various cancer types. In conclusion, this investigation not only uncovers vital genes and microRNAs associated with Sunitinib resistance in RCC but also introduces PLAUR as a prospective therapeutic target for diverse cancers. The outcomes contribute to advancing personalized healthcare and developing superior therapeutic strategies.Communicated by Ramaswamy H. Sarma.

Efficacy and safety of Qingda granule versus valsartan capsule in Chinese grade 1 hypertensive patients with low-moderate risk: A randomized, double-blind, double dummy, non-inferiority, multi-center trial.

BACKGROUND: The efficacy and safety of Qingda granule (QDG) in managing blood pressure (BP) among grade 1 hypertensive patients with low-moderate risk remain uncertain. METHODS: In the randomized, double-blind, double dummy, non-inferiority and multicenter trial, 552 patients with grade 1 hypertension at low-moderate risk were assigned at a ratio of 1:1 to receive either QDG or valsartan for 4 weeks, followed up by a subsequent 4 weeks. RESULTS: Post-treatment, clinic systolic/diastolic BPs (SBP/DBP) were reduced by a mean change of 9.18/4.04 mm Hg in the QDG group and 9.85/5.05 mm Hg in the valsartan group (SBP P = 0.47, DBP P = 0.16). Similarly, 24-hour, daytime and nighttime BPs were proportional in both groups (P > 0.05) after 4 weeks treatment. After discontinuing medications for 4 weeks, the mean reduction of clinic SBP/DBP were 0.29/0.57 mm Hg in the QDG group compared to -1.59/-0.48 mm Hg in the valsartan group (SBP P = 0.04, DBP P = 0.04). Simultaneously, the 24-hour SBP/DBP were reduced by 0.9/0.31 mm Hg in the QDG group and -1.66/-1.08 mm Hg in the valsartan group (SBP P = 0.006, DBP P = 0.02). And similar results were observed regarding the outcomes of daytime and nighttime BPs. There was no difference in occurrence of adverse events between two groups (P > 0.05). CONCLUSION: QDG proves to be efficacious for grade 1 hypertension at a low-to-medium risk, even after discontinuation of the medication for 4 weeks. These findings provide a promising option for managing grade 1 hypertension and suggest the potential for maintaining stable BP through intermittent administration of QDG. TRIAL REGISTRATION: ChiCTR2000033890.

Soluble urokinase plasminogen activator receptor and cardiotoxicity in doxorubicin-treated breast cancer patients: a prospective exploratory study.

BACKGROUND: Soluble urokinase plasminogen activator receptor is an inflammatory biomarker that may prognosticate cardiovascular outcomes. We sought to determine the associations between soluble urokinase plasminogen activator receptor and established markers of cardiotoxicity in breast cancer patients receiving doxorubicin. METHODS: We conducted a prospective cohort study of women with newly diagnosed breast cancer receiving standard-dose doxorubicin (240 mg/m2) at Rush University Medical Center and Rush Oak Park Hospital (Chicago, IL) between January 2017 and May 2019. Left ventricular ejection fraction, global longitudinal strain, and cardiac biomarkers (N-terminal prohormone B-type natriuretic peptide, troponin-I, and high-sensitivity C-reactive protein) were measured at baseline and at intervals up to 12-month follow-up after end of treatment. The associations between soluble urokinase plasminogen activator receptor and these endpoints were evaluated using multivariable mixed effects linear regression. RESULTS: Our study included 37 women (mean age 47.0 ± 9.3 years, 60% white) with a median baseline soluble urokinase plasminogen activator receptor level of 2.83 ng/dL. No participant developed cardiomyopathy based on serial echocardiography by one-year follow-up. The median percent change in left ventricular strain was -4.3% at 6-month follow-up and absolute changes in cardiac biomarkers were clinically insignificant. There were no significant associations between soluble urokinase plasminogen activator receptor and these markers of cardiotoxicity (all p > 0.05). CONCLUSIONS: In this breast cancer cohort, doxorubicin treatment was associated with a very low risk for cardiotoxicity. Across this narrow range of clinical endpoints, soluble urokinase plasminogen activator receptor was not associated with markers of subclinical cardiotoxicity. Further studies are needed to clarify the prognostic utility of soluble urokinase plasminogen activator receptor in doxorubicin-associated cardiomyopathy and should include a larger cohort of leukemia and lymphoma patients who receive higher doses of doxorubicin.

METformin for the MINimization of Geographic Atrophy Progression (METforMIN): A Randomized Trial.

Purpose: Metformin use has been associated with a decreased risk of age-related macular degeneration (AMD) progression in observational studies. We aimed to evaluate the efficacy of oral metformin for slowing geographic atrophy (GA) progression. Design: Parallel-group, multicenter, randomized phase II clinical trial. Participants: Participants aged ≥ 55 years without diabetes who had GA from atrophic AMD in ≥ 1 eye. Methods: We enrolled participants across 12 clinical centers and randomized participants in a 1:1 ratio to receive oral metformin (2000 mg daily) or observation for 18 months. Fundus autofluorescence imaging was obtained at baseline and every 6 months. Main Outcome Measures: The primary efficacy endpoint was the annualized enlargement rate of the square root-transformed GA area. Secondary endpoints included best-corrected visual acuity (BCVA) and low luminance visual acuity (LLVA) at each visit. Results: Of 66 enrolled participants, 34 (57 eyes) were randomized to the observation group and 32 (53 eyes) were randomized to the treatment group. The median follow-up duration was 13.9 and 12.6 months in the observation and metformin groups, respectively. The mean ± standard error annualized enlargement rate of square root transformed GA area was 0.35 ± 0.04 mm/year in the observation group and 0.42 ± 0.04 mm/year in the treatment group (risk difference = 0.07 mm/year, 95% confidence interval = -0.05 to 0.18 mm/year; P = 0.26). The mean ± standard error decline in BCVA was 4.8 ± 1.7 letters/year in the observation group and 3.4 ± 1.1 letters/year in the treatment group (P = 0.56). The mean ± standard error decline in LLVA was 7.3 ± 2.5 letters/year in the observation group and 0.8 ± 2.2 letters/year in the treatment group (P = 0.06). Fourteen participants in the metformin group experienced nonserious adverse events related to metformin, with gastrointestinal side effects as the most common. No serious adverse events were attributed to metformin. Conclusions: The results of this trial as conducted do not support oral metformin having effects on reducing the progression of GA. Additional placebo-controlled trials are needed to explore the role of metformin for AMD, especially for earlier stages of the disease. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Implicit Posteriori Parameter Distribution Optimization in Reinforcement Learning.

Efficient and intelligent exploration remains a major challenge in the field of deep reinforcement learning (DRL). Bayesian inference with a distributional representation is usually an effective way to improve the exploration ability of the RL agent. However, when optimizing Bayesian neural networks (BNNs), most algorithms need to specify an explicit parameter distribution such as a multivariate Gaussian distribution. This may reduce the flexibility of model representation and affect the algorithm performance. Therefore, to improve sample efficiency and exploration based on Bayesian methods, we propose a novel implicit posteriori parameter distribution optimization (IPPDO) algorithm. First, we adopt a distributional perspective on the parameter and model it with an implicit distribution, which is approximated by generative models. Each model corresponds to a learned latent space, providing structured stochasticity for each layer in the network. Next, to make it possible to optimize an implicit posteriori parameter distribution, we build an energy-based model (EBM) with value function to represent the implicit distribution which is not constrained by any analytic density function. Then, we design a training algorithm based on amortized Stein variational gradient descent (SVGD) to improve the model learning efficiency. We compare IPPDO with other prevailing DRL algorithms on the OpenAI Gym, MuJoCo, and Box2D platforms. Experiments on various tasks demonstrate that the proposed algorithm can represent the parameter uncertainty implicitly for a learned policy and can consistently outperform competing approaches.

CCL2 Knockdown Attenuates Inflammatory Response After Spinal Cord Injury Through the PI3K/Akt Signaling Pathway: Bioinformatics Analysis and Experimental Validation.

Spinal cord injury (SCI) is a common clinical problem in orthopedics with a lack of effective treatments and drug targets. In the present study, we performed bioinformatic analysis of SCI datasets GSE464 and GSE45006 in the Gene Expression Omnibus (GEO) public database and experimentally validated CCL2 expression in an animal model of SCI. This was followed by stimulation of PC-12 cells using hydrogen peroxide to construct a cellular model of SCI. CCL2 expression was knocked down using small interfering RNA (si-CCL2), and PI3K signaling pathway inhibitors and activators were used to validate and observe the changes in downstream inflammation. Through data mining, we found that the inflammatory chemokine CCL2 and PI3K/Akt signaling pathways after SCI expression were significantly increased, and after peroxide stimulation of PC-12 cells with CCL2 knockdown, their downstream cellular inflammatory factor levels were decreased. The PI3K/Akt signaling pathway was blocked by PI3K inhibitors, and the downstream inflammatory response was suppressed. In contrast, when PI3K activators were used, the inflammatory response was enhanced, indicating that the CCL2-PI3K/Akt signaling pathway plays a key role in the regulation of the inflammatory response. This study revealed that the inflammatory chemokine CCL2 can regulate the inflammatory response of PC-12 cells through the PI3K/Akt signaling pathway, and blocking the expression of the inflammatory chemokine CCL2 may be a promising strategy for the treatment of secondary injury after SCI.

Classification of Colorectal Cancer Subtypes Based on Endoplasmic Reticulum Stress.

INTRODUCTION: Endoplasmic reticulum stress (ERS) is associated with the occurrence and development of colorectal cancer (CRC). METHODS: One thousand nine CRC samples and 3 ERS gene sets from GEO database were used to screen and validate genes related to stage and prognosis of CRC. Twenty thousand five hundred thirty samples from the TCGA database validated the ERS genes related to prognosis. PPI network construction and coexpression analysis were used to investigate the correlation of genes. ConsensusClusterPlus analysis was used to classify CRC subtypes. Cox regression and the LASSO algorithm were used to screen ERS genes related to prognosis. HE staining, immunohistochemical staining, and RT-qPCR of 50 owner-central samples were used to verify the genes. The ERscore model was constructed based on the ERS genes related to prognosis. The nomogram model was used to verify that different subtypes of CRC patients have different prognosis. RESULTS: Fifty ERS differentially expressed genes related to CRC stage and 8 ERS model genes related to prognosis were screened. Three subtypes of CRC were classified based on the former 50 genes. The clinical characteristics were significantly different among the subtypes. The ERscore model was constructed based on the latter 8 genes, and its accuracy was verified by clinical samples. Finally, the nomogram was constructed based on ERscore, age, and CRC stage, and the accuracy of the nomogram prediction was verified. CONCLUSION: ERS-related genes can be used as classification criteria for CRC, and the related clinical characteristics of different CRC subtypes are different.

Planting gold nanoflower for harvesting reproducible SERS substrate.

Surface-enhanced Raman scattering (SERS) is an ultrasensitive analytical method which has been applied in many fields, and the reproducibility of the substrate is important for reliable SERS analysis. In present work, an innovative method inspired by the flower planting process is put forward to acquire gold nanoflower (AuNF) SERS substrate. Three steps (digging holes, sowing the gold nanoseeds and seeds grow into gold nanoflowers) are included in the substrate fabrication process, and the influence of preparing conditions (like reacting time and Na3Au(SO3)2 concentration) on the substrate morphology and SERS performance are investigated. The acquired AuNF substrate not only exhibits good SERS performance but also possesses excellent reproducibility while being used to detect the rhodamine 6G (R6G) molecular. The relative standard deviation (RSD) of Raman signals among substrates acquired in distinct batches (substrate-to-substrate) is as low as 6.67 %. Since the AuNF substrate is prepared by the wet chemistry route based on seed-mediated growth and there are no expensive reagents or complicated process used, the new process to obtain AuNF substrate is cost-effective and easy to scale up.

Injectable Devices for Delivery of Liquid or Solid Protein Formulations.

Sustained delivery of protein therapeutics remains a largely unsolved problem across anatomic locations. Miniaturized devices that can provide sustained delivery of protein formulations have the potential to address this challenge via minimally invasive administration. In particular, methodologies that can optimize protein formulation independent of device manufacture have the greatest potential to provide a platform suitable for wide applications. The techniques developed here demonstrate the fabrication of tubular devices for sustained release of protein therapeutics. Utilizing a dip-casting process, fine-scale tubes can be reliably produced with wall thickness down to 30 µm. Techniques were developed that enabled effective loading of either solid or liquid formulations, while maintaining a cylindrical form-factor compatible with placement in a 22-gauge needle. Further, highly compacted protein pellets that approach the expected density of the raw materials were produced with a diameter (∼300 µm) suitable for miniaturized devices. Release from a solid-loaded device was capable of sustaining release of a model protein in excess of 400 days. Given significant interest in ocular applications, intravitreal injection was demonstrated in a rabbit model with these devices. In addition, to simulate repeated injections in ocular applications, serial intravitreal injection of two devices in a rabbit model demonstrated acceptable ocular safety without significant intraocular inflammation from clinical exam and histology.

Biomembrane-Derived Nanoparticles in Alzheimer's Disease Therapy: A Comprehensive Review of Synthetic Lipid Nanoparticles and Natural Cell-Derived Vesicles.

Current therapies for Alzheimer's disease used in the clinic predominantly focus on reducing symptoms with limited capability to control disease progression; thus, novel drugs are urgently needed. While nanoparticles (liposomes, high-density lipoprotein-based nanoparticles) constructed with synthetic biomembranes have shown great potential in AD therapy due to their excellent biocompatibility, multifunctionality and ability to penetrate the BBB, nanoparticles derived from natural biomembranes (extracellular vesicles, cell membrane-based nanoparticles) display inherent biocompatibility, stability, homing ability and ability to penetrate the BBB, which may present a safer and more effective treatment for AD. In this paper, we reviewed the synthetic and natural biomembrane-derived nanoparticles that are used in AD therapy. The challenges associated with the clinical translation of biomembrane-derived nanoparticles and future perspectives are also discussed.