Tailoring lipid nanoparticles for T-cell targeting in allergic asthma: Insights into efficacy and specificity.

Asthma impacts over 300 million patients globally, with significant health implications, especially in cases of its allergic subtype. The disease is characterized by a complex interplay of airway inflammation and immune responses, often mediated by Th2 cell-related cytokines. In this study, we engineered lipid nanoparticles (LNPs) to specifically deliver therapeutic siRNA via the transferrin receptor to T cells. Strain-promoted azide-alkyne cycloaddition (SPAAC) was employed for the conjugation of transferrin ligands to PEGylated lipids in the LNPs, with the goal of enhancing cellular uptake and gene knockdown. The obtained LNPs exhibited characteristics that make them suitable for pulmonary delivery. Using methods such as nanoparticle tracking analysis (NTA) and enzyme-linked immunosorbent assay (ELISA), we determined the average number of transferrin molecules bound to individual LNPs. Additionally, we found that cellular uptake was ligand-dependent, achieving a GATA3 knockdown of more than 50% in relevant in vitro and ex vivo models. Notably, our findings highlight the limitations inherent to modifying the surface of LNPs, particularly with regard to their targeting capabilities. This work paves the way for future research aimed at optimizing targeted LNPs for the treatment of immunologic diseases such as allergic asthma.

Characteristics of and Variation in Suicide Mortality Related to Retirement during the Great Recession: Perspectives from the National Violent Death Reporting System.

BACKGROUND AND OBJECTIVES: Suicide rates typically increase during recessions. However, few studies have explored how recessions impact risk among older adults nearing retirement. This study used a large suicide mortality registry to characterize and quantify suicide related to retirement during the Great Recession (GR). RESEARCH DESIGN AND METHODS: Data come from the National Violent Death Reporting System (NVDRS, 2004-2017; N=53,298 suicide deaths ages ≥50). We analyzed the text narratives (i.e., descriptions of the most salient circumstances to each suicide) of these decedents using natural language processing (NLP) to identify cases that were "retirement-related" (RR, e.g., anticipating, being unable to, or recently retiring). We used time-series analysis to quantify variation in RR over the GR, and compared these trends to retirees (i.e., decedents whose occupation was "retired") and all decedents aged ≥50. We used content and network analysis to characterize themes represented in the narratives. RESULTS: There were 878 RR cases (1.6% of suicides aged ≥50) identified by the NLP model; only 52% of these cases were among retirees. RR cases were younger (62 vs. 75 years) and more educated (41.5% vs 24.5% college degree) than retirees. The rate of RR suicide was positively associated with indicators of the GR (e.g., short-term unemployment R2=0.70, p=0.024), but economic indicators were not correlated with the suicide rate among retirees or older adults in general. Economic issues were more central to the narratives of RR cases during the GR compared to other periods. DISCUSSION AND IMPLICATIONS: Recessions shape suicide risk related to retirement transitions.

Efficient and Targeted siRNA Delivery to M2 Macrophages by Smart Polymer Blends for M1 Macrophage Repolarization as a Promising Strategy for Future Cancer Treatment.

Cancer remains an issue on a global scale. It is estimated that nearly 10 million people succumbed to cancer worldwide in 2020. New treatment options are urgently needed. A promising approach is a conversion of tumor-promoting M2 tumor-associated macrophages (TAMs) as part of the tumor microenvironment to tumor-suppressive M1 TAMs by small interfering RNA (siRNA). In this work, we present a well-characterized polymeric nanocarrier system capable of targeting M2 TAMs by a ligand-receptor interaction. Therefore, we developed a blended PEI-based polymeric nanoparticle system conjugated with mannose, which is internalized after interaction with macrophage mannose receptors (MMRs), showing low cytotoxicity and negligible IL-6 activation. The PEI-PCL-PEI (5 kDa-5 kDa-5 kDa) and Man-PEG-PCL (2 kDa-2 kDa) blended siRNA delivery system was optimized for maximum targeting capability and efficient endosomal escape by evaluation of different polymer and N/P ratios. The nanoparticles were formulated by surface acoustic wave-assisted microfluidics, achieving a size of ∼80 nm and a zeta potential of approximately +10 mV. Special attention was given to the endosomal escape as the so-called bottleneck of RNA drug delivery. To estimate the endosomal escape capability of the nanocarrier system, we developed a prediction method by evaluating the particle stability via the inflection temperature. Our predictions were then verified in an in vitro setting by applying confocal microscopy. For cellular experiments, however, human THP-1 cells were polarized to M2 macrophages by cytokine treatment and validated through MMR expression. To show the efficiency of the nanoparticle system, GAPDH and IκBα knockdown was performed in the presence or absence of an MMR blocking excess of mannan. Cellular uptake, GAPDH knockdown, and NF-κB western blot confirmed efficient mannose targeting. Herein, we presented a well-characterized nanoparticle delivery system and a promising approach for targeting M2 macrophages by a mannose-MMR interaction.

Pulmonary siRNA Delivery with Sophisticated Amphiphilic Poly(Spermine Acrylamides) for the Treatment of Lung Fibrosis.

RNA interference (RNAi) is an efficient strategy to post-transcriptionally silence gene expression. While all siRNA drugs on the market target the liver, the lung offers a variety of currently undruggable targets, which can potentially be treated with RNA therapeutics. To achieve this goal, the synthesis of poly(spermine acrylamides) (P(SpAA) is reported herein. Polymers are prepared via polymerization of N-acryloxysuccinimide (NAS) and afterward this active ester is converted into spermine-based pendant groups. Copolymerizations with decylacrylamide are employed to increase the hydrophobicity of the polymers. After deprotection, polymers show excellent siRNA encapsulation to obtain perfectly sized polyplexes at very low polymer/RNA ratios. In vitro 2D and 3D cell culture, ex vivo and in vivo experiments reveal superior properties of amphiphilic spermine-copolymers with respect to delivery of siRNA to lung cells in comparison to commonly used lipid-based transfection agents. In line with the in vitro results, siRNA delivery to human lung explants confirm more efficient gene silencing of protease-activated receptor 2 (PAR2), a G protein-coupled receptor involved in fibrosis. This study reveals the importance of the balance between efficient polyplex formation, cellular uptake, gene knockdown, and toxicity for efficient siRNA delivery in vitro, in vivo, and in fibrotic human lung tissue ex vivo.

Evaluation of the effects of storage conditions on spray-dried siRNA-LNPs before and after subsequent drying.

In an ideal world, pharmaceutical drugs would have infinite shelf life, no susceptibility to degradation, chemical reactions or loss of efficacy. In reality, these processes occur, however, making it desirable to extend a drugs' shelf life. Nucleic acid-based drugs are most commonly stored as aqueous suspension where they are vulnerable to microbial growth and degradation processes. Drying procedures, such as lyophilization and spray drying, help to reduce the products' residual moisture while increasing the products' shelf life and stability. The present study was designed to evaluate 90 days of storage of spray-dried siRNA-lipid nanoparticles (LNPs) at 4 °C and 25 °C. An updated Onpattro® composition modified with a positively charged helper lipid was used as the LNP carrier system. In an attempt to further reduce the residual moisture of our previously reported formulations, all LNP samples were subjected to a secondary drying step in the spray drying tower for 20 min. The measurement of physicochemical properties of spray-dried and subsequently dried LNPs resulted in sizes of 180 nm, PDI values of 0.1-0.15 and zeta potentials of + 3 mV. Spray drying resulted in residual moisture levels of 3.6-4 % and was reduced by subsequent drying to 2.8-3.1 %. Aerodynamic properties after storage showed discrepancies depending on the storage conditions. MMADs remained at 2.8 µm when stored at 4 °C, whereas an increase to 5 µm at 25 °C was observed. Subsequent drying led to sizes of 3.6-3.8 µm, independent of the storage conditions. Spray-dried LNPs maintained bioactivity resulting in > 95 % protein downregulation and confirming the lack of cytotoxic effects in a lung adenocarcinoma cell line. Furthermore, the spray-dried and subsequently dried LNPs stored for 3 months at 4 °C and 25 °C achieved up to 50 % gene silencing of the house-keeping gene GAPDH after deposition on the mucus layer of Calu-3 cells. This study confirms the stability of spray-dried and subsequently dried LNPs over at least 90 days at 4 °C and 25 °C emphasizing the potential of dry powder inhalation of RNA-loaded LNPs as a therapy option for pulmonary diseases.

Protein corona investigations of polyplexes with varying hydrophobicity - From method development to in vitro studies.

In the field of non-viral drug delivery, polyplexes (PXs) represent an advanced investigated and highly promising tool for the delivery of nucleic acids. Upon encountering physiological fluids, they adsorb biological molecules to form a protein corona (PC), that influence PXs biodistribution, transfection efficiencies and targeting abilities. In an effort to understand protein - PX interactions and the effect of PX material on corona composition, we utilized cationic branched 10 kDa polyethyleneimine (b-PEI) and a hydrophobically modified nylon-3 polymer (NM0.2/CP0.8) within this study to develop appropriate methods for PC investigations. A centrifugation procedure for isolating hard corona - PX complexes (PCPXs) from soft corona proteins after incubating the PXs in fetal bovine serum (FBS) for PC formation was successfully optimized and the identification of proteins by a liquid chromatography-tandem mass spectrometry (LC-MS-MS) method clearly demonstrated that the PC composition is affected by the underlying PXs material. With regard to especially interesting functional proteins, which might be able to induce active targeting effects, several candidates could be detected on b-PEI and NM0.2/CP0.8 PXs. These results are of high interest to better understand how the design of PXs impacts the PC composition and subsequently PCPXs-cell interactions to enable precise adjustment of PXs for targeted drug delivery.

Application of wastewater-based surveillance and copula time-series model for COVID-19 forecasts.

The objective of this study was to develop a novel copula-based time series (CTS) model to forecast COVID-19 cases and trends based on wastewater SARS-CoV-2 viral load and clinical variables. Wastewater samples were collected from wastewater pumping stations in five sewersheds in the City of Chesapeake VA. Wastewater SARS-CoV-2 viral load was measured using reverse transcription droplet digital PCR (RT-ddPCR). The clinical dataset included daily COVID-19 reported cases, hospitalization cases, and death cases. The CTS model development included two steps: an autoregressive moving average (ARMA) model for time series analysis (step I), and an integration of ARMA and a copula function for marginal regression analysis (step II). Poisson and negative binomial marginal probability densities for copula functions were used to determine the forecasting capacity of the CTS model for COVID-19 forecasts in the same geographical area. The dynamic trends predicted by the CTS model were well suited to the trend of the reported cases as the forecasted cases from the CTS model fell within the 99 % confidence interval of the reported cases. Wastewater SARS CoV-2 viral load served as a reliable predictor for forecasting COVID-19 cases. The CTS model provided robust modeling to predict COVID-19 cases.

Targeted GATA3 knockdown in activated T cells via pulmonary siRNA delivery as novel therapy for allergic asthma.

GATA3 gene silencing in activated T cells displays a promising option to early-on undermine pathological pathways in the disease formation of allergic asthma. The central transcription factor of T helper 2 (Th2) cell cytokines IL-4, IL-5, and IL-13 plays a major role in immune and inflammatory cascades underlying asthmatic processes in the airways. Pulmonary delivery of small interfering RNAs (siRNA) to induce GATA3 knockdown within disease related T cells of asthmatic lungs via RNA interference (RNAi) presents an auspicious base to realize this strategy, however, still faces some major hurdles. Main obstacles for successful siRNA delivery in general comprise stability and targeting issues, while in addition the transfection of T cells presents a particularly challenging task itself. In previous studies, we have developed and advanced an eligible siRNA delivery system composed of polyethylenimine (PEI) as polycationic carrier, transferrin (Tf) as targeting ligand and melittin (Mel) as endosomolytic agent. Resulting Tf-Mel-PEI polyplexes exhibited ideal characteristics for targeted siRNA delivery to activated T cells and achieved efficient and sequence-specific gene knockdown in vitro. In this work, the therapeutic potential of this carrier system was evaluated in an optimized cellular model displaying the activated status of asthmatic T cells. Moreover, a suitable siRNA sequence combination was found for effective gene silencing of GATA3. To confirm the translatability of our findings, Tf-Mel-PEI polyplexes were additionally tested ex vivo in activated human precision-cut lung slices (PCLS). Here, the formulation showed a safe profile as well as successful delivery to the lung epithelium with 88% GATA3 silencing in lung explants. These findings support the feasibility of Tf-Mel-PEI as siRNA delivery system for targeted gene knockdown in activated T cells as a potential novel therapy for allergic asthma.

Work Expectations, Depressive Symptoms, and Passive Suicidal Ideation Among Older Adults: Evidence From the Health and Retirement Study.

BACKGROUND AND OBJECTIVES: Employment and work transitions (e.g., retirement) influence mental health. However, how psychosocial contexts such as anticipation and uncertainty about work transitions, irrespective of the transitions themselves, relate to mental health is unclear. This study examined the relationships of work expectations with depressive symptoms, major depression episodes (MDE), and passive suicidal ideation over a 10-year period among the "Baby Boom" cohort of the Health and Retirement Study. RESEARCH DESIGN AND METHODS: Analysis was limited to 13,247 respondents aged 53-70 observed from 2008 to 2018. Past-year depressive symptoms, MDE, and passive suicidal ideation were indexed using the Composite International Diagnostic Interview-Short Form. Expectations regarding working full-time after age 62 were assessed using a probability scale (0%-100%). Mixed-effect logistic regressions with time-varying covariates were used to assess the relationship of work expectations with mental health, accounting for demographics, health status, and functioning, and stratified by baseline employment status. RESULTS: At baseline, higher work expectations were inversely associated with depressive symptoms. Longitudinally, higher expectations were associated with lower odds of depressive symptoms (odds ratio [OR] = 0.93, 95% CI: 0.91, 0.94). This association was more pronounced among respondents not working at baseline (ORNot working = 0.93 vs ORWorking = 0.96). Greater uncertainty (i.e., expectations near 50%) was also inversely associated with depressive symptoms. Results were similar for past-year MDE and passive suicidal ideation. DISCUSSION AND IMPLICATIONS: Expectations (overall likelihood and uncertainty), as indicators of psychosocial context, provide insight into the processes that link work transitions with depression risk.

Language in popular American culture constructs the meaning of healthy and unhealthy eating: Narratives of craveability, excitement, and social connection in movies, television, social media, recipes, and food reviews.

Many people want to eat healthier but struggle to do so, in part due to a dominant perception that healthy foods are at odds with hedonic goals. Is the perception that healthy foods are less appealing than unhealthy foods represented in language across popular entertainment media and social media? Six studies analyzed dialogue about food in six cultural products - creations of a culture that reflect its perspectives - including movies, television, social media posts, food recipes, and food reviews. In Study 1 (N = 617 movies) and Study 2 (N = 27 television shows), healthy foods were described with fewer appealing descriptions (e.g., "couldn't stop eating"; d = 0.59 and d = 0.37, respectively) and more unappealing descriptions (e.g., "I hate peas"; d = -.57 and d = -.63, respectively) than unhealthy foods in characters' speech from the film and television industries. Using sources with richer descriptive language, Studies 3-6 analyzed popular American restaurants' Facebook posts (Study 3, N = 2275), recipe descriptions from Allrecipes.com (Study 4, N = 1000), Yelp reviews from six U.S. cities (Study 5, N = 4403), and Twitter tweets (Study 6, N = 10,000) for seven specific themes. Meta-analytic results across Studies 3-6 showed that healthy foods were specifically described as less craveworthy (d = 0.51, 95% CI: 0.44-0.59), less exciting (d = 0.40, 95% CI: 0.31-0.49), and less social (d = 0.36, 95% CI: 0.04-0.68) than unhealthy foods. Machine learning methods further generalized patterns across 1.6 million tweets spanning 42 different foods representing a range of nutritional quality. These data suggest that strategies to encourage healthy choices must counteract pervasive narratives that dissociate healthy foods from craveability, excitement, and social connection in individuals' everyday lives.

A Data Science Approach to Estimating the Frequency of Driving Cessation Associated Suicide in the US: Evidence From the National Violent Death Reporting System.

Driving cessation is a common transition experienced by aging adults that confers both a symbolic and literal loss of independence due to the central role of automobiles for mobility in the US. Prior research has shown that driving cessation has negative implications for mental health, social participation, and access to healthcare. Given these sequelae of driving cessation and prior work showing that late-life transitions related to independence (e.g., transitioning into residential care) are associated with suicide, we sought to estimate the frequency of driving cessation associated suicide. Data include suicide (n = 59,080) and undetermined (n = 6,862) deaths aged ≥55 from the National Violent Death Reporting System (NVDRS, 2003-2017). Each case in the NVDRS has both quantitative data (e.g., demographic characteristics) and qualitative text narratives, derived from coroner/medical examiner reports, which describe the most salient circumstances and features of each death. To identify cases associated with driving cessation, we employed a supervised random forest algorithm to develop a Natural Language Processing (NLP) classifier. Identified driving cessation associated cases were then categorized and characterized using descriptive statistics and qualitative content analysis. From 2003 to 2017, there were an estimated 305 cases of suicide/undetermined deaths associated with driving cessation in the NVDRS, representing 0.04% of all cases. Cases associated with driving cessation were older, more likely to be male, more likely to have a physical health problem, more likely to have experienced a recent crisis, and more likely to have lived in a rural county than other decedents. Qualitative analysis identified functional impairment, alcohol-related driving limitations, loss of employment, and recent car accidents as common themes among cases associated with driving cessation. This analysis illustrates the utility of NLP in identifying novel correlates of suicide in later life. Although driving cessation associated suicide is a rare outcome, further research is warranted on understanding the conditions under which driving cessation is associated with suicidal behavior, and how to support the well-being of aging adults during these types of major life transitions.

Suicide Among Older Adults Living in or Transitioning to Residential Long-term Care, 2003 to 2015.

Importance: Almost 25% of Medicare beneficiaries live in residential long-term care (LTC) (eg, independent or assisted living facility or nursing home). There are few reliable statistics on completed suicide in LTC, in part because of data limitations. Objectives: To estimate the number of suicides associated with residential LTC (ie, among persons in a facility, transitioning into or out of a facility, or otherwise associated with LTC) among adults 55 and older and, secondarily, to identify whether machine learning tools could improve the quality of suicide surveillance data. Design, Setting, and Participants: Cross-sectional epidemiologic study (conducted in 2018) of restricted-access data from the National Violent Death Reporting System (NVDRS) (2003-2015) using restricted-access case narratives from suicides and undetermined deaths among adults 55 years and older in 27 states. Participants were all suicides and undetermined deaths (N = 47 759) among persons 55 years and older. Exposure: Long-term care cited in the coroner/medical examiner case narrative, whether as a reason for self-harm or the injury location, identified using machine learning natural language processing (NLP) algorithms plus manual review of texts. Main Outcomes and Measures: Number and characteristics (eg, demographics, health history, and means of injury) of suicides associated with LTC. The κ statistic was used to estimate the reliability of the existing NVDRS injury location codes relative to cases identified by the algorithm. Results: Among 47 759 persons 55 years and older (median age, 64 years; 77.6% male; 90.0% non-Hispanic white), this study identified 1037 suicide deaths associated with LTC, including 428 among older adults living in LTC, 449 among older adults transitioning to LTC, and 160 otherwise associated with LTC. In contrast, there were only 263 cases coded with the existing NVDRS location code "supervised residential facility," which had poor agreement with cases that the algorithm identified as occurring in LTC (κ statistic, 0.30; 95% CI, 0.26-0.35). Conclusions and Relevance: Over a 13-year period, approximately 2.2% of suicides among adults 55 years and older were associated with LTC in some manner. Clinicians, administrators, and policy makers should consider ways to promote the mental health and well-being of older adults experiencing functioning limitations and their families. Natural language processing may be a useful way to improve abstraction of variables in the NVDRS.

Language from police body camera footage shows racial disparities in officer respect.

Using footage from body-worn cameras, we analyze the respectfulness of police officer language toward white and black community members during routine traffic stops. We develop computational linguistic methods that extract levels of respect automatically from transcripts, informed by a thin-slicing study of participant ratings of officer utterances. We find that officers speak with consistently less respect toward black versus white community members, even after controlling for the race of the officer, the severity of the infraction, the location of the stop, and the outcome of the stop. Such disparities in common, everyday interactions between police and the communities they serve have important implications for procedural justice and the building of police-community trust.