Effectiveness of autumn 2023 COVID-19 vaccination and residual protection of prior doses against hospitalisation in England, estimated using a test-negative case-control study.

INTRODUCTION: The last COVID-19 vaccine offered to all adults in England became available from November 2021. The most recent booster programme commenced in September 2023. Bivalent BA.4-5 or monovalent XBB.1.5 boosters were given. During the study period, the JN.1 variant became dominant in England. METHODS: Vaccine effectiveness against hospitalisation was estimated throughout using the test-negative case-control study design where positive PCR tests from hospitalised individuals are cases and comparable negative PCR tests are controls. Multivariable logistic regression was used to assess vaccine effectiveness against hospitalisation with the test result as the outcome, vaccination status as the primary exposure variable of interest and confounder adjustment. RESULTS: There was no evidence of residual protection for boosters given as part of previous campaigns. There were 28,916 eligible tests included to estimate the effectiveness of the autumn 2023 boosters in those aged 65 years and older. VE peaked at 50.6% (95% CI: 44.2-56.3%) after 2-4 weeks, followed by waning to 13.6% (95% CI: -11.7 to 33.2%). Estimates were generally higher for the XBB.1.5 booster than the BA.4-5 booster, but this difference was not statistically significant. Point estimates were highest against XBB sub-lineages. Effectiveness was lower against both JN.1 and EG.5.1 variants with confidence intervals non-overlapping with the effectiveness of the XBB sub-lineages at 2-4 weeks for EG.5.1 where VE was 44.5% (95% CI: 20.2-61.4%) and at 5-9 weeks for JN.1 where VE was 26.4% (95%CI: -3.4 to 47.6%). CONCLUSIONS: The recent monovalent XBB.1.5 and bivalent BA.4-5 boosters provided comparable and good protection against hospitalisation, however there was evidence of lower VE against hospitalisation of these boosters against JN.1.

Machine Learning-Based Classification of Transcriptome Signatures of Non-Ulcerative Bladder Pain Syndrome.

Lower urinary tract dysfunction (LUTD) presents a global health challenge with symptoms impacting a substantial percentage of the population. The absence of reliable biomarkers complicates the accurate classification of LUTD subtypes with shared symptoms such as non-ulcerative Bladder Pain Syndrome (BPS) and overactive bladder caused by bladder outlet obstruction with Detrusor Overactivity (DO). This study introduces a machine learning (ML)-based approach for the identification of mRNA signatures specific to non-ulcerative BPS. Using next-generation sequencing (NGS) transcriptome data from bladder biopsies of patients with BPS, benign prostatic obstruction with DO, and controls, our statistical approach successfully identified 13 candidate genes capable of discerning BPS from control and DO patients. This set was validated using Quantitative Polymerase Chain Reaction (QPCR) in a larger patient cohort. To confirm our findings, we applied both supervised and unsupervised ML approaches to the QPCR dataset. A three-mRNA signature TPPP3, FAT1, and NCALD, emerged as a robust classifier for non-ulcerative BPS. The ML-based framework used to define BPS classifiers establishes a solid foundation for comprehending the gene expression changes in the bladder during BPS and serves as a valuable resource and methodology for advancing signature identification in other fields. The proposed ML pipeline demonstrates its efficacy in handling challenges associated with limited sample sizes, offering a promising avenue for applications in similar domains.

Machine Learning-based Classification of transcriptome Signatures of non-ulcerative Bladder Pain Syndrome.

Lower urinary tract dysfunction (LUTD) presents a global health challenge with symptoms impacting a substantial percentage of the population. The absence of reliable biomarkers complicates the accurate classification of LUTD subtypes with shared symptoms such as non-ulcerative Bladder Pain Syndrome (BPS) and overactive bladder caused by bladder outlet obstruction with Detrusor Overactivity (DO). This study introduces a machine learning (ML)-based approach for the identification of mRNA signatures specific to non-ulcerative BPS. Using next-generation sequencing (NGS) transcriptome data from bladder biopsies of patients with BPS, benign prostatic obstruction with DO and controls, our statistical approach successfully identified 13 candidate genes capable of discerning BPS from control and DO patients. This set was subsequently validated using Quantitative Polymerase Chain Reaction (QPCR) in a larger patient cohort. To confirm our findings, we applied both supervised and unsupervised ML approaches to the QPCR dataset. Notably, a three-mRNA signature TPPP3, FAT1, and NCALD, emerged as a robust classifier, effectively distinguishing patients with non-ulcerative BPS from controls and patients with DO. This signature was universally selected by both supervised and unsupervised approaches. The ML-based framework used to define BPS classifiers not only establishes a solid foundation for comprehending the specific gene expression changes in the bladder of the patients with BPS but also serves as a valuable resource and methodology for advancing signature identification in other fields. The proposed ML pipeline demonstrates its efficacy in handling challenges associated with limited sample sizes, offering a promising avenue for applications in similar domains.

Integrated omics analysis unveils a DNA damage response to neurogenic injury.

Spinal cord injury (SCI) evokes profound bladder dysfunction. Current treatments are limited by a lack of molecular data to inform novel therapeutic avenues. Previously, we showed systemic inosine treatment improved bladder function following SCI in rats. Here, we applied multi-omics analysis to explore molecular alterations in the bladder and their sensitivity to inosine following SCI. Canonical pathways regulated by SCI included those associated with protein synthesis, neuroplasticity, wound healing, and neurotransmitter degradation. Upstream regulator analysis identified MYC as a key regulator, whereas causal network analysis predicted multiple regulators of DNA damage response signaling following injury, including PARP-1. Staining for both DNA damage (γH2AX) and PARP activity (poly-ADP-ribose) markers in the bladder was increased following SCI, and attenuated in inosine-treated tissues. Proteomics analysis suggested that SCI induced changes in protein synthesis-, neuroplasticity-, and oxidative stress-associated pathways, a subset of which were shown in transcriptomics data to be inosine-sensitive. These findings provide novel insights into the molecular landscape of the bladder following SCI, and highlight a potential role for PARP inhibition to treat neurogenic bladder dysfunction.

Novel phenotype characterization utilizing electrical impedance myography signatures in murine spinal cord injury neurogenic bladder models.

Neurogenic bladder (NB) affects people of all ages. Electric impedance myography (EIM) assesses localized muscle abnormalities. Here, we sought to investigate whether unique detrusor EIM signatures are present in NB due to spinal cord injury (SCI). Twenty-eight, 8-10 weeks old, C57BL/6J female mice were studied. Twenty underwent spinal cord transection; 8 served as controls. Cohorts were euthanized at 4 and 6 weeks after spinal cord transection. Each bladder was measured in-situ with EIM with applied frequencies of 1 kHz to 10 MHz, and then processed for molecular and histologic study. SCI mice had greater bladder-to-body weight ratio (p < 0.0001), greater collagen deposition (p = 0.009), and greater smooth-muscle-myosin-heavy-chain isoform A/B ratio (p < 0.0001). Compared with the control group, the SCI group was associated with lower phase, reactance, and resistance values (p < 0.01). Significant correlations (p < 0.001) between bladder-to-body weight ratios and EIM measurements were observed across the entire frequency spectrum. A severely hypertrophied phenotype was characterized by even greater bladder-to-body weight ratios and more depressed EIM values. Our study demonstrated distinct EIM alterations in the detrusor muscle of mice with NB due to SCI. With further refinement, EIM may offer a potential point-of-care tool for the assessment of NB and its response to treatment.

Erratum: Building the foundation for equitable and inclusive research: Seed grant programs to facilitate development of diverse CBPR community-academic research partnerships - CORRIGENDUM.

[This corrects the article DOI: 10.1017/cts.2022.495.].

SpheroScan: A User-Friendly Deep Learning Tool for Spheroid Image Analysis.

Background: In recent years, three-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional two-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays. Results: To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results. Conclusion: SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan.

Building the foundation for equitable and inclusive research: Seed grant programs to facilitate development of diverse CBPR community-academic research partnerships.

Introduction: The effectiveness of community-based participatory research (CBPR) partnerships to address health inequities is well documented. CBPR integrates knowledge and perspectives of diverse communities throughout the research process, following principles that emphasize trust, power sharing, co-learning, and mutual benefits. However, institutions and funders seldom provide the time and resources needed for the critical stage of equitable partnership formation and development. Methods: Since 2011, the Detroit Urban Research Center, collaborating with other entities, has promoted the development of new community-academic research partnerships through two grant programs that combine seed funding with capacity building support from community and academic instructors/mentors experienced in CBPR. Process and outcomes were evaluated using mixed methods. Results: From 2011 to 2021, 50 partnerships received grants ranging from $2,500 to $30,000, totaling $605,000. Outcomes included equitable partnership infrastructure and processes, innovative pilot research, translation of findings to interventions and policy change, dissemination to multiple audiences, new proposals and projects, and sustained community-academic research partnerships. All partnerships continued beyond the program; over half secured additional funding. Conclusions: Keys to success included participation as community-academic teams, dedicated time for partnership/relationship development, workshops to develop equity-based skills, relationships, and projects, expert community-academic instructor guidance, and connection to additional resources. Findings demonstrate that small amounts of seed funding for newly forming community-academic partnerships, paired with capacity building support, can provide essential time and resources needed to develop diverse, inclusive, equity-focused CBPR partnerships. Building such support into funding initiatives and through academic institutions can enhance impact and sustainability of translational research toward advancing health equity.

MLcps: machine learning cumulative performance score for classification problems.

BACKGROUND: Assessing the performance of machine learning (ML) models requires careful consideration of the evaluation metrics used. It is often necessary to utilize multiple metrics to gain a comprehensive understanding of a trained model's performance, as each metric focuses on a specific aspect. However, comparing the scores of these individual metrics for each model to determine the best-performing model can be time-consuming and susceptible to subjective user preferences, potentially introducing bias. RESULTS: We propose the Machine Learning Cumulative Performance Score (MLcps), a novel evaluation metric for classification problems. MLcps integrates several precomputed evaluation metrics into a unified score, enabling a comprehensive assessment of the trained model's strengths and weaknesses. We tested MLcps on 4 publicly available datasets, and the results demonstrate that MLcps provides a holistic evaluation of the model's robustness, ensuring a thorough understanding of its overall performance. CONCLUSIONS: By utilizing MLcps, researchers and practitioners no longer need to individually examine and compare multiple metrics to identify the best-performing models. Instead, they can rely on a single MLcps value to assess the overall performance of their ML models. This streamlined evaluation process saves valuable time and effort, enhancing the efficiency of model evaluation. MLcps is available as a Python package at https://pypi.org/project/MLcps/.

SpheroScan: a user-friendly deep learning tool for spheroid image analysis.

BACKGROUND: In recent years, 3-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional 2-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays. RESULTS: To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results. CONCLUSION: SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan.

A Single Cell Dissociation Approach for Molecular Analysis of Urinary Bladder in the Mouse Following Spinal Cord Injury.

We describe the implementation of spinal cord injury in mice to elicit detrusor-sphincter dyssynergia, a functional bladder outlet obstruction, and subsequent bladder wall remodeling. To facilitate assessment of the cellular composition of the bladder wall in non-injured control and spinal cord injured mice, we developed an optimized dissociation protocol that supports high cell viability and enables the detection of discrete subpopulations by flow cytometry. Spinal cord injury is created by complete transection of the thoracic spinal cord. At the time of tissue harvest, the animal is perfused with phosphate-buffered saline under deep anesthesia and bladders are harvested into Tyrode's buffer. Tissues are minced prior to incubation in digestion buffer that has been optimized based on the collagen content of mouse bladder as determined by interrogation of publicly available gene expression databases. Following generation of a single cell suspension, material is analyzed by flow cytometry for assessment of cell viability, cell number and specific subpopulations. We demonstrate that the method yields cell populations with greater than 90% viability, and robust representation of cells of mesenchymal and epithelial origin. This method will enable accurate downstream analysis of discrete cell types in mouse bladder and potentially other organs.

Enhancing Capacity of Community-Academic Partnerships to Achieve Health Equity: Results From the CBPR Partnership Academy.

Community-based participatory research (CBPR) is an equitable partnership approach that links academic researchers, community organizations, and public health practitioners to work together to understand and address health inequities. Although numerous educational materials on CBPR exist, few training programs develop the skills and knowledge needed to establish effective, equitable partnerships. Furthermore, there are few professional development opportunities for academic researchers, practitioners, and community members to obtain these competencies in an experiential co-learning process. In response, the Detroit Community-Academic Urban Research Center developed the CBPR Partnership Academy, an innovative, yearlong capacity-building program facilitated by experienced community and academic partners, involving an intensive short course, partnership development, grant proposal preparation and funding, mentoring, online learning forums, and networking. Three diverse cohorts (36 teams) from 18 states and 2 tribal nations have participated. We describe the rationale and components of the training program and present results from the first two cohorts. Evaluation results suggest enhanced competence and efficacy in conducting CBPR. Outcomes include partnerships established, grant proposals submitted and funded, workshops and research conducted, and findings disseminated. A community-academic partner-based, integrated, applied program can be effective for professional development and establishing innovative linkages between academics and practitioners aimed at achieving health equity.

Epidemiology of Secondary School Boys' and Girls' Basketball Injuries: National Athletic Treatment, Injury and Outcomes Network.

CONTEXT: Little is known about non-time-loss (NTL) injury patterns in basketball athletes. Knowledge of these patterns may aid in the development of prevention and management strategies for patients with these injuries. OBJECTIVE: To describe the epidemiology of time-loss (TL) and NTL injuries sustained by secondary school boys' and girls' basketball athletes. DESIGN: Descriptive epidemiology study. SETTING: Eighty-six unique schools provided data, with 84 and 83 contributing to boys' and girls' basketball, respectively. PATIENTS OR OTHER PARTICIPANTS: Athletes participating in secondary school-sponsored boys' and girls' basketball. MAIN OUTCOME MEASURE(S): Boys' and girls' basketball data from the National Athletic Treatment, Injury and Outcomes Network (NATION) injury-surveillance program (2011-2012 through 2013-2014 years) were analyzed. Injury counts, rates, and rate ratios (IRRs) were reported with 95% confidence intervals (CIs). RESULTS: The NATION captured 2653 injuries over 364 355 athlete-exposures (AEs) for boys' basketball and 2394 injuries over 288 286 AE for girls' basketball, producing rates of 7.28/1000 AEs (95% CI = 7.00, 7.56) for boys and 8.30/1000 AEs (95% CI = 7.97, 8.64) for girls. The overall injury rates were slightly lower for boys (IRR = 0.88; 95% CI = 0.83, 0.93). For boys, 559 (21.1%) injuries were TL and 2094 (78.9%) were NTL, producing a TL injury rate of 1.53/1000 AEs (95% CI = 1.40, 1.66) and an NTL injury rate of 5.75/1000 AEs (95% CI = 5.50, 5.99). For girls, 499 (20.8%) injuries were TL and 1895 (79.2%) were NTL, producing a TL injury rate of 1.73/1000 AEs (95% CI = 1.58, 1.88) and an NTL injury rate of 6.57/1000 AEs (95% CI = 6.28, 6.87). Rates of TL injuries were similar between boys' and girls' basketball (IRR = 0.89; 95% CI = 0.79, 1.00); NTL injury rates were lower for boys (IRR = 0.87; 95% CI = 0.82, 0.93). CONCLUSIONS: When NTL injuries were included, the rates of injury in boys' and girls' secondary school basketball were higher than previously reported.

Motivations for advance care and end-of-life planning among lesbian, gay, and bisexual older adults.

Lesbian, gay, and bisexual (LGB) older adults are more likely than their heterosexual peers to experience health disparities, discrimination from healthcare providers based on sexual orientation, and rejection from their family of origin, all of which can complicate medical care and decision making, as well as end-of-life arrangements. Yet, relatively few studies of LGB seniors have looked at motivations for advance care and end-of-life planning, which are strategies that can help ensure that healthcare treatment and end-of-life wishes are enacted as desired. The present qualitative study investigated this topic with a purposive sample of nine LGB and same-gender-loving adults in a metropolitan region of the Southeastern United States. The study involved in-depth face-to-face interviews, followed by a brief pen-and-paper survey. Participants' ages ranged from 65 to 77; the sample included five men and four women. Six individuals were white/Caucasian, while three were African American/Black. We identified three themes related to motivations for advance care and end-of-life planning: wanting a sense of agency, learning from others, and reducing conflict and confusion for loved ones. We discuss the importance of these findings for social work practice with LGB older adults and for social work education, as well as implications for future research.

Linear doggybone DNA vaccine induces similar immunological responses to conventional plasmid DNA independently of immune recognition by TLR9 in a pre-clinical model.

Vaccination with DNA that encodes cancer antigens is a simple and convenient way to raise immunity against cancer and has already shown promise in the clinical setting. Conventional plasmid DNA is commonly used which together with the encoded antigen also includes bacterial immunostimulatory CpG motifs to target the DNA sensor Toll-like receptor 9. Recently DNA vaccines using doggybone DNA (dbDNA™), have been developed without the use of bacteria. The cell-free process relies on the use of Phi29 DNA polymerase to amplify the template followed by protelomerase TelN to complete individual closed linear DNA. The resulting DNA contains the required antigenic sequence, a promoter and a poly A tail but lacks bacterial sequences such as an antibiotic resistance gene, prompting the question of immunogenicity. Here we compared the ability of doggybone DNA vaccine with plasmid DNA vaccine to induce adaptive immunity using clinically relevant oncotargets E6 and E7 from HPV. We demonstrate that despite the inability to trigger TLR9, doggybone DNA was able to induce similar levels of cellular and humoral immunity as plasmid DNA, with suppression of established TC-1 tumours.

Is State Anxiety, Trait Anxiety, or Anxiety Sensitivity a Clinical Predictor of Symptoms in Those Presenting With Mild Traumatic Brain Injury or Concussion?

Clinical Scenario: Mild traumatic brain injury, or concussion, has been associated with physical, cognitive, and emotional sequelae. Little is understood in regard to many characteristics, such as anxiety, and their effect on post-concussion symptoms. CLINICAL QUESTION: Is state anxiety, trait anxiety, or anxiety sensitivity a clinical predictor of symptoms in those presenting with mild traumatic brain injury or concussion? Summary of Key Findings: A literature search returned 3 possible studies; 3 studies met inclusion criteria and included. One study reported in athletes that greater social support was associated with decreased state-anxiety, lower state anxiety post-concussion was associated with increased social support, and that those with greater social support may experience reduced anxiety, regardless of injury type sustained. One study reported baseline trait anxiety in athletes was not significantly associated with post-concussion state anxiety, but that symptoms of depression at baseline was the strongest predictor for post-concussion state anxiety. Three studies reported that state and trait anxiety are not related to increased post-concussion symptom scores. One study reported that greater anxiety sensitivity is related to higher reported post-concussion symptom scores, which may manifest as somatic symptoms following concussion, and revealed that anxiety sensitivity may be a risk factor symptom development. Clinical Bottom Line: There is low-level to moderate evidence to support that anxiety sensitivity is linked to post-concussion symptoms. State and trait anxiety do not appear to be related to post-concussion symptoms alone. Post-concussion state anxiety may occur if post-concussion symptoms of depression are present or if baseline symptoms of depression are present. Better social support may improve state anxiety post-concussion. Strength of Recommendation: There is grade B evidence to support that state and trait anxiety are not risk factors for post-concussion symptom development. There is grade C evidence to support anxiety sensitivity as a risk factor for developing post-concussion symptoms.

Coping Strategies Used by LGB Older Adults in Facing and Anticipating Health Challenges: A Narrative Analysis.

Given that lesbian, gay, and bisexual (LGB) older adults face notable health disparities compared to their heterosexual counterparts, there is a need for understanding how LGB adults cope with health challenges in late life. The current study analyzes narratives from nine LGB adults age 65 and older living in an urban area in the Southeast U.S. Participants spoke of coping strategies related to health promotion behaviors, shifting perspectives of health and body, trusting in spirituality for comfort, and accepting the end of life. We discuss implications for social services professionals who work with older LGB adults and for future research.

Linked CD4 T Cell Help: Broadening Immune Attack Against Cancer by Vaccination.

In the last decade, immunotherapy with monoclonal antibodies targeting immunological check points has become a breakthrough therapeutic modality for solid cancers. However, only up to 50 % of patients benefit from this powerful approach. For others vaccination might provide a plausible addition or alternative. For induction of effective anticancer immunity CD4+ T cell help is required, which is often difficult to induce to self cancer targets because of tolerogenic mechanisms. Our approach for cancer vaccines has been to incorporate into the vaccine design sequences able to activate foreign T cell help, through genetically linking cancer targets to microbial sequences (King et al. in Nat Med 4(11):1281-1286, 1998; Savelyeva et al. in Nat Biotechnol 19(8):760-764, 2001). This harnesses the non-tolerized CD4 T cell repertoire available in patients to help induction of effective immunity against fused cancer antigens. Multiple immune effector mechanisms including antibody, CD8+ T cells as well as CD4 effector T cells can be activated using this strategy. Delivery via DNA vaccines has already indicated clinical efficacy. The same principle of linked T cell help has now been transferred to other novel vaccine modalities to further potentiate immunity against cancer targets.

Coculture Assays for Endothelial Cells-Mural Cells Interactions.

Coculture assays allow the investigation of the role of endothelial cell and mural cell interactions in small vessel development and function. Different setups for coculture can be used to assay questions of interest. We include here methods for direct coculture, indirect coculture, and coculture in a three-dimensional extracellular matrix scaffold for studies of either a simple and direct association between the two cell types, the exchange of soluble molecules, or the interaction within a biomimetic tissue microenvironment.