Dual-Function Smart Windows Using Polymer Stabilized Cholesteric Liquid Crystal Driven with Interdigitated Electrodes.

In this study, we present an electrically switchable window that can dynamically transmit both visible light and infrared (IR) light. The window is based on polymer stabilized cholesteric liquid crystals (PSCLCs), which are placed between a top plate electrode substrate and a bottom interdigitated electrode substrate. By applying a vertical alternating current electric field between the top and bottom substrates, the transmittance of the entire visible light can be adjusted. The cholesteric liquid crystals (CLC) texture will switch to a scattering focal conic state. The corresponding transmittance decreases from 90% to less than 15% in the whole visible region. The reflection bandwidth in the IR region can be tuned by applying an in-plane interdigital direct current (DC) electric field. The non-uniform distribution of the in-plane electric field will lead to helix pitch distortion of the CLC, resulting in a broadband reflection. The IR reflection bandwidth can be dynamically adjusted from 158 to 478 nm. The electric field strength can be varied to regulate both the transmittance in the visible range and the IR reflection bandwidth. After removing the electric field, both features can be restored to their initial states. This appealing feature of the window enables on-demand indoor light and heat management, making it a promising addition to the current smart windows available. This technology has considerable potential for practical applications in green buildings and automobiles.

Machine learning-assisted immune profiling stratifies peri-implantitis patients with unique microbial colonization and clinical outcomes.

Rationale: The endemic of peri-implantitis affects over 25% of dental implants. Current treatment depends on empirical patient and site-based stratifications and lacks a consistent risk grading system. Methods: We investigated a unique cohort of peri-implantitis patients undergoing regenerative therapy with comprehensive clinical, immune, and microbial profiling. We utilized a robust outlier-resistant machine learning algorithm for immune deconvolution. Results: Unsupervised clustering identified risk groups with distinct immune profiles, microbial colonization dynamics, and regenerative outcomes. Low-risk patients exhibited elevated M1/M2-like macrophage ratios and lower B-cell infiltration. The low-risk immune profile was characterized by enhanced complement signaling and higher levels of Th1 and Th17 cytokines. Fusobacterium nucleatum and Prevotella intermedia were significantly enriched in high-risk individuals. Although surgery reduced microbial burden at the peri-implant interface in all groups, only low-risk individuals exhibited suppression of keystone pathogen re-colonization. Conclusion: Peri-implant immune microenvironment shapes microbial composition and the course of regeneration. Immune signatures show untapped potential in improving the risk-grading for peri-implantitis.

HPV16 drives cancer immune escape via NLRX1-mediated degradation of STING.

The incidence of human papillomavirus-positive (HPV+) head and neck squamous cell carcinoma (HNSCC) has surpassed that of cervical cancer and is projected to increase rapidly until 2060. The coevolution of HPV with transforming epithelial cells leads to the shutdown of host immune detection. Targeting proximal viral nucleic acid-sensing machinery is an evolutionarily conserved strategy among viruses to enable immune evasion. However, E7 from the dominant HPV subtype 16 in HNSCC shares low homology with HPV18 E7, which was shown to inhibit the STING DNA-sensing pathway. The mechanisms by which HPV16 suppresses STING remain unknown. Recently, we characterized the role of the STING/type I interferon (IFN-I) pathway in maintaining immunogenicity of HNSCC in mouse models. Here we extended those findings into the clinical domain using tissue microarrays and machine learning-enhanced profiling of STING signatures with immune subsets. We additionally showed that HPV16 E7 uses mechanisms distinct from those used by HPV18 E7 to antagonize the STING pathway. We identified NLRX1 as a critical intermediary partner to facilitate HPV16 E7-potentiated STING turnover. The depletion of NLRX1 resulted in significantly improved IFN-I-dependent T cell infiltration profiles and tumor control. Overall, we discovered a unique HPV16 viral strategy to thwart host innate immune detection that can be further exploited to restore cancer immunogenicity.

Fast and robust deconvolution of tumor infiltrating lymphocyte from expression profiles using least trimmed squares.

Gene-expression deconvolution is used to quantify different types of cells in a mixed population. It provides a highly promising solution to rapidly characterize the tumor-infiltrating immune landscape and identify cold cancers. However, a major challenge is that gene-expression data are frequently contaminated by many outliers that decrease the estimation accuracy. Thus, it is imperative to develop a robust deconvolution method that automatically decontaminates data by reliably detecting and removing outliers. We developed a new machine learning tool, Fast And Robust DEconvolution of Expression Profiles (FARDEEP), to enumerate immune cell subsets from whole tumor tissue samples. To reduce noise in the tumor gene expression datasets, FARDEEP utilizes an adaptive least trimmed square to automatically detect and remove outliers before estimating the cell compositions. We show that FARDEEP is less susceptible to outliers and returns a better estimation of coefficients than the existing methods with both numerical simulations and real datasets. FARDEEP provides an estimate related to the absolute quantity of each immune cell subset in addition to relative percentages. Hence, FARDEEP represents a novel robust algorithm to complement the existing toolkit for the characterization of tissue-infiltrating immune cell landscape. The source code for FARDEEP is implemented in R and available for download at https://github.com/YuningHao/FARDEEP.git.

Improving Patient Experiences and Outcomes Through Personal Care Aide Training.

INTRODUCTION: The rapidly aging US population is resulting in major challenges including delivering quality care at lower costs in the face of a critical health-care workforce shortage. The movement toward home care has dramatically increased the need for qualified, paid personal care aides (PCAs). Adequate PCA training that focuses on skills for person-centered, at home support is an imperative. This study provides evidence that clients of PCAs who have completed a comprehensive, evidence-based PCA training program, titled Building Training…Building Quality (BTBQ), report higher satisfaction and better health outcomes, compared to clients of PCAs with lesser or other training. METHODS: A mixed-methods, quasi-experimental design was used to compare self-reported survey responses from clients of BTBQ-trained PCAs (treatment group) with responses from clients of non-BTBQ-trained PCAs (control group). RESULTS: Clients of BTBQ-trained PCAs had significantly fewer falls and emergency department visits compared to clients whose PCAs had no BTBQ training (P < .05). Conclusion: BTBQ-like PCA training reduces costly adverse events.

A National Survey on the Effect of the Geriatric Academic Career Award in Advancing Academic Geriatric Medicine.

A workforce that understands principles of geriatric medicine is critical to addressing the care needs of the growing elderly population. This will be impossible without a substantial increase in academicians engaged in education and aging research. Limited support of early-career clinician-educators is a major barrier to attaining this goal. The Geriatric Academic Career Award (GACA) was a vital resource that benefitted 222 junior faculty members. GACA availability was interrupted in 2006, followed by permanent discontinuation after the Geriatrics Workforce Education Program (GWEP) subsumed it in 2015, leaving aspiring clinician-educators with no similar alternatives. GACA recipients were surveyed in this cross-sectional, multimethod study to assess the effect of the award on career development, creation and dissemination of educational products, funding discontinuation consequences, and implications of program closure for the future of geriatric health care. Uninterrupted funding resulted in fulfillment of GACA goals (94%) and overall career success (96%). Collectively, awardees reached more than 40,700 learners. Funding interruption led to 55% working additional hours over and above an increased clinical workload to continue their GACA-related research and scholarship. Others terminated GACA projects (36%) or abandoned academic medicine altogether. Of respondents currently at GWEP sites (43%), only 13% report a GWEP budget including GACA-like support. Those with GWEP roles attributed their current standing to experience gained through GACA funding. These consequences are alarming and represent a major setback to academic geriatrics. GACA's singular contribution to the mission of geriatric medicine must prompt vigorous efforts to restore it as a distinct funding opportunity.