Solvent-Mediated, Reversible Ternary Graphite Intercalation Compounds for Extreme-Condition Li-Ion Batteries.

Traditional Li-ion intercalation chemistry into graphite anodes exclusively utilizes the cointercalation-free or cointercalation mechanism. The latter mechanism is based on ternary graphite intercalation compounds (t-GICs), where glyme solvents were explored and proved to deliver unsatisfactory cyclability in LIBs. Herein, we report a novel intercalation mechanism, that is, in situ synthesis of t-GIC in the tetrahydrofuran (THF) electrolyte via a spontaneous, controllable reaction between binary-GIC (b-GIC) and free THF molecules during initial graphite lithiation. The spontaneous transformation from b-GIC to t-GIC, which is different from conventional cointercalation chemistry, is characterized and quantified via operando synchrotron X-ray and electrochemical analyses. The resulting t-GIC chemistry obviates the necessity for complete Li-ion desolvation, facilitating rapid kinetics and synchronous charge/discharge of graphite particles, even under high current densities. Consequently, the graphite anode demonstrates unprecedented fast charging (1 min), dendrite-free low-temperature performance, and ultralong lifetimes exceeding 10 000 cycles. Full cells coupled with a layered cathode display remarkable cycling stability upon a 15 min charging and excellent rate capability even at -40 °C. Furthermore, our chemical strategies are shown to extend beyond Li-ion batteries to encompass Na-ion and K-ion batteries, underscoring their broad applicability. Our work contributes to the advancement of graphite intercalation chemistry and presents a low-cost, adaptable approach for achieving fast-charging and low-temperature batteries.

Experimental and computational analysis of the injection-induced mechanical changes in the skin microenvironment during subcutaneous injection of biologics.

Subcutaneous (SQ) injection is an effective delivery route for various biologics, including proteins, antibodies, and vaccines. However, pain and discomfort induced during SQ injection pose a notable challenge for the broader and routine use of biologics. Understanding the underlying mechanism and quantification of injection-induced pain and discomfort (IPD) are urgently needed. A crucial knowledge gap is what changes in the skin tissue microenvironment are induced by the SQ injection, which may ultimately cause the IPD. In this study, thus, a hypothesis is postulated that the injection of biologics solution through the skin tissue microenvironment induces spatiotemporal mechanical changes. Specifically, the injection leads to tissue swelling and subsequent increases in the interstitial fluid pressure (IFP) and matrix stress around the injection site, which ultimately causes the IPD. To test this hypothesis, an engineered SQ injection model is developed capable of measuring tissue swelling during SQ injection. The injection model consists of a skin equivalent with quantum dot-labeled fibroblasts, which enables the measurement of injection-induced spatiotemporal deformation. The IFP and matrix stress are further estimated by computational analysis approximating the skin equivalent as a nonlinear poroelastic material. The result confirms significant injection-induced tissue swelling and increases in IFP and matrix stress. The extent of deformation is correlated to the injection rate. The results also suggest that the size of biologics particulates significantly affects the pattern and extent of the deformation. The results are further discussed to propose a quantitative understanding of the injection-induced changes in the skin microenvironment.

The impact of neighborhood disadvantage on colorectal cancer screening among African Americans in Chicago.

Historically, colorectal cancer (CRC) screening rates have been lower among African Americans. Previous studies that have examined the relationship between community characteristics and adherence to CRC screening have generally focused on a single community parameter, making it challenging to evaluate the overall impact of the social and built environment. In this study, we will estimate the overall effect of social and built environment and identify the most important community factors relevant to CRC screening. Data are from the Multiethnic Prevention and Surveillance Study (COMPASS), a longitudinal study among adults in Chicago, collected between May 2013 to March 2020. A total 2,836 African Americans completed the survey. Participants' addresses were geocoded and linked to seven community characteristics (i.e., community safety, community crime, household poverty, community unemployment, housing cost burden, housing vacancies, low food access). A structured questionnaire measured adherence to CRC screening. Weighted quantile sum (WQS) regression was used to evaluate the impact of community disadvantages on CRC screening. When analyzing all community characteristics as a mixture, overall community disadvantage was associated with less adherence to CRC screening even after controlling for individual-level factors. In the adjusted WQS model, unemployment was the most important community characteristic (37.6%), followed by community insecurity (26.1%) and severe housing cost burden (16.3%). Results from this study indicate that successful efforts to improve adherence to CRC screening rates should prioritize individuals living in communities with high rates of insecurity and low socioeconomic status.

The Impact of Neighborhood Disadvantage on Asthma Prevalence in a Predominantly African-American, Chicago-Based Cohort.

This study aimed to investigate the joint effect of neighborhood disadvantages on asthma prevalence and evaluate whether individual-level variables protect residents against neighborhood disadvantages. Data from the Chicago Multiethnic Prevention and Surveillance Study (from 2013-2020) were analyzed. Eight neighborhood characteristics were measured using the Chicago Health Atlas, including neighborhood unsafety, limited access to healthy food, neighborhood alienation, severe rent burden, vacant housing, single-parent household, neighborhood poverty, and unemployment. A structured questionnaire measured asthma diagnosis (childhood or adulthood) and individual-level variables including sex, age, income, education, and race. Weighted quantile sum (WQS) regression was used to evaluate the impact of neighborhood disadvantages. Stratified analysis was performed by income and education. A total of 6,592 participants (mean age = 53.5 (standard deviation, 11.1) years) were included. Most of the study population were non-Hispanic Black (82.5%) and reported an annual household income less than $15,000 (53%). Asthma prevalence was 23.6%. The WQS index, which represents the overall neighborhood disadvantages, was associated with asthma prevalence (odds ratio = 1.14, 95% confidence interval: 1.07, 1.22) when adjusted for individual-level confounders. Neighborhood poverty contributed 40.8% to the overall impact, followed by vacant housing (23.1%) and neighborhood alienation (22.9%). When stratified by individual-level income or education, no difference was observed for the association between WQS index and asthma prevalence.

Achieving a Representative Sample of Asian Americans in Biomedical Research Through Community-Based Approaches: Comparing Demographic Data in the All of Us Research Program With the American Community Survey.

BACKGROUND: Underrepresented persons are often not included in biomedical research. It is unknown if the general Asian American population is being represented in All of Us. The purpose of this study was to compare the Asian demographic data in the All of Us cohort with the Asian nationally representative data from the American Community Survey. METHOD: Demographic characteristics and health literacy of Asians in All of Us were examined. Findings were qualitatively compared with the Asian data in the 2019 American Community Survey 1-year estimate. RESULTS: Compared with the national composition of Asians, less All of Us participants were born outside the United States (64% vs 79%), were younger, and had higher levels of education (76% vs 52%). Over 60% of All of Us participants reported high levels of health literacy. CONCLUSION: This study had implications for the development of strategies that ensure diverse populations are represented in biomedical research.

An Overview of Cancer in the First 315,000 All of Us Participants.

INTRODUCTION: The NIH All of Us Research Program will have the scale and scope to enable research for a wide range of diseases, including cancer. The program's focus on diversity and inclusion promises a better understanding of the unequal burden of cancer. Preliminary cancer ascertainment in the All of Us cohort from two data sources (self-reported versus electronic health records (EHR)) is considered. MATERIALS AND METHODS: This work was performed on data collected from the All of Us Research Program's 315,297 enrolled participants to date using the Researcher Workbench, where approved researchers can access and analyze All of Us data on cancer and other diseases. Cancer case ascertainment was performed using data from EHR and self-reported surveys across key factors. Distribution of cancer types and concordance of data sources by cancer site and demographics is analyzed. RESULTS AND DISCUSSION: Data collected from 315,297 participants resulted in 13,298 cancer cases detected in the survey (in 89,261 participants), 23,520 cancer cases detected in the EHR (in 203,813 participants), and 7,123 cancer cases detected across both sources (in 62,497 participants). Key differences in survey completion by race/ethnicity impacted the makeup of cohorts when compared to cancer in the EHR and national NCI SEER data. CONCLUSIONS: This study provides key insight into cancer detection in the All of Us Research Program and points to the existing strengths and limitations of All of Us as a platform for cancer research now and in the future.

Chemomechanics of Rechargeable Batteries: Status, Theories, and Perspectives.

Chemomechanics is an old subject, yet its importance has been revived in rechargeable batteries where the mechanical energy and damage associated with redox reactions can significantly affect both the thermodynamics and rates of key electrochemical processes. Thanks to the push for clean energy and advances in characterization capabilities, significant research efforts in the last two decades have brought about a leap forward in understanding the intricate chemomechanical interactions regulating battery performance. Going forward, it is necessary to consolidate scattered ideas in the literature into a structured framework for future efforts across multidisciplinary fields. This review sets out to distill and structure what the authors consider to be significant recent developments on the study of chemomechanics of rechargeable batteries in a concise and accessible format to the audiences of different backgrounds in electrochemistry, materials, and mechanics. Importantly, we review the significance of chemomechanics in the context of battery performance, as well as its mechanistic understanding by combining electrochemical, materials, and mechanical perspectives. We discuss the coupling between the elements of electrochemistry and mechanics, key experimental and modeling tools from the small to large scales, and design considerations. Lastly, we provide our perspective on ongoing challenges and opportunities ranging from quantifying mechanical degradation in batteries to manufacturing battery materials and developing cyclic protocols to improve the mechanical resilience.

External Validation of an Acute Respiratory Distress Syndrome Prediction Model Using Radiology Reports.

OBJECTIVES: Acute respiratory distress syndrome is frequently under recognized and associated with increased mortality. Previously, we developed a model that used machine learning and natural language processing of text from radiology reports to identify acute respiratory distress syndrome. The model showed improved performance in diagnosing acute respiratory distress syndrome when compared to a rule-based method. In this study, our objective was to externally validate the natural language processing model in patients from an independent hospital setting. DESIGN: Secondary analysis of data across five prospective clinical studies. SETTING: An urban, tertiary care, academic hospital. PATIENTS: Adult patients admitted to the medical ICU and at-risk for acute respiratory distress syndrome. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The natural language processing model was previously derived and internally validated in burn, trauma, and medical patients at Loyola University Medical Center. Two machine learning models were examined with the following text features from qualifying radiology reports: 1) word representations (n-grams) and 2) standardized clinical named entity mentions mapped from the National Library of Medicine Unified Medical Language System. The models were externally validated in a cohort of 235 patients at the University of Chicago Medicine, among which 110 (47%) were diagnosed with acute respiratory distress syndrome by expert annotation. During external validation, the n-gram model demonstrated good discrimination between acute respiratory distress syndrome and nonacute respiratory distress syndrome patients (C-statistic, 0.78; 95% CI, 0.72-0.84). The n-gram model had a higher discrimination for acute respiratory distress syndrome when compared with the standardized named entity model, although not statistically significant (C-statistic 0.78 vs 0.72; p = 0.09). The most important features in the model had good face validity for acute respiratory distress syndrome characteristics but differences in frequencies did occur between hospital settings. CONCLUSIONS: Our computable phenotype for acute respiratory distress syndrome had good discrimination in external validation and may be used by other health systems for case-identification. Discrepancies in feature representation are likely due to differences in characteristics of the patient cohorts.

Germline Mutations in ATM and BRCA1/2 Are Associated with Grade Reclassification in Men on Active Surveillance for Prostate Cancer.

BACKGROUND: Mutations in DNA repair genes are associated with aggressive prostate cancer (PCa). OBJECTIVE: To assess whether germline mutations are associated with grade reclassification (GR) in patients undergoing active surveillance (AS). DESIGN, SETTING, AND PARTICIPANTS: Two independent cohorts of PCa patients undergoing AS; 882 and 329 patients from Johns Hopkins and North Shore, respectively. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Germline DNA was sequenced for DNA repair genes, including BRCA1/2 and ATM (three-gene panel). Pathogenicity of mutations was defined according to the American College of Medical Genetics guidelines. Association of mutation carrier status and GR was evaluated by a competing risk analysis. RESULTS AND LIMITATIONS: Of 1211, 289 patients experienced GR; 11 of 26 with mutations in a three-gene panel and 278 of 1185 noncarriers; adjusted hazard ratio (HR)=1.96 (95% confidence interval [CI]=1.004-3.84, p=0.04). Reclassification occurred in six of 11 carriers of BRCA2 mutations and 283 of 1200 noncarriers; adjusted HR=2.74 (95% CI=1.26-5.96, p=0.01). The carrier rates of pathogenic mutations in the three-gene panel, and BRCA2 alone, were significantly higher in those reclassified (3.8% and 2.1%, respectively) than in those not reclassified (1.6% and 0.5%, respectively; p=0.04 and 0.03, respectively). Carrier rates for BRCA2 were greater for those reclassified from Gleason score (GS) 3+3 at diagnosis to GS ≥4+3 (4.1% vs 0.7%, p=0.01) versus GS 3+4 (2.1% vs 0.6%; p=0.03). Results are limited by the small number of mutation carriers and an intermediate end point. CONCLUSIONS: Mutation status of BRCA1/2 and ATM is associated with GR among men undergoing AS. PATIENT SUMMARY: Men on active surveillance with inherited mutations in BRCA1/2 and ATM are more likely to harbor aggressive prostate cancer.

Germline mutations in PPFIBP2 are associated with lethal prostate cancer.

BACKGROUND: Few genes have germline mutations which predispose men to more aggressive prostate cancer (PCa). This study evaluated the contribution of germline loss of function (LOF) variants in PPFIBP2 to risk of lethal PCa. METHODS: A case-case study of 1414 PCa patients with lethal PCa and low-risk localized PCa was performed. Germline DNA samples from these patients were sequenced for PPFIBP2. Mutation carrier rates and association with lethal PCa were analyzed using the Fisher exact test, logistic regression, and Kaplan-Meier survival analysis. RESULTS: In the entire study population, eight patients, all of European ancestry, were identified as carrying PPFIBP2 pathogenic or likely pathogenic mutations. Seven (1.52%) of 462 lethal PCa patients were carriers compared with only one (0.12%) carrier in 810 low-risk PCa patients, P = 0.0029. The estimated Odds Ratio (OR) of carrying PPFIBP2 mutation for lethal PCa was 13.8 in European American population. The PPFIBP2 loss-of-function mutation carrier rate in lethal PCa cases was also higher than in 33 370 non-Finnish European individuals from the Exome Aggregation Consortium (ExAC) (carrier rate of 0.17%, P = 1.92 × 10-5 ) and in 498 men with localized PCa from The Cancer Genome Atlas cohort (TCGA) cohort (carrier rate of 0%, P = 0.0058). Survival analysis in European American lethal cases revealed PPFIBP2 mutation status as an independent predictor of shorter survival after adjusting for age at diagnosis, PSA at diagnosis, and genetic background (hazard ratio = 2.62, P = 0.034). CONCLUSIONS: While larger studies are needed, germline mutations in a novel gene, PPFIBP2, differentiated risk for lethal PCa from low-risk cases and were associated with shorter survival times after diagnosis.

A comprehensive evaluation of CHEK2 germline mutations in men with prostate cancer.

BACKGROUND: Germline mutations in CHEK2 have been associated with prostate cancer (PCa) risk. Our objective is to examine whether germline pathogenic CHEK2 mutations can differentiate risk of lethal from indolent PCa. METHODS: A case-case study of 703 lethal PCa patients and 1455 patients with low-risk localized PCa of European, African, and Chinese origin was performed. Germline DNA samples from these patients were sequenced for CHEK2. Mutation carrier rates and their association with lethal PCa were analyzed using the Fisher exact test and Kaplan-Meier survival analysis. RESULTS: In the entire study population, 40 (1.85%) patients were identified as carrying one of 15 different germline CHEK2 pathogenic or likely pathogenic mutations. CHEK2 mutations were detected in 16 (2.28%) of 703 lethal PCa patients compared with 24 (1.65%) of 1455 low-risk PCa patients (P = 0.31). No association was found between CHEK2 mutation status and early-diagnosis or PCa-specific survival time. However, the most common mutation in CHEK2, c.1100delC (p.T367 fs), had a significantly higher carrier rate (1.28%) in lethal PCa patients than low-risk PCa patients of European American origin (0.16%), P = 0.0038. The estimated Odds Ratio of this mutation for lethal PCa was 7.86. The carrier rate in lethal PCa was also significantly higher than that (0.46%) in 32 461 non-Finnish European subjects from the Exome Aggregation Consortium (ExAC) (P = 0.01). CONCLUSIONS: While overall CHEK2 mutations were not significantly more common in men with lethal compared to low-risk PCa, the specific CHEK2 mutation, c.1100delC, appears to contribute to an increased risk of lethal PCa in European American men.

Germline Mutations in ATM and BRCA1/2 Distinguish Risk for Lethal and Indolent Prostate Cancer and are Associated with Early Age at Death.

BACKGROUND: Germline mutations in BRCA1/2 and ATM have been associated with prostate cancer (PCa) risk. OBJECTIVE: To directly assess whether germline mutations in these three genes distinguish lethal from indolent PCa and whether they confer any effect on age at death. DESIGN, SETTING, AND PARTICIPANTS: A retrospective case-case study of 313 patients who died of PCa and 486 patients with low-risk localized PCa of European, African, and Chinese descent. Germline DNA of each of the 799 patients was sequenced for these three genes. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Mutation carrier rates and their effect on lethal PCa were analyzed using the Fisher's exact test and Cox regression analysis, respectively. RESULTS AND LIMITATIONS: The combined BRCA1/2 and ATM mutation carrier rate was significantly higher in lethal PCa patients (6.07%) than localized PCa patients (1.44%), p=0.0007. The rate also differed significantly among lethal PCa patients as a function of age at death (10.00%, 9.08%, 8.33%, 4.94%, and 2.97% in patients who died ≤ 60 yr, 61-65 yr, 66-70 yr, 71-75 yr, and over 75 yr, respectively, p=0.046) and time to death after diagnosis (12.26%, 4.76%, and 0.98% in patients who died ≤ 5 yr, 6-10 yr, and>10 yr after a PCa diagnosis, respectively, p=0.0006). Survival analysis in the entire cohort revealed mutation carriers remained an independent predictor of lethal PCa after adjusting for race and age, prostate-specific antigen, and Gleason score at the time of diagnosis (hazard ratio=2.13, 95% confidence interval: 1.24-3.66, p=0.004). A limitation of this study is that other DNA repair genes were not analyzed. CONCLUSIONS: Mutation status of BRCA1/2 and ATM distinguishes risk for lethal and indolent PCa and is associated with earlier age at death and shorter survival time. PATIENT SUMMARY: Prostate cancer patients with inherited mutations in BRCA1/2 and ATM are more likely to die of prostate cancer and do so at an earlier age.