Atrophy of the cholinergic regions advances from early to late mild cognitive impairment

[[abstract]]Purpose We investigated the volumetric changes in the components of the cholinergic pathway for patients with early mild cognitive impairment (EMCI) and those with late mild cognitive impairment (LMCI). The effect of patients' apolipoprotein 4 (APOE-epsilon 4) allele status on the structural changes were analyzed.Methods Structural magnetic resonance imaging data were collected. Patients' demographic information, plasma data, and validated global cognitive composite scores were included. Relevant features were extracted for constructing machine learning models to differentiate between EMCI (n = 312) and LMCI (n = 541) and predict patients' neurocognitive function. The data were analyzed primarily through one-way analysis of variance and two-way analysis of covariance.Results Considerable differences were observed in cholinergic structural changes between patients with EMCI and LMCI. Cholinergic atrophy was more prominent in the LMCI cohort than in the EMCI cohort (P < 0.05 family-wise error corrected). APOE-epsilon 4 differentially affected cholinergic atrophy in the LMCI and EMCI cohorts. For LMCI cohort, APOE-epsilon 4 carriers exhibited increased brain atrophy (left amygdala: P = 0.001; right amygdala: P = 0.006, and right Ch123, P = 0.032). EMCI and LCMI patients showed distinctive associations of gray matter volumes in cholinergic regions with executive (R-2 = 0.063 and 0.030 for EMCI and LMCI, respectively) and language (R-2 = 0.095 and 0.042 for EMCI and LMCI, respectively) function.Conclusions Our data confirmed significant cholinergic atrophy differences between early and late stages of mild cognitive impairment. The impact of the APOE-epsilon 4 allele on cholinergic atrophy varied between the LMCI and EMCI groups

Evaluation of a membrane filter and platelet-rich plasma (PRP) product obtained from a prototype PRP kit that works through a new method for separating PRP based on cell dimensions

[[abstract]]The harvesting of platelet-rich plasma (PRP) from whole blood based on cell density is a standard procedure that is currently applied to commercially available PRP kits. Leukocytes and erythrocytes, which are closer in density, contaminate a significant amount of PRP products, mostly commercial PRP kits. In this study, we tested membrane filters and PRP products from our prototype PRP kit. We did this by putting a membrane filter with pores of 2 mu m in the middle of the tube, which is a new way to separate things based on the cell dimension method (CDM). The evaluations were performed for membrane filter use, hematology analysis, blood smears, viability and cytotoxicity assays, and fibrin structure by scanning electron microscopy (SEM). Compared to the density method (DM), the CDM enables the elimination of a significant number of leukocytes and erythrocytes from the PRPs (CDM-PRP) and a significant increase in the number of platelets compared to the whole blood and DM-PRP. Furthermore, both DM-PRP and CDM-PRP increased the cell viability in L929 cells by adding them at 5% in the culture medium. In addition to CDM-PRP having the lowest cytotoxicity based on the LDH assay, the fibrin structure of CDM-PRP blood clots is characterized by thickness and firmness with a network structure. Thus, we believe that the PRP from the prototype PRP kit meets the requirements as a biomaterial for medical treatments

Neutralizing IL-16 enhances the efficacy of targeting Aurora-A therapy in colorectal cancer with high lymphocyte infiltration through restoring anti-tumor immunity

[[abstract]]Cancer cells can evade immune elimination by activating immunosuppressive signaling pathways in the tumor microenvironment (TME). Targeting immunosuppressive signaling pathways to promote antitumor immunity has become an attractive strategy for cancer therapy. Aurora-A is a well-known oncoprotein that plays a critical role in tumor progression, and its inhibition is considered a promising strategy for treating cancers. However, targeting Aurora-A has not yet got a breakthrough in clinical trials. Recent reports have indicated that inhibition of oncoproteins may reduce antitumor immunity, but the role of tumor-intrinsic Aurora-A in regulating antitumor immunity remains unclear. In this study, we demonstrated that in tumors with high lymphocyte infiltration (hot tumors), higher tumor-intrinsic Aurora-A expression is associated with a better prognosis in CRC patients. Mechanically, tumor-intrinsic Aurora-A promotes the cytotoxic activity of CD8(+) T cells in immune hot CRC via negatively regulating interleukin-16 (IL-16), and the upregulation of IL-16 may impair the therapeutic effect of Aurora-A inhibition. Consequently, combination treatment with IL-16 neutralization improves the therapeutic response to Aurora-A inhibitors in immune hot CRC tumors. Our study provides evidence that tumor-intrinsic Aurora-A contributes to anti-tumor immunity depending on the status of lymphocyte infiltration, highlighting the importance of considering this aspect in cancer therapy targeting Aurora-A. Importantly, our results suggest that combining Aurora-A inhibitors with IL-16-neutralizing antibodies may represent a novel and effective approach for cancer therapy, particularly in tumors with high levels of lymphocyte infiltration

Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores

[[abstract]]We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1% to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8% to 5.1% (SBP) and 4.7% to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs

Iterative estimating equations for disease mapping with spatial zero-inflated Poisson data

[[abstract]]Spatial epidemiology often involves the analysis of spatial count data with an unusually high proportion of zero observations. While Bayesian hierarchical models perform very well for zero-inflated data in many situations, a smooth response surface is usually required for the Bayesian methods to converge. However, for infectious disease data with excessive zeros, a Wombling issue with large spatial variation could make the Bayesian methods infeasible. To address this issue, we develop estimating equations associated with disease mapping by including over-dispersion and spatial noises in a spatial zero-inflated Poisson model. Asymptotic properties are derived for the parameter estimates. Simulations and data analysis are used to assess and illustrate the proposed method

Leucine zipper downregulated in cancer-1 interacts with clathrin adaptors to control epidermal growth factor receptor (EGFR) internalization and gefitinib response in EGFR-mutated non-small cell lung cancer

[[abstract]]The epidermal growth factor receptor (EGFR) is a common driver of non-small cell lung cancer (NSCLC). Clathrin-mediated internalization (CMI) sustains EGFR signaling. AXL is associated with resistance to EGFR-tyrosine kinase inhibitors (TKIs) in EGFR-mutated (EGFR(M)) NSCLC. We investigated the effects of Leucine zipper downregulated in cancer-1 (LDOC1) on EGFR CMI and NSCLC treatment. Coimmunoprecipitation, double immunofluorescence staining, confocal microscopy analysis, cell surface labelling assays, and immunohistochemistry studies were conducted. We revealed that LDOC1 interacts with clathrin adaptors through binding motifs. LDOC1 depletion promotes internalization and plasma membrane recycling of EGFR in EGFR(M) NSCLC PC9 and HCC827 cells. Membranous and cytoplasmic EGFR decreased and increased, respectively, in LDOC1 (-) NSCLC tumors. LDOC1 depletion enhanced and sustained activation of EGFR, AXL, and HER2 and enhanced activation of HER3 in PC9 and HCC827 cells. Sensitivity to first-generation EGFR-TKIs (gefitinib and erlotinib) was significantly reduced in LDOC1-depleted PC9 and HCC827 cells. Moreover, LDOC1 downregulation was significantly associated (p < 0.001) with poor overall survival in patients with EGFR(M) NSCLC receiving gefitinib (n = 100). In conclusion, LDOC1 may regulate the efficacy of first-generation EGFR-TKIs by participating in the CMI of EGFR. Accordingly, LDOC1 may function as a prognostic biomarker for EGFR(M) NSCLC

Microbiota signatures associated with invasive Candida albicans infection in the gastrointestinal tract of immunodeficient mice

[[abstract]]Candida albicans is a commensal microorganism in the human gut but occasionally causes invasive C. albicans infection (ICA), especially in immunocompromised individuals. Early initiation of antifungal therapy is associated with reduced mortality of ICA, but rapid diagnosis remains a challenge. The ICA-associated changes in the gut microbiota can be used as diagnostic and therapeutic targets but have been poorly investigated. In this study, we utilized an immunodeficient Rag2 gamma c (Rag2-/-il2 gamma c-/-) mouse model to investigate the gut microbiota alterations caused by C. albicans throughout its cycle, from its introduction into the gastrointestinal tract to invasion, in the absence of antibiotics. We observed a significant increase in the abundance of Firmicutes, particularly Lachnospiraceae and Ruminococcaceae, as well as a significant decrease in the abundance of Candidatus Arthromitus in mice exposed to either the wild-type SC5314 strain or the filamentation-defective mutant (cph1/cph1 efg1/efg1) HLC54 strain of C. albicans. However, only the SC5314-infected mice developed ICA. A linear discriminate analysis of the temporal changes in the gut bacterial composition revealed Bacteroides vulgatus as a discriminative biomarker associated with SC5314-infected mice with ICA. Additionally, a positive correlation between the B. vulgatus abundance and fungal load was found, and the negative correlation between the Candidatus Arthromitus abundance and fungal load after exposure to C. albicans suggested that C. albicans might affect the differentiation of intestinal Th17 cells. Our findings reveal the influence of pathogenic C. albicans on the gut microbiota and identify the abundance of B. vulgatus as a microbiota signature associated with ICA in an immunodeficient mouse model

Quantifying source contributions to ambient NH(3) using Geo-AI with time lag and parcel tracking functions

[[abstract]]Ambient ammonia (NH(3)) plays an important compound in forming particulate matters (PMs), and therefore, it is crucial to comprehend NH(3)'s properties in order to better reduce PMs. However, it is not easy to achieve this goal due to the limited range/real-time NH(3) data monitored by the air quality stations. While there were other studies to predict NH(3) and its source apportionment, this manuscript provides a novel method (i.e., GEO-AI)) to look into NH(3) predictions and their contribution sources. This study represents a pioneering effort in the application of a novel geospatial-artificial intelligence (Geo-AI) base model with parcel tracking functions. This innovative approach seamlessly integrates various machine learning algorithms and geographic predictor variables to estimate NH(3) concentrations, marking the first instance of such a comprehensive methodology. The Shapley additive explanation (SHAP) was used to further analyze source contribution of NH(3) with domain knowledge. From 2016 to 2018, Taichung's hourly average NH(3) values were predicted with total variance up to 96%. SHAP values revealed that waterbody, traffic and agriculture emissions were the most significant factors to affect NH(3) concentrations in Taichung among all the characteristics. Our methodology is a vital first step for shaping future policies and regulations and is adaptable to regions with limited monitoring sites

Germline mutations of homologous recombination genes and clinical outcomes in pancreatic cancer: A multicenter study in Taiwan

[[abstract]]BackgroundCancer susceptibility germline mutations are associated with pancreatic ductal adenocarcinoma (PDAC). However, the hereditary status of PDAC and its impact on survival is largely unknown in the Asian population.MethodsExome sequencing was performed on 527 blood samples from PDAC individuals and analyzed for mutations in 80 oncogenic genes. Pathogenic and likely pathogenic (P/LP) germline variants were diagnosed according to the ACMG variant classification categories. The association between germline homologous recombination gene mutations (gHRmut, including BAP1, BRCA1, BRCA2, PALB2, ATM, BLM, BRIP1, CHEK2, NBN, MUTYH, FANCA and FANCC) and the treatment outcomes was explored in patients with stage III/IV diseases treated with first-line (1L) platinum-based versus platinum-free chemotherapy.ResultsOverall, 104 of 527 (19.7%) patients carried germline P/LP variants. The most common mutated genes were BRCA2 (3.60%), followed by ATR (2.66%) and ATM (1.9%). After a median follow-up duration of 38.3-months (95% confidence interval, 95% CI 35.0-43.7), the median overall survival (OS) was not significantly different among patients with gHRmut, non-HR germline mutations, or no mutation (P = 0.43). Among the 320 patients with stage III/IV disease who received 1L combination chemotherapy, 32 (10%) had gHRmut. Of them, patients receiving 1L platinum-based chemotherapy exhibited a significantly longer median OS compared to those with platinum-free chemotherapy, 26.1 months (95% CI 12.7-33.7) versus 9.6 months (95% CI 5.9-17.6), P = 0.001. However, the median OS of patients without gHRmut was 14.5 months (95% CI 13.2-16.9) and 12.6 months (95% CI 10.8-14.7) for patients receiving 1L platinum-based and platinum-free chemotherapy, respectively (P = 0.22). These results were consistent after adjusting for potential confounding factors including age, tumor stage, performance status, and baseline CA 19.9 in the multivariate Cox regression analysis.ConclusionsOur study showed that nearly 20% of Taiwanese PDAC patients carried germline P/LP variants. The longer survival observed in gHRmut patients treated with 1L platinum-based chemotherapy highlights the importance of germline testing for all patients with advanced PDAC at diagnosis

Occupational sitting time, leisure physical activity, and All-cause and cardiovascular disease mortality

[[abstract]]Importance: For the first time, the 2020 World Health Organization guidelines on physical activity recommended reducing sedentary behaviors owing to their health consequences. Less is known on the specific association of prolonged occupational sitting with health, especially in the context of low physical activity engagement. Objective: To quantify health risks associated with prolonged occupational sitting and to determine whether there is a certain threshold of physical activity that may attenuate it. Design, Setting, and Participants: This prospective cohort study included participants in a health surveillance program in Taiwan who were followed-up between 1996 and 2017. Data on occupational sitting, leisure-time physical activity (LTPA) habits, lifestyle, and metabolic parameters were collected. Data analysis was performed in December 2020. Main Outcomes and Measures: The all-cause and cardiovascular disease (CVD) mortality associated with 3 occupational sitting volumes (mostly sitting, alternating sitting and nonsitting, and mostly nonsitting) were analyzed applying multivariable Cox regression models to calculate the hazard ratios (HRs) for all participants and by subgroups, including 5 LTPA levels and a personal activity intelligence (PAI)-oriented metric. Deaths occurring within the initial 2 years of follow-up were excluded to prevent reverse causality. Results: The total cohort included 481 688 participants (mean [SD] age, 39.3 [12.8] years; 256 077 women [53.2%]). The study recorded 26 257 deaths during a mean (SD) follow-up period of 12.85 (5.67) years. After adjusting for sex, age, education, smoking, drinking, and body mass index, individuals who mostly sat at work had a 16% higher all-cause mortality risk (HR, 1.16; 95% CI, 1.11-1.20) and a 34% increased mortality risk from CVD (HR, 1.34; 95% CI, 1.22-1.46) compared with those who were mostly nonsitting at work. Individuals alternating sitting and nonsitting at work did not experience increased risk of all-cause mortality compared with individuals mostly nonsitting at work (HR, 1.01; 95% CI, 0.97-1.05). For individuals mostly sitting at work and engaging in low (15-29 minutes per day) or no (<15 minutes per day) LTPA, an increase in LTPA by 15 and 30 minutes per day, respectively, was associated with a reduction in mortality to a level similar to that of inactive individuals who mostly do not sit at work. In addition, individuals with a PAI score exceeding 100 experienced a notable reduction in the elevated mortality risk associated with prolonged occupational sitting. Conclusions and Relevance: As part of modern lifestyles, prolonged occupational sitting is considered normal and has not received due attention, even though its deleterious effect on health outcomes has been demonstrated. In this study, alternating between sitting and nonsitting at work, as well as an extra 15 to 30 minutes per day of LTPA or achieving a PAI score greater than 100, attenuated the harms of prolonged occupational sitting. Emphasizing the associated harms and suggesting workplace system changes may help society to denormalize this common behavior, similar to the process of denormalizing smoking