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Introduction Early lung cancer screening (LCS) through low-dose CT (LDCT) is crucial but underused due to various barriers, including incomplete or inaccurate patient smoking data in the electronic health record and limited time for shared decision-making. The objective of this trial is to investigate a patient-centred intervention, MyLungHealth, delivered through the patient portal. The intervention is designed to improve LCS rates through increased identification of eligible patients and informed decision-making.Methods and analysis MyLungHealth is a multisite pragmatic trial, involving University of Utah Health and New York University Langone Health primary care clinics. The MyLungHealth intervention was developed using a user-centred design process, informed by patient and provider focus groups and interviews. The intervention’s effectiveness will be evaluated through a patient-randomised trial, comparing the combined use of MyLungHealth and DecisionPrecision+ (a provider-focused shared decision-making intervention) against DecisionPrecision+ alone. The first study hypothesis is that among patients aged 50–79 with uncertain LCS eligibility (eg, 10–19 pack-years or unknown pack-years or unknown quit date for individuals who used to smoke), MyLungHealth eligibility questionnaires will result in increased identification of LCS-eligible patients (n~26 729 patients). The second study hypothesis is that among patients aged 50–79 with documented LCS eligibility (20+ pack-years, quit within the last 15 years if individuals who used to smoke, and no recent screening or screening discussion), MyLungHealth education will result in increased LDCT ordering (n~4574 patients). Primary outcomes will be identification of LCS-eligible patients among individuals with uncertain LCS eligibility and LDCT ordering rates among individuals with documented LCS eligibility.Ethics and dissemination The protocol was approved by the University of Utah Institutional Review Board (# 00153806). The patient data collected for this study will not be shared publicly due to the sensitive nature of the patient health information and the fact that we will not be obtaining written informed consent to allow public sharing of their data. Results will be disseminated through peer-reviewed publications.Trial registration number Clinicaltrials.gov, NCT06338592.

Abstract Histone lactylation has been reported to involve in tumorigenesis and development. However, its biological regulatory mechanism in endometrial carcinoma (EC) is yet to be reported in detail. In the present study, we evaluated the modification levels of global lactylation in EC tissues by immunohistochemistry and western blot, and it was elevated. The non-metabolizable glucose analog 2-deoxy-d-glucose (2-DG) and oxamate treatment could decrease the level of lactylation so as to inhibit the proliferation and migration ability, induce apoptosis significantly, and arrest the cell cycle of EC cells. Mechanically, histone lactylation stimulated USP39 expression to promote tumor progression. Moreover, USP39 activated PI3K/AKT/HIF-1α signaling pathway via interacting with and stabilizing PGK1 to stimulate glycolysis. The results of present study suggest that histone lactylation plays an important role in the progression of EC by promoting the malignant biological behavior of EC cells, thus providing insights into potential therapeutic strategies for endometrial cancer.

Wooden structures are prone to fire hazards, and studying their combustion properties is vital for their protection. Samples of fresh pine wood (FP) and pine subjected to artificially accelerated aging (treated at 240 circulation) were collected and prepared for analysis. The heat-release rate, smoke production, and yields of carbon monoxide (CO) and carbon dioxide (CO2) from both types of pine were assessed using conical calorimetry to determine their combustion characteristics. A historic building in Xi’an was modeled using PyroSim to serve as a representative case. The experimentally obtained combustion characteristics of the two pine wood types were inputted into the model, and the Fire Dynamics Simulator (FDS) software was utilized to simulate the development of fire in both newly constructed and aging historic buildings. The results suggest that aging impairs the wood’s combustion properties and increases the susceptibility of pine to ignition. Consequently, this accelerates the spread of fire in wooden structures, leading to a rapid increase in temperature and swift smoke production during fires, thus amplifying the fire risk to historic wooden buildings.

Abstract Background The role of immune cells in collagen degradation within the tumor microenvironment (TME) is unclear. Immune cells, particularly tumor-infiltrating lymphocytes (TILs), are known to alter the extracellular matrix, affecting cancer progression and patient survival. However, the quantitative evaluation of the immune modulatory impact on collagen architecture within the TME remains limited. Methods We introduce CollaTIL, a computational pathology method that quantitatively characterizes the immune-collagen relationship within the TME of gynecologic cancers, including high-grade serous ovarian (HGSOC), cervical squamous cell carcinoma (CSCC), and endometrial carcinomas. CollaTIL aims to investigate immune modulatory impact on collagen architecture within the TME, aiming to uncover the interplay between the immune system and tumor progression. Results We observe that an increased immune infiltrate is associated with chaotic collagen architecture and higher entropy, while immune sparse TME exhibits ordered collagen and lower entropy. Importantly, CollaTIL-associated features that stratify disease risk are linked with gene signatures corresponding to TCA-Cycle in CSCC, and amino acid metabolism, and macrophages in HGSOC. Conclusions CollaTIL uncovers a relationship between immune infiltration and collagen structure in the TME of gynecologic cancers. Integrating CollaTIL with genomic analysis offers promising opportunities for future therapeutic strategies and enhanced prognostic assessments in gynecologic oncology.

Background and Aims: Lynch syndrome (LS) is caused by pathogenic mutations in mismatch repair (MMR) genes. There are limited data on differences in colorectal cancer (CRC) surveillance by MMR genes, and an international consensus on surveillance based on genes is not established. We aimed to evaluate colonoscopy and esophagogastroduodenoscopy (EGD) surveillance outcomes and compare CRC surveillance findings by the mutated gene. Methods: One hundred one patients with LS were included and colonoscopy results were compared by MMR mutation. Primary outcomes included the development and recurrence of adenoma, CRC, high-grade dysplasia, advanced adenoma, and sessile serrated lesions. Logistic regressions evaluated the relationship between genes and the development or recurrence of primary outcomes. Survival analysis evaluated primary outcomes in patients with ≥ 2 colonoscopies. EGD results were summarized. Results: Three hundred twenty seven colonoscopies were reviewed. Compared to PMS2, MLH1 was associated with a higher risk of advanced adenoma/high-grade dysplasia/CRC development (odds ratio [OR] 9.85, 95% confidence interval [CI]: 1.97–77.24) and MSH2 was associated with a higher risk of adenoma development (OR 4.17, 95% CI: 1.11–17.61). Among those with > 2 colonoscopies, MLH1 (hazard ratio 18.98, 95% CI: 1.31–274.51) and MSH6 (hazard ratio 15.03, 95% CI: 1.16–194.65) had a higher risk of sessile serrated lesions compared to MSH2. Among patients who had adenoma detected once, MLH1 had a higher risk of adenoma recurrence compared to MSH6 (OR 14.59, 95% CI: 1.53–244.30) and PMS2 (OR 47.15, 95% CI: 4.26–984.28). MSH2 had a higher risk of adenoma recurrence compared to PMS2 (OR 11.89, 95% CI: 1.38–164.78). Of 170 EGDs, an actionable finding was identified in 16% of patients during their first 3 EGDs. Conclusion: Surveillance colonoscopy outcomes differed in patients with LS and suggest the need to guide surveillance based on MMR gene mutation.

Abstract Background Metabolic reprogramming is one of hallmarks of cancer progression and is of great importance for the tumor microenvironment (TME). As an abundant metabolite, lactate has been found to play a critical role in cancer development and immunosuppression of TME. However, the potential role of lactate metabolism-related genes in endometrial cancer (EC) remains obscure. Methods RNA sequencing data and clinical information of EC were obtained from The Cancer Genome Atlas (TCGA) database. Lactate metabolism-related genes (LMRGs) WERE from Molecular Signature Database v7.4 and then compared the candidate genes from TCGA to obtain final genes. Univariate analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression were performed to screen prognostic genes. A lactate metabolism-related risk profile was constructed using multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analysis and Kaplan-Meier analysis. The relationship between the risk score and age, grade, stage, tumor microenvironmental characteristics, and drug sensitivity was as well explored by correlation analyses. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional analysis between the high and low-risk groups were performed. CCK8, EdU, and clone formation assays were applied to detect the proliferation ability of EC cells, Transwell assay was performed to detect the migration ability of EC cells, and intracellular lactate and glucose content was used to asses lactate metabolism. Results We constructed a risk signature based on 18 LMRGs. Kaplan-Meier curves confirmed that the high-risk group had poorer prognosis compared to the low-risk group. A nomogram was then constructed to predict the probability of EC survival. We also performed GO enrichment analysis and KEGG pathway functional analysis between the high and low-risk groups, and the outcome revealed that the features were significantly associated with energy metabolism. There was a significant correspondence between LMRGs and tumor mutational load, checkpoints and immune cell infiltration. C1, C2, and C4 were the most infiltrated in the high-risk group. The high-risk group showed increased dendritic cell activation, while the low-risk group showed increased plasma cells and Treg cells. Drug sensitivity analysis showed LMRGs risk was more resistant to Scr kinase inhibitors. We further proved that one of the lactate metabolism related genes, TIMM50 could promote EC cell proliferation, migration and lactate metabolism. Conclusion In conclusion, we have established an effective prognostic signature based on LMRG expression patterns, which may greatly facilitate the assessment of prognosis, molecular features and treatment modalities in EC patients and may be useful in the future translation to clinical applications. TIMM50 was identified as a novel molecule that mediates lactate metabolism in vitro and in vivo, maybe a promising target for EC prognosis.

Abstract Prognostic markers currently utilized in clinical practice for estrogen receptor-positive (ER+) and lymph node-negative (LN−) invasive breast cancer (IBC) patients include the Nottingham grading system and Oncotype Dx (ODx). However, these biomarkers are not always optimal and remain subject to inter-/intra-observer variability and high cost. In this study, we evaluated the association between computationally derived image features from H&E images and disease-free survival (DFS) in ER+ and LN− IBC. H&E images from a total of n = 321 patients with ER+ and LN− IBC from three cohorts were employed for this study (Training set: D1 (n = 116), Validation sets: D2 (n = 121) and D3 (n = 84)). A total of 343 features relating to nuclear morphology, mitotic activity, and tubule formation were computationally extracted from each slide image. A Cox regression model (IbRiS) was trained to identify significant predictors of DFS and predict a high/low-risk category using D1 and was validated on independent testing sets D2 and D3 as well as within each ODx risk category. IbRiS was significantly prognostic of DFS with a hazard ratio (HR) of 2.33 (95% confidence interval (95% CI) = 1.02–5.32, p = 0.045) on D2 and a HR of 2.94 (95% CI = 1.18–7.35, p = 0.0208) on D3. In addition, IbRiS yielded significant risk stratification within high ODx risk categories (D1 + D2: HR = 10.35, 95% CI = 1.20–89.18, p = 0.0106; D1: p = 0.0238; D2: p = 0.0389), potentially providing more granular risk stratification than offered by ODx alone.

Background: Sepsis-associated encephalopathy (SAE) impairs hippocampal microglial efferocytosis, causing cognitive deficits. Previous research found that milk fat globule epidermal growth factor 8 protein (MFGE8) stimulates efferocytosis, reducing hippocampal inflammation in SAE rats. In this study, we explore MFGE8’s role in alleviating cognitive impairment and its impact on neural activity using functional magnetic resonance imaging (fMRI). Methods: Sixty male Sprague Dawley rats were divided into four groups: Sham, cecal ligation and puncture (CLP), CLP+MFGE8, and CLP+MFGE8+CGT (Cilengitide). After CLP, CLP+MFGE8 rats received intracerebroventricular MFGE8 (3.3 µg), while CLP+MFGE8+CGT rats received intraperitoneal Cilengitide (10 mg/kg). We assessed cognitive function with the Morris water maze and open field test over five days. Eight days post-surgery, rats underwent T2-weighted magnetic resonance imaging (MRI) and resting state (rs)-fMRI scans. Brain tissues were collected for western blot, hematoxylin-eosin (HE) staining, and immunofluorescence. Statistical analysis employed one-way analysis of variance (ANOVA) followed by Tukey’s post-test for multiple comparisons. Results: MFGE8 improved neurobehavioral performance in open field task (OFT) and morris water maze (MWM) tests. fMRI indicated a significant reduction in abnormal neural activity in the right hippocampal CA1, CA3, and dentate gyrus of SAE rats following MFGE8 treatment. Voxel-based morphometry (VBM) analysis revealed decreased high-signal areas in the hippocampus, along with reduced hippocampal volume due to alleviated neural edema. Western blot analysis demonstrated that MFGE8 enhanced ras-related C3 botulinum toxin substrate 1 (Rac1) and microtubule-associated protein 1A/1B-light chain 3 (LC3) expression in the rat hippocampus, while CGT reduced these protein levels. Behavioral experiments and fMRI results confirmed that CGT reversed the cognitive effects of MFGE8 by inhibiting microglial αVβ3/αVβ5 integrin receptors. Conclusions: Our findings show that MFGE8 reduced amplitude of low-frequency fluctuations (ALFF) values in the right hippocampal CA1, CA3, and the dentate gyrus, mitigating abnormal neural activity and decreasing hippocampal volume. This led to an improvement in cognitive dysfunction in SAE rats. These results suggest that MFGE8 enhances microglial efferocytosis by activating αVβ3 and αVβ5 integrin receptors on microglial surfaces, ultimately improving cognitive function in SAE rats.

Abstract Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC.

Abstract Background In this study we sought to explore the possibility of using patient centered care (PCC) documentation as a measure of the delivery of PCC in a health system. Methods We first selected 6 VA medical centers based on their scores for a measure of support for self-management subscale from a national patient satisfaction survey (the Survey for Healthcare Experience-Patients). We accessed clinical notes related to either smoking cessation or weight management consults. We then annotated this dataset of notes for documentation of PCC concepts including: patient goals, provider support for goal progress, social context, shared decision making, mention of caregivers, and use of the patient's voice. We examined the association of documentation of PCC with patients’ perception of support for self-management with regression analyses. Results Two health centers had

Background: Minimal clinically important difference (MCID) estimates are useful for gauging clinical relevance when interpreting changes or differences in patient-reported outcomes scores. These values are lacking in the setting of elbow trauma. Our primary purpose was to estimate the MCID of the Patient-Reported Outcomes Measurement Information System (PROMIS) physical function (PF) computer adaptive test (CAT), the PROMIS upper extremity (UE) CAT, and the QuickDASH using an anchor-based approach for patients recovering from elbow trauma and related surgeries. Secondarily, we aimed to estimate the MCID using the 1/2 standard deviation method. Materials & methods: Adult patients undergoing treatment for isolated elbow injuries between July 2014 and April 2020 were identified at a single tertiary academic medical center. Outcomes, including the PROMIS PF CAT v1.2/2.0, PROMIS UE CAT v1.2, and QuickDASH, were collected via a tablet computer. For inclusion, baseline (6 months before injury up to 11 days postoperatively or after injury) and follow-up (11 to 150 days postoperative or after injury) PF or UE CAT scores were required, as well as a response to an anchor question querying improvement in physical function. The MCID was calculated using (1) an anchor-based approach using the difference in mean score change between anchor groups reporting “No change” and “Slightly Improved/Improved” and (2) the 1/2 standard deviation method. Results: Of the 146 included patients, the mean age was 46 ± 18 years and 67 (46%) were women. Most patients (129 of 146 or 88%) were recovering from surgery, and the remaining 12% were recovering from nonoperatively managed fractures and/or dislocations. The mean follow-up was 157 ± 192 days. Scores for each instrument improved significantly between baseline and follow-up. Anchor-based MCID values were calculated as follows: 5.7, 4.6, and 5.3 for the PROMIS PF CAT, PROMIS UE CAT, and QuickDASH, respectively. MCID values estimated using the 1/2 standard deviation method were 4.3, 4.8, and 11.7 for the PROMIS PF CAT, PROMIS UE CAT, and QuickDASH, respectively. Conclusions: In the setting of elbow trauma, we propose MCID ranges of 4.3 to 5.7 for the PROMIS PF CAT, 4.6 to 4.8 for the PROMIS UE CAT, and 5.3 to 11.7 for the QuickDASH. These values will provide a framework for clinical relevance when interpreting clinical outcomes studies, or powering clinical trials, for populations recovering from trauma.

In geese breeding, due to the frequent influence of drugs and environmental and other factors, geese are extremely prone to oxidative stress, which adversely affects growth and development, geese meat quality, down production, and severely affects the development of the geese industry. Ferulic acid from plant extracts can be used as a feed additive, which is safe and non-toxic, and it can exert certain therapeutic effects on oxidative stress in geese. This experiment investigated the effect of ferulic acid on the growth performance, organs indices, and intestinal oxidative indices of Jilin white geese under lipopolysaccharide-induced oxidative stress. Geese were randomly divided into six groups: C (blank control), L (lipopolysaccharide control), F1 (60 mg/kg ferulic acid), F2 (120 mg/kg ferulic acid), F3 (180 mg/kg ferulic acid), and F4 (240 mg/kg ferulic acid). Groups L and F1-F4 were injected intraperitoneally with 0.5 mg/kg lipopolysaccharide and group C with an equivalent volume of normal saline on days 14,17 and 20, and 10 animals from each group were randomly selected for slaughter on day 21. The results showed that: 1) On day 14, the final body weight and average daily feed intake were significantly higher in group F3 than in group L, and on day 21, the final body weight was significantly higher in group F3 than in group L. 2) The thymus index was significantly higher in group F4 than in group L. 4) In the duodenum, MDA activity was reduced in group C compared with that in group L. 5) In the jejunum and ileum, MDA was significantly lower in group F3 than in group L. These results show that the addition of 180 mg/kg of ferulic acid to the diet can promote the growth of geese and alleviate the damage caused by oxidative stress in all intestinal segments.

BackgroundThe diagnosis of sepsis associated encephalopathy (SAE) remains challenging in clinical settings because of a lack of specific biomarkers. Functional magnetic resonance imaging (fMRI) and proton magnetic resonance spectroscopy (1H-MRS) can be used to aid in the diagnosis of cognition related diseases. This study investigated changes in functional activities and brain metabolites in the hippocampus in SAE rats by fMRI and 1H-MRS.Materials and methodsSepsis associated encephalopathy rats underwent cecal ligation and perforation (CLP) surgery. The Morris water maze (MWM) test was then used to evaluate cognitive function. Resting state-fMRI and 1H-MRS scanning were performed 7 and 14 days after CLP surgery to reveal spontaneous neuronal activity and metabolite changes in the hippocampus. The amplitude of low-frequency fluctuation (ALFF) was used to evaluate spontaneous neuronal activity in the hippocampus. Creatine (Cr), Myo-inositol (mI), and glutamine/glutamate (Glx) levels were measured with 1H-MRS scanning. Immunofluorescence and levels of interleukin (IL)-1β, interleukin (IL)-6, and C-reactive protein (CRP) in the hippocampus were additionally detected to evaluate microglial mediated inflammatory responses. Statistical analysis was performed to evaluate correlations between hippocampal metabolism and behavioral findings.ResultsCecal ligation and perforation treated rats exhibited impaired learning and memory function in the MWM test at days 7 and 14. Elevation of IL-1β in the hippocampus, as well as immunofluorescence results, confirmed severe neuro inflammation in the hippocampus in SAE rats. Compared with the sham group, the ALFF of the right CA-1 area of the hippocampus was higher at day 7after CLP surgery. The Glx/Cr and mI/Cr ratios were enhanced at day 7 after CLP surgery and slightly lower at day 14 after CLP surgery. The ALFF value, and Glx/Cr and mI/Cr ratios were negatively correlated with time spent in the target quadrant in the MWM test.ConclusionSpontaneous neuronal activity and metabolites showed significant alterations in SAE rats. The elevated ALFF value, Glx/Cr ratio, and mI/Cr ratio in the hippocampus were positively associated with cognitive deficits. Changes in ALFF and metabolites in hippocampus may serve as potential neuroimaging biomarkers of cognitive disorders in patients with SAE.

Abstract Background Cognitive deficits are common in patients with sepsis. Previous studies in sepsis-associated encephalopathy (SAE) implicated the C-X-C chemokine receptor type (CXCR) 5. The present study used a mouse model of SAE to examine whether CXCR5 down-regulation could attenuate cognitive deficits. Methods Sepsis was induced in adult male C57BL/6 J and CXCR5 −/− mice by cecal ligation and puncture (CLP). At 14–18 days after surgery, animals were tested in a Morris water maze, followed by a fear conditioning test. Transmission electron microscopy of hippocampal sections was used to assess levels of autophagy. Primary microglial cultures challenged with lipopolysaccharide (LPS) were used to examine the effects of short interfering RNA targeting CXCR5, and to investigate the possible involvement of the p38MAPK/NF-κB/STAT3 signaling pathway. Results CLP impaired learning and memory and up-regulated CXCR5 in hippocampal microglia. CLP activated hippocampal autophagy, as reflected by increases in numbers of autophagic vacuoles, conversion of microtubule-associated protein 1 light chain 3 (LC3) from form I to form II, accumulation of beclin-1 and autophagy-related gene-5, and a decrease in p62 expression. CLP also shifted microglial polarization to the M1 phenotype, and increased levels of IL-1β, IL-6 and phosphorylated p38MAPK. CXCR5 knockout further enhanced autophagy but partially reversed all the other CLP-induced effects, including cognitive deficits. Similar effects on autophagy and cytokine expression were observed after knocking down CXCR5 in LPS-challenged primary microglial cultures; this knockdown also partially reversed LPS-induced up-regulation of phosphorylated NF-κB and STAT3. The p38MAPK agonist P79350 partially reversed the effects of CXCR5 knockdown in microglial cultures. Conclusions CXCR5 may act via p38MAPK/NF-κB/STAT3 signaling to inhibit hippocampal autophagy during sepsis and thereby contribute to cognitive dysfunction. Down-regulating CXCR5 can restore autophagy and mitigate the proinflammatory microenvironment in the hippocampus.

Abstract Objective To compare an objective with a subjective numeracy assessment for association with self-reported health status, where numeracy refers to “the degree to which individuals have the capacity to access, process, interpret, communicate, and act on numerical, quantitative, graphical, biostatistical, and probabilistic health information needed to make effective health decisions” Results We completed a secondary analysis of two population-based surveys, the Empire State Poll (n = 763) and the Program for the International Assessment of Adult Competencies (PIAAC; n = 2609). The first survey assessed numeracy with a 3-item subjective instrument. The second assessed numeracy with more than 20 math problems. Both used the same measure for self-reported health status. Lower numeracy, whether subjectively or objectively assessed, was associated with worse self-reported health, even after controlling for education and other sociodemographic confounders. The odds ratios for the association were very similar (0.91 and 0.90 respectively). A lengthy objective numeracy assessment and a brief self-report assessment had similar associations with health status. A brief self-report measure of numeracy has similar properties to a lengthy objective assessment and is likely to be more feasible to use to screen patients in practice.

Abstract Collagen fiber organization has been found to be implicated in breast cancer prognosis. In this study, we evaluated whether computerized features of Collagen Fiber Orientation Disorder in Tumor-associated Stroma (CFOD-TS) on Hematoxylin & Eosin (H&E) slide images were prognostic of Disease Free Survival (DFS) in early stage Estrogen Receptor Positive (ER+) Invasive Breast Cancers (IBC). A Cox regression model named MCFOD-TS, was constructed using cohort St (N = 78) to predict DFS based on CFOD-TS features. The prognostic performance of MCFOD-TS was validated on cohort Sv (N = 219), a prospective clinical trial dataset (ECOG 2197). MCFOD-TS was prognostic of DFS in both St and Sv, independent of clinicopathological variables. Additionally, the molecular pathways regarding cell cycle regulation were identified as being significantly associated with MCFOD-TS derived risk scores. Our results also found that collagen fiber organization was more ordered in patients with short DFS. Our study provided a H&E image-based pipeline to derive a potential prognostic biomarker for early stage ER+ IBC without the need of special collagen staining or advanced microscopy techniques.

ObjectiveThis study aims to analyze the changes of fecal short chain fatty acids (SCFAs) content and gut microbiota composition in sepsis associated encephalopathy (SAE) mice, further evaluating the effect of SCFAs on cognitive function and the underlying mechanism in SAE mice.MethodsA total of 55 male adult C57BL/6 mice (2–3 months of age, 20–25 g) were divided into four groups randomly: sham group (n = 10), cecal ligation and puncture group (CLP group, n = 15), CLP+SCFAs group (n = 15), and CLP+SCFAs+GLPG0974 group (n = 15). Seven days after surgery, fecal samples were collected for microbiota composition and SCFA analysis from 6 mice in each group randomly. Behavioral test was applied to assess cognitive impairment at the same time. After that, mice were sacrificed and brain tissue was harvested for inflammatory cytokines analysis.ResultsThe levels of acetic acid (.57 ± 0.09 vs 2.00 ± 0.24, p < 0.001) and propionic acid (.32 ± 0.06 vs .66 ± 0.12, p = 0.002) were significantly decreased in the CLP group compared with the sham group. The administration of SCFAs significantly increased the levels of acetic acid (1.51 ± 0.12 vs. 0.57 ± 0.09, p < 0.001) and propionic acid (0.54 ± 0.03 vs. 0.32 ± 0.06, p = 0.033) in CLP+SCFAs group compared with CLP group. Relative abundance of SCFAs-producing bacteria, including Allobaculum (0.16 ± 0.14 vs. 15.21 ± 8.12, p = 0.037), Bacteroides (1.82 ± 0.38 vs. 15.21 ± 5.95, p = 0.002) and Bifidobacterium (0.16 ± 0.06 vs. 2.24 ± 0.48, p = 0.002), significantly decreased in the CLP group compared with the sham group. The behavioral tests suggested that cognitive function was impaired in SAE mice, which could be alleviated by SCFAs pretreatment. ELISA tests indicated that the levels of IL-1β, IL-6, and TNF-α were elevated in SAE mice and SCFAs could lower them. However, the GPR43 antagonist, GLPG0974, could reverse the cognitive protective effect and anti-neuroinflammation effect of SCFAs.ConclusionOur study suggested that in SAE, the levels of acetate and propionate decreased significantly, accompanied by gut microbiota dysbiosis, particularly a decrease in SCFAs-producing bacteria. GPR43 was essential for the anti-neuroinflammation and cognitive protective effect of SCFAs in SAE.

IntroductionAlthough the association between blood pressure and vitamin D has been well studied, the effects of dietary magnesium intake on this relationship are still unclear. Thus, this study aimed to determine the effects of dietary magnesium intake on the association between vitamin D and blood pressure.MethodsThe present study analyzed data from the continuous the National Health and Nutrition Examination Survey (NHANES) 2007–2014. We included 8,799 participants aged 20 years or older. Multivariable linear regression was performed to assess the association between vitamin D and systolic blood pressure (SBP) and diastolic blood pressure (DBP). Dietary magnesium intake was stratified by low magnesium intake (

Chronic thromboembolic pulmonary hypertension (CTEPH) is a serious complication of acute pulmonary embolism (PE) which remains underdiagnosed. A better understanding of risk factors for CTEPH would improve our ability to predict which PE survivors are at risk. Several medical conditions—including malignancy, splenectomy, thyroid hormone supplementation, the presence of an intravascular device, inflammatory bowel disease, osteomyelitis, and non-O blood group—have been associated with increased risk of CTEPH, primarily in studies comparing patients with CTEPH to individuals with non-thrombotic conditions. Because many of these conditions increase thrombosis risk, it remains unclear whether their association with CTEPH reflects a general effect on thrombosis risk, or a specific effect on the risk of developing CTEPH as an outcome of thrombosis. We performed a case-control study comparing the frequencies of these conditions in patients with CTEPH versus patients with acute PE who did not develop CTEPH. The conditions studied were equally frequent in the CTEPH and PE cohorts, although there was a trend towards an increased frequency of splenectomy and non-O blood group among the CTEPH cohort. Thus, other than the possible exceptions of splenectomy and non-O blood group, the investigated medical conditions do not appear likely to increase the risk of CTEPH as an outcome of acute PE, and thus are unlikely to be useful in predicting CTEPH risk among PE survivors.

Introduction: Circulating vitamin D concentrations have been associated with the risk of type 2 diabetes (T2D). Magnesium has also been reported to be associated with lower T2D risk. Besides, magnesium is an essential cofactor for vitamin D activation. However, the effect of dietary magnesium intake on the association between vitamin D and the risk of T2D has not been studied comprehensively. Therefore, we designed this cross-sectional study to assess the effect modification of magnesium intake on the association between vitamin D and risk of T2D.Research Design and Methods: The present study analyzed data from the National Health and Nutrition Examination Survey (NHANES) continuously from 2007 to 2014, involving 10,249 participants. By having stratified participants based on magnesium intake category (low magnesium intake

Abstract Background Oncotype DX (ODx) is a 12-gene assay assessing the recurrence risk (high, intermediate, and low) of ductal carcinoma in situ (pre-invasive breast cancer), which guides clinicians regarding prescription of radiotherapy. However, ODx is expensive, time-consuming, and tissue-destructive. In addition, the actual prognostic meaning for the intermediate ODx risk category remains unclear. Methods In this work, we evaluated the ability of quantitative nuclear histomorphometric features extracted from hematoxylin and eosin-stained slide images of 62 ductal carcinoma in situ (DCIS) patients to distinguish between the corresponding ODx risk categories. The prognostic value of the identified image signature was further evaluated on an independent validation set of 30 DCIS patients in its ability to distinguish those DCIS patients who progressed to invasive carcinoma versus those who did not. Following nuclear segmentation and feature extraction, feature ranking strategies were employed to identify the most discriminating features between individual ODx risk categories. The selected features were then combined with machine learning classifiers to establish models to predict ODx risk categories. The model performance was evaluated using the average area under the receiver operating characteristic curve (AUC) using cross validation. In addition, an unsupervised clustering approach was also implemented to evaluate the ability of nuclear histomorphometric features to discriminate between the ODx risk categories. Results Features relating to spatial distribution, orientation disorder, and texture of nuclei were identified as most discriminating between the high ODx and the intermediate, low ODx risk categories. Additionally, the AUC of the most discriminating set of features for the different classification tasks was as follows: (1) high vs low ODx (0.68), (2) high vs. intermediate ODx (0.67), (3) intermediate vs. low ODx (0.57), (4) high and intermediate vs. low ODx (0.63), (5) high vs. low and intermediate ODx (0.66). Additionally, the unsupervised clustering resulted in intermediate ODx risk category patients being co-clustered with low ODx patients compared to high ODx. Conclusion Our results appear to suggest that nuclear histomorphometric features can distinguish high from low and intermediate ODx risk category patients. Additionally, our findings suggest that histomorphometric features for intermediate ODx were more similar to low ODx compared to high ODx risk category.

In production practice, we have found that the gray and black down on the backs of the Holdobaggy goslings is usually darker in females than in males. Melanin is the key pigment affecting the color of poultry plumage. Therefore, to determine whether the darkness of the dorsal plumage of the Holdobaggy goslings is related to sex, we study the melanin in the feather follicles of the dorsal skin during the embryonic period. The feather follicle structure and melanin distribution on the dorsal surface of the goose embryo is observed by HE staining and melanin-specific staining. The melanin content in the feather follicles of the dorsal skin of goslings is determined by ELISA. The results showed that the melanin content is higher in female geese than in males (p < 0.05). In addition, we also analyze the mRNA and protein expression levels of melanin-related genes (TYRP1 and ASIP) by quantitative real-time PCR and Western blotting analysis. The results show that the mRNA expression level of TYRP1 is significantly higher in the females’ dorsal skin feather follicles (p < 0.05), while the mRNA expression level of ASIP is significantly higher in the dorsal skin feather follicles of male geese (p < 0.05). In conclusion, the difference between males and females in the color of the black feathers on the dorsal track of the Holdobaggy goslings is verified, and it is feasible to identify the sex by the initial plumage color.

Purpose: Both developmental language disorder (DLD) and attention-deficit/hyperactivity disorder (ADHD) represent relatively common and chronic neurodevelopmental conditions associated with increased risk for poor academic and interpersonal outcomes. Reports of common co-occurrence suggest these neurodevelopmental disruptions might also be linked. Most of the data available on the issue have been based on case-control studies vulnerable to ascertainment and other biases. Method: Seventy-eight children, representing four neurodevelopmental profiles (DLD, ADHD, co-occurring ADHD + DLD, and neurotypical development), were administered a battery of psycholinguistic tests. Parents provided standardized ratings of the severity of their children's inattention, hyperactivity/impulsivity, and executive function symptoms. Examiners were blinded to children's clinical status. Group differences, correlations, and best subset regression analyses were used to examine potential impacts of children's ADHD symptoms on their psycholinguistic abilities. Results: For children with DLD, significant links between their ADHD symptoms and psycholinguistic abilities were limited to the contributions of elevated hyperactivity/impulsivity symptoms to lower pragmatic abilities. For children without DLD, inattention symptoms contributed to lower levels of performance in pragmatic, sentence recall, receptive vocabulary, and narrative abilities. Discussion: Links among children's ADHD symptoms and their psycholinguistic abilities were different for children with and without DLD. Implications for the provision of clinical services are discussed. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) high-fidelity building models are crucial for digital twin cities. Multi-scale modeling is crucial for accurately capturing the complexity of urban environments; however, existing methods often lack the flexibility required to satisfy the varied demands of diverse applications. In this paper, we propose a framework to continuously simplify 3D building models, it dynamically adjusts mesh accuracy to meet diverse needs, enabling seamless transitions from high-poly to medium and low-poly meshes. Our method contains three main stages: First, in the mesh repair stage, we introduce a novel mesh repair framework based on an advanced Marching Cubes 33 algorithm to ensure a watertight and clean topology mesh. Then, for generating medium-poly meshes, we employ a feature-preserving mesh simplification algorithm that combines curvature and area-weighted quadratic error metrics to achieve a high-fidelity simplified mesh. For generating low-poly meshes, we use the concept of carving visual hull to generate low-poly mesh with high visual similarity. Our method has been evaluated on building subsets of the Free3D and Thingi10 K datasets, as well as on various building models generated from different observation scales, and its superiority has been validated through extensive comparisons with state-of-the-art techniques.

Improving emergency management capabilities is vital for sustainable cities. However, urban emergency management is a complex, giant system that interacts between urban virtual and real spaces, requiring simulation in the virtual space and feedback to the real space. The digital twin model can potentially play an important role in this process, but still faces significant challenges in terms of modeling, simulation, and visualization. In this study, we propose a digital-twin-based multi-scale simulation method and take epidemic transmission as a case study. First, an entity-oriented unified urban database integrating multi-source urban data was constructed as the digital twins of urban human settlements for emergency modeling. Then, a multi-scale urban emergency simulation method in 3D geographic environment was proposed to support emergency simulation for multi-level urban management units. Moreover, an adaptive fusion rendering of emergency information and 3D scene was proposed to support the refinement of emergency visualization. An experimental case study on epidemic risk estimation was conducted through thousands of outbreak scenarios. The results demonstrate that the proposed method can establish the digital twins of urban human settlements, where modeling, simulation, and visualization of emergency at multi-scales can be carried out, thus enhancing the efficacy and efficiency of emergency management.

Under high-temperature and hygrothermal conditions, sea salt erosion can lead to asphalt--aggregate interfacial failure in porous asphalt concrete and cause aggregate raveling in coastal areas. Therefore, studying the damaging effect of sea salt erosion on an asphalt--aggregate interfacial system in a hygrothermal environment is necessary. First, the asphalt film thickness of a standard asphalt--aggregate specimen used in the simulation tests was determined according to the relationship between the tensile strength of the asphalt--aggregate specimen and the thickness of the asphalt film. The damaging effect of the salt solution was simulated by the 60°C high-temperature erosion test, and the solution type, solution concentration, and immersion duration were considered. The tensile strength and asphalt film-stripping ratio of the eroded specimens were analyzed, and the interfacial asphalt film dynamic equation σ2(t) and the stripping region interface dynamic equation σ2(t) were deduced. The results show that the 6 μm asphalt film thickness corresponds to the maximum tensile strength of the asphalt--aggregate specimen. With the increase of immersion duration, the tensile strength of asphalt--aggregate specimen decreased, and the asphalt film-stripping ratio of failure surface increased. In addition, the tensile strength of the interfacial asphalt film increased gradually due to the aging effect of the salt solution. The tensile strength of the stripping region's interface did not descend to zero, but was obviously lower than the asphalt film. The 5% Na2SO4 solution has the highest damaging effect on the asphalt--aggregate interfacial system, followed by the 5% composite salt solution, 5% NaCl solution, water, and 10% NaCl solution.. [ABSTRACT FROM AUTHOR]

(1) Background: The smart city management system, with GIS technology as its core, is based on realistic visualization of multiple types of 3D model data syntheses. However, the efficiency barriers to achieving smooth and continuous visualization from outdoor scenes to small indoor scenes remain a challenge. (2) Methods: This paper uses the visibility prediction method to obtain potential visual sets at three levels—outdoor, indoor and outdoor connection, and indoor—and constructs an R-tree spatial index structure for organizing potential visual sets. By integrating these potential visible sets with spatial indexes, scene visualization can be carried out effectively. (3) Results: A near-reality indoor and outdoor scene was used for experimentation, resulting in stable 10% fluctuation visual frame rates around 90 FPS. (4) Conclusions: Spatial indexing methods that combine potential visible sets can effectively solve the continuity and stability problem of indoor and outdoor scene visualization in smart city management systems.

Graph convolution networks (GCNs) have been proven powerful in describing unstructured data. Currently, most of existing GCNs aim on more accuracy by constructing deeper models. However, these methods show limited benefits, and they often suffer from the common drawbacks brought by deep networks, such as large model size, high memory consumption and slow training speed. In this paper, different from these methods, we widen GCNs to improve the descriptiveness by expanding the width of input to avoid the above drawbacks. Specifically, we present a wider GCNs based model, WGNet, for 3D point cloud classification. A local dilated connecting (LDC) module is designed to obtain the adjacency matrix, while a context information aware (CIA) module is proposed to generate initial node representation. These two modules provide a way to transform 3D point cloud into graph structure with larger receptive field and rich initial node features. These two properties widen the channels of input and provide more rich information to describe the samples precisely. Besides, we provide analysis to formulate the above idea as the sample precision description. Then, we adopt ChebyNet as our basic network, and present a skip-connection-based GCNs to improve efficiency of feature reuse. WGNet was evaluated on two datasets. One was acquired by a mobile laser scanning system under the real road environments, while the other was the well-known public artificial dataset, ModelNet40. Experimental results show that WGNet achieves better performance than the state-of-the-art in terms of descriptiveness, efficiency and robustness. Ablation studies also demonstrate the effectiveness of our designed LDC and CIA modules.

Traffic surveillance can be used to monitor and collect the traffic condition data of road networks, which plays an important role in a wide range of applications in intelligent transportation systems (ITSs). Accurately and rapidly detecting and counting vehicles in traffic videos is one of the main problems of traffic surveillance. Traditional video-based vehicle detection methods, such as background subtraction, frame difference, and optical flow have some limitations in accuracy or efficiency. In this paper, deep learning is applied for vehicle counting in traffic videos. First, to solve the problem of the lack of annotated data, a method for vehicle detection based on transfer learning is proposed. Then, based on vehicle detection, a vehicle counting method based on fusing the virtual detection area and vehicle tracking is proposed. Finally, due to possible situations of missing detection and false detection, a missing alarm suppression module and a false alarm suppression module are designed to improve the accuracy of vehicle counting. The results show that the proposed deep learning vehicle counting framework can achieve lane-level vehicle counting without enough annotated data, and the accuracy of vehicle counting can reach up to 99%. In terms of computational efficiency, this method has high real-time performance and can be used for real-time vehicle counting.

Human daily mobility plays an important role in urban research. Commuting of urban residents is an important part of urban daily mobility, especially in working days. However, the characteristic of the mobility network formed by the commuting of urban residents and its impact on the internal structure of the city are still an important work that needs to be explored further. Aiming to study the living–working interaction pattern of meta-populations over urban divisions within cities, a fine-grained dataset of living–working tracking of Shenzhen is curated and used to construct an urban living–working mobility network, and the living–working interaction pattern is analyzed through the community structures of the network. The results show that human daily mobility plays an important role in understanding the formation of urban structure, the administrative divisions of the city affect human daily mobility, and human daily mobility reacts on the formation of urban structure.