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OBJECTIVE: The current study aimed to investigate the baseline immune and inflammatory features and in-hospital outcomes of patients infected with the Omicron variant (PIWO) who presented with different disease severities during the first wave of mass Omicron infections in the Chinese population has occurred. METHOD: A cross-sectional study was conducted on 140 hospitalized PIWO between December 11, 2022, and February 16, 2023. The clinical features, antibodies against SARS-CoV-2, immune cells, and inflammatory cytokines among mildly, severely, and critically ill PIWO at baseline and during follow-up period were compared. RESULT: Patients with severe (n = 49) and critical (n = 35) disease were primarily male, needed invasive mechanical ventilation treatment, and exhibited higher mortality than those with mild disease (n = 56). During acute infection, SARS-CoV-2-specific antibody levels fluctuated with disease severity, serum antibodies increased and the incidence of severe cases decreased in critically ill PIWO over time. Antibody titers in severe or critical PIWO with no antibody responses at baseline did not increase significantly over time. Meanwhile, CD4+T cell, CD8+T cell, and natural killer cell counts were negatively correlated with disease severity, whereas interleukin (IL)-6 and IL-10 levels were positively correlated. In addition, combined diabetes, immunosuppressive therapy before infection, serum amyloid A, IL-10 and neutrophil counts were independently associated with severe and critical illness in PIWO. Among the 11 nonsurvivors, 8, 2, 1 died of respiratory failure, sudden cardiac death, and renal failure, respectively. Compared with survivors, nonsurvivors exhibited lower seropositivity of SARS-CoV-2-specific antibody, reduced CD3+T and CD4+T cell counts, and higher IL-2R, IL-6, IL-8, and IL-10 levels. Of note, lactate dehydrogenase was a significant risk factor of death in severe or critically ill PIWO. CONCLUSION: This present study assessed the dynamic changes of SARS-CoV-2-specific antibodies, immune cells and inflammatory indexes between severely and critically ill PIWO. Critical and dead PIWO featured compromised humoral immune response and excessive inflammation, which broadened the understanding of the pathophysiology of Omicron infection and provides warning markers for severe disease and poor prognosis.
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COVID-19 , Critical Illness , SARS-CoV-2 , Severity of Illness Index , Humans , COVID-19/immunology , COVID-19/mortality , COVID-19/epidemiology , Male , Female , China/epidemiology , SARS-CoV-2/immunology , Middle Aged , Cross-Sectional Studies , Adult , Aged , Antibodies, Viral/blood , Cytokines/blood , Cytokines/immunology , Inflammation/immunologyABSTRACT
The coupling of charge and phonon transport in solids is a long-standing issue for thermoelectric performance enhancement. Herein, two new narrow-gap semiconductors with the same chemical formula of GeSe0.65Te0.35 (GST) are rationally designed and synthesized: one with a layered hexagonal structure (H-GST) and the other with a non-layered rhombohedral structure (R-GST). Thanks to the three-dimensional (3D) network structure, R-GST possesses a significantly larger weighted mobility than H-GST. Surprisingly, 3D-structured R-GST displays an extremely low lattice thermal conductivity of â¼0.5 W m-1 K-1 at 523 K, which is comparable to that of layered H-GST. The two-dimensional (2D)-like phonon transport in R-GST stems from the unique off-centering Ge atoms that induce ferroelectric instability, yielding soft polar phonons, as demonstrated by the Boson peak detected by the low-temperature specific heat and calculated phonon spectra. Furthermore, 1 mol % doping of Sb is utilized to successfully suppress the undesired phase transition of R-GST toward H-GST at elevated temperatures. Consequently, a peak ZT of 1.1 at 623 K is attained in the rhombohedral Ge0.99Sb0.01Se0.65Te0.35 sample, which is 1 order of magnitude larger than that of GeSe. This work demonstrates the feasibility of exploring high-performance thermoelectric materials with decoupled charge and phonon transport in off-centering compounds.
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PURPOSE: Histopathological growth patterns (HGPs) of colorectal liver metastases (CRLMs) have prognostic value. However, the differentiation of HGPs relies on postoperative pathology. This study aimed to develop a magnetic resonance imaging (MRI)-based radiomic model to predict HGP pre-operatively, following the latest guidelines. METHODS: This retrospective study included 93 chemotherapy-naïve patients with CRLMs who underwent contrast-enhanced liver MRI and a partial hepatectomy between 2014 and 2022. Radiomic features were extracted from the tumor zone (RTumor), a 2-mm outer ring (RT+2), a 2-mm inner ring (RT-2), and a combined ring (R2+2) on late arterial phase MRI images. Analysis of variance method (ANOVA) and least absolute shrinkage and selection operator (LASSO) algorithms were used for feature selection. Logistic regression with five-fold cross-validation was used for model construction. Receiver operating characteristic curves, calibrated curves, and decision curve analyses were used to assess model performance. DeLong tests were used to compare different models. RESULTS: Twenty-nine desmoplastic and sixty-four non-desmoplastic CRLMs were included. The radiomic models achieved area under the curve (AUC) values of 0.736, 0.906, 0.804, and 0.794 for RTumor, RT-2, RT+2, and R2+2, respectively, in the training cohorts. The AUC values were 0.713, 0.876, 0.785, and 0.777 for RTumor, RT-2, RT+2, and R2+2, respectively, in the validation cohort. RT-2 exhibited the best performance. CONCLUSION: The MRI-based radiomic models could predict HGPs in CRLMs pre-operatively.
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OBJECTIVE: To look into the effects of different anesthesia methods on the labor process and the expression of serum estrogen and progesterone in primiparas with painless labor. METHODS: 60 primiparas receiving painless labor were selected as the research objects, and they were divided into either a Spinal & Continuous epidural anesthesia group (n = 30) or a continuous epidural anesthesia group (n = 30), anesthesia is administered using the corresponding anesthesia method. The authors compared serum estrogen and progesterone, inflammatory index expression, pain degree and neonatal health status in different periods. RESULTS: At T2 and T3, serum P, LH, FSH and E2 levels in the Spinal & Continuous epidural anesthesia group were signally lower than those in the Spinal & Continuous epidural anesthesia group (p < 0.05). Spinal & Continuous epidural anesthesia group harbored faster onset and longer duration of sensory block and motor block than the Continuous epidural anesthesia group (p < 0.05). SAS and SDS scores of the Spinal & Continuous epidural anesthesia group were clearly lower than those of the Continuous epidural anesthesia group (p < 0.05). VAS score and serum TNF-α, IL-6 levels of pregnant women in the Spinal & Continuous epidural anesthesia group were memorably lower than those in the Continuous epidural anesthesia group at T2 and T3 (p < 0.05). The total incidence of postoperative complications in the Spinal & Continuous epidural anesthesia group was distinctively lower than that in the Continuous epidural anesthesia group (p < 0.05). CONCLUSION: Spinal anesthesia combined with continuous epidural anesthesia has a better anesthesia effect in the painless labor of primiparas, which can effectually ameliorate the labor process and the expression of serum estrogen and progesterone.
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Anesthesia, Epidural , Estrogens , Postpartum Period , Progesterone , Humans , Female , Pregnancy , Progesterone/blood , Anesthesia, Epidural/methods , Adult , Estrogens/blood , Postpartum Period/blood , Labor, Obstetric/blood , Anesthesia, Spinal/methods , Anesthesia, Obstetrical/methods , Young Adult , Time Factors , Pain Measurement , Parity , Interleukin-6/blood , Tumor Necrosis Factor-alpha/bloodABSTRACT
The combination of all-inorganic perovskites (PVSKs) and polymers allows for free-standing flexible optoelectronic devices. However, solubility difference of the PVSK precursors and concerns over the compatibility between polymer carriers and PVSKs imply a great challenge to incorporate different kinds of PVSKs into polymer matrices by the same manufacturing process. In this work, PVSK precursors are introduced into poly(2-hydroxyethyl acrylate) (PHEA) hydrogels in sequence, in which the PVSK-gel composites are achieved with full-color emissions by simply varying the precursor species. Moreover, it is found that CsBr has a higher interaction energy with the (111) plane of CsPbBr3 than the (110) plane; thus, the CsPbBr3 crystals with a shape of truncated cube and tetragon are observed during the CsPbBr3-Cs4PbBr6 phase transition over time. The PVSK-gel composites feature excellent bendability, elasticity, and stretchable deformation (tensile strain > 500%), which allows for 3D printing emissive customized stereoscopic architectures with shape-memory features.
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Pregabalin is a medication primarily used in the treatment of neuropathic pain and anxiety disorders, owing to its gabapentinoid properties. Pregabalin monotherapy faces limitations due to its variable efficacy and dose-dependent adverse reactions. In this study, we conducted a comprehensive investigation into the potentiation of pregabalin's analgesic effects by dexborneol, a neuroprotective bicyclic monoterpenoid compound. We performed animal experiments where pain models were induced using two methods: peripheral nerve injury, involving axotomy and ligation of the tibial and common peroneal nerves, and incisional pain through a longitudinal incision in the hind paw, while employing a multifaceted methodology that integrates behavioral pharmacology, molecular biology, neuromorphology, and lipidomics to delve into the mechanisms behind this potentiation. Dexborneol was found to enhance pregabalin's efficacy by promoting its transportation to the central nervous system, disrupting self-amplifying vicious cycles via the reduction of HMGB1 and ATP release, and exerting significant anti-oxidative effects through modulation of central lipid metabolism. This combination therapy not only boosted pregabalin's analgesic property but also notably decreased its side effects. Moreover, this therapeutic cocktail exceeded basic pain relief, effectively reducing neuroinflammation and glial cell activation-key factors contributing to persistent and chronic pain. This study paves the way for more tolerable and effective analgesic options, highlighting the potential of dexborneol as an adjuvant to pregabalin therapy.
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Background: Hepatocellular carcinoma (HCC) is often associated with the overexpression of multiple proteins and genes. For instance, patients with HCC and a high expression of the glypican-3 (GPC3) gene have a poor prognosis, and noninvasive assessment of GPC3 expression before surgery is helpful for clinical decision-making. Therefore, our primary aim in this study was to develop and validate multisequence magnetic resonance imaging (MRI) radiomics nomograms for predicting the expression of GPC3 in individuals diagnosed with HCC. Methods: We conducted a retrospective analysis of 143 patients with HCC, including 123 cases from our hospital and 20 cases from The Cancer Genome Atlas (TCGA) or The Cancer Imaging Archive (TCIA) public databases. We used preoperative multisequence MRI images of the patients for the radiomics analysis. We extracted and screened the imaging histologic features using fivefold cross-validation, Pearson correlation coefficient, and the least absolute shrinkage and selection operator (LASSO) analysis method. We used logistic regression (LR) to construct a radiomics model, developed nomograms based on the radiomics scores and clinical parameters, and evaluated the predictive performance of the nomograms using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Results: Our multivariate analysis results revealed that tumor morphology (P=0.015) and microvascular (P=0.007) infiltration could serve as independent predictors of GPC3 expression in patients with HCC. The nomograms integrating multisequence radiomics radiomics score, tumor morphology, and microvascular invasion had an area under the curve (AUC) value of 0.989. This approach was superior to both the radiomics model (AUC 0.979) and the clinical model (AUC 0.793). The sensitivity, specificity, and accuracy of 0.944, 0.800, and 0.913 for the test set, respectively, and the model's calibration curve demonstrated good consistency (Brier score =0.029). The decision curve analysis (DCA) indicated that the nomogram had a higher net clinical benefit for predicting the expression of GPC3. External validation of the model's prediction yielded an AUC value of 0.826. Conclusions: Our study findings highlight the close association of multisequence MRI imaging and radiomic features with GPC3 expression. Incorporating clinical parameters into nomograms can offer valuable preoperative insights into tailoring personalized treatment plans for patients diagnosed with HCC.
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OBJECTIVES: This study aimed to assess the trends of healthy aging and investigate its determinants in the middle-aged population. STUDY DESIGN: This was a longitudinal study. METHODS: The sample comprised 3043 participants aged 45-59 years from the China Longitudinal Study of Health and Retirement 2011-2018. We plotted the prevalence across four waves and used ordered logistic models to investigate the determinants of cumulative times of healthy aging. RESULTS: We enrolled 3043 middle-aged people in our study. The prevalence of healthy aging is 28.2% at baseline but subsequently decreased to 19.72% at wave 4. Active socializing consistently ranked the lowest among the five dimensions. Participants with older age (odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.94-0.97), low monthly income (OR = 0.82, 95% CI: 0.69-0.97) or lived in urban (OR = 0.81, 95% CI: 0.70-0.94) were less likely to have per time increase in healthy aging. Participants with more than primary school degree (OR = 1.79, 95% CI: 1.31-2.46), high life satisfaction (OR = 2.38, 95% CI: 1.86-3.06), and good self-report health (OR = 1.97, 95% CI: 1.66-2.34) were more likely to have healthy aging. CONCLUSION: The number of middle-aged individuals in China who achieved healthy aging is declining and eventually less than one in five, which was far from ideal. Particular attention should be paid to older, women, urban dwellers, individuals with low income, low life satisfaction or poor self-report health. It is urgent to develop public health policies to improve the health and well-being of the middle-aged population.
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Healthy Aging , Humans , Longitudinal Studies , China/epidemiology , Male , Female , Middle Aged , Retirement/statistics & numerical data , Socioeconomic FactorsABSTRACT
With mounting demand for high-quality agricultural products and the relentless exploitation of arable land resources, finding sustainable ways to safely cultivate food crops is becoming ever more important. Here, we investigated the effects of the integrated cropping technique "straw return + intercropping" on the soil aggregates as well as the microbial biomass carbon (MBC) content, enzyme activities and microbial diversity in soils of maize and soybean crops. Our results show that in comparison to straw removal and monoculture, straw return and intercropping increase the rhizosphere's MBC content (59.10%) of soil, along with urease (47.82%), sucrase (57.14%), catalase (16.14%) and acid phosphatase (40.66%) activities as well as the microbial diversity under maize and soybean. Under the same straw treatment, the yield of maize when intercropped surpassed that when grown in monoculture, with the land equivalent ratio of the intercropping treatment under straw return being highest. Overall, the intercropping of maize and soybean is beneficial for the healthy development of sustainable agriculture in the black soil region of northeast China, especially when combined with straw return to fields.
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Purpose: This study aims to explore the value of clinical features, CT imaging signs, and radiomics features in differentiating between adults and children with Mycoplasma pneumonia and seeking quantitative radiomic representations of CT imaging signs. Materials and methods: In a retrospective analysis of 981 cases of mycoplasmal pneumonia patients from November 2021 to December 2023, 590 internal data (adults:450, children: 140) randomly divided into a training set and a validation set with an 8:2 ratio and 391 external test data (adults:121; children:270) were included. Using univariate analysis, CT imaging signs and clinical features with significant differences (p < 0.05) were selected. After segmenting the lesion area on the CT image as the region of interest, 1,904 radiomic features were extracted. Then, Pearson correlation analysis (PCC) and the least absolute shrinkage and selection operator (LASSO) were used to select the radiomic features. Based on the selected features, multivariable logistic regression analysis was used to establish the clinical model, CT image model, radiomic model, and combined model. The predictive performance of each model was evaluated using ROC curves, AUC, sensitivity, specificity, accuracy, and precision. The AUC between each model was compared using the Delong test. Importantly, the radiomics features and quantitative and qualitative CT image features were analyzed using Pearson correlation analysis and analysis of variance, respectively. Results: For the individual model, the radiomics model, which was built using 45 selected features, achieved the highest AUCs in the training set, validation set, and external test set, which were 0.995 (0.992, 0.998), 0.952 (0.921, 0.978), and 0.969 (0.953, 0.982), respectively. In all models, the combined model achieved the highest AUCs, which were 0.996 (0.993, 0.998), 0.972 (0.942, 0.995), and 0.986 (0.976, 0.993) in the training set, validation set, and test set, respectively. In addition, we selected 11 radiomics features and CT image features with a correlation coefficient r greater than 0.35. Conclusion: The combined model has good diagnostic performance for differentiating between adults and children with mycoplasmal pneumonia, and different CT imaging signs are quantitatively represented by radiomics.
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Hydrogel-based electronics have inherent similarities to biological tissues and hold potential for wearable applications. However, low conductivity, poor stretchability, nonpersonalizability, and uncontrollable dehydration during use limit their further development. In this study, projection stereolithography 3D printing high-conductive hydrogel for flexible passive wireless sensing is reported. The prepared photocurable silver-based hydrogel is rapidly planarized into antenna shapes on substrates using surface projection stereolithography. After partial dehydration, silver flakes within the circuits form sufficient conductive pathways to achieve high conductivity (387 S cm-1). By sealing the circuits to prevent further dehydration, the resistance remains stable when tensile strain is less than 100% for at least 30 days. Besides, the sealing materials provide versatile functionalities, such as stretchability and shape memory property. Customized flexible radio frequency identification tags are fabricated by integrating with commercial chips to complete the accurate recognition of eye movement, realizing passive wireless sensing.
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Objective: Ear acupuncture, as a system for treating and preventing diseases through stimulation of points on the auricle, has been systematically introduced during the last 60 years. Although the auricular cartography was described somatotopically as an inverted fetus by Paul Nogier, MD, the underlying mechanism of auricular stimulation remains unclear. The aim of this research was to gain an understanding of the structural basis of auricular stimulation, as well as showing the distribution of the nerve fibers, and the blood and lymphatic vessels. Materials and Methods: The distribution of nerve fibers, and blood and lymphatic vessels was examined in whole-mount auricular skins of mice by combining the biomarkers protein gene product 9.5, cluster of differentiation 31, and lymphatic-vessel endothelial hyaluronan receptor-1 following tissue-clearing treatment with multiple immunofluorescent staining. Results: The labeled nerve fibers, and the blood and lymphatic vessels were distributed extensively in the inner and outer parts of the auricular skin. Auricular nerves aligning with blood vessels ran from the basal region to the peripheral region and crossed over lymphatic vessels, thus forming the neural, vascular, and lymphatic networks. Conclusions: As these are important tissue components of auricular skin, this result implies that the auricular nerve fibers, and blood and lymphatic vessels may coordinate with each other to respond directly to auricular stimulation.
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The polar oceans play a vital role in regulating atmospheric CO2 concentrations (pCO2) during the Pleistocene glacial cycles. However, despite being the largest modern reservoir of respired carbon, the impact of the subarctic Pacific remains poorly understood due to limited records. Here, we present high-resolution, 230Th-normalized export productivity records from the subarctic northwestern Pacific covering the last five glacial cycles. Our records display pronounced, glacial-interglacial cyclicity superimposed with precessional-driven variability, with warm interglacial climate and high boreal summer insolation providing favorable conditions to sustain upwelling of nutrient-rich subsurface waters and hence increased export productivity. Our transient model simulations consistently show that ice sheets and to a lesser degree, precession are the main drivers that control the strength and latitudinal position of the westerlies. Enhanced upwelling of nutrient/carbon-rich water caused by the intensification and poleward migration of the northern westerlies during warmer climate intervals would have led to the release of previously sequestered CO2 from the subarctic Pacific to the atmosphere. Our results also highlight the significant role of the subarctic Pacific in modulating pCO2 changes during the Pleistocene climate cycles, especially on precession timescale ( ~ 20 kyr).
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Dissecting the genetic components that contribute to the two main subphenotypes of steroid-sensitive nephrotic syndrome (SSNS) using genome-wide association studies (GWAS) strategy is important for understanding the disease. We conducted a multicenter cohort study (360 patients and 1835 controls) combined with a GWAS strategy to identify susceptibility variants associated with the following two subphenotypes of SSNS: steroid-sensitive nephrotic syndrome without relapse (SSNSWR, 181 patients) and steroid-dependent/frequent relapse nephrotic syndrome (SDNS/FRNS, 179 patients). The distribution of two single-nucleotide polymorphisms (SNPs) in ANKRD36 and ALPG was significant between SSNSWR and healthy controls, and that of two SNPs in GAD1 and HLA-DQA1 was significant between SDNS/FRNS and healthy controls. Interestingly, rs1047989 in HLA-DQA1 was a candidate locus for SDNS/FRNS but not for SSNSWR. No significant SNPs were observed between SSNSWR and SDNS/FRNS. Meanwhile, chromosome 2:171713702 in GAD1 was associated with a greater steroid dose (>0.75 mg/kg/d) upon relapse to first remission in patients with SDNS/FRNS (odds ratio = 3.14; 95% confidence interval, 0.97-9.87; P = 0.034). rs117014418 in APOL4 was significantly associated with a decrease in eGFR of greater than 20% compared with the baseline in SDNS/FRNS patients (P = 0.0001). Protein-protein intersection network construction suggested that HLA-DQA1 and HLA-DQB1 function together through GSDMA. Thus, SSNSWR belongs to non-HLA region-dependent nephropathy, and the HLA-DQA/DQB region is likely strongly associated with disease relapse, especially in SDNS/FRNS. The study provides a novel approach for the GWAS strategy of SSNS and contributes to our understanding of the pathological mechanisms of SSNSWR and SDNS/FRNS.
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Background: Osteoporosis, a disease stemming from bone metabolism irregularities, affects approximately 200 million people worldwide. Timely detection of osteoporosis is pivotal in grappling with this public health challenge. Deep learning (DL), emerging as a promising methodology in the field of medical imaging, holds considerable potential for the assessment of bone mineral density (BMD). This study aimed to propose an automated DL framework for BMD assessment that integrates localization, segmentation, and ternary classification using various dominant convolutional neural networks (CNNs). Methods: In this retrospective study, a cohort of 2,274 patients underwent chest computed tomography (CT) was enrolled from January 2022 to June 2023 for the development of the integrated DL system. The study unfolded in 2 phases. Initially, 1,025 patients were selected based on specific criteria to develop an automated segmentation model, utilizing 2 VB-Net networks. Subsequently, a distinct cohort of 902 patients was employed for the development and testing of classification models for BMD assessment. Then, 3 distinct DL network architectures, specifically DenseNet, ResNet-18, and ResNet-50, were applied to formulate the 3-classification BMD assessment model. The performance of both phases was evaluated using an independent test set consisting of 347 individuals. Segmentation performance was evaluated using the Dice similarity coefficient; classification performance was appraised using the receiver operating characteristic (ROC) curve. Furthermore, metrics such as the area under the curve (AUC), accuracy, and precision were meticulously calculated. Results: In the first stage, the automatic segmentation model demonstrated excellent segmentation performance, with mean Dice surpassing 0.93 in the independent test set. In the second stage, both the DenseNet and ResNet-18 demonstrated excellent diagnostic performance in detecting bone status. For osteoporosis, and osteopenia, the AUCs were as follows: DenseNet achieved 0.94 [95% confidence interval (CI): 0.91-0.97], and 0.91 (95% CI: 0.87-0.94), respectively; ResNet-18 attained 0.96 (95% CI: 0.92-0.98), and 0.91 (95% CI: 0.87-0.94), respectively. However, the ResNet-50 model exhibited suboptimal diagnostic performance for osteopenia, with an AUC value of only 0.76 (95% CI: 0.69-0.80). Alterations in tube voltage had a more pronounced impact on the performance of the DenseNet. In the independent test set with tube voltage at 100 kVp images, the accuracy and precision of DenseNet decreased on average by approximately 14.29% and 18.82%, respectively, whereas the accuracy and precision of ResNet-18 decreased by about 8.33% and 7.14%, respectively. Conclusions: The state-of-the-art DL framework model offers an effective and efficient approach for opportunistic osteoporosis screening using chest CT, without incurring additional costs or radiation exposure.
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Context: Iron is an essential element in the human body and plays a critical role in many physiological and cellular processes. However, the association between iron status and the risk of all-cause or cause-specific mortality has not been well-investigated. And it is unclear whether the association between iron metabolic biomarkers and the risk of mortality differs between people with and without diabetes mellitus (DM). Objective: This work aimed to investigate associations between iron metabolic biomarkers and all-cause and cause-specific mortality risk in the general population, and heterogeneities in the associations among population with and without DM.. Methods: A total of 29 166 adults from the National Health and Nutrition Examination Survey (NHANES) III and NHANES 1999 to 2010 were included, with linkage to the National Death Index to December 31, 2019. Cox proportional-hazard models and Fine-Gray subdistribution hazard models were used to estimate associations between iron metabolic biomarkers and outcomes. Results: During a median follow-up of 18.83 years, 9378 deaths were observed, including 3420 cardiovascular disease (CVD) deaths and 1969 cancer deaths. A significant linear association between serum ferritin (SF) and all-cause mortality was observed among the overall population and those without DM. J-shaped associations between transferrin saturation (TSAT) and all-cause and CVD mortality were observed among all populations. In the overall population, compared to the first quartile (Q1) group, the adjusted hazard ratio (HR) (95% CI) for all-cause mortality was 1.07 (1.00-1.15), 1.05 (0.98-1.12), 1.13 (1.05-1.21) in Q2, Q3, and Q4 groups for SF, while the HR was 0.94 (0.88-0.99), 0.92 (0.86-0.97), and 0.93 (0.88-0.99) for TSAT. In individuals without DM, the adjusted HR of the Q4 of SF were 1.19 (1.03-1.37) for CVD mortality and 1.25 (1.05-1.48) for cancer mortality. In individuals with DM, the adjusted HRs of the Q4 of TSAT were 0.76 (0.62-0.93) for CVD mortality and 1.47 (1.07-2.03) for cancer mortality. Conclusion: Iron metabolism abnormalities increase mortality risk in the general population. The associations of iron status with mortality were significantly different between individuals with and without DM, which indicated tailored strategies for iron homeostasis are needed.
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OBJECTIVES: Differentiating chronic total occlusion (CTO) from subtotal occlusion (SO) is often difficult to make from coronary computed tomography angiography (CCTA). We developed a CCTA-based radiomics model to differentiate CTO and SO. METHODS: A total of 66 patients with SO underwent CCTA before invasive angiography and were matched to 66 patients with CTO. Comprehensive imaging analysis was conducted for all lesioned vessels, involving the automatic identification of the lumen within the occluded segment and extraction of 1,904 radiomics features. Radiomics models were then constructed to assess the discriminative value of these features in distinguishing CTO from SO. External validation of the model was performed using data from another medical center. RESULTS: Compared to SO patients, CTO patients had more blunt stumps (internal: 53/66 (80.3%) vs. 39/66 (59.1%); external: 36/50 (72.0%) vs. 20/50 (40.0%), both p < 0.01), longer lesion length (internal: median length 15.4 mm[IQR: 10.4-22.3 mm] vs. 8.7 mm[IQR: 4.9-12.6 mm]; external:11.8 mm[IQR: 6.1-23.4 mm] vs. 6.2 mm[IQR: 3.5-9.1 mm]; both p < 0.001). Sixteen unique radiomics features were identified after the least absolute shrinkage and selection operator regression. When added to the combined model including imaging features, radiomics features provided increased value for distinguishing CTO from SO (AUC, internal: 0.772 vs. 0.846; p = 0.023; external: 0.718 vs. 0.781, p = 0.146). CONCLUSIONS: The occluded segment vessels of CTO and SO have different radiomics signatures. The combined application of radiomics features and imaging features based on CCTA extraction can enhance diagnostic confidence.
Subject(s)
Coronary Occlusion , Percutaneous Coronary Intervention , Humans , Computed Tomography Angiography/methods , Coronary Occlusion/diagnostic imaging , Coronary Occlusion/pathology , Radiomics , Coronary Angiography/methods , Retrospective Studies , Predictive Value of Tests , Chronic DiseaseABSTRACT
Rationale and objectives: Radiomic models based on normal-resolution (NR) computed tomography angiography (CTA) images can fail to distinguish between symptomatic and asymptomatic carotid atherosclerotic plaques. This study aimed to explore the effectiveness of a deep learning-based three-dimensional super-resolution (SR) CTA radiomic model for improved identification of symptomatic carotid atherosclerotic plaques. Materials and methods: A total of 193 patients with carotid atherosclerotic plaques were retrospectively enrolled and allocated into either a symptomatic (n = 123) or an asymptomatic (n = 70) groups. SR CTA images were derived from NR CTA images using deep learning-based three-dimensional SR technology. Handcrafted radiomic features were extracted from both the SR and NR CTA images and three risk models were developed based on manually measured quantitative CTA characteristics and NR and SR radiomic features. Model performances were assessed via receiver operating characteristic, calibration, and decision curve analyses. Results: The SR model exhibited the optimal performance (area under the curve [AUC] 0.820, accuracy 0.802, sensitivity 0.854, F1 score 0.847) in the testing cohort, outperforming the other two models. The calibration curve analyses and Hosmer-Lemeshow test demonstrated that the SR model exhibited the best goodness of fit, and decision curve analysis revealed that SR model had the highest clinical value and potential patient benefits. Conclusions: Deep learning-based three-dimensional SR technology could improve the CTA-based radiomic models in identifying symptomatic carotid plaques, potentially providing more accurate and valuable information to guide clinical decision-making to reduce the risk of ischemic stroke.
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Vitamin D deficiency (VDD) during early life emerges as a potential risk factor for autism spectrum disorder (ASD). Individuals with autism commonly exhibit lower vitamin D (VD) levels compared to the general population, and VD deficiency is prevalent during pregnancy and lactation. Moreover, gastrointestinal comorbidity, prevalent in ASD patients, correlates closely with disruptions in the gut microbiota and altered intestinal permeability. Therefore, it is fascinating and significant to explore the effects of maternal VD deficiency during pregnancy and lactation on the maturation of the gut microbiota of the offspring and its relevance to autism spectrum disorders. In this study, we established maternal pregnancy and lactation VD-deficient mouse models, employed shotgun macrogenomic sequencing to unveil alterations in the gut microbiome of offspring mice, and observed autism-related behaviours. Furthermore, fecal microbial transplantation (FMT) reversed repetitive and anxious behaviours and alleviated social deficits in offspring mice by modulating the gut microbiota and increasing short-chain fatty acid levels in the cecum, along with influencing the concentrations of claudin-1 and occludin in the colon. Our findings confirm that VDD during pregnancy and lactation is a risk factor for autism in the offspring, with disturbances in the structure and function of the offspring's gut microbiota contributing at least part of the effect. The study emphasises the importance of nutrition and gut health early in life. Simultaneously, this study further demonstrates the effect of VDD on ASD and provides potential ideas for early prevention and intervention of ASD.