The consistent fuzzy suitability assessment of forest land resources with multi-source heterogeneous data.

In view of the suitability assessment of forest land resources, a consistent fuzzy assessment method with heterogeneous information is proposed. Firstly, some formulas for transforming large-scale real data and interval data into fuzzy numbers are provided. To derive the unified representation of multi-granularity linguistic assessment information, a fuzzy quantitative transformation for multi-granularity uncertain linguistic information is proposed. The proofs of the desirable properties and some normalized formulas for the trapezoidal fuzzy numbers are presented simultaneously. Next, the objective weight of each assessment indicator is further determined by calculating the Jaccard-Cosine similarity between the trapezoidal fuzzy numbers. Moreover, the trapezoidal fuzzy numbers corresponding to the comprehensive assessment values of each alternative are obtained. The alternatives are effectively ranked according to the distance from the centroid of the trapezoidal fuzzy number to the origin. Finally, based on the proposed consistent fuzzy assessment method, the suitability assessment of forest land resources is achieved under a multi-source heterogeneous data setting.

Excessive fat expenditure in MCT-induced heart failure rats is associated with BMAL1/REV-ERBα circadian rhythmic loop disruption.

Fat loss predicts adverse outcomes in advanced heart failure (HF). Disrupted circadian clocks are a primary cause of lipid metabolic issues, but it's unclear if this disruption affects fat expenditure in HF. To address this issue, we investigated the effects of disruption of the BMAL1/REV-ERBα circadian rhythmic loop on adipose tissue metabolism in HF.50 Wistar rats were initially divided into control (n = 10) and model (n = 40) groups. The model rats were induced with HF via monocrotaline (MCT) injections, while the control group received equivalent solvent injections. After establishing the HF model, the model group was further subdivided into four groups: normal rhythm (LD), inverted rhythm (DL), lentivirus vector carrying Bmal1 short hairpin RNA (LV-Bmal1 shRNA), and empty lentivirus vector control (LV-Control shRNA) groups, each with 10 rats. The DL subgroup was exposed to a reversed light-dark cycle of 8 h: 16 h (dark: light), while the rest adhered to normal light-dark conditions (light: dark 12 h: 12 h). Histological analyses were conducted using H&E, Oil Red O, and Picrosirius red stains to examine adipose and liver tissues. Immunohistochemical staining, RT-qPCR, and Western blotting were performed to detect markers of lipolysis, lipogenesis, and beiging of white adipose tissue (WAT), while thermogenesis indicators were detected in brown adipose tissue (BAT). The LD group rats exhibited decreased levels of BMAL1 protein, increased levels of REV-ERBα protein, and disrupted circadian circuits in adipose tissue compared to controls. Additionally, HF rats showed reduced adipose mass and increased ectopic lipid deposition, along with smaller adipocytes containing lower lipid content and fibrotic adipose tissue. In the LD group WAT, expression of ATGL, HSL, PKA, and p-PKA proteins increased, alongside elevated mRNA levels of lipase genes (Hsl, Atgl, Peripilin) and FFA ß-oxidation genes (Cpt1, acyl-CoA). Conversely, lipogenic gene expression (Scd1, Fas, Mgat, Dgat2) decreased, while beige adipocyte markers (Cd137, Tbx-1, Ucp-1, Zic-1) and UCP-1 protein expression increased. In BAT, HF rats exhibited elevated levels of PKA, p-PKA, and UCP-1 proteins, along with increased expression of thermogenic genes (Ucp-1, Pparγ, Pgc-1α) and lipid transportation genes (Cd36, Fatp-1, Cpt-1). Plasma NT-proBNP levels were higher in LD rats, accompanied by elevated NE and IL-6 levels in adipose tissue. Remarkably, morphologically, the adipocytes in the DL and LV-Bmal1 shRNA groups showed reduced size and lower lipid content, while lipid deposition in the liver was more pronounced in these groups compared to the LD group. At the gene/protein level, the BMAL1/REV-ERBα circadian loop exhibited severe disruption in LV-Bmal1 shRNA rats compared to LD rats. Additionally, there was increased expression of lipase genes, FFA ß oxidation genes, and beige adipocyte markers in WAT, as well as higher expression of thermogenic genes and lipid transportation genes in BAT. Furthermore, plasma NT-proBNP levels and adipose tissue levels of NE and IL-6 were elevated in LV-Bmal1 shRNA rats compared with LD rats. The present study demonstrates that disruption of the BMAL1/REV-ERBα circadian rhythmic loop is associated with fat expenditure in HF. This result suggests that restoring circadian rhythms in adipose tissue may help counteract disorders of adipose metabolism and reduce fat loss in HF.

Disparities in mortality risk after diagnosis of hematological malignancies in 185 countries: A global data analysis.

This study was to report proxy measures for mortality risk in patients with hematological malignancies across 185 countries globally and explore its association with their socioeconomic status and treatment. The incidence, mortality, and 5-year prevalence data were extracted from the GLOBOCAN database. The data regarding the human development index (HDI), gross national income (GNI), vulnerability index, and concordance with cancer Essential Medicines List (EML) were obtained from open-source reports. The ratio of mortality to 5-year-prevalence (MPR) and that of mortality to incidence (MIR) were calculated and age-standardized using Segi's world standard population. Finally, the possible associations were assessed using Pearson correlation analyses. In 2020, the global incidence, mortality, and 5-year prevalence of HMs were 1,278,362, 711,840, and 3,616,685, respectively. Global age-standardized MPR and MIR were 0.15 and 0.44, respectively; they varied significantly among 6 regions, 185 countries, 4 HM types, and 4 HDI groups worldwide. Older populations always had higher ratios. The correlation of MPRs and MIRs with HDI, GNI, and concordance with cancer EML was negative, whereas it was positive with the vulnerability index (lower was better). Increasing access to cancer drugs in resource-limited regions with a focus on vulnerable children may aid in reducing HM-related mortality risk.

Integrating Paper-Based Microfluidics and Lateral Flow Strip into Nucleic Acid Amplification Device toward Rapid, Low-Cost, and Visual Diagnosis of Multiple Mycobacteria.

Efficient diagnosis of mycobacterial infections can effectively manage and prevent the transmission of infectious diseases. Unfortunately, existing diagnostic strategies are challenged by long assay times, high costs, and highly specialized expertise to distinguish between pulmonary tuberculosis (PTB) and nontuberculous mycobacterial pulmonary diseases (NTM-PDs). Herein, in this study, an optimized 3D paper-based analytical device (µPAD) is incorporated with a closed lateral flow (LF) strip into a loop-mediated isothermal amplification (LAMP) device (3D-µPAD-LF-LAMP) for rapid, low-cost, and visual detection of pathogenic mycobacteria. The platform's microfluidic feature enhanced the nucleic acid amplification, thereby reducing the costs and time as compared to boiling, easyMAG, and QIAGEN techniques. Moreover, the LF unit is specifically designed to minimize aerosol contamination for a user-friendly and visual readout. 3D-µPAD-LF-LAMP is optimized and assessed using standard strains, demonstrating a limit of detection (LOD) down to 10 fg reaction-1 . In a cohort of 815 patients, 3D-µPAD-LF-LAMP displays significantly better sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and diagnostic accuracy than conventional bacterial culture and Xpert techniques. Collectively, 3D-µPAD-LF-LAMP demonstrates enhanced accessibility, efficiency, and practicality for the diagnosis of multiple pathogenic mycobacteria, which can be applied across diverse clinical settings, thereby ultimately improving public health outcomes.

Assessment of cellular senescence potential of PM2.5 using 3D human lung fibroblast spheroids in vitro model.

Background: Epidemiological studies demonstrate that particulate matter 2.5 (PM2.5) exposure closely related to chronic respiratory diseases. Cellular senescence plays an important role in many diseases. However, it is not fully clear whether PM2.5 exposure could induce cellular senescence in the human lung. In this study, we generated a three-dimensional (3D) spheroid model using isolated primary human lung fibroblasts (HLFs) to investigate the effects of PM2.5 on cellular senescence at the 3D level. Methods: 3D spheroids were exposed to 25-100 µg/ml of PM2.5 in order to evaluate the impact on cellular senescence. SA-ß-galactosidase activity, cell proliferation, and the expression of key genes and proteins were detected. Results: Exposure of the HLF spheroids to PM2.5 yielded a more sensitive cytotoxicity than 2D HLF cell culture. Importantly, PM2.5 exposure induced the rapid progression of cellular senescence in 3D HLF spheroids, with a dramatically increased SA-ß-Gal activity. In exploiting the mechanism underlying the effect of PM2.5 on senescence, we found a significant increase of DNA damage, upregulation of p21 protein levels, and suppression of cell proliferation in PM2.5-treated HLF spheroids. Moreover, PM2.5 exposure created a significant inflammatory response, which may be at least partially associated with the activation of TGF-ß1/Smad3 axis and HMGB1 pathway. Conclusions: Our results indicate that PM2.5 could induce DNA damage, inflammation, and cellular senescence in 3D HLF spheroids, which may provide a new evidence for PM2.5 toxicity based on a 3D model which has been shown to be more in vivo-like in their phenotype and physiology than 2D cultures.

A cellular automata model coupled with partitioning CNN-LSTM and PLUS models for urban land change simulation.

Urbanisation is a key aspect of land use change (LUC), and accurately modelling of urban LUC is crucial for sustainable development. Cellular automata (CA) are widely used in LUC research. However, previous studies have overlooked the significant temporal dependence and spatial heterogeneity associated with LUC. To address these gaps, this study proposes a novel model called KCLP-CA, which integrates k-means, a convolutional neural network (CNN), a long and short-term memory neural network (LSTM), and the popular patch-generation land use model (PLUS). Initially, k-means and CNN are utilised to address spatial heterogeneity, while LSTM tackles temporal dependence. The LSTM and land expansion analysis strategy (LEAS) models of PLUS are employed to obtain land use conversion probability maps. Finally, a simulation of land use dynamic change was conducted using a linear weighted fusion conversion probability map that accounts for random factors. To validate the KCLP-CA model, land use data collected from Hangzhou between 1995 and 2000 were employed. The results showed that the KCLP-CA model outperformed traditional methods, including artificial neural networks and random forest model, with the figure of merit (FoM) index increasing from 2.12% to 4.19%. Random forest analysis of drivers impacting LUC revealed that distance to water and road network density exerted the greatest influence on urban land development in Hangzhou. Incorporation of various policy planning factors affecting urban development yielded simulation results aligning more closely with reality, resulting in a FoM index increase of 1.64-1.76%. In summary, the model developed in this study combines the strengths of two sub models to deliver an accurate and effective simulation of future land use.

Exploring the clinical outcomes and safety profile of inetetamab treatment in metastatic breast cancer patients: A multicenter assessment of a Chinese-origin recombinant Anti-HER2 monoclonal antibody.

BACKGROUND: Inetetamab is a novel recombinant humanized anti-HER2 monoclonal antibody. This study aimed to evaluate the efficacy and safety of inetetamab and predictive factors for response in HER2-positive metastatic breast cancer (MBC) patients. METHODS: A cohort of HER2-positive MBC patients who received inetetamab-based therapy between June 2020 and August 2021 was evaluated. The primary endpoint was progression-free survival (PFS), and the secondary endpoints included objective response rate (ORR) and disease control rate (DCR). Adverse events (AEs) were graded according to the National Cancer Institute Common Toxicity Criteria. RESULTS: A total of 141 patients were included in the final analysis. The median PFS of the entire cohort was 7.1 months. The median number of treatment lines administered was three. The ORR was 36.9 %, and the DCR was 80.9 %. The most frequently employed treatment strategy was inetetamab + chemotherapy (49/141, 34.8 %), followed by inetetamab + HER2-tyrosine kinase inhibitors (HER2-TKIs) + chemotherapy, inetetamab + pertuzumab + chemotherapy, inetetamab + endocrine treatment and inetetamab + HER2-TKIs. Cox multivariate analysis revealed that PFS was associated with liver metastasis (hazard ratio [HR] 2.112, 95 % confidence interval [CI] 1.334-3.343, p = 0.001), previous HER2-TKI treatment (HR 2.019, 95 % CI 1.133-3.597, p = 0.017) and estrogen receptor positivity (HR 0.587, 95 % CI 0.370-0.934, p = 0.024). The toxicity was tolerable, with neutropenia being the most common treatment-related grade 3/4 AE (14.9 %). CONCLUSION: Inetetamab demonstrates effectiveness with a manageable safety profile, offering a promising therapeutic option for HER2-positive breast cancer patients who have shown resistance to prior anti-HER2 treatments.

Microdosimetric assessment about proton spread-out Bragg peak at different depths based on the normal human mesh-type cell population model.

Objective.In clinical proton therapy, the spread-out Bragg peak (SOBP) is commonly used to fit the target shape. Dose depositions at microscopic sites vary, even with a consistent absorbed dose (D) in SOBP. In the present study, monolayer mesh-type cell population models were developed for microdosimetric assessment at different SOBP depths.Approach.Normal human bronchial epithelial (BEAS-2B) and hepatocytes (L-O2) mesh-type cell models were constructed based on fluorescence tomography images of normal human cells. Particle transport simulation in cell populations was performed coupled with Monte Carlo software PHITS. The relationship between microdosimetry and macrodosimetry of SOBP at different depths was described by analyzing the microdosimetric indicators such as specific energyz,specific energy distributionfz,D,and relative standard deviationσz/z¯within cells. Additionally, the microdosimetric distributions characteristics and their contributing factors were also discussed.Main results.The microscopic dose distribution is strongly influenced by cellular size, shape, and material. The mean specific energyz¯of nucleus and cytoplasm in the cell population is greater than the overall absorbed dose of the cell population model (Dp), with a maximumz¯/Dpof 1.1. The cellular dose distribution is different between the BEAS-2B mesh-type model and its concentric ellipsoid geometry-type model, which difference inz¯is about 10.3% for the nucleus and about 7.5% for the cytoplasm with the SOBP depth of 15 cm. WhenD= 2 Gy, the maximumzof L-O2 nucleus reaches 2.8 Gy andσz/z¯is 5.1% at the mid-depth SOBP (16-18 cm); while the maximumzof the BEAS-2B nucleus reaches 2.2 Gy with only 2.7% ofσz/z¯.Significance.The significant variation of microdosimetric distributions of SOBP different depths indicates the necessity to use mesh-type cell population models, which have the potential to be compared with biological results and build the bio-physical model.

Multiple Mesh-type Real Human Cell Models for Dosimetric Application Coupled with Monte Carlo Simulations.

The mesh-type models are superior to voxel models in cellular dose assessment coupled with Monte Carlo codes. The aim of this study was to expand the micron-scale mesh-type models based on the fluorescence tomography of real human cells, and to investigate the feasibility of these models in the application of various irradiation scenarios and Monte Carlo codes. Six different human cell lines, including pulmonary epithelial BEAS-2B, embryonic kidney 293T, hepatocyte L-02, B-lymphoblastoid HMy2.CIR, Gastric mucosal GES-1, and intestine epithelial FHs74Int, were adopted for single mesh-type models reconstruction and optimization based on laser confocal tomography images. Mesh-type models were transformed into the format of polygon mesh and tetrahedral mesh for the GATE and PHITS Monte Carlo codes, respectively. The effect of model reduction was analyzed by dose assessment and geometry consideration. The cytoplasm and nucleus doses were obtained by designating monoenergetic electrons and protons as external irradiation, and S values with different "target-source" combinations were calculated by assigning radioisotopes as internal exposure. Four kinds of Monte Carlo codes were employed, i.e., GATE with "Livermore," "Standard" and "Standard and Geant4-DNA mixed" models for electrons and protons, as well as PHITS with "EGS" mode for electrons and radioisotopes. Multiple mesh-type real human cellular models can be applied to Monte Carlo codes directly without voxelization when combined with certain necessary surface reduction. Relative deviations between different cell types were observed among various irradiation scenarios. The relative deviation of nucleus S value reaches up to 85.65% between L-02 and GES-1 cells by 3H for the "nucleus-nucleus" combination, while that of 293T and FHs74Int nucleus dose for external beams at a 5.12 cm depth of water is 106.99%. Nucleus with smaller volume is far more affected by physical codes. There is a considerable deviation for dose within BEAS-2B at the nanoscale. The multiple mesh-type real cell models were more versatile than voxel models and mathematical models. The present study provided several models which can easily be extended to other cell types and irradiation scenarios for RBE estimations and biological effect predictions, including radiation biological experiments, radiotherapy and radiation protection.

The Role of Contextual Factors in Shaping Urban Older Adults' Intention of Institutional Care in China: A Mixed-Methods Study.

BACKGROUND: This mixed-methods study explores older people's intention of institutional care and its contributing contextual factors, and the meaning given to their intention by older adults in the transitioning Chinese society. METHODS: Guided by the extended Anderson model and frameworks of the ecological theory of aging, survey data collected from 1937 Chinese older adults were used. Transcripts from six focus group interviews were analyzed to incorporate the voices of the participants. RESULTS: Community environment and services, health services, financial services, and regional service organizations were related to the institutional care intention of older people. The qualitative analysis showed that the reported conflicting feelings about institutional care was driven by the lack of supporting resources and age-friendly environment. The findings of this study suggested that the reported intention of Chinese older adults for institutional care may not be an ideal choice but a compromise or, in some cases, a forced choice. CONCLUSIONS: Rather than treating the stated institutional intention as a simple expression of older Chinese people's likes or desires, the intention of institutional care should be understood within a framework that fully considers the influence of psycho-social factors and contextual organizations.

Highly Sensitive Detection of Complicated Mutations of Drug Resistance in Mycobacterium tuberculosis Using a Simple, Accurate, Rapid, and Low-Cost Tailored-Design Competitive Wild-Type Blocking Assay.

Establishing simple, rapid, and highly sensitive molecular assays is crucial for timely diagnosis and effective treatment of drug-resistant tuberculosis. However, current genotypic drug susceptibility testing (DST) still encounters enormous challenges including lower sensitivity than phenotypic DST and insufficient accuracy. Herein, a simple, low-cost, multiplex real-time polymerase chain reaction-based assay is established to achieve highly sensitive detection of low-abundant mutants through competitive wild-type blocking (COWTB). Analytical performance of the COWTB assay can achieve 1% or even 0.1% mutants under background of 10 000 wild-type genomes/test. Furthermore, clinical practice feasibility is evaluated to identify resistance to rifampicin (RIF), isoniazid (INH), and streptomycin (SM) on 92 actual clinical samples, its sensitivity is 93.8% for RIF and 100% for INH and SM, and specificity is 100% each for RIF, INH, and SM when using DNA sequencing as the reference standard. In comparison, the sensitivity of reverse dot blotting assay commonly used in clinics is 93.8%, 90.0%, and 84.6%, and the specificity is 96.1%, 98.6%, and 100% for RIF, INH, and SM, respectively. Importantly, the COWTB assay can also be applicable for other drug-resistant mutations and pave a promising detection strategy to fill the gap between phenotypic and genotypic DST for detecting low-abundant drug-resistant M. tuberculosis.

Astragalus polysaccharide prevents heart failure-induced cachexia by alleviating excessive adipose expenditure in white and brown adipose tissue.

BACKGROUND: Astragalus polysaccharide (APS) is a key active ingredient isolated from Astragalus membranaceus that has been reported to be a potential treatment for obesity and diabetes by regulating lipid metabolism and adipogenesis, alleviating inflammation, and improving insulin resistance. However, whether APS regulates lipid metabolism in the context of cachexia remains unclear. Therefore, this study analysed the effects of APS on lipid metabolism and adipose expenditure in a heart failure (HF)-induced cardiac cachexia rat model.  METHODS: A salt-sensitive hypertension-induced cardiac cachexia rat model was used in the present study. Cardiac function was detected by echocardiography. The histological features and fat droplets in fat tissue and liver were observed by H&E staining and Oil O Red staining. Immunohistochemical staining, Western blotting and RT‒qPCR were used to detect markers of lipolysis and adipose browning in white adipose tissue (WAT) and thermogenesis in brown adipose tissue (BAT). Additionally, sympathetic nerve activity and inflammation in adipose tissue were detected. RESULTS: Rats with HF exhibited decreased cardiac function and reduced adipose accumulation as well as adipocyte atrophy. In contrast, administration of APS not only improved cardiac function and increased adipose weight but also prevented adipose atrophy and FFA efflux in HF-induced cachexia. Moreover, APS inhibited HF-induced lipolysis and browning of white adipocytes since the expression levels of lipid droplet enzymes, including HSL and perilipin, and beige adipocyte markers, including UCP-1, Cd137 and Zic-1, were suppressed after administration of APS. In BAT, treatment with APS inhibited PKA-p38 MAPK signalling, and these effects were accompanied by decreased thermogenesis reflected by decreased expression of UCP-1, PPAR-γ and PGC-1α and reduced FFA ß-oxidation in mitochondria reflected by decreased Cd36, Fatp-1 and Cpt1. Moreover, sympathetic nerve activity and interleukin-6 levels were abnormally elevated in HF rats, and astragalus polysaccharide could inhibit their activity. CONCLUSION: APS prevented lipolysis and adipose browning in WAT and decreased BAT thermogenesis. These effects may be related to suppressed sympathetic activity and inflammation. This study provides a potential approach to treat HF-induced cardiac cachexia.

Coastal Land Use Management Methodologies under Pressure from Climate Change and Population Growth.

Throughout history, humans living in the coastal area constantly adapt to the natural environment and create a changing environment. The rapid coastal development occurred in the mid-19th century and peaks in the mid-20th century, which was a common process in most industrialized areas. With increasing population growth and urban sprawl, many coastal lowlands are unprecedently vulnerable to climate change impacts such as sea level rise, increasing extreme storm events, and coastal flooding. Under the influence of urban revitalization and conservation, the landward shoreline movement accelerated and coastal land shrank, accompanied by community retreat. This research focuses on the importance of incorporating an understanding of the changing coastal land-ocean interaction into adaptive management strategies by illustrating the relationship of land use change, social-economic development, and climate change. Typical coastal changes in Connecticut were selected: New Haven Harbor reflects a dramatic seaward land accretion under industrial and transportation development, New London downtown waterfront reveals a trend of building retreat under industrial and commercial transformation and coastal hazard, New London Ocean Beach indicates how overdeveloped coastal low-lying community fully retreat after a natural disaster, and Jordan Cove barrier island shows a highly dynamic coastal land change and proactive management strategy. The results reveal that to cope with a constantly changing shoreline and the challenges of climate change, a resilient management process must incorporate a cycle of learning, experimenting, and creating with the goal of developing new solutions that are able to deal with our ever-changing environment.

[Feasibility of Single-Breath-Hold Compressed Sensing Real-Time Cine Imaging for Assessment of Ventricular Function and Left Ventricular Strain in Cardiac Magnetic Resonance].

Objective: To explore the feasibility of single-breath-hold compressed sensing real-time cine imaging (CS-cine) in the assessment of ventricular function and left ventricular (LV) strain. Methods: A total of 70 subjects were enrolled prospectively, and all subjects underwent cardiac magnetic resonance imaging (cardiac MRI) using both the standard steady-state free procession cine (sta-cine) acquisition and a prototype CS-cine sequence. For both CS-cine and sta-cine imaging, continuous short-axis cine images were acquired from the base to the apex to cover the entire left ventricle, and long-axis cine images including two-, three-, and four-chamber views were also acquired. The scanning range, number of slices, slice thickness and intervals were kept identical for the two cine images of the same participant. Subjective evaluation of the image quality was performed on all cine images. For both sequences, the conventional function parameters of the left and the right ventricles and LV strain values were assessed with post-processing software analysis. The cine image quality, conventional ventricular function parameters, and LV strain values were compared between the two cine groups and the differences were examined. Inter- and intraobserver agreements for CS-cine images were measured using intraclass correlation coefficient ( ICC). Bland-Altman analysis was performed to assess reproducibility between the two cine methods. Results: The median scanning time of CS-cine was 21 s versus 272 s for sta-cine ( P<0.001). The median image quality scores of two groups were significantly different, 4 points for sta-cine and 2 points for CS-cine ( P<0.001). Bi-ventricular end-diastolic volumes (EDV), stroke volume (SV) and ejection fraction (EF) were significantly smaller in CS-cine ( P<0.001). Nevertheless, no significant differences between the two groups in bi-ventricular ESV or LV mass were observed ( P>0.05). LV strain parameters, including the peak radial strain, peak circumferential strain and peak longitudinal strain derived from LV mid-ventricular slice, were significantly different in the two sequences ( P<0.001). Moreover, CS-cine-derived functional parameters and strain measurements have a good correlation with those of sta-cine (for RV function parameters, and left ventricular PLS, PCS values, more than 95% points fell within the limits of agreement [ LoA]; meanwhile, more than 91% points fell within the LoA for other parameters) and inter- and intraobserver agreements were strong ( ICC=0.88 to 0.99) for CS-cine. Conclusion: CS-cine can well realize the rapid acquisition of cine images for quantitative analysis of cardiac function, and the conventional ventricular function parameters and LV globalized strain values obtained from CS-cine imaging have good reproducibility.

Urban expansion simulation and development-oriented zoning of rapidly urbanising areas: A case study of Hangzhou.

Sustainable urban development is the key to regional urban development policy-making. Therefore, the comprehensive spatial zoning of rapidly urbanising areas is important. In this study, a novel spatial zoning framework was established based on the future urban spatiotemporal pattern and multidimensional dynamic index system at the township scale. First, the urban expansion of Hangzhou in 2025 was simulated based on a new method in which the hybrid bat algorithm and deep belief network (DBN) are coupled with the cellular automata (CA) model (MDBN-CA). Second, an urban development-oriented evaluation system was established at the township scale based on urban expansion simulations and indicators, including the speed and intensity, morphology, socioeconomic and ecological benefits. Finally, Hangzhou was zoned by using the K-means method. The results show that: (1) The MDBN-CA model effectively overcomes the limitations of traditional neural networks, yielding an increase in the simulation accuracy and spatial pattern similarity of 3.70% and 10.11%, respectively; (2) Hangzhou can be divided into six zones according to the 2025 urban expansion, that is, the highly urbanised, key urbanised, radiation, potential, optimised, and ecological priority zones; (3) Based on the current development trends, urban expansion in Hangzhou will have relatively large benefits by 2025. However, problems with respect to the unbalanced development of land urbanisation and population urbanisation, as well as the low efficiency of land use, were identified. Based on the results of this study, suggestions are provided with respect to spatial pattern reconstruction, urban function transformation, efficient land use, and green and healthy development; (4) Based on the combination of the MDBN-CA and K-means models with the zoning framework of the comprehensive benefits evaluation system of urban expansion, future urban expansion can be predicted and analysed.

Learning From Highly Confident Samples for Automatic Knee Osteoarthritis Severity Assessment: Data From the Osteoarthritis Initiative.

Knee osteoarthritis (OA) is a chronic disease that considerably reduces patients' quality of life. Preventive therapies require early detection and lifetime monitoring of OA progression. In the clinical environment, the severity of OA is classified by the Kellgren and Lawrence (KL) grading system, ranging from KL-0 to KL-4. Recently, deep learning methods were applied to OA severity assessment to improve accuracy and efficiency. However, this task is still challenging due to the ambiguity between adjacent grades, especially in early-stage OA. Low confident samples, which are less representative than the typical ones, undermine the training process. Targeting the uncertainty in the OA dataset, we propose a novel learning scheme that dynamically separates the data into two sets according to their reliability. Besides, we design a hybrid loss function to help CNN learn from the two sets accordingly. With the proposed approach, we emphasize the typical samples and control the impacts of low confident cases. Experiments are conducted in a five-fold manner on five-class task and early-stage OA task. Our method achieves a mean accuracy of 70.13% on the five-class OA assessment task, which outperforms all other state-of-art methods. Despite early-stage OA detection still benefiting from the human intervention of lesion region selection, our approach achieves superior performance on the KL-0 vs. KL-2 task. Moreover, we design an experiment to validate large-scale automatic data refining during training. The result verifies the ability to characterize low confidence samples. The dataset used in this paper was obtained from the Osteoarthritis Initiative.

Complexity Assessment of Chronic Pain in Elderly Knee Osteoarthritis Based on Neuroimaging Recognition Techniques.

The chronic pain of knee osteoarthritis in the elderly is investigated in detail in this paper, as well as the complexity of chronic pain utilising neuroimaging recognition techniques. Chronic pain in knee osteoarthritis (KOA) has a major effect on patients' quality of life and functional activities; therefore, understanding the causes of KOA pain and the analgesic advantages of different therapies is important. In recent years, neuroimaging techniques have become increasingly important in basic and clinical pain research. Thanks to the application and development of neuroimaging techniques in the study of chronic pain in KOA, researchers have found that chronic pain in KOA contains both injury-receptive and neuropathic pain components. The neuropathic pain mechanism that causes KOA pain is complicated, and it may be produced by peripheral or central sensitization, but it has not gotten enough attention in clinical practice, and there is no agreement on how to treat combination neuropathic pain KOA. As a result, using neuroimaging techniques such as magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS), this review examines the changes in brain pathophysiology-related regions caused by KOA pain, compares the latest results in pain assessment and prediction, and clarifies the central brain analgesic mechanistic. The capsule network model is introduced in this paper from the perspective of deep learning network structure to construct an information-complete and reversible image low-level feature bridge using isotropic representation, predict the corresponding capsule features from MRI voxel responses, and then, complete the accurate reconstruction of simple images using inverse transformation. The proposed model improves the structural similarity index by about 10%, improves the reconstruction performance of low-level feature content in simple images by about 10%, and achieves feature interpretation and analysis of low-level visual cortical fMRI voxels by visualising capsule features, according to the experimental results.

Significance of serum FGF-23 for risk assessment of contrast-associated acute kidney injury and clinical outcomes in patients undergoing coronary angiography.

BACKGROUND: Fibroblast growth factor (FGF)-23 levels rise as kidney function declines. Whether elevated FGF-23 levels are associated with an increased risk for contrast-associated acute kidney injury (CA-AKI) and major adverse cardiovascular events (MACE) in patients undergoing coronary angiography remain uncertain. METHODS: In total, 492 patients receiving coronary angiography were enrolled. Their serum FGF-23 levels were measured before administration of contrast media. The occurrence of CA-AKI was defined as a rise in serum creatinine of 0.5 mg/dL or a 25% increase from the baseline value within 48 h after the procedure. All patients were followed up for at least 1 year or until the occurrence of MACE including death, nonfatal myocardial infarction (MI), and ischemic stroke. RESULTS: Overall, CA-AKI occurred in 41 (8.3%) patients. During a median follow-up of 2.6 years, there were 24 deaths, 3 nonfatal MIs, and 7 ischemic strokes. Compared with those in the lowest FGF-23 tertile, individuals in the highest FGF-23 tertile had a significantly higher incidence of CA-AKI (P < 0.001) and lower incidence of MACE-free survival (P = 0.001). In multivariate regression analysis, higher FGF-23 level was found to be independently associated with a graded risk for CA-AKI (OR per doubling, 1.90; 95% CI 1.48-2.44) and MACE (HR per doubling, 1.25; 95% CI 1.02-1.52). CONCLUSIONS: Elevated FGF-23 levels were associated with an increased risk for CA-AKI and future MACE among patients undergoing coronary angiography. FGF-23 may play a role in early diagnosis of CA-AKI and predicting clinical outcomes after coronary angiography.

Economic Burden of Heart Failure in Asian Countries with Different Healthcare Systems.

BACKGROUND AND OBJECTIVES: Heart failure (HF) poses substantial economic burden, primarily driven by high hospitalization and mortality rates. This study aimed to understand the economic burden of HF in 4 Asian countries under varying healthcare systems. METHODS: This was a non-interventional, retrospective study conducted in South Korea, Taiwan, Thailand and Malaysia through medical chart review. Eligible patients included those who had either ≥1 hospitalization or ≥2 outpatient visits from January 1st to December 31st, 2014, and at least one year of follow-up. Resource use and direct healthcare costs (adjusted to 2015 USD) of HF were assessed. HF costs for subgroups stratified by age and sex were assessed. RESULTS: A total of 568 patients were recruited from South Korea (n=200), Taiwan (n=200), Thailand (n=100) and Malaysia (n=68). The proportion of patients hospitalized ranged from 20.0% to 93.5% (South Korea 20.0%, Thailand 49.0%, Malaysia 70.6%, and Taiwan 93.5%). The overall annual HF cost per patient was $2,357, $4,513, $3,513 and $1,443 in South Korea, Taiwan, Thailand, and Malaysia, respectively; hospitalized HF care costs were $10,714, $4,790, $7,181 and $1,776, respectively. The length of stay was more than 12.2 days except in Malaysia. No specific trend was observed in subgroup analysis. CONCLUSIONS: In Asia, HF poses significant economic burden and hospitalization has emerged as the major cost driver among healthcare costs. A streamlined treatment strategy reducing hospitalization rate can minimize the economic burden.

Healthcare Costs Associated with Complications in Patients with Type 2 Diabetes among 1.85 Million Adults in Beijing, China.

We aimed to provide reliable regression estimates of expenditures associated with various complications in type 2 diabetics in China. In total, 1,859,039 type 2 diabetes patients with complications were obtained from the Beijing Medical Claim Data for Employees database from 2008 to 2016. We estimated costs for complications using a generalized estimating equation model adjusted for age, sex, and the incidence of various complications. The average total cost for diabetic patients with complications was 17.12 thousand RMB. Prescribed drugs accounted for 63.4% of costs. We observed a significant increase in costs in the first year after the onset of complications. Compared with costs before the incidence of complications, the additional costs per person in the first year and >1 year after the event would be 10,631.16 RMB and 1150.71 RMB for cardiovascular disease, 1017.62 RMB and 653.82 RMB for cerebrovascular disease, and 301.14 RMB and 624.00 RMB for kidney disease, respectively. The estimated coefficients for outpatient visits were relatively lower than those of inpatient visits. Complications in diabetics exert a significant impact on total healthcare costs in the first year of their onset and in subsequent years. Our estimates may assist policymakers in quantifying the economic burden of diabetes complications.