Automatic quantitative stroke severity assessment based on Chinese clinical named entity recognition with domain-adaptive pre-trained large language model.

BACKGROUND: Stroke is a prevalent disease with a significant global impact. Effective assessment of stroke severity is vital for an accurate diagnosis, appropriate treatment, and optimal clinical outcomes. The National Institutes of Health Stroke Scale (NIHSS) is a widely used scale for quantitatively assessing stroke severity. However, the current manual scoring of NIHSS is labor-intensive, time-consuming, and sometimes unreliable. Applying artificial intelligence (AI) techniques to automate the quantitative assessment of stroke on vast amounts of electronic health records (EHRs) has attracted much interest. OBJECTIVE: This study aims to develop an automatic, quantitative stroke severity assessment framework through automating the entire NIHSS scoring process on Chinese clinical EHRs. METHODS: Our approach consists of two major parts: Chinese clinical named entity recognition (CNER) with a domain-adaptive pre-trained large language model (LLM) and automated NIHSS scoring. To build a high-performing CNER model, we first construct a stroke-specific, densely annotated dataset "Chinese Stroke Clinical Records" (CSCR) from EHRs provided by our partner hospital, based on a stroke ontology that defines semantically related entities for stroke assessment. We then pre-train a Chinese clinical LLM coined "CliRoberta" through domain-adaptive transfer learning and construct a deep learning-based CNER model that can accurately extract entities directly from Chinese EHRs. Finally, an automated, end-to-end NIHSS scoring pipeline is proposed by mapping the extracted entities to relevant NIHSS items and values, to quantitatively assess the stroke severity. RESULTS: Results obtained on a benchmark dataset CCKS2019 and our newly created CSCR dataset demonstrate the superior performance of our domain-adaptive pre-trained LLM and the CNER model, compared with the existing benchmark LLMs and CNER models. The high F1 score of 0.990 ensures the reliability of our model in accurately extracting the entities for the subsequent automatic NIHSS scoring. Subsequently, our automated, end-to-end NIHSS scoring approach achieved excellent inter-rater agreement (0.823) and intraclass consistency (0.986) with the ground truth and significantly reduced the processing time from minutes to a few seconds. CONCLUSION: Our proposed automatic and quantitative framework for assessing stroke severity demonstrates exceptional performance and reliability through directly scoring the NIHSS from diagnostic notes in Chinese clinical EHRs. Moreover, this study also contributes a new clinical dataset, a pre-trained clinical LLM, and an effective deep learning-based CNER model. The deployment of these advanced algorithms can improve the accuracy and efficiency of clinical assessment, and help improve the quality, affordability and productivity of healthcare services.

Telodendrimer functionalized hydrogel platform for sustained antibiotics release in infection control.

Wound infection commonly causes delayed healing, especially in the setting of chronic wounds. Local release of antibiotics is considered a viable approach to treat chronic wounds. We have developed a versatile telodendrimer (TD) platform for efficient loading of charged antibiotic molecules via a combination of multivalent and synergistic charge and hydrophobic interactions. The conjugation of TD in biocompatible hydrogel allows for topical application to provide sustained antibiotic release. Notably, a drug loading capacity as high as 20 % of the drug-to-resin dry weight ratio can be achieved. The payload content (PC) and release profile of the various antibiotics can be optimized by fine-tuning TD density and valency in hydrogel based on the charge and hydrophobic features of the drug, e.g., polymyxin B (PMB), gentamycin (GM), and daptomycin (Dap), for effective infection control. We have shown that hydrogel with moderately reduced TD density demonstrates a more favorable release profile than hydrogel with higher TD density. Antibiotics loaded in TD hydrogel have comparable antimicrobial potency and reduced cytotoxicity compared to the free antibiotics due to a prolonged, controlled drug release profile. In a mouse model of skin and soft tissue infection, the subcutaneous administration of PMB-loaded TD hydrogel effectively eliminated the bacterial burden. Overall, these results suggest that engineerable TD hydrogels have great potential as a topical treatment to control infection for wound healing. STATEMENT OF SIGNIFICANCE: Wound infection causes a significant delay in the wound healing process, which results in a significant financial and resource burden to the healthcare system. PEGA-telodendrimer (TD) resin hydrogel is an innovative and versatile platform that can be fine-tuned to efficiently encapsulate different antibiotics by altering charged and hydrophobic structural moieties. Additionally, this platform is advantageous as the TD density in the resin can also be fine-tuned to provide the desired antibiotic payload release profile. Sustained antibiotics release through optimization of TD density provides a prolonged therapeutic window and reduces burst release-induced cytotoxicity compared to conventional antibiotics application. Studies in a preclinical mouse model of bacteria-induced skin and soft tissue infection demonstrated promising therapeutic efficacy as evidenced by effective infection control and prolonged antibacterial efficacy of antibiotics-loaded PEGA-TD resin. In conclusion, the PEGA-TD resin platform provides a highly customizable approach for effective antibiotics release with significant potential for topical application to treat various bacterial wound infections to promote wound healing.

UAV hyperspectral combined with LiDAR to estimate chlorophyll content at the stand and individual tree scales.

Chlorophyll is an important indicator of vegetation health status, accurate estimation of which is important for evaluating forest carbon sink. In this study, we estimated the chlorophyll content of coniferous forests, broad-leaved forests and mixed forest stands at stand and individual tree level by unmanned air vehicle (UAV) hyperspectral data combined with light detection and ranging (LiDAR) point clouds, which improved the non-destructive estimation accuracy of forest chlorophyll. We further comprehensively analyzed the spatial distribution of chlorophyll content at different scales. A total of 36 spectral characteristic variables related to chlorophyll content were screened by correlation analysis based on the fusion of UAV hyperspectral data and LiDAR point clouds combining with the empirical data from ground plots. We constructed multiple models for chlorophyll estimation by using statistical model, including multiple stepwise regression, BP neural network, BP neural network optimized by firefly algorithm, random forest and hybrid data-driven PROSPECT mechanism model. The optimal model was selected to estimate the chlorophyll content. The horizontal and vertical distribution of chlorophyll content at the stand level and individual tree level were analyzed. The results showed that the random forest model was superior to the models constructed by multiple stepwise regression, BP neural network and BP neural network optimized by firefly algorithm for chlorophyll estimation with R2 and RMSE of 0.59-0.64 and 3.79-5.83 µg·cm-2, respectively. The accuracy of the mechanism model was the highest, with R2 and RMSE of 0.97 and 3.40 µg·cm-2. The chlorophyll contents differed across stand types, with that in broad-leaved forest (25.25-31.60 µg·cm-2) being higher than mixed forest (13.52-23.93 µg·cm-2) and coniferous forest (6.40-13.71 µg·cm-2). There were significant differences in chlorophyll contents the in vertical direction among different stands. For individual tree of different species, the chlorophyll content inside the canopy was lower than that outside the canopy in the horizontal direction. In the vertical direction, there was no difference in chlorophyll content among different layers of Pinus sylvestris var. mongolica canopy. However, significant differences were observed among the upper, middle, and lower layers of Juglans mandshurica canopy. Using the fusion of hyperspectral image and LiDAR point cloud data, the mechanism model driven by hybrid data could effectively improve the accuracy and stability of chlorophyll content estimation at different scales.

Engineering Nanotrap Hydrogel for Immune Modulation in Wound Healing.

Imbalanced immune regulation leads to the abnormal wound healing process, e.g., chronic unhealing wound or hypertrophic scar formation. Thus, the attenuation of the overflowing inflammatory factors is a viable approach to maintain the homeostatic immune regulation to facilitate normal wound healing. A versatile telodendrimer (TD) nanotrap (NT) platform is developed for efficient biomolecular protein binding. The conjugation of TD NT in size-exclusive biocompatible hydrogel resin allows for topical application for cytokine scavenging. Fine-tuning the TD NT density/valency in hydrogel resin controls resin swelling, optimizes molecular diffusion, and improves cytokine capture for effective immune modulation. The hydrogel with reduced TD NT density allows for higher protein/cytokine adsorption capacity with faster kinetics, due to the reduced barrier of TD NT nano-assembly. The positively charged TD NT hydrogel exhibits superior removal of negatively charged proinflammatory cytokines from the lipopolysaccharide (LPS, a potent endotoxin) primed immune cell culture medium. The negatively charged TD NT hydrogel removes positively charged anti-inflammatory cytokines efficiently from cell culture medium. TD NT hydrogel effectively constrains the local inflammation induced by subcutaneous LPS injection in mice. These results indicate the great potential applications of the engineered TD NT hydrogel as topical immune modulatory treatments to attenuate local inflammation.

The Regulation Network of Glycerolipid Metabolism as Coregulators of Immunotherapy-Related Myocarditis.

Background: To date, immunotherapy for patients with malignant tumors has shown a significant association with myocarditis. However, the mechanism of metabolic reprogramming changes for immunotherapy-related cardiotoxicity is still not well understood. Methods: The CD45+ single-cell RNA sequencing (scRNA-seq) of the Pdcd1-/-Ctla4+/- and wild-type mouse heart in GSE213486 was downloaded to demonstrate the heterogeneity of immunocyte atlas in immunotherapy-related myocarditis. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectrum metabolomics analysis detects the metabolic network differences. The drug prediction, organelle level interaction, mitochondrial level regulatory network, and phosphorylation site prediction for key regulators have also been screened via multibioinformatics analysis methods. Results: The scRNA analysis shows that the T cell is the main regulatory cell subpopulation in the pathological progress of immunotherapy-related myocarditis. Mitochondrial regulation pathway significantly participated in pseudotime trajectory- (PTT-) related differential expressed genes (DEGs) in the T cell subpopulation. Additionally, both the gene set enrichment analysis (GSEA) of PTT-related DEGs and LC-MS/MS metabolomics analysis showed that mitochondrial-regulated glycerolipid metabolism plays a central role in metabolic reprogramming changes for immunotherapy-related cardiotoxicity. Finally, the hub-regulated protease of diacylglycerol kinase zeta (Dgkz) was significantly identified and widely played various roles in glycerolipid metabolism, oxidative phosphorylation, and lipid kinase activation. Conclusion: Mitochondrial-regulated glycerolipid metabolism, especially the DGKZ protein, plays a key role in the metabolic reprogramming of immunotherapy-related myocarditis.

Engineering Telodendrimer Nanocarriers for Monomeric Amphotericin B Delivery.

Systemic fungal infections are an increasingly prevalent health problem. Amphotericin B (AmB), a hydrophobic polyene antibiotic, remains the drug of choice for life-threatening invasive fungal infections. However, it has dose-limiting side effects, including nephrotoxicity. The efficacy and toxicity of AmB are directly related to its aggregation state. Here, we report the preparation of a series of telodendrimer (TD) nanocarriers with the freely engineered core structures for AmB encapsulation to fine-tune AmB aggregation status. The reduced aggregation status correlates well with the optimized antifungal activity, attenuated hemolytic properties, and reduced cytotoxicity to mammalian cells. The optimized TD nanocarrier for monomeric AmB encapsulation significantly increases the therapeutic index, reduces the in vivo toxicity, and enhances antifungal effects in mouse models with Candida albicans infection in comparison to two common clinical formulations, i.e., Fungizone and AmBisome.

The clinical application value of compound Stachys sieboldii Miq granules to stable COPD patients.

BACKGROUND: The aim of this paper was to explore the application value of Stachys sieboldii Miq granules which is a kind of traditional Chinese medicine (TCM) in stable chronic obstructive pulmonary disease (COPD) patients. METHODS: Randomized double-blind method was used to select 160 patients with stable COPD. The patients were randomly divided into placebo group and Stachys sieboldii Miq group. Both groups underwent test items for 2 months, detected plasma cytokines, Saint George Respiratory Questionnaire (SGRQ) scores, pulmonary function, and the frequency of acute exacerbation (AE) at week 12. Follow-up was done every 12 weeks till 48 weeks to record the frequency of AE. RESULTS: A total of 120 patients with 60 in each group were included. At week 12, there were significant differences in the plasma concentrations of TH17, IL-17A, IFN-γ and IL-10 between the two groups (all P=0.000). The proinflammatory factors TH17 and IL-17A were significantly lower in control group, while the anti-inflammatory factors IFN-γ and IL-10 were higher in the control group. And the SGRQ Score of Stachys sieboldii Miq group was significantly lower. There was no significant difference in lung function (FEV1, FVC, and FEV1/FVC) between the two groups (P=0.510, 0.529, and 0.843). Within 48 weeks, the AE frequency and change with time showed significant differences between the two groups (P=0.029), and the incidence of AE was reduced by 47.9% in Stachys sieboldii Miq group. CONCLUSIONS: Stachys sieboldii Miq granules reduced proinflammatory factors and increased anti-inflammatory factors in stable COPD patients, reducing the probability of inducing AE treatment.

Unveiling cytokine charge disparity as a potential mechanism for immune regulation.

Cytokines are small signaling proteins that regulate the immune responses to infection and tissue damage. Surface charges of cytokines determine their in vivo fate in immune regulation, e.g., half-life and distribution. The overall negative charges in the extracellular microenvironment and the acidosis during inflammation and infection may differentially impact cytokines with different surface charges for fine-tuned immune regulation via controlling tissue residential properties. However, the trend and role of cytokine surface charges has yet to be elucidated in the literature. Interestingly, we have observed that most pro-inflammatory cytokines have a negative charge, while most anti-inflammatory cytokines and chemokines have a positive charge. In this review, we extensively examined the surface charges of all cytokines and chemokines, summarized the pharmacokinetics and tissue adhesion of major cytokines, and analyzed the link of surface charge with cytokine biodistribution, activation, and function in immune regulation. Additionally, we identified that the general trend of charge disparity between pro- and anti-inflammatory cytokines represents a unique opportunity to develop precise immune modulation approaches, which can be applied to many inflammation-associated diseases including solid tumors, chronic wounds, infection, and sepsis.

Functionalized core-shell nanogel scavenger for immune modulation therapy in sepsis.

Sepsis is a complex, life-threatening hyperinflammatory syndrome associated with organ failure and high mortality due to lack of effective treatment options. Here we report a core-shell hydrogel nanoparticle with the core functionalized with telodendrimer (TD) nanotrap (NT) to control hyperinflammation in sepsis. The combination of multi-valent charged and hydrophobic moieties in TD enables effective binding with biomolecules in NT. The higher crosslinking in the shell structure of nanogel excludes the abundant large serum proteins and allows for size-selectivity in scavenging the medium-sized septic molecules (10-30 kDa), e.g., lipopolysaccharides (LPS, a potent endotoxin in sepsis), thus reducing cytokine production. At the same time, the core-shell TD NT nanogel captures the over-flowing proinflammatory cytokines effectively both in vitro and in vivo from biological fluids to further control hyperinflammation. Intraperitoneal injection of core-shell TD NT nanogel effectively attenuates NF-κB activation and cytokine production in LPS-induced septic mouse models. These results indicate the potential applications of the injectable TD NT core-shell nanogel to attenuate local or systemic inflammation.

Modified photochemical reflectance index to estimate leaf maximum rate of carboxylation based on spectral analysis.

The maximum rate of carboxylation in leaves (Vcmax) is an important parameter used to determine the photosynthetic rate. An accurate estimation of Vcmax is important for evaluating the photosynthetic capacity of vegetation productivity and the carbon budget of forest ecosystems. In this study, we measured the light use efficiency (LUE) and Vcmax of leaves and their corresponding spectral characteristics. Spectral analysis was used to find a modified photochemical reflectance index (PRI) of leaves to estimate LUE and thereby estimate leaf Vcmax. The results showed that the precision with which the modified ratio PRI index estimated LUE was significantly increased. The R2 of the estimation model was 0.69, and the root mean square error (RMSE) was 0.0024. The R2 of the model for estimating leaf Vcmax based on the LUE was 0.72, and the RMSE was 8.439 µmol/m2/s. The Vcmax values of conifer trees (Scots pine, Korean pine, and larch) were higher than those of broadleaf trees (white birch, Manchurian walnut, Siberian elm, Manchurian ash, Mongolian oak, Korean aspen, and Amur linden). This method avoids problem that conventional PRI is not sensitive to high leaf LUE values and provides important parameter data for the quantitative estimation of the gross primary productivity of forest ecosystems.

Forest age mapping based on multiple-resource remote sensing data.

Forest age is an important stand description factor and plays an important role in the carbon cycle of forest ecosystems. However, forest age data are typically lacking or are difficult to acquire at large spatial scale. Thus, it is important to develop a method of spatial forest age mapping. In this study, a method of forest age estimation based on multiple-resource remote sensing data was developed. Forest age was estimated by using average tree height estimated from the ICESat/GLAS and MODIS BRDF products. The results showed that forest age was significantly related to average tree height with a correlation coefficient of 0.752. Then, the average tree height was inversed using a waveform parameter extracted from ICESat/GLAS and was extended to continuous space with the help of the MODIS BRDF product. Thus, forest age mapping was realized. Lastly, the structure of forest age in the study area was evaluated. The results indicated that this method can be used to estimate forest age at the local scale and at large scale and can facilitate understandings of the real forest age structure features of a research area.

Effects of compound Caoshi silkworm granules on stable COPD patients and their relationship with gut microbiota: A randomized controlled trial.

BACKGROUND AND PURPOSE: Patients with chronic obstructive pulmonary disease (COPD) usually experience recurrent acute exacerbations. These patients, especially those with stable COPD, require an effective intervention for treating exacerbations. This study aimed to evaluate the efficacy of Compound Caoshi silkworm granules (CCSGs) in stable COPD patients and to investigate their potential mechanism. METHODS: A randomized controlled trial was performed at Jinhua Hospital, Zhejiang University. Patients were enrolled in this study if they met the criterion of stable COPD. A total of 40 patients were randomly divided into the following 2 groups: Group A (n = 20, routine treatment (RT) group) and Group B (n = 20, RT plus CCSGs [RT plus CCSGs] group). The duration of treatment was 3 months. Stool samples were collected from all patients on day 0 and the gut microbiota was analyzed using 16s rRNA sequencing. The St. George's Respiratory Questionnaire (SGRQ) scores and lung function were assessed at month 0 and month 3. RESULTS: The components of gut microbiota differed between stable COPD patients and the healthy population. The RT plus CCSGs group showed improved SGRQ scores compared to the RT group. There was no difference in forced expiratory volume-one second, forced vital capacity, and forced expiratory volume-one second/forced vital capacity between the two groups. Furthermore, the abundance of gut microbiota in patients with the top 10 SGRQ scores (Group N) differed from the abundance of gut microbiota in those with the lowest 10 SGRQ scores (Group T). CONCLUSION: CCSGs have beneficial effects in the improvement of symptoms in stable COPD patients over a 3-month treatment period. The potential underlying mechanism may be attributable to the difference in gut microbiota among patients. However, more research is needed to confirm this conclusion.

Thermally induced deterioration behaviour of two dolomitic marbles under heating-cooling cycles.

Thermally induced deterioration behaviour can cause severe weathering in marbles. Most previous studies focus on the deterioration behaviour of calcitic marbles. Relevant studies of dolomitic marbles are generally carried out under a 'high temperature and low cycling times' condition. Little attention is focused on the deterioration behaviour in dolomitic marbles when they are subjected to a large quantity of heating-cooling cycles under a 'low temperature and high cycling times' condition. This paper presents experimental investigations on the thermally induced deterioration behaviour of two Beijing dolomitic marbles (Qingbaishi Marble (QM) and Hanbaiyu Marble (HM)) under heating-cooling cycles up to 1000 cycling times. The applied temperature range is from -20°C to 60°C which is to simulate the seasonal temperature variations in Beijing city, China. Related properties such as weight loss, three-dimensional microtopography, elastic wave velocity and uniaxial compressive strength were measured at certain cycles. The results indicate that thermally induced deterioration behaviour will result in a continuous weight loss in dolomitic marble samples. Mechanical properties of those two marbles are strongly affected by heating and cooling treatments, which were reflected by the reductions of dynamic Young's modulus and uniaxial compressive strength with an increase of thermal cycles. Compared with QM, HM displays a higher level of thermally induced deterioration which should be due to the abundance of quartz mineral.

Moisture content estimation of forest litter based on remote sensing data.

As a fine fuel, forest litter plays an important role in fire danger rating systems, so forest litter moisture data are necessary and meaningful for fire risk management and prevention. An optical remote sensing technique can provide continuous and regional data for litter moisture estimates, but such an approach is restricted in separating the background reflectance of the forest floor from pixel reflectance because the litter moisture information is included only in background reflectance while pixel reflectance in the forest area consists of both canopy reflectance and background reflectance. Therefore, we present a geometrical-optical model to estimate forest litter moisture by separating contributions of background reflectance from the remote sensing image and use a statistical model to estimate the forest litter moisture content based on the calculated background reflectance. The results show that the model had an R2, root mean square error (RMSE), and average precision of 0.595, 0.372, and 69.654%, respectively. This approach provides a new way of estimating forest litter moisture content from an optical remote sensing image, and it can potentially be applied in large-scale forest litter moisture content mapping.

SWNHs (Single-Wall Carbon Nanohorns) Supervises Endoplasmic Reticulum (ER) Stress in Hepatocellular Carcinoma.

SWNHs can act as a good biocompatible nanomaterials and show potential application in the field of drug carriers or therapy to influence biological function on cell. HCC (Hepatocellular carcinoma) is a most common type of malignant neoplasms in the digestive system. SWNHs have been reported to be able to induce HepG2 cell apoptosis. In the study, we implant HepG2 cell into nude mice and observe the effect of SWNHs on these tumor model mice. And then 38 apoptosis proteins were determined using Human Apoptosis Antibody Array kit. The proteins related to ER stress were examined through immunohistochemical staining and western blotting assay. Our results indicated that SWNHs did not influence on tumor in model mice. There were no significant difference expression of the 38 apoptosis proteins in xenograft between the treatment group and control. However, the proteins related to ER stress were increased. In summary, we identified that SWNHs was as a stimulator of ER stress to influence the biological function of hepatoma cells, and may be used as a potential anti-cancer agent in HCC.

Development of zwitterionic sulfobetaine block copolymer conjugation strategies for reduced platelet deposition in respiratory assist devices.

Respiratory assist devices, that utilize ∼2 m2 of hollow fiber membranes (HFMs) to achieve desired gas transfer rates, have been limited in their adoption due to such blood biocompatibility limitations. This study reports two techniques for the functionalization and subsequent conjugation of zwitterionic sulfobetaine (SB) block copolymers to polymethylpentene (PMP) HFM surfaces with the intention of reducing thrombus formation in respiratory assist devices. Amine or hydroxyl functionalization of PMP HFMs (PMP-A or PMP-H) was accomplished using plasma-enhanced chemical vapor deposition. The generated functional groups were conjugated to low molecular weight SB block copolymers with N-hydroxysuccinimide ester or siloxane groups (SBNHS or SBNHSi) that were synthesized using reversible addition fragmentation chain transfer polymerization. The modified HFMs (PMP-A-SBNHS or PMP-H-SBNHSi) showed 80-95% reduction in platelet deposition from whole ovine blood, stability under the fluid shear of anticipated operating conditions, and uninhibited gas exchange performance relative to non-modified HFMs (PMP-C). Additionally, the functionalization and SBNHSi conjugation technique was shown to reduce platelet deposition on polycarbonate and poly(vinyl chloride), two other materials commonly found in extracorporeal circuits. The observed thromboresistance and stability of the SB modified surfaces, without degradation of HFM gas transfer performance, indicate that this approach is promising for longer term pre-clinical testing in respiratory assist devices and may ultimately allow for the reduction of anticoagulation levels in patients being supported for extended periods. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 2681-2692, 2018.

Influence of site index on the relationship between forest net primary productivity and stand age.

Previous studies show that forest net primary productivity (NPP) varies pronouncedly with stand age, and these variations play a crucial role in determining forest carbon sinks or sources at regional scales. Some forest carbon cycling models, eg. InTEC (The integrated terrestrial ecosystem C-budget model), calculates annual forest NPP in the long term according to normalized NPP-age relationships and the reference forest NPP at a given age. Therefore, the accurate NPP-age relationship is important for forest NPP estimation. In this study, NPP at various stand ages for twelve major forest stand types in Heilongjiang Province in northeast China is derived from yield tables with consideration of the total biomass increment and foliage and fine-root turnovers. Similar to previous studies, our results also show that forest NPP increases quickly at young ages, reaches the maximum value at middle age (10-40 years old), and then decreases to a relative stable level at old ages. However, we additionally found that forests under better site conditions have faster growth rates in young ages and steeper declines after reaching the maximum. Therefore, when the NPP-age curves for different site indices are normalized against the maximum value of each curve, there are significant differences among them. These differences have implications on the methodology for estimating the spatial distribution of forest carbon sources and sinks.

miR-32 functions as a tumor suppressor and directly targets SOX9 in human non-small cell lung cancer.

PURPOSE: MicroRNA-32 (miR-32) is dysregulated in certain human malignancies and correlates with tumor progression. However, its expression and function in non-small cell lung cancer (NSCLC) remain unclear. Thus, the aim of this study was to explore the effects of miR-32 expression on NSCLC tumorigenesis and development. METHODS: Using real-time quantitative reverse-transcription polymerase chain reaction (qRT-PCR), we detected miR-32 expression in NSCLC cell lines and primary tumor tissues. The association of miR-32 expression with clinicopathological factors and prognosis was also analyzed. Then, the effects of miR-32 expression on the biological behavior of NSCLC cells were investigated. Finally, the potential regulatory effect of miR-32 on SOX9 expression was confirmed. RESULTS: miR-32 expression levels were significantly downregulated in NSCLC compared with the corresponding noncancerous lung tissues (P<0.001). In addition, decreased miR-32 expression was significantly associated with lymph node metastasis (P=0.002), advanced tumor/nodes/metastasis (TNM) classification stages (P<0.001), and shorter overall survival (P<0.001). Multivariate regression analysis corroborated that downregulated miR-32 expression was an independent unfavorable prognostic factor for NSCLC patients. In vitro studies demonstrated that miR-32 overexpression reduced A549 cell proliferation, migration, and invasion, and promoted apoptosis. Furthermore, SOX9 was confirmed as a direct target of miR-32, using a luciferase reporter assay. CONCLUSION: These findings indicate that miR-32 may act as a tumor suppressor in NSCLC and could serve as a novel therapeutic agent for miR-based therapy.

Chlorophyll content retrieval from hyperspectral remote sensing imagery.

Chlorophyll content is the essential parameter in the photosynthetic process determining leaf spectral variation in visible bands. Therefore, the accurate estimation of the forest canopy chlorophyll content is a significant foundation in assessing forest growth and stress affected by diseases. Hyperspectral remote sensing with high spatial resolution can be used for estimating chlorophyll content. In this study, the chlorophyll content was retrieved step by step using Hyperion imagery. Firstly, the spectral curve of the leaf was analyzed, 25 spectral characteristic parameters were identified through the correlation coefficient matrix, and a leaf chlorophyll content inversion model was established using a stepwise regression method. Secondly, the pixel reflectance was converted into leaf reflectance by a geometrical-optical model (4-scale). The three most important parameters of reflectance conversion, including the multiple scattering factor (M 0 ), and the probability of viewing the sunlit tree crown (P T ) and the background (P G ), were estimated by leaf area index (LAI), respectively. The results indicated that M 0 , P T , and P G could be described as a logarithmic function of LAI, with all R (2) values above 0.9. Finally, leaf chlorophyll content was retrieved with RMSE = 7.3574 µg/cm(2), and canopy chlorophyll content per unit ground surface area was estimated based on leaf chlorophyll content and LAI. Chlorophyll content mapping can be useful for the assessment of forest growth stage and diseases.