Refractory patients with favorable/intermediate-risk acute myeloid leukemia benefit from azacytidine maintenance therapy following allogeneic hematopoietic stem cell transplantation.

Recurrence following allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the major cause of treatment failure in patients with myeloid malignancy. Azacytidine (AZA) maintenance is a promising therapy to prevent relapse and improve survival. We conducted a prospective, one-arm study involving 78 patients with myeloid malignancy at a high risk of recurrence who were enrolled between September 2019 and April 2022. Furthermore, 102 matched historical controls were selected using propensity score matching. With a median follow-up time of 19.6 (3.5-91.7) months, AZA maintenance therapy significantly improved relapse-free survival (RFS; log-rank test, p = 0.01). The AZA and control groups had a 1-year RFS of 87.7% (95% confidence interval [CI], 0.80-0.96) and 72.2% (95% CI, 0.64-0.82), respectively, with a hazard ratio (HR) of 0.21 (95% CI, 0.09-0. 47; p < 0.01). There were no grade 4 adverse effects or deaths related to AZA. Refractory patients with favorable/intermediate-risk acute myeloid leukemia (AML) benefited more from AZA maintenance therapy than those with adverse-risk AML according to the European Leukemia Net guidelines (RFS in favorable/intermediate-risk AML, HR = 0.29, 95% CI, 0.11-0.79; RFS in adverse-risk AML, HR = 0.57, 95% CI, 0.21-1.6; p for interaction = 0.03). Our findings suggest that AZA maintenance therapy following allo-HSCT was safe and could reduce the incidence of relapse, particularly for refractory patients with favorable/intermediate-risk AML.

Prophylactic therapy using epigenetic agents for RUNX1::RUNXT1-positive high-risk AML after Allo-HSCT.

Disease recurrence is the leading cause of treatment failure in patients with RUNX1::RUNXT1-positive acute myeloid leukemia (AML) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Post-transplant maintenance therapy, guided by monitoring minimal residual disease (MRD), is commonly administered; however, relapse rates remain high. This prospective study aimed to assess the effectiveness and safety of epigenetic agents as prophylactic therapy in patients with RUNX1::RUNXT1-positive AML. Thirty high-risk patients received prophylactic therapy (n = 17 and n = 13 in the chidamide and AZA groups, respectively) between January 2019 and July 2023. 34 high-risk patients who received preemptive treatment due to molecular relapse were included in the analysis. The two-year relapse-free survival (RFS) and overall survival (OS) were significantly higher in the prophylactic group compared to the preemptive group (82.82% vs. 51.38%, P = 0.014; 86.42% vs. 56.16%, P = 0.025, respectively); 2-year cumulative incidence of relapse rates were 13.8% and 36.40%, respectively (P = 0.037). In conclusion, prophylactic therapy with epigenetic agents may improve long-term prognosis and is well-tolerated in patients with RUNX1::RUNXT1-positive high-risk AML. Timely post-transplant prophylactic therapy may be more effective than preemptive therapy based on positive MRD results.

Enantioselective α-Trifluoromethylthiolation of Carbonyl Compounds with AgSCF3 and Trichloroisocyanuric Acid.

We successfully developed an enantioselective trifluoromethylthiolation of structurally diverse carbonyl compounds. Trichloroisocyanuric acid and AgSCF3 were employed to generate active electrophilic trifluoromethylthio species in situ for asymmetric C-SCF3 bond formation. A broad variety of chiral SCF3-carbon nucleophiles (pyrazolones, ß-keto esters, and ß-keto amides) were obtained in excellent yields with high enantioselectivities (up to 92% ee) by Cinchona alkaloid derived squaramide catalysts. The reaction exhibits high efficiency, good enantioselectivity, and high functional group tolerance, which provided a novel and efficient way for asymmetric synthesis of trifluoromethylthiolated carbonyl compounds.

Development and validation of an ultrasound-based deep learning radiomics nomogram for predicting the malignant risk of ovarian tumours.

BACKGROUND: The timely identification and management of ovarian cancer are critical determinants of patient prognosis. In this study, we developed and validated a deep learning radiomics nomogram (DLR_Nomogram) based on ultrasound (US) imaging to accurately predict the malignant risk of ovarian tumours and compared the diagnostic performance of the DLR_Nomogram to that of the ovarian-adnexal reporting and data system (O-RADS). METHODS: This study encompasses two research tasks. Patients were randomly divided into training and testing sets in an 8:2 ratio for both tasks. In task 1, we assessed the malignancy risk of 849 patients with ovarian tumours. In task 2, we evaluated the malignancy risk of 391 patients with O-RADS 4 and O-RADS 5 ovarian neoplasms. Three models were developed and validated to predict the risk of malignancy in ovarian tumours. The predicted outcomes of the models for each sample were merged to form a new feature set that was utilised as an input for the logistic regression (LR) model for constructing a combined model, visualised as the DLR_Nomogram. Then, the diagnostic performance of these models was evaluated by the receiver operating characteristic curve (ROC). RESULTS: The DLR_Nomogram demonstrated superior predictive performance in predicting the malignant risk of ovarian tumours, as evidenced by area under the ROC curve (AUC) values of 0.985 and 0.928 for the training and testing sets of task 1, respectively. The AUC value of its testing set was lower than that of the O-RADS; however, the difference was not statistically significant. The DLR_Nomogram exhibited the highest AUC values of 0.955 and 0.869 in the training and testing sets of task 2, respectively. The DLR_Nomogram showed satisfactory fitting performance for both tasks in Hosmer-Lemeshow testing. Decision curve analysis demonstrated that the DLR_Nomogram yielded greater net clinical benefits for predicting malignant ovarian tumours within a specific range of threshold values. CONCLUSIONS: The US-based DLR_Nomogram has shown the capability to accurately predict the malignant risk of ovarian tumours, exhibiting a predictive efficacy comparable to that of O-RADS.

Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study.

BACKGROUND: Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized management strategies. So, we have developed an ultrasound (US)-based multiclass prediction algorithm for differentiating between benign, borderline, and malignant ovarian tumours. METHODS: We randomised data from 849 patients with ovarian tumours into training and testing sets in a ratio of 8:2. The regions of interest on the US images were segmented and handcrafted radiomics features were extracted and screened. We applied the one-versus-rest method in multiclass classification. We inputted the best features into machine learning (ML) models and constructed a radiomic signature (Rad_Sig). US images of the maximum trimmed ovarian tumour sections were inputted into a pre-trained convolutional neural network (CNN) model. After internal enhancement and complex algorithms, each sample's predicted probability, known as the deep transfer learning signature (DTL_Sig), was generated. Clinical baseline data were analysed. Statistically significant clinical parameters and US semantic features in the training set were used to construct clinical signatures (Clinic_Sig). The prediction results of Rad_Sig, DTL_Sig, and Clinic_Sig for each sample were fused as new feature sets, to build the combined model, namely, the deep learning radiomic signature (DLR_Sig). We used the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) to estimate the performance of the multiclass classification model. RESULTS: The training set included 440 benign, 44 borderline, and 196 malignant ovarian tumours. The testing set included 109 benign, 11 borderline, and 49 malignant ovarian tumours. DLR_Sig three-class prediction model had the best overall and class-specific classification performance, with micro- and macro-average AUC of 0.90 and 0.84, respectively, on the testing set. Categories of identification AUC were 0.84, 0.85, and 0.83 for benign, borderline, and malignant ovarian tumours, respectively. In the confusion matrix, the classifier models of Clinic_Sig and Rad_Sig could not recognise borderline ovarian tumours. However, the proportions of borderline and malignant ovarian tumours identified by DLR_Sig were the highest at 54.55% and 63.27%, respectively. CONCLUSIONS: The three-class prediction model of US-based DLR_Sig can discriminate between benign, borderline, and malignant ovarian tumours. Therefore, it may guide clinicians in determining the differential management of patients with ovarian tumours.

Bone Marrow Mesenchymal Stem Cells-Derived Exosomes Promote Survival of Random Flaps in Rats through NRF2-Mediated Antioxidative Stress.

BACKGROUND: Random flaps are the most used defect repair method for head and neck tumors and trauma plastic surgery. The distal part of the flap often undergoes oxidative stress (OS), ultimately leading to flap necrosis. Stem cells exosomes exhibit potential effects related to anti-inflammatory, regenerative, and antioxidant properties. Nuclear factor erythroid-2-related factor 2 (Nrf2) is an important factor in regulating oxidative balance. Exosomes have been reported to monitor its transcription to alleviate OS. This study examined the impacts and underlying mechanisms of antioxidant actions of exosomes derived from bone marrow mesenchymal stem cells (BMSCs-Exo) on random flaps. METHODS: BMSCs-Exo was injected into the tail veins of rats on days 0, 1, and 2 after surgery of random flaps. The rats were euthanized on day 3 to calculate the survival rate. Immunohistochemical staining, western blotting, dihydroethidium probe, superoxide dismutase, and malondialdehyde assay kits were used to detect OS level. Human umbilical vein endothelial cells were co-cultured with BMSCs-Exo and ML385 (an inhibitor of Nrf2) in vitro. RESULTS: BMSCs-Exo may significantly improve the survival rate of the random flaps by reducing apoptosis, inflammation, and OS while increasing angiogenesis. Besides, BMSCs-Exo can also increase mitochondrial membrane potential and reduce reactive oxygen species levels in vitro. These therapeutic effects might stem from the activation of the Keap1/Nrf2 signaling pathway. CONCLUSION: BMSCs-Exo improved the tissue antioxidant capacity by regulating the keap1/Nrf2 signaling pathway. BMSCs-Exo may be a new strategy to solve the problem of random flap necrosis.

The role of stem cells in small-cell lung cancer: evidence from chemoresistance to immunotherapy.

Small cell lung cancer (SCLC) is the most aggressive subtype of lung cancer, accounting for approximately 15% among all lung cancers. Despite the ability of chemotherapy, the first-line treatment for SCLC, to rapidly shrink tumors, nearly all patients experience recurrence and metastasis within a few months. Cancer stem cells (CSCs) are a small population of tumor cells responsible for tumorigenesis, metastasis, and recurrence after treatment, which play a crucial role in chemoresistance by promoting DNA repair and expression of drug resistance-associated proteins. Thus, targeting CSCs has been successful in certain malignancies. Tumor therapy has entered the era of immunotherapy and numerous preclinical trials have demonstrated the effectiveness of immunotherapeutic approaches targeting CSCs, such as tumor vaccines and chimeric antigen receptor (CAR) T cell, and the feasibility of combining them with chemotherapy. Therefore, a deeper understanding of the interaction between CSCs and immune system is essential to facilitate the advances of new immunotherapies approaches targeting CSCs as well as combination with standard drugs such as chemotherapy. This narrative review summarizes the mechanisms of chemoresistance of CSCs in SCLC and the latest advances in targeted therapies. Thereafter, we discuss the effects of CSCs on tumor immune microenvironment in SCLC and corresponding immunotherapeutic approaches. Eventually, we propose that the combination of immunotherapy targeting CSCs with standard drugs is a promising direction for SCLC therapies.

Combined pembrolizumab and bevacizumab therapy effectively inhibits non-small-cell lung cancer growth and prevents postoperative recurrence and metastasis in humanized mouse model.

Antibodies targeting the programmed cell death protein 1/programmed cell death ligand-1 (PD-1/PD-L1) pathway have dramatically changed the treatment landscape of advanced non-small cell lung cancer (NSCLC). However, combination approaches are required to extend this benefit beyond a subset of patients. In addition, it is of equal interest whether these combination therapy can be applied to neoadjuvant therapy of early-stage NSCLC. In this study, we hypothesized that combining immunotherapy with anti-angiogenic therapy may have a synergistic effect in local tumor control and neoadjuvant therapy. To this end, the effect of combination of bevacizumab and pembrolizumab in humanized mouse models was evaluated. Furthermore, we innovatively constructed a neoadjuvant mouse model that can simulate postoperative recurrence and metastasis of NSCLC to perform neoadjuvant study. Tumor growth and changes in the tumor vasculature, along with the frequency and phenotype of tumor-infiltrating lymphocytes, were examined. Additionally, in vivo imaging system (IVIS) was used to observe the effect of neoadjuvant therapy. Results showed that combination therapy could inhibited tumor growth by transforming tumor with low immunoreactivity into inflamed ('hot') tumor, as demonstrated by increased CD8+granzyme B+ cytotoxic T cell infiltration. Subsequent studies revealed that this process is mediated by vascular normalization and endothelial cell activation. IVIS results showed that neoadjuvant therapy can effectively prevent postoperative recurrence and metastasis. Taken together, these preclinical studies demonstrated that the combination of bevacizumab and pembrolizumab had a synergistic effect in both advanced tumor therapy and neoadjuvant setting and therefore provide a theoretical basis for translating this basic research into clinical applications.

Herombopag promotes platelet engraftment and decreases platelet transfusion after allogeneic hematopoietic stem cell transplantation.

The delayed platelet engraftment associated with allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a common complication and often results in increased transplant-related complications. A single-center, prospective, investigator-initiated pilot study was conducted to explore whether herombopag, a second generation thrombopoietin-receptor agonist, would promote platelet engraftment after allo-HSCT. Between 2/2022 and 06/2022, 17 individuals (median age 39; range 15-58 years) with hematological malignancies were enrolled. Herombopag was given for a median of 22 (range 14-61) days at a dose of 7.5 mg/d. The median time to neutrophil >500/µl was 11 (range 9-19) days. The median time to platelet >20 000/µl and >50 000/µl was 13 (range 8-22), and 20 (range 14-45) days, respectively. Compared with historical controls, the cumulative incidence of platelet engraftment after HSCT was significantly higher in the herombopag group (>20 000/µl at day +21, 88% vs 65%, p = .003; >50 000/µl at day +30, 65% vs. 43%, p = .001). Herombopag also reduced the units of platelet transfusion within 30 days post-SCT (3.6 ± 2.5 vs. 5.4 ± 3.2 U, p = .01). In conclusion, it seems likely that herombopag could enhance platelet engraftment after allo-HSCT.

Feature screening with latent responses.

A novel feature screening method is proposed to examine the correlation between latent responses and potential predictors in ultrahigh-dimensional data analysis. First, a confirmatory factor analysis (CFA) model is used to characterize latent responses through multiple observed variables. The expectation-maximization algorithm is employed to estimate the parameters in the CFA model. Second, R-Vector (RV) correlation is used to measure the dependence between the multivariate latent responses and covariates of interest. Third, a feature screening procedure is proposed on the basis of an unbiased estimator of the RV coefficient. The sure screening property of the proposed screening procedure is established under certain mild conditions. Monte Carlo simulations are conducted to assess the finite-sample performance of the feature screening procedure. The proposed method is applied to an investigation of the relationship between psychological well-being and the human genome.

The Composite Immune Risk Score predicts overall survival after allogeneic hematopoietic stem cell transplantation: A retrospective analysis of 1838 cases.

There has been little consensus on how to quantitatively assess immune reconstitution after hematopoietic stem cell transplantation (HSCT) as part of the standard of care. We retrospectively analyzed 11 150 post-transplant immune profiles of 1945 patients who underwent HSCT between 2012 and 2020. 1838 (94.5%) of the cases were allogeneic HSCT. Using the training set of patients (n = 729), we identified a composite immune signature (integrating neutrophil, total lymphocyte, natural killer, total T, CD4+ T, and B cell counts in the peripheral blood) during days 91-180 after allogeneic HSCT that was predictive of early mortality and moreover simplified it into a formula for a Composite Immune Risk Score. When we verified the Composite Immune Risk Score in the validation (n = 284) and test (n = 391) sets of patients, a high score value was found to be associated with hazard ratios (HR) of 3.64 (95% C.I. 1.55-8.51; p = .0014) and 2.44 (95% C.I., 1.22-4.87; p = .0087), respectively, for early mortality. In multivariate analysis, a high Composite Immune Risk Score during days 91-180 remained an independent risk factor for early mortality after allogeneic HSCT (HR, 1.80; 95% C.I., 1.28-2.55; p = .00085). In conclusion, the Composite Immune Risk Score is easy to compute and could identify the high-risk patients of allogeneic HSCT who require targeted effort for prevention and control of infection.

Rosai-Dorfman disease with spinal and multiple intracranial involvement: a case report and literature review.

Rosai-Dorfman disease (RDD) is a condition of unknown etiology, and characterized by the proliferation of histiocytes. RDD most commonly affects lymph nodes, and central nervous system (CNS) involvement is rare. Here, we describe the case of a 43-year-old man who presented with an intradural tumour of the thoracic spine. The patient underwent a laminectomy for tumour resection and pathology results diagnosed the tumour as a RDD. Two years later, brain magnetic resonance imaging (MRI) revealed multiple intracranial dural-based lesions. Prednisolone treatment was initiated and led to resolution of the disease. We reviewed the literature to the investigate clinical characteristics, imaging features, diagnosis and treatment protocols pertaining to such cases.

Multifunctional Textiles with Flame Retardant and Antibacterial Properties: A Review.

It is well known that bacterial infections and fire-hazards are potentially injurious in daily life. With the increased security awareness of life and properties as well as the improvement of living standards, there has been an increasing demand for multifunctional textiles with flame retardant and antibacterial properties, especially in the fields of home furnishing and medical protection. So far, various treatment methods, including the spray method, the dip-coating method, and the pad-dry-cure method, have been used to apply functional finishing agents onto fabrics to achieve the functionalization in the past exploration stage. Moreover, in addition to the traditional finishing technology, a number of novel technologies have emerged, such as layer-by-layer (LBL) deposition, the sol-gel process, and chemical grafting modification. In addition, some natural biomasses, including chitin, chitosan (CS), and several synthetic functional compounds that possess both flame-retardant and bacteriostatic properties, have also received extensive attention. Hence, this review focuses on introducing some commonly used finishing technologies and flame retardant/antibacterial agents. At the same time, the advantages and disadvantages of different methods and materials were summarized, which will contribute to future research and promote the development and progress of the industry.

Ultrasonic-assisted glycosylation with κ-carrageenan on the functional and structural properties of fish gelatin.

BACKGROUND: Fish gelatin (FG) has multifunctional properties similar to mammalian gelatin (MG), and it has been recognized as the optimal alternative to MG. While its poor surface-active and gelling properties significantly limit its application values, glycosylation has been successfully used to increase surface-active properties of FG, but the influence of ultrasonic-associated glycosylation (UAG) on the gelling and structural characteristics of FG is still rarely reported. This article explores UAG (100-200 W, 0.5-1 h) with κ-carrageenan (κC) on the functional properties (emulsifying, gelling and rheological properties) and structural characteristics of FG. RESULTS: The longer time and higher power of ultrasonics accelerated the glycosylation reaction with an increase in glycosylation degree and browning index values. Compared with original FG, FG-κC mixture and bovine gelatin, UAG-modified FG possessed higher emulsification activity index, emulsion stability index, gel strength, hardness and melting temperature values. Among them, gelatin modified by appropriate ultrasonic conditions (200 W, 0.5 h) had the highest emulsifying and gelling properties. Rheological results showed that UAG contributed to the gelation process of gelatin with advanced gelation time and endowed it with high viscosity. Structural analysis indicated that UAG promoted κC to link with FG by the formation of covalent and hydrogen bonds, restricting more bound and immobilized water in the gels, exhibiting higher gelling properties. CONCLUSION: This work showed that UAG with κC is a promising method to produce high gelling and emulsifying properties of FG that could replace MG. © 2023 Society of Chemical Industry.

Spatiotemporal Expression Patterns of Critical Genes Involved in FGF Signaling During Morphogenesis and Odontogenesis of Deciduous Molars in Miniature Pigs.

The fibroblast growth factor (FGF) pathway plays an important role in epithelial-mesenchymal interactions during tooth development. Nevertheless, how the ligands, receptors, and antagonists of the FGF pathway are involved in epithelial-mesenchymal interactions remains largely unknown. Miniature pigs exhibit tooth anatomy and replacement patterns like those in humans and hence can serve as large animal models. The present study investigated the spatiotemporal expression patterns of critical genes encoding FGF ligands (FGF3, FGF4, FGF7, and FGF9), antagonists (SPRY2 and SPRY4) and receptors (FGFR1, FGFR2, and FGFR3) in the third deciduous molars of miniature pigs at the cap (embryonic day 40, E40), early bell (E50), and late bell (E60) stages. The results of in situ hybridization (ISH) with tyramide signal amplification and of qRT-PCR analysis revealed increased expression of FGF7, FGFR1, FGFR2, and SPRY4 in dental epithelium and of FGF7 and FGFR1 in mesenchyme from E40 to E50. In contrast, the results revealed decreased expression of FGF3, FGF4, FGF9, and FGFR3 in dental epithelium and of FGF4, FGF9, FGFR2, and FGFR3 in the mesenchyme from E40 to E60. Mesenchyme signals of FGF3, FGF4, FGF7, SPRY2, FGFR2, and FGFR3 were concentrated in the odontoblast layer from E50 to E60. The distinct expression patterns of these molecules indicated elaborate regulation during dental morphogenesis. Our results provide a foundation for further investigation into fine-tuning dental morphogenesis and odontogenesis by controlling interactions between dental epithelium and mesenchyme, thus promoting tooth regeneration in large mammals.

The associations of air pollution and socioeconomic factors with esophageal cancer in China based on a spatiotemporal analysis.

Rapid urbanization and industrialization in China have incurred serious air pollution and consequent health concerns. In this study, we examined the modifying effects of urbanization and socioeconomic factors on the association between PM2.5 and incidence of esophageal cancer (EC) in 2000-2015 using spatiotemporal techniques and a quasi-Poisson generalized linear model. The results showed a downward trend of EC and high-risk areas aggregated in North China and Huai River Basin. In addition, a stronger association between PM2.5 and incidence was observed in low urbanization group, and the association was stronger for females than males. When exposure time-windows were adjusted as 0, 5, 10, 15 years, the incidence risk increased by 2.48% (95% CI: 2.23%, 2.73%), 2.20% (95% CI: 1.91%, 2.49%), 2.18% (95% CI%: 1.92%, 2.43%), 1.87% (95% CI%:1.64, 2.10%) for males, respectively and 4.03% (95% CI: 3.63%, 4.43%), 2.20% (95% CI: 1.91%, 2.49%), 3.97% (95% CI: 3.54%, 4.41%), 3.06% (95% CI: 2.71%, 3.41%) for females, respectively. The findings indicated people in low urbanization group faced with a stronger EC risk caused by PM2.5, which contributes to a more comprehensive understanding of combating EC challenges related to PM2.5 pollution.

Inhibition of Luman/CREB3 expression leads to the upregulation of testosterone synthesis in mouse Leydig cells.

Luman, also known as cAMP-response element-binding protein 3, is an endoplasmic reticulum stress-related protein that has been identified as a novel transcriptional coregulator of a variety of nuclear receptors. Herein, immunohistochemistry results showed that Luman was specifically expressed in mouse Leydig cells in an age-dependent increase manner, from prepuberty to sexual maturation. Luman was not detected in Sertoli cells within the seminiferous tubules at any developmental period. The immunofluorescent experiment indicated that Luman was mainly located within the cytoplasm of murine Leydig tumor cells (MLTC-1) and primary Leydig cells (PLCs). To investigate the physiological function of Luman, experiments were conducted to examine the consequences of short hairpin RNA- and small interfering RNA-mediated Luman knock-down in MLTC-1 and PLCs, respectively. Luman knock-down significantly upregulated the expression of steroidogenic acute regulatory, cytochrome P450 cholesterol side-chain cleavage enzymes, 3ß-hydroxysteroid dehydrogenase, and 17-α-hydroxylase/C17-20 lyase in MLTC-1 cells and PLCs. Luman knock-down caused an increase in human chorionic gonadotropin-stimulated testosterone production in vitro and in vivo. The nuclear receptors SF-1 and Nur-77 were significantly increased upon Luman knock-down in MLTC-1. By contrast, the level of the nuclear receptor SHP decreased. Luciferase reporter assay results demonstrated that Luman knock-down upregulated the activity of SF-1 and Nur-77 promoters. These data suggested that Luman expressed in mouse Leydig cells in an age-dependent increase manner. Luman knock-down upregulated the activity of SF-1 and Nur-77 promoters, which lead to the increase of testosterone synthesis and steroidogenesis genes expression. In conclusion, these findings provide us with new insights into the role Luman played in male reproduction.

Using time-series Sentinel-1 data for soil prediction on invaded coastal wetlands.

Coastal soils are particularly sensitive to nonnative species invasion. In this context, spatially explicit soil information is essential for improving the knowledge of the role of soil in changing environments, supporting coastal sustainable management. Synthetic-aperture radar (SAR) data provides an attractive opportunity to monitor soil because the acquisition of images is independent of weather and daylight. However, SAR has not been commonly used for soil prediction. In this study, we firstly investigated the temporal variation of vegetation canopy and the soil-vegetation relationship using Sentinel-1 data in an invaded coastal wetland. And then we built 3D models to predict soil properties at multiple depths. A total of 16 Sentinel-1 images were acquired in a growing season. A series of soil physicochemical properties were examined including soil bulk density, texture, organic/inorganic carbon, pH, salinity, total nitrogen, and C/N ratio, relating to three depth layers in the top 1-m depth. Our results showed that time-series Sentinel-1 data can capture temporal characteristics of vegetation, and VH/VV was more sensitive to the vegetation growth than VH and VV. The soil-vegetation relationship captured by time-series SAR data was beneficial to predict soil properties, especially for soil chemical properties. The models provided permissible prediction accuracy, with an average RPD of 0.99. We concluded that the prior understanding of the temporal variation of SAR data is essential for developing practical soil prediction strategy. Our results highlight that SAR has the potential to predict a diverse set of soil properties in coastal wetlands with dense vegetation cover.

Correlation Between Protein Primary Structure and Soluble Expression Level of HSA dAb in Escherichia coli.

It is widely accepted that features such as pI, length, molecular mass and amino acid (AA) sequence have a significant influence on protein solubility. Here, we mainly focused on AA composition and explored those that most affected the soluble expression level of human serum albumin (HSA) domain antibody (dAb). The soluble expression and sequence of 65 dAb variants were analysed using clustering and linear modelling. Certain AAs significantly affected the soluble expression level of dAb, with the specific AA combinations being (S, R, N, D, Q), (G, R, C, N, S) and (R, S, G); these combinations respectively affected the dAb expression level in the broth supernatant, the level in the pellet lysate and total soluble dAb. Among the 20 AAs, R displayed a negative influence on the soluble expression level, whereas G and S showed positive effects. A linear model was built to predict the soluble expression level from the sequence; this model had a prediction accuracy of 80%. In summary, increasing the content of polar AAs, especially G and S, and decreasing the content of R, was helpful to improve the soluble expression level of HSA dAb.