Spatiotemporally continuous PM2.5 dataset in the Mekong River Basin from 2015 to 2022 using a stacking model.

With the potential to cause millions of deaths, PM2.5 pollution has become a global concern. In Southeast Asia, the Mekong River Basin (MRB) is experiencing heavy PM2.5 pollution and the existing PM2.5 studies in the MRB are limited in terms of accuracy and spatiotemporal coverage. To achieve high-accuracy and long-term PM2.5 monitoring of the MRB, fused aerosol optical depth (AOD) data and multi-source auxiliary data are fed into a stacking model to estimate PM2.5 concentrations. The proposed stacking model takes advantage of convolutional neural network (CNN) and Light Gradient Boosting Machine (LightGBM) models and can well represent the spatiotemporal heterogeneity of the PM2.5-AOD relationship. In the cross-validation (CV), comparison with CNN and LightGBM models shows that the stacking model can better suppress overfitting, with a higher coefficient of determination (R2) of 0.92, a lower root mean square error (RMSE) of 5.58 µg/m3, and a lower mean absolute error (MAE) of 3.44 µg/m3. For the first time, the high-accuracy PM2.5 dataset reveals spatially and temporally continuous PM2.5 pollution and variations in the MRB from 2015 to 2022. Moreover, the spatiotemporal variations of annual and monthly PM2.5 pollution are also investigated at the regional and national scales. The dataset will contribute to the analysis of the causes of PM2.5 pollution and the development of mitigation policies in the MRB.

Chinese Soil Moisture Observation Network and Time Series Data Set for High Resolution Satellite Applications.

High-quality ground observation networks are an important basis for scientific research. Here, an automatic soil observation network for high-resolution satellite applications in China (SONTE-China) was established to measure both pixel- and multilayer-based soil moisture and temperature. SONTE-China is distributed across 17 field observation stations with a variety of ecosystems, covering both dry and wet zones. In this paper, the average root mean squared error (RMSE) of station-based soil moisture for well-characterized SONTE-China sites is 0.027 m3/m3 (0.014~0.057 m3/m3) following calibration for specific soil properties. The temporal and spatial characteristics of the observed soil moisture and temperature in SONTE-China conform to the geographical location, seasonality and rainfall of each station. The time series Sentinel-1 C-band radar signal and soil moisture show strong correlations, and the RMSE of the estimated soil moisture from radar data was lower than 0.05 m3/m3 for the Guyuan and Minqin stations. SONTE-China is a soil moisture retrieval algorithm that can validate soil moisture products and provide basic data for weather forecasting, flood forecasting, agricultural drought monitoring and water resource management.

An Improved Spatiotemporal Data Fusion Method for Snow-Covered Mountain Areas Using Snow Index and Elevation Information.

Remote sensing images with high spatial and temporal resolution in snow-covered areas are important for forecasting avalanches and studying the local weather. However, it is difficult to obtain images with high spatial and temporal resolution by a single sensor due to the limitations of technology and atmospheric conditions. The enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) can fill in the time-series gap of remote sensing images, and it is widely used in spatiotemporal fusion. However, this method cannot accurately predict the change when there is a change in surface types. For example, a snow-covered surface will be revealed as the snow melts, or the surface will be covered with snow as snow falls. These sudden changes in surface type may not be predicted by this method. Thus, this study develops an improved spatiotemporal method ESTARFM (iESTARFM) for the snow-covered mountain areas in Nepal by introducing NDSI and DEM information to simulate the snow-covered change to improve the accuracy of selecting similar pixels. Firstly, the change in snow cover is simulated according to NDSI and DEM. Then, similar pixels are selected according to the change in snow cover. Finally, NDSI is added to calculate the weights to predict the pixels at the target time. Experimental results show that iESTARFM can reduce the bright abnormal patches in the land area compared to ESTARFM. For spectral accuracy, iESTARFM performs better than ESTARFM with the root mean square error (RMSE) being reduced by 0.017, the correlation coefficient (r) being increased by 0.013, and the Structural Similarity Index Measure (SSIM) being increased by 0.013. For spatial accuracy, iESTARFM can generate clearer textures, with Robert's edge (Edge) being reduced by 0.026. These results indicate that iESTARFM can obtain higher prediction results and maintain more spatial details, which can be used to generate dense time series images for snow-covered mountain areas.

Experimental Research on Flexural Mechanical Properties of Ultrahigh Strength Concrete Filled Steel Tubes.

Based on the project of the Guansheng Qujiang Bridge, the flexural mechanical properties of an ultrahigh strength concrete filled steel tube (UHSCFST) were discussed. A total of six UHSCFST beam specimens were tested, and the cube strength (fcu) of the core concrete reached 80.3-115.2 MPa. The effects of concrete strength on flexural bearing capacity, deformation characteristics, and failure modes of UHSCFST specimens were discussed. Test results showed that the bending failure modes of UHSCFST specimens were the same as those of ordinary ones. The failure of UHSCFST specimens was attributed to excessive deflection, and local buckling occurred in the compression zone. Moreover, the bending capacity of the specimens did not decrease, even if they had yielded. Although ultrahigh strength concrete was poured, all of the specimens displayed outstanding bending ductility. The main function of core concrete was to provide radial restraint for the steel tube to avoid premature buckling. When the steel content of the specimen section was constant, the strength increases of core concrete had a slight impact on the bending failure mode, bearing capacity and ductility of UHSCFST specimen. The research results can deepen the understanding of the mechanical behaviors of the UHSCFST composite truss structure.

Soil Moisture Content Retrieval from Remote Sensing Data by Artificial Neural Network Based on Sample Optimization.

Soil moisture content (SMC) plays an essential role in geoscience research. The SMC can be retrieved using an artificial neural network (ANN) based on remote sensing data. The quantity and quality of samples for ANN training and testing are two critical factors that affect the SMC retrieving results. This study focused on sample optimization in both quantity and quality. On the one hand, a sparse sample exploitation (SSE) method was developed to solve the problem of sample scarcity, resultant from cloud obstruction in optical images and the malfunction of in situ SMC-measuring instruments. With this method, data typically excluded in conventional approaches can be adequately employed. On the other hand, apart from the basic input parameters commonly discussed in previous studies, a couple of new parameters were optimized to improve the feature description. The Sentinel-1 SAR and Landsat-8 images were adopted to retrieve SMC in the study area in eastern Austria. By the SSE method, the number of available samples increased from 264 to 635 for ANN training and testing, and the retrieval accuracy could be markedly improved. Furthermore, the optimized parameters also improve the inversion effect, and the elevation was the most influential input parameter.

METTL3-mediated LINC00657 promotes osteogenic differentiation of mesenchymal stem cells via miR-144-3p/BMPR1B axis.

N6-methyladenosine (m6A) modification plays a crucial role in the progression of osteoporosis (OP). The study aimed to explore the effects of methyltransferase-like 3 (METTL3) in OP. The levels of METTL3, LINC00657, miR-144-3p and BMPR1B were detected using qPCR. Osteogenesis was assessed using alizarin red and alkaline phosphatase (ALP) staining assays. The protein expression of Bglap, Runx2 and Col1a1 was measured by western blot. The targets of LINC00657 and miR-144-3p were screened by bioinformatic analysis. The interaction between miR-144-3p and LINC00657 or BMPR1B was analyzed by dual-luciferase reporter assay and RNA pull-down assay. The results showed that METTL3 was downregulated in OP. METTL3 mediated m6A methylation of LINC00657 to promote the development of osteogenesis. Further study indicated that LINC00657 functioned as a ceRNA to upregulate BMPR1B via sponging miR-144-3p. Additionally, BMPR1B knockdown alleviated the effects of METTL3 on osteogenesis of bone marrow mesenchymal stem cells (BMSCs). Taken together, METTL3 facilitated osteogenic differentiation of BMSCs via the LINC00657/miR-144-3p/BMPR1B axis. Our findings may provide a novel insight of m6A methylation in the development of OP.

Seismic Performance of Bridge Piers Constructed with PP-ECC at Potential Plastic Hinge Regions.

This work presents an experimental investigation on the seismic performance of bridge piers constructed with polypropylene fiber reinforced engineered cementitious composite (PP-ECC) at potential plastic hinge regions. Eight solid square bridge piers are tested under a combination of reversed cyclic lateral loading and constant axial vertical loading. The test variables include the reinforcement stirrup ratio (0 vol.%, 0.46 vol.%, and 0.79 vol.%), axial compression ratio (0.1 and 0.3) and height of the PP-ECC regions (0, 250, and 500 mm). Seismic performance of eight specimens is presented and interpreted, including the failure mode, hysteretic curves, loading-resistance capacity, ductility, stiffness degradation, energy dissipation, and equivalent viscous damping ratio. The material test on the PP-ECC plate specimen suggests that the PP-ECC has obvious strain-hardening behavior and multiple fine-cracking characteristics, with the tensile strength and strain capacity greater than 3.2 MPa and 2.6%, respectively. The PP-ECC material applied at the potential plastic hinge regions notably improves the seismic performance and damage tolerance of bridge piers. The influence of the aforementioned crucial parameters has also been investigated in detail. The axial compression ratio and the height of PP-ECC region have a major influence on the seismic performance of PP-ECC piers. In comparison, the stirrup ratio has a limited effect on the seismic behavior of PP-ECC piers. The experimental findings shed light on the mechanism of the PP-ECC that contributes to the seismic performance of bridge piers and provide some valuable guidance in the seismic design of PP-ECC piers.

Karacoline, identified by network pharmacology, reduces degradation of the extracellular matrix in intervertebral disc degeneration via the NF-κB signaling pathway.

Karacoline is a compound found in the plant Aconitum kusnezoffii Reichb. Although Aconitum kusnezoffii Reichb is widely used for the treatment of pain, very few studies have been carried out on the use of karacoline due to its potential toxicity. In this study, we selected key matrix metalloproteinases (MMPs), collagen II, and aggrecan as targets due to their association with intervertebral disc degeneration (IDD). Using these targets, we then used network pharmacology to predict a series of molecules that might exert therapeutic effects on IDD. Of these molecules, karacoline was predicted to have the best effect. Tumor necrosis factor (TNF)-α is known to promote the degeneration of the extracellular matrix in IDD. We therefore applied different concentrations of karacoline (0, 1.25, or 12.88 µM) along with 100 ng/mL TNF-α to rat nucleus pulposus cells and found that karacoline reduced the expression of MMP-14 in IDD by inhibiting the nuclear factor (NF)-κB pathway, while collagen II and aggrecan expression was increased. This suggested that extracellular matrix degradation was inhibited by karacoline (P < 0.05). Our data therefore reveal a new clinical application of karacoline and provide support for the use of network pharmacology in predicting novel drugs.

Chiral Induction and Remote Chiral Communication in Quinoline Oligoamide Foldamers for Determination of Enantiomeric Excess and Absolute Configuration of Chiral Amines and Their Derivatives.

Two pentameric foldamers, Q5 and Q5C-S, containing a C-F bond were synthesized based on quinoline oligamide foldamers for the measurement of enantiomeric excess and for the determination of absolute configuration of chiral amines, diamines, amino alcohols, and α-amino acid esters. Chiral induction of Q5 was triggered in situ when the chiral analytes reacted with the C-F bond in Q5 by a N-nucleophilic substitution reaction, leading to a linear correlation between the CD amplitude at the region of quinoline chromophores and the ee values of the chiral analytes, which can be used for the ee determination of chiral analytes. Furthermore, the CD intensity of Q5C-S containing a chiral motif at its C-terminus enhances via remote, favorable chiral communication when the chiral induction was triggered in situ by chiral analytes at the N-terminus matches the original helicity of Q5C-S, but decreases via remote, conflicted chiral communication when the chiral induction is triggered in situ by chiral molecules at the N-terminus mismatches the original one. The system can thus be used for determination of the absolute configuration of chiral analytes, given that the chirality of the chiral motif at the C-terminus of Q5C-S is known.

Significant Enhancement of Circularly Polarized Luminescence Dissymmetry Factors in Quinoline Oligoamide Foldamers with Absolute Helicity.

When S- or R- oxazolylaniline enantiomers were attached to achiral quinoline oligoamide foldamers (QOFs), a single diastereomerically pure P- or M-handed foldamer was observed and exhibits negative or positive circularly polarized luminescence with the emission dissymmetry factors | glum| up to 0.038, which is significantly larger than that of QOF with incomplete chiral induction. More importantly, the CPL dissymmetry factors, together with the absorption dissymmetry factors, are enhanced with increases in the lengths of QOFs.

Plasma VDBP, 25(OH)D, and GSH levels predict surgical outcome in patients with cervical spondylotic myelopathy.

This study intends to investigate the predictive values of plasma Vitamin D-binding protein (VDBP), 25-hydroxyvitamin D [25(OH)D], and glutathione (GSH) levels in the outcome of cervical spondylotic myelopathy (CSM) surgery. Surgery outcomes of 236 CSM patients were determined. Recovery rate was calculated according to Japanese Orthopaedic Association (JOA) scores during follow-up. CSM patients with a recovery rate >50% were assigned with good prognosis and the rest were with fair prognosis. Preoperative and postoperative neurologic function scores were compared among groups. Plasma VDBP and 25(OH)D levels, as well as GSH levels were measured by ELISA and glutathione reductase recycling assay, respectively. Pearson's correlation coefficient was performed to analyze the correlation among plasma VDBP, 25(OH)D, and GSH levels. Receiver operating characteristic (ROC) curve was applied to evaluate the predictive value of plasma VDBP, 25(OH)D, and GSH levels for surgical outcome. Logistic regression model was used to analyze risk factors for surgical outcome. Compared with those with fair prognosis, CSM patients with good prognosis group exhibited higher postoperative neurologic function scores, plasma VDBP, 25(OH)D, and GSH levels, and better improvements in spinal cord compression and motions of the cervical vertebra. Plasma VDBP, 25(OH)D, and GSH levels were favorable prognostic factors for CSM surgical outcome. The sensitivity and specificity of plasma VDBP, plasma 25(OH)D, and plasma GSH were 89.8% and 91.7%, 85.8% and 84.4%, and 79.5% and 91.7%, respectively. Our study provides evidence that higher plasma VDBP, 25(OH)D, and GSH levels may predict better surgical outcome in CSM patients.

Semantic Segmentation of Building Roof in Dense Urban Environment with Deep Convolutional Neural Network: A Case Study Using GF2 VHR Imagery in China.

This paper presents a novel approach for semantic segmentation of building roofs in dense urban environments with a Deep Convolution Neural Network (DCNN) using Chinese Very High Resolution (VHR) satellite (i.e., GF2) imagery. To provide an operational end-to-end approach for accurately mapping build roofs with feature extraction and image segmentation, a fully convolutional DCNN with both convolutional and deconvolutional layers is designed to perform building roof segmentation. We selected typical cities with dense and diverse urban environments in different metropolitan regions of China as study areas, and sample images were collected over cities. High performance GPU-mounted workstations are employed to perform the model training and optimization. With the building roof samples collected over different cities, the predictive model with convolution layers is developed for building roof segmentation. The validation shows that the overall accuracy (OA) and the mean Intersection Over Union (mIOU) of DCNN-based semantic segmentation results are 94.67% and 0.85, respectively, and the CRF-refined segmentation results achieved OA of 94.69% and mIOU of 0.83. The results suggest that the proposed approach is a promising solution for building roof mapping with VHR images over large areas in dense urban environments with different building patterns. With the operational acquisition of GF2 VHR imagery, it is expected to develop an automated pipeline of operational built-up area monitoring, and the timely update of building roof map could be applied in urban management and assessment of human settlement-related sustainable development goals over large areas.

Design, cyclization, and optimization of MMP13-TIMP1 interaction-derived self-inhibitory peptides against chondrocyte senescence in osteoarthritis.

The matrix metallopeptidase 13 (MMP13) is a central regulator of chondrocyte senescence that contributes to the development and progression of osteoarthritis (OA). In the present study, the native inhibitory structure of MMP13 in complex with its natural cognate inhibitor, the tissue inhibitor of metalloproteinases 1 (TIMP1), was modeled at atomic level using a grafting-based structural bioinformatics method with existing crystal structures. The modeled complex structure was then examined in detail, from which a TIMP1 inhibitory site that directly inserts into the active site of MMP13 enzyme was identified. The inhibitory site contains a coiled inhibitory loop (ILP) and a stretched N-terminal tail (NTT); they are highly structured in the intact MMP13-TIMP1 complex interface, but exhibit a large flexibility and intrinsic disorder when split from the interface context. In vitro binding assays demonstrated that the isolated ILP and NTT peptides cannot effectively rebind at the MMP13 active site (Kd > ~100 µM or = n.d.), although they have all key interacting residues in the enzyme inhibition. In silico simulations revealed that splitting of the peptide segments from TIMP1 inhibitory site does not influence the direct intermolecular interaction between MMP13 and the peptides substantially; instead, the large conformational flexibility of these isolated peptides in absence of interface context is primarily responsible for the affinity impairment, which would incur a considerable entropy penalty upon the peptide binding to MMP13. An extended version of ILP peptide, namely eILP (63TPAMESVCGY72), was redesigned with a rational strategy to derive a number of its cyclized counterparts by introducing a disulfide bridge across the peptide two-termini; the redesign reduces the peptide flexibility in free state and constrains the peptide pre-folding to a native-like conformation, which would help the peptide binding with minimized entropy penalty. Binding assays substantiated that the affinity Kd values of four designed cyclic peptides (, , and ) were improved to 23, 67, 42 and 18 µM, respectively, from the 96 µM of linear eILP peptide.

Relationship between serum levels of miR-204 and clinical features of patients with lumbar disc herniation - an analysis based on 1,589 cases.

This study aims to investigate the relationship between serum miR-204 and clinical features of patients with lumbar disc herniation (LDH). Clinical data of 1589 LDH patients were retrospectively analyzed. There were 953 patients (group A) with a duration of disease shorter than 3 months, and another 636 patients (group B) with a duration of disease longer than 3 months. A total of 300 healthy volunteers were also selected in the same period. Results showed that there was no significant difference in miR-204 expression between males and females (p>0.05). No significant differences in miR-204 expression level were found among different ages (p>0.05). miR-204 in patients with LHD at or below the fourth lumbar vertebrae was significantly higher than those in patients with LHD above the fourth lumbar vertebrae (p<0.05). miR-204 in 1485 patients with abnormal lumbar spine activity was higher than those in healthy controls (p<0.05). miR-204 expression levels was higher in patients with low back pain than those in patients without low back pain. Among patients with low back pain, miR-204 level in patients with spasm-like waist pain was significantly higher than that in patients with persistent dull low back pain (p<0.05). miR-204 increased with the increase in degree of limited walking (p<0.05). There was no significant difference in miR-204 expression level between patients with bilateral lower limb symptoms and patients with unilateral lower limb symptoms (p>0.05), while miR-204 was significantly higher in patients with lower limb symptoms than that in patients without the symptoms (p<0.05). miR-204 was correlated with knee tendon reflex, heel tendon reflex and degree of straight leg raise abnormality. miR-204 was significantly decreased in patients with improvement after treatment. miR-204 level was closely related to the clinical characteristics of LDH. miR-204 may potentially serve as a prognostic marker for patients with LDH.

MiR-34a Enhances Chondrocyte Apoptosis, Senescence and Facilitates Development of Osteoarthritis by Targeting DLL1 and Regulating PI3K/AKT Pathway.

BACKGROUND/AIMS: Osteoarthritis (OA) is the prevalent degenerative disease caused by various factors. MicroRNAs are important regulators in the inflammation and immune response. The aim of this study was to investigate the effect of microRNA-34a (MiR-34a) on the death of chondrocytes, senescence, as well as its role in OA progression. METHODS: A series of experiments involving CCK-8, flow cytometry, ß-galactosidase staining and wound healing assays were conducted to determine the cellular capabilities of proliferation, cell apoptosis, senescence and the ability of cells to recover from injury, respectively. Binding sites between miR-34a and delta-like protein 1 (DLL1) were identified using a luciferase reporter system, whereas mRNA and protein expression of target genes was determined by RT-PCR and immunoblot, respectively. OA model was generated via surgery. RESULTS: We found that miR-34a expression was increased in the cartilage of OA patients. In rat chondrocytes and chondrosarcoma cells, miR-34a transfections noticeably inhibited the expression of DLL1, triggered cell death and senescence, suppressed proliferation, and prevented scratch assay wound closure. However, transfection of a miR-34a inhibitor displayed adverse effects. Additionally, secretion and expression of factors associated with cartilage degeneration were altered via miR-34a. Moreover, miR-34a directly inhibits DLL1 mRNA. Furthermore, concentrations of DLL1, total PI3K, and p-AKT declined in chondrocytes that overexpress miR-34a. DLL1 overexpression elevated PI3K and p-AKT levels, and eliminated cell death triggered by a miR-34a mimic. In vivo, miR-34a remarkably inhibited miR-34a up-regulation, while enhanced the level of DLL1 expression. In the knee joints of surgery-induced OA rats, articular chondrocyte death and loss of cartilage were attenuated via miR-34a antagomir injection. CONCLUSIONS: These findings indicate that miR-34a contributes to chondrocyte death, causing OA progression through DLL1 and modulation of the PI3K/AKT pathway.

Estimation of different data compositions for early-season crop type classification.

Timely and accurate crop type distribution maps are an important inputs for crop yield estimation and production forecasting as multi-temporal images can observe phenological differences among crops. Therefore, time series remote sensing data are essential for crop type mapping, and image composition has commonly been used to improve the quality of the image time series. However, the optimal composition period is unclear as long composition periods (such as compositions lasting half a year) are less informative and short composition periods lead to information redundancy and missing pixels. In this study, we initially acquired daily 30 m Normalized Difference Vegetation Index (NDVI) time series by fusing MODIS, Landsat, Gaofen and Huanjing (HJ) NDVI, and then composited the NDVI time series using four strategies (daily, 8-day, 16-day, and 32-day). We used Random Forest to identify crop types and evaluated the classification performances of the NDVI time series generated from four composition strategies in two studies regions from Xinjiang, China. Results indicated that crop classification performance improved as crop separabilities and classification accuracies increased, and classification uncertainties dropped in the green-up stage of the crops. When using daily NDVI time series, overall accuracies saturated at 113-day and 116-day in Bole and Luntai, and the saturated overall accuracies (OAs) were 86.13% and 91.89%, respectively. Cotton could be identified 40∼60 days and 35∼45 days earlier than the harvest in Bole and Luntai when using daily, 8-day and 16-day composition NDVI time series since both producer's accuracies (PAs) and user's accuracies (UAs) were higher than 85%. Among the four compositions, the daily NDVI time series generated the highest classification accuracies. Although the 8-day, 16-day and 32-day compositions had similar saturated overall accuracies (around 85% in Bole and 83% in Luntai), the 8-day and 16-day compositions achieved these accuracies around 155-day in Bole and 133-day in Luntai, which were earlier than the 32-day composition (170-day in both Bole and Luntai). Therefore, when the daily NDVI time series cannot be acquired, the 16-day composition is recommended in this study.

miR-373 regulates inflammatory cytokine-mediated chondrocyte proliferation in osteoarthritis by targeting the P2X7 receptor.

Inflammatory cytokines commonly initiate extreme changes in the synovium and cartilage microenvironment of osteoarthritis (OA) patients, which subsequently cause cellular dysfunction, especially in chondrocytes. It has been reported that induction of the purinergic P2X7 receptor (P2X7R) can regulate the expression of a variety of inflammatory factors, including interleukin (IL)-6 and -8, leading to OA pathogenesis. However, knowledge of the mechanism of upregulation of P2X7R in OA is still incomplete, and its role in chondrocyte proliferation is also not clear. It was reported previously that the expression of P2X7R was controlled by certain microRNAs, and so we tested the expression of several microRNAs and found that microRNA-373 (miR-373) was downregulated in the chondrocytes from OA patients. Regarding the mechanism of action, miR-373 inhibited chondrocyte proliferation by suppressing the expression of P2X7R, as well as inflammatory factors such as IL-6 and IL-8. Furthermore, the proliferative and pro-inflammatory effects of miR-373 on the chondrocytes could be suppressed by a P2X7R antagonist, further suggesting that miR-373 mediates chondrocyte proliferation and inflammation by targeting P2X7R. Generally, our results suggest a novel method for OA treatment by targeting the miR-373-P2X7R pathway.

Structural modeling of osteoarthritis ADAMTS4 complex with its cognate inhibitory protein TIMP3 and rational derivation of cyclic peptide inhibitors from the complex interface to target ADAMTS4.

The ADAMTS4 (a disintegrin and metalloproteinase with thrombospondin motifs 4) enzyme is a matrix-associated zinc metalloendopeptidase that plays an essential role in the degradation of cartilage aggrecan in arthritic diseases and has been recognized as one of the most primary targets for therapeutic intervention in osteoarthritis (OA). Here, we reported computational modeling of the atomic-level complex structure of ADAMTS4 with its cognate inhibitory protein TIMP3 based on high-resolution crystal template. By systematically examining the modeled complex structure we successfully identified a short inhibitory loop (62EASESLC68) in TIMP3 N-terminal inhibitory domain (NID) that directly participates in blocking the enzyme's active site, which, and its extended versions, were then broken from the full-length protein to serve as the peptide inhibitor candidates of ADAMTS4. Atomistic molecular dynamics simulation, binding energetic analysis, and fluorescence-based assay revealed that the TIMP3-derived linear peptides can only bind weakly to the enzyme (Kd = 74 ±â€¯8 µM), which would incur a considerable entropy penalty due to the high conformational flexibility and intrinsic disorder of these linear peptides. In this respect, we proposed a cyclization strategy to improve enzyme-peptide binding affinity by, instead of traditionally maximizing enthalpy contribution, minimizing entropy cost of the binding, where a disulfide bond was added across the two terminal residues of linear peptides, resulting in a number of TIMP3-derived cyclic peptides. Our studies confirmed that the cyclization, as might be expected, can promote peptide binding capability against ADAMTS4 substantially, with affinity increase by 3-fold, 9-fold and 7-fold for cyclic peptides , and , respectively.

Controlling Helix Sense at N- and C-Termini in Quinoline Oligoamide Foldamers by ß-Pinene-Derived Pyridyl Moieties.

A series of quinoline oligoamide foldamers bearing a ß-pinene-derived pyridyl group at the N-terminus or the C-terminus were synthesized, and the efficiencies of chiral inductions have been evaluated by 1H NMR and CD spectra. The chiral inductions were quantitative when chiral pyridyl acid was appended at the N-terminus, but were inferior when chiral pyridyl amine was appended at the C-terminus. Unexpectedly, N-oxidation on the pyridine ring at the C-terminus does not notably enhance the chiral induction efficiency in spite of the presence of three-center hydrogen bonds.