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Abstract In vivo imaging of large-scale neuronal activity plays a pivotal role in unraveling the function of the brain's circuitry. Multiphoton microscopy, a powerful tool for deep-tissue imaging, has received sustained interest in advancing its speed, field of view and imaging depth. However, to avoid thermal damage in scattering biological tissue, field of view decreases exponentially as imaging depth increases. We present a suite of innovations to optimize three-photon microscopy for large field-of-view imaging at depths unreachable by two-photon microscopy. These techniques enable us to image neuronal activities of transgenic animals expressing protein calcium sensors in a ~ 3.5-mm diameter field-of-view with single-cell resolution in the deepest cortical layer of mouse brains. We further demonstrate simultaneous large field-of-view two-photon and three-photon imaging, subcortical imaging in the mouse brain, and whole-brain imaging in adult zebrafish. The demonstrated techniques can be integrated into typical multiphoton microscopes to enlarge field of view for system-level neural circuit research.

Abstract Background Precision medicine has led to the development of targeted treatment strategies tailored to individual patients based on their characteristics and disease manifestations. Although precision medicine often focuses on a single health outcome for individualized treatment decision rules (ITRs), relying only on a single outcome rather than all available outcomes information leads to suboptimal data usage when developing optimal ITRs. Methods To address this limitation, we propose a Bayesian multivariate hierarchical model that leverages the wealth of correlated health outcomes collected in clinical trials. The approach jointly models mixed types of correlated outcomes, facilitating the “borrowing of information” across the multivariate outcomes, and results in a more accurate estimation of heterogeneous treatment effects compared to using single regression models for each outcome. We develop a treatment benefit index, which quantifies the relative benefit of the experimental treatment over the control treatment, based on the proposed multivariate outcome model. Results We demonstrate the strengths of the proposed approach through extensive simulations and an application to an international Coronavirus Disease 2019 (COVID-19) treatment trial. Simulation results indicate that the proposed method reduces the occurrence of erroneous treatment decisions compared to a single regression model for a single health outcome. Additionally, the sensitivity analyses demonstrate the robustness of the model across various study scenarios. Application of the method to the COVID-19 trial exhibits improvements in estimating the individual-level treatment efficacy (indicated by narrower credible intervals for odds ratios) and optimal ITRs. Conclusion The study jointly models mixed types of outcomes in the context of developing ITRs. By considering multiple health outcomes, the proposed approach can advance the development of more effective and reliable personalized treatment.

Abstract Background There is a need to understand the relationship between COVID-19 Convalescent Plasma (CCP) anti-SARS-CoV-2 IgG levels and clinical outcomes to optimize CCP use. This study aims to evaluate the relationship between recipient baseline clinical status, clinical outcomes, and CCP antibody levels. Methods The study analyzed data from the COMPILE study, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) assessing the efficacy of CCP vs. control, in adults hospitalized for COVID-19 who were not receiving mechanical ventilation at randomization. SARS-CoV-2 IgG levels, referred to as ‘dose’ of CCP treatment, were retrospectively measured in donor sera or the administered CCP, semi-quantitatively using the VITROS Anti-SARS-CoV-2 IgG chemiluminescent immunoassay (Ortho-Clinical Diagnostics) with a signal-to-cutoff ratio (S/Co). The association between CCP dose and outcomes was investigated, treating dose as either continuous or categorized (higher vs. lower vs. control), stratified by recipient oxygen supplementation status at presentation. Results A total of 1714 participants were included in the study, 1138 control- and 576 CCP-treated patients for whom donor CCP anti-SARS-CoV2 antibody levels were available from the COMPILE study. For participants not receiving oxygen supplementation at baseline, higher-dose CCP (/control) was associated with a reduced risk of ventilation or death at day 14 (OR = 0.19, 95% CrI: [0.02, 1.70], posterior probability Pr(OR

Abstract DNA base editors enable direct editing of adenine (A), cytosine (C), or guanine (G), but there is no base editor for direct thymine (T) editing currently. Here we develop two deaminase-free glycosylase-based base editors for direct T editing (gTBE) and C editing (gCBE) by fusing Cas9 nickase (nCas9) with engineered human uracil DNA glycosylase (UNG) variants. By several rounds of structure-informed rational mutagenesis on UNG in cultured human cells, we obtain gTBE and gCBE with high activity of T-to-S (i.e., T-to-C or T-to-G) and C-to-G conversions, respectively. Furthermore, we conduct parallel comparison of gTBE/gCBE with those recently developed using other protein engineering strategies, and find gTBE/gCBE show the outperformance. Thus, we provide several base editors, gTBEs and gCBEs, with corresponding engineered UNG variants, broadening the targeting scope of base editors.

Regeneration of soft tissues, especially those requiring complex vascularization, is a major challenge in the field of tissue engineering. The current types of tissue engineering scaffolds include sponges, electric spinning silk, hydrogels, and 3D printed biomaterials. Among them, hydrogels have the unique property of mimicking extracellular matrix (ECM), which can provide a relatively stable microenvironment for cellular activities and facilitate cell adhesion, proliferation, and differentiation; thus, have become a promising scaffold. In this paper, we present a review of the commonly used types of natural hydrogels and their applications as scaffolds in tissue vascularization. First, we enumerate the importance and advantages of several types of commonly used hydrogels of natural origin in terms of fabricating vascularized tissues or organs. Second, we discuss two different formation modalities of blood vessels, as well as natural hydrogel-based vascularization strategies, including carrying growth factors, stem cell delivery, special scaffold structures and pharmaceutical-enhanced strategy. In addition, we describe the crosslinking strategies of hydrogels as scaffolds for regeneration of vascularized soft tissues, as well as the factors affecting it. Finally, new insights are provided for the development of natural hydrogel-based vascularized soft tissue regeneration research.

Sheep body size can directly reflect the growth rates and fattening rates of sheep and is also an important index for measuring the growth performance of meat sheep. In this study, high-resolution resequencing data from four sheep breeds (Dorper sheep, Suffolk sheep, Ouessant sheep, and Shetland sheep) were analyzed. The nonsynonymous single nucleotide polymorphisms of three candidate genes (KIAA1217, SNTA1, and LTBP1) were also genotyped in 642 healthy Ujumqin sheep using MALDI-TOFMS and the genotyping results were associated with growth traits. The results showed that different genotypes of the KIAA1217 g.24429511T>C locus had significant effects on the chest circumferences of Ujumqin sheep. The SNTA1 g.62222626C>A locus had different effects on the chest depths, shoulder widths and rump widths of Ujumqin sheep. This study showed that these two sites can be used for marker-assisted selection, which will be beneficial for future precision molecular breeding.

The ability to recognize the body sizes of sheep is significantly influenced by posture, especially without artificial fixation, leading to more noticeable changes. This study presents a recognition model using the Mask R-CNN convolutional neural network to identify the sides and backs of sheep. The proposed approach includes an algorithm for extracting key frames through mask calculation and specific algorithms for head-down, head-up, and jumping postures of Ujumqin sheep. The study reported an accuracy of 94.70% in posture classification. We measured the body size parameters of Ujumqin sheep of different sexes and in different walking states, including observations of head-down and head-up. The errors for the head-down position of rams, in terms of body slanting length, withers height, hip height, and chest depth, were recorded as 0.08 ± 0.06, 0.09 ± 0.07, 0.07 ± 0.05, and 0.12 ± 0.09, respectively. For rams in the head-up position, the corresponding errors were 0.06 ± 0.05, 0.06 ± 0.05, 0.07 ± 0.05, and 0.13 ± 0.07, respectively. The errors for the head-down position of ewes, in terms of body slanting length, withers height, hip height, and chest depth, were recorded as 0.06 ± 0.05, 0.09 ± 0.08, 0.07 ± 0.06, and 0.13 ± 0.10, respectively. For ewes in the head-up position, the corresponding errors were 0.06 ± 0.05, 0.08 ± 0.06, 0.06 ± 0.04, and 0.16 ± 0.12, respectively. The study observed that sheep walking through a passage exhibited a more curved knee posture compared to normal measurements, often with a lowered head. This research presents a cost-effective data collection scheme for studying multiple postures in animal husbandry.

Purpose: Increased incidence of anterior cruciate ligament injuries has amplified the need for quantitative research in clinical and academic settings. We used a novel digital arthrometer to measure knee laxity in healthy people and patients with anterior cruciate ligament injuries. Changes in stiffness were also assessed to develop new indicators for detecting anterior cruciate ligament injury. The purpose of this study was to use arthrometer to measure the quantitative indicator of knee laxity, bringing clinicians a new perspective on how to identify injury to the ACL.Methods: In this cross-sectional study, anterior tibial displacement under continuous loading was measured using a novel digital arthrometer in 30 patients with unilateral anterior cruciate ligament injury and 30 healthy controls. Load-displacement curves were plotted, using real-time load and displacement changes. Stiffness was defined by the slope of the applied load to tibial displacement. Anterior tibial displacement and instantaneous stiffness values under different loads were compared. The restricting contribution of the anterior cruciate ligament transformed the displacement-stiffness curve from a sharp decrease to a stable increase, resulting in a minimum stiffness value. Using the minimum stiffness as the turning point, the load-displacement curve was divided into regions 1 and 2. The two regions’ stiffness changes were compared. Based on the findings, receiver operating characteristic curves were plotted and the area under the curve was calculated to estimate the diagnostic accuracy.Results: Anterior tibial displacement was significantly greater in the anterior cruciate ligament injury group than in the controls under each 10-N increase load (p < 0.05). In the anterior cruciate ligament injury group, instantaneous stiffness was significantly lower on the injured side than on the healthy side (p < 0.05). In the two regions of the load-displacement curve, stiffness was significantly lower in the anterior cruciate ligament injury group than in the control group (all, p < 0.05). Receiver operating characteristic curves were plotted, using changes in stiffness under the two regions in both groups. Stiffness in region 2 had the largest area under the curve (0.94; 95% CI, 0.88–0.99). Using the cut-off value of 9.62 N/mm to detect ACL injury, the sensitivity and specificity were 93% and 82%, respectively.Conclusion: Our investigation of ligament stiffness provides novel insights into the properties of knee laxity. Stiffness in the later stages of increased loading

Forest gaps play an important role during forest succession in temperate forest ecosystems. However, the differences in spatial distribution and replacement patterns of woody plants (trees and shrubs) between primary and secondary forests remain unclear during the gap-filling processes, especially for temperate forests in Northeast China. We recorded 45,619 regenerated trees and shrubs in young gaps (10 m) dimensions were quantified by shade tolerance groups of trees and shrubs. We found that gap age, competition between species, and pre-existing regeneration status resulted in different species replacement patterns within gaps in primary vs. secondary forests. Gap formation in both primary and secondary forests increased species richness, with 33, 38, 39, and 41 in the primary closed stands, primary forest gaps, secondary closed stands, and secondary forest gaps, respectively. However, only 35.9% of species in primary forest gaps and 34.1% in secondary forest gaps successfully reached the upper layer. Based on the importance values (IVs) of tree species across different canopy heights, light-demanding trees in the upper layer of the secondary forests were gradually replaced by intermediate and shade-tolerant trees. In the primary forests, Korean pine exhibited intermittent growth patterns at different canopy heights, while it had continuous regeneration along vertical height gradients in the secondary forests. The differences in Korean pine regeneration between the primary and secondary forests existed before gap formation and continued during the gap-filling processes. The interspecific competition among different tree species gradually decreased with increasing vertical height, and compared to the primary forests, the secondary forests showed an earlier occurrence of competition exclusion within gaps. Our findings revealed the species replacement patterns within gaps and provided a further understanding of the competition dynamics among tree species during the gap-filling processes.

Objective: The tumor microenvironment plays a critical role in the radiotherapy and immunotherapy response of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Radioresistance is a key factor in treatment failure among patients who receive radical radiotherapy. Thus, new immune-related biomarkers associated with radiotherapy response in CESC are needed.Methods: In this study, the CIBERSORT and ESTIMATE methods were applied to determine the percentage of tumor-infiltrating cells and the number of immune components in 103 CESCs treated with radiotherapy from The Cancer Genome Atlas (TCGA) database. The main dysregulated genes were subjected to multivariate and univariate analyses. The prognostic value of this system was studied via receiver operating characteristic curve and survival analysis. For further confirmation, the biomarkers’ expression levels and predictive value were validated by immunohistochemistry (IHC) and qRT-PCR. The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in cervical cancer patients treated with radiation therapy.Results: Data for 17 radioresistant and 86 radiosensitive tumors were obtained from the The Cancer Genome Atlas database. 53 immune-related DEGs were identified. GO and KEGG analyses revealed that the DEGs were enriched in protein kinase B signaling, growth factors in cytokines, the MAPK pathway and the PI3K-Akt pathway. Then, 14 key immune-related genes built a risk scoring model were deemed prognostic in CESC with radiotherapy. The area under the curve (AUC) of the model was 0.723, and the high-risk group presented worse outcomes than the low-risk group. In addition, the high-risk group tended to have persistent tumors (p = 0.001). The high expression of WT1 and SPOUYT4 were associated with relapse, the high expression of Angiotensinogen and MIEN1 were associated with nonrelapse. Analysis of the immune microenvironment indicated that M0 macrophages, M2 macrophages, activated mast cells and resting memory CD4+ T cells were positively correlated with the risk score (p < 0.05).Conclusion: The novel immune-related risk scoring system has some advantages in predicting the prognosis and treatment response of cervical cancer patients treated with radiotherapy. Moreover, it might provide novel clues for providing targeted immune therapy to these patients.

Objective: Ankle braces can affect the kinematics of the ankle joint during landing tasks. Previous studies were primarily relied on traditional marker-based motion capture systems, which pose limitations in non-invasively capturing the motion of the talus bone. The effect of ankle braces on the in vivo kinematics of the tibiotalar and subtalar joints during landing remains unknown. This study used a high-speed dual fluoroscopic imaging system (DFIS) and magnetic resonance imaging (MRI) to investigate effect of ankle braces on the in vivo kinematics of the tibiotalar and subtalar joints during landing.Methods: Fourteen healthy participants were recruited for this study. During the experiment, static three-dimensional MRI data were collected for each participant, and 3D ankle joint models for the calcaneus, talus, and tibia were constructed. The DFIS was used to capture the images of each participant performing a single-leg landing-jump task at a height of 40 cm. The images were captured once with and without a brace in the fatigue condition, which was induced by running. The six-degree-of-freedom (6DOF) kinematic data were obtained by 2D-3D registration.Results: The flexion-extension range of motion (ROM) (42.73 ± 4.76° vs. 38.74 ± 5.43°, p = 0.049) and anterior-posterior translation ROM (16.86 ± 1.74 mm vs. 15.03 ± 1.73 mm, p = 0.009) of the tibiotalar joint were decreased. The maximum inversion angle (−3.71 ± 2.25° vs. 2.11 ± 1.83°, p = 0.047) of the subtalar joint was decreased.Conclusion: The ankle brace limited the flexion-extension ROM of the tibiotalar joints and the inversion angle of the subtalar joint during landing.

Abstract Background Measurement of knee laxity after anterior cruciate ligament (ACL) injury is crucial for appropriate treatment and rehabilitation decision-making. This study examined the potential of a new digital arthrometer (Ligs, Innomotion, Shanghai, China) to quantify anterior tibial translation (ATT) in patients with ACL injuries and in healthy subjects. Methods A total of 60 participants included 30 subjects with single-leg ACL injuries and 30 healthy subjects included as controls. The lower leg was immobilized. The thruster is positioned posterior to the lower leg and parallel to the tibial tuberosity in the sagittal plane. The load is applied vertically to the tibia under a dynamic load of 0–150 N, with continuous displacement recorded. The intrarater and interrater reliability will be examined. ATT and side-to-side differences (SSD) between the control and ACL injury groups were compared. Receiver operating characteristic (ROC) curves were analyzed, and the area under the curve (AUC) was calculated to determine the diagnostic accuracy of the Ligs. Results The interrater ICC was 0.909 and the intrarater ICC was 0.943. Significant differences in the SSD were observed between the control and ACL injury groups (for all P

Abstract Background Numerous clinical trials have been initiated to find effective treatments for COVID-19. These trials have often been initiated in regions where the pandemic has already peaked. Consequently, achieving full enrollment in a single trial might require additional COVID-19 surges in the same location over several years. This has inspired us to pool individual patient data (IPD) from ongoing, paused, prematurely-terminated, or completed randomized controlled trials (RCTs) in real-time, to find an effective treatment as quickly as possible in light of the pandemic crisis. However, pooling across trials introduces enormous uncertainties in study design (e.g., the number of RCTs and sample sizes might be unknown in advance). We sought to develop a versatile treatment efficacy assessment model that accounts for these uncertainties while allowing for continuous monitoring throughout the study using Bayesian monitoring techniques. Methods We provide a detailed look at the challenges and solutions for model development, describing the process that used extensive simulations to enable us to finalize the analysis plan. This includes establishing prior distribution assumptions, assessing and improving model convergence under different study composition scenarios, and assessing whether we can extend the model to accommodate multi-site RCTs and evaluate heterogeneous treatment effects. In addition, we recognized that we would need to assess our model for goodness-of-fit, so we explored an approach that used posterior predictive checking. Lastly, given the urgency of the research in the context of evolving pandemic, we were committed to frequent monitoring of the data to assess efficacy, and we set Bayesian monitoring rules calibrated for type 1 error rate and power. Results The primary outcome is an 11-point ordinal scale. We present the operating characteristics of the proposed cumulative proportional odds model for estimating treatment effectiveness. The model can estimate the treatment’s effect under enormous uncertainties in study design. We investigate to what degree the proportional odds assumption has to be violated to render the model inaccurate. We demonstrate the flexibility of a Bayesian monitoring approach by performing frequent interim analyses without increasing the probability of erroneous conclusions. Conclusion This paper describes a translatable framework using simulation to support the design of prospective IPD meta-analyses.

Abstract Diabetes Mellitus can cause dental pulp cells apoptosis by oxidative stress, and affect the integrity and function of dental pulp tissue. Mitochondria are the main attack targets of oxidative stress and have a critical role in apoptosis. However, whether mitochondria are involved in dental pulp damage caused by diabetes mellitus remains unclear. This study aimed to investigate the role of mitochondria in the apoptosis of odontoblast-like cell line (mDPC6T) induced by glucose oxidative stress, and to explore its possible mechanism. We established an oxidative stress model in vitro using glucose oxidase/glucose to simulate the pathological state under diabetic conditions. We found that the opening of mitochondrial permeability transition pore (mPTP) contributed to the apoptosis of mDPC6T treated with glucose oxidase, as evidenced by enhanced mitochondrial reactive oxygen species (mtROS) and intracellular Ca2+ disorder, significantly reduced mitochondrial membrane potential (MMP) and ATP production. Antioxidant N-acetylcysteine (NAC) or Cyclosporine A (mPTP inhibitor) blocked the mPTP opening, which significantly attenuated mitochondrial dysfunction and apoptosis induced by glucose oxidative stress. In addition, we found that glucose oxidative stress stimulated mPTP opening may through inhibition of Akt-GSK3β pathway. This study provides a new insight into the mitochondrial mechanism underlying diabetes-associated odontoblast-like cell apoptosis, laying a foundation for the prevention and treatment of diabetes-associated pulp injury.

Objective: Traditional knee braces unloading forces primarily from a single compartment are insufficient for patients with knee injuries or knee osteoarthritis (KOA) involving multiple compartments. We investigated how knee kinematics were altered by an overall unloading brace (OUB) designed to unload both the medial and lateral tibiofemoral (TF) compartments simultaneously during dynamic movement. Methods: Gait analysis was performed on 32 adults with normal knee alignment and no history of knee disease. Three-dimensional (3D) knee kinematic data collected during treadmill walking (3 km/h) and jogging (5 km/h) with an optical motion capture system were compared with versus without the OUB. Results: In the stance phase, wearing the OUB, versus not wearing it, increased the proximal-distal translational range of motion (ROM) of the knee by 4.04 mm (Effect size, ES = 0.97) during walking and by 3.43 mm (ES = 0.97) during jogging, decreased abduction-adduction rotational ROM by 3.09°(ES = 1.05) during walking and by 2.88°(ES = 1.50) during jogging, and decreased internal-external rotation by 2.14°(ES = 0.81) during walking and by 4.66°(ES = 1.61) during jogging. In the swing phase, the OUB increased proximal-distal translational ROM by 12.64 mm (ES = 1.31) during walking and by 9.23 mm (ES = 0.92) during jogging, decreased abduction-adduction rotational ROM by 2.83°(ES = 0.54) during walking and by 3.37°(ES = 0.67) during jogging, and decreased internal-external rotational ROM by 2.71°(ES = 0.68) during jogging. Conclusions: OUB use increased proximal-distal translation while reducing abduction-adduction rotation. This effect may increase the joint gap of the tibiofemoral joint, thereby reducing joint stress, and may contribute to disease rehabilitation in the knee of clinical orthopedics, rehabilitation, and sports medicine fields. However, additional studies are needed to assess the range of possible clinical and prophylactic benefits of OUB.

Bone tissue engineering (BTE) is a promising approach for repairing and regenerating damaged bone tissue, using stem cells and scaffold structures. Among various stem cell sources, dental pulp stem cells (DPSCs) have emerged as a potential candidate due to their multipotential capabilities, ability to undergo osteogenic differentiation, low immunogenicity, and ease of isolation. This article reviews the biological characteristics of DPSCs, their potential for BTE, and the underlying transcription factors and signaling pathways involved in osteogenic differentiation; it also highlights the application of DPSCs in inducing scaffold tissues for bone regeneration and summarizes animal and clinical studies conducted in this field. This review demonstrates the potential of DPSC-based BTE for effective bone repair and regeneration, with implications for clinical translation.

Abstract To validate the accuracy of Cone beam computed tomography (CBCT) cervical spine modeling with three dimensional (3D)-3D registration for in vivo measurements of cervical spine kinematics. CBCT model accuracy was validated by superimposition with computed tomography (CT) models in 10 healthy young adults, and then cervical vertebrae were registered in six end positions of functional movements, versus a neutral position, in 5 healthy young adults. Registration errors and six degrees of freedom (6-DOF) kinematics were calculated and reported. Relative to CT models, mean deviations of the CBCT models were

In this paper the possibility of development of the recursive digital filter using a P-spline is considered. The frequency and time response of the spline filter for real-time data are analytically obtained and investigated. The influence of the P-spline parameters on effectiveness of interpretation is explored with input metrical data. The patterns obtained during spline filter frequency analysis are confirmed by an example of Doppler function restoration.

We here reported the 1H/13C chemical shifts, binding affinity and binding free energy of 1,4-pregnadiene-11β,17α,21-triol-3,20-dione (Prednisolone; Prd) interacting with metal cations. Six different Prd/Ni or Co mixtures were examined at different molar ratios (1:0, 1:0.1, 1:0.2, 1:0.3, 1:0.4 and 1:0.5). In this analysis, the 1H and 13C chemical shifts were measured for the Prd/cation mixtures using a Bruker AV 500 MHz spectrometer (Bruker BioSpin GmbH, Rheinstetten, Germany), equipped with a 5 mm z-gradient Prodigy BBO 500 MHz probehead at 298 K, and simulation of the 1H spectra were determined from the Daisy software package (Bruker BioSpin GmbH). Binding affinity and free energy values were deduced from the 13C NMR peak intensities involved in the cation interaction, for more insight on the steroid/cation interactions please see Magnesium and Calcium Reveal Different Chelating Effects in a Steroid Compound: A Model Study of Prednisolone Using NMR Spectroscopy [1]. Keywords: Prednisolone, Nuclear magnetic resonance, Cation binding, Binding affinity

For decades, high-resolution 1H NMR spectroscopy has been routinely utilized to analyze both naturally occurring steroid hormones and synthetic steroids, which play important roles in regulating physiological functions in humans. Because the 1H signals are inevitably superimposed and entangled with various JH–H splitting patterns, such that the individual 1H chemical shift and associated JH–H coupling identities are hardly resolved. Given this, applications of thess information for elucidating steroidal molecular structures and steroid/ligand interactions at the atomic level were largely restricted. To overcome, we devoted to unraveling the entangled JH–H splitting patterns of two similar steroidal compounds having fully unsaturated protons, i.e., androstanolone and epiandrosterone (denoted as 1 and 2, respectively), in which only hydroxyl and ketone substituents attached to C3 and C17 were interchanged. Here we demonstrated that the JH–H values deduced from 1 and 2 are universal and applicable to other steroids, such as testosterone, 3β, 21-dihydroxygregna-5-en-20-one, prednisolone, and estradiol. On the other hand, the 1H chemical shifts may deviate substantially from sample to sample. In this communication, we propose a simple but novel scheme for resolving the complicate JH–H splitting patterns and 1H chemical shifts, aiming for steroidal structure determinations.

The authors wish to revise the affiliation, due to the errors regarding affiliation in this published paper [...]

Intelligent responsive materials have become one of the most exciting fields in the research of new materials in the past few decades due to their practical and potential applications in aerospace, biomedicine, textile, electronics, and other relative fields. Here, a novel thermal-responsive biomimetic shape memory wood composite is fabricated utilizing polycaprolactone-based (PCL) shape-memory polymer to modify treated-wood. The shape memory wood inherits visual characteristics and the unique three-dimension structure of natural wood that endows the shape memory wood (SMW) with outstanding tensile strength (10.68 MPa) at room temperature. In terms of shape memory performance, the shape recovery ratio is affected by multiple factors including environment temperature, first figuration angle, cycle times, and shows different variation tendency, respectively. Compared with shape recovery ratio, the shape fixity ratio (96%) is relatively high and stable. This study supplies more possibilities for the functional applications of wood, such as biomimetic architecture, self-healing wood veneering, and intelligent furniture.

Marine algal toxins, highly toxic secondary metabolites, have significant influences on coastal ecosystem health and mariculture safety. The occurrence and environmental control factors of lipophilic marine algal toxins (LMATs) in the surface seawater of the Changjiang estuary (CJE) and the adjacent East China Sea (ECS) were investigated. Pectenotoxin-2 (PTX2), okadaic acid (OA), dinophysistoxin-1(DTX1), and gymnodimine (GYM) were detected in the CJE surface seawater in summer, with concentration ranges of not detected (ND)−105.54 ng/L, ND−13.24 ng/L, ND−5.48 ng/L, and ND−12.95 ng/L, respectively. DTX1 (ND−316.15 ng/L), OA (ND−16.13 ng/L), and PTX2 (ND−4.97 ng/L) were detected in the ECS during spring. LMATs formed a unique low-concentration band in the Changjiang diluted water (CJDW) coverage area in the typical large river estuary. PTX2, OA, and DTX1 in seawater were mainly derived from Dinophysis caudate and Dinophysis rotundata, while GYM was suspected to be from Karenia selliformis. Correlation analyses showed that LMAT levels in seawater were positively correlated with dissolved oxygen and salinity, but negatively correlated with temperature and nutrients, indicating that the hydrological condition and nutritional status of seawater and climatic factors exert significant effects on the distribution of LMATs.

Magnesium-cemented poplar particleboard (MCPB) is a new environmental inorganic magnesium cementitious composite without formaldehyde release. In this study, soybean flour (SM), silane coupling agent (KH560), soybean protein isolate (SPI), polyethylene glycol (PEG-400), maleic anhydride (MAH), and polyacrylic acid (PAA) were added to MCPB to improve the mechanical properties, waterproofing properties, and flame retardancy. The results show that the SPI group had the best mechanical performance; the modulus of elasticity (MOE) was up to 5192 MPa and exceeded the Chinese national standard GBT 4897-2015 (GBT) by 67.4%, the modulus of rupture (MOR) reached 17.72 MPa and exceeded GBT by 18%. Thickness swelling (TS) after 24-hour immersion was 0.29% and reached the standard of GBT (≤16%). The fire resistance test of MCPB indicated that the KH560 group improved the flame retardancy, the heat release rate (HRR) was 18kW/m2, the total smoke produced (TSP) was 0.192 m2, the total heat release (THR) was 29.71 MJ/kg, which reached the Chinese national standard GBT 8624-2012.

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.