Hydrogel microspheres for bone regeneration through regulation of the regenerative microenvironment.

Bone defects are a prevalent category of skeletal tissue disorders in clinical practice, with a range of pathogenic factors and frequently suboptimal clinical treatment effects. In bone regeneration of bone defects, the bone regeneration microenvironment-composed of physiological, chemical, and physical components-is the core element that dynamically coordinates to promote bone regeneration. In recent years, medical biomaterials with bioactivity and functional tunability have been widely researched upon and applied in the fields of tissue replacement/regeneration, and remodelling of organ structure and function.

3D-printed bone regeneration scaffolds modulate bone metabolic homeostasis through vascularization for osteoporotic bone defects.

The treatment of osteoporotic bone defects poses a challenge due to the degradation of the skeletal vascular system and the disruption of local bone metabolism within the osteoporotic microenvironment. However, it is feasible to modulate the disrupted local bone metabolism imbalance through enhanced vascularization, a theory termed "vascularization-bone metabolic balance". This study developed a 3D-printed polycaprolactone (PCL) scaffold modified with EPLQLKM and SVVYGLR peptides (PCL-SE).

Cu/SiO synthesized with HKUST-1 as precursor: high ratio of Cu/(Cu + Cu) and rich oxygen defects for efficient catalytic hydrogenation of furfural to 2-methyl furan.

Cu/SiO is one of the most promising catalysts for the furfural (FF) hydrogenation reaction but suffers from the difficulty of tailoring the microstructure and surface properties. Herein, we developed a MOF-derived Cu/SiO catalyst (Cu/SiO-MOF) for FF hydrogenation to 2-methyl furan (2-MF). In comparison with Cu/SiO catalysts prepared from ammonia evaporation (Cu/SiO-AE) and traditional impregnation (Cu/SiO-TI), the copper species in Cu/SiO-MOF could not only be anchored on the silica surface forming Cu-O-Si bonds but also exposed many more active sites.

Surface-sealing encapsulation of phosphotungstic acid in microporous UiO-66 as a bifunctional catalyst for transfer hydrogenation of levulinic acid to γ-valerolactone.

The efficient production of γ-valerolactone (GVL) from renewable lignocellulose that is synthesized in plants by photosynthesis to replace the declining fossil resources conforms to the principles of circular economy. Compared to direct hydrogenation by H molecules, catalytic transfer hydrogenation (CTH) of levulinic acid (LA) and/or its esters to GVL with organic alcohols as a hydrogen source is a much milder route. The synergistic catalysis between Lewis and Brønsted acids is indispensable in the CTH process.

CGAN-rIRN: a data-augmented deep learning approach to accurate classification of mental tasks for a fNIRS-based brain-computer interface.

Functional near-infrared spectroscopy (fNIRS) is increasingly used to investigate different mental tasks for brain-computer interface (BCI) control due to its excellent environmental and motion robustness. Feature extraction and classification strategy for fNIRS signal are essential to enhance the classification accuracy of voluntarily controlled BCI systems. The limitation of traditional machine learning classifiers (MLCs) lies in manual feature engineering, which is considered as one of the drawbacks that reduce accuracy.

Combining robust level extraction and unsupervised adaptive classification for high-accuracy fNIRS-BCI: An evidence on single-trial differentiation between mentally arithmetic- and singing-tasks.

Functional near-infrared spectroscopy (fNIRS) is a safe and non-invasive optical imaging technique that is being increasingly used in brain-computer interfaces (BCIs) to recognize mental tasks. Unlike electroencephalography (EEG) which directly measures neural activation, fNIRS signals reflect neurovascular-coupling inducing hemodynamic response that can be slow in time and varying in the pattern. The established classifiers extend the EEG-ones by mostly employing the feature based supervised models such as the support vector machine (SVM) and linear discriminant analysis (LDA), and fail to timely characterize the level-sensitive hemodynamic pattern.

Deep-learning informed Kalman filtering for priori-free and real-time hemodynamics extraction in functional near-infrared spectroscopy.

Separation of the physiological interferences and the neural hemodynamics has been a vitally important task in the realistic implementation of functional near-infrared spectroscopy (fNIRS). Although many efforts have been devoted, the established solutions to this issue additionally rely on priori information on the interferences and activation responses, such as time-frequency characteristics and spatial patterns, etc., also hindering the realization of real-time.

Suppressing physiological interferences and physical noises in functional diffuse optical tomography via tandem inversion filtering and LSTM classification.

For performance enhancement of functional diffuse optical tomography (fDOT), we propose a tandem method that takes advantage of the inversion filtering and the long short term memory (LSTM) classification to simultaneously suppress the physiological interferences and physical noises in fDOT. In the former phase, the absorption perturbation maps over the scalp-skull (SS) and cerebral-cortex (CC) layers are firstly pre-reconstructed using a two-layer topography scheme. Then, the recovered SS-map is inversed into measurement space by the forward calculation to estimate the intensity changes associated with the physiological interferences.

Effect of Metformin on Fibroblast Growth Factor-21 Levels in Patients with Newly Diagnosed Type 2 Diabetes.

Background: Fibroblast growth factor (FGF)-21 is an important regulator of glucose metabolism. In the present study, we investigated whether plasma levels of FGF-21 changed in patients with newly diagnosed type 2 diabetes mellitus (T2DM) and assessed the effects of metformin treatment on plasma FGF-21 levels.

Materials And Methods: The plasma FGF-21 levels and the metabolic parameters of 226 patients with newly diagnosed T2DM and 100 sex- and age-matched normal glycemic tolerant (NGT) controls were measured.

Molecular analysis of Chinese truffles resembling Tuber californicum in morphology reveals a rich pattern of species diversity with emphasis on four new species.

In China the species name Tuber californicum is assigned to pale truffles in the genus Tuber that have more or less regularly globose ascospores; however, we recently discovered that the name was misapplied to some specimens collected in China. In the present study we re-examined all available Chinese collections purported to be T. californicum, including herbarium specimens and newly collected materials, with morphological and molecular methods.

Phylogenetic analyses of Chinese Tuber species that resemble T. borchii reveal the existence of the new species T. hubeiense and T. wumengense.

In phylogenetic analyses based on the internal transcribed spacers and 28S nuc rDNA and translation elongation factor 1-α to compare Chinese white truffle specimens that have ascomata resembling the European Tuber borchii, the sequences of Chinese species resembling T. borchii in morphology grouped into seven distinct clusters among three clades: Puberulum, Maculatum and Latisporum No sequences from these Chinese species matched those of the European T. borchii and the occurrence of the European T.

High prevalence of vitamin D deficiency in urban health checkup population.

Background: Vitamin D deficiency is documented as a common health problem in the world. Limited data has been found on the prevalence of vitamin D deficiency in Beijing area.

Aim: To investigate the prevalence s of vitamin D deficiency in urban Beijing residents and the seasonal and monthly serum 25(OH)D variation in this population.

Influence of islet function on typing and prognosis of new-onset diabetes after intensive insulin therapy.

Background: It is difficult in clinical practice to differentiate patients with newly diagnosed diabetes and ketosis. The aim of this study was to investigate the effect of intensive insulin therapy on islet function in patients with new-onset diabetes and concomitant ketosis, and to determine the value of alternation in islet function in the typing of diabetes.

Material/methods: A total of 206 inpatients with new-onset diabetes and ketosis were recruited after intensive insulin therapy and followed for 36 months.

[The classification and prognostic implication of islet β cell function before and in remission period in newly diagnosed diabetic patients with ketosis].

Objective: To observe β cell function in newly diagnosed diabetic patients with ketosis before and in remission period and evaluate its classification and predictive value.

Methods: A total of 206 patients newly diagnosed as diabetic ketosis who had been treated with intensive insulin therapy in our hospital and entered in the "honeymoon" after the withdraw of insulin therapy were followed for 36 months from onset of diabetes. They were divided into two groups of type 1 and type 2 diabetes (group A and B), according to the dependence or independence on insulin treatment.