TNF-α promotes osteocyte necroptosis by upregulating TLR4 in postmenopausal osteoporosis

Postmenopausal osteoporosis (PMOP) is a common kind of osteoporosis that is associated with excessive osteocyte death and bone loss. Previous studies have shown that TNF-α-induced osteocyte necroptosis might exert a stronger effect on PMOP than apoptosis, and TLR4 can also induce cell necroptosis, as confirmed by recent studies. However, little is known about the relationship between TNF-α-induced osteocyte necroptosis and TLR4. In the present study, we showed that TNF-α increased the expression of TLR4, which promoted osteocyte necroptosis in PMOP. In patients with PMOP, TLR4 was highly expressed at skeletal sites where exists osteocyte necroptosis, and high TLR4 expression is correlated with enhanced TNF-α expression. Osteocytes exhibited robust TLR4 expression upon exposure to necroptotic osteocytes in vivo and in vitro. Western blotting and immunofluorescence analyses demonstrated that TNF-α upregulated TLR4 expression in vitro, which might further promote osteocyte necroptosis. Furthermore, inhibition of TLR4 by TAK-242 in vitro effectively blocked osteocyte necroptosis induced by TNF-α. Collectively, these results suggest a novel TLR4-mediated process of osteocyte necroptosis, which might increase osteocyte death and bone loss in the process of PMOP.

Multiscale architecture design of 3D printed biodegradable Zn-based porous scaffolds for immunomodulatory osteogenesis

Reconciling the dilemma between rapid degradation and overdose toxicity is challenging in biodegradable materials when shifting from bulk to porous materials. Here, we achieve significant bone ingrowth into Zn-based porous scaffolds with 90% porosity via osteoinmunomodulation. At microscale, an alloy incorporating 0.8 wt% Li is employed to create a eutectoid lamellar structure featuring the LiZn4 and Zn phases. This microstructure optimally balances high strength with immunomodulation effects. At mesoscale, surface pattern with nanoscale roughness facilitates filopodia formation and macrophage spreading. At macroscale, the isotropic minimal surface G unit exhibits a proper degradation rate with more uniform feature compared to the anisotropic BCC unit. In vivo, the G scaffold demonstrates a heightened efficiency in promoting macrophage polarization toward an anti-inflammatory phenotype, subsequently leading to significantly elevated osteogenic markers, increased collagen deposition, and enhanced new bone formation. In vitro, transcriptomic analysis reveals the activation of JAK/STAT pathways in macrophages via up regulating the expression of Il-4, Il-10, subsequently promoting osteogenesis.

Fabrication of multifunctional ethyl cellulose/gelatin-based composite nanofilm for the pork preservation and freshness monitoring

In this study, an active and intelligent nanofilm for monitoring and maintaining the freshness of pork was developed using ethyl cellulose/gelatin matrix through electrospinning, with the addition of natural purple sweet potato anthocyanin. The nanofilm exhibited discernible color variations in response to pH changes, and it demonstrated a higher sensitivity towards volatile ammonia compared with casting film. Notably, the experimental findings regarding the wettability and pH response performance indicated that the water contact angle between 70° and 85° was more favorable for the smart response of pH sensitivity. Furthermore, the film exhibited desirable antioxidant activities, water vapor barrier properties and also good antimicrobial activities with the incorporation of ε-polylysine, suggesting the potential as a food packaging film. Furthermore, the application preservation outcomes revealed that the pork packed with the nanofilm can prolong shelf life to 6 days, more importantly, a distinct color change aligned closely with the points indicating the deterioration of the pork was observed, changing from light pink (indicating freshness) to light brown (indicating secondary freshness) and then to brownish green (indicating spoilage). Hence, the application of this multifunctional film in intelligent packaging holds great potential for both real-time indication and efficient preservation of the freshness of animal-derived food items.

Chinese family care partners of older adults in Canada have grit: A qualitative study

AIM

To explain the process taken by Chinese family care partners of older adults in the Greater Toronto Area, Canada, to access health and social services in their communities. The research question was: What mechanisms and structures impact the agency of Chinese family care partners of older adults, in the process of assisting them to access health and social services?

DESIGN

This qualitative study was informed by critical realism.

METHODS

Chinese family care partners of older adults in the Greater Toronto Area, Canada, were interviewed from August 2020 to June 2021. Transcripts underwent thematic analysis.

FINDINGS

Twenty-eight Chinese family care partners expressed a firm commitment to maintain caregiving conditions and to judiciously access health and social services. Their commitment was made up of three parts: (a) legislative and cultural norms of family, work, and society; (b) their perseverance to fill gaps with limited social and financial resources; (c) the quality of their relationship to, and illness trajectory of the older adults. The social structures created tension in how Chinese family care partners made decisions, negotiated resources, and ultimately monitored and coordinated timely access with older adults.

CONCLUSION

Participants' commitment and perseverance were conceptualized as "grit," central to their agency to conform to legislative and cultural norms. Moreover, findings support grit's power to motivate and sustain family caregiving, in order for older adults to age in place as long as possible with finite resources.

IMPLICATIONS FOR THE PROFESSION

This study highlights the importance of cultural awareness education for nurses, enabling continuity of care at a systems level and for a more resilient healthcare system.

IMPACT

Family care partners' grit may be crucial for nurses to harness when together, they face limited access to culturally appropriate health and social services in a system grounded in values of equity and inclusion, as in Canada.

REPORTING METHOD

When writing this manuscript, we adhered to relevant EQUATOR guidelines of the Consolidated Criteria for Reporting Qualitative Research (COREQ).

PATIENT OR PUBLIC INVOLVEMENT AND ENGAGEMENT

No patient or public involvement.

The potential mechanism of ursolic acid in the treatment of bladder cancer based on network pharmacology and molecular docking

OBJECTIVE

This study explored the potential molecular mechanisms of ursolic acid (UA) in bladder cancer treatment using network pharmacology and molecular docking.

METHODS

The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were used to screen potential targets of UA. Relevant bladder cancer target genes were extracted using the GeneCards database. All data were pooled and intercrossed to obtain common target genes of UA and bladder cancer. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. Molecular docking was conducted to verify the possible binding conformation between UA and bladder cancer cells. Then, in vitro experiments were performed to further validate the predicted results.

RESULTS

UA exerts anti-tumor effects on bladder cancer through multiple targets and pathways. Molecular docking indicated that UA undergoes stable binding with the proteins encoded by the top six core genes (STAT3, VEGFA, CASP3, TP53, IL1B, and CCND1). The in vitro experiments verified that UA can induce bladder cancer cell apoptosis by regulating the PI3K/Akt signaling pathway.

CONCLUSIONS

Our study illustrated the potential mechanism of UA in bladder cancer based on network pharmacology and molecular docking. The results will provide scientific references for follow-up studies and clinical treatment.

A Colorimetric Nanofiber Film Based on Ethyl Cellulose/Gelatin/Purple Sweet Potato Anthocyanins for Monitoring Pork Freshness

In this study, colorimetric indicator nanofiber films based on ethyl cellulose (EC)/gelatin (G) incorporating purple sweet potato anthocyanins (PSPAs) were designed via electrospinning technology for monitoring and maintaining the freshness of pork. The film presented good structural integrity and stability in a humid environment with water vapor permeability (WVP) of 6.07 ± 0.14 × 10-11 g·m-1s-1Pa-1 and water contact angle (WCA) of 81.62 ± 1.43°. When PSPAs were added into the nanofiber films, the antioxidant capacity was significantly improved (p < 0.05) with a DPPH radical scavenging rate of 68.61 ± 1.80%. The nanofiber films showed distinguishable color changes as pH changes and was highly sensitive to volatile ammonia than that of casting films. In the application test, the film color changed from light pink (fresh stage) to light brown (secondary freshness stage) and then to brownish green (spoilage stage), indicating that the nanofiber films can be used to detect the real-time freshness of pork during storage. Meanwhile, it could prolong the shelf life of pork by inhibiting the oxidation degree. Hence, these results suggested that the EC/G/PSPA film has promising future for monitoring freshness and extending shelf life of pork.

An automatic method using MFCC features for sleep stage classification

Sleep stage classification is a necessary step for diagnosing sleep disorders. Generally, experts use traditional methods based on every 30 seconds (s) of the biological signals, such as electrooculograms (EOGs), electrocardiograms (ECGs), electromyograms (EMGs), and electroencephalograms (EEGs), to classify sleep stages. Recently, various state-of-the-art approaches based on a deep learning model have been demonstrated to have efficient and accurate outcomes in sleep stage classification. In this paper, a novel deep convolutional neural network (CNN) combined with a long short-time memory (LSTM) model is proposed for sleep scoring tasks. A key frequency domain feature named Mel-frequency Cepstral Coefficient (MFCC) is extracted from EEG and EMG signals. The proposed method can learn features from frequency domains on different bio-signal channels. It firstly extracts the MFCC features from multi-channel signals, and then inputs them to several convolutional layers and an LSTM layer. Secondly, the learned representations are fed to a fully connected layer and a softmax classifier for sleep stage classification. The experiments are conducted on two widely used sleep datasets, Sleep Heart Health Study (SHHS) and Vincent's University Hospital/University College Dublin Sleep Apnoea (UCDDB) to test the effectiveness of the method. The results of this study indicate that the model can perform well in the classification of sleep stages using the features of the 2-dimensional (2D) MFCC feature. The advantage of using the feature is that it can be used to input a two-dimensional data stream, which can be used to retain information about each sleep stage. Using 2D data streams can reduce the time it takes to retrieve the data from the one-dimensional stream. Another advantage of this method is that it eliminates the need for deep layers, which can help improve the performance of the model. For instance, by reducing the number of layers, our seven layers of the model structure takes around 400 s to train and test 100 subjects in the SHHS1 dataset. Its best accuracy and Cohen's kappa are 82.35% and 0.75 for the SHHS dataset, and 73.07% and 0.63 for the UCDDB dataset, respectively.

In vitro and in vivo studies on biodegradable Zn porous scaffolds with a drug-loaded coating for the treatment of infected bone defect

Additively manufactured biodegradable zinc (Zn) scaffolds have great potential to repair infected bone defects due to their osteogenic and antibacterial properties. However, the enhancement of antibacterial properties depends on a high concentration of dissolved Zn2+, which in return deteriorates osteogenic activity. In this study, a vancomycin (Van)-loaded polydopamine (PDA) coating was prepared on pure Zn porous scaffolds to solve the above dilemma. Compared with pure Zn scaffolds according to comprehensive in vitro tests, the PDA coating resulted in a slow degradation and inhibited the excessive release of Zn2+ at the early stage, thus improving cytocompatibility and osteogenic activity. Meanwhile, the addition of Van drug substantially suppressed the attachment and proliferation of S. aureus and E. coli bacterial. Furthermore, in vivo implantation confirmed the simultaneously improved osteogenic and antibacterial functions by using the pure Zn scaffolds with Van-loaded PDA coating. Therefore, it is promising to employ biodegradable Zn porous scaffolds with the proposed drug-loaded coating for the treatment of infected bone defects.

High temperature oxidation treated 3D printed anatomical WE43 alloy scaffolds for repairing periarticular bone defects: In vitro and in vivo studies

Reconstruction of subarticular bone defects is an intractable challenge in orthopedics. The simultaneous repair of cancellous defects, fractures, and cartilage damage is an ideal surgical outcome. 3D printed porous anatomical WE43 (magnesium with 4 wt% yttrium and 3 wt% rare earths) scaffolds have many advantages for repairing such bone defects, including good biocompatibility, appropriate mechanical strength, customizable shape and structure, and biodegradability. In a previous investigation, we successfully enhanced the corrosion resistance of WE43 samples via high temperature oxidation (HTO). In the present study, we explored the feasibility and effectiveness of HTO-treated 3D printed porous anatomical WE43 scaffolds for repairing the cancellous bone defects accompanied by split fractures via in vitro and in vivo experiments. After HTO treatment, a dense oxidation layer mainly composed of Y2O3 and Nd2O3 formed on the surface of scaffolds. In addition, the majority of the grains were equiaxed, with an average grain size of 7.4 μm. Cell and rabbit experiments confirmed the non-cytotoxicity and biocompatibility of the HTO-treated WE43 scaffolds. After the implantation of scaffolds inside bone defects, their porous structures could be maintained for more than 12 weeks without penetration and for more than 6 weeks with penetration. During the postoperative follow-up period for up to 48 weeks, radiographic examinations and histological analysis revealed that abundant bone gradually regenerated along with scaffold degradation, and stable osseointegration formed between new bone and scaffold residues. MRI images further demonstrated no evidence of any obvious damage to the cartilage, ligaments, or menisci, confirming the absence of traumatic osteoarthritis. Moreover, finite element analysis and biomechanical tests further verified that the scaffolds was conducive to a uniform mechanical distribution. In conclusion, applying the HTO-treated 3D printed porous anatomical WE43 scaffolds exhibited favorable repairing effects for subarticular cancellous bone defects, possessing great potential for clinical application.

Additively Manufactured Zn-2Mg Alloy Porous Scaffolds with Customizable Biodegradable Performance and Enhanced Osteogenic Ability

The combination of bioactive Zn-2Mg alloy and additively manufactured porous scaffold is expected to achieve customizable biodegradable performance and enhanced bone regeneration. Herein, Zn-2Mg alloy scaffolds with different porosities, including 40% (G-40-2), 60% (G-60-2), and 80% (G-80-2), and different unit sizes, including 1.5 mm (G-60-1.5), 2 mm (G-60-2), and 2.5 mm (G-60-2.5), are manufactured by a triply periodic minimal surface design and a reliable laser powder bed fusion process. With the same unit size, compressive strength (CS) and elastic modulus (EM) of scaffolds substantially decrease with increasing porosities. With the same porosity, CS and EM just slightly decrease with increasing unit sizes. The weight loss after degradation increases with increasing porosities and decreasing unit sizes. In vivo tests indicate that Zn-2Mg alloy scaffolds exhibit satisfactory biocompatibility and osteogenic ability. The osteogenic ability of scaffolds is mainly determined by their physical and chemical characteristics. Scaffolds with lower porosities and smaller unit sizes show better osteogenesis due to their suitable pore size and larger surface area. The results indicate that the biodegradable performance of scaffolds can be accurately regulated on a large scale by structure design and the additively manufactured Zn-2Mg alloy scaffolds have improved osteogenic ability for treating bone defects.

MixSleepNet: A Multi-Type Convolution Combined Sleep Stage Classification Model

BACKGROUND AND OBJECTIVE

Sleep staging is an essential step for sleep disorder diagnosis, which is time-intensive and laborious for experts to perform this work manually. Automatic sleep stage classification methods not only alleviate experts from these demanding tasks but also enhance the accuracy and efficiency of the classification process.

METHODS

A novel multi-channel biosignal-based model constructed by the combination of a 3D convolutional operation and a graph convolutional operation is proposed for the automated sleep stages using various physiological signals. Both the 3D convolution and graph convolution can aggregate information from neighboring brain areas, which helps to learn intrinsic connections from the biosignals. Electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG) and electrocardiogram (ECG) signals are employed to extract time domain and frequency domain features. Subsequently, these signals are input to the 3D convolutional and graph convolutional branches, respectively. The 3D convolution branch can explore the correlations between multi-channel signals and multi-band waves in each channel in the time series, while the graph convolution branch can explore the connections between each channel and each frequency band. In this work, we have developed the proposed multi-channel convolution combined sleep stage classification model (MixSleepNet) using ISRUC datasets (Subgroup 3 and 50 random samples from Subgroup 1).

RESULTS

Based on the first expert's label, our generated MixSleepNet yielded an accuracy, F1-score and Cohen kappa scores of 0.830, 0.821 and 0.782, respectively for ISRUC-S3. It obtained accuracy, F1-score and Cohen kappa scores of 0.812, 0.786, and 0.756, respectively for the ISRUC-S1 dataset. In accordance with the evaluations conducted by the second expert, the comprehensive accuracies, F1-scores, and Cohen kappa coefficients for the ISRUC-S3 and ISRUC-S1 datasets are determined to be 0.837, 0.820, 0.789, and 0.829, 0.791, 0.775, respectively.

CONCLUSION

The results of the performance metrics by the proposed method are much better than those from all the compared models. Additional experiments were carried out on the ISRUC-S3 sub-dataset to evaluate the contributions of each module towards the classification performance.

Automatic sleep spindles identification and classification with multitapers and convolution

Sleep spindles are isolated transient surges of oscillatory neural activity present during sleep stages 2 and 3 in the nonrapid eye movement (NREM). They can indicate the mechanisms of memory consolidation and plasticity in the brain. Spindles can be identified across cortical areas and classified as either slow or fast. There are spindle transients across different frequencies and power, yet most of their functions remain a mystery. Using several electroencephalogram (EEG) databases, this study presents a new method, called the "spindles across multiple channels" (SAMC) method, for identifying and categorizing sleep spindles in EEGs during the NREM sleep. The SAMC method uses a multitapers and convolution (MT&C) approach to extract the spectral estimation of different frequencies present in sleep EEGs and graphically identify spindles across multiple channels. The characteristics of spindles, such as duration, power, and event areas, are also extracted by the SAMC method. Comparison with other state-of-the-art spindle identification methods demonstrated the superiority of the proposed method with an agreement rate, average positive predictive value, and sensitivity of over 90% for spindle classification across the three databases used in this paper. The computing cost was found to be, on average, 0.004 seconds per epoch. The proposed method can potentially improve the understanding of the behavior of spindles across the scalp and accurately identify and categories sleep spindles.

Experimental study on failure characteristics and rheological properties of pillar-like rock samples with different shapes

The stability of coal pillar is extremely important to the control of rock strata movement and surface subsidence. It is of great significance for mining design to analyze the stability and failure characteristics of coal and rock pillars left after mining and to study the failure characteristics and rheological properties of coal and rock with different shapes. In this paper, based on uniaxial compression and rheological tests on rock samples, the rheological properties of rock samples with different shapes were discussed by using the nonlinear theoretical mechanics and damage theory, and the rheological mechanical characteristics of coarse yellow sandstone samples under the action of different free surface areas and the same loading contact area were investigated by means of experimental research, theoretical analysis and numerical simulation. The following conclusions were drawn: the failure characteristics and dynamic change process of rock samples with different shapes under the same loading contact area are obtained by uniaxial compression test and multi-stage rheological loading. The uniaxial compressive strengths of rock samples with the same loading contact surface area and different free surface areas are inversely proportional to their free surface areas. For the round sample, the stress level in the rheological test is obviously lower than the instantaneous peak uniaxial compression strength, while for the other samples, the stress level in the rheological test is close to the instantaneous peak uniaxial compression strength. For rock all these samples, both the ratio of steady-state rheological time to final failure time and the deformation degree decrease with the increase of free surface area.

Atypical lobular endocervical glandular hyperplasia: two case report and literature review

Atypical lobular endocervical glandular hyperplasia (ALEGH) is considered a precancerous lesion of gastric-type adenocarcinoma (GAS)/minimal deviation adenocarcinoma (MDA) characterized by an insidious onset, atypical symptoms, and often negative human papillomavirus (HPV) screening. Early screening for this disease is challenging, leading to a high rate of missed clinical diagnoses and the development of malignant tumors at the onset. Increased vaginal discharge and the presence of imaging cystic masses at the internal cervical ostium are often observed in patients with ALEGH. Therefore, we reviewed the clinical data of two cases of ALEGH that were identified and diagnosed in the early stages at our hospital. Through a comprehensive analysis of the medical history and diagnosis plan, combined with a review of relevant literature, to improve the early recognition and diagnosis of ALEGH, as well as strengthen the management of cervical precancerous lesions.

Experimental and finite element analysis of the generation mechanism of high impulse noise overpressure (caused by a recoilless weapon) at the bottom of the ear

The intense impulse noise may damage the soldiers' hearing organs during a weapon's firing. It is essential to find out the generation mechanism of the overpressure at the bottom of the ear. The experiments of measuring the overpressure at the bottom of the ear were conducted through a rotating human head model at a recoilless weapon firing platform. The results showed that the overpressure peak at the bottom of the ear decreases with the increasing incident angle. A simulation of the test condition was developed based on the plane shock wave method. The finite element model was verified reasonably compared to the test results. The Friedlander wave propagating to the ear canal was implemented at different incident angles. The generation of the overpressure at the bottom of the ear was analyzed. According to the pressure nephograms, the impulse noise stagnated at the bottom of the ear, so the overpressure was the total pressure of impulse noise. Two parts of impulse noise entered the canal successively due to the influence of the pinna. The overpressure and Mach number at the entrance of the ear canal both decreased with increasing incident angles, resulting in impulse noise superimposed at the bottom of the ear. Investigating the generation of overpressure at the bottom of the ear under varying incident angles may have important reference value for analyzing and preventing auditory organ damage caused by impulse noise.

Comprehensive model development based on Dempster-Shafer evidence theory for pollution source analysis in chemical parks

Pollution source analysis is an effective method that can help chemical park managers accurately understand the characteristics and contributions of pollution sources in the park. However, as more receptor models are being used in this field, it has become difficult for managers to find the best interpretable and reasonable model among many source analysis models. Here, we present a case study of pollution source analysis in a southern chemical park using the D-S evidence theory approach to combine the source analysis results of different receptor models for comprehensive consideration. Receptor models were used to analyse the pollution sources via positive definite matrix decomposition, principal component analysis-multiple linear regression, and Unmix models. The results demonstrated that source analysis was greatly influenced by the uniqueness of pollutant characteristics and model receptor differences. Furthermore, incomparable analysis results and low fineness were observed. The D-S evidence theory model proposed in this study solved the above-mentioned problem to some extent and successfully extracted the four primary pollution sources in the study area, of which 45.73 % came from the metal processing industry (F1), whose primary pollutants were Cr, Ni, Zn, Cr(VI), and Cu, and 25.12 % came from the electronics manufacturing industry (F2), whose primary pollutants were Pb, Cr(VI), Cu, and Zn. 15.62 % of the contamination came from the production of chemical agents (F3), whose primary pollutant was TEHP, and 13.53 % came from the use of oil-containing auxiliary materials (F4), whose primary pollutant was TPH. The D-S evidence theory model used in this study provides a reference for the management of chemical parks.

Machine learning-enabled constrained multi-objective design of architected materials

Architected materials that consist of multiple subelements arranged in particular orders can demonstrate a much broader range of properties than their constituent materials. However, the rational design of these materials generally relies on experts' prior knowledge and requires painstaking effort. Here, we present a data-efficient method for the high-dimensional multi-property optimization of 3D-printed architected materials utilizing a machine learning (ML) cycle consisting of the finite element method (FEM) and 3D neural networks. Specifically, we apply our method to orthopedic implant design. Compared to uniform designs, our experience-free method designs microscale heterogeneous architectures with a biocompatible elastic modulus and higher strength. Furthermore, inspired by the knowledge learned from the neural networks, we develop machine-human synergy, adapting the ML-designed architecture to fix a macroscale, irregularly shaped animal bone defect. Such adaptation exhibits 20% higher experimental load-bearing capacity than the uniform design. Thus, our method provides a data-efficient paradigm for the fast and intelligent design of architected materials with tailored mechanical, physical, and chemical properties.

Sequencing polymers to enable solid-state lithium batteries

Rational designs of solid polymer electrolytes with high ion conduction are critical in enabling the creation of advanced lithium batteries. However, known polymer electrolytes have much lower ionic conductivity than liquid/ceramics at room temperature, which limits their practical use in batteries. Here we show that precise positioning of designed repeating units in alternating polymer sequences lays the foundation for homogenized Li+ distribution, non-aggregated Li+-anion solvation and sequence-assisted site-to-site ion migration, facilitating the tuning of Li+ conductivity by up to three orders of magnitude. The assembled all-solid-state batteries facilitate reversible and dendrite-mitigated cycling against Li metal from ambient to elevated temperatures. This work demonstrates a powerful molecular engineering means to access highly ion-conductive solid-state materials for next-generation energy devices.

Photo-induced scandium-catalyzed biomimetic skeleton conversion of lathyrane to naturally rare eupholathone Euphorbia diterpenes

The naturally scarce eupholathone-type euphornin E (1) was efficiently prepared from abundant lathyrane-type Euphorbia factor L1via a visible-light-induced Sc(OTf)3-catalyzed tandem process. Eupholathones 2 and 3 were also smoothly obtained by changing the reaction solvent. This route provides a convenient method for easily constructing scarce eupholathone- from lathyrane-type Euphorbia diterpenes, and confirms the biogenetic relationship between them from a chemical standpoint. Notably, compound 1 exhibited good anti-HIV activity.

Mechanical properties, in vitro biodegradable behavior, biocompatibility and osteogenic ability of additively manufactured Zn-0.8Li-0.1Mg alloy scaffolds

Alloying and structural design provide flexibility to modulate performance of biodegradable porous implants manufactured by laser powder bed fusion (L-PBF). Herein, bulk Zn-0.8Li-0.1Mg was first fabricated to indicate the influence of the ternary alloy system on strengthening effect. Porous scaffolds with different porosities, including 60 % (P60), 70 % (P70) and 80 % (P80), were designed and fabricated to study the influence of porosity on mechanical properties, in vitro degradation behavior, biocompatibility and osteogenic ability. Pure Zn (Zn-P70) scaffolds with a porosity of 70 % were utilized for the comparison. The results showed Zn-0.8Li-0.1Mg bulks had an ultimate tensile strength of 460.78 ± 5.79 MPa, which was more than 3 times that of pure Zn ones and was the highest value ever reported for Zn alloys fabricated by L-PBF. The compressive strength (CS) and elastic modulus (E) of scaffolds decreased with increasing porosities. The CS of P70 scaffolds was 24.59 MPa, more than 2 times that of Zn-P70. The weight loss of scaffolds during in vitro immersion increased with increasing porosities. Compared with Zn-P70, a lower weight loss, better biocompatibility and improved osteogenic ability were observed for P70 scaffolds. P70 scaffolds also exhibited the best biocompatibility and osteogenic ability among all the used porosities. Influence mechanism of alloying elements and structural porosities on mechanical behaviors, in vitro biodegradation behavior, biocompatibility and osteogenic ability of scaffolds were discussed using finite element analysis and the characterization of degradation products. The results indicated that the proper design of alloying and porosity made Zn-0.8Li-0.1Mg scaffolds promising for biodegradable applications.

The effect of pore size on the mechanical properties, biodegradation and osteogenic effects of additively manufactured magnesium scaffolds after high temperature oxidation: An in vitro and in vivo study

The effects of pore size in additively manufactured biodegradable porous magnesium on the mechanical properties and biodegradation of the scaffolds as well as new bone formation have rarely been reported. In this work, we found that high temperature oxidation improves the corrosion resistance of magnesium scaffold. And the effects of pore size on the mechanical characteristics and biodegradation of scaffolds, as well as new bone formation, were investigated using magnesium scaffolds with three different pore sizes, namely, 500, 800, and 1400 μm (P500, P800, and P1400). We discovered that the mechanical characteristics of the P500 group were much better than those of the other two groups. In vitro and in vivo investigations showed that WE43 magnesium alloy scaffolds supported the survival of mesenchymal stem cells and did not cause any local toxicity. Due to their larger specific surface area, the scaffolds in the P500 group released more magnesium ions within reasonable range and improved the osteogenic differentiation of bone mesenchymal stem cells compared with the other two scaffolds. In a rabbit femoral condyle defect model, the P500 group demonstrated unique performance in promoting new bone formation, indicating its great potential for use in bone defect regeneration therapy.

Designing F/P Hybrid Polymer as Ultrastable Cationic Shielding Interphase for High-Performance Lithium Metal Batteries

Dendrite growth on electrode-electrolyte interphase has severely limited applications of lithium metal batteries (LMBs). Here, we developed an ionic alternating polymer with fluorocarbons and phosphonium cations in repeating units to regulate Li deposition for the first time. The combined functionalities in the F/P hybrid polymer exhibit remarkable characteristics as a protective layer on top of Li anode, demonstrating outstanding electrochemical stability, ion flux redistributing capability and adaptive chain mobility. Based on characterizations and simulations, this cationic interlayer could effectively furnish long-standing electrostatic shielding for anodes, allowing restrained coating decomposition and homogenized electric field distribution to induce dendrite-free Li deposition, and enabling full cells with enhanced rate and long-term cycling performance. Given the importance of LMBs, this work will promote polymer design to stabilize anodes with superior electrochemical behavior.

3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning

A novel multi-channel-based 3D convolutional neural network (3D-CNN) is proposed in this paper to classify sleep stages. Time domain features, frequency domain features, and time-frequency domain features are extracted from electroencephalography (EEG), electromyogram (EMG), and electrooculogram (EOG) channels and fed into the 3D-CNN model to classify sleep stages. Intrinsic connections among different bio-signals and different frequency bands in time series and time-frequency are learned by 3D convolutional layers, while the frequency relations are learned by 2D convolutional layers. Partial dot-product attention layers help this model find the most important channels and frequency bands in different sleep stages. A long short-term memory unit is added to learn the transition rules among neighboring epochs. Classification experiments were conducted using both ISRUC-S3 datasets and ISRUC-S1, sleep-disorder datasets. The experimental results showed that the overall accuracy achieved 0.832 and the F1-score and Cohen's kappa reached 0.814 and 0.783, respectively, on ISRUC-S3, which are a competitive classification performance with the state-of-the-art baselines. The overall accuracy, F1-score, and Cohen's kappa on ISRUC-S1 achieved 0.820, 0.797, and 0.768, respectively, which also demonstrate its generality on unhealthy subjects. Further experiments were conducted on ISRUC-S3 subset to evaluate its training time. The training time on 10 subjects from ISRUC-S3 with 8549 epochs is 4493s, which indicates its highest calculation speed compared with the existing high-performance graph convolutional networks and [Formula: see text]Net architecture algorithms.

A drug-loaded composite coating to improve osteogenic and antibacterial properties of Zn-1Mg porous scaffolds as biodegradable bone implants

Zinc (Zn) alloy porous scaffolds produced by additive manufacturing own customizable structures and biodegradable functions, having a great application potential for repairing bone defect. In this work, a hydroxyapatite (HA)/polydopamine (PDA) composite coating was constructed on the surface of Zn-1Mg porous scaffolds fabricated by laser powder bed fusion, and was loaded with a bioactive factor BMP2 and an antibacterial drug vancomycin. The microstructure, degradation behavior, biocompatibility, antibacterial performance and osteogenic activities were systematically investigated. Compared with as-built Zn-1Mg scaffolds, the rapid increase of Zn²⁺, which resulted to the deteriorated cell viability and osteogenic differentiation, was inhibited due to the physical barrier of the composite coating. In vitro cellular and bacterial assay indicated that the loaded BMP2 and vancomycin considerably enhanced the cytocompatibility and antibacterial performance. Significantly improved osteogenic and antibacterial functions were also observed according to in vivo implantation in the lateral femoral condyle of rats. The design, influence and mechanism of the composite coating were discussed accordingly. It was concluded that the additively manufactured Zn-1Mg porous scaffolds together with the composite coating could modulate biodegradable performance and contribute to effective promotion of bone recovery and antibacterial function.

Improved Luminous Efficiency of AgInS2 Quantum Dots and Zeolitic Imidazolate Framework-70 Composite for White Light Emitting Diode Applications

The application of multiple quantum dots (QDs) in the field of white light emitting diodes (WLEDs) is still an important challenge due to their low luminous efficiency and quenching phenomenon. In this paper, we prepared AgInS2 QDs/zeolitic imidazolate framework-70 (AIS/ZIF-70) composite by a microwave hydrothermal method. Owing to the high porosity and stability of ZIF-70, it could effectively prevent quenching issues due to the aggregation of QDs. Since the ZIF-70 and QDs were chemically bonded, the formation of the ZnS layer could effectively passivate the surface defect and thus the quantum yield reached 21.49 % in aqueous solution. The luminous efficiency (LE) of the assembled AIS/ZIF-based WLED was reinforced by 6.8 times with a molar ratio of AgIn/Zn=18, i. e. at 5.26 % molar fraction of ZIF-70. Moreover, the color rendering index (CRI) and correlated color temperature (CCT) of AIS/ZIF-based WLED were 84.3 and 3631 K, respectively, indicating its potential application in solid-state lighting.

Retraction: Colloidal Cobalt Phosphide Nanocrystals as Trifunctional Electrocatalysts for Overall Water Splitting Powered by a Zinc-Air Battery

Adv. Mater. 2018, 30, 1705796 https://doi.org/10.1002/adma.201705796 The above article, published online on January 15, 2018, in Wiley Online Library (https://doi.org/10.1002/adma.201705796), has been retracted by agreement between the authors, the journal Editor in Chief Jos Lenders, and Wiley-VCH GmbH. The retraction has been agreed on following concerns raised by a third party and a subsequent investigation at Wake Forest University. Data integrity issues were found in Figures 1a, S2b, and S17. As a result, the authors consider the conclusions of this article invalid.

Retraction: Phosphorus-Rich Colloidal Cobalt Diphosphide (CoP2 ) Nanocrystals for Electrochemical and Photoelectrochemical Hydrogen Evolution

Adv. Mater. 2019, 31, 1900813. https://doi.org/10.1002/adma.201900813 The above article, published online on May 6, 2019, in Wiley Online Library (https://doi.org/10.1002/adma.201900813), has been retracted by agreement between the authors, the journal Editor in Chief Jos Lenders, and Wiley-VCH GmbH. The retraction has been agreed on following concerns raised by a third party and a subsequent investigation at Wake Forest University. Data integrity issues were found in Figures 2c, 4d, S13a, S13b, S15, and S37. As a result, the authors consider the conclusions of this article invalid.

Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network

Schizophrenia (ScZ) is a devastating mental disorder of the human brain that causes a serious impact of emotional inclinations, quality of personal and social life and healthcare systems. In recent years, deep learning methods with connectivity analysis only very recently focused into fMRI data. To explore this kind of research into electroencephalogram (EEG) signal, this paper investigates the identification of ScZ EEG signals using dynamic functional connectivity analysis and deep learning methods. A time-frequency domain functional connectivity analysis through cross mutual information algorithm is proposed to extract the features in alpha band (8-12 Hz) of each subject. A 3D convolutional neural network technique was applied to classify the ScZ subjects and health control (HC) subjects. The LMSU public ScZ EEG dataset is employed to evaluate the proposed method, and a 97.74 ± 1.15% accuracy, 96.91 ± 2.76% sensitivity and 98.53 ± 1.97% specificity results were achieved in this study. In addition, we also found not only the default mode network region but also the connectivity between temporal lobe and posterior temporal lobe in both right and left side have significant difference between the ScZ and HC subjects.

Design, synthesis and anti-inflammatory activity of diterpenoid alkaloids and non-steroidal anti-inflammatory drug hybrids based on molecular hybridization strategy

Molecular hybridization is a widely employed approach in pharmaceutical chemistry for modifying drugs with the aim of improving pharmacological efficacy and reducing adverse effects. A prime example of this is the case of benorylate, which was created by combining aspirin and acetaminophen, two non-steroidal anti-inflammatory drugs (NSAIDs). Diterpenoid alkaloids, which exhibit potent anti-inflammatory activity, have limitations in their application due to their toxicity and side effects. Thus, we aimed to design new anti-inflammatory lead compounds through the molecular hybridization of the anti-inflammatory active skeletons (lappaconitine, aconorine, and bulleyaconitine A) of diterpenoid alkaloids with classical NSAIDs. In this study, we synthesized 25 diterpenoid alkaloid derivatives with NSAIDs, organized into four series. Among these derivatives, lappaconitine derivative 1e demonstrated the strongest inhibition of lipopolysaccharide (LPS)-induced NO production in RAW 264.7 cells with minimal cytotoxicity. Additionally, 1e effectively suppressed the inflammatory response induced by carrageenan in vivo, with a swelling rate of only 1%. This anti-inflammatory potency was found to be significantly superior to that of naproxen. The molecular docking analysis revealed that the binding affinity of 1e was scored as -10.3 kcal/mol, suggesting that it forms a stable complex with cyclooxygenase-2 (COX-2). Therefore, compound 1e holds potential as a lead anti-inflammatory compound that could be further developed.

Initiator-Activation Strategy Enabled Organocatalyzed Reversible-Deactivation Radical Polymerization Driven by Light

Organocatalyzed reversible-deactivation radical polymerizations (RDRPs) are attractive for many applications. Here, we developed photoredox-mediated RDRP by activating (hetero)aryl sulfonyl chloride (ArSO2Cl) initiators with pyridines and designing a novel bis(phenothiazine)arene catalyst. The in-situ formed sulfonyl pyridinium intermediates effectively promote controlled chain-growth from ArSO2Cl, enabling access to various well-defined polymers with high initiation efficiencies and controlled dispersities under mild conditions. This versatile method allows "ON/OFF" temporal control, chain-extension, facile synthesis of different polymer brushes via organocatalyzed grafting reactions from linear chains. Time-resolved fluorescence decay studies and calculations support the reaction mechanism. This work provides a transition-metal-free RDRP to tailor polymers with readily available aromatic initiators, and will promote the design of polymerization leveraged from photoredox catalysis.

Stiffness of gangue backfilling body in goaf and its influence mechanism on rock strata control and stress evolution in gangue backfill mining

To study the influence mechanism of gangue backfilling material (GBM) with different particle sizes on overburden deformation, the particle movement characteristics and the mechanism of stiffness difference with different particle sizes of GBM were analysed by physical compression and particle flow numerical simulations. Then, combined with a similar material simulation method, the deformation characteristics of roof overburden and the evolution process of floor stress in backfill mining with backfilling bodies of different stiffness levels were studied. The results indicate that the subsidence decreased monotonously with a decrease in the particle size, and the stiffness of the GBM increased significantly under the same vertical load. The small-particle gangue moved downward in the layered law under the same load conditions, while the large-particle gangue moved downward through rotation, rubbing, crushing, and filling interaction processes. In the treatment of goaf by the backfilling method, the entire process of overlying strata movement mainly experienced bending, micro-fracture, separation, compaction, and new fracture, and the anti-deformation capacity of the backfilling body directly determined the deformation and movement of the overburden strata in a goaf. In the backfilling method, the greater the stiffness of the filling body, the smaller the advanced support pressure, and the more effective it was to inhibit pressure relief from the floor.

Development of an Indirect Enzyme-Linked Immunosorbent Assay Based on the Yeast-Expressed CO-26K-Equivalent Epitope-Containing Antigen for Detection of Serum Antibodies against Porcine Epidemic Diarrhea Virus

Porcine epidemic diarrhea (PED) is a severe contagious intestinal disease caused by the porcine epidemic diarrhea virus (PEDV), which leads to high mortality in piglets. In this study, by analyzing a total of 53 full-length spike genes and COE domain regions of PEDVs, the conserved COE fragment of the spike protein from the dominant strain SC1402 was chosen as the target protein and expressed successfully in Pichia pastoris (P. pastoris). Furthermore, an indirect enzyme-linked immunosorbent assay (iELISA) based on the recombinant COE protein was developed for the detection of anti-PEDV antibodies in pig sera. The results showed that under the optimized conditions, the cut-off value of COE-based indirect ELISA (COE-iELISA) was determined to be 0.12. Taking the serum neutralization test as standard, the relative sensitivity of the COE-iELISA was 94.4% and specificity 92.6%. Meanwhile, no cross-reactivity to other porcine pathogens was noted with this assay. The intra-assay and inter-assay coefficients of variation were less than 7%. Moreover, 164 vaccinated serum samples test showed that overall agreement between COE-iELISA and the actual diagnosis result was up to 99.4%. More importantly, the developed iELISA exhibited a 95.08% agreement rate with the commercial ELISA kit (Kappa value = 0.88), which suggested that the expressed COE protein was an effective antigen in serologic tests and the established COE-iELISA is reliable for monitoring PEDV infection in pigs or vaccine effectiveness.

Exploring deep residual network based features for automatic schizophrenia detection from EEG

Schizophrenia is a severe mental illness which can cause lifelong disability. Most recent studies on the Electroencephalogram (EEG)-based diagnosis of schizophrenia rely on bespoke/hand-crafted feature extraction techniques. Traditional manual feature extraction methods are time-consuming, imprecise, and have a limited ability to balance accuracy and efficiency. Addressing this issue, this study introduces a deep residual network (deep ResNet) based feature extraction design that can automatically extract representative features from EEG signal data for identifying schizophrenia. This proposed method consists of three stages: signal pre-processing by average filtering method, extraction of hidden patterns of EEG signals by deep ResNet, and classification of schizophrenia by softmax layer. To assess the performance of the obtained deep features, ResNet softmax classifier and also several machine learning (ML) techniques are applied on the same feature set. The experimental results for a Kaggle schizophrenia EEG dataset show that the deep features with support vector machine classifier could achieve the highest performances (99.23% accuracy) compared to the ResNet classifier. Furthermore, the proposed model performs better than the existing approaches. The findings suggest that our proposed strategy has capability to discover important biomarkers for automatic diagnosis of schizophrenia from EEG, which will aid in the development of a computer assisted diagnostic system by specialists.

Synthesis and Cytotoxicity Evaluation of Dehydroepiandrosterone Derivatives by Iron-catalyzed Stereoselective Hydroamination

The direct modification of structurally complex natural product dehydroepiandrosterone (DHEA) through Iron-catalyzed direct hydroamination of DHEA with various nitro(hetero)arenes was carried out to afford 5α-arylamino-DHEAs (1-25) in good yields (53-72%). Though as a radical reaction, it features high stereoselectivity, and only the 5α-substituted derivatives were produced. The in vitro antiproliferative activity of these synthesized compounds against the human breast cancer MCF-7 cell was evaluated, showing that most of DHEA analogues possessed the moderate cytotoxic activity. The preliminary structure-activity relationship analysis revealed that the electron-withdrawing groups installed at the para-position of arylamine ring had a great contribution to the improvement of the DHEA's cytotoxic potency. Among them, (4-trifluoromethylaniline)-DHEA (4) displayed the most potent cytotoxicity, with an IC₅₀ value of 19.3 μM, which was 2.3-fold more active than DHEA.

Identification, validation and biological characterisation of novel glioblastoma tumour microenvironment subtypes: implications for precision immunotherapy

BACKGROUND

New precision medicine therapies are urgently required for glioblastoma (GBM). However, to date, efforts to subtype patients based on molecular profiles have failed to direct treatment strategies. We hypothesised that interrogation of the GBM tumour microenvironment (TME) and identification of novel TME-specific subtypes could inform new precision immunotherapy treatment strategies.

MATERIALS AND METHODS

A refined and validated microenvironment cell population (MCP) counter method was applied to >800 GBM patient tumours (GBM-MCP-counter). Specifically, partition around medoids (PAM) clustering of GBM-MCP-counter scores in the GLIOTRAIN discovery cohort identified three novel patient clusters, uniquely characterised by TME composition, functional orientation markers and immune checkpoint proteins. Validation was carried out in three independent GBM-RNA-seq datasets. Neoantigen, mutational and gene ontology analysis identified mutations and uniquely altered pathways across subtypes. The longitudinal Glioma Longitudinal AnalySiS (GLASS) cohort and three immunotherapy clinical trial cohorts [treatment with neoadjuvant/adjuvant anti-programmed cell death protein 1 (PD-1) or PSVRIPO] were further interrogated to assess subtype alterations between primary and recurrent tumours and to assess the utility of TME classifiers as immunotherapy biomarkers.

RESULTS

TME^High tumours (30%) displayed elevated lymphocyte, myeloid cell immune checkpoint, programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 transcripts. TME^High/mesenchymal+ patients featured tertiary lymphoid structures. TME^Med (46%) tumours were enriched for endothelial cell gene expression profiles and displayed heterogeneous immune populations. TME^Low (24%) tumours were manifest as an 'immune-desert' group. TME subtype transitions upon recurrence were identified in the longitudinal GLASS cohort. Assessment of GBM immunotherapy trial datasets revealed that TME^High patients receiving neoadjuvant anti-PD-1 had significantly increased overall survival (P = 0.04). Moreover, TME^High patients treated with adjuvant anti-PD-1 or oncolytic virus (PVSRIPO) showed a trend towards improved survival.

CONCLUSIONS

We have established a novel TME-based classification system for application in intracranial malignancies. TME subtypes represent canonical 'termini a quo' (starting points) to support an improved precision immunotherapy treatment approach.

The biological properties of 3D-printed degradable magnesium alloy WE43 porous scaffolds via the oxidative heat strategy

As a biodegradable material, magnesium alloy has a modulus similar to that of bone, and given the biological activity of its degradation products, it has the potential to be a bone grafting material. Oxidation heat treatment is a very effective passivation method that may reduce the rate of magnesium alloy degradation. Oxidation heat treatment increases the rare earth oxide content of the scaffold as well as the corrosion resistance of the scaffold. The overall cytotoxicity of the as-printed scaffolds (APSs) and oxidation heat-treated scaffolds (OHSs) showed that OHSs accelerated cell proliferation. In the apoptosis experiment, the OHS group had a cell survival rate between that of the control group and of the as-printed group. In the osteogenic induction experiment, the alkaline phosphatase activity and the quantity of mineralized nodules were greater in the APS and OHS groups than in the control group. Marker proteins for bone growth were expressed at higher levels in the APS and OHS groups than in the control group. Therefore, oxidation heat-treated 3D printing scaffolds with good biocompatibility and osteogenic properties have great potential to be made into advanced biomaterials that can be used to fix bone defects. 

Synthesis, antiproliferative and anti-MDR activities of lathyrane diterpene derivatives based on configuration inversion strategy

A series of lathyrane-type Euphorbia diterpene derivatives featured 3R configuration (H-3β) were synthesized from natural rich Euphorbia factor L₃via modified Mitsunobu reaction based on configuration inversion strategy. The antiproliferation activity and MDR reversal ability of the lathyrane derivatives were evaluated, and the most synthesized compounds showed moderate or strong potencies. Among them, diterpenes 21 (IC₅₀ values of 2.6, 5.2 and 13.1 μM, respectively) and 25 (IC₅₀ values of 5.5, 8.6 and 1.3 μM, respectively) presented the strong cytotoxicity against MCF-7, 4 T1 and HepG2 cells. Meanwhile, derivative 25 exhibited excellent MDR reversal ability with the reversal fold of 16.1 higher than that of verapamil. The cellular thermal shift assay and molecular docking proved direct engagement of diterpene 25 to ABCB1, suggesting 25 could be a promising MDR modulator. Furthermore, the preliminary SARs of these diterpenes were also discussed.

In vivo antioxidant activity of Cinnamomum cassia leaf residues and their effect on gut microbiota of d-galactose-induced aging model mice

BACKGROUND

To thoroughly explore the values of Cinnamomum cassia leaf residues (CcLR), their antioxidant activity in vivo and the relationship with gut microbiota were investigated using d-galactose-induced aging mice.

RESULTS

Results showed that CcLR extract treatment exerted antioxidant activity by increasing the levels of superoxide dismutase (P < 0.01) and glutathione peroxidase (P < 0.05), as well as inhibiting the formation of malondialdehyde (P < 0.01). Meanwhile, the inflammatory response was also alleviated as the ratio of pro-inflammatory tumor necrosis factor-α (P < 0.01) and interleukin-1β (P < 0.01))/anti-inflammatory cytokines (interleukin-10; P < 0.05) in serum was decreased and the contents of inflammatory markers (induced nitrogen monoxide synthase and nitric oxide) in brain and liver tissues (P < 0.01) were reduced. Moreover, through inhibiting acetylcholinesterase activity and improving choline acetyltransferase activity, the cholinergic system in aging mice recovered to levels comparable to the normal control group. In addition, 16S rRNA sequencing results demonstrated that CcLR extract promoted the growth of beneficial bacteria. In particular, Spearman correlation analysis revealed that the abundance of Colidextribacter was negatively correlated with serum superoxide dismutase (P < 0.05, R = -0.943), and Helicobacter displayed a positive correlation with the content of brain nitric oxide (P < 0.05, R = 0.899), suggesting that regulating gut microbiota might be one of the mechanisms for reducing oxidative stress, thus postponing the aging process.

CONCLUSION

It is suggested that CcLR extract could be used as a novel antioxidant and anti-aging resource in the pharmaceutical and food industries. © 2022 Society of Chemical Industry.

Organocatalyzed Controlled Radical Copolymerization toward Hybrid Functional Fluoropolymers Driven by Light

Photo-controlled polymerizations are attractive to tailor macromolecules of complex compositions with spatiotemporal regulation. In this work, with a convenient synthesis for trifluorovinyl boronic ester (TFVB), we report a light-driven organocatalyzed copolymerization of vinyl monomers and TFVB for the first time, which enabled the controlled synthesis of a variety of hybrid fluorine/boron polymers with low dispersities and good chain-end fidelity. The good behaviors of "ON/OFF" switch, chain-extension polymerizations and post-modifications further highlight the versatility and reliability of this copolymerization. Furthermore, we demonstrate that the combination of fluorine and boron could furnish copolymer electrolytes of high lithium-ion transference number (up to 0.83), bringing new opportunities of engineering high-performance materials for energy storage purposes.

Comprehensive review of additively manufactured biodegradable magnesium implants for repairing bone defects from biomechanical and biodegradable perspectives

Bone defect repair is a complicated clinical problem, particularly when the defect is relatively large and the bone is unable to repair itself. Magnesium and its alloys have been introduced as versatile biomaterials to repair bone defects because of their excellent biocompatibility, osteoconductivity, bone-mimicking biomechanical features, and non-toxic and biodegradable properties. Therefore, magnesium alloys have become a popular research topic in the field of implants to treat critical bone defects. This review explores the popular Mg alloy research topics in the field of bone defects. Bibliometric analyses demonstrate that the degradation control and mechanical properties of Mg alloys are the main research focus for the treatment of bone defects. Furthermore, the additive manufacturing (AM) of Mg alloys is a promising approach for treating bone defects using implants with customized structures and functions. This work reviews the state of research on AM-Mg alloys and the current challenges in the field, mainly from the two aspects of controlling the degradation rate and the fabrication of excellent mechanical properties. First, the advantages, current progress, and challenges of the AM of Mg alloys for further application are discussed. The main mechanisms that lead to the rapid degradation of AM-Mg are then highlighted. Next, the typical methods and processing parameters of laser powder bed fusion fabrication on the degradation characteristics of Mg alloys are reviewed. The following section discusses how the above factors affect the mechanical properties of AM-Mg and the recent research progress. Finally, the current status of research on AM-Mg for bone defects is summarized, and some research directions for AM-Mg to drive the application of clinical orthopedic implants are suggested.

Scandium-Catalyzed Skeleton Conversion of Lathyrane to Lathyranone-Type Euphorbia Diterpenes

Naturally occurring 1(15 → 14)abeo-lathyrane rearrangement-type diterpene lathyranone A (1) was prepared from lathyrane-type Euphorbia factor L₁₁ (1a) via an efficient Sc(OTf)₃/Et₂NH-catalyzed α-ketol rearrangement, which was also suitable for the synthesis of lathyranones 2 and 3. This skeletal conversion strategy had the characteristic of biogenetically patterned synthesis and provided a convenient method for accessing naturally rare functionalized lathyranones from lathyranes. Moreover, the absolute configuration of the lathyranone skeleton was confirmed for the first time by the X-ray diffraction of 2.

Natural polyphenol self-assembled pH-responsive nanoparticles loaded into reversible hydrogel to inhibit oral bacterial activity

Periodontitis is one of the most prevalent chronic inflammatory diseases and Polyphenols isolated from Turkish gall play a major role in the treatment of inflammatory diseases for their antibacterial, anti-inflammatory and antioxidant activities. In this work, Turkish Galls effective constituent (TGEC, T) was prepared into nanoparticles (T-NPs) by principle of oxidative self-polymerization. The pH-sensitive T-NPs was encapsulated into thermosensitive type in-situ hydrogel, and 42.29 ± 1.12% of effective constituent from T-NPs were continuously released within 96 h under the periodontitis environment. In addition, the weakly alkaline oral micro-environment of patients with periodontitis is more conducive to the sustained release of effective constituent, which is 10.83% more than that of healthy periodontal environment. The bacteriostatic test showed that T-NPs had stronger antibacterial activity on oral pathogens than that of TGEC. Compared with TGEC, the minimum inhibitory concentration (MIC) of T-NPs against P. gingivalis and A. viscosus was reduced by 50% and 25%, respectively. Interestingly, T-NPs induced bacteria lysis by promoting the excessive production of ROS without periodontal tissue damage caused by excessive oxidation reaction. In conclusion, a simple method of preparing microspheres with natural polyphenols was developed, which provides beneficial reference for one-step prepared drug carriers from effective components of natural product, likewise the method offers a green and effective solution to synthesis a new adjuvant therapy drugs for treatment of gingivitis associated with periodontal pockets.

Repair of critical diaphyseal defects of lower limbs by 3D printed porous Ti6Al4V scaffolds without additional bone grafting: a prospective clinical study

The repair of critical diaphyseal defects of lower weight-bearing limbs is an intractable problem in clinical practice. From December 2017, we prospectively applied 3D printed porous Ti6Al4V scaffolds to reconstruct this kind of bone defect. All patients experienced a two-stage surgical process, including thorough debridement and scaffold implantation. With an average follow-up of 23.0 months, ten patients with 11 parts of bone defects were enrolled in this study. The case series included three females and seven males, their defect reasons included seven parts of osteomyelitis and four parts of aseptic nonunion. The bone defects located at femur (five parts) and tibia (six parts), with an average defect distance of 12.2 cm. Serial postoperative radiologic follow-ups displayed a continuous process of new bone growing and remodeling around the scaffold. One patient suffered tibial varus deformity, and he underwent a revision surgery. The other nine patients achieved scaffold stability. No scaffold breakage occurred. In conclusion, the implantation of 3D printed Ti6Al4V scaffold was feasible and effective to reconstruct critical bone defects of lower limbs without additional bone grafting. Graphical abstract.