Self-adhesive, freeze-tolerant, and strong hydrogel electrolyte containing xanthan gum enables the high-performance of zinc-ion hybrid supercapacitors.

Hydrogel electrolyte is an ideal candidate material for flexible energy storage devices due to its excellent softness and conductivity properties. However, challenges such as the inherent mechanical weakness, the susceptibility to be frozen in low-temperature environments, and the insufficiency of hydrogel-electrode contact persist. Herein, a "Multi in One" strategy is employed to effectively conquer these difficulties by endowing hydrogels with high strength, freeze-resistance, and self-adhesive ability. Multiple hydrogen bond networks and ion crosslinking networks are constructed within the hydrogel electrolyte (PVA/PAAc/XG) containing polyvinyl alcohol (PVA), acrylic acid (AAc), and xanthan gum (XG), promoting the enhanced mechanical property, and the adhesion to electrode materials is also improved through abundant active groups. The introduction of zinc ions provides the material with superior frost resistance while also promoting electrical conductivity. Leveraging its multifunction of superior mechanical strength, anti-freeze property, and self-adhesive characteristic, the PVA/PAAc/XG hydrogel electrolyte is employed to fabricate zinc ion hybrid supercapacitors (ZHS). Remarkably, ZHS exhibits outstanding electrochemical performance and cycle stability. A remarkable capacity retention rate of 83.86 % after 10,000 charge-discharge cycles can be achieved at high current densities, even when the operational temperature decreases to -60 °C, showing great potential in the field of flexible energy storage devices.

Cathepsin B degrades RbcL during freezing-induced programmed cell death in Arabidopsis.

KEY MESSAGE: Cathepsin B plays an important role that degrades the Rubisco large subunit RbcL in freezing stress. Programmed cell death (PCD) has been well documented in both development and in response to environmental stresses in plants, however, PCD induced by freezing stress and its molecular mechanisms remain poorly understood. In the present study, we characterized freezing-induced PCD and explored its mechanisms in Arabidopsis. PCD induced by freezing stress was similar to that induced by other stresses and senescence in Arabidopsis plants with cold acclimation. Inhibitor treatment assays and immunoblotting indicated that cathepsin B mainly contributed to increased caspase-3-like activity during freezing-induced PCD. Cathepsin B was involved in freezing-induced PCD and degraded the large subunit, RbcL, of Rubisco. Our results demonstrate an essential regulatory mechanism of cathepsin B for Rubisco degradation in freezing-induced PCD, improving our understanding of freezing-induced cell death and nitrogen and carbohydrate remobilisation in plants.

Strong and tough poly(vinyl alcohol)/xanthan gum-based ionic conducting hydrogel enabled through the synergistic effect of ion cross-linking and salting out.

The mechanical properties of ionic conductive hydrogels (ICHs) are generally inadequate, leading to their susceptibility to breakage under external forces and consequently resulting in the failure of flexible electronic devices. In this work, a simple and convenient strategy was proposed based on the synergistic effect of ion cross-linking and salting out, in which the hydrogels consisting of polyvinyl alcohol (PVA) and xanthan gum (XG) were immersed in zinc sulfate (ZnSO4) solution to obtain ICHs with exceptional mechanical properties. The salt-out effects between PVA chains and SO42- ions along with the cross-linked network of XG chains and Zn2+ ions contribute to the desirable mechanical properties of ICHs. Notably, the mechanical properties of ICHs can be adjusted by changing the concentration of ZnSO4 solution. Consequently, the optimum fracture stress and the fracture energy can reach 3.38 MPa and 12.13 KJ m-2, respectively. Moreover, the ICHs demonstrated a favorable sensitivity (up to 2.05) when utilized as a strain sensor, exhibiting an accurate detection of human body movements across various amplitudes.

A biomass-rich, self-healable, and high-adhesive polymer binder for advanced lithium-sulfur batteries.

Although lithium-sulfur (Li-S) batteries have attracted a great deal of attention due to their ultrahigh energy density, the significant dissolution and shuttle of polysulfides, coupled with the unstable electrode structure, result in a substantial decline in capacity, thereby hindering their practical application in rapidly advancing energy storage systems. In this work, we prepare an environmentally friendly binder (LA-GA) that possesses self-healing abilities and high adhesion by combining dynamic disulfide (SS) bonds with abundant polar functional groups. Significantly, the self-healing capability provided by SS bonds facilitates the repair of cracks resulting from cathode volume expansion. Simultaneously, the polar functional groups (carboxyl and pyrogallol) not only enhance adhesion, preserving cathode integrity, but also effectively participate in lithium polysulfide adsorption, thereby inhibiting the shuttle effect. As a result, sulfur cathodes incorporating the LA-GA binder demonstrate favorable cycling stability, with a high capacity retention of 81.9 % when tested at 0.2C for 100 cycles. Additionally, the long-term cycling performance is satisfactory, showing a small capacity decline rate of 0.0469 % per cycle over 700 cycles at 1.0C.

In silico prediction of immune-escaping hot spots for future COVID-19 vaccine design.

The COVID-19 pandemic has had a widespread impact on a global scale, and the evolution of considerable dominants has already taken place. Some variants contained certain key mutations located on the receptor binding domain (RBD) of spike protein, such as E484K and N501Y. It is increasingly worrying that these variants could impair the efficacy of current vaccines or therapies. Therefore, analyzing and predicting the high-risk mutations of SARS-CoV-2 spike glycoprotein is crucial to design future vaccines against the different variants. In this work, we proposed an in silico approach, immune-escaping score (IES), to predict high-risk immune-escaping hot spots on the receptor-binding domain (RBD), implemented through integrated delta binding free energy measured by computational mutagenesis of spike-antibody complexes and mutation frequency calculated from viral genome sequencing data. We identified 23 potentially immune-escaping mutations on the RBD by using IES, nine of which occurred in omicron variants (R346K, K417N, N440K, L452Q, L452R, S477N, T478K, F490S, and N501Y), despite our dataset being curated before the omicron first appeared. The highest immune-escaping score (IES = 1) was found for E484K, which agrees with recent studies stating that the mutation significantly reduced the efficacy of neutralization antibodies. Furthermore, our predicted delta binding free energy and IES show a high correlation with high-throughput deep mutational scanning data (Pearson's r = 0.70) and experimentally measured neutralization titers data (mean Pearson's r = -0.80). In summary, our work presents a new method to identify the potentially immune-escaping mutations on the RBD and provides valuable insights into future COVID-19 vaccine design.

Denitrification effect and strengthening mechanism of SAD/A system at low temperature by gel-immobilization technology.

Sulfur autotrophic denitrification coupled anaerobic ammonia oxidation (SAD/A) has several advantages over other denitrification processes; for example, it does not consume the organic carbon source, has low operation costs, and produces less excess sludge; however, it has certain disadvantages as well, such as a long start-up time, easy loss of bacteria, and low microbial activity at low temperature. The use of microbial immobilization technology to embed functional bacteria provides a feasible method of resolving the above problems. In this study polyvinyl alcohol­sodium alginate was used to prepare a composite carrier for fixing anaerobic ammonia oxidizing bacteria (AAOB) and sulfur oxidizing bacteria (SOB), and the structure and morphology of the encapsulated bodies were characterized by scanning electron microscopy and Fourier transform infrared spectroscopy. Subsequently, the nitrogen removal performance of the immobilized microbial carriers in the gradient cooling process (30 °C to 10 °C) was determined, and the corresponding mechanism was discussed. The results showed that the nitrate-removal efficiencies observed with granular sludge and gel embedding were at 10 °C 21.44 % and 14.31 % lower, than those at 30 °C, respectively, whereas the ammonia-removal efficiency decreased by up to approximately three-fold. The main mechanism was the 'insulation' provided by the external gel composed of PVA and SA for the internal sludge and subsequent improvement of its low temperature resistance, while protecting AAOB and SOB from oxygen inhibition, which is conducive to enriching denitrifying bacteria. In addition, the gel does not change the internal sludge species, it can shift the dominance of specific microorganisms and improve the removal efficiency of nitrogen. In summary, the immobilization of AAOB and SOB by the gel can achieve effectively mitigate nitrogen pollution in low temperature environments, thus indicating that the SAD/A process has broad engineering application prospects.

Study of a three-dimensional biofilm-electrode reactor (3D-BER) that combined heterotrophic and autotrophic denitrification (HAD) to remove nitrate from water.

A three-dimensional biofilm-electrode reactor (3D-BER) that combined heterotrophic and autotrophic denitrification (HAD) was developed to remove nitrate. The denitrification performance of the 3D-BER was evaluated under different experimental conditions, including current intensities (0-80 mA), COD/N ratios (0.5-5), and hydraulic retention times (2-12 h). The results showed that excessive current limited the nitrate removal efficiency. However, a longer hydraulic retention time was not required to achieve a better denitrification effect in the 3D-BER. Moreover, the nitrate could be effectively reduced over a broad range of COD/Ns (1-2.5), and its removal rate peaked at 89% at I = 40 mA, HRT = 8 h, and COD/N = 2. Although the current reduced the diversity of microorganisms in the system, it promoted the growth of dominant species. Nitrification microorganisms were enriched in the reactor, especially Thauera and Hydrogenophaga, which were crucial to the denitrification process. Thus, the combination of autotrophic denitrification and heterotrophic denitrification was promoted by the 3D-BER system to increase the efficiency of nitrogen removal.

Dual-network polyvinyl alcohol/polyacrylamide/xanthan gum ionic conductive hydrogels for flexible electronic devices.

Ionic conductive hydrogels (ICHs) have received widespread attention as an ideal candidate for flexible electronic devices. However, conventional ICHs failed in widespread applications due to their inability to simultaneously possess high toughness, high ionic conductivity, and anti-freezing properties. Here, polyvinyl alcohol (PVA) and polyacrylamide (PAAm) were first dissolved in the zinc chloride solution, in which zinc ions (Zn2+) act as ionic cross-linkers and conducting ions, followed by the introduction of xanthan gum (XG) with a unique structure of trisaccharide side chains into the PVA/PAAm semi-interpenetrating network to prepare a dual-network ICHs (refers as PPXZ). Enabled by the synergistic effect of intermolecular chemical covalent cross-linking and physical cross-linking, PPXZ hydrogels exhibit significantly improved mechanical properties without sacrificing electrical conductivity. Furthermore, PPXZ hydrogels are successfully applied to flexible electronic devices, such as strain sensors and zinc ion hybrid supercapacitors, exhibiting satisfactory sensing sensitivity and cycling stability at a wide temperature range, respectively. Even at a high current density (10 A g-1), the capacity of the supercapacitor retains 88.24 % after 10,000 cycles. This strategy provides new insight for ICHs in wide temperature-applied flexible electronic devices.

Silmitasertib, a casein kinase 2 inhibitor, induces massive lipid droplet accumulation and nonapoptotic cell death in head and neck cancer cells.

BACKGROUND: Accumulating evidence shows that high expression of casein kinase 2 (CK2) and phosphorylated acetyl CoA carboxylase (pACC) in patients with squamous cell carcinoma of the head and neck (SCCHN) correlates with decreased survival rates. Computational analysis has shown that ACC is a potential substrate for CK2, and its inhibition can suppress ACC phosphorylation in vitro. CX-4945, also known as silmitasertib, is an orally administered, highly specific, ATP-competitive inhibitor of CK2 and is under clinical investigation as a treatment for malignancies. We hypothesize that inhibition of CK2 by CX-4945 can reduce CK2-downstream phosphorylation of ACC as a therapeutic strategy against SCCHN. METHODS: Three aggressive SCCHN cell lines (OSC-19, FaDu and HN31) were cultured to investigate the anticancer mechanism of the CK2 inhibitor, CX-4945. Cell cycle analysis, Annexin V/PI staining, and cleavage of PARP were performed to detect apoptosis. Western blot, electron microscopy and analysis of acidic vesicular organelle development were used to detect autophagy. Interference with cellular metabolism by CX-4945 treatment was determined by Seahorse XF24 Extracellular Flux Analyzer and mass spectrometry. RESULTS: Cellular metabolism was impeded by CX-4945 in aggressive SCCHN cells by Seahorse XF24 Extracellular Flux Analyzer and mass spectrometry, and consequently time- and dose-dependent lipid droplet accumulation and non-apoptotic cell death were observed. The lipogenic enzyme ACC was demonstrated to be associated with CK2, and its repressive phosphorylation could be removed by the CK2 inhibitor CX-4945. Overexpression of ACC resulted in impaired cell survival following transient transfection. CONCLUSION: The findings demonstrate that CK2 inhibition impairs normal cellular energy metabolism and may be an attractive therapy for treating aggressive SCCHN.

Nano-α-Fe2 O3 for enhanced denitrification in a heterotrophic/biofilm-electrode autotrophic denitrification reactor.

In this study, a heterotrophic/biofilm-electrode autotrophic denitrification reactor (HAD-BER) was constructed and nano-ɑ-Fe2 O3 was coated on granular activated carbon (GAC) as a third electrode to enhance the nitrate removal performance. The introduction of nano-ɑ-Fe2 O3 could stimulate microorganisms to secrete more extracellular polymeric substances (EPS), accelerating the electron transfer. Moreover, more denitrification bacteria were enriched on the particle electrodes, especially Pseudomonas and Thermomonas, which played a significant role in denitrification. The denitrification performance at different COD/N ratios (0.65-3.23) and current intensities (0-150 mA) was investigated in depth. When the nitrate concentration of the influent was 60 mg/L, nitrate was almost completely removed at the optimal current intensity (60 mA) and COD/N ratio (1.29). At the same time, there was almost no nitrite (<0.10 mg/L) and ammonia nitrogen (0 mg/L) accumulation in the effluent. This study provided a new direction for the advancement of HAD-BER and accelerated its implementation. PRACTITIONER POINTS: By introducing nano-a-Fe2O3 into HAD-BER, more denitrification bacteria were enriched on the particle electrodes. The increased contents of polysaccharide and protein content could accelerate the electron transfer. Almost completely denitrification could be achieved at current = 60 mA and COD/N = 1.29. The study provided a new direction for the further development of HAD-BERs.

Impact of Defects for AlN Single Crystal Thin Film by Metal Nitride Vapor Phase Epitaxy.

Herein, the defect-related properties of an AlN sample prepared based on the optimal process parameters by metal nitride vapor phase epitaxy (MNVPE) were investigated. The FWHM values of the (0002)/(101̅2) planes of the sample by MNVPE are 397/422 arcsec; the advantages of similar FWHM values of (0002) and (101̅2) planes will have a huge advantage over other preparation methods such as MOCVD. From the cross-sectional TEM images of the AlN sample, it is found that the fusion of a large number of a + c type dislocations occur at the interface of the low temperature buffer layer and the epitaxial layer, which affects the growth mode of the epitaxial layer. The lower FHWM value of the E 2(high) peak of the Raman spectrum, the lower the point defect concentration, which made the sample gain higher energy defect emission bands in the PL spectra and higher transmittance in the UV-vis transmission spectrum.

Classification and Prognosis Analysis of Pancreatic Cancer Based on DNA Methylation Profile and Clinical Information.

Pancreatic adenocarcinoma (PAAD) has a poor prognosis with high individual variation in the treatment response among patients; however, there is no standard molecular typing method for PAAD prognosis in clinical practice. We analyzed DNA methylation data from The Cancer Genome Atlas database, which identified 1235 differentially methylated DNA genes between PAAD and adjacent tissue samples. Among these, 78 methylation markers independently affecting PAAD prognosis were identified after adjusting for significant clinical factors. Based on these genes, two subtypes of PAAD were identified through consistent clustering. Fourteen specifically methylated genes were further identified to be associated with survival. Further analyses of the transcriptome data identified 301 differentially expressed cancer driver genes between the two PAAD subtypes and the degree of immune cell infiltration differed significantly between the subtypes. The 14 specific genes characterizing the unique methylation patterns of the subtypes were used to construct a Bayesian network-based prognostic prediction model for typing that showed good predictive value (area under the curve value of 0.937). This study provides new insight into the heterogeneity of pancreatic tumors from an epigenetic perspective, offering new strategies and targets for personalized treatment plan evaluation and precision medicine for patients with PAAD.

Structure and Optical Properties of AlN Crystals Grown by Metal Nitride Vapor Phase Epitaxy with Different V/III Ratios.

The epitaxial aluminum nitride (AlN) crystals were grown on c-plane sapphire using high-temperature metal nitride vapor phase epitaxy at the source materials' different molar flow ratios (V/III ratios). The effects of various V/III ratios on the surface morphology, crystalline quality, material straining, and optical properties of heteroepitaxial AlN thin films were studied using X-ray diffraction, scanning electron microscopy, Raman spectroscopy, and photoluminescence (PL). With the increase in the V/III ratio from 1473 to 7367, the substrate surface underwent changes that vary from whiskers to three-dimensional island structures, two-dimensional layered stack structures, and stacked sheet structures. Additionally, due to the presence of nanoscale pits on the substrate surface, almost all samples were tensile stressers. The PL spectra demonstrated the defect luminescence of the epitaxial films, indicating that nitrogen vacancies and oxygen impurities were the samples' main defects.

Morphogenesis, Growth Cycle and Molecular Regulation of Hair Follicles.

As one of the main appendages of skin, hair follicles play an important role in the process of skin regeneration. Hair follicle is a tiny organ formed by the interaction between epidermis and dermis, which has complex and fine structure and periodic growth characteristics. The hair growth cycle is divided into three continuous stages, growth (anagen), apoptosis-driven regression (catagen) and relative quiescence (telogen). And The Morphogenesis and cycle of hair follicles are regulated by a variety of signal pathways. When the signal molecules in the pathways are abnormal, it will affect the development and cycle of hair follicles, which will lead to hair follicle-related diseases.This article will review the structure, development, cycle and molecular regulation of hair follicles, in order to provide new ideas for solving diseases and forming functional hair follicle.

Identification of pan-kinase-family inhibitors using graph convolutional networks to reveal family-sensitive pre-moieties.

BACKGROUND: Human protein kinases, the key players in phosphoryl signal transduction, have been actively investigated as drug targets for complex diseases such as cancer, immune disorders, and Alzheimer's disease, with more than 60 successful drugs developed in the past 30 years. However, many of these single-kinase inhibitors show low efficacy and drug resistance has become an issue. Owing to the occurrence of highly conserved catalytic sites and shared signaling pathways within a kinase family, multi-target kinase inhibitors have attracted attention. RESULTS: To design and identify such pan-kinase family inhibitors (PKFIs), we proposed PKFI sets for eight families using 200,000 experimental bioactivity data points and applied a graph convolutional network (GCN) to build classification models. Furthermore, we identified and extracted family-sensitive (only present in a family) pre-moieties (parts of complete moieties) by utilizing a visualized explanation (i.e., where the model focuses on each input) method for deep learning, gradient-weighted class activation mapping (Grad-CAM). CONCLUSIONS: This study is the first to propose the PKFI sets, and our results point out and validate the power of GCN models in understanding the pre-moieties of PKFIs within and across different kinase families. Moreover, we highlight the discoverability of family-sensitive pre-moieties in PKFI identification and drug design.

Therapeutic Effects of Synthetic Triblock Amphiphilic Short Antimicrobial Peptides on Human Lung Adenocarcinoma.

Because of their unique properties, antimicrobial peptides (AMPs) represent a potential reservoir of novel anticancer therapeutic agents. However, only a few AMPs can kill tumors with high efficiency, and obtaining inexpensive anticancer AMPs with strong activity is still a challenge. In our previous work, a series of original short amphiphilic triblock AMP (KnFmKn) analogues were developed which were demonstrated to exert excellent effects on bacterial infection, both in vitro and in vivo. Herein, the overall objectives were to assess the potent tumoricidal capacities of these analogues against human lung cancer cell line A549 and the underlying mechanism. The results of the CCK-8 assay revealed that the precise modification of the peptides' primary sequences could modulate their tumoricidal potency. In the tumoricidal progress, positive charge and hydrophobicity were the key driving forces. Among these peptides, K4F6K4 displayed the most remarkable tumoricidal activity. Furthermore, the excellent anticancer capacity of K4F6K4 was proven by the live/dead cell staining, colony formation assay, and tumor growth observations on xenografted mice, which indicated that K4F6K4 might be a promising drug candidate for lung cancer, with no significant adverse effects in vitro or in vivo. In addition, the cell apoptosis assay using flow cytometry, the morphology observations using the optical microscope, confocal microscopy using CellMask™ Deep Red staining, and scanning electron microscope suggested that membrane disruption was the primary mechanism of its antitumor action. Through analyzing the structure-activity relationship, it was found that the amount of positive charge required for KnFmKn to exert its optimal tumoricidal effect was more than that needed for the antimicrobial activity, while the optimal proportion of hydrophobicity was less. Our findings suggest that further analysis of the structure-activity relationship of AMPs' primary sequence variations will be beneficial. Hopefully, this work can provide guiding principles in designing peptide-based therapeutics for lung cancer.

Discovery of moiety preference by Shapley value in protein kinase family using random forest models.

BACKGROUND: Human protein kinases play important roles in cancers, are highly co-regulated by kinase families rather than a single kinase, and complementarily regulate signaling pathways. Even though there are > 100,000 protein kinase inhibitors, only 67 kinase drugs are currently approved by the Food and Drug Administration (FDA). RESULTS: In this study, we used "merged moiety-based interpretable features (MMIFs)," which merged four moiety-based compound features, including Checkmol fingerprint, PubChem fingerprint, rings in drugs, and in-house moieties as the input features for building random forest (RF) models. By using > 200,000 bioactivity test data, we classified inhibitors as kinase family inhibitors or non-inhibitors in the machine learning. The results showed that our RF models achieved good accuracy (> 0.8) for the 10 kinase families. In addition, we found kinase common and specific moieties across families using the Shapley Additive exPlanations (SHAP) approach. We also verified our results using protein kinase complex structures containing important interactions of the hinges, DFGs, or P-loops in the ATP pocket of active sites. CONCLUSIONS: In summary, we not only constructed highly accurate prediction models for predicting inhibitors of kinase families but also discovered common and specific inhibitor moieties between different kinase families, providing new opportunities for designing protein kinase inhibitors.

BYPASS1-LIKE regulates lateral root initiation via exocytic vesicular trafficking-mediated PIN recycling in Arabidopsis.

Auxin and auxin-mediated signaling pathways are known to regulate lateral root development. Although exocytic vesicle trafficking plays an important role in recycling the PIN-FORMED (PIN) auxin efflux carriers and in polar auxin transport during lateral root formation, the mechanistic details of these processes are not well understood. Here, we demonstrate that BYPASS1-LIKE (B1L) regulates lateral root initiation via exocytic vesicular trafficking-mediated PIN recycling in Arabidopsis thaliana. b1l mutants contained significantly more lateral roots than the wild type, primarily due to increased lateral root primordium initiation. Furthermore, the auxin signal was stronger in stage I lateral root primordia of b1l than in those of the wild type. Treatment with exogenous auxin and an auxin transport inhibitor indicated that the lateral root phenotype of b1l could be attributed to higher auxin levels and that B1L regulates auxin efflux. Indeed, compared to the wild type, C-terminally green fluorescent protein-tagged PIN1 and PIN3 accumulated at higher levels in b1l lateral root primordia. B1L interacted with the exocyst, and b1l showed defective PIN exocytosis. These observations indicate that B1L interacts with the exocyst to regulate PIN-mediated polar auxin transport and lateral root initiation in Arabidopsis.

Concurrent Treatment with Vitamin K2 and D3 on Spine Fusion in Patients with Osteoporosis-Associated Lumbar Degenerative Disorders.

STUDY DESIGN: A prospective and nonrandomized concurrent controlled trial. OBJECTIVE: To address the early effects of concurrent treatment with vitamin K2 and vitamin D3 on fusion rates in patients who have undergone spinal surgery. SUMMARY OF BACKGROUND DATA: Intervertebral pseudarthrosis has been reported after transforaminal lumbar interbody fusion (TLIF) or posterior lumbar interbody fusion (PLIF), especially in patients with osteopenia or osteoporosis. No study has assessed the early effects of concurrent treatment with vitamin K2 and vitamin D3 on fusion rates. METHODS: Patients with osteopenia or osteoporosis who underwent TLIF or PLIF in our department were included. Patients in the VK2+VD3 group received vitamin K2, vitamin D3, and calcium treatment, whereas subjects in the control group only received calcium and vitamin D3. Spine fusion was evaluated by computed tomography. The Japanese Orthopedic Association Back Pain Evaluation Questionnaire (JOA-BPEQ) and visual analog scale (VAS) were used to assess the clinical and neurological symptoms. Bone mineral density (BMD) and bone metabolism markers were measured for osteoporotic evaluation. RESULTS: Seventy-eight patients were included, and nine patients subsequently discontinued because of 2019-nCoV. At six months postoperatively, complete fusion rates were significantly higher in the VK2+VD3 group than that in the control group (91.18% vs 71.43%, P = 0.036). At six months postoperatively, BMD was increased in the VK2+VD3 group and was higher than that in the control group, although there was no significant difference. At three months postoperatively, a significant increase in procollagen type I amino terminal propeptide (91.81%) and a slight decrease in C-terminal end peptide (8.06%) were observed in the VK2+VD3 group. In both groups, the JOA-BPEQ and VAS scores were significantly improved after spine surgery. CONCLUSION: Administration of vitamin K2 and vitamin D3 can increase lumbar interbody fusion rates, improve clinical symptoms, promote bone information, and avoid further decline in BMD within six months after TLIF or PLIF.Level of Evidence: 3.

Convolutional neural network for human cancer types prediction by integrating protein interaction networks and omics data.

Many studies have proven the power of gene expression profile in cancer identification, however, the explosive growth of genomics data increasing needs of tools for cancer diagnosis and prognosis in high accuracy and short times. Here, we collected 6136 human samples from 11 cancer types, and integrated their gene expression profiles and protein-protein interaction (PPI) network to generate 2D images with spectral clustering method. To predict normal samples and 11 cancer tumor types, the images of these 6136 human cancer network were separated into training and validation dataset to develop convolutional neural network (CNN). Our model showed 97.4% and 95.4% accuracies in identification of normal versus tumors and 11 cancer types, respectively. We also provided the results that tumors located in neighboring tissues or in the same cell types, would induce machine make error classification due to the similar gene expression profiles. Furthermore, we observed some patients may exhibit better prognosis if their tumors often misjudged into normal samples. As far as we know, we are the first to generate thousands of cancer networks to predict and classify multiple cancer types with CNN architecture. We believe that our model not only can be applied to cancer diagnosis and prognosis, but also promote the discovery of multiple cancer biomarkers.