Prim-O-glucosylcimifugin ameliorates aging-impaired endogenous tendon regeneration by rejuvenating senescent tendon stem/progenitor cells.

Adult tendon stem/progenitor cells (TSPCs) are essential for tendon maintenance, regeneration, and repair, yet they become susceptible to senescence with age, impairing the self-healing capacity of tendons. In this study, we employ a recently developed deep-learning-based efficacy prediction system to screen potential stemness-promoting and senescence-inhibiting drugs from natural products using the transcriptional signatures of stemness. The top-ranked candidate, prim-O-glucosylcimifugin (POG), a saposhnikovia root extract, could ameliorate TPSC senescent phenotypes caused by long-term passage and natural aging in rats and humans, as well as restore the self-renewal and proliferative capacities and tenogenic potential of aged TSPCs. In vivo, the systematic administration of POG or the local delivery of POG nanoparticles functionally rescued endogenous tendon regeneration and repair in aged rats to levels similar to those of normal animals. Mechanistically, POG protects TSPCs against functional impairment during both passage-induced and natural aging by simultaneously suppressing nuclear factor-κB and decreasing mTOR signaling with the induction of autophagy. Thus, the strategy of pharmacological intervention with the deep learning-predicted compound POG could rejuvenate aged TSPCs and improve the regenerative capacity of aged tendons.

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma.

Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

Barium-induced toxic anterior segment syndrome.

Toxic anterior segment syndrome (TASS) is a rapid-onset inflammation of the eye following uneventful ocular surgery. We report a case of TASS following Baerveldt glaucoma implant (BGI) surgery. Inductively coupled plasma-mass spectrometry (ICP-MS) identified barium in the eye and in the eluate from the bleb of the BGI. We attribute TASS in our patient to the dissolution of barium from the BGI and its entry into the eye, where it causes severe inflammation.

Multiple machine learning methods aided virtual screening of NaV 1.5 inhibitors.

Nav 1.5 sodium channels contribute to the generation of the rapid upstroke of the myocardial action potential and thereby play a central role in the excitability of myocardial cells. At present, the patch clamp method is the gold standard for ion channel inhibitor screening. However, this method has disadvantages such as high technical difficulty, high cost and low speed. In this study, novel machine learning models to screen chemical blockers were developed to overcome the above shortage. The data from the ChEMBL Database were employed to establish the machine learning models. Firstly, six molecular fingerprints together with five machine learning algorithms were used to develop 30 classification models to predict effective inhibitors. A validation and a test set were used to evaluate the performance of the models. Subsequently, the privileged substructures tightly associated with the inhibition of the Nav 1.5 ion channel were extracted using the bioalerts Python package. In the validation set, the RF-Graph model performed best. Similarly, RF-Graph produced the best result in the test set in which the Prediction Accuracy (Q) was 0.9309 and Matthew's correlation coefficient was 0.8627, further indicating the model had high classification ability. The results of the privileged substructures indicated Sulfa structures and fragments with large Steric hindrance tend to block Nav 1.5. In the unsupervised learning task of identifying sulfa drugs, MACCS and Graph fingerprints had good results. In summary, effective machine learning models have been constructed which help to screen potential inhibitors of the Nav 1.5 ion channel and key privileged substructures with high affinity were also extracted.

Halomonas spp., as chassis for low-cost production of chemicals.

Halomonas spp. are the well-studied platform organisms or chassis for next-generation industrial biotechnology (NGIB) due to their contamination-resistant nature combined with their fast growth property. Several Halomonas spp. have been studied regarding their genomic information and molecular engineering approaches. Halomonas spp., especially Halomonas bluephagenesis, have been engineered to produce various biopolyesters such as polyhydroxyalkanoates (PHA), proteins including surfactants and enzymes, small molecular compounds including amino acids and derivates, as well as organic acids. This paper reviews all the progress reported in the last 10 years regarding this robust microbial cell factory. KEY POINTS: • Halomonas spp. are robust chassis for low-cost production of chemicals • Genomic information of some Halomonas spp. has been revealed • Molecular tools and approaches for Halomonas spp. have been developed • Halomonas spp. are becoming more and more important for biotechnology.

Robust prognostic model based on immune infiltration-related genes and clinical information in ovarian cancer.

Immune infiltration of ovarian cancer (OV) is a critical factor in determining patient's prognosis. Using data from TCGA and GTEx database combined with WGCNA and ESTIMATE methods, 46 genes related to OV occurrence and immune infiltration were identified. Lasso and multivariate Cox regression were applied to define a prognostic score (IGCI score) based on 3 immune genes and 3 types of clinical information. The IGCI score has been verified by K-M curves, ROC curves and C-index on test set. In test set, IGCI score (C-index = 0.630) is significantly better than AJCC stage (C-index = 0.541, p < 0.05) and CIN25 (C-index = 0.571, p < 0.05). In addition, we identified key mutations to analyse prognosis of patients and the process related to immunity. Chi-squared tests revealed that 6 mutations are significantly (p < 0.05) related to immune infiltration: BRCA1, ZNF462, VWF, RBAK, RB1 and ADGRV1. According to mutation survival analysis, we found 5 key mutations significantly related to patient prognosis (p < 0.05): CSMD3, FLG2, HMCN1, TOP2A and TRRAP. RB1 and CSMD3 mutations had small p-value (p < 0.1) in both chi-squared tests and survival analysis. The drug sensitivity analysis of key mutation showed when RB1 mutation occurs, the efficacy of six anti-tumour drugs has changed significantly (p < 0.05).

Microchemical Engineering in a 3D Ordered Channel Enhances Electrocatalysis.

The kinetics of electrode reactions including mass transfer and surface reaction is essential in electrocatalysis, as it strongly determines the apparent reaction rates, especially on nanostructured electrocatalysts. However, important challenges still remain in optimizing the kinetics of given catalysts with suitable constituents, morphology, and crystalline design to maximize the electrocatalytic performances. We propose a comprehensive kinetic model coupling mass transfer and surface reaction on the nanocatalyst-modified electrode surface to explore and shed light on the kinetic optimization in electrocatalysis. Moreover, a theory-guided microchemical engineering (MCE) strategy has been demonstrated to rationally redesign the catalysts with optimized kinetics. Experimental measurements for methanol oxidation reaction in a 3D ordered channel with tunable channel sizes confirm the calculation prediction. Under the optimized channel size, mass transfer and surface reaction in the channeled microreactor are both well regulated. This MCE strategy will bring about a significant leap forward in structured catalyst design and kinetic modulation.

Prognostic model of patients with liver cancer based on tumor stem cell content and immune process.

Globally, liver hepatocellular carcinoma (LIHC) has a high mortality and recurrence rate, leading to poor prognosis. The recurrence of LIHC is closely related to two aspects: degree of immune infiltration and content of tumor stem cells. Hence, this study aimed to used RNA-seq and clinical data of LIHC from The Cancer Genome Atlas, Estimation of Stromal and Immune cells in Malignant Tumours, mRNA stemness index score, and weighted gene correlation network analysis methods to find genes significantly linked to the aforementioned two aspects. Key genes and clinical factors were used as input. Lasso regression and multivariate Cox regression were conducted to build an effective prognostic model for patients with liver cancer. Finally, four key genes (KLHL30, PLN, LYVE1, and TIMD4) and four clinical factors (Asian, age, grade, and bilirubin) were included in the prognostic model, namely Immunity and Cancer-stem-cell Related Prognosis (ICRP) score. The ICRP score achieved a great performance in test set. The area under the curve value of the ICRP score in test set for 1, 3, and 5 years was 0.708, 0.723, and 0.765, respectively, which was better than that of other prognostic prediction methods for LIHC. The C-index evaluation method also reached the same conclusion.

Prediction and Optimization of NaV1.7 Sodium Channel Inhibitors Based on Machine Learning and Simulated Annealing.

Although the NaV1.7 sodium channel is a promising drug target for pain, traditional screening strategies for discovery of NaV1.7 inhibitors are very painstaking and time-consuming. Herein, we aimed to build machine learning models for screening and design of potent and effective NaV1.7 sodium channel inhibitors. We customized the imbalanced data set from ChEMBL and BindingDB to train and filter the best classification model. Then, the whole-cell voltage-clamp was employed to validate the inhibitors. We assembled a molecular group optimization method by combining the Grammar Variational Autoencoder, classification model, and simulated annealing. We found that the RF-CDK model (random forest + CDK fingerprint) performs best in the imbalanced data set. Of the three compounds that may have inhibitory effects, nortriptyline has been experimentally verified. In the molecule optimization process, 40 molecules located in the applicability domain of RF-CDK were used as a starting point, among which 34 molecules evolved to molecules with greater molecular scores (MS). The molecule with the highest MS was derived from CHEMBL2325245. The model and method we developed for NaV1.7 inhibitors are also applicable to other targets.

L1CAM mutations in three fetuses diagnosed by medical exome sequencing.

OBJECTIVE: The L1 cell adhesion molecule (L1CAM) gene, encodes the L1 cell adhesion molecule, is involved in the central nervous system development. Its mutations result in L1 syndrome which is associated with brain malformation and nervous developmental delay. CASE REPORT: We presented three fetuses with hydrocephalus and agenesis of the corpus callosum detected by ultrasound, followed by medical exome sequencing (MES) test with L1CAM mutations: two known missense mutation c.551G > A (p. R184Q) and c.1354G > A (p. G452R), and a novel frameshift mutation c.1322delG which causes the early termination of translation (p. G441Afs∗72). By utilizing multiple computational analysis, all the variants were scored to be likely pathogenic. CONCLUSION: Combined use of ultrasound and MES to identify the molecular etiology of fetal anomalies may contribute to expanding our knowledge of the clinical phenotype of L1 syndrome observed in the south Chinese population.

Radial Nanowire Assemblies under Rotating Magnetic Field Enabled Efficient Charge Separation.

Developing efficient charge separation strategies is essential to achieve high-power conversion efficiency in the fields of chemistry, biology, and material science. Herein, we develop a facile strategy for fabrication of unique wafer-scale radial nanowire assemblies by exploiting shear force in rotary solution. The assembly mechanism can be well revealed by the large-scale stochastic dynamics simulation. Free electrons can be rapidly generated to produce quantitatively tunable current output when the radial nanowire assemblies rotate under the magnetic field. Moreover, the photoconductive performance of the radial semiconductor nanowire assemblies can be remarkably enhanced as the electron-hole recombination was retrained by the efficient charge separation under the rotating magnetic field. Such large-scale unique nanowire assemblies will facilitate the design of an efficient charge separation process in biosystem, sensors, and photocatalysis.

Mass Production of Nanowire-Nylon Flexible Transparent Smart Windows for PM2.5 Capture.

Designing large-area flexible transparent smart windows for high-efficiency indoor fine particulate matter (PM2.5) capture is important to guarantee safe indoor environments. In this article, we demonstrate that large-area fabrication of flexible transparent Ag-nylon mesh can be performed not only to turn the indoor light illumination intensity as thermochromic smart windows after uniformly coating with thermochromic dye but also to purify indoor air as high-efficiency PM2.5 filter. It takes only about $15.03 and 20 min to fabricate 7.5-m2 Ag-nylon flexible transparent windows without any modification with a sheet resistance of as low as 8.87 Ω sq-1 and optical transmittance of 86.05%. As an excellent PM filter (can be recycled after PM filtration), the removal efficiency is as high as 99.65% and the processing speed is high, which can reduce the PM2.5 density from heavily polluted (248 µg·m-3, purple alert) to good (32.9 µg·m-3, green statement) in 50 s.

Ultrathin Tungsten Oxide Nanowires/Reduced Graphene Oxide Composites for Toluene Sensing.

Graphene-based composites have gained great attention in the field of gas sensor fabrication due to their higher surface area with additional functional groups. Decorating one-dimensional (1D) semiconductor nanomaterials on graphene also show potential benefits in gas sensing applications. Here we demonstrate the one-pot and low cost synthesis of W18O49 NWs/rGO composites with different amount of reduced graphene oxide (rGO) which show excellent gas-sensing properties towards toluene and strong dependence on their chemical composition. As compared to pure W18O49 NWs, an improved gas sensing response (2.8 times higher) was achieved in case of W18O49 NWs composite with 0.5 wt. % rGO. Promisingly, this strategy can be extended to prepare other nanowire based composites with excellent gas-sensing performance.

Manipulating nanowire assembly for flexible transparent electrodes.

Manipulating nanowire assembly could help the design of hierarchical structures with unique functionalities. Herein, we first report a facile solution-based process under ambient conditions for co-assembling two kinds of nanowires which have suitable composition and functionalities, such as Ag and Te nanowires, for the fabrication of flexible transparent electrodes. Then Te nanowires can be etched away easily, leaving Ag nanowire networks with controllable pitch. By manipulating the assembly of Ag and Te nanowires, we can precisely tailor and balance the optical transmittance and the conductivity of the resulting flexible transparent electrodes. The network of Ag nanowires which have tunable pitch forms a flexible transparent conducting electrode with an averaged transmission of up to 97.3 % and sheet resistances as low as 2.7 Ω/sq under optimized conditions. The work provides a new way for tailoring the properties of nanowire-based devices.

Ultrathin hetero-nanowire-based flexible electronics with tunable conductivity.

Flexible hetero-nanowire electronics: A simple solution process has been developed for the first time to fabricate macroscopic flexible, ordered Au-Te hetero-nanowire film electronics with tunable resistance from MΩ to Ω at room temperature (see the Figure). Nanowire films with an electrical conductivity as low as 10,000 S cm(-1) and a sheet resistance of 15Ω sq(-1) can generate reliable interconnections for light-emitting diode (LED) arrays. The Au-Te hetero-nanowire films remain conductive after bending 6000 times with a maximum bending radius of 2.0 mm without any obvious degradation.

Ordering Ag nanowire arrays by a glass capillary: a portable, reusable and durable SERS substrate.

Assembly of nanowires into ordered macroscopic structures with new functionalities has been a recent focus. In this Letter, we report a new route for ordering hydrophilic Ag nanowires with high aspect ratio by flowing through a glass capillary. The present glass capillary with well-defined silver nanowire films inside can serve as a portable and reusable substrate for surface-enhanced Raman spectroscopy (SERS), which may provide a versatile and promising platform for detecting mixture pollutions. By controlling the flow parameters of nanowire suspensions, initially random Ag nanowires can be aligned to form nanowire arrays with tunable density, forming cambered nanowire films adhered onto the inner wall of the capillary. Compared with the planar ordered Ag nanowire films by the Langmuir-Blodgett (LB) technique, the cambered nanowire films show better SERS performance.