Identifying the kind behind SMILES-anatomical therapeutic chemical classification using structure-only representations.

Anatomical Therapeutic Chemical (ATC) classification for compounds/drugs plays an important role in drug development and basic research. However, previous methods depend on interactions extracted from STITCH dataset which may make it depend on lab experiments. We present a pilot study to explore the possibility of conducting the ATC prediction solely based on the molecular structures. The motivation is to eliminate the reliance on the costly lab experiments so that the characteristics of a drug can be pre-assessed for better decision-making and effort-saving before the actual development. To this end, we construct a new benchmark consisting of 4545 compounds which is with larger scale than the one used in previous study. A light-weight prediction model is proposed. The model is with better explainability in the sense that it is consists of a straightforward tokenization that extracts and embeds statistically and physicochemically meaningful tokens, and a deep network backed by a set of pyramid kernels to capture multi-resolution chemical structural characteristics. Its efficacy has been validated in the experiments where it outperforms the state-of-the-art methods by 15.53% in accuracy and by 69.66% in terms of efficiency. We make the benchmark dataset, source code and web server open to ease the reproduction of this study.

Monolithic PMN-39PT nanograting-assisted second harmonic generation enhancement.

Second harmonic generation plays a vital role in frequency conversion which mutually promotes the laser technology and allows the wavebands extension of new coherent source. The monolithic crystals are supposed to be a superior choice for harmonic generation due to long interaction distance, however, the phase-mismatch brought a sharp reduction in the conversion efficiency. Although birefringent phase-matching and quasi-phase-matching techniques are commonly utilized to fill the phase gap in monolithic crystals, these techniques are limited by the natural refractive index of crystal and the domain engineering, respectively. In recent years, subwavelength structures evolve as a flexible scheme to realize phase matching by engineering the geometry features of crystals. Here, structured nanogratings are designed and fabricated on a monolithic PMN-39PT (Pb(Mg1/3Nb2/3)O3-0.39PbTiO3) substrate, a novel ferroelectric crystal with promising optical prospect, for enhancing second harmonic generation, where birefringent or quasi phase-matching is hard to achieve. The nanograting-assisted second harmonic generation enhancement is observed which is not limited by the availability of thin crystalline films. Meanwhile, a boost in the second harmonic signal synchronously promotes the cascading third harmonic generation. This method may provide an alternative solution for enhanced harmonic generation on monolithic substrates and develop potential nonlinear optical materials for frequency conversion.

Flexophotovoltaic Effect and Above-Band-Gap Photovoltage Induced by Strain Gradients in Halide Perovskites.

We have measured the flexophotovoltaic effect of single crystals of halide perovskites MAPbBr_{3} and MAPbI_{3}, as well as the benchmark oxide perovskite SrTiO_{3}. For halide perovskites, the flexophotovoltaic effect is found to be orders of magnitude larger than for SrTiO_{3}, and indeed large enough to induce photovoltages bigger than the band gap. Moreover, we find that in MAPbI_{3} the flexophotovoltaic effect is additional to a native bulk photovoltaic response that is switchable and ferroelectric-like. The results suggest that strain gradient engineering can be a powerful tool to modify the photovoltaic output even in already well-established photovoltaic materials.

Irreversible repolarization of tumour-associated macrophages by low-Pi stress inhibits the progression of hepatocellular carcinoma.

Numerous studies have shown the positive correlation between high levels of Pi and tumour progression. A critical goal of macrophage-based cancer therapeutics is to reduce anti-inflammatory macrophages (M2) and increase proinflammatory antitumour macrophages (M1). This study aimed to investigate the relationship between macrophage polarization and low-Pi stress. First, the spatial populations of M2 and M1 macrophages in 22 HCC patient specimens were quantified and correlated with the local Pi concentration. The levels of M2 and M1 macrophage markers expressed in the peritumour area were higher than the intratumour levels, and the expression of M2 markers was positively correlated with Pi concentration. Next, monocytes differentiated from THP-1 cells were polarized against different Pi concentrations to investigate the activation or silencing of the expression of p65, IκB-α and STAT3 as well as their phosphorylation. Results showed that low-Pi stress irreversibly repolarizes tumour-associated macrophages (TAMs) towards the M1 phenotype by silencing stat6 and activating p65. Moreover, HepG-2 and SMCC-7721 cells were cultured in conditioned medium to investigate the innate anticancer immune effects on tumour progression. Both cancer cell lines showed reduced proliferation, migration and invasion, as epithelial-mesenchymal transition (EMT) was inactivated. In vivo therapeutic effect on the innate and adaptive immune processes was validated in a subcutaneous liver cancer model by the intratumoural injection of sevelamer. Tumour growth was significantly inhibited by the partial deprivation of intratumoural Pi as the tumour microenvironment under low-Pi stress is more immunostimulatory. The anticancer immune response, activated by low-Pi stress, suggests a new macrophage-based immunotherapeutic modality.

MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph.

Accurate identification of the miRNA-disease associations (MDAs) helps to understand the etiology and mechanisms of various diseases. However, the experimental methods are costly and time-consuming. Thus, it is urgent to develop computational methods towards the prediction of MDAs. Based on the graph theory, the MDA prediction is regarded as a node classification task in the present study. To solve this task, we propose a novel method MDA-GCNFTG, which predicts MDAs based on Graph Convolutional Networks (GCNs) via graph sampling through the Feature and Topology Graph to improve the training efficiency and accuracy. This method models both the potential connections of feature space and the structural relationships of MDA data. The nodes of the graphs are represented by the disease semantic similarity, miRNA functional similarity and Gaussian interaction profile kernel similarity. Moreover, we considered six tasks simultaneously on the MDA prediction problem at the first time, which ensure that under both balanced and unbalanced sample distribution, MDA-GCNFTG can predict not only new MDAs but also new diseases without known related miRNAs and new miRNAs without known related diseases. The results of 5-fold cross-validation show that the MDA-GCNFTG method has achieved satisfactory performance on all six tasks and is significantly superior to the classic machine learning methods and the state-of-the-art MDA prediction methods. Moreover, the effectiveness of GCNs via the graph sampling strategy and the feature and topology graph in MDA-GCNFTG has also been demonstrated. More importantly, case studies for two diseases and three miRNAs are conducted and achieved satisfactory performance.

Temperature phase transitions in silver niobate and lithium tantalate-modified silver niobate ceramics.

The temperature behaviour of 0.955 AgNbO3-0.045 LiTaO3 and AgNbO3 ceramics was studied in the range from 10 to 415 K using Raman spectroscopy. Ab initio calculations of the Raman spectra in the Pmc21 phase of AgNbO3 were carried out using three potentials (A-PZ, PBE, and PBEsol) for spectral interpretation. The peculiarities in the Raman spectra in AgNbO3 ceramics are observed and explained. The differences in the spectra of the 0.955 AgNbO3-0.045 LiTaO3 and AgNbO3 ceramics are shown. The temperatures of the structural changes in the 0.955 AgNbO3-0.45 LiTaO3 and AgNbO3 ceramics were discussed. A structural phase transition below 120 K was observed in silver niobate. A phase transition was observed at 310 K and below 150 K in 0.955 AgNbO3-0.045 LiTaO3.

Machine learning algorithms for integrating clinical features to predict intracranial hemorrhage in patients with acute leukemia.

BACKGROUND: Intracranial hemorrhage (ICH) in acute leukemia (AL) patients leads to high morbidity and mortality, treatment approaches for ICH are generally ineffective. Thus, early identification of which subjects are at high risk of ICH is of key importance. Currently, machine learning can achieve well predictive capability through constructing algorithms that simultaneously exploit the information coming from clinical features. METHODS: After rigid data preprocessing, 42 different clinical features from 948 AL patients were used to train different machine learning algorithms. We used the feature selection algorithms to select the top 10 features from 42 clinical features. To test the performance of the machine learning algorithms, we calculated area under the curve (AUC) values from receiver operating characteristic (ROC) curves along with 95% confidence intervals (CIs) by cross-validation. RESULTS: With the 42 features, RF exhibited the best predictive power. After feature selection, the top 10 features were international normalized ratio (INR), prothrombin time (PT), creatinine (Cr), indirect bilirubin (IBIL), albumin (ALB), monocyte (MONO), platelet (PLT), lactic dehydrogenase (LDH), fibrinogen (FIB) and prealbumin (PA). Among the top 10 features, INR, PT, Cr, IBIL and ALB had high predictive performance with an AUC higher than 0.8 respectively. CONCLUSIONS: The RF algorithm exhibited a higher cross-validated performance compared with the classical algorithms, and the selected important risk features should help in individualizing aggressive treatment in AL patients to prevent ICH. Efforts that will be made to test and optimize in independent samples will warrant the application of such algorithm and predictors in the future.

[Mechanism of gigantol in transmembrane transport in human lens epithelial cells].

Gigantol is a phenolic component of precious Chinese medicine Dendrobii Caulis, which has many pharmacological activities such as prevent tumor and diabetic cataract. This paper aimed to investigate the molecular mechanism of gigantol in transmembrane transport in human lens epithelial cells(HLECs). Immortalized HLECs were cultured in vitro and inoculated in the laser scanning confocal microscopy(LSCM) medium at 5 000 cells/mL. The fluorescence distribution and intensity of gigantol marked by fluorescence in HLECs were observed by LSCM, and the absorption and distribution of gigantol were expressed as fluorescence intensity. The transmembrane transport process of gigantol in HLECs were monitored. The effects of time, temperature, concentration, transport inhibitors, and different cell lines on the transmembrane absorption and transport of gigantol were compared. HLECs were inoculated on climbing plates of 6-well culture plates, and the ultrastructure of HLECs was detected by atomic force microscopy(AFM) during the transmembrane absorption of non-fluorescent labeled gigantol. The results showed that the transmembrane absorption of gigantol was in time and concentration-dependent manners, which was also able to specifically target HLECs. Energy and carrier transport inhibitors reduced gigantol absorption by HLECs. During transmembrane process of gigantol, the membrane surface of HLECs became rougher and presented different degrees of pits, indicating that the transmembrane transport of gigantol was achieved by active absorption of energy and carrier-mediated endocytosis.

Quasi-phase matched second harmonic generation in a PMN-38PT crystal.

We used an all-optical poling method to fabricate quadratic nonlinearity gratings in a tetragonal 0.62Pb(Mg1/3Nb2/3)O3-0.38PbTiO3 (PMN-38PT) crystal. We then employed these gratings in quasi-phase matched collinear second harmonic generation processes. By measuring the second harmonic output, we provided, for the first time, to the best of our knowledge, quantitative estimates of all three non-zero quadratic nonlinearity coefficients of the PMN-38PT crystal.

Augmented reality for stroke rehabilitation during COVID-19.

BACKGROUND: The lack of the rehabilitation professionals is a global issue and it is becoming more serious during COVID-19. An Augmented Reality Rehabilitation System (AR Rehab) was developed for virtual training delivery. The virtual training was integrated into the participants' usual care to reduce the human trainers' effort so that the manpower scarcity can be eased. This also resulted in the reduction of the contact rate in pandemics. OBJECTIVE: To investigate the feasibility of the AR Rehab-based virtual training when integrated into the usual care in a real-world pandemic setting, by answering questions of whether the integrated trials can help fulfill the training goal and whether the trials can be delivered when resources are limited because of COVID-19. METHODS: Chronic stroke participants were randomly assigned to either a centre-based group (AR-Centre) or a home-based group (AR-Home) for a trial consisting of 20 sessions delivered in a human-machine integrated intervention. The trial of the AR-Centre was human training intensive with 3/4 of each session delivered by human trainers (PTs/OTs/Assistants) and 1/4 delivered by the virtual trainer (AR Rehab). The trial of the AR-Home was virtual training intensive with 1/4 and 3/4 of each session delivered by human and virtual trainers, respectively. Functional assessments including Fugl-Meyer Assessment for Upper Extremity (FMA-UE) and Lower Extremity (FMA-LE), Functional Ambulation Category (FAC), Berg Balance Scale (BBS), Barthel Index (BI) of Activities of Daily Living (ADL), and Physical Component Summary (SF-12v2 PCS) and Mental Component Summary (SF-12v2 MCS) of the 12-Item Short Form Health Survey (SF-12v2), were conducted before and after the intervention. User experience (UX) using questionnaires were collected after the intervention. Time and human resources required to deliver the human and virtual training, respectively, and the proportion of participants with clinical significant improvement were also used as supplementary measures. RESULTS: There were 129 patients from 10 rehabilitation centres enrolled in the integrated program with 39 of them were selected for investigation. Significant functional improvement in FMA-UE (AR-Centre: p = 0.0022, AR-Home: p = 0.0043), FMA-LE (AR-Centre: p = 0.0007, AR-Home: p = 0.0052), SF-12v2 PCS (AR-Centre: p = 0.027, AR-Home: p = 0.036) were observed in both groups. Significant improvement in balance ability (BBS: p = 0.0438), and mental components (SF-12v2 MCS: p = 0.017) were found in AR-Centre group, while activities of daily living (BI: p = 0.0007) was found in AR-Home group. Contact rate was reduced by 30.75-72.30% within AR-All, 0.00-60.00% within AR-Centre, and 75.00-90.00% within AR-Home. CONCLUSION: The human-machine integrated mode was effective and efficient to reduce the human rehabilitation professionals' effort while fulfilling the training goals. It eased the scarcity of manpower and reduced the contact rate during the pandemics.

IL-9 blockade attenuates inflammation in a murine model of mechanical ventilation-induced lung injury by inhibiting the NLRP3 inflammasome pathway.

OBJECTIVES: Ventilation-induced lung injury (VILI) causes a huge economic and social burden, and its prevention and treatment have gained increasing attention in recent years. IL-9 is an important inflammatory factor, but its potential role in VILI remains unclear. This study intended to explore whether blocking IL-9 could alleviate VILI and explore its underlying mechanism. METHODS: Lung injury was induced by mechanical ventilation (MV) in C57BL/6 mice. Changes in inflammatory factors and NLRP3-related proteins were assessed using quantitative reverse transcription-polymerase chain reaction, western blotting, and enzyme-linked immunosorbent assay. Subsequently, Nlrp3-/- mice were used to further elucidate the underlying mechanism. RESULTS: The percentage of Th9 cells in the peripheral blood, bronchoalveolar lavage fluid (BALF), and lung tissues of MV mice was increased compared to those of control mice. Treatment with anti-IL-9 mAb significantly alleviated the changes in lung histopathology, wet/dry lung proportion, total protein content, and neutrophil content in BALF induced by VILI. Additionally, administering anti-IL-9 mAb significantly downregulated the expression levels of inflammatory factors in BALF and lung tissues of mice with VILI. In addition, administering anti-IL-9 mAb inhibited NLRP3 inflammasome activation, as evidenced by the observed downregulation of NLRP3, ASC, cleaved caspase-1, and GSDMD-N. Additionally, NLRP3-deficient mice had lower lung injury induced by VILI than wild-type mice. Furthermore, the anti-IL-9 mAb only partially inhibited VILI in Nlrp3-/- mice. CONCLUSIONS: In MV mice, the anti-IL-9 mAb alleviated lung injury and reduced the secretion and expression of inflammatory factors partly by inhibiting the NLRP3 inflammasome pathway.

Protective effect of syringic acid via restoring cells biomechanics and organelle structure in human lens epithelial cells.

We have previously reported that syringic acid (SA) extracted from D. aurantiacum var. denneanum (kerr) may be used to prevent diabetic cataract (DC). However, the underlying mechanisms through which SA prevents DC in human lens epithelial cells (HLECs) remained unclear. In the present study, we employed single-molecule optics technologies, including transmission electron microscopy (TEM), atomic force microscopy (AFM), laser scanning confocal microscopy (LSCM) and Raman spectroscopy, to monitor the effect of SA on HLECs biomechanics and organelle structure in real-time. TEM suggested that SA improved the ultrastructure of HLECs with regard to nuclear chromatin condensation and reducing mitochondrial swelling and degeneration, which may aid in the maintenance of HLECs integrity in the presence of glucose. AFM revealed a reduced surface roughness and stiffness following SA treatment, suggesting an improved viscoelasticity of HELCs. Raman spectrometry and LSCM further revealed that these changes were related to a modification of cell liquidity and cytoskeletal structure by SA. Taken together, these results provide insights into the effects of SA on the biomechanics of HLECs and further strengthen the evidence for its potential use as a novel therapeutic strategy for DC prevention.

Single-path electro-optic coefficients measurement approach using multiple reflection interference.

An electro-optic coefficient (EOC) is an important optical property of optical crystals. In this work, a single-path multiple reflection interferometer is proposed to measure the components of signed EOCs with high precision. With the help of the normalization method, the influence of incident light was removed, and repeatability of the experimental results was improved. The signed EOCs of a congruent LiNbO3 crystal were determined under a small external electric field as γ31=+9.6±0.3pm/V and γ33=+29.5±0.5pm/V. This study may contribute to the development of potential anisotropic devices of optical crystals.

A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle.

In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in robot-assisted minimally invasive surgery (RMIS) is proposed. It can detect the stiffness not only when the probe is normal to the tissue surface, but also when there is a contact angle between the probe and normal direction. It solves the problem that existing sensors can only detect in the normal direction to ensure accuracy when the degree of freedom (DOF) of surgical instruments is limited. The proposed senor can distinguish samples with different stiffness and recognize lump from normal tissue effectively when the contact angle varies within [0°, 45°]. These are achieved by establishing a new detection model and sensor optimization. It deduces the influence of contact angle on stiffness detection by sensor parameters design and optimization. The detection performance of the sensor is confirmed by simulation and experiment. Five samples with different stiffness (including lump and normal samples with close stiffness) are used. Through blind recognition test in simulation, the recognition rate is 100% when the contact angle is randomly selected within 30°, 94.1% within 45°, which is 38.7% higher than the unoptimized sensor. Through blind classification test and automatic k-means clustering in experiment, the correct rate is 92% when the contact angle is randomly selected within 45°. We can get the proposed sensor can easily recognize samples with different stiffness with high accuracy which has broad application prospects in the medical field.

Characterization of B-BOX gene family and their expression profiles under hormonal, abiotic and metal stresses in Poaceae plants.

BACKGROUND: B-box (BBX) proteins play important roles in plant growth regulation and development including photomorphogenesis, photoperiodic regulation of flowering, and responses to biotic and abiotic stresses. RESULTS: In the present study we retrieved total 131 BBX members from five Poaceae species including 36 from maize, 30 from rice, 24 from sorghum, 22 from stiff brome, and 19 from Millet. All the BBX genes were grouped into five subfamilies on the basis of their phylogenetic relationships and structural features. The expression profiles of 12 OsBBX genes in different tissues were evaluated through qRT-PCR, and we found that most rice BBX members showed high expression level in the heading stage compared to seedling and booting stages. The expression of OsBBX1, OsBBX2, OsBBX8, OsBBX19, and OsBBX24 was strongly induced by abiotic stresses such as drought, cold and salt stresses. Furthermore, the expression of OsBBX2, OsBBX7, OsBBX17, OsBBX19, and OsBBX24 genes was up-regulated under GA, SA and MeJA hormones at different time points. Similarly, the transcripts level of OsBBX1, OsBBX7, OsBBX8, OsBBX17, and OsBBX19 genes were significantly affected by heavy metals such as Fe, Ni, Cr and Cd. CONCLUSION: Change in the expression pattern of BBX members in response to abiotic, hormone and heavy metal stresses signifies their potential roles in plant growth and development and in response to multivariate stresses. The findings suggest that BBX genes could be used as potential genetic markers for the plants, particularly in functional analysis and determining their roles under multivariate stresses.

Identification of methylated metabolites of oat avenanthramides in human plasma using UHPLC QToF-MS.

Oat avenanthramides (AVAs) are a group of phenolic alkaloids, consisting of an anthranilic acid and a hydroxycinnamic acid linked by a pseudo-peptide bond. Bioavailability of AVA is poor in humans, suggesting transformations for rapid excretion. Thus, we aim to identify metabolites of AVA isomers in plasma of humans after consuming AVA-enriched oats. After lipid removal, AVA and their metabolites in plasma were extracted with ethyl acetate and analysed using an Agilent UHPLC-QToF-MS. Pharmacokinetics of AVA-O showed a bimodal distribution with Cmax1 and 2 for AVA-O at 5.9 ± 5.2 and 7.9 ± 7.0 ng/mL and Tmax1 and 2 at 1.7 ± 0.7 and 3.1 ± 1.2 h, respectively. Only the methyl-AVA-O showed a single Cmax at 14 ± 9.9 ng/mL AVA-O equivalents and a Tmax of 2.4 ± 2.7 h. This analysis is the first to identify methylated metabolites of AVAs and AVA aglycones in human blood after acute AVA consumption.

[Mechanism of interaction between chrysin and leptin].

The study of interaction mechanism between chrysin and leptin was investigated by various spectroscopic techniques and atom force microscope. The ultraviolet spectrum presents a red shift in 200-220 nm after chrysin upon. And there is a structure alternative showed in 270 nm when the concentration ratio of chrysin and leptin in 10-15. From the fluorescence spectrum, it was found that chrysin could combine with leptin in physiological condition. The binding constant (Ka) values, at 298 K and 310 K, were (0.41±0.05)×106 and (3.26±0.46)×106 L·mol⁻¹, and the binding site number were 1.02±0.04 and 0.51±0.01, respectively. The atom force microscope results showed that the dimension of leptin molecules became more swollen after binding with chrysin because of the hydrophobicity. These results demonstrate that the mechanism of chrysin and leptin interaction could play a role in leptin adjust in human body, and it could provide a new aspect for the study of obesity treatment.

Interaction of AR and iNOS in lens epithelial cell: A new pathogenesis and potential therapeutic targets of diabetic cataract.

Although there is significant interest in revealing the role of aldose reductase (AR) and inducible nitric oxide synthase (iNOS) in diabetic cataract (DC), the interaction of AR and iNOS remains unknown. The aim of this study is to investigate the pathogenesis mechanisms and explore as a new potential therapeutic targets for DC. This study investigated the interaction of AR-iNOS through the methods of enzyme kinetics, molecular docking and molecular dynamics simulation, co-immunoprecipitation and fluorescence resonance energy transfer (FRET). The IC50 of AR for inhibition of iNOS activity is 0.04 µM, and the IC50 of iNOS for inhibition of AR activity is 0.042 µM through enzyme kinetics; the interface showed that ARG99 on AR and GLU317 on iNOS played the key roles in the interaction of AR-iNOS predicted by molecular docking and molecular dynamics simulation. Co-immunoprecipitation of protein complexes in human lens epithelial cell (HLEC) demonstrated that AR could association with iNOS in cell; and the interaction distance of AR-iNOS was 6.50 ± 0.22 nm detected by FRET. This study exhibited a direct inhibition interaction between AR and iNOS in HLECs. It is the first report of inhibition interaction between AR and iNOS, suggesting a new pathophysiological mechanism and providing a new insight into the therapeutic mechanism of DC.

Investigation of synergistic mechanism and identification of interaction site of aldose reductase with the combination of gigantol and syringic acid for prevention of diabetic cataract.

BACKGROUND: Gigantol and syringic acid (SA) have been shown to synergistically prevent formation of diabetic cataract (DC). However, the exact mechanism of this effect is unknown. Here, we investigate the effect of these compounds on the activity of aldose reductase (AR) and cataract formation. METHODS: We examined the synergistic anti-cataract efficacy of gigantol and SA in the high glucose- and streptozotocin -induced DC rat model; synergism was evaluated using Jin's formula. We investigated possible mechanisms of action by measuring AR expression and activity and levels of sorbitol using enzyme kinetics, Western blot, and RT-PCR. Finally, we examined binding interaction between AR and both compounds using a combination of site-directed mutagenesis, recombinant expression of wild-type and mutant proteins, and enzyme kinetics. RESULTS: Combination treatment of gigantol and SA synergistically protected both HLECs(human lens epithelial cells) grown in vitro and DC formation in STZ-induced rats in vivo. Synergism was attributed to inhibition of AR activity, downregulation of AR expression via impaired transcription, and decreased sorbitol levels. Enzyme kinetics studies showed that the activity of an AR Asn160Ala mutant protein was significantly decreased compared to wild-type AR, confirming that Asn160 is a key residue for interaction between AR and both compounds. CONCLUSION: Combined administration of gigantol and SA synergize to enhance anti-cataract efficacy. The synergistic effect is mainly attributed to disruption of the polyol pathway and inhibition of AR activity.