Enzymatic biotransformation of Rb3 from the leaves of Panax notoginseng to ginsenoside rd by a recombinant ß-xylosidase from Thermoascus aurantiacus.

Given the important pharmacological activity of ginsenoside Rd but its low content in plants, the production of Rd by enzymatic transformation is of interest. In this study, a ß-xylosidase gene Ta-XylQS from Thermoascus aurantiacus was cloned and overexpressed in Komagataella phaffii. Purified recombinant Ta-XylQS specifically hydrolyzes substrates with xylosyl residues at the optimal pH of 3.5 and temperature of 60 °C. This study established a process for producing Rd by transforming ginsenoside Rb3 in the saponins of Panax notoginseng leaves via recombinant Ta-XylQS. After 60 h, 3 g L- 1 of Rb3 was transformed into 1.46 g L- 1 of Rd, and the maximum yield of Rd reached 4.31 g kg- 1 of Panax notoginseng leaves. This study is the first report of the biotransformation of ginsenoside Rb3 to Rd via a ß-xylosidase, and the established process could potentially be adopted for the commercial production of Rd from Rb3.

Detection of Optic Disc Abnormalities in Color Fundus Photographs Using Deep Learning.

BACKGROUND: To date, deep learning-based detection of optic disc abnormalities in color fundus photographs has mostly been limited to the field of glaucoma. However, many life-threatening systemic and neurological conditions can manifest as optic disc abnormalities. In this study, we aimed to extend the application of deep learning (DL) in optic disc analyses to detect a spectrum of nonglaucomatous optic neuropathies. METHODS: Using transfer learning, we trained a ResNet-152 deep convolutional neural network (DCNN) to distinguish between normal and abnormal optic discs in color fundus photographs (CFPs). Our training data set included 944 deidentified CFPs (abnormal 364; normal 580). Our testing data set included 151 deidentified CFPs (abnormal 71; normal 80). Both the training and testing data sets contained a wide range of optic disc abnormalities, including but not limited to ischemic optic neuropathy, atrophy, compressive optic neuropathy, hereditary optic neuropathy, hypoplasia, papilledema, and toxic optic neuropathy. The standard measures of performance (sensitivity, specificity, and area under the curve of the receiver operating characteristic curve (AUC-ROC)) were used for evaluation. RESULTS: During the 10-fold cross-validation test, our DCNN for distinguishing between normal and abnormal optic discs achieved the following mean performance: AUC-ROC 0.99 (95 CI: 0.98-0.99), sensitivity 94% (95 CI: 91%-97%), and specificity 96% (95 CI: 93%-99%). When evaluated against the external testing data set, our model achieved the following mean performance: AUC-ROC 0.87, sensitivity 90%, and specificity 69%. CONCLUSION: In summary, we have developed a deep learning algorithm that is capable of detecting a spectrum of optic disc abnormalities in color fundus photographs, with a focus on neuro-ophthalmological etiologies. As the next step, we plan to validate our algorithm prospectively as a focused screening tool in the emergency department, which if successful could be beneficial because current practice pattern and training predict a shortage of neuro-ophthalmologists and ophthalmologists in general in the near future.

Application of carbamyl in structural optimization.

Carbamyl is considered a privileged structure in medicinal chemistry. It has a wide range of biological activities such as antimicrobial, anticancer, anti-epilepsy, for which the best evidence is a number of marketed carbamyl-containing drugs. Carbamyl is formed of primary amine and carbonyl moieties that act as hydrogen bond donors and hydrogen acceptors with residues of targets respectively, which are benefit for improving pharmacological activities. In other cases, the introduced carbamyl improves drug-like properties including oral bioavailability. In this review, we introduce the carbamyl-containing drugs and the application of carbamyl in structural optimization as a result of enhancing activities or/and drug-like properties.

Deep Learning and Transfer Learning for Optic Disc Laterality Detection: Implications for Machine Learning in Neuro-Ophthalmology.

BACKGROUND: Deep learning (DL) has demonstrated human expert levels of performance for medical image classification in a wide array of medical fields, including ophthalmology. In this article, we present the results of our DL system designed to determine optic disc laterality, right eye vs left eye, in the presence of both normal and abnormal optic discs. METHODS: Using transfer learning, we modified the ResNet-152 deep convolutional neural network (DCNN), pretrained on ImageNet, to determine the optic disc laterality. After a 5-fold cross-validation, we generated receiver operating characteristic curves and corresponding area under the curve (AUC) values to evaluate performance. The data set consisted of 576 color fundus photographs (51% right and 49% left). Both 30° photographs centered on the optic disc (63%) and photographs with varying degree of optic disc centration and/or wider field of view (37%) were included. Both normal (27%) and abnormal (73%) optic discs were included. Various neuro-ophthalmological diseases were represented, such as, but not limited to, atrophy, anterior ischemic optic neuropathy, hypoplasia, and papilledema. RESULTS: Using 5-fold cross-validation (70% training; 10% validation; 20% testing), our DCNN for classifying right vs left optic disc achieved an average AUC of 0.999 (±0.002) with optimal threshold values, yielding an average accuracy of 98.78% (±1.52%), sensitivity of 98.60% (±1.72%), and specificity of 98.97% (±1.38%). When tested against a separate data set for external validation, our 5-fold cross-validation model achieved the following average performance: AUC 0.996 (±0.005), accuracy 97.2% (±2.0%), sensitivity 96.4% (±4.3%), and specificity 98.0% (±2.2%). CONCLUSIONS: Small data sets can be used to develop high-performing DL systems for semantic labeling of neuro-ophthalmology images, specifically in distinguishing between right and left optic discs, even in the presence of neuro-ophthalmological pathologies. Although this may seem like an elementary task, this study demonstrates the power of transfer learning and provides an example of a DCNN that can help curate large medical image databases for machine-learning purposes and facilitate ophthalmologist workflow by automatically labeling images according to laterality.

Synthesis and Biological Evaluation of NH2-Sulfonyl Oseltamivir Analogues as Influenza Neuraminidase Inhibitors.

A series of NH2-sulfonyl oseltamivir analogues were designed, synthesized, and their inhibitory activities against neuraminidase from H5N1 subtype evaluated. The results indicated that the IC50 value of compound 4a, an oseltamivir analogue via methyl sulfonylation of C5-NH2, was 3.50 µM. Molecular docking simulations suggested that 4a retained most of the interactions formed by oseltamivir carboxylate moieties and formed an additional hydrogen bond with the methylsulfonyl group. Meanwhile, 4a showed high stability towards human liver microsomes. More importantly, 4a without basic moieties is not a zwitterion as reported on the general structure of neuraminidase inhibitors. This research will provide valuable reference for the research of new types of neuraminidase inhibitors.

Improvement of Mechanical Properties of Composites with Surface Modified B4C for Precision Machining.

In order to solve the problem of difficult sintering and high brittleness of B4C-based ceramics, B4C@ZrB2-TiB2 composite powder was synthesized by molten salt method, and B4C-(Zr, Ti)B2 composite ceramics were successfully prepared by spark plasma sintering. The effects of different raw material ratios on the composition, microstructure, and mechanical properties of the prepared composite ceramics were characterized by XRD, XPS, SEM, and TEM. The results show that ZrB2 and TiB2 were grown on the surface of B4C by template mechanism to form a dense nanocrystalline coating, and the original surface of B4C was exposed gradually with the decrease of the ratio of metal powder. When the composite powders were sintered at 1700 °C, ZrB2 and TiB2 formed a solid solution, which can refine grains and improve strength. When the raw material ratio is n(B4C): n(Zr): n(Ti) = 12:1:1, the composite ceramics have excellent comprehensive properties, the Vickers hardness reaches 41.2 GPa.

Effect of In Situ Mg-Sialon on the Oxidation Behavior of Low-Carbon MgO-C Refractories.

The in situ Mg-sialon in low-carbon MgO-C refractories was studied with respect to its oxidation behavior and mechanism at 1500 °C. The results indicated that the oxidation index and rate constant of low-carbon MgO-C refractories with Mg-sialon were 26.2% and 0.51 × 10-3 cm2/min at 1500 °C for 2 h, respectively. The formation of a dense MgO-Mg2SiO4-MgAl2O4 protective layer contributed to considerable oxidation resistance, and the generation of this thicker layer was due to the combined volume effect of Mg2SiO4 and MgAl2O4. The reduced porosity and more complex pore structure were also found in the refractories with Mg-sialon. Therefore, further oxidation was restricted as the oxygen diffusion path was effectively blocked. This work proves the potential application of Mg-sialon in improving the oxidation resistance of low-carbon MgO-C refractories.

Liquid-Phase-Assisted Catalytic Nitridation of Silicon and In Situ Growth of α-Si3N4.

Si3N4 powders were synthesized with Fe, Co, or Ni as catalysts using Si powder at 1250 °C in a nitrogen atmosphere by liquid-phase-assisted catalytic nitridation synthesis (LPA-CNS). The catalytic effects of the metals on the nitridation of silicon powder were investigated by mixing the powder with 2 wt% by mass of Fe, Co, or Ni in a high-temperature liquid phase in flowing nitrogen. The α-Si3N4 micro-morphology could be effectively changed by adjusting the type of catalyst in the initial reaction mixtures. Fe, Co, and Ni promoted the formation of α-Si3N4 at 1250 °C and controlled the morphology of the α-Si3N4 particles. The hexagonal flakes of α-Si3N4 with a better defined morphology were obtained using Ni as the catalyst, compared to that obtained from the other two catalysts.

Discovery of hydrazide-containing oseltamivir analogues as potent inhibitors of influenza A neuraminidase.

Neuraminidase (NA) inhibitors play a prime role in treating influenza. However, a variety of viruses containing mutant NAs have developed severe drug resistance towards NA inhibitors, so it is of crucial significance to solve this problem. Encouraged by urea-containing compound 12 disclosed by our lab, we designed a series of oseltamivir derivatives bearing hydrazide fragment for targeting the 150 cavity. Among the synthesized compounds, compound 17a showed 8.77-fold, 4.12-fold, 203-fold and 6.23-fold more potent activity than oseltamivir carboxylate against NAs from H5N1, H1N1, H5N1-H274Y, H1N1-H274Y, respectively. Meanwhile, the best compound 17a exhibited satisfactory metabolic stability in vitro. This study offers an important reference for the structural optimization of oseltamivir aiming at potent inhibition against H274Y mutant of NAs.

Discovery of a non-zwitterionic oseltamivir analogue as a potent influenza a neuraminidase inhibitor.

The most of potent neuraminidase inhibitors as zwitterions with poor lipophilicity suffered from the poor oral bioavailability. Herein, we describe a rational journey to discover a non-zwitterionic neuraminidase inhibitor 24a containing urea. It showed potent inhibitions against neuraminidases from group 1(H5N1 and H1N1) and group 2 (H3N2) subtypes and exhibited more strong inhibitory activities against neuraminidases from H274Y mutants than oseltamivir carboxylate. Whether administrated by orally or intravenous injection, the pharmacokinetic profile of compound 24a in SD rats were improved compared to oseltamivir carboxylate.

Design, synthesis and biological evaluation of oseltamivir derivatives containing pyridyl group as potent inhibitors of neuraminidase for influenza A.

Influenza A neuraminidase plays an indispensable role in the process of replication and transmission of influenza, so the neuraminidase inhibition can prevent the reproduction of the viruses therefore achieve the effect of treatment of influenza. However, drug resistance of neuraminidase inhibitors such as oseltamivir highlights the need to develop novel structural neuraminidase inhibitors. Here we explored a series of oseltamivir derivatives bearing pyridyl group. Among them, compound 23b exhibiting potent inhibitory activity against neuraminidase from H5N1 subtype was comparable to oseltamivir carboxylate. Cytopathic effect inhibition assay in MDCK cells indicated that compound 23b exerted powerful inhibitions on influenza viruses. And compound 23b were nontoxic to MDCK cells. Meanwhile, compound 23b showed high stability towards rat liver microsomes, human liver microsomes and human plasma. This research enriched the structural type of neuraminidase inhibitors.

Low temperature synthesis via molten-salt method of r-BN nanoflakes, and their properties.

r-BN nanoflakes were synthesized using KBH4 and NH4Cl as the main raw material in a high-purity nitrogen atmosphere. The effects of salt and salt-free conditions and heating temperature on the synthesis of BN were studied. The molten-salt method was used to synthesize BN at 650 °C, which was 250 °C lower than the BN synthesis method without salt. Furthermore, at 1000 °C the prepared flake-like BN crystals showed good crystallinity, uniform morphology, a particle diameter of 200-300 nm, and a thickness of 40-70 nm. Moreover, the specific surface area of BN was 294.26 m2/g. In addition, the BN synthesized at 1100 °C had a large elastic modulus value and good oxidation resistance.