Self-Assembly of Chiral Porous Metal-Organic Polyhedra from Trianglsalen Macrocycles.

Metal-organic polyhedra (MOPs) can exhibit tunable porosity and functionality, suggesting potential for applications such as molecular separations. MOPs are typically constructed by the bottom-up multicomponent self-assembly of organic ligands and metal ions, and the final functionality can be hard to program. Here, we used trianglsalen macrocycles as preorganized building blocks to assemble octahedral-shaped MOPs. The resultant MOPs inherit most of the preorganized properties of the macrocyclic ligands, including their well-defined cavities and chirality. As a result, the porosity in the MOPs could be tuned by modifying the structure of the macrocycle building blocks. Using this strategy, we could systematically enlarge the size of the MOPs from 26.3 to 32.1 Å by increasing the macrocycle size. The family of MOPs shows experimental surface areas of up to 820 m2/g, and they are stable in water. One of these MOPs can efficiently separate the rare gases Xe from Kr because the prefabricated macrocyclic windows of MOPs can be modified to sit at the Xe/Kr size cutoff range.

KEBLM: Knowledge-Enhanced Biomedical Language Models.

Pretrained language models (PLMs) have demonstrated strong performance on many natural language processing (NLP) tasks. Despite their great success, these PLMs are typically pretrained only on unstructured free texts without leveraging existing structured knowledge bases that are readily available for many domains, especially scientific domains. As a result, these PLMs may not achieve satisfactory performance on knowledge-intensive tasks such as biomedical NLP. Comprehending a complex biomedical document without domain-specific knowledge is challenging, even for humans. Inspired by this observation, we propose a general framework for incorporating various types of domain knowledge from multiple sources into biomedical PLMs. We encode domain knowledge using lightweight adapter modules, bottleneck feed-forward networks that are inserted into different locations of a backbone PLM. For each knowledge source of interest, we pretrain an adapter module to capture the knowledge in a self-supervised way. We design a wide range of self-supervised objectives to accommodate diverse types of knowledge, ranging from entity relations to description sentences. Once a set of pretrained adapters is available, we employ fusion layers to combine the knowledge encoded within these adapters for downstream tasks. Each fusion layer is a parameterized mixer of the available trained adapters that can identify and activate the most useful adapters for a given input. Our method diverges from prior work by including a knowledge consolidation phase, during which we teach the fusion layers to effectively combine knowledge from both the original PLM and newly-acquired external knowledge using a large collection of unannotated texts. After the consolidation phase, the complete knowledge-enhanced model can be fine-tuned for any downstream task of interest to achieve optimal performance. Extensive experiments on many biomedical NLP datasets show that our proposed framework consistently improves the performance of the underlying PLMs on various downstream tasks such as natural language inference, question answering, and entity linking. These results demonstrate the benefits of using multiple sources of external knowledge to enhance PLMs and the effectiveness of the framework for incorporating knowledge into PLMs. While primarily focused on the biomedical domain in this work, our framework is highly adaptable and can be easily applied to other domains, such as the bioenergy sector.

Mechanics and Biology Interact in Intervertebral Disc Degeneration: A Novel Composite Mouse Model.

The aim of this study was to distinguish the characteristics of intervertebral disc degeneration (IVDD) originating from mechanics imbalance, biology disruption, and their communion, and to develop a composite IVDD model by ovariectomy combined with lumbar facetectomy for mimicking elderly IVDD with osteoporosis and lumbar spinal instability. Mice were randomly divided into four groups and subjected to sham surgery (CON), ovariectomy (OVX), facetectomy (mechanical instability, INS) or their combination (COM), respectively. Radiographical (n = 4) and histological changes (n = 8) of L4/5 spinal segments were analyzed. Tartrate-resistant acid phosphatase (TRAP) staining was conducted to detect osteoclasts, and expression of osterix (OSX), type I collagen (Col I), type II collagen (Col II) and vascular endothelial growth factor (VEGF) were evaluated by immunochemistry. OVX affected the body's metabolism but INS did not, as the body weight increased and uterus weight decreased in OVX and COM mice compared to CON and INS mice. OVX, INS, and COM caused IVDD in various degrees at 12 weeks after surgery. However, the major pathogeneses of OVX- and INS-induced IVDD were different, which focused on endplate (EP) remodeling and annulus fibrosus (AF) collapse, respectively. OVX induced osteopenia of vertebra. In contrast, INS promoted the stress-adaptive increase of subchondral bone trabeculae. The COM produced a reproducible severe IVDD model with characteristics of sparse vertebral trabeculae, cartilaginous EP ossification, subchondral bone sclerosis, fibrous matrix disorder, angiogenesis, disc stiffness, as well as space fusion. Additionally, all groups had elevated bone and cartilage turnover compared with CON group, as the quantity of trap + osteoclasts and the osteogenic OSX expression increased in these groups. Likewise, the VEGF expression levels were similar, accompanied by the altered matrix expression of disc, including the changed distribution and contents of Col II and Col I. The findings suggested that the composite mouse model to some extent could effectively mimic the interactions of biology and mechanics engaged in the onset and natural course of IVDD, which would be more compatible with the IVDD of elderly with vertebral osteoporosis and spinal instability and benefit to further clarify the complicated mechanobiological environment of elderly IVDD progression.

Identification of Antitumor Constituents in Toad Venom by Spectrum-Effect Relationship Analysis and Investigation on Its Pharmacologic Mechanism.

(1) Background: Toad venom (Bufonis Venenum, known as 'Chansu' in Chinese), the secretion of the ear-side gland and skin gland of Bufo gargarizans cantor or Duttaphrynus melanostictus Schneider, has been utilized to treat several diseases in China for thousands of years. However, due to the chemical variability of the components, systematic chemical composition and the key pharmacophores in toad venom have not yet fully understood. Besides, it contains a variety of effective compounds with different physiological activity and chemotypes, mainly including alkaloids, bufogenins, bufotoxins, and so on. The recent pharmacological researches have demonstrated that several bufogenins have remarkable pharmacological effects, such as anti-inflammatory, analgesic effects, and anti-tumor effects. Aim of the study: To identify the bioactive compounds and pharmacophores originating from toad venom based on analyzing spectrum-effect relationship by chemometrics and to explore the anti-cancer mechanism primarily. (2) Materials and methods: Fingerprint of the 21 batches of samples was established using HPLC (High Performance Liquid Chromatography). The anti-tumor activity of extracts were determined by in-vitro assays. Chemometric analysis was used to establish the spectrum-effect model and screen for active ingredients. Pharmacodynamic tests for the screened active compound monomers were conducted with in-vitro assays. Further anti-tumor mechanisms were investigated using western blot and flow cytometry. (3) Results: The established spectrum-effect model has satisfactory fitting effect and predicting accuracy. The inhibitory effect of major screened compounds on lung carcinoma cells A549 were validated in vitro, demonstrating that arenobufagin, telocinobufogenin, and cinobufotalin had significant anti-tumor effects. Through further investigation of the mechanism by western blotting and flow cytometry, we elucidated that arenobufagin induces apoptosis in A549 cells with the enhanced expression of cleaved PARP (poly (ADP-ribose) polymerase). These results may provide valuable information for further structural modification of bufadienolides to treat lung cancer and a method for discovery of anti-tumor active compounds. Conclusions: Our research offers a more scientific method for screening the principal ingredients dominating the pharmacodynamic function. These screened compounds (arenobufagin, etc.) were proven to induce apoptosis by overactivation of the PARP-pathway, which may be utilized to make BRCA (breast cancer susceptibility gene) mutant cancer cells more vulnerable to DNA damaging agents and kill them.

Bacillus aciditolerans sp. nov., isolated from paddy soil.

A Gram-stain-positive, motile, rod-shaped bacterial strain, YN-1T, was isolated from a rice field in the town of Jietou, Yunnan Province, PR China. Colonies were circular, 1-2 mm in diameter, creamy white, with slightly irregular margins. The isolate grew optimally at 37 °C, pH 7.0 and with 1.0 % (w/v) NaCl. On the basis of the results of 16S rRNA gene sequence similarity comparisons, YN-1T clustered together with other species of the genus Bacillus and showed highest similarities with Bacillus onubensis 0911MAR22V3T (98.0 %), Bacillus humi LMG22167T (97.5 %), 'Bacillus timonensis' 10403023 (97.4 %) and 'Bacillussinesaloumensis' P3516 (97.1 %). However, the DNA-DNA hybridization values between YN-1T and closely related strains of species of the genus Bacillus were well below 47 %, indicating that they represent different taxa. The average nucleotide identity and the Genome-to-Genome Distance Calculator also revealed low relatedness (below 95 and 70 %, respectively) between YN-1T and type strains of closely related species of the genus Bacillus. The DNA G+C content of the strain was 40 mol%. The major cellular fatty acids were iso-C15 : 0, anteiso-C15 : 0, and C16 : 0. The polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, two unidentified phospholipids, three unidentified aminophospholipids and two other unidentified lipids. Physiological and biochemical test results were also different from those of the most closely related species. On the basis of the phenotypic, genetic and chemotaxonomic data, strain YN-1T is considered to represent a novel species of the genus Bacillus, for which the name Bacillusaciditolerans sp. nov. is proposed, with strain YN-1T (=CCTCC AB 2017280T=JCM 32973T) as the type strain.

Host defense peptide LEAP-2 contributes to monocyte/macrophage polarization in barbel steed (Hemibarbus labeo).

The liver-expressed antimicrobial peptide 2 (LEAP-2) plays a vital role in host immunity against pathogenic organisms. In the present study, cDNA of the LEAP-2 gene was cloned and sequenced from the barbel steed (Hemibarbus labeo). The predicted amino acid sequence of the barbel steed LEAP-2 comprises a signal peptide and a prodomain, which is followed by the mature peptide. Sequence analysis revealed that barbel steed LEAP-2 belongs to the fish LEAP-2A cluster and that it is closely related to zebrafish LEAP-2A. We found that barbel steed LEAP-2 transcripts were expressed in a wide range of tissues, with the highest mRNA levels detected in the liver. In response to lipopolysaccharide (LPS) treatment, LEAP-2 was significantly upregulated in the liver, head kidney, spleen, gill, and mid intestine. A chemically synthesized LEAP-2 mature peptide exhibited selective antimicrobial activity against several bacteria in vitro. Moreover, LEAP-2, alone or in combination with LPS or phorbol 12-myristate 13-acetate, strongly induced a pro-inflammatory reaction in barbel steed monocytes/macrophages (MO/MФ), involving the induction of iNOS activity, respiratory burst, and the pro-inflammatory cytokines IFN-γ, TNF-α, and IL-1ß. Collectively, the results of this study indicate the importance of fish LEAP-2 in the M1-type polarization of MO/MΦ.

[Shared functional modules for nasopharyngeal and oral squamous cell carcinoma identified by network analysis of transcriptomes].

Although nasopharyngeal carcinoma (NPC) and oral squamous cell carcinoma (OSCC) are highly correlated clinical diseases, the underling molecular mechanisms to link the two diseases remain largely unknown. The aim of this study is to identify the shared functional modules for NPC and OSCC by using large-scale transcriptomic data. Gene expression profile datasets of NPC and OSCC were obtained from the GEO database. A total of 1279 differentially expressed genes (DEGs) of NPC and 1293 DEGs of OSCC were identified by fold change and empirical Bayes method, and 278 DEGs were common to these two diseases. These overlapped genes were translated into a primary network consisting of 1290 nodes (genes) and 1766 edges. The primary network was then decomposed into 15 compacted modules (subnets) with high modularity by Newman's algorithm. Topological analysis of these modules identified a total of 58 hub genes, most of which (e.g., PCNA, CDK1, STAT1, CCL5, and MMP1) have been proved to be associated with NPC and/or OSCC, while the rest (e.g., MELK, NME1, RACGAP1, INHBA, and NID1) might be novel risk genes for the two diseases. Further bioinformatics analysis of KEGG databases revealed that these modules are involved in multiple pathogenic biological pathways for either NPC or OSCC (e.g., p53 signaling pathway, ECM-receptor interaction, focal adhesion, and cell cycle). This study demonstrates that NPC and OSCC have similar molecular bases, and the identified pleiotropic modules may shape the complicated molecular interplays underlying the two clinically correlated diseases.

[Correlative study of bufogenin constituents in venom of Bufo bufo gargarizans].

As known,simultaneous determination of various chemical indicators is one of the future trends in quality control of traditional Chinese medicines because of the extremely complex chemical compositions. This project is to screen the quality markers that can accurately control the quality of the Bufonis Venenum by exploring the intrinsic correlation of components. In this study,venom of Bufo bufo gargarizans from 17 different sources were used as research samples,and the contents of 7 bufogenin were determined by HPLC-DAD. Then,the data obtained were analyzed by Spearman correlation analysis and principal component analysis( PCA). In addition,a stepwise regression analysis was used to establish a predictive model for the contents of the seven bufogenin components( independent variable) and the total contents of the bufogenin( dependent variable). The results indicated that there is a significant positive correlation between the contents of telocinobufagin and cinobufotalin,and there is a significant positive correlation between the contents of bufalin,cinobufagin and resibufogenin. In contrast,the contents of telocinobufagin and cinobufotalin are negatively correlated with the contents of bufalin,cinobufagin and resibufogenin. However,the correlation between gamabufotalin and bufotalin and other components are not obvious. Furthermore,further study found that there is a correlation between the sum of the contents of bufalin,cinobufagin and telocinobufagin and the total contents of the bufogenin. In fact,the application of bufalin,cinobufagin and telocinobufagin as the quality control indicators of the Bufonis Venenum can better reflect the quality characteristics of the Bufonis Venenum compared with the previous quality control indicators. The conclusions will provide a reference for the revision of the quality standards of the Bufonis Venenum.

Baicalein Protects Rats with Diabetic Cardiomyopathy Against Oxidative Stress and Inflammation Injury via Phosphatidylinositol 3-Kinase (PI3K)/AKT Pathway.

BACKGROUND The aim of this study was to explore the effect of baicalein on diabetic cardiomyopathy (DCM) rats and the mechanisms involved, and to determine the theoretical basis for clinical anti-tumor therapy. MATERIAL AND METHODS DCM rat model was induced with a single injection of streptozotocin. Then, DCM rats were treated with baicalein alone or co-treated with baicalein and PI3K/Akt inhibitor. Myocardial pathological changes were detected by HE and Masson staining. The activities of SOD, GSH-Px, and MDA in myocardial tissue were measured by biochemical tests. The levels of TNF-α, IL-1ß, and cTn-I were examined by ELISA. NADP+/NADPH ratio was measured with the NADP+/NADPH assay kit. RT-PCR was used to detect the levels of PI3K and Akt. The levels of Bax, Bcl-2, Caspase-3, GSK-3ß, PI3K, and Akt were detected by Western blot. RESULTS Baicalein could improve pathological injury. SOD and GSH-Px activity decreased while the level of MDA increased in myocardial tissue. Baicalein treatment enhanced SOD activity in a dose-dependent manner but markedly reduced MDA. Similar changes were observed in both serum inflammatory factors and the NADP+/NADPH ratio. After adding PI3K-Akt inhibitor, the levels of PI3K and Akt mRNA expression were significantly decreased, but were not significantly different from the DCM group. Levels of Bcl-2, PI3K, p-GSK-3ß/GSK-3ß, and p-Akt were decreased in the DCM group, while the levels of Bax and Caspase-3 were obviously increased. CONCLUSIONS Baicalein can protect DCM rats against damage from oxidative stress and inflammation in myocardial tissue, and PI3K/Akt signaling pathway may be involved to mediating these effects.

Calibration transfer of near-infrared spectroscopy by canonical correlation analysis coupled with wavelet transform.

Calibration model transfer has played a prominent role in the practical application of NIR spectral analysis. The change of instruments and sample physical states may lead to variation of the NIR spectrum, which results in the applicability of the model in judicatory practice being unsatisfactory. Therefore, a transfer for the calibration model considering both the variation of instruments and sample states is a necessity to ensure its availability. In this paper, a novel approach, namely canonical correlation analysis coupled with wavelet transform (WTCCA), was proposed for calibration transfer between two near infrared spectrometers (a portable and a laboratory instrument), and simultaneously, among three physical states (tobacco powder, tobacco filament and intact leaf) to determine the content of total sugars, reducing sugars, and nicotine in tobacco leaf samples, respectively. Wavelet transform (WT) is introduced to reduce noise and deduct background shifts from the spectra by compression, and then, calibration transfer by canonical correlation analysis (CTCCA) extracts the compressed spectral similarities using canonical scores for spectra correction. Three similar standardization algorithms, including piecewise direct standardization (PDS), piecewise direct standardization with wavelet transform (WTPDS), and CTCCA were compared with WTCCA to evaluate its relative performance. The obtained results showed that the employment of WTCCA yielded the lowest root mean standard error of prediction (RMSEP) on the three analytes in three physical states. For the tobacco powder dataset, the RMSEP values had a reduction of 25.83%, 13.96%, and 14.22% compared with the values of direct prediction without spectra transfer, respectively. For the tobacco filament dataset, the corresponding values were decreased by 18.06%, 14.90%, and 13.61% and for the intact leaf dataset, the values had dropped by 10.70%, 18.21%, and 28.21%, respectively. In summary, the comprehensive investigation carried out in the present work shows that WTCCA is very appropriate for correcting the variations caused by the change of machines and sample states. Furthermore, WTCCA is a promising calibration transfer method which can be recommended for on-line/in-line application.

Visible-light mediated directed perfluoroalkylation of hydrazones.

Perfluoroalkylation of N-alkylhydrazones has been achieved via visible light mediated photoredox reactions between the hydrazone and perfluoroalkyl iodide (RfI). This protocol provides a convenient and efficient access to a series of perfluoroalkylated aromatic aldehyde hydrazones which tolerates a wide range of functional groups on the aromatic ring, and allows the use different types of primary and secondary perfluoroalkyl iodides with up to eight carbon atoms. Furthermore, aliphatic aldehyde hydrazones and N-monosubstituted hydrazones which are unreactive in previously reported hydrazone perfluoroalkylation reactions now take part in the reaction under our reaction conditions to give a satisfactory yield of products. Stern-Volmer quenching studies and spin-trapping experiments indicated that these reactions proceed by free radical addition of the Rf radical to the azomethine atom followed by one electron oxidation of the hydrazyl radical and deprotonation of the diazenium cation.

[Application of Intelligent Optimization Algorithms to Wavelength Selection of Near-Infrared Spectroscopy].

Near infrared spectroscopy (NIRS) is a kind of indirect analysis technology, whose application depends on the setting up of relevant calibration model. In order to improve interpretability, accuracy and modeling efficiency of the prediction model, wavelength selection becomes very important and it can minimize redundant information of near infrared spectrum. Intelligent optimization algorithm is a sort of commonly wavelength selection method which establishes algorithm model by mathematical abstraction from the background of biological behavior or movement form of material, then iterative calculation to solve combinatorial optimization problems. Its core strategy is screening effective wavelength points in multivariate calibration modeling by using some objective functions as a standard with successive approximation method. In this work, five intelligent optimization algorithms, including ant colony optimization (ACO), genetic algorithm (GA), particle swarm optimization (PSO), random frog (RF) and simulated annealing (SA) algorithm, were used to select characteristic wavelength from NIR data of tobacco leaf for determination of total nitrogen and nicotine content and together with partial least squares (PLS) to construct multiple correction models. The comparative analysis results of these models showed that, the total nitrogen optimums models of dataset A and B were PSO-PLS and GA-PLS models. GA-PLS and SA-PLS models were the optimums for nicotine, respectively. Although not all predicting performance of these optimization models was superior to that of full spectrum PLS models, they were simplified greatly and their forecasting accuracy, precision, interpretability and stability were improved. Therefore, this research will have great significance and plays an important role for the practical application. Meanwhile, it could be concluded that the informative wavelength combination for total nitrogen were 4 587~4 878 and 6 700~7 200 cm(-1), and that for tobacco nicotine were 4 500~4 700 and 5 800~6 000 cm(-1). These selected wavelengths have actually physical significance.

Entity linking for biomedical literature.

BACKGROUND: The Entity Linking (EL) task links entity mentions from an unstructured document to entities in a knowledge base. Although this problem is well-studied in news and social media, this problem has not received much attention in the life science domain. One outcome of tackling the EL problem in the life sciences domain is to enable scientists to build computational models of biological processes with more efficiency. However, simply applying a news-trained entity linker produces inadequate results. METHODS: Since existing supervised approaches require a large amount of manually-labeled training data, which is currently unavailable for the life science domain, we propose a novel unsupervised collective inference approach to link entities from unstructured full texts of biomedical literature to 300 ontologies. The approach leverages the rich semantic information and structures in ontologies for similarity computation and entity ranking. RESULTS: Without using any manual annotation, our approach significantly outperforms state-of-the-art supervised EL method (9% absolute gain in linking accuracy). Furthermore, the state-of-the-art supervised EL method requires 15,000 manually annotated entity mentions for training. These promising results establish a benchmark for the EL task in the life science domain. We also provide in depth analysis and discussion on both challenges and opportunities on automatic knowledge enrichment for scientific literature. CONCLUSIONS: In this paper, we propose a novel unsupervised collective inference approach to address the EL problem in a new domain. We show that our unsupervised approach is able to outperform a current state-of-the-art supervised approach that has been trained with a large amount of manually labeled data. Life science presents an underrepresented domain for applying EL techniques. By providing a small benchmark data set and identifying opportunities, we hope to stimulate discussions across natural language processing and bioinformatics and motivate others to develop techniques for this largely untapped domain.

Hydrogen diffusion and stabilization in single-crystal VO2 micro/nanobeams by direct atomic hydrogenation.

We report measurements of the diffusion of atomic hydrogen in single crystalline VO2 micro/nanobeams by direct exposure to atomic hydrogen, without catalyst. The atomic hydrogen is generated by a hot filament, and the doping process takes place at moderate temperature (373 K). Undoped VO2 has a metal-to-insulator phase transition at ∼340 K between a high-temperature, rutile, metallic phase and a low-temperature, monoclinic, insulating phase with a resistance exhibiting a semiconductor-like temperature dependence. Atomic hydrogenation results in stabilization of the metallic phase of VO2 micro/nanobeams down to 2 K, the lowest point we could reach in our measurement setup. Optical characterization shows that hydrogen atoms prefer to diffuse along the c axis of rutile (a axis of monoclinic) VO2, along the oxygen "channels". Based on observing the movement of the hydrogen diffusion front in single crystalline VO2 beams, we estimate the diffusion constant for hydrogen along the c axis of the rutile phase to be 6.7 × 10(-10) cm(2)/s at approximately 373 K, exceeding the value in isostructural TiO2 by ∼38×. Moreover, we find that the diffusion constant along the c axis of the rutile phase exceeds that along the equivalent a axis of the monoclinic phase by at least 3 orders of magnitude. This remarkable change in kinetics must originate from the distortion of the "channels" when the unit cell doubles along this direction upon cooling into the monoclinic structure. Ab initio calculation results are in good agreement with the experimental trends in the relative kinetics of the two phases. This raises the possibility of a switchable membrane for hydrogen transport.

In situ diffraction study of catalytic hydrogenation of VO2: stable phases and origins of metallicity.

Controlling electronic population through chemical doping is one way to tip the balance between competing phases in materials with strong electronic correlations. Vanadium dioxide exhibits a first-order phase transition at around 338 K between a high-temperature, tetragonal, metallic state (T) and a low-temperature, monoclinic, insulating state (M1), driven by electron-electron and electron-lattice interactions. Intercalation of VO2 with atomic hydrogen has been demonstrated, with evidence that this doping suppresses the transition. However, the detailed effects of intercalated H on the crystal and electronic structure of the resulting hydride have not been previously reported. Here we present synchrotron and neutron diffraction studies of this material system, mapping out the structural phase diagram as a function of temperature and hydrogen content. In addition to the original T and M1 phases, we find two orthorhombic phases, O1 and O2, which are stabilized at higher hydrogen content. We present density functional calculations that confirm the metallicity of these states and discuss the physical basis by which hydrogen stabilizes conducting phases, in the context of the metal-insulator transition.

[Study on the polarized reflectance characteristics of single greenhouse tomato nutrient deficiency leaves].

In order to improve accuracy of quantitative analysis model for the greenhouse tomato nitrogen, phosphorus and potassium nutrient stress, and explore the advantages of polarization non-destructive detection in single-leaf plants scale, polarized reflectance characteristics of greenhouse nutrient deficiency tomato leaves in different growing seasons and different deficiency extents were both examined via means of polarized reflectance spectroscopy system, which was self-developed by the research group. The main factors with effects on the polarized reflectance characteristics of tomato leaves were discussed, such as incident zenith angle, azimuth angle, detection zenith angle, light source polarizer degree, and detector polarizer degree. Experiments were carried out to verify the optimum level of above five parameters by means of range analysis of orthogonal experiments, through that way we can know the best angle combination of five parameters. Based on the above analysis, the angle combination and sorting of detecting tomato nutrients deficiency leaves via means of polarization spectroscopy system were obtained as follows: incident zenith angle 60 degrees, light source polarizer degree 0 degrees, detection zenith angle 45 degrees, detector polarizer degree 45 degrees and azimuth angle 180 degrees. At the same time, both the spectra of nitrogen, phosphorus and potassium deficiency leaves in different growth stages and different deficiency extent leaves were compared with each other. Results show that there is a positive correlation between the greenhouse nutrient deficiency tomato leaves growth cycle and tomato leaves polarized reflectance spectra. Nutrient excess or nutrient deficiency can both lead to polarized reflectance decline and polarized reflectance decline extent of greenhouse tomato leaves is more obvious during the fruiting and harvest period. This paper has a certain theoretical and practical significance in the research on nutrition rapid detection on the plant single leaf scale by means of polarized reflectance spectrum.

Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models.

Structure-based drug design (SBDD) is crucial for developing specific and effective therapeutics against protein targets but remains challenging due to complex protein-ligand interactions and vast chemical space. Although language models (LMs) have excelled in natural language processing, their application in SBDD is underexplored. To bridge this gap, we introduce a method, known as Frag2Seq, to apply LMs to SBDD by generating molecules in a fragment-based manner in which fragments correspond to functional modules. We transform 3D molecules into fragment-informed sequences using SE(3)-equivariant molecule and fragment local frames, extracting SE(3)-invariant sequences that preserve geometric information of 3D fragments. Furthermore, we incorporate protein pocket embeddings obtained from a pre-trained inverse folding model into the LMs via cross-attention to capture protein-ligand interaction, enabling effective target-aware molecule generation. Benefiting from employing LMs with fragment-based generation and effective protein context encoding, our model achieves the best performance on binding vina score and chemical properties such as QED and Lipinski, which shows our model's efficacy in generating drug-like ligands with higher binding affinity against target proteins. Moreover, our method also exhibits higher sampling efficiency compared to atom-based autoregressive and diffusion baselines with at most ~300x speedup.

Recent developments in ureteral stent: Substrate material, coating polymer and technology, therapeutic function.

The ureteral stent is an effective treatment for clinical ureteral stricture following urological surgery, and the functional coating of the stent could effectively inhibit bacterial colonization and other complications. The present review provides an analysis and description of the materials used in ureteral stents and their coatings. Emphasis is placed on the technological advancements of functional coatings, taking into consideration the characteristics of these materials and the properties of their active substances. Furthermore, recent advances in enhancing the therapeutic efficacy of functional coatings are also reviewed. It is anticipated that this article will serve as a valuable reference providing insights for future research development on new drug-loaded ureteral stents.

Salvinorin A ameliorates pilocarpine-induced seizures by regulating hippocampal microglia polarization.

ETHNOPHARMACOLOGICAL RELEVANCE: Salvia divinorum (Epling and Játiva) is a psychoactive plant traditionally used by the Latinos for various medicinal purposes. Salvinorin A (Sal A), the main bioactive constituent of S. divinorum, is a natural highly selective kappa opioid receptor (KOR) agonist. Considering the anti-inflammatory effect of S. divinorum and endogenous hippocampal dynorphin/kappa opioid receptor (KOR) system playing an anticonvulsant function, we hypothesis that Sal A can be a potential candidate to treat epilepsy. Here, we identified whether Sal A ameliorated epileptic seizures and neuronal damages in animal model and in vitro model and investigated its underlying mechanisms. MATERIALS AND METHODS: Mice epilepsy model was induced by pilocarpine following seizures assessed by Racine classification. Hippocampus tissues were obtained for genetic, protein, and histological investigation. Furthermore, lipopolysaccharide (LPS)-activated BV2 microglial cells were utilized to validate the anti-inflammatory and microglia polarization regulation effects of Sal A. RESULTS: Sal A treatment significantly prolonged the latency to status epileptics (SE) and shortened the duration of SE in the pilocarpine-induced model. It also alleviated neuronal damages via activation of the AMPK/JNK/p-38 MAPK pathway and inhibition of apoptosis-related protein in hippocampus tissues. Furthermore, Sal A dose-dependently reduced microglia-mediated expression of pro-inflammatory cytokines and increased anti-inflammatory factors levels in SE mice and LPS-activated BV2 microglial cells by regulating microglia polarization. In addition, the effect of Sal A in vitro was totally blocked by KOR antagonist nor-BNI. CONCLUSION: Sal A treatment protects against epileptic seizures and neuronal damages in pilocarpine-induced models by suppressing the inflammation response through regulating microglial M1/M2 polarization. This study might serve as a theoretical basis for clinical applications of Sal A and its analogs and provide a new insight into the development of anti-seizure drugs.

The Science of Precision Prevention: Research Opportunities and Clinical Applications to Reduce Cardiovascular Health Disparities.

Precision prevention embraces personalized prevention but includes broader factors such as social determinants of health to improve cardiovascular health. The quality, quantity, precision, and diversity of data relatable to individuals and communities continue to expand. New analytical methods can be applied to these data to create tools to attribute risk, which may allow a better understanding of cardiovascular health disparities. Interventions using these analytic tools should be evaluated to establish feasibility and efficacy for addressing cardiovascular disease disparities in diverse individuals and communities. Training in these approaches is important to create the next generation of scientists and practitioners in precision prevention. This state-of-the-art review is based on a workshop convened to identify current gaps in knowledge and methods used in precision prevention intervention research, discuss opportunities to expand trials of implementation science to close the health equity gaps, and expand the education and training of a diverse precision prevention workforce.