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Gai Ge,1 Jingzhe Shang,2,3 Tian Gan,1 Zhiming Chen,1 Chun Pan,1 Youming Mei,1 Siyu Long,4 Aiping Wu,2,3 Hongsheng Wang1,5,6 1Laboratory of Mycobacteria, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, People’s Republic of China; 2Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China; 3Suzhou Institute of Systems Medicine, Suzhou, People’s Republic of China; 4Department of Dermatology, Beijing Chao-Yang Hospital & Capital Medical University, Beijing, People’s Republic of China; 5National Center for Sexually Transmitted Disease and Leprosy Control, China Centers for Disease Control and Prevention, Nanjing, People’s Republic of China; 6Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, People’s Republic of ChinaCorrespondence: Hongsheng Wang, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 12 Jiang-wang-miao Street, Nanjing, Jiangsu Province, People’s Republic of China, Tel/Fax +86 258 5478953, Email whs33@vip.sina.comPurpose: Psoriasis (Ps) and leprosy are chronic inflammatory skin disorders, characterised by enhanced innate and adaptive immunity. Ps and leprosy rarely coexist. The molecular immune mechanism of the Ps and leprosy rarely coexistence is unclear.Patients and Methods: RNA-sequencing (RNA-seq) was performed on 20 patients with Ps, 5 adults with lepromatous leprosy (L-lep), and 5 patients with tuberculoid leprosy (T-lep) to analyse the differentially expressed genes (DEGs) between them. Moreover, the biological mechanism of Ps and leprosy was explored by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Ontology (GO) analysis, Gene Set Enrichment Analysis analysis, and protein–protein interaction (PPI) analyses. Finally, 13 DEGs of 10 skin biopsies of Ps patients, 6 samples of L-lep patients, 6 samples of T-lep patients and 5 healthy controls were confirmed by quantitative real-time polymerase chain reaction (qRT-PCR).Results: The PPI network was constructed and primarily associated with immune response, IL-17 signalling, and Toll-like receptor pathway between Ps and leprosy. Th17 markers (interleukin (IL)- 19, IL-20, IL-36A, IL-36G, IL-22, IL-17A, and lipocalin-2 (LCN2) had higher expression in Ps than in L-lep and T-lep, whereas macrophage biomarkers (CLEC4E and TREM2), SPP1, and dendritic cell (DC)-related hallmarks (ITGAX) and TNF-a had significantly lower expression across Ps and T-lep than in L-lep.Conclusion: To put it simply, Ps patients with IL-17A, IL-19, IL-20, IL-36A, IL-36G, and IL-22 in conjunction with LCN2 with up-graduated expression might be not susceptible to L-lep. However, high levels of CLEC4E, TREM2, and SPP1 in L-lep patients indicated that they unlikely suffered from Ps.Keywords: psoriasis, leprosy, Th17 cell, macrophage, IL-17A, CLEC4E

Under the premise of the value-belief-norm (VBN) model, this study examined the influence of values, beliefs and norms on social entrepreneurial intention of working adults in China. The cross-sectional design was employed, and an online survey, which involved 1,075 working adults, was conducted. All data were analyzed using partial least squares-structural equation modeling (PLS-SEM). The obtained results showed the significant and positive influence of self-enhancement, openness to change, and self-transcendence on the sense of meaning and purpose. Moreover, the sense of meaning and purpose exhibited significant and positive influence on problem awareness, and problem awareness was found to have positive effect on outcome efficacy. Besides that, the sense of meaning and purpose, problem awareness, outcome efficacy, and injunctive social norms were found to exhibit significant and positive on personal norms. Finally, personal norms and injunctive social norms exhibited statistically significant and positive influence on social entrepreneurial intention. The results of effect size confirmed the considerable influence of personal norms and injunctive social norms on social entrepreneurial intention. Therefore, policy development aimed at promoting socioeconomic and environmental sustainability through social entrepreneurship should comprehensively consider the influence of personal norms and injunctive social norms. Increasing the sense of meaning and purpose of the working population, prompting an increased problem consequence and outcome self-efficacy, as well as instilling personal norms and injunctive social norms through various social and environmental incentives are recommended.

The purpose of this research is to investigate the mediating role of farmers’ adaptive capacity between adaptation practices and economic, social, natural, technological, and institutional limitations. A survey questionnaire was employed to collect data, which was subsequently analysed using PLS-Structural Equation Modelling Structural equation modelling. The entire population was stratified into 27 Pertubuhan Peladang Kawasan out of which 500 targeted respondents were randomly selected from seven strata for data collection. The findings revealed that only 67% of farmers are aware of adaptation practices, while 33% are uninformed. The study also revealed that economic, social, natural, technological, and institutional barriers affect farmers’ adaptive capacity levels and ultimately hamper their adaptation practices. This result further affirms the influence of farmers’ adaptive capacity level on their adaptation behaviour. Adaptation strategies are essential to mitigate the negative effects of climate change. However, the success of these strategies is contingent upon the farmers’ adaptive capacity level, which is strained by several barriers. The findings contribute to the development of a national adaptation plan in a bid to aid the implementation of the 2011–2020 National Agri-Food Policy (NAP) to increase the competitiveness and production capacity of the entire agri-food industry value chain and ensure food security in Malaysia. This study will help policymakers come up with a good policy framework to get rid of the problems that get in the way of adapting to climate change.

Additional file 1. Introduction to ARIMA Model.

Drug design is a crucial step in the drug discovery cycle. Recently, various deep learning-based methods design drugs by generating novel molecules from scratch, avoiding traversing large-scale drug libraries. However, they depend on scarce experimental data or time-consuming docking simulation, leading to overfitting issues with limited training data and slow generation speed. In this study, we propose the zero-shot drug design method DESERT (Drug dEsign by SkEtching and geneRaTing). Specifically, DESERT splits the design process into two stages: sketching and generating, and bridges them with the molecular shape. The two-stage fashion enables our method to utilize the large-scale molecular database to reduce the need for experimental data and docking simulation. Experiments show that DESERT achieves a new state-of-the-art at a fast speed., Comment: NeurIPS 2022 camera-ready

Additional file 2. Jupyter (Python) code used for the ARIMA analysis.

Additional file 3. The monthly reported PTB cases, total population numbers per year and the normalized PTB incidences from January 2014 to December 2020 in China.

The diagnosis of paucibacillary (PB) leprosy often possesses a diagnostic challenge, especially for pure neuritic and lesser skin lesions with the zero bacillary load, requiring a sensitive and accurate diagnostic tool. We have included 300 clinically diagnosed new leprosy cases (comprising 98 PB cases) and analyzed the sensitivity and specificity of PB leprosy cases by nested PCR with folP, gyrA, rpoB, RLEP, and 16SrRNA and Enzyme-linked Immunospot Assay test (ELISPOT) with MMPII, NDO-BSA, and LID-1 antigens by detecting interferon gamma (IFN-γ) release. The overall positivity rates of genes tested in 300 clinical specimens were identified as 55% of 16SrRNA, 59% of RLEP, 59.3% of folP, 57.3% of rpoB, 61% of gyrA while 90% of nested folP, 92.6% of nested rpoB, and 95% of nested gyrA, and 285 (95%) of at least one gene positive cases. For PB specimens, 95% PCR positivity was achieved by three tested genes in nested PCR. The data obtained from ELISPOT for three antigens were analyzed for IFN-γ expression with 600 subjects. Among 98 PB leprosy cases, the sensitivity of MMP II, LID-1, and NDO-BSA was 90%, 87%, and 83%, respectively, and the specificity was 90%, 91%, and 86%, respectively. The total number of cases positive for at least one antigen was 90 (91.8%) in PB, which is significantly higher than that in multibacillary (MB) leprosy (56.7%). The combination of multi-targets nested PCR and ELISPOT assay provides a specific tool to early clinical laboratory diagnosis of PB leprosy cases. The two assays are complementary to each other and beneficial for screening PB patients.

3D graphene (or graphene-like porous carbon) is prepared from precursor lignin separated and purified from alkaline pulp black liquor. The lignin is pretreated using rapid freeze-dry technique for the porous, soft and dispersive microstructure. A special temperature control program is designed to keep the porous structure of lignin particles in the carbonization and graphitization process, avoiding agglomeration. The 3D graphene from lignin consist of curve graphene sheets in dimensions around dozen micrometers, which merge each other with clear dihedral angle and form wood-ear like architecture, different from fullerene like carbon crystals. The porous carbon is characterized and analyzed with FTIR, Raman, XRD, SEM, TEM, XPS, and SSA. A possible chemical mechanism in the synthesis of 3D graphene from lignin precursor is proposed. The aromatic groups and alkane fragments in lignin are decomposed during pyrolysis under high temperature, then the benzene rings compose the graphene sheets, and the sp3 free carbon atoms join the graphene sheets with chemical bonds along the framework of lignin polymer, forming the self-supporting and self-constructing 3D graphene, or porous carbon.

Graphene microcrystal (GMC) is a type of glassy carbon fabricated from lignin, in which the microcrystals of graphene are chemically bonded by sp3 carbon atoms, forming a glass-like microcrystal structure. The lignin is refined from sugarcane bagasse using an ethanol-based organosolv technique which is used for the fabrication of GMC by two technical schemes: The pyrolysis reaction of lignin in a tubular furnace at atmospheric pressure, and the hydrothermal carbonization (HTC) of lignin at lower temperature, followed by pyrolysis at higher temperature. The existence of graphene nanofragments in GMC is proven by Raman spectra and XRD patterns, the ratio of sp2 carbon atoms to sp3 carbon atoms is demonstrated by XPS spectra, and the microcrystal structure is observed in the high-resolution transmission electron microscope (HRTEM) images. Temperature and pressure have an important impact on the quality of GMC samples. With the elevation of temperature, the fraction of carbon increases, while the fraction of oxygen decreases, and the ratio of sp2 to sp3 carbon atoms increases. In contrast to the pyrolysis techniques, the HTC technique needs lower temperatures because of the high vapor pressure of water. In general, with the help of biorefinery, the biomass material, lignin, is found to be qualified and sustainable material for the manufacture of GMC. Lignin acts as a renewable substitute for the traditional raw materials of glassy carbon, copolymer resins of phenol formaldehyde, and furfuryl alcohol-phenol.

A new two-dimensional (2D) carbon crystal, different from graphene, has been prepared from 1,3,5-trihydroxybenzene, consisting of 4-carbon and 6-carbon rings in 1:1 ratio, named 4–6 carbophene by authors, in which all carbon atoms possess sp2 hybrid orbitals with some distortion, forming an extensive conjugated π-bonding planar structure. The angles between the three σ-bonds of the carbon sp2 orbitals are roughly 120°, 90°, and 150°. Each of the three non-adjacent sides of a 6C-ring is shared with a 4C-ring; and each of the two opposite sides of a 4C-ring is shared with a 6C-ring. Dodecagonal holes with a diameter of approximate 5.8 Å are regularly located throughout the 2D carbon crystal. Even though the bond energies in 4–6 carbophene are weaker than those in the graphene, the new planar crystal is quite stable in ambient conditions. The 4–6 carbophene can be synthetized from 1,3,5-trihydroxybenzene or other benzene derivatives through dehydration and polymerization reactions, and may possess several possible patterns that form a family of 2D carbon crystals. A possible side reaction involving 1,3,5-trihydroxybenzene is also discussed, which may produce a carbon-oxygen two dimensional crystal.

In this study, a sugarcane bagasse cellulose bundle crystal is converted to a cellulose few-layer two-dimensional (2D) crystal by a specially designed technique scheme, which consists of (1 → 4)-β-D-glucan chains bound to each other by hydrogen bonds in a plane. A graphene few-layer 2D crystal is fabricated from the cellulose 2D crystal by pyrolysis reaction. The fabricated graphene 2D crystal is further analysed and characterised using scanning electron microscopy, high-resolution transmission electron microscopy (HRTEM), atomic force microscopy, and Raman, X-ray diffraction and X-ray photoelectric spectroscopies. A very clear 2D crystal pattern of graphene is observed in the HRTEM image of the carbon product prepared from the cellulose 2D crystal. As a control, in a parallel experiment, multi-layer graphene (or graphite) is obtained from the cellulose bundle crystal. The following possible mechanism is proposed. During carbonization of the cellulose 2D crystal, the glucose units (C6H10O5)n lose oxygen and hydrogen atoms in the form of water, and the six carbon units (C6)n reorganise, forming the graphene 2D crystal at the structural basis of the 2D crystal of cellulose. The findings from this study provide an economical and environmentally friendly approach to the fabrication of graphene and extend the applications of sustainable biomass cellulose.

Cation–π interaction is comparable and as important as other main molecular interaction types, such as hydrogen bond, electrostatic interaction, van der Waals interaction, and hydrophobic interaction. Cation–π interactions frequently occur in protein structures, because six (Phe, Tyr, Trp, Arg, Lys, and His) of 20 natural amino acids and all metallic cations could be involved in cation–π interaction. Cation–π interactions arise from complex physicochemical nature and possess unique interaction behaviors, which cannot be modeled and evaluated by existing empirical equations and force field parameters that are widely used in the molecular dynamics. In this study, the authors present an empirical approach for cation–π interaction energy calculations in protein interactions. The accurate cation–π interaction energies of aromatic amino acids (Phe, Tyr, and Try) with protonated amino acids (Arg and Lys) and metallic cations (Li+, Na+, K+, and Ca2+) are calculated using B3LYP/6-311+G(d,p) method as the benchmark for the empirical formulization and parameterization. Then, the empirical equations are built and the parameters are optimized based on the benchmark calculations. The cation–π interactions are distance and orientation dependent. Correspondingly, the empirical equations of cation–π interactions are functions of two variables, the distance r and the orientation angle θ. Two types of empirical equations of cation–π interactions are proposed. One is a modified distance and orientation dependent Lennard–Jones equation. The second is a polynomial function of two variables r and θ. The amino acid-based empirical equations and parameters provide simple and useful tools for evaluations of cation–π interaction energies in protein interactions. © 2011 Wiley Periodicals, Inc. J Comput Chem , 2011

Sugarcane bagasse was refined into cellulose, hemicellulose, and lignin using an ethanol-based organosolv technique. The hydrothermal carbonization (HTC) reactions were applied for bagasse and its two components cellulose and lignin. Based on GC-MS analysis, 32 (13+19) organic byproducts were derived from cellulose and lignin, more than the 22 byproducts from bagasse. Particularly, more valuable catechol products were obtained from lignin with 56.8% share in the total GC-MS integral area, much higher than the 2.263% share in the GC-MS integral areas of bagasse. The organic byproducts from lignin make up more than half of the total mass of lignin, indicating that lignin is a chemical treasure storage. In general, bio-refinery and HTC are two effective techniques for the valorization of bagasse and other biomass materials from agriculture and forest industry. HTC could convert the inferior biomass to superior biofuel with higher energy quantity of combustion, at the same time many valuable organic byproducts are produced. Bio-refinery could promote the HTC reaction of biomass more effective. With the help of bio-refinery and HTC, bagasse and other biomass materials are not only the sustainable energy resource, but also the renewable and environment friendly chemical materials, the best alternatives for petroleum, coal and natural gas.

BACKGROUND: The proteins in a family, which perform the similar biological functions, may have very different amino acid composition, but they must share the similar 3D structures, and keep a stable central region. In the conservative structure region similar biological functions are performed by two or three catalytic residues with the collaboration of several functional residues at key positions. Communication signals are conducted in a position network, adjusting the biological functions in the protein family. METHODOLOGY: A computational approach, namely structural position correlation analysis (SPCA), is developed to analyze the correlation relationship between structural segments (or positions). The basic hypothesis of SPCA is that in a protein family the structural conservation is more important than the sequence conservation, and the local structural changes may contain information of biology functional evolution. A standard protein P(0) is defined in a protein family, which consists of the most-frequent amino acids and takes the average structure of the protein family. The foundational variables of SPCA is the structural position displacements between the standard protein P(0) and individual proteins P(i) of the family. The structural positions are organized as segments, which are the stable units in structural displacements of the protein family. The biological function differences of protein members are determined by the position structural displacements of individual protein P(i) to the standard protein P(0). Correlation analysis is used to analyze the communication network among segments. CONCLUSIONS: The structural position correlation analysis (SPCA) is able to find the correlation relationship among the structural segments (or positions) in a protein family, which cannot be detected by the amino acid sequence and frequency-based methods. The functional communication network among the structural segments (or positions) in protein family, revealed by SPCA approach, well illustrate the distantly allosteric interactions, and contains valuable information for protein engineering study.