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Night-shift work and sleep disorders are associated with type 2 diabetes (T2DM), and circadian rhythm disruption is intrinsically involved. Studies have identified several signaling pathways that separately link two melatonin receptors (MT1 and MT2) to insulin secretion and T2DM occurrence, but a comprehensive explanation of the molecular mechanism to elucidate the association between these receptors to T2DM, reasonably and precisely, has been lacking. This review thoroughly explicates the signaling system, which consists of four important pathways, linking melatonin receptors MT1 or MT2 to insulin secretion. Then, the association of the circadian rhythm with MTNR1B transcription is extensively expounded. Finally, a concrete molecular and evolutionary mechanism underlying the macroscopic association between the circadian rhythm and T2DM is established. This review provides new insights into the pathology, treatment, and prevention of T2DM. [ABSTRACT FROM AUTHOR]

A series of proof-of-concept models with different degrees of hydration in the same donor–acceptor system were obtained through a functional motif-oriented structural design and screening strategy. The effect of water molecules on photoinduced electron transfer was explored from a crystallographic perspective for the first time. The reasons for the structural differences caused by different degrees of hydration were also discussed. [ABSTRACT FROM AUTHOR]

A new design strategy through the synergy of Mo(VI)–Mo(V) intervalence charge transfer and π(radical)–π(radical/cation) interactions is proposed to obtain semiconductors with photoresponsive ranges covering the whole UV–SWIR (ultraviolet–shortwave near-infrared; ca. 250–3000 nm) region. With this strategy, a viologen-based molybdate semiconductor with a UV–SWIR photoresponsive range was obtained through UV/X-ray irradiation or thermal annealing. The thermally annealed semiconductor has the highest conversion and the best photocurrent response in the range of 355–2400 nm. [ABSTRACT FROM AUTHOR]

X-ray crystallography is the major approach for atomic-level protein structure determination. Since not all proteins can be easily crystallized, accurate prediction of protein crystallization propensity is critical to guiding the experimental design and improving the success rate of X-ray crystallography experiments. In this work, we proposed a new deep learning pipeline, GCmapCrys, for multi-stage crystallization propensity prediction through integrating graph attention network with predicted protein contact map. Experimental results on 1548 proteins with known crystallization records demonstrated that GCmapCrys increased the value of Matthew's correlation coefficient by 37.0% in average compared to state-of-the-art protein crystallization propensity predictors. Detailed analyses show that the major advantages of GCmapCrys lie in the efficiency of the graph attention network with predicted contact map, which effectively associates the residue-interaction knowledge with crystallization pattern. Meanwhile, the designed four sequence-based features can be complementary to further enhance crystallization propensity proprediction. [Display omitted] • We used predicted protein contact map as information source of residue-interaction at structure-level. • A graph attention network was used to associate residue-interaction knowledge with crystallization pattern. • We designed four complementary sequence-based feature representations to further enhance prediction accuracy. [ABSTRACT FROM AUTHOR]

A novel actinomycete strain, designated XHU 5089T, was isolated from a hypersaline habitat in China. The strain was aerobic, Gram-stain-positive and the optimum NaCl concentration for growth was 1-3 % (w/v). Phylogenetic analysis based on the almost-complete 16S rRNA gene sequence of strain XHU 5089T showed that the organism was related most closely to Glycomyces albusTRM 49136T (97.7 % similarity). However, it had a relatively low mean DNA-DNA relatedness value with G. albusTRM 49136T (18.9±5.8 %). The whole-cell sugar pattern consisted of glucose and galactose. The predominant menaquinones were MK-10(H4) and MK-9(H4). The major fatty acids were anteiso-C15 : 0, iso-C16 : 0, iso-C16 : 1 and anteiso-C17 : 0. The polar lipids consisted of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylinositol, two unidentified glycolipids and two unknown phospholipids. The G+C content of the genomic DNA was 68.6 mol%. A novel species, Glycomyces lacisalsi sp. nov., is proposed, with XHU 5089T (=CCTCC AA 2015034T=KCTC 39688T) as the type strain.