Deep Learning-Assisted Spectrum-Structure Correlation: State-of-the-Art and Perspectives.

Spectrum-structure correlation is playing an increasingly crucial role in spectral analysis and has undergone significant development in recent decades. With the advancement of spectrometers, the high-throughput detection triggers the explosive growth of spectral data, and the research extension from small molecules to biomolecules accompanies massive chemical space. Facing the evolving landscape of spectrum-structure correlation, conventional chemometrics becomes ill-equipped, and deep learning assisted chemometrics rapidly emerges as a flourishing approach with superior ability of extracting latent features and making precise predictions. In this review, the molecular and spectral representations and fundamental knowledge of deep learning are first introduced. We then summarize the development of how deep learning assist to establish the correlation between spectrum and molecular structure in the recent 5 years, by empowering spectral prediction (i.e., forward structure-spectrum correlation) and further enabling library matching and de novo molecular generation (i.e., inverse spectrum-structure correlation). Finally, we highlight the most important open issues persisted with corresponding potential solutions. With the fast development of deep learning, it is expected to see ultimate solution of establishing spectrum-structure correlation soon, which would trigger substantial development of various disciplines.

Impact of CAG repeat length in the androgen receptor gene on male infertility - a meta-analysis.

CAG repeats are polymorphic nucleotide repeats present in the androgen receptor gene. Many studies have estimated the association between CAG repeat length and male infertility, but the conclusions are controversial. Previous meta-analyses have come to different conclusions; however, new studies have been published. An updated meta-analysis was conducted. PubMed, CBM, CNKI and Web of Science databases were systematically searched for studies published from 1 January 2000 to 1 October 2015. Case-control studies on the association between CAG repeat length and male infertility using appropriate methodology were included. Forty studies were selected, including 3858 cases and 3161 controls. Results showed statistically significantly longer CAG repeat length among cases compared with controls (SMD = 0.14; 95% CI, 0.02-0.26). Shorter repeat length was associated with a lower risk of male infertility compared with a longer repeat length in the overall analysis (OR = 0.79, 95% CI: 0.66-0.95). Moreover, CAG repeat length was associated with male infertility in Caucasian populations, but not Asian or Egyptian populations. Subgroup analysis revealed no significant difference in German populations, but CAG repeat length was associated with male infertility in China and the USA. There were no significant differences between cases and controls in azoospermia and severe oligozoospermia.

AgNPs-Triggered Seed Metabolic and Transcriptional Reprogramming Enhanced Rice Salt Tolerance and Blast Resistance.

Seeds are facing harsher environments due to the changing climate. Improving seeds' stress resilience is critical to reduce yield loss. Here, we propose that using ROS-generating nanoparticles (NPs) to prestimulate seeds would enhance the stress resilience of seeds and seedlings through triggering stress/immune responses. We examined this hypothesis by exposing AgNPs-primed rice (Oryza sativa L.) seeds under salt conditions (NaCl). The results showed that primed seeds exhibit accelerated germination speed, increased seedling vigor (from 22.5 to 47.6), biomass (11%), and root length (83%) compared to seeds with hydropriming treatment. Multiomics (metabolomics and transcriptomics) analyses reveal that AgNPs-priming triggered metabolic and transcriptional reprogramming in rice seeds. Signaling metabolites, such as salicylic acid, niacinamide, and glycerol-3-phosphate, dramatically increased upon AgNPs-priming. KEGG pathway analysis reveals that AgNPs-priming activated stress signaling and defense related pathways, such as plant hormone signal transduction, glutathione metabolism, flavone and flavonol biosynthesis, MAPK signaling pathway, and plant-pathogen interaction. These metabolic and transcriptional changes indicate that AgNPs-priming triggered stress/immune responses. More importantly, this "stress memory" can last weeks, providing protection to rice seedlings against salt stress and rice blast fungus (Magnaporthe oryzae). Overall, we show that prestimulated seeds with ROS-generating AgNPs not only enable faster and better germination under stress conditions, but also increase seedling resistance to biotic and abiotic stresses. This simple nanobiostimulant-based strategy may contribute to sustainable agriculture by maintaining agricultural production and reducing the use of pesticides.

Engineering Climate-Resilient Rice Using a Nanobiostimulant-Based "Stress Training" Strategy.

Under a changing climate, cultivating climate-resilient crops will be critical to maintaining food security. Here, we propose the application of reactive oxygen species (ROS)-generating nanoparticles as nanobiostimulants to trigger stress/immune responses and subsequently increase the stress resilience of plants. We established three regimens of silver nanoparticles (AgNPs)-based "stress training": seed training (ST), leaf training (LT), and combined seed and leaf training (SLT). Trained rice seedlings were then exposed to either rice blast fungus (Magnaporthe oryzae) or chilling stress (10 °C). The results show that all "stress training" regimes, particularly SLT, significantly enhanced the resistance of rice against the fungal pathogen (lesion size reduced by 82% relative to untrained control). SLT also significantly enhanced rice tolerance to cold stress. The mechanisms for the enhanced resilience were investigated with metabolomics and transcriptomics, which show that "stress training" induced considerable metabolic and transcriptional reprogramming in rice leaves. AgNPs boosted ROS-activated stress signaling pathways by oxidative post-translational modifications of stress-related kinases, hormones, and transcriptional factors (TFs). These signaling pathways subsequently modulated the expression of defense genes, including specialized metabolites (SMs) biosynthesis genes, cell membrane lipid metabolism genes, and pathogen-plant interaction genes. Importantly, results showed that the "stress memory" can be transferred transgenerationally, conferring offspring seeds with improved seed germination and seedling vigor. This may provide an epigenetic breeding strategy to fortify stress resilience of crops. This nanobiostimulant-based stress training strategy will increase yield vigor against a changing climate and will contribute to sustainable agriculture by reducing agrochemical use.

Association between Serum TNF-α Levels and Recurrent Spontaneous Miscarriage: A Meta-analysis.

Most recurrent spontaneous miscarriages (RSMs) are attributed to 'unexplained' factors, the majority of which are immune factors. Furthermore, clinically, only a small number of RSM patients get early diagnosis by testing for antiphospholipid antibodies, whereas most of the patients, present no specific diagnostic indicators. We performed a meta-analysis of observational studies to detect the association between RSM and TNF-α levels. We searched PubMed, EMBase, ScienceDirect, Web of Science, and Chinese databases (including: Wanfang Data, CNKI, and VIP databases) for articles published up to 2014. Of the 151 initially identified studies, 11 case-control studies with 1371 patients were finally analyzed. Overall, baseline TNF-α levels were higher in patients than in controls. The standardized mean difference of the TNF-α levels of the patients was 2.82 units (95% confidence interval 1.57-4.06) and the overall effect z-score was 4.42 (P < 0.0001). The heterogeneity test revealed significant differences among individual studies (P = 0.000, I(2)  = 98.7%). Serum TNF-α levels were significantly increased in patients relative to those in controls. The heterogeneity could be attributed to the differences in the detection methods and sampling times used in the different studies.