Semi-supervised Double Deep Learning Temporal Risk Prediction (SeDDLeR) with Electronic Health Records.

BACKGROUND: Risk prediction plays a crucial role in planning for prevention, monitoring, and treatment. Electronic Health Records (EHRs) offer an expansive repository of temporal medical data encompassing both risk factors and outcome indicators essential for effective risk prediction. However, challenges emerge due to the lack of readily available gold-standard outcomes and the complex effects of various risk factors. Compounding these challenges are the false positives in diagnosis codes, and formidable task of pinpointing the onset timing in annotations. OBJECTIVE: We develop a Semi-supervised Double Deep Learning Temporal Risk Prediction (SeDDLeR) algorithm based on extensive unlabeled longitudinal Electronic Health Records (EHR) data augmented by a limited set of gold standard labels on the binary status information indicating whether the clinical event of interest occurred during the follow-up period. METHODS: The SeDDLeR algorithm calculates an individualized risk of developing future clinical events over time using each patient's baseline EHR features via the following steps: (1) construction of an initial EHR-derived surrogate as a proxy for the onset status; (2) deep learning calibration of the surrogate along gold-standard onset status; and (3) semi-supervised deep learning for risk prediction combining calibrated surrogates and gold-standard onset status. To account for missing onset time and heterogeneous follow-up, we introduce temporal kernel weighting. We devise a Gated Recurrent Units (GRUs) module to capture temporal characteristics. We subsequently assess our proposed SeDDLeR method in simulation studies and apply the method to the Massachusetts General Brigham (MGB) Biobank to predict type 2 diabetes (T2D) risk. RESULTS: SeDDLeR outperforms benchmark risk prediction methods, including Semi-parametric Transformation Model (STM) and DeepHit, with consistently best accuracy across experiments. SeDDLeR achieved the best C-statistics ( 0.815, SE 0.023; vs STM +.084, SE 0.030, P-value .004; vs DeepHit +.055, SE 0.027, P-value .024) and best average time-specific AUC (0.778, SE 0.022; vs STM + 0.059, SE 0.039, P-value .067; vs DeepHit + 0.168, SE 0.032, P-value <0.001) in the MGB T2D study. CONCLUSION: SeDDLeR can train robust risk prediction models in both real-world EHR and synthetic datasets with minimal requirements of labeling event times. It holds the potential to be incorporated for future clinical trial recruitment or clinical decision-making.

Phytoremediation of metals in oil sands process affected water by native wetland species.

Process affected water and other industrial wastewaters are a major environmental concern. During oil sands mining, large amounts of oil sands process affected water (OSPW) are generated and stored in ponds until reclaimed and ready for surface water discharge. While much research has focused on organics in process waters, trace metals at high concentrations may also pose environmental risks. Phytoremediation is a cost effective and sustainable approach that employs plants to extract and reduce contaminants in water. The research was undertaken in mesocosm scale constructed wetlands with plants exposed to OSPW for 60 days. The objective was to screen seven native emergent wetland species for their ability to tolerate high metal concentrations (arsenic, cadmium, copper, chromium, copper, nickel, selenium, zinc), and then to evaluate the best performing species for OSPW phytoremediation. All native plant species, except Glyceria grandis, tolerated and grew in OSPW. Carex aquatilis (water sedge), Juncus balticus (baltic rush), and Typha latifolia (cattail) had highest survival and growth, and had high metal removal efficiencies for arsenic (81-87 %), chromium (78-86 %), and cadmium (74-84 %), relative to other metals; and greater than 91 % of the dissolved portions were removed. The native plant species were efficient accumulators of all metals, as demonstrated by high root and shoot bioaccumulation factors; root accumulation was greater than shoot accumulation. Translocation factor values were greater than one for Juncus balticus (chromium, zinc) and Carex aquatilis (cadmium, chromium, cobalt, nickel). The results demonstrate the potential suitability of these species for phytoremediation of a number of metals of concern and could provide an effective and environmentally sound remediation approach for wastewaters.

Post-GWAS functional studies reveal an RA-associated CD40-induced NF-kB signal transduction and transcriptional regulation network targeted by class II HDAC inhibitors.

Currently, it remains difficult to identify which single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) are functional and how various functional SNPs (fSNPs) interact and contribute to disease susceptibility. GWAS have identified a CD40 locus that is associated with rheumatoid arthritis (RA). We previously used two techniques developed in our laboratory, single nucleotide polymorphism-next-generation sequencing (SNP-seq) and flanking restriction enhanced DNA pulldown-mass spectrometry (FREP-MS), to determine that the RA risk gene RBPJ regulates CD40 expression via a fSNP at the RA-associated CD40 locus. In the present work, by applying the same approach, we report the identification of six proteins that regulate RBPJ expression via binding to two fSNPs on the RA-associated RBPJ locus. Using these findings, together with the published data, we constructed an RA-associated signal transduction and transcriptional regulation network (STTRN) that functionally connects multiple RA-associated risk genes via transcriptional regulation networks (TRNs) linked by CD40-induced nuclear factor kappa B (NF-kB) signaling. Remarkably, this STTRN provides insight into the potential mechanism of action for the histone deacetylase inhibitor givinostat, an approved therapy for systemic juvenile idiopathic arthritis. Thus, the generation of disease-associated STTRNs based on post-GWAS functional studies is demonstrated as a novel and effective approach to apply GWAS for mechanistic studies and target identification.

Stem cells from human exfoliated deciduous teeth rejuvenate the liver in naturally aged mice by improving ribosomal and mitochondrial proteins.

BACKGROUND AIMS: Aging is accompanied by a decline in cellular proteome homeostasis, mitochondrial, and metabolic function. Mesenchymal stromal cell (MSC) therapies have been reported to extend lifespan and delay some age-related pathologies, yet the anti-aging rate and mechanisms remain unclear. Here, we investigated the effects and mechanism by transplantation of stem cells from human exfoliated deciduous teeth (SHED) into the naturally aged mice model. METHODS: SHED were cultured in vitro and injected into mice by caudal vein. The in vivo imaging uncovered that SHED labeled by DiR dye mainly migrated to the liver, spleen, and lung organs of wild-type mice. As the main metabolic organ and SHED homing place, the liver was selected for proteomics and aging clock algorithm (LiverClock) analysis, which was constructed to estimate the proteomic pattern related to liver age state. RESULTS: After 6 months of continuous SHED injections, the liver proteomic pattern was reversed from senescent (∼30 months) to a youthful state (∼3 months), accompanied with upregulation of hepatocytes marker genes, anti-aging protein Klotho, a global improvement of liver functional pathways proteins, and a dramatic regulation of ribosomal and mitochondrial proteins, including upregulation of translation elongation and ribosome-sparing proteins Rpsa and Rplp0; elongation factors Eif4a1, Eef1b2, Eif5a; protein-folding chaperones Hsp90aa and Hspe1; ATP synthesis proteins Atp5b, Atp5o, Atp5j; and downregulation of most ribosomal proteins, suggesting that the proteome homeostasis destruction and mitochondria dysfunction in the aged mice liver might be relieved after SHED treatment. CONCLUSIONS: SHED treatment could dramatically relieve the senescent state of the aged liver, affect ribosome component proteins and upregulate the ribosomal biogenesis proteins in the aged mice liver. These results may help understand the improvements and mechanisms of SHED treatment in anti-aging.

ApoM suppresses kidney renal clear cell carcinoma growth and metastasis via the Hippo-YAP signaling pathway.

Renal cell carcinoma is one of the most common malignancies worldwide, and kidney renal clear cell carcinoma (KIRC) is the most common histopathological type of renal cell carcinoma. However, the mechanism of KIRC progression remains poorly understood. Apolipoprotein M (ApoM) is a plasma apolipoprotein and a member of the lipid transport protein superfamily. Lipid metabolism is essential for tumor progression, and its related proteins can be used as therapeutic targets for tumors. ApoM influences the development of several cancers, but its relationship with KIRC remains unclear. In this study, we aimed to investigate the biological function of ApoM in KIRC and to reveal its potential molecular mechanisms. We found that ApoM expression was significantly reduced in KIRC and was strongly correlated with patient prognosis. ApoM overexpression significantly inhibited KIRC cell proliferation in vitro, suppressed the epithelial mesenchymal transition (EMT) of KIRC cells, and decreased their metastatic capacity. Additionally, the growth of KIRC cells was inhibited by ApoM overexpression in vivo. In addition, we found that overexpression of ApoM in KIRC attenuated Hippo-YAP protein expression and YAP stability and thus inhibited KIRC growth and progression. Therefore, ApoM may be a potential target for the treatment of KIRC.

Effect of light quality on polyphenol biosynthesis in three varieties of mung bean sprouts with different color seed coats.

KEY MESSAGE: We investigated the mechanism of the effect of different light qualities on the synthesis and regulation of mung bean sprouts. Light quality acts as a signal molecule, strongly enhancing polyphenol biosynthesis in sprouts. Mung bean (Vigna radiata) sprouts are a popular sprouting vegetable all over the world and are an excellent source of polyphenols with high antioxidant activity. This study investigated the effects of light qualities on the kinetic changes and metabolic regulation mechanism of light signal-mediating polyphenols in three mung bean sprout cultivars. Experimental results showed that three light qualities significantly enhanced the contents of caffeic acid, rutin, vitexin, genistin and delphinidin 3-glucoside. Interestingly, ferulic acid and vitexin responded selectively to blue light and red light, severally. Most genes involved in polyphenol biosynthesis were activated under different light quality conditions, resulting in an overaccumulation of phenylpropanoids. Pearson correlation analysis showed that PAL, F3H, F3'H and F3'5'H expression correlated highly with rutin, whereas ANS expression paralleled anthocyanin biosynthesis. Moreover, MYB111, MYB3, MYB4, MYB1 and MYC2 were critical regulators of polyphenol biosynthesis in mung bean sprouts. These changes were likely due to the changes in the expression of the photoreceptor genes CRY-D, PHOT2, PHYE and light response genes (PIF3 and HY5). Our results provide insights into polyphenol biosynthesis in sprouts and microgreens.

High-precision demodulation method for the cobweb FBG sensor network.

To improve the demodulation accuracy and speed of the cobweb fiber Bragg grating (FBG) sensor network, a demodulation algorithm based on a one-dimensional (1D) dilated convolutional neural network (CNN) combined with improved wavelet adaptive threshold de-noising is proposed. The improved wavelet adaptive threshold de-noising algorithm is used to de-noise several highly overlapping sensing signals for accurately measuring optical fiber sensing signals. Using a well-trained 1D dilated CNN model achieves extremely low signal demodulation errors, even with highly overlapping signals. Experiments show that the demodulation scheme improves the detection accuracy of the cobweb FBG sensor network and shortens detection time. Determination of the peak wavelengths of the four highly overlapping sensing signals achieves a root-mean-square error of better than 0.10 pm and an average demodulation time of 15.2 ms.

Gene co-expression network and differential expression analyses of subcutaneous white adipose tissue reveal novel insights into the pathological mechanisms underlying ketosis in dairy cows.

Ketosis is a common nutritional metabolic disease during the perinatal period in dairy cows. Although various risk factors have been identified, the molecular mechanism underlying ketosis remains elusive. In this study, subcutaneous white adipose tissue (sWAT) was biopsied for transcriptome sequencing on 10 Holstein cows with type II ketosis [blood ß-hydroxybutyric acid (BHB) >1.4 mmol/L; Ket group] and another 10 cows without type II ketosis (BHB ≤1.4 mmol/L; Nket group) at d 10 after calving. Serum concentrations of nonesterified fatty acids (NEFA) and BHB, as indicators of excessive fat mobilization and circulating ketone bodies, respectively, were significantly higher in the Ket group than in the Nket group. Aspartate transaminase (AST) and total bilirubin (TBIL), as indicators of liver damage, were higher in the Ket group than in the Nket group. Weighted gene co-expression network analysis (WGCNA) of the sWAT transcriptome revealed modules significantly correlated with serum BHB, NEFA, AST, TBIL, and total cholesterol. The genes in these modules were enriched in the regulation of the lipid biosynthesis process. Neurotrophic tyrosine kinase receptor type 2 (NTRK2) was identified as the key hub gene by intramodular connectivity, gene significance, and module membership. Quantitative reverse transcription PCR analyses for these samples, as well as a set of independent samples, validated the downregulation of NTRK2 expression in the sWAT of dairy cows with type II ketosis. NTRK2 encodes tyrosine protein kinase receptor B (TrkB), which is a high-affinity receptor for brain-derived neurotrophic factor, suggesting that abnormal lipid mobilization in cows with type II ketosis might be associated with impaired central nervous system regulation of adipose tissue metabolism, providing a novel insight into the pathogenesis underlying type II ketosis in dairy cows.

Biochar performance for preventing cadmium and arsenic accumulation, and the health risks associated with mustard (Brassica juncea) grown in co-contaminated soils.

Cadmium (Cd) and arsenic (As) in co-contaminated soil can enter the human body harming health via the food chain, such as vegetables. Biochar derived from waste has been used to reduce heavy metal uptake by plant, but long-term effects of biochar under Cd and As co-contaminated soil needs to be investigated. A following mustard (Brassica juncea) was grown on co-contaminated soil amended with different raw materials of biochar including biochars pyrolyzed by lignite coal (LCB), rice straw (RSB), silkworm excrement (SEB), and sugar refinery sludge (SSB). The results showed that compared to the control, Cd and As contents of mustard shoot in SSB treatment decreased by 45-49% and 19-37% in two growing seasons, respectively, which was the most effective among 4 biochars. This probably due to SSB owns more abundant Fe-O functional groups. Biochar also altered the microbial community composition, specifically SSB increased proteobacteria abundance by 50% and 80% in the first and second growing seasons, thereby promoted the simultaneous immobilization of Cd and As in soils which may reduce the potential risks to humans. In summary, considering the long-term effects and security of SSB application on mustard, not only is it an effective waste recycle option, but it should also be promoted as a promising approach for safe vegetable production in Cd and As co-contaminated soils.

Effect of ultrasonic pretreatment on tocochromanol and carotenoid biofortification in maize (Zea mays L.) seedlings.

BACKGROUND: Maize is a sought-after food crop because it is micronutrient-rich and affordable. It is an excellent source of carotenoids and tocochromanols. To investigate ways to enhance the micronutrients in maize, we grew maize seedlings with ultrasonic pretreatment to study the effect of ultrasound pretreatment on the biofortification of tocochromanols and carotenoids using high-performance liquid chromatography and real-time quantitative polymerase chain reaction. RESULTS: Four tocopherol isomers, three tocotrienol isomers and six carotenoid components were measured in maize seedlings. Compared with the untreated maize seedlings, carotenoid content increased and reached the highest level at 8 min ultrasonic pretreatment (19.21 ± 0.44 µg g-1 fresh weight (FW)), but tocotrienol content evidently decreased. Tocopherol dropped at first but began to rise after 8 min ultrasonic pretreatment (258.1 ± 6.4 µg g-1 FW). In particular, zeaxanthin in maize seedlings doubled after pre-sonication, while lutein was boosted to 11.81 ± 0.20 µg g-1 FW. Ultrasonic pretreatment changed the predominant component of tocochromanols in maize seedlings from γ-tocotrienol to α-tocopherol, with the latter content being 1.3 times higher than in the untreated group. Up-regulation of key genes involved in the biosynthesis of tocopherols and carotenoids in maize seedlings occurred as a result of both 2 min and 6 min sonication pretreatment. In particular, Zm HPPD, Zm ZE, Zm ZDS and Zm MPBQ-MT could partly explain the changes in these phytochemicals. CONCLUSION: Wet ultrasonic pretreatment could increase tocopherol and carotenoid accumulation in maize seedlings but decrease tocotrienol synthesis. Some up-regulating genes are related to relevant syntheses, such as Zm HPPD, Zm ZE, Zm ZDS and Zm MPBQ-MT, which could influence the accumulation of tocopherols and carotenoids after ultrasonic pretreatment. © 2022 Society of Chemical Industry.

A Highly Stable Organic Luminescent Diradical.

It is very challenging to obtain stable room-temperature luminescent open-shell singlet diradicals. Herein we report the first stable Müller's hydrocarbon TTM-PhTTM with luminescent properties. Variable-temperature electron paramagnetic resonance spectroscopy measurements and theoretical calculations show that TTM-PhTTM has an open-shell singlet ground state with a diradical character of 90 %. Because of a small singlet-triplet energy gap, the open-shell singlet ground state can be thermally excited to a triplet state. TTM-PhTTM shows room-temperature deep-red emission in various solutions. Unusually high stability of TTM-PhTTM was also observed owing to effective steric hindrance and spin delocalization. Our results are beneficial to the rational design and discovery of more stable luminescent diradical materials.

Core-Shell Reactor Partitioning Enzyme and Prodrug by ZIF-8 for NADPH-Sensitive In Situ Prodrug Activation.

Enzyme-prodrug therapies have shown unique advantages in efficiency, selectivity, and specificity of in vivo prodrug activation. However, precise spatiotemporal control of both the enzyme and its substrate at the target site, preservation of enzyme activity, and in situ substrate depletion due to low prodrug delivery efficiency continue to be great challenges. Here, we propose a novel core-shell reactor partitioning enzyme and prodrug by ZIF-8, which integrates an enzyme with its substrate and increases the drug loading capacity (DLC) using a prodrug as the building ligand to form a Zn-prodrug shell. Cytochrome P450 (CYP450) is immobilized in ZIF-8, and the antitumor drug dacarbazine (DTIC) is coordinated and deposited in its outer layer with a high DLC of 43.6±0.8 %. With this configuration, a much higher prodrug conversion efficiency of CYP450 (36.5±1.5 %) and lower IC50 value (26.3±2.6 µg/mL) are measured for B16-F10 cells with a higher NADPH concentration than those of L02 cells and HUVECs. With the tumor targeting ability of hyaluronic acid, this core-shell enzyme reactor shows a high tumor suppression rate of 96.6±1.9 % and provides a simple and versatile strategy for enabling in vivo biocatalysis to be more efficient, selective, and safer.

Volatiles Accumulation during Young Pomelo (Citrus maxima (Burm.) Merr.) Fruits Development.

As widely planted fruits with high nutritional and medical values, pomelos are managed systematically to achieve the largest economic benefits. But the annual shedding of young pomelos, which could be applied as feedstocks for essential oil extraction with their abundant volatiles, leads to a waste of source. The present study selected two commonly planted pomelo (Citrus maxima (Burm.) Merr.) varieties in Southern China, to investigate the volatile profiles during young pomelo fruits development. Combing transcriptomic analysis, this study aimed at identifying the prominent volatile components in young pomelo fruits in order to preferably extract profitable volatiles, as well, increasing the knowledge concerning regulatory roles of transcription factors (TFs) on volatiles accumulation in young pomelos. Totally 29 volatiles were identified, including 14 monoterpenoids and 13 sesquiterpenoids. Diprene was the principal component with the highest amount. Volatiles were generally decreased during fruits development but preferable stages were figured out for volatile collections. 12 and 17 TFs were related to developing time while ERF003 and MYC2 were highly correlated to monoterpenoids. These findings put forward the comprehensive usages of young pomelos and enriched the regulatory roles of TFs on both fruit development and volatiles metabolism.

Stanozolol for the treatment of anemic lower-risk myelodysplastic syndromes without del(5q) after failure of epoetin alfa: findings from a retrospective study.

Options for anemic lower-risk myelodysplastic syndromes (MDS) without del(5q) after failure of erythropoiesis-stimulating agents (ESAs) are very limited. The effectiveness of second-line treatments is uncertain. We retrospectively reviewed the clinical effectiveness and overall survival (OS) of lower-risk MDS without del(5q) patients exclusively treated with stanozolol (STZ) after failure of epoetin alfa. The response was defined according to the 2006 International Working Group (IWG) criteria. Fifty-six patients were included. The median follow-up time was 55 months (range: 5-156 months). Twenty-seven patients (48.2%) achieved hematologic improvement-erythroid response (HI-E). Higher response rates were observed in patients with lower IPSS-R scores (≤3.5, P = 0.008) and hypocellular bone marrow (P = 0.002). In univariate Cox analysis, HI-E was the strongest factor associated with better OS (P = 0.0003). In multivariate Cox, HI-E, age ≤ 50, and transfusion independence (TI) at the onset of STZ were factors associated with better OS. The estimated 5-year OS was 88.6% (68.7-96.2%) and 33.8% (14.9-54.0%) in responders and non-responders (P < 0.01), respectively. The most common side effects included masculinization and liver damage, but they were manageable with supportive measures and dose adjustments. STZ may be considered an alternative treatment in lower-risk MDS after failure of epoetin alfa.

Evaluation of Carotenoids Accumulation and Biosynthesis in Two Genotypes of Pomelo (Citrus maxima) during Early Fruit Development.

Pomelo is rich in bioactive compounds (carotenoids, phenolics and essential oil) in the early stage of fruit development, but it is often wasted in the cultivation and management process. To gain an insight into the carotenoid metabolism pathway in pomelo, the carotenoid profiles and the expression patterns of carotenogenic genes were investigated in two genotypes of pomelo during early fruit development. The results showed that a higher carotenoid content was observed in honey pomelo as compared with golden pomelo, which may be related to different gene regulation mechanisms. Lutein, α-carotene, and ß-carotene were the main carotenoids in pomelo young fruit, and lutein was the highest one. The accumulation of carotenoids during fruit early development in honey pomelo is related to the transcriptional regulation of ZISO and LUT5. In golden pomelo, the rate-limiting gene for carotenoids is PDS and ZDS. In addition, the expression of seven genes except CRTISO in honey pomelo was higher than that in golden pomelo. The results are helpful to further clarify the regulatory mechanism of carotenoid accumulation during early fruit development and provide a direction for the high-value utilization of young fruits in pomelo.

Transcriptomic and metabolomic profiling of a Rhodotorula color mutant to improve its lipid productivity in fed-batch fermentation.

Lipids produced by oleaginous microorganisms enrich the supply of feedstock for bio-fuel. In this study, a mutant (Mut) obtained by UV-nitrosoguanidine mutagenesis turned its colony color from orange-red to light-yellow and showed higher lipid productivity at 37 °C than the original strain Rhodotorula sp. U13N3 (Rht) in the glycerol medium. The metabolic changes between Mut and Rht in batch fermentation were investigated by transcriptomic and metabolomic profiling at the biomass accumulation (30 h) and lipid production (96 h) stages. The average base number in each strain was 5.80 × 109 ± 0.38 × 109 bp (mean ± SD) with 62.43% ± 0.13% GC ratio, and 7499 unigenes were assembled after Illumina sequencing. Moreover, 33 metabolites were quantified by 1H NMR-based profiling. The multi-omics results demonstrated that Mut showed increased glycerol transport and utilization capabilities especially at the first stage (30 h). Then the carbon flux shifted from the TCA cycle to lipid production (96 h). The increased lipid productivity of Mut was partially attributed to the down-regulation of mannitol biosynthesis. However, the mechanism for color change was elusive. At 96 h, the low level of cytosol glycerol probably restricted the lipid production. As a result, supplementation of glycerol in fed-batch fermentation remarkably improved the biomass, lipid production, and lipid content to 34.60 g/L, 25.72 g/L, and 74.3% (w/w dcw), respectively. The cell morphology implied that excessively prolonging the fermentation time was detrimental to the final lipid yield due to cell breakage. In conclusion, the Rhodotorula mutant provided a candidate strain for lipid production with glycerol as the carbon source.

DLDTI: a learning-based framework for drug-target interaction identification using neural networks and network representation.

BACKGROUND: Drug repositioning, the strategy of unveiling novel targets of existing drugs could reduce costs and accelerate the pace of drug development. To elucidate the novel molecular mechanism of known drugs, considering the long time and high cost of experimental determination, the efficient and feasible computational methods to predict the potential associations between drugs and targets are of great aid. METHODS: A novel calculation model for drug-target interaction (DTI) prediction based on network representation learning and convolutional neural networks, called DLDTI, was generated. The proposed approach simultaneously fused the topology of complex networks and diverse information from heterogeneous data sources, and coped with the noisy, incomplete, and high-dimensional nature of large-scale biological data by learning the low-dimensional and rich depth features of drugs and proteins. The low-dimensional feature vectors were used to train DLDTI to obtain the optimal mapping space and to infer new DTIs by ranking candidates according to their proximity to the optimal mapping space. More specifically, based on the results from the DLDTI, we experimentally validated the predicted targets of tetramethylpyrazine (TMPZ) on atherosclerosis progression in vivo. RESULTS: The experimental results showed that the DLDTI model achieved promising performance under fivefold cross-validations with AUC values of 0.9172, which was higher than the methods using different classifiers or different feature combination methods mentioned in this paper. For the validation study of TMPZ on atherosclerosis, a total of 288 targets were identified and 190 of them were involved in platelet activation. The pathway analysis indicated signaling pathways, namely PI3K/Akt, cAMP and calcium pathways might be the potential targets. Effects and molecular mechanism of TMPZ on atherosclerosis were experimentally confirmed in animal models. CONCLUSIONS: DLDTI model can serve as a useful tool to provide promising DTI candidates for experimental validation. Based on the predicted results of DLDTI model, we found TMPZ could attenuate atherosclerosis by inhibiting signal transductions in platelets. The source code and datasets explored in this work are available at https://github.com/CUMTzackGit/DLDTI .

Efficient strand displacement amplification via stepwise movement of a bipedal DNA walker on an electrode surface for ultrasensitive detection of antibiotics.

DNA walkers, one of the artificial molecular machines which are constructed via smart synthetic DNA, have attracted rapidly growing attention from researchers in the biosensing field. In this work, we design an Exonuclease III (Exo III)-aided target-aptamer binding recycling (ETBR) activated bipedal DNA machine for highly sensitive electrochemical detection of antibiotics. To the best of our knowledge, this is the first time that a bipedal DNA machine has been applied in electrochemical sensing for antibiotics. On the one hand, the bipedal DNA walker exceeds the conventional single swing arm DNA walker in terms of walking efficiency and stability. On the other hand, the ETBR strategy, along with efficient strand displacement amplification via stepwise movement of a bipedal DNA walker significantly promotes the signal amplification efficiency. Under optimal conditions, this bipedal DNA machine possesses a detection limit of 7.1 fM within a linear detection range from 10 fM to 100 pM. Moreover, this electrochemical biosensor is expected to detect a wide variety of analytes using the corresponding target recognition probes. Thus, our proposed strategy offers a highly efficient, stable and practical platform for small molecule analysis.

Highly efficient fluorescence sensing of kanamycin using Endo IV-powered DNA walker and hybridization chain reaction amplification.

An ultrasensitive fluorescence sensing strategy for kanamycin (KANA) determination using endonuclease IV (Endo IV)-powered DNA walker, and hybridization chain reaction (HCR) amplification was reported. The sensing system consists of Endo IV-powered 3D DNA walker using for the specific recognition of KANA and the formation of the initiators, two metastable hairpin probes as the substrates of HCR and a tetrahydrofuran abasic site (AP site)-embeded fluorescence-quenched probe for fluorescence signal output. On account of this skilled design of sensing system, the specific binding between KANA and its aptamer activates DNA walker, in which the swing arm can move autonomously along the 3D track via Endo IV-mediated hydrolysis of the anchorages, inducing the formation of initiators that initiates HCR and the following Endo IV-assisted cyclic cleavage of fluorescence reporter probes. The use of Endo IV offers the advantages of simplified and accessible design without the need of specific sequence in DNA substrates. Under the optimal experimental conditions, the fluorescence biosensor shows excellent sensitivity toward KANA detection with a detection limit as low as 1.01 pM (the excitation wavelength is 486 nm). The practical applicability of this strategy is demonstrated by detecting KANA in spiked milk samples with recovery in the range of 98 to 102%. Therefore, this reported strategy might create an accurate and robust fluorescence sensing platform for trace amounts of antibiotic residues determination and related safety analysis. Graphical abstract Highly efficient fluorescence sensing of kanamycin using Endo IV-powered DNA Walker and hybridization chain, reaction amplification, Xiaonan Qu, Jingfeng Wang, Rufeng Zhang, Yihan Zhao, Shasha Li, Yu Wang, Su Liu*, Jiadong Huang, and Jinghua Yu, an ultrasensitive fluorescence sensing strategy for kanamycin determination using endonuclease IV-powered DNA walker, and hybridization chain reaction amplification is reported.

A label-free electrochemical platform for the detection of antibiotics based on cascade enzymatic amplification coupled with a split G-quadruplex DNAzyme.

Herein, a split G-quadruplex DNAzyme as a signal reporter was integrated into an electrochemical sensing platform for the detection of antibiotics with specificity and sensitivity. To improve the signal-to-noise ratio, two G-rich oligonucleotide sequences (G1 and G2) were blocked into two different hairpin probes, preventing the two segments from assembling into a spilt G-quadruplex structure. Moreover, we designed a double-arch probe, consisting of an aptamer as the recognition element and two-step enzymatic signal amplification. Concretely, the first is the Nt.BbvCI-assisted nicking cyclic reaction activated by target-aptamer binding, and the second is exonuclease III-aided cyclic amplification for generating abundant G1 and G2. The modified capture probe on the electrode was used to combine G1 and G2 to form the spilt G-quadruplex/hemin when K+ and hemin were present. This complex plays the role of DNAzyme with superior horseradish peroxidase activity in catalyzing the decomposition of H2O2. Under optimal conditions, this biosensor showed an excellent performance for sensing kanamycin with a detection limit of 83 fM for kanamycin concentrations ranging from 100 fM to 1 nM. Hence, the proposed strategy has potential as an efficient and actual platform for small molecule analysis.