The role of exogenous electron donors for accelerating 2,4,6-trichlorophenol biotransformation and mineralization.

2,4,6-Trichlorophenol (TCP) is a biologically recalcitrant compound, but its biodegradation via reductive dechlorination can be accelerated by adding an exogenous electron donor. In this work, acetate and formate were evaluated for their ability to accelerate TCP reductive dechlorination, as well to accelerate mono-oxygenation of TCP's reduction product, phenol. Acetate and formate accelerated TCP reductive dechlorination, and the impact was proportional to the number of electron equivalents released by oxidation of the donor: 8 e(-) equivalents per mol for acetate, compared to 2 e(-) eq per mol for formate. The acceleration phenomenon was similar for phenol mono-oxygenation, and this increased the rate of TCP mineralization. Compared to endogenous electron equivalents generated by phenol mineralization, the impact of exogenous electron donor was stronger on a per-equivalent basis.

UV photolysis for enhanced phenol biodegradation in the presence of 2,4,6-trichlorophenol (TCP).

A bacterial strain isolated from activated sludge and identified as Bacillus amyloliquefaciens could biodegrade phenol, but 2,4,6-trichlorophenol (TCP) inhibited phenol biodegradation and biomass growth. UV photolysis converted TCP into dichlorocatechol, monochlorophenol, and dichlorophenol, and this relieved inhibition by TCP. Phenol-removal and biomass-growth rates were significantly accelerated after UV photolysis: the monod maximum specific growth rate (µ(max)) increased by 9% after TCP photolysis, and the half-maximum-rate concentration (K(S)) decreased by 36%. Thus, the major benefit of UV photolysis in this case was to transform TCP into a set of much-less-inhibitory products.

Accelerating Quinoline Biodegradation and Oxidation with Endogenous Electron Donors.

Quinoline, a recalcitrant heterocyclic compound, is biodegraded by a series of reactions that begin with mono-oxygenations, which require an intracellular electron donor. Photolysis of quinoline can generate readily biodegradable products, such as oxalate, whose bio-oxidation can generate endogenous electron donors that ought to accelerate quinoline biodegradation and, ultimately, mineralization. To test this hypothesis, we compared three protocols for the biodegradation of quinoline: direct biodegradation (B), biodegradation after photolysis of 1 h (P1h+B) or 2 h (P2h+B), and biodegradation by adding oxalate commensurate to the amount generated from photolysis of 1 h (O1+B) or 2 h (O2+B). The experimental results show that P1h+B and P2h+B accelerated quinoline biodegradation by 19% and 50%, respectively, compared to B. Protocols O1+B and O2+B also gave 19% and 50% increases, respectively. During quinoline biodegradation, its first intermediate, 2-hydroxyquinoline, accumulated gradually in parallel to quinoline loss but declined once quinoline was depleted. Mono-oxygenation of 2-hydroxyquinoline competed with mono-oxygenation of quinoline, but the inhibition was relieved when extra electrons donors were added from oxalate, whether formed by UV photolysis or added exogenously. Rapid oxalate oxidation stimulated both mono-oxygenations, which accelerated the overall quinoline oxidation that provided the bulk of the electron donor.

Coupling UV-H2O2 to accelerate dimethyl phthalate (DMP) biodegradation and oxidation.

Dimethyl phthalate (DMP), an important industrial raw material, is an endocrine disruptor of concern for human and environmental health. DMP exhibits slow biodegradation, and its coupled treatment by means of advanced oxidation may enhance its biotransformation and mineralization. We evaluated two ways of coupling UV-H2O2 advanced oxidation to biodegradation: sequential coupling and intimate coupling in an internal circulation baffled biofilm reactor (ICBBR). During sequential coupling, UV-H2O2 pretreatment generated carboxylic acids that depressed the pH, and subsequent biodegradation generated phthalic acid; both factors inhibited DMP biodegradation. During intimately coupled UV-H2O2 with biodegradation, carboxylic acids and phthalic acid (PA) did not accumulate, and the biodegradation rate was 13 % faster than with biodegradation alone and 78 % faster than with biodegradation after UV-H2O2 pretreatment. Similarly, DMP oxidation with intimate coupling increased by 5 and 39 %, respectively, compared with biodegradation alone and sequential coupling. The enhancement effects during intimate coupling can be attributed to the rapid catabolism of carboxylic acids, which generated intracellular electron carriers that directly accelerated di-oxygenation of PA and relieved the inhibition effect of PA and low pH. Thus, intimate coupling optimized the impacts of energy input from UV irradiation used together with biodegradation.

SGTR+: End-to-End Scene Graph Generation With Transformer.

Scene Graph Generation (SGG) remains a challenging visual understanding task due to its compositional property. Most previous works adopt a bottom-up, two-stage or point-based, one-stage approach, which often suffers from high time complexity or suboptimal designs. In this paper, we propose a novel SGG method to address the aforementioned issues, formulating the task as a bipartite graph construction problem. To address the issues above, we create a transformer-based end-to-end framework to generate the entity and entity-aware predicate proposal set, and infer directed edges to form relation triplets. Moreover, we design a graph assembling module to infer the connectivity of the bipartite scene graph based on our entity-aware structure, enabling us to generate the scene graph in an end-to-end manner. Based on bipartite graph assembling paradigm, we further propose a new technical design to address the efficacy of entity-aware modeling and optimization stability of graph assembling. Equipped with the enhanced entity-aware design, our method achieves optimal performance and time-complexity. Extensive experimental results show that our design is able to achieve the state-of-the-art or comparable performance on three challenging benchmarks, surpassing most of the existing approaches and enjoying higher efficiency in inference.

Acute lymphoblastic leukemia with pseudo-Chediak-Higashi granules in the initial diagnosis and relapse.

Pseudo-Chediak-Higashi granules are large cytoplasmic inclusions commonly encountered in myeloblasts or other myeloid precursors in acute myeloid leukemia and myelodysplastic syndromes. However, pseudo-Chediak-Higashi granules are rarely found in acute lymphoblastic leukemia (ALL). We present the case of an 8-year-old boy who was diagnosed with ALL with pseudo-Chediak-Higashi granules in the initial diagnosis and relapse, acting like a characteristic marker.

Atmospheric brown carbon in China haze is dominated by secondary formation.

Brown carbon (BrC) is a class of light-absorbing organic aerosols (OA) and has significant influence on atmospheric radiative forcing. However, the current limited understanding of the physicochemical properties of BrC restricts the accurate evaluation of its environmental effects. Here the optical characteristics and chemical composition of BrC during wintertime in the Yangtze River Delta (YRD) region, China were measured by using high-resolution aerosol mass spectrometry (HR-AMS) and UV-vis spectrometry. Our results showed that BrC in PM2.5 during the campaign was dominated by water-soluble organics, which consist of less oxidized oxygenated OA (LO-OOA), more oxidized oxygenated OA (MO-OOA), fossil fuel OA (FFOA) and biomass burning OA (BBOA). MO-OOA and BBOA were the strongest light absorbing BrC at 365 nm (Abs365), followed by LO-OOA and FFOA with a mass absorption coefficient (MAC) being 0.74 ± 0.04, 0.73 ± 0.03, 0.48 ± 0.04 and 0.39 ± 0.06 m2 g-1 during the campaign, respectively. In the low relative humidity (RH < 80 %) haze periods Abs365 of LO-OOA contributed to 44 % of the total light absorption at 365 nm, followed by MO-OOA (31 %), FFOA (21 %) and BBOA (4 %). In contrast, in the high-RH (RH > 80 %) haze periods Abs365 was dominated by MO-OOA, which accounted for 62 % of the total Abs365, followed by LO-OOA (17 %), BBOA (13 %) and FFOA (8 %). Chemical composition analysis further showed that LO-OOA and MO-OOA are produced from gas-phase photooxidation of VOCs and aerosol aqueous reactions, respectively, in which ammonia significantly enhanced the formation and light absorption of BrC in the high RH haze period. On average, >75 % of the total Abs365nm in the YRD region during the haze events was contributed by LO-OOA and MO-OOA, suggesting that atmospheric BrC in China haze periods is predominantly formed by secondary reactions.

Upcycle polyethylene terephthalate waste by photoreforming: Bifunction of Pt cocatalyst.

Upcycle polyethylene terephthalate (PET) waste by photoreforming (PR) is a sustainable and green approach to tackle environmental problems but with challenges to obtain valuable oxidation products and high purity hydrogen simultaneously. Noble metal cocatalysts are essential to enhance the overall PR reaction efficacy. In this work, TiO2 nanotubes (TiO2 NTs) decorated with single Pt atoms (Pt1/TiO2) or Pt nanoparticles (PtNPs/TiO2) are used in the photoreforming reaction (in one batch), and the oxidation products from ethylene glycol (EG, hydrolysed product of PET) in liquid phase and hydrogen are detected. With Pt1/TiO2, EG is oxidized to glyoxal, glyoxylate or lactate, and hydrogen evolution rate (r H2) reaches 51.8 µmol⋅h-1⋅gcat-1, that is 30 times higher than that of TiO2. For PtNPs/TiO2 (size of Pt NPs: 1.97 nm), hydrogen evolution reaches 219.1 µmol⋅h-1⋅gcat-1, but with the oxidation product of acetate only. DFT calculation demonstrates that for Pt NPs, the reaction path for hydrogen evolution is preferred thermodynamically, due to the formation of Schottky junction. On the oxidation of EG, theoretical and spectroscopic analysis suggest that bidentate adsorption of EG at the interface is facile on Pt1/TiO2, compared to that on PtNPs/TiO2 (two Pt sites), but oxidation products, adsorb less strongly, compared to PtNPs/TiO2, that eventually regulates the distribution of oxidation products. The results thus demonstrate the bifunctions of Pt in the PR reaction, i.e., electron transfer mediator for hydrogen evolution and reactive sites for molecules adsorption. The oxidation reaction is dominated by the adsorption-desorption behavior of molecules but the reduction reaction is controlled by the electron transfer. In addition, acidification of pretreated PET alkaline solution achieves separation of pure terephthalic acid (PTA), which further improves the reaction efficiency possibly by offering high density of active sites and acidic environment. Our work thus demonstrates that to upcycle PET plastics, an optimized process can be reached by atomic design of photocatalysts and proper treatment on the plastic wastes.

Downregulation of miR-181c-5p in Alzheimer's disease weakens the response of microglia to Aß phagocytosis.

Alzheimer's disease (AD) is an age-associated neurodegenerative disease. Recently, studies have demonstrated the potential involvement of microRNA-181c-5p (miR-181c-5p) in AD. However, the mechanism through which miR-181c-5p is responsible for the onset and progression of this disease remains unclear, and our study aimed to explore this problem. Differential expression analysis of the AD dataset was performed to identify dysregulated genes. Based on hypergeometric analysis, AD differential the upstream regulation genes miR-181c-5p was found. We constructed a model where SH-SY5Y and BV2 cells were exposed to Aß1-42 to simulate AD. Levels of tumor necrosis factor-alpha, interleukin-6, and IL-1ß were determined using enzyme-linked immunosorbent assay or reverse transcription quantitative polymerase chain reaction. Phosphorylation levels of p-P38 and P38 were detected by Western blot. The level of apoptosis in BV2 cells under Aß1-42 stress was exacerbated by miR-181c-5p mimic. Downregulated miR-181c-5p impaired the phagocytosis and degradation of Aß by BV2 cells. The release of proinflammatory cytokines in BV2 cells with Aß1-42 stress was alleviated by miR-181c-5p upregulation. Additionally, miR-181c-5p downregulation alleviated the phosphorylation of P38 in Aß1-42-induced SH-SY5Y cells. In conclusion, miR-181c-5p improves the phagocytosis of Aß by microglial cells in AD patients, thereby reducing neuroinflammation.

[Experimental study of radiofrequency ablation of liver in swine].

OBJECTIVE: To explore the feasibility and efficacy of multiple-radiofrequency ablation (RFA) in swine liver. METHODS: One swine undergone percutaneous and intra-operative RFA for three times in succession (an interval of 5 days) guided by real-time ultrasound. Then 6 ablated lesions formed. The outcome of RFA and the change of tissues adjacent to ablated lesions (biliary, liver vascular and abdominal wall) were observed by trans-abdominal ultrasonography (US), contrast enhanced ultrasound (CEUS), intra-operative ultrasound (IOUS) and contrast enhanced computed tomography (CT). RESULTS: Bile duct dilatation was found beside primary porta hepatis on US, CT, IOUS after RFA. There was no thrombus in liver vein through the ablated lesion with electrodes parallel to primary porta hepatis. Two ablated lesions were incompletely fused together. Small thermal injury was observed on abdominal wall after an injection of saline into subcapsular gap. Subcapsular hepatic tissue around ablation lesion changed into coagulative necrosis from hyperemia with elapsing time. Carbonizing granule formed during RFA on the top of intro-operative radio-frequency electrode easily caused bleeding along the withdrawing passage. Gelfoam was helpful to stop bleeding during intro-operative RFA. Occluding blood flow into liver definitely enlarged ablated area with the same amount of RFA energy. CONCLUSION: Multiple-RFA is feasible and efficacious for patients with RFA indication. But the complications of RFA increase if the ablation areas are adjacent to such organs as bile duct, stomach, intestine and diaphragm, etc.

Noble-Metal-Free Single- and Dual-Atom Catalysts for Artificial Photosynthesis.

Artificial photosynthesis enables direct solar-to-chemical energy conversion aimed at mitigating environmental pollution and producing solar fuels and chemicals in a green and sustainable approach, and efficient, robust, and low-cost photocatalysts are the heart of artificial photosynthesis systems. As an emerging new class of cocatalytic materials, single-atom catalysts (SACs) and dual-atom catalysts (DACs) have received a great deal of current attention due to their maximal atom utilization and unique photocatalytic properties, whereas noble-metal-free ones impart abundance, availability, and cost-effectiveness allowing for scalable implementation. This review outlines the fundamental principles and synthetic methods of SACs and DACs and summarizes the most recent advances in SACs (Co, Fe, Cu, Ni, Bi, Al, Sn, Er, La, Ba, etc.) and DACs (CuNi, FeCo, InCu, KNa, CoCo, CuCu, etc.) based on non-noble metals, confined on an arsenal of organic or inorganic substrates (polymeric carbon nitride, metal oxides, metal sulfides, metal-organic frameworks, carbon, etc.) acting as versatile scaffolds in solar-light-driven photocatalytic reactions, including hydrogen evolution, carbon dioxide reduction, methane conversion, organic synthesis, nitrogen fixation, hydrogen peroxide production, and environmental remediation. The review concludes with the challenges, opportunities, and future prospects of noble-metal-free SACs and DACs for artificial photosynthesis.

An enhanced decision-making framework for predicting future trends of sharing economy.

This work aims to provide a reliable and intelligent prediction model for future trends in sharing economy. Moreover, it presents valuable insights for decision-making and policy development by relevant governmental bodies. Furthermore, the study introduces a predictive system that incorporates an enhanced Harris Hawk Optimization (HHO) algorithm and a K-Nearest Neighbor (KNN) forecasting framework. The method utilizes an improved simulated annealing mechanism and a Gaussian bare bone structure to improve the original HHO, termed SGHHO. To achieve optimal prediction performance and identify essential features, a refined simulated annealing mechanism is employed to mitigate the susceptibility of the original HHO algorithm to local optima. The algorithm employs a mechanism that boosts its global search ability by generating fresh solution sets at a specific likelihood. This mechanism dynamically adjusts the equilibrium between the exploration and exploitation phases, incorporating the Gaussian bare bone strategy. The best classification model (SGHHO-KNN) is developed to mine the key features with the improvement of both strategies. To assess the exceptional efficacy of the SGHHO algorithm, this investigation conducted a series of comparative trials employing the function set of IEEE CEC 2014. The outcomes of these experiments unequivocally demonstrate that the SGHHO algorithm outperforms the original HHO algorithm on 96.7% of the functions, substantiating its remarkable superiority. The algorithm can achieve the optimal value of the function on 67% of the tested functions and significantly outperforms other competing algorithms. In addition, the key features selected by the SGHHO-KNN model in the prediction experiment, including " Form of sharing economy in your region " and " Attitudes to the sharing economy ", are important for predicting the future trends of the sharing economy in this study. The results of the prediction demonstrate that the proposed model achieves an accuracy rate of 99.70% and a specificity rate of 99.38%. Consequently, the SGHHO-KNN model holds great potential as a reliable tool for forecasting the forthcoming trajectory of the sharing economy.

[Leukemia Genotype Analysis of Children with Acute Lymphoblastic Leukemia in Yunnan Area].

OBJECTIVE: To analyze 43 leukemia genes in children with acute lymphoblastic leukemia (ALL) in Yunnan province, and provide the basis for the diagnosis and treatment of children with ALL in this area. METHODS: The clinical data of 428 children with newly diagnosed ALL in Yunnan area from January 2015 to December 2020 were retrospectively analyzed. Multiple nested PCR technology was used to detect 43 common leukemia genes. RESULTS: Among the 428 children with ALL, 159 were positive for leukemia genes, with a positive rate of 37.15% (159/428), and a total of 15 leukemia genes were detected. Among the 159 leukemia gene-positive children, ETV6-RUNX1+ accounted for 25.79% (41/159), followed by E2A-PBX1+ and BCR-ABL+, accounting for 24.53% (39/159) and 23.27% (37/159) respectively. MLL+ accounted for 6.29% (10/159), WT1+ accounted for 4.40% (7/159), IKZF1 gene deletion and CRLF2+ accounted for 3.77% (6/159) respectively. The positive rate of MLL (46.15%) was the highest in ＜1-year old group, the positive rate of ETV6-RUNX1 (10.56%) was the highest in 1-10-year old group, and BCR-ABL+ rate (23.65%) was the highest in >10-year old group. The distribution of leukemia genes in different age groups was statistically significant (P <0.05). CONCLUSION: The most common fusion gene of children with ALL in Yunnan is ETV6-RUNX1, followed by E2A-PBX1 and BCR-ABL.

A novel photoelectrochemical sensor based on flower-like SnS2, sea urchin-like AgBiS2 and graphene oxide nanocomposite film for efficient and sensitive detection of acetaminophen in lake water samples.

As an emerging detection technology, photoelectrochemical sensors have been widely noticed for their unique technical features. Among others, the technology has been widely used in the fields of drug, biological antibody or antigen and contaminant detection. Secondly, acetaminophen, as a novel environmental pollutant, is difficult to be degraded in the ecosystem, which in turn causes serious impacts on the ecosystem. Therefore, in this work, we designed a photoelectrochemical sensor based on a composite film of flower-like SnS2, sea urchin-like AgBiS2 and graphene oxide for the detection of acetaminophen in water samples. Among them, graphene oxide, as a two-dimensional carbon-based material, can immobilize other photoelectric materials well. In addition, the flower-like SnS2 and sea urchin-like AgBiS2 can enhance the intensity of the photoelectric response due to their synergistic effect. Notably, the combination of graphene oxide with SnS2 and AgBiS2 revealed an exponential increase in the photoresponse intensity, indicating that SnS2/AgBiS2/GO has a satisfactory photoresponse intensity. At the same time, the photoelectrochemical sensor exhibited sensitive detection performance (LOD = 4 nM) and a wide detection range (0.01-50 µM) for acetaminophen under optimal detection conditions. Moreover, it also showed excellent detection performance in the detection of actual water samples, indicating that it can be applied to the detection of acetaminophen in lakes.

Applicability of RANS models and pressure drop in edge subchannels for 19-pin wire-wrapped fuel bundle channel in CiADS.

The accelerator-driven subcritical system has a strong transmutation ability and high inherent safety, and it is internationally recognized as the most promising long-life nuclear waste disposal device. This study involves the construction of a Visual Hydraulic ExperimentaL Platform (VHELP) for the purpose of evaluating the applicability of Reynolds-averaged Navier-Stokes (RANS) models and analyzing the pressure distribution within the fuel bundle channel of China initiative accelerator-driven system (CiADS). Measurements of thirty differential pressures in edge subchannels within a 19-pin wire-wrapped fuel bundle channel were obtained under different conditions using deionized water. The pressure distribution in the fuel bundle channel at Reynolds numbers of 5000, 7500, 10,000, 12,500, and 15,000 was simulated using Fluent. The results show that RANS models obtained accurate results, and the shear stress transport k-ω model provided the most accurate prediction of the pressure distribution. The difference between the results of the Shear stress transport (SST) k-ω model and experimental data was the smallest, and the maximum difference was ±5.57%. Moreover, the error between the experimental data and numerical results of the axial differential pressure was smaller than that of the transverse differential pressure. The pressure periodicity in axial and transverse directions (one pitch) and a relatively three-dimensional pressure measurements were studied. The static pressure fluctuated and decreased periodically as the z-axis coordinate increased. These results can facilitate research on the cross-flow characteristics of liquid metal-cooled fast reactors.

A non-enzymatic photoelectrochemical sensor based on g-C3N4@CNT heterojunction for sensitive detection of antioxidant gallic acid in food.

Gallic acid (GA) is found in a wide range of natural plants and is relevant to the health of human beings. Here, a photoelectrochemical sensing platform based on g-C3N4@CNT heterojunction has been prepared for the highly sensitive and selective detection of GA. Under the light of xenon lamp, the photocurrent of g-C3N4@CNT is 7 times higher than that of g-C3N4. And the sensor generates 4 times more photocurrent in the presence of GA than without GA. This sensor has a wide linear range from 10 nM to 10 µM with a limit of detection as low as 2 nM. Also, the abundant amino groups of g-C3N4 provide excellent selectivity for the sensor. Furthermore, the sensor can be used for the analysis of GA in black tea samples, which provides a novel and rapid method for the detection of GA in food samples.

Identification of Candidate Genes Associated With Prognosis in Glioblastoma.

Background: Glioblastoma (GBM) is the most common malignant primary brain tumor, which associated with extremely poor prognosis. Methods: Data from datasets GSE16011, GSE7696, GSE50161, GSE90598 and The Cancer Genome Atlas (TCGA) were analyzed to identify differentially expressed genes (DEGs) between patients and controls. DEGs common to all five datasets were analyzed for functional enrichment and for association with overall survival using Cox regression. Candidate genes were further screened using least absolute shrinkage and selection operator (LASSO) and random forest algorithms, and the effects of candidate genes on prognosis were explored using a Gaussian mixed model, a risk model, and concordance cluster analysis. We also characterized the GBM landscape of immune cell infiltration, methylation, and somatic mutations. Results: We identified 3,139 common DEGs, which were associated mainly with PI3K-Akt signaling, focal adhesion, and Hippo signaling. Cox regression identified 106 common DEGs that were significantly associated with overall survival. LASSO and random forest algorithms identified six candidate genes (AEBP1, ANXA2R, MAP1LC3A, TMEM60, PRRG3 and RPS4X) that predicted overall survival and GBM recurrence. AEBP1 showed the best prognostic performance. We found that GBM tissues were heavily infiltrated by T helper cells and macrophages, which correlated with higher AEBP1 expression. Stratifying patients based on the six candidate genes led to two groups with significantly different overall survival. Somatic mutations in AEBP1 and modified methylation of MAP1LC3A were associated with GBM. Conclusion: We have identified candidate genes, particularly AEBP1, strongly associated with GBM prognosis, which may help in efforts to understand and treat the disease.

Identification of molecular signatures associated with sleep disorder and Alzheimer's disease.

Background: Alzheimer's disease (AD) and sleep disorders are both neurodegenerative conditions characterized by impaired or absent sleep. However, potential common pathogenetic mechanisms of these diseases are not well characterized. Methods: Differentially expressed genes (DEGs) were identified using publicly available human gene expression profiles GSE5281 for AD and GSE40562 for sleep disorder. DEGs common to the two datasets were used for enrichment analysis, and we performed multi-scale embedded gene co-expression network analysis (MEGENA) for common DEGs. Fast gene set enrichment analysis (fGSEA) was used to obtain common pathways, while gene set variation analysis (GSVA) was applied to quantify those pathways. Subsequently, we extracted the common genes between module genes identified by MEGENA and genes of the common pathways, and we constructed protein-protein interaction (PPI) networks. The top 10 genes with the highest degree of connectivity were classified as hub genes. Common genes were used to perform Metascape enrichment analysis for functional enrichment. Furthermore, we quantified infiltrating immune cells in patients with AD or sleep disorder and in controls. Results: DEGs common to the two disorders were involved in the citrate cycle and the HIF-1 signaling pathway, and several common DEGs were related to signaling pathways regulating the pluripotency of stem cells, as well as 10 other pathways. Using MEGENA, we identified 29 modules and 1,498 module genes in GSE5281, and 55 modules and 1,791 module genes in GSE40562. Hub genes involved in AD and sleep disorder were ATP5A1, ATP5B, COX5A, GAPDH, NDUFA9, NDUFS3, NDUFV2, SOD1, UQCRC1, and UQCRC2. Plasmacytoid dendritic cells and T helper 17 cells had the most extensive infiltration in both AD and sleep disorder. Conclusion: AD pathology and pathways of neurodegeneration participate in processes contributing in AD and sleep disorder. Hub genes may be worth exploring as potential candidates for targeted therapy of AD and sleep disorder.

Leptin stimulates hepatic activation of thyroid hormones and promotes early posthatch growth in the chicken.

Hepatic iodothyronine deiodinases (Ds) are involved in the conversion of thyroid hormones (THs) which interacts with growth hormone (GH) to regulate posthatch growth in the chicken. Previous studies suggest that leptin-like immunoreactive substance deposited in the egg may serve as a maternal signal to program posthatch growth. To test the hypothesis that maternal leptin may affect early posthatch growth through modifying hepatic activation of THs, we injected 5.0µg of recombinant murine leptin into the albumen of breeder eggs before incubation. Furthermore, chicken embryo hepatocytes (CEHs) were treated with leptin in vitro to reveal the direct effect of leptin on expression and activity of Ds. In ovo leptin administration markedly accelerated early posthatch growth, elevated serum levels of total and free triiodothyronine (tT3 and fT3), while that of total thyroxin (tT4) remained unchanged. Hepatic mRNA expression and activity of D1 which converts T4 to T3 or rT3 to T2, were significantly increased in leptin-treated chickens, while those of D3 which converts T3 to T2 or T4 to rT3, were significantly decreased. Moreover, hepatic expression of GHR and IGF-I mRNA was all up-regulated in leptin-treated chickens. Males demonstrated more pronounced responses. A direct effect of leptin on Ds was shown in CEHs cultured in vitro. Expression and activity of D1 were increased, whereas those of D3 were decreased, in leptin-treated cells. These data suggest that in ovo leptin administration improves early posthatch growth, in a gender-specific fashion, probably through improving hepatic activation of THs and up-regulating hepatic expression of GHR and IGF-I.

DeepPhospho accelerates DIA phosphoproteome profiling through in silico library generation.

Phosphoproteomics integrating data-independent acquisition (DIA) enables deep phosphoproteome profiling with improved quantification reproducibility and accuracy compared to data-dependent acquisition (DDA)-based phosphoproteomics. DIA data mining heavily relies on a spectral library that in most cases is built on DDA analysis of the same sample. Construction of this project-specific DDA library impairs the analytical throughput, limits the proteome coverage, and increases the sample size for DIA phosphoproteomics. Herein we introduce a deep neural network, DeepPhospho, which conceptually differs from previous deep learning models to achieve accurate predictions of LC-MS/MS data for phosphopeptides. By leveraging in silico libraries generated by DeepPhospho, we establish a DIA workflow for phosphoproteome profiling which involves DIA data acquisition and data mining with DeepPhospho predicted libraries, thus circumventing the need of DDA library construction. Our DeepPhospho-empowered workflow substantially expands the phosphoproteome coverage while maintaining high quantification performance, which leads to the discovery of more signaling pathways and regulated kinases in an EGF signaling study than the DDA library-based approach. DeepPhospho is provided as a web server as well as an offline app to facilitate user access to model training, predictions and library generation.