Dissecting Critical Factors for Electrochemical CO2 Reduction on Atomically Precise Au Nanoclusters.

This work investigates the critical factors impacting electrochemical CO2 reduction reaction (CO2 RR) using atomically precise Au nanoclusters (NCs) as electrocatalysts. First, the influence of size on CO2 RR is studied by precisely controlling NC size in the 1-2.5 nm regime. We find that the electrocatalytic CO partial current density increases for smaller NCs, but the CO Faradaic efficiency (FE) is not directly associated with the NC size. This indicates that the surface-to-volume ratio, i.e. the population of active sites, is the dominant factor for determining the catalytic activity, but the selectivity is not directly impacted by size. Second, we compare the CO2 RR performance of Au38 isomers (Au38 Q and Au38 T) to reveal that structural rearrangement of identical size NCs can lead to significant changes in both CO2 RR activity and selectivity. Au38 Q shows higher activity and selectivity towards CO than Au38 T, and density functional theory (DFT) calculations reveal that the average formation energy of the key *COOH intermediate on the proposed active sites is significantly lower on Au38 Q than Au38 T. These results demonstrate how the structural isomerism can impact stabilization of reaction intermediates as well as the overall CO2 RR performance of identical size Au NCs. Overall, this work provides important structure-property relationships for tailoring the NCs for CO2 RR.

Hydrogen Evolution Electrocatalyst Design: Turning Inert Gold into Active Catalyst by Atomically Precise Nanochemistry.

Electrocatalytic hydrogen evolution reaction (HER) holds promise in the renewable clean energy scheme. Crystalline Au and Ag are, however, poor in catalyzing HER, and the ligands on colloidal nanoparticles are generally another disadvantage. Herein, we report a thiolate (SR)-protected Au36Ag2(SR)18 nanocluster with low coverage of ligands and a core composed of three icosahedral (Ih) units for catalyzing HER efficiently. This trimeric structure, together with the monomeric Ih Au25(SR)18- and dimeric Ih Au38(SR)24, constitutes a unique series, providing an opportunity for revealing the correlation between the catalytic properties and the catalyst's structure. The Au36Ag2(SR)18 surprisingly exhibits high catalytic activity at lower overpotentials for HER due to its low ligand-to-metal ratio, low-coordinated Au atoms and unfilled superatomic orbitals. The current density of Au36Ag2(SR)18 at -0.3 V vs RHE is 3.8 and 5.1 times that of Au25(SR)18- and Au38(SR)24, respectively. Density functional theory (DFT) calculations reveal lower hydrogen binding energy and higher electron affinity of Au36Ag2(SR)18 for an energetically feasible HER pathway. Our findings provide a new strategy for constructing highly active catalysts from inert metals by pursuing atomically precise nanoclusters and controlling their geometrical and electronic structures.

Boosting CO2 Electrochemical Reduction with Atomically Precise Surface Modification on Gold Nanoclusters.

Thiolate-protected gold nanoclusters (NCs) are promising catalytic materials for the electrochemical CO2 reduction reaction (CO2 RR). In this work an atomic level modification of a Au23 NC is made by substituting two surface Au atoms with two Cd atoms, and it enhances the CO2 RR selectivity to 90-95 % at the applied potential between -0.5 to -0.9 V, which is doubled compared to that of the undoped Au23 . Additionally, the Cd-doped Au19 Cd2 exhibits the highest CO2 RR activity (2200 mA mg-1 at -1.0 V vs. RHE) among the reported NCs. This synergetic effect between Au and Cd is remarkable. Density-functional theory calculations reveal that the exposure of a sulfur active site upon partial ligand removal provides an energetically feasible CO2 RR pathway. The thermodynamic energy barrier for CO formation is 0.74 eV lower on Au19 Cd2 than on Au23 . These results reveal that Cd doping can boost the CO2 RR performance of Au NCs by modifying the surface geometry and electronic structure, which further changes the intermediate binding energy. This work offers insights into the surface doping mechanism of the CO2 RR and bimetallic synergism.

Toward the Tailoring Chemistry of Metal Nanoclusters for Enhancing Functionalities.

Ultrasmall metal nanoparticles (often called nanoclusters) possess unique geometrical structures and novel functionalities that are not accessible in conventional nanoparticles. Recent progress in their synthesis and structural determination by X-ray crystallography has led to deep understanding of the structural evolution, structure-property correlation, and growth modes, such as the layer-by-layer growth in face-centered cubic (fcc)-type nanoclusters, linear assembly of vertex-shared icosahedral units, and other unique modes. The enriched knowledge on the correlation between the structure and the properties has rendered metal nanoclusters a new class of functional nanomaterials. Despite the significant achievements in structural determinations, mapping out the structure-property correlation is still very challenging because of the core-shell structures of nanoclusters (e.g., Au n(SR) m protected by thiolate ligands) with metal atoms partitioned between the core and the shell. In such structures, the core and the surface are entangled and cannot be separately studied because changing the core structure would inevitably change the surface (or vice versa). Thus, it is of great importance to develop the "tailoring" chemistry for structural modification of the core (or surface) while retaining the other parts, in order to achieve fundamental understanding of what part of the nanocluster structure plays what role in the functionalities. In this Account, we summarize some recent work on the strategies to control the atomic structures of metal nanoclusters for tuning their properties, such as stability, optical absorption, excited-state electron dynamics, and photoluminescence, as well as their catalytic reactivity. The development of a ligand-based strategy has permitted the synthesis of structural isomers of nanoclusters with the same size but different functionalities. Successful modification of the core (or surface) structure while maintaining the other components has led us to gain some fundamental understanding of the respective roles of the core and the surface in the nanocluster functionalities. Such "tailoring" chemistry on metal nanoclusters can provide a strong basis for functional nanomaterials consisting of nanocluster components with desired properties. Further development of the tailoring chemistry will guide materials chemists to new directions and tailor-made functional nanomaterials for specific applications.

Atomically Tailored Gold Nanoclusters for Catalytic Application.

Recent advances in the synthetic chemistry of atomically precise metal nanoclusters (NCs) have significantly broadened the accessible sizes and structures. Such particles are well defined and have intriguing properties, thus, they are attractive for catalysis. Especially, those NCs with identical size but different core (or surface) structure provide unique opportunities that allow the specific role of the core and the surface to be mapped out without complication by the size effect. Herein, we summarize recent work with isomeric Aun NCs protected by ligands and isostructural NCs but with different surface ligands. The highlighted work includes catalysis by spherical and rod-shaped Au25 (with different ligands), quasi-isomeric Au28 (SR)20 with different R groups, structural isomers of Au38 (SR)24 (with identical R) and Au38 S2 (SR)20 with body-centred cubic (bcc) structure, and isostructural [Au38 L20 (PPh3 )4 ]2+ (different L). These isomeric and/or isostructural NCs have provided valuable insights into the respective roles of the kernel, surface staples, and the type of ligands on catalysis. Future studies will lead to fundamental advances and development of tailor-made catalysts.

Cancer as robust intrinsic state shaped by evolution: a key issues review.

Cancer is a complex disease: its pathology cannot be properly understood in terms of independent players-genes, proteins, molecular pathways, or their simple combinations. This is similar to many-body physics of a condensed phase that many important properties are not determined by a single atom or molecule. The rapidly accumulating large 'omics' data also require a new mechanistic and global underpinning to organize for rationalizing cancer complexity. A unifying and quantitative theory was proposed by some of the present authors that cancer is a robust state formed by the endogenous molecular-cellular network, which is evolutionarily built for the developmental processes and physiological functions. Cancer state is not optimized for the whole organism. The discovery of crucial players in cancer, together with their developmental and physiological roles, in turn, suggests the existence of a hierarchical structure within molecular biology systems. Such a structure enables a decision network to be constructed from experimental knowledge. By examining the nonlinear stochastic dynamics of the network, robust states corresponding to normal physiological and abnormal pathological phenotypes, including cancer, emerge naturally. The nonlinear dynamical model of the network leads to a more encompassing understanding than the prevailing linear-additive thinking in cancer research. So far, this theory has been applied to prostate, hepatocellular, gastric cancers and acute promyelocytic leukemia with initial success. It may offer an example of carrying physics inquiring spirit beyond its traditional domain: while quantitative approaches can address individual cases, however there must be general rules/laws to be discovered in biology and medicine.

Size Effects of Atomically Precise Gold Nanoclusters in Catalysis.

The emergence of ligand-protected, atomically precise gold nanoclusters (NCs) in recent years has attracted broad interest in catalysis due to their well-defined atomic structures and intriguing properties. Especially, the precise formulas of NCs provide an opportunity to study the size effects at the atomic level without complications by the polydispersity in conventional nanoparticles that obscures the relationship between the size/structure and properties. Herein, we summarize the catalytic size effects of atomically precise, thioate-protected gold NCs in the range of tens to hundreds of metal atoms. The catalytic reactions include electrochemical catalysis, photocatalysis, and thermocatalysis. With the precise sizes and structures, the fundamentals underlying the size effects are analyzed, such as the surface area, electronic properties, and active sites. In the catalytic reactions, one or more factors may exert catalytic effects simultaneously, hence leading to different catalytic-activity trends with the size change of NCs. The summary of literature work disentangles the underlying fundamental mechanisms and provides insights into the size effects. Future studies will lead to further understanding of the size effects and shed light on the catalytic active sites and ultimately promote catalyst design at the atomic level.

Research progress on the mechanism of angiogenesis in wound repair and regeneration.

Poor wound healing and pathological healing have been pressing issues in recent years, as they impact human quality of life and pose risks of long-term complications. The study of neovascularization has emerged as a prominent research focus to address these problems. During the process of repair and regeneration, the establishment of a new vascular system is an indispensable stage for complete healing. It provides favorable conditions for nutrient delivery, oxygen supply, and creates an inflammatory environment. Moreover, it is a key manifestation of the proliferative phase of wound healing, bridging the inflammatory and remodeling phases. These three stages are closely interconnected and inseparable. This paper comprehensively integrates the regulatory mechanisms of new blood vessel formation in wound healing, focusing on the proliferation and migration of endothelial cells and the release of angiogenesis-related factors under different healing outcomes. Additionally, the hidden link between the inflammatory environment and angiogenesis in wound healing is explored.

Deep Learning for Predicting Distant Metastasis in Patients with Nasopharyngeal Carcinoma Based on Pre-Radiotherapy Magnetic Resonance Imaging.

IMPORTANCE: Accurate pre-treatment prediction of distant metastasis in patients with Nasopharyngeal Carcinoma (NPC) enables the implementation of appropriate treatment strategies for high-risk individuals. PURPOSE: To develop and assess a Convolutional Neural Network (CNN) model using pre-therapy Magnetic Resonance (MR) imaging to predict distant metastasis in NPC patients. METHODS: We retrospectively reviewed data of 441 pathologically diagnosed NPC patients who underwent complete radiotherapy and chemotherapy at Renmin Hospital of Wuhan University (Hubei, China) between February 2012 and March 2018. Using Adobe Photoshop, an experienced radiologist segmented MR images with rectangular regions of interest. To develop an accurate model according to the primary tumour, Cervical Metastatic Lymph Node (CMLN), the largest area of invasion of the primary tumour, and image segmentation methods, we constructed intratumoural and intra-peritumoural datasets that were used for training and test of the transfer learning models. Each model's precision was assessed according to its receiver operating characteristic curve and accuracy. Generated high-risk-related Grad-Cams demonstrated how the model captured the image features and further verified its reliability. RESULTS: Among the four models, all intra-peritumoural datasets performed better than the corresponding intratumoural datasets, with the CMLN intra-peritumoural dataset exhibiting the best performance (average area under the curves (AUCs) = 0.88). There was no significant difference between average AUCs of the Max and NPC tumour datasets. AUCs of the eight datasets for the four models were higher than those of the Tumour-Node-Metastasis staging system (AUC=0.67). In most datasets, the xception model had higher AUCs than other models. The efficientnet-b0 and xception models efficiently extracted high-risk features. CONCLUSION: The CNN model predicted distant metastasis in NPC patients with high accuracy. Compared to the primary tumour, the CMLN better predicted distant metastasis. In addition to intratumoural data, peritumoural information can facilitate the prediction of distant metastasis. With a larger sample size, datasets of the largest areas of tumour invasion may achieve meaningful accuracy. Among the models, xception had the best overall performance.

Chinese expert consensus on the diagnosis and treatment of HER2-altered non-small cell lung cancer.

Human epidermal growth factor receptor 2 (HER2) possesses tyrosine kinase activity and participates in cell growth, differentiation and migration, and survival. Its alterations, mainly including mutations, amplifications, and overexpression are associated with poor prognosis and are one of the major drivers in non-small cell lung cancer (NSCLC). Several clinical trials had been investigating on the treatments of HER2-altered NSCLC, including conventional chemotherapy, programmed death 1 (PD-1) inhibitors, tyrosine kinase inhibitors (TKIs) and antibody-drug conjugates (ADCs), however, the results were either disappointing or encouraging, but inconsistent. Trastuzumab deruxtecan (T-DXd) was recently approved by the Food and Drug Administration as the first targeted agent for treating HER2-mutant NSCLC. Effective screening of patients is the key to the clinical application of HER2-targeted agents such as TKIs and ADCs. Various testing methods are nowadays available, including polymerase chain reaction (PCR), next-generation sequencing (NGS), fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), etc. Each method has its pros and cons and should be reasonably assigned to appropriate patients for diagnosis and guiding treatment decisions. To help standardize the clinical workflow, our expert group reached a consensus on the clinical management of HER2-altered NSCLC, focusing on the diagnosis and treatment strategies.

Recall Network: A Simple Brain-Inspired Algorithm for Classification.

The latest development of neuroscience has deepened the understanding of the information-processing mechanisms in the human brain and inspired a couple of sophisticated computational methods, such as deep learning, memory networks, and hierarchical temporal memory. However, it remains a challenge to explore simpler models due to the high computational cost of the above-mentioned methods. This paper proposes recall network (RN), an intuitive and simple model, that initializes itself by constructing the network path derived from the correlation of features in the training dataset and then makes classification decisions by recalling the paths that are relevant to the features in the test set. The algorithm has been applied to 263 datasets available from UCI Machine Learning Repository, and the classification results of repeated 10-fold cross-validation experiments on Weka demonstrate its competitive performance with prestigious classification algorithms, such as ANN, J48, and KNN.

Ordinal Unsupervised Domain Adaptation With Recursively Conditional Gaussian Imposed Variational Disentanglement.

There has been a growing interest in unsupervised domain adaptation (UDA) to alleviate the data scalability issue, while the existing works usually focus on classifying independently discrete labels. However, in many tasks (e.g., medical diagnosis), the labels are discrete and successively distributed. The UDA for ordinal classification requires inducing non-trivial ordinal distribution prior to the latent space. Target for this, the partially ordered set (poset) is defined for constraining the latent vector. Instead of the typically i.i.d. Gaussian latent prior, in this work, a recursively conditional Gaussian (RCG) set is proposed for ordered constraint modeling, which admits a tractable joint distribution prior. Furthermore, we are able to control the density of content vectors that violate the poset constraint by a simple "three-sigma rule". We explicitly disentangle the cross-domain images into a shared ordinal prior induced ordinal content space and two separate source/target ordinal-unrelated spaces, and the self-training is worked on the shared space exclusively for ordinal-aware domain alignment. Extensive experiments on UDA medical diagnoses and facial age estimation demonstrate its effectiveness.

Contact-electro-catalysis for the degradation of organic pollutants using pristine dielectric powders.

Mechanochemistry has been studied for some time, but research on the reactivity of charges exchanged by contact-electrification (CE) during mechanical stimulation remains scarce. Here, we demonstrate that electrons transferred during the CE between pristine dielectric powders and water can be utilized to directly catalyze reactions without the use of conventional catalysts. Specifically, frequent CE at Fluorinated Ethylene Propylene (FEP) - water interface induces electron-exchanges, thus forming reactive oxygen species for the degradation of an aqueous methyl orange solution. Contact-electro-catalysis, by conjunction of CE, mechanochemistry and catalysis, has been proposed as a general mechanism, which has been demonstrated to be effective for various dielectric materials, such as Teflon, Nylon-6,6 and rubber. This original catalytic principle not only expands the range of catalytic materials, but also enables us to envisage catalytic processes through mechano-induced contact-electrification.

Tailoring the Electron-Phonon Interaction in Au25(SR)18 Nanoclusters via Ligand Engineering and Insight into Luminescence.

Understanding the electron-phonon interaction in Au nanoclusters (NCs) is essential for enhancing and tuning their photoluminescence (PL) properties. Among all the methods, ligand engineering is the most straightforward and facile one to design Au NCs with the desired PL properties. However, a systematic understanding of the ligand effects toward electron-phonon interactions in Au NCs is still missing. Herein, we synthesized four Au25(SR)18- NCs protected by different -SR ligands and carefully examined their temperature-dependent band-gap renormalization behavior. Data analysis by a Bose-Einstein two-oscillator model revealed a suppression of high-frequency optical phonons in aromatic-ligand-protected Au25 NCs. Meanwhile, a low-frequency breathing mode and a quadrupolar mode are attributed as the main contributors to the phonon-assisted nonradiative relaxation pathway in aromatic-ligand-protected Au25 NCs, which is in contrast with non-aromatic-ligand-protected Au25 NCs, in which tangential and radial modes play the key roles. The PL measurements of the four Au25 NCs showed that the suppression of optical phonons led to higher quantum yields in aromatic-ligand-protected Au25 NCs. Cryogenic PL measurements provide insights into the nonradiative energy relaxation, which should be further investigated for a full understanding of the PL mechanism in Au25 NCs.

PRG-1 prevents neonatal stimuli-induced persistent hyperalgesia and memory dysfunction via NSF/Glu/GluR2 signaling.

Neonatal repetitive noxious stimuli (RNS) has been shown to cause long-term harmful effects on nociceptive processing, learning, and memory which persist until adulthood. Plasticity-related gene 1 (PRG-1) regulates synaptic plasticity and functional reorganization in the brain during neuronal development. In this study, neonatal RNS rats were established by repetitive needle pricks to neonatal rats on all four feet to model repetitive pain exposure in infants. Neonatal RNS caused thermal hyperalgesia, mechanical allodynia, learning, and memory impairments which manifested in young rats and persisted until adulthood. Hippocampal PRG-1/N-ethylmaleimide sensitive fusion protein (NSF) interaction was determined to be responsible for the RNS-induced impairment via enhanced extracellular glutamate release and AMPAR GluR2 trafficking deficiency in a cell-autonomous manner. These pathways likely act synergistically to cause changes in dendritic spine density. Our findings suggest that PRG-1 prevents the RNS-induced hyperalgesia, learning, and memory impairment by regulating synaptic plasticity via NSF/Glu/GluR2 signaling.

ALK1 signaling is required for the homeostasis of Kupffer cells and prevention of bacterial infection.

Macrophages are highly heterogeneous immune cells that fulfill tissue-specific functions. Tissue-derived signals play a critical role in determining macrophage heterogeneity. However, these signals remain largely unknown. The BMP receptor activin receptor-like kinase 1 (ALK1) is well known for its role in blood vessel formation; however, its role within the immune system has never been revealed to our knowledge. Here, we found that BMP9/BMP10/ALK1 signaling controlled the identity and self-renewal of Kupffer cells (KCs) through a Smad4-dependent pathway. In contrast, ALK1 was dispensable for the maintenance of macrophages located in the lung, kidney, spleen, and brain. Following ALK1 deletion, KCs were lost over time and were replaced by monocyte-derived macrophages. These hepatic macrophages showed significantly reduced expression of the complement receptor VSIG4 and alterations in immune zonation and morphology, which is important for the tissue-specialized function of KCs. Furthermore, we found that this signaling pathway was important for KC-mediated Listeria monocytogenes capture, as the loss of ALK1 and Smad4 led to a failure of bacterial capture and overwhelming disseminated infections. Thus, ALK1 signaling instructs a tissue-specific phenotype that allows KCs to protect the host from systemic bacterial dissemination.

PRG-1 relieves pain and depressive-like behaviors in rats of bone cancer pain by regulation of dendritic spine in hippocampus.

Rationale: Pain and depression, which tend to occur simultaneously and share some common neural circuits and neurotransmitters, are highly prevalent complication in patients with advanced cancer. Exploring the underlying mechanisms is the cornerstone to prevent the comorbidity of chronic pain and depression in cancer patients. Plasticity-related gene 1 (PRG-1) protein regulates synaptic plasticity and brain functional reorganization during neuronal development or after cerebral lesion. Purinergic P2X7 receptor has been proposed as a therapeutic target for various pain and neurological disorders like depression in rodents. In this study, we investigated the roles of PRG-1 in the hippocampus in the comorbidity of pain and depressive-like behaviors in rats with bone cancer pain (BCP). Methods: The bone cancer pain rat model was established by intra-tibial cell inoculation of SHZ-88 mammary gland carcinoma cells. The animal pain behaviors were assessed by measuring the thermal withdrawal latency values by using radiant heat stimulation and mechanical withdrawal threshold by using electronic von Frey anesthesiometer, and depressive-like behavior was assessed by sucrose preference test and forced swim test. Alterations in the expression levels of PRG-1 and P2X7 receptor in hippocampus were separately detected by using western blot, immunofluorescence and immunohistochemistry analysis. The effects of intra-hippocampal injection of FTY720 (a PRG-1/PP2A interaction activator), PRG-1 overexpression or intra-hippocampal injection of A438079 (a selective competitive P2X7 receptor antagonist) were also observed. Results: Carcinoma intra-tibia injection caused thermal hyperalgesia, mechanical allodynia and depressive-like behaviors in rats, and also induced the deactivation of neurons and dendritic spine structural anomalies in the hippocampus. Western blot, immunofluorescence and immunohistochemistry analysis showed an increased expression of PRG-1 and P2X7 receptor in the hippocampus of BCP rats. Intra-hippocampal injection of FTY720 or A438079 attenuated both pain and depressive-like behaviors. Furthermore, overexpression of PRG-1 in hippocampus has similar analgesic efficacy to FTY720. In addition, they rescued neuron deactivation and dendritic spine anomalies. Conclusion: The results suggest that both PRG-1 and P2X7 receptor in the hippocampus play important roles in the development of pain and depressive-like behaviors in bone cancer condition in rats by dendritic spine regulation via P2X7R/PRG-1/PP2A pathway.

The role of ligands in atomically precise nanocluster-catalyzed CO2 electrochemical reduction.

Ligand effects are of major interest in catalytic reactions owing to their potential critical role in determining the reaction activity and selectivity. Herein, we report ligand effects in the CO2 electrochemical reduction reaction at the atomic level with three unique Au25 nanoclusters comprising the same kernel but different protecting ligands (-XR, where X = S or Se, and R represents the carbon tail). It is observed that a change in the carbon tail shows no obvious impact on the catalytic selectivity and activity, but the anchoring atom (X = S or Se) strongly affects the electrocatalytic selectivity. Specifically, the S site acts as the active site and sustains CO selectivity, while the Se site shows a higher tendency of hydrogen evolution. Density functional theory (DFT) calculations reveal that the energy penalty associated with the *COOH formation is lower on the S site by 0.26 eV compared to that on the Se site. Additionally, the formation energy of the product (*CO) is lower on the sulfur-based Au nanocluster by 0.43 eV. We attribute these energetic differences to the higher electron density on the sulfur sites of the Au nanocluster, resulting in a modified bonding character of the reaction intermediates that reduce the energetic penalty for the *COOH and *CO formation. Overall, this work demonstrates that S/Se atoms at the metal-ligand interface can play an important role in determining the overall electrocatalytic performance of Au nanoclusters.

[Simultaneous determination of five illegal drugs in weight control foods with solid phase extraction-high performance liquid chromatography].

OBJECTIVE: To develop a method for simultaneous determination of hydrochlorothiazide, furosemide, clopamide, bumetanide and sibutramine hydrochloride in weight control foods with solid phase extraction-high performance liquid chromatography. METHODS: The analytes in the samples were extracted with 2% phosphoric acid-methanol (1:1, V/V) solution ultrasonically and centrifuged. The extracts were clean-up with Osis MCX SPE columns, concentrated under weak N2 stream, and reconstituted with 2% phosphoric acid-methanol (1:1, V/V) solution, vortex mixing and centrifugation at 12,000 r/min. The high performance liquid chromatography was performed with Phenomenex C18 (250 x 4.60 mm, 5 microm) as separation column, 0.02 mol/L acetonitrile potassium dihydrogen phosphate buffer as mobile phase, gradient elution of 1.0 mL/min for the flow rate, and 40 degrees C for the column temperature. The standard curve method was used for the quantitative analysis. RESULTS: A good linear range appeared for the five analytes from 0.25 to 100 microg/mL (r > or = 0.999). The detection limits were 5.2-108 microg/kg. The average recoveries were 86.5%-113.1%, with the relative standard deviations of 1.6%-8.9%. CONCLUSION: The proposed method is a reliable method with high selectivity and high sensitivity for the detection of the five illegal chemicals in the weight control foods.

The thermo-regulated genetic switch of deep-sea filamentous phage SW1 and its distribution in the Pacific Ocean.

Viruses, especially bacteriophages, are thought to have important functions in the deep-sea ecosystem, but little is known about the induction mechanism of benthic phages in response to environmental change. Our prior work characterized a cold-active filamentous phage SW1 that infects the deep-sea bacterium Shewanella piezotolerans WP3; however, the underlying mechanism of the putative thermo-regulated genetic switch of SW1 is still unclear. In this study, the DNA copy number and mRNA abundance of the deep-sea phage SW1 were quantified in the whole life cycle of its host S. piezotolerans WP3 at different temperatures. Our results demonstrated that the induction of SW1 is dependent on a threshold temperature (4°C), but this dependency is not proportional to temperature gradient. RNA-Seq analyses revealed two highly transcribed regions at 4°C and verified the presence of a long 3' untranslated region (UTR) in the SW1 genome. Interestingly, recruitment analysis showed that SW1-like inoviruses prevail in deep sea (depth >1000 m) and photic epipelagic and mesopelagic zones (depth <1000 m), which suggested that the thermo-regulated genetic switch revealed in SW1 may be widely distributed in the ocean.