Beating the break-even point with a discrete-variable-encoded logical qubit.

Quantum error correction (QEC) aims to protect logical qubits from noises by using the redundancy of a large Hilbert space, which allows errors to be detected and corrected in real time1. In most QEC codes2-8, a logical qubit is encoded in some discrete variables, for example photon numbers, so that the encoded quantum information can be unambiguously extracted after processing. Over the past decade, repetitive QEC has been demonstrated with various discrete-variable-encoded scenarios9-17. However, extending the lifetimes of thus-encoded logical qubits beyond the best available physical qubit still remains elusive, which represents a break-even point for judging the practical usefulness of QEC. Here we demonstrate a QEC procedure in a circuit quantum electrodynamics architecture18, where the logical qubit is binomially encoded in photon-number states of a microwave cavity8, dispersively coupled to an auxiliary superconducting qubit. By applying a pulse featuring a tailored frequency comb to the auxiliary qubit, we can repetitively extract the error syndrome with high fidelity and perform error correction with feedback control accordingly, thereby exceeding the break-even point by about 16% lifetime enhancement. Our work illustrates the potential of hardware-efficient discrete-variable encodings for fault-tolerant quantum computation19.

Superconductivity in a Layered Cobalt Oxychalcogenide Na2CoSe2O with a Triangular Lattice.

Unconventional superconductivity in bulk materials under ambient pressure is extremely rare among the 3d transition metal compounds outside the layered cuprates and iron-based family. It is predominantly linked to highly anisotropic electronic properties and quasi-two-dimensional (2D) Fermi surfaces. To date, the only known example of a Co-based exotic superconductor is the hydrated layered cobaltate, NaxCoO2·yH2O, and its superconductivity is realized in the vicinity of a spin-1/2 Mott state. However, the nature of the superconductivity in these materials is still a subject of intense debate, and therefore, finding a new class of superconductors will help unravel the mysteries of their unconventional superconductivity. Here, we report the discovery of superconductivity at ∼6.3 K in our newly synthesized layered compound Na2CoSe2O, in which the edge-shared CoSe6 octahedra form [CoSe2] layers with a perfect triangular lattice of Co ions. It is the first 3d transition metal oxychalcogenide superconductor with distinct structural and chemical characteristics. Despite its relatively low TC, this material exhibits very high superconducting upper critical fields, µ0HC2(0), which far exceeds the Pauli paramagnetic limit by a factor of 3-4. First-principles calculations show that Na2CoSe2O is a rare example of a negative charge transfer superconductor. This cobalt oxychalcogenide with a geometrical frustration among Co spins shows great potential as a highly appealing candidate for the realization of unconventional and/or high-TC superconductivity beyond the well-established Cu- and Fe-based superconductor families and opens a new field in the physics and chemistry of low-dimensional superconductors.

UV-B photoreceptor UVR8 interacts with MYB73/MYB77 to regulate auxin responses and lateral root development.

The UV-B photoreceptor UVR8 mediates multiple UV-B responses in plants, but the function of UVR8 in regulating root development has not previously been investigated. Here, we show that UV-B light inhibits Arabidopsis lateral root growth in a UVR8-dependent manner. Monomeric UVR8 inhibits auxin responses in a tissue-autonomous manner and thereby regulates lateral root growth. Genome-wide gene expression analysis demonstrated that auxin and UV-B irradiation antagonistically regulate auxin-regulated gene expression. We further show that UVR8 physically interacts with MYB73/MYB77 (MYB DOMAIN PROTEIN 73/77) in a UV-B-dependent manner. UVR8 inhibits lateral root development via regulation of MYB73/MYB77. When activated by UV-B light, UVR8 localizes to the nucleus and inhibits the DNA-binding activities of MYB73/MYB77 and directly represses the transcription of their target auxin-responsive genes. Our results demonstrate that UV-B light and UVR8 are critical for both shoot morphogenesis and root development. The UV-B-dependent interaction of UVR8 and MYB73/MYB77 serves as an important module that integrates light and auxin signaling and represents a new UVR8 signaling mechanism in plants.

Autonomous Stabilization of Fock States in an Oscillator against Multiphoton Losses.

Fock states with a well-defined number of photons in an oscillator have shown a wide range of applications in quantum information science. Nonetheless, their usefulness has been marred by single and multiphoton losses due to unavoidable environment-induced dissipation. Though several dissipation engineering methods have been developed to counteract the leading single-photon-loss error, averting multiple-photon losses remains elusive. Here, we experimentally demonstrate a dissipation engineering method that autonomously stabilizes multiphoton Fock states against losses of multiple photons using a cascaded selective photon-addition operation in a superconducting quantum circuit. Through measuring the photon-number populations and Wigner tomography of the oscillator states, we observe a prolonged preservation of nonclassical Wigner negativities for the stabilized Fock states |N⟩ with N=1, 2, 3 for a duration of about 10 ms. Furthermore, the dissipation engineering method demonstrated here also facilitates the implementation of a nonunitary operation for resetting a binomially encoded logical qubit. These results highlight potential applications in error-correctable quantum information processing against multiple-photon-loss errors.

Demonstrating Path-Independent Anyonic Braiding on a Modular Superconducting Quantum Processor.

Anyons, exotic quasiparticles in two-dimensional space exhibiting nontrivial exchange statistics, play a crucial role in universal topological quantum computing. One notable proposal to manifest the fractional statistics of anyons is the toric code model; however, scaling up its size through quantum simulation poses a serious challenge because of its highly entangled ground state. In this Letter, we demonstrate that a modular superconducting quantum processor enables hardware-pragmatic implementation of the toric code model. Through in-parallel control across separate modules, we generate a 10-qubit toric code ground state in four steps and realize six distinct braiding paths to benchmark the performance of anyonic statistics. The path independence of the anyonic braiding statistics is verified by correlation measurements in an efficient and scalable fashion. Our modular approach, serving as a hardware embodiment of the toric code model, offers a promising avenue toward scalable simulation of topological phases, paving the way for quantum simulation in a distributed fashion.

Mechanism of Germanium Adsorption by Iron Hydroxide Colloids during the Leaching Process of Secondary Zinc Oxide.

In the leaching process of secondary zinc oxide, there is a problem of germanium loss caused by the colloidal adsorption of germanium by iron hydroxide (Fe(OH)3) formed by Fe3+ hydrolysis. In response to this, this article elucidates the hydrolysis conditions of Fe3+ and the adsorption mechanism of the Fe(OH)3 colloid on germanium through theoretical analysis and simulation of the adsorption process. The coexistence of Fe3+ and H2GeO3 requires high acidity conditions (pH < 1.53 at 25 °C). The adsorption of germanium by the Fe(OH)3 colloid is a spontaneous exothermic entropy reduction process, which conforms to a pseudo-second-order kinetic model and includes three stages: fast, slow, and equilibrium. In addition, the adsorption process can be fitted by the Langmuir isotherm adsorption model, mainly consisting of monolayer and chemical adsorption. The Fe(OH)3 colloid has a great adsorption capacity for germanium at 328 K, and the equilibrium adsorption capacity is 261.15 mg/g in 40 min. During leaching, the adsorption of germanium by Fe(OH)3 colloids can be inhibited by increasing the reaction temperature, controlling the pH value of the solution system, and suppressing the formation of Fe3+ at the source. This study provides direction for how to suppress the adsorption of germanium by Fe(OH)3 colloids during the leaching process of secondary zinc oxide, which is of great significance for improving the germanium leaching efficiency and fully utilizing limited germanium resources.

Two {CuI[P4Mo6]2}-Based Coordination Polymers Incorporating In Situ Converted Tetrapyridyl Ligands for Trace Analysis of Nitrofuran Antibiotics.

Nitrofurans are important synthetic broad-spectrum antibacterial drugs with the basic structure of 5-nitrofuran. Due to their toxicity, it is essential to develop a sensitive sensor with strong anti-interference capabilities for their detection. In this work, two {P4Mo6O31}12--based compounds, [H4(HPTTP)]2{CuI[Mo12O24(OH)6(PO4)3(HPO4)(H2PO4)4]}·xH2O (x = 13 for (1), 7 for (2); HPTTP = 4,4',4″,4‴-(1H-pyrrole-2,3,4,5-tetrayl)tetrapyridine), exhibiting similar coordination but distinct stacking modes. Both compounds were synthesized and used for the electrochemical detection of nitrofuran antibiotics. The tetrapyridine-based ligand was generated in situ during assembly, and its potential mechanism was discussed. Composite electrode materials, formed by mixing graphite powder with compounds 1-2 and physically grinding them, proved to be highly effective in the electrochemical trace detection of furazolidone (FZD) and furaltadone hydrochloride (FTD·HCl) under optimal conditions. Besides, the possible electrochemical detection mechanisms of two nitro-antibiotics were studied.

Predicting who has delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage using machine learning approach: a multicenter, retrospective cohort study.

BACKGROUND: Early prediction of delayed cerebral ischemia (DCI) is critical to improving the prognosis of aneurysmal subarachnoid hemorrhage (aSAH). Machine learning (ML) algorithms can learn from intricate information unbiasedly and facilitate the early identification of clinical outcomes. This study aimed to construct and compare the ability of different ML models to predict DCI after aSAH. Then, we identified and analyzed the essential risk of DCI occurrence by preoperative clinical scores and postoperative laboratory test results. METHODS: This was a multicenter, retrospective cohort study. A total of 1039 post-operation patients with aSAH were finally included from three hospitals in China. The training group contained 919 patients, and the test group comprised 120 patients. We used five popular machine-learning algorithms to construct the models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, and f1 score were used to evaluate and compare the five models. Finally, we performed a Shapley Additive exPlanations analysis for the model with the best performance and significance analysis for each feature. RESULTS: A total of 239 patients with aSAH (23.003%) developed DCI after the operation. Our results showed that in the test cohort, Random Forest (RF) had an AUC of 0.79, which was better than other models. The five most important features for predicting DCI in the RF model were the admitted modified Rankin Scale, D-Dimer, intracranial parenchymal hematoma, neutrophil/lymphocyte ratio, and Fisher score. Interestingly, clamping or embolization for the aneurysm treatment was the fourth button-down risk factor in the ML model. CONCLUSIONS: In this multicenter study, we compared five ML methods, among which RF performed the best in DCI prediction. In addition, the essential risks were identified to help clinicians monitor the patients at high risk for DCI more precisely and facilitate timely intervention.

Genetic variations in MdSAUR36 participate in the negative regulation of mesocarp cell division and fruit size in Malus species.

Final fruit size of apple (Malus domestica) cultivars is related to both mesocarp cell division and cell expansion during fruit growth, but it is unclear whether the cell division and/or cell enlargement determine most of the differences in fruit size between Malus species. In this study, by using an interspecific hybrid population between Malus asiatica "Zisai Pearl" and Malus domestica cultivar "Red Fuji," we found that the mesocarp cell number was the main causal factor of diversity in fruit size between Malus species. Rapid increase in mesocarp cell number occurred prior to 28 days after anthesis (DAA), while cell size increased gradually after 28 DAA until fruit ripening. Six candidate genes related to auxin signaling or cell cycle were predicted by combining the RNA-seq data and previous QTL data for fruit weight. Two InDels and 10 SNPs in the promoter of a small auxin upregulated RNA gene MdSAUR36 in Zisai Pearl led to a lower promoter activity than that of Red Fuji. One non-synonymous SNP G/T at 379 bp downstream of the ATG codon of MdSAUR36, which was heterozygous in Zisai Pearl, exerted significant genotype effects on fruit weight, length, and width. Transgenic apple calli by over-expressing or RNAi MdSAUR36 confirmed that MdSAUR36 participated in the negative regulation of mesocarp cell division and thus apple fruit size. These results could provide new insights in the molecular mechanism of small fruit size in Malus accession and be potentially used in molecular assisted breeding via interspecific hybridization. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01441-4.

Predicting major adverse cardiovascular events within 3 years by optimization of radiomics model derived from pericoronary adipose tissue on coronary computed tomography angiography: a case-control study.

BACKGROUND: Coronary inflammation induces changes in pericoronary adipose tissue (PCAT) can be detected by coronary computed tomography angiography (CCTA). Our aim was to investigate whether different PCAT radiomics model based on CCTA could improve the prediction of major adverse cardiovascular events (MACE) within 3 years. METHODS: This retrospective study included 141 consecutive patients with MACE and matched to patients with non-MACE (n = 141). Patients were randomly assigned into training and test datasets at a ratio of 8:2. After the robust radiomics features were selected by using the Spearman correlation analysis and the least absolute shrinkage and selection operator, radiomics models were built based on different machine learning algorithms. The clinical model was then calculated according to independent clinical risk factors. Finally, an overall model was established using the radiomics features and the clinical factors. Performance of the models was evaluated for discrimination degree, calibration degree, and clinical usefulness. RESULTS: The diagnostic performance of the PCAT model was superior to that of the RCA-model, LAD-model, and LCX-model alone, with AUCs of 0.723, 0.675, 0.664, and 0.623, respectively. The overall model showed superior diagnostic performance than that of the PCAT-model and Cli-model, with AUCs of 0.797, 0.723, and 0.706, respectively. Calibration curve showed good fitness of the overall model, and decision curve analyze demonstrated that the model provides greater clinical benefit. CONCLUSION: The CCTA-based PCAT radiomics features of three major coronary arteries have the potential to be used as a predictor for MACE. The overall model incorporating the radiomics features and clinical factors offered significantly higher discrimination ability for MACE than using radiomics or clinical factors alone.

Preparation and evaluation of germanium concentrate by ultrasonic purification of tannin germanium residue.

Germanium (Ge) is a dispersed metal primarily recovered from secondary Ge-containing resources. The traditional treatment method is hindered by incomplete impurity removal, resulting in a low grade of tannin germanium residue (TGR) and Ge concentrate, high production costs, and significant hazardous waste. This study proposes a new technology involving ultrasonic pre-purification of TGR to enhance the quality of Ge concentrate prepared by roasting. Under optimal conditions (ultrasonic power 225 W, liquid-solid ratio 7:1, H2SO4 concentration 20 g/L, reaction time 30 min, and reaction temperature 40 °C), the removal efficiencies of impurities Zn, Mg, Fe, As, and S from purified tannin germanium residue (PTGR) increased by 4.2%, 4.2%, 17.4%, 8.7%, and 2.9% respectively. Moreover, the Ge content in PTGR increased from 2.9% to 4.1%. The mechanism of ultrasonic action indicated the ultrasonic energy reduced the particle size of the reactants from 67.698 µm to 31.768 µm, thereby accelerating impurity removal. Roasting ultrasonic-purified tannin germanium residue (U-PTGR) at 650 °C with 40 L/h air flow for 120 min produced Ge concentrate with a Ge grade of 33.26%, which is 6.11% higher than the regular method. Analysis using XRD and HRTEM, combined with crystallite size calculation, revealed that the Ge concentrate prepared by U-PTGR exhibited low sintering degree, good crystal properties, and high crystallinity. Implementing this technology could save enterprises approximately $57,412 annually in production costs. Additionally, it holds significant practical importance in reducing hazardous waste emissions and promoting the high-quality development of the Ge industry.

Coronary artery segmentation in CCTA images based on multi-scale feature learning.

BACKGROUND: Coronary artery segmentation is a prerequisite in computer-aided diagnosis of Coronary Artery Disease (CAD). However, segmentation of coronary arteries in Coronary Computed Tomography Angiography (CCTA) images faces several challenges. The current segmentation approaches are unable to effectively address these challenges and existing problems such as the need for manual interaction or low segmentation accuracy. OBJECTIVE: A Multi-scale Feature Learning and Rectification (MFLR) network is proposed to tackle the challenges and achieve automatic and accurate segmentation of coronary arteries. METHODS: The MFLR network introduces a multi-scale feature extraction module in the encoder to effectively capture contextual information under different receptive fields. In the decoder, a feature correction and fusion module is proposed, which employs high-level features containing multi-scale information to correct and guide low-level features, achieving fusion between the two-level features to further improve segmentation performance. RESULTS: The MFLR network achieved the best performance on the dice similarity coefficient, Jaccard index, Recall, F1-score, and 95% Hausdorff distance, for both in-house and public datasets. CONCLUSION: Experimental results demonstrate the superiority and good generalization ability of the MFLR approach. This study contributes to the accurate diagnosis and treatment of CAD, and it also informs other segmentation applications in medicine.

The effect of background liked music on acute pain perception and its neural correlates.

Music shows tremendous promise in pain relief, especially when considering its non-pharmacological nature. However, our understanding of the precise mechanisms behind music-induced analgesia (MIA) remains poor. The positive emotional state induced by music is one of the key components explaining MIA. To test this possibility and reveal its neural correlates, the present study applied nociceptive laser stimuli to 28 healthy participants when their liked or disliked songs were played as background music, or when they were resting in silence. Differences among conditions were quantified by self-reports of pain intensity and unpleasantness, as well as brain activations in response to acute laser stimuli. As expected, liked music significantly lowered pain ratings to acute painful stimuli compared to disliked music and no music. Consistent with this observation, brain activations in response to acute painful stimuli were deceased within brain areas encoding sensory components of pain, such as the right precentral and postcentral gyri (PreCG/PoCG), brain areas related to affective components of pain, such as the anterior cingulate cortex and bilateral putamen, and brain areas associated with motor control and avoidance reactions to pain, such as the left cerebellum, when liked music was played in the background in comparison to disliked music. Importantly, the relationship between music listening and differences in pain ratings of two music conditions was mediated by the magnitude of right PreCG/PoCG and left cerebellum activations. These findings deepened our understanding of the analgesic benefits of background liked music, a property relevant to clinical applications.

Ultrasensitive Self-Driven Terahertz Photodetectors Based on Low-Energy Type-II Dirac Fermions and Related Van der Waals Heterojunctions.

The exotic electronic properties of topological semimetals (TSs) have opened new pathways for innovative photonic and optoelectronic devices, especially in the highly pursuit terahertz (THz) band. However, in most cases Dirac fermions lay far above or below the Fermi level, thus hindering their successful exploitation for the low-energy photonics. Here, low-energy type-II Dirac fermions in kitkaite (NiTeSe) for ultrasensitive THz detection through metal-topological semimetal-metal heterostructures are exploited. Furthermore, a heterostructure combining two Dirac materials, namely, graphene and NiTeSe, is implemented for a novel photodetector exhibiting a responsivity as high as 1.22 A W-1 , with a response time of 0.6 µs, a noise-equivalent power of 18 pW Hz-0.5 , with outstanding stability in the ambient conditions. This work brings to fruition of Dirac fermiology in THz technology, enabling self-powered, low-power, room-temperature, and ultrafast THz detection.

Therapeutic targeting of hepatic ACSL4 ameliorates NASH in mice.

BACKGROUND AND AIMS: Globally, NAFLD is one of the most common liver disorders, with an estimated prevalence rate of more than 30% in men and 15% in women and an even higher prevalence in people with type 2 diabetes mellitus. Optimal pharmacologic therapeutic approaches for NAFLD are an urgent necessity. APPROACH AND RESULTS: In this study, we showed that compared with healthy controls, hepatic ACSL4 levels in patients with NAFLD were found to be elevated. Suppression of ACSL4 expression promoted mitochondrial respiration, thereby enhancing the capacity of hepatocytes to mediate ß-oxidation of fatty acids and to minimize lipid accumulation by up-regulating peroxisome proliferator-activated receptor coactivator-1 alpha. Moreover, we found that abemaciclib is a potent and selective ACSL4 inhibitor, and low dose of abemaciclib significantly ameliorated most of the NAFLD symptoms in multiple NAFLD mice models. CONCLUSIONS: Therefore, inhibition of ACSL4 is a potential alternative therapeutic approach for NAFLD.

Experimental Realization of Two Qutrits Gate with Tunable Coupling in Superconducting Circuits.

Gate-based quantum computation has been extensively investigated using quantum circuits based on qubits. In many cases, such qubits are actually made out of multilevel systems but with only two states being used for computational purpose. While such a strategy has the advantage of being in line with the common binary logic, it in some sense wastes the ready-for-use resources in the large Hilbert space of these intrinsic multidimensional systems. Quantum computation beyond qubits (e.g., using qutrits or qudits) has thus been discussed and argued to be more efficient than its qubit counterpart in certain scenarios. However, one of the essential elements for qutrit-based quantum computation, two-qutrit quantum gate, remains a major challenge. In this Letter, we propose and demonstrate a highly efficient and scalable two-qutrit quantum gate in superconducting quantum circuits. Using a tunable coupler to control the cross-Kerr coupling between two qutrits, our scheme realizes a two-qutrit conditional phase gate with fidelity 89.3% by combining simple pulses applied to the coupler with single-qutrit operations. We further use such a two-qutrit gate to prepare an EPR state of two qutrits with a fidelity of 95.5%. Our scheme takes advantage of a tunable qutrit-qutrit coupling with a large on:off ratio. It therefore offers both high efficiency and low crosstalk between qutrits, thus being friendly for scaling up. Our Letter constitutes an important step toward scalable qutrit-based quantum computation.

Process Engineering and Glycosyltransferase Improvement for Short Route Chemoenzymatic Total Synthesis of GM1 Gangliosides.

Large-scale synthesis of GM1, an important ganglioside in mammalian cells especially those in the nervous system, is needed to explore its therapeutic potential. Biocatalytic production is a promising platform for such a purpose. We report herein the development of process engineering and glycosyltransferase improvement strategies to advance chemoenzymatic total synthesis of GM1. Firstly, a new short route was developed for chemical synthesis of lactosylsphingosine from the commercially available Garner's aldehyde. Secondly, two glycosyltransferases including Campylobacter jejuni ß1-4GalNAcT (CjCgtA) and ß1-3-galactosyltransferase (CjCgtB) were improved on their soluble expression in E. coli and enzyme stability by fusing with an N-terminal maltose binding protein (MBP). Thirdly, the process for enzymatic synthesis of GM1 sphingosines from lactosylsphingosine was engineered by developing a multistep one-pot multienzyme (MSOPME) strategy without isolating intermediate glycosphingosines and by adding a detergent, sodium cholate, to the later enzymatic glycosylation steps. Installation of a desired fatty acyl chain to GM1 glycosphingosines led to the formation of target GM1 gangliosides. The combination of glycosyltransferase improvement with chemical and enzymatic process engineering represents a significant advance in obtaining GM1 gangliosides containing different sialic acid forms by total chemoenzymatic synthesis in a short route and with high efficiency.

Post-Modification of a Robust Covalent Organic Framework for Efficient Sequestration of 99 TcO4 - /ReO4.

Nuclear industry spent fuel reprocessing and some radioactive contamination sites often involve high acidity and salinity environments. Currently developed and reported sorbents in 99 TcO4 - sequestration from the nuclear waste are unstable and show low adsorption efficiency in harsh conditions. To address this issue, we developed a post-synthetic modification strategy by grafting imidazole-based ionic liquids (ILs) onto the backbone of covalent organic framework (COF) via vinyl polymerization. The resultant COF-polyILs sorbent exhibits fast adsorption kinetics (<5 min) and good sorption capacity (388 mg g-1 ) for ReO4 - (a nonradioactive surrogate of 99 TcO4 - ). Outstandingly, COF-polyILs composite shows superior ReO4 - removal even under highly acidic conditions and in the presence of excess competing ions of Hanford low-level radioactive waste stream, benefiting from the stable covalent bonds between the COF and polyILs, mass of imidazole rings, and hydrophobic pores in COF.

Gut-derived bacterial LPS attenuates incubation of methamphetamine craving via modulating microglia.

BACKGROUND: The microbiota-gut-brain axis plays a critical role in the pathophysiology of neuropsychiatric disorders, and the compositions of gut microbiota are altered by addictive drugs. However, the role of gut microbiota in the incubation of methamphetamine (METH) craving remains poorly understood. METHODS: 16S rRNA gene sequencing was performed to assess the richness and diversity of gut microbiota in METH self-administration model. Hematoxylin and eosin staining was performed to evaluate the integrity of intestinal barrier. Immunofluorescence and three-dimensional reconstruction were performed to assess the morphologic changes of microglia. Serum levels of lipopolysaccharide (LPS) were determined using the rat enzyme-linked immunosorbent assay kits. Quantitative real-time PCR was performed to assess transcript levels of dopamine receptor, glutamate ionotropic AMPA receptor 3 and brain-derived neurotrophic factor. RESULTS: METH self-administration induced gut microbiota dysbiosis, intestinal barrier damage and microglia activation in the nucleus accumbens core (NAcc), which was partially recovered after prolonged withdrawal. Microbiota depletion via antibiotic treatment increased LPS levels and induced a marked change in the microglial morphology in the NAcc, as indicated by the decreases in the lengths and numbers of microglial branches. Depleting the gut microbiota also prevented the incubation of METH craving and increased the population of Klebsiella oxytoca. Furthermore, Klebsiella oxytoca treatment or exogenous administration of the gram-negative bacterial cell wall component LPS increased serum and central LPS levels, induced microglial morphological changes and reduced the dopamine receptor transcription in the NAcc. Both treatments and NAcc microinjections of gut-derived bacterial LPS significantly decreased METH craving after prolonged withdrawal. CONCLUSIONS: These data suggest that LPS from gut gram-negative bacteria may enter circulating blood, activate microglia in the brain and consequently decrease METH craving after withdrawal, which may have important implications for novel strategies to prevent METH addiction and relapse.

A Comparative Study of Clinical and Aortic Morphological Characteristics between Bovine Aortic Arch and Normal Aortic Arch in Patients with Acute Type B Aortic Dissection.

INTRODUCTION: The purpose of this study was to analyze the difference in clinical and aortic morphological features between the bovine aortic arch and normal aortic arch in patients with acute type B aortic dissection (aTBAD). METHODS: A total of 133 patients diagnosed with aTBAD were retrospectively collected. Based on aortic arch morphology, they were divided into the bovine aortic arch group (n = 20) and the normal aortic arch group (n = 113). Aortic morphological features were assessed on computed tomographic angiography. Clinical and aortic morphological features were then compared between the bovine aortic arch and normal aortic arch groups. RESULTS: Patients in the bovine aortic arch group were significantly younger and with higher weight and BMI than the normal aortic arch group (p < 0.001, p = 0.045, and p = 0.016, respectively). The total aortic length in the bovine aortic arch group was significantly shorter than that in the normal aortic arch group (p = 0.039). The tortuosity of descending thoracic aorta, the tortuosity of descending aorta, and the angulation of aortic arch were significantly lower in the bovine aortic arch group (p = 0.004, p = 0.015, and p = 0.023, respectively). The width of descending aorta, the height of aorta arch, and the angle of ascending aorta were significantly smaller in the bovine aortic arch group (p = 0.045, p = 0.044, and p = 0.042, respectively). CONCLUSION: When the aTBAD occurred, patients with bovine aortic arch were prone to be younger and with higher BMI than those with normal aortic arch. The aortic curvature and the total aortic length were lower in patients with bovine aortic arch.