Escalating Carbon Export from High-Elevation Rivers in a Warming Climate.

High-elevation mountains have experienced disproportionately rapid warming, yet the effect of warming on the lateral export of terrestrial carbon to rivers remains poorly explored and understood in these regions. Here, we present a long-term data set of dissolved inorganic carbon (DIC) and a more detailed, short-term data set of DIC, δ13CDIC, and organic carbon from two major rivers of the Qinghai-Tibetan Plateau, the Jinsha River (JSR) and the Yalong River (YLR). In the higher-elevation JSR with ∼51% continuous permafrost coverage, warming (>3 °C) and increasing precipitation coincided with substantially increased DIC concentrations by 35% and fluxes by 110%. In the lower-elevation YLR with ∼14% continuous permafrost, such increases did not occur despite a comparable extent of warming. Riverine concentrations of dissolved and particulate organic carbon increased with discharge (mobilization) in both rivers. In the JSR, DIC concentrations transitioned from dilution (decreasing concentration with discharge) in earlier, colder years to chemostasis (relatively constant concentration) in later, warmer years. This changing pattern, together with lighter δ13CDIC under high discharge, suggests that permafrost thawing boosts DIC production and export via enhancing soil respiration and weathering. These findings reveal the predominant role of warming in altering carbon lateral export by escalating concentrations and fluxes and modifying export patterns.

Activating transcription factor 6 alleviates secondary brain injury by increasing cystathionine γ-lyase expression in a rat model of intracerebral hemorrhage.

BACKGROUND: Intracerebral hemorrhage (ICH) comprises primary and secondary injuries, the latter of which induces increased inflammation and apoptosis and is more severe. Activating transcription factor 6 (ATF6) is a type-II transmembrane protein in the endoplasmic reticulum (ER). ATF6 target genes could improve ER homeostasis, which contributes to cryoprotection. Hence, we predict that ATF6 will have a protective effect on brain tissue after ICH. METHOD: The ICH rat model was generated through autologous blood injection into the right basal ganglia, the expression of ATF6 after ICH was determined by WB and IF. The expression of ATF6 was effectively controlled by means of intervention, and a series of measures was used to detect cell death, neuroinflammation, brain edema, blood-brain barrier and other indicators after ICH. Finally, the effects on long-term neural function of rats were measured by behavioral means. RESULT: ATF6 was significantly increased in the ICH-induced brain tissues. Further, ATF6 was found to modulate the expression of cystathionine γ-lyase (CTH) after ICH. Upregulation of ATF6 attenuated neuronal apoptosis and inflammation in ICH rats, along with mitigation of ICH-induced brain edema, blood-brain barrier deterioration, and cognitive behavior defects. Conversely, ATF6 genetic knockdown induced effects counter to those aforementioned. CONCLUSIONS: This study thereby emphasizes the crucial role of ATF6 in secondary brain injury in response to ICH, indicating that ATF6 upregulation may potentially ameliorate ICH-induced secondary brain injury. Consequently, ATF6 could serve as a promising therapeutic target to alleviate clinical ICH-induced secondary brain injuries.

Exploring the thermal decomposition and detonation mechanisms of 2,4-dinitroanisole by TG-FTIR-MS and molecular simulations.

2,4-dinitroanisole (DNAN), an insensitive explosive, has replaced trinitrotoluene (TNT) in many melt-cast explosives to improve the safety of ammunition and becomes a promising material to desensitize novel explosives of high sensitivity. Here, we combine thermogravimetric-Fourier transform infrared spectrometry-Mass spectrometry (TG-FTIR-MS), density functional theory (DFT), and ReaxFF molecular dynamics (MD) to investigate its thermal decomposition and detonation mechanisms. As revealed by TG-FTIR-MS, the thermal decomposition of DNAN starts at ca. 453 K when highly active NO2 is produced and quickly converted to NO resulting in the formation of a large amount of Ph(OH)(OH2)OCH3+. DFT calculations show that the activation energy of DNAN is higher than that of TNT due to the lack of α-H. Further steps in both thermal decomposition and detonation reactions of the DNAN are dominated by bimolecular O-transfers. ReaxFF MD indicates that DNAN has a lower heat of explosion than TNT, in accordance with the observation that the activation energies of polynitroaromatic explosives are inversely proportional to their heat of explosion. The inactive -OCH3 group and less nitro groups also render DNAN higher thermal stability than TNT.

Structural deep multi-view clustering with integrated abstraction and detail.

Deep multi-view clustering, which can obtain complementary information from different views, has received considerable attention in recent years. Although some efforts have been made and achieve decent performances, most of them overlook the structural information and are susceptible to poor quality views, which may seriously restrict the capacity for clustering. To this end, we propose Structural deep Multi-View Clustering with integrated abstraction and detail (SMVC). Specifically, multi-layer perceptrons are used to extract features from specific views, which are then concatenated to form the global features. Besides, a global target distribution is constructed and guides the soft cluster assignments of specific views. In addition to the exploitation of the top-level abstraction, we also design the mining of the underlying details. We construct instance-level contrastive learning using high-order adjacency matrices, which has an equivalent effect to graph attention network and reduces feature redundancy. By integrating the top-level abstraction and underlying detail into a unified framework, our model can jointly optimize the cluster assignments and feature embeddings. Extensive experiments on four benchmark datasets have demonstrated that the proposed SMVC consistently outperforms the state-of-the-art methods.

Time trends and regional variation in utilization of antidiabetic medicines in China, 2015-2022.

AIM: To assess the use of non-insulin antidiabetic medicines in China. MATERIALS AND METHODS: We analysed the national procurement data for 29 non-insulin antidiabetic medicines from nine subgroups in China from 2015 to 2022. We estimated the number of defined daily doses (DDDs) procured per year in seven regions of China for nine subgroups and adjusted the data by the number of patients with diabetes. For each subgroup, the regional ratio was calculated by comparing the procurement per patient in each region with the procurement nationwide. The regional disparity was the difference between the highest and lowest regional ratios. We compared the medication patterns across regions. RESULTS: Nationally, between 2015 and 2022, the number of DDDs per patient increased from 14.45 to 47.37. The two most commonly used categories were sulphonylurea and biguanides, which increased from 7.04 to 15.39 (119%) and 3.28 to 11.11 (239%) DDDs per patient, respectively. The procurement of new drugs (dipeptidyl peptidase-4 inhibitors, sodium-glucose cotransporter type 2 inhibitors and glucagon-like peptide-1 receptor agonists) increased quickly and had >5000% relative changes. Particularly for sodium-glucose cotransporter type 2 inhibitors, it increased from 0.08 to 5.03 DDDs (6662%). The southwest region had the highest relative change (319%), while the southern region had the lowest (118%). Biguanide and thiazolidinediones had the lowest (1.19) and highest level (2.21) of regional disparity in 2022, respectively. CONCLUSION: The procurement of non-insulin antidiabetic medicines in China has increased a lot from 2015 to 2022. In terms of DDDs per patient, sulphonylurea ranked first, followed by metformin. The procurement of new drugs increased greatly. A large regional disparity existed in medicine usage and patterns.

Spatial Contraction Based on Velocity Variation for Natural Walking in Virtual Reality.

Virtual Reality (VR) offers an immersive 3D digital environment, but enabling natural walking sensations without the constraints of physical space remains a technological challenge. Previous VR locomotion methods, including game controller, teleportation, treadmills, walking-in-place, and redirected walking (RDW), have made strides towards overcoming this challenge. However, these methods also face limitations such as possible unnaturalness, additional hardware requirements, or motion sickness risks. This paper introduces "Spatial Contraction (SC)", an innovative VR locomotion method inspired by the phenomenon of Lorentz contraction in Special Relativity. Similar to the Lorentz contraction, our SC contracts the virtual space along the user's velocity direction in response to velocity variation. The virtual space contracts more when the user's speed is high, whereas minimal or no contraction happens at low speeds. We provide a virtual space transformation method for spatial contraction and optimize the user experience in smoothness and stability. Through SC, VR users can effectively traverse a longer virtual distance with a shorter physical walking. Different from locomotion gains, the spatial contraction effect is observable by the user and aligns with their intentions, so there is no inconsistency between the user's proprioception and visual perception. SC is a general locomotion method that has no special requirements for VR scenes. The experimental results of our live user studies in various virtual scenarios demonstrate that SC has a significant effect in reducing both the number of resets and the physical walking distance users need to cover. Furthermore, experiments have also demonstrated that SC has the potential for integration with existing locomotion techniques such as RDW.

BiRD: Using Bidirectional Rotation Gain Differences to Redirect Users during Back-and-forth Head Turns in Walking.

Redirected walking (RDW) facilitates user navigation within expansive virtual spaces despite the constraints of limited physical spaces. It employs discrepancies between human visual-proprioceptive sensations, known as gains, to enable the remapping of virtual and physical environments. In this paper, we explore how to apply rotation gain while the user is walking. We propose to apply a rotation gain to let the user rotate by a different angle when reciprocating from a previous head rotation, to achieve the aim of steering the user to a desired direction. To apply the gains imperceptibly based on such a Bidirectional Rotation gain Difference (BiRD), we conduct both measurement and verification experiments on the detection thresholds of the rotation gain for reciprocating head rotations during walking. Unlike previous rotation gains which are measured when users are turning around in place (standing or sitting), BiRD is measured during users' walking. Our study offers a critical assessment of the acceptable range of rotational mapping differences for different rotational orientations across the user's walking experience, contributing to an effective tool for redirecting users in virtual environments.

Effects of topography and stand spatial structure on the diameter at breast height growth of major pioneer tree species of natural broad-leaved mixed forests in Zhejiang Province, China.

Based on the continuous inventory data of forest resources in Zhejiang Province in 2019 and 2021, we used statistical methods such as polynomial regression to analyze the impacts of topography and forest spatial structure on average annual diameter at breast height (DBH) growth of main pioneer tree species in natural broad-leaved mixed forests. The results showed that DBH of Schima superba, Quercus glauca, Quercus fabri, Lithocarpus glaber, Castanopsis eyrei, and Castanopsis sclerophylla were between 5-50.8, 5-41.5, 5-50.8, 5-43.9, 5-55.5, and 5-46.1 cm, respectively. We classified all the trees into three classes based on DBH: small (6-12 cm), medium (12-14 cm), and large (>26 cm). The average annual DBH growth of S. superba and Q. glauca was the highest on semi-shady slope and shady slope, with increases of 2.9%-15.7% and 1.1%-41.2%, respectively. The average annual DBH growth of large-diameter S. superba, L. glaber, C. eyrei and C. sclerophylla decreased with the increase of slope, with a maximum decrease of 27.0% for S. superba, with no significant difference among small- and medium-diameter trees as a whole. The slope position did not affect the annual DBH growth of small-diameter trees, while that of medium- and large-diameter S. superba, Q. glauca, and large-diameter Q. fabri, L. glaber decreased with the change of slope position from downhill, mesoslope, uphill to ridge, with a maximum decrease of 28.1% for L. glabe, and the major-diameter C. eyrei was on the contrary. Appropriate increase in the mingling was beneficial to the average annual DBH growth of medium- and large-diameter trees. Moderate mixing was suitable for S. superba, while low degree mixing and moderate mixing was suitable for Q. glauca, Q. fabri and L. glaber, and intensive mixing was suitable for C. eyrei and C. sclerophylla. No significant difference was observed for minor-diameter trees under the mingling. The neighborhood comparison only had a significant effect on the average annual DBH growth of large-diameter Q. glauca, Q. fabri, and L. glaber, which was significantly higher under subdominance-moderation than moderation-inferiority. The average annual DBH growth in the study area was mainly affected by aspect and mixing degree.

Contributions of Chinese hamster ovary cell derived extracellular vesicles and other cellular materials to hollow fiber filter fouling during perfusion manufacturing of monoclonal antibodies.

Hollow fiber filter fouling is a common issue plaguing perfusion production process for biologics therapeutics, but the nature of filter foulant has been elusive. Here we studied cell culture materials especially Chinese hamster ovary (CHO) cell-derived extracellular vesicles in perfusion process to determine their role in filter fouling. We found that the decrease of CHO-derived small extracellular vesicles (sEVs) with 50-200 nm in diameter in perfusion permeates always preceded the increase in transmembrane pressure (TMP) and subsequent decrease in product sieving, suggesting that sEVs might have been retained inside filters and contributed to filter fouling. Using scanning electron microscopy and helium ion microscopy, we found sEV-like structures in pores and on foulant patches of hollow fiber tangential flow filtration filter (HF-TFF) membranes. We also observed that the Day 28 TMP of perfusion culture correlated positively with the percentage of foulant patch areas. In addition, energy dispersive X-ray spectroscopy-based elemental mapping microscopy and spectroscopy analysis suggests that foulant patches had enriched cellular materials but not antifoam. Fluorescent staining results further indicate that these cellular materials could be DNA, proteins, and even adherent CHO cells. Lastly, in a small-scale HF-TFF model, addition of CHO-specific sEVs in CHO culture simulated filter fouling behaviors in a concentration-dependent manner. Based on these results, we proposed a mechanism of HF-TFF fouling, in which filter pore constriction by CHO sEVs is followed by cake formation of cellular materials on filter membrane.

GLFNet: Global-local fusion network for the segmentation in ultrasound images.

Ultrasound imaging, as a portable and radiation-free modality, presents challenges for accurate segmentation due to the variability of lesions and the similar intensity values of surrounding tissues. Current deep learning approaches leverage convolution for extracting local features and self-attention for handling global dependencies. However, traditional CNNs are spatially local, and Vision Transformers lack image specific bias and are computationally demanding. In response, we propose the Global-Local Fusion Network (GLFNet), a hybrid structure addressing the limitations of both CNNs and Vision Transformers. The GLFNet, featuring Global-Local Fusion Blocks (GLFBlocks), integrates global semantic information with local details to improve segmentation. Each GLFBlock comprises Global and Local Branches for feature extraction in parallel. Within the Global and Local Branches, we introduce the Self-Attention Convolution Fusion Block (SACFBlock), which includes a Spatial-Attention Module and Channel-Attention Module. Experimental results show that our proposed GLFNet surpasses its counterparts in the segmentation tasks, achieving the overall best results with an mIoU of 79.58% and Dice coefficient of 74.62% in the DDTI dataset, an mIoU of 76.61% and Dice coefficient of 71.04% in the BUSI dataset, and an mIoU of 86.77% and Dice coefficient of 87.38% in the BUID dataset. The fusion of local and global features contributes to enhanced performance, making GLFNet a promising approach for ultrasound image segmentation.

Efficient CRISPR genome editing and integrative genomic analyses reveal the mosaicism of Cas-induced mutations and pleiotropic effects of scarlet gene in an emerging model system.

Despite the revolutionary impacts of CRISPR-Cas gene editing systems, the effective and widespread use of CRISPR technologies in emerging model organisms still faces significant challenges. These include the inefficiency in generating heritable mutations at the organismal level, limited knowledge about the genomic consequences of gene editing, and an inadequate understanding of the inheritance patterns of CRISPR-Cas-induced mutations. This study addresses these issues by 1) developing an efficient microinjection delivery method for CRISPR editing in the microcrustacean Daphnia pulex; 2) assessing the editing efficiency of Cas9 and Cas12a nucleases, examining mutation inheritance patterns, and analyzing the local and global mutation spectrum in the scarlet mutants; and 3) investigating the transcriptomes of scarlet mutants to understand the pleiotropic effects of scarlet underlying their swimming behavior changes. Our reengineered CRISPR microinjection method results in efficient biallelic editing with both nucleases. While indels are dominant in Cas-induced mutations, a few on-site large deletions (>1kb) are observed, most likely caused by microhomology-mediated end joining repair. Knock-in of a stop codon cassette to the scarlet locus was successful, despite complex induced mutations surrounding the target site. Moreover, extensive germline mosaicism exists in some mutants, which unexpectedly produce different phenotypes/genotypes in their asexual progenies. Lastly, our transcriptomic analyses unveil significant gene expression changes associated with scarlet knock-out and altered swimming behavior in mutants, including several genes (e.g., NMDA1, ABAT, CNTNAP2) involved in human neurodegenerative diseases. This study expands our understanding of the dynamics of gene editing in the tractable model organism Daphnia and highlights its promising potential as a neurological disease model.

Thyroid Ultrasound Image Database and Marker Mask Inpainting Method for Research and Development.

OBJECTIVE: The main objective of this study was to build a rich and high-quality thyroid ultrasound image database (TUD) for computer-aided diagnosis (CAD) systems to support accurate diagnosis and prognostic modeling of thyroid disorders. Because most of the raw thyroid ultrasound images contain artificial markers, which seriously affect the robustness of CAD systems because of their strong prior location information, we propose a marker mask inpainting (MMI) method to erase artificial markers and improve image quality. METHODS: First, a set of thyroid ultrasound images were collected from the General Hospital of the Northern Theater Command. Then, two modules were designed in MMI, namely, the marker detection (MD) module and marker erasure (ME) module. The MD module detects all markers in the image and stores them in a binary mask. According to the binary mask, the ME module erases the markers and generates an unmarked image. Finally, a new TUD based on the marked images and unmarked images was built. The TUD is carefully annotated and statistically analyzed by professional physicians to ensure accuracy and consistency. Moreover, several normal thyroid gland images and some ancillary information on benign and malignant nodules are provided. RESULTS: Several typical segmentation models were evaluated on the TUD. The experimental results revealed that our TUD can facilitate the development of more accurate CAD systems for the analysis of thyroid nodule-related lesions in ultrasound images. The effectiveness of our MMI method was determined in quantitative experiments. CONCLUSION: The rich and high-quality resource TUD promotes the development of more effective diagnostic and treatment methods for thyroid diseases. Furthermore, MMI for erasing artificial markers and generating unmarked images is proposed to improve the quality of thyroid ultrasound images. Our TUD database is available at https://github.com/NEU-LX/TUD-Datebase.

Danshensu methyl ester attenuated LPS-induced acute lung injury by inhibiting TLR4/NF-κB pathway.

Acute Lung Injury (ALI) manifests as an acute exacerbation of pulmonary inflammation with high mortality. The potential application of Danshensu methyl ester (DME, synthesized in our lab) in ameliorating ALI has not been elucidated. Our results demonstrated that DME led to a remarkable reduction in lung injury. DME promoted a marked increase in antioxidant enzymes, like superoxide dismutase (SOD), and glutathione (GSH), accompanied by a substantial decrease in reactive oxygen species (ROS), myeloperoxidase (MPO), and malondialdehyde (MDA). Moreover, DME decreased the production of IL-1ß, TNF-α and IL-6, in vitro and in vivo. TLR4 and MyD88 expression is reduced in the DME-treated cells or tissues, which further leading to a decrease of p-p65 and p-IκBα. Meanwhile, DME effectively facilitated an elevation in cytoplasmic p65 expression. In summary, DME could ameliorate ALI by its antioxidant functionality and anti-inflammation effects through TLR4/NF-κB, which implied that DME may be a viable medicine for lung injury.

Altered expression of the Plexin-B2 system in tuberous sclerosis complex and focal cortical dysplasia IIb lesions.

Tuberous sclerosis complex (TSC) and focal cortical dysplasia (FCD) type IIb are the predominant causes of drug-refractory epilepsy in children. Dysmorphic neurons (DNs), giant cells (GCs), and balloon cells (BCs) are the most typical pathogenic profiles in cortical lesions of TSC and FCD IIb patients. However, mechanisms underlying the pathological processes of TSC and FCD IIb remain obscure. The Plexin-B2-Sema4C signalling pathway plays critical roles in neuronal morphogenesis and corticogenesis during the development of the central nervous system. However, the role of the Plexin-B2 system in the pathogenic process of TSC and FCD IIb has not been identified. In the present study, we investigated the expression and cell distribution characteristics of Plexin-B2 and Sema4C in TSC and FCD IIb lesions with molecular technologies. Our results showed that the mRNA and protein levels of Plexin-B2 expression were significantly increased both in TSC and FCD IIb lesions versus that in the control cortex. Notably, Plexin-B2 was also predominantly observed in GCs in TSC epileptic lesions and BCs in FCD IIb lesions. In contrast, the expression of Sema4C, the ligand of Plexin-B2, was significantly decreased in DNs, GCs, and BCs in TSC and FCD IIb epileptic lesions. Additionally, Plexin-B2 and Sema4C were expressed in astrocytes and microglia cells in TSC and FCD IIb lesions. Furthermore, the expression of Plexin-B2 was positively correlated with seizure frequency in TSC and FCD IIb patients. In conclusion, our results showed the Plexin-B2-Sema4C system was abnormally expressed in cortical lesions of TSC and FCD IIb patients, signifying that the Plexin-B2-Sema4C system may play a role in the pathogenic development of TSC and FCD IIb.

Effect of electroacupuncture on ventricular structure and function in rats with myocardial ischemia-reperfusion injury. / ç”µé’ˆå¯¹å¿ƒè‚Œç¼ºè¡€å†çŒæ³¨æŸä¼¤å¤§é¼ å¿ƒå®¤ç»“æž„å’ŒåŠŸèƒ½çš„å½±å“.

OBJECTIVES: To observe the effect of electroacupuncture (EA) on changes of ventricular structure and function in rats with myocardial ischemia-reperfusion injury (MIRI), so as to explore its potential mechanisms underlying improvement of ventricular remodeling after MIRI. METHODS: Forty male SD rats were randomly divided into 4 groups：sham operation group, model group, EA group and medication (sacubactril valsartan, LCZ696) group, with 10 rats in each group. The MIRI model was established by ligation of the left anterior descending coronary artery and reperfusion. EA (2 Hz/100 Hz, 2 mA) was applied to bilateral "Neiguan" (PC6) for 20 min, once every other day for 21 d. Rats of the medication group received gavage of LCZ696 (60 mg·kg-1·d-1). After the intervention, echocardiography was used to detect the ejection fraction (EF) and fractional shortening (FS) of the left ventricle, and the contents of serum tumor necrosis factor-α(TNF-α), vascular cell adhesion molecule-1(VCAM-1) and intercellular cell adhesion molecule-1(ICAM-1) were assayed by enzyme-linked immunosorbent assay. The pathological changes of myocardial tissue were observed after HE staining. The Masson staining was used to evaluate the myocardial collagen deposition and myocardial fibrosis. The mRNA expression levels of collagen Ⅰ and Ⅲ and connective tissue growth factor (CTGF) in the myocardial tissue were detected by quantitative real-time PCR, and the expression levels of IL-1ß and IL-18 were detected by Western blot. RESULTS: In contrast to the sham operation group, the EF and FS levels of the left ventricle were ob-viously decreased (P<0.001), while the contents of serum TNF-α, VCAM-1 and ICAM-1, the proportion of myocardial fibrosis area, the mRNA expression levels of myocardial collagen Ⅰ, collagen Ⅲ and CTGF, the expression levels of IL-1ß and IL-18 were significantly increased (P<0.001, P<0.000 1, P<0.05, P<0.01) in the model group. Compared with the model group, the EF and FS levels were remarkably increased (P<0.01), whereas the contents of serum TNF-α, VCAM-1 and ICAM-1, the proportion of myocardial fibrosis area, the mRNA expression levels of myocardial collagen Ⅰ, collagen Ⅲ and CTGF, and the expression levels of IL-1ß and IL-18 were significantly down-regulated (P<0.001, P<0.01, P<0.05) in both the medication and EA groups. No significant differences were found between the EA and medication groups in all the indexes mentioned above. CONCLUSIONS: EA can improve the left-ventricular fibrosis and function, delay or reverse ventricular remodeling in MIRI rats, which may be related to its functions in down-regulating myocardial inflammatory response and mRNA expression levels of myocardial collagen Ⅰ, collagen Ⅲ and CTGF.

Multi-User Redirected Walking in Separate Physical Spaces for Online VR Scenarios.

With the recent rise of Metaverse, online multiplayer VR applications are becoming increasingly prevalent worldwide. However, as multiple users are located in different physical environments, different reset frequencies and timings can lead to serious fairness issues for online collaborative/competitive VR applications. For the fairness of online VR apps/games, an ideal online RDW strategy must make the locomotion opportunities of different users equal, regardless of different physical environment layouts. The existing RDW methods lack the scheme to coordinate multiple users in different PEs, and thus have the issue of triggering too many resets for all the users under the locomotion fairness constraint. We propose a novel multi-user RDW method that is able to significantly reduce the overall reset number and give users a better immersive experience by providing a fair exploration. Our key idea is to first find out the "bottleneck" user that may cause all users to be reset and estimate the time to reset given the users' next targets, and then redirect all the users to favorable poses during that maximized bottleneck time to ensure the subsequent resets can be postponed as much as possible. More particularly, we develop methods to estimate the time of possibly encountering obstacles and the reachable area for a specific pose to enable the prediction of the next reset caused by any user. Our experiments and user study found that our method outperforms existing RDW methods in online VR applications.

Antidepressant effects of dexmedetomidine compared with ECT in patients with treatment-resistant depression.

OBJECTIVE: This pilot study was designed to investigate the antidepressant effects of dexmedetomidine (DEX), a selective α2-adrenergic receptor agonist, in patients with treatment-resistant depression (TRD). The antidepressant effects of dexmedetomidine was compared with ECT, which is widely used in clinical practice for treatment of patients with TRD. METHODS: Seventy six patients with TRD were randomly assigned to receive 10 sessions of DEX infusions or electroconvulsive therapy (ECT) treatment. The primary outcome was the changes of depression severity determined by the improvement of 24-item Hamilton Depression Rating Scale (HDRS-24). The second outcomes were the rates of therapeutic response (reduction in HDRS-24 ≥ 50 %) and remission (HDRS-24 ≤ 10 and reduction in HDRS-24 ≥ 60 %) at posttreatment and after 3 months of follow-up visits. RESULTS: We found that 10 sessions of DEX infusions or ECT treatments significantly improved HDRS-24 scores at posttreatment and after 3 months of follow-up visits compared with the baseline. In addition, there was no significant difference between DEX infusions and ECT treatments regarding HDRS-24 at these evaluating points. Furthermore, the depression severity dropped to mild after 2 sessions of DEX infusion. In contrast, at least 6 sessions of ECT treatment were needed to achieve a same level. Finally, the rates of therapeutic response and remission were comparable between the two groups. No serious adverse events were observed. CONCLUSIONS: Based on current published evidence, we conclude that DEX exhibits rapid and durable antidepressant properties similar to ECT but with fewer side effects.

Strip steel surface defect detection based on lightweight YOLOv5.

Deep learning-based methods for detecting surface defects on strip steel have advanced detection capabilities, but there are still problems of target loss, false alarms, large computation, and imbalance between detection accuracy and detection speed. In order to achieve a good balance between detection accuracy and speed, a lightweight YOLOv5 strip steel surface defect detection algorithm based on YOLOv5s is proposed. Firstly, we introduce the efficient lightweight convolutional layer called GSConv. The Slim Neck, designed based on GSConv, replaces the original algorithm's neck, reducing the number of network parameters and improving detection speed. Secondly, we incorporate SimAM, a non-parametric attention mechanism, into the improved neck to enhance detection accuracy. Finally, we utilize the SIoU function as the regression prediction loss instead of the original CIoU to address the issue of slow convergence and improve efficiency. According to experimental findings, the YOLOv5-GSS algorithm outperforms the YOLOv5 method by 2.9% on the NEU-DET dataset and achieves an average accuracy (mAP) of 83.8% with a detection speed (FPS) of 100 Hz, which is 3.8 Hz quicker than the YOLOv5 algorithm. The proposed model outperforms existing approaches and is more useful, demonstrating the efficacy of the optimization strategy.

Quantification and isotope abundance determination of 13C labeled intracellular sugar metabolites with hydrophilic interaction liquid chromatography.

Metabolic flux analysis (MFA) using stable isotope labeled tracers is a powerful tool to estimate fluxes through metabolic pathways. It finds applications in studying metabolic changes in diseases, regulation of cellular energetics, and novel strategies for metabolic engineering. Accurate and precise quantification of the concentration of metabolites and their labeling states is critical for correct MFA results. Utilizing an ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) system, an analytical method for simultaneously quantifying the concentration of sugar metabolites and their mass isotopologue distribution (MID) was developed. The method performs with good linearity and coefficient of determination (R2) > 0.99, while the detection limit ranged from 0.1 to 50 mg L-1. Seven sugar metabolites were detected in a labeled Brevibacterium flavum sample using the method. The detected quantities ranged from 6.15 to 3704.21 mg L-1, and 13C abundance was between 12.77% and 66.67% in the fermentation fluid and 16.28% and 91.93% in the bacterial body. Overall, the method is efficient, accurate, and suitable for analysis of labeled sugar metabolites in 13C MFA studies.

Lessons learned from COVID-19 vaccination implementation: How psychological antecedents of vaccinations mediate the relationship between vaccine literacy and vaccine hesitancy.

BACKGROUND: Enhancing the public's vaccine literacy is critical for curbing vaccine hesitancy and enhancing society's pandemic preparedness, particularly in an era of infodemic. Evidence on vaccine literacy as an influencing factor of hesitancy is scarce. Lessons could be learned from COVID-19 vaccination implementation. Taking the COVID-19 vaccines as an example, the current study aimed to examine the relationship between vaccine literacy and hesitancy and the mediating role of psychological antecedents of vaccination on the relationship. METHODS: A baseline online questionnaire survey among the general public in China based on quota sampling was conducted in April 2021 to measure participants' vaccine literacy, psychological antecedents of vaccination, COVID-19 vaccination status, and vaccine hesitancy. A follow-up online survey tracked the updated COVID-19 vaccination status among those who hadn't taken COVID-19 vaccines at the baseline survey. Structural equation modeling has been applied to examine the direct and indirect effect of vaccine literacy on vaccine hesitancy. Time-to-event analysis was used to explore the effect of vaccine hesitancy on vaccination behavior. RESULTS: Lower vaccine hesitancy was associated with higher vaccine literacy. The "3Cs" psychological antecedents were important mediators between vaccine literacy and vaccine hesitancy. The pathway between critical/interactive vaccine literacy and vaccine hesitancy through the "3Cs" psychological antecedents played a more important role. Time-to-event analysis showed participants with a higher vaccine hesitancy were prone to have a longer delay in vaccination. CONCLUSIONS: Improving the public's ability to obtain and evaluate vaccination information can fix the public's psychological determinants of vaccination, reducing vaccine hesitancy and promoting vaccination. Governments need to put more effort into guiding and regulating the media to disseminate evidence-based information, rectifying misinformation, and improving the public's vaccine literacy through education, especially the public's capability to critically discern mixed information.