G protein-coupled receptors (GPCRs) are a large family of cell surface receptors that play a critical role in nervous system function by transmitting signals between cells and their environment. They are involved in many, if not all, nervous system processes, and their dysfunction has been linked to various neurological disorders representing important drug targets. In this review, we will first discuss the role of the nervous system GPCRs in the modulation of tripartite synapse function and how GPCRs control energy metabolism in the brain. We will then discuss the (patho)physiology and pharmacology of opioid, cannabinoid, acetylcholine, chemokine, and melatonin GPCRs in the nervous system. Furthermore, we will briefly report on adhesion GPCR function in nervous tissues. Finally, we will address orphan GPCRs, their implication in the nervous system function and disease, and the challenges that need to be addressed in the future to deorphanize them.

Objective Our study aimed to investigate the oral microbiome of patients infected with the Omicron variant (PIOV) and the changes in oral microbiota during the recovery of infection, compared to those infected with the original strain (PIOS) and provide a theoretical foundation for early diagnosis and disease prognosis of PIOV from the perspective of microecology. Design We collected 963 samples of tongue-coating prospectively, including 349 samples of PIOV, 242 samples of recovered patients from PIOV (RP), 300 samples of healthy controls (HC), and 72 samples of PIOS. We randomly selected tongue-coating samples from PIOV and HC at a ratio of 2:1, respectively, as the discovery cohort and validation cohort. Results Oral microbial diversity was significantly increased in PIOV. Compared to HC, conditional pathogenic bacteria were increased in PIOV. The classifier based on 6 optimal oral microbial markers had high diagnostic efficiency in both cohorts. Oral microbiota numbers were changed as the disease recovered. Conclusion For the first time, our study characterizes the oral microbiota of PIOV and RP, successfully establishes and validates the noninvasive diagnostic model of PIOV, and outlines the correlation between the OTUs of microbiota and clinical indicators.

Kidney transplanted patients need immunosuppressant therapies.SARS-CoV-2 may cause acute lung injury, and secondary infections are thus relevant complications in patients with COVID-19 pneumonia.In view of the contradiction between anti-rejection use of immunosuppressants in patients with transplanted organs and the need to improve the immunity of infection.Here,we report a case of the clinical pharmacist participated in the whole process of patients with novel coronavirus infection after kidney transplantation.The clinical pharmacist gave in dividualized guidance on Nematvir/Ritonavir drug interaction and the timing of discontinuation and re-use of immunosuppressive agents .Pulmonary diseases ofviral origin was well controlled and no acute rejection of transplanted kidney occurred.

Stablecoin is a medium of exchange with stable value in the world of decentralized finance (DeFi). In which, algorithmic stablecoins are one special type of stablecoins that are not backed by any asset. They stand to revolutionize the way a sovereign fiat operates. As implemented, algorithmic stablecoins are poorly stabilized in most cases; their prices easily deviate from the target or even fall into a catastrophic collapse, and are as a result often dismissed as a Ponzi scheme. However, what is the essence of Ponzi? In this paper, we try to clarify such a deceptive concept and reveal how algorithmic stablecoins work from a higher level. We find that Ponzi is basically a financial protocol that pays existing investors with funds collected from new ones. Running a Ponzi, however, does not necessarily imply that any participant is in any sense losing out, as long as the game can be perpetually rolled over. Economists call such realization as a rational Ponzi game. We thereby propose a rational model in the context of algorithmic stablecoins and draw its holding conditions. We apply the model to examine: whether or not the algorithmic stablecoin is a rational Ponzi game. Accordingly, we discuss two types of algorithmic stablecoins (Rebase & Seigniorage Shares) and dig into the historical market performance of a number of impactful projects to demonstrate the effectiveness of our model.

This paper proposes a novel event-triggered economic model predictive control (EMPC) scheme with shrinking prediction horizon of constrained nonlinear systems. Concretely, the triggered mechanism is designed by relaxing the stability constraint, while the involved parameter can be used to achieve a sensible compromise between system performance and computational complexity. The rule of shrinking prediction horizon shortens the length of the horizon as much as possible, while the length of triggered interval is ensured to avoid Zero behavior. The utilization of control sequence is improved. As the prediction horizon becomes shorter, the state always keeps in the terminal set. The sufficient conditions guaranteeing the recursive feasibility and stability of the EMPC are derived. Finally, the effectiveness of the algorithm is illustrated by a continuously stirred tank reactor example.

Gastric cancer has become a prominent research focus due to its role of cancer-related deaths in the worldwide in recent years, especially for advanced gastric cancer for which surgical resection is the only truly effective treatment. However, patients with gastric cancer have a high rate of postoperative recurrence and metastasis. Therefore, studying the mechanisms of gastric cancer development and metastasis, finding diagnostic markers and therapeutic targets has become a hot research topic nowadays. Lactate has long been considered as a metabolic byproduct of aerobic glycolysis in cancer, and an increasing number of studies have shown that lactate can regulate tumor growth through various mechanisms, such as cell cycle regulation, immunosuppression, and energy metabolism. The recent discovery of lactic acidification has attracted much attention and has become one of the hot topics in the field of cancer. Yet, the roles of lactate metabolism-related genes (LMRs) in gastric cancer remains unknown. Accordingly, we aimed to develop a unique lactate-related signal to predict the prognosis of gastric cancer patients, and such LMRs could guide clinicians to make more precise and personalized treatments for gastric cancer patients.

This letter presents a sub-6 GHz wideband low noise amplifier (LNA) based on double L-type load network and negative feedback technique. Using the cascode structure combined with the above techniques, a single-stage wideband LNA with high gain and low noise figure (NF) can be realized. Fabricated in 110-nm SOI CMOS technology, the proposed LNA achieves a maximum power gain of 15.2 dB, noise figure (NF) of 1.0–1.56 dB. The 3-dB bandwidth ranges from 3.05–4.55 GHz. The minimum power input at 1dB compression point (IP1dB) is -17.1 dBm. The LNA core area is 0.18 mm2 and dissipates a total power of 11.5 mW from 1.4 V power supply.

Strong clutter seriously affects target-of-interest detection in synthetic aperture radar (SAR) images. This letter proposes an unsupervised target detection method (U-TDM) based on a complex-valued extreme learning machine (CV-ELM), the essence of which is to transform the problem of target detection into a pixel binary classification problem. The SAR image is first divided into several unlabeled patches, and fuzzy c-means (FCM) is used to construct the reference target patch set and the clutter patch set. Based on these two patch sets, CV-ELM is used to classify the neighboring patch of the pixel to be detected. Since the pixel intensity and distribution of target-of-interest and clutter are different, unsupervised pixel classification could be realized without ground-truth through U-TDM. Experimental results on GF-3 data and Sentinel-1 data show the efficiency of the proposed method in target detection with a heterogeneous clutter environment.

Abstract Aims This study aims to assess the safety of medication that can affect blood pressure in patients with hypertension and provide practical recommendations for healthcare professionals. Methods For the development of recommendations for the drug-disease interaction (DDSI) hypertension, a six-step plan that combined literature selection and multidisciplinary expert opinion was used. The process involved (1) defining the scope of the DDSI and selecting relevant drugs, (2) collecting evidence, (3) data-extraction, (4) reaching of expert consensus, (5) publication and implementation of the recommendations in healthcare systems and (6) updating of the information. Results An increase of 10 mmHg in systolic blood pressure and 5 mmHg in diastolic blood pressure was defined as clinically relevant. Corticosteroids, danazol, and yohimbine caused a clinically relevant DDSI with hypertension. Several other drugs with warnings for hypertension in the official product information, were assessed to have no clinically relevant DDSI due to minor influence or lack of data on blood pressure. Drugs with evidence for a relevant change in blood pressure which are prescribed under close monitoring of blood pressure according to clinical guidelines, were deemed to be not clinically relevant for signalling. Conclusions This study provides specific recommendations that can be implemented directly in clinical practice, potentially resulting in safer drug use in patients with hypertension and better healthcare by reducing alert fatigue. Future research should focus on evaluating the effectiveness of implementation strategies and their impact on reducing unsafe use of medication in patients with hypertension.

Hyperspectral images contain rich spatial and spectral information, which provides a strong basis for distinguishing different land-cover objects. Therefore, hyperspectral image classification has been a hot research topic. With the advent of deep learning, convolutional neural networks (CNNs) have become a popular method for hyperspectral image classification. However, CNN has strong local feature extraction ability but cannot deal with long-distance dependence well. Vision Transformer (ViT) is a recent development that can address this limitation, but it is not effective in extracting local features and has low computational efficiency. To overcome these drawbacks, we propose a hybrid classification network that combines the strengths of both CNN and ViT, names Spatial-Spectral Former(SSF). The shallow layer employs 3D convolution to extract local features and reduce data dimensions. The deep layer employs a spectral-spatial transformer module for global feature extraction and information enhancement in spectral and spatial dimensions. Our proposed model achieves promising results on widely used public HSI datasets compared to other deep learning methods, including CNN, ViT, and hybrid models.

Soil phosphorus (P) is an important nutrient limiting plant productivity. The elevational pattern of soil P concentrations is widely used to indicate how P pools are affected by the climate. Despite previous research finding various patterns of soil P concentration across different elevations, little research has been conducted on how bedrock variation in an elevational transect affects P pools. In this study, we examined the elevational patterns of soil P pools (e.g., labile inorganic P (Pi) and organic P (Po), moderately labile Pi and Po, primary mineral P, and occluded P) in top-soils in an elevational transect with alternating bedrock types of clasolite and limestone in a subtropical karst forest. The results showed that concentrations of soil total P, labile Pi, primary P, and occluded P were significantly higher in limestone soils than clasolite soils, while there were no significant differences in labile Po, moderately labile Pi and Po concentrations between the two bedrocks. There were generally no significant linear elevational trends for soil P pools. Our results revealed that the bedrock type had a greater influence on soil P pools than climatic factors. Our study emphasizes the importance of using bedrock changes as a driving factor for the spatial distribution of soil phosphorus pools in mountainous ecosystems.

Thermal energy storage (TES) is an enabling system that provides uninterrupted energy from concentrated solar power (CSP) plants. Packed-bed TES systems have great opportunity to significantly enhance the cost-effectiveness, efficiency and sustainability of CSP plants by employing an affordable and sustainable packing material. The objective of this study is to design a packed bed TES system with a maximum storage capacity of 40 kWh, specifically tailored to store heat within the temperature range of 290 – 565 °C, thereby making it suitable for integration into CSP plants. Performance and thermal behavior of demolition waste-based packed-bed TES system was assessed through numerical analysis. The results demonstrate that a high discharging efficiency of 96.7% was achieved when the HTF flow rate was set at 300 kgh -1. However, it is important to note that at lower HTF flow rates, heat loss increases, leading to a decrease in discharging efficiency to 93.7%. The experiment also revealed a uniform thermal gradient within the packed-bed TES system, up to a fluid flow rate of 300 kgh -1. It is worth mentioning that lower flow rates can further improve the stratification effect; however, they may also result in increased heat loss and reduced storage capacity. Based on these findings, an optimal flow rate range of 100-200 kgh -1 is recommended to achieve the best performance for the packed-bed TES system.

Subsea cables suffer from induced current. There are usually two metal layers grounded at both ends for subsea cables, namely lead sheath and armor. It is observed that occasionally the induced current in lead sheath and armor layer between two ends are unbalanced. To study this phenomena, detailed modelling with both analytical approach and finite-element one is performed in this paper. Furthermore, mock-up experiment is carried out. It is shown that the unbalance between grounding ends is due to the inequal impedances of multi-grounding points and/or impedance variation of the semi-conductive layer between lead sheath and armor. Based on the analysis, a subsea cable status evaluation procedure is proposed.

Silphium integrifolium Michx. (silflower), a perennial plant, is of great interest as a potential new oilseed crop due to its long, strong, deep, extensive root systems, which can prevent erosion, capture dissolved nitrogen, and out-compete weeds eliminating the need for frequent irrigation and herbicide uses. In this study, oil was extracted from unhulled silflower seeds, and its composition and oxidative stability were evaluated. The oil content in unhulled silflower seeds was 15.2 % (w/w), and its fatty acid composition was similar to that of sunflower oil. The level of total polar compounds (TPC) in the oil was 12.3 % (w/w), and the content of total phenolics was 1.12 mg gallic acid equivalent (GAE)/g oil. Noteworthily, 4.89 % squalene was isolated from silflower oil indicating its potential application as an alternative source of squalene. Silflower oil had lower oxidative stability as indicated by the oxidative stability index (OSI) at 110 °C and thermogravimetric analysis (TGA), presumably due to its high level of chlorophyll (1002.8 mg/Kg). Even after a typical refining process involving degumming, alkali refining, and bleaching with Fuller’s earth, silflower oil contained 725.5 mg/kg chlorophyll, and its oxidative stability was not improved. Further treatments with bleaching agents including bentonite, sepiolite, and Tonsil® lowered the chlorophyll level to 4.2, 474.5, and 38.5 mg/kg, respectively, and some aspects of oxidative stability were improved and better than those of refined sunflower oil. This study presents the potential of silflower oil as new edible oil and a great plant source of squalene.

Scenedesmus is an important, rapidly growing, freshwater microalga because of its significantly high lipid content. However, the molecular basis of fatty acid biosynthesis is scarcely elucidated not only in Scenedesmus but also in microalgae as a whole. Mining the genome of Scenedesmus, we identified some of the crucial enzymes involved in fatty acid biosynthesis pathways such as acetyl-CoA carboxylase (ACC), malonyl-CoA:ACP transacylase (MAT) and fatty-acyl thioesterases (FAT). Detailed comparative analyses of  these identified enzymes demonstrated highly significant sequence similarity with homologs of bacteria suggesting an evolutionary linkage. Moreover, the molecular modeling and 3D structures of the chloroplastic enzymes revealed that the overall structural orientation and the catalytic residues are well conserved. On the other hand, biotin protein ligase and cytosolic acetyl-CoA carboxylase isoforms presented some significant differences with respect the previously reported protein models. Our analysis describes some specific features in Scenedesmus fatty acid synthesis enzymes that could be responsible for their particular lipid accumulation profile.  

The prebiotic fructan inulin can provide energy to organisms via several pathways. One pathway is that inulin fructotransferase (IFTase) firstly converted inulin to III-type difructose anhydride (DFA-III). Then DFA-III is hydrolyzed to inulobiose via difructose anhydride hydrolase (DFA-IIIase). However, only five DFA-IIIases have been reported to date and all of them are from Arthrobacter genus. Whether other microbes except Arthrobacter genus can utilize DFA-III through DFA-IIIase are unknown. In this work, a DFA-IIIase from Duffyella gerundensis A4 (D. gerundensis A4), abbreviated as DgDFA-IIIase, was cloned, expressed, purified, identified, and characterized. It was approximately 50 kDa assayed by SDS-PAGE and showed the highest catalytic activity for DFA-III at pH 6.0 and 35 °C with specific activity of 56 U mg-1. The enzyme was metal-independent and had a high pH stability but low thermostability, which kept only 28% of residual activity after incubation under 50 °C for 3 h. Moreover, Km and kcat/Km for DFA-III was 122 mM and 0.39 mM-1 s-1, respectively. The constructed model of DgDFA-IIIase showed that it has identical residues around substrate at active site with AcDFA-IIIase whose crystal structure has been revealed, indicating that DgDFA-IIIase probably adopts the same catalytic mechanism with the reported AcDFA-IIIase. The work finds that DFA-III can be catalyzed by DFA-IIIase from microorganism of non-Arthrobacter genus, which also extends the enzymatic sources of DFA-IIIase.

Background: Sentinel lymph node biopsy (SLNB) helps to determine accurate pathological stages and facilitates strategies for regional disease control in melanoma. However, whether the number of biopsied sentinel lymph nodes (SLNs) influences the patients’ survival is rarely investigated. Methods: Acral or cutaneous melanoma patients with no history of nodal disease who received SLNB in Fudan University Shanghai Cancer Center (FUSCC) from January 1, 2017, to December 31, 2021 were retrospectively enrolled. Clinicopathological variables including Breslow index, ulceration, number of positive SLNs, SLN/non-SLN status were analyzed. Pathologic nodal (pN) stage and pathological stage were defined. Results: A total of 381 eligible patients were enrolled, of whom 132 (34.7%) patients were diagnosed with SLN-positive. The median number of biopsied SLNs was 2 (range: 1 to 20). Different numbers of biopsied SLNs did not influence the release-free survival (RFS) of the general patients. However, patients with > 2 SLNs had a longer RFS than those with 1-2 SLNs in T4, N1a group and those who rejected complete lymph node dissection (CLND). Conclusions: In patients with T4 melanomas, N1a melanomas and those that did not undergo a CLND, the prognosis of those with 3 or more SLNs retrieved seemed to be improved.

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Diminished cardiovascular reactivity is a proposed marker of motivational dysregulation and is related to a range of adverse behavioural and health outcomes. Social participation represents the frequency an individual engages in social activities, is a form of motivated behaviour, and has been recently linked to lower cardiovascular responses to acute psychological stress. With recent work emphasizing the importance of assessing adaptation of the cardiovascular response to recurrent stress, the aim of the current study is to build on previous work by examining the relationship between social participation and cardiovascular stress response adaptation. Analyses were conducted using a general linear model and previously obtained data from the Pittsburgh Cold Study 3 (PCS 3). Two hundred and thirteen participants (M = 30.13; SD = 10.85) completed a social participation measure and had their systolic and diastolic blood pressure (SBP, DBP) and heart rate (HR) monitored across two separate standardized stress testing sessions. In line with previous research, lower social participation was related to lower cardiovascular responses to stress. Findings also indicate that higher levels of social participation were associated with greater blood pressure habituation to recurrent stress. Given that cardiovascular habituation to recurrent stress signifies good health, the implications of these findings are discussed. Key words: social participation, cardiovascular reactivity, cardiovascular habituation, blood pressure, Pittsburgh Cold Study.

Covid 19 infection and its subsequent post-viral sequelae (long-Covid) has been associated with a range of clinical symptoms, including the more recently recognized autonomic nervous system dysfunction/orthostatic intolerance. Included in the autonomic nervous system dysfunction spectrum includes non-cardiovascular symptoms specifically gastrointestinal symptoms. We present a case of a long-Covid patient with debilitating symptoms consistent with autonomic dysfunction and gastrointestinal symptoms. We highlight the difficulty of diagnosis and management of this patient and the importance of awareness of presentation to not delay care in this complicated patient population.

As an island endemic with a decreasing population, the Critically Endangered Grenada Dove Leptotila wellsi is threatened by accelerated loss of genetic diversity resulting from ongoing habitat fragmentation. Small, threatened populations are difficult to sample directly but advances in molecular methods mean that non-invasive samples can be used. We performed the first assessment of genetic diversity of populations of Grenada Dove by a) assessing mtDNA genetic diversity in the only two areas of occupancy on Grenada, b) defining the number of haplotypes present at each site and c) evaluating evidence of isolation between sites. We used non-invasively collected samples from two locations: Mt Hartman (n=18) and Perseverance (n=12). DNA extraction and PCR were used to amplify 1,751 bps of mtDNA from two mitochondrial markers: NADH dehydrogenase 2 (ND2) and Cytochrome b (Cyt b). Haplotype diversity (h) of 0.4, a nucleotide diversity (π) of 0.4 and two unique haplotypes were identified within the ND2 sequences; one haplotype was identified within the Cyt b sequences. Of the two haplotypes identified; the most common haplotype (haplotype A = 73.9%) was observed at both sites and the other (haplotype B = 26.1%) was unique to Perseverance. Our results show low mitochondrial genetic diversity, a non-expanding population and clear evidence for genetically isolated populations. The Grenada Dove needs urgent conservation action, including habitat protection and potentially augmentation of gene flow by translocation in order to increase genetic resilience and diversity with the ultimate aim of securing the long-term survival of this Critically Endangered species.

Solving large-scale systems of nonlinear equations/inequalities is a fundamental problem in computing and optimization. In this paper, we propose a smoothing approximate framework for this problem. We first transform the convex inequalities into a mini-max problem which is non-differentiable, and then we show that an approximate solution of the convex inequalities problem can be obtained by a smoothing approximation technique. We approach a Newton-type algorithm to solve the approximation problem. Some properties of the novel approximate function are presented and the global convergence of the algorithm is proved under some mild assumptions. Numerical results are conducted to illustrate the efficiency of the proposed method.

Understanding the effects of abandoned coal mine ecological restoration on soil quality and function is important to protect the regional ecological environment. This study aims to evaluate the ecological restoration effects of soil quality in abandoned coal mine area. Taking Fengcheng county, a typical coal- rich area in southern China as a case, this study took 120 soil samples to investigate the influence of restoration years on soil quality by using an integrated soil quality index (SQI). Results indicated that restoration years had significant effects on the saturated hydraulic conductivity (Ks) by affecting the soil bulk density (SBD), clay content and soil water content (SWC). Furthermore, clay, soil organic matter (SOM), Ks and pH were selected to assess the effect of ecological restoration years on soil quality. It was found that the ecological restoration 8 years (ER8) site had higher SQI value, indicating ecological restoration years showed a positive correlation with SQI in abandoned coal mine area. The SQI value was higher for the surface soil layer than the sub-surface soil layer of the restoration area. The results of this study is of great significance for improving the effects of ecological restoration and management in abandoned coal mine area.

The geographical environment of the Qinghai-Tibet Plateau is complex, and there are a large number of poor environmental conditions of pastures, such pastures are limited by the terrain, and the change of grassland function after grazing may be different from that of well-grown pastures. Grazing causes changes in soil physical and chemical properties and soil microbial characteristics and increases soil carbon release in grazed grasslands, which could trigger a positive feedback and threaten the soil carbon function of grazed grasslands. It is therefore necessary to investigate the grazing response of such pastures. Early observations focused on grazing, and observations of different types of grazing and grazing management concluded that insufficient attention had been paid to the effects of environmental constraints on vegetation growth and grazing response. Based on the systematic observation of the response of soil characteristics and soil microbial biomass to grazing gradient in a natural alpine meadow on the Qinghai-Tibet Plateau, the changes in soil ecosystem response to grazing and their correlations are discussed in this paper. The results showed that: 1) environmental conditions, especially the soil environment, significantly influence the response of alpine meadow ecosystems to grazing; 2) SOM is the main controlling factor in the soil material cycle, controlling both aboveground vegetation growth and belowground microbial biomass; 3) grazing increases the activity of soil microorganisms by initiating the microbial stimulation effect, thereby accelerating the consumption of soil nutrients and increasing CO2 release, while creating nutrient competition with aboveground vegetation, which is an important factor causing vegetation degradation, and the continuous increase of the microbial stimulation effect will also weaken the soil carbon sequestration function; 4) in actual production, light grazing is the best choice for alpine meadows in areas with poor growing environment.