Gut microbial metabolite targets HDAC3-FOXK1-interferon axis in fibroblast-like synoviocytes to ameliorate rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune disease. Early studies hold an opinion that gut microbiota is environmentally acquired and associated with RA susceptibility. However, accumulating evidence demonstrates that genetics also shape the gut microbiota. It is known that some strains of inbred laboratory mice are highly susceptible to collagen-induced arthritis (CIA), while the others are resistant to CIA. Here, we show that transplantation of fecal microbiota of CIA-resistant C57BL/6J mice to CIA-susceptible DBA/1J mice confer CIA resistance in DBA/1J mice. C57BL/6J mice and healthy human individuals have enriched B. fragilis than DBA/1J mice and RA patients. Transplantation of B. fragilis prevents CIA in DBA/1J mice. We identify that B. fragilis mainly produces propionate and C57BL/6J mice and healthy human individuals have higher level of propionate. Fibroblast-like synoviocytes (FLSs) in RA are activated to undergo tumor-like transformation. Propionate disrupts HDAC3-FOXK1 interaction to increase acetylation of FOXK1, resulting in reduced FOXK1 stability, blocked interferon signaling and deactivation of RA-FLSs. We treat CIA mice with propionate and show that propionate attenuates CIA. Moreover, a combination of propionate with anti-TNF etanercept synergistically relieves CIA. These results suggest that B. fragilis or propionate could be an alternative or complementary approach to the current therapies.

WGCNA and machine learning analysis identifi ed SAMD9 and IFIT3 as primary Sjögren's Syndrome key genes.

Background: Current treatments for primary Sjögren's Syndrome (pSS) are with limited effect, partially due to the heterogeneity and uncleared mechanism. Methods: We got GSE40568 (Japan) and GSE40611 (USA), and analyzed them with WGCNA to find key Differentially expressed genes (DEGs) between pSS and healthy salivary glands (SG). Key pSS genes (KPGs) were further selected through 3 machine-learning methods. The expression of KPGs was validated via two other GEO datasets (GSE127952 and GSE154926). Infiltrated immune cells, ceRNA network, and potential compounds were explored. Results: Our study identified 376 DEGs from the pSS patients, with 186 genes located in the "plum2" module, showing the strongest correlation with clinical characteristics. SAMD9 and IFIT3 emerged as KPGs with excellent diagnostic potential. SAMD9 demonstrated close association with immune cell infiltration. We constructed a lncRNA-miRNA-mRNA network comprising 2 KPGs, 12 miRNAs, 124 lncRNAs, and potential therapeutic targets. Conclusion: In the investigation of pSS public datasets, our study revealed two potential critical mediators in the pathological process of pSS salivary glands, namely SAMD9 and IFIT3. Furthermore, we put forth a hypothesis regarding the ceRNA network and made predictions regarding potential therapeutic drugs targeting these two genes.

Genome-Wide Analysis of the GLK Gene Family and Its Expression at Different Leaf Ages in the Citrus Cultivar Kanpei.

The GLK gene family plays a crucial role in the regulation of chloroplast development and participates in chlorophyll synthesis. However, the precise mechanism by which GLK contributes to citrus's chlorophyll synthesis remains elusive. The GLK gene family causes variations in the photosynthetic capacity and chlorophyll synthesis of different citrus varieties. In this study, we identified tissue-specific members and the key CcGLKs involved in chlorophyll synthesis. A total of thirty CcGLK transcription factors (TFs) were discovered in the citrus genome, distributed across all nine chromosomes. The low occurrence of gene tandem duplication events and intronic variability suggests that intronic variation may be the primary mode of evolution for CcGLK TFs. Tissue-specific expression patterns were observed for various GLK family members; for instance, CcGLK12 and CcGLK15 were specifically expressed in the skin, while CcGLK30 was specific to the ovary, and CcGLK10, CcGLK6, CcGLK21, CcGLK2, CcGLK18, CcGLK9, CcGLK28, and CcGLK8 were specifically expressed in the leaves. CcGLK4, CcGLK5, CcGLK11, CcGLK23, CcGLKl7, CcGLK26, and CcGLK20 may participate in the regulation of the ALA, prochlorophylate, protoporphyrin IX, Mg-protoporphyrin IX, Chl b, T-Chl, MG-ProtoIX ME, and POR contents in citrus.

Repurposing AS1411 for constructing ANM-PROTACs.

Proteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules consisting of two ligands joined by a linker, enabling them to simultaneously bind with an E3 ligase and a protein of interest (POI) and trigger proteasomal degradation of the POI. Limitations of PROTAC include lack of potent E3 ligands, poor cell selectivity, and low permeability. AS1411 is an antitumor aptamer specifically recognizing a membrane-nucleus shuttling nucleolin (NCL). Here, we repurpose AS1411 as a ligand for an E3 ligase mouse double minute 2 homolog (MDM2) via anchoring the NCL-MDM2 complex. Then, we construct an AS1411-NCL-MDM2-based PROTAC (ANM-PROTAC) by conjugating AS1411 with large-molecular-weight ligands for "undruggable" oncogenic STAT3, c-Myc, p53-R175H, and AR-V7. We show that the ANM-PROTAC efficiently penetrates tumor cells, recruits MDM2 and degrades the POIs. The ANM-PROTAC achieves tumor-selective distribution and exhibits excellent antitumor activity with no systemic toxicity. This is a PROTAC with built-in tumor-targeting and cell-penetrating capacities.

Immune profiling analysis of double-negative T cells in patients with systemic sclerosis.

OBJECTIVE: To construct a molecular immune map of patients with systemic sclerosis (SSc) by mass flow cytometry, and compare the number and molecular expression of double-negative T (DNT) cell subsets between patients and healthy controls (HC). METHODS: Peripheral blood mononuclear cells (PBMCs) were extracted from the peripheral blood of 17 SSc patients and 9 HC. A 42-channel panel was set up to perform mass cytometry by time of flight (CyTOF) analysis for DNT subgroups. Flow cytometry was used to validate subpopulation functions. The clinical data of patients were collected for correlation analysis. RESULTS: Compared with HC, the number of total DNT cells decreased in SSc patients. Six DNT subsets were obtained from CyTOF analysis, in which the proportion of cluster1 increased, while the proportion of cluster3 decreased. Further analysis revealed that cluster1 was characterized by high expression of CD28 and CCR7, and cluster3 was characterized by high expression of CD28 and CCR5. After in vitro stimulation, cluster1 secreted more IL-4 and cluster3 secreted more IL-10 in SSc patients compared to HC. Clinical correlation analysis suggested that cluster1 may play a pathogenic role while cluster3 may play a protective role in SSc. ROC curve analysis further revealed that cluster3 may be a potential indicator for determining disease activity in SSc patients. CONCLUSION: We found a new CCR5+CD28+ DNT cell subset, which played a protective role in the pathogenesis of SSc. Key Points • The number of DNT cells decreased in SSc patients' peripheral blood. • DNT cells do not infiltrate in the skin but secrete cytokines to participate in the pathogenesis of SSc. • A CCR5+CD28+ DNT cell population may play a protective role in SSc.

PITPNC1 Suppress CD8+ T cell immune function and promote radioresistance in rectal cancer by modulating FASN/CD155.

BACKGROUND: Radioresistance is a primary factor contributing to the failure of rectal cancer treatment. Immune suppression plays a significant role in the development of radioresistance. We have investigated the potential role of phosphatidylinositol transfer protein cytoplasmic 1 (PITPNC1) in regulating immune suppression associated with radioresistance. METHODS: To elucidate the mechanisms by which PITPNC1 influences radioresistance, we established HT29, SW480, and MC38 radioresistant cell lines. The relationship between radioresistance and changes in the proportion of immune cells was verified through subcutaneous tumor models and flow cytometry. Changes in the expression levels of PITPNC1, FASN, and CD155 were determined using immunohistochemistry and western blotting techniques. The interplay between these proteins was investigated using immunofluorescence co-localization and immunoprecipitation assays. Additionally, siRNA and lentivirus-mediated gene knockdown or overexpression, as well as co-culture of tumor cells with PBMCs or CD8+ T cells and establishment of stable transgenic cell lines in vivo, were employed to validate the impact of the PITPNC1/FASN/CD155 pathway on CD8+ T cell immune function. RESULTS: Under irradiation, the apoptosis rate and expression of apoptosis-related proteins in radioresistant colorectal cancer cell lines were significantly decreased, while the cell proliferation rate increased. In radioresistant tumor-bearing mice, the proportion of CD8+ T cells and IFN-γ production within immune cells decreased. Immunohistochemical analysis of human and animal tissue specimens resistant to radiotherapy showed a significant increase in the expression levels of PITPNC1, FASN, and CD155. Gene knockdown and rescue experiments demonstrated that PITPNC1 can regulate the expression of CD155 on the surface of tumor cells through FASN. In addition, co-culture experiments and in vivo tumor-bearing experiments have shown that silencing PITPNC1 can inhibit FASN/CD155, enhance CD8+ T cell immune function, promote colorectal cancer cell death, and ultimately reduce radioresistance in tumor-bearing models. CONCLUSIONS: PITPNC1 regulates the expression of CD155 through FASN, inhibits CD8+ T cell immune function, and promotes radioresistance in rectal cancer.

PCSK9 inhibitors for acute coronary syndrome: the era of early implementation.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, a new cholesterol-lowering strategy, can decrease low-density lipoprotein cholesterol (LDL-C) levels by inhibiting PCSK9 and reducing the degradation of LDL receptors; thus, they are impacting the management of dyslipidemia to the prevention of cardiovascular events. Recent guidelines recommend PCSK9 inhibitors for patients who fail to achieve target lipids after ezetimibe/statin therapy. As PCSK9 inhibitors have been demonstrated to significantly and safely reduce LDL-C, discussions have begun to explore its optimal timing in coronary artery disease, especially in subjects with acute coronary syndrome (ACS). Also, their additional benefits, such as anti-inflammatory effects, plaque regression effects, and cardiovascular event prevention, have become the focus of recent research. Several studies, including EPIC-STEMI, suggest the lipid-lowering effects of early PCSK9 inhibitors in ACS patients, while some studies such as PACMAN-AMI suggest that early PCSK9 inhibitors can decelerate plaque progression and reduce short-term risks of cardiovascular events. Thus, PCSK9 inhibitors are entering the era of early implementation. In this review, we are committed to summarizing the multidimensional benefits of early implementation of PCSK9 inhibitors in ACS.

Information Geometry under Hierarchical Quantum Measurement.

In most quantum technologies, measurements need to be performed on the parametrized quantum states to transform the quantum information to classical information. The measurements, however, inevitably distort the information. The characterization of the discrepancy is an important subject in quantum information science, which plays a key role in understanding the difference between the structures of quantum and classical informations. Here we analyze the difference in terms of the Fisher information metric and present a framework that can provide analytical bounds on the discrepancy under hierarchical quantum measurements. Specifically, we present a set of analytical bounds on the difference between the quantum and classical Fisher information metric under hierarchical p-local quantum measurements, which are measurements that can be performed collectively on at most p copies of quantum states. The results can be directly transformed to the precision limit in multiparameter quantum metrology, which leads to characterizations of the trade-off among the precision of different parameters. The framework also provides a coherent picture for various existing results by including them as special cases.

Clinical Efficacy of Laparoscopic-Assisted Proximal Gastrectomy with Postoperative Double-Channel Digestive Tract Reconstruction: A Case-Control Analysis.

Objective: To investigate the clinical effect of laparoscopic-assisted proximal gastrectomy with postoperative double-channel digestive tract reconstruction. Methods: A total of 40 patients with proximal gastric cancer who underwent gastrectomy in Zhujiang Hospital, Southern Medical University, were selected to collect relevant clinical data. They were divided into two groups according to their treatment methods: TG-RY group (total gastrectomy with Roux-en-Y reconstruction group) and PG-DT group (proximal gastrectomy with double tract reconstruction group). The general data, perioperative indicators, nutritional indicators, and postoperative complications of the two groups were analyzed and compared. Results: There was no statistical significance in the comparison of general data between the two groups, but the proportion of III stage patients of TNM stage in the PG-DT group was larger than that in the TG-RY group. Meanwhile, the intraoperative blood loss, postoperative hospital stay, and first exhaust time in PG-DT group were lower than those in TG-RY group (P < 0.05). After surgery, the nutritional indexes of the PG-DT group decreased, and the decrease degree was less than that of the TG-RY group, while the infection indicators of the PG-DT group increased less than that of the TG-RY group. Statistical analysis of postoperative complications showed that the total incidence of PG-DT group was lower than that of TG-RY group. Conclusion: Proximal gastric cancer resection and postoperative DTR anastomosis can effectively speed up the recovery of patients and reduce the incidence of postoperative complications, with good efficacy. This experiment provides evidence for the advantages of various postoperative anastomosis methods and also provides a reliable basis for clinicians' diagnosis and treatment, thus effectively improving patients' postoperative quality of life.

Bone-Derived Modulators That Regulate Brain Function: Emerging Therapeutic Targets for Neurological Disorders.

Bone has traditionally been regarded as a structural organ that supports and protects the various organs of the body. Recent studies suggest that bone also acts as an endocrine organ to regulate whole-body metabolism. Particularly, homeostasis of the bone is shown to be necessary for brain development and function. Abnormal bone metabolism is associated with the onset and progression of neurological disorders. Recently, multiple bone-derived modulators have been shown to participate in brain function and neurological disorders, including osteocalcin, lipocalin 2, and osteopontin, as have bone marrow-derived cells such as mesenchymal stem cells, hematopoietic stem cells, and microglia-like cells. This review summarizes current findings regarding the roles of these bone-derived modulators in the brain, and also follows their involvement in the pathogenesis of neurological disorders. The content of this review may aide in the development of promising therapeutic strategies for neurological disorders via targeting bone.

"Super-Heisenberg" and Heisenberg Scalings Achieved Simultaneously in the Estimation of a Rotating Field.

The Heisenberg scaling, which scales as N^{-1} in terms of the number of particles or T^{-1} in terms of the evolution time, serves as a fundamental limit in quantum metrology. Better scalings, dubbed as "super-Heisenberg scaling," however, can also arise when the generator of the parameter involves many-body interactions or when it is time dependent. All these different scalings can actually be seen as manifestations of the Heisenberg uncertainty relations. While there is only one best scaling in the single-parameter quantum metrology, different scalings can coexist for the estimation of multiple parameters, which can be characterized by multiple Heisenberg uncertainty relations. We demonstrate the coexistence of two different scalings via the simultaneous estimation of the magnitude and frequency of a field where the best precisions, characterized by two Heisenberg uncertainty relations, scale as T^{-1} and T^{-2}, respectively (in terms of the standard deviation). We show that the simultaneous saturation of two Heisenberg uncertainty relations can be achieved by the optimal protocol, which prepares the optimal probe state, implements the optimal control, and performs the optimal measurement. The optimal protocol is experimentally implemented on an optical platform that demonstrates the saturation of the two Heisenberg uncertainty relations simultaneously, with up to five controls. As the first demonstration of simultaneously achieving two different Heisenberg scalings, our study deepens the understanding on the connection between the precision limit and the uncertainty relations, which has wide implications in practical applications of multiparameter quantum estimation.

A machine learning approach to personalized dose adjustment of lamotrigine using noninvasive clinical parameters.

The pharmacokinetic variability of lamotrigine (LTG) plays a significant role in its dosing requirements. Our goal here was to use noninvasive clinical parameters to predict the dose-adjusted concentrations (C/D ratio) of LTG based on machine learning (ML) algorithms. A total of 1141 therapeutic drug-monitoring measurements were used, 80% of which were randomly selected as the "derivation cohort" to develop the prediction algorithm, and the remaining 20% constituted the "validation cohort" to test the finally selected model. Fifteen ML models were optimized and evaluated by tenfold cross-validation on the "derivation cohort," and were filtered by the mean absolute error (MAE). On the whole, the nonlinear models outperformed the linear models. The extra-trees' regression algorithm delivered good performance, and was chosen to establish the predictive model. The important features were then analyzed and parameters of the model adjusted to develop the best prediction model, which accurately described the C/D ratio of LTG, especially in the intermediate-to-high range (≥ 22.1 µg mL-1 g-1 day), as illustrated by a minimal bias (mean relative error (%) = + 3%), good precision (MAE = 8.7 µg mL-1 g-1 day), and a high percentage of predictions within ± 20% of the empirical values (60.47%). This is the first study, to the best of our knowledge, to use ML algorithms to predict the C/D ratio of LTG. The results here can help clinicians adjust doses of LTG administered to patients to minimize adverse reactions.

Zero-trade-off multiparameter quantum estimation via simultaneously saturating multiple Heisenberg uncertainty relations.

Quantum estimation of a single parameter has been studied extensively. Practical applications, however, typically involve multiple parameters, for which the ultimate precision is much less understood. Here, by relating the precision limit directly to the Heisenberg uncertainty relation, we show that to achieve the highest precisions for multiple parameters at the same time requires the saturation of multiple Heisenberg uncertainty relations simultaneously. Guided by this insight, we experimentally demonstrate an optimally controlled multipass scheme, which saturates three Heisenberg uncertainty relations simultaneously and achieves the highest precisions for the estimation of all three parameters in SU(2) operators. With eight controls, we achieve a 13.27-dB improvement in terms of the variance (6.63 dB for the SD) over the classical scheme with the same loss. As an experiment demonstrating the simultaneous achievement of the ultimate precisions for multiple parameters, our work marks an important step in multiparameter quantum metrology with wide implications.

Development of mass spectrometry-based relatively quantitative targeted method for amino acids and neurotransmitters: Applications in the diagnosis of major depression.

Targeted metabolomics analysis based on triple quadrupole (QQQ) MS coupled with multiple reaction monitoring mode (MRM) is the gold standard for metabolite quantification and it is widely applied in metabolomics. However, standard compounds for each metabolite and the corresponding analogs are necessary for quantitative measurements. To identify the differentially present metabolites in various groups, determining the relative concentration of metabolites would be more efficient than accurate quantification. In this study, a relatively quantitative targeted method was established for metabonomics research, on the basis of hydrophilic interaction liquid chromatography (HILIC)/QQQ MS operated in MRM mode. The quality control-base random forest signal correction algorithm (QC-RFSC algorithm) was applied for quality control instead of the internal standard method. High quality relative quantification was achieved without internal standards, and integrated peak areas were successfully used for statistical and pathway analyses. Amino acids and neurotransmitters (dopamine, kynurenic acid, urocanic acid, tryptophan, kynurenine, tyrosine, valine, threonine, serine, alanine, glycine, glutamine, citrulline, GABA, glutamate, aspartate, arginine, ornithine and histidine) in serum samples were simultaneously determined with the newly developed method. To demonstrate the applicability of this method in large-scale analyses, we analyzed the above metabolites in serum from patients with major depression. The serum levels of glutamate, aspartate, threonine, glycine and alanine were significantly higher, and those of citrulline, kynurenic acid and urocanic acid were significantly lower, in patients with major depression than in controls. This is the first report of the difference in urocanic acid, a compound reported to improve glutamate biosynthesis and release in the central nervous system, between healthy controls and patients with major depression.

Minimal Tradeoff and Ultimate Precision Limit of Multiparameter Quantum Magnetometry under the Parallel Scheme.

The precise measurement of a magnetic field is one of the most fundamental and important tasks in quantum metrology. Although extensive studies on quantum magnetometry have been carried out over past decades, the ultimate precision that can be achieved for the estimation of all three components of a magnetic field under the parallel scheme remains unknown. This is largely due to the lack of understandings on the incompatibility of the optimal probe states for the estimation of the three components. Here we provide an approach to characterize the minimal tradeoff among the precisions of multiple parameters that arise from the incompatibility of the optimal probe states, which leads to the identification of the ultimate precision limit for the estimation of all three components of a magnetic field under the parallel scheme. The optimal probe state that achieves the ultimate precision is also explicitly constructed. The obtained precision sets a benchmark on the precision of the multiparameter quantum magnetometry under the parallel scheme, which is of fundamental interest and importance in quantum metrology.

Effect of venlafaxine dosage, valproic acid concentration, sex, and age on steady state dose-corrected concentrations of venlafaxine and O-desmethylvenlafaxine: A retrospective analysis of therapeutic drug monitoring data in a Chinese population.

PURPOSE: This study aimed to investigate the influence of diagnosis, body weight, sex, age, smoking, formulations, and concomitant drugs on steady-state dose-corrected serum concentrations (C/D) of venlafaxine (VEN) and O-desmethylvenlafaxine (ODV). METHODS: A retrospective analysis of therapeutic drug monitoring (TDM) was carried out. Patients' demographic data, therapeutic regimens, and concentrations were collected. RESULTS: We included 91 verified samples from 80 patients. Females had by average 13% smaller body weight, 50% higher C/D of VEN, and VEN + ODV and 25% smaller ODV/VEN than males. Patients >60 years had by average 33-59% higher C/D levels of ODV and VEN + ODV than younger patients. The concomitant use of valproic acid caused an average 51% higher C/D of ODV and a 2.2-fold larger ODV/VEN, while clozapine was related with 40% smaller ratio of ODV/VEN and 38% lower C/D levels of ODV. Positive correlations were detected between valproic acid concentrations and the C/D of VEN and VEN + ODV. In a multiple linear regression analysis, variance in the C/D of VEN + ODV was partly attributed to the daily dose of VEN, sex, age and valproic acid concentration. CONCLUSION: Our results suggested daily dose of VEN, sex, age, and valproic acid as indicators for the C/D of VEN + ODV in Chinese patients. TDM as a valuable tool was suggested in elderly female patients and patients receiving polypharmacy.

A Retrospective Analysis of Steady-State Olanzapine Concentrations in Chinese Patients Using Therapeutic Drug Monitoring: Effects of Valproate and Other Factors.

BACKGROUND: The objective of this study was to investigate the serum concentrations of olanzapine in relation to age, sex, and other factors in Chinese patients aged between 10 and 90 years. METHODS: Data for 884 olanzapine patients, deposited between 2016 and 2017, were retrieved from the therapeutic drug monitoring database of the Affiliated Brain Hospital of Guangzhou Medical University. The effects of covariates on serum olanzapine concentration, dose-normalized concentration (C/D ratio), and normalized concentration (C/D/weight) were investigated. RESULTS: Generally, male patients had lower olanzapine concentration, C/D ratio, and C/D/weight than female patients (P < 0.001). Smoking and drinking reduced olanzapine concentration, C/D ratio, and C/D/weight (P < 0.001). Coadministration with valproate decreased olanzapine concentration, C/D ratio, and C/D/weight by about 16%, 30%, and 40%, respectively (P < 0.001). Patients younger than 60 years had higher olanzapine concentrations (P < 0.05) but lower C/D ratios and C/D/weight (P < 0.001) than patients older than 60 years. Age was correlated with olanzapine concentration (r = -0.082, P < 0.05), C/D ratio (r = 0.196, P < 0.001), and C/D/weight (r = 0.169, P < 0.001). Sample timing after dose and diagnostic factors also contributed to the olanzapine concentrations. Multiple linear regression analysis revealed significant influences of dosage, age, sex, valproate comedication, smoking, postdose interval, and schizophrenia (vs bipolar affective disorders) on serum olanzapine concentrations. CONCLUSIONS: The metabolism of olanzapine may be altered by several factors. Patients characterized with a combination of factors may benefit from therapeutic drug monitoring for the adjustment of olanzapine dose to minimize adverse reactions.

Bibliometric and Visual Analysis of Research on the Links Between the Gut Microbiota and Depression From 1999 to 2019.

Background: There is a crucial link between the gut microbiota and the host central nervous system, and the communication between them occurs via a bidirectional pathway termed the "microbiota-gut-brain axis." The gut microbiome in the modern environment has markedly changed in response to environmental factors. These changes may affect a broad range of host psychiatric disorders, such as depression, by interacting with the host through metabolic, immune, neural, and endocrine pathways. Nevertheless, the general aspects of the links between the gut microbiota and depression have not been systematically investigated through bibliometric analysis. Aim: This study aimed to analyze the current status and developing trends in gut microbiota research in the depression field through bibliometric and visual analysis. Methods: A total of 1,962 publications published between 1999 and 2019 were retrieved from the Web of Science Core Collection. CiteSpace (5.6 R5) was used to perform collaboration network analysis, co-citation analysis, co-occurrence analysis, and citation burst detection. Results: The number of publications has been rapidly growing since 2010. The collaboration network analysis revealed that the USA, University College Cork, and John F. Cryan were the most influential country, institute, and scholar, respectively. The most productive and co-cited journals were Brain Behavior and Immunity and Proceedings of the National Academy of Sciences of the United States of America, respectively. The co-citation analysis of references revealed that the most recent research focus was in the largest theme cluster, "cytokines," thus reflecting the important research foundation in this field. The co-occurrence analysis of keywords revealed that "fecal microbiota" and "microbiome" have become the top two research hotspots since 2013. The citation burst detection for keywords identified several keywords, including "Parkinson's disease," "microbiota-gut-brain axis," "microbiome," "dysbiosis," "bipolar disorder," "impact," "C reactive protein," and "immune system," as new research frontiers, which have currently ongoing bursts. Conclusions: These results provide an instructive perspective on the current research and future directions in the study of the links between the gut microbiota and depression, which may help researchers choose suitable cooperators or journals, and promote their research illustrating the underlying molecular mechanisms of depression, including its etiology, prevention, and treatment.

Continuous supercritical water oxidation treatment of oil-based drill cuttings using municipal sewage sludge as diluent.

Oil-based drill cuttings (OBDC) is a characteristic hazardous waste that is generated in oil and gas exploration. In this study, two typical OBDCs from shale gas fields were treated in a continuous supercritical water oxidation (SCWO) for the first time. Because both heat value and ash content (AC) in the OBDCs were well beyond the capacity of continuous operation, municipal sewage sludge (MSS) was innovatively adapted as the diluent. A mixed sludge with OBDC addition levels of 10%, 20%, and 30% was tested using a novel SCWO reactor. Mean residence times of reactants in different reaction zones were specifically calculated. Results indicated the organic carbon removal efficiency could reach up to 98.44%. Eight detected heavy metals were found to be almost completely removed into solid products, and the concentrations in liquid products were all below the discharge limits. It was also found that the SCWO reactor exhibited good anti-plugging and anti-corrosion performance. The AC in the feedstock was up to 28.58%. To the best of our knowledge, this has, hitherto, not been achieved in a continuous SCWO operation. This study provides a new approach for harmlessly and completely degrading OBDC, and is also helpful for the industrialization of SCWO technology.

Effects of Comedication and Genetic Factors on the Population Pharmacokinetics of Lamotrigine: A Prospective Analysis in Chinese Patients With Epilepsy.

Lamotrigine (LTG) is a second-generation anti-epileptic drug widely used for focal and generalized seizures in adults and children, and as a first-line medication in pregnant women and women of childbearing age. However, LTG pharmacokinetics shows high inter-individual variability, thus potentially leading to therapeutic failure or side effects in patients. This prospective study aimed to establish a population pharmacokinetics model for LTG in Chinese patients with epilepsy and to investigate the effects of genetic variants in uridine diphosphate glucuronosyltransferase (UGT) 1A4, UGT2B7, MDR1, ABCG2, ABCC2, and SLC22A1, as well as non-genetic factors, on LTG pharmacokinetics. The study population consisted of 89 patients with epilepsy, with 419 concentrations of LTG. A nonlinear mixed effects model was implemented in NONMEM software. A one-compartment model with first-order input and first-order elimination was found to adequately characterize LTG concentration. The population estimates of the apparent volume of distribution (V/F) and apparent clearance (CL/F) were 12.7 L and 1.12 L/h, respectively. The use of valproic acid decreased CL/F by 38.5%, whereas the co-administration of rifampicin caused an increase in CL/F of 64.7%. The CL/F decreased by 52.5% in SLC22A1-1222AA carriers. Patients with the ABCG2-34AA genotype had a 42.0% decrease in V/F, whereas patients with the MDR1-2677TT and C3435TT genotypes had a 136% increase in V/F. No obvious genetic effect of UGT enzymes was found relative to the concentrations of LTG in Chinese patients. Recommended dose regimens for patients with different gene polymorphisms and comedications were estimated on the basis of Monte Carlo simulations and the established model. These findings should be valuable for developing individualized dosage regimens in adult and adolescent Chinese patients 13-65 years of age.