Hybrid laparoscopic ureteral reimplantation for the treatment of primary vesicoureteral reflux and obstructive megaureter.

Laparoscopic ureteral reimplantation has gained increasing popularity in treating pediatric primary vesicoureteral reflux (VUR) and obstructive megaureter (OM). However, it is technically challenging with a relatively low success rate compared to open surgery. Here we designed a hybrid technique which incorporates laparoscopic surgery and pneumovesical ureteral reimplantation. From 2023 February to 2024 February, five boys and four girls underwent the hybrid reimplantation smoothly. There were seven children with VUR and two with OM. Patient age ranged from eight months to ten years. The mean time was 201.5 min (range 155-240 min) for unilateral operation and 260 min for bilateral operation. Follow-up ranged from 6.4 to 18.7 months. All patients remained asymptomatic, with voiding cystourethrogram showing cure or urinary ultrasonography showing significant improvement. In conclusion, the hybrid laparoscopic ureteral reimplantation appeared to be a simple and effective minimally invasive surgery for treating primary VUR and OM in children.

Transumbilical single-incision hybrid pyeloplasty for infant ureteropelvic junction obstruction.

Ureteropelvic junction obstruction (UPJO) can be treated by various pyeloplasty techniques. We present a hybrid technique incorporating elements of laparoendoscopic single-site surgery and open pyeloplasty through a single umbilical incision. As a result, seven infants with UPJO underwent the hybrid pyeloplasty smoothly. The mean operative time was 131.9 min. At a follow-up of 11.8-50.0 months, all infants showed significant improvement and no symptoms except for one febrile urinary tract infection. The cosmetic results were very satisfactory without obvious visible scars. Therefore, the hybrid pyeloplasty appears to be a simple and effective minimally invasive surgery for treating infant UPJO.

Machine learning-based prediction of sertraline concentration in patients with depression through therapeutic drug monitoring.

Background: Sertraline is a commonly employed antidepressant in clinical practice. In order to control the plasma concentration of sertraline within the therapeutic window to achieve the best effect and avoid adverse reactions, a personalized model to predict sertraline concentration is necessary. Aims: This study aimed to establish a personalized medication model for patients with depression receiving sertraline based on machine learning to provide a reference for clinicians to formulate drug regimens. Methods: A total of 415 patients with 496 samples of sertraline concentration from December 2019 to July 2022 at the First Hospital of Hebei Medical University were collected as the dataset. Nine different algorithms, namely, XGBoost, LightGBM, CatBoost, random forest, GBDT, SVM, lasso regression, ANN, and TabNet, were used for modeling to compare the model abilities to predict sertraline concentration. Results: XGBoost was chosen to establish the personalized medication model with the best performance (R 2 = 0.63). Five important variables, namely, sertraline dose, alanine transaminase, aspartate transaminase, uric acid, and sex, were shown to be correlated with sertraline concentration. The model prediction accuracy of sertraline concentration in the therapeutic window was 62.5%. Conclusion: In conclusion, the personalized medication model of sertraline for patients with depression based on XGBoost had good predictive ability, which provides guidance for clinicians in proposing an optimal medication regimen.

Analysis of Factors Affecting Concentrations and Concentration-To-Dose Ratios of Trazodone.

BACKGROUND: Trazodone is prescribed for several clinical conditions. Multiple factors may affect trazodone to reach its therapeutic reference range. The concentration-to-dose (C/D) ratio can be used to facilitate the therapeutic drug monitoring of trazodone. The study aimed to investigate factors on the concentrations and C/D ratio of trazodone. METHODS: This study analyzed the therapeutic drug monitoring electronic case information of inpatients in the First Hospital of Hebei Medical University from October 2021 to July 2023. Factors that could affect the concentrations and C/D ratio of trazodone were analyzed, including body mass index, sex, age, smoking, drinking, drug manufacturers, and concomitant drugs. RESULTS: A total of 255 patients were analyzed. The mean age was 52.44 years, and 142 (55.69%) were women. The mean dose of trazodone was 115.29 mg. The mean concentration of trazodone was 748.28 ng/mL, which was in the therapeutic reference range (700-1000 ng/mL). 50.20% of patients reached the reference range, and some patients (36.86%) had concentrations below the reference range. The mean C/D ratio of trazodone was 6.76 (ng/mL)/(mg/d). A significant positive correlation was found between daily dose and trazodone concentrations (r 2 = 0.2885, P < 0.001). Trazodone concentrations were significantly affected by dosage, sex, smoking, drinking, and concomitant drugs of duloxetine or fluoxetine. After dosage emendation, besides the above factors, it was influenced by age ( P < 0.05, P < 0.01, or P < 0.001). CONCLUSIONS: This study identified factors affecting trazodone concentrations and C/D ratio. The results can help clinicians closely monitor patients on trazodone therapy and maintain concentrations within the reference range.

Strain-insensitive and multiplexed potentiometric ion sensors via printed PMMA molecular layer.

Wearable biomimetic electronics have aroused tremendous attention due to their capability to continuously detect and deliver real-time dynamic physiological signals pertaining to the wearer's environment. However, upon close contact with the human skins, a wearable sensor undergoes mechanical strain which inevitably degrades the electrical performance. To address this issue, we demonstrate a universal design approach for stretchable and multiplexed biosensors that can yield unaltered ion sensing performance under variable mechanical tensile strains, which is achieved by introducing a PMMA molecular layer between stretchable substrate and ion sensors. Such design demonstrates reliable multiplexed ion sensing capability and provides high sensitivity (>50 mV/decade), reliable selectivity, as well as wide working range (0.1-100 mM) for sodium, ammonium, potassium and calcium ions in complex sweat biomarkers. Via this introduced PMMA molecular layer, our sensor even exhibits 95 % electrical performance maintained up to 30 % tensile strain, whereas the mechanical tensile property is far superior to original sensor performance. Besides, the sensors were also utilized for real-time monitoring of ions in sweat to validate its biomedical electronics applications. This sensing platform can be easily extended to other biomimetic sensors to enable stable signal acquisition for biomedical electronics.

Artificial intelligence-based model for dose prediction of sertraline in adolescents: a real-world study.

BACKGROUND: Variability exists in sertraline pharmacokinetic parameters in individuals, especially obvious in adolescents. We aimed to establish an individualized dosing model of sertraline for adolescents with depression based on artificial intelligence (AI) techniques. METHODS: Data were collected from 258 adolescent patients treated at the First Hospital of Hebei Medical University between December 2019 to July 2022. Nine different algorithms were used for modeling to compare the prediction abilities on sertraline daily dose, including XGBoost, LGBM, CatBoost, GBDT, SVM, ANN, TabNet, KNN, and DT. Performance of four dose subgroups (50 mg, 100 mg, 150 mg, and 200 mg) were analyzed. RESULTS: CatBoost was chosen to establish the individualized medication model with the best performance. Six important variables were found to be correlated with sertraline dose, including plasma concentration, PLT, MPV, GL, A/G, and LDH. The ROC curve and confusion matrix exhibited the good prediction performance of CatBoost model in four dose subgroups (the AUC of 50 mg, 100 mg, 150 mg, and 200 mg were 0.93, 0.81, 0.93, and 0.93, respectively). CONCLUSION: The AI-based dose prediction model of sertraline in adolescents with depression had a good prediction ability, which provides guidance for clinicians to propose the optimal medication regimen.

[Adsorption of Iopamidol by NaHCO3-activated Buckwheat Biochar].

NaHCO3-activated buckwheat biochar was studied, and an optimal biochar of 0.25N-BC [m(NaHCO3):m(buckwheat bark)=0.25:1]was selected. SEM, BET, XRD, Raman, FTIR, and XPS methods were applied to analyze the effects of NaHCO3 on the physicochemical properties of buckwheat biochar. The adsorption properties and mechanism of NaHCO3-activated buckwheat biochar for iopamidol(IPM), a nonionic iodol X-ray contrast agent, were also investigated. The results showed that compared with buckwheat skin biochar(BC), NaHCO3-activated biochar had higher structural defects(surface area and pore volume increased, respectively, from 480.40 m2·g-1 and 0.29 cm3·g-1 to 572.83 m2·g-1 and 0.40 cm3·g-1, with ID/IG being 1.22 times that of BC), the carbon and oxygen functional groups on the BC surface changed significantly, and the polarity increased [(N+O)/C from 0.15 to 0.24]. The maximum adsorption capacity of 0.25N-BC for IPM was 74.94 mg·g-1, which was 9.51 times that of BC(7.88 mg·g-1). The pseudo-second-order adsorption kinetics and Langmuir and Freundlich isotherm models could well fit the adsorption of 0.25N-BC for IPM. The adsorption processes were mainly chemical, monolayer, and heterogeneous multilayer adsorption. Pore filling, hydrogen bonding, π-π, and n-π interactions were the main mechanisms of 0.25N-BC adsorption for IPM. Comparing the activated buckwheat biochar by different bases [KOH, Na2CO3, NaHCO3, KHCO3, and Ca(HCO3)2], 0.25N-BC exhibited high adsorption capability and short equilibrium time and could effectively remove the IPM residue in the actual water(secondary sedimentation tank effluent and lake). The removal rate of IPM remained at 74.91% after three adsorption-desorption cycles. The results showed that NaHCO3-activated buckwheat biochar was a green, effective, and sustainable adsorbent for the removal of iodine-containing organic matter.

Discovery of Unusual Sesterterpenoids from Colquhounia coccinea var. mollis and Their Metabolic Implications.

Three unusual sesterterpenoids featuring unprecedented rearranged colquhounane (C25) and tetranorcolquhounane (C21) frameworks, colquhounoids E (1) and F (3) and norcolquhounoid F (2), were isolated from a Lamiaceae medicinal plant Colquhounia coccinea var. mollis. Their structures were elucidated by spectroscopic analysis and quantum chemical calculations. A biomimetic inspired regioselective cyclopropane cleavage was achieved under acidic conditions. The immunosuppressive activities of these new sesterterpenoids were also evaluated.

G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.

Genotype-to-phenotype (G2P) prediction has become a mainstream paradigm to facilitate genomic selection (GS)-assisted breeding in the seed industry. Many methods have been introduced for building GS models, but their prediction precision may vary depending on species and specific traits. Therefore, evaluation of multiple models and selection of the appropriate one is crucial to effective GS analysis. Here, we present the G2P container developed for the Singularity platform, which not only contains a library of 16 state-of-the-art GS models and 13 evaluation metrics. G2P works as an integrative environment offering comprehensive, unbiased evaluation analyses of the 16 GS models, which may be run in parallel on high-performance computing clusters. Based on the evaluation outcome, G2P performs auto-ensemble algorithms that not only can automatically select the most precise models but also can integrate prediction results from multiple models. This functionality should further improve the precision of G2P prediction. Another noteworthy function is the refinement design of the training set, in which G2P optimizes the training set based on the genetic diversity analysis of a studied population. Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. This functionality is quite useful in practice, as it reduces the cost of phenotyping when constructing training population. The G2P container and source codes are freely accessible at https://g2p-env.github.io/.

IP4GS: Bringing genomic selection analysis to breeders.

Genomic selection (GS), a strategy to use genotypes to predict phenotypes via statistical or machine learning models, has become a routine practice in plant breeding programs. GS can speed up the genetic gain by reducing phenotyping costs and/or shortening the breeding cycles. GS analysis is complicated involving data clean up and formatting, training and test population analysis, model selection and evaluation, and parameter optimization. In addition, GS analysis also requires some programming skills and knowledge of statistical modeling. Thus, we need a more practical GS tools for breeders. To alleviate this difficulty, we developed the web-based platform IP4GS (https://ngdc.cncb.ac.cn/ip4gs/), which offers a user-friendly interface to perform GS analysis simply through point-and-click actions. IP4GS currently includes seven commonly used models, eleven evaluation metrics, and visualization modules, offering great convenience for plant breeders with limited bioinformatics knowledge to apply GS analysis.

Modeling the influence of phenotypic plasticity on maize hybrid performance.

Phenotypic plasticity, the ability of an individual to alter its phenotype in response to changes in the environment, has been proposed as a target for breeding crop varieties with high environmental fitness. Here, we used phenotypic and genotypic data from multiple maize (Zea mays L.) populations to mathematically model phenotypic plasticity in response to the environment (PPRE) in inbred and hybrid lines. PPRE can be simply described by a linear model in which the two main parameters, intercept a and slope b, reflect two classes of genes responsive to endogenous (class A) and exogenous (class B) signals that coordinate plant development. Together, class A and class B genes contribute to the phenotypic plasticity of an individual in response to the environment. We also made connections between phenotypic plasticity and hybrid performance or general combining ability (GCA) of yield using 30 F1 hybrid populations generated by crossing the same maternal line with 30 paternal lines from different maize heterotic groups. We show that the parameters a and b from two given parental lines must be concordant to reach an ideal GCA of F1 yield. We hypothesize that coordinated regulation of the two classes of genes in the F1 hybrid genome is the basis for high GCA. Based on this theory, we built a series of predictive models to evaluate GCA in silico between parental lines of different heterotic groups.

Baseline survey of psychosocial factors levels and their health effects in a cohort study of natural gas field workers / 中华劳动卫生职业病杂志

Objective: To investigate the level of psychosocial factors in workplace and their health effects among workers in a natural gas field. Methods: A prospective and open cohort of natural gas field workers was established to study the level of workplace psychosocial factors and their health effects, with a follow-up every 5 years. In October 2018, a cluster sampling method was used to conduct a baseline survey of 1737 workers in a natural gas field, including a questionnaire survey on demographic characteristics, workplace psychosocial factors and mental health outcomes, physiological indicators such as height and weight, and biochemical indicators such as blood routine, urine routine, liver function and kidney function. The baseline data of the workers were statistically described and analyzed. The psychosocial factors and mental health outcomes were divided into high and low groups according to the mean score, and the physiological and biochemical indicators were divided into normal and abnormal groups according to the reference range of normal values. Results: The age of 1737 natural gas field workers was (41.8±8.0) years old, and the length of service was (21.0±9.7) years. There were 1470 male workers (84.6%). There were 773 (44.5%) high school (technical secondary school) and 827 (47.6%) college (junior college) graduates, 1490 (85.8%) married (including remarriage after divorce), 641 (36.9%) smokers and 835 (48.1%) drinkers. Among the psychosocial factors, the detection rates of high levels of resilience, self-efficacy, colleague support and positive emotion were all higher than 50%. Among the mental health outcomes evaluation indexes, the detection rates of high levels of sleep disorder, job satisfaction and daily stress were 41.82% (716/1712), 57.25% (960/1677) and 45.87% (794/1731), respectively. The detection rate of depressive symptoms was 22.77% (383/1682). The abnormal rates of body mass index (BMI), triglyceride and low density lipoprotein were 46.74% (810/1733), 36.50% (634/1737) and 27.98% (486/1737), respectively. The abnormal rates of systolic blood pressure, diastolic blood pressure, uric acid, total cholesterol and blood glucose were 21.64% (375/1733), 21.41% (371/1733), 20.67% (359/1737), 20.55% (357/1737) and 19.17% (333/1737), respectively. The prevalence rates of hypertension and diabetes were 11.23% (195/1737) and 3.45% (60/1737), respectively. Conclusion: The detection rates of high level psychosocial factors in natural gas field workers are high, and their effects on physical and mental health remain to be verified. The establishment of a cohort study of the levels and health effects of psychosocial factors provides an important resource for confirming the causal relationship between workplace psychosocial factors and health.

Size-dependent melting of onion-like fullerenic carbons: a molecular dynamics and machine learning study.

The melting thermodynamic characteristics of 2- to 20-layered onion-like fullerenes (OLFn) (C60@C240to C60@···@C6000···@C24000) are comprehensively explored using first-principles-based ReaxFF atomistic simulations and random forest machine learning (RF ML). It is revealed that OLFnshows lower thermal stability than the counterparts of single-walled fullerenes (SWFn). The melting point of SWFnincreases monotonically with increasing size, whereas for OLFn, an unusual size-dependent melting point is observed; OLFnwith intermediate size shows the highest melting point. For small OLFn, the melting occurs from the inner to the outer, whereas for large OLFn, it nucleates from the inner to the outer and to intermediate fullerenes. The melting and erosion behaviors of both SWFnand OLFnare mainly characterized by the nucleation of non-hexagons, nanovoids, carbon chains and emission of C2. RF ML model is developed to predict the melting points of both SWFnand OLFn. Moreover, the analysis of the feature importance reveals that the Stone-Wales transformation is a critical pathway in the melting of SWFnand OLFn. This study provides new insights and perspectives into the thermodynamics and pyrolysis chemistry of fullerenic carbons, and also may shed some lights onto the understanding of thermally-induced erosion of carbon-based resources and spacecraft materials.

Network pharmacology-based approach to investigate the mechanisms of Zingiber officinale Roscoe in the treatment of neurodegenerative diseases.

Neurodegenerative diseases (NDDs) are chronic neurological disorders associated with cognitive or motor dysfunction. As a common spice, Zingiber officinale Roscoe has been used as a medicine to treat a variety of NDDs. However, at the molecular level, the mechanisms of Z. officinale in treating of NDDs have not been deeply investigated. In this study, network pharmacology method, molecular docking, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to predict the mechanisms of Z. officinale in the treatment of NDDs. After a series of biological information analyses, five core targets were obtained, including heme oxygenase 1 (HMOX1), acetylcholinesterase (AChE), nitric oxide synthase (NOS), catechol-O-methyl-transferase (COMT), and metabotropic glutamate receptor 5 (mGluR5). Compounds 75, 68, 46, 67, 69, 49, 66, 50, 34, and 64 were identified as the main components of Z. officinale in the treatment of NDDs. The crucial pathways mainly include neuroactive ligand-receptor signaling pathways, cyclic adenosine monophosphate signaling pathways, dopamine synaptic signaling pathways, and so on. Besides, in vitro experiments by AChE inhibitory activities assay and neuroprotective activities against H2 O2 -induced injury in human neuroblastoma SH-SY5Y cells validated the reliability of the results of network analysis. PRACTICAL APPLICATIONS: Zingiber officinale Roscoe is widely used as a traditional spice and herbal medicine. It contains a number of active ingredients, which have shown activities on anti-neurodegenerative diseases (NDDs). In this paper, the potential mechanism of Z. officinale in the treatment of NDDs is explored through network pharmacology, and it was verified by in vitro experiments. The mechanism was not only clarified at the system level but also proved to be effective at the biological level. The results can be used as a reference for Z. officinale in the treating of NDDs.

QiShenYiQi pills, a Chinese patent medicine, increase bioavailability of atorvastatin by inhibiting Mrp2 expression in rats.

CONTEXT: Atorvastatin (ATV) and QiShenYiQi pills (QSYQ), a Chinese patent medicine, are often co-prescribed to Chinese cardiovascular patients. The effects of QSYQ on the pharmacokinetics of ATV have not been studied. OBJECTIVE: We investigated the influence of QSYQ on the pharmacokinetics of ATV and its metabolites upon oral or intravenous administration of ATV to rats. MATERIALS AND METHODS: Sprague-Dawley rats (n = 5/group) were pre-treated with oral QSYQ (675 mg/kg) or vehicle control for 7 days and then orally administrated ATV (10 mg/kg) or intravenously administrated ATV (2 mg/kg). Serum concentrations of ATV and metabolites were determined by ultra-high performance liquid chromatography tandem mass spectrometry. Expression of metabolic enzymes and transporters in jejunum and ileum were measured by quantitative real-time PCR and Western blot. RESULTS: QSYQ resulted in an increase of AUC0-12 h of ATV from 226.67 ± 42.11 to 408.70 ± 161.75 ng/mL/h and of Cmax of ATV from 101.46 ± 26.18 to 198.00 ± 51.69 ng/mL and in an increased of para-hydroxy atorvastatin from 9.07 ± 6.20 to 23.10 ± 8.70 ng/mL in rats administered ATV orally. No change was observed in rats treated intravenously. The expression of multidrug resistance-associated protein 2 mRNA and protein decreased in ileum, and the mRNA of P-glycoprotein decreased in jejunum, though no change in protein expression was found. DISCUSSION AND CONCLUSIONS: QSYQ increased bioavailability of ATV administered orally through inhibiting the expression of Mrp2 in ileum. Clinicians should pay close attention to potential drug-drug interactions between ATV and QSYQ.

Effect of psychological capital and social support on job satisfaction among workers in a natural gas field / 中国职业医学

@#To explore the effects of psychological capital social support and their interaction on job satisfaction in Methods natural gas field workers. A total of 1 473 workers from a natural gas field were selected as the research subjects ， using convenient sampling method. Job Satisfaction Questionnaire Psychological Capital Questionnaire and Social Support ， Results Scale were used to investigate the scores of job satisfaction psychological capital and social support level. The ， ， detection rates of job satisfaction psychological capital and social support in the high level group were 55.9% 52.5% and ， 48.1% respectively. The detection rates of job satisfaction of workers in the high level psychological capital group and high level （ social support group were higher than those in the low level psychological capital group and low level social support group 67.4% vs ， vs ， P ） 43.3% 71.9% 41.2% all <0.01 . The results of multivariate logistic regression analysis showed that psychological capital ［ （CI） （ - ） and social support had positive effects on job satisfaction odds ratio and 95% confidence interval were 1.58 1.17 2.41 （ - ）， ， P ］ ， and 2.53 1.82 3.52 respectively all <0.01 . Moreover the psychological capital and social support had additive effect on ［ CI （ - ）， CI job satisfaction relative excess risk of interaction and 95% was 3.07 1.02 5.12 attributable proportion and 95% was （ - ）， CI （ - ）］， 0.48 0.35 0.61 synergy index and 95% was 2.34 1.72 3.16 but there was no multiplication interaction between （P ）Conclusion psychological capital and social support >0.05 . Psychological capital and social support can positively affect job satisfaction of natural gas workers. There is an additive interaction between psychological capital and social support on job ， satisfaction but no multiplicative interaction is found. Keywords: ； ； ； ； ； Psychological capital Social support Job satisfaction Interaction Natural gas Worker

UPLC-MS/MS method for the determination of Lenvatinib in rat plasma and its application to drug-drug interaction studies.

Lenvatinib (LEN) is a multitargeted tyrosine kinase inhibitor registered for the first-line treatment of unresectable advanced hepatocellular carcinoma. Wuzhi capsule (WZC) is a traditional Chinese medicine preparation; it is used to decrease the aminotransferase level of the liver and protect liver function. Thus, patients with hepatocellular carcinoma (HCC) are potentially treated with a combination of LEN and WZC, but there is no information about the interaction between the two drugs. We developed a simple, rapid, and sensitive ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the quantitative determination of lenvatinib in rat plasma. Liquid-liquid extraction of plasma samples was carried out with ethyl acetate. Chromatographic separation of analyte was performed using gradient elution with acetonitrile and 0.1% formic acid water. The positive ion multi-response monitoring mode was used, and the target of the parent and daughter ions of LEN and IS were m/z 427.1→370 and m/z 432.1→370, respectively. All the validation projects were in accordance with the guidelines. Good linearity of 0.2-1000 ng/mL (r > 0.999) was achieved. The lower limit of quantification was 0.2 ng/mL. The precision and accuracy are acceptable. The method was successfully applied to pharmacokinetics and drug interaction analysis. The results show that WZC can significantly increase the Cmax (maximum plasma concentration) and AUC (area under the concentration-time curve) of LEN. An UPLC -MS/MS method that can be used for studying drug-drug interaction as a valuable tool was developed in this study. Drug-drug interactions were observed between the WZC and LEN.

Wuzhi capsule increased systemic exposure to methotrexate by inhibiting the expression of OAT1/3 and P-gp.

BACKGROUND: Methotrexate (MTX) is an important anticancer agent and immunosuppressant with a narrow therapeutic window. Wuzhi capsule (WZC) is an extract of Schisandra which is widely used to treat liver diseases. Co-administration of MTX and WZC is common in the clinical setting, but research on the interaction between WZC and MTX is limited. This study aimed to investigate the effects of WZC on the pharmacokinetics of MTX in rats and to explore the role of membrane transport proteins OAT1/3 and P-gp in the interaction of these drugs. METHODS: Plasma MTX concentration was detected by ultra-performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS), and the messenger RNA (mRNA) and protein expression of OAT1/3 and P-gp was evaluated by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and western blotting analyses, respectively. RESULTS: The study results revealed that co-administration of WZC decreased the CLz/F and Vz/F of MTX, increased the Cmax and area under the curve [(AUC)0-24 h] of MTX, and inhibited OAT1/3 expression in the kidney and P-gp expression in the small intestine. CONCLUSIONS: The findings suggested that there is a drug interaction between WZC and MTX and that OAT1/3 in the kidney and P-gp in the small intestine may be the main targets mediating the drug interaction, and attention should be paid when they are used in combination.

The effects of sodium glucose co-transporter (SGLT) 2 inhibitors on hematocrit levels: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Previous studies have suggested benefits of sodium glucose co-transporter 2 (SGLT2) inhibitors including improving glycemic control, lower body weight, uric acid-lowering effect and decreasing blood pressure. The aim of this study was to evaluate the effects of SGLT2 inhibitors on hematocrit (Hct) levels in patients with type 2 diabetes mellitus. METHODS: Embase, CENTRAL, PubMed and other databases were searched from the establishment of the database through to July 2020. Randomized controlled trials (RCTs) involving patients with type 2 diabetes mellitus who were treated with SGLT2 inhibitors were analyzed using the random effects model. Stata 12.0 statistical software was used to estimate the weighted mean difference (WMD) and the 95% confidence intervals (CIs). RESULTS: A total of 40 RCTs were included, comprising 21,050 patients. SGLT2 inhibitors resulted in a significant increase in Hct levels compared to patients treated with a placebo (WMD 2.67%, 95% CI, 2.53 to 2.82; P<0.001). Treatment with 2.5, 5, and 10 mg of dapagliflozin significantly increased Hct levels (WMD 1.96%, 2.27%, and 2.47%, respectively; P<0.001). Administration of 100 and 300 mg of canagliflozin also resulted in a significant increase in Hct (WMD 2.91% and 2.94%, respectively; P<0.001). Similarly, empagliflozin, at concentrations of 10 and 25 mg, caused a significant increase in Hct (WMD 3.39% and 3.44%, respectively; P<0.001). However, treatment with ipragliflozin (12.5 and 50 mg) and ertugliflozin (5 and 15 mg) only resulted in a slight increase in patient Hct levels (WMD 1.26% and 1.98%, respectively for ipragliflozin, P>0.05; WMD 2.24% and 2.64%, respectively for ertugliflozin; P>0.05). DISCUSSION: SGLT2 inhibitors, as a class of drugs, increased Hct levels in patients with type 2 diabetes, and this increase was slightly more pronounced at higher doses compared to lower doses. TRIAL REGISTRATION: The protocol of this study has been submitted to the PROSPERO platform (https://www.crd.york.ac.uk/PROSPERO/), and the registration number is CRD42020200699.

HIF-1α promoted vasculogenic mimicry formation in lung adenocarcinoma through NRP1 upregulation in the hypoxic tumor microenvironment.

Neovascularization is a key factor that contributes to tumor metastasis, and vasculogenic mimicry (VM) is an important form of neovascularization found in highly invasive tumors, including lung cancer. Despite the increasing number of studies focusing on VM, the mechanisms underlying VM formation remain unclear. Herein, our study explored the role of the HIF-1α/NRP1 axis in mediating lung adenocarcinoma metastasis and VM formation. HIF-1α, NRP1 expression, and VM in lung adenocarcinoma (LUAD) patient samples were examined by immunohistochemical staining. Quantitative real-time (qRT-PCR), western blot, transwell assay, wound healing assay, and tube formation assay were performed to verify the role of HIF-1α/NRP1 axis in LUAD metastasis and VM formation. ChIP and luciferase reporter assay were used to confirm whether NRP1 is a direct target of HIF-1α. In LUAD tissues, we confirmed a positive relationship between HIF-1α and NRP1 expression. Importantly, high HIF-1α and NRP1 expression and the presence of VM were correlated with poor prognosis. We also found that HIF-1α could induce LUAD cell migration, invasion, and VM formation by regulating NRP1. Moreover, we demonstrated that HIF-1α can directly bind to the NRP1 promoter located between -2009 and -2017 of the promoter. Mechanistically, MMP2, VE-cadherin, and Vimentin expression were affected. HIF-1α plays an important role in inducing lung adenocarcinoma cell metastasis and VM formation via upregulation of NRP1. This study highlights the potential therapeutic value of targeting NRP1 for suppressing lung adenocarcinoma metastasis and progression.