Host-specific SRSF7 regulates polymerase activity and replication of influenza A virus.

Avian influenza viruses crossing the host barrier to infect humans have caused great panic in human society and seriously threatened public health. Herein, we revealed that knockdown of SRSF7 significantly down-regulated influenza virus titers and viral protein expression. We further observed for the first time that human SRSF7, but not avian SRSF7, significantly inhibited polymerase activity (PB2627E). Molecular mapping demonstrated that amino acids 206 to 228 of human SRSF7 play a decisive role in regulating the polymerase activity, which contains the amino acid motif absent in avian SRSF7. Importantly, our results illustrated that the PB2627K-encoding influenza virus induces SRSF7 protein degradation more strongly via the lysosome pathway and not via the proteasome pathway. Functional enrichment analysis of SRSF7-related KEGG pathways indicated that SRSF7 is closely related to cell growth and death. Lastly, our results showed that knocking down SRSF7 interferes with normal polymerase activity. Taken together, our results advance our understanding of interspecies transmission and our findings point out new targets for the development of drugs preventing or treating influenza virus infection.

Weight, CYP3A5 Genotype, and Voriconazole Co-administration Influence Tacrolimus Initial Dosage in Pediatric Lung Transplantation Recipients with Low Hematocrit based on a Simulation Model.

OBJECTIVE: The method of administering the initial doses of tacrolimus in recipients of pediatric lung transplantation, especially in patients with low hematocrit, is not clear. The present study aims to explore whether weight, CYP3A5 genotype, and voriconazole co-administration influence tacrolimus initial dosage in recipients of pediatric lung transplantation with low hematocrit based on safety and efficacy using a simulation model. METHODS: The present study utilized the tacrolimus population pharmacokinetic model, which was employed in lung transplantation recipients with low hematocrit. RESULTS: For pediatric lung transplantation recipients not carrying CYP3A5*1 and without voriconazole, the recommended tacrolimus doses for weights of 10-13, 13-19, 19-22, 22-35, 35-38, and 38-40 kg are 0.03, 0.04, 0.05, 0.06, 0.07, and 0.08 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients carrying CYP3A5*1 and without voriconazole, the recommended tacrolimus doses for weights of 10-18, 18-30, and 30-40 kg are 0.06, 0.08, 0.11 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients not carrying CYP3A5*1 and with voriconazole, the recommended tacrolimus doses for weights of 10-20 and 20-40 kg are 0.02 and 0.03 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients carrying CYP3A5*1 and with voriconazole, the recommended tacrolimus doses for weights of 10-20, 20-33, and 33-40 kg are 0.03, 0.04, and 0.05 mg/kg/day, which are split into two doses, respectively. CONCLUSION: The present study is the first to recommend the initial dosages of tacrolimus in recipients of pediatric lung transplantation with low hematocrit using a simulation model.

Signals from intestinal microbiota mediate the crosstalk between the lung-gut axis in an influenza infection mouse model.

Introduction: Introduction: The influenza virus primarily targets the respiratory tract, yet both the respiratory and intestinal systems suffer damage during infection. The connection between lung and intestinal damage remains unclear. Methods: Our experiment employs 16S rRNA technology and Liquid Chromatography-Mass Spectrometry (LC-MS) to detect the impact of influenza virus infection on the fecal content and metabolites in mice. Additionally, it investigates the effect of influenza virus infection on intestinal damage and its underlying mechanisms through HE staining, Western blot, Q-PCR, and flow cytometry. Results: Our study found that influenza virus infection caused significant damage to both the lungs and intestines, with the virus detected exclusively in the lungs. Antibiotic treatment worsened the severity of lung and intestinal damage. Moreover, mRNA levels of Toll-like receptor 7 (TLR7) and Interferon-b (IFN-b) significantly increased in the lungs post-infection. Analysis of intestinal microbiota revealed notable shifts in composition after influenza infection, including increased Enterobacteriaceae and decreased Lactobacillaceae. Conversely, antibiotic treatment reduced microbial diversity, notably affecting Firmicutes, Proteobacteria, and Bacteroidetes. Metabolomics showed altered amino acid metabolism pathways due to influenza infection and antibiotics. Abnormal expression of indoleamine 2,3-dioxygenase 1 (IDO1) in the colon disrupted the balance between helper T17 cells (Th17) and regulatory T cells (Treg cells) in the intestine. Mice infected with the influenza virus and supplemented with tryptophan and Lactobacillus showed reduced lung and intestinal damage, decreased Enterobacteriaceae levels in the intestine, and decreased IDO1 activity. Discussion: Overall, influenza infection caused damage to lung and intestinal tissues, disrupted intestinal microbiota and metabolites, and affected Th17/Treg balance. Antibiotic treatment exacerbated these effects. Supplementation with tryptophan and Lactobacillus improved lung and intestinal health, highlighting a new understanding of the lung-intestine connection in influenza-induced intestinal disease.

Effects of Sex Differences and Combined Use of Clozapine on Initial Dosage Optimization of Valproic Acid in Patients with Bipolar Disorder.

BACKGROUND: Due to the narrow therapeutic window and large pharmacokinetic variation of valproic acid (VPA), it is difficult to make an optimal dosage regimen. The present study aims to optimize the initial dosage of VPA in patients with bipolar disorder. METHODS: A total of 126 patients with bipolar disorder treated by VPA were included to construct the VPA population pharmacokinetic model retrospectively. Sex differences and combined use of clozapine were found to significantly affect VPA clearance in patients with bipolar disorder. The initial dosage of VPA was further optimized in male patients without the combined use of clozapine, female patients without the combined use of clozapine, male patients with the combined use of clozapine, and female patients with the combined use of clozapine, respectively. RESULTS: The CL/F and V/F of VPA in patients with bipolar disorder were 11.3 L/h and 36.4 L, respectively. It was found that sex differences and combined use of clozapine significantly affected VPA clearance in patients with bipolar disorder. At the same weight, the VPA clearance rates were 1.134, 1, 1.276884, and 1.126 in male patients without the combined use of clozapine, female patients without the combined use of clozapine, male patients with the combined use of clozapine, and female patients with the combined use of clozapine, respectively. This study further optimized the initial dosage of VPA in male patients without the combined use of clozapine, female patients without the combined use of clozapine, male patients with the combined use of clozapine, and female patients with the combined use of clozapine, respectively. CONCLUSION: This study is the first to investigate the initial dosage optimization of VPA in patients with bipolar disorder based on sex differences and the combined use of clozapine. Male patients had higher clearance, and the recommended initial dose decreased with increasing weight, providing a reference for the precision drug use of VPA in clinical patients with bipolar disorder.

Legionella maceachernii pneumonia: a case report and literature review.

BACKGROUND: Legionella maceachernii pneumonia is a severe respiratory infection with low incidence but high mortality. However, the optimal treatment for this disease remains unclear. We report a case of successful treatment of Legionella maceachernii pneumonia, which is the first report of such a case in China. CASE PRESENTATION: An 87-year-old man with concomitant chronic obstructive pulmonary disease, liver cirrhosis, and history of left nephrectomy was diagnosed with Legionella maceachernii pneumonia using Dano-seq pathogen metagenomic testing. After two weeks of treatment with cefoperazone/sulbactam combined with quinolone antibiotics, the patient showed improvement and was discharged. The patient continued to take oral quinolone antibiotics for one week after discharge and recovered during outpatient follow-up. CONCLUSIONS: Dano-seq pathogen metagenomic testing can rapidly diagnose Legionella maceachernii pneumonia, and taking quinolone antibiotics is an effective treatment.

Manipulating AIE ligands into layers of pillar-layered MOFs for enhanced emission.

Four pillar-layered AIEgen-based MOFs exhibit higher thermal stability, tunable emission colors and improved QYs compared with that of non-pillar-layered AIEgen-based MOFs by confining the AIE ligands into layers. These results reveal that rationally manipulating AIE ligands into layers of pillar-layered MOFs is an effective strategy for the design and construction of tunable luminescent MOF systems.

Drug-drug interaction and initial dosage optimization of aripiprazole in patients with schizophrenia based on population pharmacokinetics.

Background: The present study aimed to investigate the drug-drug interaction and initial dosage optimization of aripiprazole in patients with schizophrenia based on population pharmacokinetics. Research design and methods: A total of 119 patients with schizophrenia treated with aripiprazole were included to build an aripiprazole population pharmacokinetic model using nonlinear mixed effects. Results: The weight and concomitant medication of fluoxetine influenced aripiprazole clearance. Under the same weight, the aripiprazole clearance rates were 0.714:1 in patients with or without fluoxetine, respectively. In addition, without fluoxetine, for the once-daily aripiprazole regimen, dosages of 0.3 and 0.2 mg kg-1 day-1 were recommended for patients with schizophrenia weighing 40-95 and 95-120 kg, respectively, while for the twice-daily aripiprazole regimen, 0.3 mg kg-1 day-1 was recommended for those weighing 40-120 kg. With fluoxetine, for the once-daily aripiprazole regimen, a dosage of 0.2 mg kg-1 day-1 was recommended for patients with schizophrenia weighing 40-120 kg, while for the twice-daily aripiprazole regimen, 0.3 and 0.2 mg kg-1 day-1 were recommended for those weighing 40-60 and 60-120 kg, respectively. Conclusion: This is the first investigation of the effects of fluoxetine on aripiprazole via drug-drug interaction. The optimal aripiprazole initial dosage is recommended in patients with schizophrenia.

Document-level biomedical relation extraction via hierarchical tree graph and relation segmentation module.

MOTIVATION: Biomedical relation extraction at the document level (Bio-DocRE) involves extracting relation instances from biomedical texts that span multiple sentences, often containing various entity concepts such as genes, diseases, chemicals, variants, etc. Currently, this task is usually implemented based on graphs or transformers. However, most work directly models entity features to relation prediction, ignoring the effectiveness of entity pair information as an intermediate state for relation prediction. In this article, we decouple this task into a three-stage process to capture sufficient information for improving relation prediction. RESULTS: We propose an innovative framework HTGRS for Bio-DocRE, which constructs a hierarchical tree graph (HTG) to integrate key information sources in the document, achieving relation reasoning based on entity. In addition, inspired by the idea of semantic segmentation, we conceptualize the task as a table-filling problem and develop a relation segmentation (RS) module to enhance relation reasoning based on the entity pair. Extensive experiments on three datasets show that the proposed framework outperforms the state-of-the-art methods and achieves superior performance. AVAILABILITY AND IMPLEMENTATION: Our source code is available at https://github.com/passengeryjy/HTGRS.

Visual Recalibration and Gating Enhancement Network for Radiology Report Generation.

Automatic radiology medical report generation is a necessary development of artificial intelligence technology in the health care. This technology serves to aid doctors in producing comprehensive diagnostic reports, alleviating the burdensome workloads of medical professionals. However, there are some challenges in generating radiological reports: (1) visual and textual data biases and (2) long-distance dependency problem. To tackle these issues, we design a visual recalibration and gating enhancement network (VRGE), which composes of the visual recalibration module and the gating enhancement module (gating enhancement module, GEM). Specifically, the visual recalibration module enhances the recognition of abnormal features in lesion areas of medical images. The GEM dynamically adjusts the contextual information in the report by introducing gating mechanisms, focusing on capturing professional medical terminology in medical text reports. We have conducted sufficient experiments on the public datasets of IU X-Ray to illustrate that the VRGE outperforms existing models.

Mercury, natural fertility and outcomes of assisted reproduction: A systematic review.

The primary route of mercury exposure for the general population is through consumption of contaminated seafood. There is a biological basis for an adverse effect of mercury exposure on human fertility. The goal of this review was to evaluate the existing literature on the association between mercury and pregnancy, among men and women attempting to conceive with and without assisted reproductive technology (ART). Systematic searches were performed in PubMed, EMBASE, Scopus and Web of Science for papers published up to March 2023 with no early date restriction, only including studies with a biomarker measurement of mercury exposure. We identified 11 studies examining mercury and natural fertility and 12 studies examining mercury and outcomes of assisted reproduction (implantation or clinical pregnancy). The accumulated evidence provides some support for a null association between bodily mercury concentrations and natural fertility among women, however, a large proportion of studies did not report adjusted estimates or were extremely imprecise. The majority of studies of natural fertility were also cross-sectional in nature. There was no evidence for an inverse or null association between mercury and natural fertility among men, or mercury and ART outcomes among men or women. In spite of biological plausibility, the existing evidence includes studies that are imprecise and often conflicting and does not allow us to make definitive conclusions on the associations of mercury exposure with successful pregnancy. Additional, larger studies are warranted, especially among individuals with high concentrations of mercury exposure as these individuals may be underrepresented in the current literature.

Spatiotemporal constrained RNA-protein heterogeneous network for protein complex identification.

The identification of protein complexes from protein interaction networks is crucial in the understanding of protein function, cellular processes and disease mechanisms. Existing methods commonly rely on the assumption that protein interaction networks are highly reliable, yet in reality, there is considerable noise in the data. In addition, these methods fail to account for the regulatory roles of biomolecules during the formation of protein complexes, which is crucial for understanding the generation of protein interactions. To this end, we propose a SpatioTemporal constrained RNA-protein heterogeneous network for Protein Complex Identification (STRPCI). STRPCI first constructs a multiplex heterogeneous protein information network to capture deep semantic information by extracting spatiotemporal interaction patterns. Then, it utilizes a dual-view aggregator to aggregate heterogeneous neighbor information from different layers. Finally, through contrastive learning, STRPCI collaboratively optimizes the protein embedding representations under different spatiotemporal interaction patterns. Based on the protein embedding similarity, STRPCI reweights the protein interaction network and identifies protein complexes with core-attachment strategy. By considering the spatiotemporal constraints and biomolecular regulatory factors of protein interactions, STRPCI measures the tightness of interactions, thus mitigating the impact of noisy data on complex identification. Evaluation results on four real PPI networks demonstrate the effectiveness and strong biological significance of STRPCI. The source code implementation of STRPCI is available from https://github.com/LI-jasm/STRPCI.

Intestinal NSD2 Aggravates Nonalcoholic Steatohepatitis Through Histone Modifications.

Mounting clinical evidence suggests that a comprised intestinal barrier contributes to the progression of nonalcoholic steatohepatitis (NASH); nevertheless, the precise mechanism remains elusive. This study unveils a significant upregulation of nuclear receptor-binding SET domain protein 2 (NSD2) in the intestines of obese humans and mice subjected to a high-fat cholesterol diet (HFCD). Intestine-specific NSD2 knockout attenuated the progression of intestinal barrier impairment and NASH, whereas NSD2 overexpression exacerbated this progression. Mechanistically, NSD2 directly regulates the transcriptional activation of Ern1 by demethylating histone H3 at lysine 36 (H3K36me2), thus activating the ERN1-JNK axis to intensify intestinal barrier impairment and subsequently foster NASH progression. These findings elucidate the crucial role of NSD2-mediated H3K36me2 in intestinal barrier impairment, suggesting that targeting intestinal NSD2 can represent a novel therapeutic approach for NASH.

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OBJECTIVES: To investigate the risk factors for bronchopulmonary dysplasia (BPD) in twin preterm infants with a gestational age of <34 weeks, and to provide a basis for early identification of BPD in twin preterm infants in clinical practice. METHODS: A retrospective analysis was performed for the twin preterm infants with a gestational age of <34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020. According to their conditions, they were divided into group A (both twins had BPD), group B (only one twin had BPD), and group C (neither twin had BPD). The risk factors for BPD in twin preterm infants were analyzed. Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins. RESULTS: A total of 904 pairs of twins with a gestational age of <34 weeks were included in this study. The multivariate logistic regression analysis showed that compared with group C, birth weight discordance of >25% between the twins was an independent risk factor for BPD in one of the twins (OR=3.370, 95%CI: 1.500-7.568, P<0.05), and high gestational age at birth was a protective factor against BPD (P<0.05). The conditional logistic regression analysis of group B showed that small-for-gestational-age (SGA) birth was an independent risk factor for BPD in individual twins (OR=5.017, 95%CI: 1.040-24.190, P<0.05). CONCLUSIONS: The development of BPD in twin preterm infants is associated with gestational age, birth weight discordance between the twins, and SGA birth.

An "off-on-enhanced on" electrochemiluminescence biosensor based on resonance energy transfer and surface plasmon coupled 3D DNA walker for ultra-sensitive detection of microRNA-21.

In this study, a novel electrochemiluminescence (ECL) biosensor was developed to detect microRNA-21 (miRNA-21) with high sensitivity by leveraging the combined mechanisms of resonance energy transfer (RET) and surface plasmon coupling (SPC). Initially, the glassy carbon electrode (GCE) were coated with Cu-Zn-In-S quantum dots (CZIS QDs), known for their defect-related emission suitable for ECL sensing. Subsequently, a hairpin DNA H3 with gold nanoparticles (Au NPs) attached at the end was modified over the surface of the quantum dots. The Au NPs could effectively quench the ECL signals of CZIS QDs via RET. Further, a significant amount of report DNA was generated through the action of a 3D DNA walker. When the report DNA opened H3-Au NPs, the hairpin structure experienced a conformational change to a linear shape, increasing the gap between the CZIS QDs and the Au NPs. Consequently, the localized surface plasmon resonance ECL (LSPR-ECL) effect replaced ECL resonance energy transfer (ECL-RET). Moreover, the report DNA was released following the addition of H4-Au NPs, resulting in the formation of Au dimers and a surface plasma-coupled ECL (SPC-ECL) effect that enhanced the ECL intensity to 6.97-fold. The integration of new ECL-RET and SPC-ECL biosensor accurately quantified miRNA-21 concentrations from 10-8 M to 10-16 M with a limit of detection (LOD) of 0.08 fM, as well as successfully applied to validate human serum samples.

Knowledge enhanced attention aggregation network for medicine recommendation.

The combination of deep learning and the medical field has recently achieved great success, particularly in recommending medicine for patients. However, patients' clinical records often contain repeated medical information that can significantly impact their health condition. Most existing methods for modeling longitudinal patient information overlook the impact of individual diagnoses and procedures on the patient's health, resulting in insufficient patient representation and limited accuracy of medicine recommendations. Therefore, we propose a medicine recommendation model called KEAN, which is based on an attention aggregation network and enhanced graph convolution. Specifically, KEAN can aggregate individual diagnoses and procedures in patient visits to capture significant features that affect patients' diseases. We further incorporate medicine knowledge from complex medicine combinations, reduce drug-drug interactions (DDIs), and recommend medicines that are beneficial to patients' health. The experimental results on the MIMIC-III dataset demonstrate that our model outperforms existing advanced methods, which highlights the effectiveness of the proposed method.

TransFOL: A Logical Query Model for Complex Relational Reasoning in Drug-Drug Interaction.

Predicting drug-drug interaction (DDI) plays a crucial role in drug recommendation and discovery. However, wet lab methods are prohibitively expensive and time-consuming due to drug interactions. In recent years, deep learning methods have gained widespread use in drug reasoning. Although these methods have demonstrated effectiveness, they can only predict the interaction between a drug pair and do not contain any other information. However, DDI is greatly affected by various other biomedical factors (such as the dose of the drug). As a result, it is challenging to apply them to more complex and meaningful reasoning tasks. Therefore, this study regards DDI as a link prediction problem on knowledge graphs and proposes a DDI prediction model based on Cross-Transformer and Graph Convolutional Networks (GCNs) in first-order logical query form, TransFOL. In the model, a biomedical query graph is first built to learn the embedding representation. Subsequently, an enhancement module is designed to aggregate the semantics of entities and relations. Cross-Transformer is used for encoding to obtain semantic information between nodes, and GCN is used to gather neighbour information further and predict inference results. To evaluate the performance of TransFOL on common DDI tasks, we conduct experiments on two benchmark datasets. The experimental results indicate that our model outperforms state-of-the-art methods on traditional DDI tasks. Additionally, we introduce different biomedical information in the other two experiments to make the settings more realistic. Experimental results verify the strong drug reasoning ability and generalization of TransFOL in complex settings.

Pregnancy Outcomes in Women Who Developed Elevated Blood Pressure and Stage I Hypertension after 20 Weeks Gestation.

OBJECTIVE: The American College of Obstetrics threshold for hypertension (≥140/90 mm Hg) differs from those of the American College of Cardiology (ACC) and the American Heart Association (AHA). It is unknown if ACC/AHA hypertension levels are associated with adverse pregnancy outcomes (APOs) after 20 weeks gestation. The purpose of this study is to analyze APOs in women with blood pressure (BP) in the elevated or stage 1 range after 20 weeks gestation. STUDY DESIGN: This was a secondary analysis of the nuMoM2b prospective cohort study of 10,038 nulliparous, singleton pregnancies between 2010 and 2014. BP was measured at three visits during the pregnancy using a standard protocol. Women without medical comorbidities, with normal BP by ACC/AHA guidelines (systolic BP [SBP] < 120 and diastolic BP [DBP] < 80 mm Hg) up to 22 weeks, were included. Exposure was BP between 22 and 29 weeks gestation: normal (SBP < 120 and DBP < 80 mm Hg), elevated (SBP: 120-129 and DBP < 80 mm Hg), and stage 1 (SBP: 130-139 or DBP: 80-89 mm Hg). The primary outcome was hypertensive disorder of pregnancy (HDP) at delivery. Secondary outcomes included fetal growth restriction (FGR), placental abruption, preterm delivery, and cesarean delivery. Multivariable-adjusted odds ratio (aORs) and 95% confidence intervals (CIs) were estimated using logistic regression models. RESULTS: Of 4,460 patients that met inclusion criteria, 3,832 (85.9%) had BP in the normal range, 408 (9.1%) in elevated, and 220 (4.9%) in stage 1 range between 22 and 29 weeks. The likelihood of HDP was significantly higher in women with elevated BP (aOR 1.71, 95%CI: 1.18,2.48), and stage 1 BP (aOR: 2.79, 95%CI: 1.84,4.23) compared to normal BP (p < 0.001). Stage 1 BP had twice odds of FGR (aOR: 2.33, 95%CI: 1.22,4.47) and elevated BP had three times odds of placental abruption (aOR: 3.03; 95%CI: 1.24,7.39). CONCLUSION: Elevated or stage 1 BP >20 weeks of pregnancy are associated with HDP, FGR, and placental abruption. KEY POINTS: · Elevated and stage 1 BP increases risk for HDP.. · Elevated BP increases risk for placental abruption.. · Stage 1 BP increases risk for FGR..

Radical cascade silylation/cyclization of 1,7-dienes to access silyl-substituted benzo[b]azepin-2-ones.

A novel silyl radical-induced cascade silylation/cyclization of 1,7-dienes has been realized employing readily available hydrosilanes as a silicon source and Cu(I) salt as a catalyst. This protocol introduces diverse silicon fragments into a challenging 7-membered ring structure and provides an efficient approach to a wide array of biologically important silyl-substituted benzo[b]azepin-2-ones. Several control experiments suggest that the reaction undergoes a free radical process. The gram-scale synthesis and late-stage transformations further demonstrate the scalability and applicability of the reaction in organic synthesis.

Effects of Aripiprazole on Olanzapine Population Pharmacokinetics and Initial Dosage Optimization in Schizophrenia Patients.

Objective: Olanzapine has already been used to treat schizophrenia patients; however, the initial dosage recommendation when multiple drugs are used in combination, remains unclear. The purpose of this study was to explore the drug-drug interaction (DDI) of multiple drugs combined with olanzapine and to recommend the optimal administration of olanzapine in schizophrenia patients. Methods: In this study, we obtained olanzapine concentrations from therapeutic drug monitoring (TDM) database. In addition, related medical information, such as physiological, biochemical indexes, and concomitant drugs was acquired using medical log. Sixty-five schizophrenia patients were enrollmented for analysis using population pharmacokinetic model by means of nonlinear mixed effect (NONMEM). Results: Weight and combined use of aripiprazole significantly affected olanzapine clearance. Without aripiprazole, for once-daily olanzapine administration dosages, 0.6, 0.5 mg/kg/day were recommended for 40-70, and 70-100 kg schizophrenia patients, respectively; for twice-daily olanzapine administration dosages, 0.6, 0.5 mg/kg/day were recommended for 40-60, and 60-100 kg schizophrenia patients, respectively. With aripiprazole, for once-daily olanzapine administration dosages, 0.4, 0.3 mg/kg/day were recommended for 40-53, and 53-100 kg schizophrenia patients, respectively; for twice-daily olanzapine administration dosages, 0.4 mg/kg/day was recommended for 40-100 kg schizophrenia patients, respectively. Conclusion: Aripiprazole significantly affected olanzapine clearance, and when schizophrenia patients use aripiprazole, the olanzapine dosages need adjust. Meanwhile, we firstly recommended the optimal initial dosages of olanzapine in schizophrenia patients.

Experimental Study on the Wind Erosion Resistance of Aeolian Sand Solidified by Microbially Induced Calcite Precipitation (MICP).

Microbially induced calcite precipitation (MICP) is an emerging solidification method characterized by high economic efficiency, environmental friendliness, and durability. This study validated the reliability of the MICP sand solidification method by conducting a small-scale wind tunnel model test using aeolian sand solidified by MICP and analyzing the effects of wind velocity (7 m/s, 10 m/s, and 13 m/s), deflation angle (0°, 15°, 30°, and 45°), wind erosion cycle (1, 3, and 5), and other related factors on the mass loss rate of solidified aeolian sand. The microstructure of aeolian sand was constructed by performing mesoscopic and microscopic testing based on X-ray diffraction analysis (XRD), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). According to the test results, the mass loss rate of solidified aeolian sand gradually increases with the increase in wind velocity, deflation angle, and wind erosion cycle. When the wind velocity was 13 m/s, the mass loss rate of the aeolian sand was only 63.6%, indicating that aeolian sand has excellent wind erosion resistance. CaCO3 crystals generated by MICP were mostly distributed on sand particle surfaces, in sand particle pores, and between sand particles to realize the covering, filling, and cementing effects.