Tandem Mass Tag-Based Proteomic Analysis of Normal and Degenerated Human Intervertebral Discs.

Background: Intervertebral disc degeneration (IVDD) is the main cause of low back pain (LBP), but the specific regulatory factors, pathways and specific molecular mechanisms remain unclear. Methods: We identified and quantitatively analyzed Pfirrmann Grade II (n=3) and Pfirrmann Grade IV (n=3) pulposus samples via MRI. The differential abundance of proteins in the samples was determined and quantitatively analyzed by relative and absolute quantitative analysis of the isotope marker levels combined with the liquid chromatography-tandem mass spectrometry (LC‒MSMS/MS). Results: A total of 70 proteins (30 significantly increased proteins (> 1.2-fold change) and 40 significantly decreased proteins (< 0.8-fold change)) showed different levels among the groups. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology (GO) enrichment analyses and Western blot analysis showed that CYCS, RAC1, and PSMD14 may play important roles in IVDD and that Epstein‒Barr virus infection, viral myocarditis, colorectal cancer, nonalcoholic fatty liver disease (NAFLD) and amyotrophic lateral sclerosis (ALS) are the main pathways involved in IVDD. Conclusion: CYCS, RAC1 and PSMD14 may play important roles in IVDD, and Epstein‒Barr virus infection, viral myocarditis, colorectal cancer, NAFLD and ALS may be the main pathways involved in IVDD.

Association Between Polymorphisms in DNA Damage Repair Pathway Genes and Female Breast Cancer Risk.

Breast cancer risk have been discussed to be associated with polymorphisms in genes as well as abnormal DNA damage repair function. This study aims to assess the relationship between genes single nucleotide polymorphisms (SNPs) related to DNA damage repair and female breast cancer risk in Chinese population. A case-control study containing 400 patients and 400 healthy controls was conducted. Genotype was identified using the sequence MassARRAY method and expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2) in tumor tissues was analyzed by immunohistochemistry assay. The results revealed that ATR rs13091637 decreased breast cancer risk influenced by ER, PR (CT/TT vs. CC: adjusted odds ratio [OR] = 1.54, 95% confidence interval [CI]: 1.04-2.27, p = 0.032; CT/TT vs. CC: adjusted OR = 1.63, 95%CI: 1.14-2.35, p = 0.008) expression. Stratified analysis revealed that PALB2 rs16940342 increased breast cancer risk in response to menstrual status (AG/GG vs. AA: adjusted OR = 1.72, 95%CI: 1.13-2.62, p = 0.011) and age of menarche (AG/GG vs. AA: adjusted OR = 1.54, 95%CI: 1.03-2.31, p = 0.037), whereas ATM rs611646 and Ku70 rs132793 were associated with reduced breast cancer risk influenced by menarche (GA/AA vs. GG: adjusted OR = 0.50, 95%CI: 0.30-0.95, p = 0.033). In a summary, PALB2 rs16940342, ATR rs13091637, ATM rs611646, and Ku70 rs132793 were associated with breast cancer risk.

Genetically predicted high serum sex hormone-binding globulin levels are associated with lower ischemic stroke risk: A sex-stratified Mendelian randomization study.

OBJECTIVE: Cross-sectional and cohort studies have found insufficient evidence of a causal relationship between sex hormone-binding globulin and ischemic stroke, only associations. Here, we performed a sex-stratified, bidirectional, two-sample Mendelian randomization analysis to evaluate whether a causal relationship exists between sex hormone-binding globulin and ischemic stroke. METHODS: Single-nucleotide polymorphisms associated with sex hormone-binding globulin and ischemic stroke were screened from genome-wide association studies summary data as instrumental variables to enable a bidirectional, two-sample Mendelian randomization study design. Inverse-variance weighted analysis was used as the main method to evaluate potential causality, and additional methods, including the weighted median and MR-Egger tests, were used to validate the Mendelian randomization results. Cochran's Q statistic, MR-Egger intercept test, and Mendelian Randomization-Pleiotropy Residual Sum and Outlier global test were used as sensitivity analysis techniques to assure the reliability of the results. Multivariable analysis was used to show the robustness of the results with key theorized confounders. RESULTS: Inverse-variance weighted analysis showed that genetically predicted higher serum sex hormone-binding globulin levels were associated with significantly decreased risk of ischemic stroke in males (odds radio = 0.934, 95 % confidence interval = 0.885-0.985, P = 0.012) and females (odds radio = 0.924, 95 % confidence interval = 0.868-0.983, P = 0.013). In an analysis of ischemic stroke subtypes, genetically predicted higher serum sex hormone-binding globulin levels were also associated with significantly decreased risk of small-vessel occlusion in both males (odds radio = 0.849, 95 % confidence interval = 0.759-0.949, P = 0.004) and females (odds radio = 0.829, 95 % confidence interval = 0.724-0.949, P = 0.006). The association remained in sensitivity analyses and multivariable analyses. The reverse analysis suggested an association between genetically predicted risk of cardioembolism and increased serum sex hormone-binding globulin in females (Beta = 0.029 nmol/L, Standard Error = 0.010, P = 0.003). CONCLUSION: Our findings provide new insight into the etiology of ischemic stroke and suggest that modulating serum sex hormone-binding globulin may be a therapeutic strategy to protect against ischemic stroke.

Deep learning-based quantification and transcriptomic profiling reveal a methyl jasmonate-mediated glandular trichome formation pathway in Cannabis sativa.

Cannabis glandular trichomes (GTs) are economically and biotechnologically important structures that have a remarkable morphology and capacity to produce, store, and secrete diverse classes of secondary metabolites. However, our understanding of the developmental changes and the underlying molecular processes involved in cannabis GT development is limited. In this study, we developed Cannabis Glandular Trichome Detection Model (CGTDM), a deep learning-based model capable of differentiating and quantifying three types of cannabis GTs with a high degree of efficiency and accuracy. By profiling at eight different time points, we captured dynamic changes in gene expression, phenotypes, and metabolic processes associated with GT development. By integrating weighted gene co-expression network analysis with CGTDM measurements, we established correlations between phenotypic variations in GT traits and the global transcriptome profiles across the developmental gradient. Notably, we identified a module containing methyl jasmonate (MeJA)-responsive genes that significantly correlated with stalked GT density and cannabinoid content during development, suggesting the existence of a MeJA-mediated GT formation pathway. Our findings were further supported by the successful promotion of GT development in cannabis through exogenous MeJA treatment. Importantly, we have identified CsMYC4 as a key transcription factor that positively regulates GT formation via MeJA signaling in cannabis. These findings provide novel tools for GT detection and counting, as well as valuable information for understanding the molecular regulatory mechanism of GT formation, which has the potential to facilitate the molecular breeding, targeted engineering, informed harvest timing, and manipulation of cannabinoid production.

Associations of Intracranial Artery Length and Branch Number on Time-of-Flight MRA With Cognitive Impairment in Hypertensive Older Males.

BACKGROUND: Hypertension-induced impairment of the cerebral artery network contributes to cognitive impairment. Characterizing the structure and function of cerebral arteries may facilitate the understanding of hypertension-related pathological mechanisms and lead to the development of new indicators for cognitive impairment. PURPOSE: To investigate the associations between morphological features of the intracranial arteries distal to the circle of Willis on time-of-flight MRA (TOF-MRA) and cognitive performance in a hypertensive cohort. STUDY TYPE: Prospective observational study. POPULATION: 189 hypertensive older males (mean age 64.9 ± 7.2 years). FIELD STRENGTH/SEQUENCE: TOF-MRA sequence with a 3D spoiled gradient echo readout and arterial spin labeling perfusion imaging sequence with a 3D stack-of-spirals fast spin echo readout at 3T. ASSESSMENT: The intracranial arteries were segmented from TOF-MRA and the total length of distal arteries (TLoDA) and number of arterial branches (NoB) were calculated. The mean gray matter cerebral blood flow (GM-CBF) was extracted from arterial spin labeling perfusion imaging. The cognitive level was assessed with short-term and long-term delay-recall auditory verbal learning test (AVLT) scores, and with montreal cognitive assessment. STATISTICAL TESTS: Univariable and multivariable linear regression were used to analyze the associations between TLoDA, NoB, GM-CBF and the cognitive assessment scores, with P < 0.05 indicating significance. RESULTS: TLoDA (r = 0.314) and NoB (r = 0.346) were significantly correlated with GM-CBF. Multivariable linear regression analyses showed that TLoDA and NoB, but not GM-CBF (P = 0.272 and 0.141), were significantly associated with short-term and long-term delay-recall AVLT scores. These associations remained significant after adjusting for GM-CBF. DATA CONCLUSION: The TLoDA and NoB of distal intracranial arteries on TOF-MRA are significantly associated with cognitive impairment in hypertensive subjects. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

An Artificial Intelligence Enabled System for Retinal Nerve Fiber Layer Thickness Damage Severity Staging.

Purpose: To develop an objective glaucoma damage severity classification system based on OCT-derived retinal nerve fiber layer (RNFL) thickness measurements. Design: Algorithm development for RNFL damage severity classification based on multicenter OCT data. Subjects and Participants: A total of 6561 circumpapillary RNFL profiles from 2269 eyes of 1171 subjects to develop models, and 2505 RNFL profiles from 1099 eyes of 900 subjects to validate models. Methods: We developed an unsupervised k-means model to identify clusters of eyes with similar RNFL thickness profiles. We annotated the clusters based on their respective global RNFL thickness. We computed the optimal global RNFL thickness thresholds that discriminated different severity levels based on Bayes' minimum error principle. We validated the proposed pipeline based on an independent validation dataset with 2505 RNFL profiles from 1099 eyes of 900 subjects. Main Outcome Measures: Accuracy, area under the receiver operating characteristic curve, and confusion matrix. Results: The k-means clustering discovered 4 clusters with 1382, 1613, 1727, and 1839 samples with mean (standard deviation) global RNFL thickness of 58.3 (8.9) µm, 78.9 (6.7) µm, 87.7 (8.2) µm, and 101.5 (7.9) µm. The Bayes' minimum error classifier identified optimal global RNFL values of > 95 µm, 86 to 95 µm, 70 to 85 µm, and < 70 µm for discriminating normal eyes and eyes at the early, moderate, and advanced stages of RNFL thickness loss, respectively. About 4% of normal eyes and 98% of eyes with advanced RNFL loss had either global, or ≥ 1 quadrant, RNFL thickness outside of normal limits provided by the OCT instrument. Conclusions: Unsupervised machine learning discovered that the optimal RNFL thresholds for separating normal eyes and eyes with early, moderate, and advanced RNFL loss were 95 µm, 85 µm, and 70 µm, respectively. This RNFL loss classification system is unbiased as there was no preassumption or human expert intervention in the development process. Additionally, it is objective, easy to use, and consistent, which may augment glaucoma research and day-to-day clinical practice. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Anti-deadzone adaptive fuzzy dynamic surface control for planar space robot with elastic base and flexible links.

In order to combat the impact of the dead zone and reduce vibration of the space robot's elastic base and flexible links, the trajectory tracking and vibration suppression of a multi-flexible-link free-floating space robot system are addressed. First, the elastic connection between the base and the link is considered as a linear spring. Then the assumed mode approach is used to derive the dynamic model of the flexible system. Secondly, a slow subsystem characterizing the rigid motion and a fast subsystem relating to vibration of the elastic base and multiple flexible links are generated utilizing two-time scale hypotheses of singular perturbation. For the slow subsystem with a dead zone in joint input torque, a dynamic surface control method with adaptive fuzzy approximator is designed. Dynamic surface control scheme is adopted to avoid calculation expansion and to simplify calculation. The fuzzy logic function is applied to approximate uncertain terms of the dynamic equation including the dead zone errors. For the fast subsystem, an optimal linear quadratic regulator controller is used to suppress the vibration of the multiple flexible links and elastic base, ensuring the stability and tracking accuracy of the system. Lastly, the simulation results verify the effectiveness of the proposed control strategy.

The effect of the Ankle Pump Exercise (APE) counter system assisted ankle pump motion in patients after femoral neck fracture.

OBJECTIVE: To explore the effect of the Ankle Pump Exercise (APE) counter system on moderate to high-risk Venous thromboembolism (VTE) after femoral neck fracture surgery. METHODS: From June 2021 to June 2022, a total of 140 patients with moderate and high-risk VTE after femoral neck fracture surgery treated at the Department of Orthopedics of a tertiary hospital in Zhejiang were included and divided into observation (70 cases) and control (70 cases) groups according to whether APE counter system was used or not. The control group was given routine oral propaganda, and the observation group was given a comprehensive nursing intervention with APE counter system on the basis of the control group's treatment. The compliance rates of the two groups on the postoperative 3st, 5rd, and 7th days were compared. Moreover, the General self-efficacy scale (GSES) was used to evaluate self-efficacy before and after exercise. RESULTS: The compliance rates of the control group and the observation group on the postoperative 3st, 5rd, and 7th days were 74.3% vs. 85.7%, 67.1% vs. 85.7%, and 61.4% vs. 82.9%. On the 5rd and 7th days, the compliance of the observation group was obviously higher than that of the control group. Moreover, the mean postoperative GSES score was also significantly higher than that in the control group (23.20 ± 3.516 vs. 25.31 ± 4.583, P < 0.05, values are expressed in mean ± standard). CONCLUSION: APE counter system can significantly improve the compliance and self-efficacy of patients with moderate and high-risk VTE after lower limb fracture surgery.

Artificial intelligence in glaucoma: opportunities, challenges, and future directions.

Artificial intelligence (AI) has shown excellent diagnostic performance in detecting various complex problems related to many areas of healthcare including ophthalmology. AI diagnostic systems developed from fundus images have become state-of-the-art tools in diagnosing retinal conditions and glaucoma as well as other ocular diseases. However, designing and implementing AI models using large imaging data is challenging. In this study, we review different machine learning (ML) and deep learning (DL) techniques applied to multiple modalities of retinal data, such as fundus images and visual fields for glaucoma detection, progression assessment, staging and so on. We summarize findings and provide several taxonomies to help the reader understand the evolution of conventional and emerging AI models in glaucoma. We discuss opportunities and challenges facing AI application in glaucoma and highlight some key themes from the existing literature that may help to explore future studies. Our goal in this systematic review is to help readers and researchers to understand critical aspects of AI related to glaucoma as well as determine the necessary steps and requirements for the successful development of AI models in glaucoma.

Identifying factors associated with fast visual field progression in patients with ocular hypertension based on unsupervised machine learning.

Purpose: To identify ocular hypertension (OHT) subtypes with different trends of visual field (VF) progression based on unsupervised machine learning and to discover factors associated with fast VF progression. Design: Cross-sectional and longitudinal study. Participants: A total of 3133 eyes of 1568 ocular hypertension treatment study (OHTS) participants with at least five follow-up VF tests were included in the study. Methods: We used a latent class mixed model (LCMM) to identify OHT subtypes using standard automated perimetry (SAP) mean deviation (MD) trajectories. We characterized the subtypes based on demographic, clinical, ocular, and VF factors at the baseline. We then identified factors driving fast VF progression using generalized estimating equation (GEE) and justified findings qualitatively and quantitatively. Main Outcome Measure: Rates of SAP mean deviation (MD) change. Results: The LCMM model discovered four clusters (subtypes) of eyes with different trajectories of MD worsening. The number of eyes in clusters were 794 (25%), 1675 (54%), 531 (17%) and 133 (4%). We labeled the clusters as Improvers, Stables, Slow progressors, and Fast progressors based on their mean of MD decline, which were 0.08, -0.06, -0.21, and -0.45 dB/year, respectively. Eyes with fast VF progression had higher baseline age, intraocular pressure (IOP), pattern standard deviation (PSD) and refractive error (RE), but lower central corneal thickness (CCT). Fast progression was associated with calcium channel blockers, being male, heart disease history, diabetes history, African American race, stroke history, and migraine headaches. Conclusion: Unsupervised clustering can objectively identify OHT subtypes including those with fast VF worsening without human expert intervention. Fast VF progression was associated with higher history of stroke, heart disease, diabetes, and history of more using calcium channel blockers. Fast progressors were more from African American race and males and had higher incidence of glaucoma conversion. Subtyping can provide guidance for adjusting treatment plans to slow vision loss and improve quality of life of patients with a faster progression course.

Corrigendum to "Influence of on emotions and behavior of adolescents with major depressive disorder" [Heliyon 9(5) (May 2023) e15890].

[This corrects the article DOI: 10.1016/j.heliyon.2023.e15890.].

LPS induces SGPP2 to participate metabolic reprogramming in endothelial cells.

Sepsis often causes organ dysfunction and is manifested in increased endothelial cell permeability in blood vessels. Early-stage inflammation is accompanied by metabolic changes, but it is unclear how the metabolic alterations in the endothelial cells following lipopolysaccharide (LPS) stimulation affect endothelial cell function. In this study, the effects of 1 µg/ml of LPS on the metabolism of human umbilical vein endothelial cells (HUVECs) were investigated, and the metabolic changes after LPS stimulation were explained from the perspective of mRNA expression, chromatin openness and metabolic flux. We found changes in the central metabolism of endothelial cells after LPS stimulation, such as enhanced glycolysis function, decreased mitochondrial membrane potential, and increased production of reactive oxygen species (ROS). Sphingolipid metabolic pathways change at the transcriptome level, and sphingosine-1-phosphatase 2 (SGPP2) was upregulated in LPS-stimulated endothelial cells and zebrafish models. Overexpression of SGPP2 improved cell barrier function, enhanced mitochondrial respiration capacity, but also produced oxidative respiration chain uncoupling. In addition, SGPP2 overexpression inhibited the degradation of HIF-1α protein. The molecular and biochemical processes identified in this study are not only beneficial for understanding the metabolic-related mechanisms of LPS-induced endothelial injury, but also for the discovery of general therapeutic targets for inflammation and inflammation-related diseases.

Development of an interfering peptide M1-20 with potent anti-cancer effects by targeting FOXM1.

Disrupting protein-protein interactions (PPIs) has emerged as a promising strategy for cancer drug development. Interfering peptides disrupting PPIs can be rationally designed based on the structures of natural sequences mediating these interactions. Transcription factor FOXM1 overexpresses in multiple cancers and is considered an effective target for cancer therapeutic drug development. Using a rational design approach, we have generated a peptide library from the FOXM1 C-terminal sequence and screened FOXM1-binding peptides. Combining FOXM1 binding and cell inhibitory results, we have obtained a FOXM1-targeting interfering peptide M1-20 that is optimized from the natural parent peptide to the D-retro-inverso peptide. With improved stability characteristics, M1-20 inhibits proliferation and migration, and induces apoptosis of cancer cells. Mechanistically, M1-20 inhibits FOXM1 transcriptional activities by disrupting its interaction between the MuvB complex and the transcriptional co-activator CBP. These are consistent with the results that M1-20 suppresses cancer progression and metastasis without noticeable toxic and side effects in wild-type mice. These findings reveal that M1-20 has the potential to be developed as an anti-cancer drug candidate targeting FOXM1.

The development of an anti-cancer peptide M1-21 targeting transcription factor FOXM1.

BACKGROUND: Transcription factor FOXM1 is a potential target for anti-cancer drug development. An interfering peptide M1-21, targeting FOXM1 and FOXM1-interacting proteins, is developed and its anti-cancer efficacy is evaluated. METHODS: FOXM1 C-terminus-binding peptides are screened by in silico protocols from the peptide library of FOXM1 (1-138aa) and confirmed by cellular experiments. The selected peptide is synthesized into its D-retro-inverso (DRI) form by fusing a TAT cell-penetrating sequence. Anti-cancer activities are evaluated in vitro and in vivo with tumor-grafted nude mice, spontaneous breast cancer mice, and wild-type metastasis-tracing mice. Anti-cancer mechanisms are analyzed. Distribution and safety profiles in mice are evaluated. RESULTS: With improved stability and cell inhibitory activity compared to the parent peptide, M1-21 binds to multiple regions of FOXM1 and interferes with protein-protein interactions between FOXM1 and its various known partner proteins, including PLK1, LIN9 and B-MYB of the MuvB complex, and ß-catenin. Consequently, M1-21 inhibits FOXM1-related transcriptional activities and FOXM1-mediated nuclear importation of ß-catenin and ß-catenin transcriptional activities. M1-21 inhibits multiple types of cancer (20 µM in vitro or 30 mg/kg in vivo) by preventing proliferation, migration, and WNT signaling. Distribution and safety profiles of M1-21 are favorable (broad distribution and > 15 h stability in mice) and the tested non-severely toxic dose reaches 200 mg/kg in mice. M1-21 also has low hemolytic toxicity and immunogenicity in mice. CONCLUSIONS: M1-21 is a promising interfering peptide targeting FOXM1 for the development of anti-cancer drugs.

A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data.

Early diagnosis and treatment of glaucoma are challenging. The discovery of glaucoma biomarkers based on gene expression data could potentially provide new insights for early diagnosis, monitoring, and treatment options of glaucoma. Non-negative Matrix Factorization (NMF) has been widely used in numerous transcriptome data analyses in order to identify subtypes and biomarkers of different diseases; however, its application in glaucoma biomarker discovery has not been previously reported. Our study applied NMF to extract latent representations of RNA-seq data from BXD mouse strains and sorted the genes based on a novel gene scoring method. The enrichment ratio of the glaucoma-reference genes, extracted from multiple relevant resources, was compared using both the classical differentially expressed gene (DEG) analysis and NMF methods. The complete pipeline was validated using an independent RNA-seq dataset. Findings showed our NMF method significantly improved the enrichment detection of glaucoma genes. The application of NMF with the scoring method showed great promise in the identification of marker genes for glaucoma.

Identification of Potential Biomarkers for Group I Pulmonary Hypertension Based on Machine Learning and Bioinformatics Analysis.

A number of processes and pathways have been reported in the development of Group I pulmonary hypertension (Group I PAH); however, novel biomarkers need to be identified for a better diagnosis and management. We employed a robust rank aggregation (RRA) algorithm to shortlist the key differentially expressed genes (DEGs) between Group I PAH patients and controls. An optimal diagnostic model was obtained by comparing seven machine learning algorithms and was verified in an independent dataset. The functional roles of key DEGs and biomarkers were analyzed using various in silico methods. Finally, the biomarkers and a set of key candidates were experimentally validated using patient samples and a cell line model. A total of 48 key DEGs with preferable diagnostic value were identified. A gradient boosting decision tree algorithm was utilized to build a diagnostic model with three biomarkers, PBRM1, CA1, and TXLNG. An immune-cell infiltration analysis revealed significant differences in the relative abundances of seven immune cells between controls and PAH patients and a correlation with the biomarkers. Experimental validation confirmed the upregulation of the three biomarkers in Group I PAH patients. In conclusion, machine learning and a bioinformatics analysis along with experimental techniques identified PBRM1, CA1, and TXLNG as potential biomarkers for Group I PAH.

Influence of on emotions and behavior of adolescents with major depressive disorder.

Background: Major depressive disorder in adolescents is characterized by high prevalence rate, high recurrence rate, high suicide rate and high disability rate. However, the recognition rate and cure rate are low, and the disease has a very bad influence on the family and society. The lack of psychiatrists and psychotherapists in villages and small towns makes it difficult to get timely and professional intervention and treatment for adolescent with major depressive disorder. Methods: A total of 84 adolescents with major depressive disorder who received treatment in the department of psychosomatic medicine of the Second Affiliated Hospital of Nanchang University participated in this survey, and they were divided into the control group and the intervention group by random number table. Adolescent Non-suicidal Self-injury Assessment Questionnaire (ANSSIAQ), Self-rating Questionnaire for Adolescent Problematic Mobile Phone Use (SQAPMPU), Screen for Child Anxiety Related Emotional Disorders (SCARED) and Depression Self-Rating Scale for Childhood (DSRS) were used to investigate the negative emotions and behavior of adolescents with major depressive disorder at baseline and intervention for 12 weeks. Results: There were no significant differences in the baseline information of adolescents (sex ratio, age, education level), including the total score of SCARED, DSRS and SQAPMPU, the total mean score of ANSSIAQ between the two groups (P > 0.05). After 12-week intervention, the score of SCARED, DSRS and SQAPMPU, the total mean score of ANSSIAQ in both groups were lower than that of the baseline, and the score of the intervention group showed a more obvious downward trend (P < 0.05). Conclusions: In-person and remote Satir family therapy not only effectively reduced the anxiety and depression level among participants, but also validly reduced their non-suicidal self-injury behavior and mobile phone use behavior. The results verified that the model we adopted can be well applied for the out-patient management of adolescents with major depressive disorder, especially in villages and small towns.

Changes of microbiota level in urinary tract infections: A meta-analysis.

No consensus has been reached on the dysbiosis signs of microbiota in patients with urinary tract infections (UTIs). This meta-analysis aimed to verify the relationship between microbiota levels and UTIs. PubMed, Web of Science, and Embase databases were retrieved for related articles published from inception until October 20, 2021. The standardized mean difference (SMD) and its related 95% confidence intervals (CIs) of the microbiota diversity and abundance were pooled under a random-effects model. Twelve studies were included in this meta-analysis. The pooled analysis revealed that the microbiota diversity was lower in patients with UTIs than in healthy individuals (SMD = -0.655, 95% CI = -1.290, -0.021, I 2 = 81.0%, P = 0.043). The abundance of specific bacteria was higher in UTI subjects compared with healthy control individuals (SMD = 0.41, 95% CI = 0.07-0.74, P = 0.017), especially in North America patients with UTIs. Similar results were also found in studies with the total sample size being greater than 30. Importantly, Escherichia coli levels were increased in patients with UTI, whereas Lactobacillus levels decreased. E. coli and Lactobacilli have huge prospects as potential microbiota markers in the treatment of UTIs.

Efficacy and safety of nanopaclitaxel formulation for cancer treatment: evidence from randomized clinical trials.

Aim: We aimed to analyze efficacy and adverse events for nano-bound paclitaxel in cancer treatment, which remain controversial. Method: We obtained relevant previously published studies and extracted data on the efficacy and adverse events of nano-bound paclitaxel. Fifteen randomized clinical trials were included. Results: Nanoparticle albumin-bound (Nab-) paclitaxel was beneficial in terms of objective response rate (odds ratio [OR]: 1.08, 95% CI: 0.72-1.62) and partial response (OR: 1.28, 95% CI: 0.89-1.83), while polymeric micellar (PM-) paclitaxel was beneficial in terms of objective response rate (OR: 1.76) and partial disease (hazard ratio [HR]: 0.65). Both Nab-paclitaxel and PM-paclitaxel resulted in slightly longer overall survival (HR: 0.93 and 0.94) and progression-free survival (HR: 0.93 and 0.87) when compared with solvent-based paclitaxel. Peripheral sensory neuropathy (OR: 3.47), neutropenia (OR: 1.79) and anemia (OR: 1.79) were more frequent after Nab-paclitaxel treatment. Conclusion: Nanopaclitaxel formulations have a better efficacy in cancer treatment; however, they increase the risk of hematological adverse events and peripheral sensory neuropathy. The PM-paclitaxel treatment had a high safety effect.

This was a pooled analysis of the efficacy and adverse events of nano-bound paclitaxel (polymeric micellar [PM] or nanoparticle-bound formulation) in cancer treatment. Relevant studies published since 2016 were retrieved from the PubMed, ISI Web of Science and Embase databases. Fifteen randomized clinical trials (4925 patients) were included in this meta-analysis. Compared with solvent-based paclitaxel, nanoparticle albumin-bound paclitaxel (Nab-paclitaxel) had beneficial effects in terms of objective response rate and partial response, while PM-paclitaxel exhibited beneficial effects in terms of objective response rate and partial disease. Both Nab-paclitaxel and PM-paclitaxel were associated with a slightly longer overall survival and better progression-free survival when compared with solvent-based paclitaxel. Peripheral sensory neuropathy, neutropenia and anemia adverse events were more frequent after Nab-paclitaxel treatment. The nanopaclitaxel formulation had an improved efficacy in treatment of solid-organ tumors, but it increased the risk of hematological adverse events and peripheral sensory neuropathy. This study provided evidence on the efficacy and safety of the nanocarriers of paclitaxel.