Effectiveness of animal-assisted activities and therapies for autism spectrum disorder: a systematic review and meta-analysis.

Background: Given the rising interest in complementary therapeutic strategies for autism spectrum disorder (ASD), this research aims to provide a comprehensive analysis of the impact of animal-assisted activities and therapies (AAAT) on various ASD symptoms. Methods: A meticulous search of databases, including Scopus and PubMed, was conducted to gather relevant research on AAAT for ASD. This process led to the selection of 45 studies encompassing 1,212 participants. The chosen studies were then subjected to a meta-analysis to evaluate the efficacy of AAAT in alleviating core ASD symptoms. Results: The meta-analysis revealed significant improvements in several core ASD symptoms due to AAAT. Notably, there were improvements in social communication (MD = -4.96, 95% CI [-7.49, -2.44]), irritability (MD = -2.38, 95% CI [-4.06, -0.71]), hyperactivity (MD = -4.03, 95% CI [-6.17, -1.89]), and different word usage skills (MD = 20.48, 95% CI [7.41, 33.55]). However, social awareness (MD = -1.63, 95% CI [-4.07, 0.81]), social cognition (MD = -3.60, 95% CI [-9.36, 2.17]), social mannerisms (MD = -0.73, 95% CI [-2.55, 1.09]), social motivation (MD = -1.21, 95% CI [-2.56, 0.13]), lethargy (MD = -1.12, 95% CI [-3.92, 1.68]), and stereotypical behaviors (MD = -0.23, 95% CI [-1.27, 0.80]) did not significantly improve. Conclusion: The study demonstrates the potential of AAAT in improving certain core symptoms of ASD, such as social communication, irritability, hyperactivity, and word usage skills. However, the effectiveness of AAAT in other ASD symptom domains remains uncertain. The research is limited by the absence of long-term follow-up data and a high risk of bias in existing studies. Therefore, while the findings indicate the promise of AAAT in specific areas, caution is advised in generalizing its efficacy across all ASD symptoms.

Health-related quality of life in patients with inborn errors of immunity: a bibliometric analysis.

Background: Inborn Errors of Immunity (IEI) are characterized by a heightened susceptibility to infections, allergies, and various other health complications. Health-Related Quality of Life (HRQOL) in patients with IEI is a critical area of research that demands attention due to the impact of IEI on patients' lives. This study utilized bibliometric methods, aiming to comprehensively explore the research content and hotspots in the field of HRQOL in patients with IEI. Methods: This bibliometric analysis utilized data from the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) within the Web of Science core datasets up to January 1, 2024. The study focused on literature that addressed HRQOL in IEI patients, involving a total of 1,807 authors and 309 articles published across 112 journals. The analysis included publication volume and growth trends, country and institutional contributions, authorship, and journal analysis. Results: The research found that despite the importance of HRQOL in IEI, the volume of publications in this field remains consistently low, with no significant increase in trend. The USA leads in publication and citation volumes, reflecting a geographical imbalance in research contributions. Key journals in this field include the Journal of Clinical Immunology, Frontiers in Immunology, and the Journal of Allergy and Clinical Immunology. The study highlights that while treatments like hematopoietic stem cell transplants and gene therapy have improved patient IEI survival rates, they still often come with significant side effects impacting HRQOL. The analysis underlines the need for comprehensive HRQOL assessments in IEI, considering the physical and psychological impacts of treatments. Conclusions: This study represents a bibliometric analysis focusing on HRQOL in patients with. It underscores the need for more extensive and systematic research in this area, emphasizing the importance of a multidisciplinary approach. Despite advancements in medical treatments for IEI, there is a crucial need to focus on HRQOL to enhance patient satisfaction and overall well-being. The findings advocate for more personalized treatment plans and a better understanding of the psychosocial needs of patients with IEI to improve their quality of life.

In Silico Analysis Revealed Five Novel High-Risk Single-Nucleotide Polymorphisms (rs200384291, rs201163886, rs193141883, rs201139487, and rs201723157) in ELANE Gene Causing Autosomal Dominant Severe Congenital Neutropenia 1 and Cyclic Hematopoiesis.

Single-nucleotide polymorphisms in the ELANE (Elastase, Neutrophil Expressed) gene are associated with severe congenital neutropenia, while the ELANE gene provides instructions for making a protein called neutrophil elastase. We identified disease susceptibility single-nucleotide polymorphisms (SNPs) in the ELANE gene using several computational tools. We used cutting-edge computational techniques to investigate the effects of ELANE mutations on the sequence and structure of the protein. Our study suggested that eight nsSNPs (rs28931611, rs57246956, rs137854448, rs193141883, rs201723157, rs201139487, rs137854451, and rs200384291) are the most deleterious in ELANE gene and disturb protein structure and function. The mutants F218L, R34W, G203S, R193W, and T175M have not yet been identified in patients suffering from SCN and cyclic hematopoiesis, while C71Y, P139R, C151Y, G214R, and G203C reported in our study are already associated with both of the disorders. These mutations are shown to destabilize structure and disrupt ELANE protein activation, splicing, and folding and might diminish trypsin-like serine protease efficiency. Prediction of posttranslation modifications highlighted the significance of deleterious nsSNPs because some of nsSNPs affect potential phosphorylation sites. Gene-gene interactions showed the relation of ELANE with other genes depicting its importance in numerous pathways and coexpressions. We identified the deleterious nsSNPs, constructed mutant protein structures, and evaluated the impact of mutation by employing molecular docking. This research sheds light on how ELANE failure upon mutation results in disease progression, including congenital neutropenia, and validation of these novel predicted nsSNPs is required through the wet lab.

Novel Disease-Associated Missense Single-Nucleotide Polymorphisms Variants Predication by Algorithms Tools and Molecular Dynamics Simulation of Human TCIRG1 Gene Causing Congenital Neutropenia and Osteopetrosis.

T Cell Immune Regulator 1, ATPase H + Transporting V0 Subunit A3 (TCIRG1 gene provides instructions for making one part, the a3 subunit, of a large protein complex known as a vacuolar H + -ATPase (V-ATPase). V-ATPases are a group of similar complexes that act as pumps to move positively charged hydrogen atoms (protons) across membranes. Single amino acid changes in highly conserved areas of the TCIRG1 protein have been linked to autosomal recessive osteopetrosis and severe congenital neutropenia. We used multiple computational approaches to classify disease-prone single nucleotide polymorphisms (SNPs) in TCIRG1. We used molecular dynamics analysis to identify the deleterious nsSNPs, build mutant protein structures, and assess the impact of mutation. Our results show that fifteen nsSNPs (rs199902030, rs200149541, rs372499913, rs267605221, rs374941368, rs375717418, rs80008675, rs149792489, rs116675104, rs121908250, rs121908251, rs121908251, rs149792489 and rs116675104) variants are likely to be highly deleterious mutations as by incorporating them into wild protein they destabilize the wild protein structure and function. They are also located in the V-ATPase I domain, which may destabilize the structure and impair TCIRG1 protein activation, as well as reduce its ATPase effectiveness. These mutants have not yet been identified in patients suffering from CN and osteopetrosis while (G405R, R444L, and D517N) reported in our study are already associated with osteopetrosis. Mutation V52L reported in our study was identified in a patient suspected for CN. Finally, these mutants can help to further understand the broad pool of illness susceptibilities associated with TCIRG1 catalytic kinase domain activation and aid in the development of an effective treatment for associated diseases.

Identification of The Immune Subtype Among Muscle-invasive Bladder Cancer Patients by Multiple Datasets.

BACKGROUND: Immunotherapies including PD-1/PD-L1 antibodies have been approved for the treatment of Muscle-invasive Bladder Cancer (MIBC) patients. However, immunotherapies could only be beneficial for about 20% MIBC patients. Thus, identification of the immune subtype is becoming increasingly important. This study aimed to explore the immune subtype by analyzing the gene expression profiles. METHODS: A total of 6 datasets including (GSE13507, GSE31684, GSE32548, GSE32894, GSE69795, and TCGA-BLCA) were downloaded. The gene expression profiles from different datasets were combined since the batch effects were removed. We performed unsupervised clustering analysis to identify the immune subtype by the combined gene expression profiles. The tumor-infiltration levels of 22 immune cells, immune scores, and tumor purity were calculated, and the survival analysis was performed to investigate the prognosis difference between immune subtypes. The enriched pathways for each immune subtype were obtained. RESULTS: We identified four novel immune subtypes (referred to S1, S2, S3, and S4) among MIBC patients. We found that S1 was enriched in immune scores had the best prognosis. In contrast, S3 was poor in immune scores and had the worst prognosis. Subtype S1, S2, S3, and S4 were enriched in immune-related pathways, extracellular matrix-related pathways, metabolism-related pathways, and cancer-related pathways, respectively. CONCLUSION: The current study suggests that the immune subtypes based on gene expression profiles could contribute to select the appropriate MIBC patient for immunotherapies.

Predicting the Most Deleterious Missense Nonsynonymous Single-Nucleotide Polymorphisms of Hennekam Syndrome-Causing CCBE1 Gene, In Silico Analysis.

Hennekam lymphangiectasia-lymphedema syndrome has been linked to single-nucleotide polymorphisms in the CCBE1 (collagen and calcium-binding EGF domains 1) gene. Several bioinformatics methods were used to find the most dangerous nsSNPs that could affect CCBE1 structure and function. Using state-of-the-art in silico tools, this study examined the most pathogenic nonsynonymous single-nucleotide polymorphisms (nsSNPs) that disrupt the CCBE1 protein and extracellular matrix remodeling and migration. Our results indicate that seven nsSNPs, rs115982879, rs149792489, rs374941368, rs121908254, rs149531418, rs121908251, and rs372499913, are deleterious in the CCBE1 gene, four (G330E, C102S, C174R, and G107D) of which are the highly deleterious, two of them (G330E and G107D) have never been seen reported in the context of Hennekam syndrome. Twelve missense SNPs, rs199902030, rs267605221, rs37517418, rs80008675, rs116596858, rs116675104, rs121908252, rs147974432, rs147681552, rs192224843, rs139059968, and rs148498685, are found to revert into stop codons. Structural homology-based methods and sequence homology-based tools revealed that 8.8% of the nsSNPs are pathogenic. SIFT, PolyPhen2, M-CAP, CADD, FATHMM-MKL, DANN, PANTHER, Mutation Taster, LRT, and SNAP2 had a significant score for identifying deleterious nsSNPs. The importance of rs374941368 and rs200149541 in the prediction of post-translation changes was highlighted because it impacts a possible phosphorylation site. Gene-gene interactions revealed CCBE1's association with other genes, showing its role in a number of pathways and coexpressions. The top 16 deleterious nsSNPs found in this research should be investigated further in the future while researching diseases caused CCBE1 gene specifically HS. The FT web server predicted amino acid residues involved in the ligand-binding site of the CCBE1 protein, and two of the substitutions (R167W and T153N) were found to be involved. These highly deleterious nsSNPs can be used as marker pathogenic variants in the mutational diagnosis of the HS syndrome, and this research also offers potential insights that will aid in the development of precision medicines. CCBE1 proteins from Hennekam syndrome patients should be tested in animal models for this purpose.

Defining muscle-invasive bladder cancer immunotypes by introducing tumor mutation burden, CD8+ T cells, and molecular subtypes.

Immunotherapy, especially anti-PD-1, is becoming a pillar of modern muscle-invasive bladder cancer (MIBC) treatment. However, the objective response rates (ORR) are relatively low due to the lack of precise biomarkers to select patients. Herein, the molecular subtype, tumor mutation burden (TMB), and CD8+ T cells were calculated by the gene expression and mutation profiles of MIBC patients. MIBC immunotypes were constructed using clustering analysis based on tumor mutation burden, CD8+ T cells, and molecular subtypes. Mutated genes, enriched functional KEGG pathways and GO terms, and co-expressed network-specific hub genes have been identified. We demonstrated that ORR of immunotype A patients identified by molecular subtype, CD8+ T cells, and TMB is about 36% predictable. PIK3CA, RB1, FGFR3, KMT2C, MACF1, RYR2, and EP300 are differentially mutated among three immunotypes. Pathways such as ECM-receptor interaction, PI3K-Akt signaling pathway, and TGF-beta signaling pathway are top-ranked in enrichment analysis. Low expression of ACTA2 was associated with the MIBC survival benefit. The current study constructs a model that could identify suitable MIBC patients for immunotherapy, and it is an important step forward to the personalized treatment of bladder cancers.

A co-expression network for differentially expressed genes in bladder cancer and a risk score model for predicting survival.

BACKGROUND: Urothelial bladder cancer (BLCA) is one of the most common internal malignancies worldwide with poor prognosis. This study aims to explore effective prognostic biomarkers and construct a prognostic risk score model for patients with BLCA. METHODS: Weighted gene co-expression network analysis (WGCNA) was used for identifying the co-expression module related to the pathological stage of BLCA based on the RNA-Seq data retrieved from The Cancer Genome Atlas database. Prognostic biomarkers screened by Cox proportional hazard regression model and random forest were used to construct a risk score model that can predict the prognosis of patients with BLCA. The GSE13507 dataset was used as the independent testing dataset to test the performance of the risk score model in predicting the prognosis of patients with BLCA. RESULTS: WGCNA identified seven co-expression modules, in which the brown module consisted of 77 genes was most significantly correlated with the pathological stage of BLCA. Cox proportional hazard regression model and random forest identified TPST1 and P3H4 as prognostic biomarkers. Elevated TPST1 and P3H4 expressions were associated with the high pathological stage and worse survival. The risk score model based on the expression level of TPST1 and P3H4 outperformed pathological stage indicators and previously proposed prognostic models. CONCLUSION: The gene co-expression network-based study could provide additional insight into the tumorigenesis and progression of BLCA, and our proposed risk score model may aid physicians in the assessment of the prognosis of patients with BLCA.

Identification of miR-200c and miR141-Mediated lncRNA-mRNA Crosstalks in Muscle-Invasive Bladder Cancer Subtypes.

Basal and luminal subtypes of muscle-invasive bladder cancer (MIBC) have distinct molecular profiles and heterogeneous clinical behaviors. The interactions between mRNAs and lncRNAs, which might be regulated by miRNAs, have crucial roles in many cancers. However, the miRNA-dependent crosstalk between lncRNA and mRNA in specific MIBC subtypes still remains unclear. In this study, we first classified MIBC into two conservative subtypes using miRNA, mRNA and lncRNA expression data derived from The Cancer Genome Atlas. Then we investigated subtype-related biological pathways and evaluated the subtype classification performance using Decision Trees, Random Forest and eXtreme Gradient Boosting (XGBoost). At last, we explored potential miRNA-mediated lncRNA-mRNA crosstalks based on co-expression analysis. Our results show that: (1) the luminal subtype is primarily characterized by upregulation of metabolism-related pathways while the basal subtype is predominantly characterized by upregulation of epithelial-mesenchymal transition, metastasis, and immune system process-related pathways; (2) the XGBoost prediction model is consistently robust for classification of the molecular subtypes of MIBC across four datasets (The area under the ROC curve > 0.9); (3) the expression levels of the molecules in the miR-200c and miR141-mediated lncRNA-mRNA crosstalks differ considerably between the two subtypes and have close relationships with the prognosis of MIBC. The miR-200c and miR-141-dependent mRNA-lncRNA crosstalks might be of great significance in tumorigenesis and tumor progression and may serve as the novel prognostic predictors and classification markers of MIBC subtypes.