Elucidating trauma-related and disease-related regional cortical activity in post-traumatic stress disorder.

Trauma exposure may precipitate a cascade of plastic modifications within the intrinsic activity of brain regions, but it remains unclear which regions could be responsible for the development of post-traumatic stress disorder based on intrinsic activity. To elucidate trauma-related and post-traumatic stress disorder-related alterations in cortical intrinsic activity at the whole-brain level, we recruited 47 survivors diagnosed with post-traumatic stress disorder, 64 trauma-exposed controls from a major earthquake, and 46 age- and sex-matched healthy controls. All subjects were scanned with an echo-planar imaging sequence, and 5 parameters including the amplitude of low-frequency fluctuations, fractional amplitude of low-frequency fluctuations, regional homogeneity, degree centrality, and voxel-mirrored homotopic connectivity were calculated. We found both post-traumatic stress disorder patients and trauma-exposed controls exhibited decreased amplitude of low-frequency fluctuations in the bilateral posterior cerebellum and inferior temporal gyrus, decreased fractional amplitude of low-frequency fluctuation and regional homogeneity in the bilateral anterior cerebellum, and decreased fractional amplitude of low-frequency fluctuation in the middle occipital gyrus and cuneus compared to healthy controls, and these impairments were more severe in post-traumatic stress disorder patients than in trauma-exposed controls. Additionally, fractional amplitude of low-frequency fluctuation in left cerebellum was positively correlated with Clinician-Administered PTSD Scale scores in post-traumatic stress disorder patients. We identified brain regions that might be responsible for the emergence of post-traumatic stress disorder, providing important information for the treatment of this disorder.

Single-cell RNA sequencing reveals the heterogeneity of MYH11+ tumour-associated fibroblasts between left-sided and right-sided colorectal cancer.

Colorectal cancer (CRC) exhibits considerable heterogeneity on tumour location. However, there is still a lack of comprehensive annotation regarding the characteristics and differences between the left-sided (L-CRC) and right-sided (R-CRC) CRC. Here, we performed single-cell RNA sequencing (scRNA-seq) on immune and stromal cells from 12 L-CRC and 10 R-CRC patients. We found that L-CRC exhibited stronger tumour invasion and poor prognosis compared with R-CRC. In addition, functional enrichment analysis of a normal cohort showed that fibroblasts of left colon are associated with tumour-related pathways. This suggested that the heterogeneity observed in both L-CRC and R-CRC may be influenced by the specific location within the colon itself. Further, we identified a potentially novel MYH11+ cancer-associated fibroblast (CAF) subset predominantly enriched in L-CRC. Moreover, we found that MYH11+ CAFs may promote tumour migration via interacting with macrophages, and was associated with poor prognosis in CRC. In summary, our study revealed the crucial role of MYH11+ CAFs in predicting a poor prognosis, thereby contributing valuable insights to the exploration of heterogeneity in L-CRC and R-CRC.

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome.

Very preterm (VPT) infants (born at less than 32 weeks gestational age) are at high risk for various adverse neurodevelopmental deficits. Unfortunately, most of these deficits cannot be accurately diagnosed until the age of 2-5 years old. Given the benefits of early interventions, accurate diagnosis and prediction soon after birth are urgently needed for VPT infants. Previous studies have applied deep learning models to learn the brain structural connectome (SC) to predict neurodevelopmental deficits in the preterm population. However, none of these models are specifically designed for graph-structured data, and thus may potentially miss certain topological information conveyed in the brain SC. In this study, we aim to develop deep learning models to learn the SC acquired at term-equivalent age for early prediction of neurodevelopmental deficits at 2 years corrected age in VPT infants. We directly treated the brain SC as a graph, and applied graph convolutional network (GCN) models to capture complex topological information of the SC. In addition, we applied the supervised contrastive learning (SCL) technique to mitigate the effects of the data scarcity problem, and enable robust training of GCN models. We hypothesize that SCL will enhance GCN models for early prediction of neurodevelopmental deficits in VPT infants using the SC. We used a regional prospective cohort of ∼280 VPT infants who underwent MRI examinations at term-equivalent age from the Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS). These VPT infants completed neurodevelopmental assessment at 2 years corrected age to evaluate cognition, language, and motor skills. Using the SCL technique, the GCN model achieved mean areas under the receiver operating characteristic curve (AUCs) in the range of 0.72∼0.75 for predicting three neurodevelopmental deficits, outperforming several competing models. Our results support our hypothesis that the SCL technique is able to enhance the GCN model in our prediction tasks.

Artificial intelligence alphafold model for molecular biology and drug discovery: a machine-learning-driven informatics investigation.

AlphaFold model has reshaped biological research. However, vast unstructured data in the entire AlphaFold field requires further analysis to fully understand the current research landscape and guide future exploration. Thus, this scientometric analysis aimed to identify critical research clusters, track emerging trends, and highlight underexplored areas in this field by utilizing machine-learning-driven informatics methods. Quantitative statistical analysis reveals that the AlphaFold field is enjoying an astonishing development trend (Annual Growth Rate = 180.13%) and global collaboration (International Co-authorship = 33.33%). Unsupervised clustering algorithm, time series tracking, and global impact assessment point out that Cluster 3 (Artificial Intelligence-Powered Advancements in AlphaFold for Structural Biology) has the greatest influence (Average Citation = 48.36 ± 184.98). Additionally, regression curve and hotspot burst analysis highlight "structure prediction" (s = 12.40, R2 = 0.9480, p = 0.0051), "artificial intelligence" (s = 5.00, R2 = 0.8096, p = 0.0375), "drug discovery" (s = 1.90, R2 = 0.7987, p = 0.0409), and "molecular dynamics" (s = 2.40, R2 = 0.8000, p = 0.0405) as core hotspots driving the research frontier. More importantly, the Walktrap algorithm further reveals that "structure prediction, artificial intelligence, molecular dynamics" (Relevance Percentage[RP] = 100%, Development Percentage[DP] = 25.0%), "sars-cov-2, covid-19, vaccine design" (RP = 97.8%, DP = 37.5%), and "homology modeling, virtual screening, membrane protein" (RP = 89.9%, DP = 26.1%) are closely intertwined with the AlphaFold model but remain underexplored, which implies a broad exploration space. In conclusion, through the machine-learning-driven informatics methods, this scientometric analysis offers an objective and comprehensive overview of global AlphaFold research, identifying critical research clusters and hotspots while prospectively pointing out underexplored critical areas.

Self-Catalyzed Hydrogenated Carbon Nano-Onions Facilitates Mild Synthesis of Transparent Nano-Polycrystalline Diamond.

Transparent nano-polycrystalline diamond (t-NPD) possesses superior mechanical properties compared to single and traditional polycrystalline diamonds. However, the harsh synthetic conditions significantly limit its synthesis and applications. In this study, a synthesis routine is presented for t-NPD under low pressure and low temperature conditions, 10 GPa, 1600 °C and 15 GPa, 1350 °C similar with the synthesis condition of organic precursor. Self-catalyzed hydrogenated carbon nano-onions (HCNOs) from the combustion of naphthalene enable synthesis under nearly industrial conditions, which are like organic precursor and much lower than that of graphite and other carbon allotropes. This is made possible thanks to the significant impact of hydrogen on the thermodynamics, as it chemically facilitates phase transition. Ubiquitous nanotwinned structures are observed throughout t-NPD due to the high concentration of puckered layers and stacking faults of HCNOs, which impart a Vickers hardness about 140 GPa. This high hardness and optical transparency can be attributed to the nanocrystalline grain size, thin intergranular films, absence of secondary phase and pore-free features. The facile and industrial-scale synthesis of the HCNOs precursor, and mild synthesis conditions make t-NPD suitable for a wide range of potential applications.

HIV-1 mRNA knockdown with CRISPR/CAS9 enhances neurocognitive function.

Mixed glia are infiltrated with HIV-1 virus early in the course of infection leading to the development of a persistent viral reservoir in the central nervous system. Modification of the HIV-1 genome using gene editing techniques, including CRISPR/Cas9, has shown great promise towards eliminating HIV-1 viral reservoirs; whether these techniques are capable of removing HIV-1 viral proteins from mixed glia, however, has not been systematically evaluated. Herein, the efficacy of adeno-associated virus 9 (AAV9)-CRISPR/Cas9 gene editing for eliminating HIV-1 messenger RNA (mRNA) from cortical mixed glia was evaluated in vitro and in vivo. In vitro, a within-subjects experimental design was utilized to treat mixed glia isolated from neonatal HIV-1 transgenic (Tg) rats with varying doses (0, 0.9, 1.8, 2.7, 3.6, 4.5, or 5.4 µL corresponding to a physical titer of 0, 4.23 × 109, 8.46 × 109, 1.269 × 1010, 1.692 × 1010, 2.115 × 1010, and 2.538 × 1010 gc/µL) of CRISPR/Cas9 for 72 h. Dose-dependent decreases in the number of HIV-1 mRNA, quantified using an innovative in situ hybridization technique, were observed in a subset (i.e., n = 5 out of 8) of primary mixed glia. In vivo, HIV-1 Tg rats were retro-orbitally inoculated with CRISPR/Cas9 for two weeks, whereby treatment resulted in profound excision (i.e., approximately 53.2%) of HIV-1 mRNA from the medial prefrontal cortex. Given incomplete excision of the HIV-1 viral genome, the clinical relevance of HIV-1 mRNA knockdown for eliminating neurocognitive impairments was evaluated via examination of temporal processing, a putative neurobehavioral mechanism underlying HIV-1-associated neurocognitive disorders (HAND). Indeed, treatment with CRISPR/Cas9 protractedly, albeit not permanently, restored the developmental trajectory of temporal processing. Proof-of-concept studies, therefore, support the susceptibility of mixed glia to gene editing and the potential of CRISPR/Cas9 to serve as a novel therapeutic strategy for HAND, even in the absence of full viral eradication.

The role of HGH1 in breast cancer prognosis: a study on immune response and cell cycle.

BACKGROUND: Breast cancer (BRCA) remains to be among the main causes of cancer-associated mortality in women globally. HGH1 homolog (HGH1) has been reported to be associated with tumor immunity. However, the function of HGH1 in BRCA remains unclear. Therefore, the present study examined the potential role of HGH1 in BRCA. METHODS: The Cancer Genome Atlas (TCGA) databases and Gene Expression Omnibus (GEO) were used to obtain RNA-seq data for BRCA. A protein localization of HGH1 was determined by using the Human Protein Atlas (HPA), and immunohistochemistry (IHC) staining revealed an upregulation in the expression of HGH1 in clinical BRCA tissues. Xenograft mice were used to test tumor growth and HGH1 expression in breast cancer cells. The protein interaction information of HGH1 was analyzed using the GeneMANIA website. Based on univariate Cox regression and Kaplan-Meier methods, we evaluated the role of HGH1 in BRCA prognosis. HGH1-related differentially expressed genes were analyzed using GO, KEGG, and GSEA. We also examined the relationship between HGH1 expression, immune checkpoints, and immune infiltration. CCK-8, EdU, and colony formation assays were used to measure cell proliferation, and western blot analysis was used to evaluate HGH1's role in BRCA. RESULTS: IHC results showed that the expression of HGH1 was significantly upregulated in BRCA tissues compared to normal tissues. High levels of HGH1 expression was associated with worse clinical features and a worse prognosis. HGH1 expression was an independent predictor of BRCA outcomes in both univariate and multivariate analyses. Functionally, western blot analysis showed that HGH1 is implicated in cell cycle. As well, knocking down HGH1 significantly reduced BRCA cells' proliferative abilities. Crucially, HGH1 expression levels were positively correlated with Th2 cell infiltration and negatively correlated with Tcm cell infiltration. CONCLUSION: Biomarkers such as HGH1 can reliably predict prognosis in BRCA patients.

Binding with HSP90ß, cimifugin ameliorates fibrotic cataracts in vitro and in vivo by inhibiting TGFß signaling pathways.

Fibrotic cataracts, the most frequent complications after phacoemulsification, cannot be cured by drugs in clinic. The primary mechanism underlying the disease is the epithelial-mesenchymal transition (EMT). Cimifugin is a natural monomer component of traditional Chinese medicines. Previous researches have demonstrated the effect of cimifugin inhibiting EMT in the lung. The purpose of this work is to evaluate the impact of cimifugin on EMT in the lens and elucidate its precise mechanism. The pathogenesis of fibrotic cataracts was simulated using TGFß2-induced cell model of EMT and the injury-induced anterior subcapsular cataract animal model. Through H&E staining and immunofluorescence of mice eyeballs, we discovered that cimifugin can inhibit the expansion of fibrotic lesions in vivo. Furthermore, at mRNA and protein levels, we confirmed that cimifugin can allay EMT of lens epithelial cells (LECs) in vitro and in vivo. Additionally, the inhibition of cimifugin on the activation of TGFß-related signaling pathways was certified by immunoblot. HSP90ß, the target of cimifugin, was predicted by network pharmacology and verified by drug affinity responsive target stability, the cellular thermal shift assay, and microscale thermophoresis. Moreover, co-immunoprecipitation revealed the interaction between HSP90ß and TGFß receptor (TGFßR) II. Together, our findings showed that by weakening the binding of HSP90ß and TGFßRII, cimifugin suppressed the TGFß signaling pathways to alleviate fibrotic cataracts. Cimifugin is a promising medication for the treatment of fibrotic cataracts.

Paenalcaligenes faecalis sp. nov., a novel species of the family Alcaligenaceae isolated from chicken faeces.

A Gram-negative, motile, rod-shaped aerobic and alkalogenic bacterium, designated as strain YLCF04T, was isolated from chicken faeces. Its growth was optimal at 28 °C (range, 10-40 °C), pH 8 (range, pH 6-9) and in 1 % (w/v) NaCl (range, 0-10 %). It was classified to the genus Paenalcaligenes and was most closely related to Paenalcaligenes hominis CCUG 53761AT (97.5 % similarity) based on 16S rRNA gene sequence analysis. Average nucleotide identity and digital DNA-DNA hybridization values between YLCF04T and P. hominis CCUG 53761AT were 76.3 and 18.2 %, respectively. Strain YLCF04T has a genome size of 2.7 Mb with DNA G+C content of 46.3 mol%. Based on its phylogenetic, genomic, phenotypic and biochemical characteristics, strain YLCF04T represents a novel species of the genus Paenalcaligenes, for which the name Paenalcaligenes faecalis sp. nov. is proposed. The type strain is YLCF04T (=CCTCC AB 2022359T= KCTC 92789T).

Machine Learning Diagnosis of Small-Bowel Crohn Disease Using T2-Weighted MRI Radiomic and Clinical Data.

BACKGROUND. Radiologists have variable diagnostic performance and considerable interreader variability when interpreting MR enterography (MRE) examinations for suspected Crohn disease (CD). OBJECTIVE. The purposes of this study were to develop a machine learning method for predicting ileal CD by use of radiomic features of ileal wall and mesenteric fat from noncontrast T2-weighted MRI and to compare the performance of the method with that of expert radiologists. METHODS. This single-institution study included retrospectively identified patients who underwent MRE for suspected ileal CD from January 1, 2020, to January 31, 2021, and prospectively enrolled participants (patients with newly diagnosed ileal CD or healthy control participants) from December 2018 to October 2021. Using axial T2-weighted SSFSE images, a radiologist selected two slices showing greatest terminal ileal wall thickening. Four ROIs were segmented, and radiomic features were extracted from each ROI. After feature selection, support-vector machine models were trained to classify the presence of ileal CD. Three fellowship-trained pediatric abdominal radiologists independently classified the presence of ileal CD on SSFSE images. The reference standard was clinical diagnosis of ileal CD based on endoscopy and biopsy results. Radiomic-only, clinical-only, and radiomic-clinical ensemble models were trained and evaluated by nested cross-validation. RESULTS. The study included 135 participants (67 female, 68 male; mean age, 15.2 ± 3.2 years); 70 were diagnosed with ileal CD. The three radiologists had accuracies of 83.7% (113/135), 88.1% (119/135), and 86.7% (117/135) for diagnosing CD; consensus accuracy was 88.1%. Interradiologist agreement was substantial (κ = 0.78). The best-performing ROI was bowel core (AUC, 0.95; accuracy, 89.6%); other ROIs had worse performance (whole-bowel AUC, 0.86; fat-core AUC, 0.70; whole-fat AUC, 0.73). For the clinical-only model, AUC was 0.85 and accuracy was 80.0%. The ensemble model combining bowel-core radiomic and clinical models had AUC of 0.98 and accuracy of 93.5%. The bowel-core radiomic-only model had significantly greater accuracy than radiologist 1 (p = .009) and radiologist 2 (p = .02) but not radiologist 3 (p > .99) or the radiologists in consensus (p = .05). The ensemble model had greater accuracy than the radiologists in consensus (p = .02). CONCLUSION. A radiomic machine learning model predicted CD diagnosis with better performance than two of three expert radiologists. Model performance improved when radiomic data were ensembled with clinical data. CLINICAL IMPACT. Deployment of a radiomic-based model including T2-weighted MRI data could decrease interradiologist variability and increase diagnostic accuracy for pediatric CD.

Deep Learning Models for Abdominal CT Organ Segmentation in Children: Development and Validation in Internal and Heterogeneous Public Datasets.

BACKGROUND. Deep learning abdominal organ segmentation algorithms have shown excellent results in adults; validation in children is sparse. OBJECTIVE. The purpose of this article is to develop and validate deep learning models for liver, spleen, and pancreas segmentation on pediatric CT examinations. METHODS. This retrospective study developed and validated deep learning models for liver, spleen, and pancreas segmentation using 1731 CT examinations (1504 training, 221 testing), derived from three internal institutional pediatric (age ≤ 18 years) datasets (n = 483) and three public datasets comprising pediatric and adult examinations with various pathologies (n = 1248). Three deep learning model architectures (SegResNet, DynUNet, and SwinUNETR) from the Medical Open Network for Artificial Intelligence (MONAI) framework underwent training using native training (NT), relying solely on institutional datasets, and transfer learning (TL), incorporating pretraining on public datasets. For comparison, TotalSegmentator, a publicly available segmentation model, was applied to test data without further training. Segmentation performance was evaluated using mean Dice similarity coefficient (DSC), with manual segmentations as reference. RESULTS. For internal pediatric data, the DSC for TotalSegmentator, NT models, and TL models for normal liver was 0.953, 0.964-0.965, and 0.965-0.966, respectively; for normal spleen, 0.914, 0.942-0.945, and 0.937-0.945; for normal pancreas, 0.733, 0.774-0.785, and 0.775-0.786; and for pancreas with pancreatitis, 0.703, 0.590-0.640, and 0.667-0.711. For public pediatric data, the DSC for TotalSegmentator, NT models, and TL models for liver was 0.952, 0.871-0.908, and 0.941-0.946, respectively; for spleen, 0.905, 0.771-0.827, and 0.897-0.926; and for pancreas, 0.700, 0.577-0.648, and 0.693-0.736. For public primarily adult data, the DSC for TotalSegmentator, NT models, and TL models for liver was 0.991, 0.633-0.750, and 0.926-0.952, respectively; for spleen, 0.983, 0.569-0.604, and 0.923-0.947; and for pancreas, 0.909, 0.148-0.241, and 0.699-0.775. The DynUNet TL model was selected as the best-performing NT or TL model considering DSC values across organs and test datasets and was made available as an open-source MONAI bundle (https://github.com/cchmc-dll/pediatric_abdominal_segmentation_bundle.git). CONCLUSION. TL models trained on heterogeneous public datasets and fine-tuned using institutional pediatric data outperformed internal NT models and Total-Segmentator across internal and external pediatric test data. Segmentation performance was better in liver and spleen than in pancreas. CLINICAL IMPACT. The selected model may be used for various volumetry applications in pediatric imaging.

SPACA6P-AS: a trailblazer in breast cancer pathobiology and therapeutics.

OBJECTIVE: The primary objective of this investigation is to delve into the involvement of the long noncoding RNA (lncRNA) SPACA6P-AS in breast cancer (BC) development, focusing on its expression pattern, association with clinical-pathological features, impact on prognosis, as well as its molecular and immunological implications. METHODS: Bioinformatics analysis was conducted utilizing RNA sequencing data of 1083 BC patients from the TCGA database. Functional exploration of SPACA6P-AS was carried out through the construction of survival curves, GO and KEGG enrichment analysis, and single-sample gene set enrichment analysis (ssGSEA). Furthermore, its functionality was validated through in vitro cell experiments and in vivo nude mouse model experiments. RESULTS: SPACA6P-AS showed a remarkable increase in expression levels in BC tissues (p < 0.001) and demonstrated a close relationship to poor prognosis (overall survival HR = 1.616, progression-free interval HR = 1.40, disease-specific survival HR = 1.54). Enrichment analysis revealed that SPACA6P-AS could impact biological functions such as protease regulation, endopeptidase inhibitor activity, taste receptor activity, taste transduction, and maturity-onset diabetes of the young pathway. ssGSEA analysis indicated a negative correlation between SPACA6P-AS expression and immune cell infiltration like dendritic cells and neutrophils, while a positive correlation was observed with central memory T cells and T helper 2 cells. Results from in vitro and in vivo experiments illustrated that silencing SPACA6P-AS significantly inhibited the proliferation, migration, and invasion capabilities of BC cells. In vitro experiments also highlighted that dendritic cells with silenced SPACA6P-AS exhibited enhanced capabilities in promoting the proliferation of autologous CD3 + T cells and cytokine secretion. These discoveries elucidate the potential multifaceted roles of SPACA6P-AS in BC, including its potential involvement in modulating immune cell infiltration in the tumor microenvironment. CONCLUSION: The high expression of lncRNA SPACA6P-AS in BC is closely linked to poor prognosis and may facilitate tumor progression by influencing specific biological processes, signaling pathways, and the immune microenvironment. The regulatory role of SPACA6P-AS positions it as a prospective biomarker and target for therapeutic approaches for BC diagnosis and intervention.

Epidemiology of Vancomycin in Combination With Piperacillin/Tazobactam-Associated Acute Kidney Injury in Children: A Systematic Review and Meta-analysis.

BACKGROUND: Several studies have shown that vancomycin combined with piperacillin/tazobactam (VPT) increased the risk of acute kidney injury (AKI) compared with other antibiotics in children. However, the epidemiology of VPT-associated AKI in children is unknown. OBJECTIVE: To evaluate the incidence and risk factors of VPT-associated AKI in children. DATA SOURCES: Literature databases of PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, WanFang Database, and China Biology Medicine Disc were searched from inception to November 2023. References of included studies were also manually checked. STUDY SELECTION AND DATA EXTRACTION: Two independent reviewers selected studies, extracted data, and quality assessment. Meta-analyses were performed to quantify the incidence and risk factors of VPT-associated AKI in children. DATA SYNTHESIS: Sixteen cohort studies were identified. Overall, the incidence of VPT-associated AKI in children was 24.3% (95% CI: 17.9%-30.6%). The incidence of VPT-associated AKI in critically ill children (26.6%) was higher than that in noncritically ill children (10.9%). Moreover, higher serum vancomycin trough concentration (>15 mg/L), use of vasopressors, combination of nephrotoxins and intensive care unit admission were risk factors for VPT-associated AKI in children (P < 0.05). RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE: Identifying high-risk groups and determining safer treatments is critical to reducing the incidence of VPT-associated AKI in children. CONCLUSIONS: The incidence of VPT-associated AKI in children is high, especially in critically ill children. Medication regimens should be personalized based on the presence of individual risk factors. Moreover, renal function was regularly assessed throughout treatment with VPT.

Reference guides for the safe use of drugs during pregnancy: a systematic review and comparative analysis.

PURPOSE: To comprehensively evaluate and compare all the available reference guides for the safe use of drugs during pregnancy, with the goal of determining the scientificity and reliability of these reference guides. METHODS: We searched PubMed, EMbase, CNKI, Wanfang Database, and VIP database to comprehensively identify the available reference guides. Moreover, we selected 103 drugs based on relevant literatures, and compared the recommendations of each drug from different reference guides. RESULTS: A total of 14 available reference guides were identified. However, none of these reference guides assessed the risk of bias of original studies or the quality of current evidence. Seven reference guides adopted expert consensus method to formulate pregnancy recommendations, while the rest reference guides did not report the formation method. Moreover, 77.7% of the selected drugs had inconsistent recommendations among different reference guides. In addition, the referenced human and animal studies for the same drug differed among different reference guides. CONCLUSION: Our results indicate that current reference guides for the safe use of drugs during pregnancy are less scientific and reliable, and there are considerable discrepancies in recommendations from different reference guides concerning drug use during pregnancy. The reasons for the discrepancies in recommendations include ① the literature search in most reference guides was not comprehensive, ② none of the available reference guides assessed the risk of bias of original studies or the quality of current evidence, and ③ the method adopted by current reference guides to formulate recommendations had obvious subjectivity and lacked of scientificity.

Use of statins and risks of ovarian, uterine, and cervical diseases: a cohort study in the UK Biobank.

PURPOSE: To examine the associations between use of statins and risks of various ovarian, uterine, and cervical diseases, including ovarian cancer, endometrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp. METHODS: We conducted a cohort study among female participants in the UK Biobank. Information on the use of statins was collected through verbal interview. Outcome information was obtained by linking to national cancer registry data and hospital inpatient data. We used Cox proportional hazards regression to examine the associations. RESULTS: A total of 180,855 female participants (18,403 statin users and 162,452 non-users) were included. Use of statins was significantly associated with increased risks of cervical cancer (adjusted hazard ratio (HR), 1.55; 95% confidence interval (95% CI), 1.05-2.30) and polycystic ovarian syndrome (adjusted HR, 4.39; 95% CI, 1.68-11.49). However, we observed no significant association between use of statins and risk of ovarian cancer, endometrial cancer, ovarian cyst, endometriosis, endometrial hyperplasia, endometrial polyp, or cervical polyp. CONCLUSION: Our findings suggest that use of statins is associated with increased risks of cervical cancer and polycystic ovarian syndrome, but is not associated with increased or decreased risk of ovarian cancer, endometrial cancer, ovarian cyst, endometriosis, endometrial polyp, or cervical polyp.

Theoretical Investigation on the Initial Reaction Mechanism of Hexaethynylbenzene on Au(111) Surface.

Graphyne has attracted considerable interest and attention since its successful synthesis, due to its enormous potential for applications in the fields of electronics, energy, catalysis, information technology, etc. Although various methods for synthesizing graphyne have been explored, single-layer graphynes have not been successfully developed. Hexaethynylbenzene (HEB) is considered an ideal precursor molecule because it can undergo Glaser coupling reactions between molecules to synthesize single layer graphdiyne on single crystal metal surfaces via on-surface reactions. Unfortunately, this method fails to achieve the expected results, and the underlying mechanism is not clear. In this work, we employed a combination of ab initio molecular dynamics (AIMD) and quantum mechanics (QM) methods to investigate the initial reaction mechanism of HEB molecules on a Au(111) surface. We revealed that HEB molecules undergo both intermolecular coupling and intramolecular cyclization on the Au(111) surface. The favorable pathways of these two types of reactions were then distinguished, confirming that the distance between the terminal carbon atoms of the ethynyl groups plays an important role in C-C coupling. The insights revealed from this work could facilitate the rational design of precursor molecules and deepen the understanding of the reaction processes.

Development of an AIE-active fluorescent probe for the simultaneous detection of Al3+ and viscosity and imaging in Alzheimer's disease model.

Alzheimer's disease is associated both with imbalances in Al3+ production and changes in viscosity in cells. Their simultaneous measurement could therefore provide valuable insights into Alzheimer's disease pathology. Their simultaneous measurement would therefore be of great value in investigating the pathological mechanism of Alzheimer's disease. We designed a fluorescent probe YM2T with AIE effect that is capable of selectively responding to Al3+ by fluorescence colormetrics and to viscosity by fluorescence "turn on" modes. Additionally, Al3+ and viscosity were simultaneously detected in PC12 cells using the low cytotoxic probe YM2T via blue and green fluorescence channels. More importantly, the YM2T probe was used to image mice with AD. Hence, the YM2T probe shows potential as a useful molecular instrument for studying the pathological impact of Al3+ and viscosity.

Structure-based design and synthesis of anti-fibrotic compounds derived from para-positioned 3,4,5-trisubstituted benzene.

Liver fibrosis is an abnormal wound-healing response to liver injuries. It can lead to liver cirrhosis, and even liver cancer and liver failure. There is a lack of treatment for liver fibrosis and it is of great importance to develop anti-fibrotic drugs. A pivotal event in the process of developing liver fibrosis is the activation of hepatic stellate cells (HSCs), in which the nuclear receptor Nur77 plays a crucial role. This study aimed to develop novel anti-fibrotic agents with Nur77 as the drug target by modifying the structure of THPN, a Nur77-binding and anti-melanoma compound. Specifically, a series of para-positioned 3,4,5-trisubstituted benzene ring compounds with long-chain backbone were generated and tested for anti-fibrotic activity. Among these compounds, compound A8 was with the most potent and Nur77-dependent inhibitory activity against TGF-ß1-induced activation of HSCs. In a crystal structure analysis, compound A8 bound Nur77 in a peg-in-hole mode as THPN did but adopted a different conformation that could interfere the Nur77 interaction with AKT, which was previous shown to be important for an anti-fibrotic activity. In a cell-based assay, compound A8 indeed impeded the interaction between Nur77 and AKT leading to the stabilization of Nur77 without the activation of AKT. In a mouse model, compound A8 effectively suppressed the activation of AKT signaling pathway and up-regulated the cellular level of Nur77 to attenuate the HSCs activation and ameliorate liver fibrosis with no significant toxic side effects. Collectively, this work demonstrated that Nur77-targeting compound A8 is a promising anti-fibrotic drug candidate.

Adverse drug reaction signal detection methods in spontaneous reporting system: A systematic review.

BACKGROUND: A series of signal detection methods have been developed to detect adverse drug reaction (ADR) signals in spontaneous reporting system. However, different signal detection methods yield quite different signal detection results, and we do not know which method has the best detection performance. How to choose the most suitable signal detection method is an urgent problem to be solved. In this study, we systematically reviewed the characteristics and application scopes of current signal detection methods, with the goal of providing references for the optimization selection of signal detection methods in spontaneous reporting system. METHODS: We searched six databases from inception to January 2023. The search strategy targeted literatures regarding signal detection methods in spontaneous reporting system. We used thematic analysis approach to summarize the advantages, disadvantages, and application scope of each signal detection method. RESULTS: A total of 93 literatures were included, including 27 reviews and 66 methodological studies. Moreover, 31 signal detection methods were identified in these literatures. Each signal detection method has its inherent advantages and disadvantages, resulting in different application scopes of these methods. CONCLUSION: Our systematic review finds that there are variabilities in the advantages, disadvantages, and application scopes of different signal detection methods. This finding indicates that the most suitable signal detection method varies across different drug safety scenarios. Moreover, when selecting signal detection method in a particular drug safety scenario, the following factors need to be considered: purpose of research, database size, drug characteristics, adverse event characteristics, and characteristics of the relations between drugs and adverse events.

Use of municipal solid waste incineration fly ash as a supplementary cementitious material: CO2 mineralization coupled with mechanochemical pretreatment.

The use of municipal solid waste incineration fly ash, commonly referred to as "fly ash", as a supplementary cementitious material (SCM), has been explored to mitigate the CO2 emissions resulting from cement production. Nevertheless, the incorporation of fly ash as an SCM in mortar has been shown to weaken its compressive strength and increase the risk of heavy metal leaching. In light of these challenges, this study aims to comprehensively evaluate the influence of CO2 pressure, temperature, and residual water/binder ratio on the CO2 uptake and compressive strength of mortar when combined with fly ash. Additionally, this study systematically examines the feasibility of mechanochemical pretreatment, which enhances the homogenization of fly ash and augments the density of the mortar's microstructure. The results indicate that the use of mechanochemical pretreatment leads to a notable 43.6% increase in 28-day compressive strength and diminishes the leaching of As, Ba, Ni, Pb, Se, and Zn by 17.9-77.8%. Finally, a reaction kinetics model is proposed to elucidate the CO2 sequestration process under varying conditions. These findings offer valuable guidance for incorporating fly ash as an SCM and CO2 sequestrator in mortar.