Construction and Application of a Traditional Chinese Medicine Syndrome Differentiation Model for Dysmenorrhea Based on Machine Learning.

BACKGROUND: Dysmenorrhea is one of the most common ailments affecting young and middle-aged women, significantly impacting their quality of life. Traditional Chinese Medicine (TCM) offers unique advantages in treating dysmenorrhea. However, an accurate diagnosis is essential to ensure correct treatment. This research integrates the age-old wisdom of TCM with modern Machine Learning (ML) techniques to enhance the precision and efficiency of dysmenorrhea syndrome differentiation, a pivotal process in TCM diagnostics and treatment planning. METHODS: A total of 853 effective cases of dysmenorrhea were retrieved from the CNKI database, including patients' syndrome types, symptoms, and features, to establish the TCM information database of dysmenorrhea. Subsequently, 42 critical features were isolated from a potential set of 86 using a selection procedure augmented by Python's Scikit-Learn Library. Various machine learning models were employed, including Logistic Regression, Random Forest Classifier, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Artificial Neural Networks (ANN), each chosen for their potential to unearth complex patterns within the data. RESULTS: Based on accuracy, precision, recall, and F1-score metrics, SVM emerged as the most effective model, showcasing an impressive precision of 98.29% and an accuracy of 98.24%. This model's analytical prowess not only highlighted the critical features pivotal to the syndrome differentiation process but also stands to significantly aid clinicians in formulating personalized treatment strategies by pinpointing nuanced symptoms with high precision. CONCLUSION: The study paves the way for a synergistic approach in TCM diagnostics, merging ancient wisdom with computational acuity, potentially innovating the diagnosis and treatment mode of TCM. Despite the promising outcomes, further research is needed to validate these models in real-world settings and extend this approach to other diseases addressed by TCM.

LncCMRR Plays an Important Role in Cardiac Differentiation by Regulating the Purb/Flk1 Axis.

As crucial epigenetic regulators, long noncoding RNAs (lncRNAs) play critical functions in development processes and various diseases. However, the regulatory mechanism of lncRNAs in early heart development is still limited. In this study, we identified cardiac mesoderm-related lncRNA (LncCMRR). Knockout (KO) of LncCMRR decreased the formation potential of cardiac mesoderm and cardiomyocytes during embryoid body differentiation of mouse embryonic stem (ES) cells. Mechanistic analyses showed that LncCMRR functionally interacted with the transcription suppressor PURB and inhibited its binding potential at the promoter region of Flk1, which safeguarded the transcription of Flk1 during cardiac mesoderm formation. We also carried out gene ontology term and signaling pathway enrichment analyses for the differentially expressed genes after KO of LncCMRR, and found significant correlation of LncCMRR with cardiac muscle contraction, dilated cardiomyopathy, and hypertrophic cardiomyopathy. Consistently, the expression level of Flk1 at E7.75 and the thickness of myocardium at E17.5 were significantly decreased after KO of LncCMRR, and the survival rate and heart function index of LncCMRR-KO mice were also significantly decreased as compared with the wild-type group. These findings indicated that the defects in early heart development led to functional abnormalities in adulthood heart of LncCMRR-KO mice. Conclusively, our findings elucidate the main function and regulatory mechanism of LncCMRR in cardiac mesoderm formation, and provide new insights into lncRNA-mediated regulatory network of mouse ES cell differentiation.

Long noncoding RNA Q associates with Sox2 and is involved in the maintenance of pluripotency in mouse embryonic stem cells.

Large intergenic noncoding RNAs (lincRNAs) in ESCs may play an important role in the maintenance of pluripotency. The identification of stem cell-specific lincRNAs and their interacting partners will deepen our understanding of the maintenance of stem cell pluripotency. We identified a lincRNA, LincQ, which is specifically expressed in ESCs and is regulated by core pluripotent transcription factors. It was rapidly downregulated during the differentiation process. Knockdown of LincQ in ESCs led to differentiation, downregulation of pluripotency-related genes, and upregulation of differentiation-related genes. We found that exon 1 of LincQ can specifically bind to Sox2. The Soxp region in Sox2, rather than the high mobility group domain, is responsible for LincQ binding. Importantly, the interaction between LincQ and Sox2 is required for the maintenance of pluripotency in ESCs and the transcription of pluripotency genes. Esrrb and Tfcp2l1 are key downstream targets of LincQ and Sox2, since overexpression of Esrrb and Tfcp2l1 can restore the loss of ESC pluripotency that is induced by LincQ depletion. In summary, we found that LincQ specifically interacts with Sox2 and contributes to the maintenance of pluripotency, highlighting the critical role of lincRNA in the pluripotency regulatory network.

Motifs in the amino-terminus of CENP-A are required for its accumulation within the nucleus and at the centromere.

Centromere protein A (CENP-A) is a variant of core histone H3 that marks the centromere's location on the chromosome. The mechanisms that target the protein to the nucleus and the centromere have not been defined. In this study, we found that deletion of the first 53 but not the first 29 residues of CENP-A from the amino-terminus, resulted in its cytoplasmic localization. Two motifs, R42R43R44 and K49R52K53K56, which are reported to be required for DNA contact in the centromere nucleosome, were found to be critical for CENP-A nuclear accumulation. These two motifs potentially mediated its interaction with Importin-ß but were not involved in CENP-A centromeric localization. A third novel motif, L60L61I62R63K64, was found to be essential for the centromeric accumulation of CENP-A. The nonpolar hydrophobic residues L60L61I62, but not the basic residues R63K64, were found to be the most important residues. A protein interaction assay suggested that this motif is not involved in the interaction of CENP-A with its deposition factors but potentially mediates its interaction with core histone H4 and CENP-B. Our study uncovered the role of the amino-terminus of CENP-A in localization.

HDAC10 promotes lung cancer proliferation via AKT phosphorylation.

Histone deacetylase 10 (HDAC10) is a member of the class II HDACs, and its role in cancer is emerging. In this study, we found that HDAC10 is highly expressed in lung cancer tissues. It resides mainly in the cytoplasm of lung cancer cells but resides in the nucleus of adjacent normal cells. Further examinations revealed that HDAC10 resides in the cytoplasm in multiple lung cancer cell lines, including the A549, H358 and H460 cell lines, but mainly resides in the nucleus of normal lung epithelial 16HBE cells. A leucine-rich motif, R505L506L507C508V509A510L511, was identified as its nuclear localization signal (NLS), and a mutant (Mut-505-511) featuring mutations to A at each of its original R and L positions was found to be nuclear-localization defective. Functional analysis revealed that HDAC10 promoted lung cancer cell growth and that its knockdown induced cell cycle arrest and apoptosis. Mechanistic studies showed that HDAC10 knockdown significantly decreased the phosphorylation of AKT at Ser473 and that AKT expression significantly rescued the cell cycle arrest and apoptosis elicited by HDAC10 knockdown. A co-immunoprecipitation assay suggested that HDAC10 interacts with AKT and that inhibition of HDAC10 activity decreases its interaction with and phosphorylation of AKT. Finally, we confirmed that HDAC10 promoted lung cancer proliferation in a mouse model. Our study demonstrated that HDAC10 localizes and functions in the cytoplasm of lung cancer cells, thereby underscoring its potential role in the diagnosis and treatment of lung cancer.

A motif from Lys216 to Lys222 in human BUB3 protein is a nuclear localization signal and critical for BUB3 function in mitotic checkpoint.

Human BUB3 is a key mitotic checkpoint factor that recognizes centromeric components and recruits other mitotic checkpoint molecules to the unattached kinetochore. The key amino acid residues responsible for its localization are not yet defined. In this study, we identified a motif from Lys(216) to Lys(222) in BUB3 as its nuclear localization signal. A BUB3 mutant with deletion of this motif (Del216-222) was found to localize to both the cytoplasm and the nucleus, distinct from the exclusively nuclear distribution of wild-type BUB3. Further analysis revealed that residues Glu(213), Lys(216), Lys(217), Lys(218), Tyr(219), and Phe(221), but not Lys(222), contribute to nuclear localization. Interestingly, the nuclear localization signal was also critical for the kinetochore localization of BUB3. The deletion mutant Del216-222 and a subtle mutant with four residue changes in this region (E213Q/K216E/K217E/K218E (QE)) did not localize to the kinetochore efficiently or mediate mitotic checkpoint arrest. Protein interaction data suggested that the QE mutant was able to interact with BUB1, MAD2, and BubR1 but that its association with the centromeric components CENP-A and KNL1 was impaired. A motif from Leu(61) to Leu(65) in CENP-A was found to be involved in the association of BUB3 and CENP-A in cells; however, further assays suggested that CENP-A does not physically interact with BUB3 and does not affect BUB3 localization. Our findings help to dissect the mechanisms of BUB3 in mitotic checkpoint signaling.