Background: The human head is an integrated biological structure composed of the brain, cranial bones, facial structures, neuromuscular systems, and sensory organs, all interconnected through coordinated signaling. The relationship between brain development, function, and craniofacial growth is most evident after birth, during which the head increases approximately fourfold in size before adulthood. Brain morphology and volume are associated not only with neurological disorders but also with cognitive and behavioral characteristics. For example, children with holoprosencephaly often present with varying degrees of facial anomalies, while studies have shown that adolescents with malocclusion exhibit higher levels of anxiety, depression, and psychological stress. With the increasing availability of magnetic resonance imaging (MRI), it has become an essential diagnostic tool in clinical practice. MRI is particularly advantageous in pediatric populations due to the absence of ionizing radiation and its superior soft tissue contrast. Recent advances in image processing techniques have enabled comprehensive analysis of both brain structures and craniofacial morphology from a single MRI dataset, forming the basis of this study. Aim: To investigate the relationship between brain tissue volumes and maxillary hypoplasia using MRI-based voxelbased morphometry in children with neurological conditions. Materials and Methods: This study was conducted at the School of Biomedicine, Mongolian National University of Medical Sciences, in collaboration with Chifeng University, as part of the project titled “Investigation of the relationship between craniofacial anomalies and brain disorders using MRI”, funded by the Ministry of Education and Science. Voxel-based morphometry (VBM) analysis was performed on brain MRI scans of children aged 9–11 years. Results: Among the 25 children included in the study, 17 (68%) were male. The youngest average age was observed in the maxillary hypoplasia group (8.4±0.95 years). The signal-to-noise ratio (SNR) of MRI was lowest in the non-temporal epilepsy group (41.1±1.35) and higher in the maxillary hypoplasia group (49.6±8.22). Both epilepsy and maxillary hypoplasia groups demonstrated physiological asymmetry of the cerebral hemispheres, with left parietal lobe dominance (−0.1% and −0.3 cm, respectively). Right frontal lobe dominance (+1.1%) was observed only in the epilepsy group. Conclusion Children aged 9–11 years with maxillary hypoplasia showed a reduction in both gray and white matter volumes of the brain. These findings highlight the importance of early diagnosis of neurodevelopmental disorders affecting odontogenesis and emphasize the need for a multidisciplinary team-based management approach.

Objective:To evaluate the diagnostic performance of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination.Methods:Cervical cytology slide data were retrospectively collected from four hospitals for the external validation of the developed artificial intelligence-assisted diagnostic system. Subsequently, prospective data collection was conducted for human-machine assisted studies.Results:In the retrospective study, a total of 3 162 valid samples were collected as external validation data. The system showed an area under the curve (AUC) of 0.890 (95% CI: 0.878-0.902), accuracy of 0.885 (95% CI: 0.873-0.896), sensitivity of 0.928 (95% CI: 0.914-0.941), and specificity of 0.852 (95% CI: 0.834-0.867). In the prospective study, 212 valid samples were collected, and five junior cytologists participated in the human-machine assisted study. Without artificial intelligence assistance, the average AUC for the five cytologists was 0.686 (95% CI: 0.650-0.722), the accuracy was 0.699 (95% CI: 0.671-0.727), the sensitivity was 0.653 (95% CI: 0.599-0.703), the specificity was 0.719 (95% CI: 0.685-0.750), the Fleiss κ value was 0.510, and the reading time was 223 seconds. With artificial intelligence assistance, the AUC, accuracy, sensitivity, and specificity increased by 0.166, 0.143, 0.225, and 0.107, respectively. Additionally, Fleiss κ was 0.730 and the reading time decreased by 188 seconds. All differences were statistically significant (all P<0.001). Conclusions:Artificial intelligence-assisted diagnosis system shows excellent performance and good generalizability, significantly improving the diagnostic accuracy, consistency, and efficiency of junior cytologists. It can be an effective auxiliary tool for junior cytologists in clinical practice.

Objective To analyze the expression levels of miR-27a-3p mRNA and Yes-associated protein 1(YAP1)mRNA in breast cancer,and to explore their relationships with clinicopathological features and the survival prognosis of patients.Methods A total of 130 breast cancer patients who underwent mastectomy in our hospital between January 2019 and January 2021 were enrolled.The expression levels of miR-27a-3p and YAP1 mRNA in breast tumor tissues and adjacent normal breast tissues were assessed by qRT-PCR.Furthermore,the relationships between their expression and clinicopathological features,as well as the survival prognosis of patients,were investigated.Results Compared with adjacent normal breast tissues,the expression of miR-27a-3p mRNA in breast tumor tissues was lower(P＜0.05),while that of YAP1 mRNA was higher(P＜0.05).A negative correlation was observed between the expression of miR-27a-3p mRNA and YAP1 mRNA in breast tumor tissues(r=-0.456,P＜0.05).The expression of miR-27a-3p mRNA was correlated with tumor diameter,histological grade,tumor staging by the TNM system,lymph node metastasis,and vascular invasion in patients with breast cancer(P＜0.05).The YAP1 mRNA expression was correlated with histological grade,tumor staging by the TNM system,lymph node metastasis,and vascular invasion(P＜0.05).Kaplan-Meier survival analysis revealed that the 3-year overall survival rate of the miR-27a-3p low-expression group was 71.60％(48/67),which was lower than the 91.50％(54/59)of the miR-27a-3p high-expression group(log-rank x2=8.211,P=0.004).The 3-year overall survival rate of the YAP1 high-expression group was 73.80％(45/61),lower than that of the YAP1 low-expression group(87.70％,57/65)(log-rank x2=4.429,P=0.035).Multivariate regression analysis indicated that lymph node metastasis(hazard ratio[HR]=1.409;95％CI,1.057-1.644;P=0.046),vascular invasion(HR=1.541;95％CI,1.076-1.869;P=0.045),low miR-27a-3p mRNA expression(HR=0.593;95％CI,0.388-0.925;P=0.018),and high YAP1 mRNA expression(HR=0.628;95％CI,0.405-0.912;P=0.022)were relevant factors affecting the 3-year overall survival of patients with breast cancer.Conclusion A significant downregulation of miR-27a-3p mRNA and upregulation of YAP1 mRNA are observed in breast tumor tissues.The low expression of miR-27a-3p mRNA and the high expression of YAP1 mRNA are associated with adverse clinicopathological features and poor survival prognosis,and are risk factors affecting the 3-year overall survival of patients with breast cancer.They show promise as new potential therapeutic targets for breast cancer.

Objective:To evaluate the diagnostic performance of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination.Methods:Cervical cytology slide data were retrospectively collected from four hospitals for the external validation of the developed artificial intelligence-assisted diagnostic system. Subsequently, prospective data collection was conducted for human-machine assisted studies.Results:In the retrospective study, a total of 3 162 valid samples were collected as external validation data. The system showed an area under the curve (AUC) of 0.890 (95% CI: 0.878-0.902), accuracy of 0.885 (95% CI: 0.873-0.896), sensitivity of 0.928 (95% CI: 0.914-0.941), and specificity of 0.852 (95% CI: 0.834-0.867). In the prospective study, 212 valid samples were collected, and five junior cytologists participated in the human-machine assisted study. Without artificial intelligence assistance, the average AUC for the five cytologists was 0.686 (95% CI: 0.650-0.722), the accuracy was 0.699 (95% CI: 0.671-0.727), the sensitivity was 0.653 (95% CI: 0.599-0.703), the specificity was 0.719 (95% CI: 0.685-0.750), the Fleiss κ value was 0.510, and the reading time was 223 seconds. With artificial intelligence assistance, the AUC, accuracy, sensitivity, and specificity increased by 0.166, 0.143, 0.225, and 0.107, respectively. Additionally, Fleiss κ was 0.730 and the reading time decreased by 188 seconds. All differences were statistically significant (all P<0.001). Conclusions:Artificial intelligence-assisted diagnosis system shows excellent performance and good generalizability, significantly improving the diagnostic accuracy, consistency, and efficiency of junior cytologists. It can be an effective auxiliary tool for junior cytologists in clinical practice.

Humans ; Siblings ; Gene Frequency ; Microsatellite Repeats

Multiple plant lineages have independently evolved sex chromosomes and variable kary-otypes to maintain their sessile lifestyles through constant biological innovation.Morus notabilis,a dioecious mulberry species,has the fewest chromosomes among Morus spp.,but the genetic basis of sex determination and karyotype evolution in this species has not been identified.In this study,three high-quality genome assemblies were generated for Morus spp.[including dioecious M.notabilis(male and female)and Morus yunnanensis(female)]with genome sizes of 301-329 Mb and were grouped into six pseudochromosomes.Using a combination of genomic approaches,we found that the putative ancestral karyotype of Morus species was close to 14 protochromosomes,and that sev-eral chromosome fusion events resulted in descending dysploidy(2n=2x=12).We also charac-terized a～6.2-Mb sex-determining region on chromosome 3.Four potential male-specific genes,a partially duplicated DNA helicase gene(named MSDH)and three Ty3_Gypsy long terminal repeat retrotransposons(named MSTG1/2/3),were identified in the Y-linked area and considered to be strong candidate genes for sex determination or differentiation.Population genomic analysis showed that Guangdong accessions in China were genetically similar to Japanese accessions of mul-berry.In addition,genomic areas containing selective sweeps that distinguish domesticated mul-berry from wild populations in terms of flowering and disease resistance were identified.Our study provides an important genetic resource for sex identification research and molecular breeding in mulberry.

OBJECTIVETo analyze the clinical manifestations and gene mutation of a 6 year old boy with autism spectrum disorders (ASD).

METHODSPeripheral blood of the boy and his parents were subjected to genetic testing.

RESULTSThe patient was diagnosed with typical autism. Exome sequencing has identified mutations of four candidate genes, namely TUT1, DIAPH3, REELIN and SETD2, which were confirmed with Sanger sequencing. Analysis of family members confirmed that the missense mutations of DIAPH3 and SETD2 genes were of de novo origin.

CONCLUSIONMissense mutations of DIAPH3 and SETD2 genes may have contributed to the risk of ASD. Disrupted neurogenesis associated with such mutations may have been the underlying mechanism for ASD.

Adaptor Proteins, Signal Transducing ; chemistry ; genetics ; Amino Acid Sequence ; Autism Spectrum Disorder ; etiology ; genetics ; Child ; Humans ; Male ; Molecular Sequence Data ; Mutation

Acupuncture Points ; Acupuncture Therapy ; Adult ; Female ; Humans ; Infertility, Female ; therapy

This article was aimed to propose and develop traditional Chinese medicine (TCM) health engineering, using modern science and technology, in order to carry out the detection research which reflected TCM features of human functional state. It was an important way to achieve TCM diagnosis and the objective evaluation on therapeutic effects of TCM. The combination of TCM health engineering with information technology, and the formation of TCM functional state intelligent identification system, as well as the extension into the Health Internet of Things (HIT) could provide more accurate and convenient services for human healthcare in the age of big health. And identification on TCM syndromes was the core to achieve this goal. Using characterization data on TCM syndromes could realize the data processing between TCM syndrome and prescription through intelligent computing, in order to form the TCM syndrome differentiation and treatment intelligent system. It had great significance in the promotion of TCM health project.

ObjectiveTo summarize the nursing measures for patients with nasal facial soft tissue defect treated with transplantation of free foot skin flap.MethodThe clinical data of 13 patients with transplantation were reviewed to summarize the nursing measures.ResultAll skin flaps of the 13 patients survived.ConclusionEnough preoperative preparation,active psychological nursing and careful postoperative observation are critical for the success of the operation.