A cross-sectional study: correlation of forehead morphology and dentoskeletal malocclusion in Chinese people.

BACKGROUND: The lateral profile is an important indicator of facial attractiveness. This study explored the general characteristics of the forehead profile and protrusion, and their relationship with related factors in structure and development. METHODS: Four hundred fourteen Chinese participants in the Yangtze River Delta region were involved. Including 206 males (17.15 ± 7.68 years old) and 208 females (18.35 ± 8.06 years old); 94 children (8.54 ± 2.21 years old, ranging from 4 to 12 years old), 166 adolescents (14.83 ± 1.50 years old, ranging from 13 to 17 years old), and 154 adults (25.52 ± 4.89, 18 years or older). The frontal section of the forehead was used to explore its shape. The straight distance between the vertical line of the FH plane through the nasal root point and its parallel line, which is tangential to the forehead, indicates the forehead prominence. Frontal sinus width was measured using the method described by Mahmood. RESULTS: The general shape of the forehead was straight and slightly bulged near the eyebrow arch in males but rounder in females. The average forehead protrusion in males was higher than that in females in adults. Significant differences in forehead protrusion between the dentoskeletal classifications and growth phases were notable. Frontal protrusion significantly correlated with frontal sinus depth, especially in males, adults, Class I, and those whose convex points were located in the lower section of the forehead. CONCLUSIONS: Age, race, and sex affect the forehead protrusion and frontal sinus width. Forehead protrusion may be an indicator of dentoskeletal deformities in the early stage. And dentoskeletal deformities may impair the correlation between the frontal sinuses and forehead protrusion during development. TRIAL REGISTRATION: This retrospective, cross-sectional study was reviewed and approved by the Research Ethical Committee (T2020008), and registered at ClinicalTrial.gov with an identified number (ChiCTR2100041913).

PI-RADSAI: introducing a new human-in-the-loop AI model for prostate cancer diagnosis based on MRI.

BACKGROUND: This study aims to develop and validate an artificial intelligence (AI)-aided Prostate Imaging Reporting and Data System (PI-RADSAI) for prostate cancer (PCa) diagnosis based on MRI. METHODS: The deidentified MRI data of 1540 biopsy-naïve patients were collected from four centres. PI-RADSAI is a two-stage, human-in-the-loop AI capable of emulating the diagnostic acumen of subspecialists for PCa on MRI. The first stage uses a UNet-Seg model to detect and segment biopsy-candidate prostate lesions, whereas the second stage leverages UNet-Seg segmentation is trained specifically with subspecialist' knowledge-guided 3D-Resnet to achieve an automatic AI-aided diagnosis for PCa. RESULTS: In the independent test set, UNet-Seg identified 87.2% (628/720) of target lesions, with a Dice score of 44.9% (range, 22.8-60.2%) in segmenting lesion contours. In the ablation experiment, the model trained with the data from three centres was superior (kappa coefficient, 0.716 vs. 0.531) to that trained with single-centre data. In the internal and external tests, the triple-centre PI-RADSAI model achieved an overall agreement of 58.4% (188/322) and 60.1% (92/153) with a referential subspecialist in scoring target lesions; when one-point margin of error was permissible, the agreement rose to 91.3% (294/322) and 97.3% (149/153), respectively. In the paired test, PI-RADSAI outperformed 5/11 (45.5%) and matched the performance of 3/11 (27.3%) general radiologists in achieving a clinically significant PCa diagnosis (area under the curve, internal test, 0.801 vs. 0.770, p < 0.01; external test, 0.833 vs. 0.867, p = 0.309). CONCLUSIONS: Our closed-loop PI-RADSAI outperforms or matches the performance of more than 70% of general readers in the MRI assessment of PCa. This system might provide an alternative to radiologists and offer diagnostic benefits to clinical practice, especially where subspecialist expertise is unavailable.

Partial GCK gene deletion mutations causing maturity-onset diabetes of the young.

AIMS: Maturity-onset diabetes of the young (MODY) is an autosomal dominant monogenic form of diabetes, and glucokinase-maturity-onset diabetes of the young (GCK-MODY), or MODY 2, being the most prevalent type. However, the presence of copy number variants (CNVs) may lead to misdiagnoses, as genetic testing for MODY is typically reliant on sequencing techniques. This study aimed to describe the process of diagnosis in a Chinese pedigree with an exon 8-10 deletion of the GCK gene. METHODS: This study collected clinical data and medical history through direct interviews with the patient and reviewing relevant medical records. Sanger sequencing and whole exome sequencing (WES) were conducted over years of follow up. WES-based CNV sequencing technology was used to detect CNVs and the results were validated by multiplex ligation-dependent amplification dosage assay (MLPA). Additionally, we reviewed the previously reported cases caused by heterozygous exon deletion of the GCK gene. RESULTS: WES-based CNV detection revealed a heterozygous exon 8-10 deletion in the GCK gene within this particular pedigree after Sanger sequencing and WES failed to find causal variants in single nucleotide variations (SNVs) and small indels. The deletion was considered pathogenic according to ACMG/AMP and ClinGen guidelines. Most of the previously reported cases caused by heterozygous exon deletion or whole gene deletion of the GCK gene present similarly to GCK-MODY caused by SNVs and small indels. CONCLUSIONS: This study contributed to progress in our comprehension of the mutation spectrum of the GCK gene and underscored the significance of CNV detection in the genetic testing of MODY.

Ten-year clinical characteristics of patients with early-onset type 2 diabetes: A single-center experience in China.

AIMS: The incidence of type 2 diabetes in China has exhibited an increasing trend, including younger individuals, over the past years. Early-onset type 2 diabetes (EOT2D) refers to diabetes diagnosed before 40 years of age. These patients have poor metabolic control and are highly susceptible to diabetic complications, which poses challenges for treatment. However, few studies have reported on the treatment of EOT2D. We determined clinical features and trends in drug use in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: This retrospective study was performed at the Endocrinology Ward, Peking Union Medical College Hospital (PUMCH). "Diabetes" was used when searching PUMCH's Electronic Medical Record Analytical Database to obtain clinical data of patients between January 2013 and May 2022. RESULTS: The analysis included 1590 patients with T2DM. Among them, 609 (38.3%) had EOT2D. Compared with late-onset type 2 diabetes (LOT2D) patients, EOT2D patients exhibited worse glycemic control and higher body weight and lipid levels despite significant age differences. EOT2D patients also had a higher risk of diabetic retinopathy and nephropathy. Under the general trend of increasing use of dipeptidylpeptidase-4 inhibitors, sodium-glucose cotransporter-2 inhibitors, and glucagon-like peptide-1 agonists, patients with EOT2D were more likely to use organ-protective drugs. CONCLUSIONS: Compared with LOT2D patients, EOT2D patients have a longer course of diabetes, worse metabolic control, and a higher rate of developing microvascular complications. The administration of combined therapy, including new agents, may require consideration when selecting hypoglycemic agents for treating EOT2D.

The small RNA PrrH aggravates Pseudomonas aeruginosa-induced acute lung injury by regulating the type III secretion system activator ExsA.

Pseudomonas aeruginosa is an opportunistic pathogen that causes acute and chronic infections in immunocompromised individuals. Small regulatory RNAs (sRNAs) regulate multiple bacterial adaptations to environmental changes, especially virulence. Our previous study showed that sRNA PrrH negatively regulates the expression of a number of virulence factors, such as pyocyanin, rhamnolipid, biofilm, and elastase in the P. aeruginosa strain PAO1. However, previous studies have shown that the prrH-deficient mutant attenuates virulence in an acute murine lung infection model. All ΔprrH-infected mice survived the entire 28-day course of the experiment, whereas all mice inoculated with the wild-type or the complemented mutant succumbed to lung infection within 4 days of injection, but the specific mechanism is unclear. Herein, we explored how PrrH mediates severe lung injury by regulating the expression of virulence factors. In vivo mouse and in vitro cellular assays demonstrated that PrrH enhanced the pathogenicity of PAO1, causing severe lung injury. Mechanistically, PrrH binds to the coding sequence region of the mRNA of exsA, which encodes the type III secretion system master regulatory protein. We further demonstrated that PrrH mediates a severe inflammatory response and exacerbates the apoptosis of A549 cells. Overall, our results revealed that PrrH positively regulates ExsA, enhances the pathogenicity of P. aeruginosa, and causes severe lung injury. IMPORTANCE: Pseudomonas aeruginosa is a Gram-negative bacterium and the leading cause of nosocomial pneumonia. The pathogenicity of P. aeruginosa is due to the secretion of many virulence factors. Small regulatory RNAs (sRNAs) regulate various bacterial adaptations, especially virulence. Therefore, understanding the mechanism by which sRNAs regulate virulence is necessary for understanding the pathogenicity of P. aeruginosa and the treatment of the related disease. In this study, we demonstrated that PrrH enhances the pathogenicity of P. aeruginosa by binding to the coding sequence regions of the ExsA, the master regulatory protein of type III secretion system, causing severe lung injury and exacerbating the inflammatory response and apoptosis. These findings revealed that PrrH is a crucial molecule that positively regulates ExsA. Type III-positive strains are often associated with a high mortality rate in P. aeruginosa infections in clinical practice. Therefore, this discovery may provide a new target for treating P. aeruginosa infections, especially type III-positive strains.

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.

Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway structures remains prohibitively time-consuming. While significant efforts have been made towards enhancing automatic airway modelling, current public-available datasets predominantly concentrate on lung diseases with moderate morphological variations. The intricate honeycombing patterns present in the lung tissues of fibrotic lung disease patients exacerbate the challenges, often leading to various prediction errors. To address this issue, the 'Airway-Informed Quantitative CT Imaging Biomarker for Fibrotic Lung Disease 2023' (AIIB23) competition was organized in conjunction with the official 2023 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). The airway structures were meticulously annotated by three experienced radiologists. Competitors were encouraged to develop automatic airway segmentation models with high robustness and generalization abilities, followed by exploring the most correlated QIB of mortality prediction. A training set of 120 high-resolution computerised tomography (HRCT) scans were publicly released with expert annotations and mortality status. The online validation set incorporated 52 HRCT scans from patients with fibrotic lung disease and the offline test set included 140 cases from fibrosis and COVID-19 patients. The results have shown that the capacity of extracting airway trees from patients with fibrotic lung disease could be enhanced by introducing voxel-wise weighted general union loss and continuity loss. In addition to the competitive image biomarkers for mortality prediction, a strong airway-derived biomarker (Hazard ratio>1.5, p < 0.0001) was revealed for survival prognostication compared with existing clinical measurements, clinician assessment and AI-based biomarkers.

CUL4B orchestrates mesenchymal stem cell commitment by epigenetically repressing KLF4 and C/EBPδ.

Dysregulated lineage commitment of mesenchymal stem cells (MSCs) contributes to impaired bone formation and an imbalance between adipogenesis and osteogenesis during skeletal aging and osteoporosis. The intrinsic cellular mechanism that regulates MSC commitment remains unclear. Here, we identified Cullin 4B (CUL4B) as a critical regulator of MSC commitment. CUL4B is expressed in bone marrow MSCs (BMSCs) and downregulated with aging in mice and humans. Conditional knockout of Cul4b in MSCs resulted in impaired postnatal skeletal development with low bone mass and reduced bone formation. Moreover, depletion of CUL4B in MSCs aggravated bone loss and marrow adipose accumulation during natural aging or after ovariectomy. In addition, CUL4B deficiency in MSCs reduced bone strength. Mechanistically, CUL4B promoted osteogenesis and inhibited adipogenesis of MSCs by repressing KLF4 and C/EBPδ expression, respectively. The CUL4B complex directly bound to Klf4 and Cebpd and epigenetically repressed their transcription. Collectively, this study reveals CUL4B-mediated epigenetic regulation of the osteogenic or adipogenic commitment of MSCs, which has therapeutic implications in osteoporosis.

Depletion of CUL4B in macrophages ameliorates diabetic kidney disease via miR-194-5p/ITGA9 axis.

Diabetic kidney disease (DKD) is the most prevalent chronic kidney disease. Macrophage infiltration in the kidney is critical for the progression of DKD. However, the underlying mechanism is far from clear. Cullin 4B (CUL4B) is the scaffold protein in CUL4B-RING E3 ligase complexes. Previous studies have shown that depletion of CUL4B in macrophages aggravates lipopolysaccharide-induced peritonitis and septic shock. In this study, using two mouse models for DKD, we demonstrate that myeloid deficiency of CUL4B alleviates diabetes-induced renal injury and fibrosis. In vivo and in vitro analyses reveal that loss of CUL4B suppresses migration, adhesion, and renal infiltration of macrophages. Mechanistically, we show that high glucose upregulates CUL4B in macrophages. CUL4B represses expression of miR-194-5p, which leads to elevated integrin α9 (ITGA9), promoting migration and adhesion. Our study suggests the CUL4B/miR-194-5p/ITGA9 axis as an important regulator for macrophage infiltration in diabetic kidneys.

The Effects of Dietary Nutrition Intake on Glycemic Variability in Type 1 Diabetes Mellitus Adults.

INTRODUCTION: Type 1 diabetes mellitus (T1DM) is characterized by an absolute deficiency of insulin and dependence on insulin therapy. Therefore, glycemic control and management are important for T1DM patients, particularly glycemic variability, which is associated with the development of diabetic complications. However, insufficient attention has been paid to the glycemic variability in T1DM patients so far. Our objective was to identify the effects of food intake on glycemic variability in T1DM patients. METHODS: This was a single-center study that took place in the outpatient clinics of Peking Union Medical College Hospital. A total of 68 Chinese T1DM patients between June 2018 and June 2019 were enrolled. After the baseline demographic and clinical characteristics were evaluated, each participant underwent 14-day flash glucose monitoring (FGM). They recorded caloric intake of breakfast, lunch, and dinner at least 3 days/week using a "Menthol Health" app. After 2 weeks, we obtained the FGM data and did further data analysis. Baseline characteristics and glycemic variability index generated by FGM were compared among groups. A general linear model was used to compare data among groups after adjusting for potential confounding factors. The quantitative relationship between two continuous variables was explored by constructing a linear regression equation. RESULTS: The results showed that the C-peptide level was independently correlated with the mean of daily differences (MODD) after adjusting for the possible confounders (ß = - 0.239, p = 0.046). The dietary nutrition intake had no effect on glycemic variability. However, the nutritional composition of carbohydrate, fat, and protein was an independent risk factor for time spent in hypoglycemia (TBR) post adjustment (ß = - 0.213, p = 0.054). However, there was no impact of daily total energy intake on glycemic variability index. CONCLUSION: In our study, dietary nutrition intake had no effect on glycemic variability, but residual ß-cell function was identified as an influencing factor for glycemic variability in T1DM adults. However, nutritional macronutrient composition played some roles in the occurrence of hypoglycemia. This might provide new evidence for the clinical glycemic control and management of T1DM in the Chinese population.