Sphingolipid metabolites as potential circulating biomarkers for sarcopenia in men.

BACKGROUND: Sarcopenia is an age-related progressive loss of muscle mass and function. Sarcopenia is a multifactorial disorder, including metabolic disturbance; therefore, metabolites may be used as circulating biomarkers for sarcopenia. We aimed to investigate potential biomarkers of sarcopenia using metabolomics. METHODS: After non-targeted metabolome profiling of plasma from mice of an aging mouse model of sarcopenia, sphingolipid metabolites and muscle cells from the animal model were evaluated using targeted metabolome profiling. The associations between sphingolipid metabolites identified from mouse and cell studies and sarcopenia status were assessed in men in an age-matched discovery (72 cases and 72 controls) and validation (36 cases and 128 controls) cohort; women with sarcopenia (36 cases and 36 controls) were also included as a discovery cohort. RESULTS: Both non-targeted and targeted metabolome profiling in the experimental studies showed an association between sphingolipid metabolites, including ceramides (CERs) and sphingomyelins (SMs), and sarcopenia. Plasma SM (16:0), CER (24:1), and SM (24:1) levels in men with sarcopenia were significantly higher in the discovery cohort than in the controls (all P < 0.05). There were no significant differences in plasma sphingolipid levels for women with or without sarcopenia. In men in the discovery cohort, an area under the receiver-operating characteristic curve (AUROC) of SM (16:0) for low muscle strength and low muscle mass was 0.600 (95% confidence interval [CI]: 0.501-0.699) and 0.647 (95% CI: 0.557-0.737). The AUROC (95% CI) of CER (24:1) and SM (24:1) for low muscle mass in men was 0.669 (95% CI: 0.581-0.757) and 0.670 (95% CI: 0.582-0.759), respectively. Using a regression equation combining CER (24:1) and SM (16:0) levels, a sphingolipid (SphL) score was calculated; an AUROC of the SphL score for sarcopenia was 0.712 (95% CI: 0.626-0.798). The addition of the SphL score to HGS significantly improved the AUC from 0.646 (95% CI: 0.575-0.717; HGS only) to 0.751 (95% CI: 0.671-0.831, P = 0.002; HGS + SphL) in the discovery cohort. The predictive ability of the SphL score for sarcopenia was confirmed in the validation cohort (AUROC = 0.695, 95% CI: 0.591-0.799). CONCLUSIONS: SM (16:0), reflecting low muscle strength, and CER (24:1) and SM (16:0), reflecting low muscle mass, are potential circulating biomarkers for sarcopenia in men. Further research on sphingolipid metabolites is required to confirm these results and provide additional insights into the metabolomic changes relevant to the pathogenesis and diagnosis of sarcopenia.

In vivo adenine base editing rescues adrenoleukodystrophy in a humanized mouse model.

X-linked adrenoleukodystrophy (ALD), an inherited neurometabolic disorder caused by mutations in ABCD1, which encodes the peroxisomal ABC transporter, mainly affects the brain, spinal cord, adrenal glands, and testes. In ALD patients, very-long-chain fatty acids (VLCFAs) fail to enter the peroxisome and undergo subsequent ß-oxidation, resulting in their accumulation in the body. It has not been tested whether in vivo base editing or prime editing can be harnessed to ameliorate ALD. We developed a humanized mouse model of ALD by inserting a human cDNA containing the pathogenic variant into the mouse Abcd1 locus. The humanized ALD model showed increased levels of VLCFAs. To correct the mutation, we tested both base editing and prime editing and found that base editing using ABE8e(V106W) could correct the mutation in patient-derived fibroblasts at an efficiency of 7.4%. Adeno-associated virus (AAV)-mediated systemic delivery of NG-ABE8e(V106W) enabled robust correction of the pathogenic variant in the mouse brain (correction efficiency: ∼5.5%), spinal cord (∼5.1%), and adrenal gland (∼2%), leading to a significant reduction in the plasma levels of C26:0/C22:0. This established humanized mouse model and the successful correction of the pathogenic variant using a base editor serve as a significant step toward treating human ALD disease.

Associations between plasma metabolites and heavy metal exposure in residents of environmentally polluted areas.

Heavy metals are commonly released into the environment through industrial processes such as mining and refining. The rapid industrialization that occurred in South Korea during the 1960s and 1970s contributed significantly to the economy of the country; however, the associated mining and refining led to considerable environmental pollution, and although mining is now in decline in South Korea, the detrimental effects on residents inhabiting the surrounding areas remain. The bioaccumulation of toxic heavy metals leads to metabolic alterations in human homeostasis, with disruptions in this balance leading to various health issues. This study used metabolomics to explore metabolomic alterations in the plasma samples of residents living in mining and refining areas. The results showed significant increases in metabolites involved in glycolysis and the surrounding metabolic pathways, such as glucose-6-phosphate, phosphoenolpyruvate, lactate, and inosine monophosphate, in those inhabiting polluted areas. An investigation of the associations between metabolites and blood clinical parameters through meet-in-the-middle analysis indicated that female residents were more affected by heavy metal exposure, resulting in more metabolomic alterations. For women, inhabiting the abandoned mine area, metabolites in the glycolysis and pentose phosphate pathways, such as ribose-5-phosphate and 3-phosphoglycerate, have shown a negative correlation with albumin and calcium. Finally, Mendelian randomization(MR) was used to determine the causal effects of these heavy metal exposure-related metabolites on heavy metal exposure-related clinical parameters. Metabolite biomarkers could provide insights into altered metabolic pathways related to exposure to toxic heavy metals and improve our understanding of the molecular mechanisms underlying the health effects of toxic heavy metal exposure.

Accuracy of posteroanterior cephalogram landmarks and measurements identification using a cascaded convolutional neural network algorithm: A multicenter study.

Objective: : To quantify the effects of midline-related landmark identification on midline deviation measurements in posteroanterior (PA) cephalograms using a cascaded convolutional neural network (CNN). Methods: : A total of 2,903 PA cephalogram images obtained from 9 university hospitals were divided into training, internal validation, and test sets (n = 2,150, 376, and 377). As the gold standard, 2 orthodontic professors marked the bilateral landmarks, including the frontozygomatic suture point and latero-orbitale (LO), and the midline landmarks, including the crista galli, anterior nasal spine (ANS), upper dental midpoint (UDM), lower dental midpoint (LDM), and menton (Me). For the test, Examiner-1 and Examiner-2 (3-year and 1-year orthodontic residents) and the Cascaded-CNN models marked the landmarks. After point-to-point errors of landmark identification, the successful detection rate (SDR) and distance and direction of the midline landmark deviation from the midsagittal line (ANS-mid, UDM-mid, LDM-mid, and Me-mid) were measured, and statistical analysis was performed. Results: : The cascaded-CNN algorithm showed a clinically acceptable level of point-to-point error (1.26 mm vs. 1.57 mm in Examiner-1 and 1.75 mm in Examiner-2). The average SDR within the 2 mm range was 83.2%, with high accuracy at the LO (right, 96.9%; left, 97.1%), and UDM (96.9%). The absolute measurement errors were less than 1 mm for ANS-mid, UDM-mid, and LDM-mid compared with the gold standard. Conclusions: : The cascaded-CNN model may be considered an effective tool for the auto-identification of midline landmarks and quantification of midline deviation in PA cephalograms of adult patients, regardless of variations in the image acquisition method.

Internal structural analysis of the nasomaxillary complex in patients with skeletal class III asymmetry: A study on asymmetry patterns.

OBJECTIVES: To investigate the internal structure of the nasomaxillary complex, including the maxillary sinus, nasal cavity and nasal septum according to the facial asymmetry pattern and to evaluate its correlation with external maxillomandibular asymmetry in Class III patients based on cone-beam computerized tomography (CBCT) images. MATERIALS AND METHODS: Facial asymmetry was analysed in a total of 100 Class III patients aged 16 years or older using CBCT scans. Patients were categorized into subgroups based on asymmetry pattern. Measurements of the nasomaxillary complex were obtained from the CBCT scans, including the volume and width of the maxillary sinuses and nasal cavities on deviated and non-deviated sides, as well as the displacement of the nasal septum. Statistical analysis was performed to compare the internal nasomaxillary variables within and between groups, and regression analysis was conducted to evaluate the correlation between facial asymmetry and the internal nasomaxillary variables. RESULTS: Group comparisons showed that there were no significant differences in the volume of the maxillary sinus and nasal cavity. However, the direction and extent of nasal septum deviation, as well as the width of the nasal cavity, varied depending on the maxillary asymmetry pattern. Regression analysis indicated a correlation between nasal septum deviation and the difference in maxillary height, while the difference in nasal cavity width was correlated with the difference in maxillary width. CONCLUSION: A comprehensive evaluation of the internal nasal anatomy is vital for understanding the intricate relationship between nasal structure and maxillary growth.

Significant Reduction in External Ventricular Drain-Related Infections After Introducing a Novel Bundle Protocol: A Before and After Trial.

BACKGROUND: External ventricular drain (EVD)-related infection (ERI) is a serious complication in neurosurgical patients. The estimated ERI rates range from 5 to 20 cases per 1,000 EVD catheter days. The pathophysiology of ERI is similar to central line-associated bloodstream infections (CLABSIs) stemming from skin-derived bacterial colonization. The use of bundle management can reduce CLABSI rates. Due to the pathogenic similarities between infections related to the two devices, we developed and evaluated the effectiveness of an ERI-bundle protocol based on CLABSI bundles. METHODS: From November 2016 to November 2021, we conducted a study to evaluate the effectiveness of an ERI-bundle protocol. This study adopted a before-and-after trial, comparing the ERI rates for the 2 years before and 3 years after the introduction of the newly developed ERI-bundle protocol. We also analyzed the contributing factors to ERI using logistic regression analysis. RESULTS: A total of 183 patients with 2,381 days of catheter use were analyzed. The ERI rate decreased significantly after the ERI-bundle protocol from 16.7% (14 of 84; 14.35 per 1,000 catheter days) to 4.0% (4 of 99; 3.21 per 1,000 catheter days) (P = 0.004). CONCLUSION: Introduction of the ERI-bundle protocol was very effective in reducing ERI.

Reduced Ceramides Are Associated with Acute Rejection in Liver Transplant Patients and Skin Graft and Hepatocyte Transplant Mice, Reducing Tolerogenic Dendritic Cells.

We set up this study to understand the underlying mechanisms of reduced ceramides on immune cells in acute rejection (AR). The concentrations of ceramides and sphingomyelins were measured in the sera from hepatic transplant patients, skin graft mice and hepatocyte transplant mice by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Serum concentrations of C24 ceramide, C24:1 ceramide, C16:0 sphingomyelin, and C18:1 sphingomyelin were lower in liver transplantation (LT) recipients with than without AR. Comparisons with the results of LT patients with infection and cardiac transplant patients with cardiac allograft vasculopathy in humans and in mouse skin graft and hepatocyte transplant models suggested that the reduced C24 and C24:1 ceramides were specifically involved in AR. A ceramide synthase inhibitor, fumonisin B1 exacerbated allogeneic immune responses in vitro and in vivo, and reduced tolerogenic dendritic cells (tDCs), while increased P3-like plasmacytoid DCs (pDCs) in the draining lymph nodes from allogeneic skin graft mice. The results of mixed lymphocyte reactions with ceranib-2, an inhibitor of ceramidase, and C24 ceramide also support that increasing ceramide concentrations could benefit transplant recipients with AR. The results suggest increasing ceramides as novel therapeutic target for AR, where reduced ceramides were associated with the changes in DC subsets, in particular tDCs.

The prediction of sagittal chin point relapse following two-jaw surgery using machine learning.

The study aimed to identify critical factors associated with the surgical stability of pogonion (Pog) by applying machine learning (ML) to predict relapse following two-jaw orthognathic surgery (2 J-OGJ). The sample set comprised 227 patients (110 males and 117 females, 207 training and 20 test sets). Using lateral cephalograms taken at the initial evaluation (T0), pretreatment (T1), after (T2) 2 J-OGS, and post treatment (T3), 55 linear and angular skeletal and dental surgical movements (T2-T1) were measured. Six ML modes were utilized, including classification and regression trees (CART), conditional inference tree (CTREE), and random forest (RF). The training samples were classified into three groups; highly significant (HS) (≥ 4), significant (S) (≥ 2 and < 4), and insignificant (N), depending on Pog relapse. RF indicated that the most important variable that affected relapse rank prediction was ramus inclination (RI), CTREE and CART revealed that a clockwise rotation of more than 3.7 and 1.8 degrees of RI was a risk factor for HS and S groups, respectively. RF, CTREE, and CART were practical tools for predicting surgical stability. More than 1.8 degrees of CW rotation of the ramus during surgery would lead to significant Pog relapse.

Screening obstructive sleep apnea patients via deep learning of knowledge distillation in the lateral cephalogram.

The lateral cephalogram in orthodontics is a valuable screening tool on undetected obstructive sleep apnea (OSA), which can lead to consequences of severe systematic disease. We hypothesized that a deep learning-based classifier might be able to differentiate OSA as anatomical features in lateral cephalogram. Moreover, since the imaging devices used by each hospital could be different, there is a need to overcome modality difference of radiography. Therefore, we proposed a deep learning model with knowledge distillation to classify patients into OSA and non-OSA groups using the lateral cephalogram and to overcome modality differences simultaneously. Lateral cephalograms of 500 OSA patients and 498 non-OSA patients from two different devices were included. ResNet-50 and ResNet-50 with a feature-based knowledge distillation models were trained and their performances of classification were compared. Through the knowledge distillation, area under receiver operating characteristic curve analysis and gradient-weighted class activation mapping of knowledge distillation model exhibits high performance without being deceived by features caused by modality differences. By checking the probability values predicting OSA, an improvement in overcoming the modality differences was observed, which could be applied in the actual clinical situation.

Orthognathic surgical planning using graph CNN with dual embedding module: External validations with multi-hospital datasets.

BACKGROUND AND OBJECTIVE: Despite recent development of AI, prediction of the surgical movement in the maxilla and mandible by OGS might be more difficult than that of tooth movement by orthodontic treatment. To evaluate the prediction accuracy of the surgical movement using pairs of pre-(T0) and post-surgical (T1) lateral cephalograms (lat-ceph) of orthognathic surgery (OGS) patients and dual embedding module-graph convolution neural network (DEM-GCNN) model. METHODS: 599 pairs from 3 institutions were used as training, internal validation, and internal test sets and 201 pairs from other 6 institutions were used as external test set. DEM-GCNN model (IEM, learning the lat-ceph images; LTEM, learning the landmarks) was developed to predict the amount and direction of surgical movement of ANS and PNS in the maxilla and B-point and Md1crown in the mandible. The distance between T1 landmark coordinates actually moved by OGS (ground truth) and predicted by DEM-GCNN model and pre-existed CNN-based Model-C (learning the lat-ceph images) was compared. RESULTS: In both internal and external tests, DEM-GCNN did not exhibit significant difference from ground truth in all landmarks (ANS, PNS, B-point, Md1crown, all P > 0.05). When the accumulated successful detection rate for each landmark was compared, DEM-GCNN showed higher values than Model-C in both the internal and external tests. In violin plots exhibiting the error distribution of the prediction results, both internal and external tests showed that DEM-GCNN had significant performance improvement in PNS, ANS, B-point, Md1crown than Model-C. DEM-GCNN showed significantly lower prediction error values than Model-C (one-jaw surgery, B-point, Md1crown, all P < 0.005; two-jaw surgery, PNS, ANS, all P < 0.05; B point, Md1crown, all P < 0.005). CONCLUSION: We developed a robust OGS planning model with maximized generalizability despite diverse qualities of lat-cephs from 9 institutions.

Systemic antibiotics cause deterioration of emphysema associated with exaggerated inflammation and autophagy.

The interaction between the microbial environment and the host is important for immune homeostasis. Recent research suggests that microbiota dysbiosis can be involved in respiratory diseases. Emphysema is a chronic inflammatory disease, but it is unclear whether dysbiosis caused by antibiotics can affect disease progression. Here, we tried to elucidate the effect of systemic antibiotics on smoking-exposed emphysema models. In this study, the antibiotic mixture caused more alveolar destruction and airspace expansion in the smoking group than in the smoking only or control groups. This emphysema aggravation as a result of antibiotic exposure was associated with increased levels of inflammatory cells, IL-6, IFNγ and protein concentrations in bronchoalveolar lavage fluid. Proteomics analysis indicated that autophagy could be involved in antibiotic-associated emphysema aggravation, and increased protein levels of LC3B, atg3, and atg7 were identified by Western blotting. In microbiome and metabolome analyses, the composition of the gut microbiota was different with smoking and antibiotic exposure, and the levels of short-chain fatty acids (SCFAs), including acetate and propionate, were reduced by antibiotic exposure. SCFA administration restored emphysema development with reduced inflammatory cells, IL-6, and IFNγ and decreased LC3B, atg3, and atg7 levels. In conclusion, antibiotics can aggravate emphysema, and inflammation and autophagy may be associated with this aggravation. This study provides important insight into the systemic impact of microbial dysbiosis and the therapeutic potential of utilizing the gut microbiota in emphysema.

Firing of Replication Origins Is Disturbed by a CDK4/6 Inhibitor in a pRb-Independent Manner.

Over the last decade, CDK4/6 inhibitors (palbociclib, ribociclib and abemaciclib) have emerged as promising anticancer drugs. Numerous studies have demonstrated that CDK4/6 inhibitors efficiently block the pRb-E2F pathway and induce cell cycle arrest in pRb-proficient cells. Based on these studies, the inhibitors have been approved by the FDA for treatment of advanced hormonal receptor (HR) positive breast cancers in combination with hormonal therapy. However, some evidence has recently shown unexpected effects of the inhibitors, underlining a need to characterize the effects of CDK4/6 inhibitors beyond pRb. Our study demonstrates how palbociclib impairs origin firing in the DNA replication process in pRb-deficient cell lines. Strikingly, despite the absence of pRb, cells treated with palbociclib synthesize less DNA while showing no cell cycle arrest. Furthermore, this CDK4/6 inhibitor treatment disturbs the temporal program of DNA replication and reduces the density of replication forks. Cells treated with palbociclib show a defect in the loading of the Pre-initiation complex (Pre-IC) proteins on chromatin, indicating a reduced initiation of DNA replication. Our findings highlight hidden effects of palbociclib on the dynamics of DNA replication and of its cytotoxic consequences on cell viability in the absence of pRb. This study provides a potential therapeutic application of palbociclib in combination with other drugs to target genomic instability in pRB-deficient cancers.

Oxygen-independent stabilization of HIF-2α in breast cancer through direct interaction with peptidyl-prolyl cis-trans isomerase NIMA-interacting 1.

Peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (Pin1) isomerizes the nearby proline (Pro) residue when it detects phosphorylated serine (Ser) or threonine (Thr) of target proteins, altering their structure, stability, function, and interaction with other proteins. Hypoxia-inducible factor 2α (HIF-2α), a transcription factor that transactivates many oncogenic genes under hypoxic conditions, harbours the pSer/Thr-Pro motif. We found for the first time that Pin1 binds to HIF-2α physically in normoxic as well as hypoxic conditions in human breast cancer cells. The level of ubiquitinated HIF-2α was significantly raised by Pin1 knockdown, while expression of its mRNA transcript was unaffected. In agreement with this observation, the cycloheximide chase assay demonstrated that Pin1 prolonged the stability of HIF-2α. Serine 672, 696, and 790 of HIF-2α were found to undergo phosphorylation. Of these, the main amino acid involved in the Pin1 binding and HIF-2α stabilization was identified as serine 790, located in the nuclear export signal region of HIF-2α. The tissue array with human breast cancer specimens showed elevated expression of HIF-2α as well as Pin1 compared to adjacent normal tissues. Knockdown of Pin1 or HIF-2α diminished breast cancer cell migration and colony formation. In conclusion, Pin1 stabilizes HIF-2α through direct interaction, which contributes to the growth of breast cancer.

Comparison of translucency, thickness, and gap width of thermoformed and 3D-printed clear aligners using micro-CT and spectrophotometer.

The present study compared the thickness and gap width of thermoformed and 3D-printed clear aligners (CAs) using micro-computed tomography (micro-CT) and evaluated their translucency using spectrophotometer. Four groups of CAs were tested: thermoformed with polyethylene terephthalate glycol (TS) or copolyester-elastomer combination (TM), and 3D-printed TC-85 cleaned with alcohol (PA) or with centrifuge (PC). CIELab coordinates were measured (n = 10) to evaluate translucency. CAs (n = 10) were fitted onto respective models and micro-CT was performed to evaluate the thickness and gap width. Thickness and gap width were measured for different tooth type and location in sagittal sections on all sides. The PC group showed significantly higher translucency than the PA group, which was similar to the TS and TM groups (p < 0.01). After the manufacturing process, thickness reduction was observed in the thermoformed groups, whereas thickness increase was observed in the 3D printed-groups. The TM group showed the least gap width amongst the groups (p < 0.01). Thermoformed and 3D-printed CAs had significantly varied thicknesses and regions of best fit depending on the tooth type and location. Differences in the translucency and thickness of the 3D-printed CAs were observed depending on the cleaning methods.

A targeted metabolomics approach for sepsis-induced ARDS and its subphenotypes.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is etiologically and clinically a heterogeneous disease. Its diagnostic characteristics and subtype classification, and the application of these features to treatment, have been of considerable interest. Metabolomics is becoming important for identifying ARDS biology and distinguishing its subtypes. This study aimed to identify metabolites that could distinguish sepsis-induced ARDS patients from non-ARDS controls, using a targeted metabolomics approach, and to identify whether sepsis-induced direct and sepsis-induced indirect ARDS are metabolically distinct groups, and if so, confirm their metabolites and associated pathways. METHODS: This study retrospectively analyzed 54 samples of ARDS patients from a sepsis registry that was prospectively collected from March 2011 to February 2018, along with 30 non-ARDS controls. The cohort was divided into direct and indirect ARDS. Metabolite concentrations of five analyte classes (energy metabolism, free fatty acids, amino acids, phospholipids, sphingolipids) were measured using liquid chromatography-tandem mass spectrometry and gas chromatography-mass spectrometry by targeted metabolomics. RESULTS: In total, 186 metabolites were detected. Among them, 102 metabolites could differentiate sepsis-induced ARDS patients from the non-ARDS controls, while 14 metabolites could discriminate sepsis-induced ARDS subphenotypes. Using partial least-squares discriminant analysis, we showed that sepsis-induced ARDS patients were metabolically distinct from the non-ARDS controls. The main distinguishing metabolites were lysophosphatidylethanolamine (lysoPE) plasmalogen, PE plasmalogens, and phosphatidylcholines (PCs). Sepsis-induced direct and indirect ARDS were also metabolically distinct subgroups, with differences in lysoPCs. Glycerophospholipid and sphingolipid metabolism were the most significant metabolic pathways involved in sepsis-induced ARDS biology and in sepsis-induced direct/indirect ARDS, respectively. CONCLUSION: Our study demonstrated a marked difference in metabolic patterns between sepsis-induced ARDS patients and non-ARDS controls, and between sepsis-induced direct and indirect ARDS subpheonotypes. The identified metabolites and pathways can provide clues relevant to the diagnosis and treatment of individuals with ARDS.

Aquaporin-4 Deficiency is Associated with Cognitive Impairment and Alterations in astrocyte-neuron Lactate Shuttle.

Cognitive impairment refers to notable declines in cognitive abilities including memory, language, and emotional stability leading to the inability to accomplish essential activities of daily living. Astrocytes play an important role in cognitive function, and homeostasis of the astrocyte-neuron lactate shuttle (ANLS) system is essential for maintaining cognitive functions. Aquaporin-4 (AQP-4) is a water channel expressed in astrocytes and has been shown to be associated with various brain disorders, but the direct relationship between learning, memory, and AQP-4 is unclear. We examined the relationship between AQP-4 and cognitive functions related to learning and memory. Mice with genetic deletion of AQP-4 showed significant behavioral and emotional changes including hyperactivity and instability, and impaired cognitive functions such as spatial learning and memory retention. 18 F-FDG PET imaging showed significant metabolic changes in the brains of AQP-4 knockout mice such as reductions in glucose absorption. Such metabolic changes in the brain seemed to be the direct results of changes in the expression of metabolite transporters, as the mRNA levels of multiple glucose and lactate transporters in astrocytes and neurons were significantly decreased in the cortex and hippocampus of AQP-4 knockout mice. Indeed, AQP-4 knockout mice showed significantly higher accumulation of both glucose and lactate in their brains compared with wild-type mice. Our results show that the deficiency of AQP-4 can cause problems in the metabolic function of astrocytes and lead to cognitive impairment, and that the deficiency of AQP4 in astrocyte endfeet can cause abnormalities in the ANLS system.

Gut microbiota composition and metabolite profiling in smokers: a comparative study between emphysema and asymptomatic individuals with therapeutic implications.

BACKGROUND: Diet has a crucial role in the gut microbiota, and dysbiosis in the gut and lungs has been suggested to be associated with chronic obstructive pulmonary disease. We compared the diet, microbiome and metabolome between asymptomatic smokers and those with emphysema. METHODS: We enrolled 10 asymptomatic smokers with preserved lung function and 16 smokers with emphysema with severe airflow limitation. Dietary intake information was gathered by a self-reported questionnaire. Sputum and faecal samples were collected for microbial and metabolomics analysis. A murine model of emphysema was used to determine the effect of metabolite supplementation. RESULTS: Despite having a similar smoking history with emphysema patients, asymptomatic smokers had higher values of body mass index, fibre intake and faecal acetate level. Linear discriminant analysis identified 17 microbial taxonomic members that were relatively enriched in the faeces of asymptomatic smokers. Analysis of similarity results showed dissimilarity between the two groups (r=0.287, p=0.003). Higher acetate level was positively associated with forced expiratory volume in one second in the emphysema group (r=0.628, p=0.012). Asymptomatic smokers had a greater number of species associated with acetate and propionate (r>0.6) than did those with emphysema (30 vs 19). In an emphysema mouse model, supplementation of acetate and propionate reduced alveolar destruction and the production of proinflammatory cytokines, and propionate decreased the CD3+CD4+IL-17+ T-cell population in the lung and spleen. CONCLUSION: Smokers with emphysema showed differences in diet, microbiome and short-chain fatty acids compared with asymptomatic smokers. Acetate and propionate showed therapeutic effects in a smoking-induced murine model of emphysema.

Subregional pharyngeal changes after orthognathic surgery in skeletal Class III patients analyzed by convolutional neural networks-based segmentation.

OBJECTIVES: To evaluate the accuracy of fully automatic segmentation of pharyngeal volume of interests (VOIs) before and after orthognathic surgery in skeletal Class III patients using a convolutional neural network (CNN) model and to investigate the clinical applicability of artificial intelligence for quantitative evaluation of treatment changes in pharyngeal VOIs. METHODS: 310 cone-beam computed tomography (CBCT) images were divided into a training set (n = 150), validation set (n = 40), and test set (n = 120). The test datasets comprised matched pairs of pre- and post-treatment images of 60 skeletal Class III patients (mean age 23.1 ± 5.0 years; ANB<-2°) who underwent bimaxillary orthognathic surgery with orthodontic treatment. A 3D U-Net CNNs model was applied for fully automatic segmentation and measurement of subregional pharyngeal volumes of pre-treatment (T0) and post-treatment (T1) scans. The model's accuracy was compared to semi-automatic segmentation outcomes by humans using the dice similarity coefficient (DSC) and volume similarity (VS). The correlation between surgical skeletal changes and model accuracy was obtained. RESULTS: The proposed model achieved high performance of subregional pharyngeal segmentation on both T0 and T1 images, representing a significant T1-T0 difference of DSC only in the nasopharynx. Region-specific differences amongst pharyngeal VOIs, which were observed at T0, disappeared on the T1 images. The decreased DSC of nasopharyngeal segmentation after treatment was weakly correlated with the amount of maxillary advancement. There was no correlation between the mandibular setback amount and model accuracy. CONCLUSIONS: The proposed model offers fast and accurate subregional pharyngeal segmentation on both pre-treatment and post-treatment CBCT images in skeletal Class III patients. CLINICAL SIGNIFICANCE: We elucidated the clinical applicability of the CNNs model to quantitatively evaluate subregional pharyngeal changes after surgical-orthodontic treatment, which offers a basis for developing a fully integrated multiclass CNNs model to predict pharyngeal responses after dentoskeletal treatments.