Ganoderma tsuage promotes pain sensitivity in aging mice.

Advances in modern medicine have extended human life expectancy, leading to a world with a gradually aging society. Aging refers to a natural decline in the physiological functions of a species over time, such as reduced pain sensitivity and reaction speed. Healthy-level physiological pain serves as a warning signal to the body, helping to avoid noxious stimuli. Physiological pain sensitivity gradually decreases in the elderly, increasing the risk of injury. Therefore, geriatric health care receives growing attention, potentially improving the health status and life quality of the elderly, further reducing medical burden. Health food is a geriatric healthcare choice for the elderly with Ganoderma tsuage (GT), a Reishi type, as the main product in the market. GT contains polysaccharides, triterpenoids, adenosine, immunoregulatory proteins, and other components, including anticancer, blood sugar regulating, antioxidation, antibacterial, antivirus, and liver and stomach damage protective agents. However, its pain perception-related effects remain elusive. This study thus aimed at addressing whether GT could prevent pain sensitivity reduction in the elderly. We used a galactose-induced animal model for aging to evaluate whether GT could maintain pain sensitivity in aging mice undergoing formalin pain test, hot water test, and tail flexes. Our results demonstrated that GT significantly improved the sensitivity and reaction speed to pain in the hot water, hot plate, and formalin tests compared with the control. Therefore, our animal study positions GT as a promising compound for pain sensitivity maintenance during aging.

Profile of a Multivariate Observation under Destructive Sampling-A Monte Carlo Approach to a Case of Spina Bifida.

A biodegradable hybrid polymer patch was invented at the University of Cincinnati to cover gaps on the skin over the spinal column of a growing fetus, characterized by the medical condition spina bifida. The inserted patch faces amniotic fluid (AF) on one side and cerebrospinal fluid on the other side. The goal is to provide a profile of the roughness of a patch over time at 0, 4, 8, 12, and 16 weeks with a 95% confidence band. The patch is soaked in a test tube filled with either amniotic fluid (AF) or phosphate-buffered saline (PBS) in the lab. If roughness is measured at any time point for a patch, the patch is destroyed. Thus, it is impossible to measure roughness at all weeks of interest for any patch. It is important to assess the roughness of a patch because the rougher the patch is, the faster the skin grows under the patch. We use a model-based approach with Monte Carlo simulations to estimate the profile over time with a 95% confidence band. The roughness profiles are similar with both liquids. The profile can be used as a template for future experiments on the composition of patches.

Development of a modified 3D region proposal network for lung nodule detection in computed tomography scans: a secondary analysis of lung nodule datasets.

BACKGROUND: Low-dose computed tomography (LDCT) has been shown useful in early lung cancer detection. This study aimed to develop a novel deep learning model for detecting pulmonary nodules on chest LDCT images. METHODS: In this secondary analysis, three lung nodule datasets, including Lung Nodule Analysis 2016 (LUNA16), Lung Nodule Received Operation (LNOP), and Lung Nodule in Health Examination (LNHE), were used to train and test deep learning models. The 3D region proposal network (RPN) was modified via a series of pruning experiments for better predictive performance. The performance of each modified deep leaning model was evaluated based on sensitivity and competition performance metric (CPM). Furthermore, the performance of the modified 3D RPN trained on three datasets was evaluated by 10-fold cross validation. Temporal validation was conducted to assess the reliability of the modified 3D RPN for detecting lung nodules. RESULTS: The results of pruning experiments indicated that the modified 3D RPN composed of the Cross Stage Partial Network (CSPNet) approach to Residual Network (ResNet) Xt (CSP-ResNeXt) module, feature pyramid network (FPN), nearest anchor method, and post-processing masking, had the optimal predictive performance with a CPM of 92.2%. The modified 3D RPN trained on the LUNA16 dataset had the highest CPM (90.1%), followed by the LNOP dataset (CPM: 74.1%) and the LNHE dataset (CPM: 70.2%). When the modified 3D RPN trained and tested on the same datasets, the sensitivities were 94.6%, 84.8%, and 79.7% for LUNA16, LNOP, and LNHE, respectively. The temporal validation analysis revealed that the modified 3D RPN tested on LNOP test set achieved a CPM of 71.6% and a sensitivity of 85.7%, and the modified 3D RPN tested on LNHE test set had a CPM of 71.7% and a sensitivity of 83.5%. CONCLUSION: A modified 3D RPN for detecting lung nodules on LDCT scans was designed and validated, which may serve as a computer-aided diagnosis system to facilitate lung nodule detection and lung cancer diagnosis.

A modified 3D RPN for detecting lung nodules on CT images that exhibited greater sensitivity and CPM than did several previously reported CAD detection models was established.

Therapeutic Decision Making in Prevascular Mediastinal Tumors Using CT Radiomics and Clinical Features: Upfront Surgery or Pretreatment Needle Biopsy?

The study aimed to develop machine learning (ML) classification models for differentiating patients who needed direct surgery from patients who needed core needle biopsy among patients with prevascular mediastinal tumor (PMT). Patients with PMT who received a contrast-enhanced computed tomography (CECT) scan and initial management for PMT between January 2010 and December 2020 were included in this retrospective study. Fourteen ML algorithms were used to construct candidate classification models via the voting ensemble approach, based on preoperative clinical data and radiomic features extracted from the CECT. The classification accuracy of clinical diagnosis was 86.1%. The first ensemble learning model was built by randomly choosing seven ML models from a set of fourteen ML models and had a classification accuracy of 88.0% (95% CI = 85.8 to 90.3%). The second ensemble learning model was the combination of five ML models, including NeuralNetFastAI, NeuralNetTorch, RandomForest with Entropy, RandomForest with Gini, and XGBoost, and had a classification accuracy of 90.4% (95% CI = 87.9 to 93.0%), which significantly outperformed clinical diagnosis (p < 0.05). Due to the superior performance, the voting ensemble learning clinical-radiomic classification model may be used as a clinical decision support system to facilitate the selection of the initial management of PMT.

Probiotic supplementation modifies the gut microbiota profile of very low birth weight preterm infants during hospitalization.

BACKGROUND: Probiotic supplementation is increasingly being given to very low birth weight (VLBW) preterm infants. This preliminary observational study aimed to investigate the effects of multiple-strain probiotics on the gut microbiota of VLBW preterm infants. METHODS: We collected meconium and stool samples on days 14, 30, and 60 after birth from 49 VLBW infants with a gestational age of <32 weeks. The infants were divided into the probiotics (n = 24) and control (n = 25) groups. The microbial composition and diversity in the gut of the two groups were analyzed using 16 S rRNA gene sequencing. RESULTS: The relative abundance of Bifidobacterium and Lactobacillus was significantly higher in the probiotics group than in the control group on days 14, 30, and 60 (Bifidobacterium: p = 0.002, p < 0.0001, and p < 0.0001, respectively; Lactobacillus: p = 0.012, p < 0.0001, and p < 0.0001, respectively). The control group exhibited a significantly higher proportion of participants with a low abundance (<1%) of Bifidobacterium or Lactobacillus on days 14, 30, and 60 than those in the probiotic group. Moreover, the probiotics group exhibited a significantly lower abundance of Klebsiella on days 14 and 30 (2.4% vs. 11.6%, p = 0.037; and 7.9% vs. 16.6%, p = 0.032, respectively) and of Escherichia-Shigella on day 60 than the control group (6.1% vs. 12.3%, p = 0.013). Beta diversity analysis revealed that the microbiota profile was clearly divided into two groups on days 30 and 60 (p = 0.001). CONCLUSION: Probiotic supplementation significantly increased the relative abundance of Bifidobacterium and Lactobacillus and inhibited the growth of potential pathogens. Furthermore, probiotic supplementation led to a distinct gut microbiota profile. Further research is needed to identify probiotic strains that exert significant influence on the gut microbiome and their long-term health implications in preterm infants.

Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT.

OBJECTIVES: The study aimed to develop a combined model that integrates deep learning (DL), radiomics, and clinical data to classify lung nodules into benign or malignant categories, and to further classify lung nodules into different pathological subtypes and Lung Imaging Reporting and Data System (Lung-RADS) scores. MATERIALS AND METHODS: The proposed model was trained, validated, and tested using three datasets: one public dataset, the Lung Nodule Analysis 2016 (LUNA16) Grand challenge dataset (n = 1004), and two private datasets, the Lung Nodule Received Operation (LNOP) dataset (n = 1027) and the Lung Nodule in Health Examination (LNHE) dataset (n = 1525). The proposed model used a stacked ensemble model by employing a machine learning (ML) approach with an AutoGluon-Tabular classifier. The input variables were modified 3D convolutional neural network (CNN) features, radiomics features, and clinical features. Three classification tasks were performed: Task 1: Classification of lung nodules into benign or malignant in the LUNA16 dataset; Task 2: Classification of lung nodules into different pathological subtypes; and Task 3: Classification of Lung-RADS score. Classification performance was determined based on accuracy, recall, precision, and F1-score. Ten-fold cross-validation was applied to each task. RESULTS: The proposed model achieved high accuracy in classifying lung nodules into benign or malignant categories in LUNA 16 with an accuracy of 92.8%, as well as in classifying lung nodules into different pathological subtypes with an F1-score of 75.5% and Lung-RADS scores with an F1-score of 80.4%. CONCLUSION: Our proposed model provides an accurate classification of lung nodules based on the benign/malignant, different pathological subtypes, and Lung-RADS system.

Early drainage reduces the length of hospital stay in patients with lung abscess.

Background: Although percutaneous transthoracic catheter drainage (PCD) has been proven effective in lung abscesses, the optimal timing of PCD is still unclear. The study aimed to evaluate the safety and efficacy of early versus delayed drainage in patients with lung abscesses. Methods: This retrospective study included 103 consecutive patients with liquefied lung abscesses more than 3 cm confirmed by a CT scan received CT-guided PCD over 16 years, from July 2005 to September 2021, in a single institution were reviewed. Early drainage was defined as PCD within one week after a lung abscess was diagnosed. The primary outcome was 90-day mortality. The secondary outcomes included perioperative complications and patients' length of hospital stay (LoS). Factors associated with 90-day mortality and LoS were also analyzed. The key statistical methods were Chi-square test, Fisher's exact test, Student t-test, and Pearson correlation. Results: Amount the 103 patients, there were 64 patients who received early PCD, and 39 patients received delayed PCD. Between the two groups, there were no significant differences in clinical characteristics, 90-day mortality, or perioperative complications. The LoS was significantly shortened in early PCD group (28.6 ± 25.5 vs. 39.3 ± 26.8 (days), p = 0.045). Higher Charlson comorbidity index, secondary lung abscess, and liver cirrhosis were associated with higher mortality (all p < 0.05). Positive sputum culture significantly increased the LoS (coefficient 19.35 (10.19, 28.50), p < 0.001). Conclusion: The 90-day mortality and complications were similar for early PCD and delayed PCD patients, but LoS was significantly shortened in early PCD patient.

Monitoring of the Healthy Neonatal Transition Period with Serial Lung Ultrasound.

Ultrasound has been used to observe lung aeration and fluid clearance during the neonatal transition period, but there is no consensus regarding the optimal timing of lung ultrasound. We aimed to monitor the trend of the serial lung ultrasound score (LUS) and extended LUS (eLUS) throughout the neonatal transition period (≤1, 2, 4, 8, 24, and 48 h after birth), assess any correlation to the clinical presentation (using the Silverman Andersen Respiratory Severity Score (RSS)), and determine the optimal time of the ultrasound. We found both LUS and eLUS decreased significantly after 2 h of life and had similar statistical differences among the serial time points. Although both scores had a positive, moderate correlation to the RSS overall (Pearson correlation 0.499 [p < 0.001] between LUS and RSS, 0.504 [p < 0.001] between eLUS and RSS), the correlation was poor within 1 h of life (Pearson correlation 0.15 [p = 0.389] between LUS and RSS, 0.099 [p = 0.573] between eLUS and RSS). For better clinical correlation, the first lung ultrasound for the neonate may be performed at 2 h of life. Further research is warranted to explore the clinical value and limitations of earlier (≤1 h of life) lung ultrasound examinations.

The impact of small-for-gestational-age Status on the outcomes in very-Low-birth-weight (VLBW) premature infants: a prospective cohort study in Taiwan.

Background: The impact of small-for-gestational-age (SGA) on very-low-birth-weight (VLBW) premature infants remains inconclusive. This study aimed to assess the effects of being born SGA status on the short-term and long-term outcomes in VLBW preterm infants. Methods: We conducted a population-based, prospective cohort study on VLBW preterm infants born in Taiwan between 2012 and 2017. Sociodemographic, neonatal, growth and neurological data at 2 years of corrected age were collected. A total of 4243 VLBW infants born at 24 through 32 completed weeks' gestation participated in this study, of whom 1,005 had SGA status defined as a birth weight <10th percentile of gestation, and 3,238 did not (the non-SGA group).We compared the risks of short-term outcomes (neonatal mortality and morbidities), long-term outcomes (growth status, including weight, height, and head circumference <10th percentile, and neurodevelopmental impairments at 2 years of age). Subgroup analysis was performed by stratification of gestation age (GA): GA 24-26, 27-29 and 30-32 weeks. Results: In the analysis of short-term outcomes, the SGA group had an increased risk of neonatal mortality [adjusted odds ratio (OR) = 2.66, 2.99, and 2.19, respectively] in all GA subgroups in comparison with the non-SGA group (p < 0.05). The SGA group had a significantly increased risk of bronchopulmonary dysplasia in GA 27-29 and 30-32 weeks (adjusted OR = 2.11 and 1.86, respectively). We also found that there was an increased risk of severe retinopathy of prematurity in GA 24-26 and 27-29 weeks in the SGA group compared with the non-SGA group (adjusted OR = 1.68 and 1.59, respectively).In the analysis of long-term outcomes, the SGA group had a significantly increased risk of NDI throughout all GA subgroups (adjusted = 1.94, 1.33, and 1.35, respectively) in comparison with the non-SGA group. The SGA groups also had an increased risk of growth status <10th percentile at 2 years of age (p < 0.05). Conclusions: SGA VLBW premature infants had higher risks of neonatal death, growth status <10th percentile, and NDI at 2 years of corrected age compared with the non- SGA premature infants. Prenatal surveillance, postnatal attention, and long- term follow-up are warranted to improve the outcomes of VLBW SGA premature infants.

The effect of patient volume on mortality and morbidity of extremely low birth weight infants in Taiwan.

BACKGROUND: To assess whether the number of extremely low birth weight (ELBW) infants treated annually in neonatal intensive care units (NICUs) in Taiwan affects the mortality and morbidity of this patient population. METHODS: This retrospective cohort study included preterm infants with ELBW (≤1000 g). NICUs were divided into three subgroups according to the annual admissions of ELBW infants (low, ≤10; medium, 11-25; and high, >25). Perinatal characteristics, mortality, and short-term morbidities were compared between groups. RESULTS: A total of 1945 ELBW infants from 17 NICUs were analyzed (low-volume, n = 263; medium-volume, n = 420; and high-volume, n = 1262). After risk adjustments, infants from NICUs with low patient volumes were at a higher risk of death. The risk-adjusted odds ratios (aOR) for mortality were 0.61 (95% CI, 0.43-0.86) in the high-volume NICUs and 0.65 (95% CI, 0.43-0.98) in medium-volume NICUs, compared with infants admitted to low-volume NICUs. Infants in medium-volume NICUs had the lowest incidence of prenatal steroid exposure (58.1%, P < 0.001) and were associated with the highest risk of necrotizing enterocolitis (aOR, 2.35 [95% CI, 1.48-3.72]), severe intraventricular hemorrhage (aOR, 1.55 [95% CI, 1.01-2.28]), and bronchopulmonary dysplasia (aOR, 1.61 [95% CI, 1.10-2.35]). However, survival without major morbidity did not differ between the groups. CONCLUSION: The mortality risk was higher among ELBW infants admitted to NICUs with a low annual patient volume. This may emphasize the importance of systematically referring patients from these vulnerable populations to appropriate care settings.

Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

[This corrects the article DOI: 10.3389/fonc.2023.1105100.].

Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

Purpose: To compare the diagnostic performance of radiomic analysis with machine learning (ML) model with a convolutional neural network (CNN) in differentiating thymic epithelial tumors (TETs) from other prevascular mediastinal tumors (PMTs). Methods: A retrospective study was performed in patients with PMTs and undergoing surgical resection or biopsy in National Cheng Kung University Hospital, Tainan, Taiwan, E-Da Hospital, Kaohsiung, Taiwan, and Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan between January 2010 and December 2019. Clinical data including age, sex, myasthenia gravis (MG) symptoms and pathologic diagnosis were collected. The datasets were divided into UECT (unenhanced computed tomography) and CECT (enhanced computed tomography) for analysis and modelling. Radiomics model and 3D CNN model were used to differentiate TETs from non-TET PMTs (including cyst, malignant germ cell tumor, lymphoma and teratoma). The macro F1-score and receiver operating characteristic (ROC) analysis were performed to evaluate the prediction models. Result: In the UECT dataset, there were 297 patients with TETs and 79 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 83.95%, ROC-AUC = 0.9117) had better performance than the 3D CNN model (macro F1-score = 75.54%, ROC-AUC = 0.9015). In the CECT dataset, there were 296 patients with TETs and 77 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 85.65%, ROC-AUC = 0.9464) had better performance than the 3D CNN model (macro F1-score = 81.01%, ROC-AUC = 0.9275). Conclusion: Our study revealed that the individualized prediction model integrating clinical information and radiomic features using machine learning demonstrated better predictive performance in the differentiation of TETs from other PMTs at chest CT scan than 3D CNN model.

Unlocking the Therapeutic Potential of Irisin: Harnessing Its Function in Degenerative Disorders and Tissue Regeneration.

Physical activity is well-established as an important protective factor against degenerative conditions and a promoter of tissue growth and renewal. The discovery of Fibronectin domain-containing protein 5 (FNDC5) as the precursor of Irisin in 2012 sparked significant interest in its potential as a diagnostic biomarker and a therapeutic agent for various diseases. Clinical studies have examined the correlation between plasma Irisin levels and pathological conditions using a range of assays, but the lack of reliable measurements for endogenous Irisin has led to uncertainty about its prognostic/diagnostic potential as an exercise surrogate. Animal and tissue-engineering models have shown the protective effects of Irisin treatment in reversing functional impairment and potentially permanent damage, but dosage ambiguities remain unresolved. This review provides a comprehensive examination of the clinical and basic studies of Irisin in the context of degenerative conditions and explores its potential as a therapeutic approach in the physiological processes involved in tissue repair/regeneration.

Clinical outcomes of percutaneous transhepatic biliary drainage at different Couinaud's hepatic entry segments for treating obstructive jaundice.

Introduction: Percutaneous transhepatic biliary drainage (PTBD) is a common procedure for biliary obstructive jaundice caused by biliary tract obstruction. In clinical practice, PTBD can be carried out at right- or left-sided approach. However, different hepatic entry site may affect success rates and complications. Couinaud classification of liver anatomy further divides the liver into functionally independent segments (segment 2/3, segment 5/6, and segment 7/8). Therefore, this study aimed to elucidate whether different Couinaud hepatic segments as PTBD entry site are associated with high PTBD success and low complications. Methods: A total of 617 patients who underwent PTBD were retrospectively reviewed. Univariate and multivariate logistic regression analyses were performed to identify entry segments associated with PTBD success, bilirubin reduction, and complications. Results: With higher hepatic segment of PTBD entry site (segment 2/3, 5/6, and 7/8), the trend of PTBD success rate (82.0%, 71.7% and 60.7%; P<0.001) and bilirubin reduction (93.2%, 89.5%, and 82.0%; P=0.012) decreased. Furthermore, PTBD entry at segment 7/8 (42.6%) had highest complication rate than segment 5/6 (6.4%) and 2/3 (9.4%). Univariate and multivariate logistic regression analyses showed that PTBD entry segment was an independent factor associated with PTBD success, bilirubin reduction, and complications. Compared to segment 7/8, segment 2/3 and 5/6 had higher odds of PTBD success (aOR=2.699 and aOR=1.454, respectively) and bilirubin reduction (aOR=3.472 and aOR=2.361, respectively) and associated with lower risk of complications (aOR=0.143 and aOR=0.098, respectively). No independent risk factor for PTBD success and bilirubin reduction were identified in intrahepatic tumors. Moreover, for extrahepatic tumors, PTBD entry at segment 2/3 and segment 5/6 was more likely achieve PTBD success (aOR=3.037 and aOR=1.929, respectively), bilirubin reduction (aOR=3.069 and aOR=3.515) and low complications (aOR=0.102 and aOR=0.126, respectively). Discussion: Good clinical outcomes were observed for PTBD entry at segments 5/6 and 2/3. In contrast, segment 7/8 had the lowest success rate, smallest bilirubin reduction, and the highest complication rate. For patients with obstructive jaundice, PTBD entry in hepatic segments 2/3 and 5/6 is recommended to achieve high success rates and low complications.

Risk Factors of Language Delay at Two Years of Corrected Age among Very-Low-Birth-Weight Preterm Infants: A Population-Based Study.

Language delays are often underestimated in very-low-birth-weight (VLBW) preterm infants. We aimed to identify the risk factors of language delay at two years of corrected age in this vulnerable population. VLBW infants, who were assessed at two years of corrected age using the Bayley Scale of Infant Development, third edition, were included using a population-based cohort database. Language delay was defined as mild to moderate if the composite score was between 70 and 85 and severe if the score was < 70. Multivariable logistic regression analysis was used to identify the perinatal risk factors associated with language delay. The study comprised 3797 VLBW preterm infants; 678 (18%) had a mild to moderate delay and 235 (6%) had a severe delay. After adjusting for confounding factors, low maternal education level, low maternal socioeconomic status, extremely low birth weight, male sex, and severe intraventricular hemorrhage (IVH) and/or cystic periventricular leukomalacia (PVL) were found to be significantly associated with both mild to moderate and severe delays. Resuscitation at delivery, necrotizing enterocolitis, and patent ductus arteriosus requiring ligation showed significant associations with severe delay. The strongest factors predicting both mild to moderate and severe language delays were the male sex and severe IVH and/or cystic PVL; thus, early targeted intervention is warranted in these populations.

Improving puncture accuracy in percutaneous CT-guided needle insertion with wireless inertial measurement unit: a phantom study.

OBJECTIVES: A novel method applying inertial measurement units (IMUs) was developed to assist CT-guided puncture, which enables real-time displays of planned and actual needle trajectories. The method was compared with freehand and laser protractor-assisted methods. METHODS: The phantom study was performed by three operators with 8, 2, and 0 years of experience in CT-guided procedure conducted five consecutive needle placements for three target groups using three methods (freehand, laser protractor-assisted, or IMU-assisted method). The endpoints included mediolateral angle error and caudocranial angle error of the first pass, the procedure time, the total number of needle passes, and the radiation dose. RESULTS: There was a significant difference in the number of needle passes (IMU 1.2 ± 0.42, laser protractor 2.9 ± 1.6, freehand 3.6 ± 2.0 time, p < 0.001), the procedure time (IMU 3.0 ± 1.2, laser protractor 6.4 ± 2.9, freehand 6.2 ± 3.1 min, p < 0.001), the mediolateral angle error of the first pass (IMU 1.4 ± 1.2, laser protractor 1.6 ± 1.3, freehand 3.7 ± 2.5 degree, p < 0.001), the caudocranial angle error of the first pass (IMU 1.2 ± 1.2, laser protractor 5.3 ± 4.7, freehand 3.9 ± 3.1 degree, p < 0.001), and the radiation dose (IMU 250.5 ± 74.1, laser protractor 484.6 ± 260.2, freehand 561.4 ± 339.8 mGy-cm, p < 0.001) among three CT-guided needle insertion methods. CONCLUSION: The wireless IMU improves the angle accuracy and speed of CT-guided needle punctures as compared with laser protractor guidance and freehand techniques. KEY POINTS: • The IMU-assisted method showed a significant decrease in the number of needle passes (IMU 1.2 ± 0.42, laser protractor 2.9 ± 1.6, freehand 3.6 ± 2.0 time, p < 0.001). • The IMU-assisted method showed a significant decrease in the procedure time (IMU 3.0 ± 1.2, laser protractor 6.4 ± 2.9, freehand 6.2 ± 3.1 min, p < 0.001). • The IMU-assisted method showed a significant decrease in the mediolateral angle error of the first pass and the caudocranial angle error of the first pass.

Characteristics of Gut Microbiota in Small for Gestational Age Infants with Very Low Birth Weight.

Small for gestational age (SGA) birth is associated with high rates of mortality and morbidity in preterm infants. The aim of this preliminary observational study was to investigate the difference in gut microbiota between SGA and appropriate for gestational age (AGA) preterm infants with very low birth weight (VLBW). We included 20 VLBW preterm infants (SGA, n = 10; AGA, n = 10) in this study. Stool samples were collected on days 7, 14, and 30 after birth. We performed 16S ribosomal DNA sequencing to compare microbiota composition between both groups. The SGA group exhibited a lower abundance of Klebsiella on day 14 (SGA, 0.57%; AGA, 7.42%; p = 0.037). On day 30, the SGA group exhibited a lower abundance of Klebsiella (SGA 3.76% vs. AGA 16.05%; p = 0.07) and Enterobacter (SGA 5.09% vs. AGA 27.25%; p = 0.011) than the AGA group. Beta diversity demonstrated a separation of the bacterial community structure between both groups on day 30 (p = 0.019). The present study revealed that a distinct gut microbiota profile gradually develops in SGA preterm infants with VLBW during the early days of life. The role of changes in gut microbiota structure warrants further investigation.

Diagnostic value of apparent diffusion coefficient in predicting pathological T stage in patients with thymic epithelial tumor.

PURPOSES: This study aimed to evaluate the diagnostic capacity of apparent diffusion coefficient (ADC) in predicting pathological Masaoka and T stages in patients with thymic epithelial tumors (TETs). METHODS: Medical records of 62 patients who were diagnosed with TET and underwent diffusion-weighted imaging (DWI) prior to surgery between August 2017 and July 2021 were retrospectively analyzed. ADC values were calculated from DWI images using b values of 0, 400, and 800 s/mm2. Pathological stages were determined by histological examination of surgical specimens. Cut-off points of ADC values were calculated via receiver operating characteristic (ROC) analysis. RESULTS: Patients had a mean age of 56.3 years. Mean ADC values were negatively correlated with pathological Masaoka and T stages. Higher values of the area under the ROC curve suggested that mean ADC values more accurately predicated pathological T stages than pathological Masaoka stages. The optimal cut-off points of mean ADC were 1.62, 1.31, and 1.48 × 10-3 mm2/sec for distinguishing pathological T2-T4 from pathological T1, pathological T4 from pathological T1-T3, and pathological T3-T4 from pathological T2, respectively. CONCLUSION: ADC seems to more precisely predict pathological T stages, compared to pathological Masaoka stage. The cut-off values of ADC identified may be used to preoperatively predict pathological T stages of TETs.

U(1) dynamics in neuronal activities.

Neurons convert external stimuli into action potentials, or spikes, and encode the contained information into the biological nervous system. Despite the complexity of neurons and the synaptic interactions in between, rate models are often adapted to describe neural encoding with modest success. However, it is not clear whether the firing rate, the reciprocal of the time interval between spikes, is sufficient to capture the essential features for the neuronal dynamics. Going beyond the usual relaxation dynamics in Ginzburg-Landau theory for statistical systems, we propose that neural activities can be captured by the U(1) dynamics, integrating the action potential and the "phase" of the neuron together. The gain function of the Hodgkin-Huxley neuron and the corresponding dynamical phase transitions can be described within the U(1) neuron framework. In addition, the phase dependence of the synaptic interactions is illustrated and the mapping to the Kinouchi-Copelli neuron is established. It suggests that the U(1) neuron is the minimal model for single-neuron activities and serves as the building block of the neuronal network for information processing.