Internet Gaming Disorder and Mental Health Literacy: A Latent Profile Analysis of Korean Adolescents.

OBJECTIVE: This study identified latent subtypes of mental health literacy (MHL) for Internet gaming disorder (IGD) and explored their characteristics and differences in various factors in adolescents. METHODS: This study analyzed secondary data from the 2019 Youth Smart Digital Media Survey and included data from 1,936 middle and high school students (14-18 years old). Thirteen items of the MHL questionnaire were used for latent profile analysis. We compared the characteristics and predictors of the identified types using various statistical analyses, including one-way ANOVA, chi-square test, and multinomial logistic regression. RESULTS: We identified three subtypes of MHL for IGD in adolescents: "low perception-prefer informal resources," "moderate perception-preferred resources unclear," and "high perception-prefer professional resources." Subtypes showed significant differences in sex, age, family affluence, e-learning time during weekdays, mental health risks, level of problematic smartphone use, and IGD. All variables except IGD predicted one or more latent types. CONCLUSION: Practical interventions are required to improve IGD MHL, including customized prevention based on the differences between the three types.

AI analytics can be used as imaging biomarkers for predicting invasive upgrade of ductal carcinoma in situ.

OBJECTIVES: To evaluate whether the quantitative abnormality scores provided by artificial intelligence (AI)-based computer-aided detection/diagnosis (CAD) for mammography interpretation can be used to predict invasive upgrade in ductal carcinoma in situ (DCIS) diagnosed on percutaneous biopsy. METHODS: Four hundred forty DCIS in 420 women (mean age, 52.8 years) diagnosed via percutaneous biopsy from January 2015 to December 2019 were included. Mammographic characteristics were assessed based on imaging features (mammographically occult, mass/asymmetry/distortion, calcifications only, and combined mass/asymmetry/distortion with calcifications) and BI-RADS assessments. Routine pre-biopsy 4-view digital mammograms were analyzed using AI-CAD to obtain abnormality scores (AI-CAD score, ranging 0-100%). Multivariable logistic regression was performed to identify independent predictive mammographic variables after adjusting for clinicopathological variables. A subgroup analysis was performed with mammographically detected DCIS. RESULTS: Of the 440 DCIS, 117 (26.6%) were upgraded to invasive cancer. Three hundred forty-one (77.5%) DCIS were detected on mammography. The multivariable analysis showed that combined features (odds ratio (OR): 2.225, p = 0.033), BI-RADS 4c or 5 assessments (OR: 2.473, p = 0.023 and OR: 5.190, p < 0.001, respectively), higher AI-CAD score (OR: 1.009, p = 0.007), AI-CAD score ≥ 50% (OR: 1.960, p = 0.017), and AI-CAD score ≥ 75% (OR: 2.306, p = 0.009) were independent predictors of invasive upgrade. In mammographically detected DCIS, combined features (OR: 2.194, p = 0.035), and higher AI-CAD score (OR: 1.008, p = 0.047) were significant predictors of invasive upgrade. CONCLUSION: The AI-CAD score was an independent predictor of invasive upgrade for DCIS. Higher AI-CAD scores, especially in the highest quartile of ≥ 75%, can be used as an objective imaging biomarker to predict invasive upgrade in DCIS diagnosed with percutaneous biopsy. CRITICAL RELEVANCE STATEMENT: Noninvasive imaging features including the quantitative results of AI-CAD for mammography interpretation were independent predictors of invasive upgrade in lesions initially diagnosed as ductal carcinoma in situ via percutaneous biopsy and therefore may help decide the direction of surgery before treatment. KEY POINTS: • Predicting ductal carcinoma in situ upgrade is important, yet there is a lack of conclusive non-invasive biomarkers. • AI-CAD scores-raw numbers, ≥ 50%, and ≥ 75%-predicted ductal carcinoma in situ upgrade independently. • Quantitative AI-CAD results may help predict ductal carcinoma in situ upgrade and guide patient management.

Mental Health Status of New Police Trainees before and during the COVID-19 Pandemic.

This study aimed to investigate the mental health of new police trainees during the coronavirus disease 2019 (COVID-19) pandemic in Korea. Two groups of police trainees were surveyed considering the distribution of gender, age, and education level: those who joined the school before COVID-19 and those who joined during the outbreak. Mental health indicators, including insomnia, depression, and anxiety, were compared between the two groups. The prevalence of insomnia, depression, and anxiety significantly varied in the group that joined during COVID-19 compared with the group that joined before. Specifically, insomnia showed a significant change in women, with a higher rate of 2.6%. Although the prevalence of depression was initially low, it increased from 0.4% to 1.3% during the pandemic. Anxiety rates also showed notable differences, particularly among women, with a higher rate of 4.7%. The highest differences in prevalence were observed in the low-income group, with a rate of 7.7% for anxiety. The findings highlight the vulnerability of police officers to psychosocial effects during disasters such as pandemics. Disaster preparedness programs or education can be integrated into new police officer training institutions to help manage mental health changes and promote overall well-being.

Supervised diagnostic classification of cognitive attributes using data augmentation.

Over recent decades, machine learning, an integral subfield of artificial intelligence, has revolutionized diverse sectors, enabling data-driven decisions with minimal human intervention. In particular, the field of educational assessment emerges as a promising area for machine learning applications, where students can be classified and diagnosed using their performance data. The objectives of Diagnostic Classification Models (DCMs), which provide a suite of methods for diagnosing students' cognitive states in relation to the mastery of necessary cognitive attributes for solving problems in a test, can be effectively addressed through machine learning techniques. However, the challenge lies in the latent nature of cognitive status, which makes it difficult to obtain labels for the training dataset. Consequently, the application of machine learning methods to DCMs often assumes smaller training sets with labels derived either from theoretical considerations or human experts. In this study, the authors propose a supervised diagnostic classification model with data augmentation (SDCM-DA). This method is designed to utilize the augmented data using a data generation model constructed by leveraging the probability of correct responses for each attribute mastery pattern derived from the expert-labeled dataset. To explore the benefits of data augmentation, a simulation study is carried out, contrasting it with classification methods that rely solely on the expert-labeled dataset for training. The findings reveal that utilizing data augmentation with the estimated probabilities of correct responses substantially enhances classification accuracy. This holds true even when the augmentation originates from a small labeled sample with occasional labeling errors, and when the tests contain lower-quality items that may inaccurately measure students' true cognitive status. Moreover, the study demonstrates that leveraging augmented data for learning can enable the successful classification of students, thereby eliminating the necessity for specifying an underlying response model.

Dental trauma trends in emergency care:a comparative analysis before, during, and after COVID-19.

Objectives: This analysis details the characteristics of dental trauma in South Korea during the coronavirus disease 2019 (COVID-19) (DC) pandemic and compares them in patients before and after COVID-19 (BC and AC, respectively). Materials and Methods: Data were collected from medical records of patients who visited Seoul National University Bundang Hospital's Emergency Dental Care Center during three 12-month periods: BC, DC, and AC (BC from March 1, 2019 to February 29, 2020; DC from March 1, 2020 to February 28, 2021; AC from March 1, 2022 to February 28, 2023). A retrospective review was conducted to investigate patient age, sex, time of visit, cause, and diagnosis. The study included 1,544 patients: 660 BC, 374 DC, and 510 AC. Results: Significant difference in age and sex was not observed among the three periods; 1-9 years of age was the largest group (38.3% in BC, 29.6% in DC, and 27.8% in AC), and the percentage of male patients was greater than of female patients (male proportion as 63.5% in BC, 67.4% in DC, and 64.9% in AC). The number of patients generally peaked at a Saturday night in spring (for BC: May, Saturday, 18:00-19:59; for DC: March, Saturday, 18:00-19:59; for AC: April as the second most (October as the most peaked), Saturday, 20:00-21:59). The primary etiology of the dental trauma was identical in the three periods: falls, followed by sports. The most frequent diagnosis was laceration, followed by tooth avulsion and jaw fracture. Conclusion: Significant differences were not found between the characteristics and patterns of dental trauma in the BC, DC, and AC periods. However, due to the pandemic and social distancing, activities decreased and associated dental trauma-related incidents declined.

Depolymerized Chitosan-g-[Poly(MMA-co-HEMA-cl-EGDMA)] Based Nanogels for Controlled Local Release of Bupivacaine.

This study is designed to formulate and characterize chitosan-based nanogels that provide the controlled delivery of anesthetic drugs, such as bupivacaine (BPV), for effective postoperative pain management over prolonged periods of time. Drug carriers of chitosan/poly (MMA-co-HEMA-cl-EGDMA) (CsPMH) nanogels were prepared by varying the composition of comonomers such as MMA, HEMA, and redox initiator CAN. The nanogels were then characterized using FTIR, TGA, SEM, and TEM. The CsPMH nanogels showed greater encapsulation efficiencies from 43.20-91.77%. Computational studies were also conducted to evaluate the interaction between the drug and CsPMH nanoparticles. Finally, BPV-loaded nanoparticles were used to examine their in vitro release behavior. At pH 7.4, all the drug carriers displayed the "n" value around 0.7, thus the BPV release follows anomalous diffusion. Drug carrier 7 demonstrated a steady and sustained release of BPV for approximately 24 h and released about 91% of BPV, following the K-P mechanism of drug release. On the other hand, drug carrier 6 exhibited controlled release for approximately 12 h and released only 62% of BPV.

Risk Factors of Pneumocystis jirovecii Pneumonia in Patients with Inflammatory Bowel Disease: A Nationwide Population-Based Study.

Background/Aims: : Pneumocystis jirovecii pneumonia (PJP) is a rare but potentially fatal infection. This study was conducted to investigate the risk factors for PJP in inflammatory bowel disease (IBD) patients. Methods: : This nationwide, population-based study was conducted in Korea using claims data. Cases of PJP were identified in patients diagnosed with ulcerative colitis (UC) or Crohn's disease (CD) between 2010 and 2017, and the clinical data of each patient was analyzed. Dual and triple therapy was defined as the simultaneous prescription of two or three of the following drugs: steroids, calcineurin inhibitors, immunomodulators, and biologics. Results: : During the mean follow-up period (4.6±2.3 years), 84 cases of PJP were identified in 39,462 IBD patients (31 CD and 53 UC). For CD patients, only age at diagnosis >40 years (hazard ratio [HR], 6.12; 95% confidence interval [CI], 1.58 to 23.80) was significantly associated with the risk of PJP, whereas in UC patients, diagnoses of diabetes (HR, 2.51; 95% CI, 1.19 to 5.31) and chronic obstructive pulmonary disease (HR, 3.41; 95% CI, 1.78 to 6.52) showed significant associations with PJP risk. Triple therapy increased PJP risk in both UC (HR, 3.90; 95% CI, 1.54 to 9.88) and CD patients (HR, 5.69; 95% CI, 2.32 to 14.48). However, dual therapy increased PJP risk only in UC patients (HR, 2.53; 95% CI, 1.36 to 4.70). Additionally, 23 patients (27%) received intensive care treatment, and 10 (12%) died within 30 days. Conclusions: : PJP risk factors differ in CD and UC patients. Considering the potential fatality of PJP, prophylaxis should be considered for at-risk IBD patients.

Transcriptional control of motor pool formation and motor circuit connectivity by the LIM-HD protein Isl2.

The fidelity of motor control requires the precise positional arrangement of motor pools and the establishment of synaptic connections between them. During neural development in the spinal cord, motor nerves project to specific target muscles and receive proprioceptive input from these muscles via the sensorimotor circuit. LIM-homeodomain transcription factors are known to play a crucial role in successively restricting specific motor neuronal fates. However, their exact contribution to limb-based motor pools and locomotor circuits has not been fully understood. To address this, we conducted an investigation into the role of Isl2, a LIM-homeodomain transcription factor, in motor pool organization. We found that deletion of Isl2 led to the dispersion of motor pools, primarily affecting the median motor column (MMC) and lateral motor column (LMC) populations. Additionally, hindlimb motor pools lacked Etv4 expression, and we observed reduced terminal axon branching and disorganized neuromuscular junctions in Isl2-deficient mice. Furthermore, we performed transcriptomic analysis on the spinal cords of Isl2-deficient mice and identified a variety of downregulated genes associated with motor neuron (MN) differentiation, axon development, and synapse organization in hindlimb motor pools. As a consequence of these disruptions, sensorimotor connectivity and hindlimb locomotion were impaired in Isl2-deficient mice. Taken together, our findings highlight the critical role of Isl2 in organizing motor pool position and sensorimotor circuits in hindlimb motor pools. This research provides valuable insights into the molecular mechanisms governing motor control and its potential implications for understanding motor-related disorders in humans.

The Effect of Language Dominance on Classic Semantic, Action, Emotional, and Phonemic Fluency in Unbalanced Bilinguals.

OBJECTIVE: Verbal fluency evaluation in bilingual speakers should include dual-language assessment to obtain a comprehensive profile of word retrieval abilities. This study is the first to compare classic semantic, action, emotional, and phonemic fluency in terms of the magnitude of their performance gaps between the dominant and nondominant language in unbalanced bilingual speakers. We also examined the quantitative relationship between language dominance and verbal fluency performance. METHOD: Twenty-six bilingual adults completed a comprehensive set of classic semantic ("animals," "vegetables"), action ("do"), emotional ("happy," "sad," "afraid"), and phonemic ("F," "A," "S") fluency tasks in their dominant language (English) and nondominant language (Spanish) in two sessions on separate days. Participants also completed subjective and objective measures of language proficiency. RESULTS: All tasks yielded fewer correct responses in the nondominant language. The between-languages performance gap was the largest for "animals" and the smallest for emotional fluency. "Happy" yielded the most balanced performance among all semantic tasks and a positivity bias that was unaffected by language dominance. Finally, language dominance scores computed by a newly developed formula indicated relationships between self-rated proficiency and fluency performance. CONCLUSIONS: This study provides preliminary, normative data of classic semantic, action, emotional, and phonemic fluency that could be used to gauge unbalanced bilingual speakers' performance. Significant impacts of language dominance on "animals" demand caution in using this widely used classic semantic category in evaluating bilingual speakers' performance. The data also underscore the robustness of positivity biases in emotional fluency and the validity of using subjective measures to supplement neuropsychological assessment of fluency performance.

Systematic Review of Extended Reality Digital Therapy for Enhancing Mental Health Among South Korean Adolescents and Young Adults.

Digital therapy using extended reality (XR) holds great promise for addressing the mental health needs of adolescents and young adults. This study addresses a notable research gap in South Korea by systematically reviewing XR-based digital therapy for the mental health of South Korean adolescents and young adults. We analyzed 26 studies encompassing various aspects, including study type, publication date, research field, research methodology, data sources, program types, program content, sample characteristics, target population, assessment tools, and program effectiveness. Notably, 46.15% of the studies employed an experimental design, whereas over 53% utilized non-experimental approaches. Experimental studies lacked a genuine design, standardized questionnaires, and control variables. Similarly, non-experimental studies failed to report specific literature selection criteria. Consequently, future studies should adopt rigorous methodologies to enhance reliability and validity. Moreover, over 85% of the 26 studies focused solely on virtual reality and did not incorporate augmented or mixed reality. This study identifies the limitations of the previous research. These findings emphasize the need for structured investigations to advance the development of XR-based digital therapy to promote mental health in adolescents and young adults in South Korea.

Cyclic Stretch Promotes Cellular Reprogramming Process through Cytoskeletal-Nuclear Mechano-Coupling and Epigenetic Modification.

Advancing the technologies for cellular reprogramming with high efficiency has significant impact on regenerative therapy, disease modeling, and drug discovery. Biophysical cues can tune the cell fate, yet the precise role of external physical forces during reprogramming remains elusive. Here the authors show that temporal cyclic-stretching of fibroblasts significantly enhances the efficiency of induced pluripotent stem cell (iPSC) production. Generated iPSCs are proven to express pluripotency markers and exhibit in vivo functionality. Bulk RNA-sequencing reveales that cyclic-stretching enhances biological characteristics required for pluripotency acquisition, including increased cell division and mesenchymal-epithelial transition. Of note, cyclic-stretching activates key mechanosensitive molecules (integrins, perinuclear actins, nesprin-2, and YAP), across the cytoskeletal-to-nuclear space. Furthermore, stretch-mediated cytoskeletal-nuclear mechano-coupling leads to altered epigenetic modifications, mainly downregulation in H3K9 methylation, and its global gene occupancy change, as revealed by genome-wide ChIP-sequencing and pharmacological inhibition tests. Single cell RNA-sequencing further identifies subcluster of mechano-responsive iPSCs and key epigenetic modifier in stretched cells. Collectively, cyclic-stretching activates iPSC reprogramming through mechanotransduction process and epigenetic changes accompanied by altered occupancy of mechanosensitive genes. This study highlights the strong link between external physical forces with subsequent mechanotransduction process and the epigenetic changes with expression of related genes in cellular reprogramming, holding substantial implications in the field of cell biology, tissue engineering, and regenerative medicine.

Sensor development for multiple simultaneous classifications using genetically engineered M13 bacteriophages.

Sensors for detecting infinitesimal amounts of chemicals in air have been widely developed because they can identify the origin of chemicals. These sensing technologies are also used to determine the variety and freshness of fresh food and detect explosives, hazardous chemicals, environmental hormones, and diseases using exhaled gases. However, there is still a need to rapidly develop portable and highly sensitive sensors that respond to complex environments. Here, we show an efficient method for optimising an M13 bacteriophage-based multi-array colourimetric sensor for multiple simultaneous classifications. Apples, which are difficult to classify due to many varieties in distribution, were selected for classifying targets. M13 was adopted to fabricate a multi-array colourimetric sensor using the self-templating process since a chemical property of major coat protein p8 consisting of the M13 body can be manipulated by genetic engineering to respond to various target substances. The twenty sensor units, which consisted of different types of manipulated M13, exhibited colour changes because of the change of photonic crystal-like nanostructure when they were exposed to target substances associated with apples. The classification success rate of the optimal sensor combinations was achieved with high accuracy for the apple variety (100%), four standard fragrances (100%), and aging (84.5%) simultaneously. We expect that this optimisation technique can be used for rapid sensor development capable of multiple simultaneous classifications in various fields, such as medical diagnosis, hazardous environment monitoring, and the food industry, where sensors need to be developed in response to complex environments consisting of various targets.

Learnability of Thyroid Nodule Assessment on Ultrasonography: Using a Big Data Set.

OBJECTIVE: The aims of the work described here were to evaluate the learnability of thyroid nodule assessment on ultrasonography (US) using a big data set of US images and to evaluate the diagnostic utilities of artificial intelligence computer-aided diagnosis (AI-CAD) used by readers with varying experience to differentiate benign and malignant thyroid nodules. METHODS: Six college freshmen independently studied the "learning set" composed of images of 13,560 thyroid nodules, and their diagnostic performance was evaluated after their daily learning sessions using the "test set" composed of images of 282 thyroid nodules. The diagnostic performance of two residents and an experienced radiologist was evaluated using the same "test set." After an initial diagnosis, all readers once again evaluated the "test set" with the assistance of AI-CAD. RESULTS: Diagnostic performance of almost all students increased after the learning program. Although the mean areas under the receiver operating characteristic curves (AUROCs) of residents and the experienced radiologist were significantly higher than those of students, the AUROCs of five of the six students did not differ significantly compared with that of the one resident. With the assistance of AI-CAD, sensitivity significantly increased in three students, specificity in one student, accuracy in four students and AUROC in four students. Diagnostic performance of the two residents and the experienced radiologist was better with the assistance of AI-CAD. CONCLUSION: A self-learning method using a big data set of US images has potential as an ancillary tool alongside traditional training methods. With the assistance of AI-CAD, the diagnostic performance of readers with varying experience in thyroid imaging could be further improved.

Technical Feasibility of Quantitative Measurement of Various Degrees of Small Bowel Motility Using Cine Magnetic Resonance Imaging.

OBJECTIVE: Cine magnetic resonance imaging (MRI) has emerged as a noninvasive method to quantitatively assess bowel motility. However, its accuracy in measuring various degrees of small bowel motility has not been extensively evaluated. We aimed to draw a quantitative small bowel motility score from cine MRI and evaluate its performance in a population with varying degrees of small bowel motility. MATERIALS AND METHODS: A total of 174 participants (28.5 ± 7.6 years; 135 males) underwent a 22-second-long cine MRI sequence (2-dimensional balanced turbo-field echo; 0.5 seconds per image) approximately 5 minutes after being intravenously administered 10 mg of scopolamine-N-butyl bromide to deliberately create diverse degrees of small bowel motility. In a manually segmented area of the small bowel, motility was automatically quantified using a nonrigid registration and calculated as a quantitative motility score. The mean value (MV) of motility grades visually assessed by two radiologists was used as a reference standard. The quantitative motility score's correlation (Spearman's ρ) with the reference standard and performance (area under the receiver operating characteristics curve [AUROC], sensitivity, and specificity) for diagnosing adynamic small bowel (MV of 1) were evaluated. RESULTS: For the MV of the quantitative motility scores at grades 1, 1.5, 2, 2.5, and 3, the mean ± standard deviation values were 0.019 ± 0.003, 0.027 ± 0.010, 0.033 ± 0.008, 0.032 ± 0.009, and 0.043 ± 0.013, respectively. There was a significant positive correlation between the quantitative motility score and the MV (ρ = 0.531, P < 0.001). The AUROC value for diagnosing a MV of 1 (i.e., adynamic small bowel) was 0.953 (95% confidence interval, 0.923-0.984). Moreover, the optimal cutoff for the quantitative motility score was 0.024, with a sensitivity of 100% (15/15) and specificity of 89.9% (143/159). CONCLUSION: The quantitative motility score calculated from a cine MRI enables diagnosis of an adynamic small bowel, and potentially discerns various degrees of bowel motility.

Comparison of Posttreatment Stability Between Mandibular Setback Surgery-Early and Conventional Surgery in Class III Patients: A 4.6-Year Follow-Up.

OBJECTIVES: This retrospective study aims to compare long-term stability between the mandibular setback surgery-early (MSE) approach, involving minimal orthodontics, and the mandibular setback conventional surgery (MCS) approach, involving sufficient orthodontics, in Class III patients with mandibular prognathism. METHODS: Among 210 patients who underwent orthognathic surgery, a total of 40 subjects were enrolled based on standardized inclusion criteria: only mandibular surgery, <5 mm setback difference between right and left of the mandible, orthodontics with fixed appliances, and more than 2 years of follow-up after treatment. These patients were allocated to the MSE (n = 20) and MCS groups (n = 20) according to the duration of presurgical orthodontics. Changes in cephalometric measurements were compared between the MSE and MCS groups before surgery (T0), 1 month after surgery (T1), at the end of treatment (T2), and posttreatment retention (T3). RESULTS: The MSE and MCS groups had a mean presurgical orthodontic duration of 2 and 9.5 months, respectively. From T1 to T2, the MSE group showed a significantly larger forward movement of the mandible than the MCS group (2.1 versus 0.7 mm; P < 0.001). In addition, from T2 to T3 (average 4.6 years), the MSE group presented anterior relapse of 0.6 mm in the mandible, but there were no statistically significant intergroup differences. CONCLUSION: Although the MSE group showed greater postsurgical forward mandibular relapse than the MCS group, the two groups exhibited similar skeletal and dental stability during the posttreatment retention.

Adult-onset megacolon with focal hypoganglionosis: A detailed phenotyping and prospective cohort study.

BACKGROUND: In this prospective cohort study, we evaluated features of "adult-onset megacolon with focal hypoganglionosis." METHODS: We assessed the radiologic, endoscopic, and histopathologic phenotyping and treatment outcomes of 29 patients between 2017 and 2020. Data from community controls, consisting of 19,948 adults undergoing health screenings, were analyzed to identify risk factors. Experts reviewed clinical features and pathological specimens according to the London Classification for gastrointestinal neuromuscular pathology. KEY RESULTS: The median age of the patients with adult-onset megacolon with focal hypoganglionosis at symptom onset was 59 years (range, 32.0-74.9 years), with mean symptom onset only 1 year before diagnosis. All patients had focal stenotic regions with proximal bowel dilatation (mean diameter, 78.8 mm; 95% confidence interval [CI], 72-86). The comparison with community controls showed no obvious risk factors. Ten patients underwent surgery, and all exhibited significant hypoganglionosis: 5.4 myenteric ganglion cells/cm (interquartile range [IQR], 3.7-16.4) in the stenotic regions compared to 278 cells/cm (IQR, 190-338) in the proximal and 95 cells/cm (IQR, 45-213) in the distal colon. Hypoganglionosis was associated with CD3+ T cells along the myenteric plexus. Colectomy was associated with significant symptom improvement compared to medical treatment [change in the Global Bowel Satisfaction score, -5.4 points (surgery) vs. -0.3 points (medical treatment); p < 0.001]. CONCLUSIONS AND INFERENCES: Adult-onset megacolon with focal hypoganglionosis has distinct features characterized by hypoganglionosis due to inflammation. Bowel resection appears to benefit these patients.

Lidocaine intensifies the anti-osteogenic effect on inflammation-induced human dental pulp stem cells via mitogen-activated protein kinase inhibition.

Background/purpose: Human dental pulp stem cells (hDPSCs) are an emerging source of mesenchymal stem cells (MSCs) for bone tissue regeneration and engineering. In bone regeneration using transplanted MSCs, the extracellular environment or co-injected drugs can affect their success or failure. In this study, we investigated the effects and signaling mechanisms of lidocaine on osteogenic differentiation of hDPSCs after inducing inflammatory conditions with lipopolysaccharide (LPS) and tumor necrosis factor-alpha (TNF-α). Materials and methods: To investigate the effect of lidocaine on the osteogenic differentiation of LPS/TNF-α-treated hDPSCs, alkaline phosphatase (ALP) and Alizarin red S (ARS) staining were conducted. The expression of osteogenesis-related genes was assessed using quantitative real-time polymerase chain reaction and western blotting. The expression of mitogen-activated protein kinases was analyzed to evaluate the effect of lidocaine on osteogenic differentiation of LPS/TNF-α-treated hDPSCs. Results: Various concentrations of lidocaine (0.05, 0.2, and 1 mM) further decreased ALP and ARS staining of LPS/TNF-α-treated hDPSCs. Similarly, the mRNA and protein expression of osteogenesis-related genes was suppressed via lidocaine treatment in LPS/TNF-α-treated hDPSCs. Lidocaine treatment downregulated the protein expression of p-ERK and p-JNK in LPS/TNF-α-treated hDPSCs. Conclusion: Lidocaine intensified the inhibition of osteogenic differentiation on inflammation-induced hDPSCs by inhibiting the ERK and JNK signaling pathways. This in vitro study suggested that lidocaine may have an inhibitory effect on bone regeneration.

Ketamine-propofol (ketofol) in procedural sedation: a narrative review.

Sedation methods for dental treatment are increasingly explored. Recently, ketofol, which is a combination of ketamine and propofol, has been increasingly used because the advantages and disadvantages of propofol and ketamine complement each other and increase their effectiveness. In this review, we discuss the pharmacology of ketamine and propofol, use of ketofol in various clinical situations, and differences in efficacy between ketofol and other sedatives.

Comparison of postoperative nausea and vomiting between Remimazolam and Propofol in Patients undergoing oral and maxillofacial surgery: a prospective Randomized Controlled Trial.

BACKGROUND: Remimazolam is a recently approved, ultra-short-acting benzodiazepine. However, few studies have investigated remimazolam in relation to postoperative nausea and vomiting (PONV). This study aimed to compare the effects of remimazolam and propofol on PONV in patients undergoing oral and maxillofacial surgery. METHODS: Patients (n = 206) aged 19-65 years who were scheduled for oral and maxillofacial surgery were randomized into two groups, the remimazolam (R) and propofol group (P). In the R group (n = 94), remimazolam was used to induce anesthesia at 12 mg/kg/h and to maintain anesthesia at 1-2 mg/kg/h. In the P group (n = 95), anesthesia was induced and maintained with propofol (target effect-site concentration: 3-5 µg/ml). In both groups, remifentanil was administered at a target effect-site concentration of 2.5-4 ng/ml. The primary outcome was the overall incidence of PONV during the first 24 h after surgery. Secondary outcomes included the severity of nausea, use of rescue antiemetics, severity of postoperative pain, use of rescue analgesia, and quality of recovery. RESULTS: The incidence of PONV during the first 24 h after surgery was 11.7% and 10.5% in the R group and P group, respectively, and there was no significant difference in the severity of nausea (P > 0.05). Ten patients in the R group and ten patients in the P group required rescue antiemetics during the first 24 h after surgery (P = 0.98). No inter-group differences were observed in terms of postoperative pain score, use of rescue analgesia, and quality of recovery (P > 0.05). CONCLUSIONS: In this study, remimazolam did not increase the incidence and severity of PONV compared with propofol. TRIAL REGISTRATION: KCT0006965, Clinical Research Information Service (CRIS), Republic of Korea. Registration date: 26/01/2022.

Evaluating diagnostic content of AI-generated chest radiography: A multi-center visual Turing test.

BACKGROUND: Accurate interpretation of chest radiographs requires years of medical training, and many countries face a shortage of medical professionals to meet such requirements. Recent advancements in artificial intelligence (AI) have aided diagnoses; however, their performance is often limited due to data imbalance. The aim of this study was to augment imbalanced medical data using generative adversarial networks (GANs) and evaluate the clinical quality of the generated images via a multi-center visual Turing test. METHODS: Using six chest radiograph datasets, (MIMIC, CheXPert, CXR8, JSRT, VBD, and OpenI), starGAN v2 generated chest radiographs with specific pathologies. Five board-certified radiologists from three university hospitals, each with at least five years of clinical experience, evaluated the image quality through a visual Turing test. Further evaluations were performed to investigate whether GAN augmentation enhanced the convolutional neural network (CNN) classifier performances. RESULTS: In terms of identifying GAN images as artificial, there was no significant difference in the sensitivity between radiologists and random guessing (result of radiologists: 147/275 (53.5%) vs result of random guessing: 137.5/275, (50%); p = .284). GAN augmentation enhanced CNN classifier performance by 11.7%. CONCLUSION: Radiologists effectively classified chest pathologies with synthesized radiographs, suggesting that the images contained adequate clinical information. Furthermore, GAN augmentation enhanced CNN performance, providing a bypass to overcome data imbalance in medical AI training. CNN based methods rely on the amount and quality of training data; the present study showed that GAN augmentation could effectively augment training data for medical AI.