Impact of AI-assisted CXR analysis in detecting incidental lung nodules and lung cancers in non-respiratory outpatient clinics.

Purpose: The use of artificial intelligence (AI) for chest X-ray (CXR) analysis is becoming increasingly prevalent in medical environments. This study aimed to determine whether AI in CXR can unexpectedly detect lung nodule detection and influence patient diagnosis and management in non-respiratory outpatient clinics. Methods: In this retrospective study, patients over 18 years of age, who underwent CXR at Yongin Severance Hospital outpatient clinics between March 2021 and January 2023 and were identified to have lung nodules through AI software, were included. Commercially available AI-based lesion detection software (Lunit INSIGHT CXR) was used to detect lung nodules. Results: Out Of 56,802 radiographic procedures, 40,191 were from non-respiratory departments, with AI detecting lung nodules in 1,754 cases (4.4%). Excluding 139 patients with known lung lesions, 1,615 patients were included in the final analysis. Out of these, 30.7% (495/1,615) underwent respiratory consultation and 31.7% underwent chest CT scans (512/1,615). As a result of the CT scans, 71.5% (366 cases) were found to have true nodules. Among these, the final diagnoses included 36 lung cancers (7.0%, 36/512), 141 lung nodules requiring follow-up (27.5%, 141/512), 114 active pulmonary infections (22.3%, 114/512), and 75 old inflammatory sequelae (14.6%, 75/512). The mean AI nodule score for lung cancer was significantly higher than that for other nodules (56.72 vs. 33.44, p < 0.001). Additionally, active pulmonary infection had a higher consolidation score, and old inflammatory sequelae had the highest fibrosis score, demonstrating differences in the AI analysis among the final diagnosis groups. Conclusion: This study indicates that AI-detected incidental nodule abnormalities on CXR in non-respiratory outpatient clinics result in a substantial number of clinically significant diagnoses, emphasizing AI's role in detecting lung nodules and need for further evaluation and specialist consultation for proper diagnosis and management.

Single-molecule structural and kinetic studies across sequence space.

At the core of molecular biology lies the intricate interplay between sequence, structure, and function. Single-molecule techniques provide in-depth dynamic insights into structure and function, but laborious assays impede functional screening of large sequence libraries. We introduce high-throughput Single-molecule Parallel Analysis for Rapid eXploration of Sequence space (SPARXS), integrating single-molecule fluorescence with next-generation sequencing. We applied SPARXS to study the sequence-dependent kinetics of the Holliday junction, a critical intermediate in homologous recombination. By examining the dynamics of millions of Holliday junctions, covering thousands of distinct sequences, we demonstrated the ability of SPARXS to uncover sequence patterns, evaluate sequence motifs, and construct thermodynamic models. SPARXS emerges as a versatile tool for untangling the mechanisms that underlie sequence-specific processes at the molecular scale.

Molecular Confirmation of Taenia solium Taeniasis in Child, Timor-Leste.

We report a case of Taenia solium taeniasis in a 10-year-old child in Timor-Leste, confirmed by molecular analysis, suggesting T. solium transmission to humans is occurring in Timor-Leste. Proactive measures are needed to improve public understanding of prevalence, geographic spread, and health implications of human taeniasis and cysticercosis in Timor-Leste.

Activity-based protein profiling and global proteome analysis reveal MASTL as a potential therapeutic target in gastric cancer.

BACKGROUND: Gastric cancer (GC) is a prevalent malignancy with limited therapeutic options for advanced stages. This study aimed to identify novel therapeutic targets for GC by profiling HSP90 client kinases. METHODS: We used mass spectrometry-based activity-based protein profiling (ABPP) with a desthiobiotin-ATP probe, combined with sensitivity analysis of HSP90 inhibitors, to profile kinases in a panel of GC cell lines. We identified kinases regulated by HSP90 in inhibitor-sensitive cells and investigated the impact of MASTL knockdown on GC cell behavior. Global proteomic analysis following MASTL knockdown was performed, and bioinformatics tools were used to analyze the resulting data. RESULTS: Four kinases-MASTL, STK11, CHEK1, and MET-were identified as HSP90-regulated in HSP90 inhibitor-sensitive cells. Among these, microtubule-associated serine/threonine kinase-like (MASTL) was upregulated in GC and associated with poor prognosis. MASTL knockdown decreased migration, invasion, and proliferation of GC cells. Global proteomic profiling following MASTL knockdown revealed NEDD4-1 as a potential downstream mediator of MASTL in GC progression. NEDD4-1 was also upregulated in GC and associated with poor prognosis. Similar to MASTL inhibition, NEDD4-1 knockdown suppressed migration, invasion, and proliferation of GC cells. CONCLUSIONS: Our multi-proteomic analyses suggest that targeting MASTL could be a promising therapy for advanced gastric cancer, potentially through the reduction of tumor-promoting proteins including NEDD4-1. This study enhances our understanding of kinase signaling pathways in GC and provides new insights for potential treatment strategies.

Ion pair extractant selective for LiCl and LiBr.

Improved methods for achieving the selective extraction of lithium salts from lithium sources, including rocky ores, salt-lake brines, and end-of-life lithium-ion batteries, could help address projected increases in the demand for lithium. Here, we report an ion pair receptor (2) capable of extracting LiCl and LiBr into an organic receiving phase both from the solid state and from aqueous solutions. Ion pair receptor 2 consists of a calix[4]pyrrole framework, which acts as an anion binding site, linked to a phenanthroline cation binding motif via ether linkages. Receptor 2 binds MgBr2 and CaCl2 with high selectivity over the corresponding lithium salts in a nonpolar aprotic solvent. The preference for Mg2+ and Ca2+ salts is reversed in polar protic media, allowing receptor 2 to complex LiCl and LiBr with high selectivity and affinity in organic media containing methanol or water. The effectiveness of receptor 2 as an extractant for LiCl and LiBr under liquid-liquid extraction (LLE) conditions was found to be enhanced by the presence of other potentially competitive salts in the aqueous source phase.

Regiospecific Coelenterazine Analogs for Bioassays and Molecular Imaging.

Bioluminescence (BL) generated by luciferase-coelenterazine (CTZ) reactions is broadly employed as an optical readout in bioassays and in vivo molecular imaging. In this study, we demonstrate a systematic approach to elucidate the luciferase-CTZ binding chemistry with a full set of regioisomeric CTZ analogs, where all the functional groups were regiochemically modified. When the chemical structures were categorized into Groups 1-6, the even-numbered Groups (2, 4, and 6) of the CTZ analogs are found to be exceptionally bright with NanoLuc enzyme. A CTZ analogue M2 was the brightest with NanoLuc and the reason was deciphered by a computational analysis of the binding modes. We also report that (i) the regioisomeric CTZ analogs collectively create unique intensity patterns according to each marine luciferase, (ii) the quantitative structure-activity relationship analysis revealed the roles of respective functional groups of CTZ analogs, and (iii) the regioisomeric CTZ analogs also exert red shifts of the BL spectra and color variation: that is, the λmax values are near 500 nm with NanoLuc, near 530 nm with ALuc16, and near 570 nm with RLuc86SG. The advantages of the regioisomeric CTZ analogs were finally demonstrated using (i) a dual-luciferase system with M2-specific NanoLuc and native CTZ-specific ALuc16, (ii) an estrogen activatable single-chain BL probe by imaging, and (iii) BL imaging of live mice bearing tumors expressing NanoLuc and RLuc8.6SG. This study is the first systematic approach to elucidate the regiochemistry in BL imaging studies. This study provides new insights into how CTZ analogs regiochemically work in BL reporter systems and guides the specific applications to molecular imaging.

Development and external validation of a model to predict multidrug-resistant bacterial infections in patients with cirrhosis.

With the increasing rate of infections caused by multidrug-resistant organisms (MDRO), selecting appropriate empiric antibiotics has become challenging. We aimed to develop and externally validate a model for predicting the risk of MDRO infections in patients with cirrhosis. METHODS: We included patients with cirrhosis and bacterial infections from two prospective studies: a transcontinental study was used for model development and internal validation (n = 1302), and a study from Argentina and Uruguay was used for external validation (n = 472). All predictors were measured at the time of infection. Both culture-positive and culture-negative infections were included. The model was developed using logistic regression with backward stepwise predictor selection. We externally validated the optimism-adjusted model using calibration and discrimination statistics and evaluated its clinical utility. RESULTS: The prevalence of MDRO infections was 19% and 22% in the development and external validation datasets, respectively. The model's predictors were sex, prior antibiotic use, type and site of infection, MELD-Na, use of vasopressors, acute-on-chronic liver failure, and interaction terms. Upon external validation, the calibration slope was 77 (95% CI .48-1.05), and the area under the ROC curve was .68 (95% CI .61-.73). The application of the model significantly changed the post-test probability of having an MDRO infection, identifying patients with nosocomial infection at very low risk (8%) and patients with community-acquired infections at significant risk (36%). CONCLUSION: This model achieved adequate performance and could be used to improve the selection of empiric antibiotics, aligning with other antibiotic stewardship program strategies.

Primary treatments for solitary hepatocellular carcinoma ≤ 3 cm: A systematic review and network meta-analysis.

Various treatment modalities are available for small solitary hepatocellular carcinoma (HCC), yet the optimal primary treatment strategy for tumors ≤ 3 cm remains unclear. This network meta-analysis investigates the comparative efficacy of various interventions on the long-term outcomes of patients with solitary HCC ≤ 3 cm. A systematic search of electronic databases from January 2000 to December 2023 was conducted to identify studies that compared at least two of the following treatments: surgical resection (SR), radiofrequency ablation (RFA), microwave ablation (MWA), and transarterial chemoembolization (TACE). Survival data were extracted, and pooled hazard ratios with 95% confidence intervals were calculated using a frequentist network meta-analysis. A total of 30 studies, comprising 2 randomized controlled trials and 28 retrospective studies, involving 8,053 patients were analyzed. Surgical resection showed the highest overall survival benefit with a p-score of 0.95, followed by RFA at 0.59, MWA at 0.23, and TACE, also at 0.23. Moreover, SR provided the most significant recurrence-free survival advantage, with a p-score of 0.95, followed by RFA at 0.31 and MWA at 0.19. Sensitivity analyses, excluding low-quality or retrospective non-matched studies, corroborated these findings. This network meta-analysis demonstrates that SR is the most effective first-line curative treatment for single HCC ≤ 3 cm, followed by RFA in patients with preserved liver function. The limited data on MWA and TACE underscore the need for further studies.

Machine Learning-Based Predictive Models for Early Detection of Cardiovascular Diseases: A Study Utilizing Patient Samples from a Tertiary Health Promotion Center in Korea.

A machine learning model was developed for cardiovascular diseases prediction based on 21,118 patient checkups data from a tertiary medical institution in Seoul, Korea, collected between 2009 and 2021. XGBoost algorithm showed the highest predictive performance, with an average AUROC of 0.877. In survival analysis, XGBSE achieved an AUROC exceeding 0.9 for 2-9 year predictions, with a C-index of 0.878 across all diseases, outperforming Cox regression (C-index of 0.887). A high-performance prediction model for cardiovascular diseases using the XGBSE algorithm was successfully developed and is poised for real-world clinical application following external simplification and validation.

Senescence-associated microvascular endothelial dysfunction: A focus on the blood-brain and blood-retinal barriers.

The blood-brain barrier (BBB) and blood-retinal barrier (BRB) constitute critical physiochemical interfaces, precisely orchestrating the bidirectional communication between the brain/retina and blood. Increased permeability or leakage of these barriers has been demonstrably linked to age-related vascular and parenchymal damage. While it has been suggested that the gradual aging process may coincide with disruptions in these barriers, this phenomenon is significantly exacerbated in individuals with age-related neurodegenerative disorders (ARND). This review focuses on the microvascular endothelium, a key constituent of BBB and BRB, highlighting the impact of endothelial senescence on barrier dysfunction and exploring recent discoveries regarding core pathways implicated in its breakdown. Subsequently, we address the "vascular senescence hypothesis" for ARND, with a particular emphasis on Alzheimer's disease and age-related macular degeneration, centered on endothelial senescence. Finally, we discuss potential senotherapeutic strategies targeting barrier dysfunction.

Orally dissolving film as a potential vaccine delivery carrier to prevent influenza virus infection.

Orally dissolving films (ODF) are designed to be dissolved on the tongue and absorbed in the mouth. It offers multiple advantages over the commonly used needle-based vaccines, especially in terms of convenience allowing safe, painless, and easy self-administration. As the efficacy of ODF-encapsulated influenza vaccines has not been demonstrated, we assessed the protection elicited by inactivated influenza virus (A/PR/8/34, PR8) vaccine delivered using ODFs in mice. Trehalose and pullulan components of the ODF ensured that the HA antigens of the inactivated PR8 virus retained their stability while ensuring the rapid release of the vaccines upon exposure to murine saliva. Mice were immunized thrice by placing the PR8-ODF on the tongues of mice at 4-week intervals, and vaccine-induced protection was evaluated upon lethal homologous challenge infection. The PR8-ODF vaccination elicited virus-specific serum IgG and IgA antibody responses, hemagglutinin inhibition (HAI), and viral neutralization. Upon challenge infection, ODF vaccination showed higher levels of IgG and IgA antibody responses in the lungs and antibody-secreting cell (ASC) responses in both lung and spleen compared to unimmunized controls. These results corresponded with the enhanced T cell and germinal center B cell responses in the lungs and spleens. Importantly, ODF vaccination significantly reduced lung virus titers and inflammatory cytokines (IFN-γ, IL-6) production compared to unvaccinated control. ODF vaccination ensured 100% survival and prevented weight loss in mice. These findings suggest that influenza vaccine delivery through ODFs could be a promising approach for oral vaccine development.

Speakers-Used as sensors for detecting acoustic loads with artificial intelligence.

Previous research demonstrated the potential of using speakers as sensors to detect ear canal conditions. This study continues that effort by using a single speaker to measure electrical impedance across various acoustic loads. Electrical impedance data were collected and preprocessed for machine learning model training. Different image forms were tested, including magnitude only and combined magnitude phase. Using 2100 data samples with convolutional neural network-based models (AlexNet, ResNet, and DenseNet), binary and multiclass classifications achieved average accuracies of 0.9716 and 0.907, respectively. This innovative approach is set to revolutionize acoustic sensing through artificial intelligence.

Efficacy of Saccharomyces yeast postbiotics on cell turnover, immune responses, and oxidative stress in the jejunal mucosa of young pigs.

This study aimed to determine the effects of Saccharomyces yeast postbiotics on cell turnover, immune responses, and oxidative stress in the jejunal mucosa of pigs. Thirty-two newly weaned pigs at 6.05 ± 0.24 kg were assigned to two dietary treatments based on a randomized complete block design. The treatments were control group receiving a basal diet and a group supplemented with Saccharomyces yeast postbiotics (175 g/ton diet) in the basal diet. After 35 d of the study, pigs were euthanized and jejunal mucosa were collected to assess immune status, oxidative stress, barrier markers, cell proliferation, and apoptosis. Saccharomyces yeast postbiotics reduced (P < 0.05) the fecal score from d 3 to d 7 and tended to increase the gene expression of interferon-γ (IFN-γ) (P = 0.071) and mammalian/mechanistic target of rapamycin (mTOR) (P = 0.080), decrease the gene expression of B-cell lymphoma 2-associated X protein 1 (BAX1) (P < 0.05), tended to decrease the gene expression of serum and glucocorticoid-induced protein kinase 1 (SGK1) (P = 0.066), increased (P < 0.05) cell proliferation in the crypts, and tended to increase the villus height (P = 0.078) and crypt depth (P = 0.052) in the jejunum. In conclusion, the supplementation of Saccharomyces yeast postbiotics in nursery diets reduced diarrhea within the first week after weaning and provided protection to the villi in the jejunum by enhancing the immune responses of nursery pigs, promoting crypt cell proliferation, and reducing the expression of genes associated with apoptosis without affecting inflammatory and oxidative stress status in the jejunum of the nursery pigs.

Laparoscopic resection for retroperitoneum ganglioneuroma with Supine hypotension syndrome.

BACKGROUND: Supine hypotension syndrome (SHS) has been reported to occur due to compression by a giant tumor such as ovarian tumor. We herein report a case of retroperitoneal ganglioneuroma with SHS treated with laparoscopic resection. CASE PRESENTATION: The patient was an 11-year-old male with right-sided abdominal pain. He had a pale complexion and tachycardia while falling asleep. Computed tomography (CT) and magnetic resonance imaging (MRI) showed a giant mass lesion (60 × 35 mm) with compression of the inferior vena cava (IVC) and duodenum ventrally and the right kidney caudally. The IVC was flattened by mass compression. Abdominal ultrasonography (US) revealed narrowing of the IVC due to the mass and accelerated blood flow after IVC stenosis in the supine and left lateral recumbent position. His pale complexion and tachycardia while falling asleep was thought to be due to decreased venous return caused by the tumor compressing the IVC, resulting hypotension. 123I-MIBG scintigraphy revealed no abnormal findings. Tumor markers were normal. He was diagnosed with SHS due to a right adrenal gland tumor. The tumor compressed the IVC from the dorsal side, and hemostasis was expected to be difficult during bleeding. Therefore, a guidewire was inserted from the right femoral vein into the IVC for emergency balloon insertion during bleeding. A laparoscopic tumor resection was performed. A histopathological examination confirmed the diagnosis of primary retroperitoneal ganglioneuroma. CONCLUSIONS: The treatment of symptomatic retroperitoneal tumors requires a multidisciplinary approach.

A neural basis for learning sequential memory in brain loop structures.

Introduction: Behaviors often involve a sequence of events, and learning and reproducing it is essential for sequential memory. Brain loop structures refer to loop-shaped inter-regional connection structures in the brain such as cortico-basal ganglia-thalamic and cortico-cerebellar loops. They are thought to play a crucial role in supporting sequential memory, but it is unclear what properties of the loop structure are important and why. Methods: In this study, we investigated conditions necessary for the learning of sequential memory in brain loop structures via computational modeling. We assumed that sequential memory emerges due to delayed information transmission in loop structures and presented a basic neural activity model and validated our theoretical considerations with spiking neural network simulations. Results: Based on this model, we described the factors for the learning of sequential memory: first, the information transmission delay should decrease as the size of the loop structure increases; and second, the likelihood of the learning of sequential memory increases as the size of the loop structure increases and soon saturates. Combining these factors, we showed that moderate-sized brain loop structures are advantageous for the learning of sequential memory due to the physiological restrictions of information transmission delay. Discussion: Our results will help us better understand the relationship between sequential memory and brain loop structures.

Propolis suppresses atopic dermatitis through targeting the MKK4 pathway.

Propolis is a natural resinous substance made by bees through mixing various plant sources. Propolis has been widely recognized as a functional food due to its diverse range of beneficial bioactivities. However, the therapeutic effects of consuming propolis against atopic dermatitis (AD) remain largely unknown. The current study aimed to investigate the potential efficacy of propolis against AD and explore the active compound as well as the direct molecular target. In HaCaT keratinocytes, propolis inhibited TNF-α-induced interleukin (IL)-6 and IL-8 secretion. It also led to a reduction in chemokines such as monocyte chemoattractant protein-1 (MCP-1) and macrophage-derived chemokine (MDC), while restoring the levels of barrier proteins, filaggrin and involucrin. Propolis exhibited similar effects in AD-like human skin, leading to the suppression of AD markers and the restoration of barrier proteins. In DNCB-induced mice, oral administration of propolis attenuated AD symptoms, improved barrier function, and reduced scratching frequency and transepidermal water loss (TEWL). In addition, propolis reversed the mRNA levels of AD-related markers in mouse dorsal skin. These effects were attributed to caffeic acid phenethyl ester (CAPE), the active compound identified by comparing major components of propolis. Mechanistic studies revealed that CAPE as well as propolis could directly and selectively target MKK4. Collectively, these findings demonstrate that propolis may be used as a functional food agent for the treatment of AD.

Polymorphism analysis of tri- and tetranucleotide repeat microsatellite markers in Hanwoo cattle.

The Hanwoo traceability system currently utilizes 11 dinucleotide repeat microsatellite (MS) markers. However, dinucleotide repeat markers are known to have a high incidence of polymerase chain reaction (PCR) artifacts, such as stutter bands, which can complicate the accurate reading of alleles. In this study, we examined the polymorphisms of the 11 dinucleotide repeat MS markers currently employed in traceability systems. Additionally, we explored four trinucleotide repeat MS markers and one tetranucleotide repeat MS marker in a sample of 1,106 Hanwoo cattle. We also assessed the potential utility of the tri- and tetranucleotide repeat MS markers. The polymorphic information content (PIC) of the five tri- and tetranucleotide repeat markers ranged from 0.663 to 0.767 (mean: 0.722), sufficiently polymorphic and slightly higher than the mean (0.716) of the current 11 dinucleotide repeat markers. Using all 16 markers, the mean PIC was 0.718. The estimated probability of identity (PI) was 3.13 × 10-12 using the 11 dinucleotide repeat markers, 7.03 × 10-6 using the five tri- and tetranucleotide repeat markers, and 2.39 × 10-17 using all 16 markers; the respective PIhalf-sibs values were 2.69 × 10-9, 1.29 × 10-4, and 3.42 × 10-13; and the respective PIsibs values were 3.89 × 10-5, 9.6 × 10-3, and 3.69 × 10-7. The probability of exclusion1 (PE1) was 0.999864 for the 11 dinucleotide repeat markers, 0.981141 for five of the tri- and tetranucleotide repeat markers, and > 0.99 for all 16 markers; the respective PE2 values were 0.994632, 0.901369, and > 0.99; and the respective PE3 values were 0.998702, > 0.99, and > 0.99. The five investigated tri- and tetranucleotide repeat MS markers can be used in combination with the 11 existing MS markers to improve the accuracy of individual identification and paternity testing in Hanwoo.

Forensic height estimation using polygenic score in Korean population.

Height is known to be a classically heritable trait controlled by complex polygenic factors. Numerous height-associated genetic variants across the genome have been identified so far. It is also a representative of externally visible characteristics (EVC) for predicting appearance in forensic science. When biological evidence at a crime scene is deficient in identifying an individual, the examination of forensic DNA phenotyping using some genetic variants could be considered. In this study, we aimed to predict 'height', a representative forensic phenotype, by using a small number of genetic variants when short tandem repeat (STR) analysis is hard with insufficient biological samples. Our results not only replicated previous genetic signals but also indicated an upward trend in polygenic score (PGS) with increasing height in the validation and replication stages for both genders. These results demonstrate that the established SNP sets in this study could be used for height estimation in the Korean population. Specifically, since the PGS model constructed in this study targets only a small number of SNPs, it contributes to enabling forensic DNA phenotyping even at crime scenes with a minimal amount of biological evidence. To the best of our knowledge, this was the first study to evaluate a PGS model for height estimation in the Korean population using GWAS signals. Our study offers insight into the polygenic effect of height in East Asians, incorporating genetic variants from non-Asian populations.

Deep-Transfer-Learning-Based Natural Language Processing of Serial Free-Text Computed Tomography Reports for Predicting Survival of Patients With Pancreatic Cancer.

PURPOSE: To explore the predictive potential of serial computed tomography (CT) radiology reports for pancreatic cancer survival using natural language processing (NLP). METHODS: Deep-transfer-learning-based NLP models were retrospectively trained and tested with serial, free-text CT reports, and survival information of consecutive patients diagnosed with pancreatic cancer in a Korean tertiary hospital was extracted. Randomly selected patients with pancreatic cancer and their serial CT reports from an independent tertiary hospital in the United States were included in the external testing data set. The concordance index (c-index) of predicted survival and actual survival, and area under the receiver operating characteristic curve (AUROC) for predicting 1-year survival were calculated. RESULTS: Between January 2004 and June 2021, 2,677 patients with 12,255 CT reports and 670 patients with 3,058 CT reports were allocated to training and internal testing data sets, respectively. ClinicalBERT (Bidirectional Encoder Representations from Transformers) model trained on the single, first CT reports showed a c-index of 0.653 and AUROC of 0.722 in predicting the overall survival of patients with pancreatic cancer. ClinicalBERT trained on up to 15 consecutive reports from the initial report showed an improved c-index of 0.811 and AUROC of 0.911. On the external testing set with 273 patients with 1,947 CT reports, the AUROC was 0.888, indicating the generalizability of our model. Further analyses showed our model's contextual interpretation beyond specific phrases. CONCLUSION: Deep-transfer-learning-based NLP model of serial CT reports can predict the survival of patients with pancreatic cancer. Clinical decisions can be supported by the developed model, with survival information extracted solely from serial radiology reports.