The effect of nebulized N-acetylcysteine on the phlegm of chronic obstructive pulmonary disease: the NEWEST study.

BACKGROUND: Phlegm is prevalent symptom in patients with chronic obstructive pulmonary disease (COPD). Few studies have investigated the effectiveness of N-acetylcysteine (NAC) nebulizer therapy in COPD patients. We evaluated the effect of nebulized NAC on the improvement of phlegm symptom in COPD patients. METHODS: This was a 12-week, prospective, single-arm, open-label, phase IV multi-center trial (NCT05102305, Registration Date: 20-October-2021). We enrolled patients aged ≥ 40 years with post bronchodilator forced expiratory volume in one second/forced vital capacity (FEV1/FVC) < 0.7 and COPD assessment test (CAT) phlegm score ≥ 2; the patients were current or ex-smoker with smoking pack-years ≥ 10. The primary endpoint was to determine the change in CAT phlegm score at 12 weeks compared to the baseline. Patients were assessed at baseline, 4, 8, and 12 weeks of treatment using the CAT score. RESULTS: In total, 100 COPD patients were enrolled from 10 hospitals. The mean age of the patients was 71.42 ± 8.20 years, with 19.78% being current-smokers and 80.22% being ex-smokers. The mean smoking pack-years was 40.32 ± 35.18. The mean FVC, FEV1, and FEV1/FVC were 3.94 L (75.44%), 2.22 L (58.50%), and 0.53, respectively. The CAT phlegm score at baseline was 3.47 ± 1.06, whereas after 12 weeks of nebulized NAC it significantly decreased to 2.62 ± 1.30 (p < 0.01). More than half (53.5%) of the patients expressed satisfaction with the effects of nebulized NAC therapy. Adverse events occurred in 8 (8.0%) patients. Notably, no serious adverse drug reactions were reported. CONCLUSION: In this study, we have established the effectiveness and safety of nebulized NAC over 12 weeks.

The association between cumulative exposure to PM2.5 and DNA methylation measured using methyl-capture sequencing among COPD patients.

BACKGROUND: Particulate matter with a diameter of < 2.5 µm (PM2.5) influences gene regulation via DNA methylation; however, its precise mechanism of action remains unclear. Thus, this study aimed to examine the connection between personal PM2.5 exposure and DNA methylation in CpG islands as well as explore the associated gene pathways. METHODS: A total of 95 male patients with chronic obstructive pulmonary disease (COPD) were enrolled in this study. PM2.5 concentrations were measured for 12 months, with individual exposure recorded for 24 h every 3 months. Mean indoor and estimated individual PM2.5 exposure levels were calculated for short-term (7 days), mid-term (35 days), and long-term (90 days). DNA methylation analysis was performed on the blood samples, which, after PCR amplification and hybridization, were finally sequenced using an Illumina NovaSeq 6000 system. Correlation between PM2.5 exposure and CpG methylation sites was confirmed via a mixed-effects model. Functional enrichment analysis was performed on unique CpG methylation sites associated with PM2.5 exposure to identify the relevant biological functions or pathways. RESULTS: The number of CpG sites showing differential methylation was 36, 381, and 182 for the short-, mid-, and long-term indoor models, respectively, and 3, 98, and 28 for the short-, mid-, and long-term estimated exposure models, respectively. The representative genes were TMTC2 (p = 1.63 × 10-3, R2 = 0.656), GLRX3 (p = 1.46 × 10-3, R2 = 0.623), DCAF15 (p = 2.43 × 10-4, R2 = 0.623), CNOT6L (p = 1.46 × 10-4, R2 = 0.609), BSN (p = 2.21 × 10-5, R2 = 0.606), and SENP6 (p = 1.59 × 10-4, R2 = 0.604). Functional enrichment analysis demonstrated that the related genes were mostly associated with pathways related to synaptic transmission in neurodegenerative diseases and cancer. CONCLUSION: A significant association was observed between PM2.5 exposure and DNA methylation upon short-term exposure, and the extent of DNA methylation was the highest upon mid-term exposure. Additionally, various pathways related to neurodegenerative diseases and cancer were associated with patients with COPD. GOV IDENTIFIER: NCT04878367.

Anoikis in cell fate, physiopathology, and therapeutic interventions.

The extracellular matrix (ECM) governs a wide spectrum of cellular fate processes, with a particular emphasis on anoikis, an integrin-dependent form of cell death. Currently, anoikis is defined as an intrinsic apoptosis. In contrast to traditional apoptosis and necroptosis, integrin correlates ECM signaling with intracellular signaling cascades, describing the full process of anoikis. However, anoikis is frequently overlooked in physiological and pathological processes as well as traditional in vitro research models. In this review, we summarized the role of anoikis in physiological and pathological processes, spanning embryonic development, organ development, tissue repair, inflammatory responses, cardiovascular diseases, tumor metastasis, and so on. Similarly, in the realm of stem cell research focused on the functional evolution of cells, anoikis offers a potential solution to various challenges, including in vitro cell culture models, stem cell therapy, cell transplantation, and engineering applications, which are largely based on the regulation of cell fate by anoikis. More importantly, the regulatory mechanisms of anoikis based on molecular processes and ECM signaling will provide new strategies for therapeutic interventions (drug therapy and cell-based therapy) in disease. In summary, this review provides a systematic elaboration of anoikis, thus shedding light on its future research.

Safeguarding Public Health: Advanced Detection of Food Adulteration Using Nanoparticle-Based Sensors.

Food adulteration, whether intentional or accidental, poses a significant public health risk. Traditional detection methods often lack the precision required to detect subtle adulterants that can be harmful. Although chromatographic and spectrometric techniques are effective, their high cost and complexity have limited their widespread use. To explore and validate the application of nanoparticle-based sensors for enhancing the detection of food adulteration, focusing on their specificity, sensitivity, and practical utility in the development of resilient food safety systems. This study integrates forensic principles with advanced nanomaterials to create a robust detection framework. Techniques include the development of nanoparticle-based assays designed to improve the detection specificity and sensitivity. In addition, sensor-based technologies, including electronic noses and tongues, have been assessed for their capacity to mimic and enhance human sensory detection, offering objective and reliable results. The use of nanomaterials, including functionalized nanoparticles, has significantly improved the detection of trace amounts of adulterants. Nanoparticle-based sensors demonstrate superior performance in terms of speed, sensitivity, and selectivity compared with traditional methods. Moreover, the integration of these sensors into food safety protocols shows promise for real-time and onsite detection of adulteration. Nanoparticle-based sensors represent a cutting-edge approach for detecting food adulteration, and offer enhanced sensitivity, specificity, and scalability. By integrating forensic principles and nanotechnology, this framework advances the development of more resilient food-safety systems. Future research should focus on optimizing these technologies for widespread application and adapting them to address emerging adulteration threats.

Reliability of brain volume measures of accelerated 3D T1-weighted images with deep learning-based reconstruction.

PURPOSE: The time-intensive nature of acquiring 3D T1-weighted MRI and analyzing brain volumetry limits quantitative evaluation of brain atrophy. We explore the feasibility and reliability of deep learning-based accelerated MRI scans for brain volumetry. METHODS: This retrospective study collected 3D T1-weighted data using 3T from 42 participants for the simulated acceleration dataset and 48 for the validation dataset. The simulated acceleration dataset consists of three sets at different simulated acceleration levels (Simul-Accel) corresponding to level 1 (65% undersampling), 2 (70%), and 3 (75%). These images were then subjected to deep learning-based reconstruction (Simul-Accel-DL). Conventional images (Conv) without acceleration and DL were set as the reference. In the validation dataset, DICOM images were collected from Conv and accelerated scan with DL-based reconstruction (Accel-DL). The image quality of Simul-Accel-DL was evaluated using quantitative error metrics. Volumetric measurements were evaluated using intraclass correlation coefficients (ICCs) and linear regression analysis in both datasets. The volumes were estimated by two software, NeuroQuant and DeepBrain. RESULTS: Simul-Accel-DL across all acceleration levels revealed comparable or better error metrics than Simul-Accel. In the simulated acceleration dataset, ICCs between Conv and Simul-Accel-DL in all ROIs exceeded 0.90 for volumes and 0.77 for normative percentiles at all acceleration levels. In the validation dataset, ICCs for volumes > 0.96, ICCs for normative percentiles > 0.89, and R2 > 0.93 at all ROIs except pallidum demonstrated good agreement in both software. CONCLUSION: DL-based reconstruction achieves clinical feasibility of 3D T1 brain volumetric MRI by up to 75% acceleration relative to full-sampled acquisition.

Similarity analyses of causative viruses for chronic obstructive pulmonary disease and asthma exacerbations : Author.

BACKGROUND: The representativeness of cohort studies compared to nationwide data is a major concern. This study evaluated the similarity and seasonality of causative respiratory viruses for chronic obstructive pulmonary disease (COPD) and asthma exacerbations between retrospective multicenter cohort study and nationwide data. METHODS: We compared data from the retrospective multicenter cohort study with Korean Influenza and Respiratory Surveillance System data between 2015 and 2018. Correlation, dynamic time warping (DTW), and seasonal autoregressive integrated moving average (SARIMA) analyses were performed. RESULTS: Spearman correlation coefficients [ρ] indicated very strong (respiratory syncytial virus [RSV] [ρ = 0.8458] and influenza virus [IFV] [ρ = 0.8272]), strong (human metapneumovirus [HMPV] [ρ = 0.7177] and parainfluenza virus [PIV] [ρ = 0.6742]), and moderate (rhinovirus [RV] [ρ = 0.5850] and human coronavirus [HCoV] [ρ = 0.5158]) correlations. DTW analyses showed moderate (PIV) and high (IFV, RSV, and HMPV) synchronicity between the two datasets, while RV and HCoV showed low synchronicity. SARIMA analyses revealed 12-month seasonality for IFV, RSV, PIV, and HMPV. The peak season was winter for RSV and IFV, spring to summer for PIV, and spring for HMPV. CONCLUSIONS: This was the first study to report the synchronicity between a retrospective multicenter cohort study of viruses that can cause COPD or asthma exacerbations and nationwide surveillance system data.

Development and Validation of a Real-Time Service Model for Noise Removal and Arrhythmia Classification Using Electrocardiogram Signals.

Arrhythmias range from mild nuisances to potentially fatal conditions, detectable through electrocardiograms (ECGs). With advancements in wearable technology, ECGs can now be monitored on-the-go, although these devices often capture noisy data, complicating accurate arrhythmia detection. This study aims to create a new deep learning model that utilizes generative adversarial networks (GANs) for effective noise removal and ResNet for precise arrhythmia classification from wearable ECG data. We developed a deep learning model that cleans ECG measurements from wearable devices and detects arrhythmias using refined data. We pretrained our model using the MIT-BIH Arrhythmia and Noise databases. Least squares GANs were used for noise reduction, maintaining the integrity of the original ECG signal, while a residual network classified the type of arrhythmia. After initial training, we applied transfer learning with actual ECG data. Our noise removal model significantly enhanced data clarity, achieving over 30 dB in a signal-to-noise ratio. The arrhythmia detection model was highly accurate, with an F1-score of 99.10% for noise-free data. The developed model is capable of real-time, accurate arrhythmia detection using wearable ECG devices, allowing for immediate patient notification and facilitating timely medical response.

A Prospective Clinical Trial of Radiofrequency Ablation in Patients with Low-Risk Unifocal Papillary Thyroid Microcarcinoma Favoring Active Surveillance Over Surgery.

Background: Active surveillance (AS) of papillary thyroid microcarcinomas (PTMC) is emerging as an alternative to immediate surgery. While thermal ablation has also shown promise for low-risk PTMC, it has not been prospectively studied in patients appropriate for AS. This study aimed to evaluate the efficacy and safety of ultrasound (US)-guided radiofrequency ablation (RFA) for tumor control and quality of life (QoL) management in patients with PTMC who favored AS over immediate surgery. Methods: This prospective clinical trial was conducted at a single tertiary referral hospital from 2018 to 2021. Of 227 adult patients aged ≤60 years with low-risk unifocal PTMC favoring AS over immediate surgery, 100 patients underwent RFA for their management. The primary endpoint was the disease progression rate, and secondary endpoints were technical success, volume reduction rate (VRR), complication rates, and QoL. Results: The median age of the study population was 42 years (range, 27-59 years), and 83% (83/100, [CI: 66.1-100]) were female. The median follow-up was 30 months (range, 12-56 months). All 100 patients underwent RFA with technical success. Most of the ablation zones showed continuous volume reduction, and 95.9% (94/98, [CI: 77.5-100.0]) showed complete disappearance at the last follow-up. The median VRR was 100.0% at 1-year follow-up and persisted throughout the last follow-up. The cumulative disease progression rate among 98 patients who underwent at least 1-year follow-up was 3.1% (3/98, [CI: 0.6-9.0]); one patient had lymph node metastasis (treated with surgery), and two patients had new PTMC (1 treated with RFA, 1 ongoing AS). Major complications were not observed. Psychological (baseline vs. last follow-up, 7.3 vs. 8.0, p = 0.002) and social (8.0 vs. 8.7, p = 0.005) QoL scores significantly improved during follow-up without compromising physical QoL (8.6 vs. 8.5, p = 0.99). Conclusions: RFA can be a reasonable strategy for effectively and safely controlling tumors and improving QoL in non-elderly patients with low-risk PTMC appropriate for AS. Clinical Trial registration: This trial is registered with ClinicalTrials.gov: NCT03432299.

Malnutrition is associated with mortality in Sjögren's syndrome-associated interstitial lung disease.

The role of nutritional status as a prognostic factor in patients with Sjögren's syndrome-associated interstitial lung disease (SjS-ILD) is currently unclear. This study aimed to predict the prognosis of patients with SjS-ILD through their nutritional status assessment. In this retrospective observational study, nutritional status was evaluated at the time of diagnosis using body mass index (BMI) and nutritional markers such as controlling nutritional status (CONUT), the Glasgow prognostic score (GPS), and prognostic nutrition index (PNI) for all participants. Receiver operating characteristic (ROC) analyses were performed using BMI and each nutritional marker data to compare the area under the ROC curve (AUC) and find the cutoff value using the maximum Youden index. Kaplan-Meier analysis and Cox proportional hazards regression analysis were performed to predict the prognosis of SjS-ILD patients. A total of 112 SjS-ILD patients were enrolled in the study, and 8.9% died during the follow-up period. The median time from diagnosis to follow-up period was 4.2 years. The AUC for PNI was the highest among nutritional markers and BMI, and PNI cutoff value was used to distinguish between the PNI < 47.7 and PNI ≥ 47.7 groups. A statistical difference was observed in the Kaplan-Meier analysis and log-rank test (p = 0.005). In multivariable analyses, PNI < 47.7 (hazard ratio 9.40, 95% confidence interval 1.54-57.21) is associated with increased mortality, suggesting the importance of early nutritional intervention for malnutrition in SjS-ILD patients.

Molecular Identification of Spotted Fever Group Rickettsiae in Ticks in the Republic of Korea.

The Rickettsia species transmitted by ticks are mostly classified within the spotted fever group rickettsiae (SFGR), which causes tick-borne rickettsiosis. Although efforts have been made to investigate their prevalence in the Republic of Korea (ROK), research has been limited to certain areas. Furthermore, the pooling method for ticks does not fully reflect the exact infection rate. Therefore, we aimed to perform molecular identification of SFGR in ticks to elucidate the current prevalence of tick-borne rickettsiosis in the ROK. The SFGR of ticks was identified using polymerase chain reaction targeting the 17 kDa antigen, ompA, and gltA, followed by sequencing for species identification and phylogenetic analysis. In total, 302 ticks belonging to four species (Haemaphysalis flava, H. longicornis, Ixodes nipponensis, and Amblyomma testudinarium) were collected between April and November 2022. The overall SFGR infection rate was 26.8% (81/302 patients). Both adult and nymphal ticks and the SFGR infection rate increased during April-May, reaching their peaks in June, followed by a marked decline in August and July, respectively. Phylogenetic analysis revealed three species (R. monacensis, R. heilongjiangensis, and Candidatus R. jingxinensis) of SFGR. Thus, our results emphasize the importance of tick surveys for the prevention and management of tick-borne rickettsiosis.

Gut microbiota-based machine-learning signature for the diagnosis of alcohol-associated and metabolic dysfunction-associated steatotic liver disease.

Alcoholic-associated liver disease (ALD) and metabolic dysfunction-associated steatotic liver disease (MASLD) show a high prevalence rate worldwide. As gut microbiota represents current state of ALD and MASLD via gut-liver axis, typical characteristics of gut microbiota can be used as a potential diagnostic marker in ALD and MASLD. Machine learning (ML) algorithms improve diagnostic performance in various diseases. Using gut microbiota-based ML algorithms, we evaluated the diagnostic index for ALD and MASLD. Fecal 16S rRNA sequencing data of 263 ALD (control, elevated liver enzyme [ELE], cirrhosis, and hepatocellular carcinoma [HCC]) and 201 MASLD (control and ELE) subjects were collected. For external validation, 126 ALD and 84 MASLD subjects were recruited. Four supervised ML algorithms (support vector machine, random forest, multilevel perceptron, and convolutional neural network) were used for classification with 20, 40, 60, and 80 features, in which three nonsupervised ML algorithms (independent component analysis, principal component analysis, linear discriminant analysis, and random projection) were used for feature reduction. A total of 52 combinations of ML algorithms for each pair of subgroups were performed with 60 hyperparameter variations and Stratified ShuffleSplit tenfold cross validation. The ML models of the convolutional neural network combined with principal component analysis achieved areas under the receiver operating characteristic curve (AUCs) > 0.90. In ALD, the diagnostic AUC values of the ML strategy (vs. control) were 0.94, 0.97, and 0.96 for ELE, cirrhosis, and liver cancer, respectively. The AUC value (vs. control) for MASLD (ELE) was 0.93. In the external validation, the AUC values of ALD and MASLD (vs control) were > 0.90 and 0.88, respectively. The gut microbiota-based ML strategy can be used for the diagnosis of ALD and MASLD.ClinicalTrials.gov NCT04339725.

ARHGEF5 binds Drebrin and affects α-tubulin acetylation to direct neuronal morphogenesis and migration during mouse brain development.

Rho guanine nucleotide exchange factors (Rho GEFs) activate Rho GTPases, which act as molecular switches regulating various essential cellular functions. This study investigated the role of ARHGEF5, a Rho GEF known for its involvement in cell migration and invasion processes, in the context of brain development. We found that ARHGEF5 is essential for dendrite development during the early stages of neuronal growth. We also discovered that ARHGEF5 binds to Drebrin E, which is vital for coordinating actin and microtubule dynamics, and facilitates the interaction between Drebrin E and Cyclin-dependent kinase 5, which phosphorylates Drebrin E. Notably, ARHGEF5 deficiency resulted in a decrease in acetylated α-tubulin levels, and the expression of an α-tubulin acetylation mimetic mutant (K40Q) rescued the defects in dendrite development and neuronal migration, suggesting ARHGEF5's role in modulating microtubule stability. Additionally, ARHGEF5 was shown to influence Golgi positioning in the leading processes of migrating cortical neurons during brain development. Our study suggests that ARHGEF5 plays a crucial role in integrating cytoskeletal dynamics with neuronal morphogenesis and migration processes during brain development.

Molecular Analysis of Tick-Borne Bacterial Pathogens from Ticks Infesting Animal Hosts in Kyrgyzstan, 2021.

This study investigated the prevalence of Anaplasma and Ehrlichia in 494 engorged ticks collected from various animal hosts, including cattle, horses, sheep, chickens, dogs, and cats, in six regions of northern Kyrgyzstan. Ten tick species, belonging to two families and six genera, were identified based on CO1, 16S rRNA, and ITS2 genes: Argas persicus (26.5%), Haemaphysalis punctata (18.0%), Dermacentor spp. (16.0%), Rhipicephalus annulatus (11.8%), R. turanicus (10.9%), D. marginatus (7.7%), Hyalomma scupense (4.5%), Hy. marginatum (3.8%), R. sangineus complex (0.6%), and Ornithodoros lahorensis (0.2%). PCR analysis revealed a 15.0% (74/494) overall infection rate of Anaplasma and Ehrlichia. Anaplasma species were found in six tick species and were identified as A. bovis (n = 44), Anaplasma spp. (n = 20), A. ovis (n = 5), and A. capra (n = 2). Ehrlichia species were found only in H. punctata (n = 5) and identified as E. chaffeensis (n = 1) and Ehrlichia spp. (n = 4). Additionally, two H. punctata were co-infected with Anaplasma and Ehrlichia. This is the first study to investigate tick-borne bacterial pathogens in ticks collected from animal hosts in Kyrgyzstan. Our findings contribute to a better understanding of the epidemiology and emergence of tick-borne infections in Kyrgyzstan.

Heat-Killed Lactococcus Lactis KC24 Ameliorates Scopolamine-Induced Memory Impairment in ICR Mice.

Heat-killed Lactococcus lactis KC24 (H-KC24) has been examined for its neuroprotective effects in SH-SY5Y cells. We hypothesized that H-KC24 could alleviate memory impairment through the gut-brain axis. Scopolamine (1 mg/kg/day) was administered to ICR mice to induce memory impairment. Low- and high-dose H-KC24 cells (1 × 109 and 2 × 109 CFU/day, respectively) or donepezil (DO, 2 mg/kg) were administered for 14 days. H-KC24 treatment alleviated the deleterious scopolamine-induced memory effects on the recognition index and object recognition ability in the novel object recognition test and the Y-maze test. Changes in neurotransmitters and synaptic plasticity were confirmed by measuring acetylcholine, acetylcholinesterase, choline acetyltransferase, brain-derived neurotrophic factor, cyclic AMP response element-binding protein, and phosphorylated cyclic AMP response element-binding protein expression in brain tissues. In the H-KC24 and DO groups, ß-secretase levels increased, whereas amyloid ß levels decreased, demonstrating that H-KC24 can improve memory impairment caused by oxidative stress. This study demonstrated the positive effects of H-KC24 in a scopolamine-induced memory impairment mouse model.

Internal validation of Automated Visual Evaluation (AVE) on smartphone images for cervical cancer screening in a prospective study in Zambia.

OBJECTIVES: Visual inspection with acetic acid (VIA) is a low-cost approach for cervical cancer screening used in most low- and middle-income countries (LMICs) but, similar to other visual tests, is subjective and requires sustained training and quality assurance. We developed, trained, and validated an artificial-intelligence-based "Automated Visual Evaluation" (AVE) tool that can be adapted to run on smartphones to assess smartphone-captured images of the cervix and identify precancerous lesions, helping augment VIA performance. DESIGN: Prospective study. SETTING: Eight public health facilities in Zambia. PARTICIPANTS: A total of 8204 women aged 25-55. INTERVENTIONS: Cervical images captured on commonly used low-cost smartphone models were matched with key clinical information including human immunodeficiency virus (HIV) and human papillomavirus (HPV) status, plus histopathology analysis (where applicable), to develop and train an AVE algorithm and evaluate its performance for use as a primary screen and triage test for women who are HPV positive. MAIN OUTCOME MEASURES: Area under the receiver operating curve (AUC); sensitivity; specificity. RESULTS: As a general population screening tool for cervical precancerous lesions, AVE identified cases of cervical precancerous and cancerous (CIN2+) lesions with high performance (AUC = 0.91, 95% confidence interval [CI] = 0.89-0.93), which translates to a sensitivity of 85% (95% CI = 81%-90%) and specificity of 86% (95% CI = 84%-88%) based on maximizing the Youden's index. This represents a considerable improvement over naked eye VIA, which as per a meta-analysis by the World Health Organization (WHO) has a sensitivity of 66% and specificity of 87%. For women living with HIV, the AUC of AVE was 0.91 (95% CI = 0.88-0.93), and among those testing positive for high-risk HPV types, the AUC was 0.87 (95% CI = 0.83-0.91). CONCLUSIONS: These results demonstrate the feasibility of utilizing AVE on images captured using a commonly available smartphone by nurses in a screening program, and support our ongoing efforts for moving to more broadly evaluate AVE for its clinical sensitivity, specificity, feasibility, and acceptability across a wider range of settings. Limitations of this study include potential inflation of performance estimates due to verification bias (as biopsies were only obtained from participants with visible aceto-white cervical lesions) and due to this being an internal validation (the test data, while independent from that used to develop the algorithm was drawn from the same study).

Association between exposure to specific PM2.5 constituents and environment, lifestyle, and clinical parameters in patients with COPD.

This study investigated the correlation between the individual chemical constituents of particulate matter 2.5 µm (PM2.5) and respiratory parameters as well as the living environment and daily behaviors in patients with chronic obstructive pulmonary disease (COPD). Data were obtained from prospective COPD panel conducted in South Korea. Following collection via a microPEM, 18 metallic elements were determined using energy-dispersive X-ray fluorescence spectroscopy. All participants completed detailed questionnaires on living environments and lifestyle practices. Eighty-nine stable COPD patients (mean age 68.1 years; 94.4% male) were analyzed. Several constituents (titanium, aluminum, bromine, and silicone) were significantly associated with respiratory outcomes. Copper and manganese concentrations were significantly associated with the living environment. Increased ventilation time and air purifier operation were associated with lower concentrations of copper, silicone, barium, and titanium. These findings suggest varying relationships between PM2.5 constituents and clinical parameters in COPD patients, providing a basis for personalized interventions and future research.

Cheungsam Seed Husk Extract Reduces Skin Inflammation through Regulation of Inflammatory Mediator in TNF-α/IFN-γ-Induced HaCaT Cells.

Cannabis contains numerous natural components and has several effects such as anticancer, anti-inflammatory and antioxidant. Cheungsam is a variety of non-drug-type hemp, developed in Korea and is used for fiber (stem) and oil (seed). The efficacy of Cheungsam on skin is not yet known, and although there are previous studies on Cheungsam seed oil, there are no studies on Cheungsam seed husk. In this study, we investigated the potential of Cheungsam seed husk ethanol extract (CSSH) to alleviate skin inflammation through evaluating the gene and protein expression levels of inflammatory mediators. The results showed that CSSH reduced pro-inflammatory cytokines (IL-1ß, IL-6, IL-8, MCP-1 and CXCL10) and atopic dermatitis-related cytokines (IL-4, CCL17, MDC and RANTES) in TNF-α/IFN-γ-induced HaCaT cells. Furthermore, ERK, JNK and p38 phosphorylation were decreased and p-p65, p-IκBα, NLRP3, caspase-1, p-JAK1 and p-STAT6 were suppressed after CSSH treatment. CSSH significantly increased the level of the skin barrier factors filaggrin and involucrin. These results suggest that Cheungsam seed husk ethanol extract regulates the mechanism of skin inflammation and can be used as a new treatment for skin inflammatory diseases.

Saikosaponin D Inhibits Lung Metastasis of Colorectal Cancer Cells by Inducing Autophagy and Apoptosis.

Saikosaponin D (SSD), derived from Bupleurum falcatum L., has various pharmacological properties, including immunoregulatory, anti-inflammatory, and anti-allergic effects. Several studies have investigated the anti-tumor effects of SSD on cancer in multiple organs. However, its role in colorectal cancer (CRC) remains unclear. Therefore, this study aimed to elucidate the suppressive effects of SSD on CRC cell survival and metastasis. SSD reduced the survival and colony formation ability of CRC cells. SSD-induced autophagy and apoptosis in CRC cells were measured using flow cytometry. SSD treatment increased LC3B and p62 autophagic factor levels in CRC cells. Moreover, SSD-induced apoptosis occurred through the cleavage of caspase-9, caspase-3, and PARP, along with the downregulation of the Bcl-2 family. In the in vivo experiment, a reduction in the number of metastatic tumor nodules in the lungs was observed after the oral administration of SSD. Based on these results, SSD inhibits the metastasis of CRC cells to the lungs by inducing autophagy and apoptosis. In conclusion, SSD suppressed the proliferation and metastasis of CRC cells, suggesting its potential as a novel substance for the metastatic CRC treatment.