Lipopolysaccharide-Induced CD300b Receptor Binding to Toll-like Receptor 4 Alters Signaling to Drive Cytokine Responses that Enhance Septic Shock.

Receptor CD300b is implicated in regulating the immune response to bacterial infection by an unknown mechanism. Here, we identified CD300b as a lipopolysaccharide (LPS)-binding receptor and determined the mechanism underlying CD300b augmentation of septic shock. In vivo depletion and adoptive transfer studies identified CD300b-expressing macrophages as the key cell type augmenting sepsis. We showed that CD300b, and its adaptor DAP12, associated with Toll-like receptor 4 (TLR4) upon LPS binding, thereby enhancing TLR4-adaptor MyD88- and TRIF-dependent signaling that resulted in an elevated pro-inflammatory cytokine storm. LPS engagement of the CD300b-TLR4 complex led to the recruitment and activation of spleen tyrosine kinase (Syk) and phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K). This resulted in an inhibition of the ERK1/2 protein kinase- and NF-κB transcription factor-mediated signaling pathways, which subsequently led to a reduced interleukin-10 (IL-10) production. Collectively, our data describe a mechanism of TLR4 signaling regulated by CD300b in myeloid cells in response to LPS.

A simulation-based bias analysis to assess the impact of unmeasured confounding when designing non-randomized database studies.

BACKGROUND: Unmeasured confounding is often raised as a source of potential bias during the design of non-randomized studies but quantifying such concerns is challenging. METHODS: We developed a simulation-based approach to assess the potential impact of unmeasured confounding during the study design stage. The approach involved generation of hypothetical individual-level cohorts using realistic parameters including a binary treatment (prevalence 25%), a time-to-event outcome (incidence 5%), 13 measured covariates, a binary unmeasured confounder (u1, 10%), and a binary measured 'proxy' variable (p1) correlated with u1. Strength of unmeasured confounding and correlations between u1 and p1 were varied in simulation scenarios. Treatment effects were estimated with, a) no adjustment, b) adjustment for measured confounders (Level 1), c) adjustment for measured confounders and their proxy (Level 2). We computed absolute standardized mean differences in u1 and p1 and relative bias with each level of adjustment. RESULTS: Across all scenarios, Level 2 adjustment led to improvement in balance of u1, but this improvement was highly dependent on the correlation between u1 and p1. Level 2 adjustments also had lower relative bias than Level 1 adjustments (in strong u1 scenarios: relative bias of 9.2%, 12.2%, 13.5% at correlations 0.7, 0.5, and 0.3, respectively versus 16.4%, 15.8%, 15.0% for Level 1, respectively). CONCLUSION: An approach using simulated individual-level data was useful to explicitly convey the potential for bias due to unmeasured confounding while designing non-randomized studies and can be helpful in informing design choices.

Targeted Learning with an Undersmoothed Lasso Propensity Score Model for Large-Scale Covariate Adjustment in Healthcare Database Studies.

Lasso regression is widely used for large-scale propensity score (PS) estimation in healthcare database studies. In these settings, previous work has shown that undersmoothing (overfitting) Lasso PS models can improve confounding control, but it can also cause problems of non-overlap in covariate distributions. It remains unclear how to select the degree of undersmoothing when fitting large-scale Lasso PS models to improve confounding control while avoiding issues that can result from reduced covariate overlap. Here, we used simulations to evaluate the performance of using collaborative-controlled targeted learning to data-adaptively select the degree of undersmoothing when fitting large-scale PS models within both singly and doubly robust frameworks to reduce bias in causal estimators. Simulations showed that collaborative learning can data-adaptively select the degree of undersmoothing to reduce bias in estimated treatment effects. Results further showed that when fitting undersmoothed Lasso PS-models, the use of cross-fitting was important for avoiding non-overlap in covariate distributions and reducing bias in causal estimates.

Risk factors for prediabetes in community-dwelling adults: A generalized estimating equation logistic regression approach with natural language processing insights.

The global prevalence of prediabetes is expected to reach 8.3% (587 million people) by 2045, with 70% of people with prediabetes developing diabetes during their lifetimes. We aimed to classify community-dwelling adults with a high risk for prediabetes based on prediabetes-related symptoms and to identify their characteristics, which might be factors associated with prediabetes. We analyzed homecare nursing records (n = 26,840) of 1628 patients aged over 20 years. Using a natural language processing algorithm, we classified each nursing episode as either low-risk or high-risk for prediabetes based on the detected number and category of prediabetes-symptom words. To identify differences between the risk groups, we employed t-tests, chi-square tests, and data visualization. Risk factors for prediabetes were identified using multiple logistic regression models with generalized estimating equations. A total of 3270 episodes (12.18%) were classified as potentially high-risk for prediabetes. There were significant differences in the personal, social, and clinical factors between groups. Results revealed that female sex, age, cancer coverage as part of homecare insurance coverage, and family caregivers were significantly associated with an increased risk of prediabetes. Although prediabetes is not a life-threatening disease, uncontrolled blood glucose can cause unfavorable outcomes for other major diseases. Thus, medical professionals should consider the associated symptoms and risk factors of prediabetes. Moreover, the proposed algorithm may support the detection of individuals at a high risk for prediabetes. Implementing this approach could facilitate proactive monitoring and early intervention, leading to reduced healthcare expenses and better health outcomes for community-dwelling adults.

Evaluating and improving real-world evidence with Targeted Learning.

BACKGROUND: The Targeted Learning roadmap provides a systematic guide for generating and evaluating real-world evidence (RWE). From a regulatory perspective, RWE arises from diverse sources such as randomized controlled trials that make use of real-world data, observational studies, and other study designs. This paper illustrates a principled approach to assessing the validity and interpretability of RWE. METHODS: We applied the roadmap to a published observational study of the dose-response association between ritodrine hydrochloride and pulmonary edema among women pregnant with twins in Japan. The goal was to identify barriers to causal effect estimation beyond unmeasured confounding reported by the study's authors, and to explore potential options for overcoming the barriers that robustify results. RESULTS: Following the roadmap raised issues that led us to formulate alternative causal questions that produced more reliable, interpretable RWE. The process revealed a lack of information in the available data to identify a causal dose-response curve. However, under explicit assumptions the effect of treatment with any amount of ritodrine versus none, albeit a less ambitious parameter, can be estimated from data. CONCLUSIONS: Before RWE can be used in support of clinical and regulatory decision-making, its quality and reliability must be systematically evaluated. The TL roadmap prescribes how to carry out a thorough, transparent, and realistic assessment of RWE. We recommend this approach be a routine part of any decision-making process.

A collaborative study of the impact of N-nitrosamines presence and ARB recall on ARB utilization - results from IQVIA™ Disease Analyzer Germany.

PURPOSE: Regulators are increasingly concerned with  the impact of recalls on drug adherence. In 2018, N-nitrosamines impurities were detected in valsartan containing medical products. Concerned products were immediately recalled in July 2018 by regulatory agencies internationally. In Germany, recalls were issued for valsartan, losartan and irbesartan from July 2018 to March 2019. This study examined angiotensin II receptor blocker (ARB) utilization trends and switching patterns in Germany before and after July 2018. METHODS: Patients prescribed ARBs from January 2014 to June 2020 in general practices in Germany were included in a collaborative framework common protocol drug utilization study led by the US Food and Drug Administration. Trends in monthly and quarterly proportions of total ARB prescribing were analysed for individual ARBs using descriptive statistics and interrupted time series analysis. The rate of switching to an alternative ARB was analysed before and after the recalls. RESULTS: The proportion of valsartan prescriptions immediately decreased from 35.9 to 17.8% following the first recalls in July 2018, mirrored by an increased proportion for candesartan. Increased switching from valsartan to candesartan was observed. No increased switching was observed after losartan recalls, whereas for irbesartan, increased switching was observed 6-12 months after the last recall. Increased switching from ARBs to angiotensin-converting enzyme (ACE) inhibitors or ARB treatment discontinuations were not observed. CONCLUSION: This study showed that patients were able to continue ARB treatment despite the July 2018-March 2019 recalls, although many patients needed to switch to an alternative ARB. The duration of the impact of ARB recalls appeared to be limited.

The Impact of Union Membership on Nursing Turnover and Job Satisfaction.

OBJECTIVE: The present study examines the scope of nursing unions and the relationship with turnover and job satisfaction among RNs. BACKGROUND: There is no recent empirical literature documenting evidence on workplace performance measures (turnover and job satisfaction) among unionized nurses at the national level. METHODS: This cross-sectional study analyzed secondary data (n = 43 960), the 2018 National Sample Survey of Registered Nurses. RESULTS: Approximately 16% of the sample reported being represented by labor unions. The overall nursing turnover rate for the sample was 12.8%. Unionized nurses were less likely than their counterparts to report turnover (mean, 10.9% vs 13.16%; P = 0.02) and less job satisfaction (mean, 3.20 vs 3.28). Union nurses were more likely than nonunion nurses to be male (12.72% vs 9.46%; P = 0.0004), minorities (37.65% vs 25.67%, P < 0.001), be employed in hospital settings (70.1% vs 57.9%, P = 0.001), but report fewer hours of work per week (mean, 36.73 vs 37.66; P = 0.003). Regression results revealed a positive association between union status and nursing turnover (odds ratio, 0.83; P < 0.05), whereas union status was inversely associated with job satisfaction (B = -0.13, P < 0.001) after adjusting for age, gender, race/ethnicity, care coordination time per week, weekly hours of work, and employment settings. CONCLUSION: Overall, job satisfaction was high among all nurses, regardless of union membership. However, when comparing specifically union and nonunion members, unionized nurses were less likely to report turnover, but were more likely to experience job dissatisfaction.

Developing a Classification Algorithm for Prediabetes Risk Detection From Home Care Nursing Notes: Using Natural Language Processing.

This study developed and validated a rule-based classification algorithm for prediabetes risk detection using natural language processing from home care nursing notes. First, we developed prediabetes-related symptomatic terms in English and Korean. Second, we used natural language processing to preprocess the notes. Third, we created a rule-based classification algorithm with 31 484 notes, excluding 315 instances of missing data. The final algorithm was validated by measuring accuracy, precision, recall, and the F1 score against a gold standard testing set (400 notes). The developed terms comprised 11 categories and 1639 words in Korean and 1181 words in English. Using the rule-based classification algorithm, 42.2% of the notes comprised one or more prediabetic symptoms. The algorithm achieved high performance when applied to the gold standard testing set. We proposed a rule-based natural language processing algorithm to optimize the classification of the prediabetes risk group, depending on whether the home care nursing notes contain prediabetes-related symptomatic terms. Tokenization based on white space and the rule-based algorithm were brought into effect to detect the prediabetes symptomatic terms. Applying this algorithm to electronic health records systems will increase the possibility of preventing diabetes onset through early detection of risk groups and provision of tailored intervention.

Evaluation of a New Chemiluminescent Immunoassay-Based Interferon-Gamma Release Assay for Detection of Latent Tuberculosis Infection.

Background and Objectives: This study aimed to evaluate the performance of a new chemiluminescent immunoassay-based tuberculosis (TB) interferon-gamma release assay (IGRA), AdvanSureI3 TB-IGRA (LG Chem Ltd., Seoul, Republic of Korea), for detecting latent tuberculosis infection in comparison with T-SPOT.TB (Oxford Immunotec, Oxford, UK). Materials and Methods: Between June 2021 and December 2021, 125 non-duplicate blood specimens were collected from adult volunteers; each subject received both tests concurrently. Total agreement and Cohen's kappa coefficient (κ) were used to calculate concordance. The Jonckheere-Terpstra test was used to examine the correlation between interferon-gamma (IFN-γ) levels in AdvanSureI3 TB-IGRA and spot counts in T-SPOT.TB. Results: The IGRA findings of the two assays revealed 90.8% (95% confidence interval [CI] = 84.2-94.8) total agreement with κ of 0.740 (95% CI = 0.595-0.885), showing substantial agreement between the two tests. Additionally, the amount of IFN-γ in AdvanSureI3 TB-IGRA increased with the spot counts in T-SPOT.TB (p < 0.001). Conclusions: Our research revealed that the results of the AdvanSureI3 TB-IGRA were comparable to those of T-SPOT.TB.

Tetraspanin 7 regulates osteoclast function through association with the RANK/αvß3 integrin complex.

Actin rings are unique structures that facilitate the attachment of osteoclasts to the bone matrix during bone resorption. Previous studies have shown that tetraspanin7 (TSPAN7) plays an important role in the reorganization of the cytoskeleton necessary for the bone-resorbing activity of osteoclasts. However, questions remain as to the mechanisms by which TSPAN7 regulates this cytoskeletal rearrangement. In this study, we investigated the roles of TSPAN7 in osteoclasts by deleting the Tm4sf2 gene in mice, which encodes TSPAN7. The Tm4sf2 global knockout model showed protective effects on pathological bone loss, but no discernible changes in bone phenotypes under physiological conditions. In vitro study revealed that ablation of Tm4sf2 caused significant defects in integrin-mediated actin ring formation, thereby leading to significantly decreased bone resorption. Additionally, we demonstrated an association between TSPAN7 and the receptor activator of nuclear factor-кB/αvß3 integrin. Overall, our findings suggest that TSPAN7 acts as a novel modulator regulating the bone-resorbing function of osteoclasts.

Data-Adaptive Selection of the Propensity Score Truncation Level for Inverse-Probability-Weighted and Targeted Maximum Likelihood Estimators of Marginal Point Treatment Effects.

Inverse probability weighting (IPW) and targeted maximum likelihood estimation (TMLE) are methodologies that can adjust for confounding and selection bias and are often used for causal inference. Both estimators rely on the positivity assumption that within strata of confounders there is a positive probability of receiving treatment at all levels under consideration. Practical applications of IPW require finite inverse probability (IP) weights. TMLE requires that propensity scores (PS) be bounded away from 0 and 1. Although truncation can improve variance and finite sample bias, this artificial distortion of the IP weights and PS distribution introduces asymptotic bias. As sample size grows, truncation-induced bias eventually swamps variance, rendering nominal confidence interval coverage and hypothesis tests invalid. We present a simple truncation strategy based on the sample size, n, that sets the upper bound on IP weights at $\sqrt{\textit{n}}$ ln n/5. For TMLE, the lower bound on the PS should be set to 5/($\sqrt{\textit{n}}$ ln n/5). Our strategy was designed to optimize the mean squared error of the parameter estimate. It naturally extends to data structures with missing outcomes. Simulation studies and a data analysis demonstrate our strategy's ability to minimize both bias and mean squared error in comparison with other common strategies, including the popular but flawed quantile-based heuristic.

Long-term persistence of infectious Zika virus: Inflammation and behavioral sequela in mice.

The neurodevelopmental defects associated with ZIKV infections early in pregnancy are well documented, however the potential defects and long-term consequences associated with milder infections in late pregnancy and perinatal period are less well understood. To model these, we challenged 1 day old (P1) immunocompetent C57BL/6 mice with ZIKV. The animals developed a transient neurological syndrome including unsteady gait, kinetic tremors, severe ataxia and seizures 10-15 days post-infection (dpi) but symptoms subsided after a week, and most animals survived. Despite apparent recovery, MRI of convalescent mice show reduced cerebellar volume that correlates with altered coordination and motor function as well as hyperactivity and impulsivity. Persistent mRNA levels of pro-inflammatory genes including Cd80, Il-1α, and Ifn-γ together with Cd3, Cd8 and perforin (PrfA), suggested persistence of low-grade inflammation. Surprisingly, the brain parenchyma of convalescent mice harbor multiple small discrete foci with viral antigen, active apoptotic processes in neurons, and cellular infiltrates, surrounded by activated astrocytes and microglia as late as 1-year post-infection. Detection of negative-sense strand viral RNA and isolation of infectious virus derived from these convalescent mice by blinded passage in Vero cells confirmed long-term persistence of replicating ZIKV in CNS of convalescent mice. Although the infection appears to persist in defined reservoirs within CNS, the resulting inflammation could increase the risk of neurodegenerative disorders. This raises concern regarding possible long-term effects in asymptomatic children exposed to the virus and suggests that long-term neurological and behavioral monitoring as well as anti-viral treatment to clear virus from the CNS may be useful in patients exposed to ZIKV at an early age.

Resolvin D1 suppresses inflammation-associated tumorigenesis in the colon by inhibiting IL-6-induced mitotic spindle abnormality.

While failure in resolution of inflammation is considered to increase the risk of tumorigenesis, there is paucity of experimental as well as clinical evidence supporting this association. Resolvin D1 (RvD1) is a representative pro-resolving lipid mediator that is endogenously generated from docosahexaenoic acid for the resolution of inflammation. Here, we report a decreased level of RvD1 in the blood from colorectal cancer patients and mice having inflammation-induced colon cancer, suggesting plasma RvD1 as a potential biomarker for monitoring colorectal cancer. Administration of RvD1 attenuated dextran sodium sulfate (DSS)-induced colitis and azoxymethane (AOM) plus DSS-induced colorectal carcinogenesis by suppressing the production of interleukin-6 (IL-6) and IL-6-mediated chromosomal instability. The protective effect of RvD1 against chromosomal instability is associated with downregulation of IL-6-induced Cyclin D1 expression, which appears to be mediated by blocking the Janus kinase 2 (JAK2)-signal transducer and activator of transcription 3 (STAT3) axis. RvD1 inhibited the STAT3 signaling pathway by interfering with the binding of IL-6 to its receptor (IL-6R), suggesting the novel function of RvD1 as a putative IL-6R antagonist. Together, our findings suggest that RvD1-mediated blockade of IL-6 signal transmission may contribute to inhibition of chromosomal instability and tumorigenesis.

Validations of satellite ozone profiles in austral spring using ozonesonde measurements in the Jang Bogo station, Antarctica.

Using ozonesonde measurements from 2015 to 2018 at the Jang Bogo station located in the southeastern Antarctic region, we evaluate ozone profiles retrieved from the three satellite measurements that are widely used: Ozone Monitoring Instrument (OMI), Microwave Limb Sounder (MLS), and Ozone Mapping Profiler Suite (OMPS) data. For the fair validation, ozonesonde profiles are smoothed using the weighting function of each satellite retrieval algorithm (i.e., convolution process). Compared with limb-viewing MLS and OMPS ozone profiles, the OMI ozone profiles are relatively less qualified: coarser vertical resolution and larger inter-annual variation. Nevertheless, our validation reveals that the quality of all three satellite ozone profiles looks comparable; In general, difference from ozonesonde profile is ∼1 ppm absolutely, and -20 to 30% relatively at maximum. This quantitative range well corresponds to previous work, meaning that our new validation confirms the reliability of satellite ozone profiles in the southeastern Antarctic region where the measurement data for the validation were not enough. Another interesting feature is the role of a priori ozone profile; Nadir-viewing OMI satellite can have qualified ozone profiles by a proper assumption of a priori ozone profile. Since the performance of limb-viewing ozone profiles is better, however, the careful usage of nadir-viewing ozone profile is still required. We think that the simultaneous usage of multiple satellite ozone profiles can contribute to better understanding of Antarctic ozone characteristics.

Micro-Current Stimulation Suppresses Inflammatory Responses in Peptidoglycan-Treated Raw 264.7 Macrophages and Propionibacterium acnes-Induced Skin Inflammation via TLR2/NF-κB Signaling Pathway.

Acne is a common inflammatory disorder of the human skin and a multifactorial disease caused by the sebaceous gland and Propionibacterium acnes (P. acnes). This study aimed to evaluate the anti-inflammatory effect of micro-current stimulation (MC) on peptidoglycan (PGN)-treated raw 264.7 macrophages and P. acnes-induced skin inflammation. To specify the intensity with anti-inflammatory effects, nitric oxide (NO) production was compared according to various levels of MC. As the lowest NO production was shown at an intensity of 50 µA, subsequent experiments used this intensity. The changes of expression of the proteins related to TLR2/NF-κB signaling were examined by immunoblotting. Also, immunofluorescence analysis was performed for observing NF-κB p65 localization. All of the expression levels of proteins regarding TLR2/NF-κB signaling were decreased by the application of MC. Moreover, the application of MC to PGN-treated raw 264.7 cells showed a significant decrease in the amount of nuclear p65-protein. In the case of animal models with P. acnes-induced skin inflammation, various pro-inflammatory cytokines and mediators significantly decreased in MC-applied mice. In particular, the concentration of IL-1ß in serum decreased, and the area of acne lesions, decreased from the histological analysis. We suggest for the first time that MC can be a novel treatment for acne.

Comparison of the Antihypertensive Activity of Phenolic Acids.

Phenolic acids, found in cereals, legumes, vegetables, and fruits, have various biological functions. We aimed to compare the antihypertensive potential of different phenolic acids by evaluating their ACE inhibitory activity and cytoprotective capacity in EA.hy 926 endothelial cells. In addition, we explored the mechanism underlying the antihypertensive activity of sinapic acid. Of all the phenolic acids studied, sinapic acid, caffeic acid, coumaric acid, and ferulic acid significantly inhibited ACE activity. Moreover, gallic acid, sinapic acid, and ferulic acid significantly enhanced intracellular NO production. Based on the results of GSH depletion, ROS production, and MDA level analyses, sinapic acid was selected to study the mechanism underlying the antihypertensive effect. Sinapic acid decreases endothelial dysfunction by enhancing the expression of antioxidant-related proteins. Sinapic acid increased phosphorylation of eNOS and Akt in a dose-dependent manner. These findings indicate the potential of sinapic acid as a treatment for hypertension.

Cinchonine inhibits osteoclast differentiation by regulating TAK1 and AKT, and promotes osteogenesis.

Cinchonine (CN) has been known to exert antimalarial, antiplatelet, and antiobesity effects. It was also recently reported to inhibit transforming growth factor ß-activated kinase 1 (TAK1) and protein kinase B (AKT) through binding to tumor necrosis factor receptor-associated factor 6 (TRAF6). However, its role in bone metabolism remains largely unknown. Here, we showed that CN inhibits osteoclast differentiation with decreased expression of nuclear factor of activated T-cells, cytoplasmic 1 (NFATc1), a key determinant of osteoclastogenesis. Immunoblot and quantitative real-time polymerase chain reaction analysis as well as the reporter assay revealed that CN inhibits nuclear factor-κB and activator protein-1 by regulating TAK1. CN also attenuated the activation of AKT, cyclic AMP response element-binding protein, and peroxisome proliferator-activated receptor-γ coactivator 1ß (PGC1ß), an essential regulator of mitochondrial biogenesis. Collectively, these results suggested that CN may inhibit TRAF6-mediated TAK1 and AKT activation, which leads to downregulation of NFATc1 and PGC1ß resulting in the suppression of osteoclast differentiation. Interestingly, CN not only inhibited the maturation and resorption function of differentiated osteoclasts but also promoted osteoblast differentiation. Furthermore, CN protected lipopolysaccharide- and ovariectomy-induced bone destruction in mouse models, suggesting its therapeutic potential for treating inflammation-induced bone diseases and postmenopausal osteoporosis.

Two-way mixed-effects methods for joint association analysis using both host and pathogen genomes.

Infectious diseases are often affected by specific pairings of hosts and pathogens and therefore by both of their genomes. The integration of a pair of genomes into genome-wide association mapping can provide an exquisitely detailed view of the genetic landscape of complex traits. We present a statistical method, ATOMM (Analysis with a Two-Organism Mixed Model), that maps a trait of interest to a pair of genomes simultaneously; this method makes use of whole-genome sequence data for both host and pathogen organisms. ATOMM uses a two-way mixed-effect model to test for genetic associations and cross-species genetic interactions while accounting for sample structure including interactions between the genetic backgrounds of the two organisms. We demonstrate the applicability of ATOMM to a joint association study of quantitative disease resistance (QDR) in the Arabidopsis thaliana-Xanthomonas arboricola pathosystem. Our method uncovers a clear host-strain specificity in QDR and provides a powerful approach to identify genetic variants on both genomes that contribute to phenotypic variation.

Micro-Current Stimulation Has Potential Effects of Hair Growth-Promotion on Human Hair Follicle-Derived Papilla Cells and Animal Model.

Recently, a variety of safe and effective non-pharmacological methods have been introduced as new treatments of alopecia. Micro-current electrical stimulation (MCS) is one of them. It is generally known to facilitate cell proliferation and differentiation and promote cell migration and ATP synthesis. This study aimed to investigate the hair growth-promoting effect of MCS on human hair follicle-derived papilla cells (HFDPC) and a telogenic mice model. We examined changes in cell proliferation, migration, and cell cycle progression with MCS-applied HFDPC. The changes of expression of the cell cycle regulatory proteins, molecules related to the PI3K/AKT/mTOR/Fox01 pathway and Wnt/ß-catenin pathway were also examined by immunoblotting. Subsequently, we evaluated the various growth factors in developing hair follicles by RT-PCR in MCS-applied (MCS) mice model. From the results, the MCS-applied groups with specific levels showed effects on HFDPC proliferation and migration and promoted cell cycle progression and the expression of cell cycle-related proteins. Moreover, these levels significantly activated the Wnt/ß-catenin pathway and PI3K/AKT/mTOR/Fox01 pathway. Various growth factors in developing hair follicles, including Wnts, FGFs, IGF-1, and VEGF-B except for VEGF-A, significantly increased in MCS-applied mice. Our results may confirm that MCS has hair growth-promoting effect on HFDPC as well as telogenic mice model, suggesting a potential treatment strategy for alopecia.

Upregulation of LAMB1 via ERK/c-Jun Axis Promotes Gastric Cancer Growth and Motility.

Gastric cancer is the fifth most common cancer worldwide with a poor survival rate. Therefore, it is important to identify predictive and prognostic biomarkers of gastric cancer. Laminin subunit beta 1 (LAMB1) is involved in attachment, migration, and organization during development, and its elevated expression has been associated with several cancers. However, the role and mechanism of LAMB1 in gastric cancer remains unknown. Here, we determined that LAMB1 is upregulated in gastric cancer tissues and contributes to cell growth and motility. Using a public database, we showed that LAMB1 expression was significantly upregulated in gastric cancer compared to normal tissues. LAMB1 was also found to be associated with poor prognosis in patients with gastric cancer. Overexpression of LAMB1 elevated cell proliferation, invasion, and migration; however, knockdown of LAMB1 decreased these effects in gastric cancer cells. U0126, an extracellular signal-regulated kinase (ERK) inhibitor, regulated the expression of LAMB1 in gastric cancer cells. Additionally, we showed that c-Jun directly binds to the LAMB1 promoter as a transcription factor and regulates its gene expression via the ERK pathway in gastric cancer cells. Therefore, our study indicates that LAMB1 promotes cell growth and motility via the ERK/c-Jun axis and is a potential biomarker and therapeutic target of gastric cancer.