The effectiveness of tumor necrosis factor-α blocker therapy in patients with axial spondyloarthritis who failed conventional treatment: a comparative study focused on improvement in ASAS Health Index.

Objective: The purpose of this study is to evaluate the impact of tumor necrosis factor (TNF)-α blocker therapy on the Assessment of SpondyloArthritis international Society Health Index (ASAS-HI) among patients who have failed conventional nonsteroidal anti-inflammatory drugs. Methods: A comparative study was conducted involving axial spondyloarthritis (axSpA) patients treated with either TNF-α blocker or conventional therapy. Patient data, including demographics, disease characteristics, and ASAS-HI scores, were collected before and after treatment. Statistical analysis was performed to compare changes in ASAS-HI scores between the TNF-α blocker and the conventional therapy group. Results: The study population consisted of patients with axSpA, with a mean age of 38.3 years in conventional treatment group and 29.3 years in TNF-α blocker group. Most variables, including C-reactive protein levels, other comorbidities, and disease assessment scores showed no significant difference between groups. Longitudinal analysis within each treatment group from Week 0 to 12 showed no significant change in the conventional treatment group, whereas the TNF-α blocker group experienced a significant reduction in ASAS-HI scores, demonstrating the effectiveness of the treatment. The TNF-α blocker group exhibited a significantly greater improvement in ASAS-HI scores compared to the conventional therapy group. The Bath Ankylosing Spondylitis Functional Index and the Bath Ankylosing Spondylitis Disease Activity Index demonstrated strong positive correlations with ASAS-HI scores, indicating higher disease activity and functional limitation are associated with worse health outcomes in patients. Conclusion: The research demonstrates that ASAS-HI scores significantly improve with TNF-α blocker therapy in axSpA patients, underscoring ASAS-HI's effectiveness as a tool for evaluating drug responses.

PSMA-PET follow-up to assess response in patients not receiving PSMA therapy: Is there value beyond localization of disease?

Introduction: Prostate Specific Membrane Antigen Positron Emission Tomography (PSMA-PET) is routinely used for the staging of patients with prostate cancer, but data on response assessment are sparse and primarily stem from metastatic castration-resistant prostate cancer (mCRPC) patients treated with PSMA radioligand therapy. Still, follow-up PSMA-PET is employed in earlier disease stages in case of clinical suspicion of disease persistence, recurrence or progression to decide if localized or systemic treatment is indicated. Therefore, the prognostic value of PSMA-PET derived tumor volumes in earlier disease stages (i.e., hormone-sensitive prostate cancer (HSPC) and non-[177Lu]Lu-PSMA-617 (LuPSMA) therapy castration resistant prostate cancer (CRPC)) are evaluated in this manuscript. Methods: A total number of 73 patients (6 primary staging, 42 HSPC, 25 CRPC) underwent two (i.e., baseline and follow-up, median interval: 379 days) whole-body [68Ga]Ga-PSMA-11 PET/CT scans between Nov 2014 and Dec 2018. Analysis was restricted to non-LuPSMA therapy patients. PSMA-PETs were retrospectively analyzed and primary tumor, lymph node-, visceral-, and bone metastases were segmented. Body weight-adjusted organ-specific and total tumor volumes (PSMAvol: sum of PET volumes of all lesions) were measured for baseline and follow-up. PSMAvol response was calculated as the absolute difference of whole-body tumor volumes. High metastatic burden (>5 metastases), RECIP 1.0 and PSMA-PET Progression Criteria (PPP) were determined. Survival data were sourced from the cancer registry. Results: The average number of tumor lesions per patient on the initial PET examination was 10.3 (SD 28.4). At baseline, PSMAvol was strongly associated with OS (HR 3.92, p <0.001; n = 73). Likewise, response in PSMAvol was significantly associated with OS (HR 10.48, p < 0.005; n = 73). PPP achieved significance as well (HR 2.19, p <0.05, n = 73). Patients with hormone sensitive disease and poor PSMAvol response (upper quartile of PSMAvol change) in follow-up had shorter outcome (p < 0.05; n = 42). PSMAvol in bones was the most relevant parameter for OS prognostication at baseline and for response assessment (HR 31.11 p < 0.001; HR 32.27, p < 0.001; n = 73). Conclusion: PPP and response in PSMAvol were significantly associated with OS in the present heterogeneous cohort. Bone tumor volume was the relevant miTNM region for OS prognostication. Future prospective evaluation of the performance of organ specific PSMAvol in more homogeneous cohorts seems warranted.

Tissue Mechanics and Hedgehog Signaling Crosstalk as a Key Epithelial-Stromal Interplay in Cancer Development.

Epithelial-stromal interplay through chemomechanical cues from cells and matrix propels cancer progression. Elevated tissue stiffness in potentially malignant tissues suggests a link between matrix stiffness and enhanced tumor growth. In this study, employing chronic oral/esophageal injury and cancer models, it is demonstrated that epithelial-stromal interplay through matrix stiffness and Hedgehog (Hh) signaling is key in compounding cancer development. Epithelial cells actively interact with fibroblasts, exchanging mechanoresponsive signals during the precancerous stage. Specifically, epithelial cells release Sonic Hh, activating fibroblasts to produce matrix proteins and remodeling enzymes, resulting in tissue stiffening. Subsequently, basal epithelial cells adjacent to the stiffened tissue become proliferative and undergo epithelial-to-mesenchymal transition, acquiring migratory and invasive properties, thereby promoting invasive tumor growth. Notably, transcriptomic programs of oncogenic GLI2, mechano-activated by actin cytoskeletal tension, govern this process, elucidating the crucial role of non-canonical GLI2 activation in orchestrating the proliferation and mesenchymal transition of epithelial cells. Furthermore, pharmacological intervention targeting tissue stiffening proves highly effective in slowing cancer progression. These findings underscore the impact of epithelial-stromal interplay through chemo-mechanical (Hh-stiffness) signaling in cancer development, and suggest that targeting tissue stiffness holds promise as a strategy to disrupt chemo-mechanical feedback, enabling effective cancer treatment.

Future Perspectives of Artificial Intelligence in Bone Marrow Dosimetry and Individualized Radioligand Therapy.

Radioligand therapy is an emerging and effective treatment option for various types of malignancies, but may be intricately linked to hematological side effects such as anemia, lymphopenia or thrombocytopenia. The safety and efficacy of novel theranostic agents, targeting increasingly complex targets, can be well served by comprehensive dosimetry. However, optimization in patient management and patient selection based on risk-factors predicting adverse events and built upon reliable dose-response relations is still an open demand. In this context, artificial intelligence methods, especially machine learning and deep learning algorithms, may play a crucial role. This review provides an overview of upcoming opportunities for integrating artificial intelligence methods into the field of dosimetry in nuclear medicine by improving bone marrow and blood dosimetry accuracy, enabling early identification of potential hematological risk-factors, and allowing for adaptive treatment planning. It will further exemplify inspirational success stories from neighboring disciplines that may be translated to nuclear medicine practices, and will provide conceptual suggestions for future directions. In the future, we expect artificial intelligence-assisted (predictive) dosimetry combined with clinical parameters to pave the way towards truly personalized theranostics in radioligand therapy.

Exploring oral bacterial compositional network in two oral disease groups using a convergent approach of NGS-molecular diagnostics.

BACKGROUND: Since most of the commonly known oral diseases are explained in link with balance of microbial community, an accurate bacterial taxonomy profiling for determining bacterial compositional network is essential. However, compared to intestinal microbiome, research data pool related to oral microbiome is small, and general 16S rRNA screening method has a taxonomy misclassification issue in confirming complex bacterial composition at the species level. OBJECTIVE: Present study aimed to explore bacterial compositional networks at the species level within saliva of 39 oral disease patients (Dental Caries group: n = 26 and Periodontitis group: n = 13) through comparison with public Korean-specific healthy oral microbiome data. METHODS: Here, we applied comprehensive molecular diagnostics based on qRT-PCR and Sanger sequencing methods to complement the technical limitations of NGS-based 16S V3-V4 amplicon sequencing technology. RESULTS: As a result of microbiome profiling at the genus level, relative frequencies of many nitrate-reducing bacteria within each oral disease group were found to be significantly low compared to the healthy group. In addition, the molecular diagnostics-based bacterial identification method allowed the determination of the correct taxonomy of screened primary colonizers (Streptococcus and Actinomyces unclassification clusters) for each oral disease. Finally, as with the results of microbiome profiling at the genus level, many core-species classified within the saliva of each oral disease group were also related to nitrate-reduction, and it was estimated that various pathogens associated with each disease formed a bacterial network with the core-species. CONCLUSION: Our study introduced a novel approach that can compensate for the difficulty of identifying an accurate bacterial compositional network at the species level due to unclear taxonomy classification by using the convergent approach of NGS-molecular diagnostics. Ultimately, we suggest that our experimental approach and results could be potential reference materials for researchers who intend to prevent oral disease by determining the correlation between oral health and bacterial compositional network according to the changes in the relative frequency for nitrate-reducing species.

Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low-risk endometrial cancer patients: A Korean Gynecologic Oncology Group ancillary study.

OBJECTIVES: Fertility-sparing treatment (FST) might be considered an option for reproductive patients with low-risk endometrial cancer (EC). On the other hand, the matching rates between preoperative assessment and postoperative pathology in low-risk EC patients are not high enough. We aimed to predict the postoperative pathology depending on preoperative myometrial invasion (MI) and grade in low-risk EC patients to help extend the current criteria for FST. METHODS/MATERIALS: This ancillary study (KGOG 2015S) of Korean Gynecologic Oncology Group 2015, a prospective, multicenter study included patients with no MI or MI <1/2 on preoperative MRI and endometrioid adenocarcinoma and grade 1 or 2 on endometrial biopsy. Among the eligible patients, Groups 1-4 were defined with no MI and grade 1, no MI and grade 2, MI <1/2 and grade 1, and MI <1/2 and grade 2, respectively. New prediction models using machine learning were developed. RESULTS: Among 251 eligible patients, Groups 1-4 included 106, 41, 74, and 30 patients, respectively. The new prediction models showed superior prediction values to those from conventional analysis. In the new prediction models, the best NPV, sensitivity, and AUC of preoperative each group to predict postoperative each group were as follows: 87.2%, 71.6%, and 0.732 (Group 1); 97.6%, 78.6%, and 0.656 (Group 2); 71.3%, 78.6% and 0.588 (Group 3); 91.8%, 64.9%, and 0.676% (Group 4). CONCLUSIONS: In low-risk EC patients, the prediction of postoperative pathology was ineffective, but the new prediction models provided a better prediction.

Intra-articular hydrogel formulation prolongs the in vivo stability of Toll-like receptor antagonistic peptides for rheumatoid arthritis treatment.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation that primarily affects joint tissue and requires frequent medication. Recently, we developed cyclic phage-display-derived inhibitory peptides (CPs), which act as Toll-like Receptor 4 antagonists. These CPs exhibited therapeutic efficacy against joint diseases by alleviating inflammatory factors. Nonetheless, CP exhibits in vivo instability and a short half-life. Therefore, this study sought to improve the in vivo stability of CP, thereby reducing the frequency of CP administration through the development of an injectable hydrogel depot formulation. To improve in vivo stability, CP was chemically conjugated to hyaluronic acid (HA-CP) and subsequently mixed into a temperature-sensitive hydrogel [methoxy polyethylene glycol-b-poly(ε-caprolactone)-ran-poly(lactide) (PC)] as an injectable depot (PC+(HA-CP)). For comparison, CP was physically mixed with HA and PC (PC+(HA+CP)). Both PC+(HA-CP) and PC+(HA+CP) were found to rapidly form depots upon injection into the joint space. Cell viability assays confirmed the non-toxic nature of PC+(HA-CP) and PC+(HA+CP), whereas both formulations exhibited inhibition of inflammatory factors. Furthermore, PC+(HA-CP) retained CP for a longer duration compared to PC+(HA+CP) in the presence of hyaluronidase and within the RA joint space. Following intra-articular injection, both the PC+(HA-CP) and PC+(HA+CP) depots exhibited reductions in RA symptoms, cartilage regeneration, and suppression of pro-inflammatory cytokine levels. Specifically, by extending the in vivo retention of CP, PC+(HA-CP) demonstrated superior RA treatment efficacy compared to PC+(HA+CP). In conclusion, intra-articular injection of PC+(HA-CP) was validated as an effective strategy for treating RA, owing to its ability to prolong the in vivo retention of CP. This approach holds promise for improving RA management and patient outcomes.

Successful Distribution of Tecovirimat During the Peak of the Mpox Outbreak - Los Angeles County, June 2022-January 2023.

Tecovirimat is the first-line antiviral treatment recommended for severe mpox or for persons with mpox who are at risk for severe disease; tecovirimat is available in the United States under an expanded access investigational new drug (IND) protocol. During the 2022-2023 mpox outbreak, local U.S. health jurisdictions facilitated access to tecovirimat. In June 2022, Los Angeles County (LAC) rapidly developed strategies for tecovirimat distribution using existing medical countermeasure distribution networks established by the Public Health Emergency Preparedness Program and the Hospital Preparedness Program, creating a hub and spoke distribution network consisting of 44 hub facilities serving 456 satellite sites across LAC. IND patient intake forms were analyzed to describe mpox patients treated with tecovirimat. Tecovirimat treatment data were matched with case surveillance data to calculate time from specimen collection to patients receiving tecovirimat. Among 2,281 patients with mpox in LAC, 735 (32%) received tecovirimat during June 2022-January 2023. Among treated patients, approximately two thirds (508; 69%) received treatment through community clinics and pharmacies. The median interval from specimen collection to treatment was 2 days (IQR = 0-5 days). Local data collection and analysis helped to minimize gaps in treatment access and facilitated network performance monitoring. During public health emergencies, medical countermeasures can be rapidly deployed across a large jurisdiction using existing distribution networks, including clinics and pharmacies.

Effect of direct-acting antivirals on disease burden of hepatitis C virus infection in South Korea in 2007-2021: a nationwide, multicentre, retrospective cohort study.

Background: It is unclear whether direct-acting antivirals (DAAs) treatment improves the disease burden in hepatitis C virus (HCV) infection. This study aimed to investigate the effect of DAA treatment on the reduction of disease burden in patients with HCV infection using individual participant data. Methods: This nationwide multicentre retrospective cohort study recruited patients with HCV infection from 29 tertiary institutions in South Korea. The data collection was done from medical records in each institution. The study included the untreated patients and the DAAs-treated patients and excluded those with a history of interferon-based treatments. Disease burden was the primary outcome, as represented by disability-adjusted life years (DALYs). Improvement in fibrosis after DAA treatment was assessed using APRI, FIB-4 index, and liver stiffness (LS) as assessed by transient elastography. Clinical outcomes were hepatocellular carcinoma (HCC), decompensation, and mortality. Findings: Between January 1, 2007, and February 17, 2022, data from 11,725 patients with HCV infection, 8464 (72%) of whom were treated with DAAs, were analysed. DAA treatment significantly improved APRI- (median 0.64 [interquartile range (IQR), 0.35-1.31]-0.33 [0.23-0.52], p < 0.0001), FIB-4- (median 2.42 [IQR, 1.48-4.40]-1.93 [1.31-2.97], p < 0.0001), and liver LS-based fibrosis (median 7.4 [IQR, 5.3-12.3]-6.2 [4.6-10.2] kPa, p < 0.0001). During the median follow-up period of 27.5 months (IQR, 10.6-52.4), 469 patients died (4.0%), 586 (5.0%) developed HCC, and 580 (4.9%) developed decompensation. The APRI-based DALY estimate was significantly lower in the DAA group than in the untreated group (median 4.55 vs. 5.14 years, p < 0.0001), as was the FIB-4-based DALY estimate (median 5.43 [IQR, 3.00-6.44] vs. 5.79 [3.85-8.07] years, p < 0.0001). The differences between the untreated and DAA groups were greatest in patients aged 40-60 years. In multivariable analyses, the DAA group had a significantly reduced risk of HCC, decompensation, and mortality compared with the untreated group (hazard ratios: 0.41 [95% confidence interval (CI), 0.34-0.48], 0.31 [95% CI, 0.30-0.38], and 0.22 [95% CI, 0.17-0.27], respectively; p < 0.0001). Interpretation: Our findings suggest that DAA treatment is associated with the improvement of liver-related outcomes and a reduction of liver fibrosis-based disease burden in patients with HCV infection. However, further studies using liver biopsy are needed to clarify the effect of DAA treatment on the reduction in the exact fibrosis-based disease burden beyond noninvasive tests. Funding: The Korea Disease Control and Prevention Agency.

The effect of IGFBP3 gene knockout by the CRISPR/Cas9 system on the IGF-1 pathway in murine cells.

BACKGROUND: The IGF-1 signaling pathway has been deeply involved in the aging mechanism. The insulin-like growth factor binding protein 3 (IGFBP-3) is a protein that binds to IGF-1 that regulates growth, survival, and aging. OBJECTIVE: The purpose of this study was to investigate the impact of the IGFBP3 gene knockout (KO) on the expressions of aging-related proteins and genes using the CRISPR/Cas9 system. METHODS: The IGFBP3 gene knockout (KO) was performed by the CRISPR/Cas9 system. Sanger DNA sequencing and Indel analyses were used to verify the induction of mutation. RESULTS: First, Sanger DNA sequencing was used to analyze the IGFBP3 gene knockout in murine cells (B16F1). The isolation of three colonies with the mutated DNA sequences in the IGFBP3 gene was validated. In addition, the expression levels of the IGFBP3 gene and protein in the edited B16F1 cells were lower than in those of normal B16F1 cells in western blot analysis as well as RT-PCR and qPCR. Moreover, IGFBP3 gene KO cells enhanced the level of SA-ß-gal staining and short telomere length compared to normal B16F1 cells. In particular, it was found that the expression levels of senescence-related proteins such as PI3K, AKT1, PDK1, and p53 were higher in IGFBP3 gene KO cells than in normal cells in both the absence and presence of IGF-1. CONCLUSIONS: Therefore, the above findings could provide a clue that IGFBP3 could play a key role in the aging mechanism.

Using machine learning models to estimate Escherichia coli concentration in an irrigation pond from water quality and drone-based RGB imagery data.

The rapid and efficient quantification of Escherichia coli concentrations is crucial for monitoring water quality. Remote sensing techniques and machine learning algorithms have been used to detect E. coli in water and estimate its concentrations. The application of these approaches, however, is challenged by limited sample availability and unbalanced water quality datasets. In this study, we estimated the E. coli concentration in an irrigation pond in Maryland, USA, during the summer season using demosaiced natural color (red, green, and blue: RGB) imagery in the visible and infrared spectral ranges, and a set of 14 water quality parameters. We did this by deploying four machine learning models - Random Forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), and K-nearest Neighbor (KNN) - under three data utilization scenarios: water quality parameters only, combined water quality and small unmanned aircraft system (sUAS)-based RGB data, and RGB data only. To select the training and test datasets, we applied two data-splitting methods: ordinary and quantile data splitting. These methods provided a constant splitting ratio in each decile of the E. coli concentration distribution. Quantile data splitting resulted in better model performance metrics and smaller differences between the metrics for both the training and testing datasets. When trained with quantile data splitting after hyperparameter optimization, models RF, GBM, and XGB had R2 values above 0.847 for the training dataset and above 0.689 for the test dataset. The combination of water quality and RGB imagery data resulted in a higher R2 value (>0.896) for the test dataset. Shapley additive explanations (SHAP) of the relative importance of variables revealed that the visible blue spectrum intensity and water temperature were the most influential parameters in the RF model. Demosaiced RGB imagery served as a useful predictor of E. coli concentration in the studied irrigation pond.

SAROS: A dataset for whole-body region and organ segmentation in CT imaging.

The Sparsely Annotated Region and Organ Segmentation (SAROS) dataset was created using data from The Cancer Imaging Archive (TCIA) to provide a large open-access CT dataset with high-quality annotations of body landmarks. In-house segmentation models were employed to generate annotation proposals on randomly selected cases from TCIA. The dataset includes 13 semantic body region labels (abdominal/thoracic cavity, bones, brain, breast implant, mediastinum, muscle, parotid/submandibular/thyroid glands, pericardium, spinal cord, subcutaneous tissue) and six body part labels (left/right arm/leg, head, torso). Case selection was based on the DICOM series description, gender, and imaging protocol, resulting in 882 patients (438 female) for a total of 900 CTs. Manual review and correction of proposals were conducted in a continuous quality control cycle. Only every fifth axial slice was annotated, yielding 20150 annotated slices from 28 data collections. For the reproducibility on downstream tasks, five cross-validation folds and a test set were pre-defined. The SAROS dataset serves as an open-access resource for training and evaluating novel segmentation models, covering various scanner vendors and diseases.

Amplifying endogenous stem cell migration for in situ bone tissue formation: Substance P analog and BMP mimetic peptide-loaded click-crosslinked hyaluronic acid hydrogel.

Endogenous stem cell-driven in situ bone tissue formation has recently garnered increasing attention. Therefore, our study sought to refine methods to enhance the migration and subsequent osteogenic differentiation of these cells. Our innovative approach involves using an injectable hydrogel that combines click cross-linking sites and a BMP-2 mimetic peptide (BP) with hyaluronic acid (HA). This injectable formulation, hereinafter referred to as SPa + Cx-HA-BP, incorporates a substance P analog peptide (SPa) with Cx-HA-BP, proving versatile for in vitro and in vivo applications without cytotoxicity. The controlled release of SPa creates a gradient that guides endogenous stem cells towards the Cx-HA scaffold from specific tissue niches. Both Cx-HA and SPa+Cx-HA induced minimal changes in the expression of genes associated with osteogenic differentiation. In contrast, these genes were robustly induced by both SPa + Cx-HA+BP and SPa + Cx-HA-BP, in which BP was respectively integrated via physical and chemical methods. Remarkably, chemically incorporating BP (Cx-HA-BP) resulted in 4-9 times higher osteogenic gene expression than physically mixed BP in Cx-HA+BP. This study validates the role of SPa role in guiding endogenous stem cells toward the hydrogel and underscores the substantial impact of sustained BP presence within the hydrogel. Collectively, our findings offer valuable insights for the development of innovative strategies to promote endogenous stem cell-based tissue regeneration. The developed hydrogel effectively guides stem cells from their natural locations and facilitates sustained osteogenic differentiation, thus holding great promise for applications in regenerative medicine.

The Association between Low Fetal Fraction of Non-Invasive Prenatal Testing and Adverse Pregnancy Outcomes for Placental Compromise.

(1) Background: Non-invasive prenatal testing (NIPT) is a screening test for fetal aneuploidy using cell-free fetal DNA. The fetal fragments (FF) of cell-free DNA (cfDNA) are derived from apoptotic trophoblast of the placenta. The level of fetal cfDNA is known to be influenced by gestational age, multiple pregnancies, maternal weight, and height. (2) Methods: This study is a single-center retrospective observational study which examines the relationship between the fetal fraction (FF) of cell-free DNA in non-invasive prenatal testing (NIPT) and adverse pregnancy outcomes in singleton pregnancies. A total of 1393 samples were collected between 10 weeks and 6 days, and 25 weeks and 3 days of gestation. (3) Results: Hypertensive disease of pregnancy (HDP) occurred more frequently in the low FF group than the normal FF group (5.17% vs. 1.91%, p = 0.001). Although the rates of small for gestational age (SGA) and placental abruption did not significantly differ between groups, the composite outcome was significantly higher in the low FF group (7.76% vs. 3.64%, p = 0.002). Furthermore, women who later experienced complications such as HDP or gestational diabetes mellitus (GDM) had significantly lower plasma FF levels compared to those without complications (p < 0.001). After adjustments, the low FF group exhibited a significantly higher likelihood of placental compromise (adjusted odds ratio: 1.946). (4) Conclusions: Low FF in NIPT during the first and early second trimesters is associated with adverse pregnancy outcomes, particularly HDP, suggesting its potential as a predictive marker for such outcomes.

CuO nanostructure-decorated InGaN nanorods for selective H2S gas detection.

Establishing a heterostructure is one of the adequate strategies for enhancing device performance and has been explored in sensing, and energy applications. In this study, we constructed a heterostructure through a two-step process involving hydrothermal synthesis of CuO nanostructures and subsequent spin coating on MBE-grown InGaN NRs. We found that the CuO content on the InGaN NRs has a great impact on carrier injection at the heterojunction and thus the H2S gas sensing performance. Popcorn CuO/InGaN NR shows excellent gas sensing performance towards different concentrations of H2S at room temperature. The highest response is up to 35.54% to a H2S concentration of 100 ppm. Even more significantly, this response is further enhanced significantly (123.70%) under 365 nm UV light. In contrast, this composite structure exhibits negligibly low responses to 100 ppm of NO2, H2, CO, and NH3. The heterostructure band model associated with a surface reaction model is manifested to elucidate the sensing mechanism.

Validation of MELD 3.0 in patients with alcoholic liver cirrhosis using prospective KACLiF cohort.

BACKGROUND AND AIM: The Model for End-Stage Liver Disease (MELD) is a reliable prognostic tool for short-term outcome prediction in patients with end-stage liver disease. MELD 3.0 was introduced to enhance the predictive accuracy. This study assessed the performance of MELD 3.0, in comparison to MELD and MELD-Na, in patients with alcoholic liver cirrhosis. METHODS: This multicenter prospective cohort study comprised patients with alcoholic cirrhosis admitted for acute deterioration of liver function in the Republic of Korea between 2015 and 2019. This study compared the predictive abilities of MELD, MELD-Na, and MELD 3.0, for 30-day and 90-day outcomes, specifically death or liver transplantation, and explored the factors influencing these outcomes. RESULTS: A total of 1096 patients were included in the study, with a mean age of 53.3 ± 10.4 years, and 82.0% were male. The mean scores for MELD, MELD-Na, and MELD 3.0 at the time of admission were 18.7 ± 7.2, 20.6 ± 7.7, and 21.0 ± 7.8, respectively. At 30 and 90 days, 7.2% and 14.1% of patients experienced mortality or liver transplantation. The areas under the receiver operating characteristic curves for MELD, MELD-Na, and MELD 3.0 at 30 days were 0.823, 0.820, and 0.828; and at 90 days were 0.765, 0.772, and 0.776, respectively. Factors associated with the 90-day outcome included concomitant chronic viral hepatitis, prolonged prothrombin time, elevated levels of aspartate transaminase, bilirubin, and creatinine, and low albumin levels. CONCLUSION: MELD 3.0 demonstrated improved performance compared to previous models, although the differences were not statistically significant.

Inactivation of Escherichia coli, Salmonella enterica, and Listeria monocytogenes using the Contamination Sanitization Inspection and Disinfection (CSI-D) device.

The Contamination Sanitization Inspection and Disinfection (CSI-D) device is a handheld fluorescence-based imaging system designed to disinfect food contact surfaces using ultraviolet-C (UVC) illumination. This study aimed to determine the optimal CSI-D parameters (i.e., UVC exposure time and intensity) for the inactivation of the following foodborne bacteria plated on non-selective media: generic Escherichia coli (indicator organism) and the pathogens enterohemorrhagic E. coli, enterotoxigenic E. coli, Salmonella enterica, and Listeria monocytogenes. Each bacterial strain was spread-plated on non-selective agar and exposed to high-intensity (10 mW/cm2) or low-intensity (5 mW/cm2) UVC for 1-5 s. Control plates were not exposed to UVC. The plates were incubated overnight at 37 °C and then enumerated. Three trials for each bacterial strain were conducted. Statistical analysis was carried out to determine if there were significant differences in bacterial growth between UVC intensities and exposure times. Overall, exposure to low or high intensity for 3-5 s resulted in consistent inhibition of bacterial growth, with reductions of 99.9-100 % for E. coli, 96.8-100 % for S. enterica, and 99.2-100 % for L. monocytogenes. The 1 s exposure time showed inconsistent results, with a 66.0-100 % reduction in growth depending on the intensity and bacterial strain. When the results for all strains within each species were combined, the 3-5 s exposure times showed significantly greater (p < 0.05) growth inhibition than the 1 s exposure time. However, there were no significant differences (p > 0.05) in growth inhibition between the high and low UVC intensities. The results of this study show that, in pure culture conditions, exposure to UVC with the CSI-D device for ≥3 s is required to achieve consistent reduction of E. coli, S. enterica, and L. monocytogenes.

Recombinant human fibroblast growth factor 7 obtained from stable Chinese hamster ovary cells enhances wound healing.

Although fibroblast growth factor 7 (FGF7) is known to promote wound healing, its mass production poses several challenges and very few studies have assessed the feasibility of producing FGF7 in cell lines such as Chinese hamster ovary (CHO) cells. Therefore, this study sought to produce recombinant FGF7 in large quantities and evaluate its wound healing effect. To this end, the FGF7 gene was transfected into CHO cells and FGF7 production was optimized. The wound healing efficacy of N-glycosylated FGF7 was evaluated in animals on days 7 and 14 post-treatment using collagen patches (CPs), FGF7-only, and CP with FGF7 (CP+FGF7), whereas an untreated group was used as the control. Wound healing was most effective in the CP+FGF7 group. Particularly, on day 7 post-exposure, the CP+FGF7 and FGF7-only groups exhibited the highest expression of hydroxyproline, fibroblast growth factor, vascular endothelial growth factor, and transforming growth factor. Epidermalization in H&E staining showed the same order of healing as hydroxyproline content. Additionally, the CP+FGF7 and FGF7-only group exhibited more notable blood vessel formation on days 7 and 14. In conclusion, the prepared FGF7 was effective in promoting wound healing and CHO cells can be a reliable platform for the mass production of FGF7.