Genomic instabilities in hepatocellular carcinoma: biomarkers and application in immunotherapies.

Hepatocellular carcinoma (HCC) is one of the deadliest cancers. For patients with advanced HCC, liver function decompensation often occurs, which leads to poor tolerance to chemotherapies and other aggressive treatments. Therefore, it remains critical to develop effective therapeutic strategies for HCC. Etiological factors for HCC are complex and multifaceted, including hepatitis virus infection, alcohol, drug abuse, chronic metabolic abnormalities, and others. Thus, HCC has been categorized as a "genomically unstable" cancer due to the typical manifestation of chromosome breakage and aneuploidy, and oxidative DNA damage. In recent years, immunotherapy has provided a new option for cancer treatments, and the degree of genomic instability positively correlates with immunotherapy efficacies. This article reviews the endogenous and exogenous causes that affect the genomic stability of liver cells; it also updates the current biomarkers and their detection methods for genomic instabilities and relevant applications in cancer immunotherapies. Including genomic instability biomarkers in consideration of cancer treatment options shall increase the patients' well-being.

Repulsion, Acceleration, and Coalescence between Water Droplets on Superhydrophobic Glass by Triboelectrification.

Manipulating the motion of water droplets on surfaces, which is crucial for various applications, such as microfluidics and heat transfer, presents considerable challenges, primarily due to the significant influence of capillary forces. This effect becomes more pronounced when droplets are in close proximity, often resulting in undesired coalescence. Triboelectrification, which involves charging pure water droplets, is a promising approach to enhance the ability to manipulate water droplets. For effective triboelectrification, charges must accumulate within the droplets; this ensures efficient and sustained droplet manipulation while minimizing dissipation. Low-friction, superhydrophobic, insulating surfaces are ideal for this purpose. However, few studies have explored the application of insulating superhydrophobic surfaces to manipulate droplet motion. In this study, we investigated the behavior of water droplets on insulating superhydrophobic quartz surfaces after triboelectrification. The droplets acquired significant charge when dripped onto a superhydrophobic glass surface. Consequently, these charged droplets exhibited behaviors such as repulsion and acceleration from one another, uphill movement, and rapid long-distance transport to specific positions. These advancements in droplet manipulation techniques hold promise for diverse fields such as microfluidics and heat exchangers.

Live and Dead Clostridium butyricum GKB7 Diminish Osteoarthritis Pain and Progression in Preclinical Animal Model.

Osteoarthritis (OA) is a degenerative joint disease primarily affecting the elderly. It is characterized by the progressive decline of joint cartilage and alterations in the underlying bone. Several probiotic strains have exhibited immunomodulatory and anti-inflammatory properties. Here, we examined the functions of live and dead Clostridium butyricum GKB7 (GKB7-L and GKB7-D) in a preclinical anterior cruciate ligament transection (ACLT)-enhanced OA procedure. Oral administration of GKB7-L and GKB7-D ameliorated ACLT-induced bone pain as assessed by weight-bearing behavioral testing but did not affect body weight. Micro-computed tomography (CT) results showed that GKB7-L and GKB7-D diminished ACLT-induced bone destruction and loss. GKB7-L and GKB7-D-enriched therapies also reduced ACLT-induced production of the pro-inflammatory cytokines interleukin (IL)-1ß and tumor necrosis factor (TNF)-α, as well as the chondrolytic factor matrix metalloproteinase (MMP)-3, leading to inhibition of aggrecan and collagen type II degradation and thereby blocking cartilage breakdown. We therefore suggest that oral supplementation with GKB7-L or GKB7-D can be beneficial in the prevention and treatment of OA.

Lemon Peel Water Extract: A Novel Material for Retinal Health, Protecting Retinal Pigment Epithelial Cells against Dynamin-Related Protein 1-Mediated Mitochondrial Fission by Blocking ROS-Stimulated Mitogen-Activated Protein Kinase/Extracellular Signal-Regulated Kinase Pathway.

Previous studies showed that NaIO3 can induce oxidative stress-mediated retinal pigment epithelium (RPE) damage to simulate age-related macular degeneration (AMD). Lemon peel is rich in antioxidants and components that can penetrate the blood-retinal barrier, but their role in retinal oxidative damage remains unexplored. Here, we explore the protection of lemon peel ultrasonic-assisted water extract (LUWE), containing large amounts of flavonoids and polyphenols, against NaIO3-induced retinal degeneration. We initially demonstrated that LUWE, orally administered, prevented retinal distortion and thinning on the inner and outer nuclei layers, downregulating cleaved caspase-3 protein expression in RPE cells in NaIO3-induced mice. The effect of LUWE was achieved through the suppression of apoptosis and the associated proteins, such as cleaved PARP and cleaved caspase-3, as suggested by NaIO3-induced ARPE-19 cell models. This is because LUWE reduced reactive oxygen species-mediated mitochondrial fission via regulating p-Drp-1 and Fis1 expression. We further confirmed that LUWE suppresses the expression of p-MEK-1/2 and p-ERK-1/2 in NaIO3-induced ARPE-19 cells, thereby providing the protection described above, which was confirmed using PD98059 and U0126. These results indicated that LUWE prevents mitochondrial oxidative stress-mediated RPE damage via the MEK/ERK pathway. Elucidation of the molecular mechanism may provide a new protective strategy against retinal degeneration.

The associations among peptic ulcer disease, Helicobacter pylori infection, and abdominal aortic aneurysms: A nationwide population-based cohort study.

BACKGROUND: There are overlapping risk factors and underlying molecular mechanisms for both peptic ulcer disease (PUD) and abdominal aortic aneurysm (AAA). Despite improvements in the early diagnosis and treatment of AAA, ruptured AAAs continue to cause a substantial number of deaths. Helicobacter pylori are Gram-negative, microaerophilic bacteria that are now recognized as the main cause of PUD. H. pylori infection (HPI) is associated with an increased risk of certain cardiovascular diseases. HPIs can be treated with at least two different antibiotics to prevent bacteria from developing resistance to one particular antibiotic. METHODS: We conducted a population-based cohort study using the National Health Insurance Research Database to evaluate whether associations exist among PUD, HPI, and eradication therapy for HPI and AAA. The primary outcome of this study was the cumulative incidence of AAA among patients with or without PUD and HPI during the 14-year follow-up period. RESULTS: Our analysis included 7003 patients with PUD/HPI, 7003 patients with only PUD, and another 7003 age-, sex-, and comorbidity-matched controls from the database. We found that patients with PUD/HPI had a significantly increased risk of AAA compared to those with PUD alone and matched controls. The patients who had PUD/HPI had a significantly higher cumulative risk of developing AAA than those with PUD and the comparison group (2.67 % vs. 1.41 % vs. 0.73 %, respectively, p < 0.001). Among those patients with PUD/HPI, patients who had eradication therapy had a lower incidence of AAA than those without eradication therapy (2.46 % vs. 3.88 %, p = 0.012). CONCLUSIONS: We revealed an association among PUD, HPI, and AAA, even after adjusting for age, sex, comorbidities, and annual medical follow-up visits. Notably, we found that HPI eradication therapy reduced the incidence of AAA among patients with PUD.

Quantifying source contributions to ambient NH3 using Geo-AI with time lag and parcel tracking functions.

Ambient ammonia (NH3) plays an important compound in forming particulate matters (PMs), and therefore, it is crucial to comprehend NH3's properties in order to better reduce PMs. However, it is not easy to achieve this goal due to the limited range/real-time NH3 data monitored by the air quality stations. While there were other studies to predict NH3 and its source apportionment, this manuscript provides a novel method (i.e., GEO-AI)) to look into NH3 predictions and their contribution sources. This study represents a pioneering effort in the application of a novel geospatial-artificial intelligence (Geo-AI) base model with parcel tracking functions. This innovative approach seamlessly integrates various machine learning algorithms and geographic predictor variables to estimate NH3 concentrations, marking the first instance of such a comprehensive methodology. The Shapley additive explanation (SHAP) was used to further analyze source contribution of NH3 with domain knowledge. From 2016 to 2018, Taichung's hourly average NH3 values were predicted with total variance up to 96%. SHAP values revealed that waterbody, traffic and agriculture emissions were the most significant factors to affect NH3 concentrations in Taichung among all the characteristics. Our methodology is a vital first step for shaping future policies and regulations and is adaptable to regions with limited monitoring sites.

Indigofera suffruticosa aerial parts extract induce G2/M arrest and ATR/CHK1 pathway in Jurkat cells.

BACKGROUND: Indigofera suffruticosa Mill. is used as a folk medicine for treating patients with leukemia, however very little is known regarding the molecular mechanism of its anti-leukemic activity and the chemical profile of the active extract. The present study aimed to reveal the molecular effect of I. suffruticosa aerial parts extract (ISAE) on leukemia cells and its chemical constituents. METHODS: Cytotoxicity of ISAE were determined by resazurin viability assay, multitox - Glo multiplex cytotoxicity assay, and Annexin V staining assay. Cell cycle profiles were revealed by propidium iodide staining assay. The effects of ISAE on G2/M arrest signaling and DNA damage were evaluated by Western blot assay and phospho-H2A.X staining assay. The chemical profile of ISAE were determined by tandem mass spectroscopy and molecular networking approach. RESULTS: We showed that the acute lymphoblastic leukemia cell line Jurkat cell was more responsive to ISAE treatment than other leukemia cell lines. In contrast, ISAE did not induce cytotoxic effects in normal fibroblast cells. Cell cycle analysis revealed that ISAE triggered G2/M arrest in Jurkat cells in dose- and time-dependent manners. Elevation of annexin V-stained cells and caspase 3/7 activity suggested ISAE-induced apoptosis. Furthermore, ISAE alone could increase the phosphorylation of CDK1 at Y15 and activate the ATR/CHK1/Wee1/CDC25C signaling pathway. However, the addition of caffeine, a widely used ATR inhibitor to ISAE, reduced the phosphorylation of ATR, CHK1, and CDK1, as well as G2/M arrest in Jurkat cells. Moreover, increased phospho-H2A.X stained cells indicated the involvement of DNA damage in the anti-leukemic effect of ISAE. Finally, qualitative analysis using UPLC-tandem mass spectroscopy and molecular networking revealed that tryptanthrin was the most abundant organoheterocyclic metabolite in ISAE. At equivalent concentrations to ISAE, tryptanthrin induced G2/M arrest of Jurkat cells, which can be prevented by caffeine. CONCLUSIONS: ISAE causes G2/M arrest via activating ATR/CHK1/CDK1 pathway and tryptanthrin is one of the active components of ISAE. Our findings provide subtle support to the traditional use of I. suffruitcosa in leukemia management in folk medicine.

A machine learning-based ensemble model for estimating diurnal variations of nitrogen oxide concentrations in Taiwan.

Air pollution is inextricable from human activity patterns. This is especially true for nitrogen oxide (NOx), a pollutant that exists naturally and also as a result of anthropogenic factors. Assessing exposure by considering diurnal variation is a challenge that has not been widely studied. Incorporating 27 years of data, we attempted to estimate diurnal variations in NOx across Taiwan. We developed a machine learning-based ensemble model that integrated hybrid kriging-LUR, machine-learning, and an ensemble learning approach. Hybrid kriging-LUR was performed to select the most influential predictors, and machine-learning algorithms were applied to improve model performance. The three best machine-learning algorithms were suited and reassessed to develop ensemble learning that was designed to improve model performance. Our ensemble model resulted in estimates of daytime, nighttime, and daily NOx with high explanatory powers (Adj-R2) of 0.93, 0.98, and 0.94, respectively. These explanatory powers increased from the initial model that used only hybrid kriging-LUR. Additionally, the results depicted the temporal variation of NOx, with concentrations higher during the daytime than the nighttime. Regarding spatial variation, the highest NOx concentrations were identified in northern and western Taiwan. Model evaluations confirmed the reliability of the models. This study could serve as a reference for regional planning supporting emission control for environmental and human health.

Estimating morning and evening commute period O3 concentration in Taiwan using a fine spatial-temporal resolution ensemble mixed spatial model with Geo-AI technology.

Elevated levels of ground-level ozone (O3) can have harmful effects on health. While previous studies have focused mainly on daily averages and daytime patterns, it's crucial to consider the effects of air pollution during daily commutes, as this can significantly contribute to overall exposure. This study is also the first to employ an ensemble mixed spatial model (EMSM) that integrates multiple machine learning algorithms and predictor variables selected using Shapley Additive exExplanations (SHAP) values to predict spatial-temporal fluctuations in O3 concentrations across the entire island of Taiwan. We utilized geospatial-artificial intelligence (Geo-AI), incorporating kriging, land use regression (LUR), machine learning (random forest (RF), categorical boosting (CatBoost), gradient boosting (GBM), extreme gradient boosting (XGBoost), and light gradient boosting (LightGBM)), and ensemble learning techniques to develop ensemble mixed spatial models (EMSMs) for morning and evening commute periods. The EMSMs were used to estimate long-term spatiotemporal variations of O3 levels, accounting for in-situ measurements, meteorological factors, geospatial predictors, and social and seasonal influences over a 26-year period. Compared to conventional LUR-based approaches, the EMSMs improved performance by 58% for both commute periods, with high explanatory power and an adjusted R2 of 0.91. Internal and external validation procedures and verification of O3 concentrations at the upper percentile ranges (in 1%, 5%, 10%, 15%, 20%, and 25%) and other conditions (including rain, no rain, weekday, weekend, festival, and no festival) have demonstrated that the models are stable and free from overfitting issues. Estimation maps were generated to examine changes in O3 levels before and during the implementation of COVID-19 restrictions. These findings provide accurate variations of O3 levels in commute period with high spatiotemporal resolution of daily and 50m * 50m grid, which can support control pollution efforts and aid in epidemiological studies.

Patients with Hepatitis C Undergoing Direct-Acting Antiviral Treatment Have a Lower SARS-CoV-2 Infection Rate.

This study retrospectively analyzed the medical records of 602 patients with first-time positive results for the HCV nucleic acid test between 1 May 2021 and 31 March 2023, exploring the association between DAA treatment and SARS-CoV-2 infection. The results showed that 9.8% of HCV patients were co-infected with SARS-CoV-2. Gender, age, vaccination status, and HCV genotype did not significantly affect SARS-CoV-2 infection. However, patients undergoing DAA treatment showed significantly lower rates of SARS-CoV-2 infection and mortality compared to those not undergoing DAA treatment. The analysis also compared patients undergoing different DAA treatments, with Epclusa and Maviret showing superior protection against SARS-CoV-2. Furthermore, this study explored the severity and mortality of SARS-CoV-2 infection in patients undergoing and having completed DAA treatment. It revealed that patients diagnosed with COVID-19 during DAA treatment experienced only mild symptoms, and none died, suggesting a potential protective effect of DAA treatment against severe outcomes of SARS-CoV-2 infection. The findings contribute to the understanding of the interplay between HCV, DAA treatment, and SARS-CoV-2 infection, highlighting the need for continued monitoring and healthcare measures for individuals with chronic conditions during the ongoing COVID-19 pandemic.

Evaluating long-term and high spatiotemporal resolution of wet-bulb globe temperature through land-use based machine learning model.

BACKGROUND: The increase in global temperature and urban warming has led to the exacerbation of heatwaves, which negatively affect human health and cause long-term loss of work productivity. Therefore, a global assessment in temperature variation is essential. OBJECTIVE: This paper is the first of its kind to propose land-use based spatial machine learning (LBSM) models for predicting highly spatial-temporal variations of wet-bulb globe temperature (WBGT), which is a heat stress indicator used to assess thermal comfort in indoor and outdoor environments, specifically for the main island of Taiwan. METHODS: To develop spatiotemporal prediction models for both the working period and noon period, we calculated the WBGT of each weather station from 2001 to 2019 using temperature, humidity, and solar radiation data. These WBGT estimations were then used as the dependent variable for developing the spatiotemporal prediction models. To enhance model performance, we used innovative approaches that combined SHapley Additive exPlanations (SHAP) values for the selection of non-linear variables, along with machine learning algorithms for model development. RESULTS: When incorporating temperature along with other land-use/land cover predictor variables, the performance of LBSM models was excellent, with an R2 value of up to 0.99. The LBSM models explained 98% and 99% of the spatial-temporal variations in WBGT for the working and noon periods, respectively, within the complete models. In the temperature-excluded models, the explained variances were 94% and 96% for the working and noon periods, respectively. IMPACT: WBGT is a common method used by many organizations to access the impact of heat stress on human beings. However, limited studies have mentioned the association between WBGT and health impacts due to the absence of spatiotemporal databases. This study develops a new approach using land-use-based spatial machine learning (LBSM) models to better predict the fine spatial-temporal WBGT levels, with a 50-m × 50-m grid resolution for both working time and noontime. Our proposed methodology could be used in future studies aimed at evaluating the potential long-term loss of work productivity due to the effects of global warming or urban heat island.

High-mobility group box-1 impedes skeletal muscle regeneration via downregulation of Pax-7 synthesis by increasing miR-342-5p expression.

High mobility group box-1 (HMGB1) is a driver of inflammation in various muscular diseases. In a previous study, we determined that HMGB1 induced the atrophy of skeletal muscle by impairing myogenesis. Skeletal muscle regeneration after injury is dependent on pair box 7 (Pax-7)-mediated myogenic differentiation. In the current study, we determined that the HMGB1-induced downregulation of Pax-7 expression in myoblasts inhibited the regeneration of skeletal muscle. We also determined that HMGB1 inhibits Pax-7 and muscle differentiation by increasing miR-342-5p synthesis via receptors for advanced glycation end-products (RAGE), toll-like receptor (TLR) 2, TLR4, and c-Src signaling pathways. In a mouse model involving glycerol-induced muscle injury, the therapeutic inhibition of HMGB1 was shown to rescue Pax-7 expression and muscle regeneration. The HMGB1/Pax-7 axis is a promising therapeutic target to promote muscular regeneration.

Association between pain and cognitive and daily functional impairment in older institutional residents: a cross-sectional study.

BACKGROUND: Pain is often neglected in disabled older population, especially in Taiwan where the population of institutional residents is rapidly growing. Our study aimed to investigate pain prevalence and associated factors among institutional residents to improve pain assessment and management. METHODS: This nationwide study recruited 5,746 institutional residents in Taiwan between July 2019 and February 2020. Patient self-report was considered the most valid and reliable indicator of pain. A 5-point verbal rating scale was used to measure pain intensity, with a score ranging from 2 to 5 indicating the presence of pain. Associated factors with pain, including comorbidities, functional dependence, and quality of life, were also assessed. RESULTS: The mean age of the residents was 77.1 ± 13.4 years, with 63.1% of them aged over 75 years. Overall, 40.3% of the residents reported pain, of whom 51.2% had moderate to severe pain. Pain was more common in residents with comorbidities and significantly impacted emotions and behavior problems, and the mean EQ5D score, which is a measure of health-related quality of life (p < .001). Interestingly, pain was only related to instrumental activities of daily living (IADL) and not activities of daily living (ADL). On the other hand, dementia was significantly negatively associated with pain (p < .001), with an estimated odds of 0.63 times (95% CI: 0.53-0.75) for the presence of pain when compared to residents who did not have dementia. CONCLUSIONS: Unmanaged pain is common among institutional residents and is associated with comorbidities, IADL, emotional/behavioral problems, and health-related quality of life. Older residents may have lower odds of reporting pain due to difficulty communicating their pain, even through the use of a simple 5-point verbal rating scale. Therefore, more attention and effort should be directed towards improving pain evaluation in this vulnerable population .

Downregulation of CRTAC1 in Urothelial Carcinoma Promotes Tumor Aggressiveness and Confers Poor Prognosis.

BACKGROUND: Cartilage acidic protein 1 (CRTAC1) is a glycosylated calcium-binding extracellular matrix protein. The oncological functions of CRTAC1 in urothelial carcinoma (UC) of the urinary bladder (UB) and upper urinary tract (UT) have not yet been elucidated. Based on the published UBUC transcriptome data, we re-evaluated the differential expression profile of calcium ion binding-related genes (GO:0005509), and we found that CRTAC1 was the most significantly downregulated gene in UBUC progression. Therefore, we analyzed the prognostic value and biological significance of CRTAC1 expression in UC. METHODS: We used immunohistochemistry to determine the CRTAC1 expression levels in 340 patients with UTUC and 295 patients with UBUC. The CRTAC1 expression was compared with the clinicopathological characteristics, and the prognostic impact of CRTAC1 on metastasis-free survival (MFS) and disease-specific survival (DSS) was evaluated. To study the biological functions of CRTAC1, the proliferation, migration, invasion, and tube formation abilities of UC-derived cells were evaluated. RESULTS: A low CRTAC1 expression significantly correlated with high tumor stage, high histological grade, perineural invasion, vascular invasion, nodal metastasis, and high mitotic rate (all p < 0.01). Moreover, the CRTAC1 immunoexpression status was an independent prognostic factor for MFS and DSS in UBUC and UTUC patients (all p < 0.001) in the multivariate analysis. The exogenous expression of CRTAC1 suppressed the cell proliferation, invasion, and angiogenesis, and downregulated the matrix metallopeptidase 2 (MMP2) level in BFTC909 and T24 cells. CONCLUSIONS: CRTAC1 may participate in progression of UC and serve as a prognostic marker for metastasis. Low CRTAC1 expression was significantly associated with aggressive UC characteristics and worse clinical outcomes. The inclusion of CRTAC1 immunoexpression in the standard pathological variables may optimize the risk stratification of patients.

Mei-Gin Formula Ameliorates Obesity through Lipolysis, Fatty Oxidation, and Thermogenesis in High-Fat Diet-Induced Obese Rats.

Obesity is a metabolic dysfunction characterized by excessive body fat deposition as a consequence of an energy imbalance. Novel therapeutic strategies have emerged that are safe and have comparatively low side effects for obesity treatment. Functional foods and nutraceuticals have recently received a great deal of attention because of their components with the properties of antimetabolic syndrome. Based on our previous in vitro and in vivo investigations on anti-adipogenesis activity and improved body fat accumulation in serials, the combination of three ingredients (including bainiku-ekisu, black garlic, and Mesona procumbens Hemsl), comprising the Mei-Gin formula (MGF), was eventually selected as a novel inhibitor that exhibited preventive effects against obesity. Herein, we verify the anti-obesity effects of MGF in obese rats induced by a high-fat diet and discuss the potential molecular mechanisms underlying obesity development. Oral administration of MGF significantly suppressed the final body weight, weight change, energy and water intake, subcutaneous and visceral fat mass, liver weight, hepatic total lipids and triglycerides (TG), and serum levels of TG, triglycerides (TC), low-density lipoprotein cholesterol (LDL-C), alanine transaminase (AST), uric acid, and ketone bodies and augmented fecal total lipids, TG, and cholesterol excretion in the high-dose MGF-supplemented groups. Furthermore, the corresponding lipid metabolic pathways revealed that MGF supplementation effectively increased lipolysis and fatty acid oxidation gene expression and attenuated fatty acid synthesis gene expression in the white adipose tissue (WAT) and liver and it also increased mitochondrial activation and thermogenic gene expression in the brown adipose tissue (BAT) of rats with obesity induced by a high-fat diet (HFD). These results demonstrate that the intake of MGF can be beneficial for the suppression of HFD-induced obesity in rats through the lipolysis, fatty oxidation, and thermogenesis pathway. In conclusion, these results demonstrate the anti-obesity efficacy of MGF in vivo and suggest that MGF may act as a potential therapeutic agent against obesity.

Using artificial intelligence to predict adverse outcomes in emergency department patients with hyperglycemic crises in real time.

BACKGROUND: Hyperglycemic crises are associated with high morbidity and mortality. Previous studies have proposed methods to predict adverse outcomes of patients in hyperglycemic crises; however, artificial intelligence (AI) has never been used to predict adverse outcomes. We implemented an AI model integrated with the hospital information system (HIS) to clarify whether AI could predict adverse outcomes. METHODS: We included 2,666 patients with hyperglycemic crises from emergency departments (ED) between 2009 and 2018. The patients were randomized into a 70%/30% split for AI model training and testing. Twenty-two feature variables from the electronic medical records were collected. The performance of the multilayer perceptron (MLP), logistic regression, random forest, Light Gradient Boosting Machine (LightGBM), support vector machine (SVM), and K-nearest neighbor (KNN) algorithms was compared. We selected the best algorithm to construct an AI model to predict sepsis or septic shock, intensive care unit (ICU) admission, and all-cause mortality within 1 month. The outcomes between the non-AI and AI groups were compared after implementing the HIS and predicting the hyperglycemic crisis death (PHD) score. RESULTS: The MLP had the best performance in predicting the three adverse outcomes, compared with the random forest, logistic regression, SVM, KNN, and LightGBM models. The areas under the curves (AUCs) using the MLP model were 0.852 for sepsis or septic shock, 0.743 for ICU admission, and 0.796 for all-cause mortality. Furthermore, we integrated the AI predictive model with the HIS to assist decision making in real time. No significant differences in ICU admission or all-cause mortality were detected between the non-AI and AI groups. The AI model performed better than the PHD score for predicting all-cause mortality (AUC 0.796 vs. 0.693). CONCLUSIONS: A real-time AI predictive model is a promising method for predicting adverse outcomes in ED patients with hyperglycemic crises. Further studies recruiting more patients are warranted.

The efficacy and safety of cuttlebone for lowering serum phosphate in patients with end-stage renal disease: a meta-analysis of randomized controlled trials.

Background: The efficacy of cuttlebone for treating hyperphosphatemia in patients with end-stage renal disease and its safety remained unclear. Methods: Randomized controlled trials comparing the efficacy of cuttlebone with conventional interventions were retrieved from MEDLINE, EMBASE, Cochrane Library, Airiti Library, and other major Chinese databases until 1 February 2023. The primary outcome was circulating phosphate concentration, while secondary outcomes included circulating calcium and intact parathyroid hormone levels, calcium-phosphorus product, and treatment-related side-effects. Results: Analysis of nine studies published between 2000 and 2019 including 726 participants showed a lower circulating phosphate concentration in the cuttlebone group than in controls [mean difference (MD) = -0.23, 95% CI: -0.39 to -0.06, p = 0.006, I2 = 94%, 726 patients] and a dose-dependent effect of cuttlebone against hyperphosphatemia. Therapeutic benefits were noted after both short-term (1-2 months) and long-term (3-6 months) treatments. Besides, patients receiving hemodialysis showed a better response to cuttlebone than those receiving peritoneal dialysis. There was no difference in circulating calcium level (mean difference = 0.03, 95% CI: -0.01 to 0.07, p = 0.17, I2 = 34%, 654 patients), while patients receiving cuttlebone showed lower circulating iPTH level and calcium-phosphorus product (MD = -43.63, 95% CI: -74.1 to -13.16, p = 0.005, I2 = 76%, 654 patients), (MD = -0.38, 95% CI: -0.38 to -0.01, p = 0.04, I2 = 83%, 520 patients). No difference in the risks of constipation, gastrointestinal discomfort, and elevated blood calcium was noted between the two groups. Conclusion: Compared with conventional phosphate-binding agents, cuttlebone more efficiently suppressed hyperphosphatemia with a dose-dependent effect. The limited number of included studies warrants further clinical investigations to verify our findings. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023396300.

High G9a Expression in DLBCL and Its Inhibition by Niclosamide to Induce Autophagy as a Therapeutic Approach.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is a malignant lymphoid tumor disease that is characterized by heterogeneity, but current treatment does not benefit all patients, which highlights the need to identify oncogenic genes and appropriate drugs. G9a is a histone methyltransferase that catalyzes histone H3 lysine 9 (H3K9) methylation to regulate gene function and expression in various cancers. METHODS: TCGA and GTEx data were analyzed using the GEPIA2 platform. Cell viability under drug treatment was assessed using Alamar Blue reagent; the interaction between G9a and niclosamide was assessed using molecular docking analysis; mRNA and protein expression were quantified in DLBCL cell lines. Finally, G9a expression was quantified in 39 DLBCL patient samples. RESULTS: The TCGA database analysis revealed higher G9a mRNA expression in DLBCL compared to normal tissues. Niclosamide inhibited DLBCL cell line proliferation in a time- and dose-dependent manner, reducing G9a expression and increasing p62, BECN1, and LC3 gene expression by autophagy pathway regulation. There was a correlation between G9a expression in DLBCL samples and clinical data, showing that advanced cancer stages exhibited a higher proportion of G9a-expressing cells. CONCLUSION: G9a overexpression is associated with tumor progression in DLBCL. Niclosamide effectively inhibits DLBCL growth by reducing G9a expression via the cellular autophagy pathway; therefore, G9a is a potential molecular target for the development of therapeutic strategies for DLBCL.

Characterization of the sources and health risks of polycyclic aromatic hydrocarbons in PM2.5 and their relationship with black carbon: A case study in northern Taiwan.

Polycyclic aromatic hydrocarbons (PAHs) and black carbon (BC) often coexist in PM2.5 because both form during the incomplete combustion of organic matter. These compounds are regarded as hazardous air pollutants with potential health effects, including respiratory and cardiovascular effects. In this study, to evaluate the health risks of PAHs and BC at an urban site in northern Taiwan, 16 priority PAHs and BC, identified by the United States Environmental Protection Agency, were analyzed and quantified in PM2.5 to determine their concentrations, their relationship with each other, and their likely sources. The results indicated that the mean concentrations of total PAHs and BC were 0.91 ng m-3 and 0.97 µg m-3, respectively, with a significant positive correlation between them, indicating the same emission sources. The results also indicated that fossil fuel combustion and traffic emissions were primary contributors to PAHs, with wood and biomass combustion playing a less prominent role. Among these 16 priority PAHs, benzo[a]pyrene, dibenz[a,h]anthracene, benzo[b]fluoranthene, and indeno[1,2,3-cd]pyrene served as major carcinogenic compounds, accounting for 89.0% of the total carcinogenic toxicity. Thus, the lifetime excess cancer risk resulting from PAH exposure was estimated as 8.03 × 10-6, indicating a potential carcinogenic risk to human health at the sampling site. Overall, this study highlights the need for future mitigation policies for traffic emissions and fossil fuel combustion for reducing the local emissions of BC and co-produced PAHs in northern Taiwan.