Latent space representation of electronic health records for clustering dialysis-associated kidney failure subtypes.

OBJECTIVE: Kidney failure manifests in various forms, from sudden occurrences such as Acute Kidney Injury (AKI) to progressive like Chronic Kidney Disease (CKD). Given its intricate nature, marked by overlapping comorbidities and clinical similarities-including treatment modalities like dialysis-we sought to design and validate an end-to-end framework for clustering kidney failure subtypes. MATERIALS AND METHODS: Our emphasis was on dialysis, utilizing a comprehensive dataset from the UK Biobank (UKB). We transformed raw Electronic Health Record (EHR) data into standardized matrices that incorporate patient demographics, clinical visit data, and the innovative feature of visit time-gaps. This matrix structure was achieved using a unique data cutting method. Latent space transformation was facilitated using a convolution autoencoder (ConvAE) model, which was then subjected to clustering using Principal Component Analysis (PCA) and K-means algorithms. RESULTS: Our transformation model effectively reduced data dimensionality, thereby accelerating computational processes. The derived latent space demonstrated remarkable clustering capacities. Through cluster analysis, two distinct groups were identified: CKD-majority (cluster 1) and a mixed group of non-CKD and some CKD subtypes (cluster 0). Cluster 1 exhibited notably low survival probability, suggesting it predominantly represented severe CKD. In contrast, cluster 0, with substantially higher survival probability, likely to include milder CKD forms and severe AKI. Our end-to-end framework effectively differentiates kidney failure subtypes using the UKB dataset, offering potential for nuanced therapeutic interventions. CONCLUSIONS: This innovative approach integrates diverse data sources, providing a holistic understanding of kidney failure, which is imperative for patient management and targeted therapeutic interventions.

Global burden and health inequality of nutritional deficiencies from 1990 to 2019.

Introduction: Nutritional deficiencies (NDs) manifest in various forms and are widespread globally. However, a systematic evaluation of the epidemiology of NDs across all causes and age groups in different countries and regions has not been conducted. Materials and methods: This study aimed to utilize data from the 2019 Global Burden of Disease (GBD) study to assess the burden and trends of NDs, including their incidence, prevalence, mortality, and disability-adjusted life years (DALYs). Additionally, the study evaluated health inequalities at global, regional, and national levels from 1990 to 2019. Result: In 2019, the age-standardized incidence rate of NDs was 2,207.71 per 100,000 individuals (95% UI 1,863.04-2,604.67), and the age-standardized DALYs (ASR-DALYs) was 680.12 per 100,000 individuals (95% UI 507.21-894.89). Among the causes of NDs, dietary iron deficiency had the highest ASR-DALYs and exhibited minimal variation. Children under the age of 5 years faced the greatest risk of NDs. Sex disparity was evident, with males having lower rates than females. Although the gap in the burden of NDs between regions classified as poor and wealthy decreased, disparities persist. Conclusion: These findings provide critical insights for the development of global health strategies aimed at mitigating NDs and may guide policymakers in implementing effective and economically viable interventions.

Syntheses, crystal structures of copper (II)-based complexes of sulfonamide derivatives and their anticancer effects through the synergistic effect of anti-angiogenesis, anti-inflammation, pro-apoptosis and cuproptosis.

Three novel copper(II)-based complexes Cu-1, Cu-2, and Cu-3 containing sulfamethoxazole or sulfamethazine ligand were obtained, and their single structures were characterized. Both Cu-1 and Cu-3 show a broad spectrum of cytotoxicity than Cu-2, and Cu-1 is more cytotoxic than Cu-3. What's interesting is that Cu-1 can exhibit obvious inhibitory effect on the growth of human triple-negative breast cancer in vivo and vitro through anti-proliferative, anti-angiogenic, anti-inflammatory, pro-apoptotic and cuproptotic synergistic effects. Though Cu-3 shows no significant cytotoxicity against MDA-MB-231 cells, it can significantly inhibit the growth of SKOV3 cells in vitro by down-regulating the expression of some key proteins in the VEGF/VEGFR2 signaling pathway and the expression of some pro-inflammatory cytokines, and by disrupting the balance of intracellular reactive oxygen species levels.

The association of ideal cardiovascular health and its change with subclinical atherosclerosis according to glucose status: A prospective cohort study.

BACKGROUND: An updated definition was developed to better evaluate cardiovascular health (CVH). We aimed to investigate whether optimal or improvement of six CVH metrics defined by new Life's Essential 8 (LE8) may counteract the risk of subclinical atherosclerosis among patients with hyperglycemia. METHODS: We conducted a prospective analysis of 5225 participants without prior cardiovascular diseases, of whom 4768 had complete data on CVH change. Subjects with CVH scores of 0-49, 50-79, and 80-100 points were categorized as having low, moderate, or high CVH, respectively. Subclinical atherosclerosis was evaluated by brachial-ankle pulse wave velocity, pulse pressure and albuminuria, both separately and in combination. RESULTS: Of the 5225 participants, 1937 (37.1%) had normal glucose regulation, while 3288 (62.9%) had hyperglycemia. The multivariable-adjusted odds ratio (OR) for composite subclinical atherosclerosis was 2.34 (95% confidence interval [CI], 1.88-2.91), 1.43 (95% CI, 1.21-1.70), and 0.74 (95% CI, 0.46-1.18), for participants with hyperglycemia who had low, moderate, or high overall CVH scores, respectively, compared with participants with normal glucose regulation. In addition, compared with those with stable CVH and normal glucose regulation, participants who exhibited greater improvements in overall CVH from 2010 to 2014 had a reduced risk of composite subclinical atherosclerosis with an OR of 0.72 (95% CI, 0.53-0.98) for those with normal glucose regulation, and 1.13 (95% CI, 0.87-1.48) for those with hyperglycemia. CONCLUSIONS: The novel defined CVH using six metrics was inversely associated with subsequent risk of subclinical atherosclerosis. Both the status of CVH and its changes modified the relationship between hyperglycemia and subclinical atherosclerosis.

Discovery of a novel benzimidazole conjugated quinazolinone derivative as a promising SARS-CoV-2 3CL protease inhibitor.

This report presents the design and synthesis of quinazolinone-based derivatives as promising SARS-CoV-2 3CL protease inhibitors. Two novel series, namely, febrifugine analogues 4a-i and quinazolinone conjugated benzimidazoles 9a-c, were successfully synthesized starting from isatoic anhydride. The synthesized quinazolinone derivatives were evaluated for their cytotoxicity against cancer cell lines and SARS-CoV-2 3CL inhibitory activity. The results showed that the synthesized compounds did not have significant toxicity for the non-cancer HEK293 cell line and MCF-7, MDA-MB-231, HEPG2 and HEPG2.2.15 cancer cell lines. Notably, compound 9b exhibited anti-3CL enzymatic activity in a dose-dependent manner, with the calculated IC50 value of 10.73 ± 1.17 µM. Docking results highlighted the interaction between 9b and 3CL protease through hydrogen bonding with key amino acids, including His41, Met49, Cys145, Met165, Arg188, His164, and Glu166, at the active site of the protease. Pharmacokinetic studies and ADME analyses provide valuable insights into the potential of compound 9b as a drug candidate. These findings support the new scaffold as a candidate for 3CLpro inhibition and advanced anti-coronavirus drug research.

Isolation, characterization, and application of a novel Pseudomonas fluorescens phage vB_PF_Y1-MI in contaminated milk.

The food industry has incurred substantial losses from contamination by Pseudomonas fluorescens, emphasizing the critical importance of implementing effective control strategies. Phages are potential sterilizers due to their specific killing abilities and the difficulty bacteria face in developing resistance. However, a significant barrier to their development is the lack of diversity among phage types. In this study, we characterized a novel lytic P. fluorescens phage, named vB_PF_Y1-MI. Phage vB_PF_Y1-MI displayed a latent period of nearly 10 min and a high burst size of 1493 PFU/cell. This phage showed good activity over a wide range of temperature (up to 70 °C) and pH (3-12). The genome of phage vB_PF_Y1-MI spans 93,233 bp with a GC content of 45%. It encompasses 174 open-reading frames and 19 tRNA genes, while no lysogeny or virulence-associated genes were detected. Phylogenetic analysis positions it as a novel unassigned evolutionary lineage within the Caudoviricetes class among related dsDNA phages. Our study provides foundational insights into vB_PF_Y1-MI and emphasizes its potential as an effective biological control agent against P. fluorescens. This research offers crucial theoretical groundwork and technical support for subsequent efforts in preventing and controlling P. fluorescens contamination.

Clustering-based risk stratification of prediabetes populations: Insights from the Taiwan and UK Biobanks.

AIMS/INTRODUCTION: This study aimed to identify low- and high-risk diabetes groups within prediabetes populations using data from the Taiwan Biobank (TWB) and UK Biobank (UKB) through a clustering-based Unsupervised Learning (UL) approach, to inform targeted type 2 diabetes (T2D) interventions. MATERIALS AND METHODS: Data from TWB and UKB, comprising clinical and genetic information, were analyzed. Prediabetes was defined by glucose thresholds, and incident T2D was identified through follow-up data. K-means clustering was performed on prediabetes participants using significant features determined through logistic regression and LASSO. Cluster stability was assessed using mean Jaccard similarity, silhouette score, and the elbow method. RESULTS: We identified two stable clusters representing high- and low-risk diabetes groups in both biobanks. The high-risk clusters showed higher diabetes incidence, with 15.7% in TWB and 13.0% in UKB, compared to 7.3% and 9.1% in the low-risk clusters, respectively. Notably, males were predominant in the high-risk groups, constituting 76.6% in TWB and 52.7% in UKB. In TWB, the high-risk group also exhibited significantly higher BMI, fasting glucose, and triglycerides, while UKB showed marginal significance in BMI and other metabolic indicators. Current smoking was significantly associated with increased diabetes risk in the TWB high-risk group (P < 0.001). Kaplan-Meier curves indicated significant differences in diabetes complication incidences between clusters. CONCLUSIONS: UL effectively identified risk-specific groups within prediabetes populations, with high-risk groups strongly associated male gender, higher BMI, smoking, and metabolic markers. Tailored preventive strategies, particularly for young males in Taiwan, are crucial to reducing T2D risk.

The hydroxycarboxylic acid receptor HCA2 is required for the protective effect of ketogenic diet in epilepsy.

One third of epilepsy patients are resistant to treatment with current anti-seizure medications. The ketogenic diet is used to treat some forms of refractory epilepsy, but the mechanism of its action has not yet been elucidated. In this study, we aimed to investigate whether the hydroxycarboxylic acid receptor 2 (HCA2), a known immunomodulatory receptor, plays a role in mediating the protective effect of this diet. We demonstrate for the first time that selective agonists at this receptor can directly reduce seizures in animal models. Agonists also reduce network activity in rodent and human brain slices. Ketogenic diet is known to increase circulating levels of endogenous HCA2 agonists, and we show that the effect of ketogenic diet in reducing seizures in the 6 Hz seizure model is negated in HCA2-deficient mice. Our data support the potential of HCA2 as a target for the treatment of epilepsy and potentially for neurodegenerative diseases.

Transcriptome-wide Mendelian randomization during CD4+ T cell activation reveals immune-related drug targets for cardiometabolic diseases.

Immunity has shown potentials in informing drug development for cardiometabolic diseases, such as type 2 diabetes (T2D) and coronary artery disease (CAD). Here, we performed a transcriptome-wide Mendelian randomization (MR) study to estimate the putative causal effects of 11,021 gene expression profiles during CD4+ T cells activation on the development of T2D and CAD. Robust MR and colocalization evidence was observed for 162 genes altering T2D risk and 80 genes altering CAD risk, with 12% and 16% respectively demonstrating CD4+ T cell specificity. We observed temporal causal patterns during T cell activation in 69 gene-T2D pairs and 34 gene-CAD pairs. These genes were eight times more likely to show robust genetic evidence. We further identified 25 genes that were targets for drugs under clinical investigation, including LIPA and GCK. This study provides evidence to support immune-to-metabolic disease connections, and prioritises immune-mediated drug targets for cardiometabolic diseases.

Corrigendum: Effectiveness, safety, and treatment pattern of sodium zirconium cyclosilicate in Chinese patients with hyperkalemia: interim analysis from a multicenter, prospective, real-world study (Actualize Study).

[This corrects the article DOI: 10.3389/fphar.2024.1398953.].

Relationship of SSVEP response between flash frequency conditions.

This study delves into the application of Brain-Computer Interfaces (BCIs), focusing on exploiting Steady-State Visual Evoked Potentials (SSVEPs) as communication tools for individuals facing mobility impairments. SSVEP-BCI systems can swiftly transmit substantial volumes of information, rendering them suitable for diverse applications. However, the efficacy of SSVEP responses can be influenced by variables such as the frequency and color of visual stimuli. Through experiments involving participants equipped with electrodes on the brain's visual cortex, visual stimuli were administered at 4, 17, 25, and 40Hz, using white, red, yellow, green, and blue light sources. The results reveal that white and green stimuli evoke higher SSVEP responses at lower frequencies, with color's impact diminishing at higher frequencies. At low light intensity (1W), white and green stimuli elicit significantly higher SSVEP responses, while at high intensity (3W), responses across colors tend to equalize. Notably, due to seizure risks, red and blue lights should be used cautiously, with white and green lights preferred for SSVEP-BCI systems. This underscores the critical consideration of color and frequency in the design of effective and safe SSVEP-BCI systems, necessitating further research to optimize designs for clinical applications.

Optimizing user experience in SSVEP-BCI systems.

The emergence of brain-computer interface (BCI) technology provides enormous potential for human medical and daily applications. Therefore, allowing users to tolerate the visual response of SSVEP for a long time has always been an important issue in the SSVEP-BCI system. We recruited three subjects and conducted visual experiments in groups using different frequencies (17 and 25Hz) and 60Hz light. After recording the physiological signal, use FFT to perform a time-frequency analysis on the physiological signal to check whether there is any difference in the signal-to-noise ratio and amplitude of the 60Hz light source compared with a single low-frequency signal source. The results show that combining a 60Hz light source with low-frequency LEDs can reduce participants' eye discomfort while achieving effective light stimulation control. At the same time, there was no significant difference in signal-to-noise ratio and amplitude between the groups. This also means that 60Hz can make vision more continuous and improve the subject's experience and comfort. At the same time, it does not affect the performance of the original SSVEP-induced response. This study highlights the importance of considering technical aspects and user comfort when designing SSVEP-BCI systems to increase the usability of SSVEP systems for long-term flash viewing.

Four-party evolutionary game analysis of enterprise environmental behavior.

With the implementation of the "Rural Revitalization Strategy" in China, it is common for enterprises to go to the countryside to develop business. However, enterprises often neglect the local environmental protection in rural areas while developing the economy to pursue profits. As the end of the national administrative system and the villagers' autonomous organization, the village committee needs to participate in monitoring enterprises' environmental behavior. With this in mind, this paper builds a game model of enterprises, grass-roots governments, farmers, and village committees and analyzes the impact of village committees, grass-roots governments, and farmers on enterprise environmental behavior. The conclusions are as follows: (i) it is difficult for the village committee to promote the positive environmental behavior of enterprises, which needs the supervision of the grass-roots government; (ii) Improving the coordination ability of village committees is conducive to reducing the burden of government supervision; (iii) Farmers' awareness of environmental protection can affect the environmental behavior of enterprises through the rights protection mechanism and reputation mechanism.

cNEK6 induces gemcitabine resistance by promoting glycolysis in pancreatic ductal adenocarcinoma via the SNRPA/PPA2c/mTORC1 axis.

Resistance to gemcitabine in pancreatic ductal adenocarcinoma (PDAC) leads to ineffective chemotherapy and, consequently, delayed treatment, thereby contributing to poor prognosis. Glycolysis is an important intrinsic reason for gemcitabine resistance as it competitively inhibits gemcitabine activity by promoting deoxycytidine triphosphate accumulation in PDAC. However, biomarkers are lacking to determine which patients can benefit significantly from glycolysis inhibition under the treatment of gemcitabine activity, and a comprehensive understanding of the molecular mechanisms that promote glycolysis in PDAC will contribute to the development of a strategy to sensitize gemcitabine chemotherapy. In this study, we aimed to identify a biomarker that can robustly indicate the intrinsic resistance of PDAC to gemcitabine and guide chemotherapy sensitization strategies. After establishing gemcitabine-resistant cell lines in our laboratory and collecting pancreatic cancer and adjacent normal tissues from gemcitabine-treated patients, we observed that circRNA hsa_circ_0008383 (namely cNEK6) was highly expressed in the peripheral blood and tumor tissues of patients and xenografts with gemcitabine-resistant PDAC. cNEK6 enhanced resistance to gemcitabine by promoting glycolysis in PDAC. Specifically, cNEK6 prevented K48 ubiquitination of small ribonucleoprotein peptide A from the BTRC, a ubiquitin E3 ligase; thus, the accumulated SNRPA stopped PP2Ac translation by binding to its G-quadruplexes in 5' UTR of mRNA. mTORC1 pathway was aberrantly phosphorylated and activated owing to the absence of PP2Ac. The expression level of cNEK6 in the peripheral blood and tumor tissues correlated significantly and positively with the activation of the mTORC1 pathway and degree of glycolysis. Hence, the therapeutic effect of gemcitabine is limited in patients with high cNEK6 levels, and in combination with the mTORC1 inhibitor, rapamycin, can enhance sensitivity to gemcitabine chemotherapy.

Performance and stability analysis of interacting multiple model estimator under unobservable packet loss.

For a system with packet loss, if the estimator cannot observe the packet-loss status (PLS), the system is called an unobservable-packet-loss (UPL) system. Otherwise, it is called an observable-packet-loss (OPL) system. This paper studies the interacting multiple model (IMM) estimator for UPL systems, and the main contributions are twofold. (i) Estimation accuracy of the unobservable PLS. For an unstable UPL system, we prove that the UPL system will become an OPL one with time, since the PLS can be exactly estimated with time. For a stable UPL system, there exists an accuracy threshold such that the estimation accuracy of the PLS cannot be better than this threshold. (ii) Stability of the IMM estimator. For an unstable UPL system, we establish a necessary and sufficient condition: there exists a threshold such that the IMM estimator is stable almost everywhere if and only if the packet-arrival rate is greater than this threshold. For a stable UPL system, we show that the IMM estimator is stable, no matter what value the packet-arrival rate is.

Evaluation of traditional Chinese medicine tea bag TBDESJS in patients with Sjögren's syndrome and dry eye syndrome: A phase II pilot study.

ETHNOPHARMACOLOGICAL RELEVANCE: Sjögren's syndrome (SJS) and dry eye syndrome (DES) are characterized by ocular dryness from inadequate tear production or excessive evaporation. To evaluate the effectiveness of TBDESJS (Chun-Yu-Ching-Hua-Yin, CYCHY), a TCM tea bag, in treating SJS and DES patients compared with healthy controls (NHC). MATERIALS AND METHODS: This phase II pilot study included 100 participants (60 SJS, 30 DES, 10 NHC) across 8 weeks, assessing changes in Schirmer's test, OSDI, ESSPRI, PSQI, FIRST, and artificial tear usage, using repeated measurement ANOVA and Tukey's honestly significant difference (HSD) for analysis. RESULTS: Total 97 subjects completed the trial, for the left eye (OS) of Schirmer's test, significant improvements at 4, and 8 weeks were observed in SJS (0.13 ± 0.43-5.77 ± 2.87, and 7.60 ± 4.84 mm) and DES (0.21 ± 0.41-6.21 ± 2.97, and 7.86 ± 3.47 mm) (all p < .001). For the right eye (OD), significant improvements were observed in SJS (0.13 ± 0.39-6.77 ± 4.53, and 8.79 ± 5.92 mm) and DES (0.34 ± 0.55-6.59 ± 2.50, and 8.24 ± 3.42 mm) (all p < .001). Secondary outcomes showed reduced the dryness of ESSPRI scores in SJS (6.37 ± 1.97-5.57 ± 1.79, p < .001) and DES (6.10 ± 1.97-5.28 ± 2.23, p < .05). PSQI global scores improved significantly in all groups at 8 weeks (p < .05). Artificial tear usage decreased in SJS (4.93 ± 2.45-1.00 ± 0.82 times/day), DES (4.47 ± 1.99-0.66 ± 0.67 times/day) (all p < .001). No serious adverse events in this study. CONCLUSION: TBDESJS significantly improved tear production, ocular dryness, and sleep quality, indicating potential neural regulation, anti-inflammatory and immunomodulatory benefits. These findings advocate for TBDESJS (Chun-Yu-Ching-Hua-Yin, CYCHY)'s comprehensive therapeutic value in SJS and DES treatment, emphasizing the need for further research to understand long-term effects and mechanisms.

Exploring critical quality indicators and developing a non-destructive detection method using near-infrared spectroscopy for sea bass (Lateolabrax japonicus) quality evaluation.

In this study, chemometrics were employed to explore the relationship between sensory evaluation and physicochemical indicators of sea bass (Lateolabrax japonicus). Through principal component analysis, cluster analysis, and Pearson correlation analysis, three pivotal indicators were identified: protein content, b* value, and condition factor. Leveraging the grey relational analysis, weights were assigned to these three core quality indicators, resulting in a comprehensive sea bass quality evaluation model: Y = 0.911 × protein (g/100 g) + 0.742 × b* + 0.747 × condition factor. Moreover, near-infrared spectroscopy combined with chemometrics were employed to evaluate the quality of sea bass. The different origins of sea bass were accurately distinguished using orthogonal partial least squares discriminant analysis. The partial least squares regression model was constructed for predicting the critical quality indicator, protein content, with R2P of 0.926. This study offers new insights for developing rapid, economical, and reliable methods for assessing aquatic product quality.

Site selection and effects of background towers on urban CO2 estimates: A case study from central downtown Zhengzhou in China.

With China's proposed carbon reduction goals, many carbon monitoring pilot city projects have been launched, involving greenhouse gas (GHG) inverse estimate analysis based on GHG observations. For the evaluation of emissions estimates in a targeted urban area, the contributions of extra-urban fluxes on urban GHG observations must be excluded, especially for core cities within urban agglomerations, which face more severe emission interference from adjacent cities. In this study, we quantified the impact of external emissions on urban carbon dioxide (CO2) mole fraction observations across different seasons in the central downtown area of Zhengzhou, a core city of the Central Plains Urban Agglomeration in China. Results showed that 60% of the CO2 enhancement from the 500-km square area including the city originated outside the core urban area in autumn and winter, predominantly originating from far-field sources (>50 km) in the northeast, west, and northwest of Zhengzhou. To design an optimal monitoring network that accurately accounts for CO2 mole fractions entering the urban domain of interest, three different selection methods (distance, meteorological trajectory, and multiple regression) were used to select background station locations, and the resulting background values were evaluated through the application of observing system simulation experiments, including synthetic flux inverse estimate. Results indicated that the background stations selected by meteorological trajectories more effectively captured CO2 variability, introducing the smallest errors to inverse estimate flux (-8%). This study provides a valuable reference for designing background monitoring stations in dense urban agglomerations, thereby improving the accuracy of high-resolution urban GHG emission inverse estimates.