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Abstract Background Microsatellites are increasingly realized to have biological significance in human genome and health in past decades, the assembled complete reference sequence of human genome T2T-CHM13 brought great help for a comprehensive study of short tandem repeats in the human genome. Results Microsatellites density landscapes of all 24 chromosomes were built here for the first complete reference sequence of human genome T2T-CHM13. These landscapes showed that short tandem repeats (STRs) are prone to aggregate characteristically to form a large number of STRs density peaks. We classified 8,823 High Microsatellites Density Peaks (HMDPs), 35,257 Middle Microsatellites Density Peaks (MMDPs) and 199, 649 Low Microsatellites Density Peaks (LMDPs) on the 24 chromosomes; and also classified the motif types of every microsatellites density peak. These STRs density aggregation peaks are mainly composing of a single motif, and AT is the most dominant motif, followed by AATGG and CCATT motifs. And 514 genomic regions were characterized by microsatellite density feature in the full T2T-CHM13 genome. Conclusions These landscape maps exhibited that microsatellites aggregate in many genomic positions to form a large number of microsatellite density peaks with composing of mainly single motif type in the complete reference genome, indicating that the local microsatellites density varies enormously along the every chromosome of T2T-CHM13.

Abstract Background Diabetic retinopathy (DR), the principal cause of acquired blindness among the working-age population, is the most frequent microvascular complication of diabetes. Although metabolic disorders are hypothesized to play a role in its pathogenesis, the underlying mechanism remains largely elusive. Methods To elucidate the mechanism, we initially compared metabolite profiles of vitreous fluid between 23 patients with DR and 12 non-diabetic controls using liquid chromatography/tandem mass spectrometry, identifying the distinct metabolite indoxyl sulfate (IS). Subsequently, streptozotocin (STZ)-induced diabetic and IS-injected rat models were established to examine the effects of IS on retinal microvasculature. RNA sequencing was conducted to identify potential regulatory mechanisms in IS-treated human retinal endothelial cells (HREC). Finally, target gene knockdown in HREC and treatment of IS-injected rats with inhibitors (targeting IS production or downstream regulators) were employed to elucidate the detailed mechanisms and identify therapeutic targets for DR. Results Metabolomics identified 172 significantly altered metabolites in the vitreous humor of diabetics, including the dysregulated tryptophan metabolite indoxyl sulfate (IS). IS was observed to breach the blood-retinal barrier and accumulate in the intraocular fluid of diabetic rats. Both in vivo and in vitro experiments indicated that elevated levels of IS induced endothelial apoptosis and disrupted cell junctions. RNA sequencing pinpointed prostaglandin E2 (PGE2) synthetase-cyclooxygenase 2 (COX-2) as a potential target of IS. Validation experiments demonstrated that IS enhanced COX-2 expression, which subsequently increased PGE2 secretion by promoting transcription factor EGR1 binding to COX-2 DNA following entry into cells via organic anion transporting polypeptides (OATP2B1). Furthermore, inhibition of COX-2 in vivo or silencing EGR1/OATP2B1 in HREC mitigated IS-induced microcapillary damage and the activation of COX-2/PGE2. Conclusion Our study demonstrated that indoxyl sulfate (IS), a uremic toxin originating from the gut microbiota product indole, increased significantly and contributed to retinal microvascular damage in diabetic retinopathy (DR). Mechanistically, IS impaired retinal microvascular integrity by inducing the expression of COX-2 and the production of PGE2. Consequently, targeting the gut microbiota or the PGE2 pathway may offer effective therapeutic strategies for the treatment of DR. Graphical Abstract

Abstract Recent studies have increasingly focused on the effect of relativistic motion on quantum coherence. Prior research predominantly examined the influence of relative motion on basis-dependent quantum coherence, underscoring its susceptibility to decoherence under accelerated conditions. Yet, the effect of relativistic motion on basis-independent quantum coherence, which is critical for understanding the intrinsic quantum features of a system, remains an interesting open question. This paper addresses this question by examining how total, collective, and localized coherence are affected by acceleration and coupling strength. Our analysis reveals that both total and collective coherence significantly decrease with increasing acceleration and coupling strength, ultimately vanishing at high levels of acceleration. This underscores the profound impact of Unruh thermal noise. Conversely, localized coherence exhibits relative stability, decreasing to zero only under the extreme condition of infinite acceleration. Moreover, we demonstrate that collective, localized, and basis-independent coherence collectively satisfy the triangle inequality. These findings are crucial for enhancing our understanding of quantum information dynamics in environments subjected to high acceleration and offer valuable insights on the behavior of quantum coherence under relativistic conditions.

Quantum secure direct communication (QSDC) can directly transmit secret messages through quantum channel without keys. Device-independent (DI) QSDC guarantees the message security relying only on the observation of the Bell-inequality violation, but not on any detailed description or trust of the devices’ inner workings. Compared with conventional QSDC, DI-QSDC has relatively low secret message capacity. To increase DI-QSDC’s secret messages capacity, we propose a high-capacity DI-QSDC protocol based on the hyper-encoding technique. The total message leakage rate of our DI-QSDC protocol only relies on the most robust degree of freedom. We provide the numerical simulation of its secret message capacity altered with the communication distance. Our work serves as an important step toward the further development of DI-QSDC systems.

The regulation of the cell cycle is essential for maintaining normal cellular function, especially in the development of diseases such as lung cancer. The cell cycle consists of four major phases (G1, S, G2 and M phases), which are characterized by a series of precise molecular events to ensure proper cell proliferation and division. In lung cancer cells, cell cycle dysregulation can lead to disordered proliferation and increased invasiveness of cancer cells. G2 and S-phase expressed 1 (GTSE1) is a regulatory protein found in the cytoplasm of the cell, which plays a key role in the cell cycle distribution of a wide range of cancer cells and is involved in life processes such as cell proliferation and apoptosis. GTSE1 affects cell cycle progression by interacting with cyclin-dependent kinase inhibitor 1A (p21) and maintaining the stability of p21, which in turn inhibits the activity of cyclin-dependent kinase 1/2 (CDK1/2). In addition, GTSE1 is also involved in the regulation of tumor protein 53 (p53) signaling pathway. With the assistance of mouse double minute 2 homolog (MDM2), GTSE1 is able to transport p53 from the nucleus to the cytoplasm and promote its ubiquitination and degradation, thus affecting cell cycle and cell death-related signaling pathways. This paper reviews the expression of GTSE1 in lung cancer cells and its effects on lung cancer, as well as its potential mechanisms involved in cell cycle regulation.

Abstract In the past two decades, the exploration of quantumness within Schwarzschild spacetime has garnered significant interest, particularly regarding the Hawking radiation’s impact on quantum correlations and quantum coherence. Building on this foundation, we investigate how Hawking radiation influences maximal steered coherence (MSC)-a crucial measure for gauging the ability to generate coherence through steering. We find that as the Hawking temperature increases, the physically accessible MSC degrade while the unaccessible MSC increase. This observation is attributed to a redistribution of the initial quantum correlations, previously acknowledged by inertial observers, across all bipartite modes. In particular, we find that in limit case that the Hawking temperature tends to infinity, the accessible MSC equals to $$1/\sqrt{2}$$ 1 / 2 of its initial value, and the unaccessible MSC between mode A and $$\overline{B}$$ B ¯ also equals to the same value. Our findings illuminate the intricate dynamics of quantum information in the vicinity of black holes, suggesting that Hawking radiation plays a pivotal role in reshaping the landscape of quantum coherence and entanglement in curved spacetime. This study not only advances our theoretical understanding of black hole thermodynamics but also opens new avenues for investigating the interface between quantum mechanics and general relativity.

Facial age recognition has been widely used in real-world applications. Most of current facial age recognition methods use deep learning to extract facial features to identify age. However, due to the high dimension features of faces, deep learning methods might extract a lot of redundant features, which is not beneficial for facial age recognition. To improve facial age recognition effectively, this paper proposed the deep manifold learning (DML), a combination of deep learning and manifold learning. In DML, deep learning was used to extract high-dimensional facial features, and manifold learning selected age-related features from these high-dimensional facial features for facial age recognition. Finally, we validated the DML on Multivariate Observations of Reactions and Physical Health (MORPH) and Face and Gesture Recognition Network (FG-NET) datasets. The results indicated that the mean absolute error (MAE) of MORPH is 1.60 and that of FG-NET is 2.48. Moreover, compared with the state of the art facial age recognition methods, the accuracy of DML has been greatly improved.

Abstract Objective Early identification of cognitive impairment in neurodegenerative diseases like Alzheimer's disease (AD) is crucial. Neurofilament, a potential biomarker for neurological disorders, has gained attention. Our study aims to investigate the relationship between serum neurofilament light (sNfL) levels and cognitive function in elderly individuals in the United States. Methods This cross‐sectional study analyzed data from participants aged 60 and above in the National Health and Nutrition Examination Survey (2013–2014). We collected sNfL levels, cognitive function tests, sociodemographic characteristics, comorbidities, and other variables. Weighted multiple linear regression models examined the relationship between ln(sNfL) and cognitive scores. Restricted cubic spline (RCS) visualization explored nonlinear relationships. The stratified analysis examined subgroups' ln(sNfL) and cognitive function association. Results The study included 446 participants (47.73% male). Participants with ln(sNfL) levels between 2.58 and 2.81 pg/mL (second quintile) performed relatively well in cognitive tests. After adjusting for multiple factors, ln(sNfL) levels were negatively correlated with cognitive function, with adjusted β (95% CI) as follows: immediate recall test (IRT): −0.763 (−1.301 to −0.224), delayed recall test (DRT): −0.308 (−0.576 to −0.04), animal fluency test (AFT): −1.616 (−2.639 to −0.594), and digit symbol substitution test (DSST): −2.790 (−4.369 to −1.21). RCS curves showed nonlinear relationships between ln(sNfL) and DRT, AFT, with inflection points around 2.7 pg/mL. The stratified analysis revealed a negative correlation between ln(sNfL) and cognition in specific subgroups with distinct features, with an interaction between diabetes and ln(sNfL). Interpretation Higher sNfL levels are associated with poorer cognitive function in the elderly population of the United States. sNfL shows promise as a potential biomarker for early identification of cognitive decline.

Crassulaceae plants are valued for their horticultural, ecological, and economic significance, but their genetic improvement is hindered by the absence of efficient and stable genetic transformation methods. Therefore, the development of a tailored genetic transformation method is crucial for enhancing the progress of the genetic improvement of Crassulaceae plants. The results indicate that, in the transformation experiments conducted on Kalanchoe tetraphylla, the K599 strain exhibited the highest transformation efficiency (76.67%), while C58C1 was least efficient (21.43%). An acetosyringone concentration of 100 μM was optimal for the hairy root transformation, and the immersion method yielded the highest efficiency. Additionally, the Silwet L-77 concentration significantly influenced the transformation efficiency, with 0.05% leading to a decrease. Upon four Crassulaceae species, notable differences were observed, with K. tetraphylla exhibiting the highest efficiency of 100%, and Sedum alfredii displaying the lowest efficiency of 5%. The RUBY reporter gene offers a more distinct advantage over GFP in observing the transformation effects. This study developed a simple, feasible, and cost-effective method for obtaining transgenic roots from leaves of Crassulaceae. The methodology provides technical support for the genetic improvement and gene function research of Crassulaceae plants.

In the context of high academic pressure and inadequate physical activity (PA) among adolescents, it is important to study how the physical environment and students’ perceptions affect their physical activity during school recess. An empirical study was conducted in four secondary schools in Xi’an to gather data on students’ physical activity using DJI Mini Drone recordings and self-reported questionnaires. Three physical activity indices—concentration, type richness and intensity—were visualized and quantified for intercomparison. This study found that physical environmental factors such as the building shape complexity and green space proportion significantly affected the PA concentration and intensity indices, whereas the campus area per student, the average distance to PA facilities and the number of PA facilities indicated a strong correlation with the PA richness index at the school level. Additionally, perceived environmental factors like space safety, facilities enjoyment and visual accessibility exerted influence on the PA intensity and frequency at the individual level. The study’s results confirmed previous findings from a social–ecological perspective and provide a comprehensive assessment framework that includes the spatial organization/spatial quality of the school and the perceived variables of safety, comfort, aesthetics, accessibility and functionality. By incorporating spatial, perceptual and behavioral aspects, this approach provides an efficient and integrated analytical methodology to promote adolescents’ health in school.

ObjectiveThe significance of interstitial cells of Cajal (ICC) in the gastrointestinal tract has garnered increasing attention. In recent years, approximately 80 articles on ICC have been published annually in various journals. However, no bibliometric study has specifically focused on the literature related to ICC. Therefore, we conducted a comprehensive bibliometric analysis of ICC to reveal dynamic scientific developments, assisting researchers in exploring hotspots and emerging trends while gaining a global perspective.MethodsWe conducted a literature search in the Web of Science Core Collection (WoSCC) from January 1, 2013, to December 31, 2023, to identify relevant literature on ICC. We employed bibliometric software, namely VOSviewer and CiteSpace, to analyze various aspects including annual publication output, collaborations, research hotspots, current status, and development trends in this domain.ResultsA total of 891 English papers were published in 359 journals by 928 institutions from 57 countries/regions. According to the keyword analysis of the literature, researchers mainly focused on “c-Kit,” “expression,” “smooth muscle,” and “nitric oxide” related to ICC over the past 11 years. However, with “SIP syncytium,” “ANO1,” “enteric neurons,” “gastrointestinal stromal tumors (GIST),” and “functional dyspepsia (FD),” there has been a growing interest in the relationship between ANO1, SIP syncytium, and ICC, as well as the role of ICC in the treatment of GIST and FD.ConclusionBibliometric analysis has revealed the current status of ICC research. The association between ANO1, SIP syncytium, enteric neurons and ICC, as well as the role of ICC in the treatment of GIST versus FD has become the focus of current research. However, further research and collaboration on a global scale are still needed. Our analysis is particularly valuable to researchers in gastroenterology, oncology, and cell biology, providing insights that can guide future research directions.

Ligusticum Chuanxiong, a perennial herb of considerable medicinal value commonly known as Chuanxiong, holds pivotal importance in sliced form for ensuring quality and regulating markets through geographical origin identification. This study introduces an integrated approach utilizing Near-Infrared Spectroscopy (NIRS) and Convolutional Neural Networks (CNNs) to establish an efficient method for rapidly determining the geographical origin of Chuanxiong slices. A dataset comprising 300 samples from 6 distinct origins was analyzed using a 1D-CNN model. In this study, we initially established a traditional classification model. By utilizing the Spectrum Outlier feature in TQ-Analyst 9 software to exclude outliers, we have enhanced the performance of the model. After evaluating various spectral preprocessing techniques, we selected Savitzky–Golay filtering combined with Multiplicative Scatter Correction (S-G + MSC) to process the raw spectral data. This approach significantly improved the predictive accuracy of the model. After 2000 iterations of training, the CNN model achieved a prediction accuracy of 92.22%, marking a 12.09% improvement over traditional methods. The application of the Class Activation Mapping algorithm not only visualized the feature extraction process but also enhanced the traditional model’s classification accuracy by an additional 7.41% when integrated with features extracted from the CNN model. This research provides a powerful tool for the quality control of Chuanxiong slices and presents a novel perspective on the quality inspection of other agricultural products.

Muscle fatigue represents the most prevalent symptom of long-term COVID, with elusive pathogenic mechanisms. We performed a longitudinal study to characterize histopathological and transcriptional changes in skeletal muscle in a hamster model of respiratory SARS-CoV-2 infection and compared them with influenza A virus (IAV) and mock infections. Histopathological and bulk RNA sequencing analyses of leg muscles derived from infected animals at days 3, 30, and 60 post-infection showed no direct viral invasion but myofiber atrophy in the SARS-CoV-2 group, which was accompanied by persistent downregulation of the genes related to myofibers, ribosomal proteins, fatty acid β-oxidation, tricarboxylic acid cycle, and mitochondrial oxidative phosphorylation complexes. While both SARS-CoV-2 and IAV infections induced acute and transient type I and II interferon responses in muscle, only the SARS-CoV-2 infection upregulated TNF-α/NF-κB but not IL-6 signaling in muscle. Treatment of C2C12 myotubes, a skeletal muscle cell line, with combined IFN-γ and TNF-α but not with IFN-γ or TNF-α alone markedly impaired mitochondrial function. We conclude that a respiratory SARS-CoV-2 infection can cause myofiber atrophy and persistent energy metabolism suppression without direct viral invasion. The effects may be induced by the combined systemic interferon and TNF-α responses at the acute phase and may contribute to post-COVID-19 persistent muscle fatigue.

We study an excitation hopping on a one-dimensional (1D) dimer chain of coupled resonators with the alternate on-site photon energies, which interacts with a two-level emitter (TLE) by a coupling point or two adjacent coupling points. In the single-excitation subspace, this system not only possesses two energy bands with propagating states, but also possesses photonic bound states. The number of bound states depends on the coupling forms between the TLE and the dimer chain. It is found that when the TLE is locally coupled to one resonator of the dimer chain, the bound-state that has mirror reflection symmetry. When the TLE is nonlocally coupled to two adjacent resonators, three bound states with preferred direction arise due to the mirror symmetry breaking. By using chirality to measure the asymmetry, it is found that the chirality of these bound states can be tuned by changing the energy differences of single photon in the adjacent resonators, the coupling strengths and the transition energy of the TLE.

Abstract With the enrichment of large-scale group decision-making (LSGDM) methods, the decentralized consensus reaching process (CRP) has demonstrated many advantages. However, when the probabilistic linguistic preference relation (PLPR) is utilized in the decentralized CRP, its consistency and readability are hardly to maintain. Besides, the low-cost consensus adjustment and non-cooperative behaviors of subgroups are still not considered simultaneously in the decentralized CRP. In order to solve these problems, this article proposes a decentralized feedback-based consensus model to support CRP in LSGDM based on PLPR with complete readability. First, to maintain the consistency of PLPR throughout the LSGDM process, an additive expected consistency for PLPR is specifically defined. This definition enables the automatic consistency maintenance of PLPR during linear-weight-based clustering, opinion adjustment, and opinion aggregation. Given that the existing consistency adjustment method always destroys the readability of the original PLPR, a definition of complete readability for PLPR, reflected by a reasonable probability distribution of its elements, is proposed. This is followed by a consistency-improving optimization model that considers both the adjustment cost and complete readability. Subsequently, in order to support a more realistic CRP, a decentralized feedback-based minimum cost consensus model is established to improve the group consensus level while addressing the non-cooperative behaviors of subgroups. Furthermore, an illustrative example of the selection of expressway repair plans is presented to testify the practicality of the proposed methods and demonstrate the distinctive characteristics in comparison with the existing approaches.

Temperature stability is a critical factor affecting the performance of the most subsystems in the lithography system, due to the high precision and sensitivity of system components to temperature variations. The temperature control system of the lithography machine is characterized by its large inertial constant, time delay characteristics, as well as susceptibility to multiple disturbances. The temperature control system of the lithography machine chiefly requires response speed, high accuracy, and stable and constant temperature control. The contribution of this study is not only avoiding complex precision modeling processes based on real-time parameter estimation and neural network self-tuning but also improving the performance of temperature control in real time under external disturbances. A novel adaptive algorithm with a cascade structure based on generalized predictive control (GPC) and backpropagation (BP) neural network proportional-integral (PI) control is successfully proposed for high accuracy temperature control of lithography machine with a large inertial constant, time delay, and multiple disturbances. In this study, firstly, the liquid circulating temperature control system is developed based on heat exchanger and heater. Secondly, an adaptive controller composed of GPC and BP neural network PI control is successfully proposed. A BP neural network is employed to enable the parameters of the PI controller to adjust in real time, and the mathematical model parameters of the control system are identified in real time by the least square method. Also, the performance of the proposed controller is evaluated comparing with conventional PI controller and GPC controller in terms of robustness and quantitative study of error analysis. Finally, the temperature stability and robustness of the temperature control system controlled with the proposed adaptive GPC-PI algorithm has been investigated by the simulation results carried out in different working scenarios. The simulation results show that the steady-state error from the proposed algorithm is less than 0.01°C under the action of disturbance input. It can effectively counteract the influence of environmental interference and time-varying system parameters. The results of the simulation experiment indicate that the proposed adaptive GPC and PI control algorithm exhibits significant advantages in terms of control accuracy, anti-interference ability, and robustness compared to the conventional control method. [ABSTRACT FROM AUTHOR]

Among 495 patients who were immunocompromised and tested positive for SARS-CoV-2, polymerase chain reaction cycle thresholds remained <33 beyond 20 days more frequently in patients with hematologic malignancies, particularly those receiving B-cell–depleting or Bruton tyrosine kinase inhibitor therapy, as compared with those with solid organ malignancy (26% vs 5%). [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence suggests that the gut microbiota and metabolites can modulate tumor responses to immunotherapy; however, limited data has been reported on biliary tract cancer (BTC). This study used metagenomics and metabolomics to identify characteristics of the gut microbiome and metabolites in immunotherapy-treated BTC and their potential as prognostic and predictive biomarkers. Methods: This prospective cohort study enrolled 88 patients with BTC who received PD-1/PD-L1 inhibitors from November 2018 to May 2022. The microbiota and metabolites significantly enriched in different immunotherapy response groups were identified through metagenomics and LC-MS/MS. Associations between microbiota and metabolites, microbiota and clinical factors, and metabolites and clinical factors were explored. Results: Significantly different bacteria and their metabolites were both identified in the durable clinical benefit (DCB) and non-durable clinical benefit (NDB) groups. Of these, 20 bacteria and two metabolites were significantly associated with survival. Alistipes were positively correlated with survival, while Bacilli, Lactobacillales, and Pyrrolidine were negatively correlated with survival. Predictive models based on six bacteria, four metabolites, and the combination of three bacteria and two metabolites could all discriminated between patients in the DCB and NDB groups with high accuracy. Beta diversity between two groups was significantly different, and the composition varied with differences in the use of immunotherapy. Conclusions: Patients with BTC receiving immunotherapy have specific alterations in the interactions between microbiota and metabolites. These findings suggest that gut microbiota and metabolites are potential prognostic and predictive biomarkers for clinical outcomes of anti-PD-1/PD-L1-treated BTC. [ABSTRACT FROM AUTHOR]

Coronary artery disease (CAD) poses a significant health risk to the global population and behavioural change theory intervention on lifestyle and physical activities are needed to improve patient's quality of life. Our main objective is to examine the application of behaviour change intervention program on the on the lifestyle and quality of life of patients after coronary intervention. The randomised controlled trial was carried at Fuawi Hospital consisting of 156 participants divided into control and intervention groups. The primary outcomes showed significant changes and increase in levels of physical activity between intervention and controls with the intervention group showing higher frequency, duration and intensity in both moderate physical activity and walking. Secondary outcomes showed significant reductions in the blood pressure, BMI, and improved healthcare-related quality of life. Alsos, significant lifestyle changes were observed with cessation of smoking, increased intake of healthy diets, stress and sleep management. Thus, the behavioural intervention change program was significant in improving the outcomes of CAD patients through increased levels of physical activity, increased quality of life and lifestyle changes. [ABSTRACT FROM AUTHOR]

Bacteria are the causative agents of various infectious diseases; however, the anti‐tumor effect of some bacterial species has attracted the attention of many scientists. The human oral cavity is inhabited by abundant and diverse bacterial communities and some of these bacterial communities could play a role in tumor suppression. Therefore, it is crucial to find oral bacterial species that show anti‐tumor activity on oral cancers. In the present study, we found that a high abundance of Porphyromonas gingivalis, an anaerobic periodontal pathogen, in the tumor microenvironment (TME) was positively associated with the longer survival of patients with oral squamous cell carcinoma (OSCC). An in vitro assay confirmed that P. gingivalis accelerated the death of OSCC cells by inducing cell cycle arrest at the G2/M phase, thus exerting its anti‐tumor effect. We also found that P. gingivalis significantly decreased tumor growth in a 4‐nitroquinoline‐1‐oxide‐induced in situ OSCC mouse model. The transcriptomics data demonstrated that P. gingivalis suppressed the biosynthesis of mucin O‐glycan and other O‐glycans, as well as the expression of chemokines. Validation experiments further confirmed the downregulation of mucin‐1 (MUC1) and C‐X‐C motif chemokine 17 (CXCL17) expression by P. gingivalis treatment. Flow cytometry analysis showed that P. gingivalis successfully reversed the immunosuppressive TME, thereby suppressing OSCC growth. In summary, the findings of the present study indicated that the rational use of P. gingivalis could serve as a promising therapeutic strategy for OSCC. [ABSTRACT FROM AUTHOR]

The aim of this study was to systematically evaluate the protective effect of kaempferol (KPF) against renal injury in diabetic rats, and to explore the mechanism of KPF via the NLRP3/ caspase-1 signaling pathway. A diabetic rat model was established by high-fat diet combined with STZ induction, and the urinary levels of urinary creatinine, urinary protein and urea nitrogen were detected. HE and Masson staining were used to assess pathological changes. Western blot was used to detect the expression of NLRP3, cleaved caspase--1, GSDMD, GSDMD-N, and RT-qPCR was used to detect the mRNA expression levels of NLRP3, caspase-1, and GSDMD. KPF significantly improved renal function, attenuated pathological changes, and reduced the levels of NLRP3, cleaved caspase-1, GSDMD and GSDMD-N protein and mRNA expressions in diabetic nephropathy (DN) rats. KPF has a protective effect against kidney injury in diabetic rats, and its mechanism may be related to the inhibition of the NLRP3/ caspase-1 signaling pathway. [ABSTRACT FROM AUTHOR]

Ending the HIV/AIDS pandemic is among the sustainable development goals for the next decade. To overcome the problem caused by the imbalances between the need for care and the limited resources, we shall improve our understanding of the local HIV epidemics, especially for key populations at high risk of HIV infection. However, HIV prevalence rates for key populations have been difficult to estimate because their HIV surveillance data are very scarce. This paper develops a multivariate spatial model for predicting unknown HIV prevalence rates among key populations. The proposed multivariate conditional auto-regressive model efficiently pools information from neighbouring locations and correlated populations. As the real data analysis illustrates, it provides more accurate predictions than independently fitting the sub-epidemic for each key population. Furthermore, we investigate how different pieces of surveillance data contribute to the prediction and offer practical suggestions for epidemic data collection. [ABSTRACT FROM AUTHOR]

Objectives: Our study elucidates the prognostic role of cluster of differentiation (CD) 24 expression in oral squamous cell carcinoma (OSCC) and determines whether targeting CD24 enhances the anti‐tumor immune response by inhibiting tumor‐associated macrophages (TAMs). Materials and Methods: The expression of CD24 and CD68 was analyzed immunohistochemically via tissue microarrays constructed using 56 cohorts of patients with OSCC and 20 control specimens. Further, CD24 was inhibited in an allograft squamous cell carcinoma (SCC) related mouse model with CD24mAb to determine the tumor volume and weight. Changes in immune cells such as TAMs and T cells in the tumor microenvironment (TME) were analyzed by Flow cytometry. The expression of CD4, CD8, and Ki67 was analyzed via immunohistochemistry. The inhibition of CD24 was confirmed by Western blot and immunohistochemistry. Results: CD24 was overexpressed in OSCC. High expression of CD24 indicated poor survival in patients with OSCC (p = 0.0334). CD24 expression was significantly correlated with CD68 (p = 0.0424). The inhibition of CD24 delayed tumor growth in vivo. A decrease in TAMs number and an increase in T cell number were confirmed, while the ability of tumor proliferation was impaired. Conclusion: Targeting CD24 could enhance anti‐tumor immune response by inhibiting TAMs. [ABSTRACT FROM AUTHOR]

Inhibition of P2X7 receptor overexpression is essential in cardiovascular diseases (CVDs). Flavonoids can reduce the mortality of CVDs through anti-inflammatory effects, and P2X7 receptor activation can lead to inflammation. Therefore, studying the effect of flavonoids on P2X7 will help develop safe and effective target drugs for the prevention and treatment of CVDs. The aim of this article was to review the literature regarding flavonoids and their various actions on P2X7. Molecular docking showed that the VINA scores of naringin, genistin, and baicalin were lower or equal to the specific inhibitor A804598, which will help in the development of novel therapeutic agents for CVDs. [ABSTRACT FROM AUTHOR]

To explore the effect of long non-coding RNA cancer susceptibility 19 (lncRNA CASC19) on the activity, apoptosis, and oxidative stress response of cardiomyocytes, so as to assess the clinical relevance and molecular mechanism of CASC19 in myocardial infarction (MI). CASC19 level was determined by using real-time quantitative polymerase chain reaction (RT-qPCR). MI model was constructed using hypoxia induction, and rat cardiomyocytes H9c2 were divided into control group, MI group, MI small interference negative control (MI-si-NC) group, MI-si-CASC19 group, MI-si-CASC19+microRNA-NC (miR-NC) group, and MI-si-CASC19+miR-218-5p inhibitor group. Tetramethylazolium salt colorimetric method and flow cytometry were used to evaluate cell activity and apoptotic capacity. Cellular oxidative stress was evaluated using malondialdehyde and superoxide dismutase kits. The relationship between CASC19 and miR-218-5p was confirmed by using dual-luciferase activity assay. CASC19 levels were enhanced in MI patients and hypoxia-induced cardiomyocytes. Downregulating CASC19 promoted the proliferation, while suppressed apoptosis and oxidative stress in the MI cell model. Moreover, low expression of miR-218-5p reversed the promotion of proliferation and inhibition of apoptosis and oxidative stress in MI cell models by silencing CASC19. Briefly, CASC19 may serve as a diagnostic marker for MI by sponging miR-218-5p to inhibit apoptosis and oxidative stress in cardiomyocytes and promote cell survival. [ABSTRACT FROM AUTHOR]

Background and Purpose Methods Results Conclusion The absence of a consensus data quality control (DQC) process inhibits the widespread adoption of MR spectroscopy. Poor DQC can lead to unreliable clinical diagnosis and irreproducible research conclusions. Currently, manual visual assessment or the standard quantitative metrics of signal‐to‐noise, linewidth, and model fit are used as classifiers, but these measures may not be sufficient. To supplement standard metrics, this paper proposes a novel automated DQC pipeline named Visual Evaluative Control Technology Of Resonance Spectroscopy (VECTORS).Manual DQC ratings were conducted on 7180 spectra obtained from 110 young adults using short‐echo chemical shift imaging at 3 Tesla. Four reviewers conducted manual ratings on the presence of artifacts and location of metabolites. The ratings were labor intensive, taking over 180 hours. VECTORS was developed to quantify their DQC criteria, detecting artifacts that present as duplicate peaks, vertical shifts, and glutamine + glutamate and myoinositol peak shapes. Run on the same data using a standard laptop, VECTORS only took 2 hours.The manual ratings were not monotonic to the standard quantitative metrics. VECTORS correctly flagged spectra that the manual ratings missed. VECTORS accurately flagged an additional 126 poor DQ spectra that consensus cutoffs of the standard quantitative metrics deemed good DQ.Standard quantitative metrics may not account for all DQC artifacts as they are not monotonic to the manual ratings. However, manual ratings are labor intensive, subjective, and irreproducible. VECTORS addresses these issues and should be used in conjunction with standard quantitative metrics. [ABSTRACT FROM AUTHOR]

Abstract Background and aim China has used traditional Chinese medicine (TCM) to treat diseases for more than 2000 years. Traditionally, TCMs in medicine cabinets are arranged alphabetically or on the basis of experience, but this arrangement greatly affects dispensing efficiency. However, owing to the unique properties and qualities of TCM, very few automatic approaches or systems have specifically addressed TCM dispensing problems. Therefore, it is necessary to establish a method of optimizing the traditional Chinese medicine placement scheme (TCMPS) via computer algorithms to improve the work efficiency of pharmacists. Methods A prescription dataset from a hospital in 2022 was obtained, and the association rule algorithm (ARA) was used to calculate the frequency of use for each type of TCM and the associations between different types of TCMs. On the basis of these association and frequency data, the optimal TCMPS was calculated using the simulated annealing algorithm (SAA) and then verified using the prescription dataset from 2023. Results A total of 10,601 prescriptions were collected in 2022, involving 360 different TCMs, and each prescription contained an average of 9.485 TCMs, with Danggui (3628) being the most frequently used. When the threshold of support was set to 0.05 and the confidence was set to 0.8, 78 couplet medicines used in orthopedics clinics were found through ARA. When the threshold value of support was set to 0, the confidence was set to 0, and the rule length was 2, a total of 129,240 rules were obtained, indicating support between all pairwise TCMs. The TCMPS, calculated using SAA, had a correlation sum of 14.183 and a distance sum of 3.292. The TCMPS was verified using a prescription dataset from 2023 and theoretically improved the dispensing efficiency of pharmacists by approximately 50%. Conclusions In this study, the ARA and SAA were successfully applied to pharmacies for the first time, and the optimal TCMPS was calculated. This approach not only significantly improves the dispensing efficiency of pharmacists and reduces patient waiting time but also enhances the quality of medical services and patient satisfaction, and provides a valuable reference for the development of smart medicine.

Cell culture experiments can support characterization of enzymatic activities in healthy and tumorous human tissues. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) enables simultaneous measurement of several steroids from a single sample, facilitating analysis of molecular pathways involved in steroid biosynthesis. We developed a reliable but fast method for quantification of cortisol, cortisone and aldosterone in cell culture supernatant. Validation, including investigation of matrix-matched calibration, was performed for two different cell types. Utility of the method was demonstrated in the study of 11β-hydroxysteroid dehydrogenase type 2 (HSD11B2) activity under conditions of glucocorticoid and mineralocorticoid excess in different cell types. Aldosterone, cortisol and cortisone were extracted by liquid-liquid extraction (LLE) with methyl tert-butyl ether from 1 mL of cell culture supernatant. Steroids were separated on a Kinetex biphenyl column (50 ×2.1 mm, 2.6 µm) with gradient elution of water and methanol containing 2 mM ammonium format and analysed in multiple reaction monitoring mode after positive electrospray ionization. Application of the method included cell culture experiments with two different primary cell types, human coronary artery smooth muscle cells (HCSMC) and human coronary artery endothelial cells (EC). Cells were treated with different concentrations of cortisol, aldosterone and mifepristone, a glucocorticoid receptor antagonist and quantitative PCR was performed. The method exhibits high precision (CV ≤ 6 %) and accuracy (deviation from nominal concentration ≤ 6 %) for concentrations above the limit of quantification (LoQ) which is 0.11, 0.56 and 0.69 nmol/L for aldosterone, cortisone and cortisol, respectively. Calibration curves did not differ when prepared in media or solvent. The method enabled us to confirm activity of HSD11B2 and concentration dependent conversion of cortisol to cortisone in HCSMC (median conversion ratio at 140 nM cortisol = 1.46 %). In contrast we did not observe any HSD11B2 activity in EC. Neither addition of high aldosterone, nor addition of 1 µM mifepristone had impact on glucocorticoid concentrations. Quantitative PCR revealed expression of HSD11B1 and HSD11B2 in HCSMC but not in EC. We present a fast and reliable method for quantification of cortisol, cortisone and aldosterone in cell culture supernatants. The method enabled us to study HSD11B2 activity in two different cell types and will support future experiments investigating mechanisms of target organ damage in conditions of glucocorticoid and mineralocorticoid excess., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests. Martin Bidlingmaier reports financial support was provided by German Research Foundation. Holger Schneider reports financial support was provided by German Research Foundation. Martin Reincke reports financial support was provided by German Research Foundation. Marily Theodoropoulou reports financial support was provided by German Research Foundation. Martin Reincke reports financial support was provided by European Research Council. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Sepsis is a common critical illness characterized by high mortality rates and a significant disease burden. In the context of sepsis-induced organ dysfunction, the lungs are among the initial organs affected, which may progress to acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Recent studies have highlighted the crucial roles of mitophagy and ferroptosis in the development and progression of sepsis-induced ALI/ARDS. Identifying key convergence points in these processes may provide valuable insights for the treatment of this condition. In recent years, certain herbs and their bioactive compounds have demonstrated unique benefits in managing sepsis-induced ALI/ARDS by modulating mitophagy or ferroptosis. This review summary the mechanisms of mitophagy and ferroptosis, explores their interactions, and emphasizes their regulatory roles in the progression of sepsis-induced ALI/ARDS. Additionally, it offers a novel perspective on treatment strategies by summarizing various herbs and their bioactive compounds relevant to this condition., Competing Interests: The authors declare no conflicts of interest in this work., (© 2024 Cheng et al.)