Pulmonary fibrosis (PF) is an intractable chronic interstitial lung disease with limited effective therapeutic options. Accumulating evidence suggests that astilbin (AST), a natural flavonoid isolated from traditional Chinese herbs, possesses anti-inflammatory and anti-fibrotic properties. However, its therapeutic potential and underlying mechanisms in PF remain incompletely understood. In this study, a bleomycin (BLM)-induced mouse model was established to evaluate the in vivo anti-fibrotic efficacy of AST. HE staining and Masson's Trichrome staining were employed to assess the severity of PF. Western blot, RT-qPCR, ELISA, and immunofluorescence assays were used to investigate the mechanism of AST. Molecular docking, molecular dynamics simulations, and microscale thermophoresis (MST) were performed to evaluate whether TGS1 may serve as a direct binding target of AST. Finally, trimethylguanosine synthase 1 (TGS1) knockdown was performed to validate whether AST exerts its anti-fibrotic effects in a TGS1-dependent manner. The results supported a direct interaction between AST and TGS1, increased telomerase-related components, and alleviated the DNA damage response (DDR). These changes were associated with suppression of the STING-IRF3-NF-κB cascade, leading to reduced release of senescence-associated secretory phenotype (SASP) factors. This further inhibited the TGF-β1/SMAD pathway and reduced the expression of fibrotic markers in lung tissues. Collectively, these findings indicate that AST exerts anti-fibrotic effects, at least in part, through interaction with TGS1, thereby providing a basis for the development of AST-based anti-fibrotic drugs.
Raoultella ornithinolytica is an emerging Gram-negative pathogen implicated in nosocomial infections. However, it remains understudied, especially in low-resource regions, including East Africa. Here, we sought to unravel genomic virulence and antimicrobial resistance (AMR) profiles of a strain (RSM7096), isolated from a Ugandan patient with sepsis and diabetes mellitus. We combined antimicrobial susceptibility testing (AST) based on CLSI M100, 2022, with minimum inhibitory concentration (MIC) to determine its susceptibility/resistance to 16 antibiotics. Then we sequenced its genome (Illumina NovaSeq 6000) and performed multiple bioinformatic analyses to establish its clinical relevance. The BD Phoenix™ system classified the isolate as ESBL phenotype (code 1505), consistent with the presence of blaCTX-M-15, blaTEM-1B and blaOXA-1. The isolate was susceptible to imipenem, gentamicin, tigecycline, levofloxacin, and colistin but resistant to 11 antibiotics, including ceftriaxone and piperacillin/tazobactam used for treatment. Using PathogenFinder, the strain was predicted as a human pathogen (97.63% confidence). Virulence profiling revealed siderophore gene clusters for yersiniabactin and enterobactin, as well as capsular (type KL115) and O-antigen (OL2α.3; serotype O2αγ) loci, suggesting potential immune evasion capacity based on genomic predictions. Further, our detailed genomic analysis enabled us to reconstruct a megaplasmid (pRSM7096p5), which harbored 10 AMR genes, including blaCTX-M-15, blaTEM-1B, and blaOXA-1, responsible for the ESBL phenotype. The megaplasmid also harbors multiple mobile genetic elements, including the transposon Tn3 and insertion sequence ISec9 (ISec9), which are associated with high rates of interspecies horizontal antimicrobial resistance gene transfer. Our results demonstrate that Raoultella ornithinolytica poses a significant health risk, especially to patients with comorbidities. We advocated for rigorous surveillance to monitor and mitigate its impact, particularly in low-resource healthcare settings.
Antimicrobial resistance (AMR) is a major threat to human health worldwide. The rapid detection of AMR and antibiotic susceptibility facilitates diagnostic and therapeutic processes. Over the past few years, several novel methodologies, including the use of fluorescence and colorimetric sensors, have been developed as promising strategies for rapid antimicrobial susceptibility testing (AST). However, these methods may result in false signals owing to uncontrollable factors. Therefore, fusing dual-mode features is necessary to improve diagnostic accuracy. This study developed a precise AST method by coupling catalase-expressing pathogens with a dual-modality integrated fluorescence/colorimetric biosensor. A bovine serum albumin-modified gold nanoclusters (BSA-AuNCs) bifunctional integrated sensor was explored for AST based on the bacterial catalase activity after exposure to antibiotics, which resulted in a different response to H2O2. Using this integrated dual-modality biosensor platform, the study successfully determined the antibiotic susceptibilities of Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus with values of area under the curve (AUC) from 0.9881 to 1. The dual-signal readout mode improves the accuracy and reliability of AST, which can be used to guide antibiotic prescriptions in clinical decision-making.
Astaxanthin (AST), a potent natural antioxidant, has demonstrated promising therapeutic potential in mitigating inflammation. However, the precise anti-inflammatory mechanisms of AST, particularly in whole-organism contexts, remain incompletely understood. Given the zebrafish (Danio rerio)'s remarkable genomic, physiological, and immunological similarities to humans, it offers a uniquely advantageous vertebrate model for biomedical research. Therefore, in this study, we utilized adult zebrafish to investigate AST's capacity to attenuate microcystin-LR (MC-LR)-induced inflammatory toxicity and attempted to elucidate underlying mechanistic pathways. AST administration significantly alleviated intestinal inflammation, as evidenced by preservation of normal intestinal morphology, reduced intestinal permeability, and modulation of gene expression profiles linked to inflammation and intestinal homeostasis. Transcriptome sequencing coupled with bioinformatics analysis revealed that AST primarily suppressed inflammatory responses through regulation of peroxisome proliferator-activated receptor (PPAR) signaling axis. Notably, AST did not merely inhibit pro-inflammatory pathways but also enhanced the expression of genes critical for maintaining intestinal barrier integrity and metabolic homeostasis. Furthermore, the 16S rRNA gene amplicon sequencing of zebrafish microbiota revealed that AST treatment restructured the gut microbial community in the MC-LR-exposed fish. Specifically, AST promoted the expansion of beneficial flora, including Lactobacillus rhamnosus GG (LGG), which correlated with improved inflammatory outcomes. Collectively, these findings establish AST as an effective modulator of MC-LR-induced intestinal inflammation in zebrafish, acting via dual mechanisms: PPAR-mediated transcriptional regulation and optimization of the gut microbiome. These insights provide a robust preclinical rationale for exploring AST-based therapies in inflammatory disorders.
Patients with Zenker's diverticulum (ZD) often suffer from oropharyngeal dysphagia that can go undiagnosed for years. Diagnosis of ZD typically requires specialized centers and videofluoroscopy. Our study aims to create a noninvasive, accessible, sound-based screening tool for healthcare professionals to reduce diagnostic barriers and enable earlier detection of ZD. We developed a two-stage deep learning model to detect ZD using cervical auscultation sounds. The first stage identifies swallowing sounds (idle vs. swallow), and the second classifies detected swallows as healthy or pathological (Healthy vs. ZD). We used transfer learning with a pre-trained audio spectrogram transformer (AST) backbone and fine-tuned it for our task. A fivefold cross-validation protocol was applied to evaluate the model's performance. For data collection, we built a portable cervical auscultation device to gather recordings from 23 ZD patients and 27 healthy volunteers. The proposed method achieved a patient-level ZD diagnosis accuracy of 88.7 ± 7.7 % and an F1-score of 87.6 ± 8.3 % . We report the intermediate results for the individual stage on a snippet level and perform an ablation study to justify our design decisions and benchmark our approach. This study demonstrates, to our knowledge, the first deep learning-based cervical auscultation approach for identifying ZD. The results indicate that auscultation-driven AST-based models can provide clinically meaningful sensitivity and may help to lower diagnostic barriers, enable earlier referral, and ultimately reduce healthcare costs in dysphagia care.
Helicobacter pylori resistance to antibiotics commonly used in eradication regimens is increasing dramatically in many locations; new strategies are needed to manage this infectious disease. This study's aim was to collect and update information on antibiotic resistance (AR) rates in H. pylori as well as current strategies for H. pylori management, including public health issues, from a global perspective. An international survey was conducted in 31 countries on 6 continents to address key issues concerning the management of H. pylori-related AR. Individual aspects included the prevalence of AR for specific antibiotics, antibiotic susceptibility testing (AST) in different healthcare systems, availability of drugs, reimbursement issues and strategies for H. pylori AR surveillance. Resistance to the most effective antibiotics used in H. pylori eradication regimens is increasing globally, with clarithromycin and levofloxacin resistance exceeding 15% in 24/31 and 18/31 countries, respectively. Amoxicillin remains an exception, with resistance rates under 2% in 14/31 countries; though African countries have reported amoxicillin resistance rates of over 90%. Bismuth-based treatment regimens are the most effective and are recommended as first-line treatment in several countries. However, more than 1 billion inhabitants worldwide have no access to bismuth-based regimens. PCR-based tests for AR are used in 16/26 countries but are reimbursed in only 4, while next generation sequencing-based tests are available, but not reimbursed, in 3 countries. In 22/26 countries only culture-based methods are available (reimbursed in 9/26 countries). AR surveillance programmes have only been established in 4/26 countries. Therefore, in most countries, empirical therapy with the most effective local regimen available locally is practiced. The dramatic global rise in H. pylori antibiotic resistance requires an urgent revision of current management strategies. Possible solutions include AST-based selection of effective treatment regimens, identification of novel combinations of existing drugs and exploration of novel drugs.
With the development of AI technology, the number of cyber security threats that exploit it is increasing rapidly, and it is urgent to build an effective security threat detection system to respond to these threats. There is active research on AI-based security tools to detect and respond to these security threats. This study explores how heterogeneous data, such as signs of security attacks from security threat news and weaknesses in source code, can be analyzed integrally in an ML model and LLM environment. In this study, we applied scaling and normalization techniques to the Post News data to improve bias, and we used syntax analysis, semantic analysis, and data flow information to perform an integrated analysis of the source code to improve detection performance. It is designed to be applied to both ML models and LLM by systematizing data labeling and data formats. The results showed that the constructed learning model performed well in both text analysis and source code analysis. In the post-news data learning, the ML-based models XGBoost, SVM, and Random Forest all showed f1-scores of 0.96 to 0.97, while the LLM-based models ST5-xxl, XLNet, BERT, CodeBERT, and GraphCodeBERT all showed a score of 0.97. Additionally, in the C/C++ weakness code detection data learning, the LLM series model ST5-xxl achieved 0.9999, XLNet achieved 0.9999, BERT achieved 0.9037, CodeBERT achieved 0.9999, and GraphCodeBERT achieved 0.9999. The ML-based model XGBoost showed an accuracy of 0.9999 with the TF-IDF embedding method, SVM showed 0.9699 with the TF-IDF embedding method, and Random Forest showed 0.9493 with the TF-IDF method. The models demonstrated higher performance with the TF-IDF embedding method than with the Word2Vec embedding. This study proposed an ML and LLM integrated framework that could effectively detect source code vulnerabilities using abstract syntax trees (AST). This framework overcame the limitations of existing static analysis tools and improved detection accuracy by simultaneously considering the structural characteristics and semantic context of the code. In particular, by combining AST-based feature extraction with LLM's natural language understanding capabilities, it improved generalization performance for new types of vulnerabilities and significantly reduced false positives.
Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) are the most commonly used biomarkers for liver injury, but they are insufficient on their own as prognostic indicators. This study aims to develop a simple method that combines aminotransferases with other routinely available liver function parameters to identify pediatric patients at high risk of adverse outcomes. Medical records from 144,044 pediatric patients with ALT and AST test results were analyzed. The trend in the change of adverse outcome rates by percentiles of AST and ALT was examined to identify a sub-population potentially at risk of liver injury. Within this sub-population, a logistic regression-based prediction rule was developed using liver injury and function markers to predict adverse outcomes. Results showed that an AST level of 80 IU/L can serve as a threshold to identify pediatric patients at higher risk for adverse outcomes. The prediction rule for AST-based risk stratification for liver injury (ASTLI) was developed as follows: among patients with AST > 80 IU/L, the presence of up to two abnormalities in total protein (or albumin), lactate dehydrogenase, or international normalized ratio (or prothrombin time) can help further stratify those at high risk for adverse outcomes (training set: sensitivity = 76%, specificity = 73%; validation set: sensitivity = 76%, specificity = 79%). Age and disease subgroup analysis demonstrated potential for broad applicability across various pediatric populations. The stratification rule could serve as a fast risk stratification tool for liver injury among pediatric patients. • ALT and AST are the most commonly used biomarkers for liver injury. • An elevation in AST and ALT does not always necessitate specific therapeutic intervention nor does it necessarily correlate with disease severity or prognosis. • A stratification rule was developed to identify pediatric patients at high risk for adverse outcomes. It incorporates AST > 80 IU/L and up to two abnormalities in total protein (or albumin), lactate dehydrogenase, or international normalized ratio (or prothrombin time).
Rapid and accurate antimicrobial susceptibility testing (AST) is crucial for guiding treatment and combating resistance. However, conventional ASTs are time-consuming and require pure colonies, delaying the initiation of targeted antimicrobial therapy. Herein, a novel AST based on an aggregation-induced emission luminogen (AIEgen), DATVP, which can directly assess the antimicrobial susceptibility of Gram-negative bacteria in positive blood cultures, is reported. DATVP specifically lights up Gram-negative bacteria with damaged cell membranes while showing no fluorescence in intact bacteria. The antimicrobial-induced fluorescence turn-on of DATVP is found to be fast (within 6 h) and sensitive, allowing for reliable determination of antimicrobial susceptibility. Using DATVP, a wash-free AST is developed and its performance was validated on clinical isolates. The DATVP-based AST showed high categorical agreement (84-95%) with the standard method while shortening the time-to-result from days to hours. This method represents a new paradigm in phenotypic AST, offering speed, simplicity, and direct applicability to patient samples, with the potential to enable timely and targeted antimicrobial treatment.
Astaxanthin (AST), a potent bioactive compound known for its exceptional antioxidant, anti-inflammatory, and anti-apoptotic capacities, has been widely applied in advanced biomedical domains, including regenerative tissue engineering and targeted drug delivery systems. However, its chemical instability limits broader applications. To address this issue, various multifunctional biomaterials, such as nanoliposomes, nanoparticles, glass microspheres, and algal calcium beads, have been employed to stabilize AST and enhance its therapeutic efficacy. This review provides a comprehensive overview of AST, examines its mechanisms of action, and discusses the development and biomedical applications of AST-based biomaterials. We demonstrate the excellent properties and potential applications of these biomaterials in various biomedical contexts, outline existing challenges, and propose future directions to optimize their design and advance their clinical translation.
Active school travel (AST) is an effective approach for increasing children's physical activity and independent mobility, but policy supporting AST is lacking. This study aims to explore children's experiences of AST to inform a policy recommendation. Photovoice methodology with a qualitative approach was applied, with children taking pictures on their way to school. This was followed by focus groups where the children explored their experiences of AST based on their photos. The data were analyzed using qualitative content analysis. The results show that the children valued independent mobility and wanted to be involved in decisions about their travels; they also expressed feelings of increased responsibility and personal growth as a consequence. Although the children recognized areas of improvement regarding infrastructure, especially regarding heavy traffic that jeopardized travel safety, they continued using AST. Finally, the children talked about the value of the health and environmental benefits of AST. Opportunities for friendship, play, and making decisions about their own time were highlighted as important incentives. The benefits from AST are many for children, as well as for society. The result has informed policy recommendations for AST, and the children's input will be used to communicate the recommendations. Listening to the voices of children could be a steppingstone toward forming future healthy mobility initiatives. In that process, it is key to include children's perspectives when formulating the AST policy for successful adoption and implementation.
Targeted next-generation sequencing (tNGS) offers a high-throughput, culture-independent approach that delivers a comprehensive resistance profile in a significantly shorter turn-around time, making it promising in enhancing tuberculosis (TB) diagnosis and informing treatment decisions. This study aims to evaluate the performance of tNGS in the TB diagnosis and drug resistance detection of Mycobacterium tuberculosis (MTB) using MTB clinical isolates and bronchoalveolar lavage fluid (BALF) samples. A total of 143 MTB clinical isolates were assessed, tNGS, phenotypic antimicrobial susceptibility testing (AST), and AST based on whole genome sequencing (WGS) exhibited high concordance rates, averaging 95.10% and 97.05%. Among 158 BALF samples, culture, Xpert MTB/RIF, and tNGS reported 29, 70 and 111 positives, respectively. In the confirmed cases with etiological evidence (smears, cultures, or molecular test), the positive rate of tNGS (73/83, 87.95%) was higher than that of Xpert MTB (67/83, 80.72%). Additionally, 45% (27/60) of clinically diagnosed cases (with imaging or immunological evidence) were positive for tNGS. Further validation on the discrepant results between tNGS and Xpert MTB/RIF with droplet digital PCR (ddPCR) yielded 35 positives, tNGS detected all, and Xpert MTB/RIF only identified 6 positives. In conclusion, tNGS demonstrates robust and rapid performance in the identification of MTB and its associated drug resistance, and can be directly applied to clinical samples, positioning it as a promising approach for laboratory testing of tuberculosis.
In this retrospective, single-center, observational study we assessed the performance of the BIOFIRE® Blood Culture Identification 2 (BCID2) Panel for the identification of multidrug-resistant bacteria (MDRB)-colonized critical care unit patients compared with a standard culture and antimicrobial susceptibility testing (AST)-based approach. A total of 146 rectal/pharyngeal/nasal combined specimens from 130 patients were tested by using the BCID2 panel. MDRB were detected in 40/146 (27.3%) specimens from 39 patients (30%) by the BCID2 panel; MDRB were recovered by culture in 32/146 (21.9%) specimens from 30 patients (23%). Concordance between the MDRB detected by the BCID2 panel and those recovered by culture was observed in 29/43 cases; MDRB were more frequently extended-spectrum beta-lactamase-harboring Enterobacterales or vanA/B-carrying Enterococcus faecium. The per specimen positive and negative percentage agreement values were 90.6% and 90.3%, respectively (Kappa value: 0.73). The BCID2 panel shows promise as a tool for the rapid identification of MDRB carriers in critical care units. Its use may lead to prescription of more refined empirical antimicrobial therapies on an individual basis and allow timely isolation of patients to prevent MDRB spreading. Nevertheless, larger, multicenter, prospective, and Next-generation sequencing-validated studies are needed to corroborate our findings.
Introduction: Periodontitis is one of the most common diseases affecting teeth over the age of 40 years, a process that can be exacerbated by diabetes. People with diabetes are more prone to periodontal disorders. The determination of biomarkers in saliva may be useful for evaluating abnormal periodontal processes. Objective: The main aim of this study was to identify possible biomarkers (aspartate aminotransferase [AST], C-reactive protein [CRP], and albumin) in saliva that could help assess periodontal progression in type 2 diabetic patients. Method: Patients were selected at the Department of Periodontology of the Faculty of Dentistry, University of Debrecen. Considering the study criteria, 18 diabetic and 19 non-diabetic patients were recruited with an average age of 62 ± 9 years. After anamnesis was taken, resting saliva sample was collected from each study participant, and periodontal screening test was performed. In addition to the routine laboratory tests, AST activity, CRP and albumin concentrations were determined in the saliva samples. Using ROC curve analysis, we further evaluated the diagnostic value of AST based on the area under the curve (AUC) value. Results: AST activity values measured in the saliva samples of the diabetic patients were significantly higher compared to the control group (56 [44–107] vs. 33 [14–64] U/L, P = 0.02), however, there was no significant correlation between HgbA1c values and salivary AST levels. Nevertheless, increased AST values in the saliva samples can be attributed to the presence of the combined effect of diabetes mellitus and periodontitis (n = 13), as we observed an even higher AST activity in diabetic patients who developed periodontitis (92 [55–154] vs. 48 [31–55] U/L, P = 0.019) compared with the subgroup showing milder gingivitis (n = 5). On the other hand, compared to the control group, the saliva samples of diabetic patients did not show significant differences in CRP and albumin levels, furthermore, the age did not influence AST results in diabetes mellitus (r = 0.217, P = 0.415). Finally, based on the ROC curve analysis, AST measured in saliva was able to differentiate gingivitis and periodontitis subgroups (AUC: 0.803, P = 0.005) as well as diabetic patients from controls (AUC: 0.744, P = 0.021) at a 49 U/L cut-off value. Conclusion: AST enzyme activity that can be measured in saliva can be a potential laboratory biomarker for the effective investigation of the periodontal clinical status in diabetic patients. Orv Hetil. 2025; 166(16): 613–622. Bevezetés: A fogágy szöveteinek progresszív destrukciójával járó parodontitis a 40 év feletti korosztályban az egyik leggyakoribb fogászati megbetegedés, amelynek súlyosságát a diabetes mellitus jelentősen fokozhatja. Célkitűzés: A jelen tanulmányban célunk volt olyan, nyálban mérhető biomarkerek (glutamát-oxálacetát-transzamináz [GOT], C-reaktív protein [CRP] és albumin) vizsgálata, amelyek esetleg segíthetik a parodontalis kórfolyamatok progressziójának megítélését cukorbetegségben. Módszer: A vizsgálatban részt vevőket a Debreceni Egyetem Fogorvostudományi Kara Parodontológiai Tanszékének szakrendelésén megjelent betegek közül választottuk ki. A beválasztási kritériumok alapján 18 fő, 2-es típusú diabetes mellitusban szenvedő beteget és 19 nem diabeteses személyt (kontrollcsoport) vontunk be, akik átlagéletkora 62 ± 9 év volt. Az anamnézis rögzítése után nyugalmi nyálmintát gyűjtöttünk, és megtörtént a parodontalis statust értékelő szűrővizsgálat. A rutin laboratóriumi vizsgálatok során a nyálmintákban meghatároztuk a GOT-aktivitást, a CRP- és az albuminkoncentrációt. ROC-görbe-analízissel a görbe alatti terület (AUC) értéke alapján tovább értékeltük a GOT diagnosztikai hasznosságát. Eredmények: A diabeteses betegek nyálmintáiban mért GOT-aktivitási értékek jelentősen nagyobbak voltak a kontrollcsoporthoz képest (56 [44–107] vs. 33 [14–64] U/l, P = 0,02), ugyanakkor a HgbA1c-értékek és a nyál-GOT-szintek között nem volt szignifikáns összefüggés. A nyálmintákban az emelkedett GOT-értékek mégis a diabetes mellitus és a parodontitis együttes jelenlétének tulajdoníthatók, mivel azoknál a cukorbetegeknél tapasztaltunk még nagyobb GOT-aktivitást (92 [55–154] vs. 48 [31–55] U/l, P = 0,019), akiknél parodontitis (n = 13) alakult ki, összehasonlítva az enyhébb fokú fogínygyulladást (gingivitis) mutató alcsoporttal (n = 5). Ezzel szemben a cukorbetegek nyálmintái a kontrollcsoporthoz képest nem mutattak jelentős eltérést a CRP- és az albuminszintekben, valamint cukorbetegségben az életkor nem befolyásolta a GOT-eredményeket (r = 0,217, P = 0,415). Végül a ROC-görbe-analízis alapján a nyálban mért GOT 49 U/l-es küszöbérték mellett képes volt elkülöníteni egymástól a gingivitises és a parodontitises alcsoportokat (AUC: 0,803, P = 0,005). Következtetés: A nyálban mérhető GOT-enzim-aktivitás potenciális laboratóriumi biomarker lehet a parodontalis folyamat hatékony vizsgálatára diabeteses betegekben. Orv Hetil. 2025; 166(116): 613–622.
Curcumin, as an antioxidant agent, has been proposed as a potential treatment for nonalcoholic fatty liver disease (NAFLD). The aim of the current systematic review and meta-analysis was to summarize earlier findings regarding the effect of curcumin supplementation on liver enzymes and ALP in NAFLD patients. All studies published up to November 18, 2022, were searched through the PubMed, SCOPUS, and Web of Science databases to collect all randomized clinical trials (RCTs) on NAFLD patients in which curcumin was used as a treatment. A random-effects model was used to measure pooled effect sizes. Weighted mean differences (WMDs) and 95% confidence intervals (CIs) were used to report pooled effect sizes. Subgroup analysis was utilized to investigate heterogeneity. A total of 14 studies were included in this systematic review and meta-analysis. Our pooled meta-analysis indicated a significant decrease in alanine aminotransferase (ALT) following curcumin therapy by pooling 12 effect sizes (WMD: -8.72; 95% CI: -15.16, -2.27, I 2 = 94.1%) and in aspartate aminotransferase (AST) based on 13 effect sizes (WMD: -6.35; 95% CI: -9.81, -2.88, I 2 = 94.4%). However, the pooled analysis of five trials indicated that there was no significant association between curcumin therapy and alkaline phosphatase (ALP) in NAFLD patients (WMD: -4.71; 95% CI: -13.01, 3.58, I 2 = 64.2%). Nevertheless, subgroup analyses showed significant effects of curcumin on ALP with a longer duration of supplementation. The findings of this systematic review and meta-analysis support the potential effect of curcumin on the management of NAFLD. Further randomized controlled trials should be conducted in light of our findings.
The sensitive detection of foodborne pathogenic and rapid antibiotic susceptibility testing (AST) is of great significance. This paper reports the enzyme-triggered in situ synthesis of yellow emitting silicon nanoparticles (SiNPs) and the detection of Escherichia coli (E. coli) O157:H7 in food samples and the rapid AST. The rapid counting of E. coli O157:H7 has been achieved through direct visual observation, equipment detection, and smartphone digitalization. A simple detection platform based on smartphone senses and cotton swabs has been established. Meanwhile, rapid AST based on enzyme-catalyzed SiNPs can intuitively obtain colorimetric samples. This paper established a system for bacterial enzyme-triggered in situ synthesis of SiNPs, with high responsiveness, luminescence ratio, and specificity. The detection limit for E. coli O157:H7 can reach 100 CFU/mL during 5 h, and the recovery efficiency ranges from 90.14% to 110.16%, which makes it a promising strategy for the rapid detection of E. coli O157:H7 and AST.
Moderate-to-severe atopic dermatitis (AD) significantly impacts quality of life. Advanced systemic therapeutics (AST) represent a new generation of medications targeting AD pathogenesis, but many who may benefit from these medications are AST-naïve. We compared patients in the United States who had started AST with those who had not started AST to evaluate associated characteristics. TARGET-DERM AD, (NCT03661866, "A Longitudinal Observational Study of Patients Undergoing Therapy for IMISC (TARGET-DERM)" launched in 2019, is an ongoing, longitudinal, observational study of patients managed at 37 United States sites. Patients were aged 12 years and above, had moderate-to-severe AD based on validated Investigator Global Assessment (vIGA) at enrollment, at least one follow-up visit post-enrollment, and treatment with any of the following: a topical/systemic corticosteroid, immunomodulator, or phototherapy. AST included dupilumab and upadacitinib. Variables of interest gathered at enrollment included demographics, vIGA and Body Surface Area (BSA), patient-reported outcomes, and all recorded therapeutics. Of 3,076 patients, 436 qualified for inclusion, 52 were AST-treated adolescents and 141 AST-treated adults. Both groups had increased likelihood of AST initiation if they had private insurance and higher BSA, vIGAxBSA, or Patient-Oriented SCORing Atopic Dermatitis scores. Adults were more likely to start AST based on minority/ethnicity, more severe vIGA, higher patient-reported outcomes, or if treated at a community clinic. Substantial numbers of adolescent and adult patients (47 and 58%, respectively) with severe disease were AST-naïve. Disease severity and patient access to AST are major factors driving AST initiation. However, some patients are undertreated. This analysis supports AD patient advocacy for those inadequately managed with conventional therapies. Further investigations are necessary to delineate AST initiation barriers and relevant outcomes.
Considering the potential role of anterior scleral thickness (AST) in myopia and the ubiquitous use of optical biometers, we applied and validated a biometry-based technique for estimating AST using optical coherence tomography (OCT) landmarks. The AST was determined across four meridians in 62 participants (aged 20-37 years) with a swept-source OCT and a noncontact optical biometer at a mean ± SD distance of 3.13 ± 0.88 mm from the limbus. The biometer's graticule was focused and aligned with the anterior scleral reflex, which led to the generation of four prominent A-scan peaks: P1 (anterior bulbar conjunctiva), P2 (anterior episclera), P3 (anterior margin of anterior sclera), and P4 (posterior margin of anterior sclera), which were analyzed and compared with the corresponding OCT landmarks to determine tissue thickness. The AST measurements between biometer and OCT correlated for all meridians (r ≥ 0.70, overall r = 0.82; coefficient of variation [CV], 9%-12%; P < 0.01). The mean difference ± SD between two instruments for overall AST measures was 3 ± 2.8 µm (range, -18 to +16 µm; lower limits of agreement, -89 to +83 µm; P = 0.23) across all meridians. The mean ± SE AST with both instruments was found to be thickest at the inferior (562 ± 7 µm and 578 ± 7 µm) and thinnest at the superior (451 ± 7 µm and 433 ± 6 µm) meridian. The biometer demonstrated good intrasession (CV, 8.4%-9.6%) and intersession (CV, 7.9%-13.3%) repeatability for AST measurements across all meridians. The noncontact optical biometer, which is typically used to determine axial length, is capable of accurately estimating AST based on OCT landmarks. The high-resolution optical biometers can demonstrate wider application in the field of myopia research and practice to determine AST.
Astragaloside IV (AST) has been confirmed to have antiasthmatic effects. However, the underline mechanism is unclear. The study aimed to explore the treatment mechanism of AST based on autophagy of memory T cells. AST treatment significantly decreased the number of T effector cells in asthma mice blood and the nude mice that received AST-treated TCMs had relieved inflammation compared with the untreated group; meanwhile, we found that AST significantly decreased the autophagy level and inhibited OX40/OX40L signal pathway of lymphocytes. The results highlighted that AST regulated autophagy to inhibit differentiation of effector T-cell phenotype.
Infections caused by pathogenic Escherichia coli are a serious threat to human health, while conventional antibiotic susceptibility tests (AST) have a long turn-around time, and rapid antibiotic susceptibility methods are urgently needed to save lives in the clinic, reduce antibiotic misuse and prevent emergence of antibiotic-resistant bacteria. We optimized and validated the feasibility of a novel rapid AST based on SYBR Green I and Propidium Iodide (SGPI-AST) for E. coli drug susceptibility test. A total of 112 clinical isolates of E. coli were collected and four antibiotics (ceftriaxone, cefoxitin, imipenem, meropenem) were selected for testing. Bacterial survival rate of E. coli was remarkably linearly correlated with S value at different OD600 values. After optimizing the antibiotic concentrations, the sensitivity and specificity of SGPI-AST reached 100%/100%, 97.8%/100%, 100%/100% and 98.4%/99% for ceftriaxone, cefoxitin, imipenem and meropenem, respectively, and the corresponding concordances of the SGPI-AST with conventional AST were 1.000, 0.980, 1.000 and 0.979, respectively. The SGPI-AST can rapidly and accurately determine the susceptibility of E. coli clinical isolates to multiple antibiotics in 60 min, and has the potential to be applied to guide the precise selection of antibiotics for clinical management of infections caused by pathogenic E. coli.