Gut microbiota induced abnormal amino acids and their correlation with diabetic retinopathy.

AIM: To explore the correlation of gut microbiota and the metabolites with the progression of diabetic retinopathy (DR) and provide a novel strategy to elucidate the pathological mechanism of DR. METHODS: The fecal samples from 32 type 2 diabetes patients with proliferative retinopathy (PDR), 23 with non-proliferative retinopathy (NPDR), 27 without retinopathy (DM), and 29 from the sex-, age- and BMI- matched healthy controls (29 HC) were analyzed by 16S rDNA gene sequencing. Sixty fecal samples from PDR, DM, and HC groups were assayed by untargeted metabolomics. Fecal metabolites were measured using liquid chromatography-mass spectrometry (LC-MS) analysis. Associations between gut microbiota and fecal metabolites were analyzed. RESULTS: A cluster of 2 microbiome and 12 metabolites accompanied with the severity of DR, and the close correlation of the disease progression with PDR-related microbiome and metabolites were found. To be specific, the structure of gut microbiota differed in four groups. Diversity and richness of gut microbiota were significantly lower in PDR and NPDR groups, than those in DM and HC groups. A cluster of microbiome enriched in PDR group, including Pseudomonas, Ruminococcaceae-UCG-002, Ruminococcaceae-UCG-005, Christensenellaceae-R-7, was observed. Functional analysis showed that the glucose and nicotinate degradations were significantly higher in PDR group than those in HC group. Arginine, serine, ornithine, and arachidonic acid were significantly enriched in PDR group, while proline was enriched in HC group. Functional analysis illustrated that arginine biosynthesis, lysine degradation, histidine catabolism, central carbon catabolism in cancer, D-arginine and D-ornithine catabolism were elevated in PDR group. Correlation analysis revealed that Ruminococcaceae-UCG-002 and Christensenellaceae-R-7 were positively associated with L-arginine, ornithine levels in fecal samples. CONCLUSION: This study elaborates the different microbiota structure in the gut from four groups. The relative abundance of Ruminococcaceae-UCG-002 and Parabacteroides are associated with the severity of DR. Amino acid and fatty acid catabolism is especially disordered in PDR group. This may help provide a novel diagnostic parameter for DR, especially PDR.

Effects of dietary intervention on diabetic nephropathy: an umbrella review of systematic reviews and meta-analyses of randomized controlled trials.

Objective: To evaluate the quality of evidence, potential biases, and validity of all available studies on dietary intervention and diabetic nephropathy (DN). Methods: We conducted an umbrella review of existing meta-analyses of randomized controlled trials (RCTs) that focused on the effects of dietary intervention on DN incidence. The literature was searched via PubMed, Embase, Web of Science, and the Cochrane Database of Systematic Reviews. According to the Grading of Recommendations, Assessment, Development and Evaluation (GRADE), evidence of each outcome was evaluated and graded as "high", "moderate", "low" or "very low" quality to draw conclusions. Additionally, we classified evidence of outcomes into 4 categories. Results: We identified 36 meta-analyses of RCTs and 55 clinical outcomes of DN from 395 unique articles. Moderate-quality evidence suggested that probiotic supplementation could significantly improve blood urea nitrogen (BUN), total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels in DN patients. Low-quality evidence indicated that probiotic supplementation significantly improved the serum creatinine concentration, urinary albumin-creatinine ratio (UACR), fasting blood glucose (FBG), HbA1c and high-density lipoprotein cholesterol (HDL-C) in DN patients. In addition, low-quality evidence suggested that a salt restriction diet could significantly improve the creatinine clearance rate (CrCl) in patients with DN. Low-quality evidence suggested that vitamin D supplementation could significantly improve the UACR in patients with DN. In addition, low-quality evidence has indicated that soy isoflavone supplementation could significantly improve BUN, FBG, total cholesterol (TC), triglyceride (TG) and LDL-C levels in patients with DN. Furthermore, low-quality evidence suggested that coenzyme Q10 supplementation could significantly improve HbA1c, TC and HDL-C in patients with DN, and dietary polyphenols also significantly improved HbA1c in patients with DN. Finally, low-quality evidence suggested that supplementation with antioxidant vitamins could significantly improve the serum creatinine concentration, systolic blood pressure, and HbA1c level in patients with DN. Given the small sample size, all significantly associated outcomes were evaluated as class IV evidence. Conclusion: Moderate to low amounts of evidence suggest that supplementation with probiotics, vitamin D, soy isoflavones, coenzyme Q10, dietary polyphenols, antioxidant vitamins, or salt-restricted diets may significantly improve clinical outcomes in patients with DN. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024512670.

A High-Avidity, Thermostable, and Low-Cost Synthetic Capture for Ultrasensitive Detection and Quantification of Viral Antigens and Aerosols.

Lateral flow assays (LFAs) are currently the most popular point-of-care diagnostics, rapidly transforming disease diagnosis from expensive doctor checkups and laboratory-based tests to potential on-the-shelf commodities. Yet, their sensitive element, a monoclonal antibody, is expensive to formulate, and their long-term storage depends on refrigeration technology that cannot be met in resource-limited areas. In this work, LCB1 affibodies (antibody mimetic miniproteins) were conjugated to bovine serum albumin (BSA) to afford a high-avidity synthetic capture (LCB1-BSA) capable of detecting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and virus like particles (VLPs). Substituting the monoclonal antibody 2B04 for LCB1-BSA (stable up to 60 °C) significantly improved the thermal stability, shelf life, and affordability of plasmonic-fluor-based LFAs (p-LFAs). Furthermore, this substitution significantly improved the sensitivity of p-LFAs toward the spike protein and VLPs with precise quantitative ability over 2 and 3 orders of magnitude, respectively. LCB1-BSA sensors could detect VLPs at 100-fold lower concentrations, and this improvement, combined with their robust nature, enabled us to develop an aerosol sampling technology to detect aerosolized viral particles. Synthetic captures like LCB1-BSA can increase the ultrasensitivity, availability, sustainability, and long-term accuracy of LFAs while also decreasing their manufacturing costs.

Carbon quantum dots from hemicucur[6]bit and the application for the detection of Pb2.

A macrocyclic compound, hemicucurbit[6]uril (HemiQ[6]), is employed as the carbon source to produce a novel sort of carbon quantum dots (CQDs) with blue fluorescence in aqueous solution. The CQDs are fully identified by transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Nuclear Magnetic Resonance (NMR), zeta potential, ultraviolet/visible (UV-vis) and photoluminescence spectroscopy (PL). The nanomaterial is developed for the analysis of Pb2+ in the light of the Resonance Rayleigh scattering (RRS) changes with the increasing Pb2+ concentration. The proposed probe emerges a high selectivity to Pb2+ and excellent sensitivity in the linear concentration range of 0-6 µM with a detection limit low to 0.42 µM, which is superior to the previous values of Pb2+ sensors, as well as the good anti-interference ability is confirmed by the specifical response to Pb2+ in the presence of other metal cations. Therefore, the proposed analysis of Pb2+ is explored for the application in real samples of tap water and lake water, in satisfied results of acceptable recoveries.

Multi-hierarchy Network Configuration Can Predict Brain States and Performance.

The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we proposed an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules, and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.

Hydrophobic substrate binding pocket remodeling of echinocandin B deacylase based on multi-dimensional rational design.

Actinoplanes utahensis deacylase (AAC)-catalyzed deacylation of echinocandin B (ECB) is a promising method for the synthesis of anidulafungin, the newest of the echinocandin antifungal agents. However, the low activity of AAC significantly limits its practical application. In this work, we have devised a multi-dimensional rational design strategy for AAC, conducting separate analyses on the substrate-binding pocket's volume, curvature, and length. Furthermore, we quantitatively analyzed substrate properties, particularly on hydrophilic and hydrophobic. Accordingly, we tailored the linoleic acid-binding pocket of AAC to accommodate the extended long lipid chain of ECB. By fine-tuning the key residues, the resulting AAC mutants can accommodate the ECB lipid chain with a lower curvature binding pocket. The D53A/I55F/G57M/F154L/Q661L mutant (MT) displayed 331 % higher catalytic efficiency than the wild-type (WT) enzyme. The MT product conversion was 94.6 %, reaching the highest reported level. Utilizing a multi-dimensional rational design for a customized mutation strategy of the substrate-binding pocket is an effective approach to enhance the catalytic efficiency of enzymes in handling complicated substrates.

Absolute monocyte counts could predict disease activity and secondary loss of response of patients with Crohn's disease treated with anti-TNF-α drug.

BACKGROUND: Assessing Crohn's disease (CD) activity is critical for monitoring disease progression. In CD, monocytes could release TNF-α. Thus, it is extremely important to study its role in the disease activity and loss of response to anti-TNF-α biologics. METHODS: In this study, we collected CD patients treated with biologics from January 2017 to May 2022. Indicators associated with disease activity were evaluated by Spearman correlation analysis and Mann-Whitney U test. Specifically, logistic analyses were used to explore the predictors of primary nonresponse (PNR) and secondary loss of response (SLOR) within 1 year of anti-TNF-α agents. In addition, a nomogram was developed for therapeutic effect prediction. RESULTS: 283 patients with CD were identified. Disease activity group, defined as CDAI equal to or greater than 150, had significant elevated absolute monocyte counts than disease remission group based on CDAI score (p = 0.019, Z = -2.354). Logistic analyses showed that absolute monocyte counts could be an independent predictor of 1-year SLOR of anti-TNF-α agents in CD patients (p = 0.013). A nomogram established based on gender, absolute monocyte counts, and hemoglobin could predict SLOR within 1 year of anti-TNF-α agents reliably. CONCLUSION: The results of this study support the utility of absolute monocyte counts detecting disease activity and anti-TNF-α therapy effect in patients with CD.

Signals that control MAIT cell function in healthy and inflamed human tissues.

Mucosal-associated invariant T (MAIT) cells have a semi-invariant T-cell receptor that allows recognition of antigen in the context of the MHC class I-related (MR1) protein. Metabolic intermediates of the riboflavin synthesis pathway have been identified as MR1-restricted antigens with agonist properties. As riboflavin synthesis occurs in many bacterial species, but not human cells, it has been proposed that the main purpose of MAIT cells is antibacterial surveillance and protection. The majority of human MAIT cells secrete interferon-gamma (IFNg) upon activation, while some MAIT cells in tissues can also express IL-17. Given that MAIT cells are present in human barrier tissues colonized by a microbiome, MAIT cells must somehow be able to distinguish colonization from infection to ensure effector functions are only elicited when necessary. Importantly, MAIT cells have additional functional properties, including the potential to contribute to restoring tissue homeostasis by expression of CTLA-4 and secretion of the cytokine IL-22. A recent study provided compelling data indicating that the range of human MAIT cell functional properties is explained by plasticity rather than distinct lineages. This further underscores the necessity to better understand how different signals regulate MAIT cell function. In this review, we highlight what is known in regards to activating and inhibitory signals for MAIT cells with a specific focus on signals relevant to healthy and inflamed tissues. We consider the quantity, quality, and the temporal order of these signals on MAIT cell function and discuss the current limitations of computational tools to extrapolate which signals are received by MAIT cells in human tissues. Using lessons learned from conventional CD8 T cells, we also discuss how TCR signals may integrate with cytokine signals in MAIT cells to elicit distinct functional states.

Beta-informativeness-diffusion multilayer graph embedding for brain network analysis.

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

One-Step Hydrothermal Synthesis of NVO Cathodes with Varied Lattice NH4 + Content: Effect on Structural Evolution and Electrochemical Performance.

Aqueous zinc ion batteries have been extensively researched due to their distinctive advantages such as low cost and high safety. Vanadium oxides are important cathode materials, however, poor cycle life caused by vanadium dissolution limits their application. Recent studies show that the lattice NH4 + in vanadium oxides can act as a pillar to enhance structural stability and play a crucial role in improving its cycling stability. Nevertheless, there is still a lack of research on the effect of the lattice NH4 + content on structural evolution and electrochemical performance. Herein, we synthesize vanadium oxides with different contents of lattice NH4 + by a one-step hydrothermal reaction. The vanadium oxides with lattice NH4 + exhibit high initial capacity, as well as good cycling stability and rate performance compared to bare vanadium oxide. Combined with electrochemical analyses, ex-situ structural characterizations, and in-situ X-ray diffraction tests, we reveal that the lattice NH4 + content plays a positive role in vanadium oxides' structural stability and cation diffusion kinetics. This work presents a direction for designing high-performance vanadium cathodes for aqueous zinc ion batteries.

Deterioration of fine motor skills and functional disability in patients with moderate-to-advanced Parkinson disease: A longitudinal follow-up study.

INTRODUCTION: Parkinson disease (PD) caused substantially disability. The impairment of fine motor skills (FMSs) is correlated with the severity of functional disability (FD) cross-sectionally in people with PD (PwP). The present study investigated the decline in FMSs and the predictive value of baseline FMSs for the progression of FD. METHODS: People with moderate-to-advanced PD who received two evaluations within 1-5 years were identified from the Taiwan Data Bank of Persons with Disability database. The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) was used to evaluate FD, and FMSs including pen-holding, buttoning, and knotting were assessed. RESULTS: Our study included 2,271 people with moderate-to-advanced PD. We observed annual progression of FD in each domain of the WHODAS 2.0, with no difference between the sexes. The most significant correlation between FD and FMSs was that of decline in buttoning ability and deterioration of summary WHODAS 2.0 scores. Deterioration in FD across all domains of WHODAS 2.0 was associated with at least one FMS. The extent of disability in all three types of FMS at baseline was also correlated with deterioration of motility. Additionally, baseline disability in buttoning was significantly correlated with cognitive decline, and disability in knotting was significantly associated with the progression of FD. CONCLUSION: FMSs may be reliable markers for further FD, particularly in the areas of cognition, motility, and life activity. Because of the significant FD observed in people with moderate-to-advanced PD, the availability of predictors is essential for applying precautionary measures and providing appropriate treatment.

The value of CT-based radiomics in predicting hemorrhagic transformation in acute ischemic stroke patients without recanalization therapy.

Objective: The aim of this study is to investigate the clinical value of radiomics based on non-enhanced head CT in the prediction of hemorrhage transformation in acute ischemic stroke (AIS). Materials and methods: A total of 140 patients diagnosed with AIS from January 2015 to August 2022 were enrolled. Radiomic features from infarcted areas on non-enhanced CT images were extracted using ITK-SNAP. The max-relevance and min-redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select features. The radiomics signature was then constructed by multiple logistic regressions. The clinicoradiomics nomogram was constructed by combining radiomics signature and clinical characteristics. All predictive models were constructed in the training group, and these were verified in the validation group. All models were evaluated with the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Of the 140 patients, 59 experienced hemorrhagic transformation, while 81 remained stable. The radiomics signature was constructed by 10 radiomics features. The clinicoradiomics nomogram was constructed by combining radiomics signature and atrial fibrillation. The area under the ROC curve (AUCs) of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the training group were 0.64, 0.86, and 0.86, respectively. The AUCs of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the validation group were 0.63, 0.90, and 0.90, respectively. The DCA curves showed that the radiomics signature performed well as well as the clinicoradiomics nomogram. The DCA curve showed that the clinical application value of the radiomics signature is similar to that of the clinicoradiomics nomogram. Conclusion: The radiomics signature, constructed without incorporating clinical characteristics, can independently and effectively predict hemorrhagic transformation in AIS patients.

Potential molecular biomarkers for the diagnosis and prognosis of bladder cancer.

Bladder cancer (BC) is a common malignant tumor of urinary system, which can be divided into muscle-invasive BC (MIBC) and nonmuscle-invasive BC (NMIBC). The number of BC patients has been gradually increasing currently. At present, bladder tumours are diagnosed and followed-up using a combination of cystoscopic examination, cytology and histology. However, the detection of early grade tumors, which is much easier to treat effectively than advanced stage disease, is still insufficient. It frequently recurs and can progress when not expeditiously diagnosed and monitored following initial therapy for NMIBC. Treatment strategies are totally different for different stage diseases. Therefore, it is of great practical significance to study new biomarkers for diagnosis and prognosis. In this review, we summarize the current state of biomarker development in BC diagnosis and prognosis prediction. We retrospectively analyse eight diagnostic biomarkers and eight prognostic biomarkers, in which CK, P53, PPARγ, PTEN and ncRNA are emphasized for discussion. Eight molecular subtype systems are also identified. Clinical translation of biomarkers for diagnosis, prognosis, monitoring and treatment will hopefully improve outcomes for patients. These potential biomarkers provide an opportunity to diagnose tumors earlier and with greater accuracy, and help identify those patients most at risk of disease recurrence.

The relationship between nonsteroidal anti-inflammatory drugs and cancer incidence: An umbrella review.

Several clinical and preclinical studies have shown that nonsteroidal anti-inflammatory drugs (NSAIDs), particularly aspirin, reduce the incidence of various cancer types. However, there is still a lack of literature evaluating the overall association between multiple cancer morbidities and NSAIDs. Thus, we conducted an umbrella review to evaluate the quality of evidence, validity, and biases of the existing systematic reviews and meta-analyses on the relationships between NSAIDS and multiple tumor incidence outcomes. We found that NSAIDs might be associated with a decreased risk of several cancers, including the central nervous system, breast, esophageal, gastric, head and neck, hepatocellular, cholangiocarcinoma, colorectal, endometrial, lung, ovary, prostate, and pancreatic cancers, but regular intake of any dose of non-aspirin NSAIDs (NA-NSAIDs) could increase the incidence of kidney cancer. However, most of included studies are evaluated as low quality according to our evidence assessment. Furthermore, due to the potential side effects, such as hemorrhage, digestive symptoms and peptic ulcer, it is still not recommend to use NSAIDs regularly to prevent cancers.

Temporal trend of anisometropia incidence in Chinese school-aged children before and during the COVID-19 pandemic.

Objective: To analyze and compare the temporal trends in the incidence of anisometropia among Chinese school-aged children both before and during the COVID-19 pandemic, and to investigate the impact of the pandemic on the incidence of anisometropia. Methods: We conducted a retrospective study comprising six distinct and independent longitudinal cohorts, each including children aged 6 to 13 years who visited the Joint Shantou International Eye Center between January 2010 and December 2021. Children were grouped into cohorts based on the year of their first eye clinic visit: 2010, 2012, 2014, 2016, 2018, or 2020. Only children without anisometropia at initial visits, followed for 18 ± 6 months, were included. The cumulative incidence and risk factors of anisometropia were analyzed using Kaplan-Meier estimation and Cox proportional hazards regression models. Subgroup analyses were performed based on sex, age groups, initial refractive error status, and initial interocular SE difference. Anisometropic children were further categorized into myopic and non-myopic, with subsequent subgroup analyses conducted. Results: Of 11,235 children were recruited from six cohorts (2010: n = 1,366; 2012: n = 1,708; 2014: n = 1,896; 2016: n = 2,354; 2018: n = 2,514; 2020: n = 1,397), 869 children developed anisometropia during a mean follow-up of 17.5 ± 3.7 months. After adjustment of confounding factors, we found that the risk of anisometropia remained relatively stable before 2020 but significantly increased in the 2020 cohort (adjusted HR 2.93, 95% CI 2.23 to 3.86; p < 0.001). This trend persisted in studies of spherical anisometropia (adjusted HR 2.52, 95% CI 1.60 to 3.97; p < 0.001) and cylindrical anisometropia (adjusted HR 2.91, 95% CI 1.69 to 3.62; p < 0.001). Older age and a greater initial difference in SE between the two eyes were also significantly associated with a higher risk of developing anisometropia (p < 0.001). Subgroup analyses consistently showed increased risk in the 2020 cohort. Conclusion: This study reveals a concerning rise in anisometropia incidence among Chinese school-aged children during the period of the COVID-19 pandemic. These findings highlight the worrisome rise in anisometropia risk during the COVID-19 pandemic and emphasize the importance of early detection and management to safeguard children's visual health.

Fetal overgrowth and weight trajectories during infancy and adiposity in early childhood.

BACKGROUND: Large-for-gestational age (LGA), a marker of fetal overgrowth, has been linked to obesity in adulthood. Little is known about how infancy growth trajectories affect adiposity in early childhood in LGA. METHODS: In the Shanghai Birth Cohort, we followed up 259 LGA (birth weight >90th percentile) and 1673 appropriate-for-gestational age (AGA, 10th-90th percentiles) children on body composition (by InBody 770) at age 4 years. Adiposity outcomes include body fat mass (BFM), percent body fat (PBF), body mass index (BMI), overweight/obesity, and high adiposity (PBF >85th percentile). RESULTS: Three weight growth trajectories (low, mid, and high) during infancy (0-2 years) were identified in AGA and LGA subjects separately. BFM, PBF and BMI were progressively higher from low- to mid-to high-growth trajectories in both AGA and LGA children. Compared to the mid-growth trajectory, the high-growth trajectory was associated with greater increases in BFM and the odds of overweight/obesity or high adiposity in LGA than in AGA children (tests for interactions, all P < 0.05). CONCLUSIONS: Weight trajectories during infancy affect adiposity in early childhood regardless of LGA or not. The study is the first to demonstrate that high-growth weight trajectory during infancy has a greater impact on adiposity in early childhood in LGA than in AGA subjects. IMPACT: Large-for-gestational age (LGA), a marker of fetal overgrowth, has been linked to obesity in adulthood, but little is known about how weight trajectories during infancy affect adiposity during early childhood in LGA subjects. The study is the first to demonstrate a greater impact of high-growth weight trajectory during infancy (0-2 years) on adiposity in early childhood (at age 4 years) in subjects with fetal overgrowth (LGA) than in those with normal birth size (appropriate-for-gestational age). Weight trajectory monitoring may be a valuable tool in identifying high-risk LGA children for close follow-ups and interventions to decrease the risk of obesity.

Identify production area, growth mode, species, and grade of Astragali Radix using metabolomics "big data" and machine learning.

BACKGROUND: Astragali Radix (AR) is a widely used herbal medicine. The quality of AR is influenced by several key factors, including the production area, growth mode, species, and grade. However, the markers currently used to distinguish these factors primarily focus on secondary metabolites, and their validation on large-scale samples is lacking. PURPOSE: This study aims to discover reliable markers and develop classification models for identifying the production area, growth mode, species, and grade of AR. METHODS: A total of 366 batches of AR crude slices were collected from six provinces in China and divided into learning (n = 191) and validation (n = 175) sets. Three ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) methods were developed and validated for determining 22 primary and 10 secondary metabolites in AR methanol extract. Based on the quantification data, seven machine learning algorithms, such as Nearest Neighbors and Gradient Boosted Trees, were applied to screen the potential markers and build the classification models for identifying the four factors associated with AR quality. RESULTS: Our analysis revealed that secondary metabolites (e.g., astragaloside IV, calycosin-7-O-ß-D-glucoside, and ononin) played a crucial role in evaluating AR quality, particularly in identifying the production area and species. Additionally, fatty acids (e.g., behenic acid and lignoceric acid) were vital in determining the growth mode of AR, while amino acids (e.g., alanine and phenylalanine) were helpful in distinguishing different grades. With both primary and secondary metabolites, the Nearest Neighbors algorithm-based model was constructed for identifying each factor of AR, achieving good classification accuracy (>70%) on the validation set. Furthermore, a panel of four metabolites including ononin, astragaloside II, pentadecanoic acid, and alanine, allowed for simultaneous identification of all four factors of AR, offering an accuracy of 86.9%. CONCLUSION: Our findings highlight the potential of integrating large-scale targeted metabolomics and machine learning approaches to accurately identify the quality-associated factors of AR. This study opens up possibilities for enhancing the evaluation of other herbal medicines through similar methodologies, and further exploration in this area is warranted.

Primary malignant melanoma of the urethra: Report of 9 cases in China.

BACKGROUND: Primary urethral melanoma is extremely rare and malignant, and accounts for <1% of all melanoma cases. Here, we aimed to gain more insight into the pathological and follow-up outcomes of patients with this tumor type. METHODS: We conducted a retrospective analysis of nine patients who had undergone comprehensive treatment at West China Hospital since 2009. Furthermore, we also performed a questionnaire-based survey to determine the quality of life and health statuses of surviving patients. RESULTS: Most participants were women, and their ages ranged between 57 and 78 years (mean age: 64.9 years). Common clinical presentations included pigmentation, moles, and irregular neoplasms in the urethral meatus with or without bleeding. The final diagnosis was based on pathological and immunohistochemical examination results. All patients underwent regular follow-ups after receiving surgical or non-surgical therapy, such as chemotherapy or radiotherapy. DISCUSSION/CONCLUSION: Our study revealed that pathological and immunohistochemical tests are crucial for precise diagnosis, especially in asymptomatic patients. Primary malignant urethral melanoma generally has a poor prognosis; therefore, early and accurate diagnosis is imperative. Timely surgical intervention and immunotherapy can help improve patient prognosis. Moreover, an optimistic outlook and family support may augment the clinical management of this disease.

Dynamic Stereochemistry of M8 Pd6 Supramolecular Cages Based on Metal-Center Lability for Differential Chiral Induction, Resolution, and Recognition.

A series of isostructural supramolecular cages with a rhombic dodecahedron shape have been assembled with distinct metal-coordination lability (M8 Pd6 -MOC-16, M=Ru2+ , Fe2+ , Ni2+ , Zn2+ ). The chirality transfer between metal centers generally imposes homochirality on individual cages to enable solvent-dependent spontaneous resolution of Δ8 /Λ8 -M8 Pd6 enantiomers; however, their distinguishable stereochemical dynamics manifests differential chiral phenomena governed by the cage stability following the order Ru8 Pd6 >Ni8 Pd6 >Fe8 Pd6 >Zn8 Pd6 . The highly labile Zn centers endow the Zn8 Pd6 cage with conformational flexibility and deformation, enabling intrigue chiral-Δ8 /Λ8 -Zn8 Pd6 to meso-Δ4 Λ4 -Zn8 Pd6 transition induced by anions. The cage stabilization effect differs from inert Ru2+ , metastable Fe2+ /Ni2+ , and labile Zn2+ , resulting in different chiral-guest induction. Strikingly, solvent-mediated host-guest interactions have been revealed for Δ8 /Λ8 -(Ru/Ni/Fe)8 Pd6 cages to discriminate the chiral recognition of the guests with opposite chirality. These results demonstrate a versatile procedure to control the stereochemistry of metal-organic cages based on the dynamic metal centers, thus providing guidance to maneuver cage chirality at a supramolecular level by virtue of the solvent, anion, and guest to benefit practical applications.

Controlling periodic Fano resonances of quantum acoustic waves with a giant atom coupled to a microwave waveguide.

Nanoscale Fano resonances, with applications from telecommunications to ultra-sensitive biosensing, have prompted extensive research. We demonstrate that a superconducting qubit, jointly coupled to microwave waveguides and an inter-digital transducer composite device, can exhibit acoustic Fano resonances. Our analytical framework, leveraging the Taylor series approximation, elucidates the origins of these quantum acoustic resonances with periodic Fano-like interference. By analyzing the analytical Fano parameter, we demonstrate that the Fano resonances and their corresponding Fano widths near the resonance frequency of a giant atom can be precisely controlled and manipulated by adjusting the time delay. Moreover, not just the near-resonant Fano profiles, but the entire periodic Fano resonance features can be precisely modulated from Lorentz, Fano to quasi-Lorentz shapes by tuning the coupling strength of the microwave waveguide. Our analytical framework offers insights into the control and manipulation of periodic Fano resonances in quantum acoustic waves, thereby presenting significant potential for applications such as quantum information processing, sensing, and communication.