Screening potential biomarkers for acute respiratory infectious diseases from antipyretics, antiviral, and antibiotics in wastewater.

Since the onset of COVID-19, respiratory diseases have emerged as a focal concern within the field of public health. This study aims to reveal the prevalence of acute respiratory infectious diseases by screening antipyretic, antiviral, and antibiotic biomarkers through wastewater analysis. Samples were collected over a seven-day period each year in 2022, 2023, and 2024 from a northern city in China, assessing the concentrations of two antipyretics (paracetamol and ibuprofen), one antiviral drug (oseltamivir), eleven antibiotics, and three pathogens (influenza A, influenza B, and Mycoplasma pneumoniae). The usage of most antipyretics and antibiotics was higher in 2023 and 2024, primarily due to the outbreak of COVID-19 in 2023 and the prevalence of influenza A, influenza B, and Mycoplasma pneumoniae in 2024. The prevalence assessed using antipyretics (2.68 %) and pathogens (2.70 %) demonstrated a high degree of consistency, whereas the prevalence estimated using antibiotics and antiviral drugs was only 0.53 % and 0.36 %, respectively. Antibiotics are generally used to treat a broad spectrum of bacterial infections rather than targeting a specific pathogen, so their presence in wastewater may not directly reflect the prevalence of a particular disease. In contrast, antipyretics and specific pathogens exhibit a stronger correlation, suggesting that they may serve as more reliable biomarkers than antiviral and antibiotic drugs. The research findings offer alternative biomarkers, such as antipyretics, aside from pathogens, for the assessment of acute respiratory infectious diseases.

An AI Agent for Fully Automated Multi-Omic Analyses.

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle bioinformatics analysis continues to grow. In response to this need, Automated Bioinformatics Analysis (AutoBA) is introduced, an autonomous AI agent designed explicitly for fully automated multi-omic analyses based on large language models (LLMs). AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step-by-step plans for various bioinformatics tasks. AutoBA's unique capacity to self-design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA offers multiple LLM backends, with options for both online and local usage, prioritizing data security and user privacy. In comparison to ChatGPT and open-source LLMs, an automated code repair (ACR) mechanism in AutoBA is designed to improve its stability in automated end-to-end bioinformatics analysis tasks. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents an advanced and convenient tool, offering robustness and adaptability for conventional multi-omic analyses.

Symbiont-mediated antisense RNA delivery controls Nosema ceranae infections in Apis mellifera.

Nosema ceranae is a main parasite for honeybees (Apis mellifera) which causes colony collapse in spring. Effective management of N. ceranae infections in bees is imperative for beekeepers. RNA interference (RNAi) has been proven a promising method to control bee pathogens, including IAPV, Varroa destructor, and Nosema. Most studies in this field focused on oral inoculation of double-stranded RNA (dsRNA). We developed an easier method with long-term RNAi effects by engineering the bee symbiont, Bacillus subtilis, to deliver single-stranded antisense RNA (asRNA) in the bee guts, targeting N. ceranae genes. We interfered with the expression of a spore wall protein (SWP12) and a polar tube protein (PTP3) of N. ceranae, resulting in a 60.5% increase in bee lifespan and a 72.7% decrease in Nosema spore load. Our research introduced a novel approach to bee parasite control: B. subtilis-mediated asRNA delivery. Our strategy simplifies the procedure of RNAi, presenting a more efficient mechanism with both prophylactic and therapeutic effects on N. ceranae-infected bees.

Preparation of WSi@SiOx/Ti3C2 from photovoltaic silicon waste as high-performance anode materials for lithium-ion batteries.

Silicon anodes hold promise for future lithium-ion batteries (LIBs) due to their high capacity, but they face challenges such as severe volume expansion and low electrical conductivity. In this study, we present a straightforward and scalable electrostatic self-assembly method to fabricate WSi@SiOx/Ti3C2 composites for LIBs. Silicon nanosheets and the ultra-thin oxide layer SiOx serve as sufficient buffers against volume changes, while the layered MXene enhances the electrical conductivity of the composite and promoted Li+/e- transport. Additionally, cationic surfactant-treated Ti3C2 provides more active sites for WSi@SiOx attachment and acts as an intercalating agent, enabling WSi@SiOx to enter the interlayer spaces of Ti3C2. The WSi@SiOx/Ti3C2 electrodes significantly improved electrochemical performance, achieving a capacity of 1,130 mAh g-1 after 800 charge/discharge cycles at 500 mA g-1. This study not only presents a straightforward pathway for high-value utilization of silicon waste but also offers a feasible route for preparing high-performance and cost-effective silicon-based LIBs.

Ni-Electrocatalytic CO2 Reduction Toward Ethanol.

The electroreduction of CO2 offers a sustainable route to generate synthetic fuels. Cu-based catalysts have been developed to produce value-added C2+ alcohols; however, the limited understanding of complex C-C coupling and reaction pathway hinders the development of efficient CO2-to-C2+ alcohols catalysts. Herein, a Cu-free, highly mesoporous NiO catalyst, derived from the microphase separation of a block copolymer, is reported, which achieves selective CO2 reduction toward ethanol with a Faradaic efficiency of 75.2% at -0.6 V versus RHE. The dense mesopores create a favorable local reaction environment with CO2-rich and H2O-deficient interfaces, suppressing hydrogen evolution and maximizing catalytic activity of NiO for CO2 reduction. Importantly, the C1-feeding experiments, in situ spectroscopy, and theoretical calculations consistently show that the direct coupling of *CO2 and *COOH is responsible for C-C bond formation on NiO, and subsequent reduction of *CO2-COOH to ethanol is energetically facile through the *COCOH and *OC2H5 pathway. The unconventional C-C coupling mechanism on NiO, in contrast to the *CO dimerization on Cu, is triggered by strong CO2 adsorption on the polarized Ni2+-O2- sites. The work not only demonstrates a highly selective Cu-free Ni-based alternative for CO2-to-C2+ alcohols transformation but also provides a new perspective on C-C coupling toward C2+ synthesis.

Disease burden of AIDS in last 30-year period and its predicted level in next 25-years based on the global burden disease 2019.

BACKGROUND: This study examines global trends in acquired immune deficiency syndrome (AIDS) incidence, mortality, and disability-adjusted life years (DALYs) from 1990 to 2019, focusing on regional disparities in AIDS incidence, mortality, and DALYs across various levels of socio-demographic index (SDI). It also investigates variations in AIDS incidence, mortality, and DALYs across different age groups, and projects specific trends for the next 25 years. METHODS: Comprehensive data on AIDS from 1990 to 2019 in 204 countries and territories was obtained from a GBD study. This included information on AIDS incidence, mortality, DALYs, and age-standardized rates (ASRs). Projections for AIDS incidence and mortality over the next 25 years were generated using the Bayesian age-period-cohort model. RESULTS: From 1990 to 2019, the global incidence of HIV cases increased from 1,989,282 to 2,057,710, while the age-standardized incidence rate (ASIR) decreased from 37.59 to 25.24 with an estimated annual percentage change (EAPC) of -2.38. The ASIR exhibited an upward trend in high SDI and high-middle SDI regions, a stable trend in middle SDI regions, and a downward trend in low-middle SDI and low SDI regions. In regions with higher SDI, the ASIR was higher in males than in females, while the opposite was observed in lower SDI regions. Throughout 1990 to 2019, the age-standardized death rate (ASDR) and age-standardized DALY rate remained stable, with EAPCs of 0.24 and 0.08 respectively. Countries with the highest HIV burden affecting women and children under five years of age are primarily situated in lower SDI regions, particularly in sub-Saharan Africa. Projections indicate a significant continued decline in the age-standardized incidence and mortality rates of AIDS over the next 25 years, for both overall and by gender. CONCLUSIONS: The global ASIR decreased from 1990 to 2019. Higher incidence and death rates were observed in the lower SDI region, indicating a greater susceptibility to AIDS among women and < 15 years old. This underscores the urgent need for increased resources to combat AIDS in this region, with focused attention on protecting women and < 15 years old as priority groups. The AIDS epidemic remained severe in sub-Saharan Africa. Projections for the next 25 years indicate a substantial and ongoing decline in both age-standardized incidence and mortality rates.

Development of a quinic acid-induced CRISPR/Cas9 genome editing system and its application for the activation of ilicicolin H biosynthesis in Trichoderma reesei.

The CRISPR/Cas9 genome editing tool has been extensively utilized in filamentous fungi, including Trichoderma reesei. However, most existing systems employ constitutive promoters for the expression of Cas9 protein within the cells or directly introduce Cas9 protein into the cells, which often leads to continuous expression of Cas9 resulting in undesired phenotypes or increased operational cost. In this study, we identified a quinic acid (QA)-induced qai5 promoter and employed it to express Cas9, thereby establishing an inducible genome editing system in T. reesei. By utilizing this system, we successfully edited the ypr1 gene and the silent gene cluster involved in ilicicolin H synthesis using donor DNA labeling 41-bp homology arm (HA), resulting in an editing efficiency ranging from 29.2 % to 46.7 %. Consequently, biosynthesis of ilicicolin H was achieved in T. reesei. To summarize, this study presents a novel form of CRISPR/Cas9 genome editing system that enables efficient and controllable genetic modifications in T. reesei.

Development of a Standardized Photo Guideline for Online Hair Transplantation Consultation.

BACKGROUND: Telemedicine has rapidly advanced in plastic and aesthetic surgery, but obtaining high-quality images during online hair transplantation consultations remains challenging, impeding doctors' visual evaluation. OBJECTIVE: To investigate patients' attitude and satisfaction with online hair transplantation consultations, and to develop a standardized photo guideline to help patients capture high-quality images. METHODS: We surveyed patients' attitudes and satisfaction with online hair transplantation consultations from November 23, 2023 to May 3, 2024. Meanwhile, five surgeons developed a standardized photo guideline and assessed its effectiveness by comparing image quality between two patient groups: those using the photo guideline and those not using it. RESULTS: We collected 570 responses to the attitude questionnaire, with 76.66% of participants expressing a willingness to undergo online hair transplantation consultations. The patient satisfaction survey yielded an overall satisfaction score of 4.44 ± 0.72 out of 5 for online hair transplantation consultations. Furthermore, all five surgeons rated photographs taken by patients following the photo guideline as higher quality compared to those taken by patients who did not use it. CONCLUSION: Patients show high satisfaction with online hair transplantation consultations. The standardized photo guideline proves effective in helping patients take high-quality photographs for online consultations. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Highly Efficient Ultraviolet Third-Harmonic Generation in an Isolated Thin Si Meta-Structure.

Nonlinear nanophotonic devices have shown great potential for on-chip information processing, quantum source, 3D microfabrication, greatly promoting the developments of integrated optics, quantum science, nanoscience and technologies, etc. To promote the applications of nonlinear nanodevices, improving the nonlinear efficiency, expanding the spectra region of nonlinear response and reducing device thickness are three key issues. Herein, this study focuses on the nonlinear effect of third-harmonic generation (THG), and present a thin Si meta-sructure to improve the THG efficiency in the ultraviolet (UV) region. The measured THG efficiency is up to 10-5 at an emission wavelength of 309 nm. Also, the THG nanosystem is only 100 nm in thickness, which is two-five times thinner than previous all-dielectric nanosystems applied in THG studies. These findings not only present a powerful thin meta-structure with highly efficient THG emission in UV region, but also provide a constructive avenue for further understanding the light-matter interactions at subwavelength scales, guiding the design and fabricating of advanced photonic devices in future.

A randomized controlled trial on hair follicular-derived microtissue for promoting wound healing and alleviating postoperative complications after hair transplantation.

BACKGROUND: Hair transplantation, particularly through follicular unit extraction (FUE), can lead to postoperative complications, such as numbness, itching, and pain in donor areas, primarily because of delayed wound healing. Efficient management of donor-site healing is crucial to mitigate these complications and improve overall patient outcomes. OBJECTIVE: This study aimed to assess the efficacy of hair follicular-derived microtissue (HFMT) in promoting wound healing and alleviating postoperative complications in donor areas after FUE hair transplantation. METHODS: Perifollicular tissue obtained during the trimming phase of hair transplantation was processed into HFMT and analyzed for its properties using histological and molecular techniques. In a single-blind, split-scalp study involving 98 participants, Group A received HFMT or mupirocin, whereas Group B received HFMT or no treatment. Dermatoscopic images were captured postoperatively, and visual analog scale scores were used to evaluate pain, itching, and numbness. RESULTS: HFMT-treated donor sites in Group A demonstrated a significantly higher wound closure ratio on postoperative day 3 than mupirocin-treated sites. Pain scores for HFMT-treated sites were consistently lower on postoperative days 3, 5, and 7. Similar trends were observed for itching scores. Group B exhibited outcomes comparable with Group A. CONCLUSION: The application of HFMT homogenates effectively accelerated wound healing and alleviated donor-site complications after FUE hair transplantation.

YOLOC-tiny: a generalized lightweight real-time detection model for multiripeness fruits of large non-green-ripe citrus in unstructured environments.

This study addresses the challenges of low detection precision and limited generalization across various ripeness levels and varieties for large non-green-ripe citrus fruits in complex scenarios. We present a high-precision and lightweight model, YOLOC-tiny, built upon YOLOv7, which utilizes EfficientNet-B0 as the feature extraction backbone network. To augment sensing capabilities and improve detection accuracy, we embed a spatial and channel composite attention mechanism, the convolutional block attention module (CBAM), into the head's efficient aggregation network. Additionally, we introduce an adaptive and complete intersection over union regression loss function, designed by integrating the phenotypic features of large non-green-ripe citrus, to mitigate the impact of data noise and efficiently calculate detection loss. Finally, a layer-based adaptive magnitude pruning strategy is employed to further eliminate redundant connections and parameters in the model. Targeting three types of citrus widely planted in Sichuan Province-navel orange, Ehime Jelly orange, and Harumi tangerine-YOLOC-tiny achieves an impressive mean average precision (mAP) of 83.0%, surpassing most other state-of-the-art (SOTA) detectors in the same class. Compared with YOLOv7 and YOLOv8x, its mAP improved by 1.7% and 1.9%, respectively, with a parameter count of only 4.2M. In picking robot deployment applications, YOLOC-tiny attains an accuracy of 92.8% at a rate of 59 frames per second. This study provides a theoretical foundation and technical reference for upgrading and optimizing low-computing-power ground-based robots, such as those used for fruit picking and orchard inspection.

Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data.

Parkinson's disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals' phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.

A prefrontal-habenular circuitry regulates social fear behaviour.

The medial prefrontal cortex (mPFC) has been implicated in the pathophysiology of social impairments including social fear. However, the precise subcortical partners that mediate mPFC dysfunction on social fear behaviour have not been identified. Employing a social fear conditioning paradigm, we induced robust social fear in mice and found that the lateral habenula (LHb) neurons and LHb-projecting mPFC neurons are synchronously activated during social fear expression. Moreover, optogenetic inhibition of the mPFC-LHb projection significantly reduced social fear responses. Importantly, consistent with animal studies, we observed an elevated prefrontal-habenular functional connectivity in subclinical individuals with higher social anxiety characterized by heightened social fear. These results unravel a crucial role of the prefrontal-habenular circuitry in social fear regulation and suggest that this pathway could serve as a potential target for the treatment of social fear symptom often observed in many psychiatric disorders.

Real-World Effectiveness of Nirmatrelvir in Protecting Long COVID for Outpatient Adult Patients - A Large-Scale Observational Cohort Study from the RECOVER Initiative.

Paxlovid has been approved for use in patients who are at high risk for severe acute COVID-19 illness. Evidence regarding whether Paxlovid protects against Post-Acute Sequelae of SARS-CoV-2 infection (PASC), or Long COVID, is mixed in high-risk patients and lacking in low-risk patients. With a target trial emulation framework, we evaluated the association of Paxlovid treatment within 5 days of SARS-CoV-2 infection with incident Long COVID and hospitalization or death from any cause in the post-acute period (30-180 days after infection) using electronic health records from the Patient-Centered Clinical Research Networks (PCORnet) RECOVER repository. The study population included 497,499 SARS-CoV-2 positive patients between March 1, 2022, to February 1, 2023, and among which 165,256 were treated with Paxlovid within 5 days since infection and 307,922 were not treated with Paxlovid or other COVID-19 treatments. Compared with the non-treated group, Paxlovid treatment was associated with reduced risk of Long COVID with a Hazard Ratio (HR) of 0.88 (95% CI, 0.87 to 0.89) and absolute risk reduction of 2.99 events per 100 persons (95% CI, 2.65 to 3.32). Paxlovid treatment was associated with reduced risk of all-cause death (HR, 0.53, 95% CI 0.46 to 0.60; risk reduction 0.23 events per 100 persons, 95% CI 0.19 to 0.28) and hospitalization (HR, 0.70, 95% CI 0.68 to 0.73; risk reduction 2.37 events per 100 persons, 95% CI 2.19 to 2.56) in the post-acute phase. For those without documented risk factors, the associations (HR, 1.03, 95% CI 0.95 to 1.11; risk increase 0.80 events per 100 persons, 95% CI -0.84 to 2.45) were inconclusive. Overall, high-risk, nonhospitalized adult patients with COVID-19 who were treated with Paxlovid within 5 days of SARS-CoV-2 infection had a lower risk of Long COVID and all-cause hospitalization or death in the post-acute period. However, Long COVID risk reduction with Paxlovid was not observed in low-risk patients.

Genome assembly of redclaw crayfish (Cherax quadricarinatus) provides insights into its immune adaptation and hypoxia tolerance.

BACKGROUND: The introduction of non-native species is a primary driver of biodiversity loss in freshwater ecosystems. The redclaw crayfish (Cherax quadricarinatus) is a freshwater species that exhibits tolerance to hypoxic stresses, fluctuating temperatures, high ammonia concentration. These hardy physiological characteristics make C. quadricarinatus a popular aquaculture species and a potential invasive species that can negatively impact tropical and subtropical ecosystems. Investigating the genomic basis of environmental tolerances and immune adaptation in C. quadricarinatus will facilitate the development of management strategies of this potential invasive species. RESULTS: We constructed a chromosome-level genome of C. quadricarinatus by integrating Nanopore and PacBio techniques. Comparative genomic analysis suggested that transposable elements and tandem repeats drove genome size evolution in decapod crustaceans. The expansion of nine immune-related gene families contributed to the disease resistance of C. quadricarinatus. Three hypoxia-related genes (KDM3A, KDM5A, HMOX2) were identified as being subjected to positive selection in C. quadricarinatus. Additionally, in vivo analysis revealed that upregulating KDM5A was crucial for hypoxic response in C. quadricarinatus. Knockdown of KDM5A impaired hypoxia tolerance in this species. CONCLUSIONS: Our results provide the genomic basis for hypoxic tolerance and immune adaptation in C. quadricarinatus, facilitating the management of this potential invasive species. Additionally, in vivo analysis in C. quadricarinatus suggests that the role of KDM5A in the hypoxic response of animals is complex.

SANTO: a coarse-to-fine alignment and stitching method for spatial omics.

With the flourishing of spatial omics technologies, alignment and stitching of slices becomes indispensable to decipher a holistic view of 3D molecular profile. However, existing alignment and stitching methods are unpractical to process large-scale and image-based spatial omics dataset due to extreme time consumption and unsatisfactory accuracy. Here we propose SANTO, a coarse-to-fine method targeting alignment and stitching tasks for spatial omics. SANTO firstly rapidly supplies reasonable spatial positions of two slices and identifies the overlap region. Then, SANTO refines the positions of two slices by considering spatial and omics patterns. Comprehensive experiments demonstrate the superior performance of SANTO over existing methods. Specifically, SANTO stitches cross-platform slices for breast cancer samples, enabling integration of complementary features to synergistically explore tumor microenvironment. SANTO is then applied to 3D-to-3D spatiotemporal alignment to study development of mouse embryo. Furthermore, SANTO enables cross-modality alignment of spatial transcriptomic and epigenomic data to understand complementary interactions.

HELM-GPT: de novo macrocyclic peptide design using generative pre-trained transformer.

MOTIVATION: Macrocyclic peptides hold great promise as therapeutics targeting intracellular proteins. This stems from their remarkable ability to bind flat protein surfaces with high affinity and specificity while potentially traversing the cell membrane. Research has already explored their use in developing inhibitors for intracellular proteins, such as KRAS, a well-known driver in various cancers. However, computational approaches for de novo macrocyclic peptide design remain largely unexplored. RESULTS: Here, we introduce HELM-GPT, a novel method that combines the strength of the hierarchical editing language for macromolecules (HELM) representation and generative pre-trained transformer (GPT) for de novo macrocyclic peptide design. Through reinforcement learning (RL), our experiments demonstrate that HELM-GPT has the ability to generate valid macrocyclic peptides and optimize their properties. Furthermore, we introduce a contrastive preference loss during the RL process, further enhanced the optimization performance. Finally, to co-optimize peptide permeability and KRAS binding affinity, we propose a step-by-step optimization strategy, demonstrating its effectiveness in generating molecules fulfilling both criteria. In conclusion, the HELM-GPT method can be used to identify novel macrocyclic peptides to target intracellular proteins. AVAILABILITY AND IMPLEMENTATION: The code and data of HELM-GPT are freely available on GitHub (https://github.com/charlesxu90/helm-gpt).

A facile synthesis of water-soluble copper nanoclusters as label-free fluorescent probes for rapid, selective and sensitive determination of alizarin red.

Copper nanoclusters (FA@CuNCs) emitting blue fluorescence were successfully developed via a one-pot technique. In this method, the copper chloride, folic acid and hydrazine hydrate were applied as a precursor, protective agent and reducing agent, respectively. The absorption, fluorescence excitation and emission spectra of FA@CuNCs were carried out by using ultraviolet-visible and fluorescence spectrometry, respectively. The morphology, particle size, functional groups, oxidation states of elements of FA@CuNCs were discussed via using transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS). The stability of FA@CuNCs was studied under various conditions, such as storage time at 25 ℃, ultraviolet radiation time, sodium chloride solutione and pH. The FA@CuNCs displayed blue fluorescence under the excitation wavelength of 361 nm, and the fluorescence quantum yield was 7.45 %. As a result of the inner filter effect, the alizarin red could significantly weaken the blue fluorescence of FA@CuNCs. Thus, the as-prepared FA@CuNCs could be utilized as fluorescence nanosensors for the trace determination of alizarin red. This platform suggested an excellent linear range for alizarin red varying from 0.5 to 200 µM with a fitting coefficient of 0.9955. The detection limit was calculated to be 0.064 µM in the light of the 3b/k (b and k refer to the standard deviation and slope of fitted curve, respectively). Furthermore, the as-developed FA@CuNCs could be used to detect the alizarin red in real samples and for the sensing of temperature.

Evaluating the necessity of lymph node sampling in lung adenocarcinoma with ground glass opacities.

BACKGROUND: Ground glass opacity is observed frequently in the early stages of lung adenocarcinoma and is associated with a favorable prognosis and a low incidence of lymph node metastasis. However, the necessity of lymph node sampling in these patients is questionable, although current guidelines still recommend it. METHODS: Radiologic and clinical data were retrospectively collected and analyzed for 2,298 patients with lung cancer who underwent surgical resection for lesions ≤15 mm during 2022. Based on the consolidation tumor ratios, patients were categorized into 4 groups (pure ground glass opacity, ground glass opacity-predominant, solid-predominant, and pure solid). The incidence of lymph node metastasis in each group was examined. RESULTS: A total of 2,298 patients with a median age of 54.0 years were enrolled in this study. Tumors were categorized into 4 types: 1,427 (62.1%) were pure ground glass opacity, which constituted the majority, while 421 (18.3%) were ground glass opacity-predominant, 330 (14.4%) were solid-predominant, and the remaining 120 (5.2%) were pure solid. Significant positive correlations were revealed between the consolidation tumor ratio group and pathologic grade (P < .001, ρ = 0.307), T stage (P < .001, ρ = 0.270), and N stage (P < .001, ρ = 0.105). Among the included cases, only 7 cases with metastasis were in the pure solid group. Within this group, 113 cases (94.2%) were N0, 5 cases (4.2%) were N1, and 2 cases (1.7%) were N2. CONCLUSION: Lymph node metastasis exclusively occurred in the pure solid group, suggesting that for nodules <15 mm, lymph node sampling may be crucial for pure solid nodules but less so for those containing ground glass opacities.

Purification and Structural Analyses of Sulfated Polysaccharides from Low-Value Sea Cucumber Stichopus naso and Anticoagulant Activities of Its Oligosaccharides.

Three polysaccharides (SnNG, SnFS and SnFG) were purified from the body wall of Stichopus naso. The physicochemical properties, including monosaccharide composition, molecular weight, sulfate content, and optical rotation, were analyzed, confirming that SnFS and SnFG are sulfated polysaccharides commonly found in sea cucumbers. The highly regular structure {3)-L-Fuc2S-(α1,}n of SnFS was determined via a detailed NMR analysis of its oxidative degradation product. By employing ß-elimination depolymerization of SnFG, tri-, penta-, octa-, hendeca-, tetradeca-, and heptadeca-saccharides were obtained from the low-molecular-weight product. Their well-defined structures confirmed that SnFG possessed the backbone of {D-GalNAc4S6S-ß(1,4)-D-GlcA}, and each GlcA residue was branched with Fuc2S4S. SnFS and SnFG are both structurally the simplest version of natural fucan sulfate and fucosylated glycosaminoglycan, facilitating the application of low-value sea cucumbers S. naso. Bioactivity assays showed that SnFG and its derived oligosaccharides exhibited potent anticoagulation and intrinsic factor Xase (iXase) inhibition. Moreover, a comparative analysis with the series of oligosaccharides solely branched with Fuc3S4S showed that in oligosaccharides with lower degrees of polymerization, such as octasaccharides, Fuc2S4S led to a greater increase in APTT prolongation and iXase inhibition. As the degree of polymerization increases, the influence from the sulfation pattern diminishes, until it is overshadowed by the effects of molecular weight.