Counterion Blockade in a Heterogeneously Charged Single-File Water Channel.

The Possion-Nernst-Planck theories fail to describe the ionic transport in Angstrom channels, where conduction deviates from Ohm's law, which is attributed to the dehydration/self-energy barrier and dissociation of Bjerrum ion pairs in previous work. Here, we find that the cations can be strongly bound to the surface charge, which blocks the ionic transport in a single-file water channel, causing nonlinear current-voltage curves. The presence of free ions significantly increases the probability of bound ions being released, resulting in an ionic current. We find that ionic conduction gradually becomes Ohmic as the surface charge density increases, but the conduction amplitude decreases due to the increased friction from the bound ions. We rationalize the ionic transport using 1D Kramers' escape theory framework, which describes nonlinear ionic current and the impact of surface charge density on the I-V curves. Our results show that the strong Coulomb interaction between the counterion and surface charge may cause ionic blockade in Angstrom channels.

Two-dimensional nanomaterials: A multifunctional approach for robust for diabetic wound repair.

Diabetic wounds pose a clinical challenge due to persistent inflammation, severe bacterial infections, inadequate vascularization, and pronounced oxidative stress. Current therapeutic modalities fail to provide satisfactory outcomes in managing these conditions, resulting in considerable patient distress. Two-dimensional nanomaterials (2DNMs), characterized by their unique nanosheet structures, expansive surface areas, and remarkable physicochemical properties, have garnered considerable attention for their potential in therapeutic applications. Emerging 2DNMs can be loaded with various pharmacological agents, including small molecules, metal ions, and liposomes. Moreover, they can be integrated with various biomaterials such as hydrogels, microneedles, and microspheres, thus demonstrating unprecedented advantages in expediting the healing process of diabetic wounds. Moreover, 2DNMs exhibit exceptional performance characteristics, including high biocompatibility, effective antimicrobial properties, optimal phototherapeutic effects, and enhanced electrostimulation capabilities. These properties enable them to modulate the wound microenvironment, leading to widespread application in tissue repair with remarkable outcomes. This review delineates several emerging 2DNMs, such as graphene and its derivatives, black phosphorus, MXenes, and transition metal dichalcogenides, in the context of diabetic wound repair. Furthermore, it elucidates the translational challenges and future perspectives of 2DNMs in wound healing treatments. Overall, 2DNMs present a highly promising strategy for ameliorating diabetic wounds, thus providing novel avenues for diagnostic and therapeutic strategies in diabetic wound management.

Association of ambient air pollutant mixtures with IVF/ICSI-ET clinical pregnancy rates during critical exposure periods.

STUDY QUESTION: Does exposure to a mixture of ambient air pollutants during specific exposure periods influence clinical pregnancy rates in women undergoing IVF/ICSI-embryo transfer (ET) cycles? SUMMARY ANSWER: The specific exposure period from ET to the serum hCG test was identified as a critical exposure window as exposure to sulfur dioxide (SO2) or a combination of air pollutants was associated with a decreased likelihood of clinical pregnancy. WHAT IS KNOWN ALREADY: Exposure to a single pollutant may impact pregnancy outcomes in women undergoing ART. However, in daily life, individuals often encounter mixed pollution, and limited research exists on the effects of mixed air pollutants and the specific exposure periods. STUDY DESIGN SIZE DURATION: This retrospective cohort study involved infertile patients who underwent their initial IVF/ICSI-ET cycle at an assisted reproduction center between January 2020 and January 2023. Exclusions were applied for patients meeting specific criteria, such as no fresh ET, incomplete clinical and address information, residency outside the 17 cities in the Sichuan Basin, age over 45 years, use of donor semen, thin endometrium (<8 mm) and infertility factors unrelated to tubal or ovulation issues. In total, 5208 individuals were included in the study. PARTICIPANTS/MATERIALS SETTING METHODS: Daily average levels of six air pollutants (fine particulate matter (PM2.5), inhalable particulate matter (PM10), SO2, nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3)) were acquired from air quality monitoring stations. The cumulative average levels of various pollutants were determined using the inverse distance weighting (IDW) method across four distinct exposure periods (Period 1: 90 days before oocyte retrieval; Period 2: oocyte retrieval to ET; Period 3: ET to serum hCG test; Period 4: 90 days before oocyte retrieval to serum hCG test). Single-pollutant logistic regression, two-pollutant logistic regression, Quantile g-computation (QG-C) regression, and Bayesian kernel machine regression (BKMR) were employed to evaluate the influence of pollutants on clinical pregnancy rates. Stratified analyses were executed to discern potentially vulnerable populations. MAIN RESULTS AND THE ROLE OF CHANCE: The clinical pregnancy rate for participants during the study period was 54.53%. Single-pollutant logistic models indicated that for PM2.5 during specific exposure Period 1 (adjusted odds ratio [aOR] = 0.83, 95% CI: 0.70-0.99) and specific exposure Period 4 (aOR = 0.83, 95% CI: 0.69-0.98), and SO2 in specific exposure Period 3 (aOR = 0.92, 95% CI: 0.86-0.99), each interquartile range (IQR) increment exhibited an association with a decreased probability of clinical pregnancy. Consistent results were observed with dual air pollution models. In the multi-pollution analysis, QG-C indicated a 12% reduction in clinical pregnancy rates per IQR increment of mixed pollutants during specific exposure Period 3 (aOR = 0.89, 95% CI: 0.79-0.99). Among these pollutants, SO2 (33.40%) and NO2 (33.40%) contributed the most to the negative effects. The results from BKMR and QG-C were consistent. Stratified analysis revealed increased susceptibility to ambient air pollution among individuals who underwent transfer of two embryos, those with BMI ≥ 24 kg/m2 and those under 35 years old. LIMITATIONS REASONS FOR CAUTION: Caution was advised in interpreting the results due to the retrospective nature of the study, which was prone to selection bias from non-random sampling. Smoking and alcohol, known confounding factors in IVF/ICSI-ET, were not accounted for. Only successful cycles that reached the hCG test were included, excluding a few patients who did not reach the ET stage. While IDW was used to estimate pollutant concentrations at residential addresses, data on participants' work locations and activity patterns were not collected, potentially affecting the accuracy of exposure prediction. WIDER IMPLICATIONS OF THE FINDINGS: Exposure to a mixture of pollutants, spanning from ET to the serum hCG test (Period 3), appeared to be correlated with a diminished probability of achieving clinical pregnancy. This association suggested a potential impact of mixed pollutants on the interaction between embryos and the endometrium, as well as embryo implantation during this critical stage, potentially contributing to clinical pregnancy failure. This underscored the importance of providing women undergoing ART with comprehensive information to comprehend the potential environmental influences and motivating them to adopt suitable protective measures when feasible, thereby mitigating potential adverse effects of contaminants on reproductive health. STUDY FUNDING/COMPETING INTERESTS: This work received support from the National Key Research and Development Program of China (No. 2023YFC2705900), the National Natural Science Foundation of China (Nos. 82171664, 81971391, 82171668), the Natural Science Foundation of Chongqing Municipality of China (Nos. CSTB2022NSCQ-LZX0062, CSTB2023TIAD-KPX0052) and the Foundation of State Key Laboratory of Ultrasound in Medicine and Engineering (No. 2021KFKT013). The authors report no conflicts of interest. TRIAL REGISTRATION NUMBER: N/A.

Comprehensive physicochemical indicators analysis and quality evaluation model construction for the post-harvest ripening rapeseeds.

Rapeseed (Brassica napus L.) is the second largest globally cultivated oil crop, but the effects of post-harvested ripening on rapeseed quality is unclear and unpredictable. This study reveals the relationship between post-harvest ripening periods (PHR) and physicochemical quality of different rapeseed cultivars using comprehensive physicochemical indicators analysis. The results indicate that PHR led to a gradual decrease in chlorophyll, carotenoid and moisture content but continually increased oil and total phenol content (TPC). Besides, 295 lipid molecules from 13 lipid subclasses were identified, revealing that the relative content of triacylglycerol (TG) was progressively increased while diacylglycerol (DG) demonstrated a consistent decline throughout the PHR. Correlation analysis, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were employed to construct and verify the comprehensive quality evaluation model for rapeseeds in PHR. This paper develops a comprehensive quality evaluation model for post-harvest ripening rapeseeds and advances the development of agricultural products.

PM2.5-mediated cardiovascular disease in aging: Cardiometabolic risks, molecular mechanisms and potential interventions.

Air pollution, particularly fine particulate matter (PM2.5) with <2.5 µm in diameter, is a major public health concern. Studies have consistently linked PM2.5 exposure to a heightened risk of cardiovascular diseases (CVDs) such as ischemic heart disease (IHD), heart failure (HF), and cardiac arrhythmias. Notably, individuals with pre-existing age-related cardiometabolic conditions appear more susceptible. However, the specific impact of PM2.5 on CVDs susceptibility in older adults remains unclear. Therefore, this review addresses this gap by discussing the factors that make the elderly more vulnerable to PM2.5-induced CVDs. Accordingly, we focused on physiological aging, increased susceptibility, cardiometabolic risk factors, CVDs, and biological mechanisms. This review concludes by examining potential interventions to reduce exposure and the adverse health effects of PM2.5 in the elderly population. The latter includes dietary modifications, medications, and exploration of the potential benefits of supplements. By comprehensively analyzing these factors, this review aims to provide a deeper understanding of the detrimental effects of PM2.5 on cardiovascular health in older adults. This knowledge can inform future research and guide strategies to protect vulnerable populations from the adverse effects of air pollution.

Sinonasal teratocarcinosarcoma involving the nasal cavity, unilateral paranasal sinuses, and intracranial invasion: A case report.

BACKGROUND: Sinonasal teratocarcinosarcoma (SNTCS) is a rare and highly invasive neoplasm originating from the nasal cavity and sinuses. Typically, it exhibits an invasive behavior towards adjacent structures; however, in exceptional instances, it may infiltrate the intracranial compartment. Due to the tumor's rarity and lack of distinctive features on computed tomography (CT) and magnetic resonance imaging (MRI) images, SNTCS is often misdiagnosed. CASE SUMMARY: In this study, we present a case of SNTCS in a 56-year-old patient who exhibited unexplained cognitive impairment before admission. CT and MRI scans revealed the presence of a mass in the right nasal cavity, with lesions extending to the right ethmoid sinus and right frontal region. Subsequently, the patient underwent pathological examination for confirmation and received surgical intervention to excise the tumor. The future advancement in our understanding of this disease will significantly contribute to the precise diagnosis and treatment of SNTCS. CONCLUSION: SNTCS is an exceptionally rare malignant tumor that originates from the nasal cavity and paranasal sinuses, presenting a diagnostic challenge due to its non-specific imaging findings. MRI accurately delineates the location, morphological characteristics, size, internal structure, extent of surrounding involvement, and metabolic information of the lesion. These aspects play a pivotal role in the precise localization and qualitative assessment of SNTCS. Nevertheless, a definitive diagnosis still requires a pathological biopsy.

Screen-Printed Electrodes as Low-Cost Sensors for Breast Cancer Biomarker Detection.

This review explores the emerging role of screen-printed electrodes (SPEs) in the detection of breast cancer biomarkers. We discuss the fundamental principles and fabrication techniques of SPEs, highlighting their adaptability and cost-effectiveness. The review examines various modification strategies, including nanomaterial incorporation, polymer coatings, and biomolecule immobilization, which enhance sensor performance. We analyze the application of SPEs in detecting protein, genetic, and metabolite biomarkers associated with breast cancer, presenting recent advancements and innovative approaches. The integration of SPEs with microfluidic systems and their potential in wearable devices for continuous monitoring are explored. While emphasizing the promising aspects of SPE-based biosensors, we also address current challenges in sensitivity, specificity, and real-world applicability. The review concludes by discussing future perspectives, including the potential for early screening and therapy monitoring, and the steps required for clinical implementation. This comprehensive overview aims to stimulate further research and development in SPE-based biosensors for improved breast cancer management.

Mesoporous metal-organic framework NH2-MIL-101(Cr) as an efficient photocatalyst for the epoxidation of styrene.

Oxidation of styrene is a key reaction in the synthesis of pharmaceuticals and fine chemicals, and therefore oxidizing styrene with selective, efficient, and recyclable heterogeneous catalysts is significant from an environmental and economic standpoint. In this study, we report the transition Cr-based metal-organic framework [NH2-MIL-101(Cr)] as a heterogeneous photocatalyst, which efficiently promotes styrene epoxidation using H2O2 as a green oxidant, achieving high conversion efficiency (98%) and excellent selectivity (82%) under ambient conditions. Radical detection and quenching experiments reveal that the superoxide radical anion (O2˙-) acts as an active oxygen species, selectively promoting the oxidation of styrene to its oxidized form. This work provides insight into the development of a sustainable and cost-effective method for producing styrene oxide.

Slow sound mode prediction and band structure calculation in 1D phononic crystal nanobeams using an artificial neural network.

Phononic crystals, which are artificial crystals formed by the periodic arrangement of materials with different elastic coefficients in space, can display modulated sound waves propagating within them. Similar to the natural crystals used in semiconductor research with electronic bandgaps, phononic crystals exhibit the characteristics of phononic bandgaps. A gap design can be utilized to create various resonant cavities, confining specific resonance modes within the defects of the structure. In studies on phononic crystals, phononic band structure diagrams are often used to investigate the variations in phononic bandgaps and elastic resonance modes. As the phononic band frequencies vary nonlinearly with the structural parameters, numerous calculations are required to analyze the gap or mode frequency shifts in phononic band structure diagrams. However, traditional calculation methods are time-consuming. Therefore, this study proposes the use of neural networks to replace the time-consuming calculation processes of traditional methods. Numerous band structure diagrams are initially obtained through the finite-element method and serve as the raw dataset, and a certain proportion of the data is randomly extracted from the dataset for neural network training. By treating each mode point in the band structure diagram as an independent data point, the training dataset for neural networks can be expanded from a small number to a large number of band structure diagrams. This study also introduces another network that effectively improves mode prediction accuracy by training neural networks to focus on specific modes. The proposed method effectively reduces the cost of repetitive calculations.

Beyond the Gut: The intratumoral microbiome's influence on tumorigenesis and treatment response.

The intratumoral microbiome (TM) refers to the microorganisms in the tumor tissues, including bacteria, fungi, viruses, and so on, and is distinct from the gut microbiome and circulating microbiota. TM is strongly associated with tumorigenesis, progression, metastasis, and response to therapy. This paper highlights the current status of TM. Tract sources, adjacent normal tissue, circulatory system, and concomitant tumor co-metastasis are the main origin of TM. The advanced techniques in TM analysis are comprehensively summarized. Besides, TM is involved in tumor progression through several mechanisms, including DNA damage, activation of oncogenic signaling pathways (phosphoinositide 3-kinase [PI3K], signal transducer and activator of transcription [STAT], WNT/ß-catenin, and extracellular regulated protein kinases [ERK]), influence of cytokines and induce inflammatory responses, and interaction with the tumor microenvironment (anti-tumor immunity, pro-tumor immunity, and microbial-derived metabolites). Moreover, promising directions of TM in tumor therapy include immunotherapy, chemotherapy, radiotherapy, the application of probiotics/prebiotics/synbiotics, fecal microbiome transplantation, engineered microbiota, phage therapy, and oncolytic virus therapy. The inherent challenges of clinical application are also summarized. This review provides a comprehensive landscape for analyzing TM, especially the TM-related mechanisms and TM-based treatment in cancer.

Novel therapeutic targets: bifidobacterium-mediated urea cycle regulation in colorectal cancer.

BACKGROUND AND PURPOSE: Colorectal cancer (CRC) is a widespread malignancy with a complex and not entirely elucidated pathogenesis. This study aims to explore the role of Bifidobacterium in the urea cycle (UC) and its influence on the progression of CRC, a topic not extensively studied previously. EXPERIMENTAL APPROACH: Utilizing both bioinformatics and experimental methodologies, this research involved analyzing bacterial abundance in CRC patients in comparison to healthy individuals. The study particularly focused on the abundance of BA. Additionally, transcriptomic data analysis and cellular experiments were conducted to investigate the impact of Bifidobacterium on ammonia metabolism and mitochondrial function, specifically examining its regulation of the key UC gene, ALB. KEY RESULTS: The analysis revealed a significant decrease in Bifidobacterium abundance in CRC patients. Furthermore, Bifidobacterium was found to suppress ammonia metabolism and induce mitochondrial dysfunction through the regulation of the ALB gene, which is essential in the context of UC. These impacts contributed to the suppression of CRC cell proliferation, a finding corroborated by animal experimental results. CONCLUSIONS AND IMPLICATIONS: This study elucidates the molecular mechanism by which Bifidobacterium impacts CRC progression, highlighting its role in regulating key metabolic pathways. These findings provide potential targets for novel therapeutic strategies in CRC treatment, emphasizing the importance of microbiota in cancer progression.

Analysis of surgical complexity and short-term prognostic indicators in NSCLC patients: neoadjuvant targeted therapy versus neoadjuvant chemoimmunotherapy.

Background: Neoadjuvant therapy improves survival benefits in patients with locally advanced non-small cell lung cancer but increases tissue density, presenting challenges for surgeons. Objectives: To compare the differences in surgical complexity and short-term prognostic outcomes between neoadjuvant targeted therapy (NTT) and neoadjuvant chemoimmunotherapy (NCI). Design/methods: This study enrolled 106 patients underwent curative surgery after neoadjuvant therapy between January 2020 and December 2023 at the National Cancer Center of China. Differences in surgical complexity and short-term prognostic outcomes between the two neoadjuvant therapy cohorts were evaluated. The pathological indicators such as pathological response rate and lymph node upstaging/downstaging were then analyzed. Results: In total, 33 patients underwent NTT and 73 underwent NCI preoperatively. Patients who received NTT showed a higher minimally invasive surgery rate (84.8% versus 53.4%, p < 0.01), shorter operative time (144 versus 184 min, p < 0.01), lower conversion rate (3.3% versus 17.8%, p = 0.03), less postoperative drainage (day 3: 140 versus 200 mL, p = 0.03), and lower incidence of postoperative complications including arrhythmias (6.1% versus 26%, p = 0.02). The pathological response rate in the NTT and NCI groups was 70% and 75%, respectively, with the latter group showing a higher complete pathological response rate. The two groups had no significant differences in major pathological response and lymph node pathological response rate. Conclusion: Patients who received NTT presented fewer surgical challenges for surgeons and had better surgical outcomes than those who received NCI therapy, with comparable pathological response rates between the two cohorts. Accordingly, NTT is the preferred induction regimen for patients harboring mutation status.

van der Waals-bonded graphene clusters enhance thermal conductivity of phase-change materials for advanced thermal energy management.

Organic phase-change materials possess immense application potential, but their low thermal conductivity (≤0.5 W m-1 K-1) severely limits the thermal energy charge/discharge rate, impeding their practical implementation in the field of advanced energy. While incorporating thermally conductive fillers into the phase-change matrix can address this issue, achieving a thermal conductivity exceeding 10 W m-1 K-1 at a filler content below 30 vol% remains challenging, attributed to the absence of a well-designed filler interface and structure. Herein, a strategy for developing planar graphene clusters and subsequently integrating them with phase-change microcapsules to fabricate composites using compression molding was demonstrated. The proposed graphene clusters are formed by closely aligned and overlapping graphene sheets that bond together through van der Waals forces, resulting in a significant decrease in junction thermal resistance within the composites. Combining this interface design with compression-induced construction of a highly oriented structure, the composites achieved a remarkable thermal conductivity of 103 W m-1 K-1 with ≈29 vol% filler addition, enhancing the thermal energy charge/discharge rate by over two orders of magnitude. Furthermore, we demonstrated that the composites possess the essential enthalpy values, competent strength, and ease of shaping, making them applicable across various domains of thermal energy management.

The efficacy and safety of anti-vascular endothelial growth factor combined with Ahmed glaucoma valve implantation in the treatment of neovascular glaucoma: a systematic review and meta-analysis.

Background: The intraocular injections of anti-vascular endothelial growth factor (anti-VEGF) demonstrates significant efficacy in inhibiting the formation of ocular neovascularization in neovascular glaucoma (NVG). Ahmed glaucoma valve implantation (AGVI) is extensively employed for the management of diverse glaucoma types. Objective: To further evaluate the efficacy and safety of anti-VEGF combined with AGVI in the treatment of neovascular glaucoma. Methods: A thorough search for randomized controlled trials (RCTs) was conducted across eight databases: PubMed, EMBASE, the Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang, SinoMed, and VIP. The search period was set from the inception of each database until March 2, 2024, to identify RCTs investigating the effectiveness and safety of combining AGVI with anti-VEGF therapy for NVG. We used the Cochrane Risk of Bias Assessment Tool to evaluate the quality of the literature and performed statistical analysis using Stata 15.0 software. Results: Fourteen RCTs were included in this study. Compared with AGVI alone, the combination of anti-VEGF drugs and AGVI can reduce postoperative intraocular pressure (IOP) at 1 week [WMD = -4.03, 95% CI (-5.73, -2.34), p < 0.001], 1 month [WMD = -5.39, 95% CI (-7.05, -3.74), p < 0.001], 3 months [WMD = -6.59, 95% CI (-7.85, -5.32), p < 0.001], 6 months [WMD = -4.99, 95% CI (-9.56, -0.43), p = 0.032], and more than 12 months [WMD = -3.86, 95% CI (-6.82, -0.90), p = 0.011], with a higher Effective rate [RR = 1.27, 95% CI (1.18, 1.37), p < 0.001], decreased incidence of postoperative hyphema [RR = 0.24, 95% CI (0.15, 0.39), p < 0.001], reduced use of postoperative antiglaucoma medications [WMD = -0.48, 95% CI (-0.61, -0.35), p < 0.001], and decreased aqueous humor VEGF levels [SMD = -2.84, 95% CI (-4.37, -1.31), p < 0.001]. Conclusion: In comparison to AGVI alone, the combination of AGVI with anti-VEGF therapy has better effects in reducing IOP at various time intervals, diminishing postoperative antiglaucoma medication requirements and reducing aqueous humor VEGF levels. Furthermore, it effectively minimizes the incidence of postoperative hyphema. Nevertheless, due to the variability in the quality of the trials included, further high-quality experiments will be required in the future to substantiate this conclusion. Systematic review registration: PROSPERO, identifier CRD42024519862, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024519862.

The distribution and key influential factors of antibiotic resistance genes in agricultural soils polluted by multiple heavy metals.

Due to anthropogenic activities such as mining, several agricultural soils are polluted by multiple heavy metals. However, it is still unclear whether multiple heavy metals could affect the distribution of antibiotic resistance genes (ARGs), and how metals affect ARGs. To understand ARGs' distribution in heavy metal-polluted soils, we chose soils contaminated by different types and contents of heavy metals to determine the ARGs' number and abundance through high-throughput quantitative real-time PCR (HT-qPCR) in this study. Additionally, the factors affecting ARGs' distribution, such as soil properties, mobile genetic genes (MGEs), and bacterial communities, were explored. The results demonstrated that the sampled soils were primarily contaminated by Cd, As, Pb, and Zn, and the pollution load index (PLI) values of these metals ranged from 1.3 to 2.7, indicating a low to moderate degree of heavy metal contamination. The number and abundance of ARGs ranged from 44 to 113 and from 2.74 × 107 copies/g to 1.07 × 108 copies/g, respectively. Besides, abundant MGEs in soils, ranging from 1.84 × 106 copies/g to 5.82 × 106 copies/g, were observed. The pathway analysis suggested that MGEs were the most important factor directly affecting ARG abundance (0.89). Notably, heavy metals also affected the ARG abundance. Proteobacteria and Actinobacteria, the main heavy metal tolerant bacteria, were found to be the main hosts of ARGs through network analysis. ARG-carrying pathogens (ACPs) in agricultural soils were found to carry MGEs, indicating a high risk of dissemination. This study provided important information for understanding the ARGs' fate and also the key factors affecting ARGs' spread in multiple heavy metal-contaminated soils.

Refractory COD removal from bio-treated paper wastewater using powdered activated coke adsorption technology with ozonation regeneration: Performance and molecular insights.

The present study employed powdered activated coke (PAC) for the adsorptive removal of refractory COD from the bio-treated paper wastewater (BTPW). The adsorption reached equilibrium after 3 h, resulting in a decrease in the COD concentration from 98.9 mg L-1 in BTPW to 42.6 mg L-1 when utilizing a PAC dosage of 5 g L-1. The dominant fractions of dissolved organic matter in BTPW were hydrophilic acids (HIA), hydrophilic neutrals (HIN), and hydrophobic acids (HOA), accounting for 48.8%, 34.2%, and 17.0% of the total dissolved organic carbon, respectively. Three fractions were all predominantly composed of humic/fulvic acid-like substances, while the HOA fraction exhibited highest susceptibility to adsorption by PAC, followed by the HIA and HIN fractions. FT-ICR MS data revealed PAC preferentially adsorbed the unsaturated and oxygen-rich substances containing more carboxyl groups. Additionally, the spent PAC was regenerated through ozonation and subsequently utilized in the adsorption cycles. The regeneration was successfully conducted under an ozone concentration of 1 mg L-1 for a duration of 10 min, and the regeneration efficiency remained about 87.0% even after undergoing five-cycle of adsorption-regeneration. The findings of this study demonstrate that PAC adsorption is a viable and efficacious treatment technology for efficiently removing refractory COD from BTPW.

Deep Learning-Based Model for Non-invasive Hemoglobin Estimation via Body Parts Images: A Retrospective Analysis and a Prospective Emergency Department Study.

Anemia is a significant global health issue, affecting over a billion people worldwide, according to the World Health Organization. Generally, the gold standard for diagnosing anemia relies on laboratory measurements of hemoglobin. To meet the need in clinical practice, physicians often rely on visual examination of specific areas, such as conjunctiva, to assess pallor. However, this method is subjective and relies on the physician's experience. Therefore, we proposed a deep learning prediction model based on three input images from different body parts, namely, conjunctiva, palm, and fingernail. By incorporating additional body part labels and employing a fusion attention mechanism, the model learns and enhances the salient features of each body part during training, enabling it to produce reliable results. Additionally, we employ a dual loss function that allows the regression model to benefit from well-established classification methods, thereby achieving stable handling of minority samples. We used a retrospective data set (EYES-DEFY-ANEMIA) to develop this model called Body-Part-Anemia Network (BPANet). The BPANet showed excellent performance in detecting anemia, with accuracy of 0.849 and an F1-score of 0.828. Our multi-body-part model has been validated on a prospectively collected data set of 101 patients in National Taiwan University Hospital. The prediction accuracy as well as F1-score can achieve as high as 0.716 and 0.788, respectively. To sum up, we have developed and validated a novel non-invasive hemoglobin prediction model based on image input from multiple body parts, with the potential of real-time use at home and in clinical settings.

Phillyrin and its metabolites exert antipyretic effects by targeting the NAD+ binding domain of GAPDH, MDH2 and IDH2.

BACKGROUND: Fever is one of the main pathophysiological reactions that occurs during the acute phase of various diseases. Excessive body temperature can lead to various adverse consequences such as brain tissue damage and abnormal immune responses. Phillyrin (Phr) is the main active ingredient in Forsythia suspensa (Thunb.) Vahl (Lian Qiao) and has antipyretic effects; however, its antipyretic mechanism of action remains unclear. PURPOSE: This study aimed to explore the antipyretic mechanisms of Phr and provide a new treatment plan for fever. METHODS: The antipyretic effects of Phr were evaluated using a mouse model of pneumonia fever. The main metabolites of Phr involved in its antipyretic function were identified using a mitochondrial temperature-sensitive probe. Further synthesis of the main metabolite, phillygenin (Phg), an alkynylated probe, was performed, and chemical proteomics was used to capture and analyze its direct target for antipyretic effects. The mechanism of action of Phg and its antipyretic targets was explored using metabolomics and various molecular biology methods. RESULTS: Phr showed significant antipyretic and anti-inflammatory effects in a mouse model of lipopolysaccharide-induced fever. Phg reversibly targeted the nicotinamide adenine dinucleotide (NAD+) binding domain of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), malate dehydrogenase 2 (MDH2), and isocitrate dehydrogenase 2 (IDH2) to inhibit their enzymatic activity. In-depth analysis of cellular metabolomics and mitochondrial stress testing indicated that inhibition of GAPDH, MDH2, and IDH2 enzyme activity by Phg led to a decrease in cellular energy supply and heat production regulated by glycolysis, tricarboxylic acid cycle, and oxidative phosphorylation signaling pathways. Phg specifically targeted macrophages and inhibited LPS-induced macrophage activation by downregulating GAPDH enzyme activity, thereby exerting anti-inflammatory effects. In vivo experiments also confirmed that the antipyretic effect of Phr in LPS-induced fever model mice was related to its main metabolites, Phg and Phg-sulfonate (Phg-S), which directly targeted the NAD+ binding domain of GAPDH, IDH2, and MDH2, inhibiting the activity of these enzymes, thereby reducing energy supply and regulating febrile-related inflammatory factors. CONCLUSION: This study reported for the first time that the antipyretic effect of Phr is produced by targeting GAPDH, IDH2, and MDH2 to regulate energy supply and febrile-related inflammatory factors through its main metabolites Phg and Phg-S. This study not only provides potential drugs for fever treatment but also provides new ideas for improving clinical fever treatment plans.

Accelerating Global Search of Large-Sized Silver Clusters Using Cluster Graph Attention Network.

Great efforts have been devoted to understanding the stability and reactivity of silver clusters, which usually depend on geometric structures, electronic configuration, and cluster size. Despite the fact that the jellium model and Wulff construction rule have successfully rationalized the stable clusters with "magic number" behavior, some experiments imply that silver clusters with 48 valence electrons also possess puzzling enhanced stability. In this work, using a recently developed deep learning technology, i.e., cluster graph attention network (CGANet), combined with a homemade comprehensive genetic algorithm (CGA) program, we searched the global minimum (GM) structures of Agn (n = 30-60) clusters with graphics processing unit acceleration, whose efficiency is about 2 orders of magnitude higher than that of the conventional density functional theory (DFT) calculations. GM structures and some representative isomers are reported at each size, revealing the competitive structural patterns based on truncated octahedra and icosahedra as well as the icosahedra-based layer-by-layer growth mode of large-sized Ag clusters. Most importantly, the size-dependent evolution behavior of structural and electronic properties of Agn (n = 30-60) clusters can successfully explain the observed stability at Ag48. Therefore, CGANet provides a powerful tool for rapidly exploring the potential energy surface of atoms with an accuracy comparable to that of DFT.

Puerarin Alleviates Blood Pressure via Inhibition of ROS/TLR4/NLRP3 Inflammasome Signaling Pathway in the Hypothalamic Paraventricular Nucleus of Salt-Induced Prehypertensive Rats.

BACKGROUND: Puerarin is an isoflavone compound isolated from the roots of a leguminous plant, the wild kudzu. Various functional activities of this compound in multiple diseases have been reported. However, the effect and mechanism of puerarin in improving blood pressure remain non-elucidated. PURPOSE: The current study was designed to assess the preventive effects of puerarin on the onset and progression of hypertension and to verify the hypothesis that puerarin alleviates blood pressure by inhibiting the ROS/TLR4/NLRP3 inflammasome signaling pathway in the hypothalamic paraventricular nucleus (PVN) of salt-induced prehypertensive rats. METHODS: Male Dahl salt-sensitive rats were fed low NaCl salt (3% in drinking water) for the control (NS) group or 8% (HS) to induce prehypertension. Each batch was divided into two group and treated by bilateral PVN microinjection with either artificial cerebrospinal fluid or puerarin through a micro-osmotic pump for 6 weeks. The mean arterial pressure (MAP) was recorded, and samples were collected and analyzed. RESULTS: We concluded that puerarin significantly prevented the elevation of blood pressure and effectively alleviated the increase in heart rate caused by high salt. Norepinephrine (NE) in the plasma of salt-induced prehypertensive rats also decreased upon puerarin chronic infusion. Additionally, analysis of the PVN sample revealed that puerarin pretreatment decreased the positive cells and gene level of TLR4 (Toll-like receptor 4), NLRP3, Caspase-1 p10, NOX2, MyD88, NOX4, and proinflammatory cytokines in the PVN. Puerarin pretreatment also decreased NF-κBp65 activity, inhibited oxidative stress, and alleviated inflammatory responses in the PVN. CONCLUSION: We conclude that puerarin alleviated blood pressure via inhibition of the ROS/TLR4/NLRP3 inflammasome signaling pathway in the PVN, suggesting the therapeutic potential of puerarin in the prevention of hypertension.