Accurate patient mortality prediction is crucial in the emergency department (ED) to improve emergency healthcare services. Current prediction models are limited in both accuracy and practicality, particularly in identifying high-risk patients early. Machine Learning is deeply affected by data quality because mortality samples are significantly fewer than survival samples. This study aimed to achieve balanced and better accuracy of patient mortality prediction and evaluate the effectiveness of data balancing methods. This study analyzed 2,437,341 non-traumatic adult ED visit records collected between 2008 and 2016 from five medical centers in Taiwan, including four mortality timeframes: death within 24, 72, and 168 h, and final death, and evaluated three data balancing methods: Random Under Sampling (RUS), Synthesized Minority Oversampling Technique (SMOTE), and Random Over Sampling (ROS). We adopted Random Forest (RF), AdaBoost (ADA), XG Boost (XGB). Logistic Regression (LR) is the meta learner for these models. Besides, we performed feature importance analysis based on RF, ADA, AdaBoost with BootStrap (ADA-BS), and Information Gain (IG). Our model with XGB achieved the best AUROC, 91.41%, which is better than 90.2% in the previous study by Wu et al. using the same dataset in 168-hour mortality timeframe. Our True Positive Rate (TPR) and True Negative Rate (TNR) are 79.88% and 86.73%, which are more balanced than 25% and 100% in the previous study. ROS achieves the better results than RUS and SMOTE and becomes our primary data balancing method. While adopting XGB in 24-hour mortality timeframes, ROS achieved the best AUROC, 93.72%, RUS achieved 93.61% and SMOTE achieved 91.73%. Compared with the previous study by Lin et al., the feature importance analysis shows our balanced dataset has better feature importance impacts, especially for the "Age" and "Triage" features. Our method achieves better AUROC than the previous study, especially in the long challenging death-hour mortality timeframe with XGB and ROS. Our method achieves balanced TPR and TNR, which are more practical than AUROC. Besides, feature importance analysis shows our balanced dataset has better feature importance impacts.
Plants face significant threats from pathogens while chemical pesticides remain the primary method for disease control. However, excessive use of chemical pesticides has led to increased pathogen resistance and environmental hazards, highlighting the urgent need for sustainable alternatives such as plant immune priming agents. Among these, levan have shown great potential compared to commercial priming agents, but their high degree of polymerization (DP) results in low solubility. To address this, we synthesized levan-derived oligosaccharides (LOS) with reduced DP. However, if LOS could induce plant immunity and what's the priming mechanism remain unclear. This study evaluated the effects in foliar applications on melon (Cucumis melo L.) and watermelon (Citrullus lanatus Thunb.), focusing on two pathogens, Botrytis cinerea (B. cinerea) and Phytophthora capsica (P. capsica). While LOS did not significantly reduce lesion area caused by B. cinerea in either crop, it reduced the lesion area caused by P. capsica by more than 65% in melons and watermelons. LOS also decreased disease severity by increasing the proportion of mild lesions (grades 1-2) and reducing the proportion of severe lesions (grades 3-4). Compared to CK, foliar application of LOS to single-leaf melons and watermelons did not significantly alter lesion area of untreated leaves, but it did significantly reduce the proportion of severe disease symptoms. Besides, LOS showed efficacy across multiple melon and watermelon cultivars while also demonstrated better immune effects compared to commercially available elicitors. Although LOS did not significantly improve melon quality compared to CK, it significantly increased the soluble solids content in watermelon fruit by 16%. LOS spraying promoted reactive oxygen species production, with H₂O₂ levels increasing 4.8-fold in melons and 44.5% in watermelons at 72 h. Physiological analysis revealed significant enhancement in the activity of antioxidant enzymes, such as catalase, peroxidase, and polyphenol oxidase in both crops. Besides, lignin content remained elevated in both melon types compared to CK, enhancing the plant's physical defense capabilities. Furthermore, gene expression analysis showed upregulation of several immunity-related genes (RBOHD, PR1, PAL, NPR1), indicating activation of the salicylic acid and jasmonic acid signaling pathways. These results suggest that LOS, as a broad-spectrum priming agent, enhances disease resistance in watermelons and melons, making it a promising sustainable solution for plant disease management.
Driven by rising patient awareness and treatment expectations, implant dentistry has advanced rapidly, increasing the demand for educators to deliver well-structured implant dentistry curricula. However, research on the efficacy of clinical probation within undergraduate dental education remains limited. In this study, we aimed to compare the impact of online mode with offline mode of clinical probation on students' knowledge acquisition and self-reported clinical abilities. A total of 150 fourth-year undergraduate dental students, comprising 50 students each from Grade 2017 to Grade 2019, were enrolled. Students from Grade 2017 (Group A) received conventional theoretical lectures only. The Grade 2018 (Group B) completed online clinical probation besides the theoretical lectures. Students from Grade 2019 (Group C) participated in offline clinical probation alongside the theoretical lectures. The results of different teaching approaches were evaluated through an online questionnaire and closed-book final exam. Overall, clinical probation significantly enhanced students' satisfaction levels, class engagement, and willingness to become implantologists (p < 0.05). Further analysis of favourable modes of clinical probation revealed that the offline mode could effectively promote class engagement, student-teacher interaction, and critical thinking ability. An early development of medical humanistic spirit was also seen in Group C students (p < 0.05). Final examination results showed a drastic improvement in academic performance for students in Group C (p < 0.05). Offline clinical probation in implant dentistry curriculum strengthened undergraduates' professional knowledge and prepared them for future clinical practice, thereby bridging the gap between theoretical knowledge and clinical practice.
Eyesight/vision is important of all five senses as it accounts for about 80% of the function of all the senses combined. Hence, visual impairment leads to a restriction in all areas of life and, in particular, VRQOL by reducing activities associated with participation in society and religion, mobility, recreation, daily living, and intense visual tasks. An institution-based cross-sectional analytical study was conducted from March 2024 to June 2024 involving 210 participants. NEI-VFQ-25 questionnaire was explained in their vernacular language by the interviewer. The scoring was given according to validated scoring algorithm for the questionnaire. The overall mean VRQOL score was low (52.1 ± 16.4) and the poor VRQOL was significantly associated with blindness. The subscale score was highest for colour vision (78.3 ± 22.1), followed by ocular pain (66.8 ± 23.4). The QOL was worst in the near activities subscale (37.2 ± 22.5) and general vision (38.6 ± 12.9). VRQOL was significantly associated with age and level of education. The association between VRQOL and gender, area of residence, status of employment, cause of visual impairment, and systemic comorbidities was statically insignificant in our study. Older age people and those with lower levels of literacy have significantly affected VRQOL. The common causes of visual impairment, such as cataract, are avoidable causes and can be treated to improve the VRQOL. The eye care professionals should assess the VRQOL in almost all patients besides visual acuity so that early intervention can be planned to improve the overall quality of life.
Sulfur(VI) fluorides based on sulfur(VI) fluoride exchange (SuFEx) chemistry have demonstrated their unique versatility and high efficiency in the field of medicinal chemistry. Acting as both covalent and hydrogen bond donors, the novel N-CF2H sulfamoyl fluoride will enhance the binding strength between drugs and receptors in organism, thereby injecting new vitality into the research of targeted drugs. Herein, we report the two-step synthesis of N-CF2H sulfamoyl fluorides from primary amines via successive fluorosulfonylation and insertion of difluorocarbene. This method shows broad scope, provides a platform for rapidly generating N-CF2H sulfamoyl fluorides by virtue of the diversity and availability of amines. The stability of N-CF2H sulfamoyl fluorides was tested in aqueous environment at different pH, showing that most compounds remained >95% intact for 72 h. As a novel SuFEx building block, N-CF2H sulfamoyl fluoride shows chemoselectivity toward phenol and does not react with amines and alcohols. Besides, N-CF2H sulfamoyl fluorides were subjected to debenzylation and amide-bond-formation reactions to generate peptides, Sitagliptin derivative and bioactive alkylamine. Finally, N-CF2H sulfamoyl fluoride underwent successful F-18 labeling. With the reported syntheses, we believe that N-CF2H sulfamoyl fluoride will soon be practically applied in drugs, covalent targeted radioligand, F-18 PET tracers, electrolyte in general.
In this study, 20 amino acids were utilized both as reducing and capping agents in a one-pot green synthesis of gold nanoparticles (GNPs) to be used in sensor applications for water, environment, and food monitoring. Tyrosine, tryptophan, valine, serine, phenylalanine, arginine, glutamic acid, and cysteine proved to be more suitable under the tested conditions, compared to the other amino acids, considering their colloidal stability. Amino acid-capped GNPs (AAGNPs) were then characterized in terms of absorbance spectrum, size, zeta potential, polydispersity index, geometry, and atomic content. After characterization, synthesized AAGNPs were utilized in sensory applications for Cyanide (CN-) and heavy metal (Al3+, Cu2+, and Fe3+) detection. The synthesized AAGNPs exhibited promising CN- detection capability that is comparable to conventionally synthesized GNPs via the Turkevich method. Besides, ArgGNPs, GluGNPs, and CysGNPs exhibited distinct sensing behaviors, reflecting differences in surface chemistry and interaction mechanisms. Sensing platforms that utilized PheGNPs, TrpGNPs, and TyrGNPs showed detection limits in the range of 0.3-0.7 μM. Amino acid capping of GNPs imparted differential recognition capability toward various heavy metal ions, where detection limits were calculated for various AAGNPs as 0.27 mM for Cu2+ with CysGNPs, 0.25 mM for Al3+ with GluGNPs, and 0.44 mM for Fe3+ with SerGNPs. This phenomenon shows that synthesizing and capping GNPs with various amino acids not only alters the size and geometry, but also the capability of AAGNPs as parts of recognition elements of sensor systems. This study highlights the potential of amino acid-mediated green synthesis as an environmentally friendly and versatile approach for developing functional nanomaterials with tunable sensing capabilities for pollutant detection.
The Shono oxidation stands as a premier electrochemical method for the α-C-H functionalization of amines. While glycine esters serve as ideal substrates with immense synthetic potential, their electrochemical derivatization has historically been restricted primarily to C-C and C-P bond formation. Herein, we report the first electrochemical strategy for the direct N-heteroarylation of α-C-H bonds in Gly-containing natural products, drug molecules, and peptides via a controllable anodic oxidation pathway under transition-metal-free conditions. At the same time, modified target product 3x exhibited good inhibitory activities toward the SKOV3 and MDA-MB-231 cell lines, with IC50 values of 9.94 ± 1.46 and 17.11 ± 3.67, respectively, far superior to the antitumor activities of unmodified substrate 1a (IC50 > 50). Therefore, besides synthetic applications, this method also provides new possibilities for discovering potentially bioactive molecules.
Morphine dependence is a major challenge worldwide. Besides, it has many adverse effects and suppresses its user's immune systems. Antigen-presenting cells (APCs) play a crucial role in activating T cells, thereby protecting us from various diseases. Therefore, understanding the influence of morphine on APC function may reveal its impact on immune modulation. Macrophages and dendritic cells (DCs) were cultured with morphine and assessed for antigen uptake, processing, and presentation using flow cytometry, confocal microscopy, and colony-forming units (CFU). TLR-4 involvement was examined through gene silencing and pharmacological inhibition. Autophagy markers (LC3, Atg7, Atg12) were analyzed by RT-qPCR and immunofluorescence. We observed that morphine inhibited antigen uptake, as evidenced by reduced phagocytosis of Mycobacterium tuberculosis (Mtb), E. coli, and other antigens. Further, it inhibited the killing of Mtb and E. coli and the processing of their antigens, as evidenced by reduced colocalization of LC3/LAMP1 with Mtb and E. coli. It prevented LC3 colocalization with the lysosomal marker LAMP1. Furthermore, morphine impaired antigen presentation, as evidenced by downregulation of MHC I, MHC II, CD80, and CD86, and reduced activation of CD4 T cells. Additionally, we observed that morphine exerted its mechanistic effects for immunosuppression through the TLR-4/NF-ĸB and autophagy pathways. This study identifies a mechanism by which morphine suppresses immune function by impairing antigen uptake, processing, and presentation in antigen-presenting cells through TLR-4-dependent autophagy pathways. These findings provide important insights into opioid-induced immunosuppression and have direct clinical relevance for the use of morphine in immunocompromised individuals.
BackgroundIntervertebral disc degeneration (IVDD) is a prevalent musculoskeletal condition that affects the spine, particularly in the lumbar region and induces low back pain. Tuina therapy has been widely utilized to alleviate low back pain for a long time. However, the specific mechanism underlying this effect of Tuina therapy on IVDD remains unclear.MethodsThe rat IVDD model was established by puncturing caudal vertebrae. Magnetic resonance imaging, Hematoxylin and eosin staining, and Safranin O staining were operated to assess histological changes. RT-qPCR and Western blot were carried out to measure mRNA and protein levels, respectively. Prussian Blue Staining and an iron assay kit were utilized to measure iron content in NP tissues.ResultsThe chaotic fibrous tissues, loss of NP tissues and cartilaginous components were observed in IVDD rats, and these pathological changes were alleviated by Tuina therapy. Besides, the mRNA and protein levels of inflammatory factors (TNF-alpha, IL-1beta, and IL-6) were significantly upregulated in IVDD group compared to sham group, and Tuina therapy reduced the release of these inflammatory factors. Moreover, the increased content of iron ion in IVDD rats was also reduced by Tuina therapy. Furthermore, the upregulation of ACSL4 protein, the downregulation of GPX and FTH proteins in IVDD groups were reversed by Tuina therapy.ConclusionsTuina therapy prevented IVDD aggravation by suppressing inflammatory response and ferroptosis in rat model.
Mustard (Brassica alba L.) oil is widely used edible oil in the Indian subcontinent. Its use is restricted in many countries because of the presence of some unsaturated fatty acids (USFA) such as erucic acid that are responsible for myocardial lipidosis and heart disease. Deficiency of Zn in plants indirectly affects in maintaining the ratio of SFA (saturated fatty acid) and USFA in mustard oil. In this work, mustard seeds, submerged in ZnSO4-H2O solution treated with multi-tube air bubble discharge plasma jet for 10-, 20-, 30, and 40 min under the effect of magnetic field. Treated and control seeds were sown in the field. In addition, plasma processed water (PPW) was applied to the plants developed from the plasma treated seeds. Different growth characteristics, enzymatic activities, nutritional composition and fatty acids were studied. The findings show that the plant length (PL), stem diameter (SD), dry weight (DW), antioxidant enzymes, nutritional composition and yield were improved. Several fatty acids including 9,12-octadecadienoic, hexadecanoic acid, and octadecanoic acid were reduced, but the beneficial fatty acids such as 15-tetracosenoic acid, cis-11,14-eicosadienoic acid and 13-docosenamide were enhanced in the mustard oil. Besides, the highest yield was optimized where seeds were treated for 30- min in combination with six times PPW foliar spray. In comparison to control, mustard yield was increased by 60%.
Metastatic breast cancer refers to the spread of cancer cells to distant parts of the body. Metastatic cells spread via the lymphatics or vascular system to form metastatic lesions, also called secondary tumors. Most cases are associated with mutations in the BRCA1 and BRCA2 genes. These defective genes pass from generation to generation. Germline testing helps in screening patients with a positive family history, thus aiding in protection from metastasis and helping in targeted therapy. The physician should offer genetic counseling to patients with a positive history of breast cancer. Treatment strategies include chemotherapy, hormonal therapy, radiotherapy, and immunotherapy. Surgical options include breast conservation surgeries and mastectomy, which is followed by breast reconstruction surgery. Palliative therapy includes control of symptoms and pain management. Supportive services such as counseling, support groups, and integrative therapy could assist patients and their families in overcoming emotional, social and spiritual needs. Besides treatment, clinical trials could enhance cancer research and lead to effective treatment.
To investigate the prevalence and determinants of subretinal drusenoid deposits (SDDs; also known as reticular pseudodrusen, RPDs) in the European general population. Altogether 18 931 adults from eight population-based studies were included. SDDs/RPDs were determined on optical coherence tomography and/or infrared photography. The prevalence of SDDs/RPDs and associated ocular and systemic determinants using multivariable logistic regression modelling per study and pooled results using random effects meta-analysis were analysed. Mean age ranged from 58.7±10.6 to 88.4±0.0 years in the different studies and prevalence of SDDs/RPDs ranged from 0.6% to 56.0%. Meta-analyses showed that increasing age (OR 1.09 per year, 95% CI 1.04 to 1.13; p<0.001), prevalent early/intermediate and late age-related macular degeneration (AMD) (OR 10.93, 95% CI 5.55 to 21.51; p<0.001 and OR 11.65, 95% CI 4.78 to 28.40; p<0.001, respectively) and AMD genetic risk score (OR 1.21 per unit, 95% CI 1.05 to 1.39; p=0.008) are associated with prevalent SDDs/RPDs. Sex, smoking, education and cardiovascular disease showed borderline association at some cohort levels but not in the meta-analysis. In sensitivity analyses, only age and AMD genetic risk score remained associated with SDDs/RPDs prevalence among participants without any AMD. This multi-cohort analysis emphasises the wide range of SDDs/RPDs prevalence and determinants. Besides age, presence of AMD and AMD genetic risk variants increase the risk of SDDs/RPDs. These cross-sectional findings are compatible with the hypothesis that SDDs/RPDs may not represent a separate disease entity but be an additional sign of retinal pigment epithelium and photoreceptor stress.
Colorectal cancer (CRC) remains the main cause of cancer-related mortality worldwide, highlighting the need for effective therapy. Cerium oxide nanoparticles (Cer-NPs) and Ferula latisecta have anticancer properties. This study aimed to green-synthesize of Cer-NPs using Ferula latisecta to assess oxidative stress, apoptosis, and autophagy signaling in CRC cells. The seed extract of Ferula latisecta was combined with cerium salt, synthesized the Cer-NPs, and investigated anticancer effects on human CRC cells with a focus on oxidative stress, apoptosis, and autophagy pathways. XRD, FTIR, and FESEM techniques were utilized to characterize Cer-NPs. HT29 and SW480 CRC cells were treated with a serial dilution of Cer-NPs for cell viability for 24 h and 48 h. Caspase-3 activity assay, AO/PI staining, and real-time PCR method were employed to assess the apoptosis rate and autophagy in cells. Besides, oxidative stress measurements, including intracellular ROS, MDA, LDH, and GSH, were performed. The protein levels of p53 were measured through ELISA. The synthesized Cer-NPs showed a fluorite cubic structure, a crystalline construction, and a spherical morphology with sizes of 20-50 nm. Cer-NPs significantly reduced cell viability in a dose- and time-dependent manner and increased caspase-3 activity (P < 0.05). IC50 values were 0.68 mM and 0.88 mM for HT29 and SW480 cells after 48 h. The number of AO/PI-positive cells was increased alongside ROS production within cells. The levels of MDA and LDH were increased, while the level of GSH was decreased significantly in treated cells (P < 0.05). Furthermore, Cer-NPs could significantly increase Bax, Bcl-2, Beclin-1, P62, Bax/Bcl-2, LC3 II/I ratio as well as up-regulate p53 protein level (P < 0.05). The green-synthesized Cer-NPs could directly induce oxidative stress and apoptosis, and indirectly mediate apoptosis by impairing autophagy.
Diabetic kidney disease (DKD) is a serious condition associated with diabetes, and the role of uric acid (UA) in its development remains debated. This study used a Mendelian randomization (MR) analysis, epidemiological validation, transcriptome data mining and animal study to assess the causal relationship between high serum uric acid (HUA) and DKD. Meanwhile, differential expression analysis of lactate-related genes were conducted. Besides, the suggested lactylation associated genes was verified in vivo and vitro. MR shows that gene-predicted serum uric acid level was positively correlated with the risk of DKD (OR = 1.25, 95% CI: 1.01-1.54, P = 0.0396). The finding was further supported by US National Health and Nutrition Survey data. Lactylation associated transcriptome analysis identified associated genes, HMOX1, OGDH, and SPP1. In type 1 and type 2 diabetes HUA mouse model, the expression of HMOX1, OGDH, and SPP1 was significantly enhanced and HUA treatment significantly aggravated renal injury. In podocyte cell line, inhibition of the expression of HMOX1, OGDH, and SPP1 significantly improve the podocyte function. This study provides evidence that high serum uric acid is associated with DKD, and indicates HMOX1, OGDH, and SPP1 as possible important molecules linked to disease progression. These findings offer new biomarkers and potential therapeutic targets for early diagnosis and intervention of DKD.
Activating mutations in NOTCH1 are frequent in T-cell acute lymphoblastic leukemia (T-ALL) and, in the absence of alterations in RAS or PTEN, are associated with favorable prognosis. Besides classical heterodimerization and PEST domain mutations, juxtamembrane internal tandem duplications (JME-ITDs) represent a third class of activating variants. Their intermediate size and sequence composition can challenge short-read next-generation sequencing and variant calling algorithms, leading to underdetection in routine diagnostics. An index case of newly diagnosed T-ALL harboring a NOTCH1 juxtamembrane insertion that was discordantly detected by variant callers during routine targeted NGS (Hematology OncoKitDx v2) prompted further analysis. The variant was evaluated using VarDict and VarScan2, followed by manual inspection with IGV and orthogonal confirmation by Sanger sequencing. To further assess variability in the detection of JME-ITDs, six additional BAM files from patients with previously confirmed variants were reanalyzed using VarDict, VarScan2, Mutect2, and Pindel. In the index case, VarDict detected a 51-bp NOTCH1 JME-ITD (c.5168-2_5216dup) that was missed by VarScan2 and confirmed by Sanger sequencing. Reanalysis of the seven cases showed that Mutect2 and VarDict detected all JME-ITDs (100%), VarScan2 identified only three (42.8%), and Pindel detected six mutations (85.7%). These results reflect differences in algorithmic strategies where haplotype-based callers incorporate soft-clipped and split reads, whereas pileup-based discard them. Detection of NOTCH1 JME-ITDs depends strongly on variant-calling strategy. Combining haplotype-based callers with split-read structural variant tools may reduce false negatives and improve detection of clinically relevant insertions in diagnostic NGS pipelines.
Temporal lobe epilepsy (TLE) is one of the most common types of epilepsy, with frequent seizures often leading to cognitive, emotional, and psychiatric issues. A prominent pathological change associated with TLE is hippocampal sclerosis (HS), characterized by neuronal loss, gliosis, and increased neuron fibre density. However, the pathogenesis of Temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) remains unclear. This study aimed to investigate the abnormal expression and regulatory mechanism of hub genes in TLE-HS. The source data were obtained from the epilepsy dataset (GSE256068) of the Gene Expression Omnibus GEO database. Then, differential expression gene (DEG) analysis and weighted gene coexpression network analysis (WGCNA) were employed to screen for module-related DEGs in TLE-HS, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Subsequently, these intersected targets were subjected to cross-validation using three machine learning algorithms- LASSO regression, SVM-RFE, and RF, ultimately identifying three hub genes. Finally, CIBERSORT and ssGSEA algorithms were used to analyze the infiltration status of different immune cell populations in TLE-HS patients, followed by assessing the association between hub genes and immune cell populations. The expression of hub genes was determined using RT-qPCR and western blot. Functional experiments were performed using CCK-8, flow cytometry, and special kits. Results indicated that three hub genes, NADH dehydrogenase (ubiquinone) 1 alpha subcomplex subunit 4-like 2 (NDUFA4L2), Protein-tyrosine Phosphatase 4A3 (PTP4A3), and Zinc-alpha-2-glycoprotein (AZGP1), were identified in TLE-HS, which are associated with the infiltration of specific immune cells. Besides, NDUFA4L2 expression was reduced in kainic acid (KA)-induced HT22 cells compared to the other two hub genes. Thus, NDUFA4L2 was selected for this research. Moreover, NDUFA4L2 overexpression alleviated KA‑induced HT22 cell neurotoxicity, apoptosis, oxidative stress, and mitochondrial dysfunction. In conclusion, NDUFA4L2 upregulation could alleviate KA-induced neurotoxicity oxidative stress, which provided a theoretical foundation and a potential therapeutic target for epilepsy.
ConspectusSynthetic molecular/nanoporous structures have shown wide utilization in multidisciplinary aspects of catalysis, adsorption/loading, surface property control, precise separations, and so forth. In contrast to conventional disordered pores, chemically synthesized molecular frameworks through covalent/coordination bonds exhibit more controllable ordered channel architectures for various functional purposes. The definite dimensions and topologies provide tunable pathways for selective molecular recognition and nanorecognition, delivery, and interface activation. However, the structure of these frameworks is relatively rigid, making it difficult for them to be processed and fine-tuned, and they are not easy to repair or recycle. Moreover, when combined with polymers, they are prone to phase separation, which limits their application in membrane sustainability. Therefore, developing distinctive strategies to overcome these limitations remains a critical scientific and technological priority. Given that the main cause of these problems lies in the stiff chemical bonds and crystalline synthesis, the changes in binding form and building units become decisive factors. One of the effective strategies is to use multiple intermolecular interactions as the driving forces to construct supramolecular ionic frameworks (SIFs). Although the assembly mode reduces the rigidity and orderliness of the framework structure, such a route simultaneously brings about significant structural flexibility, convenient modifications, excellent membrane-forming performance, and processability through a simple preparation method. To further enhance the functions of SIFs, the selection of building units that can balance both driving forces and diversified topological configurations becomes a prerequisite for rational design. As a class of stable nanoscale particles, polyoxometalates (POMs) offer more possibilities for the arrangement of the framework structures and possess rich functionalities. Additionally, POMs provide multiple driving forces, including ionic interactions, host-guest interactions, and hydrogen bonds, thereby endowing the framework with both structural stability and flexibility. Relying on the induced structural characteristic, such cluster-based SIFs (CSIFs) directly lead to multiple potentials upon size exclusion, the hydrophobic/hydrophilic effect, and electrostatic adsorption stemming from inherent charges to POMs, demonstrating a landscape of advanced applications for precise separations at nano/molecular scales.To outline the fundamental strategy and typical results, this Account focuses on the construction of CSIFs for various topological architectures, synergistic principles of building units and driving forces, structural analysis of frameworks, membrane separations, and the discussion of separation mechanisms. While exploring the advances of CSIFs, we analyze the limitations and possible breakthroughs of assembly structures. The optimized routes for the precise isolation of a series of substrates via CSIF-based membranes are discussed. Besides primary size screening, the composition adjustment brings about sieving nanoparticles/molecules with a certain charge and chiral selectivity. The tunable hydrophilicity and hydrophobicity in the pores hold the liquid-switchable ability for the separations of incompatible liquids. Finally, the local surface electrical potential difference enables selective adsorption with high capacities for gases based on molecular/bond polarity. The systematic evaluation highlights the distinct advantages of CSIFs in high structural flexibility for processability, recyclability, and the feasibility of engineering diverse morphologies. Moreover, CSIFs show potential in the fields of selective ion separation, anode protection of batteries, and catalysis-possessing functions in the future.
Atherosclerosis, a chronic inflammatory disease of the arterial wall, is a leading cause of cardiovascular diseases worldwide. The complex pathogenesis of atherosclerosis involves genetic predisposition, environmental factors, and immune responses. N-Methyl-d-aspartate receptors (NMDARs), a subclass of glutamate receptors, are critical for synaptic plasticity, learning, and memory in the central nervous system (CNS). Non-neuronal NMDARs are poorly understood compared to neuronal receptors, but there is a developing consensus that they have distinct structural and functional properties when activated by glutamate and NMDARs co-agonists. Emerging evidence indicates that non-neuronal NMDARs may participate in an array of physiological and pathophysiological processes, including but not limited to driving macrophage polarization, lipid dysregulation in macrophages, inflammation response, vascular smooth muscle cells phenotype switching and endothelial dysfunction, thereby fueling atherogenesis. This review discusses the association between NMDARs genes and atherosclerosis risk, molecular mechanisms underlying NMDARs-mediated regulation of atherosclerosis-related cells, and potential therapeutic implications. Besides, we introduce some pharmacological tools that can be used for studying NMDARs outside the CNS, which reflect modern subunit-selective agents to provide more precise insight into NMDARs mediate the various effects. Overall, the study of NMDARs may provide insights into the pathogenesis of atherosclerosis and lead to the development of more effective therapeutic strategies.
Large Reasoning Models (LRMs) significantly improve the reasoning ability of Large Language Models (LLMs) by learning to reason, exhibiting promising performance in solving complex tasks. However, their deliberative reasoning process leads to inefficiencies in token usage, memory consumption, and inference time. Thus, this survey provides a review of efficient inference methods designed specifically for LRMs, focusing on mitigating token inefficiency while preserving the reasoning quality. The overview structure of this paper is shown in Figure 1. First, we introduce a taxonomy to group the recent methods into two main categories: (a) explicit compact Chain-of-Thought (CoT), which reduces tokens while keeping the explicit reasoning structure, and (b) implicit latent CoT, which encodes reasoning steps within hidden representations instead of explicit tokens. Meanwhile, we discuss their strengths and weaknesses. Then, we conduct empirical analyses on existing methods from reasoning scenarios, object functions, and performance & efficiency aspects. Besides, we present open challenges in this field, including human-centric controllable reasoning, trade-off between interpretability and efficiency of reasoning, ensuring the safety of efficient reasoning, and broader applications of efficient reasoning. In addition, we highlight key insights for enhancing LRMs' inference efficiency via techniques such as model merging, new architectures, and agent routers. We hope this work serves as a valuable guide, helping researchers overcome challenges in this vibrant field. A collection of efficient reasoning methods for LRMs (papers and codes) is provided at this link: https://github.com/yueliu1999/Awesome-Efficient-Inference-for-LRMs.
Nicotine is a highly bioactive and addictive alkaloid that exerts prevalent cardiovascular and metabolic toxicity independent of other combustion-derived chemicals. Its rapid absorption and interaction with nicotinic acetylcholine receptors initiate a cascade of oxidative, inflammatory, and neuropharmacological responses that interrupt vascular, renal, and metabolic homeostasis. Nicotine triggers NADPH oxidase, mitochondrial dysfunction, and acid sphingomyelinase-ceramide signaling, resulting in reduced nitric oxide bioavailability, endothelial dysfunction, and lipid raft aggregation that promotes NLRP3 inflammasome activation. These mechanisms contribute to hypertension, atherosclerosis, arrhythmias, and heart failure through augmented oxidative stress, impaired vasodilation, sympathetic activation, and structural cardiac remodeling. Besides the cardiovascular system, nicotine disrupts lipid and glucose metabolism, induces podocyte injury, accelerates chronic kidney disease and promotes insulin resistance via inflammatory and redox-sensitive pathways. Understanding the molecular mechanisms driving nicotine toxicity is essential for developing targeted interventions. Emerging therapeutic strategies include pharmacotherapies for dependence, antihypertensive and lipid-lowering agents, metabolic modulators, antioxidants, and inhibitors of inflammasome or ceramide signaling. Overall, this review synthesizes current mechanistic and pharmacological evidence to clarify how nicotine contributes to cardiovascular and systemic disease and highlights the therapeutic opportunities to mitigate its increasing public health burden.