Serum and Fecal Metabolite Profiles Linking With Gut Microbiome in Triple-Negative Breast Cancer Patients.

Background: Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by poor prognosis due to the absence of effective targeted therapies. Emerging evidence indicates that the gut microbiota and its metabolites play a key role in the occurrence and development of TNBC. This study aimed to explore the metabolic changes and potential mechanisms associated with TNBC. Objectives: This study aimed to explore the potential relationship between targeted metabolites and the gut microbiota in TNBC. Design: We recruited 8 participants, including 4 with TNBC and 4 with benign fibroadenomas as controls. Methods: The gut microbiota was analyzed using metagenomics on fecal samples. Liquid chromatography-mass spectrometry (LC-MS) was employed to identify differential metabolites in serum and fecal samples. The correlation between the gut microbiota and metabolites was analyzed using Spearman's correlation analysis. Results: Analysis of altered serum metabolites in the TNBC group revealed changes, particularly in carboxylic acids and derivatives, benzene, and substituted derivatives. Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis revealed significant enrichment in 18 pathways. Regarding fecal metabolites, differences between the 2 groups also included carboxylic acids and derivatives, benzene, and substituted derivatives, with 28 metabolic pathways enriched based on KEGG pathway analysis. Metagenomics analysis showed differences in the relative abundance of Anaerococcus, Fischerella, and Schizosaccharomyces at the genus level, which have been previously associated with breast cancer. Furthermore, 4 serum metabolites-L-glutamine, citrate, creatinine, and creatine-along with 9 fecal metabolites, were associated with the aforementioned microbiota. Conclusion: Our findings highlight distinct metabolite profiles in the serum and feces of patients with TNBC. The identification of gut microbiota and their associated metabolites provides new insights into the pathophysiological mechanisms underlying TNBC.

Recent Advances in Piezoelectric Coupled with Photocatalytic Reaction System: Synergistic Mechanism, Enhancement Factors, and Application.

The field of photocatalysis has demonstrated numerous advantages in the domains of environmental protection, energy, and materials science. However, conventional modification methods fail to simultaneously enhance carrier separation efficiency, redox capacity, and visible light absorption solely through light activation due to the intrinsic band structure limitations of photocatalysts. In addition to modification methods, the introduction of an external field, such as a piezoelectric field, can effectively address deficiencies in each step of the photocatalytic process and enhance the overall performance. The assistance of a piezoelectric field overcomes the limitations inherent in traditional photocatalytic systems. Hence, this review provides a comprehensive overview of recent advancements in piezoelectric-assisted photocatalysis and thoroughly investigates the interaction between the alternating piezoelectric field and photocatalytic processes. Various ideas for synergistic enhancement of the piezoelectric and photocatalytic properties are also explored. This multifield catalytic system shows remarkable performance in stability, pollutant degradation, and energy conversion, distinguishing it from single catalytic systems. Finally, an in-depth analysis is conducted to address the challenges and prospects associated with piezoelectric photocatalysis technology.

Global distribution, drivers, and potential hazards of microplastics in groundwater: A review.

Since microplastics (MPs) were first detected in groundwater, an increasing number of studies have focused on groundwater pollution by MPs. However, knowledge of the global properties of groundwater MPs: distribution, concentration, composition, and morphology remains limited, while potential factors regulating their transport and distribution in groundwater, especially the hydrogeological background and climate warming conditions, have been omitted from most analyses. Furthermore, previous field investigations did not assess the risks posed by groundwater MPs to the environment and to human health, a necessary preliminary to remediation. In this work, to promote future MP pollution studies and remediation policies, we assimilated and synthesized the current knowledge on this topic. We reviewed current data on global groundwater pollution by MPs, analyzed the driving factors of their transport and distribution, and summarized the ecological and health hazards posed by MPs, before discussing current knowledge limits and suggesting perspectives for future work.

Convolutional Transformer-based Cross Subject Model for SSVEP-based BCI Classification.

Steady-state visual evoked potential (SSVEP) is a commonly used brain-computer interface (BCI) paradigm. The performance of cross-subject SSVEP classification has a strong impact on SSVEP-BCI. This study designed a cross subject generalization SSVEP classification model based on an improved transformer structure that uses domain generalization (DG). The global receptive field of multi-head self-attention is used to learn the global generalized SSVEP temporal information across subjects. This is combined with a parallel local convolution module, designed to avoid oversmoothing the oscillation characteristics of temporal SSVEP data and better fit the feature. Moreover, to improve the cross-subject calibration-free SSVEP classification performance, an DG method named StableNet is combined with the proposed convolutional transformer structure to form the DG-Conformer method, which can eliminate spurious correlations between SSVEP discriminative information and background noise to improve cross-subject generalization. Experiments on two public datasets, Benchmark and BETA, demonstrated the outstanding performance of the proposed DG-Conformer compared with other calibration-free methods, FBCCA, tt-CCA, Compact-CNN, FB-tCNN, and SSVEPNet. Additionally, DG-Conformer outperforms the classic calibration-required algorithms eCCA, eTRCA and eSSCOR when calibration is used. An incomplete partial stimulus calibration scheme was also explored on the Benchmark dataset, and it was demonstrated to be a potential solution for further high-performance personalized SSVEP-BCI with quick calibration.

Genome-Wide Analysis of the Histone Modification Gene (HM) Family and Expression Investigation during Anther Development in Rice (Oryza sativa L.).

Histone modification plays a crucial role in chromatin remodeling and regulating gene expression, and participates in various biological processes, including plant development and responses to stress. Several gene families related to histone modification have been reported in various plant species. However, the identification of members and their functions in the rice (Oryza sativa L.) histone modification gene family (OsHM) at the whole-genome level remains unclear. In this study, a total of 130 OsHMs were identified through a genome-wide analysis. The OsHM gene family can be classified into 11 subfamilies based on a phylogenetic analysis. An analysis of the genes structures and conserved motifs indicates that members of each subfamily share specific conserved protein structures, suggesting their potential conserved functions. Molecular evolutionary analysis reveals that a significant number of OsHMs proteins originated from gene duplication events, particularly segmental duplications. Additionally, transcriptome analysis demonstrates that OsHMs are widely expressed in various tissues of rice and are responsive to multiple abiotic stresses. Fourteen OsHMs exhibit high expression in rice anthers and peaked at different pollen developmental stages. RT-qPCR results further elucidate the expression patterns of these 14 OsHMs during different developmental stages of anthers, highlighting their high expression during the meiosis and tetrad stages, as well as in the late stage of pollen development. Remarkably, OsSDG713 and OsSDG727 were further identified to be nucleus-localized. This study provides a fundamental framework for further exploring the gene functions of HMs in plants, particularly for researching their functions and potential applications in rice anthers' development and male sterility.

Effect of magnesium and calcium ions on the strength and biofunctionality of GelMA/SAMA composite hydrogels.

Natural polymers and synthetic polymers have been extensively studied as scaffold materials, with the former offering advantages such as biocompatibility, biodegradability, and structural similarity to the natural extracellular matrix (ECM). However, the use of natural polymers in extrusion-based 3D printing has been limited by their poor mechanical properties and challenging rheological properties. In this study, gelatin and sodium alginate were utilized as scaffold materials, with the addition of Ca2+ and Mg2+ components to enhance their physical and chemical properties, and influence early cell behavior. Subsequently, these materials were fabricated into scaffolds using 3D printing. Our results demonstrated that the addition of Ca2+ and Mg2+ could improve the compactness of the 3D network structure, mechanical strength, swelling properties and degradation properties of methacrylated gelatin/methacrylated sodium alginate (GelMA/SAMA) composite hydrogel. In vitro cell tests revealed that the GelMA/SAMA composite hydrogel exhibited negligible cytotoxicity and promoted early cell viability, particularly with the higher concentration of Mg2+ in the material. Notably, the extrusion 3D printing process successfully produced GelMA/SAMA scaffolds. These results collectively indicate that GelMA/SAMA composite scaffolds hold promise as potential biomaterials for tissue engineering applications.

Iron-based magnetic nanocomplexes for combined chemodynamic and photothermal cancer therapy through enhanced ferroptosis.

Chemodynamic therapy (CDT) guided by Fenton chemistry and iron-containing materials can induce ferroptosis as a prospective cancer treatment method, but the inefficient Fe3+/Fe2+ conversion restricts the monotherapeutic performances. Here, an iron-based nanoplatform (Fe3O4-SRF@FeTA) including a magnetic core and a reductive film is developed for combined CDT and photothermal therapy (PTT) through ferroptosis augmentation. The inner iron oxide core serves as a photothermal transducer, a magnet-responsive module, and an iron reservoir for CDT. The coated Fe3+-tannic acid film (FeTA) provides extra iron and reductants for Fe3+/Fe2+ conversion acceleration, and functions as a door keeper for the pH- and light-responsive release of the embedded ferroptosis inducer sorafenib (SRF). The in vitro results demonstrate that the iron-based nanocomplexes promote the production of lipid peroxide through the amplified Fenton activity, and downregulate glutathione involved in lipid peroxide repair system through the responsively released SRF. Upon accumulation in tumor by magnetic targeting and sequential laser irradiation locoregionally, Fe3O4-SRF@FeTA nanocomplexes present prominent in vivo anticancer efficacy by leveraging PTT and CDT-enhanced ferroptosis.

Screening of polyurethane-degrading microbes using a quenching fluorescence probe by microfluidic droplet sorting.

Excessive use of polyurethane (PU) polymers has led contributed to serious environmental pollution. The plastic recycling technology using microorganisms and enzymes as catalysts offers a promising green and low-carbon approach for managing plastic waste. However, current methods for screening PU-degrading strains suffer from drawbacks such as being time-consuming and inefficient. Herein, we present a novel approach for screening PU-degrading microorganisms using a quenching fluorescent probe along with the fluorescence-activated droplet sorting (FADS). The FPAP could specifically recognize the 4,4'-methylenedianiline (MDA) derivates released from PU degradation, with fluorescence quenching as a response. Based on the approach, we successfully screen two PU-degrading strains (Burkholderia sp. W38 and Bacillus sp. C1). After 20 d of cultivation, strain W38 and C1 could degrade 41.58% and 31.45% of polyester-PU film, respectively. Additionally, three metabolites were identified during the degradation of PU monomer (2,4-toluene diamine, 2,4-TDA) and a proposed degradation pathway was established. Consequently, the fluorescence probe integrated with microfluidic droplet systems, demonstrates potential for the development of innovative PU-biocatalysts. Furthermore, the identification of the 2,4-TDA degradation pathway provides valuable insights that can propel advancements in the field of PU biodegradation.

Combining Fast Pure Shift NMR and GEMSTONE-Based Selective TOCSY for Efficient NMR Analysis of Complex Systems.

As one of the commonly used intact detection techniques, liquid NMR spectroscopy offers unparalleled insights into the chemical environments, structures, and dynamics of molecules. However, it generally encounters the challenges of crowded or even overlapped spectra, especially when probing complex sample systems containing numerous components and complicated molecular structures. Herein, we exploit a general NMR protocol for efficient NMR analysis of complex systems by combining fast pure shift NMR and GEMSTONE-based selective TOCSY. First, this protocol enables ultrahigh-selective observation on the coupling networks that are totally correlated with targeted resonances or components, even where they are situated in severely overlapped spectral regions. Second, pure shift simplification is introduced to enhance the spectral resolution and further resolve the subspectra containing spectral congestion, thus facilitating the dissection of overlapped spectra. Additionally, sparse sampling accompanied by spectral reconstruction is adopted to significantly accelerate acquisition and improve spectral quality. The advantages of this protocol were demonstrated on different complex sample systems, including a challenging compound of estradiol, a mixture of sucrose and d-glucose, and natural grape juice, verifying its feasibility and power, and boosting the potential application landscapes in various chemical fields.

The Design and Analysis of the Fabrication of Micro- and Nanoscale Surface Structures and Their Performance Applications from a Bionic Perspective.

This paper comprehensively discusses the fabrication of bionic-based ultrafast laser micro-nano-multiscale surface structures and their performance analysis. It explores the functionality of biological surface structures and the high adaptability achieved through optimized self-organized biomaterials with multilayered structures. This study details the applications of ultrafast laser technology in biomimetic designs, particularly in preparing high-precision, wear-resistant, hydrophobic, and antireflective micro- and nanostructures on metal surfaces. Advances in the fabrications of laser surface structures are analyzed, comparing top-down and bottom-up processing methods and femtosecond laser direct writing. This research investigates selective absorption properties of surface structures at different scales for various light wavelengths, achieving coloring or stealth effects. Applications in dirt-resistant, self-cleaning, biomimetic optical, friction-resistant, and biocompatible surfaces are presented, demonstrating potential in biomedical care, water-vapor harvesting, and droplet manipulation. This paper concludes by highlighting research frontiers, theoretical and technological challenges, and the high-precision capabilities of femtosecond laser technology in related fields.

The dual role of microglia in intracerebral hemorrhage.

Intracerebral hemorrhage has the characteristics of high morbidity, disability and mortality, which has caused a heavy burden to families and society. Microglia are resident immune cells in the central nervous system, and their activation plays a dual role in tissue damage after intracerebral hemorrhage. The damage in cerebral hemorrhage is embodied in the following aspects: releasing inflammatory factors and inflammatory mediators, triggering programmed cell death, producing glutamate induced excitotoxicity, and destroying blood-brain barrier; The protective effect is reflected in the phagocytosis and clearance of harmful substances by microglia, and the secretion of anti-inflammatory and neurotrophic factors. This article summarizes the function of microglia and its dual regulatory mechanism in intracerebral hemorrhage. In the future, drugs, acupuncture and other clinical treatments can be used to intervene in the activation state of microglia, so as to reduce the harm of microglia.

Development and validation of a CT-based radiomics model to predict survival-graded fibrosis in pancreatic ductal adenocarcinoma.

BACKGROUND: Tumor fibrosis plays an important role in chemotherapy resistance in pancreatic ductal adenocarcinoma (PDAC), however there remains a contradiction in the prognostic value of fibrosis. We aimed to investigate the relationship between tumor fibrosis and survival in patients with PDAC, classify patients into high- and low-fibrosis groups, and develop and validate a CT-based radiomics model to non-invasively predict fibrosis before treatment. MATERIALS AND METHODS: This retrospective, bicentric study included 295 patients with PDAC without any treatments before surgery. Tumor fibrosis was assessed using the collagen fraction (CF). Cox regression analysis was used to evaluate the associations of CF with overall survival (OS) and disease-free survival (DFS). Receiver operating characteristic (ROC) analyses were used to determine the rounded threshold of CF. An integrated model (IM) was developed by incorporating selected radiomic features and clinical-radiological characteristics. The predictive performance was validated in the test cohort (Center 2). RESULTS: The CFs were 38.22±6.89% and 38.44±8.66% in center 1 (131 patients, 83 males) and center 2 (164 patients, 100 males), respectively (P=0.814). Multivariable Cox regression revealed that CF was an independent risk factor in the OS and DFS analyses at both centers. ROCs revealed that 40% was the rounded cut-off value of CF. IM predicted CF with areas under the curves (AUCs) of 0.825 (95% confidence interval [CI], 0.749-0.886) and 0.745 (95% CI, 0.671-0.810) in the training and test cohorts, respectively. Decision curve analyses revealed that IM outperformed radiomics model and clinical-radiological model for CF prediction in both cohorts. CONCLUSIONS: Tumor fibrosis was an independent risk factor for survival of patients with PDAC, and a rounded cut-off value of 40% provided a good differentiation of patient prognosis. The model combining CT-based radiomics and clinical-radiological features can satisfactorily predict survival-grade fibrosis in patients with PDAC.

AbdomenAtlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking.

We introduce the largest abdominal CT dataset (termed AbdomenAtlas) of 20,460 three-dimensional CT volumes sourced from 112 hospitals across diverse populations, geographies, and facilities. AbdomenAtlas provides 673 K high-quality masks of anatomical structures in the abdominal region annotated by a team of 10 radiologists with the help of AI algorithms. We start by having expert radiologists manually annotate 22 anatomical structures in 5,246 CT volumes. Following this, a semi-automatic annotation procedure is performed for the remaining CT volumes, where radiologists revise the annotations predicted by AI, and in turn, AI improves its predictions by learning from revised annotations. Such a large-scale, detailed-annotated, and multi-center dataset is needed for two reasons. Firstly, AbdomenAtlas provides important resources for AI development at scale, branded as large pre-trained models, which can alleviate the annotation workload of expert radiologists to transfer to broader clinical applications. Secondly, AbdomenAtlas establishes a large-scale benchmark for evaluating AI algorithms-the more data we use to test the algorithms, the better we can guarantee reliable performance in complex clinical scenarios. An ISBI & MICCAI challenge named BodyMaps: Towards 3D Atlas of Human Body was launched using a subset of our AbdomenAtlas, aiming to stimulate AI innovation and to benchmark segmentation accuracy, inference efficiency, and domain generalizability. We hope our AbdomenAtlas can set the stage for larger-scale clinical trials and offer exceptional opportunities to practitioners in the medical imaging community. Codes, models, and datasets are available at https://www.zongweiz.com/dataset.

Research on Mechanism and Effect of Enhancing Gas Recovery by CO2 Huff-n-Puff in Shale Gas Reservoir.

The technology of CO2-enhanced gas recovery (CO2-EGR) plays a pivotal role in the CCUS (Carbon Capture, Utilization, and Storage) industry, which helps to achieve a win-win situation of economic benefit and environmental benefit for gas fields. Shale gas reservoirs, with their unique geological and surface engineering advantages, are one of the most promising options for CCUS implementation. Focusing on shale formations within the mid-deep blocks of the Sichuan Basin, this study conducted competitive adsorption experiments using multicomponent gases. Through physical simulations and single-well numerical modeling, factors such as injection volume, timing, shut-in time, and huff-n-puff rounds were examined for their impact on recovery. The results show that the higher the CO2 content in the injected medium, the more pronounced advantage in gas adsorption on shale surfaces. Optimal performance was achieved with a CO2 content in the injection medium of 80% to 100%, an injection volume of 0.2-0.3 PV, a shut-in time exceeding 6 h, and a relatively delayed injection timing. The recovery in the first round of huff-n-puff was increased by 24.2% to 47.8%, which gave a full play to the role of huff-n-puff and achieved favorable benefits. Based on the middle-deep geological parameters, a single-well numerical simulation was established, which demonstrates that single-well EUR (estimated ultimate recovery) can be increased by 14.2% to 19.8% compared to gas wells without CO2 injection. This study provides essential guidance for the enhanced recovery in shale gas reservoirs through CO2 huff-n-puff.

Shared genetic architecture of cortical thickness alterations in major depressive disorder and schizophrenia.

BACKGROUND: Major depressive disorder (MDD) and schizophrenia (SCZ) are heritable brain disorders characterized by alterations in cortical thickness. However, the shared genetic basis for cortical thickness changes in these disorders remains unclear. METHODS: We conducted a systematic literature search on cortical thickness in MDD and SCZ through PubMed and Web of Science. A coordinate-based meta-analysis was performed to identify cortical thickness changes. Additionally, utilizing summary statistics from the largest genome-wide association studies for depression (Ncase = 268,615, Ncontrol = 667,123) and SCZ (Ncase = 53,386, Ncontrol = 77,258), we explored shared genomic loci using conjunctional false discovery rate (conjFDR) analysis. Transcriptome-neuroimaging association analysis was then employed to identify shared genes associated with cortical thickness alterations, and enrichment analysis was finally carried out to elucidate the biological significance of these genes. RESULTS: Our search yielded 34 MDD (Ncase = 1621, Ncontrol = 1507) and 19 SCZ (Ncase = 1170, Ncontrol = 1043) neuroimaging studies for cortical thickness meta-analysis. Specific alterations in the left supplementary motor area were observed in MDD, while SCZ exhibited widespread reductions in various brain regions, particularly in the frontal and temporal areas. The conjFDR approach identified 357 genomic loci jointly associated with MDD and SCZ. Within these loci, 55 genes were found to be associated with cortical thickness alterations in both disorders. Enrichment analysis revealed their involvement in nervous system development, apoptosis, and cell communication. CONCLUSION: This study revealed the shared genetic architecture underlying cortical thickness alterations in MDD and SCZ, providing insights into common neurobiological pathways. The identified genes and pathways may serve as potential transdiagnostic markers, informing precision medicine approaches in psychiatric care.

Cascade Electrocatalytic Nitrate Reduction Reaching 100% Nitrate-N to Ammonia-N Conversion over Cu2O@CoO Yolk-Shell Nanocubes.

The electroreduction of nitrate to ammonia via a selective eight-electron transfer nitrate reduction reaction offers a promising, low energy consumption, pollution-free, green NH3 synthesis strategy alternative to the Haber-Bosch method. However, it remains a great challenge to achieve high NH4+ selectivity and complete conversion from NO3--N to NH4+-N. Herein, we report ingredients adjustable Cu2O@CoO yolk-shell nanocubes featured with tunable inner void spaces and diverse activity centers, favoring the rapid cascade conversion of NO3- into NO2- on Cu2O and NO2- into NH4+ on CoO. Cu2O@CoO yolk-shell nanocubes exhibit super NH4+ Faradaic efficiencies (>99%) over a wide potential window (-0.2 V to -0.9 V versus RHE) with a considerable NH4+ yield rate of 15.27 mg h-1 cm-2 and fantastic cycling stability and long-term chronoamperometric durability. Cu2O@CoO yolk-shell nanocubes exhibited glorious NO3--N to NH4+-N conversion efficiency in both dilute (500 ppm) and highly concentrated (0.1 and 1 M) NO3- electrolytes, respectively. The nitrate electrolysis membrane electrode assembly system equipped with Cu2O@CoO yolk-shell nanocubes delivers over 99.8% NH4+ Faradaic efficiency at cell voltages of 1.9-2.3 V.

Highly sensitive turn-on electrochemical sensing of organophosphorus pesticides by integration of homogeneous reaction and heterogeneous catalytic signal amplification.

Enzyme-inhibited electrochemical sensor is a promising strategy for detecting organophosphorus pesticides (OPs). However, the poor stability of enzymes and the high oxidation potential of thiocholine signal probe limit their potential applications. To address this issue, an indirect strategy was proposed for highly sensitive and reliable detection of chlorpyrifos by integrating homogeneous reaction and heterogeneous catalysis. In the homogeneous reaction, Hg2+ with low oxidation potential was employed as signal probe for chlorpyrifos detection since its electroactivity can be inhibited by thiocholine, which was the hydrolysate of acetylthiocholine catalyzed by acetylcholinesterase. Additionally, Co,N-doped hollow porous carbon nanocage@carbon nanotubes (Co,N-HPNC@CNT) derived from ZIF-8@ZIF-67 was utilized as high-performance electrode material to amplify the stripping voltammetry signal of Hg2+. Thanks to their synergistic effect, the sensor exhibited outstanding sensing performance, excellent stability and good anti-interference ability. This strategy paves the way for the development of high-performance OP sensors and their application in food safety.

Emergency preparedness in the central sterile supply department: a multicenter cross-sectional survey.

OBJECTIVE: To investigate the current situation of emergency preparation and emergency drill in the CSSD, and analyze its influence on the nurses' emergency attitude and ability. METHODS: This study employed a multicenter stratified sampling method, conducted from January to June 2023 using the online survey, participants completed the general data, emergency preparedness and drill questionnaire, public health emergency response questionnaire and emergency capacity scale. An independent samples t test or Kruskal-Wallis test was used to analyse differences in nurses' emergency capacity and attitudes. RESULTS: The data from 15 provinces 55 hospitals in China. Overall, 77.58% of participants' institutions set up emergency management teams, 85.45% have an emergency plan and revise it regularly. 92.12% store emergency supplies. All survey staff participated in the emergency drill, which predominantly consisted of individual drills (51.52%), with 90.30% being real combat drills, 49.09% of participants engaging in drills every quarter, and 91.52% of the drill's participants exceeding 50%. The respondents' emergency attitude score was (29.346 ± 6.029), their emergency ability score was (63.594 ± 10.413), and those with rescue experience showed a more positive attitude (Z = -2.316, P = 0.021). Different titles, education levels, rescue experience and the frequency of emergency drill affected the emergency rescue ability of the respondents (P < 0.05). CONCLUSIONS: Most medical institutions establish emergency management systems and plans, yet the content lacks geographical specificity.The duration and participation of emergency drills are high, but the effectiveness of the drills needs to be further improved, and the response capacity and attitudes of CSSD nurses are low. It is recommended that agencies develop comprehensive and targeted contingency plans to strengthen the inspection and evaluation of team strength, equipment and safeguards against the contingency plans, so as to ensure that the measures mandated by the contingency plans can be implemented promptly after the emergency response is initiated.

Recent Advances in Targeted Cancer Therapy: Are PDCs the Next Generation of ADCs?

Antibody-drug conjugates (ADCs) comprise antibodies, cytotoxic payloads, and linkers, which can integrate the advantages of antibodies and small molecule drugs to achieve targeted cancer treatment. However, ADCs also have some shortcomings, such as non-negligible drug resistance, a low therapeutic index, and payload-related toxicity. Many studies have focused on changing the composition of ADCs, and some have even further extended the concept and types of targeted conjugated drugs by replacing the targeted antibodies in ADCs with peptides, revolutionarily introducing peptide-drug conjugates (PDCs). This Perspective summarizes the current research status of ADCs and PDCs and highlights the structural innovations of ADC components. In particular, PDCs are regarded as the next generation of potential targeted drugs after ADCs, and the current challenges of PDCs are analyzed. Our aim is to offer fresh insights for the efficient design and expedited development of innovative targeted conjugated drugs.

A nomogram combining neutrophil to lymphocyte ratio (NLR) and prognostic nutritional index (PNI) to predict distant metastasis in gastric cancer.

In this study, We aim to explore the association between the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), lymphocyte to monocyte ratio (LMR) and prognostic nutritional index (PNI) and distant metastasis of gastric cancer and develop an efficient nomogram for screening patients with distant metastasis. A total of 1281 inpatients with gastric cancer were enrolled and divided into the training and validation set.Univariate, Lasso regression and Multivariate Logistic Regression Analysis was used to identify the risk factors of distant metastasis. The independent predictive factors were then enrolled in the nomogram model. The nomogram's predictive perform and clinical practicality was evaluated by receiver operating characteristics (ROC) curves, calibration curves and decision curve analysis. Multivariate Logistic Regression Analysis identified D-dimer, CA199, CA125, NLR and PNI as independent predictive factors. The area under the curve of our nomogram based on these factors was 0.838 in the training cohort and 0.811 in the validation cohort. The calibration plots and decision curves demonstrated the nomogram's good predictive performance and clinical practicality in both training and validation cohort. Therefore,our nomogram could be an important tool for clinicians in screening gastric cancer patients with distant metastasis.