Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma.

BACKGROUND: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD). METHODS: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS). RESULTS: This study identified TIME-related lncRNAs from integrated analysis of single­cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy. CONCLUSIONS: This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.

Cellular Ligand-Receptor Perturbations Unravel MEIS2 as a Key Factor for the Aggressive Progression and Prognosis in Stage II/III Colorectal Cancer.

Approximately 10-15% of stage II and 25-30% of stage III colorectal cancer (CRC) patients experience recurrence within 5 years after surgery, and existing taxonomies are insufficient to meet the needs of clinical precision treatment. Thus, robust biomarkers and precise management were urgently required to stratify stage II and III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alongside, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated. Herein, based on multiple large-sample multicenter cohorts and perturbations of the ligand-receptor interaction network, four well-characterized ligand-receptor-driven subtypes (LRDS) were established and further validated. These molecular taxonomies perform with unique heterogeneity in terms of molecular characteristics, immune and mutational landscapes, and clinical features. Specifically, MEIS2, a key LRDS4 factor, performs significant associations with proliferation, invasion, migration, and dismal prognosis of stage II/III CRC, revealing promising directions for prognostic assessment and individualized treatment of CRC patients. Overall, our study sheds novel insights into the implications of intercellular communication on stage II/III CRC from a ligand-receptor interactome perspective and revealed MEIS2 as a key factor in the aggressive progression and prognosis for stage II/III CRC.

Tertiary lymphoid structural heterogeneity determines tumour immunity and prospects for clinical application.

Tertiary lymphoid structures (TLS) are clusters of immune cells that resemble and function similarly to secondary lymphoid organs (SLOs). While TLS is generally associated with an anti-tumour immune response in most cancer types, it has also been observed to act as a pro-tumour immune response. The heterogeneity of TLS function is largely determined by the composition of tumour-infiltrating lymphocytes (TILs) and the balance of cell subsets within the tumour-associated TLS (TA-TLS). TA-TLS of varying maturity, density, and location may have opposing effects on tumour immunity. Higher maturity and/or higher density TLS are often associated with favorable clinical outcomes and immunotherapeutic response, mainly due to crosstalk between different proportions of immune cell subpopulations in TA-TLS. Therefore, TLS can be used as a marker to predict the efficacy of immunotherapy in immune checkpoint blockade (ICB). Developing efficient imaging and induction methods to study TA-TLS is crucial for enhancing anti-tumour immunity. The integration of imaging techniques with biological materials, including nanoprobes and hydrogels, alongside artificial intelligence (AI), enables non-invasive in vivo visualization of TLS. In this review, we explore the dynamic interactions among T and B cell subpopulations of varying phenotypes that contribute to the structural and functional diversity of TLS, examining both existing and emerging techniques for TLS imaging and induction, focusing on cancer immunotherapies and biomaterials. We also highlight novel therapeutic approaches of TLS that are being explored with the aim of increasing ICB treatment efficacy and predicting prognosis.

Ferroptosis and EMT: key targets for combating cancer progression and therapy resistance.

Iron-dependent lipid peroxidation causes ferroptosis, a form of regulated cell death. Crucial steps in the formation of ferroptosis include the accumulation of ferrous ions (Fe2+) and lipid peroxidation, of which are controlled by glutathione peroxidase 4 (GPX4). Its crucial role in stopping the spread of cancer has been shown by numerous studies undertaken in the last ten years. Epithelial-mesenchymal transition (EMT) is the process by which epithelial cells acquire mesenchymal characteristics. EMT is connected to carcinogenesis, invasiveness, metastasis, and therapeutic resistance in cancer. It is controlled by a range of internal and external signals and changes the phenotype from epithelial to mesenchymal like. Studies have shown that mesenchymal cancer cells tend to be more ferroptotic than their epithelial counterparts. Drug-resistant cancer cells are more easily killed by inducers of ferroptosis when they undergo EMT. Therefore, understanding the interaction between ferroptosis and EMT will help identify novel cancer treatment targets. In-depth discussion is given to the regulation of ferroptosis, the potential application of EMT in the treatment of cancer, and the relationships between ferroptosis, EMT, and signaling pathways associated with tumors. Invasion, metastasis, and inflammation in cancer all include ferroptosis and EMT. The goal of this review is to provide suggestions for future research and practical guidance for applying ferroptosis and EMT in clinical practice.

Recent advances and applications of CRISPR-Cas9 in cancer immunotherapy.

The incidence and mortality of cancer are the major health issue worldwide. Apart from the treatments developed to date, the unsatisfactory therapeutic effects of cancers have not been addressed by broadening the toolbox. The advent of immunotherapy has ushered in a new era in the treatments of solid tumors, but remains limited and requires breaking adverse effects. Meanwhile, the development of advanced technologies can be further boosted by gene analysis and manipulation at the molecular level. The advent of cutting-edge genome editing technology, especially clustered regularly interspaced short palindromic repeats (CRISPR-Cas9), has demonstrated its potential to break the limits of immunotherapy in cancers. In this review, the mechanism of CRISPR-Cas9-mediated genome editing and a powerful CRISPR toolbox are introduced. Furthermore, we focus on reviewing the impact of CRISPR-induced double-strand breaks (DSBs) on cancer immunotherapy (knockout or knockin). Finally, we discuss the CRISPR-Cas9-based genome-wide screening for target identification, emphasis the potential of spatial CRISPR genomics, and present the comprehensive application and challenges in basic research, translational medicine and clinics of CRISPR-Cas9.

Multifaceted role of redox pattern in the tumor immune microenvironment regarding autophagy and apoptosis.

The reversible oxidation-reduction homeostasis mechanism functions as a specific signal transduction system, eliciting related physiological responses. Disruptions to redox homeostasis can have negative consequences, including the potential for cancer development and progression, which are closely linked to a series of redox processes, such as adjustment of reactive oxygen species (ROS) levels and species, changes in antioxidant capacity, and differential effects of ROS on downstream cell fate and immune capacity. The tumor microenvironment (TME) exhibits a complex interplay between immunity and regulatory cell death, especially autophagy and apoptosis, which is crucially regulated by ROS. The present study aims to investigate the mechanism by which multi-source ROS affects apoptosis, autophagy, and the anti-tumor immune response in the TME and the mutual crosstalk between these three processes. Given the intricate role of ROS in controlling cell fate and immunity, we will further examine the relationship between traditional cancer therapy and ROS. It is worth noting that we will discuss some potential ROS-related treatment options for further future studies.

Radiogenomics: a key component of precision cancer medicine.

Radiogenomics, focusing on the relationship between genomics and imaging phenotypes, has been widely applied to address tumour heterogeneity and predict immune responsiveness and progression. It is an inevitable consequence of current trends in precision medicine, as radiogenomics costs less than traditional genetic sequencing and provides access to whole-tumour information rather than limited biopsy specimens. By providing voxel-by-voxel genetic information, radiogenomics can allow tailored therapy targeting a complete, heterogeneous tumour or set of tumours. In addition to quantifying lesion characteristics, radiogenomics can also be used to distinguish benign from malignant entities, as well as patient characteristics, to better stratify patients according to disease risk, thereby enabling more precise imaging and screening. Here, we have characterised the radiogenomic application in precision medicine using a multi-omic approach. we outline the main applications of radiogenomics in diagnosis, treatment planning and evaluations in the field of oncology with the aim of developing quantitative and personalised medicine. Finally, we discuss the challenges in the field of radiogenomics and the scope and clinical applicability of these methods.

Machine learning algorithm-generated and multi-center validated melanoma prognostic signature with inspiration for treatment management.

BACKGROUND: Although immunotherapy and targeted treatments have dramatically improved the survival of melanoma patients, the intra- or intertumoral heterogeneity and drug resistance have hindered the further expansion of clinical benefits. METHODS: The 96 combination frames constructed by ten machine learning algorithms identified a prognostic consensus signature based on 1002 melanoma samples from nine independent cohorts. Clinical features and 26 published signatures were employed to compare the predictive performance of our model. RESULTS: A machine learning-based prognostic signature (MLPS) with the highest average C-index was developed via 96 algorithm combinations. The MLPS has a stable and excellent predictive performance for overall survival, superior to common clinical traits and 26 collected signatures. The low MLPS group with a better prognosis had significantly enriched immune-related pathways, tending to be an immune-hot phenotype and possessing potential immunotherapeutic responses to anti-PD-1, anti-CTLA-4, and MAGE-A3. On the contrary, the high MLPS group with more complex genomic alterations and poorer prognoses is more sensitive to the BRAF inhibitor dabrafenib, confirmed in patients with BRAF mutations. CONCLUSION: MLPS could independently and stably predict the prognosis of melanoma, considered a promising biomarker to identify patients suitable for immunotherapy and those with BRAF mutations who would benefit from dabrafenib.

Gastrointestinal symptoms of long COVID-19 related to the ectopic colonization of specific bacteria that move between the upper and lower alimentary tract and alterations in serum metabolites.

BACKGROUND: Since the coronavirus disease 2019 (COVID-19) outbreak, many COVID-19 variants have emerged, causing several waves of pandemics and many infections. Long COVID-19, or long-term sequelae after recovery from COVID-19, has aroused worldwide concern because it reduces patient quality of life after rehabilitation. We aimed to characterize the functional differential profile of the oral and gut microbiomes and serum metabolites in patients with gastrointestinal symptoms associated with long COVID-19. METHODS: We prospectively collected oral, fecal, and serum samples from 983 antibiotic-naïve patients with mild COVID-19 and performed a 3-month follow-up postdischarge. Forty-five fecal and saliva samples, and 25 paired serum samples were collected from patients with gastrointestinal symptoms of long COVID-19 at follow-up and from healthy controls, respectively. Eight fecal and saliva samples were collected without gastrointestinal symptoms of long COVID-19 at follow-up. Shotgun metagenomic sequencing of fecal samples and 2bRAD-M sequencing of saliva samples were performed on these paired samples. Two published COVID-19 gut microbiota cohorts were analyzed for comparison. Paired serum samples were analyzed using widely targeted metabolomics. RESULTS: Mild COVID-19 patients without gastrointestinal symptoms of long COVID-19 showed little difference in the gut and oral microbiota during hospitalization and at follow-up from healthy controls. The baseline and 3-month samples collected from patients with gastrointestinal symptoms associated with long COVID-19 showed significant differences, and ectopic colonization of the oral cavity by gut microbes including 27 common differentially abundant genera in the Proteobacteria phylum, was observed at the 3-month timepoint. Some of these bacteria, including Neisseria, Lautropia, and Agrobacterium, were highly related to differentially expressed serum metabolites with potential toxicity, such as 4-chlorophenylacetic acid, 5-sulfoxymethylfurfural, and estradiol valerate. CONCLUSIONS: Our study characterized the changes in and correlations between the oral and gut microbiomes and serum metabolites in patients with gastrointestinal symptoms associated with long COVID-19. Additionally, our findings reveal that ectopically colonized bacteria from the gut to the oral cavity could exist in long COVID-19 patients with gastrointestinal symptoms, with a strong correlation to some potential harmful metabolites in serum.

Hyperkalaemia prevalence and dialysis patterns in Chinese patients on haemodialysis: an interim analysis of a prospective cohort study (PRECEDE-K).

BACKGROUND: Hyperkalaemia is a known risk factor for cardiac arrhythmia and mortality in patients on haemodialysis. Despite standard adequate haemodialysis, hyperkalaemia is common in patients with end-stage renal disease (ESRD) at interdialytic intervals. Data on hyperkalaemia burden and its effects on dialysis patterns and serum potassium (sK) fluctuations in patients on haemodialysis in China remain limited. The prospective, observational cohort study (PRECEDE-K; NCT04799067) investigated the prevalence, recurrence, and treatment patterns of hyperkalaemia in Chinese patients with ESRD on haemodialysis. METHODS: Six hundred adult patients were consecutively enrolled from 15 secondary and tertiary hospitals in China. In this interim analysis, we report the baseline characteristics of the cohort, the prevalence of predialysis hyperkalaemia (sK > 5.0 mmol/L), and the trends in serum-dialysate potassium gradient and intradialytic sK shift at Visit 1 (following a long interdialytic interval [LIDI]). RESULTS: At baseline, most patients (85.6%) received three-times weekly dialysis; mean duration was 4.0 h. Mean urea reduction ratio was 68.0% and Kt/V was 1.45; 60.0% of patients had prior hyperkalaemia (previous 6 months). At Visit 1, mean predialysis sK was 4.83 mmol/L, and 39.6% of patients had hyperkalaemia. Most patients (97.7%) received a dialysate potassium concentration of 2.0 mmol/L. The serum-dialysate potassium gradient was greater than 3 mmol/L for over 40% of the cohort (1- < 2, 2- < 3, 3- < 4, and ≥ 4 mmol/L in 13.6%, 45.1%, 35.7%, and 5.2% of patients, respectively; mean: 2.8 mmol/L). The intradialytic sK reduction was 1- < 3 mmol/L for most patients (0- < 1, 1- < 2, 2- < 3, and ≥ 3 mmol/L in 24.2%, 62.2%, 12.8%, and 0.9% of patients, respectively; mean: 1.4 mmol/L). CONCLUSIONS: Hyperkalaemia after a LIDI was common in this real-world cohort of Chinese patients despite standard adequate haemodialysis, and led to large serum-dialysate potassium gradients and intradialytic sK shifts. Previous studies have shown hyperkalaemia and sK fluctuations are highly correlated with poor prognosis. Effective potassium-lowering treatments should be evaluated for the improvement of long-term prognosis through the control of hyperkalaemia and sK fluctuations. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04799067.

PI3K pathway mutation predicts an activated immune microenvironment and better immunotherapeutic efficacy in head and neck squamous cell carcinoma.

BACKGROUND: PI3K pathway is the most frequently mutated pathway in head and neck squamous cell carcinoma (HNSC), which plays a crucial role in tumorigenesis and progression. In the present study, we aimed to investigate the role of PI3K pathway mutation in clinical prognosis prediction and the relationship with immune microenvironment and response rate to immunotherapy. METHODS: We collected 129 samples with immunotherapy information from MSKCC-2019 cohort as well as 501 and 40 samples from TCGA-HNSC and MD-Anderson non-immunotherapy cohorts, respectively. Somatic mutation data was utilized to characterize the mutational status of the PI3K pathway. Subsequently, we further analyzed the differences in prognosis, immunotherapy response, genomic alterations, functional characteristics, and immune microenvironment between the mutation and wild groups. RESULTS: The Kaplan-Meier survival curves displayed that PI3K pathway mutation predicted observably prolonged overall survival (OS) in the immunotherapy cohort MSKCC-2019 (p = 0.012) but did not reach statistical significance in the non-immunotherapy cohorts TCGA-HNSC (p = 0.68) and MD-Anderson (p = 0.68). After incorporating several clinicopathologic features such as age, gender, and tumor mutation burden (TMB), the results of multivariate Cox regression analysis also demonstrated that the PI3K pathway mutation could indicate better immunotherapy outcomes in HNSC patients with a hazard ratio (HR) of 0.533 (95% CI: 0.313-0.910; p = 0.021) in the immunotherapy cohort MSKCC-2019, compared with 0.888 (95% CI: 0.636-1.241; p = 0.487) and 1.939 (95% CI: 0.483-7.781; p = 0.351) in the non-immunotherapy cohorts TCGA-HNSC and MD-Anderson. In addition, the results of the subclass mapping (SubMap) and the tumor immune dysfunction and exclusion (TIDE) also consistently suggested that patients in the mutation group are more likely to benefit from immunotherapy. And further studies showed that the mutation group owned significantly higher TMB, activated immune-related pathways, richer abundance of immune cells, and higher expression levels of immunomodulators. To improve the prognosis of the wild group, we identified five relatively sensitive potential drugs for the wild group, including "BMS-536924," "linsitinib," "NVP-TAE684," "PLX-4720," and "clonazepam." CONCLUSIONS: The PI3K pathway mutation status could be considered as a potential biomarker to predict better immunotherapeutic efficacy and clinical outcomes after immunotherapy in HNSC patients.

FeNC nanozyme-based electrochemical immunoassay for sensitive detection of human epidermal growth factor receptor 2.

The proof-of-concept of sensitive electrochemical immunoassay for the quantitative monitoring of human epidermal growth factor receptor 2 (HER2) is reported. The assay is carried out on iron nitrogen-doped carbon (FeNC) nanozyme-modified screen-printed carbon electrode using chronoamperometry. Introduction of target HER2 can induce the sandwiched immunoreaction between anti-HER2 monoclonal antibody-coated microplate and biotinylated anti-HER2 polyclonal antibody. Thereafter, streptavidin-glucose oxidase (GOx) conjugate is bonded to the detection antibody. Upon addition of glucose, 3,3',5,5'-tetramethylbenzidine (TMB) is oxidized through the produced H2O2 with the assistance of GOx and FeNC nanozyme. The oxidized TMB is determined via chronoamperometry. Experimental results revealed that electrochemical immunosensing system exhibited good amperometric response, and allowed the detection of target HER2 as low as 4.5 pg/mL. High specificity and long-term stability are acquired with FeNC nanozyme-based sensing strategy. Importantly, our system provides a new opportunity for protein diagnostics.

Three-Dimensional Printed Poly (Lactic-co-Glycolic Acid)-Magnesium Composite Scaffolds for the Promotion of Osteogenesis Through Immunoregulation.

Scaffolds play an important role in bone tissue engineering. The ideal engineered scaffold needs to be biocompatible, bioactive, and able to regulate immune cells to enhance bone regeneration. In this study, magnesium (Mg)-contained poly(lactic-co-glycolic acid) (PLGA) scaffolds (hereinafter, referred to as PLGA-2Mg) were fabricated by 3-dimensional printing using a mixture of PLGA and MgSO 4 powder. Poly(lactic-co-glycolic acid) scaffolds (hereinafter, referred to as PLGA) were also fabricated by 3-dimensional printing and were used as control. The biocompatibility, immunoregulatory ability, and osteogenic properties of PLGA-2Mg were analyzed and compared with those of PLGA. The results indicate that the incorporation of Mg increased the Young modulus and surface roughness of the scaffold, but did not affect its degradation. The PLGA-2Mg further promoted the adhesion and proliferation of MC3T3-E1 cells compared with PLGA, which indicates its improved biocompatibility and bioactivity. In addition, PLGA-2Mg inhibited the polarization of RAW 264.7 cells toward the M1 phenotype by down-regulating the IL-1ß , IL-6 , and iNOs gene expression when challenged with lipopolysaccharide stimulation. In contrast, it promoted the polarization of RAW 264.7 cells toward the M2 phenotype by up-regulating the TGF-ß , IL-10 , and Arg-1 gene expression without lipopolysaccharide stimulation. Finally, MC3T3-E1 cells were cocultured with RAW 264.7 cells and scaffolds using a transwell system. It was found that the expression level of osteogenic-related genes ( ALP , COL-1 , BMP2 , and BSP ) was significantly upregulated in the PLGA-2Mg group compared with that in the PLGA group. Consequently, PLGA-2Mg with increased biocompatibility and bioactivity can promote osteogenesis through immunoregulation and has the potential to be used as a novel scaffold in bone tissue engineering.

Calcium leaching characteristics in landfill leachate collection systems from bottom ash of municipal solid waste incineration.

Calcium leaching is a critical factor in the clogging of leachate collection systems (LCS), a phenomenon that affects landfill stability and operation. The bottom ash (BA) of municipal solid waste (MSW) incineration plants contains large quantities of calcium-based compounds. Landfilling is the main disposal method for BA in China that intensifies the consequences of LCS clogging. The factors influencing BA calcium leaching were investigated using simulated leachate. The results showed that fine BA particles, low pH values, high temperature, and ratios of leachate to BA solids were conducive to calcium leaching. Calcium leaching was found to be higher in actual leachate than in simulated leachate. At pH = 5, the cumulative calcium dissolution ratios (CDRs) were 83.36% and 31.49% after 20 days of leaching in the actual and simulated leachate, respectively; at pH = 6, the values were 50.67% and 12.06%, respectively. The introduction of landfill gas could decrease the calcium dissolution and leaching rates. When the ratio of leachate to BA solid was 20:1 mL/g, the accumulative CDR values were 45.98% (pH = 6) and 5.80% (pH = 8) without landfill gases, and 4.59% (pH = 6) and 0.48% (pH = 8) with landfill gases. These results provide the scientific basis for clogging risk prediction with respect to calcium leaching in the LCS of landfills. BA landfilling in old landfill areas with relatively high leachate pH and low chemical oxygen demand, as well as when leachate mixed with an appropriate amount of landfill gases, could be feasible measures to reduce calcium leaching and further prevent clogging in LCS.

Bioaccessibility and health risk assessment of arsenic in soil and indoor dust in rural and urban areas of Hubei province, China.

Incidental oral ingestion is the main exposure pathway by which human intake contaminants in both soil and indoor dust, and this is especially true for children as they frequently exhibit hand-to-mouth behaviour. Research on comprehensive health risk caused by incidental ingestion of both soil and indoor dust is limited. The aims of this study were to investigate the arsenic concentration and to characterize the health risks due to arsenic (As) exposure via soil and indoor dust in rural and urban areas of Hubei province within central China. Soil and indoor dust samples were collected from schools and residential locations and bioaccessibility of arsenic in these samples was determined by a simplified bioaccessibility extraction test (SBET). The total arsenic content in indoor dust samples was 1.78-2.60 times that measured in soil samples. The mean As bioaccessibility ranged from 75.4% to 83.2% in indoor dust samples and from 13.8% to 20.2% in soil samples. A Pearson's analysis showed that As bioaccessibility was significantly correlated with Fe and Al in soil and indoor dust, respectively, and activity patterns of children were utilised in the assessment of health risk via incidental ingestion of soil and indoor dust. The results suggest no non-carcinogenic health risks (HQ<1) or acceptable carcinogenic health risks (1×10(-6)

Exploring the effect of part differences on metabolite molecule changes in refrigerated pork: Identifying key metabolite compounds and their conversion pathways.

Effect of part differences on metabolite molecule alterations in refrigerated pork was investigated. A metabolomics methodology combined with chemometric analysis was successfully established to identify key compounds and their conversion pathways, including precursors and volatile metabolites, in the Longissimus lumborum as well as the breast and flank stored for 11 days. In total, 12 discriminative precursors were identified using the Short Time-series Expression Miner. In tandem with Random Forest and ANOVA analyses, nine volatile metabolites were identified as key compounds that could be attributed to differences in pork sections. Bidirectional orthogonal partial least squares analysis revealed a potential correlation between these key metabolites and discriminative precursors. Metabolic pathway enrichment analysis demonstrated that the primary metabolic process affected by variations in pork sections is linoleic acid metabolism, which participates in the metabolism of cysteine and glutamic acid to produce methoxy-phenyl-oxime. This study provides valuable insights into the identification of differential metabolites.

In-depth metaproteomics analysis reveals the protein profile and metabolism characteristics in pork during refrigerated storage.

Alterations in microbiotas and endogenous enzymes have been implicated in meat deterioration. However, the factors that mediate the interactions between meat quality and microbiome profile were inadequately investigated. In this study, we collected pork samples throughout the refrigeration period and employed metaproteomics to characterize both the pork and microbial proteins. Our findings demonstrated that pork proteins associated with the catabolic process are upregulated during storage compared to the initial stage. Pseudomonas, Clostridium, Goodfellowiella, and Gonapodya contribute to the spoilage process. Notably, we observed an elevated abundance of microbial proteins related to glycolytic enzymes in refrigerated pork, identifying numerous proteins linked to biogenic amine production, thus highlighting their essential role in microbial decay. Further, we reveal that many of these microbial proteins from Pseudomonas are ribosomal proteins, promoting enzyme synthesis by enhancing transcription and translation. This study provides intrinsic insights into the underlying mechanisms by which microorganisms contribute to meat spoilage.

Quality, Thermo-Rheology, and Microstructure Characteristics of Cubic Fat Substituted Pork Patties with Composite Emulsion Gel Composed of Konjac Glucomannan and Soy Protein Isolate.

Composite emulsion gel can effectively mimic animal adipose tissue. In this study, composite emulsion gels composed of soy protein isolates and konjac glucomannan (KGM) were prepared as plant-based cubic fat substitutes (CFS). The effects of CFS on the quality and structure of pork patties were investigated in terms of the proximate composition, lipid oxidation stability, technological characteristics, color, sensory attributes, texture, thermo-rheological behavior, and microstructure. CFS samples composed of various ratios of KGM were added to lean meat patties to ascertain the optimal CFS composition for its potential replacement of pork back fat in patties. The addition of CFS containing 7.0% KGM was found to decrease the hardness of the lean meat patties by 71.98% while simultaneously improving their sensory quality. The replacement of pork back fat with CFS also reduced the fat content of the patties to as little as 3.65%. Furthermore, the addition of CFS enhanced the technological characteristics, lipid oxidation stability, and surface color of the fat-replaced patties, with no significant impact on their overall acceptability. The gel network of the patties was shown to be fine and remained compact as the fat replacement ratio increased to 75%, while the texture parameters, storage modulus, and fractal dimension all increased. Quality and structure improvements may allow the composite emulsion gels to replace fat in pork patties to support a healthy diet. This study may be beneficial for the application and development of plant-based cubic fat substitutes.

Development of a rhodamine-based fluorescent probe for ATP detection for potential applications in meat freshness assessment.

Adenosine triphosphate (ATP) plays a vital role in physiological processes and is an essential indicator of microbial content in food. Herein, a new sensitive, rapid and water-soluble probe for ATP detection was developed. Rhodamine B and pentaethylenehexamine were employed to design and synthesise the probe rhodamine-pentaethylenehexamine (RP) for selective ATP detection. The synthesised probe RP was characterized using Fourier transform infrared, NMR and dynamic light scattering size distributions. Upon the addition of ATP, the probe exhibited a distinct change in fluorescence intensity, with fluorescence emission at 580 nm. A linear relationship was observed between fluorescence intensity and ATP concentrations at 0-50 µmol/L, with a limit of detection of 10.97 × 10-9 mol/L. The results of the zeta potential and molecular dynamics simulation demonstrated that the detection mechanism of the probe RP is associated with the electrostatic adsorption interaction between the multi-positively charged sites of RP and the negatively charged triphosphate structure of ATP. Our study provides new insights into improving charge site identification in small molecule detection. Furthermore, the successful detection of ATP on meat surfaces indicates that RP has the potential to assess meat freshness.

Machine learning-driven diagnostic signature provides new insights in clinical management of hypertrophic cardiomyopathy.

AIMS: In an era of evolving diagnostic possibilities, existing diagnostic systems are not fully sufficient to promptly recognize patients with early-stage hypertrophic cardiomyopathy (HCM) without symptomatic and instrumental features. Considering the sudden death of HCM, developing a novel diagnostic model to clarify the patients with early-stage HCM and the immunological characteristics can avoid misdiagnosis and attenuate disease progression. METHODS AND RESULTS: Three hundred eighty-five samples from four independent cohorts were systematically retrieved. The weighted gene co-expression network analysis, differential expression analysis (|log2(foldchange)| > 0.5 and adjusted P < 0.05), and protein-protein interaction network were sequentially performed to identify HCM-related hub genes. With a machine learning algorithm, the least absolute shrinkage and selection operator regression algorithm, a stable diagnostic model was developed. The immune-cell infiltration and biological functions of HCM were also explored to characterize its underlying pathogenic mechanisms and the immune signature. Two key modules were screened based on weighted gene co-expression network analysis. Pathogenic mechanisms relevant to extracellular matrix and immune pathways have been discovered. Twenty-seven co-regulated genes were recognized as HCM-related hub genes. Based on the least absolute shrinkage and selection operator algorithm, a stable HCM diagnostic model was constructed, which was further validated in the remaining three cohorts (n = 385). Considering the tight association between HCM and immune-related functions, we assessed the infiltrating abundance of various immune cells and stromal cells based on the xCell algorithm, and certain immune cells were significantly different between high-risk and low-risk groups. CONCLUSIONS: Our study revealed a number of hub genes and novel pathways to provide potential targets for the treatment of HCM. A stable model was developed, providing an efficient tool for the diagnosis of HCM.