Tetradentate Pt(II) complexes based on xylenylamino linked dual pyrazolate chelates for organic light emitting diodes.

In this work, we report the syntheses of three Pt(II) emitters, namely, Pt4N1, Pt4N2, and Pt4N3, to which their tetradentate chelates were assembled by linking two pyrazolate chelates with a single xylenylamino entity. Functionalization of Pt4N1 was achieved upon addition of electronegative CF3 substituent on pyridinyl groups and switching to more electron deficient pyrazinyl groups in giving Pt4N2 and Pt4N3, respectively. The vertical arranged xylenylamino entity has effectively suppressed the inter-molecular π-π stacking and Pt···Pt interaction, as shown by the single crystal X-ray structural analyses. Upon fabrication of OLED devices, Pt4N2 and Pt4N3 based devices delivered efficient cyan and green emission, with an EQEmax of 15.2% and 11.2%, respectively, affirming the successfulness of the tetradentate chelating strategy.

Joint use of population pharmacokinetics and machine learning for prediction of valproic acid plasma concentration in elderly epileptic patients.

BACKGROUND: Valproic acid (VPA) is a commonly used broad-spectrum antiepileptic drug. For elderly epileptic patients, VPA plasma concentrations have a considerable variation. We aim to establish a prediction model via a combination of machine learning and population pharmacokinetics (PPK) for VPA plasma concentration. METHODS: A retrospective study was performed incorporating 43 variables, including PPK parameters. Recursive Feature Elimination with Cross-Validation was used for feature selection. Multiple algorithms were employed for ensemble model, and the model was interpreted by Shapley Additive exPlanations. RESULTS: The inclusion of PPK parameters significantly enhances the performance of individual algorithm model. The composition of categorical boosting, light gradient boosting machine, and random forest (7:2:1) with the highest R2 (0.74) was determined as the ensemble model. The model included 11 variables after feature selection, of which the predictive performance was comparable to the model that incorporated all variables. CONCLUSIONS: Our model was specifically tailored for elderly epileptic patients, providing an efficient and cost-effective approach to predict VPA plasma concentration. The model combined classical PPK with machine learning, and underwent optimization through feature selection and algorithm integration. Our model can serve as a fundamental tool for clinicians in determining VPA plasma concentration and individualized dosing regimens accordingly.

Advances in Artificial Intelligence-Assisted Coronary Computed Tomographic Angiography for Atherosclerotic Plaque Characterization.

Coronary artery disease is a leading cause of death worldwide. Major adverse cardiac events are associated not only with coronary luminal stenosis but also with atherosclerotic plaque components. Coronary computed tomography angiography (CCTA) enables non-invasive evaluation of atherosclerotic plaque along the entire coronary tree. However, precise and efficient assessment of plaque features on CCTA is still a challenge for physicians in daily practice. Artificial intelligence (AI) refers to algorithms that can simulate intelligent human behavior to improve clinical work efficiency. Recently, cardiovascular imaging has seen remarkable advancements with the use of AI. AI-assisted CCTA has the potential to facilitate the clinical workflow, offer objective and repeatable quantitative results, accelerate the interpretation of reports, and guide subsequent treatment. Several AI algorithms have been developed to provide a comprehensive assessment of atherosclerotic plaques. This review serves to highlight the cutting-edge applications of AI-assisted CCTA in atherosclerosis plaque characterization, including detecting obstructive plaques, assessing plaque volumes and vulnerability, monitoring plaque progression, and providing risk assessment. Finally, this paper discusses the current problems and future directions for implementing AI in real-world clinical settings.

Exploring brain asymmetry in early-stage Parkinson's disease through functional and structural MRI.

OBJECTIVE: This study explores the correlation between asymmetrical brain functional activity, gray matter asymmetry, and the severity of early-stage Parkinson's disease (PD). METHODS: Ninety-three early-stage PD patients (ePD, H-Y stages 1-2.5) were recruited, divided into 47 mild (ePD-mild, H-Y stages 1-1.5) and 46 moderate (ePD-moderate, H-Y stages 2-2.5) cases, alongside 43 matched healthy controls (HCs). The study employed the Hoehn and Yahr (H-Y) staging system for disease severity assessment and utilized voxel-mirrored homotopic connectivity (VMHC) for analyzing brain functional activity asymmetry. Asymmetry voxel-based morphometry analysis (VBM) was applied to evaluate gray matter asymmetry. RESULTS: The study found that, relative to HCs, both PD subgroups demonstrated reduced VMHC values in regions including the amygdala, putamen, inferior and middle temporal gyrus, and cerebellum Crus I. The ePD-moderate group also showed decreased VMHC in additional regions such as the postcentral gyrus, lingual gyrus, and superior frontal gyrus, with notably lower VMHC in the superior frontal gyrus compared to the ePD-mild group. A negative correlation was observed between the mean VMHC values in the superior frontal gyrus and H-Y stages, UPDRS, and UPDRS-III scores. No significant asymmetry in gray matter was detected. CONCLUSIONS: Asymmetrical brain functional activity is a significant characteristic of PD, which exacerbates as the disease severity increases, resembling the dissemination of Lewy bodies across the PD neurological framework. VMHC emerges as a potent tool for characterizing disease severity in early-stage PD.

Automated segmentation of brain metastases with deep learning: a multi-center, randomized crossover, multi-reader evaluation study.

BACKGROUND: Artificial intelligence has been proposed for brain metastasis (BM) segmentation but it has not been fully clinically validated. The aim of this study was to develop and evaluate a system for BM segmentation. METHODS: A deep-learning-based BM segmentation system (BMSS) was developed using contrast-enhanced MR images from 488 patients with 10,338 brain metastases. A randomized crossover, multi-reader study was then conducted to evaluate the performance of the BMSS for BM segmentation using data prospectively collected from 50 patients with 203 metastases at five centers. Five radiology residents and five attending radiologists were randomly assigned to contour the same prospective set in assisted and unassisted modes. Aided and unaided Dice similarity coefficients (DSCs) and contouring times per lesion were compared. RESULTS: The BMSS alone yielded a median DSC of 0.91 (95% confidence interval, 0.90-0.92) in the multi-center set and showed comparable performance between the internal and external sets (p = 0.67). With BMSS assistance, the readers increased the median DSC from 0.87 (0.87-0.88) to 0.92 (0.92-0.92) (p < 0.001) with a median time saving of 42% (40-45%) per lesion. Resident readers showed a greater improvement than attending readers in contouring accuracy (improved median DSC, 0.05 [0.05-0.05] vs. 0.03 [0.03-0.03]; p < 0.001), but a similar time reduction (reduced median time, 44% [40-47%] vs. 40% [37-44%]; p = 0.92) with BMSS assistance. CONCLUSIONS: The BMSS can be optimally applied to improve the efficiency of brain metastasis delineation in clinical practice.

Asian Screening Array and Next-Generation Sequencing Based Panels Applied to Preimplantation Genetic Testing for Monogenic Disorders Preclinical Workup in 294 Families: A Retrospective Analysis.

OBJECTIVE: Currently, the most commonly used methods for linkage analysis of pre-implantation genetic testing for monogenic disorders (PGT-M) are next generation sequencing (NGS) and SNP array. We aim to investigate whether the application efficacy of Asian screening array (ASA) in PGT-M preclinical workup for the Chinese population is superior to NGS based single nucleotide polymorphism (SNP) panels. METHODS: We conducted a retrospective analysis by reviewing 294 couples from a single center over the past 4 years and compared the detection results between NGS-based SNP panels and ASA. Using the numbers of informative SNPs upstream and downstream flanking of variants, we assessed the detection efficiency of both methods in monogenic diseases, chromosomal microdeletion syndrome and males with de novo variants, among other scenarios. RESULTS: Results indicate that ASA offers a greater number of informative SNPs compared with NGS-based SNP panels. Additionally, data analysis for ASA is generally more straightforward and may require less computational resources. While ASA can address most PGT-M challenges, we have also identified certain genes in previous tests that are not suitable for PGT-M using ASA. CONCLUSION: The application of ASA in PGT-M preclinical workup for Chinese populations has good practical value as it can perform linkage analysis for most genetic variants. However, for certain variants, NGS or other testing methods, such as mutated allele revealed by sequencing with aneuploidy and linkage analysis (MARSALA), may still be necessary for completion.

Fully Flexible Molecular Alignment Enables Accurate Ligand Structure Modeling.

Accurate protein-ligand binding poses are the prerequisites of structure-based binding affinity prediction and provide the structural basis for in-depth lead optimization in small molecule drug design. However, it is challenging to provide reasonable predictions of binding poses for different molecules due to the complexity and diversity of the chemical space of small molecules. Similarity-based molecular alignment techniques can effectively narrow the search range, as structurally similar molecules are likely to have similar binding modes, with higher similarity usually correlated to higher success rates. However, molecular similarity is not consistently high because molecules often require changes to achieve specific purposes, leading to reduced alignment precision. To address this issue, we propose a new alignment method─Z-align. This method uses topological structural information as a criterion for evaluating similarity, reducing the reliance on molecular fingerprint similarity. Our method has achieved success rates significantly higher than those of other methods at moderate levels of similarity. Additionally, our approach can comprehensively and flexibly optimize bond lengths and angles of molecules, maintaining a high accuracy even when dealing with larger molecules. Consequently, our proposed solution helps in achieving more accurate binding poses in protein-ligand docking problems, facilitating the development of small molecule drugs. Z-align is freely available as a web server at https://cloud.zelixir.com/zalign/home.

Serum metabolomics analysis of patients with chronic obstructive pulmonary disease and 'frequent exacerbator' phenotype.

Chronic obstructive pulmonary disease (COPD) exacerbations accelerate loss of lung function and increased mortality. The complex nature of COPD presents challenges in accurately predicting and understanding frequent exacerbations. The present study aimed to assess the metabolic characteristics of the frequent exacerbation of COPD (COPD­FE) phenotype, identify potential metabolic biomarkers associated with COPD­FE risk and evaluate the underlying pathogenic mechanisms. An internal cohort of 30 stable patients with COPD was recruited. A widely targeted metabolomics approach was used to detect and compare serum metabolite expression profiles between patients with COPD­FE and patients with non­frequent exacerbation of COPD (COPD­NE). Bioinformatics analysis was used for pathway enrichment analysis of the identified metabolites. Spearman's correlation analysis assessed the associations between metabolites and clinical indicators, while receiver operating characteristic (ROC) analysis evaluated the ability of metabolites to distinguish between two groups. An external cohort of 20 patients with COPD validated findings from the internal cohort. Out of the 484 detected metabolites, 25 exhibited significant differences between COPD­FE and COPD­NE. Metabolomic analysis revealed differences in lipid, energy, amino acid and immunity pathways. Spearman's correlation analysis demonstrated associations between metabolites and clinical indicators of acute exacerbation risk. ROC analysis demonstrated that the area under the curve (AUC) values for D­fructose 1,6­bisphosphate (AUC=0.871), arginine (AUC=0.836), L­2­hydroxyglutarate (L­2HG; AUC=0.849), diacylglycerol (DG) (16:0/20:5) (AUC=0.827), DG (16:0/20:4) (AUC=0.818) and carnitine­C18:2 (AUC=0.804) were >0.8, highlighting their discriminative capacity between the two groups. External validation results demonstrated that DG (16:0/20:5), DG (16:0/20:4), carnitine­C18:2 and L­2HG were significantly different between patients with COPD­FE and those with COPD­NE. In conclusion, the present study offers insights into early identification, mechanistic understanding and personalized management of the COPD­FE phenotype.

Hydrophobic tagging of small molecules: an overview of the literature and future outlook.

INTRODUCTION: Hydrophobic tagging (HyT) technology presents a distinct therapeutic strategy diverging from conventional small molecule drugs, providing an innovative approach to drug design. This review aims to provide an overview of the HyT literature and future outlook to offer guidance for drug design. AREAS COVERED: In this review, the authors introduce the composition, mechanisms and advantages of HyT technology, as well as summarize the detailed applications of HyT technology in anti-cancer, neurodegenerative diseases (NDs), autoimmune disorders, cardiovascular diseases (CVDs), and other fields. Furthermore, this review discusses key aspects of the future development of HyT molecules. EXPERT OPINION: HyT emerges as a highly promising targeted protein degradation (TPD) strategy, following the successful development of proteolysis targeting chimeras (PROTAC) and molecular glue. Based on exploring new avenues, modification of the HyT molecule itself potentially enhances the technology. Improved synthetic pathways and emphasis on pharmacokinetic (PK) properties will facilitate the development of HyT. Furthermore, elucidating the biochemical basis by which the compound's hydrophobic moiety recruits the protein homeostasis network will enable the development of more precise assays that can guide the optimization of the linker and hydrophobic moiety.

Corrigendum: Cortical gyrification pattern of depression in Parkinson's disease: a neuroimaging marker for disease severity?

[This corrects the article DOI: 10.3389/fnagi.2023.1241516.].

Advancing Real-World Image Dehazing: Perspective, Modules, and Training.

Restoring high-quality images from degraded hazy observations is a fundamental and essential task in the field of computer vision. While deep models have achieved significant success with synthetic data, their effectiveness in real-world scenarios remains uncertain. To improve adaptability in real-world environments, we construct an entirely new computational framework by making efforts from three key aspects: imaging perspective, structural modules, and training strategies. To simulate the often-overlooked multiple degradation attributes found in real-world hazy images, we develop a new hazy imaging model that encapsulates multiple degraded factors, assisting in bridging the domain gap between synthetic and real-world image spaces. In contrast to existing approaches that primarily address the inverse imaging process, we design a new dehazing network following the "localization-and-removal" pipeline. The degradation localization module aims to assist in network capture discriminative haze-related feature information, and the degradation removal module focuses on eliminating dependencies between features by learning a weighting matrix of training samples, thereby avoiding spurious correlations of extracted features in existing deep methods. We also define a new Gaussian perceptual contrastive loss to further constrain the network to update in the direction of the natural dehazing. Regarding multiple full/no-reference image quality indicators and subjective visual effects on challenging RTTS, URHI, and Fattal real hazy datasets, the proposed method has superior performance and is better than the current state-of-the-art methods. See more results: https://github.com/fyxnl/KA Net.

Melatonin ameliorates multiorgan injuries induced by severe acute pancreatitis in mice by regulating the Nrf2 signaling pathway.

Severe acute pancreatitis (SAP) is a complicated inflammatory reaction that impacts the pancreas, often resulting in damage to numerous organs. This disorder encompasses a range of processes such as inflammation, oxidative stress, and pancreatitis. The hormone melatonin (MT) is primarily secreted by the pineal gland and plays a crucial role in mitigating inflammation, countering the harmful effects of free radicals, and regulating oxidative stress. The aim of this research was to investigate the potential protective impact and the underlying mechanism of melatonin in mice afflicted with SAP. The biochemical and histological assessments unequivocally demonstrated that melatonin effectively inhibited necrosis, infiltration, edema and cell death in pancreatic tissues, thereby suppressing acute pancreatitis. Notably, melatonin also alleviated the consequent harm to distant organs, notably the lungs, liver, and kidneys. Furthermore, both preventive and therapeutic administration of melatonin prompted nuclear factor E2-related factor 2 (Nrf2) activation followed by Nrf2 target gene expression. Nrf2 initiates the activation of antioxidant genes, thereby providing defense against oxidative stress. Conversely, Nrf2 reduction may contribute to impaired antioxidant protection in SAP. The beneficial impact of Nrf2 on antioxidants was absent in Nrf2-knockout mice, leading to the accumulation of LDH and exacerbation of cell death. This deterioration in both pancreatitis and injuries in distant organs intensified significantly. The results indicate that melatonin has an enhanced ability to protect against multiorgan damage caused by SAP, which is accomplished through the increase in Nrf2 expression. Additionally, Nrf2 initiates the activation of antioxidant genes that offer defense against cell death.

Novel insights into dimethylsulfoniopropionate cleavage by deep subseafloor fungi.

Dimethylsulfoniopropionate (DMSP), a key organic sulfur compound in marine and subseafloor sediments, is degraded by phytoplankton and bacteria, resulting in the release of the climate-active volatile gas dimethylsulfide (DMS). However, it remains unclear if dominant eukaryotic fungi in subseafloor sediments possess specific abilities and metabolic mechanisms for DMSP degradation and DMS formation. Our study provides the first evidence that fungi from coal-bearing sediments ∼2 km below the seafloor, such as Aspergillus spp., Chaetomium globosum, Cladosporium sphaerospermum, and Penicillium funiculosum, can degrade DMSP and produce DMS. In Aspergillus sydowii 29R-4-F02, which exhibited the highest DMSP-dependent DMS production rate (16.95 pmol/µg protein/min), two DMSP lyase genes, dddP and dddW, were identified. Remarkably, the dddW gene, previously observed only in bacteria, was found to be crucial for fungal DMSP cleavage. These findings not only extend the list of fungi capable of degrading DMSP, but also enhance our understanding of DMSP lyase diversity and the role of fungi in DMSP decomposition in subseafloor sedimentary ecosystems.

Coronary CTA-based Vascular Radiomics Predicts Atherosclerosis Development Proximal to LAD Myocardial Bridging.

BACKGROUND: Cardiac cycle morphological changes can accelerate plaque growth proximal to myocardial bridging (MB) in the left anterior descending artery (LAD). OBJECTIVE: To assess coronary CT angiography (CCTA)-based vascular radiomics for predicting proximal plaque development in LAD MB. METHODS: Patients with repeated CCTA scans showing LAD MB without proximal plaque in index CCTA were included from Jinling Hospital as development set. They were divided into training and internal testing in an 8:2 ratio. Patients from 4 other tertiary hospitals were set as external validation set. The endpoint was proximal plaque development of LAD MB in follow-up CCTA. Four vascular radiomics models were built: MB centerline (MB CL), proximal MB CL (pMB CL), MB cross section (MB CS), and proximal MB CS (pMB CS), whose performances were evaluated using area under the curve (AUC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI). RESULTS: 295 patients were included in the development (n=192; median age, 54±11 years; 137 men) and external validation sets (n=103; median age, 57±9 years; 57 men). The pMB CS vascular radiomics model exhibited higher AUCs in training, internal test, and external sets (AUC=0.78, 0.75, 0.75) than the clinical and anatomical model (all p<0.05). Integration of the pMB CS vascular radiomics model significantly raised the AUC of the clinical and anatomical model from 0.56 to 0.75 (p=0.002), along with enhanced NRI (0.76 [0.37-1.14], p<0.001) and IDI (0.17 [0.07-0.26], p<0.001) in the external validation set. CONCLUSION: The CCTA-based pMB CS vascular radiomics model can predict plaque development in LAD MB.

Base-Promoted Synthesis of Isoquinolines through a Tandem Reaction of 2-Methyl-arylaldehydes and Nitriles.

A convenient method for preparing 3-aryl isoquinolines via a base-promoted tandem reaction is presented. Simply combining commercially available 2-methyl-arylaldehydes, benzonitriles, NaN(SiMe3)2, and Cs2CO3 enabled the synthesis of a variety of isoquinolines (23 examples, ≤90% yield). Among the syntheses of isoquinolines, the transition metal-free method described here is straightforward, practical, and operationally simple.

E3 ubiquitin ligase UBR5 promotes gemcitabine resistance in pancreatic cancer by inducing O-GlcNAcylation-mediated EMT via destabilization of OGA.

Pancreatic cancer (PC) is among the deadliest malignancies, with an extremely poor diagnosis and prognosis. Gemcitabine (GEM) remains the first-line drug for treating PC; however, only a small percentage of patients benefit from current immunotherapies or targeted therapies. Resistance to GEM is prevalent and affects long-term survival. We found that ubiquitin-protein ligase E3 module N-recognition 5 (UBR5) is a therapeutic target against GEM resistance. UBR5 was markedly upregulated in clinical GEM-resistant PC samples and GEM-resistant PC cells. UBR5 knockdown markedly increased GEM sensitivity in GEM-resistant PC cell lines. UBR5-mediated GEM resistance was accompanied by activation of epithelial-mesenchymal transition (EMT) and could be mitigated by inhibiting EMT. Further analysis revealed that UBR5 promoted GEM resistance in PC cells by enhancing O-GlcNAcylation-mediated EMT. In addition, UBR5 knockdown resulted in increased O-GlcNAase (OGA) levels, an essential negatively regulated enzyme in the O-GlcNAcylation process. We identified a negative association between OGA and UBR5 levels, which further supported the hypothesis that O-GlcNAcylation-mediated GEM resistance induced by UBR5 is OGA-dependent in PC cells. Mechanistic studies revealed that UBR5 acts as an E3 ubiquitin ligase of OGA and regulates O-GlcNAcylation by binding and modulating OGA, facilitating its degradation and ubiquitination. Additionally, high-throughput compound library screening using three-dimensional protein structure analysis and drug screening identified a Food and Drug Administration drug, Y-39983 dihydrochloride, as a potent GEM sensitiser and UBR5 inhibitor. The combination of Y-39983 dihydrochloride and GEM attenuated tumour growth in a mouse xenograft tumour model. Collectively, these data demonstrated that UBR5 plays a pivotal role in the sensitisation of PC to GEM and provides a potential therapeutic strategy to overcome GEM resistance.

Effects of modified-BHI medium on the growth and metabolites of Akkermansia muciniphila.

Akkermansia muciniphila (Akk) has recently become popular due to its therapeutic effect on various diseases. However, Akk's high-density cultivation is difficult due to its anaerobic characteristics. Therefore, Akk was cultured with modified brain-heart infusion (M-BHI) to reach 1011 CFU/mL. 1H-NMR determined the metabolites of Akk and validated them by an amino acid analyzer. Compared to the BHI, Akk significantly up-regulated lactate, histidine, fumaric acid, cytidine, threonine, arginine, and hydroxyproline in the M-BHI and significantly down-regulated methionine, trimethylamine, and sarcosine. Regarding pathway enrichment analysis, histidine metabolism, arginine and proline metabolism, cysteine and methionine metabolism mainly regulate differential metabolites. In addition, M-BHI alters the metabolic profile by affecting Akk's involvement in amino acid metabolism remodeling. Changed metabolites showed that Akk fermentation in M-BHI may play a physiological role in regulating immune homeostasis and reducing risk factors related to diseases. Therefore, M-BHI provides a promising reference for Akk cultivation in future industrial preparation. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-023-01492-x.

Diagnostic and prognostic performance of artificial intelligence-based fully-automated on-site CT-FFR in patients with CAD.

Currently, clinically available coronary CT angiography (CCTA) derived fractional flow reserve (CT-FFR) is time-consuming and complex. We propose a novel artificial intelligence-based fully-automated, on-site CT-FFR technology, which combines the automated coronary plaque segmentation and luminal extraction model with reduced order 3 dimentional (3D) computational fluid dynamics. A total of 463 consecutive patients with 600 vessels from the updated China CT-FFR study in Cohort 1 undergoing both CCTA and invasive fractional flow reserve (FFR) within 90 d were collected for diagnostic performance evaluation. For Cohort 2, a total of 901 chronic coronary syndromes patients with index CT-FFR and clinical outcomes at 3-year follow-up were retrospectively analyzed. In Cohort 3, the association between index CT-FFR from triple-rule-out CTA and major adverse cardiac events in patients with acute chest pain from the emergency department was further evaluated. The diagnostic accuracy of this CT-FFR in Cohort 1 was 0.82 with an area under the curve of 0.82 on a per-patient level. Compared with the manually dependent CT-FFR techniques, the operation time of this technique was substantially shortened by 3 times and the number of clicks from about 60 to 1. This CT-FFR technique has a highly successful (> 99%) calculation rate and also provides superior prediction value for major adverse cardiac events than CCTA alone both in patients with chronic coronary syndromes and acute chest pain. Thus, the novel artificial intelligence-based fully automated, on-site CT-FFR technique can function as an objective and convenient tool for coronary stenosis functional evaluation in the real-world clinical setting.

Antiaging Effects of Human Fecal Transplants with Different Combinations of Bifidobacterium bifidum LTBB21J1 and Lactobacillus casei LTL1361 in d-Galactose-Induced Mice.

The feces of healthy middle-aged and old people were first transplanted into d-galactose-induced aging mice to construct humanized aging mice with gut microbiota (FMTC) to confirm the antiaging effect of probiotics produced from centenarians. The mouse model was then treated with centenarian-derived Bifidobacterium bifidum (FMTL), Lactobacillus casei (FMTB), and their mixtures (FMTM), and young mice were used as the control. Compared with the FMTC group, the results demonstrated that the probiotics and their combinations alleviated neuronal damage, increased antioxidant capacity, decreased inflammation, and enhanced cognitive and memory functions in aging mice. In the gut microbiota, the relative abundance of Lactobacillus, Ligilactobacillus, and Akkermansia increased and that of Desulfovibrio and Colidextribacter decreased in the FMTM group compared with that in the FMTC group. The three probiotic groups displayed significant changes in 15 metabolites compared with the FMTC group, with 4 metabolites showing increased expression and 11 metabolites showing decreased expression. The groups were graded as Control > FMTM > FMTB > FMTL > FMTC using a newly developed comprehensive quantitative scoring system that thoroughly analyzed the various indicators of this study. The beneficial antiaging effects of probiotics derived from centenarians were quantitatively described using a novel perspective in this study; it is confirmed that both probiotics and their combinations exert antiaging effects, with the probiotic complex group exhibiting a larger effect.

Exogenous 5-Aminolevulinic acid improved low-temperature tolerance tomato seedling by regulating starch content and phenylalanine metabolism.

Tomato is an important horticultural cash crop, and low-temperature stress has seriously affected the yield and quality of tomato. 5-Aminolevulinic acid (ALA) is widely used in agriculture as an efficient and harmless growth regulator. It is currently unclear whether exogenous ALA can cope with low-temperature stress by regulating tomato starch content and phenylalanine metabolism. In this study, exogenous ALA remarkably improved the low-temperature tolerance of tomato seedlings. RNA-sequencing results showed that exogenous ALA affected starch metabolism and phenylalanine metabolism in tomato seedling leaves under low-temperature stress. Subsequently, we used histochemical staining, observation of chloroplast microstructure, substance content determination, and qRT-PCR analysis to demonstrate that exogenous ALA could improve the low-temperature tolerance of tomato seedlings by regulating starch content and phenylalanine metabolism (SlPAL, SlPOD1, and SlPOD2). Simultaneously, we found that exogenous ALA induced the expression of SlMYBs and SlWRKYs under low-temperature stress. In addition, dual luciferase, yeast one hybrid, and electrophoretic mobility shift assays indicate that SlMYB4 and SlMYB88 could regulate the expression of SlPOD2 in phenylalanine metabolism. We demonstrated that exogenous ALA could improve the low-temperature tolerance of tomato seedlings by regulating starch content and phenylalanine metabolism.