Genome-wide variants and optimal allelic combinations for citric acid in tomato.

Citric acid (CA) plays a crucial role as a fruit flavor enhancer and serves as a mediator in multiple metabolic pathways in tomato fruit development. Understanding factors influencing CA metabolism is essential for enhancing fruit flavor and CA-mediated biological processes. The accumulation of CA, however, is influenced by a complex interplay of genetic and environmental factors, leading to challenges in accurately predicting and regulating its levels. In this study, we conducted a genome-wide association study (GWAS) on CA, employing six landmark models based on genome-wide variations including structural variants, insertions and deletions, and single nucleotide polymorphisms. The identification of 11 high-confidence candidate genes was further facilitated by leveraging linkage disequilibrium and causal variants associated with CA. The transcriptome data from candidate genes were examined, revealing higher correlations between the expression of certain candidate genes and changes in CA metabolism. Three CA-associated genes exerted a positive regulatory effect on CA accumulation, while the remaining genes exhibited negative impacts based on gene cluster and correlation analyses. The CA content of tomatoes is primarily influenced by improvement sweeps with minimal influence from domestication sweeps in the long-term breeding history, as evidenced by population differentiation and variants distribution. The presence of various causal variants within candidate genes is implicated in the heterogeneity of CA content observed among the tomato accessions. This observation suggests a potential correlation between the number of alternative alleles and CA content. This study offers significant function-based markers that can be utilized in marker-assisted breeding, thereby enhancing their value and applicability.

Outcome comparison of meniscal allograft transplantation (MAT) and meniscal scaffold implantation (MSI): A systematic review.

BACKGROUND: Although numerous studies have reported successful clinical outcomes of Meniscal allograft transplantation (MAT) or Meniscal scaffold implantation (MSI), the difference between the outcome of MAT and MSI remains unclear. PURPOSE: To compare the overall outcomes and survival rates of MAT and MSI, aiming to provide comprehensive evidence for determining the optimal treatment strategy for meniscal defects. METHODS: A systematic review was performed via a comprehensive search of PubMed, Embase, and the Cochrane Library. Studies of MAT or MSI were included according to the inclusion and exclusion criteria. The Lysholm score was chosen as the primary outcome measure, while secondary outcomes encompassed Patient-reported Outcome Measures (PROMs), Return to Sports (RTS) rates, survival rates, and complication rates. The outcomes were stratified into two groups: MAT group and MSI group, followed by statistical comparison (P<0.05). The quality of the included studies was assessed by the Cochrane Risk of Bias 2 (RoB2) assessment tool for randomized controlled trials (RCTs) and the Coleman Methodology Score (CMS) for non-randomized controlled trials. RESULTS: A total of 3932 patients (2859 MAT, 1073 MSI) in 83 studies (51 MAT, 32 MSI) had the overall significant improvement in all clinical scores. The group MSI had higher Lysholm score of both preoperative (P=0.002) and postoperative (P<0.001) than group MAT; however, the mean improvements were similar between the two groups (P=0.105). Additionally, MSI had higher improvements of IKDC (P<0.001), KOOS symptom (P=0.010), KOOS pain (P=0.036), and KOOS ADL (P=0.004) than MAT. Interestingly, MAT had higher preoperative (P=0.018) and less postoperative VAS pain (P=0.006), which was more improved in MAT (P<0.001). Compared with MAT, MSI had higher 10-year survival rate (P=0.034), similar mid-term survival rate MAT (P=0.964), and lower complication rate (P<0.001). CONCLUSION: Both MAT and MSI could have good clinical outcomes after surgery with the similar improvement in Lysholm score. MSI had higher 10-year survival rate and less complications than MAT. LEVEL OF EVIDENCE: IV, systematic review.

Transcriptomic and metabolomic insights into the antimony stress response of tall fescue (Festuca arundinacea).

Antimony (Sb) is a toxic heavy metal that severely inhibits plant growth and development and threatens human health. Tall fescue, one of the most widely used grasses, has been reported to tolerate heavy metal stress. However, the adaptive mechanisms of Sb stress in tall fescue remain largely unknown. In this study, transcriptomic and metabolomic techniques were applied to elucidate the molecular mechanism of the Sb stress response in tall fescue. These results showed that the defense process in tall fescue was rapidly triggered during the early stages of Sb stress. Sb stress had toxic effects on tall fescue, and the cell wall and voltage-gated channels are crucial for regulating Sb permeation into the cells. In addition, the pathway of glycine, serine and threonine metabolism may play key roles in the Sb stress response of tall fescue. Genes such as ALDH7A1 and AGXT2 and metabolites such as aspartic acid, pyruvic acid, and biuret, which are related to biological processes and pathways, were key genes and compounds in the Sb stress response of tall fescue. Therefore, the regulatory mechanisms of specific genes and pathways should be investigated further to improve Sb stress tolerance.

Mechanism insight into the N-C polar bond and Pd-Co heterojunction for improved hydrogen evolution activity.

Constructing platinum-like materials with excellent catalytic activity and low cost has great significance for hydrogen evolution reaction (HER) during electrolysis of water. Herein, palladium nanoparticles (NPs) deposition on the surface of Co NPs using nitrogen-doped carbon (NC) as substrate, denoted as N-ZIFC/CoPd-30, are manufactured and served as HER electrocatalysts. Characterization results and density functional theory calculations validate that Pd-Co heterojunctions with NC acting as "electron donators" promote the Pd species transiting to the electron-rich state based on an efficient electron transfer mechanism, namely the N-C polar bonds induced strong metal-support interaction effect. The electron-rich Pd sites are beneficial to HER. Satisfactorily, N-ZIFC/CoPd-30 have only low overpotentials of 16, 162, and 13 mV@-10 mA cm-2 with the small Tafel slopes of 98 mV/decade, 126 mV/decade, and 72 mV/decade in pH of 13, 7, and 0, respectively. The success in fabricating N-ZIFC/CoPd opens a promising path to constructing other platinum-like electrocatalysts with high HER activity.

Reevaluating Adiponectin's impact on obesity hypertension: a Chinese case-control study.

BACKGROUND: Obesity and hypertension are major risk factors for cardiovascular diseases that affect millions of people worldwide. Both conditions are associated with chronic low-grade inflammation, which is mediated by adipokines such as adiponectin. Adiponectin is the most abundant adipokine that has a beneficial impact on metabolic and vascular biology, while high serum concentrations are associated with some syndromes. This "adiponectin paradox" still needs to be clarified in obesity-associated hypertension. The aim of this study was to investigate how adiponectin affects blood pressure, inflammation, and metabolic function in obesity hypertension using a Chinese adult case-control study. METHODS: A case-control study that had finished recruiting 153 subjects divided as four characteristic groups. Adiponectin serum levels were tested by ELISA in these subjects among these four characteristic Chinese adult physical examination groups. Waist circumference (WC), body mass index (BMI), systolic blood pressure (SB), diastolic blood pressure (DB), and other clinical laboratory data were collected. Analyzation of correlations between the research index and differences between groups was done by SPSS. RESULTS: Serum adiponectin levels in the| normal healthy group (NH group) were significantly higher than those in the newly diagnosed untreated just-obesity group (JO group), and negatively correlated with the visceral adiposity index. With multiple linear egression analysis, it was found that, for serum adiponectin, gender, serum albumin (ALB), alanine aminotransferase (ALT) and high-density lipoprotein cholesterol (HDLC) were the significant independent correlates, and for SB, age and HDLC were the significant independent correlates, and for DB, alkaline phosphatase (ALP) was the significant independent correlate. The other variables did not reach significance in the model. CONCLUSIONS: Our study reveals that adiponectin's role in obesity-hypertension is multifaceted and is influenced by the systemic metabolic homeostasis signaling axis. In obesity-related hypertension, compensatory effects, adiponectin resistance, and reduced adiponectin clearance from impaired kidneys and liver all contribute to the "adiponectin paradox".

Agomir-122-loaded nanoparticles coated with cell membrane of activated fibroblasts to treat frozen shoulder based on homologous targeting.

As a common musculoskeletal disorder, frozen shoulder is characterized by thickened joint capsule and limited range of motion, affecting 2-5% of the general population and more than 20% of patients with diabetes mellitus. Pathologically, joint capsule fibrosis resulting from fibroblast activation is the key event. The activated fibroblasts are proliferative and contractive, producing excessive collagen. Albeit high prevalence, effective anti-fibrosis modalities, especially fibroblast-targeting therapies, are still lacking. In this study, microRNA-122 was first identified from sequencing data as a potential therapeutic agent to antagonize fibroblast activation. Then, Agomir-122, an analog of microRNA-122, was loaded into poly(lactic-co-glycolic acid) (PLGA) nanoparticles (Agomir-122@NP), a carrier with excellent biocompatibility for the agent delivery. Moreover, relying on the homologous targeting effect, we coated Agomir-122@NP with the cell membrane derived from activated fibroblasts (Agomir-122@MNP), with an attempt to inhibit the proliferation, contraction, and collagen production of abnormally activated fibroblasts. After confirming the targeting effect of Agomir-122@MNP on activated fibroblasts in vitro, we proved that Agomir-122@MNP effectively curtailed fibroblasts activation, ameliorated joint capsule fibrosis, and restored range of motion in mouse models both prophylactically and therapeutically. Overall, an effective targeted delivery method was developed with promising translational value against frozen shoulder.

Crosstalk between autophagy and ferroptosis mediate injury in ischemic stroke by generating reactive oxygen species.

Stroke represents a significant threat to global human health, characterized by high rates of morbidity, disability, and mortality. Predominantly, strokes are ischemic in nature. Ischemic stroke (IS) is influenced by various cell death pathways, notably autophagy and ferroptosis. Recent studies have increasingly highlighted the interplay between autophagy and ferroptosis, a process likely driven by the accumulation of reactive oxygen species (ROS). Post-IS, either the inhibition of autophagy or its excessive activation can escalate ROS levels. Concurrently, the interaction between ROS and lipids during ferroptosis further augments ROS accumulation. Elevated ROS levels can provoke endoplasmic reticulum stress-induced autophagy and, in conjunction with free iron (Fe2+), can trigger ferroptosis. Moreover, ROS contribute to protein and lipid oxidation, endothelial dysfunction, and an inflammatory response, all of which mediate secondary brain injury following IS. This review succinctly explores the mechanisms of ROS-mediated crosstalk between autophagy and ferroptosis and the detrimental impact of increased ROS on IS. It also offers novel perspectives for IS treatment strategies.

Is matching or discrepancy between filial piety expectation and filial support better? The role of filial support of children and social support.

Filial piety in traditional Chinese culture is an essential variable in explaining intergenerational interaction. However, previous studies have not clarified whether older adults' filial responsibility expectations matched children's filial support and the effects of the filial discrepancy on their life satisfaction and loneliness. The latent profile analysis showed that older adults were divided into two groups: (1) high expectations and support, and (2) low expectations and support. The results showed that compared with older adults with low expectations and low support, those with high expectations and high support reported higher life satisfaction and lower loneliness. Additionally, social support played a moderating role in the effect of the groups of older adults on life satisfaction and loneliness. Our conclusion shows that filial support is an essential factor influencing older adult life satisfaction and loneliness, and social support is an effective supplement to filial support.

Multi-hierarchy Network Configuration Can Predict Brain States and Performance.

The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we proposed an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules, and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.

Comments on "Planar Tetracoordinate Hydrogen: Pushing the Limit of Multicentre Bonding".

In a recent communication (Angew. Chem. Int. Ed. 2024, 63, e202317312), Kalita et al. studied In4H+ system within the frame of single-reference approximation (SRA) and found that the global energy minimum (1 a) adopted the singlet state and a planar tetracoordinate hydrogen (ptH), while the second lowest isomer (1 b) located 3.0 kcal/mol above 1 a and adopted the triplet state as well as non-planar structure with a quasi-ptH. They assessed the reliability of SRA by checking the T1-diagnostic values of coupled cluster calculations. However, according to our multi-configurational second-order perturbation theory calculations at the CASPT2(12,13)/aug-cc-pVQZ (aug-cc-pVQZ-PP for In) level, both 1 a and 1 b exhibit obvious multi-referential characters, as reflected by their largest reference coefficients of 0.928 (86.1 %) and 0.938 (88.0 %), respectively. Moreover, 1 b is 5.05 kcal/mol lower than 1 a at this level, that is, what can be observed in In4H+ system is the quasi-ptH.

Ambient air pollution exposure and the risk of probable sarcopenia: A prospective cohort study.

BACKGROUND: Sarcopenia is characterized by decreased muscle mass and strength, posing threat to quality of life. Air pollutants are increasingly recognized as risk factors for diseases, while the relationship between the two remains to be elucidated. This study investigated whether exposure to ambient air pollution contributes to the development of sarcopenia. METHODS: We employed the data from the UK Biobank with 303,031 eligible participants. Concentrations of PM2·5, NO2, and NOx were estimated. Cox proportional hazard regression models were applied to investigate the associations between pollutants and sarcopenia. RESULTS: 30,766 probable sarcopenia cases was identified during the follow-up. We observed that exposure to PM2.5 (HR, 1.232; 95% CI, 1.053-1.440), NO2 (HR, 1.055; 95% CI, 1.032-1.078) and NOx (HR, 1.016; 95% CI, 1.007-1.026) were all significantly associated with increased risk for probable sarcopenia for each 10 µg/m3 increase in pollutant concentration. In comparison with individuals in the lowest quartiles of exposure, those in the upper quartiles had significantly increased risk of probable sarcopenia. Sarcopenia-related factors, e.g., reduced lean muscle mass, diminished walking pace, and elevated muscle fat infiltration ratio, also exhibited positive associations with exposure to ambient air pollution. On the contrary, high level physical activity significantly mitigated the influence of air pollutants on the development of probable sarcopenia. CONCLUSIONS: Air pollution exposure elevated the risk of developing sarcopenia and related manifestations in a dose-dependent manner, while physical activity maintained protective under this circumstance. Efforts should be made to control air pollution and emphasize the importance of physical activity for skeletal muscle health under this circumstance.

Identification of relevant differential genes to the divergent devel-opment of pectoral muscle in ducks by transcriptomic analysis.

Objective: The objective of this study was to identify candidate genes that play im-portant roles in skeletal muscle development in ducks. Methods: In this study, we investigated the transcriptional sequencing of embryonic pectoral muscles from two specialized line LCA and LCC ducks which were devel-oped from Liancheng White ducks (female) and Cherry Valley ducks (male) F6 hybrid population. In addition, prediction of target genes for the differentially expressed mRNAs was conducted and the enriched gene ontology (GO) terms and Kyoto En-cyclopedia of Genes and Genomes (KEGG) signaling pathways were further analyzed. Finally, a protein-to-protein interaction (PPI) network was analyzed by using the tar-get genes to gain insights into their potential functional association. Results: A total of 1428 differentially expressed genes (DEGs) with 762 being up-regulated genes and 666 being down-regulated genes in pectoral muscle of LCA and LCC ducks identified by RNA-seq (p < 0.05). Meanwhile, 23 GO terms in the down-regulated genes and 75 GO terms in up-regulated genes were significantly en-riched (p < 0.05). Furthermore, the top 5 most enriched pathways were ECM-receptor interaction, fatty acid degradation, pyruvate degradation, PPAR signaling pathway, and glycolysis/gluconeogenesis. Finally, the candidate genes including Integrin b3 (Itgb3), Pyruvate kinase M1/2 (Pkm), Insulin-like growth factor 1 (Igf1), glu-cose-6-phosphate isomerase（Gpi）, GABA type A receptor-associated protein-like 1(Gabarapl1), and Thyroid hormone receptor beta (Thrb) showed the most expression difference, and then were selected to verification by qRT-PCR. The result of qRT-PCR was consistent with that of transcriptome sequencing. Conclusion: This study provided information of molecular mechanisms underlying the developmental differences in skeletal muscles between specialized duck lines.

The mechanism of NOx removal in the sintering process based on source reduction of carbon emissions.

This study systematically investigates the mechanism of NOx emissions during the sintering process, with a focus on the utilization of biochar as an auxiliary fuel to replace a portion of the coke traditionally used in iron ore sintering. The research involved the simulation of sintering raw material ratios using iron ore, biochar, and coke powder. Substitution levels of biochar for coke were set at 0%, 20%, 40%, 50%, 60%, 80%, and 100%. NOx emissions during the sintering process were monitored using a sintering flue gas detection system. Simultaneously, a comprehensive analysis of the sintered ore was conducted with the aim of producing samples that meet sintered ore requirements while reducing NOx emissions. Experimental results revealed that when biomass charcoal substitution for coke reached 50%, the lowest NO emissions were observed during the sintering process, with a reduction of over 90% in accumulated NO emissions in the exhaust gas. In this process, due to the participation of biochar, CO2 emissions were reduced by approximately 50% compared to traditional sintering processes. The study also analyzed the physicochemical properties of the sintered ore using methods such as XRD, Raman, FTIR, and Vickers hardness testing. The results indicated that the hardness fluctuated within the range of 610 to 710N for sintered products with different levels of biochar substitution, and there were minimal changes in Fe element content and crystal phase transformations.

Analysis of carcass traits, meat quality, amino acid and fatty acid profiles between different duck lines.

To investigate the effect of genetic selection on meat quality in ducks, twenty of each fast growth ducks (LCA) and slow growth ducks (LCC) selected from F6 generation of Cherry Valley ducks (♂) x Liancheng white ducks (♀) were analyzed for carcass characteristics, meat quality (physicochemical and textural characteristics), amino acid and fatty acid profiles at 7 wk. Results showed that live body weight, slaughter weight, eviscerated yield and abdominal fat percentage of LCA were significantly higher than those in LCC ducks (P < 0.01). Moreover, the average area and diameter of myofiber were larger in LCA than LCC ducks (P < 0.01). The breast and thigh muscles of LCA exhibited significantly lower water holding capacity and thermal loss compared with LCC ducks (P < 0.01). In addition, the content of nonessential amino acids (Glu, Asp, and Arg) in breast muscles and Asp, Ser, Thr, and Met in thigh muscles was higher in LCC than LCA ducks (P < 0.05). The proportion of polyunsaturated fatty acids (PUFA) in breast muscles of LCC was higher than LCA ducks (P < 0.05). However, the content of saturated fatty acids (SFA) in breast and thigh muscles of LCA was higher compared with LCC ducks (P < 0.05). The proportion of monounsaturated fatty acids (MUFA) in thigh muscles was significantly higher in LCC compared with LCA ducks (P < 0.01). Finally, multiple traits were evaluated by applying principal component analysis (PCA) and the results indicated that PUFA and SFA in breast muscles of LCA played important roles in meat quality, followed by Warner-Bratzler shear force (WBSF) and MUFA. However, water holding capacity (WHC) had a dominant effect in meat quality of thigh muscles in both LCA and LCC ducks.

Biomimetic nanodrug blocks CD73 to inhibit adenosine and boosts antitumor immune response synergically with photothermal stimulation.

Combination of tumor immunotherapy with photothermal therapy (PTT) is a feasible tactic to overcome the drawback of immunotherapy such as poor immune response. Via triggering the immunogenic cells death (ICD), PTT can stimulate the activity of immune cells, but meanwhile, the level of adenosine is elevated via the CD73-induced decomposition of ATP which is overexpressed accompanying with the PTT process, resulting in negative feedback to impair the immune stimulation. Herein, we developed a novel biomimetic photothermal nanodrug to specifically block CD73 for inhibition of adenosine production and more efficient priming of the suppressive immune microenvironments. The nanodrug, named as AptEM@CBA, is constructed by encapsulation of photothermal agent black phosphorus quantum dots (BPQDs) and selective CD73 inhibitor α, ß-Methyleneadenosine 5'-diphosphate (AMPCP) in chitosan nanogels, which are further covered with aptamer AS1411 modified erythrocyte membrane (EM) for biomimetic camouflage. With AS1411 induced active targeting and EM induced long blood circulation time, the enrichment of the nanodrug tumor sites is promoted. The photothermal treatment promotes the maturation of dendritic cells. Meanwhile, the release of AMPCP suppress the adenosine generation via CD73 blockade, alleviating the impairment of adenosine to dendritic cells and suppressing regulatory T cells, synergically stimulate the activity of T cells. The combination of CD73 blockade with PTT, not only suppresses the growth of primary implanted tumors, but also boosts strong antitumor immunity to inhibit the growth of distal tumors, providing good potential for tumor photoimmunotherapy.

Beta-informativeness-diffusion multilayer graph embedding for brain network analysis.

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

Mechanical Field Guiding Structure Design Strategy for Meta-Fiber Reinforced Hydrogel Composites by Deep Learning.

Fiber-reinforced hydrogel composites are widely employed in many engineering applications, such as drug release, and flexible electronics, with more flexible mechanical properties than pure hydrogel materials. Comparing to the hydrogel strengthened by continuous fiber, the meta-fiber reinforced hydrogel provides stronger individualized design ability of deformation patterns and tunable stiffness, especially for the elaborate applications in joint, cartilage, and organ. In this paper, a novel structure design strategy based on deep learning algorithm is proposed for hydrogel reinforced by meta-fiber to achieve targeted mechanical properties, such as stress and displacement fields. A solid mechanic model for meta-fiber reinforced hydrogel is first developed to construct the dataset of fiber distribution and the corresponding mechanical properties of the composite. Generative adversarial network (GAN) is then trained to characterize the relationship between stress or displacement field, and meta-fiber distribution. The well-trained GAN is implemented to design meta-fiber reinforced hydrogel composite structure under specific operation conditions. The results show that the deep learning method may efficiently predict the structure of the hydrogel composite with satisfied confidence, and has great potential for applications in drug delivery and flexible electronics.

Predictive Value of Lysophosphatidylcholine for Determining the Disease Severity and Prognosis of Elderly Patients with Community-Acquired Pneumonia.

Purpose: To investigate the clinical value of serum lysophosphatidylcholine (LPC) as a predictive biomarker for determining disease severity and mortality risk in hospitalized elderly patients with community-acquired pneumonia (CAP). Methods: This prospective, single-center study enrolled 208 elderly patients, including 67 patients with severe CAP (SCAP) and 141 with non-SCAP between November 1st, 2020, and November 30th, 2021 at the Qingdao Municipal Hospital, Shandong Province, China. The demographic and clinical parameters were recorded for all the included patients. Serum LPC levels were measured on day 1 and 6 after admission using ELISA. Propensity score matching (PSM) was used to balance the baseline variables between SCAP and non-SCAP patient groups. Receiver operative characteristic (ROC) curve analysis was used to compare the predictive performances of LPC and other clinical parameters in discriminating between SCAP and non-SCAP patients and determining the 30-day mortality risk of the hospitalized CAP patients. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with SCAP. Cox proportional hazard regression analysis was used to determine if serum LPC was an independent risk factor for the 30-day mortality of CAP patients. Results: The serum LPC levels at admission were significantly higher in the non-SCAP patients than in the SCAP patients (P = 0.011). Serum LPC level <24.36 ng/mL, and PSI score were independent risk factors for the 30-day mortality in the elderly patients with CAP. The risk of 30-day mortality in the elderly CAP patients with low serum LPC levels (< 24.36ng/mL) was >5-fold higher than in the patients with high serum LPC levels (≥ 24.36ng/mL). Conclusion: Low serum LPC levels were associated with significantly higher disease severity and 30-day mortality in the elderly patients with CAP. Therefore, serum LPC is a promising predictive biomarker for the early identification of elderly CAP patients with poor prognosis.