Myositis as a prominent manifestation of primary skeletal muscle peripheral T-cell lymphoma: a case report and literature review.

The patient presented to the clinic with painful muscle swelling in the right lower extremity, which improved with immunosuppressive therapy. Initially, the condition was diagnosed as polymyositis but recurred soon after. After imaging and biopsy, the final diagnosis was primary skeletal muscle peripheral T-cell lymphoma, not otherwise specified (PSM-PTCL, NOS). In this report, we discuss the challenges in diagnosing and treating this aggressive malignancy and review the literature on PSM-PTCL, NOS. Key Points • To date, there are few reports of PSM-PTCL, NOS, and our case is the tenth. • It is crucial to consider PSM-PTCL, NOS, when presenting with localized muscle edema and unexplained pain. • Histopathological examination is likely the most effective method for diagnosing this rare disease.

Deletion of Impdh2 in adipocyte precursors limits the expansion of white adipose tissue and enhances metabolic health with overnutrition.

The equilibrium between the hypertrophic growth of existing adipocytes and adipogenesis is vital in managing metabolic stability in white adipocytes when faced with overnutrition. Adipogenesis has been established as a key player in combating metabolic irregularities caused by various factors. However, the benefits of increasing adipogenesis-mediated white adipose tissue (WAT) expansion for metabolic health regulation remain uncertain. Our findings reveal an increase in Impdh2 expression during the adipogenesis phase, both in vivo and in vitro. Xmp enhances adipogenic potential by fostering mitotic clonal expansion (MCE). The conditional knockout of Impdh2 in adipocyte progenitor cells(APCs) in adult and aged mice effectively curbs white adipose tissue expansion, ameliorates glucose tolerance, and augments energy expenditure under high-fat diet (HFD). However, no significant difference is observed under normal chow diet (NCD). Concurrently, the knockout of Impdh2 in APCs significantly reduces the count of new adipocytes induced by HFD, without affecting adipocyte size. Mechanistically, Impdh2 regulates the proliferation of APCs during the MCE phase via Xmp. Exogenous Xmp can significantly offset the reduction in adipogenic abilities of APCs due to Impdh2 deficiency. In summary, we discovered that adipogenesis-mediated WAT expansion, induced by overnutrition, also contributes to metabolic abnormalities. Moreover, the pivotal role of Impdh2 in regulating adipogenesis in APCs offers a novel therapeutic approach to combat obesity.

Prediction of ovarian cancer prognosis using statistical radiomic features of ultrasound images.

Ovarian cancer is the deadliest gynecologic malignancy worldwide. Ultrasound is the most useful non-invasive test for preoperative diagnosis of ovarian cancer. In this study, by leveraging multiple ultrasound images from the same patient to generate personalized, informative statistical radiomic features, we aimed to develop improved ultrasound image-based prognostic models for ovarian cancer. A total of 2,057 ultrasound images from 514 ovarian cancer patients, including 355 patients with epithelial ovarian cancer, from two hospitals in China were collected for this study. The models were constructed using our recently developed Frequency Appearance in Multiple Univariate pre-Screening (FAMUS) feature selection algorithm and Cox proportional hazards model. The models showed high predictive performance for overall survival (OS) and recurrence-free survival (RFS) in both epithelial and nonepithelial ovarian cancer, with concordance indices (C-index) ranging from 0.773 to 0.794. Radiomic scores predicted 2-year OS and RFS risk groups with significant survival differences (log-rank test, P<1.0e-4 for both validation cohorts). OS and RFS hazard ratios between low- and high-risk groups were 15.994 and 30.692 (internal cohort) and 19.339 and 19.760 (external cohort), respectively. The improved performance of these newly developed prognostic models was mainly attributed to the use of multiple preoperative ultrasound images from the same patient to generate statistical radiomic features, rather than simply using the largest tumor ROI among them. The models also revealed that the roundness of tumor lesion shape was positively correlated with prognosis for ovarian cancer. In summary, the newly developed prognostic models based on statistical radiomic features from ultrasound images were highly predictive of the risk of cancer-related death and possible recurrence not only for patients with epithelial ovarian cancer but also for those with nonepithelial ovarian cancer. They thereby provide reliable, non-invasive markers for individualized prognosis evaluation and clinical decision-making for patients with ovarian cancer.

Additively manufactured bioceramic scaffolds based on triply periodic minimal surfaces for bone regeneration.

The study focused on the effects of a triply periodic minimal surface (TPMS) scaffolds, varying in porosity, on the repair of mandibular defects in New Zealand white rabbits. Four TPMS configurations (40%, 50%, 60%, and 70% porosity) were fabricated with ß-tricalcium phosphate bioceramic via additive manufacturing. Scaffold properties were assessed through scanning electron microscopy and mechanical testing. For proliferation and adhesion assays, mouse bone marrow stem cells (BMSCs) were cultured on these scaffolds. In vivo, the scaffolds were implanted into rabbit mandibular defects for 2 months. Histological staining evaluated osteogenic potential. Moreover, RNA-sequencing analysis and RT-qPCR revealed the significant involvement of angiogenesis-related factors and Hippo signaling pathway in influencing BMSCs behavior. Notably, the 70% porosity TPMS scaffold exhibited optimal compressive strength, superior cell proliferation, adhesion, and significantly enhanced osteogenesis and angiogenesis. These findings underscore the substantial potential of 70% porosity TPMS scaffolds in effectively promoting bone regeneration within mandibular defects.

Water-Capture Filter Paper Separator Realizing Ambient Li-Air Battery.

Lithium-air battery (LAB) is regarded as one of the most promising energy storage systems. However, the challenges arising from the lithium metal anode have significantly impeded the progress of LAB development. In this study, cellulose-based filter paper (FP) is utilized as a separator for ambient Li-air batteries to suppress dendrite growth and prevent H2O crossover. Thermogravimetric analysis and molecular spectrum reveal that FP enables ambient Li-air battery operation due to its surface functional groups derived from cellulose. The oxygen-enriched surface of cellulose not only enhances ion conductivity but also captures water and confines solvent molecules, thereby mitigating anode corrosion and side reactions. Compared with commercial glassfiber (GF) separator, this cellulose-based FP separator is cheaper, renewable, and environmentally friendly. Moreover, it requires less electrolyte while achieving prolonged and stable cycle life under real air environment conditions. This work presents a novel approach to realizing practical Li-air batteries by capturing water on the separator's surface. It also provides insights into the exploration and design of separators for enabling practical Li-air batteries toward their commercialization.

Effect of guar gum, gelatin, and pectin on moisture changes in freeze-dried restructured strawberry blocks.

This study aimed to investigate the effects of edible gum addition on moisture changes in freeze-dried restructured strawberry blocks (FRSB), which involved five groups: the control, 1.2% guar gum, 1.2% gelatin, 1.2% pectin, and the composite group with 0.5% guar gum, 0.5% gelatin, and 0.45% pectin. The results indicated that the drying rates of the five groups of FRSB presented similar early acceleration and later deceleration trends. Moisture content in FRSB was linearly predicted by peak area of low field nuclear magnetic resonance with R2 higher than 0.90 for all the five groups. The FRSB samples in the gelatin and composition groups formed a denser porous structure and had a lower hygroscopicity after four days of storage. This study provides a theoretical basis for controlling the processing of FRSB.

Combined Mutual Learning Net for Raman Spectral Microbial Strain Identification.

Infectious diseases pose a significant threat to global health, yet traditional microbiological identification methods suffer from drawbacks, such as high costs and long processing times. Raman spectroscopy, a label-free and noninvasive technique, provides rich chemical information and has tremendous potential in fast microbial diagnoses. Here, we propose a novel Combined Mutual Learning Net that precisely identifies microbial subspecies. It demonstrated an average identification accuracy of 87.96% in an open-access data set with thirty microbial strains, representing a 5.76% improvement. 50% of the microbial subspecies accuracies were elevated by 1% to 46%, especially for E. coli 2 improved from 31% to 77%. Furthermore, it achieved a remarkable subspecies accuracy of 92.4% in the custom-built fiber-optical tweezers Raman spectroscopy system, which collects Raman spectra at a single-cell level. This advancement demonstrates the effectiveness of this method in microbial subspecies identification, offering a promising solution for microbiology diagnosis.

L-Type Calcium Channel Modulates Low-Intensity Pulsed Ultrasound-Induced Excitation in Cultured Hippocampal Neurons.

As a noninvasive technique, ultrasound stimulation is known to modulate neuronal activity both in vitro and in vivo. The latest explanation of this phenomenon is that the acoustic wave can activate the ion channels and further impact the electrophysiological properties of targeted neurons. However, the underlying mechanism of low-intensity pulsed ultrasound (LIPUS)-induced neuro-modulation effects is still unclear. Here, we characterize the excitatory effects of LIPUS on spontaneous activity and the intracellular Ca2+ homeostasis in cultured hippocampal neurons. By whole-cell patch clamp recording, we found that 15 min of 1-MHz LIPUS boosts the frequency of both spontaneous action potentials and spontaneous excitatory synaptic currents (sEPSCs) and also increases the amplitude of sEPSCs in hippocampal neurons. This phenomenon lasts for > 10 min after LIPUS exposure. Together with Ca2+ imaging, we clarified that LIPUS increases the [Ca2+]cyto level by facilitating L-type Ca2+ channels (LTCCs). In addition, due to the [Ca2+]cyto elevation by LIPUS exposure, the Ca2+-dependent CaMKII-CREB pathway can be activated within 30 min to further regulate the gene transcription and protein expression. Our work suggests that LIPUS regulates neuronal activity in a Ca2+-dependent manner via LTCCs. This may also explain the multi-activation effects of LIPUS beyond neurons. LIPUS stimulation potentiates spontaneous neuronal activity by increasing Ca2+ influx.

Injectable Bombyx mori (B. mori) silk fibroin/MXene conductive hydrogel for electrically stimulating neural stem cells into neurons for treating brain damage.

Brain damage is a common tissue damage caused by trauma or diseases, which can be life-threatening. Stem cell implantation is an emerging strategy treating brain damage. The stem cell is commonly embedded in a matrix material for implantation, which protects stem cell and induces cell differentiation. Cell differentiation induction by this material is decisive in the effectiveness of this treatment strategy. In this work, we present an injectable fibroin/MXene conductive hydrogel as stem cell carrier, which further enables in-vivo electrical stimulation upon stem cells implanted into damaged brain tissue. Cell differentiation characterization of stem cell showed high effectiveness of electrical stimulation in this system, which is comparable to pure conductive membrane. Axon growth density of the newly differentiated neurons increased by 290% and axon length by 320%. In addition, unfavored astrocyte differentiation is minimized. The therapeutic effect of this system is proved through traumatic brain injury model on rats. Combined with in vivo electrical stimulation, cavities formation is reduced after traumatic brain injury, and rat motor function recovery is significantly promoted.

Chemical Logic Gates on Active Colloids.

Recent studies have shown that active colloidal motors using enzymatic reactions for propulsion hold special promise for applications in fields ranging from biology to material science. It will be desirable to have active colloids with capability of computation so that they can act autonomously to sense their surroundings and alter their own dynamics. It is shown how small chemical networks that make use of enzymatic chemical reactions on the colloid surface can be used to construct motor-based chemical logic gates. The basic features of coupled enzymatic reactions that are responsible for propulsion and underlie the construction and function of chemical gates are described using continuum theory and molecular simulation. Examples are given that show how colloids with specific chemical logic gates, can perform simple sensing tasks. Due to the diverse functions of different enzyme gates, operating alone or in circuits, the work presented here supports the suggestion that synthetic motors using such gates could be designed to operate in an autonomous way in order to complete complicated tasks.

The effect of trisomic chromosomes on spatial genome organization and global transcription in embryonic stem cells.

Aneuploidy frequently occurs in cancer and developmental diseases such as Down syndrome, with its functional consequences implicated in dosage effects on gene expression and global perturbation of stress response and cell proliferation pathways. However, how aneuploidy affects spatial genome organization remains less understood. In this study, we addressed this question by utilizing the previously established isogenic wild-type (WT) and trisomic mouse embryonic stem cells (mESCs). We employed a combination of Hi-C, RNA-seq, chromosome painting and nascent RNA imaging technologies to compare the spatial genome structures and gene transcription among these cells. We found that trisomy has little effect on spatial genome organization at the level of A/B compartment or topologically associating domain (TAD). Inter-chromosomal interactions are associated with chromosome regions with high gene density, active histone modifications and high transcription levels, which are confirmed by imaging. Imaging also revealed contracted chromosome volume and weakened transcriptional activity for trisomic chromosomes, suggesting potential implications for the transcriptional output of these chromosomes. Our data resources and findings may contribute to a better understanding of the consequences of aneuploidy from the angle of spatial genome organization.

Recent advances in discovery and biosynthesis of natural products from myxobacteria: an overview from 2017 to 2023.

Covering: 2017.01 to 2023.11Natural products biosynthesized by myxobacteria are appealing due to their sophisticated chemical skeletons, remarkable biological activities, and intriguing biosynthetic enzymology. This review aims to systematically summarize the advances in the discovery methods, new structures, and bioactivities of myxobacterial NPs reported in the period of 2017-2023. In addition, the peculiar biosynthetic pathways of several structural families are also highlighted.

RSPSSL: A novel high-fidelity Raman spectral preprocessing scheme to enhance biomedical applications and chemical resolution visualization.

Raman spectroscopy has tremendous potential for material analysis with its molecular fingerprinting capability in many branches of science and technology. It is also an emerging omics technique for metabolic profiling to shape precision medicine. However, precisely attributing vibration peaks coupled with specific environmental, instrumental, and specimen noise is problematic. Intelligent Raman spectral preprocessing to remove statistical bias noise and sample-related errors should provide a powerful tool for valuable information extraction. Here, we propose a novel Raman spectral preprocessing scheme based on self-supervised learning (RSPSSL) with high capacity and spectral fidelity. It can preprocess arbitrary Raman spectra without further training at a speed of ~1 900 spectra per second without human interference. The experimental data preprocessing trial demonstrated its excellent capacity and signal fidelity with an 88% reduction in root mean square error and a 60% reduction in infinite norm ([Formula: see text]) compared to established techniques. With this advantage, it remarkably enhanced various biomedical applications with a 400% accuracy elevation (ΔAUC) in cancer diagnosis, an average 38% (few-shot) and 242% accuracy improvement in paraquat concentration prediction, and unsealed the chemical resolution of biomedical hyperspectral images, especially in the spectral fingerprint region. It precisely preprocessed various Raman spectra from different spectroscopy devices, laboratories, and diverse applications. This scheme will enable biomedical mechanism screening with the label-free volumetric molecular imaging tool on organism and disease metabolomics profiling with a scenario of high throughput, cross-device, various analyte complexity, and diverse applications.

Using clinical and genetic risk factors for risk prediction of 8 cancers in the UK Biobank.

BACKGROUND: Models with polygenic risk scores and clinical factors to predict risk of different cancers have been developed, but these models have been limited by the polygenic risk score-derivation methods and the incomplete selection of clinical variables. METHODS: We used UK Biobank to train the best polygenic risk scores for 8 cancers (bladder, breast, colorectal, kidney, lung, ovarian, pancreatic, and prostate cancers) and select relevant clinical variables from 733 baseline traits through extreme gradient boosting (XGBoost). Combining polygenic risk scores and clinical variables, we developed Cox proportional hazards models for risk prediction in these cancers. RESULTS: Our models achieved high prediction accuracy for 8 cancers, with areas under the curve ranging from 0.618 (95% confidence interval = 0.581 to 0.655) for ovarian cancer to 0.831 (95% confidence interval = 0.817 to 0.845) for lung cancer. Additionally, our models could identify individuals at a high risk for developing cancer. For example, the risk of breast cancer for individuals in the top 5% score quantile was nearly 13 times greater than for individuals in the lowest 10%. Furthermore, we observed a higher proportion of individuals with high polygenic risk scores in the early-onset group but a higher proportion of individuals at high clinical risk in the late-onset group. CONCLUSION: Our models demonstrated the potential to predict cancer risk and identify high-risk individuals with great generalizability to different cancers. Our findings suggested that the polygenic risk score model is more predictive for the cancer risk of early-onset patients than for late-onset patients, while the clinical risk model is more predictive for late-onset patients. Meanwhile, combining polygenic risk scores and clinical risk factors has overall better predictive performance than using polygenic risk scores or clinical risk factors alone.

Changes and correlation analysis of volatile flavor compounds, amino acids, and soluble sugars in durian during different drying processes.

Durian contains rich flavor components that undergo complex changes during drying. In this study, durian was subjected to integrated freeze-drying (IFD), conventional freeze-drying (CFD), and hot air drying (AD). Compared with the fresh samples, those dried by IFD, CFD, and AD lost 11, 9, and 7 original volatile compounds, respectively, and generated 7, 6, and 8 new volatile compounds, respectively, and showed a rapid and then slow decreasing trend in the total content during drying. However, the types of amino acids and soluble sugars remained unchanged during each of the drying methods. Furthermore, volatile compounds showed a significant negative correlation with the majority of amino acids and a significant positive correlation with soluble sugars. The IFD samples had the highest content of volatile compounds, amino acids, and soluble sugars. Therefore, IFD is recommended as a preferable drying method for durian.

Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study.

OBJECTIVES: To evaluate the performance of deep learning image reconstruction (DLIR) algorithm in dual-energy spectral CT (DEsCT) as a function of radiation dose and image energy level, in comparison with filtered-back-projection (FBP) and adaptive statistical iterative reconstruction-V (ASIR-V) algorithms. METHODS: An ACR464 phantom was scanned with DEsCT at four dose levels (3.5 mGy, 5 mGy, 7.5 mGy, and 10 mGy). Virtual monochromatic images were reconstructed at five energy levels (40 keV, 50 keV, 68 keV, 74 keV, and 140 keV) using FBP, 50% and 100% ASIR-V, DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H) settings. The noise power spectrum (NPS), task-based transfer function (TTF) and detectability index (d') were computed and compared among reconstructions. RESULTS: NPS area and noise increased as keV decreased, with DLIR having slower increase than FBP and ASIR-V, and DLIR-H having the lowest values. DLIR had the best 40 keV/140 keV noise ratio at various energy levels, DLIR showed higher TTF (50%) than ASIR-V for all materials, especially for the soft tissue-like polystyrene insert, and DLIR-M and DLIR-H provided higher d' than DLIR-L, ASIR-V and FBP in all dose and energy levels. As keV increases, d' increased for acrylic insert, and d' of the 50 keV DLIR-M and DLIR-H images at 3.5 mGy (7.39 and 8.79, respectively) were higher than that (7.20) of the 50 keV ASIR-V50% images at 10 mGy. CONCLUSIONS: DLIR provides better noise containment for low keV images in DEsCT and higher TTF(50%) for the polystyrene insert over ASIR-V. DLIR-H has the lowest image noise and highest detectability in all dose and energy levels. DEsCT 50 keV images with DLIR-M and DLIR-H show potential for 65% dose reduction over ASIR-V50% withhigher d'.

Advances in Nanoplatforms for Immunotherapy Applications Targeting the Tumor Microenvironment.

Cancer immunotherapy is a treatment method that activates or enhances the autoimmune response of the body to fight tumor growth and metastasis, has fewer toxic side effects and a longer-lasting efficacy than radiotherapy and chemotherapy, and has become an important means for the clinical treatment of cancer. However, clinical results from immunotherapy have shown that most patients lack responsiveness to immunotherapy and cannot benefit from this treatment strategy. The tumor microenvironment (TME) plays a critical role in the response to immunotherapy. The TME typically prevents effective lymphocyte activation, reducing their infiltration, and inhibiting the infiltration of effector T cells. According to the characteristic differences between the TME and normal tissues, various nanoplatforms with TME targeting and regulation properties have been developed for more precise regulation of the TME and have the ability to codeliver a variety of active pharmaceutical ingredients, thereby reducing systemic toxicity and improving the therapeutic effect of antitumor. In addition, the precise structural design of the nanoplatform can integrate specific functional motifs, such as surface-targeted ligands, degradable backbones, and TME stimulus-responsive components, into nanomedicines, thereby reshaping the tumor microenvironment, improving the body's immunosuppressive state, and enhancing the permeability of drugs in tumor tissues, in order to achieve controlled and stimulus-triggered release of load cargo. In this review, the physiological characteristics of the TME and the latest research regarding the application of TME-regulated nanoplatforms in improving antitumor immunotherapy will be described. Furthermore, the existing problems and further applications perspectives of TME-regulated platforms for cancer immunotherapy will also be discussed.

Enhanced antibiotic degradation via photo-assisted peroxymonosulfate over graphitic carbon nitride nanosheets/CuBi2O4: Highly efficiency of oxygen activation and interfacial charge transfer.

Improving the activation capacity of peroxymonosulfate (PMS) to increase radical and non-radical production is critical for antibiotic degradation. However, how to boost reactive oxygen species (ROS) and speed interfacial charge transfer remains an essential challenge. We report a coupling system of 10 %CNNS/CuBi2O4 photocatalyst and sulfate radical-based advanced oxidation processes (SO4--AOPs) to enhance the activation of PMS and improve antibiotic degradation. Owing to highly efficient oxygen activation and interfacial charge transfer, the degradation efficiency of the photo-assisted PMS system was as high as 51.6 times and 2.8 times that of photocatalyst and SO4--AOPs alone, respectively. Importantly, the highly efficient oxygen activation resulted in the production of O2-, which in turn could utilize the excess electrons generated through efficient interfacial charge transfer to convert into non-radical 1O2. The total organic carbon (TOC) elimination effectiveness of the photo-assisted PMS system reached 82 % via the synergy of radicals and non-radicals (O2-, OH, 1O2, SO4-, h+). This system also had excellent potential for reducing the generation and toxicity of disinfection by-products (DBPs), as evidenced through significant reductions in concentrations of trichloromethane (TCM), dichloroacetic acid (DCAA), and trichloronitromethane (TCNM) by 76 %, 64 %, and 35 %, respectively, providing an effective and eco-friendly strategy for antibiotic treatment.

Realization of qualitative to semi-quantitative trace detection via SERS-ICA based on internal standard method.

Surface-enhanced Raman spectroscopy (SERS) can quickly identify molecular fingerprints and has been widely used in the field of rapid detection. However, the non-uniformity inherent in SERS substrate signals, coupled with the finite nature of the detection object, significantly hampers the advancement of SERS. Nowadays, the existing mature immunochromatographic assay (ICA) method is usually combined with SERS technology to address the defects of SERS detection. Nevertheless, the porous structure of the strip will also affect the signal uniformity during detection. Obviously, a method using SERS-ICA is needed to effectively solve signal fluctuations, improve detection accuracy, and has certain versatility. This paper introduces an internal standard method combining deep learning to predict and process Raman data. Based on the signal fluctuation of single-antigen SERS-ICA test strip, the double-antigen SERS-ICA test strip was constructed. The full spectrum Raman data of double-antigen SERS-ICA test strip was normalized by the sum of two characteristic peaks of internal standard molecules, and then processed by deep learning algorithm. The Relative Standard Deviation (RSD) of Raman data of bisphenol A was compared before and after internal standard normalization of double-antigen SERS-ICA test strip. The RSD processed by this method was increased by 3.8 times. After normalization, the prediction accuracy of Root Mean Square Error (RMSE) is improved by 2.66 times, and the prediction accuracy of R-square (R2) is increased from 0.961 to 0.994. The results showed that RMSE and R2 were used to comprehensively predict the collected data of double-antigen SERS-ICA test strip, which could effectively improve the prediction accuracy. The internal standard algorithm can effectively solve the challenges of uneven hot spots and poor signal reproducibility on the test strip to a certain extent, so as to improve the semi-quantitative accuracy.

The relationship between social frailty and loneliness in community-dwelling older adults: a cross-sectional study.

BACKGROUND: Social frailty (SF) is associated with multiple adverse health outcomes, yet there has been an inadequate focus on social frailty. The convoy model portrays the social networks through the perspective of the life course, thus providing a framework to explain the occurrence of social frailty. This study aimd to figure out the prevalence of social frailty and loneliness among community-dwelling older adults and to explore their correlations based on convoy model. METHODS: This was a cross-sectional study, and 295 older adults from 10 communities of Zhengzhou in Henan Province participated in the study. Social frailty and loneliness were assessed separately with the Social Frailty Scale and University of California at Los Angeles-Loneliness Scale. The scores of social frailty of the older adults in different characteristic communities were compared by independent sample t-test and single factor analysis of variance. The influencing factors of social frailty were analysed by multiple stepwise linear regression and the structural equation model. The correlation between social frailty and loneliness was analysed by Pearson correlation analysis. RESULTS: The total scores of social frailty and loneliness of the older adults in the community were (2.09 ± 1.53) and (43.19 ± 8.91), respectively. There was a moderate positive correlation between social frailty and loneliness (r = 0.621, P < 0.01). The results of multiple stepwise linear regression analysis showed that age, living styles, balance of payments, and loneliness were the main influencing factors of the social frailty of older adults in the community (F = 27.180, P < 0.001). The structural equation model of social frailty fitted well (χ2 = 47.292, df = 26, χ2/df = 1.819, P = 0.007; RMSEA = 0.053, 95%CI (0.028, 0.076), P = 0.359; GFI = 0.971; AGFI = 0.939; NFI = 0.904; IFI = 0.955; TLI = 0.918; CFI = 0.953; SRMR = 0.0466). CONCLUSIONS: The convoy model had certain applicability in explanation of the relationship between loneliness and social frailty among older adults in community. The incidence of social frailty among the older adults in the community was high, and loneliness was at a medium level. It is necessary to strengthen the intervention of social frailty and loneliness of the older adults in the community, improve the quality of life of the older adults, and promote the development of healthy aging.