Design of a Mobile App Interface That Engages Community Members in a Food System Pilot Study.

Supermarkets are scarce in many under-resourced urban communities, and small independently owned retail stores often carry few fresh or healthy items. The Baltimore Urban food Distribution (BUD) mobile application (app) was previously developed to address supply-side challenges in moving healthy foods from local suppliers to retailers. In-app opportunities for consumers to indicate demand for these foods are crucial, but remain absent. We sought to understand community members' perspectives on the overall role, function and features of a proposed consumer-engagement module (BUDConnect) to expand the BUD app. A series of initial high-fidelity wireframe mockups were developed based on formative research. In-depth interviews (n = 20) were conducted and thematically analyzed using ATLAS.ti Web. Participants revealed a desire for real-time crowd-sourced information to navigate their food environments safely and effectively, functionality to help build community and social networks among store owners and their customers, opportunities to share positive reviews and ratings of store quality and offerings, and interoperability with existing apps. Rewards and referral systems resulting in the discounted purchasing of promoted healthy items were suggested to increase adoption and sustained app use. Wireframe mockups were further refined for future development and integration into the BUD app, the program and policy implications of which are discussed.

Fucoidan-hybrid hydroxyapatite nanoparticles promote the osteogenic differentiation of human periodontal ligament stem cells under inflammatory condition.

Inflammation-related bone defects often lead to poor osteogenesis. Therefore, it is crucial to reduce the inflammation response and promote the osteogenic differentiation of stem/progenitor cells to revitalize bone physiology. Here, a kind of hybrid nano-hydroxyapatite was prepared using the confined phosphate ion release method with the participation of fucoidan, a marine-sourced polysaccharide with anti-inflammation property. The physicochemical analyses confirmed that the fucoidan hybrid nano-hydroxyapatite (FC/n-HA) showed fine needle-like architectures. With a higher amount of fucoidan, the crystal size and crystallinity of the FC/n-HA reduced while the liquid dispersibility was improved. Cell experiences showed that FC/n-HA had an optimal cytocompatibility at concentration of 50 µg/mL. Moreover, the lipopolysaccharide-induced cellular inflammatory model with PDLSCs was established and used to evaluate the anti-inflammatory and osteogenic properties. For the 1%FC/n-HA group, the expression levels of TNF-α and IL-1ß were significantly reduced at 24 h, while the expression of alkaline phosphatase of PDLSCs was significantly promoted at days 3 and 7, and calcium precipitates was enhanced at 21 days. In this study, the FC/n-HA particles showed effective anti-inflammatory properties and facilitated osteogenic differentiation of PDLSCs, indicating which has potential application in treating bone defects associated with inflammation, such as periodontitis.

Machine Learning Model Based on Radiomics for Preoperative Differentiation of Jaw Cystic Lesions.

OBJECTIVE: This study aims to use machine learning techniques together with radiomics methods to build a preoperative predictive diagnostic model from spiral computed tomography (CT) images. The model is intended for the differential diagnosis of common jaw cystic lesions. STUDY DESIGN: Retrospective, case-control study. SETTING: This retrospective study was conducted at Sun Yat-sen Memorial Hospital of Sun Yat-sen University (Guangzhou, Guangdong, China). All the data used to build the predictive diagnostic model were collected from 160 patients, who were treated at the Department of Oral and Maxillofacial Surgery at Sun Yat-sen Memorial Hospital of Sun Yat-sen University between 2019 and 2023. METHODS: We included a total of 160 patients in this study. We extracted 107 radiomic features from each patient's CT scan images. After a feature selection process, we chose 15 of these radiomic features to construct the predictive diagnostic model. RESULTS: Among the preoperative predictive diagnostic models built using 3 different machine learning methods (support vector machine, random forest [RF], and multivariate logistic regression), the RF model showed the best predictive performance. It demonstrated a sensitivity of 0.923, a specificity of 0.643, an accuracy of 0.825, and an area under the receiver operating characteristic curve of 0.810. CONCLUSION: The preoperative predictive model, based on spiral CT radiomics and machine learning algorithms, shows promising differential diagnostic capabilities. For common jaw cystic lesions, this predictive model has potential clinical application value, providing a scientific reference for treatment decisions.

Chronic trans fatty acid consumption shortens lifespan in male Drosophila melanogaster on a high-sugar and high-fat diet.

Aging entails the progressive decline in the body's self-regulation and functionality over time. Notably, obesity and aging exhibit parallel phenotypes, with obesity further accelerating the aging process across multiple dimensions and diminishing lifespan. In this study, we explored the impact of trans fatty acid (TFA) consumption on the overall health and lifespan of male Drosophila melanogaster under an isocaloric high-sugar and high-fat diet. Our results indicate that TFA intake results in a shortened lifespan, elevated body weight, and increased triglyceride levels in flies fed a high-sugar and high-fat diet with equivalent caloric intake. Additionally, TFA exposure induces oxidative stress, locomotor deficits, and damage to the intestinal barrier in flies. Collectively, chronic TFA consumption expedites the aging process and reduces the lifespan of male Drosophila melanogaster. These results contribute supplementary evidence regarding the adverse health effects associated with TFAs.

A Turing test of whether AI chatbots are behaviorally similar to humans.

We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a traditional Big-5 psychological survey that measures personality traits. ChatGPT-4 exhibits behavioral and personality traits that are statistically indistinguishable from a random human from tens of thousands of human subjects from more than 50 countries. Chatbots also modify their behavior based on previous experience and contexts "as if" they were learning from the interactions and change their behavior in response to different framings of the same strategic situation. Their behaviors are often distinct from average and modal human behaviors, in which case they tend to behave on the more altruistic and cooperative end of the distribution. We estimate that they act as if they are maximizing an average of their own and partner's payoffs.

Yo-Yo Dieting Delays Male Drosophila melanogaster Aging Through Enhanced Mitochondrial Function, Relative to Sustained High-Calorie Diet Feeding.

Weight regain subsequent to weight reduction resulting from dietary interventions represents a prevalent phenomenon recognized as "Yo-yo dieting." However, the impact of prolonged Yo-yo dieting on health, especially in relation to the aging process, remains poorly understood. This study aimed to investigate the influence of Yo-yo dieting on the aging process in male Drosophila melanogaster that have been exposed to a high-calorie (HC) diet. Fruit flies were fed with either a consistent HC diet or an alternating regimen of HC and low-calorie diets every 3 days (referred to as "Yo-yo dieting") for a total of 24 days. Biochemical assays were utilized to quantify levels of oxidative stress and activities of the mitochondrial respiratory chain complexes. The frozen section staining method was employed to assess the presence of lipid droplets, reactive oxygen species, cellular viability, and mitochondrial abundance in tissues. Additionally, we examined the expression of key regulators involved in mitochondrial dynamics and biogenic signaling pathways. Yo-yo dieting resulted in an extension of the fruit flies' lifespan, concomitant with reduced body weight, decreased body protein content, and lower triglyceride levels compared to continuous a HC diet feeding. Furthermore, Yo-yo dieting ameliorated impairments in motility and intestinal barrier function. Importantly, it improved mitochondrial function and upregulated the expression of essential mitochondrial fusion proteins, namely mitofusin 1 and mitofusin 2, optic atrophy 1, and peroxisome proliferator-activated receptor-γ coactivator-1α. Therefore, the practice of Yo-yo dieting extends the lifespan of fruit flies by modulating mitochondrial dynamics and the associated biogenic signaling pathways.

Modeling annotator preference and stochastic annotation error for medical image segmentation.

Manual annotation of medical images is highly subjective, leading to inevitable annotation biases. Deep learning models may surpass human performance on a variety of tasks, but they may also mimic or amplify these biases. Although we can have multiple annotators and fuse their annotations to reduce stochastic errors, we cannot use this strategy to handle the bias caused by annotators' preferences. In this paper, we highlight the issue of annotator-related biases on medical image segmentation tasks, and propose a Preference-involved Annotation Distribution Learning (PADL) framework to address it from the perspective of modeling an annotator's preference and stochastic errors so as to produce not only a meta segmentation but also the annotator-specific segmentation. Under this framework, a stochastic error modeling (SEM) module estimates the meta segmentation map and average stochastic error map, and a series of human preference modeling (HPM) modules estimate each annotator's segmentation and the corresponding stochastic error. We evaluated our PADL framework on two medical image benchmarks with different imaging modalities, which have been annotated by multiple medical professionals, and achieved promising performance on all five medical image segmentation tasks. Code is available at https://github.com/Merrical/PADL.

ReFs: A hybrid pre-training paradigm for 3D medical image segmentation.

Self-supervised learning (SSL) has achieved remarkable progress in medical image segmentation. The application of an SSL algorithm often follows a two-stage training process: using unlabeled data to perform label-free representation learning and fine-tuning the pre-trained model on the downstream tasks. One issue of this paradigm is that the SSL step is unaware of the downstream task, which may lead to sub-optimal feature representation for a target task. In this paper, we propose a hybrid pre-training paradigm that is driven by both self-supervised and supervised objectives. To achieve this, a supervised reference task is involved in self-supervised learning, aiming to improve the representation quality. Specifically, we employ the off-the-shelf medical image segmentation task as reference, and encourage learning a representation that (1) incurs low prediction loss on both SSL and reference tasks and (2) leads to a similar gradient when updating the feature extractor from either task. In this way, the reference task pilots SSL in the direction beneficial for the downstream segmentation. To this end, we propose a simple but effective gradient matching method to optimize the model towards a consistent direction, thus improving the compatibility of both SSL and supervised reference tasks. We call this hybrid pre-training paradigm reference-guided self-supervised learning (ReFs), and perform it on a large-scale unlabeled dataset and an additional reference dataset. The experimental results demonstrate its effectiveness on seven downstream medical image segmentation benchmarks.

The mechanism of high mobility group box-1 protein and its bidirectional regulation in tumors.

High mobility group protein box-1 (HMGB1) is a nonhistone chromatin-related protein widely found in eukaryotic cells. It is involved in the transcription, replication and repair of DNA to maintain nuclear homeostasis. It participates in cell growth, differentiation and signal transduction. Recent studies showed that HMGB1 has a bidirectional regulatory effect on tumors by regulating TLR4/MYD88/NF-κB and RAGE/AMPK/mTOR signaling pathways. On one hand, it is highly expressed in a variety of tumors, promoting tumor proliferation and invasion, whilst on the other hand, it induces autophagy and apoptosis of tumor cells and stimulates tumor-infiltrating lymphocytes to produce anti-tumor immune response. At present, HMGB1 could be used as a target to regulate the drug-resistance and prognostication in cancer. Clinical applications of HMGB1 in cancer need further in-depth studies.

Prediction of postoperative recurrence of oral cancer by artificial intelligence model: Multilayer perceptron.

BACKGROUND: Postoperative recurrence of oral cancer is an important factor affecting the prognosis of patients. Artificial intelligence is used to establish a machine learning model to predict the risk of postoperative recurrence of oral cancer. METHODS: The information of 387 patients with postoperative oral cancer were collected to establish the multilayer perceptron (MLP) model. The comprehensive variable model was compared with the characteristic variable model, and the MLP model was compared with other models to evaluate the sensitivity of different models in the prediction of postoperative recurrence of oral cancer. RESULTS: The overall performance of the MLP model under comprehensive variable input was the best. CONCLUSION: The MLP model has good sensitivity to predict postoperative recurrence of oral cancer, and the predictive model with variable input training is better than that with characteristic variable input.

Learning From Partially Labeled Data for Multi-Organ and Tumor Segmentation.

Medical image benchmarks for the segmentation of organs and tumors suffer from the partially labeling issue due to its intensive cost of labor and expertise. Current mainstream approaches follow the practice of one network solving one task. With this pipeline, not only the performance is limited by the typically small dataset of a single task, but also the computation cost linearly increases with the number of tasks. To address this, we propose a Transformer based dynamic on-demand network (TransDoDNet) that learns to segment organs and tumors on multiple partially labeled datasets. Specifically, TransDoDNet has a hybrid backbone that is composed of the convolutional neural network and Transformer. A dynamic head enables the network to accomplish multiple segmentation tasks flexibly. Unlike existing approaches that fix kernels after training, the kernels in the dynamic head are generated adaptively by the Transformer, which employs the self-attention mechanism to model long-range organ-wise dependencies and decodes the organ embedding that can represent each organ. We create a large-scale partially labeled Multi-Organ and Tumor Segmentation benchmark, termed MOTS, and demonstrate the superior performance of our TransDoDNet over other competitors on seven organ and tumor segmentation tasks. This study also provides a general 3D medical image segmentation model, which has been pre-trained on the large-scale MOTS benchmark and has demonstrated advanced performance over current predominant self-supervised learning methods.

Computed tomography (CT) characteristics and pathologic basis of ciliated muconodular papillary tumors of the lung.

Background: Ciliated muconodular papillary tumor (CMPT) is a rare pulmonary tumor with papillary architecture. Most studies have focused on the clinicopathological features of CMPT, while computed tomography (CT) characteristics have rarely been systematically described. Methods: A cohort of 27 patients with surgically resected CMPT were identified. Clinical and demographic features were recorded. Preoperative CT images of the CMPTs and the corresponding histopathological basis were also retrospectively analyzed. Results: All of the tumors appeared as solitary nodules. Pure ground glass, part-solid nodules and solid nodules were detected in 2/27 (7.4%), 17/27 (63.0%), and 8/27 (29.6%) patients, respectively. Twenty-one tumors (77.8%) were located in the lower lobe. The average tumor size was 1.21±0.74 (range, 0.44-3.46) cm. Eighteen (66.7%) of the 27 patients had tumors with well-defined margins and lobulated contours. Fifteen patients (55.6%) had air bronchograms in the tumor, and 19 patients (70.4%) had air-containing space. There were two patients whose tumor size was enlarged and accompanied by an increase in solid components, and one patient simply had an increase in tumor size at the preoperative follow-up duration. Notably, one patient with solid tumor components was finally diagnosed with CMPT accompanied by adenocarcinoma. Conclusions: CMPTs of the lung mostly manifest as solitary, lobulated, well-defined tumors with air-containing spaces on CT and often occur in the periphery of the pulmonary lower lobe. When CT findings meet these criteria, the possibility of CMPT should be considered. Additionally, CMPT can coexist with adenocarcinoma. Further investigation will contribute significantly to the biological properties of CMPT and its relationship to the potential for malignant transformation.

Human gingival mesenchymal stem cell-derived exosomes cross-regulate the Wnt/ß-catenin and NF-κB signalling pathways in the periodontal inflammation microenvironment.

AIM: To examine the immunomodulatory effect of exosomes originating from gingival mesenchymal stem cells (GMSC-Exo) on periodontal bone regeneration and its role in the regulation of the nuclear-factor kappaB (NF-κB) and Wnt/ß-catenin pathways in the periodontal inflammatory microenvironment. MATERIALS AND METHODS: First, periodontal ligament stem cells (PDLSCs) were treated with GMSC-Exo or Porphyromonas gingivalis-derived lipopolysaccharide (P.g-LPS) in vitro. Quantitative real-time PCR (qRT-PCR) and western blot were carried out to detect the expressions of osteogenic differentiation-related factors in cells. Further, PDLSCs were treated with P.g-LPS or inhibitors. The expression of NF-κB pathway-related factors as well as of Wnt/ß-catenin pathway-related factors were detected by qRT-PCR and western blot. RESULTS: GMSC-Exo treatment promoted the expression of osteogenic differentiation-related factors within PDLSCs in both normal and inflammatory environments. Further investigations showed that GMSC-Exo could also inhibit the P.g-LPS-induced activation of the NF-κB pathway, leading to the up-regulation of the Wnt/ß-catenin pathway. When the Wnt/ß-catenin signalling was blocked, the inhibitory effect of GMSC-Exo on the NF-κB pathway was abolished. CONCLUSIONS: GMSC-Exo could promote the osteogenic differentiation of PDLSCs. There could be mutually exclusive regulatory roles between the NF-κB and Wnt/ß-catenin signalling pathways in a periodontal inflammatory environment. GMSC-Exo exhibited an effective cross-regulation ability for both pathways.

Dose-dependent action of cordycepin on the microbiome-gut-brain-adipose axis in mice exposed to stress.

The high risk for anxiety and depression among individuals with stress has become a growing concern globally. Stress-related mental disorders are often accompanied by symptoms of metabolic dysfunction. Cordycepin is a Chinese herbal medicine commonly used for its metabolism-enhancing effects. We aimed to investigate the dose-dependent effects of cordycepin on psycho-metabolic disorders induced by stress. Our behavioral tests revealed that 12.5 mg/kg cordycepin by oral gavage significantly attenuated the anxiety- and depression-like behaviors induced by stress in mice. At 25 mg/kg, cordycepin restored the reduced weight and cell size of adipose tissues caused by stress. Besides ameliorating the metabolic dysbiosis of gut microbiota due to stress, cordycepin significantly reduced the elevated contents of 5-hydroxyindoleacetic acid in the serum and prefrontal cortex at 12.5 mg/kg and reversed the decrease in adipose induced by stress at 25 mg/kg. Correlation analyses further revealed that 12.5 mg/kg cordycepin reversed stress-induced changes in the intestinal microbiome of NK4A214_group and decreased serum Myristic acid and PC(15:0/18:1(11Z)) and cytokines, such as IFN-γ and IL-1ß. 25 mg/kg cordycepin reversed stress-induced changes in the abundances of Prevoteaceae_UCG-001 and Desulfovibrio, increased serum L-alanine level, and decreased serum Inosine-5'-monophosphate level. Cordycepin thereby ameliorated the anxiety- and depression-like behaviors as well as disturbances in the adipose metabolism of mice exposed to stress. Overall, these findings offer evidence indicating that the prominent effects of cordycepin in the brain and adipose tissues are dose dependent, thus highlight the importance of evaluating the precise therapeutic effects of different cordycepin doses on psycho-metabolic diseases.

[Analysis of a Typical Ozone Pollution Process in Guangzhou in Winter].

This study focused on an ozone pollution event occurring in winter (January) in Guangzhou. Various influencing factors were analyzed, including various atmospheric trace gases, meteorological conditions during the whole pollution process, as well as the characteristics of the main O3 precursor volatile organic compounds (VOCs). The main sources of VOCs and the O3 formation regime were analyzed using an array of tools:the ozone potential formation (OFP), positive matrix factorization (PMF) model, and empirical kinetic modeling approach (EKMA) curve. Feasible strategies for O3 control were suggested. The results showed that O3 and NO2 exceeded the corresponding standards in this winter pollution event, when the concentrations of PM10 and PM2.5 were also high, differing from the air pollution characteristics in summer and autumn. Low boundary layer height (<75 m) and high atmospheric stability at night exacerbated the accumulation of ozone precursors and fine particles. Meteorological conditions such as the increased daytime temperature (5℃), stronger solar radiation (10%), and low horizontal wind speed (<1 m·s-1) favored photochemical reactions and promoted the formation of ozone and fine particles. VOCs were mainly composed of alkanes, and the proportions of alkanes and alkynes in winter were higher than those in the other seasons. Aromatics (xylenes and toluene) and propylene were the key VOCs species leading to O3 formation. The main VOCs sources were vehicle exhaust (22.4%), solvent usage (20.5%), and industrial emissions (17.9%); however, the source with highest OFP was identified as solvent usage. O3 formation in this event was in the VOCs-limited regime, and reducing O3 precursors in the VOCs/NOx ratio of 3:1 was effective and feasible for O3 control. This study explored the causes of an O3 pollution event in winter, which will serve as reference for the synergistic control of O3 and PM2.5 in heavy pollution seasons.

[Chemical constituents from Artocarpus incisus and their inhibitory effects on proliferation of synoviocytes in vitro].

The chemical constituents from the branches and leaves of Artocarpus incisus were isolated and purified via silica gel, ODS, and Sephadex LH-20 column chromatography as well as preparative HPLC. The chemical structures of all isolated compounds were identified in the light of their physicochemical properties, spectroscopic analyses, and comparisons of their physicochemical and spectroscopic data with the reported data in literature. As a result, 20 compounds were isolated and characterized from the 90% ethanol extract of the branches and leaves of A. incisus, which were identified as tephrosin(1), 6-hydroxy-6 a, 12 a-dehydrodeguelin(2), sarcolobin(3), lupiwighteone(4), 12-deoxo-12α-methoxyelliptone(5), 6 aα,12 aα-12 a-hydroxyelliptone(6), homopterocarpin(7), 3-hydroxy-8,9-dimethoxypterocarpan(8), pterocarpin(9), maackiain(10), medicarpin(11), calycosin(12), genistein(13), formononetin(14), 5-hydroxy-4',7-dimethoxy isoflavone(15), liquiritigenin(16), 4(15)-eudesmene-1ß,7α-diol(17), ent-4(15)-eudesmene-1ß,6α-diol(18), 1α-hydroxyisodauc-4-en-15-al(19), and guaianediol(20). Except compounds 13 and 16, all other compounds were isolated from the Artocarpus plants for the first time. Additionally, using MTS assay, compounds 1-20 were eva-luated for their anti-rheumatoid arthritis activities by measuring their anti-proliferative effects on synoviocytes in vitro. As a consequence, compounds 1-16 showed notable anti-rheumatoid arthritis activities, which displayed inhibitory effects on the proliferation of MH7 A synovial fibroblast cells, with the IC_(50) values in range of(9.86±0.09)-(218.07±1.96) µmol·L~(-1).

Role and Mechanisms of Tumor-Associated Macrophages in Hematological Malignancies.

Mounting evidence has revealed that many nontumor cells in the tumor microenvironment, such as fibroblasts, endothelial cells, mesenchymal stem cells, and leukocytes, are strongly involved in tumor progression. In hematological malignancies, tumor-associated macrophages (TAMs) are considered to be an important component that promotes tumor growth and can be polarized into different phenotypes with protumor or antitumor roles. This Review emphasizes research related to the role and mechanisms of TAMs in hematological malignancies. TAMs lead to poor prognosis by influencing tumor progression at the molecular level, including nurturing cancer stem cells and laying the foundation for metastasis. Although detailed molecular mechanisms have not been clarified, TAMs may be a new therapeutic target in hematological disease treatment.

Risk Factors Associated With Misdiagnosis of Digital Glomus Tumor: A Retrospective Cohort Study.

OBJECTIVE: Glomus tumors are benign with unique triad of symptoms; however, the delayed diagnosis of these tumors is common. We investigated the possible risk factors for the misdiagnosis of digital glomus tumors, with an aim to treat these patients on time. METHODS: We conducted a retrospective cohort study of 104 patients with digital glomus tumors from October 2009 to February 2021. Data pertaining to sex, age, tumor locations, symptoms, imaging modalities, and clinical departments visited by the patients were extracted and analyzed through logistic regression. RESULTS: The duration of delayed diagnosis ranged from 3 months to 40 years (mean, 5.5 ± 6.5 years). The total misdiagnosis and recurrence rate are 34.6% and 3.8%, respectively. On the multivariate logistic regression, the misdiagnosis of digital glomus tumor was significantly associated with the clinical departments visited by the patients ( P < 0.001). The risk of misdiagnosis of nonhand surgery department visit is 179.741-fold higher than that of hand surgery department visit. CONCLUSIONS: The misdiagnosis rate of digital glomus tumor was closely related to the clinical departments visited by the patients. Hand surgeons are the first choice for the treatment of the tumor.

Melatonin promotes peripheral nerve repair through Parkin-mediated mitophagy.

Schwann cells (SCs) are the major glial cells in peripheral nervous system. They unsheathe and myelinate axons and play an essential role in peripheral nerve regeneration. Several studies report that Parkin-mediated mitophagy is associated with various diseases. Melatonin promotes proliferation of central glial cells. Little is known about the effect of melatonin and Parkin-mediated mitophagy on peripheral nerve repair. In this study, using a rat model of a peripheral nerve injury (PNI) and in vitro model established by RSC96 cells treated with tert-butyl hydroperoxide (TBHP), we found that Parkin-mediated mitophagy can effectively reduce the production of mitochondrial reactive oxygen species (ROS), maintain the balance of mitochondrial membrane potential, maintain autophagic flux, and inhibit mitochondrial apoptosis. At the same time, we found that the increase of Parkin under stress is a manifestation of the RSC96 cells' resistance to oxidative stress to maintain RSC96 cells' balance. In our experiment, melatonin is similar to a Parkin agonist, up-regulating the expression of Parkin, enhancing all the positive results of Parkin in a stress state, such as inhibiting active oxygen production, maintaining autophagic flux, and inhibiting mitochondrial apoptosis. In addition, we design in vivo experiments to verify in In vitro experiments. In in vivo, melatonin promotes the expression of Parkin, maintains autophagic flux, inhibits apoptosis, promotes myelin regeneration, reduces the regeneration of collagen fibers around damaged tissues, and promotes peripheral nerve repair. When adenovirus was used to down-regulate the expression of Parkin, we found that all the positive effects of melatonin were attenuated. Collectively, these findings indicate that melatonin upregulates Parkin-mediated mitophagy and promotes peripheral nerve repair. The results provide a basis for development of effective drugs for PNI treatment.

Siglec-9, a Putative Immune Checkpoint Marker for Cancer Progression Across Multiple Cancer Types.

Siglec-9, a cell surface transmembrane receptor mainly expressed on B cells, CD56+ NK cells, and CD4+ and CD8+ T cells, is strongly related to the tumor immune microenvironment. However, the expression pattern of Siglec-9 and its prognostic potential have not been investigated in a pan-cancer perspective. This study aimed to explore the association of Siglec-9 with prognosis, tumor stage, molecular subtype, and the immune microenvironment in pan-cancer. The mRNA expression of Siglec-9 was obtained from The Cancer Genome Atlas (TCGA), the Broad Institute Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx). The relationship between Siglec-9 mRNA expression and prognosis was evaluated by the Kaplan-Meier analysis. The correlation between Siglec-9 and tumor-infiltrating immune cells, immune subtype, and molecular subtype was evaluated on Tumor Immune Estimation Resource (TIMER) and Integrated Repository Portal for Tumor-Immune System Interactions (TISIDB). The correlation between Siglec-9 expression and immune checkpoint, mismatch repair (MMR), DNA methyltransferase (DNMT), tumor mutation burden (TMB), and microsatellite instability (MSI) was also analyzed. It showed that Siglec-9 expression was significantly altered in most TCGA tumors. Siglec-9 expression was associated with the prognosis of patients with adrenocortical carcinoma (ACC), lung adenocarcinoma (LUSC), thymoma (THYM), colon adenocarcinoma (COAD), glioblastoma multiforme (GBM), prostate adenocarcinoma (PRAD), esophageal carcinoma (ESCA), and brain lower-grade glioma (LGG). Particularly, increased Siglec-9 expression was strongly correlated with poor prognosis in LGG. Correlation between Siglec-9 expression and tumor stage was also observed in various cancers. In addition, Siglec-9 was positively associated with infiltration of immune cells including neutrophils, dendritic cells (DCs), macrophage, and CD4+ and CD8+ T cells. Moreover, a significant correlation between Siglec-9 and MSI, TMB, MMR, DNMT, immune checkpoint, immune subtype, molecular subtype, and immunomodulators was observed in multiple cancers. Specifically, poor prognostic value and strong correlation to immune cell infiltration were verified with the LGG dataset from the Chinese Glioma Genome Atlas (CGGA). These findings indicated that Siglec-9 can be a novel biomarker and a potential target for cancer immunotherapy.