Multimodal ischemic stroke recurrence prediction model based on the capsule neural network and support vector machine.

Ischemic stroke (IS) has a high recurrence rate. Machine learning (ML) models have been developed based on single-modal biochemical tests, and imaging data have been used to predict stroke recurrence. However, the prediction accuracy of these models is not sufficiently high. Therefore, this study aimed to collect biochemical detection and magnetic resonance imaging (MRI) data to establish a dataset and propose a high-performance heterogeneous multimodal IS recurrence prediction model based on deep learning. This is a retrospective cohort study. Data were retrospectively collected from 634 IS patients in Zhuhai, China, a 12-month follow-up was conducted to determine stroke recurrence. We propose the ischemic stroke multi-group learning (ISGL) model, an integrated model for predicting the recurrence risk of multimodal IS in patients, based on a capsule neural network and a linear support vector machine (SVM). Two capsule neural network prediction models based on T1 and T2 signals in the MRI data and a SVM prediction model based on biochemical test data were established. Finally, a vote was conducted on the final judgment of the integrated model. The ISGL model was compared with 6 classical ML and deep learning models: k-nearest neighbors, SVM, logistic regression, random forest, eXtreme Gradient Boosting, and visual geometry group. The results revealed that the accuracy, specificity, sensitivity and the area under the curve of the ISGL model were 95%, 96%, 94%, and 95%, respectively. Among the comparison models, the visual geometry group method exhibited the best performance, but it much lower than those of the ISGL model. Analysis of the importance of biochemical test data revealed that low-density lipoprotein, smoking, and heart disease history were the positively correlated factors, and total cholesterol, high-density lipoprotein, and diabetes were and the negatively correlated factors. This study proposes the ISGL model can be used simultaneously with MRI and biochemical data to predict IS recurrence. This combination resulted in higher rate of performance than that of the other ML models. Additionally, this study found related risk factors affected recurrence, which can be used to intervene in high-risk patients' recurrence as early as possible and promote the development of secondary prevention of stroke.

The nomogram for predicting nasal bleeding after endoscopic transsphenoidal resection of pituitary adenomas: a retrospective study.

Objective: This study aimed to develop and validate a dynamic nomogram to assess the risk of nasal bleeding after endoscopic transnasal transsphenoidal pituitary tumor resection. Methods: A retrospective analysis was conducted on patients who underwent endoscopic transnasal transsphenoidal pituitary tumor resection from June 2019 to June 2021. Univariate and multivariate logistic regression analyses were used to screen for independent risk factors for nasal bleeding from the training set. A multivariate logistic regression model was established, a nomogram was plotted, and it was validated in an internal validation set. The performance of the nomogram was evaluated based on the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: The nomogram indicators included anticoagulant use, sphenoid sinus artery injury, nasal irrigation, platelet count (PLT), and constipation. The predictive model had an area under the ROC curve of 0.932 (95% CI: 0.873-0.990) and 0.969 (95% CI: 0.940-0.997) for the training and validation sets, respectively, indicating good discrimination. The calibration curve showed good consistency between the actual and predicted incidence of nasal bleeding (p > 0.05). DCA indicated that the nomogram had good clinical net benefit in predicting postoperative nasal bleeding in patients. Conclusion: In summary, this study explored the incidence and influencing factors of nasal bleeding after endoscopic transnasal transsphenoidal pituitary tumor resection and established a predictive model to assist clinical decision-making.

Quality of life in patients with acromegaly: a scoping review.

PURPOSE: To evaluate the available evidence regarding the quality of life (QoL) in patients with acromegaly, by synthesizing the psychosocial factors of QoL, QoL measures, and complementary interventions targeting QoL. METHODS: A scoping review was conducted using the PRISMA-ScR guideline. We searched six English databases (PubMed, Embase, CINAHL, Scopus, Web of Science, and the Cochrane Library) from the inception to August 21, 2023. We included observational studies involving psychosocial factors and complementary interventions targeting QoL (concept) in patients with acromegaly (population) in any setting (context). The design characteristics, psychosocial factors, measures, details of interventions, and outcomes of included studies were described in detail. RESULTS: Twenty-one studies were identified, including sixteen cross-sectional studies and five interventional studies. Ten categories of psychosocial factors that are associated with QoL in acromegaly. Depression and anxiety were the most frequent psychosocial factors. Seven different validated QoL measures were used. AcroQoL was the most common measure. Two categories of complementary interventions targeting QoL were identified including psychological and exercise interventions. CONCLUSIONS: Our scoping review provides a reasonably clear picture of the current research status of QoL in acromegaly. However, this review also highlights the need to deepen understanding of QoL and psychosocial factors in the future, as well as conduct longitudinal research and qualitative research to clarify the changing trends of psychosocial factors and specific experiences of patients. Further, more potential clinical complementary interventions are needed to improve QoL for patients with acromegaly.

Co-infection of H9N2 subtype avian influenza virus and QX genotype live attenuated infectious bronchitis virus increase the pathogenicity in SPF chickens.

Avian influenza virus (AIV) infection and vaccination against live attenuated infectious bronchitis virus (aIBV) are frequent in poultry worldwide. Here, we evaluated the clinical effect of H9N2 subtype AIV and QX genotype aIBV co-infection in specific-pathogen-free (SPF) white leghorn chickens and explored the potential mechanisms underlying the observed effects using by 4D-FastDIA-based proteomics. The results showed that co-infection of H9N2 AIV and QX aIBV increased mortality and suppressed the growth of SPF chickens. In particular, severe lesions in the kidneys and slight respiratory signs similar to the symptoms of virulent QX IBV infection were observed in some co-infected chickens, with no such clinical signs observed in single-infected chickens. The replication of H9N2 AIV was significantly enhanced in both the trachea and kidneys, whereas there was only a slight effect on the replication of the QX aIBV. Proteomics analysis showed that the IL-17 signaling pathway was one of the unique pathways enriched in co-infected chickens compared to single infected-chickens. A series of metabolism and immune response-related pathways linked with co-infection were also significantly enriched. Moreover, co-infection of the two pathogens resulted in the enrichment of the negative regulation of telomerase activity. Collectively, our study supports the synergistic effect of the two pathogens, and pointed out that aIBV vaccines might increased IBV-associated lesions due to pathogenic co-infections. Exacerbation of the pathogenicity and mortality in H9N2 AIV and QX aIBV co-infected chickens possibly occurred because of an increase in H9N2 AIV replication, the regulation of telomerase activity, and the disturbance of cell metabolism and the immune system.

Analysis of Relevant Predictive Indicators for Postoperative Condition Change in Brain Tumor Patients.

BACKGROUND: Novice nurse need more guidance and professional confidence. This study aimed to explore early relevant predictive indicators for postoperative condition changes in brain tumor patients, which can be used to map patients' condition changes for novice nurses. METHODS: The authors prospectively collected clinical data, including nursing records of cerebral tumor patients after operation from July 2020 to June 2021 in the Department of Neurosurgery. Univariant analysis and multivariable logistic regression analysis were performed to identify independent predictors, the satisfaction questionnaire for teaching nurses is used to evaluate the new nurse's performance during perioperative period, psychometric scale is used to assess nurses' psychological stress. RESULTS: Nine hundred ninety-five cerebral tumor patients were enrolled in this study, and 115 (11.6%) patients' conditions were changed. Relevant predictive indicators, including vision, myodynamia, urine volume, nausea, vomit, pain, Glasgow Coma Scale (GCS), and Modified Early Warning System (MEWS), among them GCS, MEWS, and vision can basically cover the above indicators through simulation and calculation of the integrated model was set as Z=22*vision+1*GCS+3*MEWS. The satisfaction rate of teaching nurses has increased from 78.125 to 86.25%. Novice nurses' psychological stress was dropped from 30.637% to 19.844%. CONCLUSIONS: GCS and MEWS. GCS, MEWS and vision can map patients' condition change after cerebral tumor operation. The warning model has reduced their psychological stress, and the teaching nurse expressed that the effective evaluation of postoperative patient conditions by novice nurses reduces their nursing and teaching work greatly.

PneumoLLM: Harnessing the power of large language model for pneumoconiosis diagnosis.

The conventional pretraining-and-finetuning paradigm, while effective for common diseases with ample data, faces challenges in diagnosing data-scarce occupational diseases like pneumoconiosis. Recently, large language models (LLMs) have exhibits unprecedented ability when conducting multiple tasks in dialogue, bringing opportunities to diagnosis. A common strategy might involve using adapter layers for vision-language alignment and diagnosis in a dialogic manner. Yet, this approach often requires optimization of extensive learnable parameters in the text branch and the dialogue head, potentially diminishing the LLMs' efficacy, especially with limited training data. In our work, we innovate by eliminating the text branch and substituting the dialogue head with a classification head. This approach presents a more effective method for harnessing LLMs in diagnosis with fewer learnable parameters. Furthermore, to balance the retention of detailed image information with progression towards accurate diagnosis, we introduce the contextual multi-token engine. This engine is specialized in adaptively generating diagnostic tokens. Additionally, we propose the information emitter module, which unidirectionally emits information from image tokens to diagnosis tokens. Comprehensive experiments validate the superiority of our methods.

Dual-source dual-energy CT and deep learning for equivocal lymph nodes on CT images for thyroid cancer.

OBJECTIVES: This study investigated the diagnostic performance of dual-energy computed tomography (CT) and deep learning for the preoperative classification of equivocal lymph nodes (LNs) on CT images in thyroid cancer patients. METHODS: In this prospective study, from October 2020 to March 2021, 375 patients with thyroid disease underwent thin-section dual-energy thyroid CT at a small field of view (FOV) and thyroid surgery. The data of 183 patients with 281 LNs were analyzed. The targeted LNs were negative or equivocal on small FOV CT images. Six deep-learning models were used to classify the LNs on conventional CT images. The performance of all models was compared with pathology reports. RESULTS: Of the 281 LNs, 65.5% had a short diameter of less than 4 mm. Multiple quantitative dual-energy CT parameters significantly differed between benign and malignant LNs. Multivariable logistic regression analyses showed that the best combination of parameters had an area under the curve (AUC) of 0.857, with excellent consistency and discrimination, and its diagnostic accuracy and sensitivity were 74.4% and 84.2%, respectively (p < 0.001). The visual geometry group 16 (VGG16) based model achieved the best accuracy (86%) and sensitivity (88%) in differentiating between benign and malignant LNs, with an AUC of 0.89. CONCLUSIONS: The VGG16 model based on small FOV CT images showed better diagnostic accuracy and sensitivity than the spectral parameter model. Our study presents a noninvasive and convenient imaging biomarker to predict malignant LNs without suspicious CT features in thyroid cancer patients. CLINICAL RELEVANCE STATEMENT: Our study presents a deep-learning-based model to predict malignant lymph nodes in thyroid cancer without suspicious features on conventional CT images, which shows better diagnostic accuracy and sensitivity than the regression model based on spectral parameters. KEY POINTS: Many cervical lymph nodes (LNs) do not express suspicious features on conventional computed tomography (CT). Dual-energy CT parameters can distinguish between benign and malignant LNs. Visual geometry group 16 model shows superior diagnostic accuracy and sensitivity for malignant LNs.

Single-Cell Transcriptional Profile Construction of Rat Pituitary Glands before and after Sexual Maturation and Identification of Novel Marker Spp1 in Gonadotropes.

The mammalian pituitary gland drives highly conserved physiological processes such as somatic cell growth, pubertal transformation, fertility, and metabolism by secreting a variety of hormones. Recently, single-cell transcriptomics techniques have been used in pituitary gland research. However, more studies have focused on adult pituitary gland tissues from different species or different sexes, and no research has yet resolved cellular differences in pituitary gland tissue before and after sexual maturation. Here, we identified a total of 15 cell clusters and constructed single-cell transcriptional profiles of rats before and after sexual maturation. Furthermore, focusing on the gonadotrope cluster, 106 genes were found to be differentially expressed before and after sexual maturation. It was verified that Spp1, which is specifically expressed in gonadotrope cells, could serve as a novel marker for this cell cluster and has a promotional effect on the synthesis and secretion of follicle-stimulating hormone. The results provide a new resource for further resolving the regulatory mechanism of pituitary gland development and pituitary hormone synthesis and secretion.

RedCDR: Dual Relation Distillation for Cancer Drug Response Prediction.

Based on multi-omics data and drug information, predicting the response of cancer cell lines to drugs is a crucial area of research in modern oncology, as it can promote the development of personalized treatments. Despite the promising performance achieved by existing models, most of them overlook the variations among different omics and lack effective integration of multi-omics data. Moreover, the explicit modeling of cell line/drug attribute and cell line-drug association has not been thoroughly investigated in existing approaches. To address these issues, we propose RedCDR, a dual relation distillation model for cancer drug response (CDR) prediction. Specifically, a parallel dual-branch architecture is designed to enable both the independent learning and interactive fusion feasible for cell line/drug attribute and cell line-drug association information. To facilitate the adaptive interacting integration of multi-omics data, the proposed multi-omics encoder introduces the multiple similarity relations between cell lines and takes the importance of different omics data into account. To accomplish knowledge transfer from the two independent attribute and association branches to their fusion, a dual relation distillation mechanism consisting of representation distillation and prediction distillation is presented. Experiments conducted on the GDSC and CCLE datasets show that RedCDR outperforms previous state-of-the-art approaches in CDR prediction. The source code is available at https://github.com/mhxu1998/RedCDR.

Risk factors for delayed extubation after pediatric perineal anaplasty in patients less than 1 year of age: a retrospective study.

BACKGROUND: Anorectal malformation is a common congenital problem occurring in 1 in 5,000 births and has a spectrum of anatomical presentations, requiring individualized surgical treatments for normal growth. Delayed extubation or reintubation may result in a longer intensive care unit (ICU) stay and hospital stay, increased mortality, prolonged duration of mechanical ventilation, increased tracheostomy rate, and higher hospital costs. Extensive studies have focused on the role of risk factors in early extubation during major infant surgery such as Cardiac surgery, neurosurgery, and liver surgery. However, no study has mentioned the influencing factors of delayed extubation in neonates and infants undergoing angioplasty surgery. MATERIALS AND METHODS: We performed a retrospective study of neonates and infants who underwent anorectal malformation surgery between June 2018 and June 2022. The principal goal of this study was to observe the incidence of delayed extubation in pediatric anorectal malformation surgery. The secondary goals were to identify the factors associated with delayed extubation in these infants. RESULTS: We collected data describing 123 patients who had anorectal malformations from 2019 to 2022. It shows that 74(60.2%) in the normal intubation group and 49(39.8%) in the longer extubation. In the final model, anesthesia methods were independently associated with delayed extubation (P < 0.05). CONCLUSION: We found that the anesthesia method was independently associated with early extubation in neonates and infants who accepted pediatric anorectal malformation surgery.

Avian leukosis virus usurps the cellular SERBP1 protein to enhance its transcription and promote productive infections in avian cells.

Avian leukosis virus subgroup K (ALV-K) is composed of newly emerging isolates, which cluster separately from the well-characterized subgroups A, B, C, D, E, and J in sequence analysis, and exhibits a specific host range and a unique pattern of superinfection interference. Avian leukosis virus subgroup K replicate more slowly in avian cells than other ALV strains, leading to escaped detection during ALV eradication, but the underlying mechanism are largely unknown. In our previous study, we have reported that JS11C1 and most of other suspected ALV-K strains possessed unique mutations in the U3 region. Here, we selected 5 mutations in some important transcriptional regulation elements to explore the possible factor contributing for the lower activity of LTR, including CA-TG mutation in the CAAT box, 21 nt deletion in the CAAT box, A-G and A-T mutations in the CArG boxes, 11 nt insertion in the PRE boxes, and C-T mutation in the TATA box. On the basis of infectious clone of JS11C1, we demonstrated that the 11 nt fragment in the PRE boxes was associated with the transcription activity of LTR, the enhancer ability of U3, and the replication capacity of the virus. Notably, we determined the differential U3-protein interaction profile of ALVs and found that the 11 nt fragment specifically binds to cellular SERPINE1 mRNA binding protein 1 (SERBP1) to increase the LTR activity and enhance virus replication. Collectively, these findings reveal that a 11 nt fragment in the U3 gene contributed to its binding ability to the cellular SERBP1 to enhance its transcription and the infectious virus productions in avian cells. This study highlighted the vital role of host factor in retrovirus replication and thus provides a new perspective to elucidate the interaction between retrovirus and its host and a molecular basis to develop efficient strategies against retroviruses.

Characterization of Bacillus amyloliquefaciens PM415 as a potential bio-preserving probiotic.

Animal feed is vulnerable to fungal infections, and the use of bio-preserving probiotics has received increasing attention. In contrast to Lactobacillus and Bifidobacteria spp., fewer Bacillus spp. have been recognized as antifungal probiotics. Therefore, our objective was to screen antifungal strains and provide more Bacillus candidates to bridge this gap. Here, we screened 56 bacterial strains for cyclic lipopeptide genes and conducted an antifungal assay with Aspergillus niger as a representative fungus. We found that a Bacillus strain Bacillus amyloliquefaciens PM415, isolated from pigeon manure, exhibited the highest fungal inhibition activity as demonstrated by the confrontation assay and morphological observation under scanning electron microscope (SEM). Preliminary safety assessment and probiotic characterization revealed its non-pathogenic feature and stress tolerance capability. Whole genome sequencing of Bacillus amyloliquefaciens PM415 revealed a genome size of 4.16 Mbp and 84 housekeeping genes thereof were used for phylogenetic analysis showing that it is most closely related to Bacillus amyloliquefaciens LFB112. The in silico analysis further supported its non-pathogenic feature at the genomic level and revealed potential biosynthetic gene clusters responsible for its antifungal property. RNA-seq analysis revealed genome-wide changes in transportation, amino acid metabolism, non-ribosomal peptides (NRPs) biosynthesis and glycan degradation during fungal antagonism. Our results suggest that Bacillus amyloliquefaciens PM415 is a safe and effective probiotic strain that can prevent fungal growth in animal feeds.

The Synergetic Effect of 3D Printing and Electrospinning Techniques in the Fabrication of Bone Scaffolds.

The primary goal of bone tissue engineering is to restore and rejuvenate bone defects by using a suitable three-dimensional scaffold, appropriate cells, and growth hormones. Various scaffolding methods are used to fabricate three-dimensional scaffolds, which provide the necessary environment for cell activity and bone formation. Multiple materials may be used to create scaffolds with hierarchical structures that are optimal for cell growth and specialization. This study examines a notion for creating an optimal framework for bone regeneration using a combination of the robocasting method and the electrospinning approach. Research indicates that the integration of these two procedures enhances the benefits of each method and provides a rationale for addressing their shortcomings via this combination. The hybrid approach is anticipated to provide a manufactured scaffold that can effectively replace bone defects while possessing the necessary qualities for bone regeneration.

Clinical Analysis of Atorvastatin Calcium, Fenofibrate, and Acipimox in the Treatment of Hypertriglyceridemia-induced Acute Pancreatitis.

Background: Hypertriglyceridemia-induced acute pancreatitis (HTG-AP) is an increasingly recognized and potentially severe form of acute pancreatitis. The effective management of HTG-AP is critical due to its association with significant morbidity and mortality. HTG-AP poses a considerable burden on affected individuals and healthcare systems. It can result in persistent upper abdominal pain, nausea, vomiting, abdominal distension, fever, and in severe cases, hypotension or shock and multiple organ dysfunction. Standard treatment strategies often involve lipid-lowering agents, but the optimal therapeutic approach remains a subject of ongoing research. This study aims to evaluate the efficacy of atorvastatin calcium, fenofibrate, and acipimox, either individually or in combination, in the treatment of HTG-AP, providing insights into more effective management strategies. Methods: 150 HTG-AP patients admitted to the first hospital of Putian from June 2020 to December 2022 were selected. The age range of the patients included in the study was between 30 and 70 years, with an average age of approximately 48 years. The cohort consisted of 90 males and 60 females, resulting in a male-to-female ratio of 3:2. The patients were grouped: atorvastatin calcium, acipimox, fenofibrate, fenofibrate + Atorvastatin calcium, fenofibrate + acipimox, and no drug. The therapeutic effects and clinical indicators of the six groups were compared. Results: Patients in the fenofibrate + acipimox and fenofibrate groups experienced significantly reduced hospitalization duration compared to the other groups. They also had shorter abdominal pain relief time and gastrointestinal function relief time. Additionally, these groups had lower peak levels of amylase (an enzyme) and cholesterol compared to the other groups. In terms of neutrophil (NEUT) increase, the fenofibrate + acipimox, atorvastatin calcium, and fenofibrate groups had significantly lower peak levels compared to the other groups, indicating a less pronounced increase in NEUT. Furthermore, the fenofibrate and acipimox groups exhibited significantly lower peak levels of C-reactive protein (CRP) compared to the other groups. CRP is an indicator of inflammation. On the other hand, the atorvastatin calcium group had higher levels of procalcitonin (a marker of infection) and a higher peak score on the acute physiology and chronic health evaluation II (APACHE II) scale, which assesses the severity of acute pancreatitis, compared to the other groups (all P < .05). Conclusion: The findings of this study highlight the effectiveness of combining fenofibrate and acipimox in the treatment of HTG-AP, leading to rapid disease recovery and significant improvement in clinical symptoms. These results have important implications for clinical practice, as the combination therapy can be widely adopted as an effective treatment strategy for HTG-AP patients. Moreover, this study provides valuable insights into the management of HTG-AP and suggests that lipid-lowering agents, such as atorvastatin calcium and fenofibrate, play a crucial role in the treatment of this condition. However, further research is needed to explore the optimal dosages, treatment durations, and potential side effects of these medications in HTG-AP patients.

Virome characterization of diarrheic red-crowned crane (G. japonensis).

BACKGROUND: The red-crowned crane is one of the vulnerable bird species. Although the captive population has markedly increased over the last decade, infectious diseases can lead to the death of young red-crowned cranes while few virological studies have been conducted. METHODS: Using a viral metagenomics approach, we analyzed the virome of tissues of the dead captive red-crowned crane with diarrhea symptoms in Dongying Biosphere Reserve, Shandong Province, China and feces of individual birds breeding at the corresponding captive breeding center, which were pooled separately. RESULTS: There is much more DNA and RNA viruses in the feces than that of the tissues. RNA virus belonging to the families Picornaviridae, and DNA viruses belonging to the families Parvoviridae, associated with enteric diseases were detected in the tissues and feces. Genomes of the picornavirus, genomovirus, and parvovirus identified in the study were fully characterized, which further suggested that infectious viruses of these families were possibly presented in the diseased red-crowned crane. CONCLUSION: RNA virus belonging to the families Picornaviridae, and DNA viruses belonging to the families Genomoviridae and Parvoviridae were possibly the causative agent for diarrhea of red-crowned crane. This study has expanded our understanding of the virome of red-crowned crane and provides a baseline for elucidating the etiology for diarrhea of the birds.

Sweet taste receptors play roles in artificial sweetener-induced enhanced urine output in mice.

Sweet taste receptors found in oral and extra oral tissues play important roles in the regulation of many physiological functions. Studies have shown that urine volume increases during the lifetime exposure to artificial sweeteners. However, the detailed molecular mechanism and the general effects of different artificial sweeteners exposure on urine volume remain unclear. In this study, we investigated the relationship between urinary excretion and the sweet taste receptor expression in mice after three artificial sweeteners exposure in a higher or lower concentration via animal behavioral studies, western blotting, and real-time quantitative PCR experiment in rodent model. Our results showed that high dose of acesulfame potassium and saccharin can significantly enhance the urine output and there was a positive correlation between K+ and urination volume. The acesulfame potassium administration assay of T1R3 knockout mice showed that artificial sweeteners may affect the urine output directly through the sweet taste signaling pathway. The expression of T1R3 encoding gene can be up-regulated specifically in bladder but not in kidney or other organs we tested. Through our study, the sweet taste receptors, distributing in many tissues as bladder, were indicated to function in the enhanced urine output. Different effects of long-term exposure to the three artificial sweeteners were shown and acesulfame potassium increased urine output even at a very low concentration.

Mechanisms and therapeutic targets of mitophagy after intracerebral hemorrhage.

Mitochondria are dynamic organelles responsible for cellular energy production. In addition to regulating energy homeostasis, mitochondria are responsible for calcium homeostasis, clearance of damaged organelles, signaling, and cell survival in the context of injury and pathology. In stroke, the mechanisms underlying brain injury secondary to intracerebral hemorrhage are complex and involve cellular hypoxia, oxidative stress, inflammatory responses, and apoptosis. Recent studies have shown that mitochondrial damage and autophagy are essential for neuronal metabolism and functional recovery after intracerebral hemorrhage, and are closely related to inflammatory responses, oxidative stress, apoptosis, and other pathological processes. Because hypoxia and inflammatory responses can cause secondary damage after intracerebral hemorrhage, the restoration of mitochondrial function and timely clearance of damaged mitochondria have neuroprotective effects. Based on studies on mitochondrial autophagy (mitophagy), cellular inflammation, apoptosis, ferroptosis, the BNIP3 autophagy gene, pharmacological and other regulatory approaches, and normobaric oxygen (NBO) therapy, this article further explores the neuroprotective role of mitophagy after intracerebral hemorrhage.

Postoperative outcomes of pediatric patients with perioperative COVID-19 infection: a systematic review and meta-analysis of observational studies.

OBJECTIVE: To quantify the risk of adverse postoperative outcomes in pediatric patients with COVID-19 infection. METHODS: We searched PubMed, Embase, Cochrane Library from December 2019 to 21 April 2023. Observational cohort studies that reported postoperative early mortality and pulmonary complications of pediatric patients with confirmed COVID-19-positive compared with COVID-19-negative were eligible for inclusion. We excluded pediatric patients underwent organ transplantation or cardiac surgery. Reviews, case reports, letters, and editorials were also excluded. We used the Newcastle-Ottawa Scale to assess the methodological quality and risk of bias for each included study. The primary outcome was postoperative early mortality, defined as mortality within 30 days after surgery or during hospitalization. The random-effects model was performed to assess the pooled estimates, which were expressed as risk ratio (RR) or mean difference (MD) with 95% confidence intervals (CI). RESULTS: 9 studies involving 23,031 pediatric patients were included, and all studies were rated as high quality. Compared with pediatric patients without COVID-19, pediatric patients with COVID-19 showed a significantly increased risk of postoperative pulmonary complications (PPCs) (RR = 4.24; 95% CI 2.08-8.64). No clear evidence was found for differences in postoperative early mortality (RR = 0.84; 95% CI 0.34-2.06), postoperative intensive care unit (ICU) admission (RR = 0.80; 95% CI 0.39-1.68), and length of hospital stay (MD = 0.35, 95% CI -1.81-2.51) between pediatric patients with and without COVID-19. CONCLUSION: Perioperative COVID-19 infection was strongly associated with increased risk of PPCs, but it did not increase the risk of postoperative early mortality, the rate of postoperative ICU admission, and the length of hospital stay in pediatric patients. Our preplanned sensitivity analyses confirmed the robustness of our study findings.

LM-Net: A light-weight and multi-scale network for medical image segmentation.

Current medical image segmentation approaches have limitations in deeply exploring multi-scale information and effectively combining local detail textures with global contextual semantic information. This results in over-segmentation, under-segmentation, and blurred segmentation boundaries. To tackle these challenges, we explore multi-scale feature representations from different perspectives, proposing a novel, lightweight, and multi-scale architecture (LM-Net) that integrates advantages of both Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) to enhance segmentation accuracy. LM-Net employs a lightweight multi-branch module to capture multi-scale features at the same level. Furthermore, we introduce two modules to concurrently capture local detail textures and global semantics with multi-scale features at different levels: the Local Feature Transformer (LFT) and Global Feature Transformer (GFT). The LFT integrates local window self-attention to capture local detail textures, while the GFT leverages global self-attention to capture global contextual semantics. By combining these modules, our model achieves complementarity between local and global representations, alleviating the problem of blurred segmentation boundaries in medical image segmentation. To evaluate the feasibility of LM-Net, extensive experiments have been conducted on three publicly available datasets with different modalities. Our proposed model achieves state-of-the-art results, surpassing previous methods, while only requiring 4.66G FLOPs and 5.4M parameters. These state-of-the-art results on three datasets with different modalities demonstrate the effectiveness and adaptability of our proposed LM-Net for various medical image segmentation tasks.

[Expression and Clinical Significance of Exosome Component 4 in Newly Diagnosed Patients with Diffuse Large B-Cell Lymphoma].

OBJECTIVE: To explore the expression of Exosome Component 4（EXOSC4） in the tissues of newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL) and its clinical significance. METHODS: The expression of EXOSC4 protein in the tissues of 181 newly diagnosed DLBCL patients was analyzed by immunohistochemical staining. Clinical data were collected. The correlation between EXOSC4 protein expression in the tissues of newly diagnosed DLBCL patients and clinical features were analyzed and its prognostic significance. RESULTS: The positive rate of EXOSC4 protein expression was 68.51% in the tissues of 181 newly diagnosed DLBCL patients. These patients were divided into two groups, with 44 cases in high expression group and 137 cases in low expression group. There were no significant differences in age, gender, B symptoms, serum lactate dehydrogenase (LDH) level, Eastern Cooperative Oncology Group (ECOG) score, Ann Arbor stage, extranodal disease, International Prognostic Index (IPI) score, National Comprehensive Cancer Network IPI (NCCN-IPI) score, and cell origin between the two groups (P>0.05). Cox multivariate regression analysis showed that high EXOSC4 protein expression in tissues was an independent poor prognostic factor for OS and PFS in newly diagnosed DLBCL patients (all P<0.05). K-M survival analysis showed that newly diagnosed DLBCL patients with high EXOSC4 protein expression had significantly shorter overall survival (OS) and progression free survival (PFS) than those patients with low EXOSC4 protein expression (all P<0.05). CONCLUSION: High EXOSC4 protein expression in tissues of newly diagnosed DLBCL patients is an independent poor prognostic factor for survival.