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BackgroundTargeted next-generation sequencing (tNGS) has become a trending tool in the field of infection diagnosis, but concerns are also raising about its performance compared with metagenomic next-generation sequencing (mNGS). This study aims to explore the clinical feasibility of a tNGS panel for respiratory tract infection diagnosis and compare it with mNGS in the same cohort of inpatients.Methods180 bronchoalveolar lavage fluid samples were collected and sent to two centers for mNGS and tNGS blinded tests, respectively. The concordance between pathogen reports of both methods and the clinical significance among samples with/without known etiology was further evaluated.ResultsOverall, both methods displayed high agreement on pathogen reports, as the average percent agreement reached 95.29%. But tNGS presented a slightly higher detection rate per species than mNGS (PWilcoxon=1.212e-05; standard mean difference = 0.2887091), as detection rates for 32 out of 48 species were higher than those of mNGS. Due to limitations of panel coverage, tNGS identified 28 fewer species than mNGS, among which only 3 were considered clinically relevant. In reference to composite reference standard, accuracy, sensitivity, and specificity combining both tNGS and mNGS reached 95.61%, 96.71%, and 95.68%, respectively, while positive prediction value (PPV) was low at 48.13%, which was caused by low agreement regarding opportunistic pathogens. tNGS and mNGS improved the etiology identification in 30.6% (55/180) and 33.9% (61/180) cases, respectively.ConclusionCollectively, tNGS presented a similar overall performance in pathogen identification compared to mNGS, but outperformed in some pathogens. This study also demonstrated that deployment of tNGS significantly improves etiology identification in routine practice and provides hints for clinical decisions. The low agreement between clinical diagnosis and NGS reports towards opportunistic pathogens implies that adjudication is essential for report interpretation. Finally, We proposed tNGS as a diagnosis option in clinical practice due to its cost-efficiency.

BackgroundCritical illness-associated immune dysfunction (CIID) is prevalent in the ICU and frequently resulted in uncontrollably immune responses. Critical immunological dysfunction is understood to be important, although there are currently no clinically accepted diagnostic criteria for it. Given this, we examined the literature and developed an initial diagnostic criterion that we validated using the MIMIC-IV database.MethodsWe searched the related literature in the last 32 years. Patients admitted to the ICU for the first time were selected by screening the MIMIC-IV database. Different criteria were used to categorize patients into groups related to immune dysfunction (ID) and non-immune dysfunction (NID). Within the ID group, patients were subdivided into three subgroups: hyperinflammatory (HI), immunosuppression (IS), and a subgroup combining immunosuppression and hyperinflammation (HI+IS). The APACHE II was used to measure the patients’ severity. The association between immune dysfunction and mortality after 30 or 180 days was evaluated through the KM curves and COX regression analysis.ResultsBy summarizing relevant literature, we proposed the initial diagnostic criteria. The analysis included 43,965 patients, with approximately 77% meeting the diagnostic criteria for CIID. We observed that patients with immune dysfunction possessed higher APACHE II scores and there were differences in peak APACHE II among the three subgroups. When comparing patients’ 30-day mortality in the COX model, it is evident that patients in the IS subgroup had the lowest risk and patients in the HI subgroup the greatest risk after accounting for all covariates. In contrast, patients in the IS subgroup had the highest risk of death, those in the HI subgroup had the lowest risk when comparing long-term mortality. In summary, we propose and validate diagnostic criteria related to CIID. Subgroup analyses were carried out, which also revealed variations between the three groups.ConclusionThe diagnostic criteria were confirmed by the MIMIC-IV database, demonstrating the diagnostic criteria were scientifically valid and reliable.

IntroductionThe Cinnamomum Camphora var. Borneol (CCB) tree is a valuable timber species with significant medicinal importance, widely cultivated in mountainous areas but susceptible to pests and diseases, making manual surveillance costly.MethodsThis paper proposes a method for detecting CCB pests and diseases using Unmanned aerial vehicle (UAV) as an advanced data collection carrier, capable of gathering large-scale data. To tackle the high cost and challenging data processing issues associated with traditional hyper-spectral/multi-spectral sensors, this method only relies on UAV visible light RGB bands. The process first involves calculating and normalizing 24 visible light vegetation indices from the UAV RGB images of the monitoring area, along with the original RGB bands. To account for the collinearity relationship between indices, the random forest variable importance and correlation coefficient iterative analysis algorithm are employed to select indices, retaining the most important or lowest collinearity multiple vegetation indices. Subsequently, the Beluga Whale Optimization (BWO) algorithm is utilized to generate a new vegetation index, which is then combined with the multi-threshold segmentation method to propose a BWO-weighted ensemble strategy for obtaining the final pests and diseases detection results.Results and discussionThe experimental results suggest that the new BWO-based vegetation index has a higher feature expression ability than single indices, and the new BWO-based ensemble strategy can yield more accurate detection results. This approach provides an effective means for low-cost pests and diseases detection of CCB trees.

In tea (Camellia sinensis), anthocyanins are important secondary metabolites that are linked to leaf color. Anthocyanin biosynthesis is a complex biological process, in which multiple genes including structural and regulatory genes are involved. Here, we describe the cloning and characterizing of a new R2R3-MYB transcription factor gene, CsRAB, isolated from purple tea variety ‘Hongfei’. Consistent with its predicted role as a transcription factor, the CsRAB protein localized to nuclei when expressed in onion (Allium cepa) epidermal cell. A dual-luciferase reporter assay demonstrated that CsRAB acts as a transcriptional activator in vivo. CsRAB overexpression in Arabidopsis seedlings led to higher expression levels of anthocyanin biosynthesis-related genes, and consequently, purple stems and higher anthocyanin contents were exhibited in overexpressing lines compared to wild type. The results indicated that CsRAB plays critical roles in positively regulating anthocyanins biosynthesis in tea plants.

BackgroundCerebral syphilitic gumma (CSG), a rare manifestation of neurosyphilis, presents characteristics akin to intracranial tumors, often leading to clinical misdiagnosis.ObjectiveThis study aimed to summarize the clinical experience in diagnosing and treating CSG.Materials and methodsThe present study conducted a retrospective analysis of clinical data, encompassing the baseline characteristics, clinical presentation, diagnosis, treatment, and prognosis of eight patients with CSG who were treated and diagnosed by our institution.ResultsThe median age at the initial diagnosis was 57.5 years, comprising six males and two females. The predominant clinical manifestations included headaches in eight cases, motor and sensory disorders in four cases, epileptic seizures in one case, and dysarthria in one patient. The serum Treponema pallidum haemagglutination assay (TPHA) and toluidine red unheated serum test (TRUST) yielded positive in all eight patients. The contrast-enhanced magnetic resonance imaging (MRI) revealed irregular ring-shaped enhancement of lesions in three patients, while nodular enhancement of lesions was observed in five patients. In terms of treatment, seven patients underwent surgery. The postoperative pathological tissue showed granulomatous inflammation. Six patients exhibited an elevated protein concentration in their cerebrospinal fluid (CSF), while two patients demonstrated a reduced CSF glucose level. Additionally, positive results were obtained for both CSF TPHA and TRUST in all eight patients. The clinical diagnosis of CSG was confirmed in eight patients who exhibited notable clinical improvement following penicillin treatment. Subsequent reevaluation of the imaging findings demonstrated complete resolution of the enhanced lesions.ConclusionIn clinical practice, CSG should be considered for patients with intracranial lesions and positive serum syphilis antibodies. Timely and accurate diagnosis enables patients with CSG to achieve a more favorable prognosis through active anti-syphilis treatment.

IntroductionMucosal deficiency is one of the most challenging conditions in patients with acute severe ulcerative colitis (ASUC). Intravenous corticosteroids (CS) are the first-line treatment, with infliximab (IFX) used as a rescue therapy. However, the efficacy remains unsatisfactory. We investigated whether CS combined with IFX as first-line therapy would improve outcomes in patients with ASUC with mucosal deficiency.MethodsA retrospective study was performed at a tertiary inflammatory bowel disease center. The primary outcomes included clinical remission, endoscopic improvement, and endoscopic remission at week 14. The secondary outcomes included the colectomy rate within 90 days and durable clinical remission.ResultsA total of 43 patients with ASUC with mucosal deficiency were included in the analysis (25 in the CS combined with the IFX group and 18 in the CS sequential IFX group). At week 14, endoscopic improvement was observed in 21 of 25 patients (84.0%) receiving the CS combined with the IFX regimen, compared to 9 of 18 (50.0%) patients receiving the CS sequential IFX regimen (p = 0.017). Durable clinical remission rates were significantly higher in the combined group than in the sequential group (85.7% vs. 35.7%, p = 0.004). There was no statistically significant difference between the two groups in terms of clinical and endoscopic remission at week 14 or colectomy rate within 90 days. Multivariate analysis confirmed that the CS combined with the IFX regimen was an independent predictive factor for a higher endoscopic improvement rate at week 14 (odds ratio (OR) 8.428, 95%confidence interval (CI) 1.539–46.153, p = 0.014) and a higher durable clinical remission rate (OR 10.800, 95%CI 2.095–55.666, p = 0.004).ConclusionCS combined with IFX as first-line therapy may be an effective induction strategy in patients with ASUC with mucosal deficiency. Further large-scale, multicenter prospective studies are needed.

ObjectiveThe aim of this investigation was to assess the diagnostic and therapeutic efficacy of G2 and S-phase expressed 1 (GTSE1) in lung adenocarcinoma (LUAD), while examining its impact on immune infiltration and drug treatment mechanisms.MethodsThis research involved examining the expression patterns and diagnostic accuracy of GTSE1 in LUAD using various databases and clinical samples. The databases utilized included Gene Expression Omnibus (GEO), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and The Cancer Genome Atlas (TCGA). Both gene expression and protein levels were analyzed. Subsequently, the prognostic ability of GTSE1 was evaluated based on clinical follow-up data using methods such as using univariate, multivariate, and prognostic meta-analysis. Additionally, potential mechanisms of action of GTSE1 were explored through enrichment analysis. Furthermore, the correlation between GTSE1 expression and the tumor microenvironment, immune cell infiltration, and immune checkpoints was assessed using ESTIMATE and CIBERSORT algorithms. The effectiveness of chemotherapy and targeted therapy was predicted using the “pRophetic” R package, which analyzed gene expression data.ResultsAnalysis of GEO data, CPTAC data, TCGA data, and clinical samples revealed increased levels of GTSE1 in LUAD tissues. Enhanced GTSE1 expression demonstrated excellent diagnostic accuracy and served as a significant prognostic indicator for LUAD patients. GTSE1 expression emerged as an independent predictive factor in both univariate and multivariate Cox regression analyses. Furthermore, functional enrichment analysis suggested a potential association between GTSE1 and the cell cycle, p53 signaling pathway, as well as ubiquitin-mediated protein degradation. High expression of GTSE1 was associated with increased immune cell infiltration and heightened sensitivity to a specific type of chemotherapy and targeted drugs.ConclusionIncreased expression of GTSE1 in patients with LUAD showed significant diagnostic and prognostic significance. It was also associated with increased immune infiltration and an unfavorable response to targeted medication.

Non-invasive vagus nerve stimulation (VNS) represents a transformative approach for managing a broad spectrum of inflammatory and autoimmune conditions, including rheumatoid arthritis and inflammatory bowel disease. This comprehensive review delineates the mechanisms underlying VNS, emphasizing the cholinergic anti-inflammatory pathway, and explores interactions within the neuro-immune and vagus-gut axes based on both clinical outcomes and pre-clinical models. Clinical applications have confirmed the efficacy of VNS in managing specific autoimmune diseases, such as rheumatoid arthritis, and chronic inflammatory conditions like inflammatory bowel disease, showcasing the variability in stimulation parameters and patient responses. Concurrently, pre-clinical studies have provided insights into the potential of VNS in modulating cardiovascular and broader inflammatory responses, paving the way for its translational application in clinical settings. Innovations in non-invasive VNS technology and precision neuromodulation are enhancing its therapeutic potential, making it a viable option for patients who are unresponsive to conventional treatments. Nonetheless, the widespread adoption of this promising therapy is impeded by regulatory challenges, patient compliance issues, and the need for extensive studies on long-term efficacy and safety. Future research directions will focus on refining VNS technology, optimizing treatment parameters, and exploring synergistic effects with other therapeutic modalities, which could revolutionize the management of chronic inflammatory and autoimmune disorders.

Improving the reproductive ability and fertility of male ruminants is a central concern in animal husbandry. Phytogenic feed additives, known for their anti-inflammatory, antioxidant, and immunomodulatory properties, are commonly used in animal feed. Icariin (ICA), the primary flavonoid glucoside derived from Epimedium, is a traditional tonic in Chinese herbal medicine. However, its potential to enhance the reproductive performance of male ruminants remains unclear. In this study, twelve healthy adult male dairy goats were divided into two groups. The goats received oral administration of ICA at doses of 0 (control) and 50 mg/kg body weight daily for a consecutive period of 80 days during the breeding season. The effects of ICA on the reproductive performance was analyzed by histological examinations, semen quality analysis, and ELISA experiments. ELISA results showed a progressive increase in serum levels of GnIH, LH, and testosterone with the prolonged ICA treatment (p

PurposeImpairment in perception and sensory reweighting could predispose older adults to falls. This exploratory study aimed to investigate the differences in sensory reweighting and self-motion perception for postural control under single-sensory and multisensory perturbations between older Tai Chi (TC) practitioners and healthy active older controls.MethodsTwenty-four TC practitioners and 23 age-matched non-practitioners were recruited in this observational study. Participants stood on a force plate with or without a foam surface (baseline), followed by 36 s of visual rotation stimuli, vestibular rotation stimuli, or reduced somatosensory input (adaptation), and then continued standing for 44 s (reintegration). The center-of-pressure (COP) trajectories and self-motion perception were recorded. COP signals were analyzed using traditional sway, multiscale entropy, and wavelet analysis methods and the time-window-of-integration model to examine the postural balance performance and the flexibility and speed of sensory reweighting.ResultsSignificant interaction effects of group with sensory perturbation and group with time window on COP parameters were observed (p

This case describes a patient with anaphylaxis caused by traditional Chinese medicine. Skin prick test with the traditional Chinese medicine decoction indicates that he was allergic to Suan Zao Ren. The patient had pollinosis and had never taken Suan Zao Ren before, thus we need to think the possibility of pollen food allergy syndrome. This paper also proposes a procedure for doctors to identify the specific culprit of traditional Chinese medicine decoction.

Glioma is one of the common tumors in the central nervous system, and its treatment methods (surgery, radiotherapy, and chemotherapy) lack specificity and have a poor prognosis. With the development of immunology, cell biology, and genomics, tumor immunotherapy has ushered in a new era of tumor therapy, achieving significant results in other invasive cancers such as advanced melanoma and advanced non-small cell lung cancer. Currently, the clinical trials of immunotherapy in glioma are also progressing rapidly. Here, this review summarizes promising immunotherapy methods in recent years, reviews the current status of clinical trials, and discusses the challenges and prospects of glioma immunotherapy.

ObjectiveTo explore the impact of exercise self-efficacy on college students’ emotion management ability and to analyze the mediating effects of exercise behavior and screen media use between exercise self-efficacy and emotion management ability.MethodsThis study adopted stratified, whole-cluster, and staged sampling methods, using an online questionnaire that included demographic information, exercise self-efficacy, exercise behavior, screen media use, and other relevant aspects, obtaining a total of 12,687 valid questionnaires.ResultsThe study indicated a significant positive correlation between exercise self-efficacy and emotion management ability (r = 0.349, p

In recent years, artificial intelligence (AI), especially deep learning models, has increasingly been integrated into diagnosing and treating diabetic retinopathy (DR). From delving into the singular realm of ocular fundus photography to the gradual development of proteomics and other molecular approaches, from machine learning (ML) to deep learning (DL), the journey has seen a transition from a binary diagnosis of “presence or absence” to the capability of discerning the progression and severity of DR based on images from various stages of the disease course. Since the FDA approval of IDx-DR in 2018, a plethora of AI models has mushroomed, gradually gaining recognition through a myriad of clinical trials and validations. AI has greatly improved early DR detection, and we’re nearing the use of AI in telemedicine to tackle medical resource shortages and health inequities in various areas. This comprehensive review meticulously analyzes the literature and clinical trials of recent years, highlighting key AI models for DR diagnosis and treatment, including their theoretical bases, features, applicability, and addressing current challenges like bias, transparency, and ethics. It also presents a prospective outlook on the future development in this domain.

Geological disasters in the Emei to Mianning section of the Chengdu–Kunming Railway located in southwestern China occur frequently, and many debris flow gullies are distributed along the line. Debris flows often cause damage to the railway and highway that threatens the safe operation of the original line and the double-track line. Along the railway, the debris flow outbreak risks are analyzed for 53 debris flow gullies using field survey, remote sensing interpretation, and numerical simulation. Their developmental characteristics were judged according to the code. The results are used for numerical simulation of debris flow to further determine the movement characteristics and the accumulation range of debris flow. The results are combined with high-definition satellite images to analyze the form of the railway passing from the mouth of the ditch and the simulation results to determine the impact on the safe operation of the Chengdu–Kunming Railway when the debris flow erupts. Finally, disaster prevention and mitigation projects are proposed, and the prevention and control effects of the proposed works are validated.

Accurate fruit detection is crucial for automated fruit picking. However, real-world scenarios, influenced by complex environmental factors such as illumination variations, occlusion, and overlap, pose significant challenges to accurate fruit detection. These challenges subsequently impact the commercialization of fruit harvesting robots. A tomato detection model named YOLO-SwinTF, based on YOLOv7, is proposed to address these challenges. Integrating Swin Transformer (ST) blocks into the backbone network enables the model to capture global information by modeling long-range visual dependencies. Trident Pyramid Networks (TPN) are introduced to overcome the limitations of PANet’s focus on communication-based processing. TPN incorporates multiple self-processing (SP) modules within existing top-down and bottom-up architectures, allowing feature maps to generate new findings for communication. In addition, Focaler-IoU is introduced to reconstruct the original intersection-over-union (IoU) loss to allow the loss function to adjust its focus based on the distribution of difficult and easy samples. The proposed model is evaluated on a tomato dataset, and the experimental results demonstrated that the proposed model’s detection recall, precision, F1 score, and AP reach 96.27%, 96.17%, 96.22%, and 98.67%, respectively. These represent improvements of 1.64%, 0.92%, 1.28%, and 0.88% compared to the original YOLOv7 model. When compared to other state-of-the-art detection methods, this approach achieves superior performance in terms of accuracy while maintaining comparable detection speed. In addition, the proposed model exhibits strong robustness under various lighting and occlusion conditions, demonstrating its significant potential in tomato detection.

BackgroundCathepsins, key regulators of the pathology of gastrointestinal disorders such as inflammatory bowel disease (IBD), are a target protease that has attracted much attention in recent years. IBD is a chronic and relapsing inflammatory disorder of the gut. Traditional studies have shown a correlation between cathepsin and the risk of IBD, while the causal relationship remains unclear.MethodsThis study utilized Mendelian randomization techniques to evaluate the causal relationships between eleven cathepsins and the subtypes of IBD, such as ulcerative colitis (UC) and Crohn’s disease (CD). We also performed a series of sensitivity analyses to validate the primary Mendelian randomization (MR) results, including Cochran’s Q test, the MR-PRESSO global test, and the MR pleiotropy test.ResultsThe forward MR analyses showed no significant association between cathepsins and IBD. Reverse Mendelian randomization analyses suggested that UC might lead to elevated cathepsin G levels [inverse-variance weighted (IVW): p = 0.038, b = 9.966], and CD might cause a decrease in cathepsin B levels [IVW: p = 0.002, b = −10.525] and cathepsin L1 levels [IVW: p = 0.045, b = −4.742].ConclusionsOur findings offer novel and comprehensive evidence on the impact of UC or CD on cathepsins, potentially providing valuable insights into the treatment and prognosis of IBD.

Immunotherapy using inflammatory cytokines, such as interleukin (IL)-2 and interferon (IFN)-α, has been clinically validated in treating various cancers. However, systemic immunocytokine-based therapies are limited by the short half-life of recombinant proteins and severe dose-limiting toxicities. In this study, we exploited local immunotherapy by intratumoral administration of lipid nanoparticle (LNP)-encapsulated mRNA cocktail encoding cytokines IL-12, IL-7, and IFN-α. The cytokine mRNA cocktail induced tumor regression in multiple syngeneic mouse models and anti-tumor immune memory in one syngeneic mouse model. Additionally, immune checkpoint blockade further enhanced the anti-tumor efficacy of the cytokine mRNAs. Furthermore, human cytokine mRNAs exhibited robust anti-tumor efficacy in humanized mouse tumor models. Mechanistically, cytokine mRNAs induced tumor microenvironment inflammation, characterized by robust T cell infiltration and significant inflammatory cytokine and chemokine production.

Bipolar disorder (BD) is a severe psychiatric disease with high rates of misdiagnosis and underdiagnosis, resulting in a significant disease burden on both individuals and society. Abnormal neural oscillations have garnered significant attention as potential neurobiological markers of BD. However, untangling the mechanisms that subserve these baseline alternations requires measurement of their electrophysiological underpinnings. This systematic review investigates consistent abnormal resting-state EEG power of BD and conducted an initial exploration into how methodological approaches might impact the study outcomes. This review was conducted in Pubmed-Medline and Web-of-Science in March 2024 to summarize the oscillation changes in resting-state EEG (rsEEG) of BD. We focusing on rsEEG to report spectral power in different frequency bands. We identified 10 studies, in which neural oscillations was compared with healthy individuals (HCs). We found that BD patients had abnormal oscillations in delta, theta, beta, and gamma bands, predominantly characterized by increased power, indicating potential widespread neural dysfunction, involving multiple neural networks and cognitive processes. However, the outcomes regarding alpha oscillation in BD were more heterogeneous, which is thought to be potentially influenced by the disease severity and the diversity of samples. Furthermore, we conducted an initial exploration into how demographic and methodological elements might impact the study outcomes, underlining the importance of implementing standardized data collection methods. Key aspects we took into account included gender, age, medication usage, medical history, the method of frequency band segmentation, and situation of eye open/eye close during the recordings. Therefore, in the face of abnormal multiple oscillations in BD, we need to adopt a comprehensive research approach, consider the multidimensional attributes of the disease and the heterogeneity of samples, and pay attention to the standardized experimental design to improve the reliability and reproducibility of the research results.

ObjectiveTo observe the intervention effect of comprehensive psychological interventions on the mental health of the elderly population.Methods133 elderly aged 60 and above in two urban districts of Tianshui City from January 2020 to December 2020 were selected and divided into the intervention group (n=67) and the control group (n=66). The intervention group received comprehensive psychological interventions, with no intervention given to the control group. The anxiety rate, depression rate, loneliness rate and happiness rate of the two groups were collected and compared pre- and post-intervention. Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), University of California, Los Angeles Loneliness Scale (UCLA) and Memorial University of Newfoundland Scale of Happiness (MUNSH) were used to compare the psychological status of the elderly pre- and post-intervention.ResultsDifferences in the inter-group main effects and time-point main effects for SAS, SDS, UCLA, and MUNSH scores of the intervention group were significant (all p

The outbreak of coronavirus disease 19 (COVID-19) has highlighted the demand for vaccines that are safe and effective in inducing systemic and airway mucosal immunity against the aerosol transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we developed a novel helper-dependent adenoviral vector-based COVID-19 mucosal vaccine encoding a full-length SARS-CoV-2 spike protein (HD-Ad-FS). Through intranasal immunization (single-dose and prime-boost regimens), we demonstrated that the HD-Ad-FS was immunogenic and elicited potent systemic and airway mucosal protection in BALB/c mice, transgenic ACE2 (hACE2) mice, and hamsters. We detected high titers of neutralizing antibodies (NAbs) in sera and bronchoalveolar lavages (BALs) in the vaccinated animals. High levels of spike-specific secretory IgA (sIgA) and IgG were induced in the airway of the vaccinated animals. The single-dose HD-Ad-FS elicited a strong immune response and protected animals from SARS-CoV-2 infection. In addition, the prime-boost vaccination induced cross-reactive serum NAbs against variants of concern (VOCs; Beta, Delta, and Omicron). After challenge, VOC infectious viral particles were at undetectable or minimal levels in the lower airway. Our findings highlight the potential of airway delivery of HD-Ad-FS as a safe and effective vaccine platform for generating mucosal protection against SARS-CoV-2 and its VOCs.

ObjectivesIn-depth understanding of osteonecrosis of femoral head (ONFH) has revealed that degeneration of the hip cartilage plays a crucial role in ONFH progression. However, the underlying molecular mechanisms and susceptibility to environmental factors in hip cartilage that contribute to ONFH progression remain elusive.MethodsWe conducted a multiomics study and chemical−gene interaction analysis of hip cartilage in ONFH. The differentially expressed genes (DEGs) involved in ONFH progression were identified in paired hip cartilage samples from 36 patients by combining genome-wide DNA methylation profiling, gene expression profiling, and quantitative proteomics. Gene functional enrichment and pathway analyses were performed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Functional links between proteins were discovered through protein−protein interaction (PPI) networks. The ONFH-associated chemicals were identified by integrating the DEGs with the chemical−gene interaction sets in the Comparative Toxicogenomics Database (CTD). Finally, the DEGs, including MMP13 and CHI3L1, were validated via quantitative real-time PCR (qRT−PCR) and immunohistochemistry (IHC).ResultsTwenty-two DEGs were identified across all three omics levels in ONFH cartilage, 16 of which were upregulated and six of which were downregulated. The collagen-containing extracellular matrix (ECM), ECM structural constituents, response to amino acids, the relaxin signaling pathway, and protein digestion and absorption were found to be primarily involved in cartilage degeneration in ONFH. Moreover, ten major ONFH-associated chemicals were identified, including, benzo(a)pyrene, valproic acid, and bisphenol A.ConclusionOverall, our study identified several candidate genes, pathways, and chemicals associated with cartilage degeneration in ONFH, providing novel clues into the etiology and biological processes of ONFH progression.

BackgroundBrain network dysfunction has been characterized by resting-state electroencephalography (EEG) and magnetic resonance imaging (MRI) in the prodromal stage. This study aimed to identify multi-modal electrophysiological and neuroimaging biomarkers for differential diagnosis in synucleinopathies and phenoconversion in isolated rapid eye movement sleep behavior disorder (iRBD).MethodsWe enrolled 35 patients with multiple system atrophy (MSA), 32 with Parkinson's disease (PD), 30 with iRBD and 30 matched healthy controls (HC). Power spectral density (PSD) was calculated in different frequency bands. EEG functional connectivity (FC) was calculated using the weighted Phase Lag Index (wPLI) after source localization. Significant network disruptions were further confirmed by MRI FC analysis.ResultsQuantitative EEG analysis demonstrated that delta and theta power spectral density significantly differed among MSA, PD and HC. The increased PSD was correlated with cognitive decline and olfactory dysfunction in PD. Band-specific FC profiles were observed in theta, alpha, and gamma bands. The hypoconnected alpha network significantly correlated with motor dysfunction, while the gamma FC distinguished PD from MSA. By integrating EEG and MRI network analyses, we found that FC between the olfactory cortex and dorsolateral prefrontal cortex was significantly different between MSA and PD. A multimodal discriminative model for MSA and PD, integrating spectral and FC attributes of EEG and MRI, yielded an area under the receiver operating characteristic curve of 0.900. Simultaneously, we found the FC abnormalities were more prominent than spectral features in iRBD indicating prodromal dysfunction. The decreased FC between the angular gyrus and striatum was identified in α-synucleinopathies. This hypoconnectivity was associated with dopaminergic degeneration in iRBD examined by dopamine transporter imaging.DiscussionOur study demonstrated EEG spectral and functional profiles in prodromal and clinical-defined synucleinopathies. Multimodal EEG and MRI provided a novel approach to discriminate MSA and PD, and monitor neurodegenerative progression in the preclinical phase.

IntroductionThe human leukocyte antigen (HLA) evolutionary divergence (HED) reflects immunopeptidome diversity and has been shown to predict the response of tumors to immunotherapy. Its impact on allogeneic hematopoietic stem cell transplantation (HSCT) is controversial in different studies.MethodsIn this study, we retrospectively analyzed the clinical impact of class I and II HED in 225 acute lymphoblastic leukemia patients undergoing HSCT from related haploidentical donors. The HED for recipient, donor, and donor-recipient pair was calculated based on Grantham distance, which accounts for variations in the composition, polarity, and volume of each amino acid within the peptide-binding groove of two HLA alleles. The median value of HED scores was used as a cut-off to stratify patients with high or low HED.ResultsThe class I HED for recipient (R_HEDclass I) showed the strongest association with cumulative incidence of relapse (12.2 vs. 25.0%, P = 0.00814) but not with acute graft-versus-host disease. The patients with high class II HED for donor-recipient (D/R_HEDclass II) showed a significantly higher cumulative incidence of severe aGVHD than those with low D/R_HEDclass II (24.0% vs. 6.1%, P = 0.0027). Multivariate analysis indicated that a high D/R_HEDclass II was an independent risk factor for the development of severe aGVHD (P = 0.007), and a high R_HEDclass I had a more than two-fold reduced risk of relapse (P = 0.028). However, there was no discernible difference in overall survival (OS) or disease-free survival (DFS) for patients with high or low HED, which was inconsistent with the previous investigation.DiscussionWhile the observation are limited by the presented single center retrospective cohort, the results show that HED has poor prognostic value in OS or DFS, as well as the associations with relapse and aGVHD. In haploidentical setting, class II HED for donor-recipient pair (D/R_HEDclass II) is an independent and novel risk factor for finding the best haploidentical donor, which could potentially influence clinical practice if verified in larger cohorts.

BackgroundPhase angle (PhA) is a variable obtained from bioelectrical impedance analysis (BIA). It is highly sensitive and specific and is commonly used in clinical nutrition assessment. Recently, PhA has shown promise in predicting clinical outcomes, especially as a new indicator of mortality, but its use in pediatric research is limited. This study aims to investigate the association between PhA measured at admission using BIA and PICU length of stay (LOS) and 60-day mortality in critically ill children and adolescents.MethodsA consecutive series of pediatric patients in the PICU underwent BIA measurements within 72 h of admission. All patients met the inclusion and exclusion criteria. Patient demographics, anthropometric measurements, pediatric index of mortality 2 score (PIM-2), and laboratory exams were recorded. Kaplan–Meier (K–M) survival curves were constructed based on the critical PhA value to assess differences in survival status within the 60-day window. Multivariate cox regression model was employed to illustrate the relationship between PhA and 60-day mortality rates. The Youden’s index method was used to identify the critical cut-off value for PhA in relation to mortality rates. ROC curves provided the area under the curve (AUC) and a 95% confidence interval (CI).ResultsA total of 205 pediatric patients (118 boys) were included, with a mean age of 9.2 years (±6.0). Survival curves indicated a cutoff value of 3.1°, with higher survival in patients with PhA ≥3.1° compared to those with PhA

The purpose of this study is to present a case of a patient with a negative skin biopsy who was diagnosed with neuronal intranuclear inclusion disease (NIID) through a retrospective review of a bladder biopsy specimen obtained 10 years ago. The patient initially presented with encephalitis-like symptoms, including fever, headache, and abnormal mental behavior. However, the DWI hyperintensity in the corticomedullary junction indicated the possibility of NIID. Due to the negative results of the skin biopsy, we initially refrained from hastily diagnosing the patient with NIID. However, 6 months later, the patient was readmitted to the hospital due to similar symptoms, and a follow-up MRI showed significant enlargement of the lesions at the corticomedullary junction. This time we identified intranuclear inclusions in her tissue specimens from bladder surgery. Subsequently, genetic testing was performed, leading to the diagnosis of NIID in the patient. Our case report indicates that detecting intranuclear inclusions from previous surgical specimens, rather than relying solely on skin biopsy, could significantly enhance diagnostic methods for NIID.

PurposeThe objective of this study was to create and validate a machine learning (ML)-based model for predicting the likelihood of lung infections following chemotherapy in patients with lung cancer.MethodsA retrospective study was conducted on a cohort of 502 lung cancer patients undergoing chemotherapy. Data on age, Body Mass Index (BMI), underlying disease, chemotherapy cycle, number of hospitalizations, and various blood test results were collected from medical records. We used the Synthetic Minority Oversampling Technique (SMOTE) to handle unbalanced data. Feature screening was performed using the Boruta algorithm and The Least Absolute Shrinkage and Selection Operator (LASSO). Subsequently, six ML algorithms, namely Logistic Regression (LR), Random Forest (RF), Gaussian Naive Bayes (GNB), Multi-layer Perceptron (MLP), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) were employed to train and develop an ML model using a 10-fold cross-validation methodology. The model’s performance was evaluated through various metrics, including the area under the receiver operating characteristic curve (ROC), accuracy, sensitivity, specificity, F1 score, calibration curve, decision curves, clinical impact curve, and confusion matrix. In addition, model interpretation was performed by the Shapley Additive Explanations (SHAP) analysis to clarify the importance of each feature of the model and its decision basis. Finally, we constructed nomograms to make the predictive model results more readable.ResultsThe integration of Boruta and LASSO methodologies identified Gender, Smoke, Drink, Chemotherapy cycles, pleural effusion (PE), Neutrophil-lymphocyte count ratio (NLR), Neutrophil-monocyte count ratio (NMR), Lymphocytes (LYM) and Neutrophil (NEUT) as significant predictors. The LR model demonstrated superior performance compared to alternative ML algorithms, achieving an accuracy of 81.80%, a sensitivity of 81.1%, a specificity of 82.5%, an F1 score of 81.6%, and an AUC of 0.888(95%CI(0.863-0.911)). Furthermore, the SHAP method identified Chemotherapy cycles and Smoke as the primary decision factors influencing the ML model’s predictions. Finally, this study successfully constructed interactive nomograms and dynamic nomograms.ConclusionThe ML algorithm, combining demographic and clinical factors, accurately predicted post-chemotherapy lung infections in cancer patients. The LR model performed well, potentially improving early detection and treatment in clinical practice.

ObjectivesTo construct deep learning-assisted diagnosis models based on automatic segmentation of ultrasound images to facilitate radiologists in differentiating benign and malignant parotid tumors.MethodsA total of 582 patients histopathologically diagnosed with PGTs were retrospectively recruited from 4 centers, and their data were collected for analysis. The radiomics features of six deep learning models (ResNet18, Inception_v3 etc) were analyzed based on the ultrasound images that were obtained under the best automatic segmentation model (Deeplabv3, UNet++, and UNet). The performance of three physicians was compared when the optimal model was used and not. The Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI) were utilized to evaluate the clinical benefit of the optimal model.ResultsThe Deeplabv3 model performed optimally in terms of automatic segmentation. The ResNet18 deep learning model had the best prediction performance, with an area under the receiver-operating characteristic curve of 0.808 (0.694−0.923), 0.809 (0.712−0.906), and 0.812 (0.680−0.944) in the internal test set and external test sets 1 and 2, respectively. Meanwhile, the optimal model-assisted clinical and overall benefits were markedly enhanced for two out of three radiologists (in internal validation set, NRI: 0.259 and 0.213 [p = 0.002 and 0.017], IDI: 0.284 and 0.201 [p = 0.005 and 0.043], respectively; in external test set 1, NRI: 0.183 and 0.161 [p = 0.019 and 0.008], IDI: 0.205 and 0.184 [p = 0.031 and 0.045], respectively; in external test set 2, NRI: 0.297 and 0.297 [p = 0.038 and 0.047], IDI: 0.332 and 0.294 [p = 0.031 and 0.041], respectively).ConclusionsThe deep learning model constructed for automatic segmentation of ultrasound images can improve the diagnostic performance of radiologists for PGTs.

BackgroundTo explore the clinical efficacy and safety of Kirschner wires (KWs) as a blocking screw technique for extra-articular fractures of the distal tibia treated with intramedullary nails (IMNs).MethodsFifty-three patients were treated with KW-assisted IMN for extra-articular fractures of the distal tibia via the blocking screw technique or Poller screw (PS) technique. The operation time, number of fluoroscopies, number of blocking screws used, blood loss and time to union were compared between the two groups. Additionally, the functional outcomes of the two groups were compared using range of motion (ROM), visual analog scale (VAS), American Orthopedic Foot and Ankle Society (AOFAS), and Lysholm scores.ResultsCompared with those in the PS group, the operation time in the KW group was significantly shorter, and the number of fluoroscopy procedures and amount of blood loss during KW surgery were also significantly lower (p = 0.014, 0.001, and 0.036, respectively). Regarding the functional outcomes, there were no significant differences in the ROM, VAS score, AOFAS score or Lysholm score between the two groups (p > 0.05).ConclusionIn the treatment of extra-articular fractures of the distal tibia with nails, the use of KW as a blocking screw technique is safe and reliable.

The cucumber disease images obtained from natural environments often contain noise such as variations in lighting and soil conditions, which significantly impact the accuracy of disease recognition. Additionally, existing detection models require large memory footprints, making real-time cucumber disease detection challenging. To address the challenges associated with detecting small targets in cucumber disease images, this study presents an algorithm named CucumberDet, which integrates global information perception and feature fusion. Initially, we employ the Swin Transformer as the backbone network for RetinaNet to augment the primary network’s feature extraction capabilities, thus enhancing its ability to extract information globally. Subsequently, to strengthen the network’s detection capabilities, especially for remote and small targets, we introduce a highly effective Small Target Feature Fusion Module (SFFM) to meticulously integrate detailed data of small targets into shallow feature maps. Finally, to further refine the network’s capability to identify multi-scale targets and facilitate the flow of low-level feature information to high-level features, we introduce a novel Multi-level Feature Adaptive Fusion Module (MFAFM). Encouraging detection results are obtained across three distinct datasets, with experimental findings on a self-compiled cucumber disease image dataset revealing that our proposed algorithm improves detection accuracy by 6.8% compared to the original RetinaNet baseline network. The proposed model achieves an mAP of 92.5%, with a parameter count of 38.39 million and a frame per second (FPS) rate of 23.6, underscoring its superior performance in detecting small targets and demonstrating its effectiveness across various application scenarios.

BackgroundNonalcoholic fatty liver disease (NAFLD), also known as metabolic associated fatty liver disease (MAFLD), is a common liver condition characterized by excessive fat accumulation in the liver which is not caused by alcohol. The main causes of NAFLD are obesity and insulin resistance. Dachaihu decoction (DCHD), a classic formula in traditional Chinese medicine, has been proved to treat NAFLD by targeting different aspects of pathogenesis and is being progressively used in the treatment of NAFLD. DCHD is commonly applied in a modified form to treat the NAFLD. In light of this, it is imperative to conduct a systematic review and meta-analysis to assess the effectiveness and safety of DCHD in the management of NAFLD. There is a need for a systematic review and meta-analysis to assess the effectiveness and safety of modified DCHD in treating NAFLD.ObjectiveThe objective of this meta-analysis was to systematically assess the clinical effectiveness and safety of DCHD in treating NAFLD.MethodsThis meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Including seven databases, both Chinese and English databases were searched for relevant studies. The quality of included studies was carefully assessed using the bias risk assessment tool in the Cochrane Handbook. Eligible articles were the source of extracted data which was meta-analyzed by using Review Manager 5.4 and Stata 17.0.ResultsA total of 10 studies containing 825 patients were included. Compared with conventional treatments, combined treatment could clearly improve the liver function of NAFLD patients, which could reduce the levels of ALT (MD = −7.69 U/L, 95% CI: −11.88 to −3.51, p

ObjectivesThis study aimed to evaluate 10 estimating glomerular filtration rate (eGFR) equations in central China population and construct a diagnostic prediction model for assessing the kidney damage severity.MethodsThe concordance of 10 eGFR equations was investigated in healthy individuals from central China, and their clinical effectiveness in diagnosing kidney injury was evaluated. Subsequently, relevant clinical indicators were selected to develop a clinical prediction model for kidney damage.ResultsThe overall concordance between CKD-EPIASR-Scr and CKD-EPI2021-Scr was the highest (weightedκ = 0.964) in healthy population. The CG formula, CKD-EPIASR-Scr and CKD-EPI2021-Scr performed better than others in terms of concordance with referenced GFR (rGFR), but had poor ability to distinguish between rGFR < 90 or < 60 mL/min·1.73 m2. This finding was basically consistent across subgroups. Finally, two logistic regression prediction models were constructed based on rGFR < 90 or 60 mL/min·1.73 m2. The area under the curve of receiver operating characteristic values of two prediction models were 0.811 vs 0.846 in training set and 0.812 vs 0.800 in testing set.ConclusionThe concordance of CKD-EPIASR-Scr and CKD-EPI2021-Scr was the highest in the central China population. The Cockcroft-Gault formula, CKD-EPIASR-Scr, and CKD-EPI2021-Scr more accurately reflected true kidney function, while performed poorly in the staging diagnosis of CKD. The diagnostic prediction models showed the good clinical application performance in identifying mild or moderate kidney injury. These findings lay a solid foundation for future research on renal function assessment and predictive equations.

BackgroundThe human immunodeficiency virus (HIV) remains a critical global health issue, with a pressing need for effective diagnostic and monitoring tools.MethodologyThis study explored distinctions in salivary metabolome among healthy individuals, individuals with HIV, and those receiving highly active antiretroviral therapy (HAART). Utilizing LC–MS/MS for exhaustive metabolomics profiling, we analyzed 90 oral saliva samples from individuals with HIV, categorized by CD4 count levels in the peripheral blood.ResultsOrthogonal partial least squares-discriminant analysis (OPLS-DA) and other analyses underscored significant metabolic alterations in individuals with HIV, especially in energy metabolism pathways. Notably, post-HAART metabolic profiles indicated a substantial presence of exogenous metabolites and changes in amino acid pathways like arginine, proline, and lysine degradation. Key metabolites such as citric acid, L-glutamic acid, and L-histidine were identified as potential indicators of disease progression or recovery. Differential metabolite selection and functional enrichment analysis, combined with receiver operating characteristic (ROC) and random forest analyses, pinpointed potential biomarkers for different stages of HIV infection. Additionally, our research examined the interplay between oral metabolites and microorganisms such as herpes simplex virus type 1 (HSV1), bacteria, and fungi in individuals with HIV, revealing crucial interactions.ConclusionThis investigation seeks to contribute understanding into the metabolic shifts occurring in HIV infection and following the initiation of HAART, while tentatively proposing novel avenues for diagnostic and treatment monitoring through salivary metabolomics.

Post-stroke cognitive impairment (PSCI) is a clinical syndrome characterized by cognitive deficits that manifest following a stroke and persist for up to 6 months post-event. This condition is grave, severely compromising patient quality of life and longevity, while also imposing substantial economic burdens on societies worldwide. Despite significant advancements in identifying risk factors for PSCI, research into its underlying mechanisms and therapeutic interventions remains inadequate. Microglia, the brain’s primary immune effector cells, are pivotal in maintaining, nurturing, defending, and repairing neuronal function, a process intrinsically linked to PSCI’s progression. Thus, investigating microglial activation and mechanisms in PSCI is crucial. This paper aims to foster new preventive and therapeutic approaches for PSCI by elucidating the roles, mechanisms, and characteristics of microglia in the condition.

Cellular movement is essential for many vital biological functions where it plays a pivotal role both at the single cell level, such as during division or differentiation, and at the macroscopic level within tissues, where coordinated migration is crucial for proper morphogenesis. It also has an impact on various pathological processes, one for all, cancer spreading. Cell migration is a complex phenomenon and diverse experimental methods have been developed aimed at dissecting and analysing its distinct facets independently. In parallel, corresponding analytical procedures and tools have been devised to gain deep insight and interpret experimental results. Here we review established experimental techniques designed to investigate specific aspects of cell migration and present a broad collection of historical as well as cutting-edge computational tools used in quantitative analysis of cell motion.

BackgroundFalcotentorial meningiomas (FM) are surgical challenges for protecting sinus, and the technique notes on the management of superior sagittal or transverse sinus are required for good results.MethodsWe improved the technique notes on the management of superior sagittal or transverse sinus in three FM patients with signs of increased intracranial pressure or chronic headache.ResultsAll patients underwent surgeries in the prone position, and occipital/sup-occipital/sub-occipital craniotomy was performed. In one patient, the skull was removed traditionally with exposure of the confluence of sinuses, superior sagittal, and transverse sinus, while the longitudinal skull bridge was left to suspend the dura for protecting the superior sagittal sinus in one patient, and the transverse skull bridge was left to suspend the dura for protecting the transverse sinus in one patient. The dura was opened infratentorially or supratentorially to spare the sinus and then the “skull bridge” was suspended. The tumor was then removed completely without brain swelling or significant venous bleeding. Complete tumor resection was confirmed by early postoperative imaging, and all patients recovered well without postoperative morbidity.ConclusionThe authors recommend the “skull bridge” to suspend the dura for optimal control of the venous sinuses during FM surgery (less venous bleeding).

IntroductionSweet sorghum juice is a typical production feedstock for natural, eco-friendly sweeteners and beverages. Clostridium tyrobutyricum is one of the widely used microorganisms in the food industry, and its principal product, bio-butyric acid is an important food additive. There are no published reports of Clostridium tyrobutyricum producing butyric acid using SSJ as the sole substrate without adding exogenous substances, which could reach a food-additive grade. This study focuses on tailoring a cost-effective, safe, and sustainable process and strategy for their production and application.MethodsThis study modeled the enzymolysis of non-reducing sugars via the first/second-order kinetics and added food-grade diatomite to the hydrolysate. Qualitative and quantitative analysis were performed using high-performance liquid chromatography, gas chromatography-mass spectrometer, full-scale laser diffraction method, ultra-performance liquid chromatography–tandem mass spectrometry, the cell double-staining assay, transmission electron microscopy, and Oxford nanopore technology sequencing. Quantitative real-time polymerase chain reaction, pathway and process enrichment analysis, and homology modeling were conducted for mutant genes.ResultsThe treated sweet sorghum juice showed promising results, containing 70.60 g/L glucose and 63.09 g/L fructose, with a sucrose hydrolysis rate of 98.29% and a minimal sucrose loss rate of 0.87%. Furthermore, 99.62% of the colloidal particles and 82.13% of the starch particles were removed, and the concentrations of hazardous substances were effectively reduced. A food microorganism Clostridium tyrobutyricum TGL-A236 with deep utilization value was developed, which showed superior performance by converting 30.65% glucose and 37.22% fructose to 24.1364 g/L bio-butyric acid in a treated sweet sorghum juice (1:1 dilution) fermentation broth. This titer was 2.12 times higher than that of the original strain, with a butyric acid selectivity of 86.36%. Finally, the Genome atlas view, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and evolutionary genealogy of genes: Non-supervised Orthologous (eggNOG) functional annotations, three-dimensional structure and protein cavity prediction of five non-synonymous variant genes were obtained.ConclusionThis study not only includes a systematic process flow and in-depth elucidation of relevant mechanisms but also provides a new strategy for green processing of food raw materials, improving food microbial performance, and ensuring the safe production of food additives.

IntroductionThe strong aromatic characteristics of the tender leaves of Toona sinensis determine their quality and economic value.Methods and resultsHere, GC-MS analysis revealed that caryophyllene is a key volatile compound in the tender leaves of two different T. sinensis varieties, however, the transcriptional mechanisms controlling its gene expression are unknown. Comparative transcriptome analysis revealed significant enrichment of terpenoid synthesis pathway genes, suggesting that the regulation of terpenoid synthesis-related gene expression is an important factor leading to differences in aroma between the two varieties. Further analysis of expression levels and genetic evolution revealed that TsTPS18 is a caryophyllene synthase, which was confirmed by transient overexpression in T. sinensis and Nicotiana benthamiana leaves. Furthermore, we screened an AP2/ERF transcriptional factor ERF-IX member, TsERF66, for the potential regulation of caryophyllene synthesis. The TsERF66 had a similar expression trend to that of TsTPS18 and was highly expressed in high-aroma varieties and tender leaves. Exogenous spraying of MeJA also induced the expression of TsERF66 and TsTPS18 and promoted the biosynthesis of caryophyllene. Transient overexpression of TsERF66 in T. sinensis significantly promoted TsTPS18 expression and caryophyllene biosynthesis.DiscussionOur results showed that TsERF66 promoted the expression of TsTPS18 and the biosynthesis of caryophyllene in T. sinensis leaves, providing a strategy for improving the aroma of tender leaves.

ObjectiveDespite extensive research on the relationship between pulmonary tuberculosis (PTB) and inflammatory factors, more robust causal evidence has yet to emerge. Therefore, this study aims to screen for inflammatory proteins that may contribute to the susceptibility to PTB in different populations and to explain the diversity of inflammatory and immune mechanisms of PTB in different ethnicity.MethodsThe inverse variance weighted (IVW) model of a two-sample Mendelian Randomization (MR) study was employed to conduct causal analysis on data from a genome-wide association study (GWAS). This cohort consisting PTB GWAS datasets from two European and two East Asian populations, as well as 91 human inflammatory proteins collected from 14,824 participants. Colocalization analysis aimed to determine whether the input inflammatory protein and PTB shared the same causal single nucleotide polymorphisms (SNPs) variation within the fixed region, thereby enhancing the robustness of the MR Analysis. Meta-analyses were utilized to evaluate the combined causal effects among different datasets.ResultsIn this study, we observed a significant negative correlation between tumor necrosis factor-beta levels (The alternative we employ is Lymphotoxin-alpha, commonly referred to as LT) (P < 0.05) and tumor necrosis factor receptor superfamily member 9 levels (TNFRSF9) (P < 0.05). These two inflammatory proteins were crucial protective factors against PTB. Additionally, there was a significant positive correlation found between interleukin-20 receptor subunit alpha levels (IL20Ra) (P < 0.05), which may elevate the risk of PTB. Colocalization analysis revealed that there was no overlap in the causal variation between LT and PTB SNPs. A meta-analysis further confirmed the significant combined effect of LT, TNFRSF9, and IL20Ra in East Asian populations (P < 0.05).ConclusionsLevels of specific inflammatory proteins may play a crucial role in triggering an immune response to PTB. Altered levels of LT and TNFRSF9 have the potential to serve as predictive markers for PTB development, necessitating further clinical validation in real-world settings to ascertain the impact of these inflammatory proteins on PTB.

BackgroundWe sought to assess the risk of hypertension based on the trajectory of changes in serum albumin concentrations.MethodsA total of 11,946 nonhypertension adults aged 30–60 years who underwent at least 3 medical examinations between 2009 and 2016 were included in this study. Group-based trajectory models were obtained for 4 category groups, and logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for each category group of serum albumin concentration and the risk of hypertension.ResultsDuring a mean follow-up period of 4.30 years, 1,537 hypertension events occurred in 11,946 subjects without hypertension. A high stable trajectory of serum albumin concentrations (OR, 0.70, 95% CI, 0.51–0.96) was associated with a significantly lower risk of developing hypertension. The results of the sensitivity analysis of the high stable trajectory (OR, 0.64, 95% CI, 0.43–0.96) remained statistically significant. Subjects with normal weight and those ≥45 years of age had a significantly lower risk of hypertension at moderate increase (P = 0.053 or 0.026) and high stable trajectories (P = 0.011 or 0.016). In males and overweight subjects, the risk of hypertension was significantly lower in the high stable trajectory (P = 0.038 or 0.044).ConclusionIn this study, we found that moderate increase in serum albumin concentrations and a high stable trajectory were significantly associated with a reduced risk of hypertension in subjects aged ≥45 years and those with normal weight and that high stable serum albumin concentrations were significantly associated with a reduced risk of hypertension in males and overweight subjects.

BackgroundMultiple primary lung cancer (MPLC) is an increasingly well-known clinical phenomenon. However, its molecular characterizations are poorly understood, and still lacks of effective method to distinguish it from intrapulmonary metastasis (IM). Herein, we propose an identification model based on molecular multidimensional analysis in order to accurately optimize treatment.MethodsA total of 112 Chinese lung cancers harboring at least two tumors (n = 270) were enrolled. We retrospectively selected 74 patients with 121 tumor pairs and randomly divided the tumor pairs into a training cohort and a test cohort in a 7:3 ratio. A novel model was established in training cohort, optimized for MPLC identification using comprehensive genomic profiling analyzed by a broad panel with 808 cancer-related genes, and evaluated in the test cohort and a prospective validation cohort of 38 patients with 112 tumors.ResultsWe found differences in molecular characterizations between the two diseases and rigorously selected the characterizations to build an identification model. We evaluated the performance of the classifier using the test cohort data and observed an 89.5% percent agreement (PA) for MPLC and a 100.0% percent agreement for IM. The model showed an excellent area under the curve (AUC) of 0.947 and a 91.3% overall accuracy. Similarly, the assay achieved a considerable performance in the independent validation set with an AUC of 0.938 and an MPLC predictive value of 100%. More importantly, the MPLC predictive value of the classification achieved 100% in both the test set and validation cohort. Compared to our previous mutation-based method, the classifier showed better κ consistencies with clinical classification among all 112 patients (0.84 vs. 0.65, p

Currently the determination of cyanidin 3-rutinoside content in plant petals usually requires chemical assays or high performance liquid chromatography (HPLC), which are time-consuming and laborious. In this study, we aimed to develop a low-cost, high-throughput method to predict cyanidin 3-rutinoside content, and developed a cyanidin 3-rutinoside prediction model using near-infrared (NIR) spectroscopy combined with partial least squares regression (PLSR). We collected spectral data from Michelia crassipes (Magnoliaceae) tepals and used five different preprocessing methods and four variable selection algorithms to calibrate the PLSR model to determine the best prediction model. The results showed that (1) the PLSR model built by combining the blockScale (BS) preprocessing method and the Significance multivariate correlation (sMC) algorithm performed the best; (2) The model has a reliable prediction ability, with a coefficient of determination (R2) of 0.72, a root mean square error (RMSE) of 1.04%, and a residual prediction deviation (RPD) of 2.06. The model can be effectively used to predict the cyanidin 3-rutinoside content of the perianth slices of M. crassipes, providing an efficient method for the rapid determination of cyanidin 3-rutinoside content.

BackgroundNegative emotions in college students are a significant factor affecting mental health, with suicide behaviors caused by negative emotions showing an annual increasing trend. Existing studies suggest that physical exercise is essential to alleviate negative feelings, yet the intrinsic mechanisms by which it affects negative emotions have not been fully revealed.ObjectiveNegative emotions in college students represent a significant issue affecting mental health. This study investigates the relationship between physical exercise and negative emotions among college students, incorporating sleep quality and self-rated health (SRH) as mediators to analyze the pathway mechanism of how physical exercise affects students’ negative emotions.MethodsA cross-sectional study design was utilized, employing online questionnaires for investigation. The scales included the Physical Activity Rating Scale-3 (PARS-3), the Depression Anxiety Stress Scales-21 (DASS-21), the Pittsburgh Sleep Quality Index (PSQI), and the 12-Item Short Form Health Survey (SF-12), resulting in the collection of 30,475 valid questionnaires, with a validity rate of 91%. Chain mediation tests and Bootstrap methods were applied for effect analysis.ResultsThe proportions of university students engaged in low, medium, and high levels of physical exercise were 77.6, 13.1, and 9.3%, respectively. The proportions of students experiencing “very severe” levels of stress, anxiety, and depression were 4.5, 10.9, and 3.6%, respectively. Physical exercise was significantly positively correlated with self-rated health (r = 0.194, p

To expand the application of nobiletin (NOB) in semi-solid functional foods, bovine serum albumin (BSA)/carboxymethyl inulin (CMI) complexes-stabilized Pickering emulsion (BCPE) (φoil = 60%, v/v) was fabricated, and the swallowing index and bioavailability of the NOB-loaded Pickering emulsion was evaluated. Confocal laser scanning microscope (CLSM) and cryo-scanning electron microscopy (cryo-SEM) images revealed that BSA/CMI complexes attached to the oil–water interface. NOB-loaded BCPE exhibited a viscoelastic and shear-thinning behavior. Fork drip test results suggested that the textural value of unloaded and NOB-loaded emulsions was International Dysphagia Diet Standardisation Initiative Level 4, which could be swallowed directly without chewing. The in vitro lipolysis model suggested that NOB had a faster digestive profile and a higher bioaccessibility in the BCPE than in the oil suspension. The in vivo rat model revealed that the oral bioavailability of NOB was increased by 2.07 folds in BCPE compared to its bioavailability in unformulated oil. Moreover, BCPE led to a higher plasma concentration of the major demethylated metabolite of NOB (4′-demethylnobiletin) than the unformulated oil. Accordingly, BCPE enhanced the oral bioavailability of NOB by improving bioaccessibility, absorption, and biotransformation.

BackgroundClinical signs of dysphagia, pancreatic achalasia, and esophagitis have been reported in patients with COVID-19. However, the causal relationship between COVID-19 and esophageal diseases is not clear. Therefore, we utilized Mendelian randomization to explore the potential association between COVID-19 and esophageal diseases.MethodsThe summary statistics for a Genome-wide association study (GWAS) were obtained from The COVID-19 Host Genetics Initiative, encompassing four types of COVID-19 as exposure: severe COVID-19, hospitalized COVID-19 versus ambulatory COVID-19, hospitalized COVID-19 versus uninfected, and confirmed COVID-19. Additionally, summary statistics for ten esophageal diseases as outcomes were sourced from the GWAS Catalog and FinnGen databases. Univariate Mendelian randomization (MR) analysis was utilized to thoroughly investigate and validate the potential causal association between COVID-19 and various esophageal conditions, including esophageal varices, Barrett’s esophagus, esophagitis, esophageal obstruction, esophageal ulcer, esophageal perforation, gastroesophageal reflux, congenital esophageal malformations, benign esophageal tumors, and esophageal adenocarcinoma.ResultsAn inverse variance-weighted (IVW) model was utilized for univariate Mendelian randomization (MR) analysis, which revealed that genetic liability in patients with confirmed COVID-19 was associated with esophageal obstruction (OR [95% CI]: 0.5275458 [0.2822400–0.9860563]; p-value = 0.0450699). Furthermore, a suggestive causal association was found between genetic liability and a reduced risk of benign esophageal tumors (OR [95% CI]: 0.2715453 [0.09368493–0.7870724]; p-value = 0.0163510), but with a suggestively increased risk of congenital esophageal malformations (OR [95% CI]: 6.959561 [1.1955828–40.51204]; p-value = 0.03086835). Additionally, genetic liability in hospitalized COVID-19 patients, compared to non-hospitalized COVID-19 patients, was suggestively associated with an increased risk of esophagitis (OR [95% CI]: 1.443859 [1.0890568–1.914252]; p-value = 0.01068201). The reliability of these causal findings is supported by Cochran’s Q statistic and the MR-Egger intercept test.ConclusionThe results of this study suggest the existence of a causal relationship between COVID-19 and esophageal diseases, highlighting differing risk effects of COVID-19 on distinct esophageal conditions.