Desorption Separation Ionization Mass Spectrometry (DSI-MS) for Rapid Analysis of COVID-19.

During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.

The long-term changing patterns of suicide mortality in China from 1987 to 2020: continuing urban-rural disparity.

BACKGROUND: Over the past three decades, China has experienced significant changes in urban-rural, gender, and age-specific suicide mortality patterns. This study aimed to investigate the long-term trends in suicide mortality in China from 1987 to 2020. METHODS: Suicide mortality data were obtained from China's National Health Commission. Joinpoint regression analysis was used to examine changes in trends and age-period-cohort modeling to estimate age, period, and cohort effects on suicide mortality from 1987 to 2020. Net drift, local drift, longitudinal age curves, and period relative risks were also calculated. RESULTS: Crude and age-standardized suicide mortality in China showed continuing downward trends from 1987 to 2020, with a more pronounced decrease in rural areas (net drift = -7.07%, p<0.01) compared to urban areas (net drift = -3.41%, p<0.01). The decline curve of urban areas could be divided into three substages. Period and cohort effects were more prominent in rural areas. Suicide risk was highest among individuals aged 20-24 and gradually increased after age 60. Females, particularly those of childbearing age, had higher suicide risk than males, with a reversal observed after age 50. This gender reversal showed distinct patterns in urban and rural areas, with a widening gap in urban areas and a relatively stable gap in rural areas. CONCLUSIONS: Suicide mortality in China has consistently declined over the past three decades. However, disparities in age, gender, and urban-rural settings persist, with new patterns emerging. Targeted suicide prevention programs are urgently needed for high-risk groups, including females of childbearing age and the elderly, and to address the slower decrease and reversing urban-rural gender trends.

Factors associated with out-of-school physical activity among Chinese children and adolescents: A stratified cross-sectional study.

OBJECTIVE: This observational study examined the factors associated with the physical activity (PA) of children and adolescents outside of school within the framework of Problem Behavior Theory (PBT). METHODS: This cross-sectional study obtained data from 6528 children and adolescents aged 6-16 years recruited from ten schools in Shanghai, China. The questionnaire measured out-of-school PA and PBT-based correlates. A series of multiple linear regressions were used to explore the factors influencing children and adolescents' out-of-school PA separately. Structural equation modeling (SEM) was used to explore the association between the three systems of PBT and out-of-school PA. RESULTS: Higher intrinsic motivation is positively associated with increased PA for children (b = 1.038, 95%CI: 0.897-1.180) and adolescents (b = 1.207, 95%CI: 0.890-1.524). Greater frequency of parental involvement in PA correlates with elevated PA for both children (b = 2.859, 95%CI: 2.147-3.572) and adolescents (b = 2.147, 95%CI: 0.311-3.983). In children, increased use of community exercise areas or facilities (b = 1.705, 95%CI: 0.234-3.176) and higher recreational screen time (b = 9.732, 95%CI: 5.614-13.850) are associated with higher PA. The SEM showed that factors of the personality system had a significant direct effect on out-of-school PA among children and adolescents, and factors of the behavior system also had a significant effect on children. CONCLUSIONS: Our findings suggest that the personality system, particularly intrinsic motivation, is important in promoting out-of-school PA in children and adolescents. For children, modifiable health behaviors in the behavior system can similarly influence PA.

Role of MIC levels and 23S rRNA mutation sites to clarithromycin in 14-day clarithromycin bismuth quadruple therapy for Helicobacter pylori eradication: A prospective trial in Beijing.

Background: Rising clarithromycin resistance undermines Helicobacter pylori (H. pylori) treatment efficacy. We aimed to determine clarithromycin's minimum inhibitory concentration (MIC) levels and identify specific mutation sites in the 23S ribosomal subunit (23S rRNA) that predict treatment outcomes in a 14-day regimen of clarithromycin bismuth quadruple therapy (amoxicillin 1g, clarithromycin 500 mg, rabeprazole 10 mg, and colloidal bismuth pectin 200 mg). Materials and methods: We included adult H. pylori patients who hadn't previously undergone clarithromycin-based treatment, either as initial or rescue therapy. Exclusions were made for penicillin allergy, recent use of related medications, severe illnesses, or inability to cooperate. Patients underwent a 14-day clarithromycin bismuth quadruple therapy. Gastric mucosa specimens were obtained during endoscopy before eradication. MIC against amoxicillin and clarithromycin was determined using the E-test method. The receiver operating characteristic (ROC) curve helped to find the optimal clarithromycin resistance MIC breakpoint. Genetic sequences of H. pylori 23S rRNA were identified through Sanger Sequencing. (ChiCTR2200061476). Results: Out of 196 patients recruited, 92 met the inclusion criteria for the per-protocol (PP) population. The overall intention-to-treat (ITT) eradication rate was 80.00 % (84/105), while the modified intention-to-treat (MITT) and PP eradication rates were 90.32 % (84/93) and 91.30 % (84/92) respectively. No amoxicillin resistance was observed, but clarithromycin resistance rates were 36.19 % (38/105), 35.48 % (33/93), and 34.78 % (33/92) in the ITT, MITT, and PP populations respectively. Compared with the traditional clarithromycin resistance breakpoint of 0.25 µg/mL, a MIC threshold of 12 µg/mL predicted better eradication. Among 173 mutations on 152 sites in the 23S rRNA gene, only the 2143A > G mutation could predict eradication outcomes (p < 0.000). Conclusions: Interpretation of elevated MIC values is crucial in susceptibility testing, rather than a binary "susceptible" or "resistant" classification. The 2143A > G mutation has limited specificity in predicting eradication outcomes, necessitating further investigation into additional mutation sites associated with clarithromycin resistance.

SLC35A2 expression is associated with HER2 expression in breast cancer.

The role of SLC35A2 in breast cancer remains poorly understood, with limited available information on its significance. This study aimed to investigate the expression of SLC35A2 and clinicopathological variables in breast cancer patients. Immunohistochemical analysis of SLC35A2 protein was conductedon 40 adjacent non-neoplastic tissues and 320 breast cancer tissues. The study also assesed the association between SLC35A2 expression and breast cancer clinicopathological features of breast cancer, as well as its impact on overall survival. In comparison to adjacent non-neoplastic tissues, a significantly higher expression of SLC35A2 was observed in breast cancer tissues (P = 0.020), and this expression was found to be independently correlated with HER2 positivity (P = 0.001). Survival analysis indicated that patients with low SLC35A2 expression had a more favorable prognosis in HER2-positive subtype breast cancer (P = 0.017). These results suggest that SLC35A2 is overexpressed in breast cancer tissues compared to adjacent non-neoplastic tissues and may serve as a potential prognostic marker for HER2-positive subtype breast cancer. Furthermore, breast cancer patients with the HER2 positive subtype who exhibited decreased levels of SLC35A2 expression demonstrated improved long-term prognostic outcomes.

Structure elucidation and antiviral activity of a cold water-extracted mannogalactofucan Ts1-1A from Trametes sanguinea against human cytomegalovirus in vitro.

In this study, we purified a partially acetylated heteropolysaccharide (Ts1-1A) from the fruit bodies of Trametes sanguinea Lloyd through cold water extraction and serial chromatographic separation. The purified polysaccharide Ts1-1A (12.8 kDa) was characterized as a branched mannogalactofucan with a backbone of alternately connected 1,3-linked α-Fucp and 1,6-linked α-Galp, which was partially substituted by non-reducing end units of ß-Manp at O-2 and O-3 positions of 1,6-linked α-Galp. Ts1-1A showed pronounced anti-human cytomegalovirus activity at the concentration of 200 and 500 µg/mL in systematical assessments including morphological changes, western blotting, qPCR, indirect immunofluorescence and tissue culture infective dose assays. Moreover, Ts1-1A exerted its antiviral activity at two distinct stages of viral proliferation manifesting as significantly inhibiting viral protein (IE1/2 and p52) expression and reducing viral gene (UL123, UL44 and UL32) replication in the HCMV-infected WI-38 cells. At viral attachment stage, Ts1-1A interacted with HCMV and prevented HCMV from attaching to its host cells. While at early phase of viral replication stage, Ts1-1A suppressed HCMV replication by downregulating NQO1 and HO-1 proteins related to oxidative stress as an antioxidant. To sum up, Ts1-1A is a promising anti-HCMV agent which could be developed for HCMV infection prevention and therapy.

Repeatability of epithelium thickness measured by an AS-OCT in different grades keratoconus and compared to AS-OCT/Placido topography.

PURPOSE: To compare agreement of corneal epithelium thickness (ET) between AS-OCT system (RTVue, Optovue, Fremont, USA) and AS-OCT/Placido topographer (MS-39, CSO, Florence, Italy) in different stages keratoconus (KC) eyes, and to assess the repeatability of RTVue AS-OCT. DESIGN: Prospective reliability analysis. METHODS: KC eyes were classified into forme fruste KC (FFKC), mild, moderate and severe KC. Agreement was evaluated with Bland-Altman plots and 95% limits of agreement (LoA). The repeatability of RTVue was assessed via within-subject standard deviation (Sw), test-retest variability (TRT), coefficient of variation (CoV), and intraclass correlation coefficient (ICC). RESULTS: Totally, 119 KC eyes were enrolled, with 21 FFKC, 26 mild, 39 moderate, and 34 severe. The 95% LoA ranged between -5.9 and 4.8 µm for center epithelium thickness (CET), between -5.7 and 8.2 µm for thinnest epithelium thickness (TET). At 1mm measuring points, the 95% LoA of superior, inferior, nasal and temporal were -4.2 to 4.7 µm, -5.2 to 6.0 µm, -7.9 to 10.2 µm, -11.2 to 6.0 µm. At 3mm measuring points, the corresponding values were -2.8 to 9.3 µm, -2.0 to 13.0 µm, -4.6 to 9.6 µm, -6.3 to 9.7 µm, indicating the two instruments weren't interchangeable without adjustment. Despite the repeatability of RTVue in KC patients were acceptable, repeatability decreased gradually with the peripheralization of the measurement points. CONCLUSIONS: The two OCT-based devices, RTVue and MS-39, don't provide interchangeable measurements of ET in KC patients. Repeatability decreases in severer KC, emphasizing the importance of grading before clinical examination to avoid diagnostic errors.

Association between triglyceride-glucose index trajectories and radiofrequency ablation outcomes in patients with stage 3D atrial fibrillation.

BACKGROUND: This study investigates the relationship between triglyceride-glucose (TyG) index trajectories and the results of ablation in patients with stage 3D atrial fibrillation (AF). METHODS: A retrospective cohort study was carried out on patients who underwent AF Radiofrequency Catheter Ablation (RFCA) at the Cardiology Department of the Fourth Affiliated Hospital of Zhejiang University and Taizhou Hospital of Zhejiang Province from January 2016 to December 2022. The main clinical endpoint was determined as the occurrence of atrial arrhythmia for at least 30 s following a 3-month period after ablation. Using a latent class trajectory model, different trajectory groups were identified based on TyG levels. The relationship between TyG trajectory and the outcome of AF recurrence in patients was assessed through Kaplan-Meier survival curve analysis and multivariable Cox proportional hazards regression model. RESULTS: The study included 997 participants, with an average age of 63.21 ± 9.84 years, of whom 630 were males (63.19%). The mean follow-up period for the participants was 30.43 ± 17.75 months, during which 200 individuals experienced AF recurrence. Utilizing the minimum Bayesian Information Criterion (BIC) and the maximum Entropy principle, TyG levels post-AF RFCA were divided into three groups: Locus 1 low-low group (n = 791), Locus 2 low-high-low group (n = 14), and Locus 3 high-high group (n = 192). Significant differences in survival rates among the different trajectories were observed through the Kaplan-Meier curve (P < 0.001). Multivariate Cox regression analysis showed a significant association between baseline TyG level and AF recurrence outcomes (HR = 1.255, 95% CI: 1.087-1.448). Patients with TyG levels above 9.37 had a higher risk of adverse outcomes compared to those with levels below 8.67 (HR = 2.056, 95% CI: 1.335-3.166). Furthermore, individuals in Locus 3 had a higher incidence of outcomes compared to those in Locus 1 (HR = 1.580, 95% CI: 1.146-2). CONCLUSION: The TyG trajectories in patients with stage 3D AF are significantly linked to the outcomes of AF recurrence. Continuous monitoring of TyG levels during follow-up may help in identifying patients at high risk of AF recurrence, enabling the early application of effective interventions.

Genome Editing VEGFA Prevents Corneal Neovascularization In Vivo.

Corneal neovascularization (CNV) is a common clinical finding seen in a range of eye diseases. Current therapeutic approaches to treat corneal angiogenesis, in which vascular endothelial growth factor (VEGF) A plays a central role, can cause a variety of adverse side effects. The technology of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 can edit VEGFA gene to suppress its expression. CRISPR offers a novel opportunity to treat CNV. This study shows that depletion of VEGFA with a novel CRISPR/Cas9 system inhibits proliferation, migration, and tube formation of human umbilical vein endothelial cells (HUVECs) in vitro. Importantly, subconjunctival injection of this dual AAV-SpCas9/sgRNA-VEGFA system is demonstrated which blocks suture-induced expression of VEGFA, CD31, and α-smooth muscle actin as well as corneal neovascularization in mice. This study has established a strong foundation for the treatment of corneal neovascularization via a gene editing approach for the first time.

Rapid screening of infertility-associated gynecological conditions via ambient glow discharge mass spectrometry utilizing urine metabolic fingerprints.

Infertility presents a widespread challenge for many families worldwide, often arising from various gynecological diseases (GDs) that hinder successful pregnancies. Current diagnostic methods for GDs have disadvantages such as low efficiency, high cost, misdiagnose, invasive injury and etc. This paper introduces a rapid, non-invasive, efficient, and straightforward analytical method that utilizes desorption, separation, and ionization mass spectrometry (DSI-MS) platform in conjunction with machine learning (ML) to detect urine metabolite fingerprints in patients with different GDs. We analyzed 257 samples from patients diagnosed with polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI), diminished ovarian reserve (DOR), endometriosis (EMS), recurrent pregnancy loss (RPL), recurrent implantation failure (RIF), and 87 samples from healthy control (HC) individuals. We identified metabolite differences and dysregulated pathways through dimensionality reduction methods, with the result of the discovery of 7 potential biomarkers for GDs diagnosis. The ML method effectively distinguished subtle differences in urine metabolite fingerprints. We anticipate that this innovative approach will offer a patient-friendly, rapid screening, and differentiation method for infertility-related GDs patients.

Optimization-derived blood input function using a kernel method and its evaluation with total-body PET for brain parametric imaging.

Dynamic PET allows quantification of physiological parameters through tracer kinetic modeling. For dynamic imaging of brain or head and neck cancer on conventional PET scanners with a short axial field of view, the image-derived input function (ID-IF) from intracranial blood vessels such as the carotid artery (CA) suffers from severe partial volume effects. Alternatively, optimization-derived input function (OD-IF) by the simultaneous estimation (SIME) method does not rely on an ID-IF but derives the input function directly from the data. However, the optimization problem is often highly ill-posed. We proposed a new method that combines the ideas of OD-IF and ID-IF together through a kernel framework. While evaluation of such a method is challenging in human subjects, we used the uEXPLORER total-body PET system that covers major blood pools to provide a reference for validation. METHODS: The conventional SIME approach estimates an input function using a joint estimation together with kinetic parameters by fitting time activity curves from multiple regions of interests (ROIs). The input function is commonly parameterized with a highly nonlinear model which is difficult to estimate. The proposed kernel SIME method exploits the CA ID-IF as a priori information via a kernel representation to stabilize the SIME approach. The unknown parameters are linear and thus easier to estimate. The proposed method was evaluated using 18F-fluorodeoxyglucose studies with both computer simulations and 20 human-subject scans acquired on the uEXPLORER scanner. The effect of the number of ROIs on kernel SIME was also explored. RESULTS: The estimated OD-IF by kernel SIME showed a good match with the reference input function and provided more accurate estimation of kinetic parameters for both simulation and human-subject data. The kernel SIME led to the highest correlation coefficient (R = 0.97) and the lowest mean absolute error (MAE = 10.5 %) compared to using the CA ID-IF (R = 0.86, MAE = 108.2 %) and conventional SIME (R = 0.57, MAE = 78.7 %) in the human-subject evaluation. Adding more ROIs improved the overall performance of the kernel SIME method. CONCLUSION: The proposed kernel SIME method shows promise to provide an accurate estimation of the blood input function and kinetic parameters for brain PET parametric imaging.

Effects of Rainfall Exclusion Treatment on Photosynthetic Characteristics of Black Locust in the Sub-Humid Region of the Loess Plateau, China.

The mesic-origin species Robinia pseudoacacia L. (black locust) is widely planted in the semiarid and sub-humid areas of the Loess Plateau for the reforestation of vegetation-degraded land. Under the scenario of changing precipitation patterns, exploring the response of photosynthesis to drought allows us to assess the risk to sustainable development of these plantations. In this study, paired plots were established including the control and a treatment of 30% exclusion of throughfall (since 2018). The photosynthetic characteristics were investigated using a portable photosynthesis system for four periods in the full-leaf growing season of 2021-2022, the fourth and fifth years, on both treated and controlled sampling trees. Leaf gas exchange parameters derived from diurnal changing patterns, light response curves, and CO2 response curves showed significant differences except for period II (9-11 September 2021) between the two plots. The photosynthetic midday depression was observed in 2022 in the treated plot. Meanwhile, the decline of net photosynthetic rate in the treated plot was converted from stomatal limitation to non-stomatal limitation. Furthermore, we observed that black locust adapted to long-term water deficiency by reducing stomatal conductance, increasing water use efficiency and intrinsic water use efficiency. The results demonstrate that reduction in precipitation would cause photosynthesis decrease, weaken the response sensitivity to light and CO2, and potentially impair photosynthetic resilience of the plantations. They also provide insights into the changes in photosynthetic functions under global climate change and a reference for management of plantations.

Ultrahigh Critical Current Density across Sliding Electrical Contacts in Structural Superlubric State.

In conventional sliding electrical contacts (SECs), large critical current density (CCD) requires a high ratio between actual and apparent contact area, while low friction and wear require the opposites. Structural superlubricity (SSL) has the characteristics of zero wear, near zero friction, and all-atoms in real contact between the contacting surfaces. Here, we show a measured current density up to 17.5 GA/m^{2} between microscale graphite contact surfaces while sliding under ambient conditions. This value is nearly 146 times higher than the maximum CCD of other SECs reported in literatures (0.12 GA/m^{2}). Meanwhile, the coefficient of friction for the graphite contact is less than 0.01 and the sliding interface is wear-free according to the Raman characterization, indicating the presence of the SSL state. Furthermore, we estimate the intrinsic CCD of single crystalline graphite to be 6.69 GA/m^{2} by measuring the scaling relation of CCD. Theoretical analysis reveals that the CCD is limited by thermal effect due to the Joule heat. Our results show the great potential of the SSL contacts to be used as SECs, such as micro- or nanocontact switches, conductive slip rings, or pantographs.

Models predicting mortality risk of patients with burns to ≥ 50% of the total body surface.

BACKGROUND: Several models predicting mortality risk of burn patients have been proposed. However, models that consider all such patients may not well predict the mortality of patients with extensive burns. METHOD: This retrospective multicentre study recruited patients with extensive burns (≥ 50% of the total body surface area [TBSA]) treated in three hospitals of Eastern China from 1 January 2016 to 30 June 2022. The performances of six predictive models were assessed by drawing receiver operating characteristic (ROC) and calibration curves. Potential predictors were sought via "least absolute shrinkage and selection operator" regression. Multivariate logistic regression was employed to construct a predictive model for patients with burns to ≥ 50% of the TBSA. A nomogram was prepared and the performance thereof assessed by reference to the ROC, calibration, and decision curves. RESULT: A total of 465 eligible patients with burns to ≥ 50% TBSA were included, of whom 139 (29.9%) died. The FLAMES model exhibited the largest area under the ROC curve (AUC) (0.875), followed by the models of Zhou et al. (0.853) and the ABSI model (0.802). The calibration curve of the Zhou et al. model fitted well; those of the other models significantly overestimated the mortality risk. The new nomogram includes four variables: age, the %TBSA burned, the area of full-thickness burns, and blood lactate. The AUCs (training set 0.889; internal validation set 0.934; external validation set 0.890) and calibration curves showed that the nomogram exhibited an excellent discriminative capacity and that the predictions were very accurate. CONCLUSION: For patients with burns to ≥ 50％of the TBSA, the Zhou et al. and FLAMES models demonstrate relatively high predictive ability for mortality. The new nomogram is sensitive, specific, and accurate, and will aid rapid clinical decision-making.

A complete scheme for multi-character classification using EEG signals from speech imagery.

Some classification studies of brain-computer interface (BCI) based on speech imagery show potential for improving communication skills in patients with amyotrophic lateral sclerosis (ALS). However, current research on speech imagery is limited in scope and primarily focuses on vowels or a few selected words. In this paper, we propose a complete research scheme for multi-character classification based on EEG signals derived from speech imagery. Firstly, we record 31 speech imagery contents, including 26 alphabets and 5 commonly used punctuation marks, from seven subjects using a 32-channel electroencephalogram (EEG) device. Secondly, we introduce the wavelet scattering transform (WST), which shares a structural resemblance to Convolutional Neural Networks (CNNs), for feature extraction. The WST is a knowledge-driven technique that preserves high-frequency information and maintains the deformation stability of EEG signals. To reduce the dimensionality of wavelet scattering coefficient features, we employ Kernel Principal Component Analysis (KPCA). Finally, the reduced features are fed into an Extreme Gradient Boosting (XGBoost) classifier within a multi-classification framework. The XGBoost classifier is optimized through hyperparameter tuning using grid search and 10-fold cross-validation, resulting in an average accuracy of 78.73% for the multi-character classification task. We utilize t-Distributed Stochastic Neighbor Embedding (t-SNE) technology to visualize the low-dimensional representation of multi-character speech imagery. This visualization effectively enables us to observe the clustering of similar characters. The experimental results demonstrate the effectiveness of our proposed multi-character classification scheme. Furthermore, our classification categories and accuracy exceed those reported in existing research.

Millimeter-scale magnetic implants paired with a fully integrated wearable device for wireless biophysical and biochemical sensing.

Implantable sensors can directly interface with various organs for precise evaluation of health status. However, extracting signals from such sensors mainly requires transcutaneous wires, integrated circuit chips, or cumbersome readout equipment, which increases the risks of infection, reduces biocompatibility, or limits portability. Here, we develop a set of millimeter-scale, chip-less, and battery-less magnetic implants paired with a fully integrated wearable device for measuring biophysical and biochemical signals. The wearable device can induce a large amplitude damped vibration of the magnetic implants and capture their subsequent motions wirelessly. These motions reflect the biophysical conditions surrounding the implants and the concentration of a specific biochemical depending on the surface modification. Experiments in rat models demonstrate the capabilities of measuring cerebrospinal fluid (CSF) viscosity, intracranial pressure, and CSF glucose levels. This miniaturized system opens the possibility for continuous, wireless monitoring of a wide range of biophysical and biochemical conditions within the living organism.

Rapid analysis and authentication of Chinese propolis using nanoelectrospray ionization mass spectrometry combined with machine learning.

In this study, we established a simple, rapid, and high-throughput method for the analysis and classification of propolis samples. We utilized nanoESI-MS to analyze 37 samples of propolis from China for the first time, obtaining characteristic fingerprint spectra in negative ion mode, which were then integrated with multivariate analysis to explore variations between water extract of propolis (WEP) and ethanol extract of propolis (EEP). Furthermore, we categorized propolis samples based on different climate zones and colors, screening 10 differential metabolites among propolis from various climate zones, and 11 differential metabolites among propolis samples of different color. By employing machine learning models, we achieved high-precision discrimination and prediction between samples from different climate zones and colors, achieving predictive accuracies of 95.6% and 85.6%, respectively. These results highlight the significant potential of the nanoESI-MS coupled with machine learning methodology for precise classification within the realm of food products.

Posterior Pedicle Screw Fixation With Indirect Decompression Versus Direct Decompression in Treating Thoracolumbar Burst Fracture: A Systematic Review and Meta-Analysis.

OBJECTIVE: To compare the safety and efficacy between posterior pedicle screw fixation with direct versus indirect decompression in treating patients with thoracolumbar burst fracture. METHODS: This study was conducted on the basis of PRISMA statement. We systematically searched the PubMed and Embase databases up to July 3, 2023. Relevant studies comparing indirect decompression and direct decompression were recruited. Weighted mean differences (WMDs), odds ratios (ORs) and 95% confidence intervals (CIs) were analyzed for continuous and dichotomous data, respectively. P < 0.05 was considered statistically significant. RESULTS: The operation time (WMD: -37.14, 95% CI: [-42.64, 31.64], P < 0.00001, I2 = 0%) and intraoperative blood loss (WMD: -316.82, 95% CI: [-469.80, -163.85], P < 0.0001, I2 = 99%) of indirect decompression group were significantly lower. Percentage of anterior vertebral body height (WMD: 3.98, 95% CI: [2.36, 5.60], P < 0.00001, I2 = 32%) and encroachment rate of the spinal canal (WMD: 1.48, 95% CI: [0.56, 2.40], P = 0.002, I2 = 35%) of indirect decompression group were significantly higher. No statistical difference was identified in grades of neurologic recovery and Cobb angle. CONCLUSIONS: Posterior pedicle screw fixation with indirect decompression was safe and effective for thoracolumbar burst fracture with or without neurologic deficits when posterior longitudinal ligament was intact.

Wenyang-Tianjing-Jieyu Decoction Improves Depression Rats of Kidney Yang Deficiency Pattern by Regulating T Cell Homeostasis and Inflammation Level.

Purpose: Chronic inflammation is one of the key mechanisms of depression. Wenyang-Tianjin-Jie Decoction (WTJD) is an effective antidepressant found in the course of diagnosis and treatment, but the mechanism of therapeutic effect is not clear. The study aimed to evaluate the efficacy of WTJD in the kidney yang deficiency (KYD) type of depression rats and reveal its mechanisms. Materials and Methods: We selected forty 6-week-old male Sprague-Dawley rats for the study. We established a KYD [Phellodendron amurense Rupr (Huangbai) solution oral gavage and 4°C environments; 8 weeks] type of depression (chronic unpredictable mild stimulus; 6 weeks) rat model first. After successful modeling, we used WTJD or fluoxetine on rats for 3 weeks. Then we evaluated the depression and KYD behavior. Finally, we observed the expression of key inflammatory factors and proteins in peripheral blood and hippocampus, and further investigated the immune balance of Th17/Treg and Th1/Th2 cells and the activity of their main regulatory pathways JAK2/STAT3 and TLR4/TRAF6/NF-κB. Results: The imbalance of Th17/Treg and Th1/Th2 cells in rats were related to KYD and depressive symptoms. Through this study, we found that WTJD can inhibit the activity of JAK2/STAT3 and TLR4/TRAF6/NF-κB pathways, balance Th17/Treg and Th1/Th2 cell homeostasis, regulate the levels of inflammatory factors in the hippocampus and peripheral blood, and reverse KYD and depression. Conclusion: This study confirmed that WTJD had a reliable effect on depression rats with KYD, and its mechanism was to regulate the immune homeostasis of hippocampal T cells and related inflammatory factors to improve KYD and depression symptoms in rats.

High-Temporal-Resolution Kinetic Modeling of Lung Tumors with Dual-Blood Input Function Using Total-Body Dynamic PET.

The lungs are supplied by both the pulmonary arteries carrying deoxygenated blood originating from the right ventricle and the bronchial arteries carrying oxygenated blood downstream from the left ventricle. However, this effect of dual blood supply has never been investigated using PET, partially because the temporal resolution of conventional dynamic PET scans is limited. The advent of PET scanners with a long axial field of view, such as the uEXPLORER total-body PET/CT system, permits dynamic imaging with high temporal resolution (HTR). In this work, we modeled the dual-blood input function (DBIF) and studied its impact on the kinetic quantification of normal lung tissue and lung tumors using HTR dynamic PET imaging. Methods: Thirteen healthy subjects and 6 cancer subjects with lung tumors underwent a dynamic 18F-FDG scan with the uEXPLORER for 1 h. Data were reconstructed into dynamic frames of 1 s in the early phase. Regional time-activity curves of lung tissue and tumors were analyzed using a 2-tissue compartmental model with 3 different input functions: the right ventricle input function, left ventricle input function, and proposed DBIF, all with time delay and dispersion corrections. These models were compared for time-activity curve fitting quality using the corrected Akaike information criterion and for differentiating lung tumors from lung tissue using the Mann-Whitney U test. Voxelwise multiparametric images by the DBIF model were further generated to verify the regional kinetic analysis. Results: The effect of dual blood supply was pronounced in the high-temporal-resolution time-activity curves of lung tumors. The DBIF model achieved better time-activity curve fitting than the other 2 single-input models according to the corrected Akaike information criterion. The estimated fraction of left ventricle input was low in normal lung tissue of healthy subjects but much higher in lung tumors (∼0.04 vs. ∼0.3, P < 0.0003). The DBIF model also showed better robustness in the difference in 18F-FDG net influx rate [Formula: see text] and delivery rate [Formula: see text] between lung tumors and normal lung tissue. Multiparametric imaging with the DBIF model further confirmed the differences in tracer kinetics between normal lung tissue and lung tumors. Conclusion: The effect of dual blood supply in the lungs was demonstrated using HTR dynamic imaging and compartmental modeling with the proposed DBIF model. The effect was small in lung tissue but nonnegligible in lung tumors. HTR dynamic imaging with total-body PET can offer a sensitive tool for investigating lung diseases.