Multiomics analysis of canine myocardium after circumferential pulmonary vein ablation: Effect of neuropeptide Y on long-term reinduction of atrial fibrillation.

Catheter ablation (CA) is an essential method for the interventional treatment of atrial fibrillation (AF), and it is very important to reduce long-term recurrence after CA. The mechanism of recurrence after CA is still unclear. We established a long-term model of beagle canines after circumferential pulmonary vein ablation (CPVA). The transcriptome and proteome were obtained using high-throughput sequencing and TMT-tagged LC-MS/LC analysis, respectively. Differentially expressed genes and proteins were screened and enriched, and the effect of fibrosis was found and verified in tissues. A downregulated protein, neuropeptide Y (NPY), was selected for validation and the results suggest that NPY may play a role in the long-term reinduction of AF after CPVA. Then, the molecular mechanism of NPY was further investigated. The results showed that the atrial effective refractory period (AERP) was shortened and fibrosis was increased after CPVA. Atrial myocyte apoptosis was alleviated by NPY intervention, and Akt activation was inhibited in cardiac fibroblasts. These results suggest that long-term suppression of NPY after CPVA may lead to induction of AF through promoting cardiomyocyte apoptosis and activating the Akt pathway in cardiac fibroblasts, which may make AF more likely to reinduce.

Long-Range π-π Stacking Brings High Electron Delocalization for Enhanced Photocatalytic Activity in Hydrogen-Bonded Organic Framework.

Unlike many studies that regulate transport and separation behaviour of photogenerated charge carriers through controlling the chemical composite, our work demonstrates this goal can be achieved through simply tuning the molecular π-π packing from short-range to long-range within hydrogen-bonded organic frameworks (HOFs) without altering the building blocks or network topology. Further investigations reveal that the long-range π-π stacking significantly promotes electron delocalization and enhances electron density, thereby effectively suppressing electron-hole recombination and augmenting the charge transfer rate. Simultaneously, acting as a porous substrate, it boosts electron density of Pd nanoparticle loaded on its surfaces, resulting in remarkable CO2 photoreduction catalytic activity (CO generation rate: 48.1 µmol/g/h) without the need for hole scavengers. Our study provide insight into regulating the charge carrier behaviours in molecular assemblies based on hydrogen bonds, offering a new clue for efficient photocatalyst design.

Predicting Intracranial Aneurysm Rupture: A Multifactor Analysis Combining Radscore, Morphology, and PHASES Parameters.

RATIONALE AND OBJECTIVES: We aimed at developing and validating a nomogram and machine learning (ML) models based on radiomics score (Radscore), morphology, and PHASES to predict intracranial aneurysm (IA) rupture. MATERIALS AND METHODS: We collected 440 patients with IAs in our hospital from 2015 to 2023, totaling 475 IAs (214 ruptured and 261 unruptured). A 7:3 random split was utilized to allocate participants into training and testing sets. To optimize the selection of radiomics features extracted from digital subtraction angiography, we employed t-tests and LASSO regression. Subsequently, we built single-factor and multifactor logistic regression (LR) models, alongside a nomogram. Furthermore, we employed four ML algorithms. After a comprehensive evaluation, including area under the curve (AUC), calibration curves, decision curve analysis (DCA), and other metrics, the best model was determined. RESULTS: The AUCs for LR models P (PHASES), M (Morphology), and R (Radscore) in the testing set were 0.859, 0.755, and 0.803, respectively, while those for multifactor models R+M (Radscore and Morphology), R+P (Radscore and PHASES), and R+M+P (Radscore, Morphology, and PHASES) were 0.818, 0.899, and 0.887, respectively. The AUCs of random forest, extreme gradient boosting, gradient boosting machine, and light gradient boosting machine were 0.880, 0.888, 0.891, and 0.892 in testing set, respectively. In the training set, the LR model showed significant differences in AUCs compared with the four ML models (all p < 0.05). However, in the testing set, no statistically significant differences were found between them (all p > 0.05). Both ML models and the nomogram exhibit excellent performance in DCA and calibration curves. CONCLUSION: Nomogram and ML models based on Radscore, morphology, and PHASES show high precision in predicting aneurysm rupture.

Facet-Controlled Synthesis of Unconventional-Phase Metal Alloys for Highly Efficient Hydrogen Oxidation.

Facet control and phase engineering of metal nanomaterials are both important strategies to regulate their physicochemical properties and improve their applications. However, it is still a challenge to tune the exposed facets of metal nanomaterials with unconventional crystal phases, hindering the exploration of the facet effects on their properties and functions. In this work, by using Pd nanoparticles with unconventional hexagonal close-packed (hcp, 2H type) phase, referred to as 2H-Pd, as seeds, a selective epitaxial growth method is developed to tune the predominant growth directions of secondary materials on 2H-Pd, forming Pd@NiRh nanoplates (NPLs) and nanorods (NRs) with 2H phase, referred to as 2H-Pd@2H-NiRh NPLs and NRs, respectively. The 2H-Pd@2H-NiRh NRs expose more (100)h and (101)h facets on the 2H-NiRh shells compared to the 2H-Pd@2H-NiRh NPLs. Impressively, when used as electrocatalysts toward hydrogen oxidation reaction (HOR), the 2H-Pd@2H-NiRh NRs show superior activity compared to the NiRh alloy with conventional face-centered cubic (fcc) phase (fcc-NiRh) and the 2H-Pd@2H-NiRh NPLs, revealing the crucial role of facet control in enhancing the catalytic performance of unconventional-phase metal nanomaterials. Density functional theory (DFT) calculations further unravel that the excellent HOR activity of 2H-Pd@2H-NiRh NRs can be attributed to the more exposed (100)h and (101)h facets on the 2H-NiRh shells, which possess high electron transfer efficiency, optimized H* binding energy, enhanced OH* binding energy, and a low energy barrier for the rate-determining step during the HOR process.

Crystal-Phase-Selective Etching of Heterophase Au Nanostructures.

Selective oxidative etching is one of the most effective ways to prepare hollow nanostructures and nanocrystals with specific exposed facets. The mechanism of selective etching in noble metal nanostructures mainly relies on the different reactivity of metal components and the distinct surface energy of multimetallic nanostructures. Recently, phase engineering of nanomaterials (PEN) offers new opportunities for the preparation of unique heterostructures, including heterophase nanostructures. However, the synthesis of hollow multimetallic nanostructures based on crystal-phase-selective etching has been rarely studied. Here, a crystal-phase-selective etching method is reported to selectively etch the unconventional 4H and 2H phases in the heterophase Au nanostructures. Due to the coating of Pt-based alloy and the crystal-phase-selective etching of 4H-Au in 4H/face-centered cubic (fcc) Au nanowires, the well-defined ladder-like Au@PtAg nanoframes are prepared. In addition, the 2H-Au in the fcc-2H-fcc Au nanorods and 2H/fcc Au nanosheets can also be selectively etched using the same method. As a proof-of-concept application, the ladder-like Au@PtAg nanoframes are used for the electrocatalytic hydrogen evolution reaction (HER) in acidic media, showing excellent performance that is comparable to the commercial Pt/C catalyst.

Development and External Validation of a Machine Learning-based Fall Prediction Model for Nursing Home Residents: A Prospective Cohort Study.

OBJECTIVES: To develop and externally validate a machine learning-based fall prediction model for ambulatory nursing home residents. The focus is on predicting fall occurrences within 6 months after baseline assessment through a binary classification task, aiming to provide staff with an effective and user-friendly fall-risk assessment tool. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: A total of 864 older residents living in 4 nursing homes between May 2022 and March 2023 in China. METHODS: Potential fall-risk predictors were collected through in-person interviews and assessments of anthropometric and physical function. Participants were followed for 6 months, with falls recorded by trained nurses. Seven machine learning algorithms, including Logistic Regression (LR), Gradient Boosting Machine (GBM), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Neural Networks (NN), and Decision Tree (DT), were used to develop prediction models. Performance was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) and Precision-Recall curve (PR-AUC), with calibration assessed via a calibration curve. Feature importance was visualized using SHapley Additive exPlanations (SHAP). RESULTS: The 6 selected predictors were balance, grip strength, fatigue, fall history, age, and comorbidity. The ROC-AUC for the models ranged from 0.710 to 0.750, PR-AUC from 0.415 to 0.473, sensitivity from 0.704 to 0.914, and specificity from 0.511 to 0.687 in the validation cohort. The LR model was converted into a nomogram. CONCLUSIONS AND IMPLICATIONS: The machine learning-based fall-prediction models effectively identified nursing home residents at high risk of falls. The developed nomogram can be integrated into clinical practice to enhance fall risk assessment protocols, ultimately improving patient safety and care in nursing homes.

RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1-3 node-positive breast cancer (RIGAIN): a study protocol for a multicentre, open-label, randomised controlled prospective, phase III trial.

INTRODUCTION: Postoperative radiotherapy in patients with breast cancer with one to three lymph node metastases, particularly within the pT1-2N1M0 cohort with a low clinical risk of local-regional recurrence (LRR), has incited a discourse surrounding personalised treatment strategies. Multigene testing for Recurrence Index (RecurIndex) model capably differentiates patients based on their level of LRR risk. This research aims to validate whether a more aggressive treatment approach can enhance clinical outcomes in N1 patients who possess a clinically low risk of LRR, yet a high RecurIndex-determined risk of LRR. Specifically, this entails postoperative whole breast irradiation combined with regional lymph node irradiation (RNI) following breast-conserving surgery or chest wall irradiation with RNI after mastectomy. METHODS AND ANALYSIS: The RIGAIN (RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1-3 node-positive breast cancer) Study is a multicentre, prospective, randomised, open-label, phase III clinical trial that is being conducted in China. In this study, patients with low clinical LRR risk but high RecurIndex-LRR risk are randomly assigned in a 1:1 ratio to the experimental group or the control group. In the experimental group, RNI is performed and the control group omits RNI. Efficacy and safety analyses will be conducted, enrolling a total of 540 patients (270 per group). The primary endpoint is invasive disease-free survival, and secondary endpoints include any first recurrence, LRR-free survival, distant metastasis-free survival, recurrence-free survival, overall survival, disease-free survival, breast cancer-specific mortality and assessment of patient quality of life. The study began in April 2023 and with a follow-up period of 60 months after the last participant completes radiation therapy. ETHICS AND DISSEMINATION: The study was approved by the Ethics Committee of Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University (SYSKY-2022-097-02, V.3.1). It adheres to the Helsinki Declaration and Good Clinical Practice. Research findings will be submitted for publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04069884.

Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.

OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who underwent radical radiotherapy using a pairwise machine learning algorithm. METHODS: The 130 datasets enrolled were randomly divided into a training set and a testing set in a 7:3 ratio. Clinical factors were included and radiomics features were extracted from pretreatment CT scans using pyradiomics-based software, and a pairwise naive Bayes (NB) model was developed. The performance of the model was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). To facilitate practical application, we attempted to construct an automated esophageal cancer diagnosis system based on trained models. RESULTS: To the follow-up date, 64 patients (49.23%) had experienced LR. Ten radiomics features and two clinical factors were selected for modeling. The model demonstrated good prediction performance, with area under the ROC curve of 0.903 (0.829-0.958) for the training cohort and 0.944 (0.849-1.000) for the testing cohort. The corresponding accuracies were 0.852 and 0.914, respectively. Calibration curves showed good agreement, and DCA curve confirmed the clinical validity of the model. The model accurately predicted LR in elderly patients, with a positive predictive value of 85.71% for the testing cohort. CONCLUSIONS: The pairwise NB model, based on pre-treatment enhanced chest CT-based radiomics and clinical factors, can accurately predict LR in elderly patients with ESCC. The esophageal cancer automated diagnostic system embedded with the pairwise NB model holds significant potential for application in clinical practice.

Prevalence of physical inactivity and its determinants among older adults living in nursing homes: A cross-sectional study based on COM-B model.

AIMS: To investigate the prevalence of physical inactivity in older adults living in nursing homes and explore the determinants of physical inactivity by using the Capability, Opportunity, Motivation-Behaviour model. DESIGN: A multisite, cross-sectional study was performed by convenience sampling and questionnaire survey. METHODS: A total of 390 nursing home residents were recruited from three nursing homes in Southern China from May 2022 to April 2023. The participants completed a self-designed general information questionnaire, Physical Activity Scale for the Elderly, Self-Efficacy for Exercise Scale, Exercise Benefits Scale, Patient Health Questionnaire-9 and the Short Physical Performance Battery test. Descriptive statistics, univariate analysis, Spearman correlation analysis, and ordinal logistic regression were applied for data analysis. RESULTS: The prevalence of physical inactivity among the nursing home residents reached 88.46%. Ordinal logistic regression results showed that exercise self-efficacy, perceived exercise benefits, physical function, availability of physical activity instruction, having depression, number of chronic diseases and living with spouse were the main influencing determinants of physical inactivity and explained 63.7% of the variance. CONCLUSIONS: Physical inactivity was considerable in nursing home residents in China and influenced by complex factors. Tailored measures should be designed and implemented based on these factors to enhance physical activity while considering the uniqueness of Chinese culture. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Healthcare professionals should enhance physical activity of residents by increasing benefits understanding, boosting self-efficacy, improving physical function, alleviating depression and integrating personalized physical activity guidance into routine care services. And more attention should be paid to the residents who had more chronic diseases or did not live with spouse. IMPACT: Physical inactivity is a significant problem in nursing home residents. Understanding physical inactivity and its determinants enables the development of tailored interventions to enhance their physical activity level. REPORTING METHOD: This study was reported conforming to the STROBE statement. PATIENTS OR PUBLIC CONTRIBUTION: Nursing home residents who met the inclusion criteria were recruited.

Lethal pulmonary thromboembolism in mice induced by intravenous human umbilical cord mesenchymal stem cell-derived large extracellular vesicles in a dose- and tissue factor-dependent manner.

Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have obvious advantages over MSC therapy. But the strong procoagulant properties of MSC-EVs pose a potential risk of thromboembolism, an issue that remains insufficiently explored. In this study, we systematically investigated the procoagulant activity of large EVs derived from human umbilical cord MSCs (UC-EVs) both in vitro and in vivo. UC-EVs were isolated from cell culture supernatants. Mice were injected with UC-EVs (0.125, 0.25, 0.5, 1, 2, 4 µg/g body weight) in 100 µL PBS via the tail vein. Behavior and mortality were monitored for 30 min after injection. We showed that these UC-EVs activated coagulation in a dose- and tissue factor-dependent manner. UC-EVs-induced coagulation in vitro could be inhibited by addition of tissue factor pathway inhibitor. Notably, intravenous administration of high doses of the UC-EVs (1 µg/g body weight or higher) led to rapid mortality due to multiple thrombus formations in lung tissue, platelets, and fibrinogen depletion, and prolonged prothrombin and activated partial thromboplastin times. Importantly, we demonstrated that pulmonary thromboembolism induced by the UC-EVs could be prevented by either reducing the infusion rate or by pre-injection of heparin, a known anticoagulant. In conclusion, this study elucidates the procoagulant characteristics and mechanisms of large UC-EVs, details the associated coagulation risk during intravenous delivery, sets a safe upper limit for intravenous dose, and offers effective strategies to prevent such mortal risks when high doses of large UC-EVs are needed for optimal therapeutic effects, with implications for the development and application of large UC-EV-based as well as other MSC-EV-based therapies.

Ilizarov technique for treating elbow stiffness caused by myositis ossificans: A case report.

BACKGROUND: Myositis ossificans (MO) is a rare disease involving the formation of bone outside the musculoskeletal system. While surgical intervention is the main treatment approach, preventing recurrence and standardized rehabilitation are also crucial. Here, we present a surgical strategy to prevent the recurrence of MO. CASE SUMMARY: A 28-year-old female patient was admitted for the first time for a comminuted fracture of the left olecranon. However, incorrect postoperative rehabilitation resulted in the development of elbow joint stiffness with ectopic ossification, causing a loss of normal range of motion. The patient was diagnosed with MO based on physical examination, X-ray findings, and clinical presentation. We devised a surgical strategy to remove MO, followed by fixation with an Ilizarov frame, and implemented a scientifically reasonable rehabilitation plan. The surgery lasted for 3 h with an estimated blood loss of 45 mL. A drainage tube was placed after surgery, and fluid was aspirated through ultrasound-guided puncture. The patient experienced a significant reduction in joint stiffness after surgery. In the final follow-up at 9 mouths, there was evident improvement in the range of motion of the elbow joint, and no other symptoms were reported. CONCLUSION: The Ilizarov frame is an advantageous surgical technique for facilitating rehabilitation after MO removal. It offers benefits such as passive recovery, individualized treatment, and prompt recovery.

[Effect of CD8+ CD28- T Cells on Acute Graft-Versus-Host Disease after Haploidentical Hematopoietic Stem Cell Transplantation].

OBJECTIVE: To investigate the effect of CD8+ CD28- T cells on acute graft-versus-host disease(aGVHD) after haploidentical hematopoietic stem cell transplantation(haplo-HSCT). METHODS: The relationship between absolute count of CD8+ CD28- T cells and aGVHD in 60 patients with malignant hematological diseases was retrospectively analyzed after haplo-HSCT, and the differences in the incidence rate of chronic graft-versus host disease(cGVHD), infection and prognosis between different CD8+ CD28- T absolute cells count groups were compared. RESULTS: aGVHD occurred in 40 of 60 patients after haplo-HSCT, with an incidence rate of 66.67%. The median occurrence time of aGVHD was 32.5(20-100) days. At 30 days after the transplantation, the absolute count of CD8+ CD28- T cells of aGVHD group was significantly lower than that of non-aGVHD group (P =0.03). Thus the absolute count of CD8+ CD28- T cells at 30 days after transplantation can be used to predict the occurrence of aGVHD to some extent. At 30 days after transplantation, the incidence rate of aGVHD in the low cell count group (CD8+ CD28- T cells absolute count < 0.06/µl) was significantly higher than that in the high cell count group (CD8+ CD28- T cells absolute count ≥0.06/µl,P =0.011). Multivariate Cox regression analysis further confirmed that the absolute count of CD8+ CD28-T cells at 30 days after transplantation was an independent risk factor for aGVHD, and the risk of aGVHD in the low cell count group was 2.222 times higher than that in the high cell count group (P =0.015). The incidence of cGVHD, fungal infection, EBV infection and CMV infection were not significantly different between the two groups with different CD8+ CD28- T cells absolute count. The overall survival, non-recurrent mortality and relapse rates were not significantly different between different CD8+ CD28- T cells absolute count groups. CONCLUSION: Patients with delayed CD8+ CD28- T cells reconstitution after haplo-HSCT are more likely to develop aGVHD, and the absolute count of CD8+ CD28- T cells can be used to predict the incidence of aGVHD to some extent. The absolute count of CD8+ CD28- T cells after haplo-HSCT was not associated with cGVHD, fungal infection, EBV infection, and CMV infection, and was also not significantly associated with the prognosis after transplantation.

Construction of high-density genetic map based on SLAF-seq and QTL analysis of major traits in sweetpotato [Ipomoea batatas (L.) Lam.].

Sweetpotato, Ipomoea batatas (L.) Lam., is an important worldwide crop used as feed, food, and fuel. However, its polyploidy, high heterozygosity and self-incompatibility makes it difficult to study its genetics and genomics. Longest vine length (LVL), yield per plant (YPP), dry matter content (DMC), starch content (SC), soluble sugar content (SSC), and carotenoid content (CC) are some of the major agronomic traits being used to evaluate sweetpotato. However limited research has actually examined how these traits are inherited. Therefore, after selecting 212 F1 from a Xin24 × Yushu10 crossing as the mapping population, this study applied specific-locus amplified fragment sequencing (SLAF-seq), at an average sequencing depth of 26.73 × (parents) and 52.25 × (progeny), to detect single nucleotide polymorphisms (SNPs). This approach generated an integrated genetic map of length 2441.56 cM and a mean distance of 0.51 cM between adjacent markers, encompassing 15 linkage groups (LGs). Based on the linkage map, 26 quantitative trait loci (QTLs), comprising six QTLs for LVL, six QTLs for YPP, ten QTLs for DMC, one QTL for SC, one QTL for SSC, and two QTLs for CC, were identified. Each of these QTLs explained 6.3-10% of the phenotypic variation. It is expected that the findings will be of benefit for marker-assisted breeding and gene cloning of sweetpotato.

Experimental Study on the Dielectric Properties of Coal In Situ with Variable Temperatures.

The aim of this study was to explore the mapping relationship between the temperature and the dielectric parameters of coal and rock under variable temperatures as well as to determine the characteristics of a dielectric anomaly response. Experiments were performed using lignite, nonstick coal, gas coal, coking coal, and anthracite. The evolution of pyrolysis characteristics, microcrystal structure, and dielectric properties with changing temperature was investigated, and the changes in the dielectric parameters of coal and rock were comprehensively analyzed. As such, the cause of the dielectric anomaly with changing temperatures of coal and rock was revealed. The results show that the dielectric properties of coal at different pyrolysis temperatures are closely related to the degree of intermolecular thermal motion, the evolution of microcrystal structure, and the mechanism of polarization response. In the low-temperature stage, the thermal motion of coal molecules is weak and exhibits electronic polarization, and the dielectric parameters change slightly with temperature while being dependent on the moisture content. In the high-temperature pyrolysis stage, the intense molecular thermal motion leads to the breaking of chemical bonds and the release of volatiles; moreover, the distance between aromatic layers of coal decreases, the order of aromatic structure increases, the dipole turning polarization is the main polarization type, and the dielectric response is obvious. When the pyrolysis reaction is basically complete, the dielectric constants of the five coal samples reach the maximum. As the temperature increases continuously, the coal structure is destroyed by the weakening of the thermal motion of the coal molecules and the accumulation of thermal stress; meanwhile, the dielectric constant decreases gradually, while the dielectric loss and tangent of dielectric loss increase rapidly. At the same temperature, the dielectric constant decreases with an increase in test frequency. These results lay a foundation for the inversion of dielectric data in fire areas of coal mines.

Progress in the treatment of Osteoarthritis with avocado-soybean unsaponifiable.

Osteoarthritis (OA) is one of the leading causes of joint dysfunction and disability in the elderly, posing serious social problems and a huge socio-economic burden. Existing pharmacological treatments have significant drawbacks, and searching for an effective pharmacological intervention is an urgent priority. Recent studies have demonstrated the chondroprotective, anabolic, and anti-catabolic properties of avocado-soybean unsaponifiable (ASU), a natural plant extract made from avocado and soybean oils, consisting of the remainder of the saponified portion of the product that cannot be made into soap. The main components of ASU are phytosterols, beta-sitosterol, canola stanols, and soya stanols, which are rapidly incorporated into cells. Studies have confirmed the anti-inflammatory, antioxidant, and analgesic properties of phytosterols. ASU slows down the progression of OA primarily by inhibiting pathways involved in the development of OA disease. ASU prevents cartilage degradation by inhibiting the release and activity of matrix metalloproteinases and by increasing the tissue inhibition of these catabolic enzymes; ASU is also involved in the inhibition of the activation of nuclear factor κB (NF-κB) which is a transcriptional inhibitor that regulates the inflammatory response of chondrocytes. NF-κB is a transcription factor that regulates the inflammatory response of chondrocytes, and inhibition of the transfer of the transcription factor NF-κB from the cytoplasm to the nucleus regulates the transcription of many pro-inflammatory factors. By appealing to the mechanism of action and thus achieving anti-inflammatory, anti-catabolic, and pro-synthetic effects on cartilage tissues, AUS is clinically responsive to the reduction of acute pain and OA symptom progression. This paper aims to summarize the studies on the use of avocado-soybean unsaponifiable in the pharmacological treatment of osteoarticular.

A mathematical model for the role of dopamine-D2 self-regulation in the production of ultradian rhythms.

Many self-motivated and goal-directed behaviours display highly flexible, approximately 4 hour ultradian (shorter than a day) oscillations. Despite lacking direct correspondence to physical cycles in the environment, these ultradian rhythms may be involved in optimizing functional interactions with the environment and reflect intrinsic neural dynamics. Current evidence supports a role of mesostriatal dopamine (DA) in the expression and propagation of ultradian rhythmicity, however, the biochemical processes underpinning these oscillations remain to be identified. Here, we use a mathematical model to investigate D2 autoreceptor-dependent DA self-regulation as the source of ultradian behavioural rhythms. DA concentration at the midbrain-striatal synapses is governed through a dual-negative feedback-loop structure, which naturally gives rise to rhythmicity. This model shows the propensity of striatal DA to produce an ultradian oscillation characterized by a flexible period that is highly sensitive to parameter variations. Circadian (approximately 24 hour) regulation consolidates the ultradian oscillations and alters their response to the phase-dependent, rapid-resetting effect of a transient excitatory stimulus. Within a circadian framework, the ultradian rhythm orchestrates behavioural activity and enhances responsiveness to an external stimulus. This suggests a role for the circadian-ultradian timekeeping hierarchy in governing organized behaviour and shaping daily experience through coordinating the motivation to engage in recurring, albeit not highly predictable events, such as social interactions.

[Extracorporeal Membrane Oxygenation Combined With Interventional Thrombectomy for Treating High-Risk Pulmonary Embolism Caused by Protein C Deficiency:Report of One Case].

Hereditary protein C deficiency is a chromosomal genetic disease caused by mutations in the protein C gene,which can lead to venous thrombosis and is mostly related to mutations in exons 4-9 and intron 8.Fatal pulmonary embolism caused by mutations in the protein C gene is rare,and the treatment faces great challenges.This article reports a case of fatal pulmonary embolism caused by a frameshift mutation in exon 8 of the protein C gene and summarizes the treatment experience of combining extracorporeal membrane oxygenation (for respiratory and circulatory support) with interventional thrombectomy,providing a basis for the diagnosis and treatment of this disease.

Impact of preoperative anemia on patients undergoing total joint replacement of lower extremity: a systematic review and meta-analysis.

PURPOSE: Preoperative anemia increases postoperative morbidity, mortality, and the risk of allogeneic transfusion. However, the incidence of preoperative anemia in patients undergoing total hip arthroplasty and total knee arthroplasty (TKA) and its relationship to postoperative outcomes has not been previously reported. METHODS: We conducted a comprehensive literature search through PubMed, Cochrane Library, Web of Sincien, and Embase from inception to July 2023 to investigate the prevalence of preoperative anemia in patients undergoing Total Joint Arthroplasty, comorbidities between anemic and non-anemicpatients before surgery, and postoperative outcomes. postoperative outcomes were analyzed. Overall prevalence was calculated using a random-effects model, and heterogeneity between studies was examined by Cochran's Q test and quantified by the I2 statistic. Subgroup analyses and meta-regression analyses were performed to identify sources of heterogeneity. Publication bias was assessed by funnel plots and validated by Egger's test. RESULTS: A total of 21 studies with 369,101 samples were included, all of which were retrospective cohort studies. 3 studies were of high quality and 18 studies were of moderate quality. The results showed that the prevalence of preoperative anemia was 22% in patients awaiting arthroplasty; subgroup analyses revealed that the prevalence of preoperative anemia was highest in patients awaiting revision of total knee arthroplasty; the highest prevalence of preoperative anemia was found in the Americas; preoperative anemia was more prevalent in the female than in the male population; and preoperative anemia with a history of preoperative anemia was more common in the female than in the male population. patients with a history of preoperative anemia; patients with joint replacement who had a history of preoperative anemia had an increased risk of infection, postoperative blood transfusion rate, postoperative blood transfusion, Deep vein thrombosis of the lower limbs, days in hospital, readmission within three months, and mortality compared with patients who did not have preoperative anemia. CONCLUSION: The prevalence of preoperative anemia in patients awaiting total joint arthroplasty is 22%, and is higher in TKA and female patients undergoing revision, while preoperative anemia is detrimental to the patient's postoperative recovery and will increase the risk of postoperative complications, transfusion rates, days in the hospital, readmission rates, and mortality.

Fast and accurate variant identification tool for sequencing-based studies.

BACKGROUND: Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into microbiomes often require processing numerous sequencing datasets, necessitating variant identifiers with high speed, accuracy, and robustness. RESULTS: We present QuickVariants, a bioinformatics tool that effectively summarizes variant information from read alignments and identifies variants. When tested on diverse bacterial sequencing data, QuickVariants demonstrates a ninefold higher median speed than bcftools, a widely used variant identifier, with higher accuracy in identifying both point mutations and indels. This accuracy extends to variant identification in virus samples, including SARS-CoV-2, particularly with significantly fewer false negative indels than bcftools. The high accuracy of QuickVariants is further demonstrated by its detection of a greater number of Omicron-specific indels (5 versus 0) and point mutations (61 versus 48-54) than bcftools in sewage metagenomes predominated by Omicron variants. Much of the reduced accuracy of bcftools was attributable to its misinterpretation of indels, often producing false negative indels and false positive point mutations at the same locations. CONCLUSIONS: We introduce QuickVariants, a fast, accurate, and robust bioinformatics tool designed for identifying genetic variants for microbial studies. QuickVariants is available at https://github.com/caozhichongchong/QuickVariants .