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.

Liver enzymes mediate the association between aldehydes co-exposure and hypertriglyceridemia.

Aldehydes are recognized environmental toxicants that may affect lipid metabolism. For instance, acrolein has been found to increase serum triglyceride (TG) levels exclusively. However, it remains unclear whether other aldehydes are also associated with hypertriglyceridemia (HTG), and what mechanisms may be involved. This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES, 2013-2014) to identify associations between serum aldehydes, liver enzymes, and HTG. Serum aldehydes included crotonaldehyde (CRAL), propanaldehyde (3AL), butyraldehyde (4AL), pentanaldehyde (5AL), isopentanaldehyde (I5AL), and heptanaldehyde (7AL). Liver enzymes included alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and gamma-glutamyltransferase (GGT). HTG was defined as fasting TG levels ≥ 1.7 mmol/L. Aldehyde co-exposure was quantified using weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR), while mediation analysis was performed to investigate the role of liver enzymes. Among 1474 participants (mean age 38.6 years, male 50.0%), 426 were diagnosed with HTG. 4AL, 5AL, I5AL, and 7AL were shown to be positively associated with HTG (all P values <0.05). Aldehydes co-exposure was also positively associated with HTG (OR 1.706, 95%CI 1.299-2.240), with 5AL contributing the highest weight (35.3%). Furthermore, aldehydes co-exposure showed positive associations with ALT, AST, and GGT (all P values <0.05), and all four liver enzymes were positively associated with HTG (all P values <0.05). Mediation analysis revealed that liver enzymes (ALT, AST, and GGT) may mediate the associations of 5AL and 7AL with HTG (all P values <0.05). This study identified a positive association between aldehyde co-exposure and HTG, which may be partially mediated by liver enzymes.

Implantable Electronic Medicine Enabled by Bioresorbable Microneedles for Wireless Electrotherapy and Drug Delivery.

A combined treatment using medication and electrostimulation increases its effectiveness in comparison with one treatment alone. However, the organic integration of two strategies in one miniaturized system for practical usage has seldom been reported. This article reports an implantable electronic medicine based on bioresorbable microneedle devices that is activated wirelessly for electrostimulation and sustainable delivery of anti-inflammatory drugs. The electronic medicine is composed of a radio frequency wireless power transmission system and a drug-loaded microneedle structure, all fabricated with bioresorbable materials. In a rat skeletal muscle injury model, periodic electrostimulation regulates cell behaviors and tissue regeneration while the anti-inflammatory drugs prevent inflammation, which ultimately enhance the skeletal muscle regeneration. Finally, the electronic medicine is fully bioresorbable, excluding the second surgery for device removal.

Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2.

BACKGROUND: The pneumonia caused by the 2019 novel coronavirus (SARS-CoV-2, also called 2019-nCoV) recently break out in Wuhan, China, and was named as COVID-19. With the spread of the disease, similar cases have also been confirmed in other regions of China. We aimed to report the imaging and clinical characteristics of these patients infected with SARS-CoV-2 in Guangzhou, China. METHODS: All patients with laboratory-identified SARS-CoV-2 infection by real-time polymerase chain reaction (PCR) were collected between January 23, 2020, and February 4, 2020, in a designated hospital (Guangzhou Eighth People's Hospital). This analysis included 90 patients (39 men and 51 women; median age, 50 years (age range, 18-86 years). All the included SARS-CoV-2-infected patients underwent non-contrast enhanced chest computed tomography (CT). We analyzed the clinical characteristics of the patients, as well as the distribution characteristics, pattern, morphology, and accompanying manifestations of lung lesions. In addition, after 1-6 days (mean 3.5 days), follow-up chest CT images were evaluated to assess radiological evolution. FINDINGS: The majority of infected patients had a history of exposure in Wuhan or to infected patients and mostly presented with fever and cough. More than half of the patients presented bilateral, multifocal lung lesions, with peripheral distribution, and 53 (59%) patients had more than two lobes involved. Of all included patients, COVID-19 pneumonia presented with ground glass opacities in 65 (72%), consolidation in 12 (13%), crazy paving pattern in 11 (12%), interlobular thickening in 33 (37%), adjacent pleura thickening in 50 (56%), and linear opacities combined in 55 (61%). Pleural effusion, pericardial effusion, and lymphadenopathy were uncommon findings. In addition, baseline chest CT did not show any abnormalities in 21 patients (23%), but 3 patients presented bilateral ground glass opacities on the second CT after 3-4 days. CONCLUSION: SARS-CoV-2 infection can be confirmed based on the patient's history, clinical manifestations, imaging characteristics, and laboratory tests. Chest CT examination plays an important role in the initial diagnosis of the novel coronavirus pneumonia. Multiple patchy ground glass opacities in bilateral multiple lobular with periphery distribution are typical chest CT imaging features of the COVID-19 pneumonia.

Adhesive Hemostatic Conducting Injectable Composite Hydrogels with Sustained Drug Release and Photothermal Antibacterial Activity to Promote Full-Thickness Skin Regeneration During Wound Healing.

Developing injectable nanocomposite conductive hydrogel dressings with multifunctions including adhesiveness, antibacterial, and radical scavenging ability and good mechanical property to enhance full-thickness skin wound regeneration is highly desirable in clinical application. Herein, a series of adhesive hemostatic antioxidant conductive photothermal antibacterial hydrogels based on hyaluronic acid-graft-dopamine and reduced graphene oxide (rGO) using a H2 O2 /HPR (horseradish peroxidase) system are prepared for wound dressing. These hydrogels exhibit high swelling, degradability, tunable rheological property, and similar or superior mechanical properties to human skin. The polydopamine endowed antioxidant activity, tissue adhesiveness and hemostatic ability, self-healing ability, conductivity, and NIR irradiation enhanced in vivo antibacterial behavior of the hydrogels are investigated. Moreover, drug release and zone of inhibition tests confirm sustained drug release capacity of the hydrogels. Furthermore, the hydrogel dressings significantly enhance vascularization by upregulating growth factor expression of CD31 and improve the granulation tissue thickness and collagen deposition, all of which promote wound closure and contribute to a better therapeutic effect than the commercial Tegaderm films group in a mouse full-thickness wounds model. In summary, these adhesive hemostatic antioxidative conductive hydrogels with sustained drug release property to promote complete skin regeneration are an excellent wound dressing for full-thickness skin repair.

Baroreceptor-Inspired Microneedle Skin Patch for Pressure-Controlled Drug Release.

Objective: We have developed a baroreceptor-inspired microneedle skin patch for pressure-controlled drug release. Impact Statement: This design is inspired by the skin baroreceptors, which are mechanosensitive elements of the peripheral nervous system. We adopt the finger touching to trigger the electric stimulation, ensuring a fast-response and user-friendly administration with potentially minimal off-target effects. Introduction: Chronic skin diseases bring about large, recurrent skin damage and often require convenient and timely transdermal treatment. Traditional methods lack spatiotemporal controllable dosage, leaving a risk of skin irritation or drug resistance issues. Methods: The patch consists of drug-containing microneedles and stretchable electrode array. The electrode array, integrated with the piezoconductive switch and flexible battery, provides a mild electric current only at the spot that is pressed. Drugs in microneedles will then flow along the current into the skin tissues. The stretchable feature also provides the mechanical robustness and electric stability of the device on large skin area. Results: This device delivers Cy3 dye in pig skin with spatiotemporally controlled dosage, showing ~8 times higher fluorescence intensity than the passive delivery. We also deliver insulin and observe the reduction of the blood glucose level in the mouse model upon pressing. Compared with passive delivery without pressing, the dosage of drugs released by the simulation is 2.83 times higher. Conclusion: This baroreceptor-inspired microneedle skin patch acts as a good example of the biomimicking microneedle device in the precise control of the drug release profile at the spatiotemporal resolution.

Association of red blood cell distribution width and hemoglobin-to-RDW ratio with contrast-associated acute kidney injury in patients undergoing coronary angiography: A retrospective study.

BACKGROUND: Inflammation contributes to poor prognosis in cardiovascular diseases. A novel biomarker for systemic inflammation that has garnered attention is the red blood cell distribution width (RDW). This study is designed to explore potential associations between RDW and hemoglobin-to-RDW ratio (HRR) with contrast-associated acute kidney injury (CA-AKI). METHODS: This study retrospectively analyzed 4054 patients undergoing coronary angiography (CAG). Linear regression models were employed to assess the relationships between RDW or HRR and the elevation of serum creatinine (Scr). The associations between RDW or HRR and CA-AKI were explored using restricted cubic spline and log-binomial regression analyses taking into account specific cutoff values and quintiles. Exploratory analyses were also conducted to further investigate these associations. RESULTS: Among enrolled patients, the average age was 66.9 years and 34.3% were female. Notably, patients who developed CA-AKI tended to have higher RDW and lower HRR. Multivariable linear regression models demonstrated that RDW exhibited a positive association with Scr elevation (ß = 2.496, 95% confidence interval [CI] = 1.784-3.208), while HRR displayed a negative association (ß = -3.559, 95% CI = -4.243 to -2.875). Multivariable log-binomial regression models confirmed that both high RDW (RDW ≥ 13.8%) and low HRR (HRR < 8.9) were significantly associated with a higher risk of CA-AKI (RDW [≥13.8% vs. <13.8%]: relative risk [RR] = 1.540, 95% CI = 1.345-1.762; HRR [<8.9 vs. ≥8.9]: RR = 1.822, 95% CI = 1.584-2.096). Exploratory analysis determined that such associations still existed regardless of age, gender, estimated glomerular filtration rate, or anemia. CONCLUSIONS: Elevated preoperative RDW and decreased HRR were significantly associated with CA-AKI in patients undergoing CAG.

GFI-YOLOv8: Sika Deer Posture Recognition Target Detection Method Based on YOLOv8.

As the sika deer breeding industry flourishes on a large scale, accurately assessing the health of these animals is of paramount importance. Implementing posture recognition through target detection serves as a vital method for monitoring the well-being of sika deer. This approach allows for a more nuanced understanding of their physical condition, ensuring the industry can maintain high standards of animal welfare and productivity. In order to achieve remote monitoring of sika deer without interfering with the natural behavior of the animals, and to enhance animal welfare, this paper proposes a sika deer individual posture recognition detection algorithm GFI-YOLOv8 based on YOLOv8. Firstly, this paper proposes to add the iAFF iterative attention feature fusion module to the C2f of the backbone network module, replace the original SPPF module with AIFI module, and use the attention mechanism to adjust the feature channel adaptively. This aims to enhance granularity, improve the model's recognition, and enhance understanding of sika deer behavior in complex scenes. Secondly, a novel convolutional neural network module is introduced to improve the efficiency and accuracy of feature extraction, while preserving the model's depth and diversity. In addition, a new attention mechanism module is proposed to expand the receptive field and simplify the model. Furthermore, a new pyramid network and an optimized detection head module are presented to improve the recognition and interpretation of sika deer postures in intricate environments. The experimental results demonstrate that the model achieves 91.6% accuracy in recognizing the posture of sika deer, with a 6% improvement in accuracy and a 4.6% increase in mAP50 compared to YOLOv8n. Compared to other models in the YOLO series, such as YOLOv5n, YOLOv7-tiny, YOLOv8n, YOLOv8s, YOLOv9, and YOLOv10, this model exhibits higher accuracy, and improved mAP50 and mAP50-95 values. The overall performance is commendable, meeting the requirements for accurate and rapid identification of the posture of sika deer. This model proves beneficial for the precise and real-time monitoring of sika deer posture in complex breeding environments and under all-weather conditions.

Ammonia Sensing Performance at Room Temperature of Ca-Doped CNFs/Al2O3 Gas Sensor.

When NH3 in the environment exceeds a certain concentration, it may have adverse effects on human health. Ammonia gas sensors currently on the market usually work under high temperatures and are not only expensive but also have poor performance in terms of selectivity. Therefore, the preparation of an ammonia gas sensor that works at room temperature, is low cost, and has high sensitivity and selectivity is particularly important. This paper introduces a room temperature ammonia gas sensor based on a Ca-doped CNFs/Al2O3 nanocomposite material, prepared using electrospinning, pre-oxidation, and carbonization processes. The surface morphology, microstructure, and chemical composition of the materials have been characterized by scanning electron microscopy, Raman, and X-ray photoelectron spectroscopy. The Ca-doped CNFs/Al2O3 gas sensor has excellent selectivity for ammonia at room temperature and low sensitivity to other volatile gases such as ethanol, dimethylformamide, HCl, and methanol. At 100 ppm of NH3, the response value of the Ca-doped CNFs/Al2O3 gas sensor can reach 22.73, demonstrating excellent repeatability and long-term stability. Its performance is not affected by environmental temperature and humidity, providing great convenience for practical applications. In addition, we also discuss the sensing mechanism of the Ca-doped CNFs/Al2O3 gas sensor. This paper not only provides effective materials and methods for the development of high-performance room temperature ammonia gas sensors but is also expected to play a role in the field of environmental monitoring.

Shared genetic architecture and causal relationship between liver and heart disease.

This study investigates the relationship and genetic mechanisms of liver and heart diseases, focusing on the liver-heart axis (LHA) as a fundamental biological basis. Through genome-wide association study analysis, we explore shared genes and pathways related to LHA. Shared genetic factors are found in 8 out of 20 pairs, indicating genetic correlations. The analysis reveals 53 loci with pleiotropic effects, including 8 loci exhibiting shared causality across multiple traits. Based on SNP-p level tissue-specific multi-marker analysis of genomic annotation (MAGMA) analysis demonstrates significant enrichment of pleiotropy in liver and heart diseases within different cardiovascular tissues and female reproductive appendages. Gene-specific MAGMA analysis identifies 343 pleiotropic genes associated with various traits; these genes show tissue-specific enrichment primarily in the liver, cardiovascular system, and other tissues. Shared risk loci between immune cells and both liver and cardiovascular diseases are also discovered. Mendelian randomization analyses provide support for causal relationships among the investigated trait pairs.

Research on the Behavior Recognition of Beef Cattle Based on the Improved Lightweight CBR-YOLO Model Based on YOLOv8 in Multi-Scene Weather.

In modern animal husbandry, intelligent digital farming has become the key to improve production efficiency. This paper introduces a model based on improved YOLOv8, Cattle Behavior Recognition-YOLO (CBR-YOLO), which aims to accurately identify the behavior of cattle. We not only generate a variety of weather conditions, but also introduce multi-target detection technology to achieve comprehensive monitoring of cattle and their status. We introduce Inner-MPDIoU Loss and we have innovatively designed the Multi-Convolutional Focused Pyramid module to explore and learn in depth the detailed features of cattle in different states. Meanwhile, the Lightweight Multi-Scale Feature Fusion Detection Head module is proposed to take advantage of deep convolution, achieving a lightweight network architecture and effectively reducing redundant information. Experimental results prove that our method achieves an average accuracy of 90.2% with a reduction of 3.9 G floating-point numbers, an increase of 7.4%, significantly better than 12 kinds of SOTA object detection models. By deploying our approach on monitoring computers on farms, we expect to advance the development of automated cattle monitoring systems to improve animal welfare and farm management.

A skin patch integrating swellable microneedles and electrochemical test strips for glucose and alcohol measurement in skin interstitial fluid.

Microneedle (MN)-based diagnostic devices can efficiently access skin interstitial fluid (ISF) for accurate and minimally invasive detection of health-related biomarkers. This work reports a biomarker (i.e., glucose or alcohol) monitoring MN device that is composed of swellable MNs and electrochemical test strip. This device is constructed by adhering MN patch on the electrochemical strips using the chitosan as the connecting layer. The MNs penetrate the skin for extraction of ISF that flows to the backing layer of MNs and is analyzed by the test strip. In the in vitro skin models, this device accurately detects the glucose from 0 mM to 12 mM and alcohol from 0 mM to 20 mM. In vivo experiment shows this MN device is capable of minimally invasive sampling of ISF and analysis of glucose levels to determine the glycemic status of mice.

A nanometallic conductive composite-hydrogel core-shell microneedle skin patch for real-time monitoring of interstitial glucose levels.

A microneedle-based skin patch system allows the minimally invasive extraction of skin interstitial fluid, which offers hope for the realization of quantitative and non-invasive diagnosis/monitoring of biological/physiological signals (biomarkers) in the human body. This work describes a nanometallic conductive composite-hydrogel core-shell microneedle skin patch that can realize minimally invasive real-time monitoring of physiological signals. The microneedle sensing system contains an inner conductive silver paste core and an outer bioactive hydrogel layer. The inner core is coated with biomarker-specific enzymes while the outer hydrogel layer extracts the biomarkers from the skin interstitial fluid. This patch can be integrated with the commercial signal processing and transmission modules and enable real-time monitoring. Taking glucose as a model biomarker, we confirm the function and potential application of this core-shell microneedle patch for transdermal diagnosis. It is proven that the core-shell microneedle patch can quickly extract skin interstitial fluid within 30 seconds and has a fast and linear response to glucose concentrations from 0 to 21 mM with a correlation coefficient of 0.9970, which may pave the way for the future development of smart wearable devices with minimally invasive transdermal biosensors.

Cardiac remodeling on echocardiogram is related to contrast-associated acute kidney injury after coronary angiography: a cross-section study.

Background: Cardiac dysfunction is a well-established risk factor for contrast-associated acute kidney injury (CA-AKI). Nevertheless, the relationship between cardiac remodeling, as assessed by echocardiography, and CA-AKI remains uncertain. Method: A total of 3,241 patients undergoing coronary angiography (CAG) with/without percutaneous coronary intervention (PCI) were enrolled in this retrospective study. Collected echocardiographic parameters were normalized by body surface area (BSA) and divided according to quartile, including the left ventricular internal end-diastolic diameter index (LVIDDI), left ventricular internal end-systolic diameter index (LVIDSI), and left ventricular mass index (LVMI). Logistic regression analysis was conducted to ascertain the association between structural parameter changes and CA-AKI. Further investigation was performed in different subgroups. Results: The mean age of the participants was 66.6 years, and 16.3% suffered from CA-AKI. LVIDSI [≥22.9 mm/m2: OR = 1.953, 95%CI (1.459 to 2.615), P < 0.001], LVIDDI [≥33.2 mm/m2: OR = 1.443, 95%CI (1.087 to 1.914), P = 0.011], and LVMI [≥141.0 g/m2: OR = 1.530, 95%CI (1.146 to 2.044), P = 0.004] in quartile were positively associated with CA-AKI risk in general (all P for trend <0.05). These associations were consistent when stratified by age, left ventricular ejection fraction, estimated glomerular filtration rate, and N-terminal brain natriuretic peptide (all P for interaction >0.05). The presence of eccentric hypertrophy [OR = 1.400, 95%CI (1.093 to 1.793), P = 0.008] and the coexistence of hypertrophy and dilation [OR = 1.397, 95%CI (1.091 to 1.789), P = 0.008] carried a higher CA-AKI risk. Conclusion: The presence of cardiac remodeling, assessed by echocardiography, is associated with a higher risk of CA-AKI.

Luteolin intake is negatively associated with all-cause and cardiac mortality among patients with type 2 diabetes mellitus.

BACKGROUND: Luteolin, a common flavonoid in our daily diet, has potent anti-diabetic effects. However, its prognostic impact on type 2 diabetes mellitus (T2DM) is still uncertain. This study aimed to clarify this association. METHODS: In this prospective cohort study, 2,461 patients with T2DM were included from the National Health and Nutrition Examination Survey. Dietary luteolin intake was estimated by the type and amount of food consumed in a 24-hour dietary recall. All-cause and cardiac mortality were ascertained by National Death Index Mortality data (as of December 31, 2019). The association of luteolin intake with mortality risk was estimated by Cox proportional hazards model. RESULTS: The median (interquartile range) luteolin intake was 0.355 (0.130, 0.835) mg/day. During the follow-up (median, 8.4 years), 561 all-cause deaths (including 136 cardiac deaths) were documented. Per-unit increment of luteolin intake (natural logarithm transformed) was found to reduce all-cause mortality by 7.0% (P = 0.024) and cardiac mortality by 22.6% (P = 0.001) in patients with T2DM. An inverse dose-response association was identified between luteolin intake (range: 0.005-9.870 mg/day) and mortality risk. The consistent result was also shown when stratified by age, gender, race, body mass index, HbA1c level, and T2DM duration. Moreover, luteolin intake increment was also shown to be associated with a lower C-reactive protein level at baseline (ß =-0.332; 95% CI =-0.541, -0.122). CONCLUSION: The current study confirmed that the dietary luteolin intake increment reduced all-cause mortality (especially cardiac mortality) in patients with T2DM, which may be attributed to the anti-inflammatory property of luteolin.

Transdermal delivery of dextran using conductive microneedles assisted by iontophoresis.

The combination of microneedles (MNs) and iontophoresis (ITP) can enhance the drug penetration in the skin. We previously demonstrated the enhanced delivery of small molecule lidocaine in dentistry by the conductive MNs assisted by ITP. However, the delivery of macromolecules is yet to be explored for this strategy. This study fabricates conductive MNs with polyaniline and hyaluronic acid, which is combined with ITP to deliver dextran macromolecules. This combination improves the penetration of dextran molecules (3-5 kDa, 150 kDa, and 500 kDa) to a depth of around 1536 µm in the agarose gel model. Compared to non-conductive MNs assisted by ITP or conductive MNs alone, conductive MNs assisted by ITP also improves dextran's penetration through the skin, fat, muscle, and cartilage.

Lightweight-Convolutional Neural Network for Apple Leaf Disease Identification.

As a widely consumed fruit worldwide, it is extremely important to prevent and control disease in apple trees. In this research, we designed convolutional neural networks (CNNs) for five diseases that affect apple tree leaves based on the AlexNet model. First, the coarse-grained features of the disease are extracted in the model using dilated convolution, which helps to maintain a large receptive field while reducing the number of parameters. The parallel convolution module is added to extract leaf disease features at multiple scales. Subsequently, the series 3 × 3 convolutions shortcut connection allows the model to deal with additional nonlinearities. Further, the attention mechanism is added to all aggregated output modules to better fit channel features and reduce the impact of a complex background on the model performance. Finally, the two fully connected layers are replaced by global pooling to reduce the number of model parameters, to ensure that the features are not lost. The final recognition accuracy of the model is 97.36%, and the size of the model is 5.87 MB. In comparison with five other models, our model design is reasonable and has good robustness; further, the results show that the proposed model is lightweight and can identify apple leaf diseases with high accuracy.

Lightweight individual cow identification based on Ghost combined with attention mechanism.

Individual cow identification is a prerequisite for intelligent dairy farming management, and is important for achieving accurate and informative dairy farming. Computer vision-based approaches are widely considered because of their non-contact and practical advantages. In this study, a method based on the combination of Ghost and attention mechanism is proposed to improve ReNet50 to achieve non-contact individual recognition of cows. In the model, coarse-grained features of cows are extracted using a large sensory field of cavity convolution, while reducing the number of model parameters to some extent. ResNet50 consists of two Bottlenecks with different structures, and a plug-and-play Ghost module is inserted between the two Bottlenecks to reduce the number of parameters and computation of the model using common linear operations without reducing the feature map. In addition, the convolutional block attention module (CBAM) is introduced after each stage of the model to help the model to give different weights to each part of the input and extract the more critical and important information. In our experiments, a total of 13 cows' side view images were collected to train the model, and the final recognition accuracy of the model was 98.58%, which was 4.8 percentage points better than the recognition accuracy of the original ResNet50, the number of model parameters was reduced by 24.85 times, and the model size was only 3.61 MB. In addition, to verify the validity of the model, it is compared with other networks and the results show that our model has good robustness. This research overcomes the shortcomings of traditional recognition methods that require human extraction of features, and provides theoretical references for further animal recognition.

Micropatterned conductive elastomer patch based on poly (glycerol sebacate)-graphene for cardiac tissue repair.

Preparing a micropatterned elastomer film with characteristics that can simulate the mechanical properties, anisotropy, and electroactivity of natural myocardial tissues is crucial in cardiac tissue engineering after myocardial infarction (MI). Therefore, in this study, we developed several elastomeric films with a surface micropattern based on poly (glycerol sebacate) (PGS) and graphene (Gr). These films have sufficient mechanical strength (0.6 ± 0.1-3.2 ± 0.08 MPa) to withstand heartbeats, and the micropatterned structure also satisfies the natural myocardium anisotropy in the transverse and vertical. Moreover, Gr makes these films conductive (up to 5.80 × 10-7S m-1), which is necessary for the conduction of electrical signals between cardiomyocytes and the cardiac tissue. Furthermore, they have good cytocompatibility and can promote cell proliferation in H9c2 rat cardiomyocyte cell lines.In vivotest results indicate that these films have good biocompatibility. Notably, a film with 1 wt% Gr content (PGS-Gr1) significantly affects the recovery of myocardial function in rats after MI. This film effectively decreased the infarct size and degree of myocardial fibrosis and reduced collagen deposition. Echocardiographic evaluation showed that after treatment with this film, the left ventricular internal dimension (LVID) in systole and LVID in diastole of rats exhibited a significant downward trend, whereas the fractional shortening and ejection fraction were significantly increased compared with the control group. These data indicate that this electroactive micropatterned anisotropic elastomer film can be applied in cardiac tissue engineering.

Prognostic nomogram incorporating radiological features for predicting overall survival in patients with AIDS-related non-Hodgkin lymphoma.

BACKGROUND: Acquired immune deficiency syndrome (AIDS)-related non-Hodgkin lymphoma (AR-NHL) is a high-risk factor for morbidity and mortality in patients with AIDS. This study aimed to determine the prognostic factors associated with overall survival (OS) and to develop a prognostic nomogram incorporating computed tomography imaging features in patients with acquired immune deficiency syndrome-related non-Hodgkin lymphoma (AR-NHL). METHODS: A total of 121 AR-NHL patients between July 2012 and November 2019 were retrospectively reviewed. Clinical and radiological independent predictors of OS were confirmed using multivariable Cox analysis. A prognostic nomogram was constructed based on the above clinical and radiological factors and then provided optimum accuracy in predicting OS. The predictive accuracy of the nomogram was determined by Harrell C-statistic. Kaplan-Meier survival analysis was used to determine median OS. The prognostic value of adjuvant therapy was evaluated in different subgroups. RESULTS: In the multivariate Cox regression analysis, involvement of mediastinal or hilar lymph nodes, liver, necrosis in the lesions, the treatment with chemotherapy, and the CD4 ≤100 cells/µL were independent risk factors for poor OS (all P < 0.050). The predictive nomogram based on Cox regression has good discrimination (Harrell C-index = 0.716) and good calibration (Hosmer-Lemeshow test, P = 0.620) in high- and low-risk groups. Only patients in the high-risk group who received adjuvant chemotherapy had a significantly better survival outcome. CONCLUSION: A survival-predicting nomogram was developed in this study, which was effective in assessing the survival outcomes of patients with AR-NHL. Notably, decision-making of chemotherapy regimens and more frequent follow-up should be considered in the high-risk group determined by this model.