Wireless Flexible System for Highly Sensitive Ammonia Detection Based on Polyaniline/Carbon Nanotubes.

Ammonia (NH3) is a harmful atmospheric pollutant and an important indicator of environment, health, and food safety conditions. Wearable devices with flexible gas sensors offer convenient real-time NH3 monitoring capabilities. A flexible ammonia gas sensing system to support the internet of things (IoT) is proposed. The flexible gas sensor in this system utilizes polyaniline (PANI) with multiwall carbon nanotubes (MWCNTs) decoration as a sensitive material, coated on a silver interdigital electrode on a polyethylene terephthalate (PET) substrate. Gas sensors are combined with other electronic components to form a flexible electronic system. The IoT functionality of the system comes from a microcontroller with Wi-Fi capability. The flexible gas sensor demonstrates commendable sensitivity, selectivity, humidity resistance, and long lifespan. The experimental data procured from the sensor reveal a remarkably low detection threshold of 0.3 ppm, aligning well with the required specifications for monitoring ammonia concentrations in exhaled breath gas, which typically range from 0.425 to 1.8 ppm. Furthermore, the sensor demonstrates a negligible reaction to the presence of interfering gases, such as ethanol, acetone, and methanol, thereby ensuring high selectivity for ammonia detection. In addition to these attributes, the sensor maintains consistent stability across a range of environmental conditions, including varying humidity levels, repeated bending cycles, and diverse angles of orientation. A portable, stable, and effective flexible IoT system solution for real-time ammonia sensing is demonstrated by collecting data at the edge end, processing the data in the cloud, and displaying the data at the user end.

Tertiary Plasticity Drives the Efficiency of Enterocin 7B Interactions with Lipid Membranes.

The ability of antimicrobial peptides to efficiently kill their bacterial targets depends on the efficiency of their binding to the microbial membrane. In the case of enterocins, there is a three-part interaction: initial binding, unpacking of helices on the membrane surface, and permeation of the lipid bilayer. Helical unpacking is driven by disruption of the peptide hydrophobic core when in contact with membranes. Enterocin 7B is a leaderless enterocin antimicrobial peptide produced from Enterococcus faecalis that functions alone, or with its cognate partner enterocin 7A, to efficiently kill a wide variety of Gram-stain positive bacteria. To better characterize the role that tertiary structural plasticity plays in the ability of enterocin 7B to interact with the membranes, a series of arginine single-site mutants were constructed that destabilize the hydrophobic core to varying degrees. A series of experimental measures of structure, stability, and function, including CD spectra, far UV CD melting profiles, minimal inhibitory concentrations analysis, and release kinetics of calcein, show that decreased stabilization of the hydrophobic core is correlated with increased efficiency of a peptide to permeate membranes and in killing bacteria. Finally, using the computational technique of adaptive steered molecular dynamics, we found that the atomistic/energetic landscape of peptide mechanical unfolding leads to free energy differences between the wild type and its mutants, whose trends correlate well with our experiment.

Effects of Brown Fishmeal on Growth Performance, Digestibility, and Lipid Metabolism of the Chinese Soft-Shelled Turtle (Pelodiscus sinensis).

The aim of this study was to evaluate the effect of brown fishmeal in replacement of white fishmeal in the diet of Chinese soft-shelled turtles and to find the optimal amount of brown fishmeal to add. Five experimental groups were set up and fed to animals, and they were composed by different proportions of white and brown fishmeal: G1 (30% white and 25% brown fishmeal), G2 (25% white and 30% brown fishmeal), G3 (20% white and 35% brown fishmeal), G4 (15% white and 40% brown fishmeal), G5 (10% white and 45% brown fishmeal). G1 is regarded as the control group. Turtles were randomly divided into five experimental groups with four replicates each. The experiment lasted 72 days. The results showed that the WGR, SGR, FCR, and HSI of the G3 group were not significantly different from those of the control group (P > 0.05). In addition, brown fishmeal can increase the crude protein content in the muscles of them. Among the serum biochemical indices, there was no significant difference between the G3 group and the G1 group, except for the level of TG (P > 0.05). Meanwhile, the activities of AST, ALT, and CAT in the liver of the G3 group did not differ significantly from those of the G1 group (P > 0.05). However, the activities of ACP, AKP, and T-AOC were significantly decreased in the G3 group (P < 0.05). In addition, the alteration of fishmeal did not affect the digestive enzyme activities in the stomach, liver, and intestine, and there is no significant difference (P > 0.05). Importantly, with increasing brown fishmeal addition, the expression of Fas, Pparγ, Scd, and Stat3 showed a significant increase, while the expression of Bmp4 decreased significantly (P < 0.05). In this study, the addition of 20% white fishmeal and 35% brown fishmeal to the diet of Chinese soft-shelled turtles did not adversely affect growth performance. Therefore, 20% white fishmeal and 35% brown fishmeal are the most practical feed formulations for Chinese soft-shelled turtles in this study.

Interstitial pneumonia combined with nocardia cyriacigeorgica infection: A case report.

BACKGROUND: Nocardia infection is a relatively uncommon disease, with no reports among patients with interstitial pneumonia. Due to its atypical clinical symptoms and chest computed tomography (CT) findings and the frequent yielding of negative results by conventional cultures, it poses challenges for timely diagnosis and treatment. CASE SUMMARY: A 63-year-old female patient presented to our hospital in July 2022 with a 3-mo history of intermittent cough and poor appetite, accompanied by a 2-wk long duration of headaches. She had a previous medical history of interstitial pneumonia and was on oral prednisone and cyclosporine. Chest CT revealed the presence of newly developed round nodules. The diagnosis of Nocardia cyriacigeorgica infection was confirmed through metagenomic next-generation sequencing (mNGS) performed on bronchoalveolar lavage fluid. Targeted anti-infection therapy was initiated, resulting in symptom improvement and radiological resolution, further validating the mNGS results. CONCLUSION: Nocardia cyriacigeorgica infection is a clinically rare condition that is primarily observed in immunocompromised patients. Its clinical and radiological manifestations lack specificity, but mNGS can aid in rapidly obtaining pathogenic information. Early initiation of targeted antimicrobial therapy based on mNGS results can improve patient prognosis.

The ribosomal protein P0A is required for embryo development in rice.

BACKGROUND: The P-stalk is a conserved and vital structural element of ribosome. The eukaryotic P-stalk exists as a P0-(P1-P2)2 pentameric complex, in which P0 function as a base structure for incorporating the stalk onto 60S pre-ribosome. Prior studies have suggested that P0 genes are indispensable for survival in yeast and animals. However, the functions of P0 genes in plants remain elusive. RESULTS: In the present study, we show that rice has three P0 genes predicted to encode highly conserved proteins OsP0A, OsP0B and OsP0C. All of these P0 proteins were localized both in cytoplasm and nucleus, and all interacted with OsP1. Intriguingly, the transcripts of OsP0A presented more than 90% of the total P0 transcripts. Moreover, knockout of OsP0A led to embryo lethality, while single or double knockout of OsP0B and OsP0C did not show any visible defects in rice. The genomic DNA of OsP0A could well complement the lethal phenotypes of osp0a mutant. Finally, sequence and syntenic analyses revealed that OsP0C evolved from OsP0A, and that duplication of genomic fragment harboring OsP0C further gave birth to OsP0B, and both of these duplication events might happen prior to the differentiation of indica and japonica subspecies in rice ancestor. CONCLUSION: These data suggested that OsP0A functions as the predominant P0 gene, playing an essential role in embryo development in rice. Our findings highlighted the importance of P0 genes in plant development.

Effective and efficient content-based similarity retrieval of large lung CT images based on WSSLN model.

The in-depth combination and application of AI technology and medical imaging, especially high- definition CT imaging technology, make accurate diagnosis and treatment possible. Retrieving similar CT image(CI)s to an input one from the large-scale CI database of labeled diseases is helpful to realize a precise computer-aided diagnosis. In this paper, we take lung CI as an example and propose progressive content-based similarity retrieval(CBSR) method of the lung CIs based on a Weakly Supervised Similarity Learning Network (WSSLN) model. Two enabling techniques (i.e., the WSSLN model and the distance- based pruning scheme) are proposed to facilitate the CBSR processing of the large lung CIs. The main result of our paper is that, our approach is about 45% more effective than the state-of-the-art methods in terms of the mean average precision(mAP). Moreover, for the retrieval efficiency, the WSSLN-based CBSR method is about 150% more efficient than the sequential scan.

Structurally Diverse Sesquiterpenoids from the Genus of Ainsliaea.

The genus of Ainsliaea embraces approximately 70 recognized species, many of which have been used to treat various diseases in folklore medicines. As the main metabolites of Ainsliaea plants, Ainsliaea sesquiterpenoids have drawn considerable attention in related scientific communities due to their intriguing structures and a variety of bioactivities. In this review, we intend to provide a full-aspect coverage of sesquiterpenoids reported from the genus of Ainsliaea, including 145 monomeric sesquiterpenoids and 30 oligomeric ones. Multiple aspects will be summarized, including their classification, distributions, structures, bioactivities, and biomimetic syntheses. In addition, their possible biosynthetic pathway will be discussed in detail.

The diagnostic value of serum insulin-like growth factor binding protein 7 in gastric cancer.

Backgrounds: Early detection might help in reducing the burden and promoting the survival rate of gastric cancers. Herein, we tried to explore the diagnostic value of insulin-like growth factor binding protein 7 (IGFBP7) in gastric cancers. Methods: In this study, we first analyzed the expression levels and prognostic value of IGFBP7 mRNA in gastric cancers from The Cancer Genome Atlas (TCGA) database. Then, we recruited 169 gastric cancer patients and 100 normal controls as training cohort, and 55 gastric cancer patients and 55 normal controls as independent validation cohort. Enzyme-linked immunosorbent assay was applied to test the serum levels of IGFBP7. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were applied to evaluation the diagnostic value. Results: TCGA showed that IGFBP7 mRNA was dysregulated and associated with prognosis in gastric cancer patients. Then, we examined the expression of serum IGFBP7 and found that serum IGFBP7 expressed lower in gastric cancer patients than normal controls both in training and independent validation cohorts (p < 0.0001). In training cohort, with the cutoff value of 1.515 ng/ml, the AUC for distinguishing gastric cancer patients was 0.774 (95% CI [0.713-0.836]) with sensitivity of 36.7% (95% CI [29.5-44.5]) and specificity of 90.0% (95% CI [82.0-94.8]). As for early-stage EJA, the AUC was 0.773 (95% CI [0.701-0.845]) with the sensitivity of 33.3% (95% CI [14.4-58.8]). In independent validation cohort, with the same cutoff value, the AUC reached to 0.758 (95% CI [0.664-0.852]). Similarly, for early-stage gastric cancer diagnosis in the independent validation cohort, the AUC value was 0.778 (95% CI [0.673-0.882]). Conclusions: This study indicated that serum IGFBP7 might act as a potential early diagnostic marker for gastric cancers.

Value of multiparametric magnetic resonance imaging for evaluating chronic kidney disease and renal fibrosis.

OBJECTIVES: To identify optimized MRI markers for evaluating chronic kidney disease (CKD) and renal interstitial fibrosis (IF). MATERIALS AND METHODS: This prospective study included 43 patients with CKD and 20 controls. The CKD group was divided into mild and moderate-to-severe subgroups based on pathological results. Scanned sequences included T1 mapping, R2* mapping, intravoxel incoherent motion imaging, and diffusion-weighted imaging. One-way analyses of variance were used to compare MRI parameters among groups. Correlations of MRI parameters with estimated glomerular filtration rate (eGFR) and renal IF were analyzed using age as covariates. The support vector machine (SVM) model was used to evaluate the diagnostic efficacy of multiparametric MRI. RESULTS: Compared to control values, renal cortical apparent diffusion coefficient (cADC), medullary ADC (mADC), cortical pure diffusion coefficient (cDt), medullary Dt (mDt), cortical shifted apparent diffusion coefficient (csADC), and medullary sADC (msADC) values gradually decreased in the mild and moderate-to-severe groups, while cortical T1 (cT1) and medullary T1 (mT1) values gradually increased. Values of cADC, mADC, cDt, mDt, cT1, mT1, csADC, and msADC were significantly associated with eGFR and IF (p < 0.001). The SVM model indicated that multiparametric MRI combining cT1 and csADC can distinguish patients with CKD from controls with high accuracy (0.84), sensitivity (0.70), and specificity (0.92) (AUC: 0.96). Multiparametric MRI combining cT1 and cADC exhibited high accuracy (0.91), sensitivity (0.95), and specificity (0.81) for evaluating IF severity (AUC: 0.96). CONCLUSION: Multiparametric MRI combining T1 mapping and diffusion imaging may be of clinical utility in non-invasive assessment of CKD and IF. CLINICAL RELEVANCE STATEMENT: This study shows that multiparametric MRI combining T1 mapping and diffusion imaging may be clinically useful in the non-invasive assessment of chronic kidney disease (CKD) and interstitial fibrosis; this could provide information for risk stratification, diagnosis, treatment, and prognosis. KEY POINTS: • Optimized MRI markers for evaluating chronic kidney disease and renal interstitial fibrosis were investigated. • Renal cortex/medullary T1 values increased as interstitial fibrosis increased; cortical shifted apparent diffusion coefficient (csADC) correlated significantly with eGFR and interstitial fibrosis. • Support vector machine (SVM) combining cortical T1 (cT1) and csADC/cADC effectively identifies chronic kidney disease and accurately predicts renal interstitial fibrosis.

Deep Learning Network with Spatial Attention Module for Detecting Acute Bilirubin Encephalopathy in Newborns Based on Multimodal MRI.

BACKGROUND: Acute bilirubin encephalopathy (ABE) is a significant cause of neonatal mortality and disability. Early detection and treatment of ABE can prevent the further development of ABE and its long-term complications. Due to the limited classification ability of single-modal magnetic resonance imaging (MRI), this study aimed to validate the classification performance of a new deep learning model based on multimodal MRI images. Additionally, the study evaluated the effect of a spatial attention module (SAM) on improving the model's diagnostic performance in distinguishing ABE. METHODS: This study enrolled a total of 97 neonates diagnosed with ABE and 80 neonates diagnosed with hyperbilirubinemia (HB, non-ABE). Each patient underwent three types of multimodal imaging, which included T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and an apparent diffusion coefficient (ADC) map. A multimodal MRI classification model based on the ResNet18 network with spatial attention modules was built to distinguish ABE from non-ABE. All combinations of the three types of images were used as inputs to test the model's classification performance, and we also analyzed the prediction performance of models with SAMs through comparative experiments. RESULTS: The results indicated that the diagnostic performance of the multimodal image combination was better than any single-modal image, and the combination of T1WI and T2WI achieved the best classification performance (accuracy = 0.808 ± 0.069, area under the curve = 0.808 ± 0.057). The ADC images performed the worst among the three modalities' images. Adding spatial attention modules significantly improved the model's classification performance. CONCLUSION: Our experiment showed that a multimodal image classification network with spatial attention modules significantly improved the accuracy of ABE classification.

Single-Atomic-Layer Stanene on Ferromagnetic Co Nanoislands with Topological Band Structures.

Introducing magnetism to two-dimensional topological insulators is a central issue in the pursuit of magnetic topological materials in low dimensionality. By means of low-temperature growth at 80 K, we succeeded in fabricating a monolayer stanene on Co/Cu(111) and resolving ferromagnetic spin contrast by field-dependent spin-polarized scanning tunneling microscopy (SP-STM). Increases of both remanence to saturation magnetization ratio (Mr/Ms) and coercive field (Hc) due to an enhanced perpendicular magnetic anisotropy (PMA) are further identified by out-of-plane magneto-optical Kerr effect (MOKE). In addition to ultraflat stanene fully relaxed on bilayer Co/Cu(111) from density functional theory (DFT), characteristic topological properties including an in-plane s-p band inversion and a spin-orbit coupling (SOC) induced gap about 0.25 eV at the Γ̅ point have also been verified in the Sn-projected band structure. Interfacial coupling of single-atomic-layer stanene with ferromagnetic Co biatomic layers allows topological band features to coexist with ferromagnetism, facilitating a conceptual design of atomically thin magnetic topological heterostructures.

Moxibustion attenuates liver metastasis of colorectal cancer by regulating gut microbial dysbiosis.

The liver metastasis is the primary factor attributing to the poor prognosis of colorectal cancer (CRC). Moxibustion has been used clinically against multiple malignancies. In this study, we explored the safety, efficacy, and the potential functional mechanisms of moxibustion in modulating the liver metastasis of CRC by using GFP-HCT116 cells-derived CRC liver metastasis model in Balb/c nude mice. The tumor bearing mice were randomly divided into model control and treatment groups. Moxibustion was applied to the BL18 and ST36 acupoints. CRC liver metastasis was measured by fluorescence imaging. Furthermore, feces from all mice were collected, and 16S rRNA analysis was used to assess their microbial diversity, which was analyzed for its correlation with liver metastasis. Our results indicated that the liver metastasis rate was decreased significantly by moxibustion treatment. Moxibustion treatment also caused statistically significant changes in the gut microbe population, suggesting that moxibustion reshaped the imbalanced gut microbiota in the CRC liver metastasis mice. Therefore, our findings provide new insights into the host-microbe crosstalk during CRC liver metastasis and suggest moxibustion could inhibit CRC liver metastasis by remolding the structure of destructed gut microbiota community. Moxibustion may serve as a complementary and alternative therapy for the treatment of patients with CRC liver metastasis.

A Computer-Aided Heart Valve Disease Diagnosis System Based on Machine Learning.

Cardiac auscultation is a noninvasive, convenient, and low-cost diagnostic method for heart valvular disease, and it can diagnose the abnormality of the heart valve at an early stage. However, the accuracy of auscultation relies on the professionalism of cardiologists. Doctors in remote areas may lack the experience to diagnose correctly. Therefore, it is necessary to design a system to assist with the diagnosis. This study proposed a computer-aided heart valve disease diagnosis system, including a heart sound acquisition module, a trained model for diagnosis, and software, which can diagnose four kinds of heart valve diseases. In this study, a training dataset containing five categories of heart sounds was collected, including normal, mitral stenosis, mitral regurgitation, and aortic stenosis heart sound. A convolutional neural network GoogLeNet and weighted KNN are used to train the models separately. For the model trained by the convolutional neural network, time series heart sound signals are converted into time-frequency scalograms based on continuous wavelet transform to adapt to the architecture of GoogLeNet. For the model trained by weighted KNN, features from the time domain and time-frequency domain are extracted manually. Then feature selection based on the chi-square test is performed to get a better group of features. Moreover, we designed software that lets doctors upload heart sounds, visualize the heart sound waveform, and use the model to get the diagnosis. Model assessments using accuracy, sensitivity, specificity, and F1 score indicators are done on two trained models. The results showed that the model trained by modified GoogLeNet outperformed others, with an overall accuracy of 97.5%. The average accuracy, sensitivity, specificity, and F1 score for diagnosing four kinds of heart valve diseases are 98.75%, 96.88%, 99.22%, and 97.99%, respectively. The computer-aided diagnosis system, with a heart sound acquisition module, a diagnostic model, and software, can visualize the heart sound waveform and show the reference diagnostic results. This can assist in the diagnosis of heart valve diseases, especially in remote areas, which lack skilled doctors.

Purinergic signaling in myocardial ischemia-reperfusion injury.

Purines and their derivatives, extensively distributed in the body, act as a class of extracellular signaling molecules via a rich array of receptors, also known as purinoceptors (P1, P2X, and P2Y). They mediate multiple intracellular signal transduction pathways and participate in various physiological and pathological cell behaviors. Since the function in myocardial ischemia-reperfusion injury (MIRI), this review summarized the involvement of purinergic signal transduction in diversified pathological processes, including energy metabolism disorder, oxidative stress injury, calcium overload, inflammatory immune response, platelet aggregation, coronary vascular dysfunction, and cell necrosis and apoptosis. Moreover, increasing evidence suggests that purinergic signaling also mediates the prevention and treatment of MIRI, such as ischemic conditioning, pharmacological intervention, and some other therapies. In conclusion, this review exhibited that purinergic signaling mediates the complex processes of MIRI which shows its promising application and prospecting in the future.

Correlation between chemical denaturation and the unfolding energetics of Acanthamoeba actophorin.

The actin filament network is in part remodeled by the action of a family of filament severing proteins that are responsible for modulating the ratio between monomeric and filamentous actin. Recent work on the protein actophorin from the amoeba Acanthamoeba castellani identified a series of site-directed mutations that increase the thermal stability of the protein by 22°C. Here, we expand this observation by showing that the mutant protein is also significantly stable to both equilibrium and kinetic chemical denaturation, and employ computer simulations to account for the increase in thermal or chemical stability through an accounting of atomic-level interactions. Specifically, the potential of mean force (PMF) can be obtained from steered molecular dynamics (SMD) simulations in which a protein is unfolded. However, SMD can be inefficient for large proteins as they require large solvent boxes, and computationally expensive as they require increasingly many SMD trajectories to converge the PMF. Adaptive steered molecular dynamics (ASMD) overcomes the second of these limitations by steering the particle in stages, which allows for convergence of the PMF using fewer trajectories compared with SMD. Use of the telescoping water scheme within ASMD partially overcomes the first of these limitations by reducing the number of waters at each stage to only those needed to solvate the structure within a given stage. In the PMFs obtained from ASMD, the work of unfolding Acto-2 was found to be higher than the Acto-WT by approximately 120 kCal/mol and reflects the increased stability seen in the chemical denaturation experiments. The evolution of the average number of hydrogen bonds and number of salt bridges during the pulling process provides a mechanistic view of the structural changes of the actophorin protein as it is unfolded, and how it is affected by the mutation in concert with the energetics reported through the PMF.

[Research progress in chemical constituents, pharmacological activity, and quality markers of Bruceae Fructus].

Bruceae Fructus is a Chinese herbal medicine with the chemical constituents mainly including Brucea javanica oil, quassinoids, flavonoids, steroids, triterpenoids, and alkaloids. Modern research demonstrates that Bruceae Fructus has anti-tumor, anti-malaria, anti-inflammatory, and lipid-lowering activities. This paper introduces the resource distribution, chemical constituents, and pharmacological activities of Bruceae Fructus. Further, according to the concept of quality marker(Q-marker), this paper predicts the Q-markers of Bruceae Fructus from the specificity of chemical components, pharmaceutical activity, measurability of chemical constituents, compatibility, and clinical efficacy, aiming to provide a theoretical basis for establishing the quality standard of Bruceae Fructus.

Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate.

As the technology of Internet of Things (IoT) becomes popular, the number of sensor nodes also increases. The network coverage, extensibility, and reliability are also the key points of technical development. To address the challenge of environmental restriction and deployment cost, most sensor nodes are powered by batteries. Therefore, the low-power consumption becomes an important issue because of the finite value of battery capacity. In addition, significant interference occurs in the environment, thereby complicating reliable wireless communication. This study proposes a fuzzy-based adaptive data rate for the transmission power control in wireless sensor networks to balance the communication quality and power consumption. The error count and error interval perform the inputs of a fuzzy system and the corresponding fuzzy system output is guard that is utilized for limiting the upper bounds of data rate and transmission power. The long-term experimental results are introduced to demonstrate that the control algorithm can overcome environmental interference and obtain low-power performance. The sensor nodes have reliable communication under an ultra-low-power consumption. The experimental results show that the total power consumption of the proposed approach has been improved 73% compared with the system without executing the algorithm and also indicate the Packet Error Rate (PER) is close to 1%. Therefore, the proposed method is suitable for the battery supply IoT system.

Improving performance of deep learning models using 3.5D U-Net via majority voting for tooth segmentation on cone beam computed tomography.

Deep learning allows automatic segmentation of teeth on cone beam computed tomography (CBCT). However, the segmentation performance of deep learning varies among different training strategies. Our aim was to propose a 3.5D U-Net to improve the performance of the U-Net in segmenting teeth on CBCT. This study retrospectively enrolled 24 patients who received CBCT. Five U-Nets, including 2Da U-Net, 2Dc U-Net, 2Ds U-Net, 2.5Da U-Net, 3D U-Net, were trained to segment the teeth. Four additional U-Nets, including 2.5Dv U-Net, 3.5Dv5 U-Net, 3.5Dv4 U-Net, and 3.5Dv3 U-Net, were obtained using majority voting. Mathematical morphology operations including erosion and dilation (E&D) were applied to remove diminutive noise speckles. Segmentation performance was evaluated by fourfold cross validation using Dice similarity coefficient (DSC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV). Kruskal-Wallis test with post hoc analysis using Bonferroni correction was used for group comparison. P < 0.05 was considered statistically significant. Performance of U-Nets significantly varies among different training strategies for teeth segmentation on CBCT (P < 0.05). The 3.5Dv5 U-Net and 2.5Dv U-Net showed DSC and PPV significantly higher than any of five originally trained U-Nets (all P < 0.05). E&D significantly improved the DSC, accuracy, specificity, and PPV (all P < 0.005). The 3.5Dv5 U-Net achieved highest DSC and accuracy among all U-Nets. The segmentation performance of the U-Net can be improved by majority voting and E&D. Overall speaking, the 3.5Dv5 U-Net achieved the best segmentation performance among all U-Nets.

Thermal Transport through Polymer-Linked Gold Nanoparticles.

Polymer-nanoparticle networks have potential applications in molecular electronics and nanophononics. In this work, we use all-atom molecular dynamics to reveal the fundamental mechanisms of thermal transport in polymer-linked gold nanoparticle (AuNP) dimers at the molecular level. Attachment of the polymers to AuNPs of varying sizes allows the determination of effects from the flexibility of the chains when their ends are not held fixed. We report heat conductance (G) values for six polymers-viz. polyethylene, poly(p-phenylene), polyacene, polyacetylene, polythiophene, and poly(3,4-ethylenedioxythiophene)-that represent a broad range of stiffness. We address the multimode effects of polymer type, AuNP size, polymer chain length, polymer conformation, system temperature, and number of linking polymers on G. The combination of the mechanisms for phonon boundary scattering and intrinsic phonon scattering has a strong effect on G. We find that the values of G are larger for conjugated polymers because of the stiffness in their backbones. They are also larger in the low-temperature region for all polymers owing to the quenching of segmental rotations at low temperature. Our simulations also suggest that the total G is additive as the number of linking polymers in the AuNP dimer increases from 1 to 2 to 3.

Bovine lactoferricin on non-specific immunity of giant freshwater prawns, Macrobrachium rosenbergii.

This study aimed to investigate the effects of dietary Bovine lactoferricin (LFcinB) on the growth performance and non-specific immunity in Macrobrachium rosenbergii. Five experimental diets were 1.0‰ Bovine lactoferricin (LCB1); 1.5‰ Bovine lactoferricin (LCB1.5); 2.0‰ Bovine lactoferricin (LCB2); 2.5‰ Bovine lactoferricin (LCB2.5); the control group, basal diet without Bovine lactoferricin. A total of 600 prawns were randomly assigned to 5 groups in triplicate in 15 tanks for an 8-week feeding trial. The results showed the final weight, weight gain rate, specific growth rate and survival rate of prawns in the treatment groups were significantly improved versus the control (P < 0.05). The feed conversion ratio was reduced significantly in treatment groups compared to the control (P < 0.05). Compared with the control, alkaline phosphatase (AKP), acid phosphatase (ACP), lysozyme (LZM), catalase (CAT), superoxide dismutase (SOD) activities in the hepatopancreas of the treatment groups were significantly enhanced, and malondialdehyde (MDA) content was reduced significantly (P < 0.05). Compared with the control, the relative expression levels of AKP, ACP, LZM, CAT, SOD, Hsp70, peroxiredoxin-5, Toll, dorsal and relish genes were significantly higher among treatment groups, except for the AKP gene in the LCB1 group and the Hsp70 gene in the LCB1.5 group (P < 0.05). Compared with the control, the relative expression levels of TOR, 4E-BP, eIF4E1α and eIF4E2 genes were significantly enhanced in the LCB1.5 group (P < 0.05). When resistance against Vibrio parahaemolyticus in prawn is considered, higher doses of Bovine lactoferricin show better antibacterial ability. The present study indicated that dietary Bovine lactoferricin could significantly improve the growth performance and improve the antioxidative status of M. rosenbergii. The suitable addition level is 1.5 g/kg. LFcinB has great potential as a new feed additive without the threat of drug resistance.