Efficacy and Safety of a Home-Use Light-Emitting Diode Neck Device for Improvement in Neck Wrinkles: A Multicenter, Randomized, Double-Blind, Sham Device, Superiority Verification, Confirmatory Clinical Trial.

BACKGROUND: Light-emitting diode (LED) light sources have become an increasingly popular choice for the treatment and rejuvenation of various dermatological conditions. AIMS: This study aimed to evaluate the effects of neck rejuvenation, patient satisfaction, and the safety of LED application to the neck in an Asian population. METHODS: This was a multicenter, randomized, double-blind, sham device study. Seventy participants were enrolled in the study. The participants wore the home-use LED neck device for 9 min a day, 5 times a week, for a total of 60 sessions. The Lemperle Wrinkle Scale (LWS) and Global Aesthetic Improvement Scale (GAIS) were used to evaluate the results of both investigators and participants. The thyroid gland was examined using ultrasonography to evaluate the safety of the investigational device. RESULTS: The percentage of participants with improved LWS at Week 12 was significantly higher in the study group. Additionally, the percentage of participants with improved LWS was significantly higher in the study group at Weeks 8, 12, and 16. The LWS at Week 12 corrected with baseline values was found to be significantly different between the two groups. GAIS showed significant differences at 8, 12, and 16 weeks in the investigators' evaluation but not in the participants' evaluation. Repeated-measures analysis of variance at Weeks 4, 8, 12, and 16 also confirmed a significant difference between the two groups only in investigator assessment. No significant thyroid-related complications were observed. CONCLUSION: LED application to the neck may be considered a satisfactory and safe procedure for neck rejuvenation.

Unsupervised speckle noise reduction technique for clinical ultrasound imaging.

PURPOSE: Deep learning-based image enhancement has significant potential in the field of ultrasound image processing, as it can accurately model complicated nonlinear artifacts and noise, such as ultrasonic speckle patterns. However, training deep learning networks to acquire reference images that are clean and free of noise presents significant challenges. This study introduces an unsupervised deep learning framework, termed speckle-to-speckle (S2S), designed for speckle and noise suppression. This framework can complete its training without the need for clean (speckle-free) reference images. METHODS: The proposed network leverages statistical reasoning for the mutual training of two in vivo images, each with distinct speckle patterns and noise. It then infers speckle- and noise-free images without needing clean reference images. This approach significantly reduces the time, cost, and effort experts need to invest in annotating reference images manually. RESULTS: The experimental results demonstrated that the proposed approach outperformed existing techniques in terms of the signal-to-noise ratio, contrast-to-noise ratio, structural similarity index, edge preservation index, and processing time (up to 86 times faster). It also performed excellently on images obtained from ultrasound scanners other than the ones used in this work. CONCLUSION: S2S demonstrates the potential of employing an unsupervised learning-based technique in medical imaging applications, where acquiring a ground truth reference is challenging.

Interactive regulation of immune-related resistance genes with salicylic acid and jasmonic acid signaling in systemic acquired resistance in the Xanthomonas-Brassica pathosystem.

Pathogen-responsive immune-related genes (resistance genes [R-genes]) and hormones are crucial mediators of systemic acquired resistance (SAR). However, their integrated functions in regulating SAR signaling components in local and distal leaves remain largely unknown. To characterize SAR in the Xanthomonas campestris pv. campestris (Xcc)-Brassica napus pathosystem, the responses of R-genes, (leaf and phloem) hormone levels, H2O2 levels, and Ca2+ signaling-related genes were assessed in local and distal leaves of plants exposed to four Xcc-treatments: Non-inoculation (control), only secondary Xcc-inoculation in distal leaves (C-Xcc), only primary Xcc-inoculation in local leaves (Xcc), and both primary and secondary Xcc-inoculation (X-Xcc). The primary Xcc-inoculation provoked disease symptoms as evidenced by enlarged destructive necrosis in the local leaves of Xcc and X-Xcc plants 7 days post-inoculation. Comparing visual symptoms in distal leaves 5 days post-secondary inoculation, yellowish necrotic lesions were clearly observed in non Xcc-primed plants (C-Xcc), whereas no visual symptom was developed in Xcc-primed plants (X-Xcc), demonstrating SAR. Pathogen resistance in X-Xcc plants was characterized by distinct upregulations in expression of the PAMP-triggered immunity (PTI)-related kinase-encoding gene, BIK1, the (CC-NB-LRR-type) R-gene, ZAR1, and its signaling-related gene, NDR1, with a concurrent enhancement of the kinase-encoding gene, MAPK6, and a depression of the (TIR-NB-LRR-type) R-gene, TAO1, and its signaling-related gene, SGT1, in distal leaves. Further, in X-Xcc plants, higher salicylic acid (SA) and jasmonic acid (JA) levels, both in phloem and distal leaves, were accompanied by enhanced expressions of the SA-signaling gene, NPR3, the JA-signaling genes, LOX2 and PDF1.2, and the Ca2+-signaling genes, CAS and CBP60g. However, in distal leaves of C-Xcc plants, an increase in SA level resulted in an antagonistic depression of JA, which enhanced only SA-dependent signaling, EDS1 and NPR1. These results demonstrate that primary Xcc-inoculation in local leaves induces resistance to subsequent pathogen attack by upregulating BIK1-ZAR1-mediated synergistic interactions with SA and JA signaling as a crucial component of SAR.

Topographic analysis of retinal and choroidal vascular displacements after macular hole surgery.

It has been reported that the retinal vessel and macular region of the retina are displaced after macular hole (MH) surgery. However, there is no detailed information for correlations between retinal and choroidal displacements. We obtained optical coherence tomography angiography (OCTA) and en-face optical coherence tomography (OCT) images from 24 eyes to measure the retinal and choroidal vascular displacement before and after surgery. These images were merged into infrared images using blood vessel patterns. The same vascular bifurcation points were automatically selected for each follow-up image, and the displacements of the bifurcation points were analyzed as a vector unit for prespecified grid regions in a semi-automated fashion. The results showed displacements of the choroidal intermediate vessels and retinal vessels following MH surgery (p = 0.002, p < 0.001). The topographic changes showed inferior, nasal, and centripetal displacement of the retina and inferiorly displaced choroid. The ILM peeling size and basal MH size were significantly associated with the retinal displacement (p < 0.001 and p = 0.010). Additionally, changes in the amount of the choroidal displacement were significantly correlated with that of the retinal displacements (p = 0.002). Clinicians should keep in mind that there might be topographic discrepancies of the displacement between retina and choroid when analyzing them following surgery.

FR-MIL: Distribution Re-calibration based Multiple Instance Learning with Transformer for Whole Slide Image Classification.

In digital pathology, whole slide images (WSI) are crucial for cancer prognostication and treatment planning. WSI classification is generally addressed using multiple instance learning (MIL), alleviating the challenge of processing billions of pixels and curating rich annotations. Though recent MIL approaches leverage variants of the attention mechanism to learn better representations, they scarcely study the properties of the data distribution itself i.e., different staining and acquisition protocols resulting in intra-patch and inter-slide variations. In this work, we first introduce a distribution re-calibration strategy to shift the feature distribution of a WSI bag (instances) using the statistics of the max-instance (critical) feature. Second, we enforce class (bag) separation via a metric loss assuming that positive bags exhibit larger magnitudes than negatives. We also introduce a generative process leveraging Vector Quantization (VQ) for improved instance discrimination i.e., VQ helps model bag latent factors for improved classification. To model spatial and context information, a position encoding module (PEM) is employed with transformer-based pooling by multi-head self-attention (PMSA). Evaluation of popular WSI benchmark datasets reveals our approach improves over state-of-the-art MIL methods. Further, we validate the general applicability of our method on classic MIL benchmark tasks and for point cloud classification with limited points https://github.com/PhilipChicco/FRMIL.

Video domain adaptation for semantic segmentation using perceptual consistency matching.

Unsupervised domain adaptation (UDA) aims to transfer knowledge in previous and related labeled datasets (sources) to a new unlabeled dataset (target). Despite the impressive performance, existing approaches have largely focused on image-based UDA only, and video-based UDA has been relatively understudied and received less attention due to the difficulty of adapting diverse modal video features and modeling temporal associations efficiently. To address this, existing studies use optical flow to capture motion cues between in-domain consecutive frames, but is limited by heavy compute requirements and modeling flow patterns across diverse domains is equally challenging. In this work, we propose an adversarial domain adaptation approach for video semantic segmentation that aims to align temporally associated pixels in successive source and target domain frames without relying on optical flow. Specifically, we introduce a Perceptual Consistency Matching (PCM) strategy that leverages perceptual similarity to identify pixels with high correlation across consecutive frames, and infer that such pixels should correspond to the same class. Therefore, we can enhance prediction accuracy for video-UDA by enforcing consistency not only between in-domain frames, but across domains using PCM objectives during model training. Extensive experiments on public datasets show the benefit of our approach over existing state-of-the-art UDA methods. Our approach not only addresses a crucial task in video domain adaptation but also offers notable improvements in performance with faster inference times.

Spatio-Temporal Influence on the Distribution of Forensically Relevant Blowflies (Diptera: Calliphoridae) in Gyeongsangnam-do, South Korea.

The study of blowfly (Diptera: Calliphoridae) biodiversity and distribution is crucial for forensic investigations. Abiotic and biotic factors, such as season and habitat type, have a significant impact on blowfly populations. However, only a few forensic entomology studies have been conducted in South Korea, particularly in the Gyeongsangnam-do region. To address this, an extensive year-long survey was conducted to analyze the compositions, habitat preferences, distribution, and seasonal abundance of forensically relevant blowflies in urban and forested habitats of Gyeongsangnam-do, with sampling conducted twice a month using mouse carcass-baited traps set for 48 h each time. A total of 3470 adult blowflies were recorded, encompassing five genera and 13 species, with a noted absence of specimens during the winter months. The predominant species was Lucilia porphyrina, accounting for 37.2% of the total sample, followed by Chrysomya pinguis (27.6%), Lucilia sericata (7.6%), and Lucilia illustris (7.1%). The species composition was consistent across all surveyed regions; however, seasonal variation in species diversity was evident, with a peak in spring and a decline in summer. Notably, certain species exhibited clear preferences for either urban (Calliphora calliphoroides and L. sericata) or forested habitats (L. porphyrina and Ch. pinguis). This pioneering study elucidates the diverse blowfly communities in Gyeongsangnam-do, highlighting significant seasonal and habitat-dependent variations. These findings enrich our understanding of blowfly ecology in this region, offering valuable insights for forensic applications and underscoring the necessity for ongoing entomological surveillance and research.

Machine learning-based prediction of cerebral oxygen saturation based on multi-modal cerebral oximetry data.

This study develops machine learning-based algorithms that facilitate accurate prediction of cerebral oxygen saturation using waveform data in the near-infrared range from a multi-modal oxygen saturation sensor. Data were obtained from 150,000 observations of a popular cerebral oximeter, Masimo O3™ regional oximetry (Co., United States) and a multi-modal cerebral oximeter, Votem (Inc., Korea). Among these observations, 112,500 (75%) and 37,500 (25%) were used for training and test sets, respectively. The dependent variable was the cerebral oxygen saturation value from the Masimo O3™ (0-100%). The independent variables were the time of measurement (0-300,000 ms) and the 16-bit decimal amplitudes values (infrared and red) from Votem (0-65,535). For the right part of the forehead, the root mean square error of the random forest (0.06) was much smaller than those of linear regression (1.22) and the artificial neural network with one, two or three hidden layers (2.58). The result was similar for the left part of forehead, that is, random forest (0.05) vs logistic regression (1.22) and the artificial neural network with one, two or three hidden layers (2.97). Machine learning aids in accurately predicting of cerebral oxygen saturation, employing the data from a multi-modal cerebral oximeter.

Synthesis, Invitro Cytotoxic Activity and Optical Analysis of Substituted Schiff Base Derivatives.

Fluorescent cytotoxic compounds with readout delivery are crucial in chemotherapy. The growing demands of these treatment strategies require the novel heterocyclic molecules with better selectivity alongside fluorescence marker potential. In this context, a series of nine isatin Schiff base derivatives 4a-i were synthesized, characterized and evaluated for UV-visible, fluorescence, thermal and bioanalysis in order to explore the effect of structure on their bioprofiles. The analogue 4d exhibited maximum cytotoxic activity on Hella cells with percentage inhibition of 83% at 50 µM and 100% at 150 µM concentrations while 4c showed minimum cytotoxic activity with the value of 19% at 50 µM and 22% at 150 µM concentrations. Meanwhile, 4g was found to exhibit maximum inhibition potential towards Vero Cells with the percentage inhibition values of 83 at 50 µM concentration. The overall SAR study showed that the para-fluoro-substituted isatin moieties exhibited the appreciable percentage inhibition while the least activity was delivered by the isatin derivatives with para-bromo substitution.

Social context modulates multibrain broadband dynamics and functional brain-to-brain coupling in the group of mice.

Although mice are social, multiple animals' neural activities are rarely explored. To characterise the neural activities during multi-brain interaction, we simultaneously recorded local field potentials (LFP) in the prefrontal cortex of four mice. The social context and locomotive states predominately modulated the entire LFP structure. The power of lower frequency bands-delta to alpha-were correlated with each other and anti-correlated with gamma power. The high-to-low-power ratio (HLR) provided a useful measure to understand LFP changes along the change of behavioural and locomotive states. The HLR during huddled conditions was lower than that during non-huddled conditions, dividing the social context into two. Multi-brain analyses of HLR indicated that the mice in the group displayed high cross-correlation. The mice in the group often showed unilateral precedence of HLR by Granger causality analysis, possibly comprising a hierarchical social structure. Overall, this study shows the importance of the social environment in brain dynamics and emphasises the simultaneous multi-brain recordings in social neuroscience.

Synthesis of carboxymethyl chitosan-guar gum-poly(vinylpyrrolidone) ternary blended hydrogels with antibacterial/anticancer efficacy and drug delivery applications.

Biopolymers have the utmost significance in biomedical applications and blending synthetic polymers has shown favorable characteristics versus individual counterparts. The utilization of the blends can be restricted through the use of toxic chemical agents such as initiators or crosslinkers. In this regard, a chemical agent-free ionizing irradiation is a beneficial alternative for preparing the hydrogels for biomedical applications. In this study, carboxymethyl chitosan (CM-CS), guar gum (GG), and poly(vinylpyrrolidone) (PVP) based ternary blends (TB) were crosslinked using various doses of ionizing irradiation to fabricate hydrogels. The prepared hydrogels were characterized for physicochemical properties, swelling analysis, biological assays, and drug delivery applications. Swelling analysis in distilled water revealed that the hydrogels exhibit excellent swelling characteristics. An in vitro cytocompatibility assay showed that the hydrogels have greater than 90% cell viability for the human epithelial cell line and a decreasing cell viability trend for the human alveolar adenocarcinoma cell line. In addition, the prepared hydrogels possessed excellent antibacterial characteristics against gram-positive Staphylococcus aureus (S. aureus) and gram-negative Escherichia coli (E. coli). Finally, the release studies of anti-inflammatory Quercus acutissima (QA) loaded hydrogels exhibited more than 80% release in phosphate-buffered saline (pH = 7.4). These findings suggest that TB hydrogels can be used as suitable carrier media for different release systems and biomedical applications.

Evaluation of Swine Protection with Three Commercial Foot-and-Mouth Disease Vaccines against Heterologous Challenge with Type A ASIA/G-VII Lineage Viruses.

Outbreaks caused by foot-and-mouth disease (FMD) A/ASIA/G-VII lineage viruses have often occurred in Middle Eastern and Southeast Asian countries since 2015. Because A/ASIA/G-VII lineage viruses are reported to have distinct antigenic relatedness with available commercial FMD vaccine strains, it is necessary to investigate whether inoculation with vaccines used in Korea could confer cross-protection against A/ASIA/G-VII lineage viruses. In the present study, we conducted two vaccination challenge trials to evaluate the efficacy of three commercial FMD vaccines (O/Manisa + O/3039 + A/Iraq, O/Campos + A/Cruzeiro + A/2001, and O/Primorsky + A/Zabaikalsky) against heterologous challenge with ASIA/G-VII lineage viruses (A/TUR/13/2017 or A/BHU/3/2017 strains) in pigs. In each trial, clinical signs, viremia, and salivary shedding of virus were measured for 7 days after challenge. In summary, the O/Campos + A/Cruzeiro + A/2001 vaccine provided full protection against two A/ASIA/G-VII lineage viruses in vaccinated pigs, where significant protection was observed. Although unprotected animals were observed in groups vaccinated with O/Manisa + O/3039 + A/Iraq or O/Primorsky + A/Zabaikalsky vaccines, the clinical scores and viral RNA levels in the sera and oral swabs of vaccinated animals were significantly lower than those of unvaccinated controls.

In vivo effects of cell seeding technique in an ex vivo regional gene therapy model for bone regeneration.

When delivering cells on a scaffold to treat a bone defect, the cell seeding technique determines the number and distribution of cells within a scaffold, however the optimal technique has not been established. This study investigated if human adipose-derived stem cells (ASCs) transduced with a lentiviral vector to overexpress bone morphogenetic protein 2 (BMP-2) and loaded on a scaffold using dynamic orbital shaker could reduce the total cell dose required to heal a critical sized bone defect when compared with static seeding. Human ASCs were loaded onto a collagen/biphasic ceramic scaffold using static loading and dynamic orbital shaker techniques, compared with our labs standard loading technique, and implanted into femoral defects of nude rats. Both a low dose and standard dose of transduced cells were evaluated. Outcomes investigated included BMP-2 production, radiographic healing, micro-computerized tomography, histologic assessment, and biomechanical torsional testing. BMP-2 production was higher in the orbital shaker cohort compared with the static seeding cohort. No statistically significant differences were noted in radiographic, histomorphometric, and biomechanical outcomes between the low-dose static and dynamic seeding groups, however the standard-dose static seeding cohort had superior biomechanical properties. The standard-dose 5 million cell dose standard loading cohort had superior maximum torque and torsional stiffness on biomechanical testing. The use of orbital shaker technique was labor intensive and did not provide equivalent biomechanical results with the use of fewer cells.

Generation of synthetic PET/MR fusion images from MR images using a combination of generative adversarial networks and conditional denoising diffusion probabilistic models based on simultaneous 18F-FDG PET/MR image data of pyogenic spondylodiscitis.

BACKGROUND CONTEXT: Cross-modality image generation from magnetic resonance (MR) to positron emission tomography (PET) using the generative model can be expected to have complementary effects by addressing the limitations and maximizing the advantages inherent in each modality. PURPOSE: This study aims to generate synthetic PET/MR fusion images from MR images using a combination of generative adversarial networks (GANs) and conditional denoising diffusion probabilistic models (cDDPMs) based on simultaneous 18F-fluorodeoxyglucose (18F-FDG) PET/MR image data. STUDY DESIGN: Retrospective study with prospectively collected clinical and radiological data. PATIENT SAMPLE: This study included 94 patients (60 men and 34 women) with thoraco-lumbar pyogenic spondylodiscitis (PSD) from February 2017 to January 2020 in a single tertiary institution. OUTCOME MEASURES: Quantitative and qualitative image similarity were analyzed between the real and synthetic PET/ T2-weighted fat saturation MR (T2FS) fusion images on the test data set. METHODS: We used paired spinal sagittal T2FS and PET/T2FS fusion images of simultaneous 18F-FDG PET/MR imaging examination in patients with PSD, which were employed to generate synthetic PET/T2FS fusion images from T2FS images using a combination of Pix2Pix (U-Net generator + Least Squares GANs discriminator) and cDDPMs algorithms. In the analyses of image similarity between the real and synthetic PET/T2FS fusion images, we adopted the values of mean peak signal to noise ratio (PSNR), mean structural similarity measurement (SSIM), mean absolute error (MAE), and mean squared error (MSE) for quantitative analysis, while the discrimination accuracy by three spine surgeons was applied for qualitative analysis. RESULTS: Total of 2,082 pairs of T2FS and PET/T2FS fusion images were obtained from 172 examinations on 94 patients, which were randomly assigned to training, validation, and test data sets in 8:1:1 ratio (1664, 209, and 209 pairs). The quantitative analysis revealed PSNR of 30.634 ± 3.437, SSIM of 0.910 ± 0.067, MAE of 0.017 ± 0.008, and MSE of 0.001 ± 0.001, respectively. The values of PSNR, MAE, and MSE significantly decreased as FDG uptake increased in real PET/T2FS fusion image, with no significant correlation on SSIM. In the qualitative analysis, the overall discrimination accuracy between real and synthetic PET/T2FS fusion images was 47.4%. CONCLUSIONS: The combination of Pix2Pix and cDDPMs demonstrated the potential for cross-modal image generation from MR to PET images, with reliable quantitative and qualitative image similarities.

Association between migraine and the risk of vascular dementia: A nationwide longitudinal study in South Korea.

OBJECTIVE: We aimed to examine the potential association between migraine and vascular dementia (VaD) using a nationwide population database. BACKGROUND: Migraine and VaD showed similar structural and functional changes in pathophysiology process and shared common risk factors, However, whether migraine prevalence increases VaD incidence remains controversial. METHODS: This retrospective population-based cohort study used the medical records from the Korean National Health Insurance System database. Migraine (G43) was defined by using the Tenth Revision of the International Classification of Diseases code. More than two migraine diagnoses at least 3 months apart were defined as "chronic migraine". Cox proportional hazards model estimated hazard ratios (HRs) of VaD for group comparisons. RESULTS: We included 212,836 patients with migraine and 5,863,348 individuals without migraine. During 10 years of follow-up, 3,914 (1.8%) and 60,258 (1.0%) patients with and without migraine, respectively, were newly diagnosed with VaD. After adjustment, patients with migraine showed a 1.21-fold higher risk of VaD than those without migraine (HR = 1.21; 95% confidence interval (CI): 1.17-1.25). Patients with chronic migraine showed a higher cumulative incidence of VaD than those with episodic migraine. The adjusted HR for the VaD incidence with migraine was higher in: (1) patients aged <65 years; (2) women; (3) patients without hypertension, diabetes, or atrial fibrillation; and (4) non-smokers. CONCLUSION: Migraine is associated with an increased risk of VaD, particularly in chronic migraine patients. Incidence of VaD in the setting of migraine may have distinct pathophysiology from that of VaD with traditional cardiovascular risks.

Federated learning with knowledge distillation for multi-organ segmentation with partially labeled datasets.

The state-of-the-art multi-organ CT segmentation relies on deep learning models, which only generalize when trained on large samples of carefully curated data. However, it is challenging to train a single model that can segment all organs and types of tumors since most large datasets are partially labeled or are acquired across multiple institutes that may differ in their acquisitions. A possible solution is Federated learning, which is often used to train models on multi-institutional datasets where the data is not shared across sites. However, predictions of federated learning can be unreliable after the model is locally updated at sites due to 'catastrophic forgetting'. Here, we address this issue by using knowledge distillation (KD) so that the local training is regularized with the knowledge of a global model and pre-trained organ-specific segmentation models. We implement the models in a multi-head U-Net architecture that learns a shared embedding space for different organ segmentation, thereby obtaining multi-organ predictions without repeated processes. We evaluate the proposed method using 8 publicly available abdominal CT datasets of 7 different organs. Of those datasets, 889 CTs were used for training, 233 for internal testing, and 30 volumes for external testing. Experimental results verified that our proposed method substantially outperforms other state-of-the-art methods in terms of accuracy, inference time, and the number of parameters.

Symmetrical Ligand's Fabricated Porous Silicon Surface Based Photoluminescence Sensor for Metal Detection and Entrapment.

This study was based on the development of surface-based photoluminescence sensor for metal detection, quantification, and sample purification employing the solid sensory chip having the capability of metal entrapment. The Co(II), Cu(II) and Hg(II) sensitive fluorescence sensor (TP) was first synthesized and characterized its sensing abilities towards tested metal ions by using fluorescence spectral investigation while the synthesis and complexation of the receptor was confirmed by the chromogenic, optical, spectroscopic and spectrometric analysis. Under optical investigation, the ligand solution exhibited substantial chromogenic changes as well as spectral variations upon reacting with copper, cobalt, and mercuric ions, while these behaviors were not seen for the rest of tested metallic ions i.e., Na+, Ag+, Ni2+, Mn2+, Pd2+, Pb2+, Cd2+, Zn2+, Sn2+, Fe2+, Fe3+, Cr3+, and Al3+. These colorimetric alterations and spectral shifting could potentially be employed to detect and quantify these specific metal ions. After the establishment of the ligand's selective complexation ability towards selected metals, it was fabricated over the substituted porous silicon surface (FPS) keeping in view of the development of surface-based photoluminescence sensor (TP-FPS) for the selected metal sensation and entrapment to purify the sample just be putting off the metal entrapped sensory solid chip. Surface characterization and ligand fabrication was inspected by plan and cross sectional electron microscopic investigations, vibrational and electronic spectral analysis. The sensitivity of the ligand (TP) in the solution phase metal discrimination was determined by employing the fluorescence titration analysis of the ligand solution after progressive induction of Co2+, Cu2+, and Hg2+, which afford the detection limit values of 2.14 × 10- 8, 3.47 × 10- 8 and 3.13 × 10- 3, respectively. Concurrently, photoluminescence titration of the surface fabricated sensor (TP-FPS) revealed detection limit values of 3.14 × 10- 9, 7.43 × 10- 9, and 8.21 × 10- 4, respectively, for the selected metal ions.

Zeolite application mitigates NH3 and N2O emissions from pig slurry-applied field and improves nitrogen use efficiency in Italian ryegrass-maize crop rotation system for forage production.

The present study aimed to assess the efficiency of zeolite in mitigating the nitrogen (N) losses through ammonia (NH3) and nitrous oxide (N2O) emissions from pig slurry (PS) applied to Italian ryegrass (IRG)-maize fields under a crop rotation system and the consequent effect on nitrogen use efficiency (NUE) for forage production. PS was applied at rates of 150 and 200 kg N ha-1 for the IRG and maize growing seasons, respectively, with or without zeolite. Soil mineral N content and NH3 and N2O emissions were measured periodically throughout the year-round cultivation of IRG and maize. Forage yield and nutritional composition were also analyzed at the harvest time of each crop. The PS with/without zeolite application effects were interpreted by comparison with those obtained for the negative control (no-N fertilization). Soil ammonium (NH4+) content in the PS-applied plots sharply increased within the first week, then progressively decreased in both the IRG and maize growing seasons. Soil NH4+ contents in the zeolite-amended plots were higher compared to the treatment without zeolite except for the first 1 or 2 weeks after PS application when soil nitrate (NO3-) contents significantly decreased. The increase in soil NH4+ content as affected by zeolite application was more distinct in the maize growing season than in the IRG growing season. NH3 emission was predominant at the early 2 weeks after PS application. Zeolite application reduced the cumulative emission of NH3 from PS by 16.7% and 24.4% and that of N2O by 15.6% and 31.5% in the IRG growing and maize growing seasons, respectively. NUE for dry matter (DM) and total digestible nutrients (TDN) production significantly improved in annual yield basis of the IRG-maize cropping. Zeolite application in PS-applied field may represent effective management in mitigating N losses through odorous NH3 and greenhouse gas (N2O) emissions, thereby improving NUE forage production.