FORMULATION DEVELOPMENT AND CHARACTERIZATION OF TEA TREE OIL LOADED ETHOSOMES

To prepare ethosomes containing tea tree oil by hot homogenization method and to evaluate its physical characters and in-vitro release pattern.  the preformulation studies were carried out by standard procedure. The morphology of globule was studied by optical microscopy. The globule size and zeta potential was determined by Zetasizer, respectively and in-vitro study was done by diffusion method and the drug content was analyzed by HPTLC method. The release kinetics was also studied by fitting into few mathematical models.  All the formulations were showed spherical and unilamellar shape with globule size of 931 to 975 nm, the zeta potential in the range of – 40 to -52 mV and entrapment efficiency was 57 to 65 %. Finally the invitro release studies showed the drug release from the ethosomal vesicles was burst release at initial time followed by sustained release over throughout the study. From the above consideration of evaluation studies, the tea tree oil loaded ethosomal formulation F5 shows best globule size, zeta potential and entrapment efficiency. The sustained action was confirmed by invitro release studies. All the formulations are followed zero order drug release and diffusion type of mechanism of drug releases with Fickian model. Ethosome loaded tea tree oil could be the best choice for topical application

Deep Group Interest Modeling of Full Lifelong User Behaviors for CTR Prediction

Extracting users' interests from their lifelong behavior sequence is crucial for predicting Click-Through Rate (CTR). Most current methods employ a two-stage process for efficiency: they first select historical behaviors related to the candidate item and then deduce the user's interest from this narrowed-down behavior sub-sequence. This two-stage paradigm, though effective, leads to information loss. Solely using users' lifelong click behaviors doesn't provide a complete picture of their interests, leading to suboptimal performance. In our research, we introduce the Deep Group Interest Network (DGIN), an end-to-end method to model the user's entire behavior history. This includes all post-registration actions, such as clicks, cart additions, purchases, and more, providing a nuanced user understanding. We start by grouping the full range of behaviors using a relevant key (like item_id) to enhance efficiency. This process reduces the behavior length significantly, from O(10^4) to O(10^2). To mitigate the potential loss of information due to grouping, we incorporate two categories of group attributes. Within each group, we calculate statistical information on various heterogeneous behaviors (like behavior counts) and employ self-attention mechanisms to highlight unique behavior characteristics (like behavior type). Based on this reorganized behavior data, the user's interests are derived using the Transformer technique. Additionally, we identify a subset of behaviors that share the same item_id with the candidate item from the lifelong behavior sequence. The insights from this subset reveal the user's decision-making process related to the candidate item, improving prediction accuracy. Our comprehensive evaluation, both on industrial and public datasets, validates DGIN's efficacy and efficiency

Robust Adaptive Beamforming Using k-means Clustering: A Solution to High Complexity of the Reconstruction-Based Algorithm

Recently, a new robust adaptive beamforming (RAB) algorithm has been proposed to reconstruct the interference-plus-noise covariance matrix (IPNCM) based on narrowing the interference angular domain and using an annular uncertainty set (NIAD-AUS). The method is robust against unknown arbitrary-type mismatches. However, its computational complexity will increase exponentially with the number of array sensors. In this paper, a novel method is proposed to solve this problem. First, k-means clustering (KMC) algorithm is utilized to estimate the annulus uncertainty set with fewer clustering weight points rather than whole sampling. Second, the KMC Capon spectrum is used to reconstruct the IPNCM. Compared with the previous reconstruction-based algorithms, the proposed approach can retain the high performance of the state-of-the-art NIAD-AUS algorithm. More importantly, it can also obtain the IPNCM more quickly. Lastly, simulation results demonstrate the effectiveness and robustness of the proposed algorithm

Bacterial Community Structure of Pinus Thunbergii Naturally Infected by the Nematode Bursaphelenchus Xylophilus

Pine wilt disease (PWD) caused by the nematode Bursaphelenchus xylophilus is a devastating disease in conifer forests in Eurasia. However, information on the effect of PWD on the host microbial community is limited. In this study, the bacterial community structure and potential function in the needles, roots, and soil of diseased pine were studied under field conditions using Illumina MiSeq coupled with Phylogenetic Investigation of Communities by Reconstruction of Unobserved states (PICRUSt) software. The results showed that the community and functional structure of healthy and diseased trees differed only in the roots and needles, respectively (p < 0.05). The needles, roots, and soil formed unique bacterial community and functional structures. The abundant phyla across all samples were Proteobacteria (41.9% of total sequence), Actinobacteria (29.0%), Acidobacteria (12.2%), Bacteroidetes (4.8%), and Planctomycetes (2.1%). The bacterial community in the healthy roots was dominated by Acidobacteria, Planctomycetes, and Rhizobiales, whereas in the diseased roots, Proteobacteria, Firmicutes, and Burkholderiales were dominant. Functionally, groups involved in the cell process and genetic information processing had a higher abundance in the diseased needles, which contributed to the difference in functional structure. The results indicate that PWD can only affect the host bacteria community structure and function in certain anatomical regions of the host tree

Bacterial Community Structure of Pinus Thunbergii Naturally Infected by the Nematode Bursaphelenchus Xylophilus

Pine wilt disease (PWD) caused by the nematode Bursaphelenchus xylophilus is a devastating disease in conifer forests in Eurasia. However, information on the effect of PWD on the host microbial community is limited. In this study, the bacterial community structure and potential function in the needles, roots, and soil of diseased pine were studied under field conditions using Illumina MiSeq coupled with Phylogenetic Investigation of Communities by Reconstruction of Unobserved states (PICRUSt) software. The results showed that the community and functional structure of healthy and diseased trees differed only in the roots and needles, respectively (p <0.05). The needles, roots, and soil formed unique bacterial community and functional structures. The abundant phyla across all samples were Proteobacteria (41.9% of total sequence), Actinobacteria (29.0%), Acidobacteria (12.2%), Bacteroidetes (4.8%), and Planctomycetes (2.1%). The bacterial community in the healthy roots was dominated by Acidobacteria, Planctomycetes, and Rhizobiales, whereas in the diseased roots, Proteobacteria, Firmicutes, and Burkholderiales were dominant. Functionally, groups involved in the cell process and genetic information processing had a higher abundance in the diseased needles, which contributed to the difference in functional structure. The results indicate that PWD can only affect the host bacteria community structure and function in certain anatomical regions of the host tree.Peer reviewe

Bacterial Community Structure of Pinus Thunbergii Naturally Infected by the Nematode Bursaphelenchus Xylophilus

Pine wilt disease (PWD) caused by the nematode Bursaphelenchus xylophilus is a devastating disease in conifer forests in Eurasia. However, information on the effect of PWD on the host microbial community is limited. In this study, the bacterial community structure and potential function in the needles, roots, and soil of diseased pine were studied under field conditions using Illumina MiSeq coupled with Phylogenetic Investigation of Communities by Reconstruction of Unobserved states (PICRUSt) software. The results showed that the community and functional structure of healthy and diseased trees differed only in the roots and needles, respectively (p < 0.05). The needles, roots, and soil formed unique bacterial community and functional structures. The abundant phyla across all samples were Proteobacteria (41.9% of total sequence), Actinobacteria (29.0%), Acidobacteria (12.2%), Bacteroidetes (4.8%), and Planctomycetes (2.1%). The bacterial community in the healthy roots was dominated by Acidobacteria, Planctomycetes, and Rhizobiales, whereas in the diseased roots, Proteobacteria, Firmicutes, and Burkholderiales were dominant. Functionally, groups involved in the cell process and genetic information processing had a higher abundance in the diseased needles, which contributed to the difference in functional structure. The results indicate that PWD can only affect the host bacteria community structure and function in certain anatomical regions of the host tree

Experimental generation of genuine four-partite entangled states with total three-party correlation for continuous variables

We experimentally prepare a new type of continuous variable genuine four-partite entangled states, the quantum correlation property of which is different from that of the four-mode GHZ and cluster states, and which has not any qubit counterpart to be proposed at present. In the criterion inequalities for the full inseparability of the genuine four-partite entangled states, the amplitude and phase quadrature correlation variances totally consisting of three-party combination from the four entangled modes are involved. The measured correlation variances among the quadratures of the prepared entangled states satisfy the sufficient requirements for the full inseparability. The type of entangled states has especially potential application in quantum information with continuous quantum variables

Cardiotoxicity of lung cancer-related immunotherapy versus chemotherapy: a systematic review and network meta-analysis of randomized controlled trials

BackgroundPrevious clinical randomized controlled trials (RCTs) have demonstrated that immune checkpoint inhibitors (ICIs) cause various toxicities during cancer treatment, but the effects of different inhibitors in combination with chemotherapy for cardiotoxicity remain controversial. The aim of the present study was to assess cardiotoxicity caused by programmed cell death protein 1 (PD-1), programmed cell death-Ligand 1 (PD-L1), and cytotoxic T lymphocyte associate protein-4 (CTLA-4) in combination with chemotherapy to treat lung cancer.MethodsThe following ICIs were included in the present study: durvalumab, avelumab, ipilimumab, atezolizumab, pembrolizumab, cemiplimab, and nivolumab. The relevant information was extracted using a predefined data extraction table, and the risk of bias was assessed in randomized controlled trials using the Cochrane Bias Risk tool. The main outcomes were hypertension, heart failure, pericardial effusion, and other adverse cardiac events. The random effects model was used to conduct a paired meta-analysis, and a random effects network meta-analysis was then performed within a Bayesian framework.ResultsIn total, 17 RCTs were included in the present study. There were 11,063 individuals in the experimental and control groups, with an average age greater than 60 years. Based on the evaluation of all drug classes in RCTs, CTLA-4+chemotherapy (RR, -0.69 [95% CI, 2.91-1.52] and PD-L1 (RR, -0.21 [95% CI, -1.03-0.60]) were less cardiotoxic than the control arm, which indicated they were safer options for adverse cardiac events. PD-L1 alone was less cardiotoxic than PD-1 alone (RR, -0.57 [95% CI, -1.96-0.82]). Further, the dual immunotarget inhibitor, PD-1+CTLA-4, had the lowest SUCRA value and had the highest cardiotoxicity (SUCRA=9).ConclusionWhen classified according to drug type, CTLA-4+chemotherapy is associated with fewer cardiac adverse events compared to other treatments. Dual immunotarget inhibitors are more likely to have adverse cardiac reactions. Therefore, clinicians should consider this evidence when developing an ICI immunotherapy regimen for lung cancer.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, identifier CRD42023360931

Experimental generation of 6 dB continuous variable entanglement from a nondegenerate optical parametric amplifier

We experimentally demonstrated that the quantum correlations of amplitude and phase quadratures between signal and idler beams produced from a non-degenerate optical parametric amplifier (NOPA) can be significantly improved by using a mode cleaner in the pump field and reducing the phase fluctuations in phase locking systems. Based on the two technical improvements the quantum entanglement measured with a two-mode homodyne detector is enhanced from ~ 4 dB to ~ 6 dB below the quantum noise limit using the same NOPA and nonlinear crystal.Comment: 7 pages, 5 figure