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Background Because thoracic endovascular aortic repair (TEVAR) has become the standard of care for complicated type B aortic dissection (TBAD) and descending thoracic aortic (DTA) aneurysm, it is important to understand outcomes and use of TEVAR across thoracic aortic pathologies. Methods and Results This was an observational study of patients with TBAD or DTA undergoing TEVAR from 2010 to 2018, using the Nationwide Readmissions Database. In‐hospital mortality, postoperative complications, admission costs, and 30‐ and 90‐day readmissions were compared between the groups. Mixed model logistic regression was used to identify variables associated with mortality. An estimated total of 12 824 patients underwent TEVAR nationally, of which 6043 had an indication of TBAD and 6781 of DTA. Patients with aneurysms were more likely to be older, women, have cardiovascular disease, and have chronic pulmonary disease compared with patients with TBAD. Weighted in‐hospital mortality was higher for TBAD (8% [1054/12 711] versus 3% [433/14 407], P

This study introduces an enhanced version of the discrete choice model combining embedded neural architecture to enhance predictive accuracy while preserving interpretability in choice modeling across temporal dimensions. Unlike the traditional architectures, which directly utilize raw data without intermediary transformations, this study introduces a modified approach incorporating temporal embeddings for improved predictive performance. Leveraging the Phones Accelerometer dataset, the model excels in predictive accuracy, discrimination capability and robustness, outperforming traditional benchmarks. With intricate parameter estimates capturing spatial orientations and user-specific patterns, the model offers enhanced interpretability. Additionally, the model exhibits remarkable computational efficiency, minimizing training time and memory usage while ensuring competitive inference speed. Domain-specific considerations affirm its predictive accuracy across different datasets. Overall, the subject model emerges as a transparent, comprehensible, and powerful tool for deciphering accelerometer data and predicting user activities in real-world applications.

This research presents a model called the ‘Gaussian negative binomial mixture with a latent class choice model’, which serves as a robust and efficient tool for analyzing decisions across different areas. Our innovative model combines elements of mixture models, negative binomial distributions, and latent class choice modeling to create an approach that captures the complexities of decision-making processes. We explain how the model is formulated and estimated, showcasing its effectiveness in analyzing and predicting choices in scenarios. Through the use of a dataset, we demonstrate the performance of this method, marking a significant advancement in choice modeling. Our results highlight the applications of this model and point towards promising directions for future research, especially in exploring symmetrical patterns and structures, within decision-making processes.

Kinesin-8s are dual-activity motor proteins that can move processively on microtubules and depolymerize microtubule plus-ends. This study shows how kinesin-8s alternate between a promotility and a pro-microtubule-depolymerization state via their tubulin shape-sensing loop-2 region.

The current research was conducted at Vermi-tech Unit, Muzaffarabad in 2018 to evaluate the efficacy of cow dung and vermicompost on seed sprouting, seedlings, and vegetative developmental parameters of Viola x wittrokiana (pansy). In the current study, vermicompost was produced using Eisenia fetida. Physicochemical parameters of vermicompost and organic manure were recorded before each experimentation. The potting experiment was designed and comprised of eight germination mediums containing different combinations of soil, sand, cow dung, and various concentrations of vermicompost such as 10% VC, 15% VC, 20% VC, 25% VC, 30% VC, and 35% VC. Seed sprouting and seedling developmental parameters were observed for 28 days while vegetative plant growth parameters were recorded after 10 weeks of transplantation in various vermicompost amended germination media. Pre and post-physicochemical analysis of germination media were also recorded to check their quality and permanency. The current findings showed that 30% VC germination media was an effective dose for early seed germination initiation and all seed germination parameters. However, the significant vegetative plant growth and flowering parameters of pansy occurred at 35% VC. Findings revealed that vermicompost not only enhanced the seed germination and growth of pansy but also improved soil health. These results indicate that vermicompost can be exploited as a potent bio-fertilizer for ornamental plant production.

Earthworms are highly productive invertebrates and play a vital role in organic farming and improving soil structure and function. The gastrointestinal tract of earthworms possessed agricultural important bacteria. So, the current research aimed was to examine, screen, and identify the plant growth promoting bacteria existing in the digestive tract of Eisenia fetida called plant growth promoting vermi-bacteria. The plant growth promoting traits such as siderophore, phytohormone, and hydrolytic enzymes production, and phosphate solubiliation were assessed. Eleven vermi-bacteria i.e. Bacillus mycoides, B. aryabhattai, B. megaterium, Staphylococcus hominis, B. subtilis, B. spizizenii, B. licheniformis, B. mojavensis, B. toyonensis, B. anthracis, B. cereus, B. thuringiensis, and B. paranthracis were isolated and identified based on microscopic studies, biochemical tests, ribotyping, and agricultural traits. All vermi-bacteria are Gram-positive rods except Staphylococcus hominis and produce different compounds such as siderophore, indole acetic acid, catalase, oxidase, proteases, amylases, and lipases. All vermi-bacteria also act as phosphate solubilizers. Therefore, all isolated vermi-bacteria could be used as potential microbial biofertilizers to enhance crops production in Pakistan.

Background. Solanum melongena is a medicinally important vegetable crop that belongs to the family Solanaceae, which is cultivated worldwide. Methodology. In the present study, 22 eggplant varieties from the different ecogeographical regions were evaluated for nine quantitative and twenty-two qualitative morphological characters. A significant divergence was observed in all characters and wide regional variations for plant characteristics, flower, and fruit characteristics. Principle component analysis (PCA) was performed using PAST3 software to determine the relationship among eggplant accessions. Results. The principal component analysis showed that the first two principal component axes explained 97.17% of the total multivariate variation. Cluster analysis using the Unweighted Pair Group Method of Arithmetic Means (UPGMA) grouped the 22 eggplant accessions into two main clusters based on similarities in morphological characteristics. The study showed that the Solanum melongena accessions belonging to Pakistan and other geographical regions of the world possess marked variation in fruit weight, fruit shape, fruit color, leaf spine, number of locules in fruit, plant height, and flower color. Conclusion. Based on morphological diversity, the best cultivars of eggplant that show better yield can be selected for farmers.

Vermi-composting is an environmental friendly and economic process to decompose organic waste. The objective of this study was to produce vermi-compost using Eisenia fetida and to investigate the impact of vermi-compost (VC) and organic manure (cow dung) on seed germination, seedlings, and growth parameters of Tagetes erecta. Physio-chemical parameters of vermi-compost and organic manure were recorded. A potting experiment was designed, germination medium containing soil, sand, and various concentrations of vermi-composts. The composition of germinating media was: TO (Sand + Soil), TCC (Sand + Soil + Cow dung), 10% VC (Sand + Soil + 0.1 kg VC), 15% VC (Sand + Soil + 0.15 kg VC), 20% VC (Sand + Soil + 0.2 kg VC), 25% VC (Sand + Soil + 0.25 kg VC), 30% VC (Sand + Soil + 0.3 kg VC), and 35% VC (Sand + Soil + 0.35 kg VC). Seed germination, seedling, vegetative plant growth, and flowering parameters were evaluated in different germinating media. Pre and post-physio-chemical parameters of germination media were also recorded to check their stability and quality. Results showed that 20% VC was effective for the early initiation of seed germination (2.0 ± 0.0 days) and all growth parameters of marigold seedlings. The germination percentage at 20% VC was recorded as 87.5 ± 1.40 %. The best vegetative plant growth and flowering parameters of marigold plants were observed with 35% VC after transplantation. Findings showed that vermi-compost is the best-suited germination and growing media, which not only improved the soil health but also promoted seed germination and plant growth. Our study undoubtedly indicates that vermi-compost is a more encouraging and advantageous bio-fertilizer and can be used as a powerful and effective for immediate marigold production.

Earthworms (Crassiclitellata) being ecosystem engineers significantly affect the physical, chemical, and biological properties of the soil by recycling organic material, increasing nutrient availability, and improving soil structure. The efficiency of earthworms in ecology varies along with species. Therefore, the role of taxonomy in earthworm study is significant. The taxonomy of earthworms cannot reliably be established through morphological characteristics because the small and simple body plan of the earthworm does not have anatomical complex and highly specialized structures. Recently, molecular techniques have been adopted to accurately classify the earthworm species but these techniques are time-consuming and costly. To combat this issue, in this study, we propose a machine learning-based earthworm species identification model that uses digital images of earthworms. We performed a stringent performance evaluation not only through 10-fold cross-validation and on an external validation dataset but also in real settings by involving an experienced taxonomist. In all the evaluation settings, our proposed model has given state-of-the-art performance and justified its use to aid earthworm taxonomy studies. We made this model openly accessible through a cloud-based webserver and python code available at https://sites.google.com/view/wajidarshad/software and https://github.com/wajidarshad/ESIDE.

ABSTRACT Mitotic spindles assume a bipolar architecture through the concerted actions of microtubules, motors, and cross-linking proteins. In most eukaryotes, kinesin-5 motors are essential to this process, and cells will fail to form a bipolar spindle without kinesin-5 activity. Remarkably, inactivation of kinesin-14 motors can rescue this kinesin-5 deficiency by reestablishing the balance of antagonistic forces needed to drive spindle pole separation and spindle assembly. We show that the yeast form of the opportunistic fungus Candida albicans assembles bipolar spindles in the absence of its sole kinesin-5, CaKip1, even though this motor exhibits stereotypical cell-cycle-dependent localization patterns within the mitotic spindle. However, cells lacking CaKip1 function have shorter metaphase spindles and longer and more numerous astral microtubules. They also show defective hyphal development. Interestingly, a small population of CaKip1-deficient spindles break apart and reform two bipolar spindles in a single nucleus. These spindles then separate, dividing the nucleus, and then elongate simultaneously in the mother and bud or across the bud neck, resulting in multinucleate cells. These data suggest that kinesin-5-independent mechanisms drive assembly and elongation of the mitotic spindle in C. albicans and that CaKip1 is important for bipolar spindle integrity. We also found that simultaneous loss of kinesin-5 and kinesin-14 (CaKar3Cik1) activity is lethal. This implies a divergence from the antagonistic force paradigm that has been ascribed to these motors, which could be linked to the high mitotic error rate that C. albicans experiences and often exploits as a generator of diversity. IMPORTANCE Candida albicans is one of the most prevalent fungal pathogens of humans and can infect a broad range of niches within its host. This organism frequently acquires resistance to antifungal agents through rapid generation of genetic diversity, with aneuploidy serving as a particularly important adaptive mechanism. This paper describes an investigation of the sole kinesin-5 in C. albicans, which is a major regulator of chromosome segregation. Contrary to other eukaryotes studied thus far, C. albicans does not require kinesin-5 function for bipolar spindle assembly or spindle elongation. Rather, this motor protein associates with the spindle throughout mitosis to maintain spindle integrity. Furthermore, kinesin-5 loss is synthetically lethal with loss of kinesin-14—canonically an opposing force producer to kinesin-5 in spindle assembly and anaphase. These results suggest a significant evolutionary rewiring of microtubule motor functions in the C. albicans mitotic spindle, which may have implications in the genetic instability of this pathogen.

Objective: We created and validated a low-cost simulation model for robotic internal mammary artery (IMA) takedown., Methods: The simulation model utilized a calf fetus thorax cavity stented open internally and secured to a table. The simulation model was validated at a 2-day robotic cardiac surgery workshop. Each participant harvested one IMA using the da Vinci Xi robot (Intuitive Surgical, Sunnyvale, CA, USA). We compared participant self-reported confidence at robotic IMA harvest before and after using the simulator., Results: Our novel thorax-securing strategy resulted in a stable structure and allowed access to both IMAs from the same 3 ports. The cost to set up the first simulation model was $176 and $133 for every subsequent model. Fifty participants used the simulation model: 42 cardiothoracic surgery attendings and 8 fellows or residents. The feedback form response rate was 78% ( n = 39). On the Likert scale, participants rated realism of the calf model to simulate robotic IMA harvesting (0 = not realistic , 10 = highly realistic ) with a median of 8 out of 10 (interquartile range [IQR] 7 to 9). Participant confidence (0 = not at all confident , 10 = very confident ) in robotic IMA harvesting before and after using the simulator increased ( P = 0.001) from a median of 5 (IQR 1 to 7) to 9 (IQR 7 to 10)., Conclusions: This robotic IMA harvest simulation model is affordable, realistic, and improved participant confidence in robotic IMA harvest. It may provide a valuable training tool for surgeons learning robotic coronary bypass surgery and allows for training frequency necessary to pass basic learning curves., Competing Interests: Declaration of Conflicting InterestsThe authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: T.S.G. is a consultant for Edwards Lifesciences and Medtronic and case observation site and proctor for Intuitive Surgical.

Objectives: The maternal near-miss case review (NMCR) cycle is a type of clinical audit aiming at improving quality of maternal healthcare by discussing near-miss cases. In several countries this approach has been introduced and supported by WHO and partners since 2004, but information on the quality of its implementation is missing. This study aimed at evaluating the quality of the NMCR implementation in selected countries within WHO European Region., Design: Cross-sectional study., Settings: Twenty-three maternity units in Armenia, Georgia, Latvia, Moldova and Uzbekistan., Assessment Tools: A predefined checklist including 50 items, according to WHO methodology. Quality in the NMCR implementation was defined by summary scores ranging from 0 (totally inappropriate) to 3 (appropriate)., Results: Quality of the NMCR implementation was heterogeneous among different countries, and within the same country. Overall, the first part of the audit cycle (from case identification to case analysis) was fairly well performed (mean score 2.00, 95% CI 1.94 to 2.06), with the exception of the 'inclusion of users' views' (mean score 0.66, 95% CI 0.11 to 1.22), while the second part (developing recommendations, implementing them and ensuring quality) was poorly performed (mean score 0.66, 95% CI 0.11 to 1.22). Each country had at least one champion facility, where quality of the NMCR cycle was acceptable. Quality of the implementation was not associated with its duration. Gaps in implementation were of technical, organisational and attitudinal nature., Conclusions: Ensuring quality in the NMCR may be difficult but achievable. The high heterogeneity in results within the same country suggests that quality of the NMCR implementation depends, to a large extent, from hospital factors, including staff's commitment, managerial support and local coordination. Efforts should be put in preventing and mitigating common barriers that hamper successful NMCR implementation., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)