A systematic review of cost-effectiveness analyses of complex wound interventions reveals optimal treatments for specific wound types.

BackgroundComplex wounds present a substantial economic burden on healthcare systems, costing billions of dollars annually in North America alone. The prevalence of complex wounds is a significant patient and societal healthcare concern and cost-effective wound care management remains unclear. This article summarizes the cost-effectiveness of interventions for complex wound care through a systematic review of the evidence base.MethodsWe searched multiple databases (MEDLINE, EMBASE, Cochrane Library) for cost-effectiveness studies that examined adults treated for complex wounds. Two reviewers independently screened the literature, abstracted data from full-text articles, and assessed methodological quality using the Drummond 10-item methodological quality tool. Incremental cost-effectiveness ratios were reported, or, if not reported, calculated and converted to United States Dollars for the year 2013.ResultsOverall, 59 cost-effectiveness analyses were included; 71% (42 out of 59) of the included studies scored 8 or more points on the Drummond 10-item checklist tool. Based on these, 22 interventions were found to be more effective and less costly (i.e., dominant) compared to the study comparators: 9 for diabetic ulcers, 8 for venous ulcers, 3 for pressure ulcers, 1 for mixed venous and venous/arterial ulcers, and 1 for mixed complex wound types.ConclusionsOur results can be used by decision-makers in maximizing the deployment of clinically effective and resource efficient wound care interventions. Our analysis also highlights specific treatments that are not cost-effective, thereby indicating areas of resource savings. Please see related article: http://dx.doi.org/10.1186/s12916-015-0288-5

Large Language Models Based Automatic Synthesis of Software Specifications

Software configurations play a crucial role in determining the behavior of software systems. In order to ensure safe and error-free operation, it is necessary to identify the correct configuration, along with their valid bounds and rules, which are commonly referred to as software specifications. As software systems grow in complexity and scale, the number of configurations and associated specifications required to ensure the correct operation can become large and prohibitively difficult to manipulate manually. Due to the fast pace of software development, it is often the case that correct software specifications are not thoroughly checked or validated within the software itself. Rather, they are frequently discussed and documented in a variety of external sources, including software manuals, code comments, and online discussion forums. Therefore, it is hard for the system administrator to know the correct specifications of configurations due to the lack of clarity, organization, and a centralized unified source to look at. To address this challenge, we propose SpecSyn a framework that leverages a state-of-the-art large language model to automatically synthesize software specifications from natural language sources. Our approach formulates software specification synthesis as a sequence-to-sequence learning problem and investigates the extraction of specifications from large contextual texts. This is the first work that uses a large language model for end-to-end specification synthesis from natural language texts. Empirical results demonstrate that our system outperforms prior the state-of-the-art specification synthesis tool by 21% in terms of F1 score and can find specifications from single as well as multiple sentences

2-Bromo-4-tert-butyl-6-[(pyridin-2-yl­imino)­meth­yl]phenol

In the title compound, C16H17BrN2O, the pyridine and benzene rings are almost coplanar [dihedral angle = 1.3 (2)°]. An intra­molecular O—H⋯Br inter­action forms an S(5) ring motif

Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation

High-dimensional sparse data emerge in many critical application domains such as cybersecurity, healthcare, anomaly detection, and trend analysis. To quickly extract meaningful insights from massive volumes of these multi-dimensional data, scientists employ unsupervised analysis tools based on tensor decomposition (TD) methods. However, real-world sparse tensors exhibit highly irregular shapes, data distributions, and sparsity, which pose significant challenges for making efficient use of modern parallel architectures. This study breaks the prevailing assumption that compressing sparse tensors into coarse-grained structures (i.e., tensor slices or blocks) or along a particular dimension/mode (i.e., mode-specific) is more efficient than keeping them in a fine-grained, mode-agnostic form. Our novel sparse tensor representation, Adaptive Linearized Tensor Order (ALTO), encodes tensors in a compact format that can be easily streamed from memory and is amenable to both caching and parallel execution. To demonstrate the efficacy of ALTO, we accelerate popular TD methods that compute the Canonical Polyadic Decomposition (CPD) model across a range of real-world sparse tensors. Additionally, we characterize the major execution bottlenecks of TD methods on multiple generations of the latest Intel Xeon Scalable processors, including Sapphire Rapids CPUs, and introduce dynamic adaptation heuristics to automatically select the best algorithm based on the sparse tensor characteristics. Across a diverse set of real-world data sets, ALTO outperforms the state-of-the-art approaches, achieving more than an order-of-magnitude speedup over the best mode-agnostic formats. Compared to the best mode-specific formats, which require multiple tensor copies, ALTO achieves more than 5.1x geometric mean speedup at a fraction (25%) of their storage.Comment: We extend the results of our previous ICS paper to significantly improve the parallel performance of the Canonical Polyadic Alternating Least Squares (CP-ALS) algorithm for normally distributed data and the Canonical Polyadic Alternating Poisson Regression (CP-APR) algorithm for non-negative count dat

Organic matter: a critical soil health indicator in agrosystems within the Cerrado of Bahia, Brazil and South Florida, USA.

Soil health (SH) indicators, such as organic matter (OM) content and enzymatic activity (EA), are critical for assessing the sustainability of mineral soils in integrated and cover cropping systems. Taking into account the following objectives: (i) to assess the relationship between OM and other SH indicators, (ii) to evaluate the evolution of SH using two models (SH indicators (SHI) scoring approach and A Modified Comprehensive Assessment of Soil Health scoring system developed for Florida soils (A modified CASH method)), and (iii) present their effectiveness in Brazil and the USA, a medium-term study (2019–2023) in Brazil and a short-term seasonal study (2022–2023) in the USA were conducted in diverse agroecosystems. In Brazil, four agricultural systems were analyzed: Cerrado (Cer), Conventional (Conv), Integrated Crop-Livestock (ICL), and Integrated Crop-Livestock-Forestry (ICLF). In the USA, two cover cropping systems in South Florida were assessed: double cover cropping system (DCCS) and multiple cover cropping system (MCCS). Soil samples were collected for analysis of key soil properties. Results in Brazil showed higher OM in the Cer (1.08 dag kg-1) and ICL (1.12 dag kg-1) systems, and increased enzymatic activity in 2023, particularly in ICL (AS = 33.85 mg de p-nitrofenol kg-1 soil h-1 and BG = 54.65 mg de p-nitrofenol kg-1 soil h-1) and ICLF (AS = 21.07 mg de p-nitrofenol kg-1 soil h-1 and BG = 48.90 mg de p-nitrofenol kg-1 soil h-1). Enzyme activity was more responsive to management practices than OM. Principal Component Analysis revealed stronger correlations between OM, EA, and macronutrients in more sustainable systems like ICL and ICLF. The SHI scoring approach better captured changes in Brazil. In the USA short-term cover cropping systems showed no significant changes in OM or EA, but CASH method suggested slight improvements in MCCS. This study highlights the importance of OM and EA as key indicators for assessing and improving SH and suggests that while integrated and cover cropping systems offer potential benefits, longer-term management and organic amendments are necessary to achieve sustained improvements in soil health

Protein Kinase C-δ Mediates Neuronal Apoptosis in the Retinas of Diabetic Rats via the Akt Signaling Pathway

OBJECTIVE—Protein kinase C (PKC)-δ, an upstream regulator of the Akt survival pathway, contributes to cellular dysfunction in the pathogenesis of diabetes. Herein, we examined the role of PKC-δ in neuronal apoptosis through Akt in the retinas of diabetic rats

Delineation of VEGF-regulated genes and functions in the cervix of pregnant rodents by DNA microarray analysis

<p>Abstract</p> <p>Background</p> <p>VEGF-regulated genes in the cervices of pregnant and non-pregnant rodents (rats and mice) were delineated by DNA microarray and Real Time PCR, after locally altering levels of or action of VEGF using VEGF agents, namely siRNA, VEGF receptor antagonist and mouse VEGF recombinant protein.</p> <p>Methods</p> <p>Tissues were analyzed by genome-wide DNA microarray analysis, Real-time and gel-based PCR, and SEM, to decipher VEGF function during cervical remodeling. Data were analyzed by EASE score (microarray) and ANOVA (Real Time PCR) followed by Scheffe's <it>F</it>-test for multiple comparisons.</p> <p>Results</p> <p>Of the 30,000 genes analyzed, about 4,200 genes were altered in expression by VEGF, i.e., expression of about 2,400 and 1,700 genes were down- and up-regulated, respectively. Based on EASE score, i.e., grouping of genes according to their biological process, cell component and molecular functions, a number of vascular- and non-vascular-related processes were found to be regulated by VEGF in the cervix, including immune response (including inflammatory), cell proliferation, protein kinase activity, and cell adhesion molecule activity. Of interest, mRNA levels of a select group of genes, known to or with potential to influence cervical remodeling were altered. For example, real time PCR analysis showed that levels of VCAM-1, a key molecule in leukocyte recruitment, endothelial adhesion, and subsequent trans-endothelial migration, were elevated about 10 folds by VEGF. Further, VEGF agents also altered mRNA levels of decorin, which is involved in cervical collagen fibrillogenesis, and expression of eNO, PLC and PKC mRNA, critical downstream mediators of VEGF. Of note, we show that VEGF may regulate cervical epithelial proliferation, as revealed by SEM.</p> <p>Conclusion</p> <p>These data are important in that they shed new insights in VEGF's possible roles and mechanisms in cervical events near-term, including cervical remodeling.</p

Beneficial effect of Sparassis crispa on stroke through activation of Akt/eNOS pathway in brain of SHRSP

Sparassis crispa (S. crispa) is a mushroom used as a natural medicine that recently became cultivatable in Japan. In this study, we investigated not only the preventive effects of S. crispa against stroke and hypertension in stroke-prone spontaneously hypertensive rats (SHRSP) but also the mechanism involved by using studies of the cerebral cortex at a young age. Six-week-old male SHRSP were divided into 2 groups, a control group and an S. crispa group administered 1.5% S. crispa in feed, and we then observed their survival. In addition, rats of the same age were treated with 1.5% S. crispa for 4 weeks and we measured body weight, blood pressure, blood flow from the tail, NOx production, and the levels of expression of several proteins in the cerebral cortex by western blot analysis. Our results showed that the S. crispa group had a delayed incidence of stroke and death and significantly decreased blood pressure and increased blood flow after the administration. Moreover, the quantity of urinary excretion and the nitrate/nitrite concentration in cerebral tissue were higher than those of control SHRSP rats. In the cerebral cortex, phosphor-eNOS (Ser1177) and phosphor-Akt (Ser473) in S. crispa-treated SHRSP were increased compared with those of control SHRSP rats. In conclusion, S. crispa could ameliorate cerebrovascular endothelial dysfunction by promoting recovery of Akt-dependent eNOS phosphorylation and increasing NO production in the cerebral cortex. S. crispa may be useful for preventing stroke and hypertension