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Purpose Anterior cranial fossa (ACF) dural arteriovenous fistulae (DAVF) are rare, unique, and ominous. While surgical disconnection is considered as the favored management option, endovascular treatment has lately gained importance. We present a single institution experience of seven cases. Method A retrospective analysis was performed on the institutional patient database. Features analyzed were demographic details, symptoms, angioarchitecture, treatment course, angiographic results, procedural complications, and follow-up. Results This study included seven patients. The age at presentation ranged from 5–67 years. Clinical symptomatology was as intracranial hemorrhage in 4 patients and headache, chemosis and seizures in one patient each. The fistulae were paramedian at the ACF base. All DAVFs were Cognard type 4. The arterial feeders were from the anterior ethmoidal branches of the ophthalmic artery in all cases (bilateral in n  = 5), frontal branches of the middle meningeal artery (MMA) ( n  = 6), and multiple ECA branches. The arterial route was the choice for access. Complete fistula obliteration was achieved in all but one patient. A traversed vein underwent rupture in one patient. One patient suffered postsurgical hemorrhage. No clinical or angiographic recurrence was noted. Conclusion The DAVFs of the ACF are inherently high-grade lesions. Transorbital ECA-ICA branch anastomoses may be recruited as feeders. They may be best managed by multidisciplinary means personalized on an angioarchitectural basis. Endovascular embolization is safe and efficacious when performed through a navigable feeder from the frontal division of the MMA, which according to our interpretation is in anastomosis with the anterior falcine branch of the anterior ethmoidal artery.

The increase in the global population has led to a substantial increase in the demand for food supply as well as food manufacturing industries that regularly produce large amounts of food waste. Agro-industrial waste has attracted tremendous attention all over the world since ancient times, such waste is usually dumped or burned and poses a threat to human health and the environment, which has always been a matter of serious concern. However, food waste is a major source of complex carbohydrates, proteins, lipids, vitamins, minerals, fibers, and helps in the manufacture of raw materials for a variety of industrial purposes such as the production of biofuels, enzymes, bioactive compounds, biodegradable plastics, surfactants. Hence it is necessary to convert food waste into value-added products that reduce environmental problems. The present review paper attempts to outline and analyze the potential of agro-industrial residues as cost-effective substrates to produce the enzyme amylase using a wide range of microbial strains. Graphical Abstract

Citrus fruits exhibit a high level of different phytoconstituents, of which the changes in the different parts of the fruit during ripening have not been thoroughly studied yet. Thus, in this study, we have investigated how different parts of pomelo fruit (Citrus grandis L.) are modified throughout the development of two consecutive growing seasons. In detail, the main phytochemical compounds, such as total phenolic content, total flavonoid content, antioxidant capacity, DPPH free radical scavenging activity, Ferric reducing antioxidant power (FRAP), and naringin and tannin content, were analyzed. A systematic metabolism of these compounds was found during the development of the fruit, but some pomelo tissues showed a fluctuating trend, suggesting a dependence on the different growing season. Focusing on the tissue distribution of these compounds, the fruit membrane contained the highest level of total phenolic and flavonoid content; fruit flavedo displayed the highest antioxidant capacities and FRAP activities, whereas maximum accumulation of naringin was noticed in fruit albedo. Instead, the highest DPPH free radical scavenging activity and tannin contents were found in the pomelo juice. Regarding the distribution of compounds, a possible bias pattern for the accumulation of those compounds has been noticed throughout the fruit development. From the GC-MS analysis, a total of 111 compounds were identified, where 91 compounds were common in both seasons. Overall, these results could be useful for the food processing industry as guidelines for excellent quality foods and for introducing health-beneficial products and components into our daily diets.

While detection of malignancies on mammography has received a boost with the use of Convolutional Neural Networks (CNN), detection of cancers of very small size remains challenging. This is however clinically significant as the purpose of mammography is early detection of cancer, making it imperative to pick them up when they are still very small. Mammography has the highest spatial resolution (image sizes as high as 3328 × 4096 pixels) out of all imaging modalities, a requirement that stems from the need to detect fine features of the smallest cancers on screening. However due to computational constraints, most state of the art CNNs work on reduced resolution images. Those that work on higher resolutions, compromise on global context and work at single scale. In this work, we show that resolution, scale and image-context are all important independent factors in detection of small masses. We thereby use a fully convolutional network, with the ability to take any input size. In addition, we incorporate a systematic multi-scale, multi-resolution approach, and encode image context, which we show are critical factors to detection of small masses. We show that this approach improves the detection of cancer, particularly for small masses in comparison to the baseline model. We perform a single institution multicentre study, and show the performance of the model on a diagnostic mammography dataset, a screening mammography dataset, as well as a curated dataset of small cancers < 1 cm in size. We show that our approach improves the sensitivity from 61.53 to 87.18% at 0.3 False Positives per Image (FPI) on this small cancer dataset. Model and code are available from  https://github.com/amangupt01/Small_Cancer_Detection

Abstract Chest tuberculosis (CTB) is a widespread problem, especially in our country where it is one of the leading causes of mortality. The article reviews the imaging findings in CTB on various modalities. We also attempt to categorize the findings into those definitive for active TB, indeterminate for disease activity, and those indicating healed TB. Though various radiological modalities are widely used in evaluation of such patients, no imaging guidelines exist for the use of these modalities in diagnosis and follow-up. Consequently, imaging is not optimally utilized and patients are often unnecessarily subjected to repeated CT examinations, which is undesirable. Based on the available literature and our experience, we propose certain recommendations delineating the role of imaging in the diagnosis and follow-up of such patients. The authors recognize that this is an evolving field and there may be future revisions depending on emergence of new evidence.

Rubus species holds promise as a valuable source of polyphenols and bioactive compounds, offering significant potential as functional food ingredients with both nutraceutical and pharmaceutical benefits. However, many edible species within this genus remain under-explored and their importance is largely unrecognized. This review aims to provide an overview of the nutritional and bioactive components of both explored and under-explored Rubus species, highlighting their potential health advantages, value addition, and recent advancements. The economic exploitation of Rubus is currently limited to a few cultivated species, while numerous non-conventional and wild edible species are overlooked. Recognizing the economic and nutritional significance of exploited Rubus species, it is imperative to explore the untapped potential of these underutilized plants. By doing so, these species can be preserved from endangerment and contribute to nutritional and livelihood security for communities having access to them. This review emphasizes the importance of understanding the exceptional characteristics of Rubus species as \"superfoods\" and encourages the promotion and cultivation of these unexplored species. By expanding the cultivation and utilization of under-explored Rubus species, we can unlock their full potential and support sustainable nutritional and economic benefits.

Recent advancements in signal processing and computational power have revolutionized computer vision applications in diverse industries such as agriculture, food processing, biomedical, and the military. These developments are propelling efforts to automate processes and enhance efficiency. Notably, computational techniques are replacing labor-intensive manual methods for assessing the maturity indices of fruits and vegetables during critical growth stages. This review paper focuses on recent advancements in computer vision techniques specifically applied to determine the maturity indices of fruits and vegetables within the food processing sector. It highlights successful applications of Nuclear Magnetic Resonance (NMR), Near-Infrared Spectroscopy (NIR), thermal imaging, and image scanning. By examining these techniques, their underlying principles, and practical feasibility, it offers valuable insights into their effectiveness and potential widespread adoption. Additionally, integrating biosensors and AI techniques further improves accuracy and efficiency in maturity index determination. In summary, this review underscores the significant role of computational techniques in advancing maturity index assessment and provides insights into their principles and effective utilization. Looking ahead, the future of computer vision techniques holds immense potential. Collaborative efforts among experts from various fields will be crucial to address challenges, ensure standardization, and safeguard data privacy. Embracing these advancements can lead to sustainable practices, optimized resource management, and progress across industries. Graphical Abstract Highlights 1. Recent advancements in signal processing and computation drive interest in computer vision across industries. 2. The review focuses on non-destructive methods in fruits and vegetables. 3. Computational techniques replace manual methods for maturity index determination. 4. The principles of techniques are highlighted, along with their successful applications. 5. The potential of computation techniques in destructive, non-destructive methods, biosensors, and AI summarized.

This study investigates the kinetics and optimization of fluidized bed drying of onion slices using CCRD design by Response Surface Methodology, aiming to enhance drying efficiency and preserve product quality. The effects of drying process parameters viz., drying temperature (43.18, 50,60,70, & 76.82 °C), NaCl concentration (6.59, 10, 15, 20, & 23.41%) and bed thickness (1.636, 3,5, 7, & 8.362 mm) on dehydration ratio, rehydration ratio, color change, ascorbic acid content and overall acceptability were evaluated using multiple response optimization techniques. Optimization analysis revealed that a drying temperature of 70 °C, NaCl concentration of 20%, and bed thickness of 3 mm yielded the highest desirability value of 0.637. Under these optimized conditions, the dehydration ratio, rehydration ratio, color change, ascorbic acid content, and overall acceptability of onion slices were measured at 6.76, 5.87, 4.85, 8.06 and 4.02, respectively. Higher drying temperatures, NaCl concentrations and lower bed thickness were associated with faster drying rates. Various mathematical models, including Page, Logarithmic, Henderson and Pabis, Midilli and Newton models, were employed to characterize the drying kinetics, with the Page Model demonstrating superior fit to experimental data. Furthermore, quality parameters such as moisture content, water activity, ascorbic acid content, color change and crispiness of onion slices stored for three months under optimized conditions and packaged in different materials (LDPE and HDPE) were evaluated. Results indicate that the optimized fluidized bed drying process parameters effectively maintained the quality of onion slices during storage.

One of the greatest threats to global health is cancer. Probiotic foods have been shown to have therapeutic promise in the management of cancer, even though traditional treatments such as radiation therapy, chemotherapy, and surgery are still essential. The generation of anticarcinogenic compounds, immune system stimulation, and gut microbiota regulation are a few ways that probiotics when taken in sufficient quantities, might help health. The purpose of this review is to examine the therapeutic potential of probiotic foods in the management of cancer. Research suggests that certain strains of probiotics have anticancer effects by preventing the growth of cancer cells, triggering apoptosis, and reducing angiogenesis in new tumors. Probiotics have shown promise in mitigating treatment-related adverse effects, such as diarrhea, mucositis, and immunosuppression caused by chemotherapy, improving the general quality of life for cancer patients. However, there are several factors, such as patient-specific features, cancer subtype, and probiotic strain type and dosage, which affect how effective probiotic therapies are in managing cancer. More research is necessary to find the long-term safety and efficacy characteristics of probiotics as well as to clarify the best ways to incorporate them into current cancer treatment methods. Graphical abstract Graphical representation showing the role of probiotic foods in cancer management.

An investigation was carried out to evaluate the impact of pretreatments viz. wax coating, hot water dipping, and fungicide treatment on quality characteristics of kinnow. In the present study, a trial was conducted to extend the shelf life of kinnow fruits by maintaining the initial quality characteristics with three wax-to-water dilution ratios (1:1, 1:2, 1:3), hot water dipping at 56 °C with varying time (40, 60, 80 s) along with fungicide treatment at various concentration (150, 200, 250 ppm). Both treated and untreated (experimental control) samples were kept at refrigerated conditions (5–8 °C) and 90–95% RH for 60 days. The effect of the storage period on quality parameters was recorded regarding weight loss, TSS, titrable acidity, ascorbic acid, and total color difference (TCD). The process parameters i.e. wax dilution, hot water dipping time, and fungicide concentration were optimized using response surface methodology (RSM). Optimized process parameters were 1:2.66 waxing dilution, 80 s hot water dipping time, and 250 ppm fungicide concentration. It could be concluded from the results that a combination of wax coating, hot water dipping, and fungicide treatment can help to prolong the storage period of kinnow up to 60 days with retained quality, as compared to 30 days in untreated control kinnow fruits when stored at 5–8 °C and 90–95% relative humidity.