Collaboration and successful teamworking are important components of clinical practise, and these skills should be cultivated early in medical school. The breadth of current medical school curricula means that students often have limited exposure to clinical neurosciences. Since its inception in 2009, the Neurology and Neurosurgery Interest Group (NANSIG) has become a national (UK and Republic of Ireland) example of student and junior doctor synergistic collaboration to deliver educational materials, research, conferences, seminars and workshops, as well as advocating for diversity in this field. Recently, it has expanded to incorporate an international audience and cater for a larger group of young medical professionals. The organisation has overcome numerous challenges and is constantly innovating new approaches to harness the necessary knowledge, skills and network to succeed in a career in neurosciences, neurology and neurosurgery. This article summarises the initiatives undertaken by the group over its first 10 years of existence and its organisational structure, as well as its future plans.The online version contains supplementary material available at 10.1007/s00701-022-05113-0. Neurology and Neurosurgery are some of the most competitive specialties in the United Kingdom (UK) , and comNANSIG was founded in 2009 by a medical student, after finding that nearly two-thirds of medical students had no exposure to neurosurgery by the end of medical training . The aimIn the 10 years that have followed, NANSIG has proliferated into a leading student and junior doctor interest group, with over 1800 members, 18 core committee members, 13 Foundation School representatives (deanery leads) , 32 mediNANSIG consists of a core committee, regional leads (consisting of university and deanery leads), international ambassadors and its members Fig. . List ofAll members are eligible to apply to become core committee members, regional leads or international ambassadors. Elections for these positions occur annually with the term of each role being 1 year: in January for the committee, and in August for leads and ambassadors. NANSIG is committed to organising all elections in accordance with the diversity principles of the ALBA network, relating to consistency in selection criteria, and minimising bias when possible , 38. ThiIn the past 4 years, NANSIG has established itself as a platform for members to collaborate and contribute to high-quality multi-centre research; some of which has informed national specialty reports , 21. To Furthermore, NANSIG has established a cross-continental collaboration with the Association of Future African Neurosurgeons (AFAN) to develop a research incubator programme, the first of its kind in the global neurosurgical community. This programme provides students and junior doctors with the opportunity to design and lead global neurosurgical research projects within a topic of their interest, under the mentorship of experienced academics. Though in its infancy, the collaborative has since contributed to the scholarly output in Africa through identifying areas in need of improvement, such as the lack of availability and accessibility of diagnostic and management tools for aneurysmal subarachnoid haemorrhage in the continent , 13, 35.Alongside these collaborative studies, NANSIG has also published many articles discussing a range of topics including (i) women in neurosurgery and advocacy , 28, 33,With NANSIG tackling barriers that medical students and junior doctors face pursuing a career in the clinical neurosciences, an educational component emerged to counter neurophobia  and promIn keeping with international trends through the COVID-19 pandemic, since March 2020, the scope of the educational content has expanded to include a webinar series on neuroanatomy, common conditions encountered in different clinical neuroscience sub-specialties and a journal club. This branch of educational activity has been solely developed and delivered by leading academic clinicians, including world experts on a topic or principal investigators of practise-changing research , Twitter , Instagram , Linkedin and YouTube . Through these diverse channels, we raise awareness of our events and causes and provide opportunities to engage with interested individuals.We communicate with all members of NANSIG through subscribed mailing lists . In thesNANSIG has overcome several challenges since its establishment. First, one of the studies that was started but not completed was the National Traumatic Brain Injuries Referrals study in 2018. This project encountered difficulty with centre recruitment, given that there was an existing national trauma network already in place. Learning from this, we have implemented an important process when planning and constructing the protocol of a study, which is to consult experienced researchers from organisations such as the BNTRC and SBNS for advice and support throughout.Second, based on feedback from our Annual Careers days, it was evident that the event was not fully inclusive. Since then, we have tried to increase inclusivity and diversity within all our events, such as by organising our first-ever advocacy conference to educate and inspire members, creating a core committee vice chair of advocacy role to encourage representation and internally auditing the diversity perceptions of all NANSIG events . This inThird, another issue identified was the need to have a standardised and clear approach to authorship of publications, and this is communicated from inception. This is now clearly defined in all research protocols.Fourth, due to the structure of the organisation and relative interest from our members, the field of Neurology has been a lesser component of NANSIG’s focus and initiatives. With the launch of two neurology-themed multi-centre collaborative studies and an inaugural NANSIG Neurology Careers Day, we hope to broaden our scope of events, research and projects to ensure NANSIG provides useful resources to promote clinical neurosciences, in addition to Neurosurgery.Finally, NANSIG has been privileged to experience such an accelerated expansion. In a single year, we had an increase from 1000 members to over 1800 members, whilst the committee expanded from ten members to 18. We have also started actively engaging with our international ambassador programme, in which we newly recruited ambassadors from 30 different countries. This had put a substantial amount of pressure on the Chair and the core committee. Such pressures are expected and are a promising measure of NANSIG’s utility 10 years into its establishment.NANSIG’s future vision can be dichotomised into improving existing initiatives, and championing new initiatives to help promote a career in clinical neurosciences. We hope to maintain a strong relationship with both the SBNS and ABN, as well as newer partner organisations like the European Association of Neurosurgical Societies (EANS), the British Paediatric Neurology Association (BPNA), BNTRC and AFAN. We will continue to provide high-quality education and mentorship and to serve as a platform for those interested in the clinical neurosciences to express and develop their interest on a national and international scale. We will progress our existing body of research by learning from our past experiences, incorporating a proactive approach emphasising clarity and project preparation and seeking guidance throughout the entirety of the research process, from the expert bodies we are associated with. We hope this will lead to constructing an academic framework to facilitate constructive academic guidance from senior collaborators.Clarity, openness and fairness are at the heart of NANSIG’s vision going forward. This has been tackled through (1) an official NANSIG constitutional document—(nansig.org/constitution); (2) a clear, standardised and fair approach towards the election of committee members and research authorship (nansig.org/policy); (3) turning our attention to advocacy; and (4) encouraging participation in line with the ALBA framework. We also hope to involve patients, carers and families in future research projects.Finally, the prospect of collaborating on a global level is exciting. NANSIG is now well known internationally—this is indicative of our plan to expand, increasing representation on a global scale. We hope that the NANSIG model is an exemplary story that can assist the development of similar neurology/neurosurgery interest groups in other countries, for the ultimate benefit of improving the quality of care for patients.In the 10 years since its formation, NANSIG has become much more than a group of interested medical students. We have evolved to be a pioneering organisation that delivers collaborative research and education, whilst developing the next generation of neurologists, neurosurgeons and neuroscientists, and advocating for inclusivity within the specialty. Nevertheless, we believe that there is still great potential for development and growth. We aim to continue striving to promote awareness and participation in the clinical neurosciences, and encourage successful collaborations—a cornerstone of the senior organisations that support us.Supplementary file1 (DOCX 20 KB)Below is the link to the electronic supplementary material.


This work investigated the impact of three drying methods on structural and functional properties of potato flour (PF), as well as the quality characteristics of fresh noodles made from wheat-potato flours. The results indicated that ethanol drying (ED) and oven drying (OD) had small effects on the properties of starch in potato flour, however, freeze drying (FD) caused some pores and channels on the starch granules and disruption of the long- and short-range ordered structure of starch. The maximum addition of potato flour in fresh noodles was 40% for FD-PF and 50% for both ED-PF and OD-PF. With increasing addition of potato flour in noodles, the L* (lightness) values of noodles decreased gradually, while the a* (redness) and the b* (yellowness) values, as well as the hardness and springiness values of fresh potato noodles increased. This study clearly showed that drying methods have different effects on the properties of potato flour, and in turn the quality of fresh noodles made with potato flour. Solanum tuberosum L.) is the fourth-largest crop following maize, rice and wheat [Potato  drying, freeze-drying, and ethanol (solvent-exchange) drying . PreviouPreparation of commercially available potato flour usually involves boiling or steaming and heat-drying processes, which causes starch gelatinization. This treatment disrupted the structure and functional properties of potato starch in some ways, such as a decrease in the values of pasting viscosities, which may be unfavorable for the production of some steamed or frozen foods that need to be cooked before consumption . To reduWheat flour was obtained from Jinshahe Group Co., Ltd.  with total starch, protein, and fat contents of 62.93, 12.87, and 1.52 g/100 g flour, respectively. The fresh potatoes were acquired from Tianjin, China. Potato tubers were stored in a refrigerator (4 °C). All the reagents were of analytical grade.The fresh potatoes were washed thoroughly, peeled, and cut into small pieces with a kitchen knife and homogenized in a kitchen blender with 500 mL distilled water for 1–2 min at greatest speed. After centrifugation, the precipitates were subjected to three different drying medications described previously . Wet PF Moisture content was determined by drying flour to a steady weight at 105 °C. Total starch content of PF was determined by a Megazyme total starch  assay kit.The morphology of starch granules within the PF was imaged using a LEO 1530 scanning electron microscope . The samples were mounted on the aluminum stub using the double-sided carbon adhesive tapes and sputter-coated with gold. An accelerating voltage of 5 kV was used during imaging.X-ray diffraction examination was performed employing a D/max-2500 vk/pc X-ray diffractometer  working at 40 kV and 30 mA. Tests were equilibrated over an immersed sodium chloride (NaCl) arrangement at room temperature for one week before analysis. The tests were filtered from 4 °C to 35 °C, 2θ and at a checking speed of 1°/min and a step measure of 0.02°. The relative crystallinity was quantitatively assessed as a proportion of the crystalline region to the overall zone between 4 °C to 35 °C (2θ) utilizing the Origin software .The LCM-Raman spectra of the PF tests were obtained using a Renishaw Invia Raman microscope system  prepared with a Leica microscope ; a 785 nm green diode laser source was utilized. w/w). The pans were sealed and allowed to stand overnight at room temperature before analysis, heated from 20 to 100 °C at a rate of 10 °C/min. An empty pan was used as the reference.The thermal properties of the PF were measured using a differential scanning calorimeter  prepared with a thermal analysis data station . PF   concurring to STD 1 strategy. PF (2.5 g) was weighed into the RVA canisters, and the distilled water was added to make a total weight of 28 g. After RVA examination, the flour paste formed within the canister was fixed with parafilm to prevent moisture loss and stored at 4 °C for 10 days for textural examination. w/w) were warmed in a water shower at 92.5 °C for 30 min with normal shaking and cooled at 20 °C for 3 min and centrifuged at 13,000× g for 10 min. The supernatant dried at 105 °C and weighed to decide dissolvability (% of dry flour) and swelling power (g H2O absorbed/g dry flour).The swelling power and solubility of starch were decided based on the strategy of Wang and Copeland , with a w/w). The dough was made physically by adding 50% of water and NaCl aqueous solution  to the above flours. The dough shaped was put to rest in a plastic sack for 20 min and after that passed through a noodle machine to prepare noodles. The noodle strands of 4 mm in width were produced by the noodle machine and cooked at optimum time for further tests.Noodles were prepared by a noodle machine . Potato flours were blended with wheat flour at the following weight rates of 0%, 10%, 20%, 30%, 40%, 50%  was utilized to degree the color of the noodle tests. L* is a measurement of brightness (0–100), a* represents the red-green facilitates (− is green while + is red) whereas b* measures the blue-yellow arranges (− is blue with + demonstrating yellowness) of a product .A standard two-cycle program was utilized to compress the gels for a 20% strain at 1.0 mm/s test speed, 1.0 mm/s pre-test speed, 1.0 mm/s post-test speed, 2 s delay time and 5 g trigger drive. Three strands of noodles were set parallel on the testing stage, and the judgments were conducted under optimal test conditions: strain, 70%; test and post-test speed, 1 mm/s; interim time, 2 s. Texture parameters of hardness, springiness, cohesiveness, gumminess, chewiness and resilience were inferred from the bends by the instrument software.p < 0.05) was conducted utilizing the SPSS 10.0 Statistical Software Program .All tests were performed at the slightest in triplicate and the comes about are detailed as the cruel values and standard deviations. Within the case of XRD, as it were one estimation was conducted. Investigation of change (ANOVA) by Duncan’s test  and enthalpy change (ΔH) of potato flours are shown in The pasting properties of three potato flours determined using an RVA differed greatly . In contGel textural properties of three potato flours were also different greatly . PF-ED gSwelling power and starch solubility of potato flour tests are displayed in To determine the maximum addition of potato flour to wheat flour, we performed the pre-experiment, and the maximum addition of potato flour to wheat flour is 40% for PF-FD, and 50% for both PF-ED and PF-OD, the dough with more addition amount of PFs cannot be prepared the noodles. Previous studies showed that noodles with cooked whole potato flour content below 40% were acceptable , ethanolColor is considered as a major determinant of noodle quality. For white salt noodles, a clean and bright appearance is alluring, while dark or gray colors are negative traits. Color parameters of noodles are shown in In this study, we investigated the impact of three drying methods on structural and functional properties of PFs and the quality characteristics of noodles prepared by different PF/WF ratio. As a result, the FD treatment led to pores and channels on the surface of potato starch and decreased the gelatinization temperatures. The damage of the crystalline arrangement and the diminishment within the amount of double helices might have happened amid the FD process . A similThe quality characteristics of noodles by mixing different PF/WF ratio were investigated, the maximum addition of potato flour to wheat flour is 40% for PF-FD, and 50% for both PF-ED and PF-OD, the different values were attributed to the different drying methods that have significant effects on the surface granular morphology, long- and short-range requested structure of potato starches, the physicochemical characteristics of starch play a fundamental part in both noodle preparing and the ultimate noodle quality . The grep < 0.001) related with buckwheat noodle hardness, which uncovered that high final viscosity accounted for rough and stiff noodles [Fresh noodles with mixing wheat flour/potato flour are a complex system; potato starch content and the gluten protein network were the primary factor influencing the noodle’s texture properties. In common, pasting properties are related to the swelling and break of starch granules in a system . PV is a noodles . SetbackThis work deeply evaluated the effects of three drying methods on the structure and functional properties of potato flour and the quality properties of fresh potato noodles. The freeze-drying disrupted the surface and the structure of potato starch granules, compared with the ethanol drying and oven drying methods. ED and OD treatments had less effect on the surface and structure of potato starch, and it increased the potato flour content of noodles attain to 50%. The effects of different drying methods on potato starch granules determines the quality characteristics of potato noodles. This study provides valuable information for the selection of suitable drying methods of potato flour applied in the flour products and a theoretical basis for the application of potato products.


Deep neural networks can learn powerful representations from massive amounts of labeled data; however, their performance is unsatisfactory in the case of large samples and small labels. Transfer learning can bridge between a source domain with rich sample data and a target domain with only a few or zero labeled samples and, thus, complete the transfer of knowledge by aligning the distribution between domains through methods, such as domain adaptation. Previous domain adaptation methods mostly align the features in the feature space of all categories on a global scale. Recently, the method of locally aligning the sub-categories by introducing label information achieved better results. Based on this, we present a deep fuzzy domain adaptation (DFDA) that assigns different weights to samples of the same category in the source and target domains, which enhances the domain adaptive capabilities. Our experiments demonstrate that DFDA can achieve remarkable results on standard domain adaptation datasets. In recent years, deep learning has achieved great success in computer vision  and natuTraditional machine-learning algorithms assume that the training data and test data obey the same distribution; however, due to dataset bias, the data distribution on different domains often differs. The generalization ability of the algorithm will be weakened if the statistical distribution of samples is changed. The main idea of domain adaptation  is to usThere are three common approaches to domain adaptation ,7: featuSome instances are selected from the source domain so that the probability distribution of the obtained sample subset is similar to the target sample and are then trained using traditional machine-learning methods. Apart from this, the classifier-based adaptation makes the source domain model adapt to the target by regularizing the difference between the source domain and target domain model parameters ,16,17. SPrevious feature-based domain adaptation methods have mainly used explicit distances to align feature distributions between source and target domains ,19,20 orAlthough these aforementioned methods achieved good performance, there is no sample selection process, i.e., alignment of all samples in the same category, which may affect the final results. A straightforward example is shown in For samples with the true label A in the source domain that are misclassified as B or C, it may happen to be aligned with a sample in the target domain that is also misclassified as C, but is more likely to be mismatched with several samples with the true label B. This confusion degrades the ability of domain adaptation. For more accurate alignment, we propose a fuzzy maximum mean discrepancy (FMMD), which considers the predicted information of instances in the source domain to alleviate this problem. Based on this, we design a new network architecture Deep Fuzzy Domain Adaption (DFDA) to apply FMMD, and DFDA can be easily optimized by the standard gradient descent method. The experimental results show that our method outperforms state-of-the-art metric-based approaches on benchmark datasets.Before discussing the FMMD, in this section, we introduce three related aspects of work: feature-based domain adaptation, subdomain adaptation, and maximum mean discrepancy (MMD).Research  has showThe discriminator learns to distinguish between the source domain and target domain features, and the generator learns feature representations with domain invariance to confuse the discriminator. Previous works ,25,29 haMMD reduces the mean between domains in the Reproducing Kernel Hilbert Space (RKHS), CORAL reduces the difference between the covariance matrices the two domains, and CMD   aligns tSome recent approaches have improved the performance of domain adaptation by introducing category information into the network. CDAN   conditioA joint adaptation network (JAN)  combinesInspired by the concept of the instance-based transfer method and the different above-mentioned methods, we assign different weights to samples of the same category between domains by adding the predicted value of the samples and selecting some suitable samples for fine alignment. These methods perform domain feature alignment based on the hard pseudo-labeling of samples by the classifier, which will undoubtedly lead to improper alignment due to the presence of noise in these labels.MMD calculates the mean distance of the distribution in the RKHS as the distribution discrepancy between the two domains, and its effectiveness has been proven . There iWeight MMD (WMMD)  alleviatIn the unsupervised domain adaptive scenario, we are given a source domain Deep neural networks can learn more transfer representations than traditional machine learning handcrafted features. Several popular deep transfer methods have emerged by adding adaptation layers to neural networks to align the distribution of features between domains ,40. Thesc with the same probability DSAN introduces the category information of the source domain and the predicted value information of the target domain into the network and aligns each category separately, which achieves remarkable results on both object recognition tasks and digit classification tasks. However, its assumption that every sample of the same class belongs to class k . Formally, the MMD between distributions c, respectively. Assuming that the weight of each sample in the same category is equal:DSAN introduces label information to the network and proposes the Local Maximum Mean Discrepancy (LMMD) to align the distributions of the relevant subdomains within the same category in the source and target domains.c. It is used to evaluate the quality of the features here. If the predicted value of the sample is closer to the label value, it means that it is a good sample and increases the weight of the sample. On the contrary, if the predicted value deviates from the true value, the feature weight of this sample will decrease. As in DSAN, the weights on the target domain sample are calculated using the predicted values instead of the true label.However, there are gaps in quality between samples, and the alignment of outliers can easily become confusing. In particular, when a category is too sparse in a batch, the sample weight is prone to unreasonable assignments. To address this issue, we propose the FMMD as follows:We propose a new network architecture Deep Fuzzy Domain Adaption (DFDA) in order to embed FMMD into the network. Different from the previous method that only uses the label of the source domain, the predicted information of the source domain samples are also added to the network. As shown in We analyzed the effectiveness of DFDA based on the domain adaptation theory ,41.Theorem 1.S and T, then, for any Let H be a hypothesis space of VC dimension d. Given two domains In this case, the second term, This section mainly introduces the data sets and experimental environment used in the experiment and describes in detail the analysis. We evaluate our algorithm on three widely used benchmark datasets, including the Office31, Office Home, and large-scale digital recognition datasets, and compare it with several state-of-the-art distance metric-based transfer learning models: DDC, DAN, JAN, Deep CORAL, and DSAN, to assess the effectiveness of our approach.Office31  is one oOffice Home  is much Digital recognition dataset contains three widely used benchmarks: MNIST , USPS 4 and SVHNFor the digital recognition dataset, all the images are resized to 32 × 32 as the input of the network. We use the modified LeNet  as the fFor the other two datasets, we follow the settings in DSAN and employ ResNet50 as the feature extraction network, and a bottleneck layer fcb with 256 units is added after the last average pooling layer to reduce the dimensionality. Finally, we use the output of fcb as the FMMD input. We use the pre-trained model on ImageNet to fine-tune all convolutional and pooling layers, and we train the classifier layer via backpropagation.−4. The learning rate is adjusted during SGD using the following formula: We follow the settings of DSAN. For each task, we use a mini-batch stochastic gradient descent (SGD) with a momentum of 0.9, and the weight attenuation coefficient is 5 × 10This progressive strategy can effectively suppress noisy activations at the early stages of training.https://github.com/jindongwang/transferlearning/ accessed on 27 September 2021) and report the average classification accuracy and standard error for three random trials. For all MMD-based approaches, we adopt a Gaussian kernel, and the bandwidth is set to the median pairwise squared distance on the training data.For a fair comparison of the above methods, the same network architecture is used on the same dataset. We implement these with publicly available code  to visualize in To demonstrate the effect of transfer learning, we utilize t-SNE (To give an overview of the results, we compared DFDA with several other MMD-based metrics in terms of the execution time and computational cost. The performance test was performed on a computer with a NVIDIA RTX3090 GPU, and the results are shown in Our approach does increase some matrix operations over the previous approach; however, these computational costs are negligible compared to the computational effort brought by ResNet50, and considerable performance gains can be obtained. The average increase in computing time per epoch is only 0.3 s, which we believe is worth the cost.The previous subdomain adaptive approach aligns all samples within the relevant subdomain without considering the quality differences of individual features. In this paper, we proposed a new method of DFDA to measure the distance between domains, which evaluates the quality of individual features in the source domain by adding predicted information of the source domain to the network. Particularly in the setting of a large batch size, this can select more suitable samples among multiple same-class samples on the source domain to match with the target domain, which effectively improved the performance of the transfer model. Compared with previous methods, our proposed DFDA achieved 1.7% and 0.8% performance improvements on the digital recognition and Office-31 datasets, respectively, and these results support the effectiveness of our proposed method.


Scorpion stings comprise a serious problem throughout the globe, especially in regions where they are more frequent. Despite a recent upsurge of interest in scorpion venoms by various research groups, there remain many challenges.Hottentotta saulcyi, Hottentotta schach and Androctonus crassicauda, three scorpion species collected in Iran.Therefore, in this study, we aimed to study the toxicity and protein composition of venoms of A. crassicauda, H. schach and H. saulcyi by electrical stimulation of 8 and 10 V. The toxicity of each venom was established by using four groups of male Swiss albino mice aged 2 months (weighting 18–20 g) for testing each dose of venom. One group was used as a control. Venom was injected into mice by subcutaneous route. Then, animals were monitored for 24 h and LD50 was estimated by the graphic method of Miller and Tainter. Thus, high‐performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) method was used to determine amino acids in the venom, and protein concentrations were determined by the Biuret method.Scorpion species were collected from Esfahan farm scorpion company and maintained in the laboratory in containers that mimic their natural habitat. Venom was extracted from 50 of scorpion venoms by subcutaneous route was found to be 1.70 mg/kg b.w (A. crassicauda), 1.47 mg/kg b.w (H. saulcyi) and 0.85 mg/kg b.w (H. schach). A. crassicauda, H. saulcyi and H. schach contain 26, 30, and 31 amino acids, respectively. A. crassicauda contains low concentrations of alpha‐aminoadipic acid, beta‐aminoisobutyric acid, beta‐alanine and citrulline. H. saulcyi contains a concentration of hydroxylysine, whereas H. schach has no such concentration. A. crassicauda also had the highest levels of tyrosine and threonine. Only A. crassicauda venom contains a low proportion of proteins (14.80%) compared with those of H. schach (16.26%) and H. saulcyi (16.20%). Albumin content in the venoms was 11.7% (H. saulcyi), 5.4% (H. schach) and 4.4% (A. crassicauda).LDScorpions venoms have a variable toxicity and an interesting composition in amino acids and proteins. Work on the development of anti‐venom is fundamental. Hottentotta saulcyi, Hottentotta schach and Androctonus crassicauda). The results from this study show that H. saulcyi and H. schach contain more amino acids and protein and have higher toxicity than A. crassicauda.This study could be useful for understanding the venom extraction and toxicity, the protein and amino acid diversities of three species of scorpions ( Based on morphological characteristics such as body colour, pedipalp shape and size, sternum shape, telson colour and several pectin teeth, collected scorpions were identified at the species level.2.3In the laboratory, scorpions were placed in a large glass aquarium  on top layer of soil about 3 in. in depth, above which proper size stones were kept, imitating their natural habitat.As a source of drinking water, a petri dish lid containing tap water was kept in the centre of the glass aquarium. The scorpions were fed with crickets and worms of flour. At 3‐day intervals, the water content of the petri dish was checked and, if necessary, filled.Scorpions were only handled on the day of venom extraction and during soil replacement, which was done once every 2 months. The venom was not removed the day immediately following the feed and no food was added up to 3 days after the venom was removed.A. crassicauda, H. schach and H. saulcyi were stimulated twice, at 8 and 10 V, respectively, for 2–3 s with short intervals between two stimulations.The tail was held firmly wing forceps and electrically stimulated by pointing two electrodes connected to a step‐down transformer at junctions between the tail segments, one next to the telson. The other at the junction between IV and V metasomal segment. The venom was allowed to secrete over a piece of parafilm placed at the base of its tail and then transferred to a vial. The venom obtained in a single episode from many scorpions of a species were pooled, mixed with excess double distilled water and centrifuged at 15,000 rpm for 20 min to remove the mucus; the supernatant was lyophilised and stored at 20°C until used for protein estimation and toxicity studies; venom was resuspended in phosphate‐buffered saline (PBS) PH7.2.4A. crassicauda, H. schach and H. saulcyi was studied by estimating the lethal dose 50 (LD50) value under in vivo conditions. Four groups of 2‐month‐old Swiss male albino mice (weighing 18–20 g), each group containing four mice, were used to test each dose of venom for toxicity, and one group of five was used as a control. The mice were kept at room temperature where they had libitum access to rodent food and surface water throughout the experiment.The toxicity of venom from A. crassicauda , H. schach  and H. saulcyi  scorpion venoms were dissolved in 0.2 ml of PBS. The control group was injected with an equivalent volume of PBS only. The animals were monitored for 24 h and the LD50 was calculated by the graphical method of Miller and Tainter  method is used to determine amino acids in the venom of three medically important scorpion species.The HPLC–MS/MS system consists of an Agilent 1200 high‐performance liquid chromatography coupled with an Agilent 6430 series triple quadrupole mass spectrometer with an electrospray ionisation source. The chromatographic separation was achieved on a CORTECS C18 column  and the column temperature was kept at 30°C. Mobile phases which consisted of 0.1% formic acid in water (A) and acetonitrile (B) were used in the following gradient elution method: 0–10 min, 10–85% B; 10–13 min, 85–95% B; 13–19 min, 95–95% B. The flow rate was set at 0.3 ml/min, and the injection volume was 10 μl. All the data were analysed by Mass Hunter workstation software .The mass spectrometer was carried out in both positive and negative ionisation multiple reaction monitoring mode. The source parameters were as follows: the capillary voltage set at 300 V for positive ionisation mode and −300 V for negative ionisation mode, the drying gas temperature was 320°C, the flow was 11 L/min and nebulising gas pressure was 30 psi.2.6All reagents were of analytical grade; the solvents were of chromatographic purity and the water was purified by deionisation . Most of the standards were supplied by Fluka–Sigma–Aldrich . A few specific standards were supplied by Extrasynthèse , Radian International  and pharmaceutical laboratories participating in the Brazilian government DST/AIDS program. Ampholyte solutions in the pH range 6–8 and 3–10 were supplied by Amersham Pharmacia Biotech  and a 4% methylcellulose stock solution was supplied by Applied Biosystems .2.7Protein concentrations were determined by the Biuret method. In this technique, peptide bonds in proteins produce a violet colour in the presence of alkaline copper, and the intensity of the colour is estimated with a spectrometer at 540 nm wavelength.3DCE from Agilent Technologies. The P/ACE unit was equipped with a filter‐carrousel UV detector, while the HP3DCE unit was equipped with a diode array detector. Both systems had temperature control devices, maintained at 25–30°C and data acquisition and treatment software supplied by the manufacturer. Uncoated fused‐silica capillaries  were used in all experiments except for the haemoglobin analyses, where a dimethylpolysiloxane coated fused‐silica capillary  with dimensions of 27 cm total length, 20 cm effective length, 50 cm i.d. and 0.20 cm coating thickness was used. At the beginning of the day, regular capillaries were typically washed with a 1 mol L–1 NaOH solution , followed by deionised water (5 min) and electrolyte (30 min). In between runs, the capillaries were usually reconditioned by a flush with the electrolyte solution . At the beginning of the day, the coated capillary was conditioned by a flush of methanol followed by deionised water . In between runs, the coated capillary was just replenished with fresh ampholyte working solution (2 min flush). At the end of the day, the coated capillary was washed with deionised water, methanol and dried with a flush of nitrogen .All experiments were conducted in capillary electrophoresis systems, either model P/ACE 5510 from Beckman Instruments  or model HP2.8No statistical analysis was performed.33.1A. crassicauda, H. schach and H. saulcyi were collected from Esfahan Farm Scorpion Company and maintained in the laboratory in containers that mimic their natural habitat. They were captured carefully using long forceps by holding the tip of their tail without harming the animal. Scorpions were then transferred into separate containers with the soil of about two inches in depth upon which small stones were placed. The venom was extracted from A. crassicauda, H. schach and H. saulcyi by electrical stimulation (8 and 10 V).3.2Based on morphological characteristics such as body colour, pedipalp shape and size, sternum shape, telson colour and several pectin teeth, identified scorpions were presented in Table 3.3H. saulcyi venom in mice. Four doses were used for the experiment . At the end of the analyses, the LD50 obtained was 1.47 mg/kg b.w.Table H. schach venom on mice. Four doses were used for the experiment . At the end of the analyses, the LD50 obtained was 0.85 mg/kg b.w.Table A. crassicauda on mice. Four doses were used for the experiment . At the end of the analyses, the LD50 obtained was 1.70 mg/kg b.w.Table 50 recorded for the tested venoms were 1.47 mg/kg for H. saulcyi, 0.85 mg/kg for H. schach and 1.70 mg/kg for A. crassicauda. The venom of A. crassicauda thus presented the lowest toxicity and the highest toxicity was recorded for H. schach.The LD3.4A. crassicauda has few amino acids compared with the venom of H. saulcyi and H. schach. A. crassicauda venom does not contain allo‐isoleucine, cystathionine, homocitrulline, homocystine, hydroxylysine and hydroxyproline. Similarly, unlike H. schach, H. saulcyi does not contain traces of cystathionine and homocystin at all. H. saulcyi contains a concentration of hydroxylysine, whereas H. schach has no such concentration.None of the venoms studied contain argininosuccinic acid and sulfocysteine. The venom of A. crassicauda, H. saulcyi and H. schach contain 26, 30 and 31 amino acids, respectively, of which 7, 11 and 12 are in low concentrations , 5.4% (H. schach) and 4.4% (A. crassicauda). A. crassicauda had the lowest level of albumin. It should be noted that the albumin content in the different venoms was lower than that of the control group (61.1%) (Table A. crassicauda (0.05) followed by H. schach (0.06) and the highest was obtained with the venom of H. saulcyi (0.13). The most protein‐rich venoms were H. saulcyi (16.2%) and H. schach (16.26). The venom of A. crassicauda contains less proportion of proteins (14.8%) compared with those of H. schach and H. saulcyi.Albumin content in the venom was 11.7% . This voltage variability was noted by Nagaraj et al.  found that the LD,b found  Bonnet, . Also, I Bonnet,  reported Ismail, . InducedH. saulcyi venom was 0.73 mg/kg in mice , 5.4% (H. schach) and 4.4% (A. crassicauda). A. crassicauda had the lowest level of albumin. The lower albumin level recorded for A. crassicauda indicates its higher level of purity compared with other venoms. He showed a higher level of purity followed by those of H. schach and H. saulcyi, respectively. The low presence or absence of albumin in the venom expresses its higher level of purity . The results from this study show that H. saulcyi and H. schach contain more amino acids and protein and have higher toxicity than A. crassicauda. Furthermore, the venom of A. crassicauda has a high level of purity compared with the others. Note that toxicity, number of amino acids, protein content and degree of purity of scorpion venoms vary from one scorpion to another.The method adopted in this study for the maintenance of scorpions in the laboratory is efficient. The claustration device and electrical stimulation are significantly effective for the extraction of venom from scorpions of different species. The constitution of this study is important for researchers. This study could be useful for understanding the venom extraction and toxicity, the protein and amino acid diversities of three species of scorpions (Formal analysis, investigation, methodology and writing‐original draft: Ani Boghozian. Methodology, resources, supervision, validation, visualisation, writing‐review and editing: Habibollah Nazem. Conceptualisation, data curation, supervision, validation, visualisation, writing‐review and editing: Mohammad Fazilati. Formal analysis, investigation, methodology, project administration, writing‐review and editing: Seyed Hossein Hejazi. Methodology, validation, visualisation, writing‐review and editing: Mohammadreza Sheikh Sajjadieh.


NSD3 is one of six H3K36-specific lysine methyltransferases in metazoans, and the methylation of H3K36 is associated with active transcription. NSD3 is a member of the nuclear receptor-binding SET domain (NSD) family of histone methyltransferases together with NSD1 and NSD2, which generate mono- and dimethylated lysine on histone H3. NSD3 is mutated and hyperactive in some human cancers, but the biochemical mechanisms underlying such dysregulation are barely understood. In this review, the current knowledge of NSD3 is systematically reviewed. Finally, the molecular and functional characteristics of NSD3 in different tumor types according to the current research are summarized. In eukaryotes, DNA is assembled into a higher order nucleoprotein structure called chromatin. Besides the condensation of the DNA, chromatin poses a variety of different functions centered around the regulation of transcription, replication, DNA repair and recombination. The main unit of chromatin is the nucleosome consisting of 147 base pairs (bp) of DNA, which is wrapped around the histone octamer comprising two molecules of each core histone: H2A, H2B, H3 and H4 .In order to establish or maintain a cell-type-specific gene expression program, the chromatin structures need to be highly dynamic to allow access of transcription factors and other regulatory entities to the DNA at defined time points. These events are tightly regulated by post-translational modifications (PTMs) which are enriched at the unstructured and flexible N-terminal regions of the histone proteins. These histone tails protrude from the nucleosome core and are subject to a diverse array of PTMs, e.g., acetylation, phosphorylation, ubiquitination and methylation, often referred to as the “histone code” that extends the information potential of the genetic code ,7,8. TheHistone lysine methylation is among the best characterized PTM of the histone code and is attached to the basic side chains of lysine by a diverse set of sequence-specific lysine methyltransferases . HistoneNSD3 was first characterized in 2001 as the third member of the NSD gene family ,15. DespThe full-length (FL) members of the NSD family of histone methyltransferases are large multidomain proteins, which share most of the evolutionary conserved domains. They belong to the so-called SET domain-containing lysine-specific methyltransferases  and the Besides the SET domain FL-NSD family members contain two PWWP domains named after its central core Pro-Trp-Trp-Pro motif, a five plant homeo domains (PHD) and a Cys-His-rich domain (C5HCH) domain . CrystalNot much information is available about the specific roles of the other domains of NSD3, and most functions can only be roughly implied from information published for NSD1 and 2. The first N-terminal PWWP domains of NSD1 and 2 were shown to bind to methylated H3K36 to stabilize NSD2, and probably NSD1, at chromatin, and the catalytic SET domain of NSD2 propagates this gene-activating mark to adjacent nucleosomes ,25,26,27The PHD1-3 motifs of NSD2 were shown to be important for its H3K36me2 methylation activity. Specifically, the removal of PHD1 decreased H3K36me2 activity and PHD2 caused NSD2 localization into the cytoplasm, which resulted in a complete loss of activity . More deAll three members of the NSD family of histone H3K36 methyltransferases share most of the common motifs except NSD2, which contains a so-called high mobility group (HMG) domain. The HMG domain of NSD2 was shown to interact with the DNA-binding domain of the androgen receptor (AR), thereby enhancing the nuclear translocation of both proteins . Future The structure of the full-length NSD3 protein was never solved completely until now, due to its large protein size. An NSD3 construct containing amino acids 1054–1285, which spans the entire catalytic SET domain and additional residues on both sides without the reader domains, was crystallized in the presence of a histone H4 sequence flanking lysine 44 (H4K44), in which K44 was replaced by the unnatural amino acid norleucine (Nle) . The catThe recent cryo-EM studies provided a more detailed view on the importance of the nucleosome-bound DNA in the activation of NSD3 . NSD3 foFurthermore, the AWS domain extends into the core histones and contacts the H2A C-terminal fragment through hydrophobic and electrostatic interactions. These contacts result in an extended conformation of NSD3, rendering NSD3 catalytically active and contributing to the precise positioning of NSD3 to specifically bind H3K36. However, it is possible that the conformational states observed differ with the full-length protein when compared to truncated constructs, which could influence the regulation of the enzyme activity by the autoinhibitory loop. Additionally, the C-terminal part of NSD3 the crystal structure of the PWWP1 domain of NSD3 (residues 247–398) was solved and revealed a classical PWWP domain fold, as described previously ,38. An NThe catalytic activity of the NSD family of histone H3K36 methyltransferases is restricted to a lower degree methylation of H3K36, and a specificity for mono and dimethylation is observed ,40. The Apart from the regulation of their enzymatic activity through binding of the nucleosome and the resulting clearance of the catalytic site from the autoregulatory loop, all members of the NSD family of histone methyltransferases are inhibited in their activity by different post translational modifications (PTMs) on histones. The ubiquitination of histone H2A at Lys119 ,43 inhibNSD3 is ubiquitously expressed  and geneThe NSD3-short protein lacks the catalytic SET domain and only contains the amino-terminal PWWP domain  15] tha tha15] tBoth the NSD3-long and NSD3-short transcripts are co-expressed in many tissues ,15, wherAll NSD family proteins show methylation activity towards H3K36, which is restricted to mono and dimethylation ,40. NumeFurthermore, H3K36me2 is required for recruitment of DNMT3A and maintenance of DNA methylation at intergenic regions . Genome-Analogous to other known lysine methyltransferases , membersKnowledge about the function of NSD3 in individual diseases is sparse, and most of the information available is about its role in different tumors. NSD3 is located on chromosome 8p11.2, in a region which has been linked to various diseases and that is amplified in primary tumors and cell lines from breast carcinoma ,15. As wGenomic alterations of NSD3 occur in multiple cancer types, implicating its cancer-promoting role ,68. In mIn line with the function of NSD3-short as an adaptor protein of BRD4 and CHD8 , MLL-AF9In addition, the 8p11.2 region is amplified in many cancers , leadingThus far, only one non histone protein has been described, which is methylated by NSD3 . The epiFurthermore, over 260 mutations have been described within the NSD3 protein  and for Besides mutations in NSD3 itself, so-called onco-histones harboring mutations of the lysine at position 36 ,85,86,87Two recent publications shed more light on how altered NSD3 activity promotes tumor development and growth. These studies investigated the role of NSD3 in squamous cell lung cancer  and breaDespite the recent achievements in the structural and biochemical analyses of NSD3 in complex with the nucleosome, which provided a molecular basis for the nucleosomal preference and activation mechanism of NSD proteins, not much information is available on cellular functions of NSD3 itself. Nevertheless, the fact that the methylation of H3K36 plays such an important role in regulating enhancer activity ,60 and N


Spatial memory was evaluated by water Morris Maze 7 days post BCAS. After behavioral tests, neuronal apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling assay, and potential mechanisms were determined using western blotting and quantitative real-time PCR. Our results showed that GPR30 expression in the hippocampal region at mRNA level was promoted 30 min, 3 h, 6 h, and 24 h following BCAS. Ginsenoside Rg1  promoted GPR30 expression in the hippocampus of model mice  but did not alter GPR30 expression in the hippocampus of control mice. Moreover, treatment of ginsenoside Rg1 (10 mg/kg) or G1 (5 μg/kg), a GPR30 agonist, prevented BCAS-induced memory impairment and hippocampal neuronal loss and apoptosis and promoted the ratio of Bcl-2 to Bax expression in the hippocampus . On the contrary, G15 (185 μg/kg), an antagonist of GPR30, aggravated BCAS-induced hippocampal neuronal loss and apoptosis. Finally, drug-target molecular docking pointed that Rg1 had a lower binding energy with GPR30 compared with Bax and Bcl-2. Together, our data implicate that ginsenoside Rg1 prevents cognitive impairment and hippocampal neuronal apoptosis in VD mice, likely through promoting GPR30 expression. These results would provide important implications for the application of Rg1 in the treatment of VD.This study is aimed at investigating the potential roles of G protein-coupled estrogen receptor 1  in the preventive effect of ginsenoside Rg1 against cognitive impairment and hippocampal cell apoptosis in experimental vascular dementia (VD) in mice. The effects of bilateral common carotid artery stenosis (BCAS) on GPR30 expression at mRNA level were evaluated. Thereafter, the BCAS mouse model was utilized to evaluate the protection of Rg1 (0.1, 1, 10 mg/kg, 14 days,  Vascular dementia (VD) is a type of cognitive impairment syndrome caused by cerebral hypoperfusion or ischemic cerebrovascular diseases, which involves pathological changes in brain regions such as the hippocampus and cortex . VD patiPanax ginseng has been widely used to treat organic and psychosomatic diseases since ancient times [nt times . Ginsenont times . Pharmacnt times , 8. As ent times –11. Espent times . Intrigunt times , but leaG protein-coupled estrogen receptor 1  is a 7-transmembrane G protein-coupled receptor composed of 375 amino acids and has been identified as a new type of estrogen membrane receptor . The actGinsenoside Rg1 has a steroid hormone-like steroid skeleton structure, which could activate the estrogen receptor through its characteristics of estrogen to exert the neuroprotective function . Rg1 hasad libitum. All animal procedures were approved by the Ethics Committee of Anhui University of Chinese Medicine .Male C57BL/6J mice  were purchased from the Experimental Animal Center of Anhui Medical University (License number: SCXK (Wan) 2016-0009). The mice were kept in a room temperature of 22 ± 2°C and a relative humidity of 45-65% and experienced a 12 h light/dark cycle with food and water available Ginsenoside Rg1 was obtained from Yuanye Bio-Technology . GPR30 agonist (G1) and GPR30 inhibitor (G15) was purchased from Tocris . Rg1, G1, and G15 were dissolved in dimethyl sulfoxide (DMSO) and suspended in saline (DMSO concentration was lower than 0.1%), and the control group was injected with the same volume of normal saline.The mice were anesthetized with 1% sodium pentobarbital (45 mg/kg). Through a midline cervical incision, both common carotid arteries (CCA) were exposed and freed from their sheaths. Two 4–0 silk sutures were placed around the distal and proximal parts of the right CCA. Then, the artery was gently lifted by these sutures and placed between the loops of the microcoil just below the carotid bifurcation. The microcoil was twined by rotating it around the CCA. 30 minutes later, another microcoil of the same size was twined around the left CCA. The rectal temperature was maintained between 36.5°C and 37.5°C. The cessation of cerebral blood flow (CBF) for >1 minute was avoided. The diameters of the CCAs were measured under direct inspection with an operation microscope  just before applying the microcoils. In the sham group, only bilateral CCA was exposed and isolated after anesthesia, and then, the wound was sutured. The death rate of the animals during BCAS was about 22%, which was consistent with previous publication . There wN = 5) (The experiment was randomly divided into five groups (N = 5) : a sham N = 5) .N = 5 (The experiment was randomly divided into six groups (N = 5 : a sham N = 5) (μg/kg subcutaneously (sc)) and G15  per day for 7 consecutive days after modeling. The doses of G1 and G15 were selected by referring a previous publication [The experiment was randomly divided into five groups (N = 5) : a sham lication .MWM was performed one week after surgery to assess the behavioral performance between the different groups as previously described . On day -∆∆CT method as previously described [30 min, 3 h, 6 h, and 24 h after BCAS, the mice were anesthetized with isoflurane (5%) and decapitated. Thereafter, the hippocampi were isolated on ice. Total RNA was extracted with Trizol reagent (Takara Bio Inc.) and reversely transcription into cDNA using reverse transcription kit . Cycle parameters were as follows: initial denaturation at 95°C for 10 min, followed by 40 cycles of sequential incubations at 95°C for 15 s and at 60°C for 1 min. After the end of the cycle, the data was analyzed using the instrument's supporting software to obtain the cycle threshold . GPR30 expression was normalized to glyceraldehyde-3-phosphatedehydrogenase (GADPH) and calculated by the 2escribed . The priThe hippocampal tissues were added to protein lysis solution (RIPA: PMSF = 100: 1) and homogenized for lysis to detect the expression of Bax, Bcl-2, and GPR30. Protein samples were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis (12% gel) for 50 min at 120 V and transferred onto a nitrocellulose membrane for 2 h at 200 mA. The membranes were blocked with PBS containing 0.1% Tween-20 (PBST) and 5% fat-free milk for 2 h at room temperature. After blocking, the membrane was incubated with primary antibody against Bax , Danvers, MA, USA), Bcl-2 , and GPR30  at 4°C overnight. After being washed three times with PBST (3 × 10 min), the membranes were incubated with horseradish peroxidase-conjugated goat anti-rabbit IgG  2 h at room temperature. Finally, the membrane was developed with a chemiluminescent solution . ImageJ software was used to analyze the optical density of the bands.μm. Sections were blocked in 0.1 M phosphate-buffered saline (PBS) containing 10% goat serum and 0.4% TritonX-100 for 1 h and then incubated with a primary antibody against NeuN . Composition of the primary antibody dilution included PBS containing 0.3% Triton X-100 and 1% bovine serum albumin (BSA). The sections were washed 3 times in PBS (15 min each) and then incubated with goat anti-rabbit IgG H&L (Alexa Fluor® 488)  for 2 h at room temperature. The morphology of neurons in the hippocampus was observed under a microscope . ImageJ software was used to calculate the number of NeuN+ cells.The mouse brain was fixed in 4% paraformaldehyde for 24 h, cryoprotected in 30% sucrose for 24 h at 4°C, and sectioned on a freezing microtome at 20 μm. TUNEL stained was carried out according to the instructions of the TUNEL apoptosis detection kit . After staining, images were taken with an FV1000 Olympus confocal laser scanning microscope . ImageJ software was used to analyze the image and calculate the number of apoptotic cells.The mouse brain was fixed in 4% paraformaldehyde for 24 h, cryoprotected in 30% sucrose for 24 h at 4°C, and sectioned on a freezing microtome at 20 To verify the binding energy of ginsenoside Rg1 to target proteins, we monitored molecular docking between ginsenoside Rg1 and GPR30 (PDB ID 4X13), Bax (PDB ID 4S0O), and Bcl-2 (PDB ID 4CIM), respectively. We downloaded the 3D PDB format files of GPR30, BAX, and Bcl-2 from the PDB database and the 2D SDF of active ingredients from the PubChem database and imported the 2D structure into ChemBio3D14.0 software for structural optimization and revealed the 3D mol2 structure. Then, we imported the drug molecules and proteins into the AutoDock Tool for hydrogenation, charge calculation, atom addition, and ROOT docking. The algorithm was Local Search Parameters, and the lower the binding energy indicated, the better the docking result. We used Pymol software to analyze the docking result.P < 0.05 was considered significant.Data were presented as the mean ± standard error of mean (SEM) and analyzed with GraphPad Prism 5.0 software . One-way ANOVA followed by Bonferroni's test was applied to compare between-group differences. A value of P < 0.05), which suggested that the expression of GPR30 increased after the modeling of BCAS.The expression of GPR30 mRNA at 30 min, 3 h, 6 h, and 24 h after BCAS was detected. 30 min, 3 h, 6 h, and 24 h after establishment of BCAS, GPR30 expression at mRNA level in the hippocampus was higher than that in the sham group (P < 0.05). By contrast, in normal animals, treatment with ginsenoside Rg1 did not promote GPR30 expression in the hippocampus (P > 0.05).The results of qPCR and western blot suggested that the expression of GPR30 at both mRNA and protein levels in the hippocampus in the model group were significantly higher than those in the sham group Figures . CompareP < 0.05). These results suggested that G1 and Rg1 improved memory in BCAS model mice.We also tested spatial memory after Rg1 treatment. The learning trends among groups were not altered during training . HoweverP < 0.05).As the expression of GPR30 was most significantly increased in the high-dose ginsenoside group, the high-dose ginsenoside was selected in subsequent experiments. Additionally, GPR30 agonist (G1) and antagonist (G15) were selected to verify the functions of GPR30. Immunohistochemical staining results showed that BCAS modeling stimulated the loss of hippocampal neurons compared with the sham group Figures , while gP < 0.05). G15 further aggravated the apoptosis caused by BCAS modeling (P < 0.05).TUNEL staining showed that BCAS modeling caused apoptosis of hippocampal neurons compared with sham group, while ginsenoside Rg1 and G1 treatment improved neuronal apoptosis induced by BCAS modeling . The apoP < 0.05).Western blot results showed that the ratio of hippocampal Bcl-2/Bax of the model group mice decreased significantly compared with the sham group. Compared with the model group, the ratio of hippocampal Bcl-2/Bax of the Rg1 administration group and G1 group increased significantly (As ginsenoside Rg1 influenced GPR30, Bax, and Bcl-2 expression, we further investigated the possible relationships of Rg1 with GPR30, Bax, and Bcl-2. Molecular docking results showed that Rg1 had a lower binding energy with GPR30 than with Bax and Bcl-2 . BindingOur findings indicated that Rg1 improved memory in BCAS model mice. Notably, Rg1 increased the GPR30 level and ameliorated hippocampal neuronal loss and apoptosis. These data provided critical evidence supporting the protective effects of Rg1 on VD.Panax ginseng extract attenuates neuronal injury and cognitive deficits in VD rats [Ginseng has been used for thousands of years to treat aging and memory disorders . Panax g VD rats . Ginseno VD rats . Several VD rats , 35, 36. VD rats –39. Thus VD rats .In the CNS, estrogen has typical beneficial effects for trophic nerve, antioxidant, anti-inflammatory, and antiapoptosis . A previGinsenoside Rg1 has estrogen-like activity and may exert estrogenic effects via rapid activation of membrane-associated ER and GPR30 . Our stuBcl-2 gene family plays a decisive role in the process of apoptosis. It includes the antiapoptotic factor Bcl-2 and the proapoptotic factor Bax. Bcl-2 and Bax function as a dimer, and the ratio between the two determines the apoptosis [The hippocampus is an essential area in the brain associated with learning and memory –53. It hpoptosis . Our respoptosis , 59. Addpoptosis , 60, 61.In conclusion, ginsenoside Rg1 improves hippocampal neuronal injury in BCAS model mice, and GPR30 plays a pivotal role in vascular dementia. Our study would provide important implication for the application of Rg1 or the Chinese medicine with ginsenoside Rg1 as the major component in the treatment of VD.


The highest specific volume (1.47 ± 0.04 cm3 g−1) and the lowest hardness (40.97 ± 0.87 N) are observed in A30R70SL which seems to be induced by its potential to form gel. Acorn flour substitution level at 50% W/W adversely influenced the technological characteristics of final product and its perception by the consumer. Acorn flour substitution up to 30% W/W is preferred by the consumer which is attributed to its potential role to improve the unpleasant pale color of rice‐based gluten‐free products. A negatively significant correlation has been observed between the color perception by the consumer and crumb lightness .Textural, physicochemical, and sensory characteristics of rice‐based gluten‐free bread in the presence of acorn flour; inulin and different fermentation type (yeast starter fermentation [Y] or mixed fermentation based on sourdough [MF‐SD]) were investigated. Acorn flour was added to replace rice flour at a proportion of 10, 30, and 50% W/W. Furthermore, the mixture flour was replaced by inulin as a functional prebiotic ingredient at 10% W/W. Considering results obtained at this study, using mixed fermentation based on sourdough and inulin at 10% W/W provide the structure able to restore gases through baking process at formulations containing acorn flour at 30% W/W (A The influence of fermentation type and acorn flour substitution level on technological characteristics of rice‐based gluten‐free bread in the presence 10% W/W long chain inulin has been investigated. Acorn flour is influencive in improving the technological characteristics and consumer perception of gluten‐free bread. The optimum formulation from technological perspective is found at samples containing 10% W/W inulin and 30% W/W acorn flour and fermented by mixed fermentation based on sourdough. Exopolysaccharides produced by mixed fermentation based on sourdough facilitate the structure formation. Acorn flour  was provided from local market. Long‐chain inulin  was kindly donated from Akbarieh Company. The other constituents of gluten‐free breads  were purchased from local supermarkets. The required sodium hydroxide was also purchased from Merck Company for titration.2.2The influence of acorn flour replacement was investigated at three levels . Long‐chain inulin was replaced at 10% W/W in flour blends . The water absorption in each flour blend containing 10% W/W long‐chain inulin was determined by rheometer  adjustment to achieve an optimum dough consistency. In order to investigate the influence of fermentation types (yeast starter fermentation [Y] or mixed fermentation based on sourdough [MF‐SD]), the formulations were prepared as follow. The schematic diagram of gluten‐free bread preparation steps is declared in Figure 2.2.1Straight dough method was used to prepare YSF dough. Regarding, acorn: rice blend flour , containing 10% W/W long‐chain inulin were mixed by sugar, salt, oil, and active dry yeast at 0.5, 1, 3, and 2.2% W/W, respectively. The blends were then mixed with potable water at amounts as determined by rheometer. The mixture is shaped into dough then putted in baking pans and incubated for 4 h at temperature adjusted to 29±0.5℃. A piece of samples (30 g) was kept for rheological parameter determination and the other used for baking. The baking process is done in a convection oven  for 30 min at 220 ± 0.5℃   and complex modulus (G*) were determined as follow  using parallel plate geometry at 30℃. Dough sample pieces were rested for 5 min. Strain sweep test was carried out firstly to determine the linear viscoelastic region. Since results indicated the linear behavior of dough at strain lower than 0.1%, frequency sweep test was done at a range of 1–100 Hz at constant strain of 0.01%. The damping factor , nearly 1 h after leaving the oven . Then, total titratable acidity (TTA) was determined by titration with 0.1 N sodium hydroxide . Samples were placed in an air oven set at 105 ± 0.05℃, and the drying process was continued until the mass change of two weighing intervals of 15 min was less than 0.1% W/W. The moisture content was calculated as follow  according to a modified AACC Approved Method 74‐09 (2000). A piece of the crumb (20 × 20 × 25 mm) was pressed to 50% of its original height at speed of 1 mm/s with a 43 mm cylinder probe using 5 kg loading cell. The analysis was carried out in six replicates at 25 ± 3℃ on the bread slices. Hardness, cohesiveness, springiness, and chewiness of the crumb were calculated using Texture profile analysis curves , a* (green: negative and red: positive), and b* (blue: negative and yellow: positive) indices. White index (WI) was obtained based on the following formula  were used. In this regard, the crust and crumb color of each bread pieces were determined. Results were reported as 2.3.5Samples prepared at this study were sensory investigated using nine‐point hedonic scale with 1 indicative of very unpleasant, 5 acceptable, and 9 extremely pleasant samples. Assessment was done according to flavor, color, texture, and the overall acceptability by 30 semitrained panelists from students and staff  from school of public health, Shahid Sadoughi University of Medical Science. The panelist's good health and willingness to be participated has been considered. For sensory evaluation, the encoded bread sample slices were served randomly and plain water was served before and between testing  were used for sensory evaluation.33.1The viscoelastic characteristics of gluten‐free dough samples have been determined to investigate the influence of changes in formulations . It seems that protein degradation proposed by mixed fermentation based on sourdough has weaken the dough strength and consequently the complex modulus . The appearance and cross section of prepared samples are presented in Figure 3.2.1p ≤ .05). This finding showed that long‐chain inulin fortification of gluten‐free bread could produce a more shelf‐stable bread due to its lower moisture content ). However, reverse trend has been observed in A30R70SL and A10R90YL. The increase in moisture content of A30R70SL sample despite its lower water absorption ratio is supposed to be induced by the synergistic impacts of long‐chain inulin and exopolysaccharides produced by lactic acid bacteria to form gel with lower gelatinization temperature. The formation of gel will result in space restriction which reduced the cross linking of starch molecules to form an ordered structure, prevented the moisture migration in the gel, and consequently enhanced its water holding capacity. The increase in moisture content induced by MF‐SD fermentation type is dependent to the level of acorn flour incorporation. In other words, it was 2.25, 6.15, and 2.70% W/W at 10, 30, and 50% W/W acorn flour substitution, respectively. As acorn flour is considered as a rich source of dietary fiber, its enhancement up to 30% W/W facilitated the formation of gels. Increasing the acorn flour incorporation level to 50% W/W seems to decrease the potential of gel formation which is attributed to the dominance of gel inhibitory impacts of acorn flour as reported by Paciulli et al.  is considered as the key parameter in techno‐functional determination of bread. The acidification process in gluten‐free bread preparation depending on the type of fermentation and level of acorn flour used is presented in Figure 3.33 g‐1) (Table 30R70SL and A30R70Y(C) with no significant difference (p > .05). A gradual decrease has been observed via inulin inclusion in samples fermented by yeast starter. Korus et al. (The specific volume as an indicator of gas retention capacity of dough and its expansion ratio during the baking process (44) is reported in the range of 1.14–1.49 . The higher ability of MF‐SD to produce gases, which can be due to the synergistic effects of lactic acid bacteria on the metabolic activity of Saccharomyces cerevisiae, leads to more release of carbon dioxide gas . However, it has been increased by increasing the ratio of acorn flour incorporation from 30% W/W to 50% W/W (p ≤ .05). The lowest hardness in A30R70SL is coinciding with its higher specific volume compared to other samples. It seems to be induced through the effect of formulation on the specific volume . The increased hardness of A50R50SL is attributed to its higher moisture content which is similar to results obtained by Tsatsaragkou et al.  via inclusion of acorn flour at different ratio, incorporation of inulin at 10% W/W decreased the cohesiveness differently. The quantity of cohesiveness parameter is reported to be dependent to the formulation structure ). Results also indicated that using mixed fermentation based on sourdough can compensate the cohesiveness decrease induced by inulin incorporation which is attributed to its potential to produce exopolysaccharides and its synergistic impact to provide a gel‐like structure . As proteins play an important role in structural cohesiveness, the apparent decrease in protein content (7.36% W/W) (at high ratios of acorn flour) and the hydrolysis facilitated by of MF‐SD are considered as the main reasons in this regard /red (+), and blue (−)/yellow (+), respectively. While the crust is the surface brown layer of bread, the crumb is the white spongy structure under it  gluten‐free bread has been investigated and presented in Table e et al. . The cole et al. . Resultsp ≤ .05) which was similar to finding of Beltrão Martins, Gouvinhas, et al. .The sensory profile of breads prepared in this study is presented in Table 30R70SL containing 30% W/W acorn flour and 10% W/W inulin in the presence of MF‐SD. As no significant difference has been observed in flavor and color assessment resulting the type of fermentation process, its impact is evident in textural perception and overall acceptability. Considering the texture parameter, it seems that using MF‐SD which negatively influences the textural perception at formulations containing 10% W/W acorn flour improve the texture at those having higher quantity of acorn flour. The highest acceptability in texture perception is achieved by A30R70SL which is attributed to synergistic effect of gel formation by exopolysaccharides produced by MF‐SD and long‐chain inulin . On the other hand, chewiness was negatively correlated with the panelists' scores for texture . Moreover, the scores for color were significantly and negatively correlated with crumb lightness and crumb and crust white index .The correlation analysis of sensory perception and instrumental measurement through the current study has revealed that the specific volume and cohesiveness were positively correlated with sensory texture scores ; Project administration ; Writing‐original draft ; Writing‐review & editing . Mohammad Hassan Ehrampoush: Investigation ; Writing‐original draft ; Writing‐review & editing . Seyed Ali Yasini Ardakani: Investigation ; Writing‐original draft ; Writing‐review & editing . Farimah Shamsi: Investigation ; Writing‐original draft ; Writing‐review & editing . Neda Mollakhalili‐Meybodi: Project administration ; Visualization ; Writing‐original draft ; Writing‐review & editing .This study does not involve any human or animal testing. Written informed consent was obtained from all study participants. This study was approved by the Institutional Review Board of School of public health, Shahid Sadoughi University of Medical Sciences. Approval ID: IR.SSU.SPH.REC.1399.014.


PLOS One, 9, e99682) and refined by Nikolakopoulou et al . Six domains that affect the level of confidence in the NMA results are considered: (a) within‐study bias, (b) reporting bias, (c) indirectness, (d) imprecision, (e) heterogeneity, and (f) incoherence. CINeMA is freely available and open‐source and no login is required. In the configuration step users upload their data, produce network plots and define the analysis and effect measure. The dataset should include assessments of study‐level risk of bias and judgments on indirectness. CINeMA calls the netmeta routine in R to estimate relative effects and heterogeneity. Users are then guided through a systematic evaluation of the six domains. In this way reviewers assess the level of concerns for each relative treatment effect from NMA as giving rise to “no concerns,” “some concerns,” or “major concerns” in each of the six domains, which are graphically summarized on the report page for all effect estimates. Finally, judgments across the domains are summarized into a single confidence rating . In conclusion, the user‐friendly web‐based CINeMA platform provides a transparent framework to evaluate evidence from systematic reviews with multiple interventions.Network meta‐analysis (NMA) compares several interventions that are linked in a network of comparative studies and estimates the relative treatment effects between all treatments, using both direct and indirect evidence. NMA is increasingly used for decision making in health care, however, a user‐friendly system to evaluate the confidence that can be placed in the results of NMA is currently lacking. This paper is a tutorial describing the Confidence In Network Meta‐Analysis (CINeMA) web application, which is based on the framework developed by Salanti et al (2014,  The NMA found that the risk of diabetes was lower with ARB, and higher with diuretics than with placebo  and judgments on indirectness. Study‐level RoB would normally summarize considerations on selection, performance, attrition, detection, and reporting bias  rows for a T arm study. For binary outcomes, number of events and sample size per treatment arm and study should be provided. For continuous outcomes, means, standard deviations, and sample size per treatment arm and study are needed. Table The outcome can be binary or continuous and the format of the data can be either long or wide. Currently, other types of outcomes, for example, time to event or rate data, are not supported. In the long format each row represents a study treatment arm. For example, two‐arm studies occupy two rows, three‐arm studies occupy three rows, and so on. In the wide format each row represents a study treatment comparison. This corresponds to It might be that summary data are not available for each intervention group for each study. In this situation data can be imported in “inverse variance” format, where a comparison‐specific estimate of the relative treatment effect  and its standard error are reported  and outcome type (binary) and provides summary of the dataset: it includes 22 studies, 6 interventions, and 14 comparisons with direct data.3The “Configuration” tab is activated once the dataset has been uploaded and variable names have been successfully defined. In this tab the user needs to define the NMA analysis and is presented with a network plot. This page also allows users to evaluate only a subset of all possible intervention comparisons.3.1The network plot corresponding to the uploaded dataset is automatically drawn with equally sized nodes and edges. Users can choose to weight nodes and/or edges according to the sample size or the number of studies (under “Node size by” and “Edge width by”). Nodes can either be all blue or colored according to the proportion of studies with low (green), moderate (yellow), and high (red) RoB or indirectness (under “Node color by”). “Edge color by” dropdown menu allows coloring edges according to the most prevalent bias level within each comparison (“Majority RoB”), the average RoB of the included studies (“Average RoB”), or the maximum bias level within each comparison (“Highest RoB”); the respective categories for indirectness are also available . Different representations may be chosen according to users' interests: for example, “Highest RoB” or “Highest Indirectness” could be chosen when users are interested in viewing the worst pieces of evidence feeding into each comparison. The network plot image can be exported as a .png file using the “Save Plot” button. The outcome data appear next to the network plot. By clicking on a specific edge or node, the respective outcome data corresponding to that edge or node appear on the data table.3.2Here users are asked to choose whether to perform a fixed effect or a random effects NMA  and to define effect measure type (under “Effect measure”). For binary outcomes, the options “Odds Ratio,” “Risk Ratio,” and “Risk Difference” will appear, and for continuous outcomes the options “Mean Difference” and “Standardized Mean Difference.”3.3An NMA that compares several interventions produces estimates for all possible relative effects. However, it can be the case that not all of them are of interest . CINeMA offers the option to select which intervention comparisons are to be evaluated. Users should first select the interventions of interest and then specify whether they want to evaluate all the comparisons that contain these interventions (“Containing any of the above interventions”) or only the comparisons that are formed between the selected interventions (“Between the above interventions”). For example, in a network with four interventions A, B, C, and D selecting A and B with the “Containing any of the above interventions” option will result in evaluation of comparisons AB, AC, AD, BC, and BD . Selecting A and B with “Between the above interventions” option will result in evaluating a single comparison (AB). A list of the comparisons to be evaluated then appears. Note that the analysis is performed using all studies irrespective of whether a subset or all comparisons are evaluated.netmeta in R to estimate all relative effects from the network and a common heterogeneity parameter. The relative effects are found in the league table, which can be downloaded and saved as a .csv file (“Download league table”). Second, it calls an R function that calculates the contribution matrix (Papakonstantinou). The contribution matrix shows the percentage contribution of information from each study and each direct comparison (shown in columns) to the estimation of each relative effect (shown in rows). It is calculated using the flow decomposition method described in  and takes users to the “Within‐study bias” domain.3.4The results of selecting different options for weighting the network plot are shown in Figure 44.14.1.1The number of studies at low, moderate, and high RoB appears on the top of the page. CINeMA considers the per‐study contribution matrix in conjunction with RoB assessments to evaluate each relative treatment effect with respect to within‐study bias. A bar chart is drawn under the “Risk of bias contributions” section; each bar corresponds to an estimate of relative effect. Each bar also represents a reordering of a column of the per‐study contribution matrix, where studies with low, moderate, and high RoB have been grouped together and colored accordingly. Each study is represented by a colored area with white borders and is proportional to its contribution. Users can download the bar chart as a .png file using the “Save Chart” button.0.40×1+0.25×2+0.35×3=1.95 which rounds to 2 and leads to “Some concerns.” In this example the judgment for “Majority RoB” would be “No concerns” and for “Highest RoB” would be “Major concerns.”High RoB should be associated with “Major concerns,” moderate RoB with “Some concerns,” and low RoB with “No concerns.” However, for each relative effect a different combination of high, moderate, and low RoB studies contribute to the estimate. Under the bar graph, a dropdown menu offers three possible “rules” that can be used to summarize the RoB for each relative effect estimate and produce automated judgments. Options include “Majority RoB,” “Average RoB,” and “Highest RoB.” Choosing “Majority RoB” will lead to a level of concern according to the RoB with the greatest total percentage contribution . The “Highest RoB” will assign a level of concern determined by the highest RoB in each bar. Summarizing RoB assessments using “Average RoB” uses a weighted average score for each relative effect estimate according to the percentage contribution of studies at each bias level. For example, if the contributions from low (arbitrarily assigned a score of 1), moderate (score 2), and high (score 3) RoB studies are 40%, 25%, and 35% respectively, the total RoB score will be After selecting a rule, the boxes under the dropdown menu—which correspond to the each estimate of relative effects—are colored according to the level of concern, and judgments under each of the three rules are also given in the boxes. Manual change of judgments independently of the applied selection rule is possible; if a judgment is manually changed, the corresponding box is colored gray. “Reset” (the chosen rule) and “Proceed” (to “Reporting bias”) buttons also appear.4.1.2Figure 4.2The “Reporting bias” domain refers to biases that can occur due to publication bias, time‐lag bias, selective nonreporting bias, or any other bias that renders the included studies a nonrepresentative sample of the studies undertaken  as no rule for reporting bias is implemented. “Reset” and “Proceed” (to the “Indirectness” domain) buttons appear after initial population of judgments. We plan to develop the “Reporting bias” domain of CINeMA further in the months and years to come.4.3For the indirectness domain, similar to “Within‐study bias,” the summary shows how many studies have been characterized as of low, moderate, and high indirectness at the top of the page. Subsequently, a bar graph shows the contribution of studies at each indirectness level to each NMA estimate. As for the “Within‐study bias” domain, users can select between “Majority,” “Average,” and “Highest” rules to summarize indirectness for each relative effect estimate. Areas are colored accordingly, while judgments under each rule are shown in the boxes. Manual changes can be made, and “Reset” and “Proceed” (to the “Imprecision” domain) buttons appear.4.4In the CINeMA framework, imprecision is assessed by 95% confidence intervals which may include values that could lead to different clinical conclusions. The calculation of 95% confidence intervals uses the variances of the treatment effects, estimated using maximum likelihood methods, and assumes that treatment effects approximately follow the normal distribution. To judge “Imprecision,” users are asked to define a clinically important size of effect on the scale of the selected effect measure. After pressing “Set,” the range of values to be considered as clinically important appear. The clinically important value and its reciprocal value separate the range of effects into three sets. Between them are effect sizes that favor neither of the compared interventions; on the left and right sides of the two clinically important values one of the two compared interventions is favored. Note that the observed point estimate favors one of the two interventions unless it is exactly on the no‐effect line.The rules for judging imprecision are based on whether the confidence interval includes the line of no‐effect and the clinically important values. If the confidence interval crosses the line of no‐effect and extends to values that favor the opposite intervention to that favored by the point estimate, “Major concerns” is assigned Figure . If onlyAfter defining the clinically important size of effect, the boxes of the relative treatment effects appear colored according to the default rules described above. Boxes display the 95%  confidence intervals of the NMA effect, a description of its relation to the clinically important effects, and the judgment, which can be manually altered. Users can also reset the definition of the clinically important size of effect and/or the imprecision judgments with the relevant buttons. The “Proceed” button leads the user to the “Heterogeneity” domain.4.4.1For illustration, we choose an odds ratio of 1.2 as clinically important and CINeMA informs us that “relative effect estimates below 0.83 and above 1.2 are considered clinically important.” The confidence interval for the comparison between diuretics and placebo ranges from 1.12 to 1.57, which corresponds to case 3 Figure 4.5The importance of heterogeneity depends on the variability of effects (beyond chance) in relation to the clinically important size of effect. The clinically important size of effect is the same as in “Imprecision”; if already specified it will automatically appear on the top of “Heterogeneity.” Otherwise, users need to specify it here; if this is the case, it will also be copied to the “Imprecision” domain. Users can press “Reset” to reset the clinically important effect size; note that this will affect the “Imprecision” domain too.μˆ+tdfaτ2+se(μˆ)2 where μˆ is the NMA treatment effect, se(μˆ) its standard error and tdfa the 100(1−a2)% percentile of the t dustribution with df degrees of freedom. We judge the agreement of conclusions based on confidence and prediction intervals in relation to the null effect and the clinically important effect on the opposite direction to the point estimate Our judgments based on a hypothetical, clinically important odds ratio of 0.8 are summarized and illustrated in Table CINeMA considers the agreement between confidence and prediction intervals to assign a judgment for “Heterogeneity” for each NMA effect. Prediction intervals provide a range within which the true effect of a new study is likely to lie  and reference values for τ2 . The reference quantiles are taken from empirical studies and are specific to the type of outcome and comparison  has already been specified as clinically important. CINeMA reports that “The estimated value of between‐study variance for the network meta‐analysis is 0.016.” The comparison of beta blockers with placebo is judged as case 3 Figure 4.6χ2, degrees of freedom, and p value) are shown on the top of the “Incoherence” page. In each box, the results of the second method, Separating Indirect from Direct Evidence p value from SIDE greater than 0.10 are assigned “No concerns.”Effect estimates based on both direct and indirect evidence and with a (2)p value from SIDE <0.10, areas a, b, and c are defined as illustrated in Figure To assign judgments for effect estimates with both direct and indirect evidence and with a (3)p value of the design‐by‐treatment interaction test: if the p value is <0.05 then “Major concerns,” if between 0.05 and 0.10 then “Some concerns,” otherwise “No concerns.” If the design‐by‐treatment interaction test is not estimable (because the network does not have any closed loop of evidence) then “Major concerns” are assigned to all comparisons.Effect estimates based only on direct evidence or indirect evidence are assigned a judgment determined by the The rules used to produce automatic judgments are as follow:As with other domains, judgments can be updated manually and a “Reset” and “Proceed” (to “Report”) button appear if clinically important size of effect is set.4.6.1As in case 5 of Figure 5The “Report” page brings together all the judgments for the six domains across all evaluated treatment effects. Relative effects informed by only direct or both direct and indirect evidence are shown first, followed by relative effects informed only by indirect evidence. A thick gray left border line appears for judgments whose automatically generated judgments have been manually modified. Users can visit the “Report” page as soon as at least one domain has been assessed. If users wish to summarize judgments across domains, the “Confidence rating” dropdown menu can be used to manually assign an overall level of confidence to each relative effect. The default judgment is “High” confidence; downgrading by one, two, or three levels will lead to a confidence rating of “Moderate,” “Low,” or “Very low” respectively. We recommend considering judgments on different domains jointly rather than in isolation . The “Report” page will be updated so that users can click on each comparison by domain judgment and decide whether they will downgrade their confidence or not, and if yes, for one or two levels.Subjectivity is inevitable in any process or system evaluating evidence, and CINeMA is no exception. Several aspects of the evaluations such as interpretation of heterogeneity and definition of a clinically important size of effect are clearly subjective. A study to examine CINeMA's reproducibility by measuring the agreement between assessments made by researchers using CINeMA would be of interest. The clearly defined criteria on which judgments are based should increase reproducibility and the fact that CINeMA is open‐source ensures transparency.Evidence synthesis is used by organizations to take decisions about whether to reimburse a medicinal product, by clinical guideline panels to recommend one drug over another, and by clinicians to prescribe an intervention or recommend a diagnostic procedure. CINeMA is a transparent framework to evaluate evidence from systematic reviews with multiple interventions, and we hope that the software presented here will facilitate its uptake.