Karyosystematics of Kol tooth-carp, Aphanius darabensis (Teleostei: Cyprinodontidae)

The karyological and cytological characteristics of an endemic cyprinodont fish of Iran, Aphanius darabensis Esmaeili, Teimori, Gholami & Reichenbacher, 2014 have been investigated for the first time by examining metaphase chromosomes spreads obtained from gill epithelial and kidney cells. The diploid chromosome number of A. darabensis is 48. The karyotype consisted of five submetacentric and 19 subtelocentric pairs of chromosomes (5sm+19st). The fundamental number (FN) is 58. Sex chromosomes were cytologically indistinguishable in this tooth-carp. According to this study and previous karyological reports from other cyprinodont species, it can be suggested that the diploid number (2n=48) is common amongst cyprinodont fishes. These results can be used as basic informations in population studies and management and conservation programs

An Introduction to Avicenna’s thoughts on Educational Methods

The goal for this article is to express the views proposed by Avicenna regarding the methods for training and education. The current study has taken advantage of a qualitative approach with a qualitative-analytical method, and has analyzed and inferred the views held by Avicenna regarding education and civilizing methods. The educational methods inferred from his perspectives are as follows: The education method as in collective-cooperative, observation-experiment and examination (the opportunity for practical learning), the rewarding and punishment method for the learners and the rules and notes with that respect, modeling methods, repetition and practice of the learned materials, discussion and debate methods, questioning and answering methods, memorizing and retaining the information, ways to advise and guide the learners, game plays, self-discipline, moral refinement, and finally declaring love for the learners. Key Words: Moslem Scientist, Avicenna, Method, training.

Study Of Wave-Induced Scour Depth Around Group Of Piles Using Support Vector Machines

Various arrangements of pile groups are widely being used as supports of marine structures. As piles are located on erodible beds of the sea, scouring is a threat to such structures and the scour depth amounts should be considered well in their designs. Though most of these supports are constructed in form of groups of piles, majority of studies were concentrated on predictions of scouring around single piles whereas the arrangement of the piles and the spaces between them in arrangements as well as their geometry, sediment and wave characteristics should also be studied. Despite the importance of the scour hole depths, the existing prediction formulas are not capable of accurate estimations around pile groups with different arrangements. Hence, developing a robust model for the estimation of scour depth seems necessary. One of the most common approaches as an alternative to empirical ones is the soft computing methods. Artificial Neural Network as the most famous data-mining method has been successfully applied in scour studies. But there are still needs of more assessments in their applications on pile group case studies. In addition, Support Vector Machines as one of the recently applied soft computing models in scouring has scarcely been studied so far. In this study, series of large scale scouring experiments were done for various arrangements of pile groups with different pile and arrangement characteristics exposed to waves of shallow water and equilibrium scour depth around them were measured in wave basin of Ujigwa Open Laboratory of Kyoto University. Finally, by applying the provided experimental data, the applicability of data mining models were assessed in predictions of pile group scour properties. Results indicate that, data mining approaches can provide more reliable predictions of scouring properties due to waves compared to current available empirical formulae

Advancing sustainability in the food and nutrition system: a review of artificial intelligence applications

Promoting sustainability in food and nutrition systems is essential to address the various challenges and trade-offs within the current food system. This imperative is guided by key principles and actionable steps, including enhancing productivity and efficiency, reducing waste, adopting sustainable agricultural practices, improving economic growth and livelihoods, and enhancing resilience at various levels. However, in order to change the current food consumption patterns of the world and move toward sustainable diets, as well as increase productivity in the food production chain, it is necessary to employ the findings and achievements of other sciences. These include the use of artificial intelligence-based technologies. Presented here is a narrative review of possible applications of artificial intelligence in the food production chain that could increase productivity and sustainability. In this study, the most significant roles that artificial intelligence can play in enhancing the productivity and sustainability of the food and nutrition system have been examined in terms of production, processing, distribution, and food consumption. The research revealed that artificial intelligence, a branch of computer science that uses intelligent machines to perform tasks that require human intelligence, can significantly contribute to sustainable food security. Patterns of production, transportation, supply chain, marketing, and food-related applications can all benefit from artificial intelligence. As this review of successful experiences indicates, artificial intelligence, machine learning, and big data are a boon to the goal of sustainable food security as they enable us to achieve our goals more efficiently

The Effect of Diabetes on Induced Pain of Formalin and Baclofen Analgesia in Rats

One of the side effects of dibetecs epidemics today in the world is painfulneuropathy, the reasons and treatments of which are unknown. Duo to the importance of problem of pain treatment as on of the harmful phenomena in life, this research studies the effect of continued diabetes on the formalin induced pain and baclofen analgesia in rats. Moreover the effect of baclofen as a non-opiate, analgesic drug on the increased pains in the quiescent phase as the model of diabetic pain is investigated. The method is experimental, evaluating the pain level through conducting the formalin test in 3 groups of rats. The first group was divided to control (injection normal salin) and diabetc (injection aloxan 100mg per kg) which were tested, after one to four weeks from the begining of diabetes, the second one was divided to a new control and diabetic group, and before performing formalin test, the baclofen(10mg per kg) was injected to them. And the third one was divided to two diabetics groups that received baclofen and normal salin and then the pain of the quiescent phase was compared in them. The results indicate that diabetes increases formalin induced pain and remained with continud diabetes. It also indicate that diabetes establishes increased pain in the quiscent phase , yet, it has had no influene  on the baclofen analgesic effect on the first phase of formalin test but increased it on the second phase. Moreover baclofen can quiet the increased pain in quiscent phase very well. Duo to the results of this study it seems that diabetes, with changes in the centeral and peripheral pathways of the pain and also pain control, increases the pain. More studies are required to determining its mechanisms. These changes are accompanied with weakening the internal antipain systems such as Gaba ergic, which can be treated with baclofen . Diabetes has no intraction with the baclofen  analgesics effect, so, baclofen may be recommended as an effective drug to comfort painful diabetic neurophathy.  

Use of biotin targeted methotrexate–human serum albumin conjugated nanoparticles to enhance methotrexate antitumor efficacy

Biotin molecules could be used as suitable targeting moieties in targeted drug delivery systems against tumors. To develop a biotin targeted drug delivery system, we employed human serum albumin (HSA) as a carrier. Methotrexate (MTX) molecules were conjugated to HSA. MTX-HSA nanoparticles (MTX-HSA NPs) were prepared from these conjugates by cross-linking the HSA molecules. Biotin molecules were then conjugated on the surface of MTX-HSA NPs. The anticancer efficacy of biotin targeted MTX-HSA NPs was evaluated in mice bearing 4T1 breast carcinoma. A single dose of biotin targeted MTX-HSA NPs showed stronger in vivo antitumor activity than non-targeted MTX-HSA NPs and free MTX. By 7 days after treatment, average tumor volume in the biotin targeted MTX-HSA NPs-treated group decreased to 17.6% of the initial tumor volume when the number of attached biotin molecules on MTX-HSA-NPs was the highest. Average tumor volume in non-targeted MTX-HSA NPs-treated mice grew rapidly and reached 250.7% of the initial tumor volume. Biotin targeted MTX-HSA NPs increased the survival of tumor-bearing mice to 47.5 ± 0.71 days and increased their life span up to 216.7%. Mice treated with biotin targeted MTX-HSA NPs showed slight body weight loss (8%) 21 days after treatment, whereas non-targeted MTX-HSA NPs treatment at the same dose caused a body weight loss of 27.05% ± 3.1%

Trefoil Factor Family in Pre-neoplastic Lesions and Gastric Cancer

Gastric cancer is the fourth most common cancer and the second leading cause of cancer death worldwide. Although the global incidence of gastric cancer has been decreased dramatically in recent decades, north and northwest of Iran have the highest incidence rate of gastric cancer. Whilst the surgical procedures for gastric cancer have been improved, there is no cure for that. The intestinal type of GC results from pre-neoplastic conditions including atrophic gastritis, intestinal metaplasia and dysplasia. Trefoil Factors Family proteins (TFFs) are small and stable molecules secreted by the mammalian gastrointestinal tract. TFFs constitute a family of three peptides (TFF1, TFF2and TFF3) that are widely expressed in a tissue specific manner in the gastrointestinal tract. Variable TFFs expression in gastric cancer and pre-neoplastic lesions has been found. TFF1 has a tumor suppressor activity and inhibits tumorogenesis in gastric cancer. Its expression decreases in gastritis, gastric atrophy, dysplasia, intestinal metaplasia and gastric cancer.TFF2 has a protective effect on gastrointestinal epithelium. As a prognostic factor, TFF2 expression decreases in gastric ulcer, chronic atrophic gastritis and gastric cancer. TFF3 is considered as an oncogenic factor in gastric tissues. Whilst the normal gastric tissues don’t express TFF3, it increases in intestinal metaplasia. Therefore, more studies are necessary to clarify the role of TFFs in GC and pre-neoplastic conditions. This review has focused on elucidating the important role of TFFs in gastric cancer and pre-neoplastic lesions

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

異なる頭部形状を有する連続した水制工周辺の流れと土砂輸送に関する研究

京都大学0048新制・課程博士博士(工学)甲第18560号工博第3921号新制||工||1602(附属図書館)31460京都大学大学院工学研究科社会基盤工学専攻(主査)教授 中川 一, 教授 藤田 正治, 准教授 川池 健司学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDFA