Nazarbayev University

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world's rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.

This article discusses a general framework for smoothing parameter estimation for models with regular likelihoods
\nconstructed in terms of unknown smooth functions of covariates. Gaussian random effects and
\nparametric terms may also be present. By construction the method is numerically stable and convergent,
\nand enables smoothing parameter uncertainty to be quantified. The latter enables us to fix a well known
\nproblem with AIC for such models, thereby improving the range of model selection tools available. The
\nsmooth functions are represented by reduced rank spline like smoothers, with associated quadratic penalties
\nmeasuring function smoothness. Model estimation is by penalized likelihood maximization, where
\nthe smoothing parameters controlling the extent of penalization are estimated by Laplace approximate
\nmarginal likelihood. The methods cover, for example, generalized additive models for nonexponential family
\nresponses (e.g., beta, ordered categorical, scaled t distribution, negative binomial and Tweedie distributions),
\ngeneralized additive models for location scale and shape (e.g., two stage zero inflation models, and
\nGaussian location-scale models), Cox proportional hazards models and multivariate additive models. The
\nframework reduces the implementation of new model classes to the coding of some standard derivatives
\nof the log-likelihood. Supplementary materials for this article are available online.

Zebrafish (Danio rerio) are rapidly gaining popularity in translational neuroscience and behavioral research. Physiological similarity to mammals, ease of genetic manipulations, sensitivity to pharmacological and genetic factors, robust behavior, low cost, and potential for high-throughput screening contribute to the growing utility of zebrafish models in this field. Understanding zebrafish behavioral phenotypes provides important insights into neural pathways, physiological biomarkers, and genetic underpinnings of normal and pathological brain function. Novel zebrafish paradigms continue to appear with an encouraging pace, thus necessitating a consistent terminology and improved understanding of the behavioral repertoire. What can zebrafish 'do', and how does their altered brain function translate into behavioral actions? To help address these questions, we have developed a detailed catalog of zebrafish behaviors (Zebrafish Behavior Catalog, ZBC) that covers both larval and adult models. Representing a beginning of creating a more comprehensive ethogram of zebrafish behavior, this effort will improve interpretation of published findings, foster cross-species behavioral modeling, and encourage new groups to apply zebrafish neurobehavioral paradigms in their research. In addition, this glossary creates a framework for developing a zebrafish neurobehavioral ontology, ultimately to become part of a unified animal neurobehavioral ontology, which collectively will contribute to better integration of biological data within and across species.

Skin wounds greatly affect the global healthcare system, creating a substantial burden on the economy and society. Moreover, the situation is exacerbated by low healing rates, which in fact are overestimated in reports. Cutaneous wounds are generally classified into acute and chronic. The immune response plays an important role during acute wound healing. The activation of immune cells and factors initiate the inflammatory process, facilitate wound cleansing and promote subsequent tissue healing. However, dysregulation of the immune system during the wound healing process leads to persistent inflammation and delayed healing, which ultimately result in chronic wounds. The microenvironment of a chronic wound is characterized by high quantities of pro-inflammatory macrophages, overexpression of inflammatory mediators such as TNF-α and IL-1β, increased activity of matrix metalloproteinases and abundance of reactive oxygen species. Moreover, chronic wounds are frequently complicated by bacterial biofilms, which perpetuate the inflammatory phase. Continuous inflammation and microbial biofilms make it very difficult for the chronic wounds to heal. In this review, we discuss the role of innate and adaptive immunity in the pathogenesis of acute and chronic wounds. Furthermore, we review the latest immunomodulatory therapeutic strategies, including modifying macrophage phenotype, regulating miRNA expression and targeting pro- and anti-inflammatory factors to improve wound healing.

The zinc-ion battery (ZIB) is a 2 century-old technology but has recently attracted renewed interest owing to the possibility of switching from primary to rechargeable ZIBs. Nowadays, ZIBs employing a mild aqueous electrolyte are considered one of the most promising candidates for emerging energy storage systems (ESS) and portable electronics applications due to their environmental friendliness, safety, low cost, and acceptable energy density. However, there are many drawbacks associated with these batteries that have not yet been resolved. In this Review, we present the challenges and recent developments related to rechargeable ZIB research. Recent research trends and directions on electrode materials that can store Zn2+ and electrolytes that can improve the battery performance are comprehensively discussed.

Background: Arterial hypertension and its organ sequelae show characteristics of T cell–mediated inflammatory diseases. Experimental anti-inflammatory therapies have been shown to ameliorate hypertensive end-organ damage. Recently, the CANTOS study (Canakinumab Antiinflammatory Thrombosis Outcome Study) targeting interleukin-1β demonstrated that anti-inflammatory therapy reduces cardiovascular risk. The gut microbiome plays a pivotal role in immune homeostasis and cardiovascular health. Short-chain fatty acids (SCFAs) are produced from dietary fiber by gut bacteria and affect host immune homeostasis. Here, we investigated effects of the SCFA propionate in 2 different mouse models of hypertensive cardiovascular damage. Methods: To investigate the effect of SCFAs on hypertensive cardiac damage and atherosclerosis, wild-type NMRI or apolipoprotein E knockout–deficient mice received propionate (200 mmol/L) or control in the drinking water. To induce hypertension, wild-type NMRI mice were infused with angiotensin II (1.44 mg·kg –1 ·d –1 subcutaneous) for 14 days. To accelerate the development of atherosclerosis, apolipoprotein E knockout mice were infused with angiotensin II (0.72 mg·kg –1 ·d –1 subcutaneous) for 28 days. Cardiac damage and atherosclerosis were assessed using histology, echocardiography, in vivo electrophysiology, immunofluorescence, and flow cytometry. Blood pressure was measured by radiotelemetry. Regulatory T cell depletion using PC61 antibody was used to examine the mode of action of propionate. Results: Propionate significantly attenuated cardiac hypertrophy, fibrosis, vascular dysfunction, and hypertension in both models. Susceptibility to cardiac ventricular arrhythmias was significantly reduced in propionate-treated angiotensin II–infused wild-type NMRI mice. Aortic atherosclerotic lesion area was significantly decreased in propionate-treated apolipoprotein E knockout–deficient mice. Systemic inflammation was mitigated by propionate treatment, quantified as a reduction in splenic effector memory T cell frequencies and splenic T helper 17 cells in both models, and a decrease in local cardiac immune cell infiltration in wild-type NMRI mice. Cardioprotective effects of propionate were abrogated in regulatory T cell–depleted angiotensin II–infused mice, suggesting the effect is regulatory T cell–dependent. Conclusions: Our data emphasize an immune-modulatory role of SCFAs and their importance for cardiovascular health. The data suggest that lifestyle modifications leading to augmented SCFA production could be a beneficial nonpharmacological preventive strategy for patients with hypertensive cardiovascular disease.

Homo naledi is a previously-unknown species of extinct hominin discovered within the Dinaledi Chamber of the Rising Star cave system, Cradle of Humankind, South Africa. This species is characterized by body mass and stature similar to small-bodied human populations but a small endocranial volume similar to australopiths. Cranial morphology of H. naledi is unique, but most similar to early Homo species including Homo erectus, Homo habilis or Homo rudolfensis. While primitive, the dentition is generally small and simple in occlusal morphology. H. naledi has humanlike manipulatory adaptations of the hand and wrist. It also exhibits a humanlike foot and lower limb. These humanlike aspects are contrasted in the postcrania with a more primitive or australopith-like trunk, shoulder, pelvis and proximal femur. Representing at least 15 individuals with most skeletal elements repeated multiple times, this is the largest assemblage of a single species of hominins yet discovered in Africa.

) and is exposed to innumerable microorganisms from the mother as well as the surrounding environment. Concurrently, the host responses to these microbes during early life manifest during the development of an otherwise hitherto immature immune system. The human gut microbiome, which comprises an extremely diverse and complex community of microorganisms inhabiting the intestinal tract, keeps on fluctuating during different stages of life. While these deviations are largely natural, inevitable and benign, recent studies show that unsolicited perturbations in gut microbiota configuration could have strong impact on several features of host health and disease. Our microbiota undergoes the most prominent deviations during infancy and old age and, interestingly, our immune health is also in its weakest and most unstable state during these two critical stages of life, indicating that our microbiota and health develop and age hand-in-hand. However, the mechanisms underlying these interactions are only now beginning to be revealed. The present review summarizes the evidences related to the age-associated changes in intestinal microbiota and vice-versa, mechanisms involved in this bi-directional relationship, and the prospective for development of microbiota-based interventions such as probiotics for healthy aging.

BACKGROUND: Electroencephalography (EEG)-based brain-computer interface (BCI) systems are mainly divided into three major paradigms: motor imagery (MI), event-related potential (ERP), and steady-state visually evoked potential (SSVEP). Here, we present a BCI dataset that includes the three major BCI paradigms with a large number of subjects over multiple sessions. In addition, information about the psychological and physiological conditions of BCI users was obtained using a questionnaire, and task-unrelated parameters such as resting state, artifacts, and electromyography of both arms were also recorded. We evaluated the decoding accuracies for the individual paradigms and determined performance variations across both subjects and sessions. Furthermore, we looked for more general, severe cases of BCI illiteracy than have been previously reported in the literature. RESULTS: Average decoding accuracies across all subjects and sessions were 71.1% (± 0.15), 96.7% (± 0.05), and 95.1% (± 0.09), and rates of BCI illiteracy were 53.7%, 11.1%, and 10.2% for MI, ERP, and SSVEP, respectively. Compared to the ERP and SSVEP paradigms, the MI paradigm exhibited large performance variations between both subjects and sessions. Furthermore, we found that 27.8% (15 out of 54) of users were universally BCI literate, i.e., they were able to proficiently perform all three paradigms. Interestingly, we found no universally illiterate BCI user, i.e., all participants were able to control at least one type of BCI system. CONCLUSIONS: Our EEG dataset can be utilized for a wide range of BCI-related research questions. All methods for the data analysis in this study are supported with fully open-source scripts that can aid in every step of BCI technology. Furthermore, our results support previous but disjointed findings on the phenomenon of BCI illiteracy.

This article discusses a general framework for smoothing parameter estimation for models with regular likelihoods constructed in terms of unknown smooth functions of covariates. Gaussian random effects and parametric terms may also be present. By construction the method is numerically stable and convergent, and enables smoothing parameter uncertainty to be quantified. The latter enables us to fix a well known problem with AIC for such models, thereby improving the range of model selection tools available. The smooth functions are represented by reduced rank spline like smoothers, with associated quadratic penalties measuring function smoothness. Model estimation is by penalized likelihood maximization, where the smoothing parameters controlling the extent of penalization are estimated by Laplace approximate marginal likelihood. The methods cover, for example, generalized additive models for nonexponential family responses (e.g., beta, ordered categorical, scaled t distribution, negative binomial and Tweedie distributions), generalized additive models for location scale and shape (e.g., two stage zero inflation models, and Gaussian location-scale models), Cox proportional hazards models and multivariate additive models. The framework reduces the implementation of new model classes to the coding of some standard derivatives of the log-likelihood. Supplementary materials for this article are available online.

It is commonly thought that human genetic diversity in non-African populations was shaped primarily by an out-of-Africa dispersal 50-100 thousand yr ago (kya). Here, we present a study of 456 geographically diverse high-coverage Y chromosome sequences, including 299 newly reported samples. Applying ancient DNA calibration, we date the Y-chromosomal most recent common ancestor (MRCA) in Africa at 254 (95% CI 192-307) kya and detect a cluster of major non-African founder haplogroups in a narrow time interval at 47-52 kya, consistent with a rapid initial colonization model of Eurasia and Oceania after the out-of-Africa bottleneck. In contrast to demographic reconstructions based on mtDNA, we infer a second strong bottleneck in Y-chromosome lineages dating to the last 10 ky. We hypothesize that this bottleneck is caused by cultural changes affecting variance of reproductive success among males.

Teleparallel gravity (TG) has significantly increased in popularity in recent decades, bringing attention to Einstein's other theory of gravity. In this Review, we give a comprehensive introduction to how teleparallel geometry is developed as a gauge theory of translations together with all the other properties of gauge field theory. This relates the geometry to the broader metric-affine approach to forming gravitational theories where we describe a systematic way of constructing consistent teleparallel theories that respect certain physical conditions such as local Lorentz invariance. We first use TG to formulate a teleparallel equivalent of general relativity (GR) which is dynamically equivalent to GR but which may have different behaviors for other scenarios, such as quantum gravity. After setting this foundation, we describe the plethora of modified teleparallel theories of gravity that have been proposed in the literature. We attempt to connect them together into general classes of covariant gravitational theories. Of particular interest, we highlight the recent proposal of a teleparallel analogue of Horndeski gravity which offers the possibility of reviving all of the regular Horndeski contributions. In the second part of the Review, we first survey works in teleparallel astrophysics literature where we focus on the open questions in this regime of physics. We then discuss the cosmological consequences for the various formulations of TG. We do this at background level by exploring works using various approaches ranging from dynamical systems to Noether symmetries, and more. Naturally, we then discuss perturbation theory, firstly by giving a concise approach in which this can be applied in TG theories and then apply it to a number of important theories in the literature. Finally, we examine works in observational and precision cosmology across the plethora of proposal theories. This is done using some of the latest observations and is used to tackle cosmological tensions which may be alleviated in teleparallel cosmology. We also introduce a number of recent works in the application of machine learning to gravity, we do this through deep learning and Gaussian processes, together with discussions about other approaches in the literature.

Viral infections contribute as a cause of 15-20% of all human cancers. Infection by oncogenic viruses can promote different stages of carcinogenesis. Among many types of HPV, around 15 are linked to cancer. In spite of effective screening methods, cervical cancer continues to be a major public health problem. There are wide differences in cervical cancer incidence and mortality by geographic region. In addition, the age-specific HPV prevalence varies widely across different populations and showed two peaks of HPV positivity in younger and older women. There have been many studies worldwide on the epidemiology of HPV infection and oncogenic properties due to different HPV genotypes. However, there are still many countries where the population-based prevalence has not yet been identified. Moreover, cervical cancer screening strategies are different between countries. Organized cervical screening programs are potentially more effective than opportunistic screening programs. Nevertheless, screening programs have consistently been associated with a reduction in cervical cancer incidence and mortality. Developed countries have achieved such reduced incidence and mortality from cervical cancer over the past 40 years. This is largely due to the implementation of organized cytological screening and vaccination programs. HPV vaccines are very effective at preventing infection and diseases related to the vaccine-specific genotypes in women with no evidence of past or current HPV infection. In spite of the successful implementation of the HPV vaccination program in many countries all over the world, problems related to HPV prevention and treatment of the related diseases will continue to persist in developing and underdeveloped countries.

Antibacterial drugs are among the most commonly used medications in the world. Tetracycline is a widely used antibiotic for human and animal therapy due to its broad-spectrum activity, high effectiveness, and reasonable cost. The indications for treatment with tetracycline include pneumonia, bone and joint infections, infectious disorders of the skin, sexually transmitted and gastrointestinal infections. However, tetracycline has become a serious threat to the environment because of its overuse by humans and veterinarians and weak ability to degrade. Tetracycline is capable of accumulating along the food chain, causing toxicity to the microbial community, encouraging the development and spread of antibiotic resistance, creating threats to drinking and irrigation water, and disrupting microbial flora in the human intestine. It is essential to address the negative impact of tetracycline on the environment, as it causes ecological imbalance. Ineffective wastewater systems are among the main reasons for the increased antibiotic concentrations in aquatic sources. It is possible to degrade tetracycline by breaking it down into small molecules with less harmful or nonhazardous effects. A range of methods for physical, chemical, and biological degradation exists. The review will discuss the negative effects of tetracycline consumption on the aquatic environment and describe available removal methods.

With the increase of interest in the application of piezoelectric polyvinylidene fluoride (PVDF) in nanogenerators (NGs), sensors, and microdevices, the most efficient and suitable methods of their synthesis are being pursued. Electrospinning is an effective method to prepare higher content β-phase PVDF nanofiber films without additional high voltage poling or mechanical stretching, and thus, it is considered an economically viable and relatively simple method. This work discusses the parameters affecting the preparation of the desired phase of the PVDF film with a higher electrical output. The design and selection of optimum preparation conditions such as solution concentration, solvents, the molecular weight of PVDF, and others lead to electrical properties and performance enhancement in the NG, sensor, and other applications. Additionally, the effect of the nanoparticle additives that showed efficient improvements in the PVDF films was discussed as well. For instance, additives of BaTiO3, carbon nanotubes, graphene, nanoclays, and others are summarized to show their contributions to the higher piezo response in the electrospun PVDF. The recently reported applications of electrospun PVDF films are also analyzed in this review paper.

Drones, also known as mini-unmanned aerial vehicles, have attracted increasing attention due to their boundless applications in communications, photography, agriculture, surveillance, and numerous public services. However, the deployment of amateur drones poses various safety, security, and privacy threats. To cope with these challenges, amateur drone surveillance has become a very important but largely unexplored topic. In this article, we first present a brief survey to show the state-of-the-art studies on amateur drone surveillance. Then we propose a vision, named Dragnet, tailoring the recently emerging Cognitive Internet of Things framework for amateur drone surveillance. Next, we discuss the key enabling techniques for Dragnet in detail, accompanied by the technical challenges and open issues. Furthermore, we provide an exemplary case study on the detection and classification of authorized and unauthorized amateur drones, where, for example, an important event is being held and only authorized drones are allowed to fly over.

A new medicine will take an average of 10-15 years and more than US$2 billion before it can reach the pharmacy shelf. Traditionally, drug discovery relied on natural products as the main source of new drug entities, but was later shifted toward high-throughput synthesis and combinatorial chemistry-based development. New technologies such as ultra-high-throughput drug screening and artificial intelligence are being heavily employed to reduce the cost and the time of early drug discovery, but they remain relatively unchanged. However, are there other potentially faster and cheaper means of drug discovery? Is drug repurposing a viable alternative? In this review, we discuss the different means of drug discovery including their advantages and disadvantages.

Recent research on economic sanctions has produced significant advances in our theoretical and empirical understanding of the causes and effects of these phenomena. Our theoretical understanding, which has been guided by empirical findings, has reached the point where existing datasets are no longer adequate to test important hypotheses. This article presents a recently updated version of the Threat and Imposition of Economic Sanctions dataset. This version of the data extends the temporal domain, corrects errors, updates cases that were ongoing as of the last release, and includes a few additional variables. We describe the dataset, paying special attention to the key differences in the new version, and we present descriptive statistics for some of the key variables, highlighting differences across versions. Since the major change in the dataset was to more than double the time period covered, we also present some simple statistics showing trends in sanctions use over time.

Although research has examined the social media–shareholder value link, the role of consumer mindset metrics in this relationship remains unexplored. To this end, drawing on the elaboration likelihood model and accessibility/diagnosticity perspective, the authors hypothesize varying effects of owned and earned social media (OSM and ESM) on brand awareness, purchase intent, and customer satisfaction and link these consumer mindset metrics to shareholder value (abnormal returns and idiosyncratic risk). Analyzing daily data for 45 brands in 21 sectors using vector autoregression models, they find that brand fan following improves all three mindset metrics. ESM engagement volume affects brand awareness and purchase intent but not customer satisfaction, while ESM positive and negative valence have the largest effects on customer satisfaction. OSM increases brand awareness and customer satisfaction but not purchase intent, highlighting a nonlinear effect of OSM. Interestingly, OSM is more likely to increase purchase intent for high involvement utilitarian brands and for brands with higher reputation, implying that running a socially responsible business lends more credibility to OSM. Finally, purchase intent and customer satisfaction positively affect shareholder value.