Statin therapy and cardiovascular protection in type 2 diabetes: The role of baseline LDL-Cholesterol levels. A systematic review and meta-analysis of observational studies.

AIM: The guidelines recommend statins to prevent cardiovascular events in patients with type 2 diabetes (T2D) however, the importance of baseline LDL-Cholesterol (LDL-C) levels remains controversial. This study aimed to determine the association of statin use in T2D patients with major adverse cardiovascular events (MACE) and all-cause mortality and whether this association differs by baseline LDL-C levels. DATA SYNTHESIS: Medline, Embase, and Web of Science were systematically searched from inception until January 2022. Observational studies in patients with T2D comparing statin users vs non-users, with reports of the baseline LDL-C levels, were included. Random-effects meta-analysis and meta-regression were performed to estimate the overall effect on the risk of all-cause mortality and MACE (a composite of myocardial infarction, heart failure, stroke, and revascularization events) and the modification in the association by baseline LDL-C levels. We categorized studies according to their baseline LDL-C levels into 1) <100 mg/dl (2.59 mmol/l), 2) 100-130 mg/dl (2.59-3.37 mmol/l) and 3) >130 mg/dl (3.37 mmol/l) categories. A total of 9 cohort studies (n = 403,411 individuals) fulfilled our criteria. The follow-up duration ranged from 1.7 to 8 years. The overall combined estimate showed that statin therapy was associated with a significantly lower risk of MACE (Hazard Ratio (HR): 0.70 [95% CI 0.59 to 0.83], Absolute risk reduction percentage (ARR%): 3.19% [95%CI 0.88 to 5.50%) and all-cause mortality (HR: 0.60 [95% CI 0.46 to 0.79], ARR%: 5.23% [95% CI 2.18 to 8.28%), but varied, albeit not statistically significant, by baseline LDL-C levels. Studies with baseline LDL-C levels higher than 130 mg/dl had the greatest reduction of MACE (HR: 0.58 [95% CI 0.37 to 0.90]) and all-cause mortality risk (HR: 0.51 [95% CI [ 0.29 to 0.90]). The HRs of MACE in studies with LDL-C levels of 100-130 mg/dl and <100 mg/dl categories were respectively (0.70 [95% CI 0.59 to 0.83]) and (0.83 [95% CI [0.68 to 1.00]); and that of all-cause mortality were respectively (0.62 [95% CI 0.38 to 1.01]) and (0.67 [95% CI [0.44 to 1.02]). Statin use changes the HRs of MACE (0.99 [95%CI, 0.98 to 0.99]; P = 0.04) and all-cause mortality (0.99 [95% CI 0.98 to 1.01]; P = 0.8) per each mg/dl increase in baseline LDL-C level in meta-regression analyses. CONCLUSION: Statin therapy in patients with T2D was associated with reduced risk of MACE and all-cause mortality. Significant differences across studies with different baseline LDL-C levels were not observed.

Deciphering the role of epigenetic modifications in fatty liver disease: A systematic review.

BACKGROUND: Fatty liver disease (FLD), primarily nonalcoholic fatty liver disease (NAFLD), is the most common liver disorder that affects a quarter of the global population. NAFLD is a spectrum of disease ranging from simple steatosis to nonalcoholic steatohepatitis, which is associated with increased risk of developing liver cancer. Given that the pathogenic mechanisms of fatty liver remain largely elusive, it is important to further investigate potential underlying mechanisms including epigenetic modifications. Here, we performed a systematic review of human epigenetic studies on FLD presence. METHODS: Five bibliographic databases were screened until 28 August 2020. We included cross-sectional, case-control and cohort studies in humans that examined the association of epigenetic modifications including global, candidate or epigenome-wide methylation of DNA, noncoding RNAs and histone modifications with FLD. RESULTS: In total 36 articles, based on 33 unique studies, consisting of 12 112 participants met the inclusion criteria. Among these, two recent epigenome-wide association studies conducted among large population-based cohorts have reported the association between cg06690548 (SLC7A11) and FLD. Moreover, several studies have demonstrated the association between microRNAs (miRNAs) and FLD, in which miR-122, miR-34a and miR-192 were recognized as the most relevant miRNAs as biomarkers for FLD. We did not find any studies examining histone modifications in relation to FLD. CONCLUSIONS: Cumulative evidence suggests a link between epigenetic mechanisms, specifically DNA methylation and miRNAs, and FLD. Further efforts should investigate the molecular pathways by which these epigenetic markers may regulate FLD and also the potential role of histone modifications in FLD.

Opium Addiction and Ischemic Stroke in Isfahan, Iran: A Case-Control Study.

BACKGROUND: The effect of opium addiction (OA) on cerebrovascular disease is controversial. The aim of this study was to clarify this relationship in Iranian patients with ischemic stroke. METHODS: In a case-control study, 672 patients with ischemic stroke and 293 controls without a previous history of cerebrovascular or cardiovascular diseases were compared. OA as well as other risk factors such as diabetes mellitus (DM), hypertension (HTN), hyperlipidemia, tobacco smoking (TS) were compared between the 2 groups. RESULTS: OA percentage, TS, TS amount (pack/year), HTN and DM history were significantly higher in the case group compared to controls (p < 0.05). After regression analysis between risk factors, a significant difference remained between 2 groups with regards to HTN (OR 4.21, 95% CI 3.05-5.81, p < 0.001), TS (OR 2.33, 95% CI 1.51-3.59, p < 0.001), and OA (OR 2.36, 95% CI 1.16-4.85, p = 0.018). CONCLUSION: Our study showed OA is a risk factor for stroke. However, a follow-up study with a larger cohort is required to confirm the results.

Protection Group Effects During α,γ-Diol Lignin Stabilization Promote High-Selectivity Monomer Production.

Protection groups were introduced during biomass pretreatment to stabilize lignin's α,γ-diol group during its extraction and prevent its condensation. Acetaldehyde and propionaldehyde stabilized the α,γ-diol without any aromatic ring alkylation, which significantly increased final product selectivity. The subsequent hydrogenolysis catalyzed by Pd/C generated lignin monomers at near-theoretical yields based on Klason lignin (48 % from birch, 20 % from spruce, 70 % from high-syringyl transgenic poplar), and with high selectivity to a single 4-n-propanolsyringol product (80 %) in the case of the poplar. Unlike direct hydrogenation of native wood, hydrogenolysis of protected lignin with Ni/C also led to high selectivity to this single product (78 %), paving the way to high-selectivity lignin upgrading with base metal catalysts. The use of extracted lignin facilitated valorization of polysaccharides, leading to high yields of all three major biomass polymers to a single major product.

A new bio-inspired stimulator to suppress hyper-synchronized neural firing in a cortical network.

Hyper-synchronous neural oscillations are the character of several neurological diseases such as epilepsy. On the other hand, glial cells and particularly astrocytes can influence neural synchronization. Therefore, based on the recent researches, a new bio-inspired stimulator is proposed which basically is a dynamical model of the astrocyte biophysical model. The performance of the new stimulator is investigated on a large-scale, cortical network. Both excitatory and inhibitory synapses are also considered in the simulated spiking neural network. The simulation results show that the new stimulator has a good performance and is able to reduce recurrent abnormal excitability which in turn avoids the hyper-synchronous neural firing in the spiking neural network. In this way, the proposed stimulator has a demand controlled characteristic and is a good candidate for deep brain stimulation (DBS) technique to successfully suppress the neural hyper-synchronization.

Microsimulation for clinical decision-making in individual patients with established coronary artery disease: a concept.

BACKGROUND: In cardiovascular disease, numerous evidence-based prognostic models have been created, usually based on regression analyses of isolated patient datasets. They tend to focus on one outcome event, based on just one baseline evaluation of the patient, and fail to take the disease process in its dynamic nature into account. We present so-called microsimulation as an attractive alternative for clinical decision-making in individual patients. We aim to further familiarize clinicians with the concept of microsimulation and to inform them about the modeling process. METHODS AND RESULTS: We describe the modeling process, advantages and disadvantages of microsimulation. We illustrate the concept using a hypothetical 60-year-old patient, with several cardiac risk factors, who is hospitalized for myocardial infarction. By using microsimulation, we calculate this patient's probability of death. In our example, this particular patient's estimated life expectancy turns out to be 8.9 years. While calculating this life expectancy, we were able to account for multiple outcome events and changing patient characteristics. CONCLUSIONS: Microsimulation takes into account the dynamic nature of coronary artery disease by estimating most likely outcomes regarding a broad range of clinical events. Moreover, microsimulation can be used to evaluate treatment effects by estimating the event-free life expectancy with and without treatment. Hence, microsimulation has several advantages compared to modeling techniques such as regression.

A new full closed-loop brain-machine interface approach based on neural activity: A study based on modeling and experimental studies.

Background: The bidirectional brain-machine interfaces algorithms are machines that decode neural response in order to control the external device and encode position of artificial limb to proper electrical stimulation, so that the interface between brain and machine closes. Most BMI researchers typically consider four basic elements: recording technology to extract brain activity, decoding algorithm to translate brain activity to the predicted movement of the external device, external device (prosthetic limb such as a robotic arm), and encoding interface to convert the motion of the external machine to set of the electrical stimulation of the brain. New method: In this paper, we develop a novel approach for bidirectional brain-machine interface (BMI). First, we propose a neural network model for sensory cortex (S1) connected to the neural network model of motor cortex (M1) considering the topographic mapping between S1 and M1. We use 4-box model in S1 and 4-box in M1 so that each box contains 500 neurons. Individual boxes include inhibitory and excitatory neurons and synapses. Next, we develop a new BMI algorithm based on neural activity. The main concept of this BMI algorithm is to close the loop between brain and mechaical external device. Results: The sensory interface as encoding algorithm convert the location of the external device (artificial limb) into the electrical stimulation which excite the S1 model. The motor interface as decoding algorithm convert neural recordings from the M1 model into a force which causes the movement of the external device. We present the simulation results for the on line BMI which means that there is a real time information exchange between 9 boxes and 4 boxes of S1-M1 network model and the external device. Also, off line information exchange between brain of five anesthetized rats and externnal device was performed. The proposed BMI algorithm has succeeded in controlling the movement of the mechanical arm towards the target area on simulation and experimental data, so that the BMI algorithm shows acceptable WTPE and the average number of iterations of the algorithm in reaching artificial limb to the target region.Comparison with existing methods and Conclusions: In order to confirm the simulation results the 9-box model of S1-M1 network was developed and the valid "spike train" algorithm, which has good results on real data, is used to compare the performance accuracy of the proposed BMI algorithm versus "spike train" algorithm on simulation and off line experimental data of anesthetized rats. Quantitative and qualitative results confirm the proper performance of the proposed algorithm compared to algorithm "spike train" on simulations and experimental data.

Prevalence study of clinical disorders in 6-year-old children across Iranian provinces: Findings of Iranian national health assessment survey.

OBJECTIVE: To assess the national prevalence of clinical disorders in 6-year-old Iranian children before school entry using a national health assessment survey. MATERIALS AND METHODS: In a cross-sectional nationwide survey, all Iranian children entering public and private elementary schools were asked to participate in a mandatory national screening program in Iran in 2009 in two levels of screening and diagnostic levels. RESULTS: The study population consisted of 955388 children (48.5% girls and 76.1% urban). Of the whole children, 3.1% of the 6-year-old children had impaired vision. In addition, 1.2, 1.8, 1.4, 10, 10.9, 56.7, 0.7, 0.8 and 0.6% had color blindness, hearing impaired, speech disorder, height to age retardation, body mass index extremes, decayed teeth, having disease with special needs, spinal disorders, and hypertension, respectively. The distribution of these disorders was unequally distributed across provinces. CONCLUSIONS: Our results confirmed that the prevalence of clinical disorders among 6-year-old children across Iranian provinces was not similar. The observed burden of these distributions among young children needs a comprehensive national policy with evidence-based province programs to identify the reason for different distribution among provinces.

Mortality-related factors disparity among Iranian deceased children aged 1-59 months according to the medical activities in emergency units: National mortality surveillance system.

BACKGROUND: To determine disparity in mortality-related factors in 1-59 months children across Iran using hospital records of emergency units. MATERIALS AND METHODS: After designing and validating a national questionnaire for mortality data collection of children 1-59 months, all 40 medical universities has been asked to fill in the questionnaires and return to the main researcher in the Ministry of Health and Medical Education. Age and sex of deceased children, the type of health center, staying more than 2 h in emergency unit, the reason of prolonged stay in emergency, having emergency (risk) signs, vaccination, need to blood transfusion, need to electroshock and so on have also been collected across the country. There was also a comparison of children based on their BMI. Chi-square test has been applied for nominal and ordinal variables. ANOVA and t-student test have been used for measuring the difference of continuous variables among groups. RESULTS: Mortality in 1-59 months children was unequally distributed across Iran. The average month of entrance to hospital was June, the average day was 16(th) of month, and the average hour of entrance to hospital was 14:00. The average of month, day and hour for discharge was July, 16, and 14:00, respectively. The hour of discharge was statistically significant between children with and without risk signs. More than half (54%) of patients had referred to educational hospital emergency units. There were no statistically significant differences between children with and without emergency signs. There were statistically significant differences between children with and without emergency signs in age less than 24 months (0.034), nutrition situation (P = 0.031), recommendation for referring (P = 0.013), access to electroshock facilities (P = 0.026), and having successful cardiopulmonary resuscitation (P = 0.01). CONCLUSION: This study is one of the first to show the distribution of the disparity of early childhood mortality-related factors within a developing country. Our results suggest that disparity in 1-59 months mortality based on hospital records in emergency units needs more attention by policy-makers. It is advisable to conduct provincially representative surveys to provide recent estimates of hospital access disparities in emergency units and to allow monitoring over time.

Recognizing intertwined patterns using a network of spiking pattern recognition platforms.

Artificial intelligence computing adapted from biology is a suitable platform for the development of intelligent machines by imitating the functional mechanisms of the nervous system in creating high-level activities such as learning, decision making and cognition in today's systems. Here, the concentration is on improvement the cognitive potential of artificial intelligence network with a bio-inspired structure. In this regard, four spiking pattern recognition platforms for recognizing digits and letters of EMNIST, patterns of YALE, and ORL datasets are proposed. All networks are developed based on a similar structure in the input image coding, model of neurons (pyramidal neurons and interneurons) and synapses (excitatory AMPA and inhibitory GABA currents), and learning procedure. Networks 1-4 are trained on Digits, Letters, faces of YALE and ORL, respectively, with the proposed un-supervised, spatial-temporal, and sparse spike-based learning mechanism based on the biological observation of the brain learning. When the networks have reached the highest recognition accuracy in the relevant patterns, the main goal of the article, which is to achieve high-performance pattern recognition system with higher cognitive ability, is followed. The pattern recognition network that is able to detect the combination of multiple patterns which called intertwined patterns has not been discussed yet. Therefore, by integrating four trained spiking pattern recognition platforms in one system configuration, we are able to recognize intertwined patterns. These results are presented for the first time and could be the pioneer of a new generation of pattern recognition networks with a significant ability in smart machines.

A Comprehensive Review on Various Aspects of SARS-CoV-2 (COVID-19) Vaccines.

This is a comprehensive review based on the published papers in the field of COVID-19 vaccines and vaccination. Many efforts have been made to develop vaccines to combat this pandemic. Since December 2020, more than 200 vaccines have been tested in various research stages and in clinical trials on humans, of which eight vaccines reached phase four clinical trials in humans and approved by FDA and EUA. After the Pfizer-BioNTech vaccine that had the highest efficacy (95%), the efficacy of the other vaccines are as follows: Moderna 94.5%, Sputnik V 91%, Novavax 89.7%, Sinopharm 79.3%, Oxford/AstraZenaca 70.4%, Johnson and Johnson 66.9%, and Sinovac 50.7%. At present, protein-based vaccines, with 35% of all available COVID-19 vaccines, are the most common technique in the vaccine production, and then there are vaccines of non-replicating viral vector (13.3%), mRNA1 (12.1%), DNA (10.2%), replicating viral vector (9.8%), and inactivated vaccines (8.2%). The most frequently recognized adverse effects within 7 days of each vaccine dose involved fever, fatigue, headache, chill, and myalgia. The mRNA-based vaccines were associated with a higher occurrence of local side effects (78.3 vs. 70.4%; Sig. = 0.064), whereas the viral vector-based vaccine was associated with a higher prevalence of systemic side effects (87.2 vs. 61%; Sig. < 0.001). Based on the evidence and articles in the field of vaccination, AstraZeneca-Oxford and Sinopharm vaccines reported the highest and lowest side effects, respectively. Because of being emerging, pathogenicity, and high infectivity of COVID-19, vaccination against the disease to prevent its incident rate and decrease the prevalence rate is recommended immediately. Being informed of various aspects of the existing vaccines such as efficacy, effectiveness, safety, etc.can accelerate to make effective and useful choices and consequently have a vaccinated community against the epidemic.

Associations of Sex Steroids and Sex Hormone-Binding Globulin with Non-Alcoholic Fatty Liver Disease: A Population-Based Study and Meta-Analysis.

BACKGROUND: Prior studies have reported inconsistent results or less well-explored associations between sex hormones and non-alcoholic fatty liver disease (NAFLD). Here, we aimed to investigate the associations of NAFLD with sex steroids and sex hormone-binding globulin (SHBG) in the population-based study and conduct a comprehensive systematic review and meta-analysis of all published observational studies. METHODS: Analyses included 755 men and 1109 women with available data on sex steroids, SHBG, and ultrasound-based NAFLD from the Rotterdam Study. Multivariable regression models were used to examine the associations. Additionally, we searched five databases from inception to 1 April 2022 and performed a systematic review and meta-analysis. Random-effects (DerSimonian-Laird) method was used for meta-analysis, odds ratios (ORs) were calculated for the effect estimate, subgroup and leave-one-out sensitivity analyses were conducted, and meta-regression was performed to explore the pooled statistics with high heterogeneity. RESULTS: In the Rotterdam Study, lower levels of SHBG were associated with NAFLD in both sexes, while lower testosterone was associated with NAFLD only among women. Similarly, the meta-analysis of 16 studies indicated no sex-specific association between SHBG and NAFLD (men: OR = 0.37, 95%CI 0.21-0.53; women: OR = 0.40, 95%CI 0.21-0.60), yet there was a sex-specific association between testosterone and NAFLD (men: OR = 0.59, 95%CI 0.42-0.76; women: OR = 1.06, 95%CI 0.68-1.44). Moreover, men with NAFLD had lower estradiol levels than those without NAFLD. CONCLUSIONS: Lower SHBG levels were associated with NAFLD in both sexes, but testosterone levels were associated in a sex-specific manner. In addition, our results showed estradiol with the potential as a protective factor for NAFLD in healthy men.

The decline in stroke mortality: exploration of future trends in 7 Western European countries.

BACKGROUND AND PURPOSE: This article aims to make projections of future trends in stroke mortality in the Year 2030 based on recent trends in stroke mortality in 7 Western European countries. METHODS: Mortality data were obtained from national cause of death registries. Annual rates of decline in stroke mortality of 1980 to 2005 were determined for men and women in the United Kingdom, France, the Netherlands, and 4 Nordic countries on the basis of regression analysis. Estimated rates of decline were extrapolated until 2030. Cause-elimination life tables were used to determine the effect of stroke in 2030 in terms of potential gain in life expectancy. The absolute numbers of stroke deaths in 2030 were estimated using national population projections of Eurostat. RESULTS: In all countries, stroke mortality rates declined incessantly until 2005 among both men and women. If these trends were to continue, age-adjusted mortality rates would decline by approximately half between 2005 and 2030 with larger declines in France (approximately two thirds) and smaller declines in the Netherlands, Denmark, and Sweden (approximately one fourth). Similar rates of decline would be observed in terms of potential gain in life expectancy. Because of population aging, the absolute number of stroke deaths would decline slowly in the United Kingdom and France and stabilize or even increase in other countries. CONCLUSIONS: In the near future, stroke may lose much of its effects on life expectancy but remain a frequent cause of death among elderly populations. The prevention of stroke-related disability instead of mortality may become increasingly more important.

The decline in stomach cancer mortality: exploration of future trends in seven European countries.

Mortality from stomach cancer has fallen steadily during the past decades. The aim of this paper is to assess the implication of a possible continuation of the decline in stomach cancer mortality until the year 2030. Annual rates of decline in stomach cancer mortality from 1980 to 2005 were determined for the Netherlands, United Kingdom, France, and four Nordic countries on the basis of regression analysis. Mortality rates were extrapolated until 2030, assuming the same rate of decline as in the past, using three possible scenarios. The absolute numbers of deaths were projected taking into account data on the ageing of national populations. Stomach cancer mortality rates declined between 1980 and 2005 at about the same rate (3.6-4.9% per year) for both men and women in all countries. The rate of decline did not level off in recent years, and it was not smaller in countries with lower overall mortality rates in 1980. If this decline were to continue into the future, stomach cancer mortality rates would decline with about 66% between 2005 and 2030 in most populations, while the absolute number of stomach cancer deaths would diminish by about 50%. Thus, in view of the strong, stable and consistent mortality declines in recent decades, and despite population ageing, stomach cancer is likely to become far less important as a cause of death in Europe in the future.

Multiple sclerosis in Iran: An epidemiological update with focus on air pollution debate.

BACKGROUND: Multiple sclerosis (MS), as the most common neurologic disorder of the central nervous system, with growing incidence and prevalence worldwide and in the Middle East. This article aimed to find out the potential relationship between MS and air pollution in Iran. METHODS: By assessing the published articles on MS and air pollution in Iran, the situation of MS as well as air/soil pollution in Iran was clarified. Then, studies on air pollution and its potential effect on Iranian MS patients were checked until 2020. RESULTS: The MS prevalence is distributed across Iran Provinces with highest rates in Isfahan, located in the center of Iran. The higher rates of MS in Isfahan and Tehran (the Metropolitan) might be due to industrial pollution of these cities, but this hypothesis is not true for non-industrial provinces. Based on the published atlas of MS in Iran, it seems that there is a high-risk "belt" from northwest to southeast. CONCLUSION: There are many risk factors of MS in Iran including age, gender, Vitamin D deficiency, smoking, and air pollution. The potential main risk factor of MS might be air pollution considering Isfahan and Tehran provinces. However, Chahar Mahal and Bakhtiary Province, with non-industrial nature, has the second highest MS rates which does not follow this hypothesis. RELEVANCE FOR PATIENTS: By finding the air pollution as the main potential risk factor of MS in big provinces including Isfahan and Tehran, its effect of this factor can also be considered during diagnosis and treatment.

Enzyme-free sandwich-type electrochemical immunosensor for highly sensitive prostate specific antigen based on conjugation of quantum dots and antibody on surface of modified glassy carbon electrode with core-shell magnetic metal-organic frameworks.

The early diagnosis of cancer increases the chance of its treatment. In this study, an enzyme-free sandwich type of immunosensors is presented for prostate specific antigen (PSA), as prostate cancer biomarker. In this regard, the quantum dots (QDs) and magnetic metal-organic frameworks (MOFs) were used for labeling the secondary anybody and modifying the electrode surface, respectively. Herein, a bare glassy carbon electrodes is modified with iron magnetic nanoparticles with a core shell MOFs (magnetic framework Fe3O4@ TMU-10) and the primary antibodies (Ab1) are immobilized on the modified electrode. Moreover, the second antibody is successfully conjugated to a nickel-cadmium quantum dots as an electroactive non-enzymatic probe. The prepared immunosensor shows a linear range between 1 pg mL-1- 100 ng mL-1 and the detection limit of 0.45 pg mL-1 with acceptable selectivity, reproducibility and stability. The proposed sensor is also applied for determination of PSA in human serum samples and the results is confirmed by a reference method, which indicates its ability for clinical monitoring of the tumor marker.

Perceived factors to providing palliative care for patients with cancer - a qualitative systematic review.

Palliative care (PC) is one of the necessary cares given throughout a patient's experience with cancer. The aim of this study was to identify the perceived factors to providing PC for patients with cancer. Our study was a systematic review of qualitative literature. To this end, electronic databases, including CINAHL, PubMed, PsycINFO, Ovid, and Web of Science as well as Persian databases were searched and qualitative studies on the role of PC in patients with cancer published between Jan 2008 and Dec 2017 were selected. Generally, 12 studies were reviewed. A thematic synthesis approach was used to analyze the data. Exploring the selected articles, the findings on the perceived factors to providing PC for patients with cancer were categorized into three themes, including organizational factors, ethical factors, and psychological factors. This qualitative systematic review expands our knowledge about factors influencing the provision of PC for patients with cancer. It is necessary for health system managers and caregivers to pay attention to all aforesaid factors in order to improve PC for cancer patients.

Information Transmitted From Bioinspired Neuron-Astrocyte Network Improves Cortical Spiking Network's Pattern Recognition Performance.

We trained two spiking neural networks (SNNs), the cortical spiking network (CSN) and the cortical neuron-astrocyte network (CNAN), using a spike-based unsupervised method, on the MNIST and alpha-digit data sets and achieve an accuracy of 96.1% and 77.35%, respectively. We then connected CNAN to CSN by preserving maximum synchronization between them thanks to the concept of prolate spheroidal wave functions (PSWF). As a result, CSN receives additional information from CNAN without retraining. The important outcome is that CSN reaches 70.57% correct classification rate on capital letters without being trained on them. The overall contribution of transfer is 87.47%. We observed that for CSN the classifying neurons that relate to digits 0-9 of the alpha-digit data set are completely supported by the ones that relate to digits 0-9 of the MNIST data set. This means that CSN recognizes the similarity between the digits of the MNIST and alpha-digit data sets and classifies each digit of both data sets in the same class.

Environment-Wide Association Study (En WAS) of Prenatal and Perinatal Factors Associated With Autistic Traits: A Population-Based Study.

A combination of genetic and environmental factors contributes to the origins of autism spectrum disorder (ASD). While a number of studies have described specific environmental factors associating with emerging ASD, studies that compare and contrast multiple environmental factors in the same study are lacking. Thus, the goal of this study was to perform a prospective, data-driven environmental-wide association study of pre- and perinatal factors associated with the later development of autistic symptoms in childhood. The participants included 3891 6-year-old children from a birth cohort with pre- and perinatal data. Autistic symptoms were measured using the Social Responsiveness Scale in all children. Prior to any analyses, the sample was randomly split into a discovery set (2920) and a test set (921). Multiple linear regression analyses were performed for each of 920 variables, correcting for six of the most common covariates in epidemiological studies. We found 111 different pre- and perinatal factors associated with autistic traits during childhood. In secondary analyses where we controlled for parental psychopathology, 23 variables in the domains of family and interpersonal relationships were associated with the development of autistic symptoms during childhood. In conclusion, a data-driven approach was used to identify a number of pre- and perinatal risk factors associating with higher childhood autistic symptoms. These factors include measures of parental psychopathology and family and interpersonal relationships. These measures could potentially be used for the early identification of those at increased risk to develop ASD. LAY SUMMARY: A combination of genetic and environmental factors contributes to the development of autism spectrum disorder (ASD). Each environmental factor may affect the risk of ASD. In a study on 6-year-old children, a number of pre- and perinatal risk factors were identified that are associated with autistic symptoms in childhood. These factors include measures of parental psychopathology and family and interpersonal relationships. These variables could potentially serve as markers to identify those at increased risk to develop ASD or autistic symptoms. Autism Res 2020, 13: 1582-1600. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Fractionation of lignocellulosic biomass to produce uncondensed aldehyde-stabilized lignin.

Lignin is one of the most promising sources of renewable aromatic hydrocarbons. Current methods for its extraction from lignocellulosic biomass-which include the kraft, sulfite, and organosolv processes-result in the rapid formation of carbon-carbon bonds, leading to a condensed lignin that cannot be effectively depolymerized into its constituent monomers. Treatment of lignocellulosic biomass with aldehydes during lignin extraction generates an aldehyde-stabilized lignin that is uncondensed and can be converted into its monomers at near-theoretical yields. Here, we outline an efficient, reproducible, and scalable process for extracting and purifying this aldehyde-stabilized lignin as a solid, which can easily be re-dissolved in an organic solvent. Upon exposure to hydrogenolysis conditions, this material provides near-theoretical yields of aromatic monomers (~40-50% of the Klason lignin for a typical hardwood). Cellulose and hemicellulose are also efficiently fractionated. This protocol requires 6-7 h for the extraction of the stabilized lignin and a basic proficiency in synthetic chemistry.