PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics.

PERCEPTRON is a next-generation freely available web-based proteoform identification and characterization platform for top-down proteomics (TDP). PERCEPTRON search pipeline brings together algorithms for (i) intact protein mass tuning, (ii) de novo sequence tags-based filtering, (iii) characterization of terminal as well as post-translational modifications, (iv) identification of truncated proteoforms, (v) in silico spectral comparison, and (vi) weight-based candidate protein scoring. High-throughput performance is achieved through the execution of optimized code via multiple threads in parallel, on graphics processing units (GPUs) using NVidia Compute Unified Device Architecture (CUDA) framework. An intuitive graphical web interface allows for setting up of search parameters as well as for visualization of results. The accuracy and performance of the tool have been validated on several TDP datasets and against available TDP software. Specifically, results obtained from searching two published TDP datasets demonstrate that PERCEPTRON outperforms all other tools by up to 135% in terms of reported proteins and 10-fold in terms of runtime. In conclusion, the proposed tool significantly enhances the state-of-the-art in TDP search software and is publicly available at https://perceptron.lums.edu.pk. Users can also create in-house deployments of the tool by building code available on the GitHub repository (http://github.com/BIRL/Perceptron).

Multinodular goitre surgery complications and directly observed surgeons' skills: A prospective double-blind observational cohort study.

OBJECTIVE: To study multinodular goitre patients' surgery by direct observation of surgical technique, and to compare complications with surgeons' skills and experience, for improved training of future thyroid surgeons. METHODS: Based on positivist epistemology and analytical observational design, this prospective double-blind study of a cohort of multinodular goitre patients operated upon by variedly experienced surgeons, was conducted at Bahawal Victoria Hospital Bahawalpur and Nishtar Medical University Hospital Multan, Pakistan, from December 2016 to April 2019. Patients were admitted through outpatient department and operated upon in routine operation lists. The surgeons were specialists/senior registrars, assistant professors, associate professors and professors. The patients were divided into two virtual groups: the one operated upon by surgeons with >3 years of post-fellowship experience and the other operated upon by surgeons with <3 years of post-fellowship experience. Surgeries were directly observed and differences in surgical technique and complications were recorded for respective groups. Data was analysed using SPSS 20. RESULTS: Of the 134 patients, there were 73(54.5%) in group 1 and 61(45.5%) in group 2. Overall, there were 119(88.8%) females and 15(11.2%) males. The overall mean age was 37.17±13.41 years (range: 14-80 years). Of the 25 surgeons, 13(52%) were in group 1 and 12(48%) in group 2. Group 1 had fewer complications compared to group 2, which on certain parameters was statistically significant (p<0.05). CONCLUSIONS: Surgeons' experience and technique were found to have significant relationship with the rate of complications. Direct observation of surgeries is significant for real life evaluation and training of junior surgeons.

Evolution of efficacious pangenotypic hepatitis C virus therapies.

Hepatitis C compromises the quality of life of more than 350 million individuals worldwide. Over the last decade, therapeutic regimens for treating hepatitis C virus (HCV) infections have undergone rapid advancements. Initially, structure-based drug design was used to develop molecules that inhibit viral enzymes. Subsequently, establishment of cell-based replicon systems enabled investigations into various stages of HCV life cycle including its entry, replication, translation, and assembly, as well as role of host proteins. Collectively, these approaches have facilitated identification of important molecules that are deemed essential for HCV life cycle. The expanded set of putative virus and host-encoded targets has brought us one step closer to developing robust strategies for efficacious, pangenotypic, and well-tolerated medicines against HCV. Herein, we provide an overview of the development of various classes of virus and host-directed therapies that are currently in use along with others that are undergoing clinical evaluation.

Effects of increasing dietary protein supplies on milk yield, milk composition, and nitrogen use efficiency in lactating buffalo.

Nitrogen efficiency of lactating buffalo can be increased by providing dietary crude protein (CP) precisely to the requirement. Twelve lactating Nili-Ravi buffaloes (6 primiparous and 6 multiparous) at 76 ± 37.5 days in milk (DIM) were used in this study. The treatments were diets providing three levels of CP (% DM basis): (1) low-protein = 11%; (2) medium-protein = 13.1%; (3) high-protein = 14.2% according to a 3 × 3 Latin square design. The period length of each treatment was 21 days and the total duration of experiment was 63 days. The diets were designed to provide similar energy. The nitrogen intake of buffalo increased linearly by increasing CP levels. Dry matter intake showed a tendency toward decrease in quadratic fashion, whereas milk yield decreased linearly in high-protein diet. No effect was observed on milk protein yield and content. Increasing the dietary CP levels increased plasma urea nitrogen, whereas glucose and triacylglycerol levels remain unaffected. Efficiency of dietary nitrogen utilization to milk averaged 21% and showed both linear and quadratic decreases by increasing the protein supply levels. In conclusion, low CP level showed higher milk production with low plasma urea nitrogen and high nitrogen efficiency in this experiment.

A functional magnetic resonance imaging investigation of visual hallucinations in the human striate cortex.

PURPOSE: Human beings frequently experience fear, phobia, migraine and hallucinations, however, the cerebral mechanisms underpinning these conditions remain poorly understood. Towards this goal, in this work, we aim to correlate the human ocular perceptions with visual hallucinations, and map them to their cerebral origins. METHODS: An fMRI study was performed to examine the visual cortical areas including the striate, parastriate and peristriate cortex in the occipital lobe of the human brain. 24 healthy subjects were enrolled and four visual patterns including hallucination circle (HCC), hallucination fan (HCF), retinotopy circle (RTC) and retinotopy cross (RTX) were used towards registering their impact in the aforementioned visual related areas. One-way analysis of variance was used to evaluate the significance of difference between induced activations. Multinomial regression and and K-means were used to cluster activation patterns in visual areas of the brain. RESULTS: Significant activations were observed in the visual cortex as a result of stimulus presentation. The responses induced by visual stimuli were resolved to Brodmann areas 17, 18 and 19. Activation data clustered into independent and mutually exclusive clusters with HCC registering higher activations as compared to HCF, RTC and RTX. CONCLUSIONS: We conclude that small circular objects, in rotation, tend to leave greater hallucinating impressions in the visual region. The similarity between observed activation patterns and those reported in conditions such as epilepsy and visual hallucinations can help elucidate the cortical mechanisms underlying these conditions. Trial Registration 1121_GWJUNG.

Development and bioevaluation of 99mTc(CO)3-labeled (1-azido-1-deoxy-ß-D-glucopyranoside) complex as a potential tumor-seeking agent.

The 1,2,3-triazole-containing (1-azido-1-deoxy-ß-D-glucopyranoside) complex was synthesized using click chemistry approach and evaluated its potential as a tumor-seeking agent. In the present study, (99m)Tc-tricarbonyl labeled (1-azido-1-deoxy-ß-D-glucopyranoside) radiotracer [(99m)Tc(CO)(3)-BM], (where BM stands for biomolecule, e.g., (1-azido-1-deoxy-ß-D- glucopyranoside)) was synthesized via click chemistry approach and then labeled with technetium-99m through isolink kit. Radio labeled drug was tested for radiochemical purity and in vitro stability by chromatographic techniques. Normal distribution and tumoral uptake were studied in Swiss Webster mice. Radiochemical purity results show 97.9 ±1.5% labeling and its in vitro stability were studied at room temperature up to 5h. The radio labeled drug exhibited 73.6±1.1% binding with blood proteins. Normal distribution of drug shows prominent uptake in brain while in case of tumor-bearing mice, the uptake was maximum in tumor tissue and negligible amount was shown in brain. The biodistribution was further compared with 2-fluoro-2-deoxy glucose ((18)F-FDG), which was used as a positive control. The data indicate that (99m)Tc-tricarbonyl labeled (1-azido-1-deoxy-ß-D- glucopyranoside) radiotracer might be a feasible candidate with reasonable potential for tumor diagnosis.

Preparation of (99m)Tc-labelled methotraxate by a direct labeling technique as a potential diagnostic agent for breast cancer and preliminary clinical results.

Methotrexate (MTX) is being used in clinical oncology for the treatment of a wide variety of cancers. The aim of the present study was to label directly MTX with (99m)Tc by using Sn/pyrophosphate as reducing agent and to use this labeled compound as a potential anticancer radiopharmaceutical for breast cancer imaging. We studied the labeling efficiency of the (99m)Tc-MTX compound by paper chromatography and instant thin layer chromatography (ITLC) in acetone and saline and found it to be more than 95%. In vitro stability of labeled MTX in serum was studied up to 5h. Partition coefficient in n-octanol and saline indicated that the labeled radiopharmaceutical was hydrophilic. We then tested (99m)Tc-MTX in 5 breast cancer female patients. Protein bound (99m)Tc-MTX showed rapid clearance from blood. The biodistibution data suggested that (99m)Tc-MTX was cleared by the kidneys and the liver. Patients ' data also showed highly significant uptake of (99m)Tc-MTX in breast cancer. In conclusion, this study indicated that (99m)Tc-MTX may be used as a potential diagnostic agent for breast cancer patients imaging and may show treatment efficiency in case MTX is to be used for treatment.

Determination of affected brain regions at various stages of Alzheimer's disease.

The objective of study was to explore those brain areas that were affected at each stage during the progression of Alzheimer's disease (AD). Six affected brain areas were explored at mild cognitive impairment, four at first stage and six at each of second and third stage of Alzheimer's disease. The common brain regions among these stages were cuneus, precuneus, calcarine cortex, middle frontal gyrus, superior frontal gyrus, and frontal superior medial gyrus. The fMRI data at the resting state of 18 AD patients who were converted from MCI to stage 3 of Alzheimer's were taken from ADNI public source database. Among these patients, there were ten males and eight females. Independent component analysis was used to explore affected brain regions and an algorithm based on deep learning convolutional neural network was proposed for binary classification among the stages of Alzheimer's disease. The proposed CNN model delivered 94.6 % accuracy for separating stage 1 of Alzheimer's disease from mild cognitive impairment. 96.7 % accuracy was acquired to distinguish stage 2 of Alzheimer's disease from mild cognitive impairment, and stage 3 of Alzheimer's disease was separated from mild cognitive impairment with an accuracy of 97.8 %.

How does the development of digital inclusive finance in China affect green technology innovation? A theoretical mechanism study and empirical analysis.

This study employed fixed effects (FE) models, difference-in-differences (DID) methods, and mediating effect (ME) models to explore the total effect, structural effect, heterogeneous characteristics, and impact mechanism of digital inclusive finance (DIF) on green technology innovation (GTI) from 2011 to 2020. We derived the following results. First, DIF can significantly improve the level of GTI, and the positive role of internet digital inclusive finance is greater than that of traditional banks, but the three dimensions of the DIF index have different impacts on such innovation. Second, the impact of DIF on GTI has a "siphon effect," which is significantly promoted in regions with stronger economic power and inhibited in those with weaker economic power. Finally, there is an influence mechanism of "digital inclusive finance → financing constraints → green technology innovation." Our findings provide evidence to establish a lasting effect mechanism for DIF to promote GTI, and they have important reference value for other countries to develop DIF.

From crisis to resilience: strengthening climate action in OECD countries through environmental policy and energy transition.

Climate change represents a grave challenge to the global economy, environment, and societal well-being, jeopardizing their long-term sustainability. In response to this urgent issue, the study emphasizes the significance of environmental policy and energy transitions as fundamental factors in addressing the climate change crisis. The research draws upon data from OECD countries spanning the period between 1990 and 2020, utilizing robust econometric techniques to assess data properties. The study utilizes a comprehensive CS-ARDL model, incorporating multiple control variables like non-renewable energy GDP, foreign direct investment (FDI), and research and development (R&D). The results show that environmental policy and energy transitions are effective in reducing climate change impacts in the form of CO2 emissions. The non-environmental factors like GDP and FDI are positively associated and thereby accelerate climate change processes, whereas R&D promotes environmental protection by reducing CO2 emissions. Based on these findings, the study advocates for the implementation of rigorous policy measures by OECD economies to strengthen and enforce environmental policies to ensure compliance and foster sustainable practices across sectors. The study also suggests that OECD must promote energy transitions by investing in renewable energy sources at the mass level (micro and macro) and phasing out reliance on non-renewable energy.

Research and development for a carbon-neutral future and the status of EKC in G7 economies: evidence from CSARDL approach.

Climate change issues present substantial obstacles to the global community's stability and humanity's overall welfare. Reducing carbon emissions is crucial in attaining environmental sustainability and addressing the consequences of SDG 13 (climate actions). The G7 nations, representing some of the largest economies globally and significantly contributing to global carbon emissions, have achieved certain advancements in mitigating their carbon footprint. Nevertheless, the attainment of carbon neutrality continues to pose a substantial obstacle. This study examines the mechanisms leading to environmental sustainability in G7 economies, explicitly emphasizing the contribution of research and development (R&D) toward attaining carbon neutrality. The present study utilizes G7 data from 1990 to 2020 to conduct an empirical analysis employing a cross-sectional autoregressive distributed lag (CSARDL) panel model. The primary objective of this investigation is to examine the influence of R&D expenditure (R&DE) on carbon emissions metric ton (CO2Mt). Furthermore, this study investigates the current state of the EKC in the economies of the G7 nations, as well as the influence of renewable energy (RE) and non-renewable energy (NRE) on CO2Mt. The results suggest that R&DE is critical in mitigating CO2Mt and attaining carbon neutrality. The study also validates the EKC implies a negative and non-linear relationship between growth and CO2Mt. Moreover, renewable and non-renewable energy validate their respective negative and positive effects on CO2Mt. The findings of our study offer valuable insights for policymakers in the G7 nations, aiding them in developing effective regulatory measures for achieving carbon neutrality goals.

The dynamic change trends and internal driving factors of green development efficiency: robust evidence from resource-based Yellow River Basin cities.

Promoting the green development of resource-based cities is an essential way to achieve sustainable regional economic development. Based on 2009-2019 panel data of the Yellow River Basin cities, this study adopts the super-directional distance function model to measure the green development efficiency of these selected cities. Furthermore, based on the Malmquist-Luenberger index, this paper focuses on the dynamic change trend of green development efficiency and internal driving factors. Furthermore, the Tobit model is used to specifically explore the influencing factors affecting the green development of cities. The findings suggested that the green development efficiency of selected cities falls in the middle to high range and that the efficiency varies among all cities in the Yellow River Basin. Likewise, technical efficiency improvements and technological progress drive development efficiency, and the former contributes more to green development. However, financial development, energy structure adjustments, and environmental regulation can strongly contribute to the green development of cities, and each influencing factor has obvious temporal and regional differences. This paper proposes appropriate policy suggestions to promote the coordinated development of the economic development and environmental protection of the Yellow River Basin.

The role of climatic changes and financial development to the ASEAN agricultural output: a novel long-run evidence for sustainable production.

This paper examines the impact of climate variables and financial development on agricultural value-added and cereal production in selected Southeast Asian economies from 1970 to 2016. The current research applies second-generation advanced techniques to accomplish robust and reliable outcomes. The findings from the FM-OLS estimation disclose that climatic factors, for instance, CO2e and average temperature, impact both agricultural value-added and cereal production negatively, and financial development has an inverted U-shaped influence on both agricultural value-added and cereal production. Meanwhile, other important factors, including cropped area, income level, and rural labor force, significantly improve agricultural value-added and cereal production. Furthermore, the FM-OLS estimator's D-H panel causality test outcomes are reliable. The findings of our study reveal that both the short- and long-run risks of climatic changes to the agricultural sector pose a large-scale threat to food security in Southeast Asian economies. As a result, a robust and stable financial development in terms of governance of climate change finance in the agriculture sector must be achieved to enhance farmers' ability to adapt to current and future climate change adverse impacts.

Technology innovations impact on carbon emission in Chinese cities: exploring the mediating role of economic growth and industrial structure transformation.

China seems ambitious to achieve a "carbon emissions peak" before 2030 and "carbon neutrality" before 2060. To deal with this emissions mitigation plan, technology innovations are regarded as a crucial factor. However, considering its rebound effect (CO2 emissions driving effect) through economic growth, technology innovations might not prove a promising contributor to CO2 reduction. Therefore, there is a need to investigate further the nexus between technology innovations and CO2 emissions for conclusive debate. Based on the data of 215 cities in China, this paper uses mediating effects model to investigate the direct and indirect impacts (through economic growth and industrial structure transformation) of technology innovations on CO2 emissions from a microeconomic perspective. The main results suggest that technology innovations generally increase CO2 emissions in China both directly and indirectly. The impact of technology innovations and economic growth on CO2 emissions indicated the EKC characteristics. Furthermore, the contributions of technology innovations to CO2 emissions are distinguished in different regions. Thus, there is an urgent need for China to promote innovations in "clean technology" and to transform industrial structure to the tertiary industry to achieve the targets of carbon neutrality and emissions peaking.

Preparation and biodistribution in mice of a new radiopharmaceutical-technetium-99m labeled methotrexate, as a tumor diagnostic agent.

Our aim was to develop the procedure for radiolabeling of an anticancer drug e.g., methotrexate with (99m)Tc for tumors diagnosis. The study included the radiolabeling of methotrexate, in vitro stability of radiolabeled drug, in vitro binding of radiolabeled drug with plasma protein, partition coefficient and biodistribution of radiolabeled drug in mice. Results showed 98.2±0.5% radiolabeling of methotrexate with technetium-99m ((99m)Tc). In vitro stability was studied for 5h and 79.3±5% of the drug was bound with plasma proteins. Partition coefficient of the labeled drug showed that it was highly hydrophilic. Biodistribution study in tumor bearing mice exhibited high uptake in tumor cells which were further investigated by histopathological studies. In conclusion, our study indicates that technetium-99m labeled methotrexate is a potentially strong tumor diagnostic agent with low uptake in normal tissues.

Exploring Tourism Efficiency and Its Drivers to Understand the Backwardness of the Tourism Industry in Gansu, China.

Gansu Province is rich in tourism resources, and it is the hometown of the "copper galloping horse", which is the logo of China's tourism. However, the scale and revenues of tourism in Gansu province are still at a low level. This paper first evaluated the tourism efficiency of 14 cities and prefectures of Gansu Province in China from 2011 to 2019 using the super-slack-based measure (Super-SBM) and then investigated the internal driving mechanism of the efficiency change through the Global Malmquist-Luenberger (GML) index and its decomposition, and finally analyzed the external influencing elements of tourist efficiency by the Tobit model. The results revealed that the tourism efficiency of Gansu Province had increased rapidly during the study period, especially after 2016, the rising range increased. From 2011 to 2019, the cumulative changes in GML index, technological change (TC), and efficiency change (EC) of tourism efficiency in Gansu Province were 5.053, 4.145 and 1.160, respectively, indicating that the improvement of tourism efficiency in Gansu province is mainly due to technological progress. The regression results of the Tobit model show that the status of the tourism industry, trade openness, information level, and technological innovation level can significantly promote tourism efficiency in the province. At the same time, upgrading the industrial structure and the improvement of greening coverage inhibit tourism efficiency. However, the impact of the economic development level on the tourism efficiency of Gansu Province is not apparent. According to the research results, this paper puts forward corresponding suggestions to promote the development of tourism in Gansu Province. This study is crucial for hospitality, tourism, and policy sectors to understand the underlying factors and promote the healthy development of the tourism industry in Gansu Province.

The asymmetric effects of crops productivity, agricultural land utilization, and fertilizer consumption on carbon emissions: revisiting the carbonization-agricultural activity nexus in Nepal.

Agriculture plays an integral part in facilitating socioeconomic development in Nepal. However, it is also associated with environmental concerns which need to be controlled for the sake of ensuring environmental and agricultural sustainability in tandem. Against this backdrop, this current study aims to check whether shocks to the levels of agricultural productivity, land utilization for crop production, and fertilizer consumption influence the carbon dioxide emission figures of Nepal over the 1965-2018 period. The long-run associations between these variables are confirmed from the cointegration analysis. Besides, the outcomes from the asymmetric non-linear autoregressive distributed lag regression analysis show that crop productivity does not influence the emission levels in Nepal. However, a decline in the land area used for crop production purposes is evidenced to trigger higher emissions of carbon dioxide both in the short- and long run. On the other hand, higher fertilizer consumption is found to boost the short- and long-run carbon dioxide emission levels in Nepal. Accordingly, considering the objective of reducing agriculture-based emissions, this study recommends the Nepalese government to adopt policies that can enhance the productivity of low energy-intensive crop production, stimulate green agriculture and non-agriculture activities, and minimize the use of chemical fertilizers in arable lands.

Modeling the impact of climatic and non-climatic factors on cereal production: evidence from Indian agricultural sector.

The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965-2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals.

Does financial development mitigate the effects of climate variability on rice cultivation? Empirical evidence from agrarian economy.

This study is the first attempt to examine the effects of changing climate and financial development on rice cultivation in the context of agrarian economy like Thailand from 1969 to 2016. The current study also uses other important variables, such as cultivated area, organic fertilizers usage, and rural labor to determine the long-term connection amid variables. In this study, we applied several econometric techniques, for instance the autoregressive distributive lag-error correction model (ARDL-ECM), vector error correction model (VECM), impulse response functions (IMFs), and variance decomposition (VARD) method to estimate the most reliable and robust outcomes. The empirical results showed that in the long- and short-run, there is a reduction in rice cultivation as temperature increase. The carbon dioxide (CO2) positively affects rice cultivation in the long-run, while this association is negative in the short-run. The findings further revealed that in the long- and short-run, domestic credit provided by the financial sector significantly positive improved rice cultivation, while domestic credit to private sector by banks negatively affects rice cultivation. The important input factors, including cultivated area, organic fertilizers usage, and rural labor significantly positive contributed toward rice cultivation in the long- and short-run. The calculated long-run causal connection of all the studied variables with rice cultivation is validated. The estimated short-run causal relationship is unidirectional among temperature, CO2 emissions, financial development, rural labor, and rice cultivation. In addition, our outcomes are robust and also verified by IMFs and VARD method. The study offers some important policy suggestions to increase rice production with the help of sound and well-developed financial systems and climate controls.

Effects of feeding different dietary protein and energy levels on the performance of 12-15-month-old buffalo calves.

The study investigated the performance response of different dietary protein and energy levels of Nili-Ravi buffalo calves. Sixty buffalo calves of 12-15 months of age and similar body weight (140 ± 14 kg) were divided in to 12 groups, five animals in each group, according to 4 × 3 factorial arrangements. Twelve rations were formulated containing four levels of crude protein (CP; 10.5%, 12.20%, 13.80%, and 15.55%) each with three levels (1.72, 2.11, and 2.5 Mcal/Kg) of metabolizable energy (ME). Experiment lasted for 100 days; first 10 days were given for dietary adaptation. Daily feed consumption in calves fed all experimental diets were statistically significant (p<0.05) across all treatments. Higher feed intake was observed in buffalo calves fed diets containing 12.20% and 13.85% CP with 2.11 Mcal/kg ME. Results of dry matter (DM) digestion were significantly different (p<0.05) across all treatments. There was a quadratic (p<0.05) response of DM digestibility for levels of dietary protein while, curvilinear (p<0.05) trend with respect to dietary energy levels. Daily weight gain of buffalo calves did not show any treatment effect. The outcome of the present study indicate that 12-15-month-old buffalo calves perform adequately well when fed on diets containing 12.2% CP and 2.10 ME Mcal/Kg.