read more

Craig B. Arnold has been named Princeton’s first University Innovation Officer and heads the new office.

The new producing artistic director of the theater and music theater season at the arts center sat for an interview for our ‘What I think’ series.

Arguments Over Innovation Capacity Miss How Much the US and China Are Intertwined Expert comment sysadmin 30 May 2018

Most discussions of current US–China trade tensions fundamentally misrepresent the globalized nature of innovation.

Among the many issues at play in the ongoing economic and trade tensions between the US and China are questions of technological capability and innovation.

Two of the main complaints in the US Section 301 report were that American companies have been forced to transfer technology to China and been the subject of cyber espionage. The presentation of the issues in this report has been disputed, but behind it lies concern in the US that Chinese innovative and technological capability is catching up with that in the US, thanks partly to the support of state policies set out in the Made in China 2025 initiative.

One important feature of the package of measures announced by the US last month is that it was designed to contain China’s technological development as much as to reduce the trade deficit, even though the latter has been the focus of President Donald Trump’s rhetoric.

(Some have cast doubt on this picture of Chinese innovation, suggesting that China is more of a ‘fat tech dragon’ whose massive inputs into research and development do not translate into real innovative capacity.)

The problem with the debate comparing Chinese and American technological capability is that it misunderstands or misrepresents the globalized nature of innovation in today’s world.

Contrary to the economic nationalist rhetoric emanating mainly from Washington, and to a lesser extent from Beijing, the US and China are not two separate economies competing for economic hegemony. As part of the globalization of manufacturing and production over the last 40 years and the more recent globalization of consumption, the shape and structure of innovation has also changed.

As we argue in a new paper, the key to understanding this is to think of innovation as being carried out through global or transnational networks linking economic actors, not within separated economies. What the recent phase of globalization has demonstrated is that innovation is achieved most effectively and efficiently when those engaged in innovation are connected not just within national borders but across them.

China has become integrated into these global innovation networks in ways which reflect its relative strengths and weaknesses in research and development. China’s extensive manufacturing ecosystem has enabled its companies to perform well in production-related and efficiency-driven innovation. Moreover the rapid growth in its large and dynamic consumer market provides fertile ground for consumer-related innovation by Chinese and foreign-invested enterprises alike. The rapidly increasing talent pool in China also provides additional human capital for innovation and technology.

Apart from the increased emphasis by Chinese enterprises on innovation, multinationals have also been stepping up their research and development (R&D) efforts in China. These now consitute a significant part of China’s R&D landscape, and are an increasingly important part of the global innovation by multinationals.

Things are of course changing. China’s overall innovation capacity is improving, and there are concerns in both in the US and Europe that Chinese policy is moving backwards towards the promotion of ‘indigenous innovation’ – or self-reliant innovation – and away from openness. In other words, we may be seeing a more ‘techno-nationalist’ China as well as a protectionist US.

China has also been criticized for inadequate protection of intellectual property rights, though the establishment of special courts for such disputes marks a commitment to improve – and the rights of Chinese companies increasingly need protection too.

As the benefits of globalization increasingly come under question, and with some degree of nationalist political pressure in both the West and China, it is not going to be possible – or politically desirable – to do away with national borders when it comes to innovation. But at the same time, the extent to which businesses and consumers have globalized means that fully ‘indigenous’ innovation is not possible, even if it were politically desirable.

EU-China innovation relations, as well as those between Washington and Beijing, therefore need careful management. But both Americans and Europeans should have more confidence in their innovation capability, given the relative strengths and weaknesses of Chinese innovation.

Americans and Europeans should acknowledge and promote the opportunities that come from globally networked innovation processes. Taking advantage of the comparative advantage of all the players in these networks means working with China as an innovation partner.

Mobile Ecosystems as a Driver of Innovation and Growth in the Asia-Pacific 19 September 2018 — 12:30PM TO 3:00PM Anonymous (not verified) 18 September 2018 Chatham House, London

16 September 2020

Youth innovation can help shape the future of African cities Expert comment LToremark 16 August 2022

To meet the challenges of rapid urbanization, African governments must harness the potential of young innovators to help shape the future of African cities.

It is projected that 1.3 billion people will be living in Africa’s cities by 2050, an increase of almost 1 billion from today, and largely driven by young people migrating to urban centres in search of work. As the continent’s urban population grows, cities will need to adapt by nurturing new economic ecosystems to create jobs, while managing the environmental, social and political pressures that urbanization brings.

The evolution of Africa’s cities is critical for meeting the demands of its youth population and must be co-created with them. Africa’s young innovators are already proving to be an asset in shaping the future of African cities and, if they are allowed to flourish, they could be at the forefront of finding much-needed solutions to the continent’s vast urban challenges.

Growing tech hubs

African countries are increasingly benefitting from growth in technology ecosystems, which are often clustered within cities. There are currently more than 600 tech hubs helping to incubate innovative solutions across cities in Africa. Between 2015 and 2020, the number of start-ups receiving funding grew six times faster than the global average. In 2021 alone, start-ups raised over $4billion in funding – twice as much as in 2020.

But significant challenges remain. While the number of new start-ups is an encouraging indication of the entrepreneurialism and creativity of Africa’s youth, job creation on the level required will demand that they grow and scale up to generate more and higher quality jobs. Research on scaling up in Africa is sparse but research by Endeavor suggests that in Nairobi – one of Africa’s top tech ecosystems – only 5 per cent of companies are able to sustain growth of 20 per cent or more each year, yet they created 72 per cent of new jobs in the previous three years. For Africa to fully harness the potential of digital innovation, making cities the best place for young people to launch ideas and grow them into thriving businesses must become a priority policy for African governments. 

Barriers to scale

On the most basic level, business growth needs access to the services that make cities more liveable and help both urban residents and firms become more productive, such as healthcare, transport, water and sanitation. African cities already struggle to provide their residents – in particular the poorest and most vulnerable – with equitable, reliable, affordable and quality access to these services, in a sustainable manner. And these challenges will only get more acute as urban populations rise rapidly, often without any kind of integrated planning.

For example, an estimated 70-80 per cent of municipal solid waste in Africa is recyclable, yet only about 4 per cent is currently recycled, with more than 90 per cent of waste ending up in uncontrolled dumpsites and landfills. As Africa’s urban population grows, these conditions are likely to worsen – unless there is urgent action. New technology has the potential to help by creating a positive feedback loop between innovation, service delivery and growth. For example, to bridge the waste management gap, innovators are exploring various tech-enabled circular economy models. These solutions are often ground-breaking and have the potential to leapfrog traditional waste management infrastructure. Crucially, they are also formalizing a largely informal sector and creating new jobs.

Across the continent, start-ups like Kaltani, Mr Green Africa and Freetown Waste Transformers build processing facilities to turn waste into energy or reusable products, such as construction materials. Others, like Scrapays, Regenize and Soso Care, are helping households and businesses sell off their recycled materials for cash and virtual currencies or exchange them for critical services, such as micro health insurance premiums. Such start-ups help empower informal waste pickers or agents with tech-enabled tools and target low-income urban communities that would not normally prioritize recycling.

Help or hindrance from the top?

But Africa’s young people cannot do this alone – government decision-makers must become catalysts for entrepreneurial leadership. This requires nurturing a mindset that sees young innovators as Africa’s biggest resource, not a threat. While the importance of young people to Africa’s development is acknowledged in various high-level regional treaties, patterns of inhibition and outright hostility from political ‘elites’ suggest that the disruptive nature of technology start-ups and their access to significant capital through venture capital funding models – unlike existing rent-seeking business models with government control – threatens the political establishment.

The growing use of tech solutions also leads to increased transparency and efficiency of service delivery, which in turn leads to increased demand for government accountability and pressure to adopt more liberal policies. Until there is a shift towards catalysing entrepreneurial leadership, there is a stronger incentive for political elites to leverage their powers to co-opt successful technology businesses, or otherwise try to control them for political gain, than let them flourish. This shift in mindset will be critical to unlocking the full potential of Africa’s young innovators.

Ion mobility brings an additional dimension of separation to LC–MS, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to TOF mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most used to analyze these data. However, because of the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (~30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (~10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 min on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation before MS/MS analysis.

Mass spectrometry has become an indispensable tool for the characterization of glycosylation across biological systems. Our ability to generate rich fragmentation of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag behind. Although glycoproteomic informatics approaches using glycan databases have attracted considerable attention, database independent approaches have not. This has significantly limited high throughput studies of unusual or atypical glycosylation events such as those observed in bacteria. As such, computational approaches to examine bacterial glycosylation and identify chemically diverse glycans are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using N-linked glycopeptides of Campylobacter fetus subsp. fetus as well as O-linked glycopeptides of Acinetobacter baumannii and Burkholderia cenocepacia revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses before database searching. Using this approach, we demonstrate how wide tolerance searching can be used to compare glycan use across bacterial species by examining the glycoproteomes of eight Burkholderia species (B. pseudomallei; B. multivorans; B. dolosa; B. humptydooensis; B. ubonensis, B. anthina; B. diffusa; B. pseudomultivorans). Finally, we demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined, these results show that open searching is a robust computational approach for the determination of glycan diversity within bacterial proteomes.

In-depth coverage of proteomic analysis could enhance our understanding to the mechanism of the protein functions. Unfortunately, many highly hydrophobic proteins and low-abundance proteins, which play critical roles in signaling networks, are easily lost during sample preparation, mainly attributed to the fact that very few extractants can simultaneously satisfy the requirements on strong solubilizing ability to membrane proteins and good enzyme compatibility. Thus, it is urgent to screen out ideal extractant from the huge compound libraries in a fast and effective way. Herein, by investigating the interior mechanism of extractants on the membrane proteins solubilization and trypsin compatibility, a molecular dynamics simulation system was established as complement to the experimental procedure to narrow down the scope of candidates for proteomics analysis. The simulation data shows that the van der Waals interaction between cation group of ionic liquid and membrane protein is the dominant factor in determining protein solubilization. In combination with the experimental data, 1-dodecyl-3-methylimidazolium chloride (C12Im-Cl) is on the shortlist for the suitable candidates from comprehensive aspects. Inspired by the advantages of C12Im-Cl, an ionic liquid-based filter-aided sample preparation (i-FASP) method was developed. Using this strategy, over 3,300 proteins were confidently identified from 10³ HeLa cells (~100 ng proteins) in a single run, an improvement of 53% over the conventional FASP method. Then the i-FASP method was further successfully applied to the label-free relative quantitation of human liver cancer and para-carcinoma tissues with obviously improved accuracy, reproducibility and coverage than the commonly used urea-based FASP method. The above results demonstrated that the i-FASP method could be performed as a versatile tool for the in-depth coverage proteomic analysis of biological samples.

Tandem mass tag (TMT) is a multiplexing technology widely-used in proteomic research. It enables relative quantification of proteins from multiple biological samples in a single MS run with high efficiency and high throughput. However, experiments often require more biological replicates or conditions than can be accommodated by a single run, and involve multiple TMT mixtures and multiple runs. Such larger-scale experiments combine sources of biological and technical variation in patterns that are complex, unique to TMT-based workflows, and challenging for the downstream statistical analysis. These patterns cannot be adequately characterized by statistical methods designed for other technologies, such as label-free proteomics or transcriptomics. This manuscript proposes a general statistical approach for relative protein quantification in MS- based experiments with TMT labeling. It is applicable to experiments with multiple conditions, multiple biological replicate runs and multiple technical replicate runs, and unbalanced designs. It is based on a flexible family of linear mixed-effects models that handle complex patterns of technical artifacts and missing values. The approach is implemented in MSstatsTMT, a freely available open-source R/Bioconductor package compatible with data processing tools such as Proteome Discoverer, MaxQuant, OpenMS, and SpectroMine. Evaluation on a controlled mixture, simulated datasets, and three biological investigations with diverse designs demonstrated that MSstatsTMT balanced the sensitivity and the specificity of detecting differentially abundant proteins, in large-scale experiments with multiple biological mixtures.

Cross-linking MS (XL-MS) has been recognized as an effective source of information about protein structures and interactions. In contrast to regular peptide identification, XL-MS has to deal with a quadratic search space, where peptides from every protein could potentially be cross-linked to any other protein. To cope with this search space, most tools apply different heuristics for search space reduction. We introduce a new open-source XL-MS database search algorithm, OpenPepXL, which offers increased sensitivity compared with other tools. OpenPepXL searches the full search space of an XL-MS experiment without using heuristics to reduce it. Because of efficient data structures and built-in parallelization OpenPepXL achieves excellent runtimes and can also be deployed on large compute clusters and cloud services while maintaining a slim memory footprint. We compared OpenPepXL to several other commonly used tools for identification of noncleavable labeled and label-free cross-linkers on a diverse set of XL-MS experiments. In our first comparison, we used a data set from a fraction of a cell lysate with a protein database of 128 targets and 128 decoys. At 5% FDR, OpenPepXL finds from 7% to over 50% more unique residue pairs (URPs) than other tools. On data sets with available high-resolution structures for cross-link validation OpenPepXL reports from 7% to over 40% more structurally validated URPs than other tools. Additionally, we used a synthetic peptide data set that allows objective validation of cross-links without relying on structural information and found that OpenPepXL reports at least 12% more validated URPs than other tools. It has been built as part of the OpenMS suite of tools and supports Windows, macOS, and Linux operating systems. OpenPepXL also supports the MzIdentML 1.2 format for XL-MS identification results. It is freely available under a three-clause BSD license at https://openms.org/openpepxl.

Trypsin is the protease of choice in bottom-up proteomics. However, its application can be limited by the amino acid composition of target proteins and the pH of the digestion solution. In this study we characterize ProAlanase, a protease from the fungus Aspergillus niger that cleaves primarily on the C-terminal side of proline and alanine residues. ProAlanase achieves high proteolytic activity and specificity when digestion is carried out at acidic pH (1.5) for relatively short (2 h) time periods. To elucidate the potential of ProAlanase in proteomics applications, we conducted a series of investigations comprising comparative multi-enzymatic profiling of a human cell line proteome, histone PTM analysis, ancient bone protein identification, phosphosite mapping and de novo sequencing of a proline-rich protein and disulfide bond mapping in mAb. The results demonstrate that ProAlanase is highly suitable for proteomics analysis of the arginine- and lysine-rich histones, enabling high sequence coverage of multiple histone family members. It also facilitates an efficient digestion of bone collagen thanks to the cleavage at the C terminus of hydroxyproline which is highly prevalent in collagen. This allows to identify complementary proteins in ProAlanase- and trypsin-digested ancient bone samples, as well as to increase sequence coverage of noncollagenous proteins. Moreover, digestion with ProAlanase improves protein sequence coverage and phosphosite localization for the proline-rich protein Notch3 intracellular domain (N3ICD). Furthermore, we achieve a nearly complete coverage of N3ICD protein by de novo sequencing using the combination of ProAlanase and tryptic peptides. Finally, we demonstrate that ProAlanase is efficient in disulfide bond mapping, showing high coverage of disulfide-containing regions in a nonreduced mAb.

Over the past decade, modern methods of MS (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. Although MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem MS (LC-MS²) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be laborious and time-consuming, especially if the experimental LC-MS² data are tested against sequence databases covering a broad panel of different microbiological taxa. In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC–MS measurements. Peptide masses are then extracted from MS¹ data and systematically tested against an in silico library of all possible peptide mass data compiled in-house. The library has been computed from the UniProt Knowledgebase covering Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from correlation coefficients between experimental and strain-specific in silico peptide mass profiles and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient – less than 2 mins per sample - and has been successfully tested by a test set of 39 LC-MS¹ peak lists obtained from 19 different microbial pathogens. The proposed method is rapid, simple and automatable and we foresee wide application potential for future microbiological applications.

Pathway analyses are key methods to analyze 'omics experiments. Nevertheless, integrating data from different 'omics technologies and different species still requires considerable bioinformatics knowledge.

Here we present the novel ReactomeGSA resource for comparative pathway analyses of multi-omics datasets. ReactomeGSA can be used through Reactome's existing web interface and the novel ReactomeGSA R Bioconductor package with explicit support for scRNA-seq data. Data from different species is automatically mapped to a common pathway space. Public data from ExpressionAtlas and Single Cell ExpressionAtlas can be directly integrated in the analysis. ReactomeGSA greatly reduces the technical barrier for multi-omics, cross-species, comparative pathway analyses.

We used ReactomeGSA to characterize the role of B cells in anti-tumor immunity. We compared B cell rich and poor human cancer samples from five of the Cancer Genome Atlas (TCGA) transcriptomics and two of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteomics studies. B cell-rich lung adenocarcinoma samples lacked the otherwise present activation through NFkappaB. This may be linked to the presence of a specific subset of tumor associated IgG+ plasma cells that lack NFkappaB activation in scRNA-seq data from human melanoma. This showcases how ReactomeGSA can derive novel biomedical insights by integrating large multi-omics datasets.

The increasing consumption of high-fat foods combined with a lack of exercise is a major contributor to the burden of obesity in humans. Aerobic exercise such as running is known to provide metabolic benefits, but how the over-consumption of a high fat diet (HFD) and exercise interact is not well characterized at the molecular level. Here, we examined the plasma proteome in mice for the effects of aerobic exercise as both a treatment and as a preventative regime for animals on either HFD or a healthy control diet. This analysis detected large changes in the plasma proteome induced by the HFD, such as increased abundance of SERPINA7, ALDOB, and down-regulation of SERPINA1E, CFD (adipsin). Some of these changes were significantly reverted using exercise as a preventative measure, but not as a treatment regime. To determine if either the intensity, or duration, of exercise influenced the outcome, we compared high-intensity interval training (HIIT) and endurance running. Endurance running slightly out-performed HIIT exercise, but overall, both provided similar reversion in abundance of plasma proteins modulated by the high-fat diet including SERPINA7, APOE, SERPINA1E, and CFD. Finally, we compared the changes induced by over-consumption of HFD to previous data from mice fed an isocaloric high saturated fat (SFA) or polyunsaturated fat (PUFA) diet. This identified several common changes including increased APOC2 and APOE, but also highlighted changes specific for either over-consumption of HFD (ALDOB, SERPINA7, CFD), SFA-based diets (SERPINA1E), or PUFA-based diets (Haptoglobin - Hp). Together, these data highlight the importance of early intervention with exercise to revert HFD-induced phenotypes and suggest some of the molecular mechanisms leading to the changes in the plasma proteome generated by high fat diet consumption. Web-based interactive visualizations are provided for this dataset (larancelab.com/hfd-exercise), which give insight into diet and exercise phenotypic interactions on the plasma proteome.

We developed a simple and rapid method to enrich protein N-terminal peptides, in which the protease TrypN is first employed to generate protein N-terminal peptides without Lys or Arg and internal peptides with two positive charges at their N-termini, and then the N-terminal peptides with or without N-acetylation are separated from the internal peptides by strong cation exchange chromatography according to a retention model based on the charge/orientation of peptides. This approach was applied to 20 μg of human HEK293T cell lysate proteins to profile the N-terminal proteome. On average, 1,550 acetylated and 200 unmodified protein N-terminal peptides were successfully identified in a single LC/MS/MS run with less than 3% contamination with internal peptides, even when we accepted only canonical protein N-termini registered in the Swiss-Prot database. Since this method involves only two steps, protein digestion and chromatographic separation, without the need for tedious chemical reactions, it should be useful for comprehensive profiling of protein N-termini, including proteoforms with neo-N-termini.

Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of PTM profiles detected in open searches based on attributes such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multi-experiment comparisons for studying changes in modification profiles, e.g. in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed paraffin-embedded samples, detects extreme underalkylation of cysteine in some datasets, discovers an artefactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multi-center proteomics profiling study.

Oct. 31, 2024 — SNIA is pleased to return to SC24 as part of the Open Standards Pavilion, Booth 1815. At SC24, five SNIA groups and six SNIA Alliance and Collaboration […]

The post SNIA to Lead Panel on AI and HPC Innovation Standards at SC24 appeared first on HPCwire.

Large-scale scientific research labs and academic institutions are utilizing high performance computing to accelerate sequencing, simulations, and analytics for research, learning, and discovery.  File data volumes are growing rapidly, and […]

The post Accelerating Research Innovation with Qumulo’s File Data Platform appeared first on HPCwire.

About This Webinar Oracle’s next generation HPC architecture with Intel compute instance based on 3rd Generation Intel® Xeon® Scalable processors, code named “Ice Lake”, changes the game for HPC in […]

The post Speed up Innovation with performance gains of up to 42% on the most powerful HPC Cloud appeared first on HPCwire.

Nov. 7, 2024 — Since 2011, CSCS has hosted a booth at the annual SC Conference, and this year makes no exception. CSCS invites attendees to discover the latest news […]

The post CSCS to Showcase Swiss HPC Innovations at SC24 in Atlanta appeared first on HPCwire.

March 20, 2024 — The Pawsey Supercomputing Research Centre invites Australian-based research groups to join the Pawsey Uptake Project call. This initiative will provide teams with access to dedicated Pawsey […]

The post Pawsey Invites Australian Researchers to Advance Scientific Innovation Through the Pawsey Uptake Project appeared first on HPCwire.

TROY, Mich., Nov. 12, 2024 — Altair, a global leader in computational intelligence, has entered into collaboration agreement with the European Space Agency (ESA) through the ESA Partnership Initiative for […]

The post Altair Partners with European Space Agency to Advance AI-Driven Aerospace Innovation appeared first on HPCwire.

Health experts agree that there is a clear connection between an individual’s dental health and mental health. But although this fact is supported by a number of clinical studies, it is rarely explored or discussed among health professionals. A person with poor oral health may experience bad breath, tooth loss, compromised speech and other symptoms […]

The post How Innovations in Dental Services Transform Patient Care and Improve Mental Health first appeared on What is Psychology?.

In rural Kentucky, teachers and students are awarded innovation grants to solve a challenge facing their community or classroom.

FAO is pleased to announce the release of the Global Plan of Action for the Conservation, Sustainable Use and Development of Aquatic Genetic Resources for Food [...]

Read the seriesFull Article