2018 Military Strength Ranking 05-31

The complete Global Firepower list for 2018 puts the military powers of the world into full perspective.

The finalized Global Firepower ranking relies on over 55 individual factors to determine a given nation's PowerIndex ('PwrIndx') score. Our unique formula allows for smaller, more technologically-advanced, nations to compete with larger, lesser-developed, ones. Modifiers (in the form of bonuses and penalties) are added to further refine the list. Some qualities to observe in regards to the finalized ranking:

+ Ranking does not rely solely on the total number of weapons available to any one country (though it is a factor) but rather focuses on weapon diversity within the number totals to provide a better balance of firepower available. For example, fielding 100 minesweepers does not equal the strategic / tactical value of fielding 10 aircraft carriers.

+ Nuclear stockpiles are NOT taken into account but recognized / suspected nuclear powers do receive a bonus.

+ First World, Second World, and Third World statuses are taken into account.

+ Geographical factors, logistical flexibility, natural resources, and local industry influence the final ranking.

+ Available manpower is a key consideration; nations with large populations tend to rank higher due to the availability of personnel for supporting both war and industry.

+ Land-locked nations are NOT penalized for lack of a navy, however, naval powers ARE penalized for lack of diversity in available assets. For example, 100 patrol boats does not equate the same advantage that fielding 4 guided-missile frigates and 2 nuclear-attack submarines does.

+ NATO allies receive a slight bonus due to the theoretical sharing of resources should one of the members commit to war.

+ Financial stability / strength is taken into account as finances represent one of several important factors in running a successful campaign.

+ Current political / military leadership is NOT taken into account as this can be highly subjective and not necessarily influence in-the-field indivudal combat performance.

For 2018 there are a total of 136 countries included in the GFP database. New to 2018 are Ireland, Montenegro, and Liberia.

Arrow graphics correspond to each nation's placement against the previous year's list. Green Arrows indicate an increase in rank whilst Red Arrows reflect a decline. Gray 'Double Arrows' reflect no change in ranking; this does not necessarily indicate that no changes occurred across individual values but more so that changes were not great enough to affect year-over-year ranking. Increases/declines are based on many factors and can be related to attrition, financial instability, population fluxes and the like.

View the Global list

View India's Firepower Details  

View comparison between the fire power of China and India

A Resolution Revolution,Single-cell Sequencing Techniques, 05-28

Despite its promise, a lack of spatial-temporal context is one of the challenges to making the most of single-cell analysis techniques. For example, information on the location of cells is particularly important when looking at how a common form of early-stage breast cancer, called ductal carcinoma in situ (DCIS) progresses to a more invasive form, called invasive ductal carcinoma (IDC). “Exactly how DCIS invasion occurs genomically remains poorly understood,” said Nicholas Navin, Ph.D., associate professor of Genetics at the University of Texas MD Anderson Cancer Center. Navin is a pioneer in the field, developing one of the first methods for scDNA-seq.

Cellular spatial data is critical for knowing whether tumor cells are DCIS or IDC. So, Navin developed topographical single-cell sequencing (TSCS). Navin and a team of researchers published their findings in February 2018 in Cell. “What we found was that, within the ducts, mutations had already occurred and had generated multiple clones and those clones migrated into the invasive areas,” Navin said.

Navin and his colleagues are also using single-cell techniques to study how triple-negative breast cancer, becomes resistant to the standard from of treatment for the disease, neo-adjuvant chemotherapy. In that work, published in an April 2018 online issue of Cell, using scDNA-seq and scRNAseq, Navin and his colleagues found responses to chemotherapy were pre-existing, thus adaptively selected. However, the expression of resistant genes was acquired by subsequent reprogramming as a result of chemotherapy. “Our data raise the possibility of therapeutic strategies to overcome chemoresistance by targeting pathways identified in this study,” Navin said.
Revealing Complexity.

The authors of research published in 2017 in Genome Biology also identified lineage tracing as one of the technologies that will “likely have wide-ranging applications in mapping developmental and disease-progression trajectories.” In March researchers published an online study in Nature in which they combined single-cell analysis with a lineage tracing technique, called GESTALT (genome editing of synthetic target arrays for lineage tracing), to define cell type and location in the juvenile zebrafish brain.

The combined technique, called scGESTALT, uses CRISPR-Cas9 to perform the lineage tracing and single-cell RNA sequencing to extract the lineage records. Cas9-induced mutations accumulate in a CRISPR barcode incorporated into an animal’s genome. These mutations are passed onto daughter cells and their progenies over several generations and can be read via sequencing. This information has allowed researchers to build lineage trees. Using single-cell analysis, the team could then determine the diversity of cell types and their lineage relationships. Collectively, this work provided a snapshot of how cells and cell types diverge in lineages as the brain develops. “Single-cell analysis is providing us with a lot of information about small differences at cell type-specific levels, information that is missed when looking at the tissue-wide level,” said Bushra Raj, Ph.D., a postdoctoral fellow in Alex Schier’s lab at Harvard University and first author on the paper.

Raj’s collaborators included University of Washington’s Jay Shendure, Ph.D., and Harvard Medical School’s Allon Klein, Ph.D., pioneers in the field of single-cell analysis. The team sequenced 60,000 cells from the entire zebrafish brain across multiple animals. The researchers identified more than 100 cell types in the juvenile brain, including several neuronal types and subtypes in distinct regions, and dozens of marker genes. “What was unknown was the genetic markers for many of these cell types,” Raj explained. “This work is a stepping stone,” she added. “It’s easy to see how we might one day compare normal gene–expression maps of the brain and other organs to help characterize changes that occur in congenital disease or cancer.”

Raj credits single-cell analysis with accelerating the field of developmental biology.
“People have always wanted to work at the level of the cell, but the technology was lacking,” she said. “Now that we have all of these sequenced genomes, and now that we have these tools that allow us to compartmentalize individual cells, this seems like the best time to challenge ourselves as researchers to understand the nitty-gritty details we weren’t able to assay before.”

A gold leaf paint and ink depiction of the Plasmodium falciparum lifecycle by Alex Cagan.
Human disease-relevant scRNA-seq is not just for vertebrates. For example, a team of researchers at the Wellcome Sanger Institute are working on developing a Malaria Cell Atlas. Their goal is to use single-cell technology to produce gene activity profiles of individual malaria parasites throughout their complex lifecycle. “The sequencing data we get allows us to understand how the parasites are using their genomes,” said Adam Reid, Ph.D., a senior staff scientist at the Sanger. In March 2018, the team published the first part of the atlas, detailing its results for the blood stage of the Plasmodium lifecycle in mammals. Reid contends these results will change the fight against malaria. “Malaria research is a well-funded and very active area of research. We’ve managed to get quite a bit of understanding of how the parasite works. What single-cell analysis is doing is allowing us to better understand the parasite in populations. We thought they were all doing the same thing. But, now we can see they are behaving differently.”

The ability to amplify very small amounts of RNA was the key innovation for malaria researchers. “When I started doing transcriptome analysis 10 years ago, we needed to use about 5 micrograms of RNA. Now, we can use 5 pico grams, 1 million times less,” Reid said. That innovation allows scientists like Reid to achieve unprecedented levels of resolution in their work. For Reid, increased resolution means there is hope that science will be able to reveal how malaria evades the immune system in humans and how the parasites develop resistance to drugs. Reid predicted the Atlas will serve as the underpinning for work by those developing malaria drugs and vaccines. “They will know where in the life cycle genes are used and where they are being expressed,” he said. Drug developers can then target those genes. The Atlas should be complete in the next two years, Reid added.
In the meantime, Reid and his colleagues are focused on moving their research from the lab to the field, particularly to Africa. “We want to look at these parasites in real people, in real settings, in real diseases states,” he explained. Having access to fresher samples is one reason to take the research into the field. “The closer we can get to the disease, the better chance we have of making an impact.” Reid anticipates that RNA-seq technology is on the verge of being portable enough to go into the field (see Preparing scRNA-seq for the Clinic & the Field). Everything from instrumentation to software is developing rapidly, he said. Reid also said that the methods used to understand the malaria parasite will likely be used to understand and create atlases for other disease vectors.

Path Ahead

It is clear to those using single-cell analysis in basic research that the path ahead includes using the techniques in the clinic. “As the technologies become more stable, there will be a lot of opportunities for clinical applications,” Navin said. These include early detection by sampling for cancer markers in urine, prostate fluid, and the like. It also includes non-invasive monitoring of rare circulating tumor cells, as well as personalizing treatment decisions using specific markers. These methods will be particularly useful in the case of samples that today would be labeled QNS, or ‘quantity not sufficient.’ “Even with QNS samples, these methods allow you to get high-quality datasets to guide treatment decisions.” 

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For new medicines, turn to pioneers 05-21

Most transformative medicines originate in curiosity-driven science, evidence says....

Would we be wise to prioritize “shovel-ready” science over curiosity-driven, fundamental research programs? In the long term, would that set the stage for the discovery of more medicines?
To find solid answers to these questions, scientists at Harvard and the Novartis Institute for Biomedical Research (NIBR), publishing in Science Translational Medicine, looked deep into the discovery of drugs and showed that, in fact, fundamental research is “the best route to the generation of powerful new medicines.”

“The discoveries that lead to the creation of a new medicine do not usually originate in an experiment that sets out to make a drug. Rather, they have their origins in a study — or many studies — that seek to understand a biological or chemical process,” said Mark Fishman, one of three authors of the study. “And often many years pass, and much scientific evidence accumulates, before someone realizes that maybe this work holds relevance to a medical therapy. Only in hindsight does it seem obvious.”

Fishman is a professor in the Harvard Department of Stem Cell and Regenerative Biology, a faculty member of the Harvard Stem Cell Institute, and former president of NIBR. He is a consultant for Novartis and MPM Capital, and is on the board of directors of Semma Therapeutics and the scientific advisory board of Tenaya Therapeutics.

CRISPR-cas9 is a good example of discovery biology that opened new opportunities in therapeutics. It started as a study of how bacteria resist infection by viruses. Scientists figured out how the tools that bacteria use to cut the DNA of an invading virus could be used to edit the human genome, and possibly to target genetic diseases directly.

The origins of CRISPR-Cas9 were not utilitarian, but those discoveries have the potential to open a new field of genomic medicine.

Blood pressure medicines would never have been created without the discovery of the role of renin (a renal extract) in regulating blood pressure in 1898.

Blood pressure medication is another example of how fundamental discoveries can lead to transformative medicines.

People who suffer from high blood pressure often take drugs that act by blocking the angiotensin-converting enzyme. Those medicines would never have been created without the discovery of the role of renin (a renal extract) in regulating blood pressure in 1898, or without the discovery of angiotensin in 1939, or without the solid understanding of how the enzyme works, shown in 1956.

This work was not tied earlier to making pills for hypertension, mainly because hypertension was generally believed to be harmless until the 1950s, when studies showed its relationship to heart disease. Before then, the control of blood pressure was itself a fundamental science, beginning with Stephen Hales’ measurement  of blood pressure in a horse in 1733.

The discovery of ACE inhibitors really reflects the convergence of two fields of fundamental, curiosity-driven discovery.

Yet some observers believe that projects that can demonstrate up front that they could produce something useful should take priority over projects that explore fundamental questions. Would there be many more medicines if academics focused more on programs with practical outcomes? How would that shift affect people in the future?

To find answers, Fishman and his colleagues investigated the many scientific and historical paths that have led to new drugs. The study they produced is a contemporary look at the evidence linking basic research to new medicines.

The authors used a list of the 28 drugs defined by other scientists as the “most transformative” medicines in the United States between 1985 and 2009. The group examined:
Whether the drug’s discovery began with an observation about the roots of disease;
Whether the biologist believed that it would be relevant to making a new medicine; and
How long it took to realize that.

To mitigate bias, the researchers repeatedly corroborated the assignment with outside experts.
They found that eight out of 10 of the medicines on their list led back to a fundamental discovery — or series of discoveries — without a clear path to a new drug.

The average time from discovery to new drug approval was 30 years, the majority of which was usually spent in academia, before pharmaceutical or biotechnology companies started the relevant drug development programs.

Fishman concluded, “We cannot predict which fundamental discovery will lead to a new drug. But I would say, from this work and my experiences both as a drug discoverer and a fundamental scientist, that the foundation for the next wave of great drugs is being set today by scientists driven by curiosity about the workings of nature.”

What industry and academic leaders say..

Leaders in biomedicine from industry, business, and academia warmly welcome this new body of evidence, as it supports the case for funding curiosity-driven, non-directed, fundamental research into the workings of life.

“This perspective on drug discovery reminds all of us that while many in both industry and academia have been advocating for a more rational approach to R&D, the scientific substrate we depend on results from a less than orderly process. The impact of basic research and sound science is often unpredictable and underestimated. With several telling examples, the authors illustrate how they can have a ripple effect through our field.”

– Jean-François Formela, M.D., Partner, Atlas Venture...

“The paper presents a compelling argument for investing in fundamental, curiosity-driven science. If it often takes decades to recognize when a new discovery should prompt a search for targeted therapeutics, we should continue to incentivize academic scientists to follow their nose and not their wallets.”

– George Daley, M.D., Ph.D., Dean of the Faculty of Medicine, Caroline Shields Walker Professor of Medicine, and Professor of Biological Chemistry and Molecular Pharmacology at Harvard Medical School

“There is a famous story of a drunk looking for his lost keys under a streetlight because the light is better there. As Mark reminds us, if we only look for cures where the light has already shone, we will make few if any new discoveries. Basic research shines a light into the dark corners of our understanding, and by that light we can find wonderful new things.”

— Dr Laurie Glimcher, M.D., President and CEO of the Dana-Farber Cancer Institute and Richard and Susan Smith Professor of Medicine at Harvard Medical School

“The importance of fundamental discovery to advances in medicine has long been a central tenet of academic medicine, and it is wonderful to see that tenet supported by this historical analysis. For those of us committed to supporting this pipeline, it is a critical reminder that young scientists must be supported to pursue out-of-the-box questions and even new fields. In the end, that is one of the key social goods that a research university provides to future generations.”

— Katrina Armstrong, M.D., M.S.C.E., Physician-in-Chief, Department of Medicine, Massachusetts General Hospital

“Human genetics is powering important advances in translational medicine, opening new doors to treatments for both common and rare diseases at an increasingly rapid pace. Yet, these discoveries still require fundamental, basic scientific understanding into the drug targets’ mechanism of action. In this way, the potential of the science can be unlocked through a combination of curiosity, agility, and cross-functional collaboration to pursue novel therapeutic modalities like gene and cellular therapies, living biologics, and devices. This paper illustrates the value of following the science with an emphasis on practical outcomes and is highly relevant in today’s competitive biopharmaceutical environment, where much of the low-hanging fruit has already been harvested.”

– Andy Plump, M.D., Ph.D., Chief Medical and Scientific Officer, Takeda Pharmaceutical Co.
“Medicine depends on scientists asking questions, collectively and over generations, about how nature works. The evidence provided by Fishman and colleagues supports an already strong argument for continued and expanded funding of our nation’s primary source of fundamental science: the NIH and the NSF.”

– Douglas Melton, Ph.D., Xander University Professor at Harvard, Investigator of the Howard Hughes Medical Institute, and co-director of the Harvard Stem Cell Institute

“Just as we cannot translate a language we do not understand, translational medicine cannot exist without fundamental insights to be converted into effective therapies. In their excellent review, Fishman and his colleagues bring the factual evidence needed to enrich the current debate about the optimal use of public funding of biomedical research. The product of public research funding should be primarily fundamental knowledge. The product of industrial R&D should be primarily transformative products based on this knowledge.”

— Elias Zerhouni, M.D., President Global R&D Sanofi, former Director of the National Institutes of Health, 2002-2008

“Fundamental research is the driver of scientific knowledge. This paper demonstrates that fundamental research led to most of the transformative medicines approved by the FDA between 1985 and 2009. Because many genes and genetic pathways are evolutionarily conserved, discoveries made from studies of organisms that are highly tractable experimentally, such as yeasts, worms, and flies, have often led to and been integrated with findings from studies of more complex organisms to reveal the bases of human disease and identify novel therapeutic targets.”

– H. Robert Horvitz, Nobel Laureate; David H. Koch Professor, Member of the McGovern Institute for Brain Research and of the David H. Koch Institute for Integrative Cancer Research, and Howard Hughes Medical Institute Investigator at Massachusetts Institute of Technology

“This meticulous and important study of the origin of today’s most successful drugs finds convincingly that the path to discovery lies through untargeted fundamental research. The authors’ clear analysis is an effective counter to today’s restless investors, academic leaders, and philanthropists, whose impatience with academic discovery has itself become an impediment to the conquest of disease.”

— Marc Kirschner, John Franklin Enders University Professor, Department of Systems Biology, Harvard Medical School

“Some ask if there is a Return on Investment (ROI) in basic biomedical research. With transformative therapies as the ‘R,’ this work traces the path back to the starting ‘I,’ and repeatedly turns up untargeted academic discoveries — not infrequently, two or more that are unrelated to each other. Conclusion? A nation that wants the ‘R’ to keep coming must maintain, or better, step up the ‘I’: that is, funding for curiosity-driven, basic research.”

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This “Smart Drug” Could Hack Your Brain Chemistry to Increase Your Intelligence. 05-12

Qualia is a 42 ingredient 'smart drug' designed to provide users with immediate, noticeable uplift of their subjective experience within 20 minutes of taking it, as well as long-term benefits to their neurology and overall physiologic functioning.

The Science of Nootropics

Nootropics, broadly speaking, are substances that can safely enhance cognitive performance. They’re a group of (as yet unclassified) research chemicals, over-the-counter supplements, and a few prescription drugs, taken in various combinations—that are neither addictive nor harmful, and don’t come laden down with side-effects—that are basically meant to improve your brain’s ability to think.
Right now, it’s not entirely clear how nootropics as a group work, for several reasons. How effective any one component of a nootropic supplement (or a stack) is depends on many factors, including the neurochemistry of the user, which is connected to genes, mood, sleep patterns, weight, and other characteristics.

However, there are some startups creating and selling nootropics that have research scientists on their teams, with the aim of offering reliable, proven cognitive enhancers. Qualia is one such nootropic. This 42 ingredient supplement stack is created by the Neurohacker Collective, a group that boasts an interdisciplinary research team including Sara Adães, who has a PhD in neuroscience and Jon Wilkins, a Harvard PhD in biophysics.

Smart Drugs

Some of Qualia’s ingredients are found in other stacks: Noopept, for example, and Vitamin B complex are some of the usual suspects in nootropics. Green tea extract, L-Theanine, Taurine, and Gingko Biloba are also familiar to many users, although many of the other components might stray into the exotic for most of us. Mucuna Pruriens, for example, is a source of L-Dopa, which crosses the blood–brain barrier, to increase concentrations of dopamine in the brain; L-Dopa is commonly used to treat dopamine-responsive dystonia and Parkinson’s disease.

The website says that the ‘smart drug’ is designed to provide users with “immediate, noticeable uplift of [their] subjective experience within 20 minutes of taking it, as well as long-term benefits to [their] neurology and overall physiologic functioning.” For people climbing their way up in Silicon Valley, it’s a small price to pay. What would you do with 10 percent more productivity, time, income, or intelligence?

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An AI that can predict cell structures 05-12

Fluorescent-labeled cells used to train neural networks. Image: Allen Institute. 


New 3D models of living human cells generated by machine-learning algorithms are allowing scientists to understand the structure and organization of a cell's components from simple microscope images.

Why it matters: The tool developed by the Allen Institute for Cell Science could be used to better understand how cancer and other diseases affect cells or how a cell develops and its structure changes — important information for regenerative medicine.

"Each cells has billions of molecules that, fortunately for us, are organized into dozens of structures and compartments that serve specialized functions that help cells operate," says Allen Institute's Graham Johnson, who helped develop the new model.

What they did: The researchers used gene editing to label the nucleus, mitochondria and other structures inside live human induced pluripotent stem cells (iPSC) with fluorescent tags and took tens of thousands of images of the cells.

They then used those images to train a type of neural network known as Generative Adversarial Networks (GANs). That yielded a model that can predict the most likely shape of the structures and where they are in cells based on just the cell's plasma membrane and nucleus.

Using a different algorithm, they created a model that can take an image of a cell that hasn't been fluorescent-labeled — in which it's difficult to distinguish the cell's components ("it looks like static on an old TV set," Graham Johnson says) — and find the structures.

What they found: When they compare the predicted image to actual labeled ones, the Allen Institute researchers said they are nearly indistinguishable.

The advance: Gene editing and fluorescent dyes often used to study cells only allow a few components to be visualized at once and can be toxic, limiting how long researchers can observe a cell.

Plus, "knowledge gained from more expensive techniques or ones that take a while to do and do well can be inexpensively applied to everyone’s data," says the Allen Institute's Greg Johnson, who also worked on the tool. "This provides an opportunity to democratize science."

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