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Rare diseases aren’t so rare. Collectively, up to 30 million Americans, many of them children, are born with one of the approximately 7,000 known rare diseases. Most of these millions of people also share a common genetic feature: their diseases are caused by an alteration in a single gene.

Many of these alterations could theoretically be targeted with therapies designed to correct or replace the faulty gene. But there have been significant obstacles in realizing this dream. The science of gene therapy has been making real progress, but pursuing promising approaches all the way to clinical trials and gaining approval from the U.S. Food and Drug Administration (FDA) is still very difficult. Another challenge is economic: for the rarest of these conditions (which is most of them), the market is so small that most companies have no financial incentive to pursue them.

To overcome these obstacles and provide hope for those with rare diseases, we need a new way of doing things. One way to do things differently—and more efficiently—is the recently launched Bespoke Gene Therapy Consortium (BGTC). It is a bold partnership of NIH, the FDA, 10 pharmaceutical companies, and several non-profit organizations [1]. Its aim: optimize the gene therapy development process and help fill the significant unmet medical needs of people with rare diseases.

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The technology aims to deliver cost and power consumption improvements for deep learning use cases of inference, the companies said. This development follows NeuReality’s emergence from stealth earlier in February with an $8 million seed round to accelerate AI workloads at scale.

AI inference is a growing area of focus for enterprises, because it’s the part of AI where neural networks actually are applied in real application and yield results. IBM and NeuReality claim their partnership will allow the deployment of computer vision, recommendation systems, natural language processing, and other AI use cases in critical sectors like finance, insurance, healthcare, manufacturing, and smart cities. They also claim the agreement will accelerate deployments in today’s ever-growing AI use cases, which are already deployed in public and private cloud datacenters.

NeuReality has competition in Cast AI, a technology company offering a platform that “allows developers to deploy, manage, and cost-optimize applications in multiple clouds simultaneously.” Some other competitors include Comet.ml, Upright Project, OctoML, Deci, and DeepCube. However, this partnership with IBM will see NeuReality become the first start-up semiconductor product member of the IBM Research AI Hardware Center and a licensee of the Center’s low-precision high performance Digital AI Cores.

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This company’s entry in the US; market; along with other aluminum giants is said to have caused the shutdown of a large number of Aluminum manufacturers based in the US. It seemed that local US companies were unable to compete with state backed companies which were taking advantage of the free trade agreement.

However, the trade tariffs along with recent events have in turn caused this firm to become insolvent. It’s founder is now being detained by the US under fraud charges.

China Zhongwang Holdings Limited is known as the “King of Aluminum in Asia. On October 15th, China Zhongwang suddenly announced its subsidiaries “had suffered significant losses and operational difficulties. Despite efforts from various parties, they are unable to solve the current problems on their own.” The two subsidiaries mentioned are the primary companies of the corporate business.
The debt crisis of Chinese companies is spreading, which can bring about a serious financial crisis in China. For example, China’s big business conglomerate, Baoneng Group, has experienced increasing strain on its capital chain. Currently, it has defaulted on at least nine items of trusts, involving a total of about $3.1 billion US dollars. Moreover, it has seen a rising risk factor for its subsidiaries, with frequent news about equity pledges, property freezes, and legal proceedings.

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There’s no question about it: climate technology is in again.

Over the past several quarters, entrepreneurial activity and investment interest in climate tech have skyrocketed. New funds devoted specifically to climate have launched at an astonishing rate in 2021: from blue-chip venture capital firms like Union Square Ventures, from large private equity players like TPG and General Atlantic, from a whole new breed of climate-specific VCs like Lowercarbon Capital. Scarcely a day goes by now without a climate tech startup announcing a major new funding round. A whopping $49 billion of venture capital funding will pour into climate tech in 2021.

BlackRock CEO Larry Fink aptly captured the current ebullience when he declared last week that “the next 1,000 unicorns” will be in climate tech.

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China’s economy — the 2nd-largest in the world — is teetering on the brink of disaster.

Since this spring, Beijing has canceled initial public offerings, fined tech companies billions for antitrust violations, forcibly shut down China’s entire for-profit education industry, and sent CEOs running for the exits to avoid the government’s ire. Even more dire, the Chinese megadeveloper Evergrande recently started missing payments on its more than $300 billion in debt, shaking global markets. The convulsions have woken the world up to a startling new possibility — that Beijing may be willing to allow some of its private corporate behemoths to collapse in a bid to reshape the economic model that made China a superpower.

The upheaval, spanning multiple industries and vast swaths of the country, is the result of one giant issue: China’s inability to borrow or buy its way out of its current economic crisis. For decades, the country relied on cheap labor and eye-popping amounts of debt, handed out by government-owned banks, to fuel economic growth — pouring money into massive apartment developments, factories, bridges, and other projects at lightning speed. Now the country needs people to actually use, and pay for, everything that’s been built. But the bulk of China’s population lacks the income needed to shift the economy from one driven by state investments to one sustained by consumer spending.

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Cell culture is an essential in vitro experimental tool. An attempt to recapitulate the body in a dish, in two and three dimensions, it has provided the basis for decades of research and probably thousands of PhDs. When it goes wrong, however, whether through accident, infection, misidentification, cross-contamination or uncontrolled differentiation (for stem cells), it can be very stressful, especially in the case of longer-term experiments or when using hard-to-replace cell lines. Another important consideration is reproducibility, which is an acknowledged life sciences industry issue. A 2015 PLOS Biol ogy study, for example, reported in an analysis of previous studies that the prevalence of irreproducible research was over 50% – equivalent to USD $28 billion per year on irreproducible preclinical research.1 Inconsistencies in cell culture approaches are a potential issue in this regard, as if cells are not maintained or used in a consistent way, or are contaminated with an infection (like mycoplasma), this can negatively impact results and make it more difficult to reproduce and/or accurately interpret data.

“Quality control (QC) is a key part of assuring the quality of outputs from any cell culture process, and is an essential part of assuring reproducibility of scientific quality in research as well as assurance of the quality and safety of cell culture-derived products,” comments Glyn N Stacey, International Stem Cell Banking Initiative, Cambridge, UK, and the Institute for Stem Cells and Regeneration and National Stem Cell Resource Centre, Chinese Academy of Sciences, Beijing, China. “These topics are currently very much in the minds of journal editors, research funders and regulators and are thus of crucial significance to researchers.”

This article will look at these different aspects of cell culture quality control and the types of protocols that can be implemented to help ensure reliable and reproducible results.

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Australian company AMSL Aero is preparing to start flight tests on what it claims will be the world’s most efficient eVTOL design, and one of the most affordable. This box-wing beauty, the Vertiia, will travel up to 1,000 km (620 miles) on a tank of hydrogen, carrying five people or 500 kg (1,100 lb) of cargo at a quick cruise speed of 300 km/h (186 mph).

First emerging from stealth mode late last year, AMSL has a unique design, a prototype nearly ready to fly, and a target date of 2024 to get its aircraft certified and into production. Its small team has achieved an impressive amount on a shoestring budget, and it’s now raising another round of funding to finance flight testing and pre-production as it moves toward the certification process.

We spoke to co-founder Andrew Moore to learn more about this fascinating aircraft, and how Vertiia plans to stand out in a global emerging eVTOL air taxi market that’s starting to look comically crowded. What follows is an edited transcript.

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Over the past few years, the business world has increasingly turned towards intelligent solutions to help cope with the changing digital landscape. Artificial intelligence (AI) enables devices and things to perceive, reason and act intuitively—mimicking the human brain, without being hindered by human subjectivity, ego and routine interruptions. The technology has the potential to greatly expand our capabilities, bringing added speed, efficiency and precision for tasks both complex and mundane.

To get a picture of the momentum behind AI, the global artificial intelligence market was valued at $62.35 billion in 2020 and is expected to expand at a compound annual growth rate (CAGR) of 40.2% from 2021 to 2028. Given this projection, it’s not surprising that tech giants such as AWS, IBM, Google and Qualcomm have all made significant investments into AI research, development, disparate impact testing and auditing.

My coverage area of expertise, fintech (financial technology), is no exception to this trend. The AI market for fintech alone is valued at an estimated $8 Billion and is projected to reach upwards of $27 Billion in the next five years. AI and machine learning (ML) have penetrated almost every facet of the space, from customer-facing functions to back-end processes. Let’s take a closer look at these changing dynamics.

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Fijitsu retrofitted one of it’s clean rooms in a vertical farm. The project was so successful, they discovered they could enter a new market segment and sell the systems themselves. I definately want one.

Like the giant monolith in Stanley Kubrick’s 2,001 this new head of lettuce is simultaneously a product of this factory’s past and the future. Fujitsu is a space-age R&D innovator with sprawling, specialized factories. But several of its facilities, including this one, went dark when the company tightened its belt and reorganized its product lines after the 2008 global financial crisis. Now in the aftermath, it has retrofitted this facilities to serve tomorrow’s vegetable consumers, who will pay for a better-than-organic product, and who enjoy a bowl of iceberg more if they know it was monitored by thousands of little sensors.

Like the giant monolith in Stanley Kubrick’s 2001, this new head of lettuce is simultaneously a product of this factory’s past and the future. Fujitsu is a space-age R&D innovator with sprawling, specialized factories. But several of its facilities, including this one, went dark when the company tightened its belt and reorganized its product lines after the 2008 global financial crisis. Now in the aftermath, it has retrofitted this facilities to serve tomorrow’s vegetable consumers, who will pay for a better-than-organic product, and who enjoy a bowl of iceberg more if they know it was monitored by thousands of little sensors.

A year into the project, Fujitsu is now producing between 2,500 and 3,000 heads of a lettuce a day that sell for three times the normal price: The company is using its hydroponic lettuce farm to showcase its “smart” farming technologies, in the hopes of nurturing a new agribusiness.

The project is the outgrowth of a company-wide reorganization following the 2008 financial crisis, after which Fujitsu decreased its number of product lines from nine to six. Originally built in 1,967 the building where the company is now growing lettuce was once the largest transistor factory in the world. Over the years, Fujitsu expanded, buying up three other buildings and the remainder of the industrial park, bringing its total footprint in the area to roughly 260,000 square meters.

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One form of “self-sacrifice” was to stand on the banks of the Nile and masturbate into the river as offering to honour Lord Amen (this sacred act was how Amen, Cyclical Eternity, came into being originally). Lots of the neurosis around today are because of the biblical view of “onanism” The term “Onanism” is associated with personal indulgence, or excess (even mortal sin for Catholics) perhaps giving rise to infantilised and repressed sexuality and a PANDEMIC of Christian paedophilia. 216,000 children — shouldn’t the Church in France be closed down?

The Church asks for forgiveness as an inquiry says it treated victims with “cruel indifference”.

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