F-test

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/F-test

An f-test pdf with d1 and d2 = 10, at a significance level of 0.05. (Red shaded region indicates the critical region)

An F-test is a statistical test that compares variances. It's used to determine if the variances of two samples, or if the ratios of variances among multiple samples, are significantly different. The test calculates a statistic, represented by the random variable F, and checks if it follows an F-distribution. This check is valid if the null hypothesis is true and standard assumptions about the errors (ε) in the data hold.

F-tests are frequently used to compare different statistical models and find the one that best describes the population the data came from. When models are created using the least squares method, the resulting F-tests are often called "exact" F-tests. The F-statistic was developed by Ronald Fisher in the 1920s as the variance ratio and was later named in his honor by George W. Snedecor.

Common examples

Common examples of the use of F-tests include the study of the following cases

• 

  One-way ANOVA table with 3 random groups that each has 30 observations. F value is being calculated in the second to last column

  The hypothesis that the means of a given set of normally distributed populations, all having the same standard deviation, are equal. This is perhaps the best-known F-test, and plays an important role in the analysis of variance (ANOVA).
  • F test of analysis of variance (ANOVA) follows three assumptions
    1. Normality (statistics)
    2. Homogeneity of variance
    3. Independence of errors and random sampling

• The hypothesis that a proposed regression model fits the data well. See Lack-of-fit sum of squares.
• The hypothesis that a data set in a regression analysis follows the simpler of two proposed linear models that are nested within each other.
• Multiple-comparison testing is conducted using needed data in already completed F-test, if F-test leads to rejection of null hypothesis and the factor under study has an impact on the dependent variable.
  • "a priori comparisons"/ "planned comparisons"- a particular set of comparisons
  • "pairwise comparisons"-all possible comparisons
    • i.e. Fisher's least significant difference (LSD) test, Tukey's honestly significant difference (HSD) test, Newman Keuls test, Ducan's test
  • "a posteriori comparisons"/ "post hoc comparisons"/ "exploratory comparisons"- choose comparisons after examining the data
    • i.e. Scheffé's method

F-test of the equality of two variances

Main article: F-test of equality of variances

The F-test is sensitive to non-normality. In the analysis of variance (ANOVA), alternative tests include Levene's test, Bartlett's test, and the Brown–Forsythe test. However, when any of these tests are conducted to test the underlying assumption of homoscedasticity (i.e. homogeneity of variance), as a preliminary step to testing for mean effects, there is an increase in the experiment-wise Type I error rate.

Formula and calculation

Most F-tests arise by considering a decomposition of the variability in a collection of data in terms of sums of squares. The test statistic in an F-test is the ratio of two scaled sums of squares reflecting different sources of variability. These sums of squares are constructed so that the statistic tends to be greater when the null hypothesis is not true. In order for the statistic to follow the F-distribution under the null hypothesis, the sums of squares should be statistically independent, and each should follow a scaled χ²-distribution. The latter condition is guaranteed if the data values are independent and normally distributed with a common variance.

One-way analysis of variance

The formula for the one-way ANOVA F-test statistic is

${\displaystyle F=\frac{\text{explained variance}}{\text{unexplained variance}},}$

or

${\displaystyle F=\frac{\text{between-group variability}}{\text{within-group variability}}.}$

The "explained variance", or "between-group variability" is

${\displaystyle \sum _{i=1}^K{n}_i({\overline{Y}}_{i\cdot }-\overline{Y}{)}^2/(K-1)}$

where ${\displaystyle {\overline{Y}}_{i\cdot }}$ denotes the sample mean in the i-th group, ${\displaystyle n_i}$ is the number of observations in the i-th group, ${\displaystyle \overline{Y}}$ denotes the overall mean of the data, and ${\displaystyle K}$ denotes the number of groups.

The "unexplained variance", or "within-group variability" is

${\displaystyle \sum _{i=1}^K\sum _{j=1}^{n_i}{\left(Y_{ij}-{\overline{Y}}_{i\cdot }\right)}^2/(N-K),}$

where ${\displaystyle Y_{ij}}$ is the j^th observation in the i^th out of ${\displaystyle K}$ groups and ${\displaystyle N}$ is the overall sample size. This F-statistic follows the F-distribution with degrees of freedom ${\displaystyle d_1=K-1}$ and ${\displaystyle d_2=N-K}$ under the null hypothesis. The statistic will be large if the between-group variability is large relative to the within-group variability, which is unlikely to happen if the population means of the groups all have the same value.

F Table: Level 5% Critical values, containing degrees of freedoms for both denominator and numerator ranging from 1-20

The result of the F test can be determined by comparing calculated F value and critical F value with specific significance level (e.g. 5%). The F table serves as a reference guide containing critical F values for the distribution of the F-statistic under the assumption of a true null hypothesis. It is designed to help determine the threshold beyond which the F statistic is expected to exceed a controlled percentage of the time (e.g., 5%) when the null hypothesis is accurate. To locate the critical F value in the F table, one needs to utilize the respective degrees of freedom. This involves identifying the appropriate row and column in the F table that corresponds to the significance level being tested (e.g., 5%).

How to use critical F values:

If the F statistic < the critical F value

• Fail to reject null hypothesis
• Reject alternative hypothesis
• There is no significant differences among sample averages
• The observed differences among sample averages could be reasonably caused by random chance itself
• The result is not statistically significant

If the F statistic > the critical F value

• Accept alternative hypothesis
• Reject null hypothesis
• There is significant differences among sample averages
• The observed differences among sample averages could not be reasonably caused by random chance itself
• The result is statistically significant

Note that when there are only two groups for the one-way ANOVA F-test, ${\displaystyle F=t^2}$where t is the Student's ${\displaystyle t}$ statistic.

Advantages

• Multi-group Comparison Efficiency: Facilitating simultaneous comparison of multiple groups, enhancing efficiency particularly in situations involving more than two groups.
• Clarity in Variance Comparison: Offering a straightforward interpretation of variance differences among groups, contributing to a clear understanding of the observed data patterns.
• Versatility Across Disciplines: Demonstrating broad applicability across diverse fields, including social sciences, natural sciences, and engineering.

Disadvantages

• Sensitivity to Assumptions: The F-test is highly sensitive to certain assumptions, such as homogeneity of variance and normality which can affect the accuracy of test results.
• Limited Scope to Group Comparisons: The F-test is tailored for comparing variances between groups, making it less suitable for analyses beyond this specific scope.
• Interpretation Challenges: The F-test does not pinpoint specific group pairs with distinct variances. Careful interpretation is necessary, and additional post hoc tests are often essential for a more detailed understanding of group-wise differences.

Multiple-comparison ANOVA problems

The F-test in one-way analysis of variance (ANOVA) is used to assess whether the expected values of a quantitative variable within several pre-defined groups differ from each other. For example, suppose that a medical trial compares four treatments. The ANOVA F-test can be used to assess whether any of the treatments are on average superior, or inferior, to the others versus the null hypothesis that all four treatments yield the same mean response. This is an example of an "omnibus" test, meaning that a single test is performed to detect any of several possible differences. Alternatively, we could carry out pairwise tests among the treatments (for instance, in the medical trial example with four treatments we could carry out six tests among pairs of treatments). The advantage of the ANOVA F-test is that we do not need to pre-specify which treatments are to be compared, and we do not need to adjust for making multiple comparisons. The disadvantage of the ANOVA F-test is that if we reject the null hypothesis, we do not know which treatments can be said to be significantly different from the others, nor, if the F-test is performed at level α, can we state that the treatment pair with the greatest mean difference is significantly different at level α.

Regression problems

Further information: Stepwise regression

Consider two models, 1 and 2, where model 1 is 'nested' within model 2. Model 1 is the restricted model, and model 2 is the unrestricted one. That is, model 1 has p₁ parameters, and model 2 has p₂ parameters, where p₁ < p₂, and for any choice of parameters in model 1, the same regression curve can be achieved by some choice of the parameters of model 2.

One common context in this regard is that of deciding whether a model fits the data significantly better than does a naive model, in which the only explanatory term is the intercept term, so that all predicted values for the dependent variable are set equal to that variable's sample mean. The naive model is the restricted model, since the coefficients of all potential explanatory variables are restricted to equal zero.

Another common context is deciding whether there is a structural break in the data: here the restricted model uses all data in one regression, while the unrestricted model uses separate regressions for two different subsets of the data. This use of the F-test is known as the Chow test.

The model with more parameters will always be able to fit the data at least as well as the model with fewer parameters. Thus typically model 2 will give a better (i.e. lower error) fit to the data than model 1. But one often wants to determine whether model 2 gives a significantly better fit to the data. One approach to this problem is to use an F-test.

If there are n data points to estimate parameters of both models from, then one can calculate the F statistic, given by

${\displaystyle F=\frac{\left(\frac{{\text{RSS}}_1-{\text{RSS}}_2}{p_2-p_1}\right)}{\left(\frac{{\text{RSS}}_2}{n-p_2}\right)}=\frac{{\text{RSS}}_1-{\text{RSS}}_2}{{\text{RSS}}_2}\cdot \frac{n-p_2}{p_2-p_1},}$

where RSS_i is the residual sum of squares of model i. If the regression model has been calculated with weights, then replace RSS_i with χ², the weighted sum of squared residuals. Under the null hypothesis that model 2 does not provide a significantly better fit than model 1, F will have an F distribution, with (p₂−p₁, n−p₂) degrees of freedom. The null hypothesis is rejected if the F calculated from the data is greater than the critical value of the F-distribution for some desired false-rejection probability (e.g. 0.05). Since F is a monotone function of the likelihood ratio statistic, the F-test is a likelihood ratio test.

Gene delivery

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Gene_delivery

Gene delivery is the process of introducing foreign genetic material, such as DNA or RNA, into host cells. Gene delivery must reach the genome of the host cell to induce gene expression. Successful gene delivery requires the foreign gene delivery to remain stable within the host cell and can either integrate into the genome or replicate independently of it. This requires foreign DNA to be synthesized as part of a vector, which is designed to enter the desired host cell and deliver the transgene to that cell's genome. Vectors utilized as the method for gene delivery can be divided into two categories, recombinant viruses and synthetic vectors (viral and non-viral).

In complex multicellular eukaryotes (more specifically Weissmanists), if the transgene is incorporated into the host's germline cells, the resulting host cell can pass the transgene to its progeny. If the transgene is incorporated into somatic cells, the transgene will stay with the somatic cell line, and thus its host organism.

Gene delivery is a necessary step in gene therapy for the introduction or silencing of a gene to promote a therapeutic outcome in patients and also has applications in the genetic modification of crops. There are many different methods of gene delivery for various types of cells and tissues.

History

Viral based vectors emerged in the 1980s as a tool for transgene expression. In 1983, Albert Siegel described the use of viral vectors in plant transgene expression although viral manipulation via cDNA cloning was not yet available. The first virus to be used as a vaccine vector was the vaccinia virus in 1984 as a way to protect chimpanzees against hepatitis B. Non-viral gene delivery was first reported on in 1943 by Avery et al. who showed cellular phenotype change via exogenous DNA exposure.

Methods

Bacterial transformation involves moving a gene from one bacteria to another. It is integrated into the recipients plasmid. and can then be expressed by the new host.

There are a variety of methods available to deliver genes to host cells. When genes are delivered to bacteria or plants the process is called transformation and when it is used to deliver genes to animals it is called transfection. This is because transformation has a different meaning in relation to animals, indicating progression to a cancerous state. For some bacteria no external methods are need to introduce genes as they are naturally able to take up foreign DNA. Most cells require some sort of intervention to make the cell membrane permeable to DNA and allow the DNA to be stably inserted into the hosts genome.

Chemical

Chemical based methods of gene delivery can use natural or synthetic compounds to form particles that facilitate the transfer of genes into cells. These synthetic vectors have the ability to electrostatically bind DNA or RNA and compact the genetic information to accommodate larger genetic transfers. Chemical vectors usually enter cells by endocytosis and can protect genetic material from degradation.

Heat shock

One of the simplest method involves altering the environment of the cell and then stressing it by giving it a heat shock. Typically the cells are incubated in a solution containing divalent cations (often calcium chloride) under cold conditions, before being exposed to a heat pulse. Calcium chloride partially disrupts the cell membrane, which allows the recombinant DNA to enter the host cell. It is suggested that exposing the cells to divalent cations in cold condition may change or weaken the cell surface structure, making it more permeable to DNA. The heat-pulse is thought to create a thermal imbalance across the cell membrane, which forces the DNA to enter the cells through either cell pores or the damaged cell wall.

Calcium phosphate

Another simple methods involves using calcium phosphate to bind the DNA and then exposing it to cultured cells. The solution, along with the DNA, is encapsulated by the cells and a small amount of DNA can be integrated into the genome.

Liposomes and polymers

Liposomes and polymers can be used as vectors to deliver DNA into cells. Positively charged liposomes bind with the negatively charged DNA, while polymers can be designed that interact with DNA. They form lipoplexes and polyplexes respectively, which are then up-taken by the cells. The two systems can also be combined. Polymer-based non-viral vectors uses polymers to interact with DNA and form polyplexes.

Nanoparticles

The use of engineered inorganic and organic nanoparticles is another non-viral approach for gene delivery.

Physical

Artificial gene delivery can be mediated by physical methods which uses force to introduce genetic material through the cell membrane.

Electroporation

Electroporators can be used to make the cell membrane permeable to DNA

Electroporation is a method of promoting competence. Cells are briefly shocked with an electric field of 10-20 kV/cm, which is thought to create holes in the cell membrane through which the plasmid DNA may enter. After the electric shock, the holes are rapidly closed by the cell's membrane-repair mechanisms.

Biolistics

A gene gun uses biolistics to insert DNA into cells

Another method used to transform plant cells is biolistics, where particles of gold or tungsten are coated with DNA and then shot into young plant cells or plant embryos. Some genetic material enters the cells and transforms them. This method can be used on plants that are not susceptible to Agrobacterium infection and also allows transformation of plant plastids. Plants cells can also be transformed using electroporation, which uses an electric shock to make the cell membrane permeable to plasmid DNA. Due to the damage caused to the cells and DNA the transformation efficiency of biolistics and electroporation is lower than agrobacterial transformation.

Microinjection

Microinjection is where DNA is injected through the cell's nuclear envelope directly into the nucleus.

Sonoporation

Sonoporation is the transient permeation of cell membranes assisted by ultrasound, typically in the presence of gas microbubbles. Sonoporation allows for the entry of genetic material into cells.

Photoporation

Photoporation is when laser pulses are used to create pores in a cell membrane to allow entry of genetic material.

Magnetofection

Magnetofection uses magnetic particles complexed with DNA and an external magnetic field concentrate nucleic acid particles into target cells.

Hydroporation

A hydrodynamic capillary effect can be used to manipulate cell permeability.

Agrobacterium

A. tumefaciens attaching itself to a carrot cell

In plants the DNA is often inserted using Agrobacterium-mediated recombination, taking advantage of the Agrobacteriums T-DNA sequence that allows natural insertion of genetic material into plant cells. Plant tissue are cut into small pieces and soaked in a fluid containing suspended Agrobacterium. The bacteria will attach to many of the plant cells exposed by the cuts. The bacteria uses conjugation to transfer a DNA segment called T-DNA from its plasmid into the plant. The transferred DNA is piloted to the plant cell nucleus and integrated into the host plants genomic DNA.The plasmid T-DNA is integrated semi-randomly into the genome of the host cell.

By modifying the plasmid to express the gene of interest, researchers can insert their chosen gene stably into the plants genome. The only essential parts of the T-DNA are its two small (25 base pair) border repeats, at least one of which is needed for plant transformation. The genes to be introduced into the plant are cloned into a plant transformation vector that contains the T-DNA region of the plasmid. An alternative method is agroinfiltration.

Viral delivery

Foreign DNA being transduced into the host cell through an adenovirus vector.

Virus mediated gene delivery utilizes the ability of a virus to inject its DNA inside a host cell and takes advantage of the virus' own ability to replicate and implement their own genetic material. Viral methods of gene delivery are more likely to induce an immune response, but they have high efficiency. Transduction is the process that describes virus-mediated insertion of DNA into the host cell. Viruses are a particularly effective form of gene delivery because the structure of the virus prevents degradation via lysosomes of the DNA it is delivering to the nucleus of the host cell. In gene therapy a gene that is intended for delivery is packaged into a replication-deficient viral particle to form a viral vector. Viruses used for gene therapy to date include retrovirus, adenovirus, adeno-associated virus and herpes simplex virus. However, there are drawbacks to using viruses to deliver genes into cells. Viruses can only deliver very small pieces of DNA into the cells, it is labor-intensive and there are risks of random insertion sites, cytopathic effects and mutagenesis.

Viral vector based gene delivery uses a viral vector to deliver genetic material to the host cell. This is done by using a virus that contains the desired gene and removing the part of the viruses genome that is infectious. Viruses are efficient at delivering genetic material to the host cell's nucleus, which is vital for replication.

RNA-based viral vectors

RNA-based viruses were developed because of the ability to transcribe directly from infectious RNA transcripts. RNA vectors are quickly expressed and expressed in the targeted form since no processing is required [source needed]. Retroviral vectors include oncoretroviral, lentiviral and human foamy virus are RNA-based viral vectors that reverse transcript and integrated into the host genome, permits long-term transgene expression.

DNA-based viral vectors

DNA-based viral vectors include Adenoviridae, adeno-associated virus and herpes simplex virus.

Applications

Gene therapy

Main article: Gene therapy

Several of the methods used to facilitate gene delivery have applications for therapeutic purposes. Gene therapy utilizes gene delivery to deliver genetic material with the goal of treating a disease or condition in the cell. Gene delivery in therapeutic settings utilizes non-immunogenic vectors capable of cell specificity that can deliver an adequate amount of transgene expression to cause the desired effect.

Advances in genomics have enabled a variety of new methods and gene targets to be identified for possible applications. DNA microarrays used in a variety of next-gen sequencing can identify thousands of genes simultaneously, with analytical software looking at gene expression patterns, and orthologous genes in model species to identify function. This has allowed a variety of possible vectors to be identified for use in gene therapy. As a method for creating a new class of vaccine, gene delivery has been utilized to generate a hybrid biosynthetic vector to deliver a possible vaccine. This vector overcomes traditional barriers to gene delivery by combining E. coli with a synthetic polymer to create a vector that maintains plasmid DNA while having an increased ability to avoid degradation by target cell lysosomes.

Cloud storage

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Cloud_storage

Cloud storage is a model of computer data storage in which data, said to be on "the cloud", is stored remotely in logical pools and is accessible to users over a network, typically the Internet. The physical storage spans multiple servers (sometimes in multiple locations), and the physical environment is typically owned and managed by a cloud computing provider. These cloud storage providers are responsible for keeping the data available and accessible, and the physical environment secured, protected, and running. People and organizations buy or lease storage capacity from the providers to store user, organization, or application data.

Cloud storage services may be accessed through a colocated cloud computing service, a web service application programming interface (API) or by applications that use the API, such as cloud desktop storage, a cloud storage gateway or Web-based content management systems.

History

Cloud computing is believed to have been invented by J. C. R. Licklider in the 1960s with his work on ARPANET to connect people and data from anywhere at any time.

In 1983, CompuServe offered its consumer users a small amount of disk space that could be used to store any files they chose to upload.

In 1994, AT&T launched PersonaLink Services, an online platform for personal and business communication and entrepreneurship. The storage was one of the first to be all web-based, and referenced in their commercials as, "you can think of our electronic meeting place as the cloud." Amazon Web Services introduced their cloud storage service Amazon S3 in 2006, and has gained widespread recognition and adoption as the storage supplier to popular services such as SmugMug, Dropbox, and Pinterest. In 2005, Box announced an online file sharing and personal cloud content management service for businesses.

Architecture

A high level architecture of cloud storage

Cloud storage is based on highly virtualized infrastructure and is like broader cloud computing in terms of interfaces, near-instant elasticity and scalability, multi-tenancy, and metered resources. Cloud storage services can be used from an off-premises service (Amazon S3) or deployed on-premises (ViON Capacity Services).

There are three types of cloud storage: a hosted object storage service, file storage, and block storage. Each of these cloud storage types offer their own unique advantages.

Examples of object storage services that can be hosted and deployed with cloud storage characteristics include Amazon S3, Oracle Cloud Storage and Microsoft Azure Storage, object storage software like Openstack Swift, object storage systems like EMC Atmos, EMC ECS and Hitachi Content Platform, and distributed storage research projects like OceanStore and VISION Cloud.

Examples of file storage services include Amazon Elastic File System (EFS) and Qumulo Core, used for applications that need access to shared files and require a file system. This storage is often supported with a Network Attached Storage (NAS) server, used for large content repositories, development environments, media stores, or user home directories.

A block storage service like Amazon Elastic Block Store (EBS) is used for other enterprise applications like databases and often require dedicated, low latency storage for each host. This is comparable in certain respects to direct attached storage (DAS) or a storage area network (SAN).

Cloud storage is:

• Made up of many distributed resources, but still acts as one, either in a federated or a cooperative storage cloud architecture
• Highly fault tolerant through redundancy and distribution of data
• Highly durable through the creation of versioned copies
• Typically eventually consistent with regard to data replicas

Advantages

• Companies need only pay for the storage they actually use, typically an average of consumption during a month, quarter, or year. This does not mean that cloud storage is less expensive, only that it incurs operating expenses rather than capital expenses.
• Businesses using cloud storage can cut their energy consumption by up to 70% making them a more green business.
• Organizations can choose between off-premises and on-premises cloud storage options, or a mixture of the two options, depending on relevant decision criteria that is complementary to initial direct cost savings potential; for instance, continuity of operations (COOP), disaster recovery (DR), security (PII, HIPAA, SARBOX, IA/CND), and records retention laws, regulations, and policies.
• Storage availability and data protection is intrinsic to object storage architecture, so depending on the application, the additional technology, effort and cost to add availability and protection can be eliminated.
• Storage maintenance tasks, such as purchasing additional storage capacity, are offloaded to the responsibility of a service provider.
• Cloud storage provides users with immediate access to a broad range of resources and applications hosted in the infrastructure of another organization via a web service interface.
• Cloud storage can be used for copying virtual machine images from the cloud to on-premises locations or to import a virtual machine image from an on-premises location to the cloud image library. In addition, cloud storage can be used to move virtual machine images between user accounts or between data centers.
• Cloud storage can be used as natural disaster proof backup, as normally there are 2 or 3 different backup servers located in different places around the globe.
• Cloud storage can be mapped as a local drive with the WebDAV protocol. It can function as a central file server for organizations with multiple office locations.

Potential concerns

Data security

See also: Cloud computing security

Outsourcing data storage increases the attack surface area.

1. When data has been distributed it is stored at more locations increasing the risk of unauthorized physical access to the data. For example, in cloud based architecture, data is replicated and moved frequently so the risk of unauthorized data recovery increases dramatically. Such as in the case of disposal of old equipment, reuse of drives, reallocation of storage space. The manner that data is replicated depends on the service level a customer chooses and on the service provided. When encryption is in place it can ensure confidentiality. Crypto-shredding can be used when disposing of data (on a disk).
2. The number of people with access to the data who could be compromised (e.g., bribed, or coerced) increases dramatically. A single company might have a small team of administrators, network engineers, and technicians, but a cloud storage company will have many customers and thousands of servers, therefore a much larger team of technical staff with physical and electronic access to almost all of the data at the entire facility or perhaps the entire company. Decryption keys that are kept by the service user, as opposed to the service provider, limit access to data by service provider employees. As for sharing multiple data in the cloud with multiple users, a large number of keys has to be distributed to users via secure channels for decryption, also it has to be securely stored and managed by the users in their devices. Storing these keys requires rather expensive secure storage. To overcome that, key-aggregate cryptosystem can be used.
3. It increases the number of networks over which the data travels. Instead of just a local area network (LAN) or storage area network (SAN), data stored on a cloud requires a WAN (wide area network) to connect them both.
4. By sharing storage and networks with many other users/customers it is possible for other customers to access your data. Sometimes because of erroneous actions, faulty equipment, a bug and sometimes because of criminal intent. This risk applies to all types of storage and not only cloud storage. The risk of having data read during transmission can be mitigated through encryption technology. Encryption in transit protects data as it is being transmitted to and from the cloud service. Encryption at rest protects data that is stored at the service provider. Encrypting data in an on-premises cloud service on-ramp system can provide both kinds of encryption protection.

There are several options available to avoid security issues. One option is to use a private cloud instead of a public cloud. Another option is to ingest data in an encrypted format where the key is held within the on-premise infrastructure. To this end, access is often by use of on-premise cloud storage gateways that have options to encrypt the data prior of transfer.

Longevity

See also: Financial statement analysis

Companies are not permanent and the services and products they provide can change. Outsourcing data storage to another company needs careful investigation and nothing is ever certain. Contracts set in stone can be worthless when a company ceases to exist or its circumstances change. Companies can:

1. Go bankrupt.
2. Expand and change their focus.
3. Be purchased by other larger companies.
4. Be purchased by a company headquartered in or move to a country that negates compliance with export restrictions and thus necessitates a move.
5. Suffer an irrecoverable disaster.

Accessibility

• Performance for outsourced storage is likely to be lower than local storage, depending on how much a customer is willing to spend for WAN bandwidth
• Reliability and availability depends on wide area network availability and on the level of precautions taken by the service provider. Reliability should be based on hardware as well as various algorithms used.

Limitations of Service Level Agreements

Typically, cloud storage Service Level Agreements (SLAs) do not encompass all forms of service interruptions. Exclusions typically include planned maintenance, downtime resulting from external factors such as network issues, human errors like misconfigurations, natural disasters, force majeure events, or security breaches. Typically, customers bear the responsibility of monitoring SLA compliance and must file claims for any unmet SLAs within a designated timeframe. Customers should be aware of how deviations from SLAs are calculated, as these parameters may vary by other services offered within the same provider. These requirements can place a considerable burden on customers. Additionally, SLA percentages and conditions can differ across various services within the same provider, with some services lacking any SLA altogether. In cases of service interruptions due to hardware failures in the cloud provider, service providers typically do not offer monetary compensation. Instead, eligible users may receive credits as outlined in the corresponding SLA. 

Other concerns

• Security of stored data and data in transit may be a concern when storing sensitive data at a cloud storage provider
• Users with specific records-keeping requirements, such as public agencies that must retain electronic records according to statute, may encounter complications with using cloud computing and storage. For instance, the U.S. Department of Defense designated the Defense Information Systems Agency (DISA) to maintain a list of records management products that meet all of the records retention, personally identifiable information (PII), and security (Information Assurance; IA) requirements
• Cloud storage is a rich resource for both hackers and national security agencies. Because the cloud holds data from many different users and organizations, hackers see it as a very valuable target.
• Piracy and copyright infringement may be enabled by sites that permit filesharing. For example, the CodexCloud ebook storage site has faced litigation from the owners of the intellectual property uploaded and shared there, as have the Grooveshark and YouTube sites it has been compared to.
• The legal aspect, from a regulatory compliance standpoint, is of concern when storing files domestically and especially internationally.
• The resources used to produce large data centers, especially those needed to power them, is causing nations to drastically increase their energy production. This can lead to further climate damaging implications.

Hybrid cloud storage

Main article: Hybrid cloud storage

Hybrid cloud storage is a term for a storage infrastructure that uses a combination of on-premises storage resources with cloud storage. The on-premises storage is usually managed by the organization, while the public cloud storage provider is responsible for the management and security of the data stored in the cloud. Hybrid cloud storage can be implemented by an on-premises cloud storage gateway that presents a file system or object storage interface which the users can access in the same way they would access a local storage system. The cloud storage gateway transparently transfers the data to and from the cloud storage service, providing low latency access to the data through a local cache.

Hybrid cloud storage can be used to supplement an organization's internal storage resources, or it can be used as the primary storage infrastructure. In either case, hybrid cloud storage can provide organizations with greater flexibility and scalability than traditional on-premises storage infrastructure.

There are several benefits to using hybrid cloud storage, including the ability to cache frequently used data on-site for quick access, while inactive cold data is stored off-site in the cloud. This can save space, reduce storage costs and improve performance. Additionally, hybrid cloud storage can provide organizations with greater redundancy and fault tolerance, as data is stored in both on-premises and cloud storage infrastructure.

Mosquito massacre: Can we safely tackle malaria with a CRISPR gene drive?

Ricki Lewis | August 16, 2024

From the Genetic Literacy Project https://geneticliteracyproject.org/

CRISPR-Cas9 gene editing quickly decimated two caged populations of malaria-bearing mosquitoes (Anopheles gambiae) in a recent study, introducing a new way to solve an age-old problem. But the paper describing the feat in Nature Biotechnology had a broader meaning regarding the value of basic research. It also prompts us to consider the risks and rewards of releasing such a powerful gene drive into the wild.

Instead of altering a gene affecting production of a reproductive hormone, the editing has a more fundamental target: a gene that determines sex. The work was done by Andrea Crisanti and colleagues at Imperial College London. Their clever use of the ancient insect mutation doublesex rang a bell for me — I’d used a fruit fly version in grad school.

Blast from the past

In the days before genome sequencing, geneticists made mutants in model organisms like fruit flies to discover gene functions. I worked on mutations that mix up body parts.

To make mutants, I’d poison larvae or schlep them, squiggling through the goop in their old-fashioned milk bottles, from the lab at Indiana University in Bloomington to the children’s cancer center in Indianapolis and zap them with x-rays. Crossing the grown-up larvae to flies that carried already-known mutations would reveal whether we’d induced anything of interest in their offspring. One of the mutations we used in these genetic screens was doublesex.

A suite of genes determines sex in insects, not just inheriting an X or Y chromosome. Doublesex acts at a developmental crossroads to select the pathway towards femaleness or maleness. When the gene is missing or mutant, flies display a mishmash of sexual parts and altered behavior. Males with doublesex mutations “are impaired in their willingness to court females,” according to one study, and when they do seek sex, they can’t hum appropriately and “court other males at abnormally high levels.”

Back then, we used doublesex as a tool to identify new mutations. We never imagined it being used to prevent an infectious disease that causes nearly half a million deaths a year, mostly among young children.

A gene drive skews inheritance, destroying fertility

In grad school, we bred flies for many generations to select a trait, because a mutation in a carrier passes to only half the offspring. A gene drive speeds things by messing with Mendel’s first law, which says that at each generation, each member of a pair of gene variants (alleles) gets sent into a sperm or egg with equal frequency.

Austin Burt, a co-author of the new paper, introduced the idea of a gene drive in 2003, pre-CRISPR. The intervention uses a version of natural DNA repair that snips out one copy of a gene and replaces it with a copy of whatever corresponding allele is on the paired chromosome. Imagine dance partners, removing one, and inserting an identical twin of the other.

In the language of genetics, a gene drive can turn a heterozygote (2 different copies of a gene) into a homozygote (2 identical copies).

In 2014, Kevin Esvelt, George Church, and their colleagues at Harvard suggested how to use CRISPR-Cas9 gene editing to speed a gene drive. It made so much sense that in 2016, the National Academies of Sciences, Engineering, and Medicine issued a report urging caution while endorsing continued laboratory experimentation and limited field trials of gene drives.

The idea to genetically cripple mosquito reproduction isn’t new. But a CRISPRed gene drive to do so would be fast, leading to mass sterility within a few generations, with the population plummeting towards extinction. And doublesex is an inspired target. It’s so vital that only one variant in Anopheles gambiae is known in the wild — any other mutations so impair the animals that they and their genes don’t persist. That’s why the gene can’t mutate itself back into working, like bacteria developing antibiotic resistance. For doublesex, resistance is futile.

Harnessing doublesex

The doublesex gene consists of 7 protein-encoding exons and the introns that separate them. The gene is alternatively spliced: mosquitoes keeping exon 5 become females and those that jettison the exon develop as males.

The researchers injected mosquito embryos with CRISPR-Cas9 engineered to harpoon the boundary between intron 4 and exon 5 of the doublesex gene. They added genetic instructions for red fluorescent protein on the Y chromosome to mark male gonads, so the researchers could distinguish the sexes.

The modified female mosquitoes were weird. They sported male clasper organs rotated the wrong way and lacked parts of the female sex organ repertoire. They had feathery male-like “plumose antennae,” neither ovaries nor female sperm holders, yet male accessory glands and in some individuals “rudimentary pear-shaped organs resembling unstructured testes.” Most importantly, the doctored females couldn’t bite or suck up blood meals.

Malaria parasites infect two blood cells. Credit: Lennart Nilsson / Scanpix

The researchers set up two cages, each housing 300 females with normal doublesex genes, 150 normal males, and 150 males that had one copy of normal doublesex and one modified copy, called CRISPRh. Then the insects mated. (For a scintillating description of fly sex see A Fruit Fly Love Story: The Making of a Mutant.)

Within 7 generations in one cage and 11 in the other, all the female flies had CRISPRh and couldn’t mate. Because males with one copy of CRISPRh are fertile, the populations chugged along until the gene drive rendered all the females homozygous. With two copies of the modified doublesex gene, they couldn’t eat or mate.

Next steps

Gene editing of doublesex presents a question of balance. The investigators dub it “an Achilles heel” common to many insect species, yet at the same time, the DNA sequences are species-specific enough to not spread to other types of insects. A gene drive that kills off bees or aphids, for example, would be disastrous.

Next will come experiments in “large confined spaces” more like nature. Cooped up, mosquitoes don’t have much to do besides breed. In a more natural setting, they’d have to compete for resources and mates, confront changing conditions, and avoid being eaten. But computer simulations suggest that adding these stresses would only slightly slow spread of the gene drive.

Field tests are 5 to 10 years in the future, the researchers say. Dr. Burt estimates that releasing a few hundred doctored mosquitoes at a time, into selected African villages, might knock down populations sufficiently to wipe them out, even over a wider range. Local eradication of malaria would take about 15 years once a gene drive begins, he projects.

Will nature find a way around gene drives?

What about “unforeseen consequences” of unleashing a gene drive to vanquish malaria-bearing mosquitoes? To quote fictional mathematician Ian Malcolm in discussing the cloned dinosaurs of Jurassic Park, “Your scientists were so preoccupied with whether they could, they didn’t stop to think if they should.”

We’re past the “could” stage with a doublesex-mediated gene drive against the mosquitoes. But perhaps we shouldn’t ignore the history of biotechnology. Even though no superbugs or triple-headed purple monsters have escaped from recombinant DNA labs since self-policing began at the Asilomar meeting in 1975, pollen from genetically modified crops has wafted well beyond treated fields. Sometimes, as Dr. Malcolm said, “life, uh, finds a way.”

Yet the severity and persistence of malaria may justify the risk of unforeseen consequences in developing a gene drive.

About 216 million malaria cases occurred globally in 2016, with an estimated 445,000 deaths, according to the WHO’s World Malaria Report 2017, which states that “after an unprecedented period of success in global malaria control, progress has stalled.” Said Dr. Crisanti, “2016 marked the first time in over two decades that malaria cases did not fall despite huge efforts and resources, suggesting we need more tools in the fight. This breakthrough shows that a gene drive can work, providing hope in the fight against a disease that has plagued mankind for centuries.”

Just like recombinant DNA entered the clinic in 1982 with FDA approval of human insulin produced in bacteria, the first gene drive, whatever it may deliver, could open the door for many others, just as dozens of drugs are now based on combining genes of different species. Doublesex, the mutation that I used in graduate school to screen new mutations, is one gene of thousands in just that one species. If and when gene drives are validated, the possibilities to limit or eradicate infectious diseases are almost limitless, thanks to the genetic toolboxes provided from decades of basic research.

Ricki Lewis has a PhD in genetics and is a science writer and author of several human genetics books. She is an adjunct professor for the Alden March Bioethics Institute at Albany Medical College. Follow her at her website or Twitter @rickilewis

This story was originally published at the GLP on October 2, 2018.

Mutagenesis (molecular biology technique)

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Mutagenesis_(molecular_biology_technique)

Types of mutations that can be introduced by random, site-directed, combinatorial, or insertional mutagenesis

In molecular biology, mutagenesis is an important laboratory technique whereby DNA mutations are deliberately engineered to produce libraries of mutant genes, proteins, strains of bacteria, or other genetically modified organisms. The various constituents of a gene, as well as its regulatory elements and its gene products, may be mutated so that the functioning of a genetic locus, process, or product can be examined in detail. The mutation may produce mutant proteins with interesting properties or enhanced or novel functions that may be of commercial use. Mutant strains may also be produced that have practical application or allow the molecular basis of a particular cell function to be investigated.

Many methods of mutagenesis exist today. Initially, the kind of mutations artificially induced in the laboratory were entirely random using mechanisms such as UV irradiation. Random mutagenesis cannot target specific regions or sequences of the genome; however, with the development of site-directed mutagenesis, more specific changes can be made. Since 2013, development of the CRISPR/Cas9 technology, based on a prokaryotic viral defense system, has allowed for the editing or mutagenesis of a genome in vivo. Site-directed mutagenesis has proved useful in situations that random mutagenesis is not. Other techniques of mutagenesis include combinatorial and insertional mutagenesis. Mutagenesis that is not random can be used to clone DNA, investigate the effects of mutagens, and engineer proteins. It also has medical applications such as helping immunocompromised patients, research and treatment of diseases including HIV and cancers, and curing of diseases such as beta thalassemia.

Random mutagenesis

How DNA libraries generated by random mutagenesis sample sequence space. The amino acid substituted into a given position is shown. Each dot or set of connected dots is one member of the library. Error-prone PCR randomly mutates some residues to other amino acids. Alanine scanning replaces each residue of the protein with alanine, one-by-one. Site saturation substitutes each of the 20 possible amino acids (or some subset of them) at a single position, one-by-one.

Early approaches to mutagenesis relied on methods which produced entirely random mutations. In such methods, cells or organisms are exposed to mutagens such as UV radiation or mutagenic chemicals, and mutants with desired characteristics are then selected. Hermann Muller discovered in 1927 that X-rays can cause genetic mutations in fruit flies, and went on to use the mutants he created for his studies in genetics. For Escherichia coli, mutants may be selected first by exposure to UV radiation, then plated onto an agar medium. The colonies formed are then replica-plated, one in a rich medium, another in a minimal medium, and mutants that have specific nutritional requirements can then be identified by their inability to grow in the minimal medium. Similar procedures may be repeated with other types of cells and with different media for selection.

A number of methods for generating random mutations in specific proteins were later developed to screen for mutants with interesting or improved properties. These methods may involve the use of doped nucleotides in oligonucleotide synthesis, or conducting a PCR reaction in conditions that enhance misincorporation of nucleotides (error-prone PCR), for example by reducing the fidelity of replication or using nucleotide analogues. A variation of this method for integrating non-biased mutations in a gene is sequence saturation mutagenesis. PCR products which contain mutation(s) are then cloned into an expression vector and the mutant proteins produced can then be characterised.

In animal studies, alkylating agents such as N-ethyl-N-nitrosourea (ENU) have been used to generate mutant mice. Ethyl methanesulfonate (EMS) is also often used to generate animal, plant, and virus mutants.

In a European Union law (as 2001/18 directive), this kind of mutagenesis may be used to produce GMOs but the products are exempted from regulation: no labeling, no evaluation.

Site-directed mutagenesis

Main article: Site-directed mutagenesis

Prior to the development site-directed mutagenesis techniques, all mutations made were random, and scientists had to use selection for the desired phenotype to find the desired mutation. Random mutagenesis techniques has an advantage in terms of how many mutations can be produced; however, while random mutagenesis can produce a change in single nucleotides, it does not offer much control as to which nucleotide is being changed. Many researchers therefore seek to introduce selected changes to DNA in a precise, site-specific manner. Early attempts uses analogs of nucleotides and other chemicals were first used to generate localized point mutations. Such chemicals include aminopurine, which induces an AT to GC transition, while nitrosoguanidine, bisulfite, and N⁴-hydroxycytidine may induce a GC to AT transition. These techniques allow specific mutations to be engineered into a protein; however, they are not flexible with respect to the kinds of mutants generated, nor are they as specific as later methods of site-directed mutagenesis and therefore have some degree of randomness. Other technologies such as cleavage of DNA at specific sites on the chromosome, addition of new nucleotides, and exchanging of base pairs it is now possible to decide where mutations can go.

Simplified diagram of the site directed mutagenic technique using pre-fabricated oligonucleotides in a primer extension reaction with DNA polymerase

Current techniques for site-specific mutation originates from the primer extension technique developed in 1978. Such techniques commonly involve using pre-fabricated mutagenic oligonucleotides in a primer extension reaction with DNA polymerase. This methods allows for point mutation or deletion or insertion of small stretches of DNA at specific sites. Advances in methodology have made such mutagenesis now a relatively simple and efficient process.

Newer and more efficient methods of site directed mutagenesis are being constantly developed. For example, a technique called "Seamless ligation cloning extract" (or SLiCE for short) allows for the cloning of certain sequences of DNA within the genome, and more than one DNA fragment can be inserted into the genome at once.

Site directed mutagenesis allows the effect of specific mutation to be investigated. There are numerous uses; for example, it has been used to determine how susceptible certain species were to chemicals that are often used In labs. The experiment used site directed mutagenesis to mimic the expected mutations of the specific chemical. The mutation resulted in a change in specific amino acids and the effects of this mutation were analyzed.

Site saturation mutagenesis is a type of site-directed mutagenesis. This image shows the saturation mutagenesis of a single position in a theoretical 10-residue protein. The wild type version of the protein is shown at the top, with M representing the first amino acid methionine, and * representing the termination of translation. All 19 mutants of the isoleucine at position 5 are shown below.

The site-directed approach may be done systematically in such techniques as alanine scanning mutagenesis, whereby residues are systematically mutated to alanine in order to identify residues important to the structure or function of a protein. Another comprehensive approach is site saturation mutagenesis where one codon or a set of codons may be substituted with all possible amino acids at the specific positions.

Combinatorial mutagenesis

Combinatorial mutagenesis is a site-directed protein engineering technique whereby multiple mutants of a protein can be simultaneously engineered based on analysis of the effects of additive individual mutations. It provides a useful method to assess the combinatorial effect of a large number of mutations on protein function. Large numbers of mutants may be screened for a particular characteristic by combinatorial analysis. In this technique, multiple positions or short sequences along a DNA strand may be exhaustively modified to obtain a comprehensive library of mutant proteins. The rate of incidence of beneficial variants can be improved by different methods for constructing mutagenesis libraries. One approach to this technique is to extract and replace a portion of the DNA sequence with a library of sequences containing all possible combinations at the desired mutation site. The content of the inserted segment can include sequences of structural significance, immunogenic property, or enzymatic function. A segment may also be inserted randomly into the gene in order to assess structural or functional significance of a particular part of a protein.

Insertional mutagenesis

Further information: Signature tagged mutagenesis and Transposon mutagenesis

The insertion of one or more base pairs, resulting in DNA mutations, is also known as insertional mutagenesis. Engineered mutations such as these can provide important information in cancer research, such as mechanistic insights into the development of the disease. Retroviruses and transposons are the chief instrumental tools in insertional mutagenesis. Retroviruses, such as the mouse mammory tumor virus and murine leukemia virus, can be used to identify genes involved in carcinogenesis and understand the biological pathways of specific cancers. Transposons, chromosomal segments that can undergo transposition, can be designed and applied to insertional mutagenesis as an instrument for cancer gene discovery. These chromosomal segments allow insertional mutagenesis to be applied to virtually any tissue of choice while also allowing for more comprehensive, unbiased depth in DNA sequencing.

Researchers have found four mechanisms of insertional mutagenesis that can be used on humans. the first mechanism is called enhancer insertion. Enhancers boost transcription of a particular gene by interacting with a promoter of that gene. This particular mechanism was first used to help severely immunocompromised patients I need of bone marrow. Gammaretroviruses carrying enhancers were then inserted into patients. The second mechanism is referred to as promoter insertion. Promoters provide our cells with the specific sequences needed to begin translation. Promoter insertion has helped researchers learn more about the HIV virus. The third mechanism is gene inactivation. An example of gene inactivation is using insertional mutagenesis to insert a retrovirus that disrupts the genome of the T cell in leukemia patients and giving them a specific antigen called CAR allowing the T cells to target cancer cells. The final mechanisms is referred to as mRNA 3' end substitution. Our genes occasionally undergo point mutations causing beta-thalassemia that interrupts red blood cell function. To fix this problem the correct gene sequence for the red blood cells are introduced and a substitution is made.

Homologous recombination

Homologous recombination can be used to produce specific mutation in an organism. Vector containing DNA sequence similar to the gene to be modified is introduced to the cell, and by a process of recombination replaces the target gene in the chromosome. This method can be used to introduce a mutation or knock out a gene, for example as used in the production of knockout mice.

CRISPR

Main article: CRISPR gene editing

Since 2013, the development of CRISPR-Cas9 technology has allowed for the efficient introduction of different types of mutations into the genome of a wide variety of organisms. The method does not require a transposon insertion site, leaves no marker, and its efficiency and simplicity has made it the preferred method for genome editing.

Gene synthesis

As the cost of DNA oligonucleotide synthesis falls, artificial synthesis of a complete gene is now a viable method for introducing mutations into a gene. This method allows for extensive mutation at multiple sites, including the complete redesign of the codon usage of a gene to optimise it for a particular organism.