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Thursday, August 24, 2023

Progress in artificial intelligence


Progress in machine classification of images
The error rate of AI by year. Red line - the error rate of a trained human on a particular task.

Progress in Artificial Intelligence (AI) refers to the advances, milestones, and breakthroughs that have been achieved in the field of artificial intelligence over time. AI is a multidisciplinary branch of computer science that aims to create machines and systems capable of performing tasks that typically require human intelligence. Artificial intelligence applications have been used in a wide range of fields including medical diagnosis, economic-financial applications, robot control, law, scientific discovery, video games, and toys. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore." "Many thousands of AI applications are deeply embedded in the infrastructure of every industry." In the late 1990s and early 21st century, AI technology became widely used as elements of larger systems, but the field was rarely credited for these successes at the time.

Kaplan and Haenlein structure artificial intelligence along three evolutionary stages: 1) artificial narrow intelligence – applying AI only to specific tasks; 2) artificial general intelligence – applying AI to several areas and able to autonomously solve problems they were never even designed for; and 3) artificial super intelligence – applying AI to any area capable of scientific creativity, social skills, and general wisdom.

To allow comparison with human performance, artificial intelligence can be evaluated on constrained and well-defined problems. Such tests have been termed subject matter expert Turing tests. Also, smaller problems provide more achievable goals and there are an ever-increasing number of positive results.

Humans still substantially outperform both GPT-4 and models trained on the ConceptARC benchmark that scored 60% on most, and 77% on one category, while humans 91% on all and 97% on one category.

Current performance

Game Champion year Legal states (log10) Game tree complexity (log10) Game of perfect information?
Draughts (checkers) 1994 21 31 Perfect
Othello (reversi) 1997 28 58 Perfect
Chess 1997 46 123 Perfect
Scrabble 2006


Shogi 2017 71 226 Perfect
Go 2016 172 360 Perfect
2p no-limit hold 'em 2017

Imperfect
StarCraft - 270+
Imperfect
StarCraft II 2019

Imperfect

There are many useful abilities that can be described as showing some form of intelligence. This gives better insight into the comparative success of artificial intelligence in different areas.

AI, like electricity or the steam engine, is a general purpose technology. There is no consensus on how to characterize which tasks AI tends to excel at. Some versions of Moravec's paradox observe that humans are more likely to outperform machines in areas such as physical dexterity that have been the direct target of natural selection. While projects such as AlphaZero have succeeded in generating their own knowledge from scratch, many other machine learning projects require large training datasets. Researcher Andrew Ng has suggested, as a "highly imperfect rule of thumb", that "almost anything a typical human can do with less than one second of mental thought, we can probably now or in the near future automate using AI."

Games provide a high-profile benchmark for assessing rates of progress; many games have a large professional player base and a well-established competitive rating system. AlphaGo brought the era of classical board-game benchmarks to a close when Artificial Intelligence proved their competitive edge over humans in 2016. Deep Mind’s AlphaGo AI software program defeated the world’s best professional Go Player Lee Sedol. Games of imperfect knowledge provide new challenges to AI in the area of game theory; the most prominent milestone in this area was brought to a close by Libratus' poker victory in 2017. E-sports continue to provide additional benchmarks; Facebook AI, Deepmind, and others have engaged with the popular StarCraft franchise of videogames.

Broad classes of outcome for an AI test may be given as:

  • optimal: it is not possible to perform better (note: some of these entries were solved by humans)
  • super-human: performs better than all humans
  • high-human: performs better than most humans
  • par-human: performs similarly to most humans
  • sub-human: performs worse than most humans

Optimal

See also: Solved game

Super-human

High-human

Par-human

Sub-human

  • Optical character recognition for printed text (nearing par-human for Latin-script typewritten text)
  • Object recognition
  • Various robotics tasks that may require advances in robot hardware as well as AI, including:
    • Stable bipedal locomotion: Bipedal robots can walk, but are less stable than human walkers (as of 2017)
    • Humanoid soccer
  • Speech recognition: "nearly equal to human performance" (2017)
  • Explainability. Current medical systems can diagnose certain medical conditions well, but cannot explain to users why they made the diagnosis.
  • Many tests of fluid intelligence (2020)
  • Bongard visual cognition problems, such as the Bongard-LOGO benchmark (2020)
  • Visual Commonsense Reasoning (VCR) benchmark (as of 2020)
  • Stock market prediction: Financial data collection and processing using Machine Learning algorithms
  • Angry Birds video game, as of 2020
  • Various tasks that are difficult to solve without contextual knowledge, including:

Proposed tests of artificial intelligence

See also: Turing test § Versions

In his famous Turing test, Alan Turing picked language, the defining feature of human beings, for its basis. The Turing test is now considered too exploitable to be a meaningful benchmark.

The Feigenbaum test, proposed by the inventor of expert systems, tests a machine's knowledge and expertise about a specific subject. A paper by Jim Gray of Microsoft in 2003 suggested extending the Turing test to speech understanding, speaking and recognizing objects and behavior.

Proposed "universal intelligence" tests aim to compare how well machines, humans, and even non-human animals perform on problem sets that are generic as possible. At an extreme, the test suite can contain every possible problem, weighted by Kolmogorov complexity; however, these problem sets tend to be dominated by impoverished pattern-matching exercises where a tuned AI can easily exceed human performance levels.

Exams

According to OpenAI, in 2023 ChatGPT GPT-4 scored the 90th percentile on the Uniform Bar Exam. On the SATs, GPT-4 scored the 89th percentile on math, and the 93rd percentile in Reading & Writing. On the GREs, it scored on the 54th percentile on the writing test, 88th percentile on the quantitative section, and 99th percentile on the verbal section. It scored in the 99th to 100th percentile on the 2020 USA Biology Olympiad semifinal exam. It scored a perfect "5" on several AP exams.

Independent researchers found in 2023 that ChatGPT GPT-3.5 "performed at or near the passing threshold" for the three parts of the United States Medical Licensing Examination. GPT-3.5 was also assessed to attain a low, but passing, grade from exams for four law school courses at the University of Minnesota. GPT-4 passed a text-based radiology board–style examination.

Competitions

Main article: Competitions and prizes in artificial intelligence

Many competitions and prizes, such as the Imagenet Challenge, promote research in artificial intelligence. The most common areas of competition include general machine intelligence, conversational behavior, data-mining, robotic cars, and robot soccer as well as conventional games.

Past and current predictions

An expert poll around 2016, conducted by Katja Grace of the Future of Humanity Institute and associates, gave median estimates of 3 years for championship Angry Birds, 4 years for the World Series of Poker, and 6 years for StarCraft. On more subjective tasks, the poll gave 6 years for folding laundry as well as an average human worker, 7–10 years for expertly answering 'easily Googleable' questions, 8 years for average speech transcription, 9 years for average telephone banking, and 11 years for expert songwriting, but over 30 years for writing a New York Times bestseller or winning the Putnam math competition.

Chess

Deep Blue at the Computer History Museum

An AI defeated a grandmaster in a regulation tournament game for the first time in 1988; rebranded as Deep Blue, it beat the reigning human world chess champion in 1997 (see Deep Blue versus Garry Kasparov).

Estimates when computers would exceed humans at Chess
Year prediction made Predicted year Number of Years Predictor Contemporaneous source
1957 1967 or sooner 10 or less Herbert A. Simon, economist
1990 2000 or sooner 10 or less Ray Kurzweil, futurist Age of Intelligent Machines

Go

AlphaGo defeated a European Go champion in October 2015, and Lee Sedol in March 2016, one of the world's top players (see AlphaGo versus Lee Sedol). According to Scientific American and other sources, most observers had expected superhuman Computer Go performance to be at least a decade away.

Estimates when computers would exceed humans at Go
Year prediction made Predicted year Number of years Predictor Affiliation Contemporaneous source
1997 2100 or later 103 or more Piet Hutt, physicist and Go fan Institute for Advanced Study New York Times
2007 2017 or sooner 10 or less Feng-Hsiung Hsu, Deep Blue lead Microsoft Research Asia IEEE Spectrum
2014 2024 10 Rémi Coulom, Computer Go programmer CrazyStone Wired

Human-level artificial general intelligence (AGI)

AI pioneer and economist Herbert A. Simon inaccurately predicted in 1965: "Machines will be capable, within twenty years, of doing any work a man can do". Similarly, in 1970 Marvin Minsky wrote that "Within a generation... the problem of creating artificial intelligence will substantially be solved."

Four polls conducted in 2012 and 2013 suggested that the median estimate among experts for when AGI would arrive was 2040 to 2050, depending on the poll.

The Grace poll around 2016 found results varied depending on how the question was framed. Respondents asked to estimate "when unaided machines can accomplish every task better and more cheaply than human workers" gave an aggregated median answer of 45 years and a 10% chance of it occurring within 9 years. Other respondents asked to estimate "when all occupations are fully automatable. That is, when for any occupation, machines could be built to carry out the task better and more cheaply than human workers" estimated a median of 122 years and a 10% probability of 20 years. The median response for when "AI researcher" could be fully automated was around 90 years. No link was found between seniority and optimism, but Asian researchers were much more optimistic than North American researchers on average; Asians predicted 30 years on average for "accomplish every task", compared with the 74 years predicted by North Americans.

Estimates of when AGI will arrive
Year prediction made Predicted year Number of years Predictor Contemporaneous source
1965 1985 or sooner 20 or less Herbert A. Simon The shape of automation for men and management
1993 2023 or sooner 30 or less Vernor Vinge, science fiction writer "The Coming Technological Singularity"
1995 2040 or sooner 45 or less Hans Moravec, robotics researcher Wired
2008 Never / Distant future
Gordon E. Moore, inventor of Moore's Law IEEE Spectrum
2017 2029 12 Ray Kurzweil Interview
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Liquid chromatography–mass spectrometry


Liquid chromatography–mass spectrometry
Bruker Amazon Speed ETD
Ion trap LCMS system with ESI interface
AcronymLCMS
ClassificationChromatography
Mass spectrometry
Analytesorganic molecules
biomolecules
ManufacturersAgilent
Bruker
PerkinElmer
SCIEX
Shimadzu Scientific
Thermo Fisher Scientific
Waters Corporation
Other techniques
RelatedGas chromatography–mass spectrometry

Liquid chromatography–mass spectrometry (LC–MS) is an analytical chemistry technique that combines the physical separation capabilities of liquid chromatography (or HPLC) with the mass analysis capabilities of mass spectrometry (MS). Coupled chromatography - MS systems are popular in chemical analysis because the individual capabilities of each technique are enhanced synergistically. While liquid chromatography separates mixtures with multiple components, mass spectrometry provides spectral information that may help to identify (or confirm the suspected identity of) each separated component. MS is not only sensitive, but provides selective detection, relieving the need for complete chromatographic separation. LC–MS is also appropriate for metabolomics because of its good coverage of a wide range of chemicals. This tandem technique can be used to analyze biochemical, organic, and inorganic compounds commonly found in complex samples of environmental and biological origin. Therefore, LC–MS may be applied in a wide range of sectors including biotechnology, environment monitoring, food processing, and pharmaceutical, agrochemical, and cosmetic industries. Since the early 2000s, LC–MS (or more specifically LC–MS–MS) has also begun to be used in clinical applications.

In addition to the liquid chromatography and mass spectrometry devices, an LC–MS system contains an interface that efficiently transfers the separated components from the LC column into the MS ion source. The interface is necessary because the LC and MS devices are fundamentally incompatible. While the mobile phase in a LC system is a pressurized liquid, the MS analyzers commonly operate under high vacuum. Thus, it is not possible to directly pump the eluate from the LC column into the MS source. Overall, the interface is a mechanically simple part of the LC–MS system that transfers the maximum amount of analyte, removes a significant portion of the mobile phase used in LC and preserves the chemical identity of the chromatography products (chemically inert). As a requirement, the interface should not interfere with the ionizing efficiency and vacuum conditions of the MS system. Nowadays, most extensively applied LC–MS interfaces are based on atmospheric pressure ionization (API) strategies like electrospray ionization (ESI), atmospheric-pressure chemical ionization (APCI), and atmospheric pressure photoionization (APPI). These interfaces became available in the 1990s after a two decade long research and development process.

History of LC–MS

The coupling of chromatography with MS is a well developed chemical analysis strategy dating back from the 1950s. Gas chromatography (GC)–MS was originally introduced in 1952, when A. T. James and A. J. P. Martin were trying to develop tandem separation - mass analysis techniques. In GC, the analytes are eluted from the separation column as a gas and the connection with electron ionization (EI) or chemical ionization (CI) ion sources in the MS system was a technically simpler challenge. Because of this, the development of GC-MS systems was faster than LC–MS and such systems were first commercialized in the 1970s. The development of LC–MS systems took longer than GC-MS and was directly related to the development of proper interfaces. V. L. Tal'roze and collaborators started the development of LC–MS in the late 1960s, when they first used capillaries to connect an LC columns to an EI source. A similar strategy was investigated by McLafferty and collaborators in 1973 who coupled the LC column to a CI source, which allowed a higher liquid flow into the source. This was the first and most obvious way of coupling LC with MS, and was known as the capillary inlet interface. This pioneer interface for LC–MS had the same analysis capabilities of GC-MS and was limited to rather volatile analytes and non-polar compounds with low molecular mass (below 400 Da). In the capillary inlet interface, the evaporation of the mobile phase inside the capillary was one of the main issues. Within the first years of development of LC–MS, on-line and off-line alternatives were proposed as coupling alternatives. In general, off-line coupling involved fraction collection, evaporation of solvent, and transfer of analytes to the MS using probes. Off-line analyte treatment process was time consuming and there was an inherent risk of sample contamination. Rapidly, it was realized that the analysis of complex mixtures would require the development of a fully automated on-line coupling solution in LC–MS.

The key to the success and wide-spread adoption of LC–MS as a routine analytical tool lies in the interface and ion source between the liquid-based LC and the vacuum-base MS. The following interfaces were stepping-stones on the way to the modern atmospheric-pressure ionization interfaces, and are described for historical interest.

Moving-belt interface

The moving-belt interface (MBI) was developed by McFadden et al. in 1977 and commercialized by Finnigan. This interface consisted of an endless moving belt onto which the LC column effluent was deposited in a band. On the belt, the solvent was evaporated by gently heating and efficiently exhausting the solvent vapours under reduced pressure in two vacuum chambers. After the liquid phase was removed, the belt passed over a heater which flash desorbed the analytes into the MS ion source. One of the significant advantages of the MBI was its compatibility with a wide range of chromatographic conditions. MBI was successfully used for LC–MS applications between 1978 and 1990 because it allowed coupling of LC to MS devices using EI, CI, and fast-atom bombardment (FAB) ion sources. The most common MS systems connected by MBI interfaces to LC columns wre magnetic sector and quadrupole instruments. MBI interfaces for LC–MS allowed MS to be widely applied in the analysis of drugs, pesticides, steroids, alkaloids, and polycyclic aromatic hydrocarbons. This interface is no longer used because of its mechanical complexity and the difficulties associated with belt renewal as well as its inability to handle very labile biomolecules.


Direct liquid-introduction interface

The direct liquid-introduction (DLI) interface was developed in 1980. This interface was intended to solve the problem of evaporation of liquid inside the capillary inlet interface. In DLI, a small portion of the LC flow was forced through a small aperture or diaphragm (typically 10um in diameter) to form a liquid jet composed of small droplets that were subsequently dried in a desolvation chamber. The analytes were ionized using a solvent-assisted chemical ionization source, where the LC solvents acted as reagent gases. To use this interface, it was necessary to split the flow coming out of the LC column because only a small portion of the effluent (10 to 50 μl/min out of 1 ml/min) could be introduced into the source without raising the vacuum pressure of the MS system too high. Alternately, Henion at Cornell University had success with using micro-bore LC methods so that the entire (low) flow of the LC could be used. One of the main operational problems of the DLI interface was the frequent clogging of the diaphragm orifices. The DLI interface was used between 1982 and 1985 for the analysis of pesticides, corticosteroids, metabolites in horse urine, erythromycin, and vitamin B12. However, this interface was replaced by the thermospray interface, which removed the flow rate limitations and the issues with the clogging diaphragms.

A related device was the particle beam interface (PBI), developed by Willoughby and Browner in 1984. Particle beam interfaces took over the wide applications of MBI for LC–MS in 1988. The PBI operated by using a helium gas nebulizer to spray the eluant into the vacuum, drying the droplets and pumping away the solvent vapour (using a jet separator) while the stream of monodisperse dried particles containing the analyte entered the source. Drying the droplets outside of the source volume, and using a jet separator to pump away the solvent vapour, allowed the particles to enter and be vapourized in a low-pressure EI source. As with the MBI, the ability to generate library-searchable EI spectra was a distinct advantage for many applications. Commercialized by Hewlett Packard, and later by VG and Extrel, it enjoyed moderate success, but has been largely supplanted by the atmospheric pressure interfaces such as electrospray and APCI which provide a broader range of compound coverage and applications.

Thermospray interface

The thermospray (TSP) interface was developed in 1980 by Marvin Vestal and co-workers at the University of Houston. It was commercialized by Vestec and several of the major mass spectrometer manufacurers. The interface resulted from a long term research project intended to find a LC–MS interface capable of handling high flow rates (1 ml/min) and avoiding the flow split in DLI interfaces. The TSP interface was composed of a heated probe, a desolvation chamber, and an ion focusing skimmer. The LC effluent passed through the heated probe and emerged as a jet of vapor and small droplets flowing into the desolvation chamber at low pressure. Initially operated with a filament or discharge as the source of ions (thereby acting as a CI source for vapourized analyte), it was soon discovered that ions were also observed when the filament or discharge was off. This could be attributed to either direct emission of ions from the liquid droplets as they evaporated in a process related to electrospray ionization or ion evaporation, or to chemical ionization of vapourized analyte molecules from buffer ions (such as ammonium acetate). The fact that multiply-charged ions were observed from some larger analytes suggests that direct analyte ion emission was occurring under at least some conditions. The interface was able to handle up to 2 ml/min of eluate from the LC column and would efficiently introduce it into the MS vacuum system. TSP was also more suitable for LC–MS applications involving reversed phase liquid chromatography (RT-LC). With time, the mechanical complexity of TSP was simplified, and this interface became popular as the first ideal LC–MS interface for pharmaceutical applications comprising the analysis of drugs, metabolites, conjugates, nucleosides, peptides, natural products, and pesticides. The introduction of TSP marked a significant improvement for LC–MS systems and was the most widely applied interface until the beginning of the 1990s, when it began to be replaced by interfaces involving atmospheric pressure ionization (API).

FAB based interfaces

The frit fast atom bombardment (FAB) and continuous flow-FAB (CF-FAB) interfaces were developed in 1985 and 1986 respectively. Both interfaces were similar, but they differed in that the first used a porous frit probe as connecting channel, while CF-FAB used a probe tip. From these, the CF-FAB was more successful as a LC–MS interface and was useful to analyze non-volatile and thermally labile compounds. In these interfaces, the LC effluent passed through the frit or CF-FAB channels to form a uniform liquid film at the tip. There, the liquid was bombarded with ion beams or high energy atoms (fast atoms). For stable operation, the FAB based interfaces were able to handle liquid flow rates of only 1–15 μl and were also restricted to microbore and capillary columns. In order to be used in FAB MS ionization sources, the analytes of interest had to be mixed with a matrix (e.g., glycerol) that could be added before or after the separation in the LC column. FAB based interfaces were extensively used to characterize peptides, but lost applicability with the advent of electrospray based interfaces in 1988.

Liquid chromatography

Diagram of an LC–MS system
Main article: High-performance liquid chromatography

Liquid chromatography is a method of physical separation in which the components of a liquid mixture are distributed between two immiscible phases, i.e., stationary and mobile. The practice of LC can be divided into five categories, i.e., adsorption chromatography, partition chromatography, ion-exchange chromatography, size-exclusion chromatography, and affinity chromatography. Among these, the most widely used variant is the reverse-phase (RP) mode of the partition chromatography technique, which makes use of a nonpolar (hydrophobic) stationary phase and a polar mobile phase. In common applications, the mobile phase is a mixture of water and other polar solvents (e.g., methanol, isopropanol, and acetonitrile), and the stationary matrix is prepared by attaching long-chain alkyl groups (e.g., n-octadecyl or C18) to the external and internal surfaces of irregularly or spherically shaped 5 μm diameter porous silica particles.

In HPLC, typically 20 μl of the sample of interest are injected into the mobile phase stream delivered by a high pressure pump. The mobile phase containing the analytes permeates through the stationary phase bed in a definite direction. The components of the mixture are separated depending on their chemical affinity with the mobile and stationary phases. The separation occurs after repeated sorption and desorption steps occurring when the liquid interacts with the stationary bed. The liquid solvent (mobile phase) is delivered under high pressure (up to 400 bar or 5800 psi) into a packed column containing the stationary phase. The high pressure is necessary to achieve a constant flow rate for reproducible chromatography experiments. Depending on the partitioning between the mobile and stationary phases, the components of the sample will flow out of the column at different times. The column is the most important component of the LC system and is designed to withstand the high pressure of the liquid. Conventional LC columns are 100–300 mm long with outer diameter of 6.4 mm (1/4 inch) and internal diameter of 3.0–4.6 mm. For applications involving LC–MS, the length of chromatography columns can be shorter (30–50 mm) with 3–5 μm diameter packing particles. In addition to the conventional model, other LC columns are the narrow bore, microbore, microcapillary, and nano-LC models. These columns have smaller internal diameters, allow for a more efficient separation, and handle liquid flows under 1 ml/min (the conventional flow-rate). In order to improve separation efficiency and peak resolution, ultra performance liquid chromatography (UHPLC) can be used instead of HPLC. This LC variant uses columns packed with smaller silica particles (~1.7 μm diameter) and requires higher operating pressures in the range of 310000 to 775000 torr (6000 to 15000 psi, 400 to 1034 bar).

Mass spectrometry

LC–MS spectrum of each resolved peak
Main article: Mass spectrometry

Mass spectrometry (MS) is an analytical technique that measures the mass-to-charge ratio (m/z) of charged particles (ions). Although there are many different kinds of mass spectrometers, all of them make use of electric or magnetic fields to manipulate the motion of ions produced from an analyte of interest and determine their m/z. The basic components of a mass spectrometer are the ion source, the mass analyzer, the detector, and the data and vacuum systems. The ion source is where the components of a sample introduced in a MS system are ionized by means of electron beams, photon beams (UV lights), laser beams or corona discharge. In the case of electrospray ionization, the ion source moves ions that exist in liquid solution into the gas phase. The ion source converts and fragments the neutral sample molecules into gas-phase ions that are sent to the mass analyzer. While the mass analyzer applies the electric and magnetic fields to sort the ions by their masses, the detector measures and amplifies the ion current to calculate the abundances of each mass-resolved ion. In order to generate a mass spectrum that a human eye can easily recognize, the data system records, processes, stores, and displays data in a computer.

The mass spectrum can be used to determine the mass of the analytes, their elemental and isotopic composition, or to elucidate the chemical structure of the sample. MS is an experiment that must take place in gas phase and under vacuum (1.33 * 10−2 to 1.33 * 10−6 pascal). Therefore, the development of devices facilitating the transition from samples at higher pressure and in condensed phase (solid or liquid) into a vacuum system has been essential to develop MS as a potent tool for identification and quantification of organic compounds like peptides. MS is now in very common use in analytical laboratories that study physical, chemical, or biological properties of a great variety of compounds. Among the many different kinds of mass analyzers, the ones that find application in LC–MS systems are the quadrupole, time-of-flight (TOF), ion traps, and hybrid quadrupole-TOF (QTOF) analyzers.

Interfaces

The interface between a liquid phase technique (HPLC) with a continuously flowing eluate, and a gas phase technique carried out in a vacuum was difficult for a long time. The advent of electrospray ionization changed this. Currently, the most common LC–MS interfaces are electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and atmospheric pressure photo-ionization (APPI). These are newer MS ion sources that facilitate the transition from a high pressure environment (HPLC) to high vacuum conditions needed at the MS analyzer. Although these interfaces are described individually, they can also be commercially available as dual ESI/APCI, ESI/APPI, or APCI/APPI ion sources. Various deposition and drying techniques were used in the past (e.g., moving belts) but the most common of these was the off-line MALDI deposition. A new approach still under development called direct-EI LC–MS interface, couples a nano HPLC system and an electron ionization equipped mass spectrometer.

Electrospray ionization (ESI)

Main article: Electrospray ionization

ESI interface for LC–MS systems was developed by Fenn and collaborators in 1988. This ion source/ interface can be used for the analysis of moderately polar and even very polar molecules (e.g., metabolites, xenobiotics, peptides, nucleotides, polysaccharides). The liquid eluate coming out of the LC column is directed into a metal capillary kept at 3 to 5 kV and is nebulized by a high-velocity coaxial flow of gas at the tip of the capillary, creating a fine spray of charged droplets in front of the entrance to the vacuum chamber. To avoid contamination of the vacuum system by buffers and salts, this capillary is usually perpendicularly located at the inlet of the MS system, in some cases with a counter-current of dry nitrogen in front of the entrance through which ions are directed by the electric field. In some sources, rapid droplet evaporation and thus maximum ion emission is achieved by mixing an additional stream of hot gas with the spray plume in front of the vacuum entrance. In other sources, the droplets are drawn through a heated capillary tube as they enter the vacuum, promoting droplet evaporation and ion emission. These methods of increasing droplet evaporation now allow the use of liquid flow rates of 1 - 2 mL/min to be used while still achieving efficient ionisation and high sensitivity. Thus while the use of 1 - 3 mm microbore columns and lower flow rates of 50 - 200 μl/min was commonly considered necessary for optimum operation, this limitation is no longer as important, and the higher column capacity of larger bore columns can now be advantageously employed with ESI LC–MS systems. Positively and negatively charged ions can be created by switching polarities, and it is possible to acquire alternate positive and negative mode spectra rapidly within the same LC run . While most large molecules (greater than MW 1500-2000) produce multiply charged ions in the ESI source, the majority of smaller molecules produce singly charged ions.

Atmospheric pressure chemical ionization (APCI)

Main article: Atmospheric pressure chemical ionization

The development of the APCI interface for LC–MS started with Horning and collaborators in the early 1973. However, its commercial application was introduced at the beginning of the 1990s after Henion and collaborators improved the LC–APCI–MS interface in 1986. The APCI ion source/ interface can be used to analyze small, neutral, relatively non-polar, and thermally stable molecules (e.g., steroids, lipids, and fat soluble vitamins). These compounds are not well ionized using ESI. In addition, APCI can also handle mobile phase streams containing buffering agents. The liquid from the LC system is pumped through a capillary and there is also nebulization at the tip, where a corona discharge takes place. First, the ionizing gas surrounding the interface and the mobile phase solvent are subject to chemical ionization at the ion source. Later, these ions react with the analyte and transfer their charge. The sample ions then pass through small orifice skimmers by means of or ion-focusing lenses. Once inside the high vacuum region, the ions are subject to mass analysis. This interface can be operated in positive and negative charge modes and singly-charged ions are mainly produced. APCI ion source can also handle flow rates between 500 and 2000 μl/min and it can be directly connected to conventional 4.6 mm ID columns.

Atmospheric pressure photoionization (APPI)

Main article: Atmospheric pressure photoionization

The APPI interface for LC–MS was developed simultaneously by Bruins and Syage in 2000. APPI is another LC–MS ion source/ interface for the analysis of neutral compounds that cannot be ionized using ESI. This interface is similar to the APCI ion source, but instead of a corona discharge, the ionization occurs by using photons coming from a discharge lamp. In the direct-APPI mode, singly charged analyte molecular ions are formed by absorption of a photon and ejection of an electron. In the dopant-APPI mode, an easily ionizable compound (Dopant) is added to the mobile phase or the nebulizing gas to promote a reaction of charge-exchange between the dopant molecular ion and the analyte. The ionized sample is later transferred to the mass analyzer at high vacuum as it passes through small orifice skimmers.

Applications

The coupling of MS with LC systems is attractive because liquid chromatography can separate delicate and complex natural mixtures, which chemical composition needs to be well established (e.g., biological fluids, environmental samples, and drugs). Further, LC–MS has applications in volatile explosive residue analysis. Nowadays, LC–MS has become one of the most widely used chemical analysis techniques because more than 85% of natural chemical compounds are polar and thermally labile and GC-MS cannot process these samples. As an example, HPLC–MS is regarded as the leading analytical technique for proteomics and pharmaceutical laboratories. Other important applications of LC–MS include the analysis of food, pesticides, and plant phenols.

Pharmacokinetics

LC–MS is widely used in the field of bioanalysis and is specially involved in pharmacokinetic studies of pharmaceuticals. Pharmacokinetic studies are needed to determine how quickly a drug will be cleared from the body organs and the hepatic blood flow. MS analyzers are useful in these studies because of their shorter analysis time, and higher sensitivity and specificity compared to UV detectors commonly attached to HPLC systems. One major advantage is the use of tandem MS–MS, where the detector may be programmed to select certain ions to fragment. The measured quantity is the sum of molecule fragments chosen by the operator. As long as there are no interferences or ion suppression in LC–MS, the LC separation can be quite quick.

Proteomics/metabolomics

LC–MS is used in proteomics as a method to detect and identify the components of a complex mixture. The bottom-up proteomics LC–MS approach generally involves protease digestion and denaturation using trypsin as a protease, urea to denature the tertiary structure, and iodoacetamide to modify the cysteine residues. After digestion, LC–MS is used for peptide mass fingerprinting, or LC–MS/MS (tandem MS) is used to derive the sequences of individual peptides. LC–MS/MS is most commonly used for proteomic analysis of complex samples where peptide masses may overlap even with a high-resolution mass spectrometry. Samples of complex biological (e.g., human serum) may be analyzed in modern LC–MS/MS systems, which can identify over 1000 proteins. However, this high level of protein identification is possible only after separating the sample by means of SDS-PAGE gel or HPLC-SCX. Recently, LC–MS/MS has been applied to search peptide biomarkers. Examples are the recent discovery and validation of peptide biomarkers for four major bacterial respiratory tract pathogens (Staphylococcus aureus, Moraxella catarrhalis; Haemophilus influenzae and Streptococcus pneumoniae) and the SARS-CoV-2 virus.

LC–MS has emerged as one of the most commonly used techniques in global metabolite profiling of biological tissue (e.g., blood plasma, serum, urine). LC–MS is also used for the analysis of natural products and the profiling of secondary metabolites in plants. In this regard, MS-based systems are useful to acquire more detailed information about the wide spectrum of compounds from a complex biological samples. LC–nuclear magnetic resonance (NMR) is also used in plant metabolomics, but this technique can only detect and quantify the most abundant metabolites. LC–MS has been useful to advance the field of plant metabolomics, which aims to study the plant system at molecular level providing a non-biased characterization of the plant metabolome in response to its environment. The first application of LC–MS in plant metabolomics was the detection of a wide range of highly polar metabolites, oligosaccharides, amino acids, amino sugars, and sugar nucleotides from Cucurbita maxima phloem tissues. Another example of LC–MS in plant metabolomics is the efficient separation and identification of glucose, sucrose, raffinose, stachyose, and verbascose from leaf extracts of Arabidopsis thaliana.

Drug development

LC–MS is frequently used in drug development because it allows quick molecular weight confirmation and structure identification. These features speed up the process of generating, testing, and validating a discovery starting from a vast array of products with potential application. LC–MS applications for drug development are highly automated methods used for peptide mapping, glycoprotein mapping, lipodomics, natural products dereplication, bioaffinity screening, in vivo drug screening, metabolic stability screening, metabolite identification, impurity identification, quantitative bioanalysis, and quality control.
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Wednesday, August 23, 2023

Social media and suicide

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

picture of differing social media logos on a keyboard

Researchers study Social media and suicide to find if a correlation exists between the two. Some research has shown that there may be a correlation.

Background

Suicide is one of the top leading causes of death worldwide, and as of 2020, the third leading cause of death in those aged 15–24. According to the Center for Disease Control and Prevention, suicide was the third leading cause of death among adolescents in the US, from 1999 to 2006.

In 2020, people in the US ages 10-24 had a suicide rate of 10.7 per 100,000. Suicide was a leading cause of death in the United States accounting for 48,183 deaths in 2021. Suicide rates increased by 30 percent from 2000-2018 and declined in 2019 and 2020.

Despite suicide prevention programs, therapy, and pharmacological treatments, suicide remains a public health issue worldwide. Suicide has been identified not only as an individual phenomenon, but also as being influenced by social and environmental factors. There is growing evidence that online activity have influenced suicide-related behavior. The use of social media throughout the 21st century has grown exponentially. There are a variety of sources that are accessible to the public in various forms. Sites include Facebook, Instagram, Twitter, YouTube, Snapchat, TikTok and more. These platforms were intended to allow people to connect in a virtual way, but can lead to cyberbullying, insecurity, emotional distress, and sometimes may influence a person to attempt suicide.

Bullying, whether on social media or elsewhere, physical or not, significantly increases victims' risk of suicidal behavior. Since social media was introduced some people have taken their lives as a result of cyberbullying. Suicide rates among teenagers have increased from 2010 to 2022 as social media has become something that people interact with more throughout their day-to-day life.

Media algorithms tends to popularize videos and posts to inform the country of the rising trouble, which may create a popular appeal to the young and immature minds of teenagers. Social media could provide higher risks with the promotion of different kinds of pro-suicidal sites, message boards, chat rooms, and forums. Also, the Internet not only reports suicide incidents but documents suicide methods (for example, suicide pacts, an agreement between two or more people to kill themselves at a particular time and often by the same lethal means). The role the Internet plays, particularly social media, in suicide-related behavior is a topic of growing interest.

Cyberbullying

There is substantial evidence that the Internet and social media can influence suicide-related behavior. Such evidence includes an increase in exposure to graphic content. According to research by Sameer Hinduja and Justin Patchin, there is also a correlation between cyberbullying and suicide. Cyberbullying increases suicidal thoughts by 14.5 percent and suicide attempts by 8.7 percent. Children and young people under 25 who are victims of cyberbullying are more than twice as likely to self-harm and enact suicidal behavior. Overall, teen suicide rates have increased within the past decade. This is a highly considerable public health problem, having over 40,000 suicide deaths in the United States and nearly one million suicide deaths worldwide occurring yearly.

Social media's influence on suicide

The media may portray suicidal behavior or language which can potentially influence people to act on these suicidal tendencies. This may include news reports of actual suicides that have occurred or television shows and films that reenact suicides.

Some organizations have proposed guidelines about how the media should report suicide. There is evidence that compliance with the guidelines varies. Some research has found that it is unclear whether the guidelines have successfully reduced the number of suicides. Other research has found that the guidelines have worked in some cases.

Impact of pro-suicidal sites, message boards, chat rooms and forums

Social media platforms have transformed traditional methods of communication by allowing the instantaneous and interactive sharing of information created and controlled by individuals, groups, organizations, and governments. As of the third quarter of 2022, Facebook had 266 million monthly active users, between Canada and the US. An immense quantity of information on the topic of suicide is available on the Internet and via social media. The information available on social media on the topic of suicide can influence suicidal behavior, both negatively and positively.

The social cognitive theory plays a vital role in suicide attempts influenced through social media. This theory is demonstrated when one is influenced by what they see through various processes that form into modeled behaviors. This can be shown when people post their suicide attempts online or promote suicidal behavior in general.

Contributors to these social media platforms may also exert peer pressure and encourage others to take their own lives, idolize those who have killed themselves, and facilitate suicide pacts. These pro-suicidal sites reported the following. For example, on a Japanese message board in 2008, it was shared that people can kill themselves using hydrogen sulfide gas. Shortly after 220 people attempted suicide in this way, and 208 were successful. Biddle et al. conducted a systematic Web search of 12 suicide-associated terms (e.g., suicide, suicide methods, how to kill yourself, and best suicide methods) to analyze the search results and found that pro-suicide sites and chat rooms that discussed general issues associated with suicide most often occurred within the first few hits of a search. also conducted a study that examined suicide-related sites that can be found using Internet search engines. Of 373 website hits, 31% were suicide neutral, 29% were anti-suicide, and 11% were pro-suicide. Together, these studies have shown that obtaining pro-suicide information on the Internet, including detailed information on suicide methods, is very easy.

While social media has been prevalent in young adult suicide, some young adults find comfort and solace through these platforms. Young adults are making connections with people in like situations that are helping them feel less lonely. Although the public opinion is that message boards are harmful, the following studies show how they point to suicide prevention and have positive influences. A study using content analysis analyzed all of the postings on the AOL Suicide Bulletin Board over 11 months and concluded that most contributions contained positive, empathetic, and supportive postings. Then, a multi-method study was able to demonstrate that the users of such forums experience a great deal of social support and only a small amount of social strain. Lastly, in the survey participants were asked to assess the extent of their suicidal thoughts on a 7-level scale (0, absolutely no suicidal thoughts, to 7, very strong suicidal thoughts) for the time directly before their first forum visit and at the time of the survey. The study found a significant reduction after using the forum. The study however cannot conclude the forum is the only reason for the decrease. Together, these studies show how forums can reduce the number of suicides.

An example of how social media can play a role in suicide is that of a male adolescent who arrived at the emergency department with his parents after suspected medication ingestion in which he attempted to overdose. Beforehand he had sent an ex-girlfriend a Snapchat picture of himself holding a bottle of acetaminophen, which was forwarded to the young male's parents. This picture was used by medical experts to establish the time of his ingestion, oral N-acetylcysteine was administered and he was brought to a pediatric care facility, where he had an uneventful recovery and psychiatric evaluation.

In 2013, the main cause of nine teen suicides was due to hateful anonymous messages on Ask.fm.

Cyberbullying and suicide

Cyberbullying has received considerable attention as a possible cause of suicide. With the rise of social media, the risk of falling victim to blackmail has also increased. It has been deemed a major health concern for affected teens and a major health threat to those affected by the psychological trauma inflicted by perpetrators on social media. While there isn’t one Federal Law that is specific to cyberbullying, 48 states have laws against cyberbullying or online harassment with 44 of those states having criminal sanctions within the laws. Many states have enhanced their harassment laws to include online harassment. Criminal harassment statutes often provide a basis for bringing charges in severe cases, and more serious criminal charges have been brought in cases where evidence indicates a resultant suicide or other tragic consequences. Civil remedies have been sought in many cases where criminal liability was difficult to prove.

In 2006, 13 year old Megan Meier hanged herself in her bedroom closet following a series of MySpace messages that came from a friend's mother and her 18 year old associate, who posed as a teen boy named “Josh Evans” and encouraged Megan to commit suicide. The mother, Lori Drew, faced federal conspiracy charges related to computer fraud and abuse, but was later acquitted.

In 2012, Canadian high school student Amanda Todd hanged herself after being blackmailed by a stalker, and suffering from repeated cyberbulling and harassment at school. On September 7, Todd posted a 9-minute YouTube video titled My story: Struggling, bullying, suicide, self-harm, which showed her using a series of flashcards to tell of her experiences being bullied. The video went viral after her death on October 10, 2012, receiving over 1,600,000 views by October 13, 2012, with news websites from around the world linking to it.

In 2014, Conrad Roy killed himself after exchanging numerous text messages with Michelle Carter, his long-distance girlfriend, who repeatedly encouraged him to commit suicide. She was found guilty of involuntary manslaughter, and sentenced to 15 months in prison. Carter was released in January 2020.

Sadie Riggs, a Pennsylvania teen, killed herself in 2015 allegedly because of online bullying and harassment at school on her appearance. Sadie's aunt, Sarah Smith, contacted various social media companies, police, and Sadie's school in hopes to make the bullying stop. In desperation, Smith went as far as to break Sadie's phone, in her presence, in an attempt to stop the bullying. No charges were ever filed against any alleged suspect.

In a 2018 Florida case, two preteens were arrested and charged with cyberstalking after they were accused of cyberbullying another female middle school student, 12 year old Gabriella Green. Online rumors were spread about her, and she hanged herself immediately after a call with one of the abusers, who told her that "If you're going to do it, just do it" and ended the call, according to police.

In 2019, Canadian Inuk pop singer Kelly Fraser, who was most popular for her Inuktitut language covers of pop songs, was found dead in her home near Winnipeg, Manitoba. Her death was ruled a suicide, which Fraser's family attributed to "childhood traumas, racism, and persistent cyberbullying."

Media contagion effect

Suicide contagion can be viewed within the larger context of behavioral contagion, which has been described as a situation in which the same behavior spreads quickly and spontaneously through a group. Suicide contagion refers to the phenomenon of indirect exposure to suicide or suicidal behaviors influencing others to attempt to kill themselves. The Persons most susceptible to suicide contagions are those under 25 years of age. Media coverage of suicides has been shown to significantly increase the rate of suicide, and the magnitude of the increase is related to the amount, duration, and prominence of coverage. A recent study by Dunlop et al. specifically examined possible contagion effects on suicidal behavior via the Internet and social media. Of 719 individuals aged 14 to 24 years, 79% reported being exposed to suicide-related content through family, friends, and traditional news media such as newspapers, and 59% found such content through Internet sources. This information may pose a hazard for vulnerable groups by influencing decisions to die by suicide. In particular, interactions via chat rooms or discussion forums may foster peer pressure to die by suicide, encourage users to idolize those who have died by suicide, or facilitate suicide pacts. Recently there has been a trend in creating memorial social media pages in honor of a deceased person. In New Zealand, a memorial page was made after a person committed suicide, this resulted in the suicide of 8 other persons thereafter, which further shows the power of the media contagion effect. One South Korean study demonstrated that social media data can be used to predict national suicide numbers.

Suicide notes

It has generally been found that those who post suicide notes online tend to not receive help.

Several notable cases support this argument:

  • Kevin Whitrick and Abraham K. Biggs webcast both of their suicides. "I am going to leave this for whoever stumbles across my bookmarks later on."
  • Paul Zolezzi indicated via a Facebook update his intent to commit suicide.
  • In 2010, John Patrick Bedell left a Wikipedia user page and YouTube videos interpreted by some as a suicide note; the former was deleted by Wikipedia administrators.
  • Joe Stack also posted a suicide note online.
  • Chris McKinstry, an AI researcher, committed suicide after posting a note to both his blog and the Joel on Software off-topic forum explaining the reasons for his demise.
  • A girl who attended a Louisville-area high school posted a video suicide note and then killed herself in 2014. The girl did not receive any help prior to her suicide, leading H. Eric Sparks, director of the American School Counselor Association, to say that troubled students should be directed to help hotlines or to trusted authorities to seek intervention as quickly as possible.

Suicide pacts

A suicide pact is an agreement between two or more people to die by suicide at a particular time and often by the same lethal means. Suicide pacts are found to be rare. Traditional suicide pacts have typically developed among individuals who know each other, such as a couple of friends. A suicide pact that has been formed or developed in some way through the use of the Internet is a cyber suicide pact. A primary difference between cybersuicide pacts and traditional suicide pacts is that these pacts are usually formed among strangers. They use online chat rooms and virtual bulletin boards and forums as an unmediated avenue to share their feelings with other like-minded individuals, which can be easier than talking about such thoughts and feelings in person.

The first documented use of the Internet to form a suicide pact was reported in Japan in 2000. It has now become a more common form of suicide in Japan, where the suicide rate increased from 34 suicides in 2003 to 91 suicides in 2005. South Korea now has one of the world's highest suicide rates (24.7/100 000 in 2005), and evidence exists that cyber suicide pacts may account for almost one-third of suicides in that country. Suicide pacts are also in the United States. In April 2018, Macon Middle School, a middle school in North Carolina, became aware of a group on social media called "Edgy" or "Edgy Fan Page 101" in which this group came up with a suicide pact and had suicidal ideations. The middle school contacted the parents and informed them to look into their children's social media pages and talk with them about the dangers of a group like this.

Gerald Krein and William Francis Melchert-Dinkel were accused of arranging internet suicide pacts.

Interventions

Suicide intervention on social media has saved many lives on Twitter, Instagram, and Facebook. All of the aforementioned companies have slightly different ways to report posts that may seem suicidal.

Facebook

Facebook, assisted by, among a handful of other experts, Dr. Dan Reidenburg of Suicide Awareness Voices of Education—"uses an algorithm to track down buzzwords and phrases that are commonly associated with suicide" and has intervened in over 3,500 cases, according to company reports. The algorithm reportedly tracks buzzwords and phrases associated with suicide and an alert is sent to Facebook's Safety Center.

"The technology itself isn’t going to send somebody to their house. A person at Facebook would have to do that…"

–Dr. Dan Reidenburg

Twitter

  • Demi Moore and her followers intervened to stop a suicide that had been announced on Twitter.
  • Twitter followers of Chicago rapper CupcakKe alerted authorities after the rapper posted ominous phrases onto Twitter. She later thanked all of her followers after receiving help.

Forums

  • A German was prevented from killing himself after Spanish internet users saw him announcing his decision.

Discussion and support groups

The Defense Centers of Excellence have expressed interest in using social media for suicide prevention. Facebook groups have sometimes been set up for suicide prevention purposes, including one that attracted 47,000 members. Although many teens and preteens encounter suicide-related posts from peers on different social media apps, they also encounter suicide prevention hotlines and website links as well.

SAMHSA's Suicide Prevention Lifeline operates on Twitter, Facebook, and YouTube. The American Foundation For Suicide Prevention is trying to understand and prevent suicide through research, education, and advocacy.

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