Camera loggers are increasingly used to examine behavioural aspects of free-ranging animals. However, often video loggers are deployed with a focus on specific behavioural traits utilizing small cameras with a limited field of view, poor light performance and video quality. Yet rapid developments in consumer electronics provide new devices with much improved visual data allowing a wider scope for studies employing this novel methodology. We developed a camera logger that records full HD video through a wide-angle lens, providing high resolution footage with a greater field of view than other camera loggers. The main goal was to assess the suitability of this type of camera for the analysis of various aspects of the foraging ecology of a marine predator, the yellow-eyed penguin in New Zealand. Frame-by-frame analysis allowed accurate timing of prey pursuits and time spent over certain seafloor types. The recorded video footage showed that prey species were associated with certain seafloor types, revealed different predator evasion strategies by benthic fishes, and highlighted varying energetic consequences for penguins pursuing certain types of prey. Other aspects that could be analysed were the timing of breathing intervals between dives and observe exhalation events during prey pursuits, a previously undescribed behaviour. Screen overlays facilitated analysis of flipper angles and beat frequencies throughout various stages of the dive cycle. Flipper movement analysis confirmed decreasing effort during descent phases as the bird gained depth, and that ascent was principally passive. Breathing episodes between dives were short (<1 s) while the majority of the time was devoted to subsurface scanning with a submerged head. Video data recorded on free-ranging animals not only provide a wealth of information recorded from a single deployment but also necessitate new approaches with regards to analysis of visual data. Here, we demonstrate the diversity of information that can be gleaned from video logger data, if devices with high video resolution and wide field of view are utilized. Examining the at-sea behaviour of marine animals has long been a challenging endeavour. Direct visual observations of behaviour are almost impossible, especially when most of it happens under the ocean’s surface. In recent decades, advances in telemetry technologies and the emergence of bio-logging hardware have provided the means to track marine animals and reveal their foraging behaviour in great detail. Starting in the 1970s with rather crude location estimates and limited data quality recorded by unwieldy devices that could only be used on large animals, advancements in micro-electronics have resulted in ever smaller and more accurate loggers to pinpoint an animal’s position to within a few metres and record their diving depths with oceanography-grade precision . New tecIn recent years, animal-borne camera systems have made it possible to log in situ observations of behaviour from the animal’s point of view . For exaWhat most of these studies have in common is their focus on specific behavioural traits while providing limited information about the environment the behaviours occurred in. This is principally due to limitations of the video hardware used, which has to be small and lightweight so as to not overly impede the study animal’s movement capabilities  and hencMegadyptes antipodes) in New Zealand is known to be a benthic forager  videos through wide-angle lenses. The main focus of our study was to assess the suitability of the device for the visual analysis of penguin prey pursuit behaviour and characteristics of the benthic ecosystem. However, the deployment revealed far more information than was anticipated. The video data provided novel insights into physiological aspects of the penguin’s diving activities and allowed us to draw conclusions about prey capture techniques. In this paper, we summarise our findings, demonstrate analytical approaches to evaluate animal-borne video data, and highlight the multi-disciplinary potential of wide-angle, full HD video loggers.The yellow-eyed penguin, classified as “Endangered” by the IUCN Redlist , is one We developed a high-definition video logger  which is combined with a time-depth recorder  and a GPS logger . The latter two devices were combined into a single unit by gluing the AXY-depth to the longer side of the GPS device. Camera and logger combination were then attached individually in line to the lower back of the penguin using adhesive tape . Additiohttp://www.mobius-actioncam.com). To achieve the smallest and lightest device possible, the camera electronics, video sensor and lens were removed from the casing and the battery replaced with a 1,200 mAh Lithium Polymer battery to extend recording time. A small bespoke timer board was developed to allow the camera to be fired at a pre-determined time. Connections were provided to allow programming logger start time and also to access the camera’s USB port for managing camera setting, extracting the video data and recharging the battery. The board was isolated electrically to prevent the contacts from shorting as sea-water is conductive. Activation of the interface was achieved using a Hall-effect device. An Arduino-based interface was developed to allow the current date/time and logger start time to be set. The camera was programmed to record video data at a resolution of 1,920 × 1,080 pixels (1080p) at a frame rate of 30 frames per second. Video data were recorded in H.264 MPEG4 format and stored on a 32 GB MicroSD card. The camera was programmed to start recording at 11 am the following day when it was assumed that the penguin had completed its travel phase and arrived at its foraging destination. The camera operated from the programmed start time until the battery fell below the minimum operating voltage of the camera (ca. 2–4 h). The device was recovered when the penguin returned from its foraging trip; data were then downloaded through the camera’s USB interface.The camera logger consisted of a modified Mobius action-cam with a 130° wide-angle lens (Since the logger stores video data as a series of full frame images (‘progressive scan’), it was possible to conduct a frame-by-frame analysis to accurately time components of the bird’s behaviour—i.e., breathing intervals, flipper beat frequencies and amplitudes—as well as time spent over certain benthic habitats. Video analysis was conducted in professional editing software  which allows the quick and precise backward and forward navigation of the video material using the keyboard (“scrubbing”) and provides the option to display frame number in the preview timer.The video logger was deployed on a breeding male yellow-eyed penguin tending two chicks on 17 December 2015. Deployment occurred at the penguin’s nest on the evening of 17 December. The bird was removed from the nest and placed in a cloth bag to reduce stress. The instrumentation procedure lasted around 20 min after which the penguin was released back on its nest. The bird left on a single foraging trip on 18 December before the device was recovered on 19 December; the penguin continued to breed normally after the deployment.Upon device recovery, it became apparent that the GPS logger did not record any data after the camera had started operating. It has since become evident that the Mobius action-cam generates significant electromagnetic interference which prevented the GPS logger from functioning properly. This can be rectified by wrapping the camera with electrical shielding tape; however, in our case the lack of shielding resulted in failure to record GPS data.For detailed analysis of behaviours, we randomly selected 12 dive cycles (dive cycle = beginning of the surface period until the end of the following dive’s ascent phase) from the 46 dive cycles recorded  independent from prevalent behaviours exhibited during these dives. This was due to the labour-intensive frame-by-frame analysis necessary for several of the behaviours. Future analyses are ideally conducted automatically using machine learning algorithms to reduce analysis time and increase accuracy e.g., .We defined the beginning of a prey pursuit as the moment when the penguin markedly accelerated while swimming along the seafloor; the end was reached when the penguin decelerated again to its previous cruise speed (if no prey was caught), or when the prey item was swallowed completely. Acceleration and deceleration were associated with temporary blurring of the video footage due to irregular body movement, allowing for exact timing of prey pursuits. Where possible, prey species were identified from frames providing a clear view of the prey item.Ophiuroidea), anthozoans , and horse mussels (Atrina zelandica), within a 30-frame time window. For all dives, the benthic habitat was classified according to sediment type , sediment structure  and composition of the epibenthic communities. For the latter, we used a presence/absence approach with easy-to-identify epibenthic species brittlestars . This allowed us to visually determine maximum amplitude of each flipper beat to the nearest 5°.During dives, flipper beat frequencies  were determined by counting the number of frames required to complete one flipper beat cycle, beginning the count when the flipper angle reached its maximum upward inclination and ending with the frame prior to the subsequent maximum upward inclination. In the video editing software, we overlaid a template indicating 10, 30, 50, 70 and 90-degree angles radiating from the base of the flippers on the video data (https://vimeo.com/179414575#t=145). Additional observations of exhalations during the dive were noted.We timed breathing events when the penguin was at the surface following a dive. Noting frame numbers when the bird raised its head out of the water before lowering below the surface again made it possible to determine the times the penguin was able to respire  and field experiments conducted under research permits issued by the New Zealand Department of Conservation (45799-FAU).n = 159) whereas the majority of pelagic dives occurred in the upper 10 m of the water column ; camera footage confirmed these to be principally travelling behaviour (https://vimeo.com/179414642). For the first 3.5 h of the foraging trip (05:30–09:00 hrs) the bird performed mainly pelagic dives, indicating primarily travelling behaviour towards its main foraging grounds; yellow-eyed penguins are known to exhibit high individual site fidelity with regards to foraging locations . The light sensitivity of the camera was adequate to record clear images at dive depths close to 70 m and, combined with the large field of view, facilitated detailed frame-by-frame analysis.The camera operated continuously from 11:00:22 hrs to 13:01:43 hrs. Due to frame loss representing a mean 1.6 seconds of footage when video data were written to the file every 3 min, total length of the recorded footage amounted to 2 h 8 s. Forty-six complete dives were video recorded which corresponds to 16% of all dive events; of these 32 dives were benthic dives. However, dives were longer during the middle of the day so that camera footage covered 25% of the trip’s cumulative dive time. The video quality proved to be significantly better than that recorded with other animal-borne cameras deployed on penguins to date  or blue cod ; prey species could not be identified during two captures, but the penguin’s searching behaviour and ease of ingestion suggested these were opalfish and we include them with opalfish captures below and in https://vimeo.com/179414724). During the camera operation time, the penguin spent 5.7 min on prey pursuit, which corresponds to 19% of the total time the bird foraged along the seafloor (29.9 min) and 6% of its total dive time (89.9 min). The penguin spent most of its active prey pursuit on opalfish , 0.7 min were used to capture blue cod (2 events), and 1.2 min of prey pursuit did not result in successful prey capture . During encounters with blue cod prolonged pursuits ensued during which fish zigzagged at a fast pace along the seafloor (https://vimeo.com/179414724#t=2m46s). In one instance the fish was caught as it appeared to seek shelter at the base of a horse mussel protruding from the substrate (https://vimeo.com/179414724#t=2m55s). An unsuccessful prey pursuit of blue cod ended with the fish escaping under what appeared to be a half-buried back plate of a dishwasher (https://vimeo.com/179414777). A third blue cod encounter occurred just seconds after a successful capture of an opalfish; it seems likely that the resulting prolonged bottom time and oxygen-demanding prey pursuits drove the penguin to carry the fish to the surface at an almost vertical angle as indicated sun disc’s central position in the frame; the fish was ultimately dropped at the surface (https://vimeo.com/179414724#t=3m07s).Two main prey pursuit strategies became apparent that were associated with prey species. When catching opalfish, the penguin would glide closely above the seafloor, sometimes briefly accelerating before starting to hover over a certain spot while repeatedly pecking at the substrate until the prey item was captured  was spent over coarse sand, whereas time spent over fine sand (7%) and gravel (0.9%) was negligible  & 3. Twohttps://vimeo.com/179414724), while flat bottom habitat played a more important role during blue cod pursuits . With regards to epibenthic characteristics, brittle stars and anemones were present during the majority of the prey pursuit times for both fish species . In contrast, ascending was principally passive with the penguin using its natural buoyancy to return to the surface, occasionally aided by a few strokes in the early stages of the ascent, decreasing beat frequency . Despite differences in flipper movement between the two transit phases of a dive, the vertical velocities recorded by the TDR did not differ significantly .When descending to the sea floor the penguin propelled itself with fast, strong flipper strokes that got progressively slower and less pronounced with time and, thus, increasing depth . While searching the penguin showed lower flipper beat frequencies  paired with greater flipper amplitudes (53° ± 14° ) when compared to prey pursuit . Flipper beat frequency increased slightly but consistently towards the end of the bottom phase .During the bottom phase flipper amplitudes showed no correlation with relative bottom time ; for the majority of the time at the surface the bird kept its head under water  (https://vimeo.com/179414575#t=2m25s). Duration of breathing intervals increased with ongoing duration of the surface period  indicating increased respiration activity in preparation for the next dive . During the passive phase of the ascent, the penguin frequently exhaled as indicated by a stream of large bubbles released from the nostrils. The bird released substantial amounts of air on the last few meters immediately prior to reaching the surface (https://vimeo.com/179414575#t=2m18s). While some of this air may have been released from the plumage . Such exhalations were brief but performed with substantial force; air was jetted from the nostrils as a fine gas spurt .Judging from the total time the bird spent over a benthic environment dominated by coarse sand and sediment ripples  as well as almost exclusive encounters of opalfish over such habitat  & 3, it The majority of prey pursuits occurred in areas that featured anthozoans, principally sea anemones  & 3. AneDeploying video loggers on penguins could enable detailed mapping of the benthic habitat within the species’ home ranges. Yellow-eyed penguins are known to have preferred individual foraging areas often with little overlap between birds . MoreoveThe outer ranges of the marine habitat of yellow-eyed penguins from the Otago Peninsula is subject to bottom fisheries which have a profound effect on benthic ecosystems e.g., . Yellow-Beyond investigations of behaviour in a wider environmental context, our study also shows the potential application of camera loggers for the investigation of physiological aspects of marine animals.Our observations of flipper movements, i.e., strong flipper movements at the beginning of a dive that decrease with depth, and cessation of flipper movements during ascent, align with findings reported in other penguins. Using accelerometers, https://vimeo.com/179414575#t=2m18s).We provide evidence that the ascent phase in penguins is largely passive, as has been suggested using both accelerometers and magnets . Sato et2 and mobilizing O2 from oxygen stores for prey pursuit. Such pursuits must be costly in terms of oxygen consumption as is evident from the observed consecutive prey encounters during one single dive, which resulted in the penguin letting go of the second fish after a rapid ascent to the surface (https://vimeo.com/179414724#t=3m07s). Unlike seals that have been found to exhale when ascending from deep dives, most likely to reduce the drop in blood oxygen  it becomes clear that greater visual fidelity of full HD cameras comes along with a much wider range of quantifiable data. This creates a new opportunity for a more holistic approach to study the diving behaviour of marine animals that integrates behaviour, physiology and their environment.A large field of view achieved through wide-angle lenses furthermore allows detailed analysis of flipper movements, which to date could only be achieved through elaborate modelling of accelerometer data  or use ohttps://cloud.google.com/video-intelligence/) that may be used to automate the analysis process. For more basic analyses such as prey composition and encounter rates, but also determination of environmental parameters, there already exist software solutions that offer an enhanced workflow, for example the video annotation software BORIS (http://www.boris.unito.it/).Depending on which behaviours are quantified, the manual analysis of video data can be quite time-consuming. For example, flipper beats and angles require a frame-by-frame analysis; an average dive duration of 3 min translated to 5,400 frames per dive. However, the higher the resolution and quality of the video footage, the greater the potential to develop machine learning algorithms . For all these reasons, the technology currently available is best suited for short-term deployments on central place foragers. Although video data recorded on animals performing long-term foraging trips (e.g., Magellanic penguins, 10.7717/peerj.5459/supp-1Supplemental Information 1Click here for additional data file.


At the heart of their regulatory function is the formation of a highly specific aptamer–ligand complex. Understanding how these RNAs recognize the ligand to regulate gene expression at physiological concentrations of Mg2+ ions and ligand is critical given their broad impact on bacterial gene expression and their potential as antibiotic targets. In this work, we used single-molecule FRET and biochemical techniques to demonstrate that Mg2+ ions act as fine-tuning elements of the amino acid-sensing lysC aptamer's ligand-free structure in the mesophile Bacillus subtilis. Mg2+ interactions with the aptamer produce encounter complexes with strikingly different sensitivities to the ligand in different, yet equally accessible, physiological ionic conditions. Our results demonstrate that the aptamer adapts its structure and folding landscape on a Mg2+-tunable scale to efficiently respond to changes in intracellular lysine of more than two orders of magnitude. The remarkable tunability of the lysC aptamer by sub-millimolar variations in the physiological concentration of Mg2+ ions suggests that some single-aptamer riboswitches have exploited the coupling of cellular levels of ligand and divalent metal ions to tightly control gene expression.Riboswitches are  Riboswitches are noncoding mRNA sequences usually found in the 5′ untranslated regions of many genes involved in metabolite biosynthesis or transport, which they regulate by binding specific, related metabolites ,2. Ribosl-glutamine . The sequences and a schematic of the construct are shown in The experimental constructs for the wild type and variant lysine aptamers incorporate two RNA strands and a biotin-carrying DNA tether  for 4 h . The cells were then suspended in 4% paraformaldehyde in PBS and incubated 7 min at room temperature for fixation. Cells were pelleted by centrifugation and washed with an oxalate/EDTA solution (0.1 M/0.05 M) at room temperature for 7 min to remove external metals. The pellet was then suspended in 10 ml sterile 0.5 M NaCl. From this 10 ml, 2 ml were coloured with SYTO9 and used for cell volume calculation. Cellular volume was obtained using fluorescent microscopy pictures of B. subtilis taken with the fluorescent dye and it was calculated as a cylinder and two half-spheres using maximum Feret diameter (length) and minimal Feret diameter (width) evaluated by image analysis (CellProfiler 3). Images were taken using a Zeiss Axio Observer Z1 microscope. The other 8 ml were washed again with oxalate/EDTA and pelleted by centrifugation . These cells were digested on an SCP science Digiprep Jr with 600 μl of nitric acid  at 65°C for 45 min. The SCP science Digiprep Jr is a 24-position Teflon-coated block digestion system that can reach 180°C with 1.0°C uniformity across the surface. After digestion, each tube was filled with 10 ml Milli-Q water. Samples were analyzed for phosphorus and metal content on an inductively-coupled-plasma mass spectrometer  as previously described .Previous work on the lysine riboswitch has addressed aptamers from multiple organisms, both thermophilic ,33 and m ∼ 50 mM . Given tBacillus subtilis strain 168 was grown in a Spizizen  or in 10 mM extracellular Mg2+ concentration ([Mg2+]free ∼ 1.6 mM) (Spizizen  medium aectively . The int 1.6 mM) ,37.in vitro transcription assay  was added to the transcription buffer, termination efficiency reached a value of 75% in 2 mM Mg2+, which decreased to 51% in 1 mM Mg2+  decreased by half when the Mg2+ concentration increased from 1 to 2 mM, from 129 ± 15 μM to 61 ± 7 μM. However, T50 only decreased by an additional 15%, to 52 ± 7 μM, in 10 mM Mg2+  microscope (lysC aptamer from three oligonucleotide strands (Eapp) of ∼0.66 for the ligand-bound state.We wanted to determine the conformational response of the croscope . We asse strands . The Cy5 strands . We have strands . We obta strands  and the  strands  (see Sup strands . The modEapp ∼ 0.32 ± 0.01(mean ± s.d.), and the smFRET trajectories of individual aptamers remained constant until photobleaching occurred  and a similar Hill coefficient (2.2 ± 0.4)  . These dLFF) requires the formation of both tertiary contacts   Figure , so we d2+ and increasing lysine concentrations exhibited only fluctuations between U and LFF  and the changes in the barrier height (ΔΔG‡) from the single-molecule kinetic data   . This scm Figure , in whiclysC aptamer revealed that the LFF state can be efficiently populated at the high end of the physiological Mg2+ concentration range (∼2 mM). We hypothesised that LFF might function as a high-affinity binding scaffold for lysine in these conditions. To test this hypothesis, we titrated the aptamer with lysine in a background of 2 mM  as a function of lysine in both 2 mM and 10 mM Mg2+  than in 10 mM Mg2+ (∼25%), but it remained nearly constant when increasing the concentration of lysine, while the LFF and LBF states exchanged populations. A global fitting of the binding isotherms for these two states yielded KD values of 3 ± 1 μM in 2 mM and 1.3 ± 0.5 μM in 10 mM Mg2+, two orders of magnitude lower than in 0.5 mM Mg2+ (∼310 ± 50 μM). Omitting K+ ions from the medium increased the KD to 850 ± 35 μM  over direct U↔ LBF transitions can be clearly observed. In the ∼450 transitions analysed in which U was the initial state, less than 10% of them involved a direct U↔LBF transition  than the rare LBF → U transition (0.25 ± 0.06 s−1). In contrast, direct docking via the U→ LBF route, although infrequent, was 150-fold faster (2.3 ± 0.3 s−1) than docking through the LFF→FLB pathway (0.014 ± 0.003 s−1) , but this route leads to a much less stable LBF state than when formed through the LFF intermediate.A transition-density plot (TDP) of the raw number of FRET transitions revealed six populations corresponding to pairwise transitions between the s Figure . The staansition . We extrn Figure . The und) Figure . This suLFF→LBF docking rate increased by a factor of 10 and became similar to that observed for the U→FLB transition  was determined from the product KD, fold• KD, bind to be 11 ± 7 μM, close to the value of 3 ± 1 μM obtained by fitting the fractional occupancies of LFF and LBF . Thus, although Mg2+ ions pre-organize much of the tertiary structure of the aptamer, the metabolite-binding LFF→FLB transition retains the kinetic features of an induced-fit mechanism.The free energy differences between the s Figure  suggest lysC riboswitch  or increases the folding rate (induction). Many of the riboswitches studied using single-molecule microscopy to date have been shown to pre-organize into a native or native-like state in the presence of Mg2+ but the absence of ligand  the native state from a pre-existing manifold. However, it is logically possible that a riboswitch could exhibit traits of either mechanism, according to either definition, and that these ‘mixed’ mechanisms could be environmentally dependent. For example, the Pre-Q1 aptamer transitions from an induced fit mechanism to conformational selection as a result of cation-induced folding  riboswitch shows binding of the ligand to an unfolded state of the aptamer as expected of induced fit, but also the characteristic slowing of the unfolding rate with increasing HyCbl concentration that indicates conformational selection (yybP-ykoY from B. subtilis has also been shown to shift between induced-fit and conformational selection pathways in response to cellular levels of Mg2+ (This intrinsic Mg folding , while telection . The man of Mg2+ .lysC aptamer recognizes the ligand exclusively using an induced-fit mechanism (Figure 2+ concentrations. This fact is all the more remarkable given that the Mg2+-induced compaction widespread among riboswitches commonly organises the holo state directly, as in the case of Pre-Q1 (add and pbuE adenine riboswitches (lysC, Mg2+ tunes the affinity of the aptamer for lysine but switching still occurs exclusively in the presence of the ligand.Growing evidence suggests that ‘mixed’ ligand-recognition mechanisms with features of both conformational selection and induced fit are common, perhaps even prevalent, in ligand binding to RNA . Howeverm Figure  in both f Pre-Q1 , the addswitches ,61–62, aswitches ,64. In tadd riboswitch from V. vulnificus uses temperature-dependent switching between two ligand-free secondary structures to modulate its response to adenine inside and outside its host (T. tengcongensis achieves maximal aptamer preorganisation in the physiological Mg2+ concentration range, while higher concentrations favour the organisation of the expression platform (lysC aptamer's dynamic dependence on Mg2+ concentration variations within the physiological range can be considered a new type of environmental modulation, in which Mg2+ tunes the ligand affinity of the aptamer and the fidelity of its regulatory outcome by varying the structure of the encounter complex without inducing holo state formation (In vivo experiments linking the expression of lysC to the variation in the concentrations of Mg2+ and ligand in both the normal cell cycle and stressed environments is needed to illuminate the biological role of this novel dual-layer control mechanism.Other examples of environmental dependence exist among riboswitches ,61–62. Fplatform . The lysormation . In vivo2+ ions to act as a fine-tuning element of its tertiary structure. By doing so, it modulates its affinity for its cognate ligand by two orders of magnitude without the need to alter its nucleotide sequence, a strategy that might also be exploited by other regulatory elements to tightly control gene expression.In summary, we have demonstrated the first example of an RNA aptamer that has optimized its response to Mggkz316_Supplemental_FileClick here for additional data file.


Hepatocellular adenoma (HCA) is a rare benign tumor and is related to the use of an oral contraceptive pill. Turner’s syndrome requires various hormone replacement therapies, including the pill which is used as a female hormone replacement therapy. Herein we report a case of Turner’s syndrome with HCA treated by liver segmentectomy.iso-intensity in the portal and late phases, and low intensity in the hepatobiliary phase on Gb-EOB-MRI. She was diagnosed with multiple HCAs and underwent segmentectomy Section 7. Pathologically, both the tumors were diagnosed as HCAs, and inflammatory markers were detected by immunohistochemistry. Thirteen months postoperatively, she was doing well and there was no evidence of recurrence of HCA without the pill.A 36-year-old woman with Turner’s syndrome was treated with oral contraceptive pills as a female hormone replacement therapy for 20 years. She presented with fatigue and liver tumor. Liver tumors in the posterior lobe measuring 60 mm and 10 mm in diameter were detected on CT; hence, she was referred to our department. Both the tumors showed high intensity in the arterial phase, There is only one report of HCA in patients with TS . We reported a case of multiple HCAs in a patient with TS underwent hepatectomy.With the use of the contraceptive pill as a long-term female hormone replacement therapy for Turner’s syndrome, careful attention is required for HCA. She received an oral contraceptive pill as a hormone replacement therapy (HRT) from the age of 16 years. She was referred to our department in July 2017 after presenting at a local hospital with fatigue and liver tumors detected on computed tomography (CT).Her physical examination and blood tests showed no remarkable findings. Abdominal ultrasonography showed a low echoic tumor, which was 60 mm in diameter, in the posterior section of the liver and an isoechoic tumor, which was 6 mm in diameter, at the root of the right hepatic vein RHV; .Fig. 1AbCT showed a 60-mm tumor in the posterior section of the liver. This tumor showed high density in the arterial phase and isodensity in the portal and late phases. Another small 10-mm tumor at the root of RHV also showed high density in the arterial phase and isodensity in the portal and late phases .Fig. 2PlGadoxetic acid ethoxybenzyl magnetic resonance imaging (Gb-EOB-MRI) of the large tumor showed high intensity on T2-weighted images and in the arterial and portal phases, and low intensity in the late and hepatobiliary phases, while the small tumor showed low intensity in the hepatobiliary phase .Fig. 3GbBased on the diagnosis of multiple HCAs or hepatocellular carcinomas (HCCs), segmentectomy of No 7 of the liver was performed. The operation time was 178 min, and blood loss was 681 mL.Macroscopic findings showed a whitish and brownish tumor, which was 61 mm in diameter and without capsula and another small, whitish, 11-mm tumor without capsula. Pathological findings of the larger tumor showed hepatocytes without atypia, with sinusoid dilatation and a single vessel seen within the tumor. This tumor was diagnosed as HCA. Immunohistochemistry findings of the larger tumor showed that the hepatocytes were positive for C-reactive protein (CRP) and liver fatty acid-binding protein (LFABP) and negative for β-catenin, glutamine synthetase (GS), and glypican-3 . The smaThe patient was discharged on postoperative day 14. At the 13-month postoperative follow-up, she was doing well and there was no evidence of recurrence of HCA without the pill.3TS requires various HRTs, with the contraceptive pill often administered ,5, whichIn 2010, the World Health Organization classified HCA into four subtypes based on immunohistochemistry findings: IHCA, HNF1A-mutated HCA (H-HCA), β-catenin-mutated HCA (b-HCA), and unclassified HCA (UHCA) ,9. The mPatients with TS experience various complications , commonlIndication of treatment for HCA has been reported . When th4We experienced a case of multiple inflammatory HCAs in TS that were related to the long-term use of a contraceptive pill. Therefore, careful attention is required for HCA in patients with TS taking contraceptive pills as a long-term female HRT.No conflict of interest.No funding.This case report is exempt from ethical approval by our institution.Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in -Chief of this journal on request.Satoshi Nemoto: treated and helped operation, collected the data, and drafted the manuscript.Shun-ichi Ariizumi: conducted the examinations on this patient as well as treated and operated, drafted the manuscript, pathological examination and contributed to the diagnosis of this patient.Yoshihito Kotera, Akiko Omori, Taka-aki Kato and Shota Aoyama: helped treat this patient.Hiroto Egawa: conducted the manuscript.Masakazu Yamamoto: conducted the manuscript and operate the patient.All authors read and approved the final manuscript.No registration of research studies.On behalf of all author, Yamamoto Masakazu M.D. is guarantor for this paper.Not commissioned, externally peer-reviewed.


It is a widespread concern that violent video games promote aggression, reduce pro-social behaviour, increase impulsivity and interfere with cognition as well as mood in its players. Previous experimental studies have focussed on short-term effects of violent video gameplay on aggression, yet there are reasons to believe that these effects are mostly the result of priming. In contrast, the present study is the first to investigate the effects of long-term violent video gameplay using a large battery of tests spanning questionnaires, behavioural measures of aggression, sexist attitudes, empathy and interpersonal competencies, impulsivity-related constructs , mental health  as well as executive control functions, before and after 2 months of gameplay. Our participants played the violent video game Grand Theft Auto V, the non-violent video game The Sims 3 or no game at all for 2 months on a daily basis. No significant changes were observed, neither when comparing the group playing a violent video game to a group playing a non-violent game, nor to a passive control group. Also, no effects were observed between baseline and posttest directly after the intervention, nor between baseline and a follow-up assessment 2 months after the intervention period had ended. The present results thus provide strong evidence against the frequently debated negative effects of playing violent video games in adults and will therefore help to communicate a more realistic scientific perspective on the effects of violent video gaming. The concern that violent video games may promote aggression or reduce empathy in its players is pervasive and given the popularity of these games their psychological impact is an urgent issue for society at large. Contrary to the custom, this topic has also been passionately debated in the scientific literature. One research camp has strongly argued that violent video games increase aggression in its players , 2, wherTo unravel this topic of research, we designed a randomised controlled trial on adults to draw causal conclusions on the influence of video games on aggression. At present, almost all experimental studies targeting the effects of violent video games on aggression and/or empathy focussed on the effects of short-term video gameplay. In these studies the duration for which participants were instructed to play the games ranged from 4 min to maximally 2 h  and It has been suggested that the effects of studies focussing on consequences of short-term video gameplay (mostly conducted on college student populations) are mainly the result of priming effects, meaning that exposure to violent content increases the accessibility of aggressive thoughts and affect when participants are in the immediate situation . HoweverHowever, in our view the question that society is actually interested in is not: “Are people more aggressive after having played violent video games for a few minutes? And are these people more aggressive minutes after gameplay ended?”, but rather “What are the effects of frequent, habitual violent video game playing? And for how long do these effects persist (not in the range of minutes but rather weeks and months)?” For this reason studies are needed in which participants are trained over longer periods of time, tested after a longer delay after acute playing and tested with broader batteries assessing aggression but also other relevant domains such as empathy as well as mood and cognition. Moreover, long-term follow-up assessments are needed to demonstrate long-term effects of frequent violent video gameplay. To fill this gap, we set out to expose adult participants to two different types of video games for a period of 2 months and investigate changes in measures of various constructs of interest at least one day after the last gaming session and test them once more 2 months after the end of the gameplay intervention. In contrast to the GAM, we hypothesised no increases of aggression or decreases in pro-social behaviour even after long-term exposure to a violent video game due to our reasoning that priming effects of violent video games are short-lived and should therefore not influence measures of aggression if they are not measured directly after acute gaming. In the present study, we assessed potential changes in the following domains: behavioural as well as questionnaire measures of aggression, empathy and interpersonal competencies, impulsivity-related constructs , and depressivity and anxiety as well as executive control functions. As the effects on aggression and pro-social behaviour were the core targets of the present study, we implemented multiple tests for these domains. This broad range of domains with its wide coverage and the longitudinal nature of the study design enabled us to draw more general conclusions regarding the causal effects of violent video games.Grand Theft Auto V (GTA) or Sims 3 in any of its versions before). We excluded participants with psychological or neurological problems. The participants received financial compensation for the testing sessions (200 Euros) and performance-dependent additional payment for two behavioural tasks detailed below, but received no money for the training itself.Ninety healthy participants  were recruited by means of flyers and internet advertisements. The sample consisted of college students as well as of participants from the general community. The advertisement mentioned that we were recruiting for a longitudinal study on video gaming, but did not mention that we would offer an intervention or that we were expecting training effects. Participants were randomly assigned to the three groups ruling out self-selection effects. The sample size was based on estimates from a previous study with a similar design [n = 25, mean age = 26.6 years, SD = 6.0, 14 females) played the game Grand Theft Auto V on a Playstation 3 console over a period of 8 weeks. The active control group played the non-violent video game Sims 3 on the same console . The passive control group  was not given a gaming console and had no task but underwent the same testing procedure as the two other groups. The passive control group was not aware of the fact that they were part of a control group to prevent self-training attempts. The experimenters testing the participants were blind to group membership, but we were unable to prevent participants from talking about the game during testing, which in some cases lead to an unblinding of experimental condition. Both training groups were instructed to play the game for at least 30 min a day. Participants were only reimbursed for the sessions in which they came to the lab. Our previous research suggests that the perceived fun in gaming was positively associated with training outcome [The violent video game group  where the player can choose between different behaviours. The game also allows the player to engage in various side activities, such as action-adventure, driving, third-person shooting, occasional role-playing, stealth and racing elements. The open world design lets players freely roam around the fictional world so that gamers could in principle decide not to commit violent acts.Sims is a life simulation game and also classified as a sandbox game because it lacks clearly defined goals. The player creates virtual individuals called “Sims”, and customises their appearance, their personalities and places them in a home, directs their moods, satisfies their desires and accompanies them in their daily activities and by becoming part of a social network. It offers opportunities, which the player may choose to pursue or to refuse, similar as GTA but is generally considered as a pro-social and clearly non-violent game.To assess aggression and associated constructs we used the following questionnaires: Buss–Perry Aggression Questionnaire , State HOn the basis of the research question whether violent video game playing enhances aggression and reduces empathy, the focus of the present analysis was on time by group interactions. We conducted these interaction analyses separately, comparing the violent video game group against the active control group (GTA vs. Sims) and separately against the passive control group (GTA vs. Controls) that did not receive any intervention and separately for the potential changes during the intervention period (baseline vs. posttest 1) and to test for potential long-term changes (baseline vs. posttest 2). We employed classical frequentist statistics running a repeated-measures ANOVA controlling for the covariates sex and age.n tests is set to an alpha value of 0.05 by taking alpha/n = 0.00024.Since we collected 52 separate outcome variables and conduced four different tests with each , we had to conduct 52 × 4 = 208 frequentist statistical tests. Setting the alpha value to 0.05 means that by pure chance about 10.4 analyses should become significant. To account for this multiple testing problem and the associated alpha inflation, we conducted a Bonferroni correction. According to Bonferroni, the critical value for the entire set of p-values for each test, however, it controls only for the number of false discoveries in those tests that result in a discovery (namely a significant result).Since the Bonferroni correction has sometimes been criticised as overly conservative, we conducted false discovery rate (FDR) correction . FDR cort-tests, since those may hamper the interpretation of significant interactions between group and time that we were primarily interested in.Moreover, we tested for group differences at the baseline assessment using independent 01 suggests how much more likely the data is to occur under the null hypothesis. All analyses were performed using the JASP software package (https://jasp-stats.org).Since the frequentist framework does not enable to evaluate whether the observed null effect of the hypothesised interaction is indicative of the absence of a relation between violent video gaming and our dependent variables, the amount of evidence in favour of the null hypothesis has been tested using a Bayesian framework. Within the Bayesian framework both the evidence in favour of the null and the alternative hypothesis are directly computed based on the observed data, giving rise to the possibility of comparing the two. We conducted Bayesian repeated-measures ANOVAs comparing the model in favour of the null and the model in favour of the alternative hypothesis resulting in a Bayes factor (BF) using Bayesian Information criteria . The BF0χ2p-value > 0.414). However, due to the fact that differences between males and females have been observed in terms of aggression and empathy [t(51) = −2.10, p = 0.041) and the Sims group (t(50) = −2.38, p = 0.021), we also controlled for age.Sex distribution in the present study did not differ across the groups .The participants in the violent video game group played on average 35 h and the non-violent video game group 32 h spread out across the 8 weeks interval (with no significant group difference ω2) as an effect size measure. Next to the classical frequentist statistics, we report the results of a Bayesian statistical approach, namely BF01, the likelihood with which the data is to occur under the null hypothesis that there is no significant time × group interaction. In Table To test whether participants assigned to the violent GTA game show emotional, cognitive and behavioural changes, we present the results of repeated-measure ANOVA time x group interaction analyses separately for GTA vs. Sims and GTA vs. Controls Tables –3. Moreo–Since we conducted 208 separate frequentist tests we expected 10.4 significant effects simply by chance when setting the alpha value to 0.05. In fact we found only eight significant time × group interactions . According to G*Power [f = 0.16  in each separate test. When accounting for the conservative Bonferroni-corrected p-value of 0.00024, still a medium effect size of f = 0.23  would have been detectable. A meta-analysis by Anderson [r = 0.18 for experimental studies testing for aggressive behaviour and another by Greitmeyer [r = 0.19, 0.25 and 0.17 for effects of violent games on aggressive behaviour, cognition and affect, all of which should have been detectable at least before multiple test correction.To test the sensitivity of the present study to detect relevant effects we computed the effect size that we would have been able to detect. The information we used consisted of alpha error probability = 0.05, power = 0.95, our sample size, number of groups and of measurement occasions and correlation between the repeated measures at posttest 1 and posttest 2  have been trained in a violent video game for 4 weeks . In compThe present study goes beyond these studies by showing that 2 months of violent video gameplay does neither lead to any significant negative effects in a broad assessment battery administered directly after the intervention nor at a follow-up assessment 2 months after the intervention. The fact that we assessed multiple domains, not finding an effect in any of them, makes the present study the most comprehensive in the field. Our battery included self-report instruments on aggression  as well as computer-based tests measuring aggressive behaviour such as the delay frustration task and measuring the availability of aggressive words using the word completion test and a lexical decision task. Moreover, we assessed impulse-related concepts such as sensation seeking, boredom proneness and associated behavioural measures such as the computerised Balloon analogue risk task, and delay discounting. Four scales assessing empathy and interpersonal competence scales, including the reading the mind in the eyes test revealed no effects of violent video gameplay. Neither did we find any effects on depressivity (Becks depression inventory) nor anxiety measured as a state as well as a trait. This is an important point, since several studies reported higher rates of depressivity and anxiety in populations of habitual video gamers , 55. LasTaken together, the findings of the present study show that an extensive game intervention over the course of 2 months did not reveal any specific changes in aggression, empathy, interpersonal competencies, impulsivity-related constructs, depressivity, anxiety or executive control functions; neither in comparison to an active control group that played a non-violent video game nor to a passive control group. We observed no effects when comparing a baseline and a post-training assessment, nor when focussing on more long-term effects between baseline and a follow-up interval 2 months after the participants stopped training. To our knowledge, the present study employed the most comprehensive test battery spanning a multitude of domains in which changes due to violent video games may have been expected. Therefore the present results provide strong evidence against the frequently debated negative effects of playing violent video games. This debate has mostly been informed by studies showing short-term effects of violent video games when tests were administered immediately after a short playtime of a few minutes; effects that may in large be caused by short-lived priming effects that vanish after minutes. The presented results will therefore help to communicate a more realistic scientific perspective of the real-life effects of violent video gaming. However, future research is needed to demonstrate the absence of effects of violent video gameplay in children.Supplementary Material


The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access to therapy. We hypothesize that the use of machine learning analysis on home video can speed the diagnosis without compromising accuracy. We have analyzed item-level records from 2 standard diagnostic instruments to construct machine learning classifiers optimized for sparsity, interpretability, and accuracy. In the present study, we prospectively test whether the features from these optimized models can be extracted by blinded nonexpert raters from 3-minute home videos of children with and without ASD to arrive at a rapid and accurate machine learning autism classification.We created a mobile web portal for video raters to assess 30 behavioral features  that are used by 8 independent machine learning models for identifying ASD, each with >94% accuracy in cross-validation testing and subsequent independent validation from previous work. We then collected 116 short home videos of children with autism  and 46 videos of typically developing children . Three raters blind to the diagnosis independently measured each of the 30 features from the 8 models, with a median time to completion of 4 minutes. Although several models , radial kernel, and linear SVM) performed well, a sparse 5-feature LR classifier (LR5) yielded the highest accuracy (area under the curve [AUC]: 92% [95% CI 88%–97%]) across all ages tested. We used a prospectively collected independent validation set of 66 videos (33 ASD and 33 non-ASD) and 3 independent rater measurements to validate the outcome, achieving lower but comparable accuracy (AUC: 89% [95% CI 81%–95%]). Finally, we applied LR to the 162-video-feature matrix to construct an 8-feature model, which achieved 0.93 AUC (95% CI 0.90–0.97) on the held-out test set and 0.86 on the validation set of 66 videos. Validation on children with an existing diagnosis limited the ability to generalize the performance to undiagnosed populations.These results support the hypothesis that feature tagging of home videos for machine learning classification of autism can yield accurate outcomes in short time frames, using mobile devices. Further work will be needed to confirm that this approach can accelerate autism diagnosis at scale. Dennis P. Wall and colleagues demonstrate that machine learning algorithms can classify children with and without autism spectrum disorder using nonexpert tagging of home videos. Autism has risen in incidence by approximately 700% since 1996 and now impacts at least 1 in 59 children in the United States.The current standard for diagnosis requires a direct clinician-to-child observation and takes hours to administer.The sharp rise in incidence of autism, coupled with the un-scalable nature of the standard of care (SOC), has created strain on the healthcare system, and the average age of diagnosis remains around 4.5 years, 2 years past the time when it could be reliably diagnosed.Mobile measures that scale could help to alleviate this strain on the healthcare system, reduce waiting times for access to therapy and treatment, and reach underserved populations.We applied 8 machine learning models to 162 two-minute home videos of children with and without autism diagnosis to test the ability to reliably detect autism on mobile platforms.Three nonexpert raters measured 30 behavioral features needed for machine learning classification by the 8 models in approximately 4 minutes.Leveraging video ratings, a machine learning model with only 5 features achieved 86% unweighted average recall (UAR) on 162 videos and UAR = 80% on a different and independently evaluated set of 66 videos, with UAR = 83% on children at or under 4.The above machine learning process of rendering a mobile video diagnosis quickly created a novel collection of labeled video features and a new video feature–based model with >90% accuracy.Short home videos can provide sufficient information to run machine learning classifiers trained to detect children with autism from those with either typical or atypical development. Features needed by machine learning models designed to detect autism can be identified and measured in home videos on mobile devices by nonexperts in timeframes close to the total video length and under 6 minutes.The machine learning models provide a quantitative indication of autism risk that provides more granularity than a binary outcome to flag inconclusive cases, potentially adding value for use in clinical settings, e.g., for triage.The process of mobile video analysis for autism detection generates a growing matrix of video features that can be used to construct new machine learning models that may have higher accuracy for autism detection in home video.Clinical prospective testing in general pediatric settings on populations not yet diagnosed will be needed. However, these results support the possibility that mobile video analysis with machine learning may enable rapid autism detection outside of clinics to reduce waiting periods for access to care and reach underserved populations in regions with limited healthcare infrastructure. Neuropsychiatric disorders are the single greatest cause of disability due to noncommunicable disease worldwide, accounting for 14% of the global burden of disease ,3 and noLike most mental health conditions, autism has a complex array of symptoms  that areAs a step toward enabling fast and accurate access to care for ASD, we have used supervised machine learning approaches to identify minimal sets of behaviors that align with clinical diagnoses of ASD –30. We aThese preliminary studies focused on building models optimized for accuracy, sparsity, and interpretability that differentiate autism from non-autism while managing class imbalance. We chose models with small numbers of features, with performance at or no more than 1 standard error away from best test performance, and with interpretable outcomes—for example, scores generated by a boosted decision tree or logistic regression (LR) approach. In all, these studies have used score data from 11,298 individuals with autism  and 1,356 controls (including some children for whom autism may have been suspected but was ruled out) and have identified the following 8 classifiers: a 7-feature alternating decision tree (ADTree7) , a 12-feNASD = 69; Ncontrols = 153; median age = 5.8 years), the performance, measured as the unweighted average recall  on 222 children  with 8 features developed from medical data from the administration of the diagnostic instrument ADOS Module 1, and LR5 to refer to the LR with 5 behavioral features developed from analysis of ADOS Module 2 medical record data, and so on.We  appliedWe  used a dWe  performeWe  used scoIn this experiment, we  used medIn this experiment, we  used medAccounting for overlap in the features selected, these 8 models measure 23 unique features in total. The test accuracy for each model was >90%. All models contain approximately 90% fewer questions than the ADI-R and 70%–84% fewer questions than the total features measured within the ADOS. An additional 7 features were chosen for their potential diagnostic value and scored by video raters to assess their suitability for scoring home videos, creating a total of 30 features for the mobile video rating process described below .Under an approved Stanford University IRB protocol, we developed a mobile portal to facilitate the collection of videos of children with ASD, from which participants electronically consented to participate and upload their videos. Participants were recruited via crowdsourcing methods –41 targeWe relied on self-reported information provided by the parents concerning the child’s official diagnosis of autism or non-autism, the age of the child when the video was submitted, and additional demographic information for videos that were submitted directly to the web portal. For videos that were provided via YouTube URLs, we used YouTube metatags to confirm the age and diagnosis of the child in the video. If a video did not include a metatag for the age of the child in the video, the age was assigned following full agreement among the estimates made by 3 clinical practitioners in pediatrics. To evaluate the accuracy of the parents’ self-report and to safeguard against reporting biases, we commissioned a practicing pediatric specialist certified to administer the ADOS to review a random selection of 20 videos. We also commissioned a developmental pediatrician to review a nonoverlapping random selection of 10 additional videos. These clinical experts classified each video as “ASD” or “non-ASD.”We employed a total of 9 video raters who were either students  or working professionals. None had training or certification for detection or diagnosis of autism. All were given instructions on how to tag the 30 questions and were asked to score 10 example videos before performing independent feature tagging of new videos. After training, we provided the raters with unique usernames and passwords to access the secure online portal to watch videos and answer 30 questions for each video needed by the feature vectors to run the 8 machine learning classifiers . FeatureTo test the viability of feature tagging videos for rapid machine learning detection and diagnosis of autism, we empirically identified a minimum number of video raters needed to score parent-provided home videos. We selected a random subset of videos from the full set of videos collected through our crowdsourced portal and ran the ADTree8  model onAfter determining the minimally viable number of video raters, we used that minimum to generate the full set of 30-feature vectors on all videos. Seven of the models were written in Python 3 using the package scikit-learn, and one was written in R. We ran these 8 models on our feature matrices after feature tagging on videos. We measured the model accuracy through comparison of the raters’ majority classification result with the true diagnosis. We evaluated model performance further by age categories: ≤2 years, >2 to ≤4 years, >4 years to ≤6 years, and >6 years. For each category, we calculated accuracy, sensitivity, and specificity.We collected timed data from each rater for each video, which began when a video rater pressed “play” on the video and concluded when a video rater finished scoring by clicking “submit” on the video portal. We used these time stamps to calculate the time spent annotating each video. We approximated the time taken to answer the questions by excluding the length of the video from the total time spent to score a video.The process of video feature tagging provides an opportunity to generate a crowdsourced collection of independent feature measurements that are specific to the video of the child as well as independent rater impressions of that child’s behaviors. This in turn has the ability to generate a valuable feature matrix to develop models that include video-specific features rather than features identified through analysis on archived data generated through administration of the SOC  and were trained for video tagging through the same procedures.This study was conducted under approval by Stanford University’s IRB under protocol IRB-31099. Informed and written consent was obtained from all study participants who submitted videos to the study.All classifiers used for testing the time and accuracy of mobile video rating had accuracies above 90% . The unin = 25) or inadequate video quality (n = 6), leaving 162 videos (116 with ASD and 46 non-ASD) which were loaded into our mobile video rating portal for the primary analysis. To validate self-reporting of the presence or absence of an ASD diagnosis, 2 clinical staff trained and certified in autism diagnosis evaluated a random selection of 30 videos (15 with ASD and 15 non-ASD) from the 162 videos. Their classifications had perfect correspondence with the diagnoses provided through self-report by the primary caregiver.We collected a total of 193 videos  with aveWe randomly selected 50 videos (25 ASD and 25 non-ASD) from the total 162 collected videos and had 9 raters feature tag all in an effort to evaluate the potential for an optimal number of raters, with optimal being defined through a balance of scalability and information content. The average video length of this random subset was 1 minute 54 seconds (SD = 46 seconds) for the ASD class and 2 minutes 36 seconds (SD = 1 minute 15 seconds) for the non-ASD class. We then ran the ADTree8  model onThree raters performed video screening and feature tagging to generate vectors for each of the 8 machine learning models for comparative evaluation of performance . All clan = 1] class in this range). This model performed best on children between the ages of 4 and 6 years, with sensitivity and specificity both above 90%  between the average time spent to score the videos of children with ASD and the average time spent to score the non-ASD videos (6 minutes 36 seconds compared with 5 minutes 8 seconds).The median time for the 3 raters to watch and score a video was 4 minutes . Excludin = 14) of the children with ASD were male and 45% (n = 15) of the non-ASD children were male. The average video length was 3 minutes 24 seconds, with an SD of 45 seconds. For this independent replication, we used 3 different raters, each with no official training or experience with developmental pediatrics. The raters required a median time of 6 minutes 48 seconds for complete feature tagging. LR5 again yielded the highest accuracy, with a sensitivity of 87.8% and a specificity of 72.7%. A total of 13 of the 66 videos were misclassified, with 4 false negatives.To validate the feasibility and accuracy of rapid feature tagging and machine learning on short home videos, we launched a second effort for crowdsourcing videos of children with and without autism to generate an independent replication dataset. We collected 66 videos, 33 of children with autism and 33 non-ASD. This set of videos was comparable to the initial set of 162 videos in terms of gender, age, and video length. The average age for children with ASD was 4 years 5 months (SD = 1 year 9 months), and the average age for non-ASD children was 3 years 11 months (SD = 1 year 7 months). Forty-two percent  novel measures of the 30 video features used to distinguish the autism class from the neurotypical cohort. Out of these 176 videos , 162  were from the analysis set, and 14 videos  were from the set of 66 validation videos. Model hyperparameters  identified through 10-fold cross-validation were 0.01 and 0.6, respectively. We used a high L1 ratio to enforce sparsity and to decrease model complexity and the number of features. We had similar proportions (0.60) for non-ASD and ASD measures in the training set and held-out test set, which allowed us to create a model that generalizes well without a significant change in sensitivity or specificity on novel data. The model had an area under the receiver operating characteristic curve (AUC-ROC) of 93.3% and accuracy of 87.7% on the held-out test set. A comparison of LR-EN-VF with LR L2 penalty (no feature reduction) revealed similar results  . The topPrevious work –29 has sBy using a mobile format that can be accessed online, we showed that it is possible to get multiple independent feature vectors for classification. This has the potential to elevate confidence in classification outcome at the time of diagnosis  while fostering the growth of a novel matrix of features from short home videos. In the second part of our study, we tested the ability for this video feature matrix to enable development of a new model that can generalize to the task of video-based classification of autism. We found that an 8-feature LR model could achieve an AUC of 0.93 on the held-out subset and 0.86 on the prospective independent validation set. One of the features used by this model, sensory seeking, was not used by the instruments on which the original models were trained, suggesting the possibility that alternative features may provide added power for video classification.These results support the hypothesis that the detection of autism can be done effectively at scale through mobile video analysis and machine learning classification to produce a quantified indicator of autism risk quickly. Such a process could streamline autism diagnosis to enable earlier detection and earlier access to therapy that has the highest impact during earlier windows of social development. Further, this approach could help to reduce the geographic and financial burdens associated with access to diagnostic resources and provide more equal opportunity to underserved populations, including those in developing countries. Further testing and refinement should be conducted to identify the most viable method(s) of crowdsourcing video acquisition and feature tagging. In addition, prospective trials in undiagnosed and in larger, more-balanced cohorts including examples of children with non-autism developmental delays will be needed to better understand the approach’s potential for use in autism diagnosis.S1 TableLR10, LR5, and ADTree7 are the top-3 best-performing classifiers on the validation set, which falls in line with the results observed on the test dataset of 162 videos used earlier. LR5 still performs with the highest specificity out of the 8 models. ADTree7, 7-feature alternating decision tree; LR5, 5-feature logistic regression classifier; LR10, 10-feature logistic regression classifier.(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S1 Checklist(DOCX)Click here for additional data file.


This paper presents a descriptive analysis of data gathered by personal interviews from a multistage random sample of 1640 residents aged 18–34 years in Wuhan, China. First, alcohol drinkers and abstainers were compared based on demographic, attitude, and belief variables. Next, the drinkers from the sample were classified into four groups based on frequency-quantity of alcohol use, and the frequency-quantity groups were compared on the same variables. For Abstainers versus Drinkers, we found no difference by age or gender in this sample. Married people and people with children were more likely to be abstainers. University-educated, currently-employed individuals in mid-level jobs were more likely to abstain from alcohol. Vocational/Technical graduates, people who were currently attending college, currently unemployed and never-employed individuals were more likely to be drinkers. Abstainers also responded with less-positive attitudes and beliefs about drinking and attached more importance to reasons for not drinking compared to drinkers. When the drinking frequency-quantity groups were compared, gender differences became significant: more high-quantity drinkers were women; however the guideline for quantity for women was >1 drink at a time compared to >2 drinks at a time for men. Quantity and frequency of drinking was significantly associated with having children, educational level, employment status, and type of occupation. Age, marital status, and being in college did not relate significantly with quantity and frequency of drinking alcohol. Attitudes and beliefs about drinking tended to be more positive among high-frequency and high-quantity drinkers. Drinkers in all frequency-quantity groups attached greater importance to social reasons for drinking compared to personal/psychological reasons for drinking. Drinkers in the lowest frequency-quantity group attached the most importance to reasons for not drinking. These findings confirmed that in China drinking plays an important role in socializing and celebrating, and that there are important differences between alcohol drinkers and abstainers and between frequency/quantity groups of drinkers. Western models of individualized motivation of behaviors may not accurately explain alcohol use in China. We believe the findings from this study suggest the need for more detailed studies of alcohol drinking and abstaining. There is limited data available on the drinking patterns of specific age groups in China. The available literature has described the socio-demographic characteristics of alcohol use ,2,3,4,5,Descriptions of alcohol use among young people have typically been limited to student populations, and have overlooked young adults in general ,14. ThisIn 2010, in China, it was estimated that 58.4% of the males and 28.9% of the females, aged 15 years and older had consumed alcohol in the past 12 months . Among tChinese alcohol culture shares many common characteristics with other alcohol-consuming cultures, but it also differs in important ways. Chinese traditionally view alcohol drinking as an important tool for social networking and emotional expression. Business meetings, social events, and special celebrations like weddings, funerals, and festivals are often accompanied by drinking alcohol . ModeratThe data used in this secondary analysis were derived from a multistage random sample of residents aged 18–34 in Wuhan, China. Wuhan is composed of 13 administrative districts. The sample size for each administrative district was proportional to the population size. Within each administrative district, communities were randomly selected, followed by random household selection. A household member aged 18–34 who had lived in the city for at least 6 months was eligible for interview. If more than one household member was eligible, the person with the most recent birthday was selected. No replacement was allowed for non-respondents. A sample size of 1600 was planned; 1640 interviews were completed . To reduce potential bias and ensure the results accurately reflected the population of interest, the data were weighted by administrative district (urban vs. sub-urban area), age (18 to 34 years), gender, and probability of selection in the household. The survey instrument was developed by a multinational team and collected information about alcohol use, drinking effects, drinking motives, and perception of alcohol drinking. The questionnaire used in China was developed in English, forward translated to Chinese and back translated to English. Modifications accommodated cultural and linguistic nuances. It was pretested with a small sample in Wuhan and further refined. The final questionnaire was administered in face-to-face interviews conducted by specially trained epidemiology graduate students. Interviews lasted about 15 min and were conducted in environments where respondents felt comfortable.n = 704) were respondents who drank alcohol in the past 12 months and consumed at least one standard drink. Abstainers (n = 763) were respondents who have never drunk any alcohol. To distinguish clearly between drinkers and abstainers, respondents who had ever consumed alcohol but not in the last 12 months (n = 122) and respondents who consumed in the past 12 months but less than one standard drink (n = 47) were excluded from this study. These former drinkers and occasional drinkers were too few in number to justify inclusion, and the survey provided no information on their drinking histories. Four individuals who did not provide complete drinking information were also excluded from the study. The comparison of drinkers and abstainers is presented in Part 1.Respondents were divided into drinkers and abstainers based on their answers to three alcohol consumption questions: (1) had ever consumed alcohol (excluding sips), (2) during the last 12 months how often had consumed alcohol, even a small amount, and (3) during the past 12 months, how many drinks on a typical day. Drinkers  drink less than once a month and no more than the 1–2 drinks at a time as recommended for moderate alcohol consumption; high-frequency-low-quantity (HiF-LoQ) drink more than once a month but not more than the 1–2 drink guideline; low-frequency-high-quantity (LoF-HiQ) drink less than once a month but more than the recommended 1–2 drinks when they did drink; and high-frequency-high-quantity (HiF-HiQ) drink at least once a month and more than the 1–2 drinks recommended. Comparison among the four different drinking groups is presented in Part 2.Part 1 of this analysis compared drinkers and abstainers on four variables: demographics, perceptions of drinking, acceptance of drinking, and reasons for not drinking. Demographic information included age, gender, marital status, highest education level attained, employment status, occupation, if a student or not, whether or not the interviewee had children.t-test and a Mann-Whitney-Wilcoxon test for five-point Likert items generally yielded the same results and had similar power. Perceptions of drinking were assessed by three items on a 5-point bipolar scale from strongly disagree to strongly agree. They were (1) drinking is one of life’s pleasures, (2) drinking with someone else is a way of showing friendship, and (3) drinking has no benefits. With the value of skewness and excess kurtosis between −1 and +1 for all items, each item was considered as normally distributed and treated as a continuous variable, so a higher score indicated a more positive attitude towards alcohol. De Winter and Dodou  have conAcceptance of drinking was assessed in response to eight gender-specific drinking situations on a 5-point scale . For measurement parsimony, principal component analysis, using orthogonal and oblique rotations, was conducted to create a smaller set of components. An oblique rotation provided the best defined 4-component structure with loadings above 0.3 . The comRespondents were asked to rate the importance of 13 reasons for not drinking on a 4-point scale . A factor analysis failed to identify a coherent factor structure from the 13 scores, so cluster analysis was used to reduce the number of variables and identify membership groups. Three clusters emerged . A low-rPart 2 of this analysis was among the four drinking frequency-quantity groups. In addition to demographic variables, perceptions of drinking, acceptance of drinking, and reasons for not drinking, comparisons were made on the effects of drinking as well as reasons for drinking. Alcohol use in different drinking locations/situations is presented as an introduction to Part 2.Drinkers were asked to identify in which of seven locations/situations they drank alcohol: (1) drinking in restaurants for dinner, (2) in restaurants for lunch, (3) in bars, (4) at friends’ homes, (5) at their own home with friends, (6) at their own home alone, and (7) in public places like parks.Drinkers were asked to report on 13 possible effects alcohol had on them. Answers were on a 5-point scale . Principal component analysis, using orthogonal and oblique rotations, was conducted to create a smaller set of components. Two items were removed because they loaded on multiple components. The remaining items loaded above 0.3 resulting in a 4-component solution . An obliDrinkers were asked to rate the importance of 11 reasons for drinking alcohol on a 4-point scale . Principal component analysis, using orthogonal and oblique rotations, was conducted to create a smaller set of components. The selection of items with loadings above 0.3 resulted in a 3-component solution . An oblit-tests and adjusted t-tests (if the assumption of homogeneity of variance was not met) were used to test the group mean differences. Contingency tables were created to display the frequency distribution of the categorical variables by drinking status. Chi-square tests of association were used to test the relationship between categorical variables. Effect sizes for all of these tests were calculated—Cohen’s d for t-tests and Cramer’s V for chi-squares.For the comparisons between drinkers and abstainers (Part 1), means and standard deviation for the various scales were calculated. F ratio was used. Contingency tables were created to display the frequency distribution of the categorical variables by four drinking groups. Chi-square tests of association were used to test the relationship between categorical variables. Effect sizes for all tests were calculated—f for ANOVA and Cramer’s V for chi-square tests.For the comparisons between the different drinking groups (Part 2), means and standard deviations were calculated. One-way analysis of variance (ANOVA) with post hoc multiple comparisons were used to test the significance of group mean differences. When the assumption of homogeneity of variance was not met, Welch’s adjusted Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 23 for Windows .Of the 1640 interviews completed, 1467 (84.5%) were valid and used in this study; 48% from drinkers and 52% from abstainers. The description of the sample is shown in T-tests were used to test the group mean differences on each item. Drinkers and abstainers viewed drinking alcohol differently. Drinkers supported the relatively positive statements about alcohol—that drinking is one of life’s pleasures and drinking with someone is a way of showing your friendship. Abstainers believed drinking had no benefits  were not associated with whether someone drank or not. Literature on alcohol use in China has consistently reported higher drinking for males compared to females e.g., ,7,9). An,9. An7,9While there was no gender difference in drinking versus abstaining, gender differences were identified in the Frequency-Quantity group analysis. Men were more likely than women to be in the low-quantity groups (LoF-LoQ and HiF-LoQ). This finding contradicted our observations of drinking culture in China, where men are often forced to drink competitively and women are not. It is possible that this survey has detected changing drinking patterns related to gender and suggests that previous generalizations based on only gender and drinking/nondrinking categories may conceal differences in quantity and frequency of drinking that are important for a better understanding of drinking behavior. We based our classifications of drinking quantity on the official Dietary Guidelines for Chinese Residents, which defined “moderate drinking” as no more than two drinks at one time for males and no more than one drink at one time for females. The different cut-off points explains why the majority of the 18- to-34-year-old females in this survey were in the high-quantity groups (LoF-HiQ and HiF-HiQ) and the majority of the 18- to 34-year old males were in the low-quantity groups (LoF-LoQ and HiF-LoQ). A different result would have come from using a different definition for moderate drinking. We acknowledge that the drinking definitions used are conservative by Western standards, but they are consistent with Chinese drinking culture. Taylor et al.’s four-country study  found a The 18- to 34-year-olds with vocational/professional (non-university) education, as a group, had the fewest abstainers compared to those who had university degrees or those who had secondary or less education. Wu and colleagues ,3. PreviWe found that professionals and technicians were more likely to be drinkers than associate professionals and service workers. This is consistent with results reported by Li and colleagues  who suggThe present study indicated that married respondents and respondents who had a child were more likely to be abstainers. This finding contrasts with findings reported in earlier Chinese literature which reported that being married was associated with higher drinking rates ,3,4. MarIn addition to the demographic differences among the four drinking frequency-quantity groups, drinking experience seemed to influence drinking attitudes and motives. The present study consistently found that drinkers were more likely to agree that drinking is one of life’s pleasures and that drinking with someone is a way of showing friendship. Drinkers were more likely than abstainers to approve alcohol use in all four situations studied—where young children are present, in adult private context, in social drinking for men, and in social drinking for women. Frequent drinkers (HiF-LoQ and HiF-HiQ), in particular, had even stronger positive feelings about alcohol use than non-frequent drinkers (LoF-LoQ and LoF-HiQ). Positive attitudes were associated with both increased frequency of drinking and higher acceptance of others’ drinking. Other researchers have drawn this same conclusion. Wang and colleagues  reportedThe present study indicated that social motives were more important than psychological motives for drinking. Studies in China consistently reported that needs of social communication, celebrations, and coping were commonly-given reasons for drinking among college students ,8,9. TheIn this study, the high-frequency drinkers (HiF-LoQ and HiF-HiQ) were more likely to report coping with negative emotions was an effect of their drinking alcohol compared to low-frequency drinkers (LoF-LoQ and LoF-HiQ). The combination of social obligations to drink and expecting positive outcomes like mood enhancement reinforces drinkers and may lead them to drink more frequently and in higher quantities.Drinkers who participated in this survey reported the majority of their drinking was at restaurants for dinner, at a friends’ homes with friends, and at home with friends—environments that include other people. Social reasons appeared to be the main reason for drinking for all four drinking behavior groups. These findings confirm that in China drinking plays an important role in socializing, and that celebrations and festivities are typically accompanied with alcohol. Much drinking behavior research in the West is based on models and theories of behavior change that assume individualized decision-making about drinking based on experiences and outcome expectations. Clearly this is not the only way to view and understand alcohol use. Meier, Warde and Holmes  recognizThis study is limited to one city: Wuhan. How similar to other cities of the same size is unknown. The data are cross-sectional in nature, thus causal inferences are not suggested. The fact that 90% of the sample reported education beyond secondary school suggests this may be an atypical city. While this study explored a variety of dimensions of drinking it asked few questions about important drinking contexts such as the workplace. This analysis is based on self-reported alcohol use/nonuse, which could be unreliable. To improve reliability the data were gathered in face-to-face interviews to reduce misunderstandings. Also, in China, there is less cultural stigma and fewer legal prohibitions on alcohol use, compared to western countries, so there was less reason for participants to underreport alcohol use. The questions on the scales used were unique to this study so comparisons are not possible. While the sample size was large, it was not large enough to explore in detail the role of the possible covariates or additional factors because the cell sizes became too small, leading to a loss of statistical power and making interpretations tenuous. Based on these results and results from other studies, future studies could be built around hypotheses of causal relationships allowing the exploration of confounding variables. Nevertheless this study did provide useful information about alcohol drinking and abstaining in the population of 18- to 34-year olds (not just students) and did use measures worthy of further refinement for future studies.Former drinkers were excluded in this study due to small sample size and lack of information about drinking history. Former drinkers are a special group who had experience in drinking but currently do not drink. They may have a more similar attitude toward drinking to current drinkers than to lifetime abstainers. It would be worthwhile to examine the similarities and differences between former drinkers and current drinkers and lifetime abstainers in future studies.These findings of this descriptive study confirm that in China drinking plays an important role in socializing, and that celebrations and festivities are typically accompanied with alcohol. Western models of individualized motivation of behaviors may not accurately explain alcohol use in China that emphasize collective values and relationships. The questions and methods used generated useful data and should be reviewed and possibly revised for use with other samples from communities from across China. Larger samples would accommodate more sophisticated analyses. This would generate a more representative picture of drinking patterns in this age group. The findings from the study, especially those that do not concur with previous findings, suggest the need for further study.


Mission: to urge all relevant entities within the international cardiac surgery, industry and government sectors to commit to develop and implement an effective strategy to address the scourge of rheumatic heart disease in the developing world through increased access to life-saving cardiac surgery. Twelve years after cardiologists and cardiac surgeons from all over the world issued the Drakensberg Declaration on the Control of Rheumatic Fever and Rheumatic Heart Disease in Africa, calling on the world community to address the prevention and treatment of rheumatic heart disease (RHD) through improving living conditions, to develop pilot programmes at selected sites for control of rheumatic fever and rheumatic heart disease, and to periodically review progress made and challenges that remain,2Prevention efforts have been important but have failed to eradicate the disease. At the present time, the only effective treatment for symptomatic RHD is open-heart surgery, yet that life-saving cardiac surgery is woefully absent in many endemic regions. In this declaration, we propose a framework structure to create a co-ordinated and transparent international alliance to address this inequality.Elimination of RHD and relief from its debilitating consequences can only occur through interdisciplinary effort, as outlined in the Cairo Accord.Progress in the prevention of RHD has been slow during the past 15 years,6Although there is one cardiac centre per 120 000 people in the United States, there is only one centre per 33 million in Africa. Furthermore, RHD is not restricted to sub-Saharan Africa. India, Pakistan, China and Indonesia together account for 72% of the mortality rate of RHD cases worldwide.2We strongly endorse the position that building local capacity is the best solution for this serious public health problem. Many lives have been saved by humanitarian ‘fly-in’ missions, but these efforts are neither sustainable nor cost effective. The non-governmental organisations associated with these programmes are shifting focus towards building long-term partnerships with host countries to develop autonomous local services with government buy-in.It is not sufficient for governments and non-governmental organisations to support the training of cardiologists and cardiac surgeons from these regions at high-income country facilities, because they will not be trained in most of the pathologies awaiting them in their own countries and will be unfamiliar with resource-constrained circumstances.There is an urgent need for a concerted effort by all stakeholders to address the plight of the poor in these regions, who need cardiac surgery. As signatories and endorsing organisations of the Cape Town Declaration, we propose a comprehensive solution with two principal aims.Aim 1: To establish an international working group  of individuals from cardiac surgery societies and representatives from industry, cardiology and government to evaluate and endorse the development of cardiac care in low- to middle-income countries.It is proposed that the international coalition will have two representatives from each of the major cardiac surgery societies , and ideally, two additional committed members. There will be at least one representative from industry and at least one appointee to represent cardiology/the World Heart Federation. The responsibilities of the coalition will include establishing criteria for centres for clinical care and training as well as selecting and endorsing the centres. The coalition will derive metrics of quality and performance for the endorsed centres of training and clinical care and will encourage standardisation of care to the extent possible.The coalition will advocate mutually agreed policies and prescriptions to relevant governmental bodies. In addition, the coalition will engage with industry and private sources of philanthropy for financial assistance with large-scale initiatives.Aim 2: To advocate for the training of cardiac surgeons and other key specialised caregivers at identified and endorsed centres in lowto middle-income countries.The case has been made above for critical providers obtaining training in settings and conditions and dealing with the cardiac pathologies that they will be encountering in their practice in their countries of origin.It is preferred that centres endorsed by this coalition be based on an alliance of four stakeholders: a programme initiator , an audited training centre in a low- to middle-income country, a committed partner institution in a high-income country, and a consortium of industry that would sign on as benefactors to the specific programme. Because regional centres in low- to middleincome countries typically operate within a resource-scarce environment, resulting in lower case numbers than needed for the training of outside residents, a facilitated capacity increase to help achieve higher case numbers would benefit all participants.Summary: It is imperative that action be taken urgently. A nucleus of one to three centres should be identified and endorsed, with co-ordination by global stakeholders, as quickly as possible. The implementation of this initiative will only be made possible by the endorsement of all the relevant cardiothoracic societies and agencies subscribing to clearly defined targets and timelines, and committing appropriate resources. The time to act is now.For Cardiothoracic Societies Joseph Bavaria Friedhelm Beyersdorf R Morton Bolman, III Kumud Dhital Robert SD Higgins James Kirklin Robert Kleinloog Bongani Mayosi Juan Mejia Jose Pomar Karen Sliwa Shinichi Takamoto Wei Wang David Wood Charles Yankah , Ghana/Germany]Liesl Zuhlke Humanitarian and government organisations Alain Carpentier Sylvain Chauvaud Afksendiyos Kalangos Richard Kamwi René Prêtre Nicole Sekarski Magdi Yacoub Industry and health economy representatives Iraj Abedian Francois Bonnici Lenias Hwenda Sidhant Jena Samukeliso Dube Jacques Kpodonu  Salah Malek Markus Stirner-Schilling Patrice Matchaba Lee Chuen Neng Michael P Phalen Tim Ring Kathryn Gleason Devi Prassad Shetty Alistair Simpson Raenette Taljaard Helmut Straubinger Barry Wilson For major journals and publications Friedhelm Beyersdorf Sampath Kumar Dan Ncayiyana JP van Niekerk G Alexander Patterson Marko Turina David Williams Other signatory delegates to the Cape Town Dialogue Elena Aikawa (USA)Masanori Aikawa (USA)Henning Rud Andersen (Denmark)Manuel Antunes Eduardo Becerra (Chile)Solomon Benatar (South Africa/Canada)Richard Bianco (USA)Bojan Biocina (Croatia)Carlijn Bouten (Netherlands)Abdelmalek Bouzid (Algeria)Luke Brewster (USA)Johan Brink (South Africa)Taweesak Chotivatanapong (Thailand)Patrick Commerford (South Africa)David Cooper (USA)John Curci (USA)Manfred Deutsch (Austria)Richard Daly (USA)Frederick C de Beer (USA)Norberto de Vega (Spain)Howard Eisen (USA)Max Emmert (Switzerland)Giuseppe Faggian Volkmar Falk (Germany)Ted Feldman (USA)Giovanni Ferrari (USA)Teddy Fischlein (Germany)Robert Frater (USA)Glen Gaudette (USA)Gino Gerosa Bernard Gersh (USA)Allan Glanville Craig Goergen (USA)Claudia Goettsch (Germany)Mervyn Gotsman (Israel)Martin Grabenwoeger (Austria)Andrea Griesmacher (Austria)Christian Hagl (Germany)Ulf Hedin (Sweden)Simon Hoerstrup (Switzerland)Saeid Hosseini (Iran)Joshua Hutcheson (USA)Willie Koen (South Africa)Gennadiy Khubulava (Russia)Robin Kleinloog (South Africa)Walter Klepetko (Austria)Michael Knaut (Germany)Theodoros Kofidis (Singapore)Guenther Laufer (Austria)Nicolas l’Heureux (France)Georg Lutter (Germany)Simon Maltais (USA)Simon Matskeplishvili (Russia)Jo Meinhart (Austria)Ana Olga Mocumbi (Mozambique)Elmi Muller (South Africa)Mathias Mueller (Austria)Paul Mohacsi (Switzerland)Ivan Netuka (Czech Republic)Mpiko Ntsekhe (South Africa)Minoru Ono (Japan)Otmar Pachinger (Austria)Timothy Pennel (South Africa)Olga Plattner (Austria)Bruno Podesser (Austria)Darshan Reddy (South Africa)Bruno Reichart (Germany)Hermann Reichenspurner (Germany)Hector Sanchez (Argentina)Jacques Scherman (South Africa)Stephan Schueller (United Kingdom)Jim Schurman (USA)Rainald Seitelberger (Austria)Toshi Shinoka (USA)Agneta Simionescu (USA)Dan Simionescu (USA)Francis Smit (South Africa)Ulrich Steinseifer (Germany)Cynthia St Hilaire (USA)Justiaan Swanevelder (South Africa)Hendrik Treede (Germany)Nir Uriel (USA)Devagourou Velayodamu (India)David Vorp (USA)Susan Vosloo (South Africa)Beath Walpoth (Switzerland)Georg Wieselthaler (USA)Mike Wolf (USA)Andreas Zuckermann (Austria)


Purpose: To correlate computed tomographic (CT) appearance of the thymus with results from histologic examination of thymic tissue in myasthenic patients who underwent thymectomy.Materials and methods: A retrospective study, based on case series report, between January 2000 and December 2010 on 247 patients with generalized myasthenia gravis or myasthenic syndrome explored by CT using a specific protocol, in the Radiology and Medical Imaging Department of Fundeni Clinical Institute. All subjects in the study were operated and had a histologic evaluation.Results: CT examinations of these 247 subjects showed remaining thymic mass, remnant of thymic tissue, fatty infiltration of the thymus and tumoral thymus or focal thymic mass. The results of histologic examination showed normal thymus, thymic lymphoid follicular hyperplasia, thymic atrophy, fatty infiltration and thymoma.Conclusion: It was a 100% correlation between CT examinations and intra-operative findings regarding the presents of focal thymic masses in our study. In the diagnostic of focal thymic mass, the only inter-disciplinary correlation is between radiological and macroscopic aspects. CT examination has a limited value in differential diagnosis between thymic lymphoid follicular hyperplasia and thymoma. The thymus is a heterogeneous admixture of lymphoid and epithelial elements located in the superior and anterior portions of the mediastinum. It is an integral part of the immune system.Its shape is partially determined by adjacent structures. Posteriorly, it molds itself against the trachea, the left brachiocephalic vein, the aortic arch and its branches, and the pericardium covering the ascending aorta and the pulmonary trunk. Anteriorly, the sternum and the antero-medial margins of the lungs cover it. It is a bilobed structure, with the left lobe usually extending further inferiorly than the right. The two lobes usually make contact superiorly near the midline and then diverge inferiorly. Each lobe is enclosed in its own thin fibrous capsule; delicate septa divide the thymic lobes into irregular lobules in the younger subjects .The width decreases in older patients, but a large variation exists within each age group. The thymus becomes narrower with increasing age, a wide variation of the thickness exist in different age groups [The density of normal thymus in adults. The mean attenuation value of the thymus was obtained and compared with that of the chest wall muscles. The CT attenuation values decrease with aging. In patients under 25 years of age, the thymus is isodense or with a higher density than the chest wall musculature; between 25 and 49 years the thymus appears with a lower density than that of associated soft tissues because of progressive fatty infiltration; patients over 50 years of age had a thymic density approaching to the fat , diffuse enlargement of the thymus and thymic focal mass.Although CT is useful in differentiating non-invasive from invasive thymomas, it has a limited value in differentiating thymomas from lymphoid follicular hyperplasia. Sometimes, CT may suggest the histologic nature of a thymic lesion.