A temporal relationship between events of potential cause and effect is critical to generate a causal relationship because the cause has to be followed by the effect. The present study investigated the role of temporal relationships between events in causal inference in rats via Pavlovian pairings. In Experiment 1A, subjects in Group Successive received training trials whereby Event 1 (tone or light) was followed by Events 2 (light or tone) and 3 (sucrose solution), whereas those in Group Simultaneous received simultaneous pairings of Events 1 and 2, and Events 1 and 3. During testing, a lever was inserted into the experimental chamber, where subjects were allowed to press the lever which produced the occurrence of Event 2 without reward. By measuring nose-poke responses during the presentation of Event 2, assumingly based on the prediction of occurrence of sucrose solution, subjects in Group Successive showed a relatively lower response rate than did those in Group Simultaneous. In Experiment 1B, this difference was not observed if subjects received the presentations of Event 2 which was irrelevant to their lever pressing during testing. These results suggest that rats can differentiate their response based on the elemental temporal information even when the integrated temporal map was the same, and implied that rats use temporal information as well as conditional probability based on causal Bayesian network account. The issue of causality has been an important and interesting one in philosophy and psychology. The ability to infer causality, in particular, enables organisms to survive in the natural environment by allowing them, for instance, to not only predict the future based on the current status of their surroundings but also to select appropriate behaviors in order to change the environment for specific purposes. In Pavlovian conditioning, whereby subjects receive pairings of conditioned stimuli (CS) and unconditioned stimuli (US) to evoke conditioned responses (CR), organisms are also permitted to predict a future event based on associative knowledge. Despite this superficial similarity between associative and causal knowledge, fundamental differences arise between the two in specific situations.One of the occasions in which this occurs is when external manipulation intervenes in the causal structure. For example, although we cannot directly observe changes in atmospheric pressure, we can observe changes in scale as measured by a barometer and are able to then predict climate change based on this information. This kind of inference may be derived from associative knowledge between events, but if you artificially manipulated/performed some trick on the barometer to produce a change, you will not be able to predict climate change. Simple associative accounts cannot discriminate between observations of actual barometric change and observations of change based on artificial intervention. A Bayesian network or “graph surgery” would allow us to differentiate between the two, as a causal relationship between atmospheric pressure and barometric change would be removed via an artificial intervention/manipulation performed upon the barometer. These results implied that rats could derive causal information between events from pairing episodes traditionally used in associative learning paradigms. However, numerous studies have shown that rats may acquire associative knowledge based on the Pavlovian pairing of events. Thus, the argument as to whether rats acquire associative or causal knowledge, or how they employ different strategies, associative or causal, to respond in each situation, still seems to be open to debate. One key difference between associative and causal knowledge is that of temporal directionality, in which the cause has to be followed by the effect. Temporal information among events has to be encoded for causal inference, especially for Bayesian network ensembles, as these require directed acyclic graph structures among events.Temporal coding hypothesis proposed by Figures 1A,B illustrates the graph structure and temporal diagram of a common causal model examined by present study and also by The left panel of Figures 1A,B depicts the graph structure and temporal diagram of a critical procedure we performed in this experiment. During training, subjects received simultaneous pairings of Events 1 and 2, and Events 2 and 3. An integrated temporal map based on temporal coding hypothesis claims that exactly the same results will be observed as for the procedure illustrated in the left panel of Figures 1A,B. On the contrary, a Bayesian network approach proposes differing outcomes: subjects cannot generate causality because the temporal rule of cause and effect is broken. First aim of this research was to explore the role of elemental temporal information for causal inference in rats.How, then, could subjects generate causal relationships between events and differentiate between the results of associative and causal inference? As we described earlier, a critical feature of causality is the presence of a temporal relationship between cause and effect. Training procedures in which Event 1 precedes Events 2 and 3 are key to generating causality. The present study therefore aims to investigate this point by manipulating temporal properties during training. The right panel of In all honesty, the faculty of generating causal relationships in animals, especially in rodents such as rats, needs clarifying. In Experiment 1A, we examined the role of temporal relationship among events on causal reasoning. Rats in Group Successive received successive parings of Event 1 and 2 (tone or flashing light), and Event 1 and 3 (sucrose solution) in training as used in The subjects were 24 experimentally naïve male Wister rats  that were 63 days of age at the beginning of the experimental procedure obtained from CLEA Japan. Throughout the experiment, subjects were housed in plastic cages  with floors covered in paper chips and a stainless-steel grid roof. The cages in which they were housed were kept in the colony room, which was illuminated to a range between 9:00 and 21:00. The room temperature was maintained at 24∘C. Following a week’s acclimation to their home cages, with free access to food and water, all subjects were put on a food deprivation schedule whereby their body weights were maintained at 85% of their free feeding weight.All experimental procedures were conducted in an operant chamber  housed in a sound-and light attenuating isolation box (Med Associates). The walls and ceiling of the experimental chamber were constructed of clear Plexiglas, while its floor consisted of stainless-steel rods. All experimental procedures were conducted with the house light on except for the period of presenting flashing light. The operant chamber was equipped with a dipper for delivering a 20% sucrose solution located at the drinking niche. Speaker for a high-frequency tone (3000 Hz) and a light bulb were also located on the outside walls of the chamber. Levers could be inserted into the cage 4 cm to the left of the food niche and 6 cm above the floor. This research was conducted following the relevant ethics guidelines for research with animals, and was approved by the Institutional Animal Care and Use Committee (IACUC) of Senshu University’s Department of Psychology.Table 1. On Day 1, all subjects were acclimated to the operant chamber in a 60-min session, during which they were trained to access and drink the sucrose solution from the dipper. The sucrose solution was delivered according to a discrete uniform distribution (ranging from 5 to 35 s) and the dipper cup was raised for 10 s.The experimental design is summarized in Subjects were divided into two equal-sized groups, Group Successive and Group Simultaneous, and received pairing training from Days 2 to 5. Subjects in Group Successive received six trials a day in which Event 1 was followed by Event 2. On the other hand, subjects in Group Simultaneous received six simultaneous pairings of Events 1 and 2 on each day. Events 1 and 2 were the presentation of a tone or flashing light, and the assignment of stimuli was counterbalanced across subjects. Trials occurred with a mean interval of 5 min in daily 60-min sessions. The duration of each event was 10 s.On Days 6 and 7, first-order conditioning was conducted. In trials involving subjects in Group Successive Event 1 was followed by Event 3 (sucrose solution), whereas those in Group Simultaneous received simultaneous presentations of Events 1 and 3. Daily sessions lasting 60 min were held, in which 12 trials with a 5-min mean inter-trial interval (ITI) were performed.Levers were inserted into the experimental chambers on Day 8 for testing. All subjects were presented with Event 2 immediately after pressing the lever in 30-min sessions. Nose-poke responses were recorded as an index of subjects’ predictions of sucrose solution.Since it showed no lever press responses during testing, one subject in Group Simultaneous was removed from subsequent data analysis except for the analysis on the frequency of lever presses.Figure 2 illustrates the mean nose-poke responses during Event 1 in Group Successive and those during Events 1 and 3 in Group Simultaneous in Phase 2. Visual impressions clearly indicated that Group Simultaneous showed stronger responses than Group Successive although subjects in the latter demonstrated a typical learning curve. A two-factor (groups × blocks) analysis of variance revealed the main effects of groups  and the marginal main effect of blocks . Interaction was not significant . Because Event 3 (sucrose solution) was presented with Event 1 in Group Simultaneous, group differences seen in ANOVA were due to the summation effect of unconditioned approach responses to the food niche derived by the sound of a hopper and CR. In order to check whether subjects in Group Successive acquired enough magnitude of nose-poke responding, A Student’s t-test was conducted between groups in the last block of Phase 2, which yielded no significant difference, t(22) = 1.46.t-test yielded a significant difference between the numbers of lever presses, t(22) = 2.22, p < 0.05, suggesting that rats in Group Successive pressed the lever significantly more frequently.The mean number of lever presses during testing sessions was 6.83 (SD: 7.00) in Group Simultaneous and 14.08 (SD: 8.24) in Group Successive. A Student’s Figure 3 shows the mean frequency of nose-pokes during Event 2 across the first three presentations of stimuli in testing in Groups Simultaneous and Successive. There were two reasons why we adopted the first three trials for analysis. The first was response validity; because non-reinforcing probe trials were administered during testing, conditioned nose-poke responses were extinguished across trials. The second was statistical validity; the numbers of subjects that pressed the lever more than three times (five in the Group Simultaneous and 10 in the Group Successive) were not enough for statistical validation. The results of the Student’s t-test on mean nose-poke responses revealed a significant difference between the average nose-poke responses of both groups , which suggested that subjects in Group Simultaneous predicted the occurrence of Event 3, the delivery of sucrose solution, with a higher rate than those in Group Successive. In order to explore the effect of the number of lever presses, correlation analysis between nose-poke responses in first three trials and total numbers of lever presses was conducted. Pearson’s correlation was -0.11 (p = 0.75) in Group Simultaneous and 0.51 (p = 0.09) in Group Successive. The results of the correlation analysis implied that the number of lever presses had no direct impact on the rate of nose-poke responses.Although statistical analysis yielded the difference between Groups Simultaneous and Successive, it is difficult to conclude this difference was due to the situation where voluntary lever pressing was followed by Event 2. Groups Sim-Control and Suc-Control were set for rule out this confounding. Groups Sim-Control and Suc-Control received the same training procedure with Groups Simultaneous and Successive in Experiment 1A, respectively, and then received different procedure in testing with those. In testing, all subjects in Experiment 1B were presented with the lever, but the timings of presentation of Event 2 depended on the timing of lever pressing seen in Experiment 1A (yoked procedure across experiments). If only the training history was crucial and voluntary lever pressing was irrelevant to the observed difference in nose-poke responding in Experiment 1A, subjects in Group Sim-Control should show more nose-pokes than those in Group Suc-Control.Sixteen experimentally naïve male Wister rats were served as subjects obtained from CLEA Japan, that were 63 days of age at the beginning of experiment . Situation of housing and apparatus used in experimental procedure were identical with Experiment 1A. This research was conducted following the relevant ethics guidelines for research with animals, and was approved by the IACUC of Senshu University’s Department of Psychology.Subjects were divided into two equal-sized groups, Group Sim-Control and Group Suc-Control. Subjects in Group Sim-Control and Group Suc-Control were received identical procedure from Day 1 to Day 7 with those in Group Simultaneous and Group Successive in Experiment 1A, respectively. In testing, Day 8, subjects in Group Sim-Control and Suc-Control were allowed to press the lever without any consequences. Instead, subjects in those two groups received three trials of presentation of Event 2 with the timing of first three pressing the lever by subjects in Group Simultaneous and Successive in Experiment 1A. Eight subjects each were randomly selected from Group Simultaneous and Successive and the recorded timing of lever pressing in testing session were used as the timing of presentation of Event 2 in Groups Sim-Control and Suc-Control.t-test revealed no significant difference between groups [t(14) = 0.20]. This result suggested that observing Event 2 was not sufficient to differentiate the nose-poke responding and that voluntary lever press played important role for the difference between Groups Simultaneous and Successive.Mean frequency of nose-pokes in last two trials in Phase 2 in Group Sim-Control and Suc-Control were 33.3 (SE: 8.76) and 25.2 (SE: 5.78) respectively, which were almost same strength with the result in Experiment 1A. Mean frequency of nose-pokes during Event 2 across the first three presentations of stimuli in testing in Groups Sim-Control and Suc-Control were 2.42 (SE: 0.93) and 2.71 (SE: 1.10). Student’s The present study aimed to explore the effects of temporal information between events on causal reasoning. We found that a successive relationship could serve as a cue for causality, whereas a simultaneous relationship could not. The results obtained suggested that rats might use temporal relationships between events for reasoning in a different way than previously hypothesized.According to traditional accounts of associative learning, a bidirectional associative link is formed and activation of representation spreads via associative links to evoke responses based on the properties of a stimulus representation. However, temporal coding hypothesis has introduced a different assumption: subjects will respond based on predictive relationships among events acquired through the integration of elemental temporal maps. If this were the case, the rats in all groups in the present experiment would have shown similar performances, as the temporal relationship between Events 2 and 3 was the same across the groups based on the integrated temporal map. Because procedural differences between Groups Simultaneous and Successive were the temporal relationships between Events 1 and 2 and Events 1 and 3, the role of Event 1 as mediator seems to be crucial in the results of the present study. Although previous research supports the ability of rats to integrate elemental temporal maps in generating predictive responses e.g., , the preAnother important implication was that elemental temporal information could differentiate rats’ predictive responses to the event following lever presses. According to previous research and Bayesian net accounts e.g., , even raIn Experiment 1B, both of Groups Sim-Control and Suc-Control showed the same response tendency of nose-poking. This suggested that the voluntary lever pressing yielding Event 2 played critical role for different responding during testing seen in Experiment 1A. However, one potential problem is that these groups showed relatively weak response in testing. In previous research e.g., , one impAnother aim of present research was to explore the possibility of response competition account proposed by Kosuke Sawa developed the design of experiment, analyzed the data and wrote first draft. Akira Kurihara conducted the experiment. Both author contributed equally for later version of paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We wanted to analyze the factors affecting the results of multiple cannulated screws fixation in patients less than 60 years old with femoral neck fracture (FNF).We reviewed 52 patients  who were treated with multiple cannulated screws fixation for FNFs. They were followed up for more than one year during January 2002 to December 2012. They were classified by Garden’s classification. The anatomic reduction was evaluated by Garden’s alignment index on hip both anteroposterior and lateral images. Postoperative complications were analyzed during follow up periods.By Garden’s classification, 6 cases were in stage I, 13 cases in stage II, 30 cases in stage III and 3 cases in stage IV. During follow up periods, avascular necrosis of the femoral head was observed in 12 cases (23%) and nonunion was observed in 5 cases (9%). The 16 patients who had complications underwent total hip arthroplasty (31%). In non-displaced fracture groups  did not have AVN nor nonunion. The incidence of complications in displaced fracture group was 51.5%. The complicated cases showed tendency for increased apex anterior angulation of femoral neck on hip lateral images and the result was statistically significant. (p=0.0260).The patients less than 60 years old who were treated with multiple cannulated screws fixation for displaced FNFs showed the incidence of complications was more than 50%. It needs a cautious approach for anatomical reduction, especially related to anterior angulation on hip lateral image. Femoral neck fracture (FNF) is likely to develop into conditions that require hip joint replacement even after appropriate treatment due to complications, such as avascular necrosis of the femoral head (AVN) and nonunion.5Although joint replacement is presented as a good solution for elderly FNF patients as it facilitates early rehabilitation and reduces the risk of reoperation,The present study was conducted with 52 patients  who could be followed up for at least one year, who were diagnosed with a FNF, and who underwent multiple cannulated screw fixation at our institute between January 2002 and December 2012. The mean age of the subjects at the time of operation was 44.3 years (24–60 years) and the mean follow-up period was 23 months (13–43 months). FNFs were divided into types I, II, III, and IV using the Garden classification.9As regards surgical methods, cannulated screws were fixed in all cases and open reduction was not performed in any of the cases. After putting the patient under general anesthesia or spinal anesthesia and laying the patient in a supine position on the fracture table, reduction was performed under C-arm imaging. When the appropriate reduction had been obtained, a point between the greater trochanter and the lesser trochanter was marked on the skin on the lateral side of the femoral region. The region was incised to insert three or four 7.0-mm cannulated screws , ensuring the threads of the screws completely passed the fracture region to fix the region with compression. A crutch gait and partial weight bearing were allowed at 3–4 weeks after the operation and full weight bearing was allowed at 8–10 weeks after the operation.The angle between medial trabecular stream in femoral head and medial cortex of femoral shaft (trabecular-shaft angle) was measured from postoperative hip anteroposterior radiograph and the anteroposterior angulation was measured from lateral image. Classifying the FNF type and measuring the angles were performed by two orthopaedic surgeons reaching a consensus. In patients where there was no gap in the fracture line and where the bony trabeculae were connected to each other across the fracture region in plain radiographs were judged as bone union. Nonunion was defined by the absence of any fracture healing after a period of 6 months.11P-value of ≤0.05 was considered significant.SPSS 7.0 was used as a statistical program and the Mann–Whitney U-test was used to judge significance. A The subjects comprised 6 type Is, 13 type IIs, 30 type IIIs, and 3 type IVs under the Garden classification method. AVN occurred in 12 cases, and nonunion occurred in 5 cases. Total hip joint replacement was performed due to complications in 16 patients or 31% of the study subjects . When thThe time taken after being injured until operation did not exceed 24 hours in all cases, and there was no difference in operation delay time between patients with complications and those without complications.P=0.026). However, under anteroposterior radiograph, Trabecular-shaft Angle were shown to have no differences between patients with complications and those without complications (P=0.357; Whether or not to perform reduction during operation was determined using the Garden alignment index.P=0.357; .Anatomic reduction and internal fixation with an emphasis on preservation of the blood supply to the femoral head is the treatment of choice for younger patients.5ParkerVascularity is important, and it affects the survival of the femoral head. If the bone fragment is rotated during reduction or insertion of the fixatives, blood vessels will be blocked, leading to AVN, which is one of the most common complications of FNFs, the frequency of occurrence of which has been reported as 15-40%.Researchers reported that the accuracy of reduction affects prognoses.9It is a simple X-ray based study, so we could not evaluate the FNF three-dimensionally. Zhou et alWhen multiple-cannulated screw fixation was performed in FNF patients younger than 60 years, complications occurred in at least 50% of patients with Garden III, IV-type fractures, which are displaced fractures. In addition, the state of reduction immediately after operation was judged an important prognostic factor. Therefore, when treating displaced FNFs, the range of reduction should be strictly applied to avoid anterior angulation of the femoral neck during operations, and efforts should be made to obtain accurate anatomical reduction.


Results showed that a single exposure to visible light induced very little pigmentation whereas multiple exposures with visible light resulted in darker and sustained pigmentation. These findings have potential implications on the management of photo-aggravated pigmentary disorders, the proper use of sunscreens, and the treatment of depigmented lesions.Visible light (400–700 nm) lies outside of the spectral range of what photobiologists define as deleterious radiation and as a result few studies have studied the effects of visible light range of wavelengths on skin. This oversight is important considering that during outdoors activities skin is exposed to the full solar spectrum, including visible light, and to multiple exposures at different times and doses. Although the contribution of the UV component of sunlight to skin damage has been established, few studies have examined the effects of non-UV solar radiation on skin physiology in terms of inflammation, and limited information is available regarding the role of visible light on pigmentation. The purpose of this study was to determine the effect of visible light on the pro-pigmentation pathways and melanin formation in skin. Exposure to visible light in  Visible light (VL) is characterized by wavelengths ranging from 400 to 700 nm, although in some documents of the European Commission it has been defined to cover the range of 380–780 nm CIE . In thisSkin plays a role as biological active barrier to the external environment including sun exposure and the presence of cutaneous hyptothalamic-pituitary-adrenal axis (HPA) makes it an important peripheral neuroendocrine organ . The skiex-vivo and clinical studies were performed to understand the induction of pigmentation in skin with VL. In the first series we explored the induction of pigment in human skin explants extracted from abdominal skin in response to multiple exposures with VL. Melanin deposition as a result to exposure with VL was more evident at later time points. Further investigation of melanogenesis pathway in ex-vivo showed de-novo formation of melanin. In the second series we were able to reproduce the results obtained from explants study and we demonstrated clinically perceptible pigmentation after multiple exposures with VL. A single exposure to VL might prove ineffective in producing persistent pigment; therefore a pre-exposure of Caucasian skin to what might be termed, as “conditioning” dose has proved quite effective in augmenting the pigment resulting in clinically perceptible pigmentation.In this paper a series of -2 of VL demonstrated an increased darkening as a function of exposures. VL exposed explants at 7 days documented increased melanin content as compared to sham treated samples (Skin explants exposed to 150 J.cm samples .p < 0.05) was observed on day 7 for the exposed samples compared to baseline, whereas there was no significant changes for the sham treatments. The changes of absorption in the whole visible spectral range between baseline and day 7 is presented in in vivo measurements [The amount of pigment induced by VL exposure on skin explants was also assessed by diffuse reflectance spectroscopy (DRS). DRS absorption levels obtained at wavelengths from 620–700 nm is shown in urements .The explants were analyzed for gene assays at day 3 and day 7 after exposure with sham and VL treatments respectively. The respective explants were analyzed for Tyrosinase gene expression by QPCR. A significant increase in Tyrosinase gene expression by almost 3 fold was registered on day 7 as compared with the sham exposure ; howeverTyrosinase activity, as the dopa oxidase here, was measured by the rate of L-DOPA oxidation as reported . Tyrosin-2, data not shown). Of note, the single exposure study was conducted during beginning of December in the Northeastern United States, and thus occurred when subjects are not routinely exposed to the sun. A subsequent study was designed to determine whether multiple exposures to VL could induce persistent pigmentation and was based on the hypothesis that a “conditioning” dose of VL might affect the amount of pigment produced in skin.A pilot study involving individuals of Fitzpatrick skin type V-VI exposed to a single exposure of VL was conducted and the results, showed a transient pigment but no persistent pigmentation (subjects irradiated with 320 J.cm-2)  . By 24 hadiation  dose. Suadiation  to increadiation . Similar-2) as well as after the subsequent 150 J.cm-2 doses for different skin types  would be equivalent to approximately 50 minutes in the sun light . The data presented in this paper suggested one exposure with VL can produce transient pigmentation in Caucasian Skin but clinically persistent pigmentation is more evident with multiple exposures both under in vivo and ex-vivo conditions. Pre-exposure of skin which is termed as skin conditioning is required to induce pigmentation.VL comprises about 44% of solar radiation and is the only portion of the solar spectrum visible to the human eye. If we consider that the solar irradiance in the visible range is about 50 mW.cmSkin plays a vital role as a physical barrier against external influences as well as act as a neuroendocrine organ, which helps to regulate global homeostasis. Skin cells produce hormones, neurotransmitters and neuropeptides and corresponding functional receptors in response to stressors including UV . As a rein vivo and ex-vivo. The mechanism of action for the production of immediate pigmentation following exposure with VL is believed to be photo-chemical in nature; however, the mechanism of action for VL induced delayed pigmentation may be a result of neo-melanogenesis.In the present study, we have shown the induction of pigmentation with VL both -2 of VL daily for 5 days showed increased and perceptible pigmentation at day 7. Quantification of melanin both from VL exposed and sham treated explants extracted at day 7 showed increased melanin in VL exposed explants as compared to sham treated explants  Kollias N. et al  and OuyaIncrease in melanin as a result to exposure to VL in skin can be suggested as response to stress induced by the respective light source. Skin has been recently categorized as an endocrine organ with its own HPA axis that gets activated by stress response . In addiex-vivo studies and demonstrate that VL is able to induce pigmentation after multiple exposures, which suggests that preconditioning is required to activate the melanogenesis process. The findings also align very well with the findings from Mahmud et al., since both studies demonstrate that VL cannot produce persistent pigmentation with just one VL exposure, especially in subjects with Caucasian skin.In this manuscript the effect of multiple exposure of skin to VL were explored for pro-pigmentation activity. Interestingly multiple exposure with VL was able to induce pigmentation in explants extracted from Caucasian skin. Further exploration at biological endpoints suggested that besides pigment formation due to photo-oxidation activities, VL was able to activate the whole melanogenesis process. The clinical result of the current study confirm the Taken together these results demonstrate that in addition to UV, VL can have significant impact on producing uneven pigmentation in skin which is a main factor in photoaging. Furthermore this is the first report that preconditioning of the skin with VL, followed by multiple exposures to VL, can result in pigment formation. Thus photoexposure and photodamage should not be considered strictly as a result of UV exposure since the skin is exposed to whole spectra of wavelengths including VL, and VL can induce photodamage pathways in a manner similar to UV.Unless otherwise specified, all chemicals were purchased from Sigma-Aldrich .2 atmosphere at 32°C, explants were transferred to 37°C for the rest of the culture duration. Human skin explants were exposed to visible light 150 J.cm-2  along with one set of sham treatments which were kept outside for the same time as visible light exposures but without any exposure to any light. One set of explants was harvested at day 3 and another set was harvested at day 7 both from visible light and sham treatments for gene expression analysis, enzyme activity assays and quantification of melanin content.Human abdominal skin samples (otherwise to be discarded) were obtained following informed consent from healthy Caucasian females with age ranging from 38 to 59yrs undergoing abdominal plastic surgery . Patient identities were not disclosed to preserve confidentiality, in compliance with US HIPAA regulations. Punch biopsies (8 mm) were cultured in a 1:1 mixture of DMEM and F12 nutrient mixture (F-12)  supplemented with 2% FBS  and a cocktail of growth factors according to. Rossetti D et al.. After aThe clinical study was conducted in accordance to the Declaration of Helsinki principles. The clinical protocol was approved by the Allendale Institutional Review Board , and written informed consent was obtained from all subjects prior to enrollment. The enrolled subjects were in general good health and prescreened on the basis of Fitzpatrick skin type prior to enrollment.-2 when filtered with three near infrared absorbing glass filters  to attenuate IR radiation above 700 nm; and one glass filter to block wavelengths shorter than 400 nm . The output of the light source was delivered with a glass optical fiber (10 mm diameter for the skin explants and 8 mm for the in vivo studies) and the fluence rate was measured with a calibrated Newport Multi Function Optical Meter Model 1835-C  with a VL sensor model 818-C. The visible light source used in this paper has exactly the same spectral irradiance as the one published in the Mahmoud’s paper [-2 of visible light used in the study for this work, the cumulative UVA dose of 0.6 Jcm-2, what would not be enough to induce a PPD in the tested subjects.The explants and subjects were irradiated with a modified Fiber-Lite Model 180 Illuminator . This light source consists of a 150 Watt Quartz halogen lamp that is capable of producing fluence rates in excess of 300 mW.cmin vivo and ex-vivo studies. The system consisted of a light source , a bifurcated optical fiber probe  and a spectrometer . The amount of pigment produced by the exposure was calculated by the area under the absorption spectrum at 620–720 nm, in which absorption change due to blood is relatively minimal. Measurements were performed four times per site for every time points.DRS is a non-invasive assessing tool to determine changes of chromophores in skin , 43 and The expression level of Tyrosinase mRNA was quantified by QPCR. GAPDH was used as a house keeping gene and the relative abundance of mRNA obtained for both genes from respective samples was normalized to the GAPDH. The respective primers were purchased from Sabiosciences. Briefly RNA was extracted by using Trizol (Invitrogen). RNA concentration and purity was determined by measuring the absorbance using a NanoDrop . Followed by reverse transcription using the Applied Biosystems RT-PCR kit and qPCR was performed using SYBR green on 7500 Realtime PCR system . Primers for respective gene expression assays were purchased from SA Biosciences.g. The liquid phase was stored at −80°C, which was later on used for measuring protein concentration and assessing tyrosinase enzyme acitivty. Pellets consisting of cell debris and black pigment were washed twice with PBS and were centrifuged again at 1200 g. The pellet was dissolved in 1 M NaOH to dissolve the pigment at 60°C and solubilized melanin was measured at 405nm.Skim samples (1 g) were homogenized by sonication in 4 ml of RIPA buffer until the tissue was converted to liquid, then centrifuged at 1200 Tyrosinase activity, as the dopa oxidase here, was assessed by determining the catalysis of L-DOPA to dopachrome, which has an absorption peak at 475 nm. The assay was performed in a total volume of 150 μl, including 50 μl of sample  and 100 μl of freshly prepared L-dopa solution (0.1% in PBS pH 6.8). The protein concentration of the enzyme was determined using BCA assay reagent. The assays were set up on ice in triplicate in 96-well round-bottom microtiter plates and were incubated for 4h at 37°C. The absorbance at 475 nm was measured with microplate reader  to monitor the production of dopachrome, corrected for auto-oxidation of L-DOPA.To assess the role of VL on skin, we performed multiple VL irradiation in a group of 14 subjects . For in vivo studies dorsal forearm was used for exposure as it was suitable for experimentation purpose and the instruments could be easily used for the arms. Prior to irradiation subjects were allowed to rest for 15 minutes to acclimatize to the room temperature. The subjects were irradiated using the same light source used in the skin explants experiments.-2 with a fluence rate set at 150 mW.cm-2 in the dorsal forearm area. Digital photography and DRS measurements were performed on the irradiated site and an adjacently located un-exposed site used as control. The following day (day 2), prior to a second exposure, the previously treated area was imaged and DRS measurements were performed. A second exposure of 150 J.cm-2  was delivered at the very same site with the same fluence rate. After irradiation the exposed site was imaged and the DRS reading taken from the exposed and control un-exposed site. On day 3 the same procedure as on day 2 was repeated. In vivo skin images were obtained with a Nikon D50 digital camera with a 60 mm Nikon lens coupled with a Canfield Twin Flash and close up set up . Cross polarized images and DRS were taken immediately after irradiation and at different time points.Subjects at the day 1 were irradiated with an initial dose of 300 J.cmAll exvivo data are presented as mean±SD. For exvivo data were analyzed using a Student’s t-test with significance set at p > 0.05. For in vivo study, data are expressed as the mean ± SD. Statistical significance was determined with unpaired two-tailed Student's t-test using the Minitab 15 software .S1 FigThe wavelength at 330, 350, 370 and 390 nm and the wavelength on the visible range 436 nm, 525 nm and 600 nm are estimated from the clinical trials.(TIF)Click here for additional data file.


Callorhinus ursinus) with tri-axial accelerometers and magnetometers on two eastern Bering Sea islands (Bogoslof and St. Paul) with contrasting population trajectories. Using depth data, accelerometer data and spectral analysis we classified time spent diving (30%), resting (~7%), shaking and grooming their pelage (9%), swimming in the prone position (~10%) and two types of previously undocumented rolling behavior (29%), with the remaining time (~15%) unspecified. The reason for the extensive rolling behavior is not known. We ground-truthed the accelerometry signals for shaking and grooming and rolling behaviors—and identified the acceleration signal for porpoising—by filming tagged northern fur seals in captivity. Speeds from GPS interpolated data indicated that animals traveled fastest while in the prone position, suggesting that this behavior is indicative of destination-based swimming. Very little difference was found in the percentages of time spent in the categorical behaviors with respect to breeding islands (Bogoslof or St. Paul Island), forager type , and the region where the animals foraged . The lack of significant differences between islands, regions and forager type may indicate that behaviors summarized over a trip are somewhat hardwired even though foraging trip length and when and where animals dive are known to vary with island, forager type and region.We tagged 82 lactating northern fur seals ( Callorhinus ursinus), determining activity budgets could help to explain why the population trajectories of two eastern Bering Sea populations differ. The population of fur seals on St. Paul Island  has declined since 1998 at an annual rate of 5.5%, while the population on Bogoslof Island (southern Bering Sea) has increased at an annual rate of 11.7% since 1997 [Quantifying the time an animal spends in various activities such as locomotion, resting, and foraging can be used to estimate energy expenditure and understand life history strategies. In the case of northern fur seals . Our goals were to 1) differentiate between common fur seal behaviors, 2) create an at-sea activity budget, and 3) make ecologically relevant comparisons both within and between the two island populations of northern fur seals. We also validated our interpretation of some of the accelerometry data from fur seals in the field by filming instrumented female fur seals in captivity.All procedures were conducted under the National Oceanic and Atmospheric Administration permit no. 14329 and the protocol was approved by the Committee on Animal Care at the University of British Columbia (permit no. A09–0345).th to September 19th 2009, we tagged lactating northern fur seals on St. Paul Island (in the Pribilof archipelago) and on Bogoslof Island (a volcanic pinnacle south of the Pribilof Islands and just north of the Aleutian Islands chain) (From July 10s chain) . Fur seaOur behavior data were collected using the Daily Diary tag. This tag had tri-axial accelerometers and magnetometers that recorded acceleration and the earth’s magnetic field in the 3 spatial dimensions , dorsal-ventral (heave or z-axis) and lateral (sway or y-axis)). It also recorded swimming depth, internal temperature of the tag, and conductivity to indicate wet/dry. The acceleration and magnetic field sensors were set to collect data at 16Hz, while the remaining sensors recorded every second (1Hz).th behavioral category from the “mixed” category, which we termed “prone position” behavior.Behavioral analysis was conducted using the depth channel, the lateral accelerometer, and the dorso-ventral accelerometer. Behavioral analysis occurred in two stages. The first stage involved importing the data into Igor Pro wave analysis software (WaveMetrics). The Ethographer  software“Diving”, the first behavior we differentiated, was identified using the depth channel and defined as excursions below a depth of 5m during the day and below a depth of 0 meters during the night. This definition was primarily designed to distinguish between diving that was most likely foraging, and diving that was most likely other sub surface behaviors (which vary between day and night). We defined night as beginning and ending at nautical twilight, which is a solar elevation angle of 6 degrees below the horizon. Given that night dives tend to be shallow and short, we assigned diving behavior to a given minute if the animal was below the surface for more than 25% of the time in that minute. This definition differs from our “dominant behavior” designation for all other behaviors, and underestimates if diving occurred during a minute but overestimates the overall time an animal was actually diving.Rissa tridactyla), which are plunge divers that are unable to dive below the top meter of water. It is thus possible for fur seals to feed on myctophids while making very short shallow dives—hence our need to establish criteria to capture this relatively brief but important foraging behavior.Myctophids are a deep-water species and prey item for northern fur seals from Bogoslof and St. Paul Island ,27. Thes-2. We defined resting behavior using a two-step criteria: 1) average lateral acceleration > 5 m s-2 or < -5 m s-2 with 2) a standard deviation < 3 m s-2. These conditions indicated that the fur seals were laying on either lateral side at the water surface and moving very little. Shaking behavior was defined when bursts of strong lateral acceleration (> ±25 m s-2) were recorded.We differentiated the remaining time into exclusive behavioral categories using the lateral and dorsal-ventral axes of accelerometer data. Raw data from the accelerometer channel was in mV, with a reading of ~10 mV roughly coinciding with the force of gravity at 9.8 m sK-means clustering  was then used to aggregate the behavior spectra over each second by minimizing the within-cluster sum of squared Euclidean distances from the cluster (behavior) centroids, thereby determining the dominant behavior.We identified and defined other behaviors in the accelerometer data based on commonly occurring waves with consistent amplitude and frequency. Frequency analysis can be used to identify cyclical oscillation waves. We thus extracted rolling behaviors from the acceleration data by employing a frequency analysis method based on continuous wavelet transformation with a Morlet mother wavelet as described by Sakamoto et al. . This meWhile we were unable to quantify swimming effort using flipper strokes, visual inspection of the accelerometer channels indicated that the animals did spend considerable time at the surface in a prone position. This appeared to occur most often near the end of a trip and was hypothesized to indicate swimming. Seals lying on their stomachs in the prone position have a static acceleration of ~0 on the sway axis and ~10 on the heave-axis accelerometer, with some minor variation between tags due to sensor variability. We thus defined an animal to be in the prone position when the mean of the sway-axis acceleration was 0 (± 2) and the mean of the heave-axis acceleration was 10 . This slight negative skewing of the heave-axis acceleration reflected our observation that some individuals tended to roll slightly when in the prone swimming position.We filmed a group of captive fur seals  for approximately 18.5 hours over 7 days between May and December 2012 to validate the at-sea behavior our algorithm identified from the accelerometry data of the wild fur seals. One of the females in the group (NF08ME) was fitted with a specially-designed harness with an attached accelerometer. The instrumented fur seal swam freely with conspecifics in a 15 × 15 × 3.5 m deep research pool for several hours at a time, while we filmed her behavior with a high definition camera mounted above the pool. The anterior-posterior axis of acceleration was used to identify the porpoising behavior.-1 were removed. We then assigned speed to all behaviors exhibited between GPS fixes and average speeds per behavior were calculated on a per trip basis. We then used mixed effects models  to determine if specific behaviors tended to have faster traveling speeds associated with them. We investigated two models  where the basic model took the form of Speedi = βjBehaviorj+ sealkbk + ei, where bk and ei are both normally distributed random variables.Speeds were calculated between GPS fixes (obtained from the Mk-10F tag) via simple point interpolation and dividing distance traveled by time. GPS points associated with unrealistic travel speeds of greater than 3 m sWe sought to determine if there was a difference in the proportion of behaviors exhibited by different subsets of fur seals, and whether behaviors changed based on the length of the foraging trip. We were also interested whether differences existed between the two islands, between animals on St. Paul that used the on-shelf or off-shelf habitats, and between nocturnal or cathemeral foragers  and the proportions are bounded by 0 and 1. This is a classic “compositions” data set, yet popular methods to analyze these data are not necessarily intuitive and involve taking log ratios of proportions before statistically comparing the ratios. There are at least three 3 R packages available for this type of analysis in addition to numerous textbooks and papers that vastly range in their accessibility for biologists. We relied heavily on van den Boogaart and Tolosana-Delgado , while tTags from seals on Bogoslof Island  logged 111 useable foraging trips, while those from seals on St. Paul Island (n = 41) recorded 51 foraging trips. Trip duration for the Bogoslof seals averaged 3.3 days ranging from 3.75 hours to just over 13 days, while trip duration for St. Paul Island seals averaged 7.7 days ranging from just over 4 days to nearly 17 days. Trip distance as calculated by interpolation between GPS locations averaged 189 km and ranged from 0.5 to 525 km, while St. Paul Island trips averaged 582 km and ranged from 243 to 1265 km.Behaviors differentiated from the free-ranging fur seals using acceleration data included resting , shakingDiving was the most common behavior across any of the stratifications at just under 30% , followec indicates the best model is simply the constant with only four coefficients of 30 being significantly different from 0 in the most complicated model  needed to keep the fur in good thermoregulatory condition.The most surprising result was the amount of time fur seals spent rolling at the surface (combined W-wave and sine wave), which accounted for nearly one-third of the entire foraging trip. It is unclear what specific purpose rolling at the surface may serve, though it may be used to scan for predators or prey. The rolling occurred in two forms that we named based on the graphic display of the accelerometer data—a sine-wave-roll (a 360° roll) and a W-roll . The rolling behavior, particularly the W-form, often continued among wild fur seals for hours at a time with little break, while captive animals did not sustain either of the rolling behaviors for more than a minute at a time. W-rolls were associated with faster swimming speeds and hence likely associated with transiting, while the sine-rolls appear to be associated with loitering.The GPS-based speed analysis relative to the behaviors indicated that the prone position was associated with the fastest speeds—making it the most likely behavior associated with transiting. The St. Paul data were more informative as the fur seals from this island averaged a greater number of GPS fixes per day (19.1) than the Bogoslof seals (15.0 fixes per day), so calculated speeds were more likely to be associated with periods of distinct behaviors as the number of GPS fixes increased . We expeWhile it is difficult to unconditionally determine all behaviors from acceleration data, we found that many of the key behaviors that dominated the at-sea activity we recorded can be accurately categorized and successfully ground-truthed using captive animals. Some of the behaviors we classified for northern fur seals were previously known from direct observations, such as the jug handle resting position . Shaking and various forms of rolling and grooming behaviors have also been commonly seen at the surface during the summer months in the waters near St. Paul and Bogoslof Islands. We were unable to associate flipper beats or porpoising with swimming at the surface. Flipper beats are easily recognizable during dives and were easily identifiable in the relatively calm pool at the aquarium. We presume that the flipper beats that occur while swimming at or near the surface in the wild are masked by signals from ocean waves, particularly surface chop.Because of the differences between the population trajectories of the two islands, as well as differences in trip lengths and the two different regions and strategies that animals use to forage from St. Paul Island, we expected to find differences in the relative amounts of behaviors between these ecological groupings. Specifically, we expected to find that the increasing population of Bogoslof fur seals that have short feeding trips would have an easier time foraging. However, it’s difficult to predict what an “easier time” would look like in relative amounts of behavior, but one might expect less time swimming and diving, and more time resting on the surface given that a satiated animal might be expected to dive less. The lack of differences may imply that behavioral allocations are more controlled by external factors. It may be, for example, that the amount of time that can be spent diving is limited by the amount of available darkness,  and thusS1 FigTernary matrix for the 7 behaviors with the “mixed” behavior present in each ternary diagram. Proportions of each behavior are color and symbol coded by Island, Bogoslof or St. Paul. Note there is little differentiation in clumping of proportions by Island.(TIF)Click here for additional data file.S2 FigTernary matrix for the 7 behaviors with the “mixed” behavior present in each ternary diagram. Proportions of each behavior are color and symbol coded by forager type, cathemeral or nocturnal. Note there is little differentiation in clumping of proportions by forager type.(TIF)Click here for additional data file.S3 FigTernary matrix for the 7 behaviors with the “mixed” behavior present in each ternary diagram. Proportions of each behavior are color and symbol coded by region, on-shelf or off-shelf. Note there is little differentiation in clumping of proportions by region.(TIF)Click here for additional data file.S4 FigBoxplot matrix of behavior log ratios for the 7 behaviors. Note that most of the boxplot notches overlap, indicating no significant behavioral differences between Bogoslof and St. Paul islands.(TIF)Click here for additional data file.S5 FigBoxplot matrix of behavior log ratios for the 7 behaviors. Note that most of the boxplot notches overlap, indicating no significant behavioral differences between nocturnal and cathameral forager types.(TIF)Click here for additional data file.S6 FigBoxplot matrix of behavior log ratios for the 7 behaviors. Note that most of the boxplot notches overlap, indicating no significant behavioral differences between on-shelf and off-shelf regions.(TIF)Click here for additional data file.


Two dietary interventions, low fat or low carbohydrate, were investigated and consisted of a 42 day cycle of menus and recipes. Weight loss counseling and anthropometric assessment were provided at monthly clinic visits. One hundred ninety-two women completed the trial (77% retention). In comparison to the nonintervention control, both intervention arms achieved significant decreases in body weight (12.5%), body fat (27.5%), waist circumference (9.5%), and hip circumference (7.8%)  with minimal effects on lean mass (1.3% decrease). Median time to 5 and 10% weight loss was 2  and 4  months, respectively, and 23% of participants experienced ≥ 15% weight loss. Loss of body weight and fat mass was rapid and substantial irrespective of dietary approach when a structured program was provided with monthly anthropometric assessment and weight loss counseling.Body weight management is not emphasized in clinical practice guidelines for breast cancer survivors, reflecting the lack of evidence that weight loss improves prognosis. Even if this situation changes, the optimal design for weight loss interventions is unclear. We conducted a 6-month non-randomized, controlled weight loss intervention in 249 post-menopausal breast cancer survivors. This paper reports effects on two secondary endpoints, change in body weight and composition. Participants were predominantly non-Hispanic whites (89%) with a mean age of 54.9 ± 9.2 years, a mean BMI of 29.0 ± 2.6 kg/m: NCT01315483ClinicalTrials.gov  Overweight and obesity, which are associated with excessive and abnormal accumulation of body fat, have been reported to worsen prognosis for long term survival following treatment for breast cancer . AvailabThe cornerstone of therapeutic interventions to treat or prevent obesity-associated diseases is weight loss via lifestyle modifications involving energy intake and expenditure ,8. A numMany dietary approaches to weight loss have been evaluated in various populations ,14. ThosThe purpose of this paper is to report on magnitude of weight loss and differences in body composition, both designated secondary endpoints , which oThe protocol for this trial and supporting CONSORT checklist are available as supporting information; see 2). In addition, participants: did not anticipate surgery over the study duration period; did not follow a special diet excluding foods or food groups; had not lost 4 or more pounds of body weight over the month preceding study initiation; did not take pharmaceuticals or supplements for weight management; were not being treated for diabetes or blood glucose control; had no history of eating disorders; did not have digestive issues that might interfere with dietary intake, such as irritable bowel syndrome, Crohn’s, or diverticulitis; never had surgery involving constriction or removal of any portion of the gastrointestinal tract; did not have implanted electronic devices such as a pacemaker; and did not use tobacco products. Participants also had to be willing to follow a dietary plan prescribed for the duration of the study; and adhere to American Cancer Society alcohol guidelines (≤1 standard drink per day). Participants were asked to attend 10 one-on-one clinic visits and 5 group visits over 27 weeks and provide 7 fasting blood samples and 3-day pooled urine samples. Enrollment was initiated in 2008 and completed in 2012. Based on work on the primary endpoint, C-reactive protein, published in 2009 [The details of the CHOICE research protocol including eligibility criteria have been published . Briefly in 2009 .The clinical protocol was approved by the Colorado State University Institutional Review Board for the Protection of Human Subjects. Written consent was obtained before enrolling participants.Eligible women not interested in participating in the weight loss intervention arms were given the opportunity to enroll in the non-intervention control group. This group was given information about the importance of avoiding post treatment weight gain and the health benefits of having a body mass index in the normal range. Anthropometric data were only collected at baseline and end of study.Two interventions were designed based on input from participants of a pilot study of weight loss in breast cancer survivors conducted in the same clinical practice in which the intervention was conducted, one year before the intervention study was initiated. That study  indicated: 1) that a structured diet plan was beneficial to maintaining accountability in losing weight, 2) that the opportunity to evaluate a dietary plan for feasible adaptation to an individual’s taste preferences, which can be altered by cancer treatment, was critical to making a commitment to a program of weight loss, 3) that while a structured weight loss program was critical to reduce cognitive stress, it needed flexibility for life style adaptation and to match culinary abilities, and 4) that many survivors were unable or unwilling to exercise but that increasing activity by walking was highly acceptable. Accordingly, two interventions were developed and were comprised of a structured diet and physical activity program designed to create a weekly negative energy balance equivalent to 3500 kcal, after adjustments for metabolic adaptations that occur during extended periods of weight loss. The intervention groups received the same physical activity protocol promoting 10,000 steps per day and one of two diets that reflect commonly used weight loss approaches that were identified in our pilot study as being of greatest interest to the survivor population. The dietary patterns investigated contained a low percentage of dietary energy as either fat or carbohydrate.The diet plan for each intervention arm was comprised of a 42-day cycle of menus and recipes. The recipes for each day’s diet plan were entered into ProNutra Diet Analysis software  to assure that all breakfast, lunch, or dinner menus had the same percent of dietary energy from protein, fat, and carbohydrate and were therefore interchangeable in this regard. The 42-day cycle menus were designed for five calorie levels in each intervention arm. The meal plans included interchangeable meal options , educational material and a program incorporating weight loss strategies. The intervention was designed as a feeding study but was conducted in free living individuals, where strict dietary structure is presented in a format that also offers enough flexibility to be adopted into daily living. To accommodate the importance that survivors in our pilot study placed on acceptability of a dietary plan, and prior to beginning the intervention, participants followed menus and recipes for three days of each intervention and discussed their concerns with the study dietitians. Assignment to intervention arm was made by the project staff based on this dialogue. Since many participants did not have a specific dietary preference, the need to maintain balance in resected disease stage and type of treatment between intervention arms was considered in assignment to the intervention arm and it was possible to maintain balance in study arm assignment throughout the 2008–2012 time span over which the intervention was conducted. Adherence was assessed by the study registered dietitians by monthly level of weight loss as well as daily food record.Differences in cohort characteristics at baseline across intervention arms and between completers and those lost to follow-up were evaluated using the global F test in a one-way analysis of variance for continuous variables; categorical data were evaluated using a chi-square test for equal proportions. Six-month changes in weight and body composition for each diet group vs control were evaluated in an ANOVA model. For comparing 6-month change between diet groups, an ANCOVA model was used; covariates were baseline BMI, baseline resting metabolic rate, 6-month change in steps, and elapsed time since the end of treatment. The shape of the response curve for weight loss over time was estimated using a maximum likelihood method for repeated measures to accommodate the first order autocorrelation between visits for an individual; the model included baseline BMI, baseline resting metabolic rate, elapsed time since the end of treatment, and the time varying covariate steps; orthogonal polynomial contrasts were used to estimate the shape of the response curve over time. Sensitivity analysis for between-diet differences in 6-month change was done to assess the effects of limiting the comparison to those who completed the 6-month intervention (n = 139) by including all subjects who provided baseline data (n = 167) and a) coding the missing 6-month weight change as 0 or b) using a traditional LOCF (last observation carried forward) analysis; in both cases when 6-month change in steps was missing we used the last recorded value to compute change from baseline. Time-to-event data were evaluated by Kaplan-Meier plots and Cox proportional hazards models. SAS version 9.3  was used for all statistical analyses. GraphPad Prism 5.0  was used to visualize the data.2 and an average of 43 ± 5% body fat. There were no differences across study arms in clinical or demographic characteristics, including disease stage or treatment regime. During the course of the study, dropout rate was similar in the low carbohydrate (15%) and the low fat (18%) study arms, although it was higher in the non-intervention control (26%); the differences were not statistically significant (p = 0.22). Demographics for the 47 cases lost to follow up were not different from those who completed the study, with the exception of time since end of treatment (p = 0.01).A total of 249 participants were assigned to the study . Clinicap < 0.001) in an unadjusted ANOVA model. The differences between the intervention arms in the primary measures, weight loss, fat weight loss, and lean weight maintenance, gradually diverged over six months. Average cumulative weight loss (kg) (p < 0.01). The cumulative loss of lean mass was greater in the first 2 months, but there was no evidence for a trend over time. An ANCOVA model controlling for baseline BMI, RMR, elapsed time since end of treatment, and the 6-month change in steps, was used to test for between diet differences in6-month percent change  , averageoss (kg)  and aveross (kg)  are showt change . None ofBox plots were constructed and show the progressive increments in change in percent of initial body weight and the increasing variation in response among individuals over time . Weight Kaplan-Meier plots  quantifyThe following adverse events were recorded: treated for a pulmonary embolism (1), treated at an emergency room for stomach pain (1), treated for falls (2), one of which resulted in a hairline hip fracture, and allergic reaction to an antibiotic (1). All adverse events were determined to be not related to the weight loss intervention. Plasma lipid profile  and anthThe number of breast cancer survivors continues to increase . These wA curvilinear response was demonstrated in loss of body fat that directly paralleled the loss of body weight ; Fig 2B.2. While metabolic abnormalities associated with cardiovascular disease and type-2 diabetes, common co-morbidities of breast cancer survivors, are improved with weight loss within the range of 5 to 10% of initial body weight, overall mortality rates and cancer and cardiovascular disease specific death rates are lower in the general population when body mass index is in the normal range (18.5 to 24.9kg/m2)[2 as a target for maximizing survival benefit.Despite the success of the current study, there was a broad range in the percent weight loss ; Table 44.9kg/m2),32–34. TIn evaluating the anthropometric data, we recognized that no metrics are generally used to compare the success of weight loss programs, which is particularly important in the private practice setting since the staff resources committed to support weight loss can be considerable. Typical weight loss results ; Fig 2 fIn evaluating the literature, we also recognized that the magnitude of variation among participants in a weight loss program is difficult to visualize. We found no examples of the characterization of variability among individuals within a cohort during progressive months of a weight loss program. For this purpose, we used box plots into which dot density data were integrated as a graphic visualization tool. The box plot analyses  show thaThis trial had a number of strengths including monthly assessment of body weight and composition during which weight loss counseling occurred, and the use of a structured plan of interchangeable menus and recipes. The use of the print-based meal plan may have been so effective because it was paired with both physical activity and behavior modification  and frequent contact with study staff monthly Click here for additional data file.S1 Protocol(PDF)Click here for additional data file.


Incidence and prevalence estimates of acromegaly in the United States (US) are limited. Most existing reports are based on European data sources. The objective of this study was to estimate the annual incidence and prevalence of acromegaly in a large US managed care population, overall and stratified by age, sex, and geographic region, using data from 2008 to 2012.Using administrative claims data, commercial health plan enrollees were identified with acromegaly if they had two or more medical claims with an acromegaly diagnosis code (ICD-9-CM: 253.0×) or one medical claim with an acromegaly diagnosis code in combination with one other claim for a pituitary tumor or pituitary procedure. The first date for an acromegaly-related claim set the index year. Incidence rates for each year were calculated by dividing the number of new acromegaly cases by the calculated person-time at risk. Annual prevalence estimates were calculated by dividing the number with any evidence of acromegaly by the total number of health plan enrollees enrolled for at least 1 day during each calendar year. Incidence and prevalence estimates were stratified by age , sex , and US geographic region of the health plan .Overall annual incidence rates of acromegaly were relatively constant across 2008–2012 with ~11 cases per million person-years (PMPY). Rates increased with age, ranging from 3–8 cases PMPY among children aged 0–17 years old to 9–18 cases PMPY among adults aged 65 and older. Females had 12 cases PMPY on average compared to 10 cases PMPY among men. On average, the Midwest had the lowest incidence rates (7 cases PMPY) compared to the Northeast, South and West . The overall annual prevalence of acromegaly was relatively constant across the 5 years from 2008 to 2012 with approximately 78 cases per million each year. Annual prevalence estimates increased with age, ranging from 29–37 cases per million among children aged 0–17 years old to 148–182 cases per million among adults aged 65 years and older. Males and females were similarly affected; each with approximately 77 cases per million each year. The Northeast and South had the highest prevalence estimates ; while the estimates for the West and Midwest were lower  each year.This study examined 5 years of recent data to estimate the incidence and prevalence of acromegaly in a large geographically-diverse managed care population. The incidence rates were higher on average than published rates outside the US (11 vs. 3.3 PMPY), but prevalence estimates were consistent with previous reports. Incidence and prevalence both increased by age, did not differ for males and females, and varied slightly by US geographic region. The age and sex distribution of the selected population matched the known epidemiology of the disease. Using a claims-based approach, this analysis only captured acromegaly cases with an acromegaly-related medical claim. As a result, these estimates may underestimate the incidence and prevalence of acromegaly in US commercial health plans as they did not include individuals who were undiagnosed, in remission, undertreated, or not monitored during the study period. At the same time, these estimates may be viewed as an upper bound on the incidence of acromegaly in the US as the estimates did not include individuals who were in other health plans or uninsured during the study period. Additional evaluations are needed to identify the full extent of acromegaly in the US.The online version of this article (doi:10.1007/s11102-015-0701-2) contains supplementary material, which is available to authorized users. Most incidence and prevalence estimates of acromegaly come from studies conducted in countries outside of the United States (US), often using data from disease registries or national health care systems. Population-based lifetime data are ideal for tracking the development and existence of rare diseases such as acromegaly. However, estimating the presence of acromegaly in any data source is complicated by its insidious nature that changes slowly over time and often mimics many common aging conditions such as diabetes and heart disease. The signs and symptoms of acromegaly are so commonplace among the general population that diagnosis is often delayed an average of 4–7 years after the onset of excessive growth hormone (GH) secretion in adults; but in children, the disease is much less likely to go unnoticed due to their abnormally dynamic growth in physical stature .Most published estimates of acromegaly are fairly consistent with each other but dated. While incidence rates published across Europe, Asia, and New Zealand are remarkably similar, ranging around 2–4 per million per year, the majority are also more than 10 years old . PrevaleTo date, all epidemiologic studies are consistent with respect to the 1:1 sex distribution, mean age of diagnosis around mid-forties, 1:3 micro to macro adenomas, and the approximate rates of surgical success with up to 90 % for micro adenomas and <60 % for macro adenomas when in expert pituitary surgical care . HoweverThe source population was derived from a large health insurance database, which contains medical and pharmacy claims, and enrollment information from a geographically-diverse group of health plans in the US. Dating back to 1993, the database includes data on more than 123 million US health plan enrollees over time.International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes, and procedures, reported with ICD-9-CM, Current Procedural Terminology, Version 4 (CPT-4), and Healthcare Common Procedure Coding System (HCPCS) procedure codes. The medical claims also include site of service codes and health plan- and patient-paid amounts for services received. Outpatient pharmacy claims include national drug codes (NDC), drug dosage form, fill date, health plan- and patient-paid amounts for dispensed medications. All administrative claims data for this study were de-identified and compliant with the provisions of the health insurance portability and accountability act of 1996.The medical claims in the database for professional and facility services include information on diagnoses, reported with The study population included children and adult commercial health plan enrollees in the database between July 1, 2000 and June 30, 2012 (identification period) who met one of the following three acromegaly selection criteria: (1) had at least two medical claims on separate dates with an acromegaly diagnosis code (ICD-9-CM: 253.0×); or (2) had one medical claim with an acromegaly diagnosis code in combination with one medical claim with a pituitary tumor diagnosis code (ICD-9-CM: 237.0×); or (3) had one medical claim with an acromegaly diagnosis code in combination with one medical claim for a pituitary surgery (hypophysectomy) or stereotactic radiosurgery (radiation) procedure (Supplement Table A).Observation time for acromegaly began on the date of health plan entry. Person-time at risk continued to accrue until the earliest of: acromegaly onset, death, disenrollment from the health plan, or study cut-off, December 31, 2012. The date of acromegaly onset was defined as the first date for an acromegaly-related claim  on or after January 1, 2000. The date of acromegaly onset also set the index year. Years prior to the index year were defined as acromegaly-free and years following the index year were defined as having a history of the disease.Annual incidence and prevalence estimates of acromegaly from 2008 to 2012 were derived from the managed care population. Incidence rates were calculated by dividing the number of new acromegaly cases  by the total time at risk during each calendar year. All incidence rates were reported as the number of cases per one million  person-years at risk. Prevalence was calculated by dividing the number with an acromegaly-related claim during each calendar year or any time prior by the total number continuously enrolled in the health plan for the entire calendar year. Incidence and prevalence estimates were stratified by age , sex , and US geographic region of the health plan .All study variables were summarized descriptively using SAS v9.2 .Of the more than 50 million commercial health plan enrollees in the database from 2000 to 2012, 4090 had at least one claim with an acromegaly diagnosis code and 2241 had the additional criteria suggestive of true acromegaly   , but prevalence estimates were consistent with previous reports. Overall, the incidence and prevalence estimates increased by age, did not differ for males and females, and varied by US geographic region. The age and sex distribution of the selected population matched the known epidemiology of the disease.It is not surprising that our incidence rates differed from studies outside the US, given the vast differences in the methods used to collect health data around the world. There are several reasons that may explain the difference observed between our incidence estimates and the non-US studies. First, the sample of commercially-insured health plan enrollees in the database primarily includes working-age adults in the US who are more likely to be near the mean age of disease onset than the national populations included in non-US studies. Second, since administrative claims data are collected for the purposes of billing rather than research, it is possible that a diagnosis code on a medical claim may not indicate the presence of actual disease. Although only non-diagnostic medical claims were used to identify acromegaly (claims from laboratories and diagnostic testing centers may include “rule-out” procedures for diagnoses not yet confirmed), it is still possible that acromegaly may have been miscoded or misidentified on claims, which could have increased the reported incidence rates. Third, this analysis required individuals to have at least one health care service to be included in the incidence calculations, which suggests that the reported incidence rates may have been lower if the population had included healthier individuals with no health care use as well. At the same time, this analysis required at least two medical claims to identify acromegaly cases, which suggests that the reported incidence may have been even higher as the estimates did not identify individuals with acromegaly who were undiagnosed, in remission, undertreated, or not monitored during the study period. Other limitations to consider when interpreting these results include the source population and its generalizability. As noted above, the study data came from a geographically-diverse managed care population, which means the results are primarily applicable to populations that receive their care through similar delivery systems across the US. However, this still leaves out a significant proportion of the US population, many of whom have other forms of health insurance such as Medicare, Medicaid, Tricare, or none at all. In comparison, non-US surveys typically are based on disease registries or health systems that collect extensive national data like Finland and New Zealand or offer individuals ongoing access to medical coverage throughout life such as the National Health Service (NHS) in the United Kingdom , 11. In To calculate the incidence and prevalence of acromegaly correctly it is important to know not only who was diagnosed, but also when they were diagnosed and the current disease status . While US health plan databases have the ability to track individuals longitudinally, their populations can change frequently as individuals enroll and disenroll from health plans over time. As a result, acromegaly-related care received outside of the health plan is not always included in the database or may be excluded when analyzing individual cuts of the data . This study sought to overcome these limitations by requiring at least a 6-month continuous enrollment period and including all medical claims in the database dating back to January 2000 to check for acromegaly history regardless of enrollment status. Lastly, to identify our sample without clinical data such as the date of diagnosis, substantial emphasis was placed on multiple pathways to acromegaly case identification. However, no medical chart review was conducted to validate our claims-based definition. Given that acromegaly is challenging to diagnose and cannot be confirmed using claims data alone, future research should include clinical data from medical charts or electronic health records to validate the algorithm used to identify acromegaly patients in administrative claims databases.This study examined 5 years of recent data to estimate the incidence and prevalence of acromegaly in a large geographically-diverse managed care population in the US. The incidence rates were higher on average than published rates outside the US (11 vs. 3.3 per million person-years), but prevalence estimates (~78 cases per million each year) were consistent with previous reports. Overall, the incidence and prevalence estimates increased by age, did not differ for males and females, and varied slightly by US geographic region. The age and sex distribution of the selected population matched the known epidemiology of the disease. Using a claims-based approach, this analysis only captured acromegaly cases with an acromegaly-related medical claim. As a result, these estimates may underestimate the incidence and prevalence of acromegaly in US commercial health plans as they did not include individuals who were undiagnosed, in remission, undertreated, or not monitored during the study period. At the same time, these estimates may be viewed as an upper bound on the incidence of acromegaly in the US as the estimates did not include individuals who were in other health plans or uninsured during the study period. While the claims-based algorithm was not validated with a medical chart review, this study did find data that matched the known epidemiology of the disease. Additional evaluations are needed to identify the full extent of acromegaly in the US.Supplementary material 1 (DOCX 15 kb)Supplementary material 2 (DOCX 21 kb)Supplementary material 3 (DOCX 20 kb)Below is the link to the electronic supplementary material.


Current analysis of circulating tumor cells (CTCs) is hindered by sub-optimal sensitivity and specificity of devices or assays as well as lack of capability of characterization of CTCs with clinical biomarkers. Here, we validate a novel technology to enrich and characterize CTCs from blood samples of patients with metastatic breast, prostate and colorectal cancers using a microfluidic chip which is processed by using an automated staining and scanning system from sample preparation to image processing. The Celsee system allowed for the detection of CTCs with apparent high sensitivity and specificity (94% sensitivity and 100% specificity). Moreover, the system facilitated rapid capture of CTCs from blood samples and also allowed for downstream characterization of the captured cells by immunohistochemistry, DNA and mRNA fluorescence in-situ hybridization (FISH). In a subset of patients with prostate cancer we compared the technology with a FDA-approved CTC device, CellSearch and found a higher degree of sensitivity with the Celsee instrument. In conclusion, the integrated Celsee system represents a promising CTC technology for enumeration and molecular characterization. Cancer metastasis occurs when tumor cells disassociate from the primary tumor, enter the circulation, and migrate to distant organs through the peripheral blood stream or lymphatic drainage , 2. CircIn clinical practice, analysis of CTCs can provide a minimally-invasive approach for tumor characterization , 6, 7. A™ system  represents an automated system of this microfluidic device and contains a parallel network of 4 microfluidic chips each of which has approximately 56,320 capture chambers [We previously reported a novel microfluidic chip-based device to capture and analyze CTCs . In the chambers . Based oIn this study, we report the results of CTC enrichment and analysis from blood samples of patients with metastatic breast, prostate, and colorectal cancer using the automated Celsee PREP 400 system. Our data suggest that CTCs can be captured efficiently in these patients by size filtration, highlighting the potential clinical value of this technology.This study was approved by respective institutional review boards (IRB) at Thomas Jefferson University, Johns Hopkins University School of Medicine and University of Michigan. Informed and written consent was obtained from all patients. Blood samples from patients with metastatic prostate cancer were obtained from Johns Hopkins University and University of Michigan. Patients were monitored closely for disease progression using serum PSA and imaging. Eighteen of the prostate cancer samples were also tested by using both Celsee and CellSearch systems. This group has a mean PSA of 109.3 ng/ml (median = 55.5 ng/ml). Patient samples from Thomas Jefferson University were women with metastatic breast cancer. Among the patients, 41 have known status on ER ; 40 have known status on PR ; and 37 had known status on HER-2 . Following informed consent, blood samples from healthy donors and patients with metastatic breast, prostate and colorectal cancer were acquired. The samples were collected from 3 institutions, Thomas Jefferson University, Johns Hopkins University School of Medicine and University of Michigan. Blood samples were collected, stored and transported in CellSave tubes , 10 ml BCT Cell-free DNA tubes  or EDTA-coated vacutainer tubes , and shipped to Celsee Diagnostics for processing. Samples collected in either CellSave tubes or BCT Cell-free DNA tubes were used for CTC capturing and immunostaining. Samples collected in EDTA-coated tubes were used for CTC capturing and DNA and mRNA FISH analysis. All the tubes have no effect on and work equally well for immunostaining. However, only EDTA-coated tubes work fine for FISH assays because the other tubes contain fixatives that damage nucleic acids.™ 400 sample processing system and Celsee Analyzer™ imaging station  [™ 400 system can run four blood samples on four microfluidic slides simultaneously  . The labaneously . Each laaneously . All mataneously . In addi™ imaging station automatically captures bright field or fluorescence images of cells while its software allows specific analysis and reporting of the results. It is an automatic whole slide scanner that is comprised of the following components: an optical focusing system, a CCD camera, a Z-focusing system, an XY-translational stage, bright field illumination, a multi-color fluorescence excitation and emission filter system, a microprocessor control board, and a computer. The user can upload up to 8 slides for processing and can view images in up to 6 fluorescent colors. Celsee Analyzer scans the entire surface of the microfluidic slide with a series of fluorescence filters that are defined for a given assay and acquires images. A standard assay includes capture of images using filters for DAPI (nucleus), Alexafluor 488  and Alexafluor 594 . Additionally the user can capture data with filters for Cy3, Cy5 or PE and APC. After data acquisition is completed, the images are analyzed for any event where DAPI and cytokeratin are within a specified space in the slide, i.e., indicating the possible presence of a cell with a nucleus that expresses cytokeratin. Images from each fluorescent color, as well as a composite image are presented to the user in a gallery for CTC calls. A cell is classified as a CTC when it is DAPI+, PanCK+ and CD45-. A check mark is placed by the operator next to the composite images and the software tallies all the checked boxes to obtain a CTC count in the sample.The Celsee AnalyzerThe blood samples collected in the BCT Cell Free DNA tubes and CellSave tubes are processed within 72 hours while the blood sample collected in the EDTA-coated vacutainer tubes are processed within 24 hours of collection. The first step of blood preparation begins with adding 2 ml pre-treatment buffer of 0.8% paraformaldyde (PFA) to 2 ml blood. The solution is then mixed and incubated for 10 minutes in order to pre-fix the cells. This brief partial fixation step of the cells with a low concentration of the fixative ensure that the cells will have appropriate deformability while passing through the microfluidic slide. After the incubation, 2 ml of wash buffer (1X PBS) are added to the sample and the sample is loaded to the inlet funnel of one of the 4 lanes of the Celsee PREP 400 instrument. The rest of the steps are automated. Following the cell capturing, the primary antibody cocktail, Anti-PanCK  and Anti-CD45  is added and incubated for 45 minutes, followed by a washing and an incubation with secondary antibody cocktail of Alexaflour 488 and Alexaflour 594  for 30 minutes. Owing to their bigger size compared to white blood cells, cancer cells are captured by micro-chambers and the remaining solution containing red blood cells and the majority of leukocytes are collected by the outlet reservoir after passing through the pore chambers. A background level of larger leukocytes such as monocytes are also trapped by the micro-chambers but are distinguished by their surface markers in the subsequent analysis. In selected samples, a second 2 ml of blood is processed and the captured CTCs are stained with monoclonal Anti-vimentin . Selected prostate samples are also stained with monoclonal Anti-PSA .Captured cells were imaged using the Celsee Analyzer system. All images were taken with the same exposure time and conditions in order to compare the relative fluorescence intensity. CTC enumeration following antibody labeling and imaging capturing was performed manually. Nucleated PanCK+/CD45- cells were identified as CTCs. Positive and negative controls with cultured cancer cell lines for antibody performance and staining were included in each experiment.Two milliliters of blood samples from metastatic breast cancer patients and 2 ml freshly-made 0.8% paraformaldyde (PFA) were mixed and incubated for 10 minutes at room temperature. Next, the sample is applied to the microfluidic chip and washed with 1X PBS twice and fixed in 1% (v/v) formaldehyde/PBS. Immediately prior to hybridization, the cells are treated with 200 ul of 0.05% (w/v) pepsin to 1.8 ml of 0.01 N HCl, 4 ml cold 70% (v/v) ethanol, and washed with 1X PBS/MgCl2. FISH probes are denatured at 73°C with 70% formamide for 5 minutes. The probes are then placed on ice. One ml of pre-warmed denature buffer is added to the cells on the microfluidic chip and the manifold is heated by on-board heater . The denatured probe is added into the microfluidic chip and incubated for 5 minutes at 73°C and hybridized overnight at 37°C under dark conditions. Her-2 and Chromosome 17 probes from Vysis  are used to carry out the experiments. Hybridized cells were washed with 2X SSC/0.1% NP-40 (v/v)) at room temperature, counter-stained with 4’, 6-diamidino-2-phenylindole (DAPI) and sealed.Two milliliters of blood samples from metastatic breast cancer patients and 2 ml freshly-made 0.8% paraformaldehyde (PFA) are mixed and incubated for 60 minutes at room temperature. Next, the sample is applied onto the microfluidic chip and washed with 1X PBS twice. Immediately prior to hybridization, the cells are treated with 150 ul of Ready-To-Use Protease #3 (Advanced Cell Diagnostics #310842) for 15 minutes at room temperature and washed with 1X PBS twice. The cells are washed with 70% ethanol and 1X PBS twice. Pan-cytokeratin and CD45 probes  are incubated for 10 minutes at 40°C and cooled to room temperature. One ml pre-warmed denature buffer is added to the cells on the microfluidic chip and heated microfluidic chip using on board heater . Five drops of the probe are added to the microfluidic chip and incubated overnight at 37°C. The cells on the microfluidic chip are the washed with 1 ml of 2X SSCT twice. Three amplification steps are carried out according to the manufacturer’s instructions . Hybridized cells then were counter-stained with 4’, 6-diamidino-2-phenylindole (DAPI) and sealed.Blood samples from 200 healthy donors and 128 patients with metastatic breast (n = 96), prostate (n = 27) and colorectal cancer (n = 5) were processed using the Celsee PREP 400 system. The Celsee PREP 400 system showed excellent performance characteristics in the detection of CTCs in the patient samples from all 3 cancer types and no detection of any CTC in 200 blood samples from normal donors. CTCs were seen in each of the cancer patient samples, and the number of CTCs per 2 ml blood is shown in We compared CTC enumeration values between the Celsee PREP 400 system and the FDA-cleared CellSearch system using 18 blood samples from patients with metastatic prostate cancer. Two tubes of the blood samples were collected from each of the patients at the same time. One tube of blood was processed by the CellSeacrh system according to the manufacturer’s manual , and the other tube of blood was processed by the Celsee PREP 400 system. CTCs were detected in 61% (11/18) samples using CellSearch, and 94% of the samples (17/18) by the Celsee PREP 400 system. CTC counts were significantly higher using the Celsee PREP system, implying greater sensitivity for CTC detection .To characterize the captured cells using additional molecular biomarkers, we performed immunostaining experiments to analyze the expression of epithelial or mesenchymal-specific proteins. Positive staining of PanCK in the captured CTCs were observed, suggesting an epithelial nature of these cells . In addiWe performed an automated DNA FISH assay in CTCs on the Celsee PREP 400 system using the Vysis Her-2 and Chromosome 17 probes  after enumeration and fixation of captured cells from breast cancer patients. The idea here is to use Chr 17 probe as the control  and to find cells that has amplified signals with HER-2 probe . This would suggest that the cell is not only a breast cancer cell, but also a cancer cell with HER-2 amplification . SimilarWe demonstrated that CTCs can be readily captured and further characterized with molecular markers from clinical blood samples of patients with metastatic breast, prostate and colorectal cancer. Using the automated Celsee PREP 400 system, we obtained high definition images of immunostained CTCs (nucleated PanCK+/CD45- cells) in all 3 cancer types tested. Furthermore, we compared the detection and enrichment of CTCs between the Celsee PREP 400 system and the CellSearch system. In 20 prostate cancer patients with paired CTC counts, we demonstrated some levels of concordance in CTC detection by both systems. The Celsee PREP 400 system showed a higher sensitivity than the CellSearch system and detected CTCs from all 20 samples. A possible expalnation could be due to the presence of heterogeneous CTC populations with low or absent EpCAM expression, as these may not be captured by the anti-EpCAM antibody used in the CellSearch system.There is currently ongoing work to apply single-cell molecular analysis on captured CTCs, and the system described here facilitates the characterization of individual cells. We thus further characterized the captured CTCs using on-device immunostaining of additional antibodies, DNA FISH and mRNA FISH assays. Immunostaining of the CTCs on the device suggested that protein biomarkers can be used to detect differential expression of the captured cells. In addition to PanCK, vimentin was selected for the study because that it has been implicated to be specific for mesenchymal cells. Our results indicate the presence of CD45-/CK- cells that may be more mesenchymal in nature. We also developed DNA and mRNA FISH procedures to observe Her-2 amplification in CTCs of the breast cancer patients and pan-cytokeratin mRNA expression in CTCs. Additionally, although background leukocytes can create a challenge for detecting and analyzing CTCs, the present technology isolates leukocytes in separate microchambers and did not affect the analysis of the captured cells.Several methods have been reported to capture circulating tumor cells from blood with variable degree of success. Microfluidic approaches offer some advantages but such devices have been so far limited to research tools that lack automation and validation necessary for implementation in a clinical laboratory. A key feature of this platform is the ability to integrate the process of sample preparation, image analysis of CTCs and molecular characterization of the captured cells. Furthermore, the unique design of the microchannels of the chip allows separation of CTCs from the background leukocytes and improve sample purity over other methods that capture cells in aggregates. We are working on recovering single cells from the microfluidic chip for PCR and next-generation sequencing analyses. Progress towards understanding the heterogeneity and the complexity of CTCs in cancer could shed further light on the mechanisms of tumor metastasis and the delineation of tumor cells that are relevant to prognosis and therapy choice. It would also help to overcome some limitations of clinical use of CTC technologies, such as lack of standardization of CTC definition, low sensitivity in detection of CTCs in subsets of patients and high background leukocytes.Although the comparison study between the Celsee platform and the CellSearch platform, a FDA-cleared platform for CTC capturing suggested that the Celsee platform capture more cells, the study has some limitations because the sample size is relatively small. A more rigorous study needs to be carried out between our platform and CellSearch, especially to demonstrate the cause of discrepant measurements between the 2 platforms. We are proceeding with a clinical trial for the Celsee system  for clinical use.In summary, there continues to be a need for simple, non-invasive and inexpensive predictive tests for monitoring and determining response to therapy. Through improved CTC enumeration and molecular characterization it may be possible predict therapeutic response based on a single blood draw. Further development of the presented technology could potentially facilitate personalized treatment strategies and improved outcomes.S1 Table(XLSX)Click here for additional data file.