These data uncovered key roles of H3Kme and SET7/9 responsible for p21 gene expression in vivo and in vitro under diabetic conditions and confirmed preventive effect of TGF-β1 antibody on DN.Diabetic nephropathy (DN), a common complication associated with type 1 and type 2 diabetes mellitus (DM), characterized by glomerular mesangial expansion, inflammation, accumulation of extracellular matrix (ECM) protein, and hypertrophy, is the major cause of end-stage renal disease (ESRD). Increasing evidence suggested that p21-dependent glomerular and mesangial cell (MC) hypertrophy play key roles in the pathogenesis of DN. Recently, posttranscriptional modifications (PTMs) have uncovered novel molecular mechanisms involved in DN. However, precise regulatory mechanism of histone lysine methylation (HKme) mediating p21 related hypertrophy associated with DN is not clear. We evaluated the roles of HKme and histone methyltransferase (HMT) SET7/9 in p21 gene expression in glomeruli of diabetic rats and in high glucose- (HG-) treated rat mesangial cells (RMCs). p21 gene expression was upregulated in diabetic rats glomeruli; chromatin immunoprecipitation (ChIP) assays showed decreased histone H3-lysine9-dimethylation (H3K9me2) accompanied with enhanced histone H3-lysine4-methylation (H3K4me1/3) and SET7/9 occupancies at the p21 promoter. HG-treated RMCs exhibited increased p21 mRNA, H3K4me level, SET7/9 recruitment, and inverse H3K9me, which were reversed by TGF- Diabetic nephropathy (DN) is one of the most serious microvascular complications of DM and the leading cause of ESRD worldwide . Hypergl In vivo studies showed that p21 null mice did not develop glomerular hypertrophy [β1 (TGF-β1) [Prior studies have suggested that dysregulation of the p21 gene plays a critical role in the pathogenesis of DN, characterized by glomerular cell hypertrophy.ertrophy , 12, whiertrophy –17. Diveertrophy , 18, insertrophy , 19, tra(TGF-β1) , 10, con(TGF-β1) , advance(TGF-β1) . A lot o(TGF-β1) , extrace(TGF-β1) . Howeverβ1 mediated p21 mRNA expression in RMCs [β1-specific antibody pretreatment could reverse HG-induced H3Kme levels and SET7/9 recruitment [Epigenetic mechanisms have been found to play an important role in changing gene expression patterns, including posttranslational modifications (PTMs) of nucleosomal histones, DNA methylation, and miRNA regulation. PTMs such as histone lysine acetylation (HKAc) and histone lysine methylation (HKme) play key roles in the gene transcription. In general, histone H3 acetylation at lysine 9, lysine 14, lysine 18, and lysine 23, methylation of H3 lysine 4 (H3K4me), and trimethylations of H3 lysine 36 and lysine 79 (H3K36me3/H3K79me3) activate chromatin for transcription factors, while histone H3 di- or trimethylation at lysine 9 and lysine 27 silence chromatin by inhibiting transcription factors accessibility , 25. Che in RMCs , 25 and ruitment . Howeverβ1-specific antibody could reverse these HG-induced specific alterations. These data demonstrate a novel epigenetic mechanism of p21 gene expression leading to hypertrophy, the main feature of DN both in vivo and in vitro.We now show the decreased levels of H3K9me2, enriched H3K4me, and SET7/9 recruitment at p21 promoter in the glomeruli of STZ-induced type 1 diabetic rats associated with p21 gene upregulation; HG-induced changes of active and repressive H3Kme, SET7/9 recruitment to p21 promoter in RMCs, and TGF- ad libitum. Protocols applied for all animal studies were approved by the Ethics Committee on the Care and Use of Laboratory Animals of the Second Hospital of Jilin University .Male Wistar rats (220 ± 20 g body weight) were obtained from the Experimental Animal Center of Jilin University. They were housed at 22°C with a 12/12 h light-dark cycle in a pathogen-free facility; water and rat standard diet were used to feed these ratsi.p.) injection of STZ , while the control animals received the same dosage of citrate buffer. The blood glucose level of rat tails was detected using One-Touch strip on day 7 after STZ injection, and rats with blood glucose concentrations above 16.7 mmol/L were considered as diabetic models (STZ group). STZ and control rats had free access to the standard dried chow diet and water for 8 weeks; at the end of the study, all rats were sacrificed and kidneys were collected for subsequent experiments.The blood glucose of all the rats was normal before the study. After being fed adaptively for 3 days, all the rats were divided into control group and streptozotocin (STZ) group; the type 1 diabetes model was fasted for 12 h and then received a single intraperitoneal  were performed with Wistar male rats (160–180 g) using a method published previously , accordiμg isolated RNA was used in reverse transcription using TaqMan Reverse Transcription Kit  according to the manufacturer's protocol. The synthesized cDNA (3 μL) was used in the quantitative real-time PCR (qPCR) amplification. The specific primers were synthesized from Invitrogen  as described previously [μL, with ABI 7300 real-time PCR thermal cycler. Dissociation curves were run to detect nonspecific amplification in order to make sure single product was amplified in each reaction. The relative level of mRNA was calculated after normalization to internal control β-actin gene using 2−ΔΔCt method.Total RNA was isolated from RMCs and glomeruli using TRIzol  according to the manufacturer's instructions. 2 eviously . QPCRs wμg) were subjected to 10% SDS-PAGE gels and transferred to PVDF membranes. After being blocked with 5% milk blocking buffer for 1 h at room temperature, membrane was incubated with primary antibody against p21  overnight at 4°C and then washed in Tris-buffered saline with Tween and reacted with secondary goat anti-rabbit IgG antibody for 1 h at room temperature. Proteins were detected using chemiluminescence reagents (Bio-Rad). The blots were stripped and then reprobed with a monoclonal antibody against β-actin  as an internal control. The density analysis of the immunoreactive bands was performed using ImagJ (NIH).Proteins were extracted from glomeruli samples and homogenized in RIPA buffer  with the mixture of protease and phosphatase inhibitors. Equal amounts of protein samples , glomeruli were isolated, and p21 gene expression was analyzed by RT-qPCR and western blot. p21 mRNA level increased significantly in the rat glomeruli of STZ group compared with the control group, whereas the housekeeping gene CypA showed no difference between these two groups . In accoWe then examined the H3K9me2/3 levels (epigenetic “repressive” marks) at the promoter of p21 using ChIP assays with anti-histone H3 dimethyl K9 and anti-H3 trimethyl K9 antibodies. ChIP-enriched DNA samples from glomeruli were measured by quantitative PCR (qPCR) with primer at the p21 promoter as described . The resTo determine whether levels of specific activating methylation of histone H3 lysine 4 (H3K4me) were changed in the glomeruli of type 1 diabetic rats, ChIP assays were performed with H3K4me1, H3K4me2, and H3K4me3 antibodies. The results indicated that H3K4me1 and H3K4me3 levels at the p21 promoter were markedly increased in STZ group compared with control group; the levels of H3K4me2 showed no significant changes between two groups . These iβ1-specific antibody or control mouse IgG (25 μg/mL) for 1 h and then treated with normal glucose plus mannitol  or HG (30 mM glucose) for 48 hours. We first observed p21 gene expression by RT-qPCR; p21 mRNA level was significantly higher in HG group compared with NG group; the change was significantly suppressed by TGF-β1-specific antibody but not the control IgG, and there were no significant changes of housekeeping gene CypA among these groups (β1-specific antibody rather than the IgG control pretreatment could reverse these changes, and there were no significant differences at the CypA promoter (β1-specific antibody.We next studied HG-induced p21 gene expression and repressive H3K9me2/3 marks in RMCs. Serum-depleted RMCs were first incubated with TGF-e groups . Then wepromoter . These rβ1-specific antibody. RMCs were treated as mentioned above; ChIP assays were followed with specific H3K4me1, H3K4me2, and H3K4me3 antibodies. As shown in β1-specific antibody could significantly reduce the HG-induced increases. In contrast, the levels of H3K4me at the CypA promoter showed no significant differences among all the groups. These results, accompanied with the effects seen in H3K9me2/3, further reflected the mediatory role of TGF-β1 in HG-induced epigenetic events at the p21 promoter and its subsequent expression. Blockade of these events may be a key mechanism for the antihypertrophic and renoprotective effects of the TGF-β1 antibody.We further examined whether HG could alter active H3K4me marks at the p21 promoter and whether it could be reversed by the TGF-β1-specific antibody, rather than control IgG, could significantly block the HG-induced enhancement in SET7/9 recruitment (β1 in diabetic MCs hypertrophy.To investigate the alterations of HMT SET7/9 in p21 gene expression, we first examined the SET7/9 recruitment of glomeruli in STZ-induced rats using ChIP assays with SET7/9 antibody. Results showed that SET7/9 recruitment was significantly increased at the p21 promoter in STZ group compared with control group, while there was no significant change at the CypA promoter . The SETruitment . SET7/9 β1, CTGF, IGF-1, or AGEs [β1 and HG could induce significant changes of H3K9 and H3K4 methylation levels in RMCs that correlated with parallel upregulation of profibrotic genes related to ECM accumulation [β1 could change histone lysine methylation levels at the p21 promoter, which was correlated with p21 gene upregulation in RMCs [It is widely accepted that p21 gene plays a key role in the glomerular cell hypertrophy associated with DN , 28, 29. or AGEs , 30–34,  or AGEs , 35, 36. or AGEs , 38, andmulation . p21 genmulation , 40. Onemulation . In addi in RMCs . However in vivo and in vitro; further results showed that TGF-β1-specific antibody could reverse HG-induced changes of both the histone lysine methylation and SET7/9 recruitment at p21 promoter, which correlated with the antibody-induced inhibition of p21 gene expression in RMCs.In the current study, we confirmed that p21 gene expression was upregulated in the glomeruli of type 1 diabetic rats and could be induced by HG in RMCs; then we found significant changes of histone lysine methylation, such as decreased H3K9me2/3 and increased H3K4me1/2/3 levels and enhanced HMT SET7/9 occupancy at the p21 gene promoter, which were closely correlated with p21 gene expression bothα-treated conditions, which were inversely correlated with upregulated expression of these inflammatory genes [β1 and HG stimulation decreased both H3K9me2 and H3K9me3 levels at ECM associated genes promoters in RMCs, which were inversely associated with upregulated expression of these genes including Col1α1, CTGF, and PAI-1 [β1-induced decreased H3K9me2 and H3K9me3 levels at p21 gene promoter led to increased p21 gene expression [ in vivo and in vitro. We observed a decrease of H3K9me2 level in the p21 gene promoter in the glomeruli of type 1 diabetic rats for the first time, and this inversely correlated with p21 gene upregulation; as for H3K9me3 levels, there were no differences between STZ and control groups, supporting the notion that the decrease of repressive H3K9me may partly contribute to increasing p21 gene expression in vivo.Generally speaking, H3K9me2 and H3K9me3 have been extensively recognized as repressive histone modification associated with gene expression , 26. A pry genes . Furtherpression . To funcβ1 could induce increased levels of active chromatin marks H3K4me1/2/3 in parallel with decreased levels of repressive marks H3K9me2/3 in ECM associated genes; promoters accompanied the changes in expression of the ECM associated genes [β1 could also increase H3K4me1/2/3 levels at the p21 gene promoter [Histone H3 lysine 4 methylation includes mono-, di-, and trimethylation enriched at enhancer, promoter, and other regulatory sequences, which are extensively associated with active genes expression , 42–44. ed genes ; our recpromoter ; all thePrevious evidence showed that HG treatment led to the increases of H3K4me1/2/3 marks and the decreases of H3K9me2/3 levels at ECM associated genes promoters, which were correlated with HG-induced profibrotic genes expressions . To furtβ1 stimulation [β1-induced upregulations of genes associated with fibrosis and hypertrophy relevant to chronic kidney diseases including DN. To further understand the changes of HMT SET7/9 in p21 gene upregulation under diabetic conditions, we investigated the SET7/9 recruitment at p21 gene promoter in the glomeruli of STZ-induced diabetic rats and RMCs exposed to HG; the following results showed that SET7/9 occupancy was increased at p21 promoter in parallel with H3K4me1 increases both in vivo and in vitro, suggesting that SET7/9-dependent H3K4me1 plays key role in p21 gene expression leading to cellular hypertrophy associated with DN.Several studies have demonstrated that both H3K4 HMT SET7/9 expression and SET7/9 recruitment at ECM associated genes promoters and p21 promoter were increased by TGF-mulation , 26, sugβ1 could lead to epigenetic changes such as H3Kme [β1-specific antibody had significant antihypertrophic effects and antifibrotic effects in both type 1 and type 2 diabetic animal models [β1-specific antibody could reverse HG-induced significant changes in HKme and HMT SET7/9 recruitment at ECM associated genes promoters [β1-specific antibody could significantly block the stimulatory effects of HG-induced H3K9/14Ac at the p21 promoter in RMCs [β1-specific antibody could reverse HG-induced significant changes in H3Kme and SET7/9 occupancy at the p21 promoter in RMCs. All the data implicated that TGF-β1 antibody could be an effective therapeutic agent for DN.Accumulating evidence showed that TGF-as H3Kme  and H3K9as H3Kme  in RMCs l models –47, as wl models , 49. A promoters . A recen in RMCs . Our curβ1-specific antibody could reverse HG-induced changes in vitro, all of which are related to the pathogenesis of DN, suggesting that HKme and SET7/9 could act as potential therapeutic targets for cellular hypertrophy of DN and TGF-β1-specific antibody could be clinical agent for DN therapy.In summary, our data demonstrated that H3K4me and H3K9me as well as HMT SET7/9 occupancy changed significantly at p21 gene promoter in the glomeruli of type 1 diabetic rats and HG-induced RMCs, resulting in parallel increases in the p21 gene expression related to cellular hypertrophy, and that TGF-


Drowning is the major cause of death in self-contained underwater breathing apparatus (SCUBA) diving. This study proposes an embedded system with a live and light-weight algorithm which detects the breathing of divers through the analysis of the intermediate pressure (IP) signal of the SCUBA regulator. A system composed mainly of two pressure sensors and a low-power microcontroller was designed and programmed to record the pressure sensors signals and provide alarms in absence of breathing. An algorithm was developed to analyze the signals and identify inhalation events of the diver. A waterproof case was built to accommodate the system and was tested up to a depth of 25 m in a pressure chamber. To validate the system in the real environment, a series of dives with two different types of workload requiring different ranges of breathing frequencies were planned. Eight professional SCUBA divers volunteered to dive with the system to collect their IP data in order to participate to validation trials. The subjects underwent two dives, each of 52 min on average and a maximum depth of 7 m. The algorithm was optimized for the collected dataset and proved a sensitivity of inhalation detection of 97.5% and a total number of 275 false positives (FP) over a total recording time of 13.9 h. The detection algorithm presents a maximum delay of 5.2 s and requires only 800 bytes of random-access memory (RAM). The results were compared against the analysis of video records of the dives by two blinded observers and proved a sensitivity of 97.6% on the data set. The design includes a buzzer to provide audible alarms to accompanying dive buddies which will be triggered in case of degraded health conditions such as near drowning (absence of breathing), hyperventilation (breathing frequency too high) and skip-breathing (breathing frequency too low) measured by the improper breathing frequency. The system also measures the IP at rest before the dive and indicates with flashing light-emitting diodes and audible alarm the regulator malfunctions due to high or low IP that may cause fatal accidents during the dive by preventing natural breathing. It is also planned to relay the alarm signal to underwater and surface rescue authorities by means of acoustic communication. SCUBA diving tourism has grown to become a multibillion dollar industry, drawing as many as 6 million active SCUBA divers worldwide . One of The U.S. Navy has identified breathing related problems that may lead to accidents, such as drowning, threatening the lives of SCUBA divers . It is rWhile there are numerous methods of pattern recognition and classification of time-varying signals applied widely to all fields of research in medicine, engineering or computer science ,18,19, tThis study introduces the design and validation of a simple and robust breathing detection method based on identification of the sudden pressure drops in the hose of the breathing regulator of the diver triggered by inhalation.Eight scuba divers, 7 males and 1 female, volunteered for this study. They were all professional divers. There were two divers with Advanced level certification, four with Dive Master and two with Instructor level. They averaged an experience of 1300 dives per diver, and 226 dives in the past year. The age averaged 30.5 years (standard deviation (SD) of 7.3 years), ranging from 23 to 46 years old. 5 were smokers and 4 practiced a physical activity regularly. All divers had an up-to-date medical fitness-to-dive certificate delivered by a diving medical specialist. No medical condition was declared. Of the 7 male subjects, the weight averaged 73.3 kg (SD: 8.7 kg) and the height averaged 176.7 cm (SD: 5.2 cm). Written informed consent was obtained from all participants after a full explanation of the aims and procedures.The central piece of equipment of a scuba is the regulator, which drops the compressed gas contained in the tank to a breatheable pressure for the diver. This regulator is built on two stages: a first stage drops the pressure from the tank generally rated to 200 bar to an IP and the second stage drops the IP to the ambient pressure (PB). In the modern regulators, the IP is set to an absolute pressure of A system enabling recording of IP and PB signals designed in a previous study  was usedThis system is plugged to the IP hose of the BC which is normally used to inflate the BC, to sense the IP. The system senses the ambient pressure of the air with its PB sensor at start up, which is later used to calculate the depth of the diver while underwater. It starts recording in memory the PB and IP signals as soon as the diver’s depth reaches 0.5 m. The record ends after 5 min have been spent at a depth shallower than 0.3 m. Specifications of the pressure sensors and recording resolution of IP and PB signals are given in A detection algorithm was designed to fit the following constraints: it should enable (1) a live detection of inhalation events with (2) a maximum delay of ten seconds and be (3) light-weight in order to be embedded in a non digital signal processing (DSP), ultra-low power microcontroller with a RAM limited to 6 kBytes for the algorithm and a processor frequency of maximum 25 MHz, such the MSP430F5529 or equivalent. The algorithm was designed to be light-weight in order to enable embedding it in not only a custom designed electronics, but also in common existing dive equipment electronics such as dive computers. Modern dive computers use power-efficient microcontrollers such as the MSP430F5529 to perform multiple dives with a single coin cell battery.The algorithm proposes to detect inhalation events by the diver and to report the time of each detected inhalation, which by extent corresponds to monitoring the breathing of the diver.This is to compensate the fact that the IP is 9.6 bar above the PB in scuba regulators, as it is illustrated in In the second step, the obtained signal is filtered with a first order, low-pass, Butterworth filter with a normalized cut-off frequency M samples of the obtained signal is analyzed, where M is a positive integer. The minimum and maximum pressures on this M-window are determined, and a M-window, M-window and In the third step, a window of the first n is the sample number in the analyzed signal and n is reported. The algorithm then moves the window by N samples forward , at the aquarium Florya of Istanbul, Turkey, during the period of 24 October to 25 November 2016. Two tanks were used for the experiment. Tank 1 has a water temperature of 21.5 °C, a maximum depth of 7 m and hosts various species of sharks, leerfish, epinephelus marginatus, temperate basses, rays and other various marine life. Tank 2 has a temperature of 18 °C and a maximum depth of 6 m. Tank 2 hosts two banded breams, catfish, and gilt-head breams. The aquarium requires 13 dives per week for the maintenance of these tanks, involving sand and window cleaning.Each subject was equipped with a scuba diving dry suit for thermal isolation. They equipped the recording system above their left arm, plugged between the first stage regulator hose and the BC connector which is the jacket enabling divers to balance their buoyancy underwater. Each participant was also equipped with a recording video camera fixed near their right shoulder prior to each test. Each dive lasted between 49 and 69 min, and were performed at a maximum depth of 6.8 m. All tests were followed and data collected by one blinded observer who was not aware of the results obtained during the tests. The data was analyzed and inhalation events counted by another blinded observer, after all dives were performed and all data collected.The first of the two dives involved the tasks of cleaning the glass of the aquarium. This was reported before the start of the experiment as a task demanding physical effort and constant movement. On the second dive, the subjects performed the siphoning of the sand in the aquarium, which consists in cleaning the sand. This activity was reported before the start of the experiment as less demanding physically and requiring less movement.Participants were instructed to perform their work activities as usual. The assignment of the tank for the dive was not chosen by the experiment. The divers were instructed to follow at all times the safety protocol they were trained to, and to abandon the test should any equipment fail and cause to threaten their safety.The camera started recording prior to the descent in the water and was stopped after the diver reached the surface at the end of the dive. The video record was backed up in a PC after the dive. The PB and IP recording system was started prior to the descent in the water. The system was configured to start recording PB and IP signals as soon as the diver’s depth reaches 0.5 m or deeper. The system stopped the record after 5 min have been spent on the surface. The data were backed up to a PC after the dive.All analyses were performed with the numerical computing software Matlab 2015a for Windows . Each inhalation event in the collected IP signals was manually marked by a blinded observer by analyzing only the graph of the unfiltered IP signal. The inhalation detection algorithm was implemented in Matlab scripts and true positives (TP), FP and false negatives (FN) events were counted for each recorded dive. Similarly to spike detection in EEG signal analysis described in , it is un in the IP signal. It is considered a TP if a manually marked event is present within the range Each inhalation event detected by the algorithm is marked by its sample number R is defined as:The total sensitivity was computed for the whole dataset as:R than the sensitivity of the algorithm, as the end goal was to detect when the diver is not breathing, defining a case of emergency. A high ratio R expresses an algorithm with many FP, meaning that an inhalation event might be detected when there is actually none, which by extension may lead to believe the diver is breathing when he actually isn’t.An optimization criteria was defined asM and N had little influence on the global performance of the algorithm, as shown in An initial study has shown that The constants of the algorithm Two operators were given the video records of the dives and were instructed to mark down the time of each inhalation based on the sound and, when available, the vision of the diver’s face and bubbles, using the software SubtitleEdit . They marked down the 10 first min of each dive. The operators were blinded observers with no access to the PB and IP data recorded by the system, and no access to one another’s analysis.The vectors of events marked by the observer 2 were compared to the marked event vectors of observer 1 in order to evaluate the reproducibility of the marking process. The criteria of performance used for this comparison was the same as the criteria used to evaluate the performance of the algorithm: an event marked by observer 1 is considered a TP if an event marked by observer 2 is present within the range For each dive, the events marked by the blinded observers were then synchronized with the recording system’s detected event vectors. The video camera started the video recording before the start of a dive, a time offset was applied to the vectors of the event marked by the blinded observers. For each dive, the same synchronization time offset was applied to the two observers’ vectors. The PB and IP recording system’s time base running slightly faster than the video camera device’s, probably due to a time calibration insufficiently accurate for both devices, time difference was compensated for in the Matlab scripts.Finally, the events marked by the detection algorithm were compared to the events marked by observer 1 and 2, and the performance of the algorithm evaluated with the same criteria as above.A total of 16 dives were recorded and analyzed, totalling 13.9 h and 11081 marked inhalation events. N of 100 samples (5 s) and a maximum delay of the Butterworth filter of 4 samples (0.2 s) as shown in Optimization of the algorithm parameters based on the collected data and the marked events has given a solution:In order to execute the algorithm while embedded in a microcontroller, at least R for each dive. The arithmetic mean sensitivity, time-mean sensitivity, the total sensitivity and the time-event weight sensitivity (as defined in [fined in ) are allR of 2.4% for the data of observer 2 against observer 1, and a sensitivity of 94.5% and ratio R of 5.7% for the data of observer 1 against observer 2.The vectors of events marked by the observers based on the camera video recordings were compared to one another to evaluate the reproducibility of the process of identification of breathing events by analysis of the video recordings alone. The results are displayed in Synchronization of the vectors marked by the video observers with the vector of detected events by the algorithm being a tedious task, only one dive, dive 16, was synchronized and compared to the results of the algorithm. Over the 10.4 min of dive analyzed, the algorithm presented a sensitivity of 99.0% and a ratio R of 20.4% against the analysis of observer 1, and a sensitivity of 99.0% and a ratio R of 21.6% against the analysis of observer 2.In this study, the IP of the regulator of scuba divers and the PB signals were acquired in real diving conditions and an inhalation live-detection algorithm using these signals was designed and implemented with Matlab. The algorithm’s variables were optimized to obtain a high sensitivity and a low number of FP based on the collected dataset. On the dataset, the sensitivity of the algorithm was 97.5% and the total number of FP was 275 for 13.9 h of recording. The algorithm is expected to use 800 bytes of RAM and to present a maximum delay of 5.2 s.To the best of our knowledge, this study is unique by using the IP signal to monitor the breathing of the scuba diver.The initial requirement that the algorithm must be executed on a low-power microcontroller with a maximum frequency of 25 MHz remains untested. Any estimation of execution cycles and time will be too approximate to quantify, and will depend partly on the compiler’s optimization. However, since the global operation of the algorithm remains simple and involving integers, it is expected that it should execute under a second to analyze a full window. The low-pass filter, involving floating point calculation, is expected to be the longest step of the algorithm to execute. Another potential issue is that the environment running on the microcontroller is not multi-threading, which may make the implementation delicate. The risk being that during the analysis of the acquired signal, no more sensor data may be acquired until the analysis has ended.Sources of error that may have haltered the results have been identified. (1) Human error during the manual marking of the inhalation events may be the most significant. Since a large number of events have been marked manually, it is a reasonable assumption that a certain proportion of the events have been skipped, marked twice or mistakenly marked. It must be noted that verifications have been applied to remove events marked twice, but these verifications have limitations on their own; (2) The BC is an indispensable piece of equipment of the scuba diver, enabling balancing buoyancy underwater. Air is injected into the BC from the IP line. When injecting air into the BC, the IP is altered in a very similar manner to the diver’s inhalation event. It is often difficult to separate BC inflation from inhalation when manually marking the inhalation events.Although the developed algorithm aims at being applicable to all scuba diving activities, this study has limitations: (1) all subjects were experimented scuba divers. It is a possibility that the breathing habits of inexperienced divers are different and affect the IP signal, and therefore affect the global performance of the algorithm; (2) All dives were performed with a maximum depth of 7 m, while the device was designed to perform up to 100 m. It is again a possibility that the IP signal is altered in deeper dives, affecting the algorithm’s performance.Although it was shown that validation through video observation for identification of inhalation events was a reproducible process, the algorithm was compared to only one dive. Additionally, the act of synchronizing the video marked events with the algorithm’s detected event ensures one biased TP as the first event and one TP as the last event.While a remote passive or active acoustic monitoring of scuba divers solution presents the advantage of requiring no device be embedded on the SCUBA divers, there has been no study on the sensitivity of such system applied to a group of divers and the effects on non-breathing event detection mechanism. It should be expected that the system, while able to detect the presence and location of the group of divers, may be unable to isolate each diver’s breathing sound to identify a non-breathing event, as the sound of the other divers would cover the event. It is therefore required that a device such as the system presented in this study be embedded on the diver’s equipment.The system and algorithm presented in this study are a technology which aims at being implemented in existing or larger systems, such as dive computers. It only requires two pressure sensors  and a microprocessor. The light-weight algorithm makes it easy to implement in various systems.Additionally, the system can be used as a method of continuous monitoring of the scuba first stage regulator performance. Indeed, the IP is expected to be about 9.6 bar above the PB . A higher IP may cause the second stage of the regulator to not withstand the excessive pressure and let gas flow out. This is called free flow, and may cause the tank to empty very quickly while the diver is underwater, leading to shortage of breathable gas. On the other hand, a lower IP may require additional effort from the diver to inhale, causing extra fatigue and increasing the risk of decompression sickness. In the worst case, the low IP will make it impossible to inhale breathable gas from the second stage regulator. The presence of the PB and IP sensors in the systems enables a continuous monitoring of the IP relatively to PB, which should enable early detection of the regulator going out of specification range which could potentially cause a dive accident.From the detection of inhalation events can be deduced the respiratory rate, which can be used to identify novice’s irregular breathing, hyperventilation and skip-breathing, helping prevention of breathing related dive accidents.Traditional communication methods used on surface such as radio frequency (RF) must be adjusted when applied to the underwater, due to the physical properties of the medium . OpticalThe technique described in this study is subject to a Turkish patent application .The system and the algorithm presented in this study have demonstrated they enable a new method of continuous monitoring of the breathing of a scuba diver in activity underwater. The algorithm has shown a global sensitivity as high as 97.5% and a low number of 275 false positive inhalation events detected against the 11081 marked inhalation events. It has been determined that such algorithm requires only 800 bytes of RAM to execute, leaving a tiny footprint to even the smallest modern, non-DSP microprocessors and microcontrollers.Our next aims are to implement and embed the algorithm in the MSP430F5529 microcontroller of the recording system in order to confirm the performance of the solution proposed in this study. A protocol shall be established, similar to the present study, to quantify the sensitivity and number of FP of the recording system with the embedded algorithm.


As an important coexistence technology, channel hopping can reduce the interference among Wireless Body Area Networks (WBANs). However, it simultaneously brings some issues, such as energy waste, long latency and communication interruptions, etc. In this paper, we propose an enhanced channel hopping mechanism that allows multiple WBANs coexisted in the same channel. In order to evaluate the coexistence performance, some critical metrics are designed to reflect the possibility of channel conflict. Furthermore, by taking the queuing and non-queuing behaviors into consideration, we present a set of analysis approaches to evaluate the coexistence capability. On the one hand, we present both service-dependent and service-independent analysis models to estimate the number of coexisting WBANs. On the other hand, based on the uniform distribution assumption and the additive property of Possion-stream, we put forward two approximate methods to compute the number of occupied channels. Extensive simulation results demonstrate that our estimation approaches can provide an effective solution for coexistence capability estimation. Moreover, the enhanced channel hopping mechanism can significantly improve the coexistence capability and support a larger arrival rate of WBANs. Biomedical sensors, motion sensors, and other wearable devices are usually deployed on, near, or in human bodies to monitor vital signals  or non-medical signals . These wearable devices networking together forms Wireless Body Area Networks (WBANs), which are the most promising technologies in many rising and interesting applications, such as remote health care, sports, and entertainment ,2,3,4,5.Channel hopping is a trivial solution but substantially rewards coexistence resolution . In IEEEHowever, channel hopping suffers from several issues, such as energy waste, long latency and communication interruptions in WBANs. It is more challenging for switching channels in WBANs than in traditional ad hoc networks, because WBAN nodes share the same mobility pattern with the human body and more communicating node-pairs are coupled together in each channel switching operation . George The minimization of channel conflict probability is challenged by limited channel resources. Only 10 channels are specified from 402 to 405 MHz band in IEEE 802.15.6. In some dense crowds , number of channels is very limited to enabling the communications among sensor nodes, which may result in channel conflict. Fortunately, multiple WBANs can also be allocated to the same channel by beacon shifting , active This paper extends the channel hopping mechanism to be more general. Multiple WBANs are allowed to be allocated to the same channel by employing other coexistence technologies. Because these technologies are all operating in single channel, we call them Channel-shared Coexistence Technologies. Different from channel hopping studies in traditional ad hoc networks  and our An enhanced channel hopping mechanism is proposed. We extend the channel hopping techniques to be more general and multiple WBANs are allowed to be allocated to the same channel. With limited coexistence capacity extension, coexistence capability is substantially improved.A comprehensive coexistence capability analysis construction is provided. The conflict possibility of coexisting WBANs is described by a risk parameter and the coexistence behavior is modeled as a birth-and-death process. Both queuing and non-queuing behaviors are taken into account in our analysis.Two approximate methods are illustrated to estimate the coexistence capability of the enhanced channel hopping mechanism. Numerous simulation comparisons are implemented to evaluate the availability and precision of our methods.This paper investigates the coexistence capability in the view of channel conflict probability estimation, which is a macroscopic analysis based on resource allocations and could be adopted by basic channel hopping mechanisms for the performance enhancement. The studies are also suitable for active superframe interleaving, TDMA, etc., and can be applied to many other resource block allocation methods. The contributions of this paper are described as follows:The remainder of this paper is organized as follows: The coexistence technologies overview and detailed motivation of the integration between channel hopping and channel-shared coexistence technologies are presented in In this section, we firstly illustrate the coexistence technologies comprehensively, including IEEE 802.15.6 coexistence strategies and some other channel-shared coexistence technologies; Then we discuss the opportunity of channel hopping coexistence capability extension.Beacon shifting, channel hopping, and active superframe interleaving are three common techniques employed to solve coexistence problems . SeveralB2IRS , the hubBeacon shifting and channel hopping provide mobility support for more WBANs applications. When beacon shifting is available, beacons will be transmitted at different time offsets relative to the start of the beacon periods. A beacon shifting sequence not used by its neighbor hubs is chosen to mitigate potential repeated beacon collisions and scheduled allocation conflicts between overlapping or adjacent WBANs operating in the same channel. Seungku Kim et al., presented a distributed TDMA-based interval shifting scheme to avoid the wakeup of each WBAN coinciding with other networks by employing carrier sensing before a beacon transmission . A tradeDiffered from beacon shifting, channel hopping supports more WBANs coexistence (at least 10 WBANs) and is available with all narrow band frequencies specified in IEEE 802.15.6, P.S., Beacon shifting is not applicable when given Listen Before Talk (LBT) restrictions at 402 to 405 MHz band. Muhammad Mahtab Alam et al., compared channel hopping approach with time shared scheme in their work . They fobustness . HoweverConsequently, channel hopping brings substantial coexistence improvement for WBANs. However, the operation of channel hopping usually leads to resources consumption, long latency, communication interruptions, etc. The frequency of channel hopping plays a significant role in the performance of the coexisting WBANs and the channel conflict probability really needs a comprehensive estimation.Besides beacon shifting and active superframe interleaving, there are numerous technologies focusing on multi-WBAN coexistence at the same channel, such as CSMA, TDMA, etc. As two common MAC protocols, CSMA and TDMA are usually employed to avoid collisions and mitigate interferences. CSMA has a natural coexistence capable  . WBANs aNevertheless, integrating channel-shared coexistence technology will provide an attractive motivation to exploit the coexistence capability of channel hopping mechanism, which will bring more realistic benefits on coexisting WBANs.As described in o et al.  achievedIn some hybrid coexistence techniques, channel hopping is employed as an assisted mechanism . IEEE 80Static (S)-a single WBAN in a residential environment or a hospital with a single patient node and a fixed bedside hub;Semi-dynamic (SD)-slowly moving ambulatory patients in an elder care facility requiring infrequent and/or event-based low-rate data transfers;Dynamic (D)-fast moving ambulatory patients in a hospital with a large number of WBANS collecting continuous data traffic from many sensor nodes.Integrating channel hopping and other coexistence technologies provides a potential coexistence capability improvement. Therefore, it is meaningful to ascertain the maximum number of WBANs that a single channel can support. Buddhika de Silva et al., have provided the experiment of packet drop rate (PDR) performance versus the number of WBANs and transmission rate . When thled mode . When moled mode , authorsAs mentioned above, the frequency of channel hopping plays a significant role in the performance of the coexisting WBANs and how to design an enhanced channel hopping mechanism so as to exploit the coexistence capability effectively will bring more realistic benefits on coexisting WBANs. Still, there is no coexistence capability quantification work for channel hopping and estimating the probability of channel conflicts becomes a critical issue in coexisting WBANs.CC = m can be signed as m-tolerated channel conflict model. As analyzed in m = 1, 2, 3, 4, 5, 6. Coexistence capacity provides a normalized formulation for channel hopping mechanisms, which benefits the coexistence capability analysis of these common channel hopping mechanisms.This paper investigates two types of channel structures for channel hopping mechanisms. Take 10 channels for instance, Channel hopping mechanisms are usually taking place when WBANs detect a coexistence conflict. There are many different channel hopping regulations, e.g., choosing a new channel randomly or orderly, centralized or distributed implementation, event or time driven, etc. As mentioned in λ, and the service time is assumed to follow negative exponential distribution. Two classical behaviors  are taken into account in our coexistence analysis. For the first one, we suppose the coexisting WBANs environment to be one supplier of service, e.g., visiting a famous signature, buying tickets in a lobby, etc., in which customers queue up for service on first-come-first-served (FCFS) basis. We call this type of system Service-dependent coexisting WBANs, as shown in This paper considers coexistence behavior as a birth-and-death process, as shown in Channel hopping is an important coexistence technology, but brings serious shortcomings. Extension of channel coexistence capacity makes it a paradigm for coexistence resolution in WBANs. Integrating channel hopping and other coexistence techniques achieves obvious frequency reduction of channel switching and provides a new avenue in coexisting WBANs.m-tolerated channel conflict model. There is no doubt that enhanced channel hopping mechanism complicates the channel conflict analysis. In 1-tolerated channel conflict model, the number of busy channels is equivalent to the number of WBANs, and classical M/M/1 and M/M/c queuing models are suitable as basics for estimating the number of coexisting WBANs; while, for the m-tolerated channel conflict model, because the interfering WBAN joins in each channel randomly, the number of coexisting WBANs does not equal the number of busy channels any more, which fails the estimation methods based on M/M/1 or M/M/c queuing models.This paper provides an enhanced channel hopping mechanism, which aims at extending the application of channel hopping technique from 1-tolerated channel conflict model to This section presents the detailed description of enhanced channel hopping mechanism and provides the analysis construction of coexistence capability. As shown in i-th channel, n denotes the number of channels. Let m be the coexistence capacity, and let ι be the channel index of the next interfering WBAN. Once the interfering WBAN detects that the ι-th channel is conflicted, a channel hopping sequence generator signed as The joining process pseudocode of enhanced channel hopping mechanism is shown in Algorithm 1. We take vector Algorithm 1 Joining process of enhanced channel hopping mechanismInput: Interfering WBAN channel index ι, coexistence capacity m, number of channels n, occupied channels map Output: occupied channels map 1:ifthen2:ifthen 3:join in the coexisting WBANs  4:else 5:j← invoke ;  6:hop to the j-th channel;  7:endif 8:else9:refuse to join in the coexisting WBANs; 10:endif11:The analysis construction of coexistence capability is composed of parameters and metrics which reflects the features and performances of coexisting WBANs system, respectively. Firstly, we provide a parameter to illustrate the channel conflict possibility when an interfering WBANs walks towards the coexisting WBANs environment, refer to Definition 1.Definition 1.For coexisting WBANs system with n channels specified, if κ channels are occupied/busy , meanwhile the channel indexes of interfering WBANs are independent identically distributed, the channel conflict probability between the arriving interfering WBAN and coexisting WBANs is κ/n. Once the channel conflict occurs, the following channel hopping operation for interfering WBAN is inevitable. The channel conflict probability here is said to be Risk Parameter. On the contrary, (n-κ)/n is called Safety Parameter, which means that the interfering WBAN does not need to switch its channel and just joins the existing WBANs directly.N is the maximum index of coexisting state. Let To build a general analysis model, we set X as the coexisting state space directly is to reserve the scalability for more complex queuing. For instance, the arriving customer sometimes is not single but group of WBANs and the Coexisting-WBAN Parameters here are not consecutive integers any more. As described in X is equal to k in S. Comparing with Risk Parameter which reflects the instantaneous conflict probability of interfering WBAN, the properties of coexisting WBANs system are more significant. Sign i-th state in steady state. The equilibrium equations areHere, the reason why we do not employ According to the probabilistic characteristics, we get Equation .S. Accordingly, we define the duration of each state as State Period and define the probability of each state as State Rate.From Equations  and 2),,2), we cDefinition 2.For coexisting WBANs system, the probability of each state in i-th state is signed as State Period reflects the stability of coexisting WBANs. The State Period of the Definition 3.In coexisting WBANs system, the expectation of Risk Parameter is called Coexisting Risk, which represents the average channel hopping frequency in the coexisting WBANs system. Coexisting Risk is signed as RDefinition 4.In coexisting WBANs system, the variance of Risk Parameter is called Risk Variance, which represents the amplitude of channel hopping frequency. Risk Variance is signed as DIn coexisting WBANs system, there is a significant case that all the channels are occupied, leading to certainty channel conflict. We present Definition 5.Definition 5.As shown in N-th state.The reason why we give Saturation-series definitions individually is to prevent the confusions when sensor nodes in a WBAN are allowed to be allocated to different channels. There is a different situation that the coexisting WBANs system can hold no more WBANs, but the channels are still unsaturated and more sensor nodes are allowed to be allocated to these channels. As described in Coexistence Saturation Period and Coexistence Saturation Rate are significant metrics of coexisting WBANs. While there is another significant metric of interfering WBAN, referred to Definition 6.Definition 6.In coexisting WBANs system, the duration that the interfering WBAN occupies the channel is called Interfering Period.Similarly, to investigate the individual channel usage situation, we present Channel Busy State, Channel Busy Period and Channel Busy Rate, referred to Definition 7.Definition 7.In coexisting WBANs system, the state that the channel can not hold another WBAN is called Channel Busy State and the duration of Channel Busy State is called Channel Busy Period. Furthermore, the probability Channel Busy State is called Channel Busy Rate.Furthermore, when investigating the usage of channels, we provide Definition 8 and Theorem 1.Definition 8.In coexisting WBANs system, the ratio between occupied channels and specified channels is called Channel Utilization.Theorem 1.For coexisting WBANs system, Channel Utilization is equal to the average of Channel Busy Rate.Proof. i-th channel. Due to the assumption that all channels are identical as described in k busy channels. Because the channel allocation of interfering WBANs is independent identically distributed, the probability that the i-th channel is busy when there are k busy channels equals i-th channel isLet The average number of busy channels isSo the Channel Utilization isTherefore, With definitions above we provided, the basic coexistence capability analysis construction is established for enhanced channel hopping mechanism. We can illustrate coexistence capability estimations for several classical coexisting WBANs.1-tolerated channel conflict model and m-tolerated channel conflict model.This section illustrates the coexistence capability analysis for enhanced channel hopping mechanism under both In this part, we firstly discuss the basic property and theorems of 1-tolerated channel conflict model. Then we analyze the coexistence capability of the enhanced channel hopping mechanism taking into account queuing behaviors in Service-dependent coexisting WBANs and non-queuing behaviors in Service-independent coexisting WBANs, respectively. For the first one, we provide a Service-dependent analysis model. For the second one, we provide a Service-independent analysis model.A basic property should be taken into account before we investigate the coexistence capability of the enhanced channel hopping mechanism under 1-tolerated channel conflict model, referred to Property 1.Property 1.In coexisting WBANs system under 1-tolerated channel conflict model, there is one-to-one correspondence between interfering WBANs and channels.Theorem 2.In coexisting WBANs system under 1-tolerated channel conflict model, Interfering Period is equal to Channel Busy Period.Proof. Under 1-tolerated channel conflict model, each interfering WBAN joins in the coexisting WBANs. If permitted, it will occupy a channel, and the channel turns to busy until the interfering WBAN leaves. So the Interfering Period is equal to Channel Busy Period, which proves Theorem 2. ☐k. Because m = 1 is the coexistence capacity of each channel, the maximum state index N is equal to n. Therefore, According to the queuing model assumption illustrated in Theorem 3.X and Busy-channel Parameter Y have the same state space and probability distribution.In coexisting WBANs under 1-tolerated channel conflict model, Coexisting-WBAN Parameter Proof. X and Y have the same state space. According to  have the same probability distribution with S. Therefore, X and Y also have the same probability distribution, as required. ☐According to Property 1, for any X and Y assumption here is that we can employ c equals 1. While in the Service-independent analysis model, c equals the channel coexistence capacity m.The advantage of ∞-based queuing system model.As mentioned above, when taking into account queuing behavior, the Service-dependent coexisting WBANs (as shown in quations  and 9)))λk and sTherefore, the state transition diagram can be illustrated as The equilibrium equations areWe set k busy channels is equal to the state probability According to Theorem 3, the probability that there are Lemma 1.The Saturation Rate in Service-dependent coexisting WBANs is Proof. According to Definition 5 and Equation , the satAccording to the general analysis model and Definition 5 presented in Lemma 2.The average of Saturation Period in Service-dependent coexisting WBANs is Proof. N is μ. So the average of Saturation Period is According to the memoryless property of negative exponential distribution, the duration before the coming event occurrence also follows negative exponential distribution with the same parameter. In Service-dependent coexisting WBANs, the service rate of state Lemma 3.The Coexisting Risk in Service-dependent coexisting WBANs is Proof. According to Definition 3, Coexisting Risk isLemma 4.The Risk Variance in Service-dependent coexisting WBANs isProof. According to Definition 4, Risk Variance isLemma 5.The Channel Utilization and the average of Channel Busy Rate in Service-dependent coexisting WBANs are Proof. The expected value of queue length isBecause there is a one-to-one correspondence property between a WBAN and the channel in which it joins under 1-tolerated channel conflict model. The queue length represents the number of busy channels. According to Definition 8 and Theorem 1, the Channel Utilization and Channel Busy Rate areLemma 6.The average of Interfering Period and the average of Channel Busy Period are equal toProof. According to Little Law in Queuing Theory, the residence time of the consumer is As Channel Busy Period equals Interfering Period under 1-tolerated channel conflict model according to Theorem 2, Lemma 6 is proven. ☐Different from Service-dependent coexisting WBANs, the interfering WBANs leave the coexisting WBANs without any queuing constraint in Service-independent coexisting WBANs as shown in Then the state transition diagram can be illustrated as The equilibrium equations areSo Lemma 7.The Saturation Rate, Coexistence Saturation Rate and Channel Saturation Rate in Service-independent coexisting WBANs are all equal to Proof. According to Definition 5 and Equation , the CoeSimilar to Lemma 1, because Saturation State, Coexistence Saturation State and Channel Saturation State are assumed to be equivalent, the Coexistence Saturation Rate and Channel Saturation Rate are also equal to Lemma 8.The average of Saturation Period, the average of Coexistence Saturation Period and the average of Channel Saturation Period in Service-independent coexisting WBANs are all equal to Proof. N is Similar to the proof in Lemma 2, according to the memoryless property of negative exponential distribution, the duration between the arriving and leaving events follows negative exponential distribution. In Service-independent coexisting WBANs, the leaving rate of state Lemma 9.The Coexisting Risk in Service-independent coexisting WBANs is Proof. According to Definition 3, Coexisting Risk isLemma 10.The Risk Variance in Service-independent coexisting WBANs isProof. According to Definition 4, Risk Variance isLemma 11.The Channel Utilization and Channel Busy Rate in Service-independent coexisting WBANs are Proof. The expected value of queue length isAccording to Definition 8 and Theorem 1, the Channel Utilization and the average of Channel Busy Rate areLemma 12.The average of Interfering Period and the average of Channel Busy Period in Service-independent coexisting WBANs are Proof. As there is no queuing waiting in Service-independent coexisting WBANs, we can simply consider service time As analyzed above, a set of important metrics are provided for coexistence capability estimation under 1-tolerated channel conflict model.Y under m-tolerated channel conflict model not only depends on the number of interfering WBANs, but also depends on the distribution of channel allocation. It is hard to provide a theoretical solution for Busy-channel Parameter probability distribution estimation under m-tolerated channel conflict models. This paper presents two approximate methods to estimate the Busy-channel Parameter. The first one is based on a basic assumption that channel allocations of interfering WBANs are randomly and follow uniform distribution. The second one is based on the additive property of Possion stream that a Possion stream can be divided into multiple Possion substreams. As analyzed in m-tolerated channel conflict model. Therefore, this part does not represent the estimation procedure of Coexisting-WBAN Parameter in the first approximate method. While in the second approximate method, Coexisting-WBAN Parameter is not respected.Different from 1-tolerated channel conflict model, under which Coexisting-WBAN Parameter and Busy-channel Parameter have the same state space and probability distribution, the Busy-channel Parameter m > 1, the maximum coexisting state i busy channels when k WBANs are in the coexisting system. The Busy-channel Parameter distributions of each This part still supposes that the Coexisting-WBAN Parameter The value interval of As The state transition diagram can be illustrated as Assuming that the channel allocation is following uniform distribution, we employ a channel occupied bit map as shown in k WBANs in a m × n coexisting system. We employ the recursive function We sign Then we can get Further, we can obtain the global Busy-channel Parameter distribution, written asAccordingly, the Risk Parameter is written as The Risk Variance ism-tolerated channel conflict model by taking into account queuing and non-queuing behaviors, respectively.Similar to According to Theorem 1, the Channel Busy Rate and Channel Utilization in both Service-dependent coexisting WBANs and Service-independent coexisting WBANs can be written asFrom the global Busy-channel Parameter distribution m-tolerated channel conflict model are equal to their Saturate Rate, as well as that under 1-tolerated channel conflict model. According to Lemma 1, the Coexistence Saturation Rate and Channel Saturation Rate in Service-dependent coexisting WBANs and Service-independent coexisting WBANs are written as Equations (According to the queuing model assumption illustrated in quations  and 36)m-toleratAccording to Lemmas 2 and 8, the average of Saturation Period, the average of Coexistence Saturation Period and the average of Channel Saturation Period in Service-dependent coexisting WBANs and Service-independent coexisting WBANs all are equal to According to Lemma 6, the average Interfering Period in Service-dependent coexisting WBANs and Service-independent coexisting WBANs are equal to Equation  and 1μ, Consequently, we can obtain the key parameters and metrics of coexistence capability from this approximate method.This part provides another coexistence capability approximate method. We notice that there is a special additive property of Possion stream, refer to Property 2. Different from the estimation methods we provided in Property 2.n independent Possion substreams with parameters A Possion stream with λ=Lemma 13.A variable Ω n variables which follows negative exponential distribution with parameter μ can be divided into Proof. μ, the duration of each neighboring events is following negative exponential distribution with parameter μ. According to Lemma 2, the Possion stream can be divided into n substream with parameters Assuming that the occurrence times of event A within unit time are following Possion distribution with parameter n Possion substreams with μ.According to Property 2, the Possion stream can be divided into The state transition diagram can be illustrated as As each channel can be considered as an individual coexisting system, the probability that the channel is busy equals the Coexistence Saturation Rate of Ck. According to Lemmas 1 and 7 and Theorem 1, the Channel Busy Rate and Channel Utilization in Service-dependent coexisting WBANs and Service-independent coexisting WBANs are Equations  and 39)39), respThus the probability that there are quations  and 41)n1 busy cThe Coexistence Saturation Rate in Service- dependent coexisting WBANs and Service-independent coexisting WBANs are approximate to Equations  and 43)43), respAccording to Definition 3, the Coexisting Risk in Service-dependent coexisting WBANs and Service-independent coexisting WBANs are approximate to Equations  and 45)45), respAccording to Definition 4, the Risk Variance in Service-dependent coexisting WBANs and Service-independent coexisting WBANs are approximate to Equations  and 47)47), respAccording to Lemmas 6 and 13, the average of Channel Busy Period in Service-dependent coexisting WBANs ism-tolerated channel conflict model, most significant parameters and metrics can be easily achieved by our approximate methods.Consequently, parameters and metrics of coexistence capability in both Service-dependent and Service-independent coexisting WBANs could be obtained through our analysis. For This section provides extensive simulation results to verify our mechanism and coexistence capability analysis models. Firstly, the coexistence capability parameters evaluations are presented, including Coexisting-WBAN Parameter and Busy-channel Parameter. Then coexistence capability metrics are evaluated, such as Coexisting Risk, Risk Variance, Channel Saturation Rate and Interfering Period. At last, channel conflict times in each time unit are employed to reflect the coexistence performance of channel hopping mechanism. Both Service-dependent and Service-independent coexistence models are taken into account in our simulations.The parameters in our simulations are illustrated in In this part, we investigate the probability distribution of Coexisting-WBAN/Busy-channel Parameter under 1-tolerated channel conflict model and investigate the probability distribution of Busy-channel Parameter under m-tolerated channel conflict model. In our simulation, we employ the ratio between the total period of each state and the whole simulation period as Period Rate, and employ the ratio between the times of each state appears and the total state transition times as Frequency Rate.In 1-tolerated channel conflict model, the Coexisting-WBAN Parameter and Busy-channel Parameter are equivalent, as illustrated in Theorem 3.λ within the interval . We set the step to be 3, so λ, the probability of state 0 decreases obviously. As the duration between state 0 and the next WBAN arrival declines, the Period Rate and Frequency Rate appear closer. On the contrary, the probabilities of large Coexisting-WBAN/Busy-channel Parameters increase obviously along with the arriving rate λ, which means that the interfering WBAN has a higher victim probability.Firstly, because the coexistence capability in Service-dependent coexisting WBANs are weak, we investigate the influence of different arriving rates λ, we investigate the influence of arriving rate λ within the interval , and the step is set to be 20, i.e., λ, the distributions of state probability, Frequency Rate and Period Rate become more decentralized and the center shaft of them moves to the right, which also means that the interfering WBAN has a high probability to be conflicted.Secondly, because the coexistence capability in Service-independent coexisting WBANs is stronger than Service-dependent coexisting WBANs and can support higher arriving rate Comparing m-tolerated channel conflict model, it is hard to provide theoretical solution for coexistence capability estimation. We present two approximated solutions based on our estimation methods. To simplify our description, the approximate method based on uniform distribution assumption is called Approximate Method I, and the estimation results of Approximate Method I is called Approximate Value I, abbreviated as Approx. Value I. Similarly, approximate method based on additive property of Possion-stream is called Approximate Method II, and the estimation results of Approximate Method II is called Approximate Value II, abbreviated as Approx. Value II.In m = 3 for instance to investigate the Busy-channel Parameter probability distribution. Even the channel capacity is extended, we still investigate the same interval of parameter λ as 1-tolerated channel conflict model when considering queuing behavior, i.e., λ from 105 to 405, and the step is increased to 80 when considering non-queuing behavior, i.e., We take coexistence capacity λ have weaken the effect of state 0, as well as the diversity of leaving rate According to the simulation results discussed in Comparing λ simulation interval to 31 in Service-dependent coexisting WBANs and to 485 in Service-independent coexisting WBANs. As analyzed in In this part, we investigate the high-level coexistence capability metrics including Coexisting Risk, Risk Variance, Saturation Rate, Interfering Period. We aim at investigating the influence of the channel coexistence capacity variation. From single WBAN supported to multiple WBANs supported, we increase the channel coexistence capacity from 1 to 6, i.e., λ, the approximate values of Coexisting Risk based on Approximate Method II are also improved. The correctness of our theory is also verified in Service-independent coexisting WBANs, refer to λ is large. This is because the channel is easier to be occupied in this scenario and the drawback of inaction with the following operations is exposed. Along with the increase of coexistence capacity and λ, the evaluation accuracy of Approximate Method I gets worse. This is because the rationality of equal probability distribution assumption for channel allocation is decreased, which is not reflected when only coexistence capacities 1 and 3 is investigated in λ. According to the subfigures (2–6) in As shown in λ, the Risk Variance increases first, then decreases. This is because when λ is low, the average number of busy channels stay few with little probability transformation. As λ increases, the average number of busy channels increases and the range of transformation is extended until it increases to the maximum number of channels with little probability decrease. According to the λ, μ, number of channels, coexistence capacity. Interestingly, the two intersections must exist but there are no regulations to follow for ensuring if it is the most suitable parameter combination of an unknown application scenario.Accordingly, the correctness of our theory for Risk Variance estimation is also verified in both Service-independent and Service-dependent coexisting WBANs, referred to λ. On the contrary, both coexistence capacity and λ have obvious influences on Channel Saturation Rate, as shown in Similarly, λ until it reaches to As shown in Consequently, numerous simulation results show that our theoretical analysis is correct and our approximate estimation is so close to the real simulation value. Comparatively speaking, Approximate Method I has a great accuracy on all of the coexistence parameters and metrics involved in this paper. Approximate Method II performs better at Busy-channel Parameter estimation and Coexisting Risk estimation within special parameter interval in Service-independent coexisting WBANs.Since channel conflicts have a serious influence on the performance of coexisting WBAN, this part employs channel conflict times in each time unit to provide an intuitive performance evaluation of the enhanced channel hopping mechanism. Literature  has alsoλ = {9, 10, 11, 12} in the former and with arriving rate λ = {105, 205, 305, 405} in the latter. Furthermore, we implement the enhanced channel hopping mechanism with m = 1, m = 3 and m = 6, respectively. The situation m = 1 represents our enhanced channel hopping mechanism backoff to plain channel hopping mechanism.According to our simulation results in As shown in In consequence, our enhanced channel hopping mechanism outperforms the plain channel hopping.This paper provided a comprehensive coexistence capability investigation for enhanced channel hopping mechanism in WBANs. Comparing with previous states of the art which focus on the algorithm designs of channel hopping sequences generation and the specific mechanism implementation, this paper aimed at extending the channel hopping mechanism to be more general by allowing multiple WBANs coexisted in the same channel. The channel resources were treated as logical blocks, which decoupled the implementation from integrating different channel-shared coexistence technologies. We provided comprehensive coexistence capability analysis and estimation approaches. The extensive simulation results showed that our coexistence parameters and metrics provided an advantage reflection for coexistence capability performances of channel hopping mechanisms. This paper provided a quantitative further guide for channel hopping exploitation. In the near future, we will optimize our approximate methods for more accurate estimation and lager parameter interval. Furthermore, complex scenarios with more arriving models and leaving models should also be taken into account in our further work.


The mechanistic studies elucidated that EDG2 enhanced mTOR phosphorylation via PI3K/AKT signaling and consequently induced EMT of HCC cells. Moreover, EDG2 was found to promote cell viability and proliferation of HCC cell through PI3K/AKT/mTOR/Skp2/p27Kip1 signaling. Taken together, the data here demonstrated EDG2 was a potential predictor for HCC patients receiving liver resection and accelerated HCC progression via regulating EMT driven by PI3K/AKT/mTOR signaling.HCC is the leading type of the malignant liver tumors with the unsatisfied prognosis. Liver resection has been considered as the predominant curative therapy, however, the post-surgical prognostic evaluation remains an urgent problem and the mechanism of HCC metastases has not been understood completely. EDG2 has been found to accelerate tumor progression through mediating different cell pathways, however, it remains unclear about the role of EDG2 on hepatocarcinogenesis. Here, EDG2 expression was found increased notably in HCC tissues by immunohistochemistry compared with adjacent liver tissues and comparison of survival curves revealed that EDG2 upregulation in HCC tissues was associated with the worse prognosis after liver resection. The positive correlation between EDG2 up-regulation and EMT was observed in HCC samples. Furthermore, EDG2 over-expression in HCC cells brought the typical EMT characteristics including up-regulation of Vimentin, Fibronectin and N-cadherin, suppression of E-cadherin, and enhanced cell migration and invasion capacities. Knockdown of EDG2 reversed the EMT phenotype in HCC cells. The  Hepatocellular carcinoma (HCC) has been identified as the sixth leading cancer and the second most common cause of cancer-related mortality due to its unfavorable prognosis . During The concept of epithelial-mesenchymal transition (EMT) was raised by Elizabeth Hay in the early 1980s, which was described that epithelial cells losted epithelial markers and acquired mesenchymal characteristics . A growiEndothelial differentiation gene 2 (EDG2), also known as LPA1, is the first established as a kind of G protein-coupled receptor for lysophosphatidic acid (LPA) which was isolated from a mouse cerebral cortical neuroblast in 1996 , includiDuring liver resection, platelets accumulated in remnant liver tissues and secreted numerous LPA which has been confirmed to contribute to EMT induction in ovarian carcinoma , 18. It To investigate the expression of EDG2 in HCC cells and human liver cells, both qRT-PCR and western immunoblotting were carried out. There was more mRNA and protein expression of EDG2 in 5 HCC cell lines than L02 cell, a sort of immortalized human normal liver cell. SK-Hep1 cells had the highest level of EDG2 expression among the 5 HCC cells, therefore, SK-Hep1 cell line was used as the cell model in the EDG2 knockdown experiment here Figure . On the Next, we detected the EDG2 expression with IHC staining in HCC tissues (n = 210) as well as in corresponding adjacent liver tissues. Strong EDG2 expression was detectable in cytoplasm of tumor cells, with normal liver cells in adjacent liver tissues being weak positive or negative for EDG2 expression Figure . After avs. 62.1%, P = 0.004), larger tumor diameter , high Edmonson-Steiner classification , advanced TNM stage , portal vein invasion , and intra-hepatic metastases . The follow-up information was obtained from 175 of 210 HCCs and the median follow-up time was 42.5 months, ranging from 3 to 75.4 months. We classified the 175 HCC patients into two groups: EDG2 high group and EDG2 low group using the median IHC score of EDG2 in HCC tissues as the cut-off value. The 1-, 3-, and 5-year survival rates of patients from EDG2 high group were less than those of EDG2 low group . Comparison of Kaplan-Meier survival curves also demonstrated that HCC patients from EDG2 high group suffered from the worse over-all survival after liver resection than those from EDG2 low group  inhibitor which was degraded by Skp2 via mediating its ubiquitylation [Kip1 expression in SK-Hep1 cells  inhibitors and repression of p27Kip1/ CDK2 signaling has been found to contribute to hepatocarcinogenesis greatly by several evidences [Kip1/ CDK2 signaling.The following vidences , 43. TheThere have been several studies revealing that LPA induced EMT phenotype of ovarian cancer cells via different mechanisms. Dhanasekaran group showed that LPA sensitized the Src/Gαi2 signaling pathway to result in up-regulation of HIF1α and finally initiated EMT phenotype of ovarian cancer cells . Stack gKip1 signaling and reinforce the migration and invasion abilities of HCC cells via evoking EMT phenotype. These findings could provide a novel mechanism that EDG2 promoted HCC recurrence after liver resection, which would help to establish EDG2 as a predictive factor for postsurgical HCC recurrence and develop the innovative target therapy after liver resection.Taken together, the results in the present study showed that EDG2 was over-expressed aberrantly in HCC tissues, which predicted poor postsurgical outcome of HCC patients. Up-regulation of LPA and EDG2 during liver regeneration could accelerate the growth of metastased HCC cells in the remanent liver tissues via PI3K/AKT/mTOR/Skp2/ p27A total of 210 patients who were diagnosed with HCC were recruited in this investigation. All HCC patients underwent liver resection for HCC by the same surgical team in Department of Hepatobiliary Surgery at the First Hospital of Xian Jiaotong University from January 2004 to June 2007. Written informed consent was obtained from all patients, and all protocols in this investigation were approved by the Xi’an Jiaotong University Ethics Committee according to the Helsinki Declaration of 1975.Diagnosis of HCC was made according to the criteria of the Chinese Society of Liver Cancer and Chinese Anti-Cancer Association. No patients received any neo-adjuvant chemotherapy or radiotherapy before liver resection. Specimens of both HCC and adjacent liver tissues for the further assessments were obtained during liver resection and immediately stored at paraformaldehyde for immunohistochemistry staining assay. The demographic information from these 210 HCC patients were obtained from their medical records. The histopathologic information including Edmonson-Sterner classification, TNM grading, portal vein invasion, intra-hepatic metastases and tumor diameter was from two experienced pathologists who were blinded to the clinical information. We got the follow-up information from 175 of 210 HCCs (83.3%) with the median follow-up time was 42.5 months, ranging from 3 to 75.4 months. The demographic features and clinicopathological data are presented in Table Immunohistochemistry (IHC) staining was carried out as described previously . BrieflyThe scoring system for IHC staining was presented previously . StaininCell lysates were prepared in RIPA buffer containing inhibitors for proteases and sodium orthovanadate as an inhibitor of phosphatases. Western immunoblotting was conducted according to the protocol introduced previously . The pricDNA synthesis and qRT-PCR examination were carried out as presented previously . All samWe obtained human HCC cell lines including SK-Hep1, Hep3B, HepG2 and PLC/PRF/5, and the human immortalized normal hepatocyte cell line LO2 from the Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences  and Huh7 cells were a kind gift from Prof. Kefeng Dou . SK-Hep1, Hep3B, PLC/PRF/5 and LO2 were cultured in DMEM medium with 10% fetal calf serum (FBS) in a 5% CO2 humidified atmosphere at 37°C, while HepG2 was grown in RPMI 1640 medium with 10% FBS.The EDG2 expressing plasmid was built by recombining the cDNA of human EDG2 into the pCMV-Tag2B vector . EDG2 expressing plasmid was transfected into the wild-type Huh7 cells with low level of EDG2 (Huh7 EDG2 cells) with the FuGENE6 transfection reagent. Huh7 cells were transfected with the pCMV-Tag2B empty vector as Huh7 Vector cells. The stable transfection clones were selected with geneticin at a dose of 500 μg/mL for two weeks.4 cells per 35-mm well for 24 h and respectively transfected with EDG2 siRNA (SK-Hep1 EDG2 siRNA) or scrambled siRNA (SK-Hep1 Scr siRNA) using the Lipofectamine RNA iMAX reagent . EDG2 knockdown was confirmed by both qRT-PCR and Western immunoblotting.The Short interference RNA (siRNA) sequences against EDG2 (sc-43746) and the related scramble siRNA sequences (sc-37007) were both purchased from Santa Cruz Biotechnology. SK-Hep1 cells were plated at 5×10Invasion ability of HCC cells was measured by transwell chamber invasion assay, while wound healing assay was conducted to measure cell migration. The details were described in the HCC cells were grown overnight and fixed with 4% paraformaldehyde for 30 min. PBS containing 0.2% Triton X-100 was use to permeabilize HCC cells for 20 min and 2.5% BSA buffer blocked cells for 2 h. HCC cells were incubated with primary antibodies to E-cadherin  and Vimentin  at 4°C overnight, and then stained with the different secondary antibodies including Alexa Fluor-488 or -647  for 4 h at room temperature. The nuclei of HCC cells was stained with DAPI. Immunofluorescent images were captured using a laser scanning confocal microscope .4 per well in 96-well plates with 200 μl medium for 24, 48, 72 and 96 h. After removing culture medium, HCC cells were incubated with 0.25 mg/ml MTT in serum-free medium at 37°C for 4 h. The supernatant was removed and 200 μl of dimethyl sulfoxide was added to solubilize the formazan. The plates were shaken for 5 min and cell survival was assessed by measuring the value of OD570 with a colorimetric reader. The experiment with 6 replicates was conducted for three times independently.To detect the cell proliferation, BrdU incorporation assay was carried out with the BrdU ELISA kit from Abcam  according to the manual instructions . The met6 Huh7 EDG2 cells and 150μL of Matrigel. Similarly, The cell mixture of 2×106 Huh7 Vector cells and 150μL of Matrigel was injected subcutaneously into the flanks of nude mouse from Huh7 Vector group. Tumor sizes were measured with calipers every 5 days. Upon completion of the experiment (day 15), all mice from both groups were sacrificed. The volume of HCC xenografts was obtained using the following formula: volume = A × B2 × 0.52 .In order to analyze tumorigenesis, HCC xenograft assay was performed on nude mouse model. A total of 10 nude mice with 6–8 weeks old were purchased from the Animal Experiment Center of Xian Jiaotong University  and divided into two groups randomly: Huh7 EDG2 group (n = 5) and Huh7 Vector group (n = 5). In the group of Huh7 EDG2, each mouse was injected subcutaneously with the cell mixture including 2×10All data were presented as means and standard errors of the mean. Differences between groups were compared with the Mann-Whitney test or Student-t test. Cox’s proportional hazards model was used to examine the prognostic value of EDG2 protein expression associated with overall survival. Univariable regression analyses were carried out with death as the outcomes. The Cox proportional hazards model with a stepwise procedure were used for multivariate analysis. Differences of the Kaplan-Meier curves between EDG2 high group and EDG2 low group were detected using the log rank test. Statistical significance was set at P < 0.05. Multivariate analysis was conducted with SPSS V17.0 software, and Graphpad PRISM 5 was used for other statistical analyses.


The prevalence of binge drinking in 2013 was 23.1% and in 2014 the prevalence had risen to 30.1%. Gender  and socioeconomic status (type of school and mother’s education) were not associated with the increase in the frequency of binge drinking. However, higher social capital was significantly associated with an increase in binge drinking by students. Adolescents who reported that they had an increase in social cohesion in the community/neighborhood subscale were 3.4 times more likely (95%CI 1.96–6.10) to binge drink themselves. Our results provide new evidence about the “dark side” of social cohesion in promoting binge drinking among adolescents.Adolescence is characterized by heightened susceptibility to peer influence, which makes adolescents vulnerable to initiating or maintaining risky habits such as heavy drinking. The aim of the study was to investigate the association of social capital with longitudinal changes in the frequency of binge drinking among adolescents at public and private high schools in the city of Diamantina, Brazil. This longitudinal study used two waves of data collected when the adolescents were 12 and 13 years old. At the baseline assessment in 2013 a classroom survey was carried out with a representative sample of 588 students. In 2014, a follow-up survey was carried out with the same adolescents when they were aged 13 years. The Alcohol Use Disorder Identification Test-C (AUDIT C) was employed for the evaluation of alcohol intake. Our predictor variables included sociodemographic and economic characteristics  and Social Capital. For evaluation of social capital, we used the Social Capital Questionnaire for Adolescent Students (SCQ-AS). Descriptive and bivariate analyzes were performed (p <0.05). The log-binomial model was used to calculate prevalence ratios (PR) and 95% confidence intervals. The two-tailed  Adolescence, more than in any other developmental stage, is characterized by heightened susceptibility to peer influence , which mVarious risk factors for problem drinking among youth have been identified by researchers. The emphasis across studies has been on risk and protective factors ,5. ThereBinge drinking has a strong social component ,10. AdolBecause both alcohol use and peer influence increase during adolescence, it is critical to consider longitudinal influences of peer groups on the developmental trajectory of adolescent alcohol use . FurtherTo investigate an incidence of binge drinking, a survey was carried out involving all adolescents enrolled in the public and private schools of the city of Diamantina/MG, Brazil, with a full 12 years during the data collection months of the study. Data related to school addresses and number of students enrolled in each class was obtained from the State and Municipal Education Departments.Subsequently, 633 adolescents from all 13 public and private schools in Diamantina / MG were invited to participate in the study, being previously notified by telephone to schedule the researcher's visit. At that time, the objectives of the research were clarified and what activities would be carried out at the school. Also presented were an approval of the Ethics Committee and as authorizations of the State and Municipal Secretariats of Education. After the consent of the management and the teaching staff, classes with schoolchildren enrolled in public and private schools in the urban area of the city of Diamantina and who were 12 full years on the day of the exam; authorized by the parents / guardians and agreed to participate in the research (inclusion criteria) were contacted by the researcher during class time, with the teacher's presence, for awareness raising. Adolescents not authorized by parents or guardians or who did not agree to participate in the study were excluded from the study. The researcher explained the purpose of the research and asked the students to answer the questionnaires, ensuring the confidentiality of the answers, as well as the evaluation of student participation.In the baseline survey (2013), the sample consisted of 588 students (participation rate: 92.89%). The reasons for dropouts were non-authorization from parents/guardians or adolescents  and failure to complete the questionnaires . In 2014, a new data collection procedure was carried out with these adolescents when they were aged 13 years. Again, all 13 public and private schools in Diamantina / MG were invited to participate in the study and were previously notified by telephone to schedule the researcher's visit. They only included adolescents authorized by their parents or guardians and who agreed to participate in the study. Thus, the follow-up study involved a sample of 588 adolescents (100%). To achieved a 100 percent follow-up rate, the researchers responsible for the data collection made calls to the homes of students who were not present on the day previously scheduled, which led the researchers to return to some schools more than once. Furthermore, access was relatively easy because researchers live in the region and had close contact with directors of the schools.The Alcohol Use Disorder Identification Test (AUDIT C), validated for use in Brazil . was empOur predictor variables included sociodemographic and economic characteristics  and Social Capital.I agree, I do not agree or disagree and I disagree. This procedure was based on the target age group and was chosen to avoid confusion during the filling out of the questionnaire. The findings confirm indications in the literature that networks of friends and neighborhood cohesion reflect experiences one shares with one’s peers and underscore the importance of the present questionnaire as an assessment tool for measuring social capital. Based on the distribution, to analyze the social capital by the adolescent the social capital variable was dichotomized by median as high (31 points or more) and low (less than 31 points). The difference of the social capital at the follow-up in relation to the social capital at the baseline of each adolescent was calculated to obtain the difference between the measures of social capital in the two evaluations. Thus: total score of social capital at follow-up (FSC) minus total score of social capital at the baseline (BSC) presented three response options increase in social capital (FSC> BSC), reduction (FSC <BSC) and unaltered (FSC = BSC). We treated sex, type of school (public or private), maternal education and family income as time invariant.For evaluation of social capital, we used the Social Capital Questionnaire for Adolescent Students (SCQ-AS), which was developed and validated by our research team . The stup value was set at <0.05.Data analysis was performed using the Statistical Package for the Social Sciences  and included frequency distribution and association tests. The chi-square test was used to determine the statistical significance of associations between binge drinking and the independent variables (p < 0.05). Given the high prevalence of the outcome > 20%), we used log-binomial model to calculate prevalence ratios (PR) and 95% confidence intervals [%, we useThis study received approval from the Human Research Ethics Committee of the Federal University of Minas Gerais (Brazil) (COEP-317/11). All parents/guardians signed a statement of informed consent authorizing the participation of their children. All adolescents also signed a statement of assent.The sample comprised 588 students (participation rate at one-year follow-up: 100%). Boys accounted for 48.6% (n = 286) of the sample. Among these participants, the vast majority attended public schools . A total of 75.2% (n = 442) of adolescents were from families that earned up to three times the Brazilian monthly minimum wage, and 61.60% (n = 361) of the mothers had less than eight years of schooling .The prevalence of binge drinking in 2013 was 23.1% and in 2014 the prevalence had risen to 30.1%, i.e. there was a 7% increase in the prevalence of binge consumption in the period. Of the 452 teens who reported never consuming five or more alcoholic drinks at one time in 2013, 41 started to do so with some frequency in 2014 .According with the changes in the score of social capital total between baseline (2013) and follow-up (2014), 340 (58.4%) adolescents unaltered their social capital total in follow-up; 184 (31.6%) students showed an increase in social capital total in follow-up and 58 (10.0%) showed a reduction in follow-up. Six students did not adequately answer the questionnaire.increase in binge drinking by students  and socioeconomic status (type of school and mother’s education) were not associated with the increase in the frequency of binge drinking. However, social capital was significantly associated with an students .The present study examined the frequency of binge drinking among adolescents at public and private schools in the city of Diamantina (southeastern Brazil). The increase in the frequency of binge drinking in the follow-up period was 7% and this increase was fivefold greater among adolescents who exhibited an increase in social capital. Our social capital questionnaire was designed so that we can distinguish the influence of social capital in different contexts that the adolescent is exposed to, i.e. the school environment versus the neighborhood environment. We therefore analyzed the subscales separately. Our findings suggest that adolescents’ drinking behavior is more responsive to changes in the neighborhood context and trust, rather than the school context and friendship network at school. The literature suggests that the concept of social capital can be broken down into ‘structural’ and ‘cognitive’ social capital . Structulower risk for binge drinking [In contrast to the results of the present study, previous reports found that students from U.S. colleges with higher levels of social capital were at drinking ,23. The drinking . In sampdrinking . Howeverdrinking . In addidrinking . Young udrinking .Past studies have found that binge drinking is usually performed in groups; therefore, peers play an important role in promoting binge drinking, perhaps due to peer selection or peer influence  , 23. OurDespite being a well-established determinant, the influence of socioeconomic status on health is not well understood and little research has focused on the effects of this aspect on health during adolescence . In the In the present study, we did not find statistically significant difference between incidence of an increase in binge drinking and gender. This may be explained by changing gender norms over time, which has made it more acceptable for girls to engage in risky behaviors . In accoA limitation of our study is that as the data were derived from self-administered questionnaires, lack of attentiveness should be taken into consideration. Second, despite emphasizing the importance of giving honest responses, the findings may have been underestimated due to self-censoring and/or a suspicion that school authorities could gain access to the answers on the questionnaires. Third, information on the influence of friends and characteristics of friendship networks, such as density, size, quality of contacts, proximity and centrality, was not collected in the present study, despite the fact that binge drinking has been associated with such factors , 12, 13.Binge drinking involves groups of inter-connected people who evince shared behaviors, and is a public health and clinical problem. Targeting these behaviors should involve addressing groups of people and not just individuals . Our resS1 File(XLS)Click here for additional data file.