MCS Level Research Articles

Effects of low concentration of gallic acid on the growth and microcystin production of Microcystis aeruginosa

Gallic acid (GA) is an allelochemical that has been utilized in high concentrations for the management of harmful algal blooms (HABs). However, there is limited knowledge regarding its impact on the growth of M. aeruginosa as the GA concentration transitions from high to low during the HABs control process. This study has revealed that as the GA concentration decreases (from 10 mg/L to 0.001 μg/L), a dose-response relationship becomes apparent in the growth of M. aeruginosa and microcystin production, characterized by high-dose inhibition and low-dose stimulation. Notably, at the concentration of 0.1 μg/L GA, the most significant growth-promoting effect on both growth and MCs synthesis was observed. The growth rate and maximum cell density were increased by 1.09 and 1.16 times, respectively, compared to those of the control group. Additionally, the contents of MCs synthesis saw a remarkable increase, up by 1.85 times. Furthermore, lower GA concentrations stimulated the viability of cyanobacterial cells, resulting in substantially higher levels of reactive oxygen species (ROS) and chlorophyll-a (Chl a) compared to other concentrations. Most importantly, the expression of genes governing MCs synthesis was significantly upregulated, which appears to be the primary driver behind the significantly higher MCs levels compared to other conditions. The ecological risk quotient (RQ) value of 0.1 μg/L GA was the highest of all experimental groups, which was approximately 30 times higher than that of the control, indicating moderate risk. Therefore, it is essential to pay attention to the effect of M. aeruginosa growth, metabolism and water ecological risk under the process of reducing GA concentration after dosing during the HABs control process.

Link Adaptation Strategy for Underwater Acoustic Sensor Networks: A Machine Learning Approach

Abstract Due to growing concerns regarding their use in fields including oceanography, commercial marine operations, and military surveillance, demand in the exploration of underwater sensor networks for marine studies has developed. Network channels for underwater sensor network (USN) rapidly change (spatially and temporally) depending on the surroundings. To increase system efficiency by adjusting transmission parameters to channel fluctuations, it is alluring to utilize adaptive modulation and coding (AMC) for USNs. In order to determine the best link adaptation method based on the channel quality, this article focuses on evaluating a measured sea trial dataset utilizing a rule-based approach (i.e., three-dimensional evaluation, modulation-wise analysis, and a fixed-SNR strategy). To determine the optimum AMC combinations in terms of channel adaptively, we draw a situation of the measured USN data rate versus Bit Error Rate (BER) and Signal to Noise Ratio (SNR). The work further extends to apply machine learning (ML) methods to identify the MCS levels by looking into the channel characteristics due to the non-reversibility limitation of the rule-based strategy. One of the ML methods we used for the investigation, gradient boosted regression tree (GBRT), exhibits impressive accuracy of 99.988% in classifying MCS levels. The MCS levels are related to channel statistics and signal characteristics, particularly those that are susceptible to SNR and BER limitations, using an ensemble of trees that learns from the buoy and base station’s uplink data.

Function, coping and health as predictors of sick leave after rehabilitation

Abstract Background Function, coping and health are central factors in rehabilitation after injury or sickness. To investigate how these factors are associated with sick leave during 12 months after rehabilitation is the aim of this study. Methods A sample of 412 rehabilitation patients ≤ 67years were included. They were all employed, and referred to inter-professional rehabilitation in western Norway. Rehabilitation consisted of physical activity/exercise, cognitive approaches and pain management. In two surveys patients reported mental (MCS) and physical (PCS) function (SF-36), self-perceived health (EQ-VAS) and coping (SOC-13). Register data on sick leave during 12 months in the calendar year after rehabilitation was retrieved from Statistics Norway and categorised to; non, (n = 168), ≤ 364 days (n = 152) and 365 days (n = 92). Ordinal regression was used to analyse association between sick leave and MCS, PCS, EQ-VAS and SOC-13, adjusted for age, sex and diagnoses. Results The levels of MCS and PCS (SF-36) were found to be associated with sick leave; OR 0.96, 95% CI 0.92-0.99, p = 0.004 and OR 0.93, 95% CI 0.90-0.97, p < 0.001, respectively (Pseudo R2 = 0.1133). EQ-VAS and SOC-13 were significant predictors of sick leave in crude analysis (EQ-VAS: OR 0.97, 95% CI 0.96-0.98, p < 0.001. SOC-13: OR 0.98, 95% CI 0.95-0.98, p < 0.001), but not in the fully adjusted model (EQ-VAS: OR 0.98, 95% CI 0.96-1.01, p = 0.178. SOC-13: OR 0.99, 95% CI 0.99-1.03, p = 0.479). Conclusions Patientś self-reported mental and physical function were associated with sick leave 12 months after inter-professional rehabilitation. Higher level of function was associated with no sick leave. In our study, patient’s self-reported health and coping were not associated with sick leave. This suggest that interventions for functional improvement are beneficial in health care strategies to help patients return to work after injury or sickness. Key messages • Achieved higher physical and mental function after rehabilitation seems to contribute to reduced sick leave after injury or sickness. • Improving function should remain a central factor in rehabilitation.

Electricity consumption and production forecasting considering seasonal patterns: An investigation based on a novel seasonal discrete grey model

The electricity forecasting problem is among the prominent issues for policymakers to ensure a reliable and stable electricity supply. Although many studies have been executing effectively to predict China's electricity consumption and production, the results of diverse models are confusing and contradicting because they can hardly identify seasonal fluctuations and provide robust forecasts based on different sample volumes. This work focuses on using a new electricity forecasting tool to present precise results to overcome such shortcomings. Initially, a seasonal discrete grey model is designed based on the characteristics of China's electricity consumption and production. Besides, the rolling mechanism is introduced to improve forecasting accuracy further when performing the verification experiments. Secondly, the DM, SPA, and MCS tests and level accuracy is implemented to measure each competing model's forecasting performance efficiently. Lastly, this new model's robustness over different sample sizes is validated by conducting numerous experiments with diverse sample volumes. Empirical results demonstrate that the technique is convincingly an accurate, robust, and applicable method for China's electricity consumption and production forecasting, outperforming any other prevalent forecasting model.

Market sophistication and metacognition of workers in collectivistic vs. individualistic countries

The study is designed to answer the question of whether and how economic and technological factors of collectivistic vs. individualistic countries relate to metacognition, meaning self-awareness of biases (metacognitive self, MCS). The latter was measured via a questionnaire (MCSQ – 40), translated (back – forth) into Polish, English, Vietnamese, Hindu, and Spanish (n = 945). Economic and technological factors were extracted from the Global Innovation Index dataset. Knowledge workers and market sophistication were chosen as the factors. The former factor when strong in a given country enhanced MCS of participants. Conversely, the latter factor, that is market sophistication, decreased MCS level of participants when significant. The results are explained in terms of Marx's theory, the beneficial role of human technology, and the theories of consciousness.

Effects of metformin combined with glimepiride or dapagliflozin on islet function and quality of life in patients with type 2 diabetes mellitus

Objective To observe the effects of metformin combined therapies on islet function and quality of life in patients with type 2 diabetes mellitus. Methods A total of 122 elderly patients with type 2 diabetes were randomly selected and divided into control group and observation group by random number table method, with 61 cases in each group. The control group was treated with metformin combined with glimepiride. The observation group received metformin combined with dapagliflozin for treatment. Blood glucose indexes[fasting blood glucose (FBG), 2 h postprandial blood glucose (2 hPG), glycated hemoglobin (HbAlc)], fastening insulin (FINS), islet function indexes [insulin resistance index (HOMA-IR), islet β-cell function index (HOMA-β), insulin sensitivity index (ISI)], blood lipid indexes [total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C)] level and quality of life score [psychological related quality of life (MCS) score and physiological related quality of life (PCS) score] were compared. Results Before treatment, there were no significant differences in blood glucose indexes, islet function indexes, blood lipid level and quality of life score between two groups (P>0.05). After treatment, the levels of FBG, 2 hPG, HBALC, FINS, TC, TG, LDL-Cand HOMA-IR in two groups were significantly lower than before treatment, while the levels of HDL-C, HOMA-β, ISI, MCS and PCS were significantly higher than before treatment (P Conclusion Metformin combined with glimepiride or dapagliflozin can effectively control patients′ blood glucose levels, improve patients′ blood lipid levels and pancreatic islet function. Among them, metformin combined with dapagliflozin has a relatively better therapeutic effect and safety. Besides, it can regulate the blood glucose, avoid the occurrence of hypoglycemia and improve patients′ quality of life.

Only partial improvement in health-related quality of life after treatment of chronic hepatitis C virus infection with direct acting antivirals in a real-world setting-results from the German Hepatitis C-Registry (DHC-R).

Improvement of health-related quality of life (HRQoL) is frequently reported as a benefit when treating hepatitis C virus infection (HCV) with direct acting antivirals (DAA). As most of the available data were obtained from clinical trials, limited generalizability to the real-world population might exist. This study aimed to investigate the impact of DAA therapy on changes in HRQoL in a real-world setting. HRQoL of 1180 participants of the German Hepatitis C-Registry was assessed by Short-Form 36 (SF-36) questionnaires. Scores at post-treatment weeks 12-24 (FU12/24) were compared to baseline (BL). Changes of ≥2.5 in mental and physical component summary scores (MCS and PCS) were defined as a minimal clinical important difference (MCID). Potential predictors of HRQoL changes were analysed. Overall, a statistically significant increase in HRQoL after DAA therapy was observed, that was robust among various subgroups. However, roughly half of all patients failed to achieve a clinically important improvement in MCS and PCS. Low MCS (p<.001, OR=0.925) and PCS (p<.001, OR=0.899) BL levels were identified as predictors for achieving a clinically important improvement. In contrast, presence of fatigue (p=.023, OR=1.518), increased GPT levels (p=.005, OR=0.626) and RBV containing therapy regimens (p=.001, OR=1.692) were associated with a clinically important decline in HRQoL after DAA therapy. In conclusion, DAA treatment is associated with an overall increase of HRQoL in HCV-infected patients. Nevertheless, roughly half of the patients fail to achieve a clinically important improvement. Especially patients with a low HRQoL seem to benefit most from the modern therapeutic options.

Link Adaptation on an Underwater Communications Network Using Machine Learning Algorithms: Boosted Regression Tree Approach

Interest in the study of next-generation underwater sensor networks for ocean investigations has increased owing to developing concerns over their utilization in areas such as oceanography, commercial operations in maritime areas, and military surveillance. Underwater acoustic communications (UAC) network channels are fast-varying (spatially and temporally) according to environmental conditions. It is tempting to use adaptive modulation and coding (AMC) for UAC networks to improve the system efficiency by matching transmission parameters to channel variations. This paper focuses on analyzing a measured sea trial dataset by using a rule-based strategy (i.e., three-dimensional analysis, modulation-wise analysis, and a fixed-SNR strategy) to find the suitable link adaptation procedure depending on the channel quality. Hence, we plot a scenario of the measured UAC network data rate vs. Signal to Noise Ratio (SNR) and/or Bit Error Rate (BER) to pick the best AMC combinations in the context of adaptivity to the channel. Due to non-reversibility limitation of rule-based strategy, the work further extends to use machine learning (ML) algorithms to classify the MCS levels by investigating the channel characteristics. Boosted regression tree, from among the four ML algorithms we adopted for the analysis, shows formidable accuracy of 99.97% in classifying MCS levels. This ensemble of trees learns from the uplink data of the buoy and the base station and relates the MCS levels to channel metrics and signal characteristics especially subject to SNR and BER constraints.

Cyanobacterial blooms modify food web structure and interactions in western Lake Erie

With anthropogenic eutrophication and climate change causing an increase in cyanobacterial blooms worldwide, the need to understand the consequences of these blooms on aquatic ecosystems is paramount. Key questions remain unanswered with respect to how cyanobacteria blooms affect the structure of aquatic food webs, the foraging abilities of higher consumers, and the potential for cyanotoxins (e.g., microcystins [MCs]) to accumulate in fish. Toward addressing these uncertainties, physicochemical attributes, water (for MCs), phytoplankton, zooplankton, and epipelagic and benthic age-0 fish were sampled at 75 sites (44 sites for fish) of varying cyanobacteria concentration (0.1–44 μg/L) in western Lake Erie during the cyanobacteria bloom season, 2013–2014. Sites with high cyanobacteria biomass were characterized by Microcystis spp. (84–100% of biomass), detectible levels of MCs (maximum = 10.8 μg/L), and low water transparency (minimum = 0.25 m). Counter to expectations, strong positive relationships were found between cyanobacteria concentration and the biomass of several herbivorous zooplankton taxa (e.g., Daphnia, Diaphanosoma spp., Bosmina (formerly Eubosmina) coregoni, and Calanoida spp.). Expectations regarding fish were partly supported (e.g., diet selectivity varied across a cyanobacteria gradient) and partly not (e.g., consumption of zooplankton did not differ between bloom and non-bloom sites). These findings show that cyanobacterial blooms can strongly affect the distribution, composition, and interactions of zooplankton and fish, sometimes in surprising ways, highlighting the need to further explore their impact on aquatic food webs.

MCS 레벨이 가변적인 무선랜 시스템에서 전이중 MAC 프로토콜 성능 분석

자기 간섭 제거 기술 (SIC) 의 발전으로 인해 전이중 통신으로 데이터를 전송하는 것이 현실화되었다. Physical 계층에서 전이중 통신이 가능해짐에 따라 전이중 통신을 지원할 수 있는 MAC 프로토콜에 관한 연구도 함께 진행되었다. 전이중 통신 MAC 프로토콜의 성능 분석을 위해서는 자기 간섭 제거 기술의 수치, SIR 임계값에 따른 MCS 레벨의 확률, 전이중 쌍 매칭이 될 확률 등을 고려해야 하지만, 대부분의 연구에서는 이를 고려한 분석이 부족하다. 따라서 본 논문에서는 이를 종합적으로 고려하여 MCS 레벨이 가변적인 무선랜 시스템에 전이중 MAC 프로토콜의 성능을 분석하였다. 자기 간섭 제거 수치에 따른 MCS 레벨 확률 및 전이중 쌍 매칭 확률을 분석하고 그에 따른 처리율 성능을 분석하였다. 성능 분석 결과 자기 간섭 제거 수치가 높을수록 전이중 쌍 매칭 확률이 높았으며, 그로 인해 처리율 성능도 높은 것을 확인하였다. 또한 대부분의 전이중 통신은 낮은 MCS 레벨로 데이터 전송이 이루어지는 것을 확인하였다.

MCS level이 전이중 통신 무선랜 시스템 성능에 미치는 영향 분석

MCS level이 전이중 통신 무선랜 시스템 성능에 미치는 영향 분석

Decreased integration of EEG source-space networks in disorders of consciousness.

Increasing evidence links disorders of consciousness (DOC) with disruptions in functional connectivity between distant brain areas. However, to which extent the balance of brain network segregation and integration is modified in DOC patients remains unclear. Using high-density electroencephalography (EEG), the objective of our study was to characterize the local and global topological changes of DOC patients' functional brain networks.Resting state high-density-EEG data were collected and analyzed from 82 participants: 61 DOC patients recovering from coma with various levels of consciousness (EMCS (n = 6), MCS+ (n = 29), MCS- (n = 17) and UWS (n = 9)), and 21 healthy subjects (i.e., controls). Functional brain networks in five different EEG frequency bands and the broadband signal were estimated using an EEG connectivity approach at the source level. Graph theory-based analyses were used to evaluate their relationship with decreasing levels of consciousness as well as group differences between healthy volunteers and DOC patient groups.Results showed that networks in DOC patients are characterized by impaired global information processing (network integration) and increased local information processing (network segregation) as compared to controls. The large-scale functional brain networks had integration decreasing with lower level of consciousness.

Quality of Life-Repeated Measurements Are Needed In Dialysis Patients.

BACKGROUND:There is a general agreement that, besides survival, the quality of life is a highly relevant outcome in the evaluation of treatment in patients with the end-stage renal disease. Moreover, it is very important to determine whether the quality of life impacts survival.AIM:This study aims to assess whether changes or absolute scores of the quality of life (QOL) measurements better predict mortality in dialysis patients.MATERIAL AND METHODS:In a longitudinal study comprising 162 prevalent hemodialysis patients QOL was assessed with the 36-item - Short Form Health Survey Questionnaire (SF-36) at baseline and after 12 months. Patients were followed for 60 months. Mortality risk was assessed using Cox proportional hazards analysis for patients with below and above median levels of both physical and mental QOL component scores (PCS and MCS, respectively).RESULTS:At the beginning of the study the mean Physical Component score was 47.43 ± 26.94 and mean Mental Component Score was slightly higher 50.57 ± 24.39. Comparative analysis of the changes during the first year showed a marked deterioration of all quality of life scores in surviving patients. The 5-point decline for PCS was noted in 39 (24%) patients and 42 (26%) for MCS. In the follow-up period of 60 months, 69 (43%) patients died. In the Cox analysis, mortality was significantly associated with lower PCS: HR = 2.554 [95% confidence interval (CI): 1.533-4.258], (P < 0.000) and lower MCS: 2.452 (95% CI: 1.478-4.065), P < 0.001. The patients who had lower levels of PCS and MCS in the second QOL survey 1 year later, had similarly high mortality risk: 3.570 (95% CI: 1.896-6.727, P < 0.000); 2.972 (95% CI: 1.622-5.490, P < 0.000), respectively. The hazard ratios for mortality across categories for the change of PCS and MCS were not significant. In the multivariate model categorising the first and second scores as predictors and adjusted for age, only the second PCS and MCS score were associated with mortality.CONCLUSION:Low QOL scores are associated with mortality in repeated measurements, but only the more recent overwhelmed the power of the decline.

Alexithymia and Quality of Life in Adult Patients with Juvenile Idiopathic Arthritis

Patients with chronic pain disturb not only quality of life (QL) but also develop difficulties in describing their feelings. Prolonged pain, stress, pathological conditions and related emotions can alter the perceived sensation of pain. The aim of our study was to study the QL and the level of alexithymia in adult patients with different types of juvenile idiopathic arthritis (JIA).Materials and methods. 173 young people aged 18-40 years old were examined: 118 adult patients with different ILAR variants of JIA, 30 patients with ankylosing spondylitis (AS) and 25 healthy young people. The QL was assessed using the Short-Form-36 questionnaire (SF36) with further assessing the level of alexithymia by Toronto alexithymia scale (TAS-20).Results. The analysis of QL shows that PCS (44.8±9.9) was significantly lower (p=0.001) in patients with JIA than in healthy subjects (55.7±6.9) of the corresponding age and sex, but did not differ from patients with AS (42.3±7.5). Patients with JIA had lower physical (p=0.001), role functioning (p=0.001) and bodily pain (p=0.001) compared with healthy, with no difference from patients with AS. In the distribution of patients with JIA in groups by the level of alexithymia, differences in QL were not revealed by MCS or PCS and scales related with them. The relationship analysis between the alexithymia and QL in patients with JIA shows, that elevated and high levels of alexithymia were related with low levels of MCS (p&lt;0.05), role functioning (p&lt;0.05), mental health (p&lt;0.05). PCS and physical functioning did not affect the level of alexithymia in adult patients with JIA. PCS, role functioning, bodily pain, and general health were the lowest in patients with poly-articular JIA. However patients with oligo-, poly-articular, enthesyte-related JIA had no differences on scales related to PCS. Patients with poly-JIA with elevated and high levels of alexithymia revealed significantly lower social (p&lt;0.05) and role (p&lt;0.05) functioning, mental health (p&lt;0.05) compared to patients without alexithymia. The presence of low bodily pain in alexithymic patients was found. Signs of alexithymia were found in 90% and 85% of adult patients with the oligo-arthritis and enthesyte-related JIA, respectively. The comparison of the QL in patients with oligo-arthritis and enthesitis-related JIA with different levels of the alexithymia shows no significant differences.Conclusions. 85.2% of adult patients with different variants of JIA have elevated and high levels of alexithymia. Adult patients with JIA have lower physical functioning than healthy individuals of the same age and sex, although they do not differ from the control group and AS group on psychological functioning and related vitality, social and role functioning, and mental health. The presence of alexithymia is related with a low level of psychological functioning, role functioning, mental health. However, physical functioning did not affect the level of alexithymia in adult patients with JIA. Patients with poly-JIA have the lowest physical, role function, bodily pain and general health, but according to the psychological functioning there were no differences between different variants of JIA in adulthood. Patients with poly-JIA with elevated and high levels of alexithymia have significantly lower social (p&lt;0.05), role (p&lt;0.05) functioning and mental health (p&lt;0.05) compared to patients without signs of alexithymia.

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform.

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively.

AB0765 Burden of rheumatoid arthritis in russia in the real world setting

BackgroundThe prevalence of rheumatoid arthritis (RA) is relatively similar across developed nations, ranging from 0.5 to 1.0% 1,2. The prevalence in Russia has been estimated at 0.61% 3 and its...

Improvement of the Link Reliability for Ship Ad-Hoc Network by Employing Multiple Antennas

For the purpose of providing high data rate real-time services, radio transmission technologies (RTT) for ship ad-hoc network (SANET) based on the Recommendation ITU-R 1842-1 are designed. Physical layer parameters of SANET are contrived to meet the requirements of the specification. In order to improve the link reliability for SANET, in this paper, we investigate the performance of the SANET with the multiple antennas, where receive combining (RC), transmit diversity (TD), and beamforming (BF) are employed, respectively. Based on the analysis of the packet error rate (PER) under the highly correlated maritime wireless channel model, we select the efficient multiple antenna schemes for SANET to improve the link reliability. In addition, the optimal MCS levels for the single-carrier (SC) SANET with the bandwidth of 25 kHz, and the multi-carrier (MC) SANET with the bandwidth of 50 kHz and 100 kHz are finalized.

Performance Evaluation of Symbol-Wise XOR Based Bi-directional Relaying

In this paper, we investigate the system performance of decode and forward based bi-directional relaying based on symbol-wise XOR operation. This technique gives more freedom in selecting the modulation and coding scheme at relay stations, and significantly relaxes the transmission bottleneck. However, the performance degradation occurs when the modulation orders of both links differ from each other. To mitigate such an impact, we exploit a repetition coding scheme in conjunction with a redundant modulation code scheme by overlapping MCS levels. To this end, a system level simulation proves that the proposed scheme achieves about 43% capacity gain over bit-wise XOR based bi-directional relaying and gives additional 10% gain over symbol-wise XOR based bi-directional relaying.

Baseline characteristics influencing quality of life in women undergoing gynecologic oncology surgery

BackgroundQuality of life (QoL) measurements are important in evaluating cancer treatment outcomes. Factors other than cancer and its treatment may have significant effects on QoL and affect assessment of treatments. Baseline data from longitudinal studies of women with endometrial or ovarian cancer or adnexal mass determined at surgery to be benign were analyzed to determine the degree to which QoL is affected by baseline differences in demographic variables and health.MethodsThis study examined the effect of independent variables on domains of the Functional Assessment of Cancer Therapy (FACT-G) pre-operatively in gynecologic oncology patients undergoing surgery for pelvic mass suspected to be malignant or endometrial cancer. Patients also completed the Short Form Medical Outcomes Survey (SF-36) questionnaire (a generic health questionnaire that measures physical and mental health). Independent variables were surgical diagnosis (ovarian or endometrial cancer, benign mass), age, body mass index (BMI), educational level, marital status, smoking status, physical (PCS) and mental (MCS) summary scores of the SF-36. Multiple regression analysis was used to determine the influence of these variables on FACT-G domain scores (physical, functional, social and emotional well-being).ResultsData were collected on 157 women at their pre-operative visit (33 ovarian cancer, 45 endometrial cancer, 79 determined at surgery to be benign). Mean scores on the FACT-G subscales and SF-36 summary scores did not differ as a function of surgical diagnosis. PCS, MCS, age, and educational level were positively correlated with physical well-being, while increasing BMI was negatively correlated. Functional well-being was positively correlated with PCS and MCS and negatively correlated with BMI. Social well-being was positively correlated with MCS and negatively correlated with BMI and educational level. PCS, MCS and age were positively correlated with emotional well-being. Models that included PCS and MCS accounted for 30 to 44% of the variability in baseline physical, emotional, and functional well-being on the FACT-G.ConclusionAt the time of diagnosis and treatment, patients' QoL is affected by inherent characteristics. Assessment of treatment outcome should take into account the effect of these independent variables. As treatment options become more complex, these variables are likely to be of increasing importance in evaluating treatment effects on QoL.

A short-term poikilothermic period occurs just after paradoxical sleep onset in humans: characterization changes in sweating effector activity.

We examined the changes in sudorific effector activity in five healthy young (21-23 y) subjects just before, during and just after successive paradoxical sleep (PS) phases. Local sweat rates were evaluated minute by minute over the chest (mcs). Previous observations, showing that mcs levels dropped before paradoxical sleep onset was electrophysiologically scored, were confirmed. At the end of this period of mcs depression, which in the present study coincided with paradoxical sleep onset, we show for the first time a short period (3-7 min) (period I) during which sweat production completely disappeared. A second period then followed (period II), at the very beginning of which mcs was re-elicited and thereafter increased in close correlation with paradoxical sleep duration. During period II, the remaining inhibiting influences (maximal during period I) and their releases could be specified by the successive valleys (indicating mcs inhibition) and peaks (indicating release of the mcs inhibition) drawn by the minute by minute mcs changes. These inhibitions became weaker as paradoxical sleep advanced. Given the strategic position of period I (at paradoxical sleep onset) and the total mcs abolition therein observed, it may be assumed that this poikilothermic state is the re-emergence of the 'ancestral' mode of body temperature regulation. From a thermophysiological point of view, period II may be considered as more 'modern' and directly related to the extension of paradoxical sleep in humans. This extension could be underlain by the unique development of our cognitive and/or learning functions.