Gotowa bibliografia na temat „Quapaw (1867)”

Através da análise de imagens orbitais de satélite da área de Quaraí-RS, foi delimitada uma unidade fisiográfica que se desenvolveu em rochas do Grupo São Bento da Bacia do Paraná. Um estudo mais detalhado, utilizando imagens de radar e fotografias aéreas convencionais revelou que esta unidade fisiográfica apresenta estruturas de tipo falhada, dômica, em bacia e em camadas sub-horizontalizadas. Verificou-se que o principal evento na gênese das três primeiras feições estruturais identificadas foi o tectonismo por falhamento.

Apesar de sua área relativamente pequena no extremo oeste do Rio Grande do Sul, a Savana Estépica Parque constitui uma unidade singular na fitogeografia do Estado, com carência de investigação sobre sua história florística e vegetacional. Um perfil sedimentar (30º16’27.9”S e 57º26’33.6”W), com idade basal de 7.660 14C anos AP, foi realizado, com extração de 86 amostras, além de 15 amostras superficiais coletadas, provenientes desta formação vegetacional, no município de Barra do Quaraí, para análises palinológicas. Neste trabalho, são apresentadas descrições e ilustrações de 97 palinomorfos (10 fungos, quatro algas, dois briófitos, seis pteridófitos, uma gimnosperma, 73 angiospermas e um zooclasto) registrados na área de estudo, incluindo gêneros e espécies que caracterizam a vegetação Savana Estépica Parque, tais como Aspidosperma quebracho-blanco Schltdl., Parkinsonia aculeata L., Prosopis L., Tillandsia L. e Vachellia caven (Molina) Seigler & Ebinger, além da macrófita aquática Lemna L., cuja descrição é inédita para América Latina.

We present time-delay estimates for the quadruply imaged quasar PG 1115+080. Our results are based on almost daily observations for seven months at the ESO MPIA 2.2 m telescope at La Silla Observatory, reaching a signal-to-noise ratio of about 1000 per quasar image. In addition, we re-analyze existing light curves from the literature that we complete with an additional three seasons of monitoring with the Mercator telescope at La Palma Observatory. When exploring the possible source of bias we considered the so-called microlensing time delay, a potential source of systematic error so far never directly accounted for in previous time-delay publications. In 15 yr of data on PG 1115+080, we find no strong evidence of microlensing time delay. Therefore not accounting for this effect, our time-delay estimates on the individual data sets are in good agreement with each other and with the literature. Combining the data sets, we obtain the most precise time-delay estimates to date on PG 1115+080, with Δt(AB) = 8.3+1.5−1.6 days (18.7% precision), Δt(AC) = 9.9+1.1−1.1 days (11.1%) and Δt(BC) = 18.8+1.6−1.6 days (8.5%). Turning these time delays into cosmological constraints is done in a companion paper that makes use of ground-based Adaptive Optics (AO) with the Keck telescope.

Objectives: To investigate the current clinical applications and diagnostic performance of artificial intelligence (AI) in dental and maxillofacial radiology (DMFR). Methods: Studies using applications related to DMFR to develop or implement AI models were sought by searching five electronic databases and four selected core journals in the field of DMFR. The customized assessment criteria based on QUADAS-2 were adapted for quality analysis of the studies included. Results: The initial electronic search yielded 1862 titles, and 50 studies were eventually included. Most studies focused on AI applications for an automated localization of cephalometric landmarks, diagnosis of osteoporosis, classification/segmentation of maxillofacial cysts and/or tumors, and identification of periodontitis/periapical disease. The performance of AI models varies among different algorithms. Conclusion: The AI models proposed in the studies included exhibited wide clinical applications in DMFR. Nevertheless, it is still necessary to further verify the reliability and applicability of the AI models prior to transferring these models into clinical practice.

Abstract Purpose Colorectal cancer (CRC) can be classified according to the chromosomal-instability pathway (a microsatellite-stable (MSS) pathway) and the microsatellite-instability (MSI) pathway. Adjuvant therapy after surgery in advanced CRC is usually based on fluoropyrimidine 5-fluorouracil (5-FU) alone or combined with other agents. Controversy however remains on the use of 5-FU-based regimens in treating MSI-related tumours. Aims To systematically investigate the relationship between tumour microsatellite profile and 5-year overall survival in patients with CRC treated with 5-FU. Methods A systematic literature review of PubMed and Embase databases was conducted. Pre-specified criteria determined study inclusion/exclusion. The PRISMA and QUADAS-2 criteria were used to assess study suitability and quality respectively. Patients were categorised as having either MSI or MSS CRC. Overall 5-year survival was estimated from Kaplan–Meier curves. Publication bias was assessed using funnel-plots and Egger’s test. Results 1807 studies were identified, with meta-analysis performed using nine studies. 5-FU treated individuals with CRC who died at 5 years were found to be 0.31 times less likely to have MSI than those who were alive, although this was not statistically significant. There was an insufficient number of studies to enable subgroup analysis by stage. Conclusions In this meta-analysis, MSI status does not alter 5-year survival of patients with CRC patients treated with adjuvant 5-FU, however there is significant heterogeneity in the design of individual studies in the data synthesis. More studies are necessary to clarify whether CRC patients with MSI CRC, in particular early stage, should be offered 5-FU based adjuvant chemotherapy.

Abstract Ultrasonographic evaluation of polycystic ovarian morphology (PCOM) is part of the diagnostic evaluation of polycystic ovarian syndrome (PCOS). The relevance of PCOM as a diagnostic criterion for PCOS was reaffirmed in the most recent International Evidence-Based Guideline for the Assessment and Management of PCOS. However, there remains a lack of clarity regarding the best practices and specific ultrasonographic markers to define PCOM. We synthesized evidence on diagnostic test accuracy of ovarian ultrasound features to comprehensively determine the most suitable markers to diagnose PCOS. The primary outcome was diagnostic accuracy measures (e. g., thresholds, sensitivity, specificity) for PCOS using the following ovarian markers: follicle number per ovary (FNPO) or per single cross-section (FNPS), ovarian volume (OV), and stromal features. Databases of PubMed, Web of Science, Scopus, CINAHL, and CENTRAL were searched until 7 November 2021 to identify studies that compared ultrasound markers between women with PCOS to those without PCOS. Risk of bias and applicability assessment for diagnostic test accuracy studies were determined using the QUADAS-2 and QUADAS-C tool for a single index test or between multiple index tests, respectively. From a total of 1869 records initially identified, 22 studies were included and 18 (N=6,337; [n=2991 PCOS; n= 3346 Control]) were pooled for meta-analysis. FNPO was the most accurate diagnostic marker (sensitivity: 84%, CI: 81% to 87%; specificity: 91%, CI: 87% to 94%). OV and FNPS had similar but inferior pooled sensitivity (OV: 81%, CI: 75% to 86%; FNPS: 81%, CI: 70% to 89%) and specificity (OV: 79%, CI: 73% to 84%; FNPS: 83%, CI: 75% to 88%) compared to FNPO. Majority of studies had high risk of bias for patient selection and index test methodology across all markers. Subgroup analysis indicated that stratification based on age, body mass index (BMI), and previously proposed thresholds did not account for the heterogeneity in diagnostic accuracy observed across studies. For FNPO, studies that used a transducer frequency <8MHz or the Rotterdam criteria had improved positive likelihood ratio (+LR) and sensitivity, respectively. European studies had improved diagnostic accuracy (specificity, diagnostic odds ratio, +LR) compared to North American studies for FNPO, potentially due to BMI differences between PCOS populations (North America: 30.29 ± 0.61kg/m2, Europe: 27.62 ± 0.73kg/m2). Our findings support the use of FNPO as the gold standard in the ultrasonographic diagnosis of PCOS, with OV and FNPS as robust alternatives if total antral follicle counts cannot be obtained. These findings also identify avenues for future research to refine the ultrasonographic definition of PCOM for timely diagnosis of PCOS and investigations into phenotypic variations in pathogenesis and response to treatment in this condition (PROSPERO ID: CRD42021259118). Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

Typen und weiteres Material von zwölf Gattungen, davon eine neu, der Tribus Lomechusini aus der Paläarktis und der Orientalis werden revidiert. Insgesamt 70 Arten, davon 51 neu, werden beschrieben bzw. redeskribiert und/oder abgebildet: Orphnebius bakeri Bernhauer, 1929; O. breviceps Cameron, 1946; O. opticus Cameron, 1946; O. bicuspis spec. nov. (Laos; Indien: Arunachal Pradesh); O. biformis spec. nov. (Indonesien: Sumatra); O. cernens spec. nov. (Laos); O. dilatatus spec. nov. (Laos); O. effeminatus spec. nov. (Malaysia); O. extensus spec. nov. (Laos); O. fodens spec. nov. (Malaysia: Sabah); O. fuscapicalis spec. nov. (Laos); O. fusicollis spec. nov. (Laos); O. grandicollis spec. nov. (Laos); O. integer spec. nov. (Laos); O. latitibialis spec. nov. (Laos); O. lunatus spec. nov. (Laos); O. nigrapicalis spec. nov. (Laos); O. reductus spec. nov. (Laos); O. retunsus spec. nov. (Laos); O. serratus spec. nov. (Laos); O. spinans spec. nov. (Indien: Arunachal Pradesh); Orphnebius (Deroleptus) falagrioides Bernhauer, 1929; O. (D.) laticeps Cameron, 1925; O. (D.) multimpressus Assing, 2015; O. (D.) niger (Cameron, 1939); O. (D.) siamensis Cameron, 1939; O. (D.) baccillatus spec. nov. (Laos); O. (D.) biimpressus spec. nov. (Indonesien: Sumatra); O. (D.) carinatus spec. nov. (Laos); O. (D.) cultellatus spec. nov. (Thailand, Laos); O. (D.) discrepans spec. nov. (China: Yunnan); O. (D.) dispar spec. nov. (Indien: Arunachal Pradesh); O. (D.) gracilior spec. nov. (Indien: Arunachal Pradesh); O. (D.) septemcuspis spec. nov. (Laos); O. (D.) sexcarinatus spec. nov. (Indonesien: Sumatra); O. (D.) spoliatus spec. nov. (Laos); O. (D.) tortus spec. nov. (Indien: Meghalaya); O. (D.) triapicalis spec. nov. (China: Sichuan); O. (D.) ulcerosus spec. nov. (Malaysia: Sabah); O. (D.) vates spec. nov. (Laos); Drusilla bifida spec. nov. (Thailand); Rabdotodrusilla pectinata spec. nov. (Thailand); Amaurodera meorum Pace, 1992; A. thailandensis Pace, 1986; A. arunica spec. nov. (Nepal); A. dentata spec. nov. (Thailand); A. disparicollis spec. nov. (Indonesien: Sumatra); A. fasciata spec. nov. (Thailand); A. gilvios spec. nov. (Thailand); A. parvoculata spec. nov. (Thailand); A. reticulata spec. nov. (Thailand); A. spinans spec. nov. (Indonesien: Sumatra); A. varicollis spec. nov. (Indonesien: Sumatra); Tetrabothrus borneensis Cameron, 1943; T. indicus Cameron, 1939; T. inflexus Assing, 2015; T. neoguineensis Pace, 2012; T. pubescens Bernhauer, 1915; T. breviatus spec. nov. (China: Sichuan); T. collucatus spec. nov. (Laos); T. nilgiricus spec. nov. (Indien: Tamil Nadu); T. punctiventris spec. nov. (Malaysia: Sabah); T. sulawesicus spec. nov. (Indonesien: Sulawesi Utara); Zyras (Zyras) gibbus Pace, 2010; Z. (Z.) illecebrosus Last, 1982; Z. (Z.) quasar Dvořak, 1996; Z. (Z.) porrectus spec. nov. (China: Sichuan); Z. (Z.) wunderlei spec. nov. (Indonesien: Bali); Pedinopleurus notabilis (Silvestri, 1946); Aenictoides gen. nov. derivata spec. nov. (Thailand). Die phylogenetischen Beziehungen innerhalb der Gattung Orphnebius Motschulsky, 1858 sowie das derzeit gebräuchliche Untergattungssystem werden diskutiert; mehrere neue Artengruppen werden charakterisiert. Folgende Namen werden synonymisiert: Deroleptus Bernhauer, 1915 = Megalocephalobius Bernhauer, 1929, syn. nov.; Orphnebius breviceps Cameron, 1946 = O. vorax Pace, 2000, syn. nov.; Orphnebius niger (Cameron, 1939) = O. turensis Pace, 2012, syn. nov.; Drusilla canaliculata (Fabricius, 1787) = Myrmedonia polyporina Gistel, 1857, syn. nov.; Drusilla erichsoni (Peyron, 1857) = Myrmedonia aptera Peyron, 1858, syn. nov.; Drusilla zyrasoides Dvořak, 1988 = D. truncatella Pace, 2004, syn. nov.; Amaurodera kraepelini Fauvel, 1905 = A. rougemonti Pace, 1987, syn. nov., = A. smetanai Pace, 1992, syn. nov., = A. yaoana Pace, 1992, syn. nov.; Tetrabothrus bicolor Cameron, 1939 = T. chinensis Pace, 2012, syn. nov.; Tetrabothrus puetzi Assing, 2009 = T. taiwanensis Pace, 2010, syn. nov.; Tetrabothrus clavatus Bernhauer, 1915 = T. quadricollis Cameron, 1950, syn. nov., = T. japonicus Nakane, 1991, syn. nov., = T. vietnamiculus Pace, 2013, syn. nov., = T. rubricollis Assing, 2015, syn. nov.; Zyras fratrumkadooriorum Pace, 1998 = Z. chumphonensis Pace, 2004, syn. nov.; Pedinopleurus notabilis (Silvestri, 1946) = P. setosicauda Dvořák, 1996, syn. nov. Für Deroleptus niger Cameron, 1939, Orphnebius falagrioides Bernhauer, 1929, Myrmedonia aptera Peyron, 1858 und Tetrabothrus indicus Cameron, 1939 werden Lectotypen designiert. Orphnebius krypticola Pace, 2007 wird als korrekte originale Schreibweise festgelegt. Für Amaurodera Fauvel, 1905 und Tetrabothrus Bernhauer, 1915 werden aktualisierte Kataloge, für die Orphnebius-Arten von Laos und die Amaurodera-Arten Thailands werden Bestimmungstabellen erstellt. Weitere Nachweise von 41 beschriebenen und einigen unbenannten Arten werden gemeldet, darunter zahlreiche Erstnachweise. Die derzeit bekannte Verbreitung von zwei Arten wird anhand von Karten illustriert.StichwörterColeoptera, Staphylinidae, Aleocharinae, Lomechusini, Palaearctic region, Oriental region, taxonomy, new genus, new species, new synonymies, lectotype designations, keys to species, catalogues, additional records, distribution maps.Nomenklatorische Handlungenderivata Assing, 2016 (Aenictoides), spec. n.arunica Assing, 2016 (Amaurodera), spec. n.dentata Assing, 2016 (Amaurodera), spec. n.disparicollis Assing, 2016 (Amaurodera), spec. n.fasciata Assing, 2016 (Amaurodera), spec. n.gilvios Assing, 2016 (Amaurodera), spec. n.kraepelini rougemonti Pace, 1987 (Amaurodera), syn. n. of Amaurodera kraepelini Fauvel, 1905parvoculata Assing, 2016 (Amaurodera), spec. n.reticulata Assing, 2016 (Amaurodera), spec. n.smetanai Pace, 1992a (Amaurodera), syn. n. of Amaurodera kraepelini Fauvel, 1905spinans Assing, 2016 (Amaurodera), spec. n.varicollis Assing, 2016 (Amaurodera), spec. n.yaoana Pace, 1992b (Amaurodera), syn. n. of Amaurodera kraepelini Fauvel, 1905bifida Assing, 2016 (Drusilla), spec. n.truncatella Pace, 2004 (Drusilla), syn. n. of Drusilla zyrasoides Dvorák, 1988Aenictoides Assing, 2016 (Lomechusini), gen. n.aptera Peyron, 1858 (Myrmedonia), syn. n. of Drusilla (Drusilla) erichsoni (Peyron, 1857)polyporina Gistel, 1857 (Myrmedonia), syn. n. of Drusilla (Drusilla) canaliculata (Fabricius, 1787)bicuspis Assing, 2016 (Orphnebius), spec. n.biformis Assing, 2016 (Orphnebius), spec. n.cernens Assing, 2016 (Orphnebius), spec. n.dilatatus Assing, 2016 (Orphnebius), spec. n.effeminatus Assing, 2016 (Orphnebius), spec. n.extensus Assing, 2016 (Orphnebius), spec. n.falagrioides Bernhauer, 1929 (Orphnebius), LT; described as Orphnebius (Megalocephalobius) Bernhauer, 1929fodens Assing, 2016 (Orphnebius), spec. n.fuscapicalis Assing, 2016 (Orphnebius), spec. n.fuscicollis Assing, 2016 (Orphnebius), spec. n.grandicollis Assing, 2016 (Orphnebius), spec. n.integer Assing, 2016 (Orphnebius), spec. n.latitibialis Assing, 2016 (Orphnebius), spec. n.lunatus Assing, 2016 (Orphnebius), spec. n.nigrapicalis Assing, 2016 (Orphnebius), spec. n.reductus Assing, 2016 (Orphnebius), spec. n.retunsus Assing, 2016 (Orphnebius), spec. n.serratus Assing, 2016 (Orphnebius), spec. n.spinans Assing, 2016 (Orphnebius), spec. n.turensis Pace, 2012b (Orphnebius), syn. n. of Orphnebius (Deroleptus) niger (Cameron, 1939)vorax Pace, 2000 (Orphnebius), syn. n. of Orphnebius breviceps Cameron, 1946baccillatus Assing, 2016 (Orphnebius (Deroleptus)), spec. n.biimpressus Assing, 2016 (Orphnebius (Deroleptus)), spec. n.carinatus Assing, 2016 (Orphnebius (Deroleptus)), spec. n.cultellatus Assing, 2016 (Orphnebius (Deroleptus)), spec. n.discrepans Assing, 2016 (Orphnebius (Deroleptus)), spec. n.dispar Assing, 2016 (Orphnebius (Deroleptus)), spec. n.gracilior Assing, 2016 (Orphnebius (Deroleptus)), spec. n.septemcuspis Assing, 2016 (Orphnebius (Deroleptus)), spec. n.sexcarinatus Assing, 2016 (Orphnebius (Deroleptus)), spec. n.spoliatus Assing, 2016 (Orphnebius (Deroleptus)), spec. n.tortus Assing, 2016 (Orphnebius (Deroleptus)), spec. n.triapicalis Assing, 2016 (Orphnebius (Deroleptus)), spec. n.ulcerosus Assing, 2016 (Orphnebius (Deroleptus)), spec. n.vates Assing, 2016 (Orphnebius (Deroleptus)), spec. n.pectinata Assing, 2016 (Rabdotodrusilla), spec. n.breviatus Assing, 2016 (Tetrabothrus), spec. n.chinensis Pace, 2012a (Tetrabothrus), syn. n. of Tetrabothrus bicolor Cameron, 1939collucatus Assing, 2016 (Tetrabothrus), spec. n.japonicus Nakane, 1991 (Tetrabothrus), syn. n. of Tetrabothrus clavatus Bernhauer, 1915nilgiricus Assing, 2016 (Tetrabothrus), spec. n.punctiventris Assing, 2016 (Tetrabothrus), spec. n.quadricollis Cameron, 1950 (Tetrabothrus), syn. n. of Tetrabothrus clavatus Bernhauer, 1915rubricollis Assing, 2015 (Tetrabothrus), syn. n. of Tetrabothrus clavatus Bernhauer, 1915sulawesicus Assing, 2016 (Tetrabothrus), spec. n.taiwanensis Pace, 2010 (Tetrabothrus), syn. n. of Tetrabothrus puetzi Assing, 2009vietnamiculus Pace, 2013 (Tetrabothrus), syn. n. of Tetrabothrus clavatus Bernhauer, 1915chumphonensis Pace, 2004 (Zyras (Zyras)), syn. n. of Zyras (Zyras) fratrumkadooriorum Pace, 1998porrectus Assing, 2016 (Zyras (Zyras)), spec. n.wunderlei Assing, 2016 (Zyras (Zyras)), spec. n.

Introduction Female endurance athletes, such as runners, show a high prevalence of menstrual cycle (MC) related symptoms and diseases (Dusek, 2001). Almost one in four runners and 65% of long-distance runners are suffering from secondary amenorrhea (Dusek, 2001) and consecutive symptoms, such as an increased risk of injury, reduced bone mass, and a higher risk for cardiovascular diseases (Ihalainen et al., 2021). Causes for MC-related symptoms or diseases are multifactorial but in sports, a relationship to the training load, recovery, and sufficient energy availability exists (Redman & Loucks, 2005). Evidence is growing that the MC phases affect endurance performance development, training response, and recovery in eumenorrheic women (with normal or regular menstruation), and adaptions of the training program to the MC could reduce risk factors for MC-related symptoms and diseases (Ihalainen et al., 2021; McNulty et al., 2020; Oosthuye & Bosch, 2010). This assumption is based on the changes in steroid hormone concentrations of estrogen and progesterone and their interactions (Pitchers & Elliott-Sale, 2019) during the MC. Five phases usually describe the MC: the early follicular phase, beginning with the onset of menses; the late follicular phase; ovulation; early-, mid-, and late luteal phase (Janse de Jonge et al., 2019). High estrogen levels characterize the late follicular phase and ovulation. In comparison, during the mid-luteal phase, progesterone is the dominating hormone (Janse de Jonge et al., 2019). Current findings in resistance training support the idea that responses to follicular phase-based training are superior to luteal-phase-based or regular training (Thompson et al., 2020). Adaptions of a traditional training program, such as polarized training (Kenneally et al., 2018), to the individual MC phases may impact training response, adaptation, and recovery in female runners (Ihalainen et al., 2021). To our knowledge, no study has investigated the impact of a polarized training intervention tailored to the MC on performance, recovery, and well-being in eumenorrheic women. Therefore, this study aimed to assess the effectiveness of polarized training in female runners and polarized training adaption to the MC phases on endurance performance development, recovery, and MC-related symptoms, as a part of well-being. Methods Fourteen eumenorrheic, moderately trained female runners (age: 24 ±2.8 years; BMI: 22.3 ±2.6 kg/cm2; 240 ±152 min of moderate to vigorous physical activity/week) took part in an 8-week running training intervention consisting of three weekly training sessions. The participants were randomly assigned to a control and an intervention group. Menstrual cycles and time points of menstruation and ovulation were determined by calendar-based counting. The control group (CG) followed a general polarized training program (Muñoz et al., 2014) consisting of two 4-week mesocycles. The mesocycles included three weeks of progressive training load and one week with a reduced load, not adjusted to the MC. The intervention group (IG) followed the same training. However, the single training sessions were adapted to their MC with a higher training load within the follicular phase, medium training load within the luteal phase, and regeneration during the premenstrual and menstrual phases. Both interventions were load-matched and controlled by the training impulse (TRIMP) of all training sessions. At baseline and following the intervention period, anthropometrics (weight, height, BMI), performance (countermovement jump performance [CMJ] [OptoGait, MicroGait, Italy], and maximum oxygen uptake [VO2peak {treadmill: Quasar, h/p/cosmos, Germany; respiratory gas analyzer: MetaMax 3B, Cortex, Germany}]) were assessed. The TRIMP and rate of perceived exertion (RPE) were collected to determine training loads for each training session. Furthermore, recovery and well-being were monitored using the short version of the Recovery and Stress Questionnaire (SRSS; recovery subscale: rSRSS; stress subscale: sSRSS) in the baseline assessment and at the end of the training intervention. The premenstrual assessment form (PAF) was used to determine MC-related symptoms at the same time points. Results Seven females were each randomly assigned to the IG (age: 22.4 ±1.2; BMI: 22.7 ±2.9 kg/cm2; VO2peak: 41.1 ±4.4 ml/min/kg; CMJ: 26.7 ±6.2; PAF: 23.1 ±8,4; rSRSS: 16.6 ±2.3) and to the CG (age: 24.1 ±3.0; BMI: 21.8 ±2.1 kg/cm2; VO2peak: 43.6 ±6.1 ml/min/kg; CMJ: 27.1 ±5.9 cm; PAF: 25.6 ±5.8; rSRSS: 14.1 ±2.7). No significant group differences were revealed in the baseline assessment for anthropometrics, performance, recovery, and well-being (p < .05). A repeated measures ANOVA with a Greenhouse-Geisser correction determined no statistically significant time x group interaction effects in mean performance levels (VO2peak: F(1, 6) = 0.21 p = .890 η² = .003; CMJ: F(1,6) = .691 p = .690 η² = .028). Also no significant time x group interactions effects were found for PAF (F[1,6] = .293 p = .608 η² = .047); rSRSS (F[1,6] = .153 p = .709 η² = .0.25) and sSRSS (F[1,6] = .004 p = .952 η² = .0.001). A significant time effect was found for VO2peak (F[1,6] = 17.93 p = .005 partial η² = .75), but not for the other parameters (p < .05). No group effect was found for any of the parameters (p < .05). Discussion, conclusion, and research perspective An 8-week polarized running training, block-periodized or individually adapted to the MC, is efficacious in improving VO2peak in eumenorrheic female runners. These results are in line with previous findings (Muñoz et al., 2014; Stöggl & Sperlich, 2014). Running training adapted to the menstrual cycle seems to impact performance development in an 8-week training intervention to the same extent as traditional block-periodized training. Our results implicate no further benefits of an MC adapted training on recovery and premenstrual symptoms in recreational runners. However, a post-analysis revealed that in 57% of participants in the CG, training recovery phases of the block-periodized training protocol randomly matched with current recommendations for the late-luteal and early-follicular phase of their MC (Pitchers & Elliott-Sale, 2019).Therefore, the structure of the training protocols between the IG and CG did not really differ. Additionally, the less reliable calendar-based determination of the menstrual cycle (Thompson & Han, 2019) limits the generalization of the results and comparability of the IG and CG. Therefore, we are currently conducting a study with a lager sample size and enhanced study design, including determining the menstrual cycle via changes in basal body temperature and luteinizing hormone occurrence. The control group’s training program will be adapted contrary to the current menstrual cycle training recommendations (Pitchers & Elliott-Sale, 2019) to avoid random matches for the recovery phase. Furthermore, questionnaire-based data assessing recovery, well-being, and (pre-)menstrual symptoms using ecologic-momentary assessment and daily heart rate variability measurements will be included to get an in-depth insight into the well-being of the eumenorrheic women. The follow-up study results will be presented at the conference. References Dušek, T. (2001). Influence of high intensity training on menstrual cycle disorders in athletes. Croatian Medical Journal, 42(1), 79-82. Ihalainen, J. K., Kettunen, O., McGawley, K., Solli, G. S., Hackney, A. C., Mero, A. A., & Kyröläinen, H. (2021). Body composition, energy availability, training, and menstrual status in female runners. International Journal of Sports Physiology and Performance, 16(7), 1043-1048. https://doi.org/10.1123/ijspp.2020-0276 Janse de Jonge, X., Thompson, B., & Han, A. (2019). Methodological recommendations for menstrual cycle research in sports and exercise. Medicine and Science in Sports and Exercise, 51(12), 2610–2617. https://doi.org/10.1249/MSS.0000000000002073 Kenneally, M., Casado, A., & Santos-Concejero, J. (2018). The effect of periodization and training intensity distribution on middle-and long-distance running performance: A systematic review. International Journal of Sports Physiology and Performance, 13(9), 1114-1121. https://doi.org/10.1123/ijspp.2017-0327 McNulty, K. L., Elliott-Sale, K. J., Dolan, E., Swinton, P. A., Ansdell, P., Goodall, S., Thomas, K., & Hicks, K. M. (2020). 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Abstract We present the results from a MUSE survey of twelve z ≃ 3.15 quasars, which were selected to be much fainter (20 &lt; iSDSS &lt; 23) than in previous studies of Giant Lyα Nebulae around the brightest quasars (16.6 &lt; iAB &lt; 18.7). We detect H I Lyα nebulae around 100% of our target quasars, with emission extending to scales of at least 60 physical kpc, and up to 190 pkpc. We explore correlations between properties of the nebulae and their host quasars, with the goal of connecting variations in the properties of the illuminating QSO to the response in nebular emission. We show that the surface brightness profiles of the nebulae are similar to those of nebulae around bright quasars, but with a lower normalization. Our targeted quasars are on average 3.7 magnitudes (≃ 30 times) fainter in UV continuum than our bright reference sample, and yet the nebulae around them are only 4.3 times fainter in mean Lyα surface brightness, measured between 20 and 50 pkpc. We find significant correlations between the surface brightness of the nebula and the luminosity of the quasar in both UV continuum and Lyα. The latter can be interpreted as evidence for a substantial contribution from unresolved inner parts of the nebulae to the narrow components seen in the Lyα lines of some of our faint quasars, possibly from the inner CGM or from the host galaxy’s ISM.

The diagnosis chronic exertional compartment syndrome is traditionally linked to elevated intracompartmental pressures, although uncertainty regarding this diagnostic instrument is increasing. The aim of current review was to evaluate literature for alternative diagnostic tests. A search in line with PRISMA criteria was conducted. Studies evaluating diagnostic tests for chronic exertional compartment syndrome other than intracompartmental pressure measurements were included. Bias and quality of studies were evaluated using the Oxford Levels of Evidence and the QUADAS-2 instrument. A total of 28 studies met study criteria (MRI n=8, SPECT n=6, NIRS n=4, MRI and NIRS together n=1, miscellaneous modalities n=9). Promising results were reported for MRI (n = 4), NIRS (n = 4) and SPECT (n = 3). These imaging techniques rely on detecting changes of signal intensity in manually selected regions of interest in the muscle compartments of the leg. Yet, diagnostic tools and protocols were diverse. Moreover, five studies explored alternative modalities serving as an adjunct, rather than replacing pressure measurements. Future research is warranted as clinical and methodological heterogeneity were present and high quality validation studies were absent. Further optimization of specific key criteria based on a patient’s history, physical examination and symptom provocation may potentially render intracompartmental pressure measurement redundant.