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Background Personalized medicine requires the integration and analysis of vast amounts of patient data to realize individualized care. With Surgomics, we aim to facilitate personalized therapy recommendations in surgery by integration of intraoperative surgical data and their analysis with machine learning methods to leverage the potential of this data in analogy to Radiomics and Genomics. Methods We defined Surgomics as the entirety of surgomic features that are process characteristics of a surgical procedure automatically derived from multimodal intraoperative data to quantify processes in the operating room. In a multidisciplinary team we discussed potential data sources like endoscopic videos, vital sign monitoring, medical devices and instruments and respective surgomic features. Subsequently, an online questionnaire was sent to experts from surgery and (computer) science at multiple centers for rating the features’ clinical relevance and technical feasibility. Results In total, 52 surgomic features were identified and assigned to eight feature categories. Based on the expert survey (n = 66 participants) the feature category with the highest clinical relevance as rated by surgeons was “surgical skill and quality of performance” for morbidity and mortality (9.0 ± 1.3 on a numerical rating scale from 1 to 10) as well as for long-term (oncological) outcome (8.2 ± 1.8). The feature category with the highest feasibility to be automatically extracted as rated by (computer) scientists was “Instrument” (8.5 ± 1.7). Among the surgomic features ranked as most relevant in their respective category were “intraoperative adverse events”, “action performed with instruments”, “vital sign monitoring”, and “difficulty of surgery”. Conclusion Surgomics is a promising concept for the analysis of intraoperative data. Surgomics may be used together with preoperative features from clinical data and Radiomics to predict postoperative morbidity, mortality and long-term outcome, as well as to provide tailored feedback for surgeons. Graphical abstract

StructuredAbstractBackgroundLack of anatomy recognition represents a clinically relevant risk in abdominal surgery. Machine learning (ML) methods can help identify visible patterns and risk structures, however, their practical value remains largely unclear.Materials and MethodsBased on a novel dataset of 13195 laparoscopic images with pixel-wise segmentations of eleven anatomical structures, we developed specialized segmentation models for each structure and combined models for all anatomical structures using two state-of-the-art model architectures (DeepLabv3 and SegFormer), and compared segmentation performance of algorithms to a cohort of 28 physicians, medical students, and medical laypersons using the example of pancreas segmentation.ResultsMean Intersection-over-Union for semantic segmentation of intraabdominal structures ranged from 0.28 to 0.83 and from 0.23 to 0.77 for the DeepLabv3-based structure-specific and combined models, and from 0.31 to 0.85 and from 0.26 to 0.67 for the SegFormer-based structure-specific and combined models, respectively. Both the structure-specific and the combined DeepLabv3-based models are capable of near-real-time operation, while the SegFormer-based models are not. All four models outperformed at least 26 out of 28 human participants in pancreas segmentation.ConclusionsThese results demonstrate that ML methods have the potential to provide relevant assistance in anatomy recognition in minimally-invasive surgery in near-real-time. Future research should investigate the educational value and subsequent clinical impact of respective assistance systems.HighlightsMachine learning models to reduce surgical risks that precisely identify 11 anatomical structures: abdominal wall, colon, intestinal vessels (inferior mesenteric artery and inferior mesenteric vein with their subsidiary vessels), liver, pancreas, small intestine, spleen, stomach, ureter and vesicular glandsLarge training dataset of 13195 real-world laparoscopic images with high-quality anatomy annotationsSimilar performance of individual segmentation models for each structure and combined segmentation models in identifying intraabdominal structures, and similar segmentation performance of DeepLabv3-based and SegFormer-based modelsDeepLabv3-based models are capable of near-real-time operation while SegFormer-based models are not, but SegFormer-based models outperform DeepLabv3-based models in terms of accuracy and generalizabilityAll models outperformed at least 26 out of 28 human participants in pancreas segmentation, demonstrating their potential for real-time assistance in recognizing anatomical landmarks during minimally-invasive surgery.

Current micropump technology features bubble tolerance and self-priming ability, achieved with high pressure ability at shallow pump chambers for low dead volume and high compression ratio. Though, the pump dynamics are strongly affected by a pump chamber height dependent viscous squeeze film damping. Therefore, we investigated all major flow influencing effects for micro diaphragm pumps, being liquid resistive damping, cavitation based gaseous capacitive damping and reactive valve volumes. Analytical models were developed that are able to describe and predict the transient actuator displacement, derive the frequency dependent displacement and estimate the valve loss effect in order to determine the flow rate performance of micropumps. In addition, a new oscillator model is able to simulate the inception of cavitation and the time course of both actuator and liquid. The individual effect models were combined into a single-cycle based, frequency dependent, flow rate model, validated for frequencies of up to 100 Hz. Compared to the maximum achievable flow rate, the liquid resistive damping reduces dynamic stroke volume and is responsible for a reduction of 23-57 % at 100 Hz. Valve induced flow losses reduce the effectively redirected volume towards the outlet. The effect is enhanced by the strong damping, but also feeds back on the actuator by reducing initial damping significantly. Reactive valve volumes amount for 6.2-12.4% flow rate reduction at 100 Hz. Full cavitation, generated at the supply mode and affecting the pump mode, can cause gas bubble generation and lead to a drop of flow rate down to 65% at 80 Hz. By placing an in-line degasser the flow stability was improved to ±2.2% over 10 h. After reducing the frequency to 20 Hz, cavitation only affected the supply mode and in combination with a degasser a flow stability of ±0.15% over 2 h was achieved. By reducing voltage levels, cavitation was avoided completely, featuring a stability of ±0.08%. The understanding of the flow rate limiting effects enables the application specific design to meet all performance and reliability requirements for micropump based liquid dosing systems.

The U.S. Army Reserve Officers' Training Corps (ROTC) is the largest commissioning source among all branches. Physical Readiness Training (PRT) is fundamental to ROTC cadet training. However, although studies have evaluated the effectiveness of PRT in cadets with prior PRT experience, no study has examined the early phase adaptations in those cadets with no prior PRT experience.To determine the effect of PRT over the course of an academic year (9 months) in freshmen ROTC cadets, thirteen (n = 13; 7 male [180.8 ± 4.7 cm, 77.4 ± 10.0 kg; 19.8 ± 6.5 % body fat], 6 female [159.5 ± 12.1 cm; 63.4 ± 8.4 kg; 29.6 ± 6.2% body fat]) cadets with no prior PRT performed laboratory (body composition, 1-repetition maximum [1RM] bench and squat, countermovement vertical jump, maximal aerobic capacity [VONo changes occurred in body composition, VONine months of PRT improved APFT scores of freshmen cadets while minor effects were noted in laboratory-based performance. Given the lack of improvements in strength and power, it would be advisable to provide supplemental strength and power training. Being a large commissioning resource for the Army with greater access to equipment and resources, the time spent in ROTC may be a unique opportunity to improve and educate young commissioning officers on the benefits of proper strength and power training for the use in future commands while units are considerably smaller and equipment is more accessible on university grounds.

This study compared the acute cytokine response, and kinetic and kinematic profile following back squat exercise in resistance-trained men. In a randomized, cross-over design, 10 resistance-trained men (27±4 y, 1.80±0.07 m, 82.8±6.7 kg, 16.3±3.5% fat) performed the back squat exercise using traditional and cluster set configurations. Kinetic and kinematic data were sampled throughout each condition. Venous blood was sampled prior, immediately post, 30 min, 60 min, 24 h, and 48 h post-exercise for plasma interleukin-6 (IL-6) and interleukin-15 (IL-15). Cluster sets allowed for greater mean power (mean difference, 110 W; 90% confidence interval, ±63 W; benefit odds, 41 447:1), driven by higher overall mean velocities (0.053 m∙s−1; 0.039 m∙s−1; 3 105:1) as evidenced by the lack of clear contrasts for mean force. IL-15 increased post-exercise in both conditions, but increased at 24 h (0.13 pg·mL−1; ±0.11 pg·mL−1; 486:1) and 48 h (0.12 pg·mL−1; ±0.10 pg·mL−1; 667:1) in traditional sets only. IL-6 increased similarly in both conditions, post-exercise through 60 min post. Cluster set configurations allow for greater mean power, attributed to higher velocities. Despite a similar response of IL-6, traditional set configuration may provide a greater stimulus for hypertrophy as evidenced by a secondary increase in IL-15.

This investigation compared the kinetics and kinematics of cluster sets (CLU) and traditional sets (TRD) during back squat in trained (RT) and untrained (UT) men. Twenty-four participants (RT = 12, 25 ± 1 year, 179.1 ± 2.2 cm, 84.6 ± 2.1 kg; UT = 12, 25 ± 1 year, 180.1 ± 1.8 cm, 85.4 ± 3.8 kg) performed TRD (4 × 10, 120-second rest) and CLU (4 × (2 × 5) 30 seconds between clusters; 90 seconds between sets) with 70% one repetition maximum, randomly. Kinematics and kinetics were sampled through force plate and linear position transducers. Resistance-trained produced greater overall force, velocity, and power; however, similar patterns were observed in all variables when comparing conditions. Cluster sets produced significantly greater force in isolated repetitions in sets 1-3, while consistently producing greater force due to a required reduction in load during set 4 resulting in greater total volume load (CLU, 3302.4 ± 102.7 kg; TRD, 3274.8 ± 102.8 kg). Velocity loss was lessened in CLU resulting in significantly higher velocities in sets 2 through 4. Furthermore, higher velocities were produced by CLU during later repetitions of each set. Cluster sets produced greater power output for an increasing number of repetitions in each set (set 1, 5 repetitions; sets 2 and 3, 6 repetitions; set 4, 8 repetitions), and the difference between conditions increased over subsequent sets. Time under tension increased over each set and was greater in TRD. This study demonstrates greater power output is driven by greater velocity when back squatting during CLU; therefore, velocity may be a useful measure by which to assess power.

In traditional sets (TRD) repetitions are performed continuously, whereas cluster sets (CLU) allow a brief rest between groups of repetitions. We investigated the acute mechanical, metabolic, and hormonal response to CLU in men. Twelve resistance-trained (RT) and 11 untrained (UT) men performed TRD (4 × 10 repetitions with 2 min rest) and CLU [4 × (2 × 5) with 1.5 min rest between sets 30 s rest between clusters] at 70 % 1RM back squat in random order. Seven days separated trials. Average power and time under tension (TUT) were calculated. Blood was sampled pre, sets 1, 2, and 3; immediate post-exercise, 5, 15, 30, 60 min post-exercise for blood lactate, total testosterone (TT), free testosterone (FT), growth hormone (GH), and cortisol. CLU produced greater average power at an increasing number of repetitions over each set with greater total volume load. TUT was shorter for RT and lower for CLU in repetitions 1, 6, 7, 8. Blood lactate was higher Set 2 through 30 min in TRD. RT had higher TT; however, the time course was similar between RT and UT. TT and FT increased immediate post-exercise and remained elevated 30 min in both conditions. GH was significantly greater during TRD with a similar pattern observed in both conditions. Cortisol was significantly lower at 30 min in CLU. CLU allowed greater total volume load, shorter TUT, greater average power, similar anabolic hormonal response, and less metabolic stress. The acute response was similar despite training status.

Recently published pharmacoepidemiological studies associate the currently authorized Rotavirus (RV) vaccines with intussusception (IS). We aimed at investigating whether, in Germany, there are excess IS cases in RV vaccinees compared with the background incidence before market authorization in 2006. Suspected cases of IS following receipt of RV vaccines reported to the Paul-Ehrlich-Institut (PEI) from 2006 to 2010 were reviewed and validated against the criteria of the Brighton Collaboration's definition for IS. An observed-versus-expected analysis was conducted using standardized morbidity ratio (SMR) methods based on age-specific incidence rates for IS ranging from 19.2 to 98.5 per 100,000 person-years. A total of 27 cases of suspected IS in RV vaccinees were reported to the PEI. No excess of IS cases could be detected 1-7 days after receipt of either RV vaccine after any dose in the first year of life; however, in infants aged 3-5 months, a significantly increased SMR for IS was found in a risk window of 1-7 days after the first dose of either RV vaccine [SMRs: Rotarix® 4.6 (95% CI 1.5-10.7); RotaTeq® 5.8 (95% CI 1.2-17.1)]. A significantly increased risk of IS in a risk window of 1-7 days after RV vaccination was not found when the first dose was administered earlier. Therefore, it is recommended to start the vaccination course at 6-12 weeks of age.

BACKGROUND Rotavirus (RV) vaccination with the first generation vaccine (Rotashield) has been associated with intussusception (IS). Reliable age specific baseline incidence data for children ≤6 months of age in particular is fundamental for further post marketing monitoring of potential effects of recently introduced new RV vaccines. METHODS IS incidence was estimated by a 2-source capture-recapture calculation (CRC) based on ESPED (German Paediatric Surveillance Unit) reports and on hospital discharge records for 2006 and 2007. ESPED as well as hospital records were validated according to the Brighton Collaboration's Group definition for definite IS. PATIENTS Children that have been treated for IS in a hospital in one of two states of Germany (North-Rhine Westphalia and Bavaria). RESULTS The annual IS incidence for infants

pEPI-1, a vector in which a chromosomal scaffold/matrix-attached region (S/MAR) is linked to the simian virus 40 origin of replication, is propagated episomally in CHO cells in the absence of the virally encoded large T-antigen and is stably maintained in the absence of selection pressure. It has been suggested that mitotic stability is provided by a specific interaction of this vector with components of the nuclear matrix. We studied the interactions of pEPI-1 by crosslinking with cis-diamminedichloroplatinum II, after which it is found to copurify with the nuclear matrix. In a south-western analysis, the vector shows exclusive binding to hnRNP-U/SAF-A, a multifunctional scaffold/matrix specific factor. Immunoprecipitation of the crosslinked DNA-protein complex demonstrates that pEPI-1 is bound to this protein in vivo. These data provide the first experimental evidence for the binding of an artificial episome to a nuclear matrix protein in vivo and the basis for understanding the mitotic stability of this novel vector class.

Background Glucagon-like peptide-1 (GLP-1) is an incretin hormone secreted in the intestine in response to food intake. GLP-1 may be responsible for nearly 50% of insulin secretion. Postprandial GLP-1 secretion may be impaired in overweight/obese (OW/O) individuals and in patients with type-2 diabetes (T2D). Meals high in protein (HP) or high in monounsaturated fat (HMF) may increase GLP-1 response. However, there are no studies directly comparing HP with HMF meals on postprandial GLP-1 response.