Arginine vasopressin:Direct and indirect action on metabolism

From its identification and isolation in 1954, arginine vasopressin (AVP) has attracted attention, not only for its peripheral functions such as vasoconstriction and reabsorption of water from kidney, but also for its central effects. As there is now considerable evidence that AVP plays a crucial role in feeding behavior and energy balance, it has become a promising therapeutic target for treating obesity or other obesity-related metabolic disorders. However, the underlying mechanisms for AVP regulation of these central processes still remain largely unknown. In this review, we will provide a brief overview of the current knowledge concerning how AVP controls energy balance and feeding behavior, focusing on physiological aspects including the relationship between AVP, circadian rhythmicity, and glucocorticoids

Analyses of integrated EPID images for on-treatment quality assurance to account for interfractional variations in volumetric modulated arc therapy

Purpose: To investigate the effects of interfractional variation, such as anatomical changes and setup errors, on dose delivery during treatment for prostate cancer (PC) and head and neck cancer (HNC) by courses of volumetric modulated arc therapy (VMAT) aided by on‐treatment electronic portal imaging device (EPID) images. Methods: Seven patients with PC and 20 patients with HNC who had received VMAT participated in this study. After obtaining photon fluence at the position of the EPID for each treatment arc from on‐treatment integrated EPID images, we calculated the differences between the fluence for the first fraction and each subsequent fraction for each arc. The passing rates were investigated based on a tolerance level of 3% of the maximum fluence during the treatment courses and the correlations between the passing rates and anatomical changes. Results: In PC, the median and lowest passing rates were 99.8% and 95.2%, respectively. No correlations between passing rates and interfractional variation were found. In HNC, the median passing rate of all fractions was 93.0%, and the lowest passing rate was 79.6% during the 35th fraction. Spearman’s correlation coefficients between the passing rates and changes in weight or neck volume were − 0.77 and − 0.74, respectively. Conclusions: Analyses of the on‐treatment EPID images facilitates estimates of the interfractional anatomical variation in HNC patients during VMAT and thus improves assessments of the need for re‐planning or adaptive strategies and the timing thereof

Vaginal stimulation enhances ovulation of queen ovaries treated using a combination of eCG and hCG

Follicular changes throughout the oestrous phase have been poorly documented in queens because of the location and the small size of ovaries. We investigated follicular development in queens treated with a combination of equine chorionic gonadotropin (eCG) and human chorionic gonadotropin (hCG) and evaluated the effects of vaginal stimulation by a tomcat on ovulation induction. A hormonal treatment was administered using a simple crossover design. Four queens were administered 150 IU of eCG (day 1) and 250 IU of hCG on day 5 and 6. Half of the queens were mated with a vasectomised tomcat for 3 days after hCG injection. Ultrasound imaging of the ovaries clamped at a subcutaneous site was performed once a day from day 1 to 7, and on day 13, and the serum concentrations of oestradiol and progesterone were examined on day 1, 5, 7 and 13. The mean number of follicles gradually increased with the eCG treatment and decreased after hCG injection. The ovulation rate of follicles was significantly higher in the vaginal stimulation group (70.0%) than in the control group (42.6%). During the hormonal treatments, the serum concentration of oestradiol and progesterone did not differ between the two groups. Ultrasound imaging of the ovaries clamped at a subcutaneous site showed that eCG and hCG treatment promoted the follicular growth and corpus luteum formation, respectively. The combination of hCG injection with vaginal stimulation by a vasectomised tomcat enhanced the ovulation rate of follicles

Development of AI-driven prediction models to realize real-time tumor tracking during radiotherapy

[Background] In infrared reflective (IR) marker-based hybrid real-time tumor tracking (RTTT), the internal target position is predicted with the positions of IR markers attached on the patient’s body surface using a prediction model. In this work, we developed two artificial intelligence (AI)-driven prediction models to improve RTTT radiotherapy, namely, a convolutional neural network (CNN) and an adaptive neuro-fuzzy inference system (ANFIS) model. The models aim to improve the accuracy in predicting three-dimensional tumor motion. [Methods] From patients whose respiration-induced motion of the tumor, indicated by the fiducial markers, exceeded 8 mm, 1079 logfiles of IR marker-based hybrid RTTT (IR Tracking) with the gimbal-head radiotherapy system were acquired and randomly divided into two datasets. All the included patients were breathing freely with more than four external IR markers. The historical dataset for the CNN model contained 1003 logfiles, while the remaining 76 logfiles complemented the evaluation dataset. The logfiles recorded the external IR marker positions at a frequency of 60 Hz and fiducial markers as surrogates for the detected target positions every 80-640 ms for 20-40 s. For each logfile in the evaluation dataset, the prediction models were trained based on the data in the first three quarters of the recording period. In the last quarter, the performance of the patient-specific prediction models was tested and evaluated. The overall performance of the AI-driven prediction models was ranked by the percentage of predicted target position within 2 mm of the detected target position. Moreover, the performance of the AI-driven models was compared to a regression prediction model currently implemented in gimbal-head radiotherapy systems. [Results] The percentage of the predicted target position within 2 mm of the detected target position was 95.1%, 92.6% and 85.6% for the CNN, ANFIS, and regression model, respectively. In the evaluation dataset, the CNN, ANFIS, and regression model performed best in 43, 28 and 5 logfiles, respectively. [Conclusions] The proposed AI-driven prediction models outperformed the regression prediction model, and the overall performance of the CNN model was slightly better than that of the ANFIS model on the evaluation dataset

Reducing variability among treatment machines using knowledge‐based planning for head and neck, pancreatic, and rectal cancer

PURPOSE: This study aimed to assess dosimetric indices of RapidPlan model-based plans for different energies (6, 8, 10, and 15 MV; 6- and 10-MV flattening filter-free), multileaf collimator (MLC) types (Millennium 120, High Definition 120, dual-layer MLC), and disease sites (head and neck, pancreatic, and rectal cancer) and compare these parameters with those of clinical plans. METHODS: RapidPlan models in the Eclipse version 15.6 were used with the data of 28, 42, and 20 patients with head and neck, pancreatic, and rectal cancer, respectively. RapidPlan models of head and neck, pancreatic, and rectal cancer were created for TrueBeam STx (High Definition 120) with 6 MV, TrueBeam STx with 10-MV flattening filter-free, and Clinac iX (Millennium 120) with 15 MV, respectively. The models were used to create volumetric-modulated arc therapy plans for a 10-patient test dataset using all energy and MLC types at all disease sites. The Holm test was used to compare multiple dosimetric indices in different treatment machines and energy types. RESULTS: The dosimetric indices for planning target volume and organs at risk in RapidPlan model-based plans were comparable to those in the clinical plan. Furthermore, no dose difference was observed among the RapidPlan models. The variability among RapidPlan models was consistent regardless of the treatment machines, MLC types, and energy. CONCLUSIONS: Dosimetric indices of RapidPlan model-based plans appear to be comparable to the ones based on clinical plans regardless of energies, MLC types, and disease sites. The results suggest that the RapidPlan model can generate treatment plans independent of the type of treatment machine

Acute Polyradiculoneuropathy Associated With Salmonella Gastroenteritis

We reported a case of acute polyradiculoneuropathy associated with Salmonella gastroenteritis. A68-year-oldman developed progressive motor weakness and areflexia following the febrile illness and diarrhea caused by a strain of Salmonella species O8 group. He showed a rapid and complete recovery from the illness. This is the first report in which Salmonella gastroenteritis might be etiologically related to an acute polyradiculoneuropathy

Dosimetric Comparison between Dynamic Wave Arc and Co-Planar Volumetric Modulated Radiotherapy for Locally Advanced Pancreatic Cancer

Introduction: Dose reduction to the duodenum is important to decrease gastrointestinal toxicities in patients with locally advanced pancreatic cancer (LAPC) treated with definitive chemoradiotherapy. We aimed to compare dynamic wave arc (DWA), a volumetric-modulated beam delivery technique with simultaneous gantry/ring rotations passing the waved trajectories, with coplanar VMAT (co-VMAT) with respect to dose distributions in LAPC cases. Material and Methods: DWA and co-VMAT plans were created for 13 patients with LAPC. The prescribed dose was 45.6 or 48 Gy in 15 fractions. The dose volume indices (DVIs) for target volumes and organs at risk were compared between the corresponding plans. Gamma passing rate, monitor unit (MU), and beam-on time were also compared. Results: DWA significantly reduced the duodenal V39Gy, V42Gy, and V45Gy by 1.1, 0.8, and 0.2 cm3, and increased the liver mean dose and D2cm3 of the spinal cord planning volume by 1.0 and 1.5 Gy, respectively. Meanwhile, there was no significant difference in the target volumes except for D2% of PTV (111.5% in DWA vs. 110.5% in co-VMAT). Further, the gamma passing rate was similar in both plans. MU and beam-on time increased in DWA by 31 MUs and 15 seconds, respectively. Conclusion: DWA generated significantly lower duodenal doses in LAPC cases, albeit with slight increasing liver and spinal cord doses and increasing MU and the beam delivery time. Further evaluation is needed to know how the dose differences would affect the clinical outcomes in chemoradiotherapy for LAPC

Opposing role of condensin hinge against replication protein A in mitosis and interphase through promoting DNA annealing

Condensin is required for chromosome dynamics and diverse DNA metabolism. How condensin works, however, is not well understood. Condensin contains two structural maintenance of chromosomes (SMC) subunits with the terminal globular domains connected to coiled-coil that is interrupted by the central hinge. Heterotrimeric non-SMC subunits regulate SMC. We identified a novel fission yeast SMC hinge mutant, cut14-Y1, which displayed defects in DNA damage repair and chromosome segregation. It contains an amino acid substitution at a conserved hinge residue of Cut14/SMC2, resulting in diminished DNA binding and annealing. A replication protein A mutant, ssb1-418, greatly alleviated the repair and mitotic defects of cut14-Y1. Ssb1 protein formed nucleolar foci in cut14-Y1 cells, but the number of foci was diminished in cut14-Y1 ssb1-418 double mutants. Consistent with the above results, Ssb1 protein bound to single-strand DNA was removed by condensin or the SMC dimer through DNA reannealing in vitro. Similarly, RNA hybridized to DNA may be removed by the SMC dimer. Thus, condensin may wind up DNA strands to unload chromosomal components after DNA repair and prior to mitosis. We show that 16 suppressor mutations of cut14-Y1 were all mapped within the hinge domain, which surrounded the original L543 mutation site