The Wor1-like Protein Fgp1 Regulates Pathogenicity, Toxin Synthesis and Reproduction in the Phytopathogenic Fungus Fusarium graminearum

WOR1 is a gene for a conserved fungal regulatory protein controlling the dimorphic switch and pathogenicity determents in Candida albicans and its ortholog in the plant pathogen Fusarium oxysporum, called SGE1, is required for pathogenicity and expression of key plant effector proteins. F. graminearum, an important pathogen of cereals, is not known to employ switching and no effector proteins from F. graminearum have been found to date that are required for infection. In this study, the potential role of the WOR1-like gene in pathogenesis was tested in this toxigenic fungus. Deletion of the WOR1 ortholog (called FGP1) in F. graminearum results in greatly reduced pathogenicity and loss of trichothecene toxin accumulation in infected wheat plants and in vitro. The loss of toxin accumulation alone may be sufficient to explain the loss of pathogenicity to wheat. Under toxin-inducing conditions, expression of genes for trichothecene biosynthesis and many other genes are not detected or detected at lower levels in Δfgp1 strains. FGP1 is also involved in the developmental processes of conidium formation and sexual reproduction and modulates a morphological change that accompanies mycotoxin production in vitro. The Wor1-like proteins in Fusarium species have highly conserved N-terminal regions and remarkably divergent C-termini. Interchanging the N- and C- terminal portions of proteins from F. oxysporum and F. graminearum resulted in partial to complete loss of function. Wor1-like proteins are conserved but have evolved to regulate pathogenicity in a range of fungi, likely by adaptations to the C-terminal portion of the protein

Durable Local Control Following Concurrent Hypofractionated Chemoradiation for a Massive Inflammatory Breast Cancer Chest Wall Recurrence.

Breast cancer is the leading new cancer diagnosis in women in the United States and is the second most lethal cancer in this patient population after lung cancer. Chest wall recurrence after mastectomy poses unique clinical challenges, as such tumors are often not amenable to surgical resection and durable local control with radiation or systemic therapy is challenging. When uncontrolled, chest wall recurrence can lead to severe pain and other morbidity. Herein, we describe a patient with inflammatory breast cancer with a massive, rapidly growing chest wall recurrence treated with a regimen of hypofractionated concurrent chemoradiation resulting in a complete chest wall response with durable local control

Durable Local Control Following Concurrent Hypofractionated Chemoradiation for a Massive Inflammatory Breast Cancer Chest Wall Recurrence.

Breast cancer is the leading new cancer diagnosis in women in the United States and is the second most lethal cancer in this patient population after lung cancer. Chest wall recurrence after mastectomy poses unique clinical challenges, as such tumors are often not amenable to surgical resection and durable local control with radiation or systemic therapy is challenging. When uncontrolled, chest wall recurrence can lead to severe pain and other morbidity. Herein, we describe a patient with inflammatory breast cancer with a massive, rapidly growing chest wall recurrence treated with a regimen of hypofractionated concurrent chemoradiation resulting in a complete chest wall response with durable local control

Outcome measures to assess anatomy and function of the posterior vaginal compartment.

Introduction and hypothesisOptimal measures for assessing anatomy and defecatory symptoms related to posterior compartment prolapse are unknown. Our objectives were: (1) to test the inter- and intrarater reliability of commonly used or reported anatomic measures of posterior compartment prolapse performed in the clinic setting and under anesthesia; and (2) to examine the correlation between posterior compartment anatomy and defecatory symptoms prior to surgical intervention.MethodsA prospective cohort of women with pelvic floor disorders was assessed using a variety of validated questionnaires and standardized examination measures at baseline, at a preoperative visit, and intraoperatively. Inter- and intrarater reliability for anatomic measures were assessed by two separate examiners at the initial visit and repeated by one of the original examiners at a preoperative visit. Reliability was measured using kappa or intraclass correlations according to data type. Symptom and anatomic measure correlations were analyzed using Spearman rank tests.ResultsMean age of the 120 women recruited was 57 ± 15 years, 49 (41 %) had a point Bp ≥ 0; 59 % reported at least moderate bother from at least one obstructed defecation symptom on the Pelvic Floor Distress Inventory (PFDI). At baseline, most anatomic measures showed at least moderate to good inter/intrarater reliability (> 0.5). There were no moderate or better correlations between any symptom and anatomic measure (all r <  0.27).ConclusionsMost anatomic measures of posterior compartment prolapse are reliable and reproducible; however, they do not correlate well with defecatory symptoms

Outcome measures to assess anatomy and function of the posterior vaginal compartment.

Introduction and hypothesisOptimal measures for assessing anatomy and defecatory symptoms related to posterior compartment prolapse are unknown. Our objectives were: (1) to test the inter- and intrarater reliability of commonly used or reported anatomic measures of posterior compartment prolapse performed in the clinic setting and under anesthesia; and (2) to examine the correlation between posterior compartment anatomy and defecatory symptoms prior to surgical intervention.MethodsA prospective cohort of women with pelvic floor disorders was assessed using a variety of validated questionnaires and standardized examination measures at baseline, at a preoperative visit, and intraoperatively. Inter- and intrarater reliability for anatomic measures were assessed by two separate examiners at the initial visit and repeated by one of the original examiners at a preoperative visit. Reliability was measured using kappa or intraclass correlations according to data type. Symptom and anatomic measure correlations were analyzed using Spearman rank tests.ResultsMean age of the 120 women recruited was 57 ± 15 years, 49 (41 %) had a point Bp ≥ 0; 59 % reported at least moderate bother from at least one obstructed defecation symptom on the Pelvic Floor Distress Inventory (PFDI). At baseline, most anatomic measures showed at least moderate to good inter/intrarater reliability (> 0.5). There were no moderate or better correlations between any symptom and anatomic measure (all r <  0.27).ConclusionsMost anatomic measures of posterior compartment prolapse are reliable and reproducible; however, they do not correlate well with defecatory symptoms

Evaluating Automatic Segmentation for Swallowing-Related Organs for Head and Neck Cancer

Purpose: To evaluate the accuracy of deep-learning-based auto-segmentation of the superior constrictor, middle constrictor, inferior constrictor, and larynx in comparison with a traditional multi-atlas-based method. Methods and Materials: One hundred and five computed tomography image datasets from 83 head and neck cancer patients were retrospectively collected and the superior constrictor, middle constrictor, inferior constrictor, and larynx were analyzed for deep-learning versus multi-atlas-based segmentation. Eighty-three computed tomography images (40 diagnostic computed tomography and 43 planning computed tomography) were used for training the convolutional neural network, and for atlas-based model training. The remaining 22 computed tomography datasets were used for validation of the atlas-based auto-segmentation versus deep-learning-based auto-segmentation contours, both of which were compared with the corresponding manual contours. Quantitative measures included Dice similarity coefficient, recall, precision, Hausdorff distance, 95th percentile of Hausdorff distance, and mean surface distance. Dosimetric differences between the auto-generated contours and manual contours were evaluated. Subjective evaluation was obtained from 3 clinical observers to blindly score the autosegmented structures based on the percentage of slices that require manual modification. Results: The deep-learning-based auto-segmentation versus atlas-based auto-segmentation results were compared for the superior constrictor, middle constrictor, inferior constrictor, and larynx. The mean Dice similarity coefficient values for the 4 structures were 0.67, 0.60, 0.65, and 0.84 for deep-learning-based auto-segmentation, whereas atlas-based auto-segmentation has Dice similarity coefficient results at 0.45, 0.36, 0.50, and 0.70, respectively. The mean 95th percentile of Hausdorff distance (cm) for the 4 structures were 0.41, 0.57, 0.59, and 0.54 for deep-learning-based auto-segmentation, but 0.78, 0.95, 0.96, and 1.23 for atlas-based auto-segmentation results, respectively. Similar mean dose differences were obtained from the 2 sets of autosegmented contours compared to manual contours. The dose-volume discrepancies and the average modification rates were higher with the atlas-based auto-segmentation contours. Conclusion: Swallowing-related structures are more accurately generated with DL-based versus atlas-based segmentation when compared with manual contours