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ted low knowledge of the menstrual cycle, early physical signs of pregnancy, and certain contraceptives. Conclusions Undergraduate students have major reproductive knowledge gaps. Healthcare providers need to consider health literacy and knowledge level when educating college students.Federal and institutional policy changes have accelerated the use of telemental health to care for college students distant from their mental health providers during the early part of the COVID-19 pandemic. Temporary measures have made telemental health more readily available, including relaxing of regulations related to interstate licensure, controlled substance prescribing, patient privacy, and reimbursement. Though early efforts are underway to sustain these changes during and in the wake of the pandemic, there are important areas in which federal and institutional policy are still lacking. Additional steps are needed to successfully implement and sustain telemental health for college students include ensuring student access to technology and Internet; proactive outreach to optimize the student's home environment, addressing concerns about safety and confidentiality; developing the means to track rapidly shifting telemental health policy changes; and developing centralized resources that enable remote providers to become familiar with involuntary commitment laws and emergency protocols.
To identify factors independently associated with program participation and knowledge of campus processes to address sexual assault and harassment complaints.

1,182 undergraduates who completed the University of Michigan's 2015 campus climate survey on topics of sexual assault and harassment (67% response rate).

We analyze survey responses to estimate multivariable models that identify subgroups of the student population least likely to have participated in programs or to know campus processes.

Students living off campus, not involved in major organizations, and males are less likely to report attending programming. Students not involved in major organizations and females are less likely to report knowing campus processes.

Specific student subpopulations are more difficult to engage in programs designed to reduce sexual assault and harassment. Targeting additional effort to these groups may improve campus sexual climate. Careful analyses of campus climate survey data can help construct campus-specific priorities for these interventions.
Specific student subpopulations are more difficult to engage in programs designed to reduce sexual assault and harassment. Targeting additional effort to these groups may improve campus sexual climate. Careful analyses of campus climate survey data can help construct campus-specific priorities for these interventions.Pyoderma gangrenosum (PG) is a rare, immunological ulcerative, and necrotic inflammatory skin disease that can be easily misdiagnosed as cellulitis, abscess, diabetic foot ulcer, and other infectious diseases. Misdiagnosing PG leads to unnecessary surgical incision and debridement, which further exacerbates the lesion, ultimately leading to longer treatment periods and higher medical costs. Therefore, early and accurate diagnosis of PG is extremely important for its treatment. In particular, PG should be suspected in patients with inflammatory bowel disease.A wide spectrum of second cancers occur as late complications of radiation therapy (RT) used to treat various malignancies. In addition to the type and dose of radiation, lifestyle, environmental, and genetic factors are important to the development of second malignancies in cancer survivors. Typically, RT-induced malignancies (RTIMs) are biologically aggressive cancers with a variable period of 5-10 years for hematologic malignancies and 10-60 years for solid tumors between RT and the development of the second cancer. Although carcinomas and leukemias commonly develop after low-dose RT, sarcomas occur in tissues or organs that receive high-dose RT. Angiosarcomas and unclassified pleomorphic sarcomas are the two most common RT-associated sarcomas; other sarcomas include malignant peripheral nerve sheath tumors, leiomyosarcomas, osteosarcomas, chondrosarcomas, and dedifferentiated or pleomorphic liposarcomas. Select RTIMs show tumor genetic characteristics that allow accurate diagnosis. Nearly all cutaneous angiosarcomas after RT for breast cancer and 90% of RT-associated malignant peripheral nerve sheath tumors are characterized by MYC gene amplifications and loss of H3 K27me3 expression, respectively. Classic papillary thyroid carcinomas that develop after RT frequently harbor RET/PTC rearrangements and have a favorable prognosis, despite their advanced stage at patient presentation. Select RTIMs demonstrate characteristic imaging findings and typically develop in the prior radiation field. Imaging is essential to early diagnosis, characterization, localization, and staging of RTIMs. Familiarity of radiologists with the diverse spectrum of RTIMs is essential for early diagnosis and optimal management. An invited commentary by Shapiro is available online. ©RSNA, 2021.Artificial intelligence techniques involving the use of artificial neural networks-that is, deep learning techniques-are expected to have a major effect on radiology. Some of the most exciting applications of deep learning in radiology make use of generative adversarial networks (GANs). GANs consist of two artificial neural networks that are jointly optimized but with opposing goals. One neural network, the generator, aims to synthesize images that cannot be distinguished from real images. The second neural network, the discriminator, aims to distinguish these synthetic images from real images. GNE-140 clinical trial These deep learning models allow, among other applications, the synthesis of new images, acceleration of image acquisitions, reduction of imaging artifacts, efficient and accurate conversion between medical images acquired with different modalities, and identification of abnormalities depicted on images. The authors provide an introduction to GANs and adversarial deep learning methods. In addition, the different ways in which GANs can be used for image synthesis and image-to-image translation tasks, as well as the principles underlying conditional GANs and cycle-consistent GANs, are described.
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