Stent-Graft Placement for Hepatic Arterial Hemorrhage after Pancreaticobiliary Surgery: Long-Term Clinical Outcomes.

PURPOSE: To evaluate the safety and long-term clinical outcomes of stent-graft placement to treat hepatic arterial hemorrhage after pancreaticobiliary surgery. MATERIALS AND METHODS: Outcomes were retrospectively evaluated in 61 patients (50 men and 11 women; mean age, 63 years) who underwent stent-graft placement for delayed arterial hemorrhage (after 24 hours) after pancreaticobiliary surgery from 2006 to 2023. Bleeding sites included the gastroduodenal artery stump (n = 54), common or proper hepatic artery (n = 5), and right hepatic artery (n = 2). The stent-grafts used were Viabahn (n = 27), Comvi (n = 11), Jostent (n = 3), Covera (n = 11), and Lifestream (n = 7). Technical and clinical success and adverse events (AE) were evaluated. After stent-graft placement, overall survival (OS), hemorrhage-free survival (HFS), and stent patency were evaluated. RESULTS: The technical and clinical success rates of stent-graft placement were 97% and 93%, respectively. The severe AE rate was 12% and was significantly higher in patients who underwent pylorus-sacrificing rather than pylorus-preserving surgery (P = .001). None of the severe AEs were associated with patient mortality. Median OS after stent-graft placement was 854 days, and median HFS was 822 days. The 1-, 3-, 5-, and 10-year stent patency rates were 87%, 84%, 79%, and 72%, respectively. CONCLUSIONS: Stent-graft placement was safe and provided long-term control of hepatic arterial hemorrhage after pancreaticobiliary surgery.

Artificial intelligence for automatic detection of basal cell carcinoma from frozen tissue tangential biopsies.

Evaluation of basal cell carcinoma (BCC) involves tangential biopsies of a suspicious lesion that is sent for frozen sections and evaluated by a Mohs micrographic surgeon. Advances in artificial intelligence (AI) have made possible the development of sophisticated clinical decision support systems to provide real-time feedback to clinicians which could have a role in optimizing the diagnostic workup of BCC. There were 287 annotated whole-slide images of frozen sections from tangential biopsies, of which 121 contained BCC, that were used to train and test an AI pipeline to recognize BCC. Regions of interest were annotated by a senior dermatology resident, experienced dermatopathologist, and experienced Mohs surgeon, with concordance of annotations noted on final review. Final performance metrics included a sensitivity and specificity of 0.73 and 0.88, respectively. Our results on a relatively small dataset suggest the feasibility of developing an AI system to aid in the workup and management of BCC.

Nanostructured Vanadium Dioxide Materials for Optical Sensing Applications.

Vanadium dioxide (VO2) is one of the strongly correlated materials exhibiting a reversible insulator-metal phase transition accompanied by a structural transition from a low-temperature monoclinic phase to high-temperature rutile phase near room temperature. Due to the dramatic change in electrical resistance and optical transmittance of VO2, it has attracted considerable attention towards the electronic and optical device applications, such as switching devices, memory devices, memristors, smart windows, sensors, actuators, etc. The present review provides an overview of several methods for the synthesis of nanostructured VO2, such as solution-based chemical approaches (sol-gel process and hydrothermal synthesis) and gas or vapor phase synthesis techniques (pulsed laser deposition, sputtering method, and chemical vapor deposition). This review also presents stoichiometry, strain, and doping engineering as modulation strategies of physical properties for nanostructured VO2. In particular, this review describes ultraviolet-visible-near infrared photodetectors, optical switches, and color modulators as optical sensing applications associated with nanostructured VO2 materials. Finally, current research trends and perspectives are also discussed.

Artificial intelligence in medicine - dermatology compared to other medical specialties in FDA-cleared software as medical device.

Artificial intelligence (AI) and machine learning (ML) have occupied the center stage in healthcare as research groups and institutions investigate their capabilities and risks. Dermatology is often cited as one of the medical specialties most ripe for disruption with AI technology due to the heavy incorporation of visual information into clinical decisions and treatments. Although the literature on AI in dermatology is rapidly growing, there has been a noticeable absence of mature AI solutions utilized by dermatology departments or patients. This commentary provides insight into the regulatory challenges facing AI solutions for the specialty of dermatology and the unique considerations that should be factored into AI development and deployment.

ChatGPT offers an editorial on the opportunities for chatbots in dermatologic research and patient care.

ChatGPT is a chatbot developed by OpenAI, an artificial intelligence research laboratory, that is trained on massive-scale internet text data to understand a broad range of language styles and topics. As a mature, conversational chatbot, ChatGPT can respond to follow-up questions and produce coherent primary texts based on the user's request. We explore the opportunities and risks of integrating chatbots into dermatologic patient care and research while presenting ChatGPT's response to the same question.

Innovation in dermatology: where are the dermatologists? A retrospective review of the Pitchbook Database.

To investigate the extent to which dermatologists are involved in innovative dermatology start-up companies, we analyzed the Pitchbook database which covers private capital markets. From January 1, 2010 to June 23, 2021, there were 105 dermatology companies, of which six (5.7%) had a dermatologist chief executive officer (CEO), 16 (15.2%) had a dermatologist founder, and 19 (18.1%) had a dermatologist advisor or board member. There were 98 dermatologists with leadership positions, including six (6.1%) CEOs, 21 (21.4%) founders, 11 (11.2%) chief medical officers (CMOs), and 60 (61.2%) advisors. Our findings highlight the underrepresentation of dermatologists in start-up ventures relating to dermatology.

Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on Magnetic Resonance Imaging for Targeted Biopsy.

PURPOSE: Targeted biopsy improves prostate cancer diagnosis. Accurate prostate segmentation on magnetic resonance imaging (MRI) is critical for accurate biopsy. Manual gland segmentation is tedious and time-consuming. We sought to develop a deep learning model to rapidly and accurately segment the prostate on MRI and to implement it as part of routine magnetic resonance-ultrasound fusion biopsy in the clinic. MATERIALS AND METHODS: A total of 905 subjects underwent multiparametric MRI at 29 institutions, followed by magnetic resonance-ultrasound fusion biopsy at 1 institution. A urologic oncology expert segmented the prostate on axial T2-weighted MRI scans. We trained a deep learning model, ProGNet, on 805 cases. We retrospectively tested ProGNet on 100 independent internal and 56 external cases. We prospectively implemented ProGNet as part of the fusion biopsy procedure for 11 patients. We compared ProGNet performance to 2 deep learning networks (U-Net and holistically-nested edge detector) and radiology technicians. The Dice similarity coefficient (DSC) was used to measure overlap with expert segmentations. DSCs were compared using paired t-tests. RESULTS: ProGNet (DSC=0.92) outperformed U-Net (DSC=0.85, p <0.0001), holistically-nested edge detector (DSC=0.80, p <0.0001), and radiology technicians (DSC=0.89, p <0.0001) in the retrospective internal test set. In the prospective cohort, ProGNet (DSC=0.93) outperformed radiology technicians (DSC=0.90, p <0.0001). ProGNet took just 35 seconds per case (vs 10 minutes for radiology technicians) to yield a clinically utilizable segmentation file. CONCLUSIONS: This is the first study to employ a deep learning model for prostate gland segmentation for targeted biopsy in routine urological clinical practice, while reporting results and releasing the code online. Prospective and retrospective evaluations revealed increased speed and accuracy.

Social media use in residency recruitment during the COVID-19 pandemic.

To investigate the extent to which dermatology programs use social media to connect with applicants, we conducted a search of all 140 residency programs on Instagram, Facebook, Twitter, and YouTube. Our search revealed 74 (53%) Instagram, 21 (15%) Facebook, 20 (14%) Twitter, and four (3%) YouTube accounts for dermatology programs, with the number of Instagram accounts increasing five-fold from the end of 2019 to present. Our results demonstrate that conditions created during the coronavirus disease 2019 (COVID-19) pandemic accelerated dermatology residency programs' acceptance of social media, particularly Instagram, as a means to communicate and share information with applicants.

One-step H2S reactive sputtering for 2D MoS2/Si heterojunction photodetector.

A technique for directly growing two-dimensional (2D) materials onto conventional semiconductor substrates, enabling high-throughput and large-area capability, is required to realise competitive 2D transition metal dichalcogenide devices. A reactive sputtering method based on H2S gas molecules and sequential in situ post-annealing treatment in the same chamber was proposed to compensate for the relatively deficient sulfur atoms in the sputtering of MoS2 and then applied to a 2D MoS2/p-Si heterojunction photodevice. X-ray photoelectron, Raman, and UV-visible spectroscopy analysis of the as-deposited Ar/H2S MoS2 film were performed, indicating that the stoichiometry and quality of the as-deposited MoS2 can be further improved compared with the Ar-only MoS2 sputtering method. For example, Ar/H2S MoS2 photodiode has lower defect densities than that of Ar MoS2. We also determined that the factors affecting photodetector performance can be optimised in the 8-12 nm deposited thickness range.

Enhanced Performance of MoS2 Photodetectors by Inserting an ALD-Processed TiO2 Interlayer.

2D molybdenum disulfide (MoS2 ) possesses excellent optoelectronic properties that make it a promising candidate for use in high-performance photodetectors. Yet, to meet the growing demand for practical and reliable MoS2 photodetectors, the critical issue of defect introduction to the interface between the exfoliated MoS2 and the electrode metal during fabrication must be addressed, because defects deteriorate the device performance. To achieve this objective, the use of an atomic layer-deposited TiO2 interlayer (between exfoliated MoS2 and electrode) is reported in this work, for the first time, to enhance the performance of MoS2 photodetectors. The TiO2 interlayer is inserted through 20 atomic layer deposition cycles before depositing the electrode metal on MoS2 /SiO2 substrate, leading to significantly enhanced photoresponsivity and response speed. These results pave the way for practical applications and provide a novel direction for optimizing the interlayer material.

Self-Formed Channel Devices Based on Vertically Grown 2D Materials with Large-Surface-Area and Their Potential for Chemical Sensor Applications.

2D layered materials with sensitive surfaces are promising materials for use in chemical sensing devices, owing to their extremely large surface-to-volume ratios. However, most chemical sensors based on 2D materials are used in the form of laterally defined active channels, in which the active area is limited to the actual device dimensions. Therefore, a novel approach for fabricating self-formed active-channel devices is proposed based on 2D semiconductor materials with very large surface areas, and their potential gas sensing ability is examined. First, the vertical growth phenomenon of SnS2 nanocrystals is investigated with large surface area via metal-assisted growth using prepatterned metal electrodes, and then self-formed active-channel devices are suggested without additional pattering through the selective synthesis of SnS2 nanosheets on prepatterned metal electrodes. The self-formed active-channel device exhibits extremely high response values (>2000% at 10 ppm) for NO2 along with excellent NO2 selectivity. Moreover, the NO2 gas response of the gas sensing device with vertically self-formed SnS2 nanosheets is more than two orders of magnitude higher than that of a similar exfoliated SnS2 -based device. These results indicate that the facile device fabrication method would be applicable to various systems in which surface area plays an important role.

Hypovolemic shock caused by delayed-onset superior gluteal artery rupture, successfully treated with arteriographic embolization.

INTRODUCTION: Rupture of the superior gluteal artery (SGA) is usually associated with pelvic bone fractures and acetabular fractures secondary to blunt trauma. However, despite recent advances in technologies and tools, rupture of the SGA remains a challenging problem because it is difficult to manage and is frequently associated with significantly high mortality and morbidity. PATIENTS AND METHODS: We present a case of an 82-year-old man, who presented to our emergency department after a cultivator turnover accident and who showed stable initial vital signs and manifested only as blunt buttock traumatic contusion without any pelvic bone or acetabular fracture, which resulted in delayed massive bleeding from the SGA on eight days after trauma. RESULTS: A hypovolemic shock and abrupt 4.2 g/dl hemoglobin decrease caused by massive bleeding from delayed-onset SGA rupture, was successfully treated with urgent angiographic embolization. CONCLUSIONS: A delayed SGA bleeding should be considered in late-onset shock associated with blunt buttock trauma. Furthermore, early detection and embolization not only prevent further complications, such as compartment syndrome and hypovolemic shock, but also eliminate the need for any surgical interventions.

Alloyed 2D Metal-Semiconductor Heterojunctions: Origin of Interface States Reduction and Schottky Barrier Lowering.

The long-term stability and superior device reliability through the use of delicately designed metal contacts with two-dimensional (2D) atomic-scale semiconductors are considered one of the critical issues related to practical 2D-based electronic components. Here, we investigate the origin of the improved contact properties of alloyed 2D metal-semiconductor heterojunctions. 2D WSe2-based transistors with mixed transition layers containing van der Waals (M-vdW, NbSe2/WxNb1-xSe2/WSe2) junctions realize atomically sharp interfaces, exhibiting long hot-carrier lifetimes of approximately 75,296 s (78 times longer than that of metal-semiconductor, Pd/WSe2 junctions). Such dramatic lifetime enhancement in M-vdW-junctioned devices is attributed to the synergistic effects arising from the significant reduction in the number of defects and the Schottky barrier lowering at the interface. Formation of a controllable mixed-composition alloyed layer on the 2D active channel would be a breakthrough approach to maximize the electrical reliability of 2D nanomaterial-based electronic applications.

Alloyed 2D Metal-Semiconductor Atomic Layer Junctions.

Heterostructures of compositionally and electronically variant two-dimensional (2D) atomic layers are viable building blocks for ultrathin optoelectronic devices. We show that the composition of interfacial transition region between semiconducting WSe2 atomic layer channels and metallic NbSe2 contact layers can be engineered through interfacial doping with Nb atoms. WxNb1-xSe2 interfacial regions considerably lower the potential barrier height of the junction, significantly improving the performance of the corresponding WSe2-based field-effect transistor devices. The creation of such alloyed 2D junctions between dissimilar atomic layer domains could be the most important factor in controlling the electronic properties of 2D junctions and the design and fabrication of 2D atomic layer devices.

Gyro Drift Correction for An Indirect Kalman Filter Based Sensor Fusion Driver.

Sensor fusion techniques have made a significant contribution to the success of the recently emerging mobile applications era because a variety of mobile applications operate based on multi-sensing information from the surrounding environment, such as navigation systems, fitness trackers, interactive virtual reality games, etc. For these applications, the accuracy of sensing information plays an important role to improve the user experience (UX) quality, especially with gyroscopes and accelerometers. Therefore, in this paper, we proposed a novel mechanism to resolve the gyro drift problem, which negatively affects the accuracy of orientation computations in the indirect Kalman filter based sensor fusion. Our mechanism focuses on addressing the issues of external feedback loops and non-gyro error elements contained in the state vectors of an indirect Kalman filter. Moreover, the mechanism is implemented in the device-driver layer, providing lower process latency and transparency capabilities for the upper applications. These advances are relevant to millions of legacy applications since utilizing our mechanism does not require the existing applications to be re-programmed. The experimental results show that the root mean square errors (RMSE) before and after applying our mechanism are significantly reduced from 6.3 × 10(-1) to 5.3 × 10(-7), respectively.

Integrated Identification and Genetic Diversity of Potentially Invasive Clearwing Moths (Lepidoptera: Cossoidea: Sesiidae) in Korea.

The populations of clearwing moth borers in Korea have recently caused extensive and severe damage to pin oaks (Quercus palustris Munchh.). We conducted field monitoring and molecular analyses to identify them in an integrated manner. Morphological examination and molecular analyses of the COI gene, based on intra- and interspecific genetic divergences (GDs), revealed that the borers were identified as two invasive species, Sphecodoptera sheni and Paranthrenella pinoakula sp. nov. The maximum intraspecific GD was found to be 1.9%, whereas the minimum interspecific GD was confirmed as 8.1%, indicating a distinct barcoding gap. Both the MJ network and NJ tree also showed that 18 haplotypes (Hs) were detected from the 52 COI sequences. The borers revealed a total of 17 Hs: (i) H1-H7 were detected in all seven regions with S. sheni; (ii) Wonju and Goyang populations of S. sheni revealed more than three Hs; (iii) H7 was closely connected with H8 of the Chinese population of S. sheni; (iv) H9-H10 were detected in other samples from the Wonju population with P. pinoakula sp. n. and were closely located with congeneric species. A maximum likelihood tree also revealed that P. pinoacula sp. n. nested within the congeneric species, genetically separating from S. sheni.

A Mixed-Method Approach to Explore Successful Recruitment and Treatment of Minority Patients on Therapeutic Cancer Clinical Trials at a Tertiary Referral Center Using Photo-Elicitation Interviews.

Introduction: Under-represented minority patients (URM) enroll in cancer clinical trials (CCT) at low rates. To gain insight into barriers and facilitators to CCT enrollment, we conducted a mixed method study of URM patients who were successfully treated on a therapeutic CCT from 2018-2021 at all institutional sites. Methods: A retrospective chart review of 270 minority patients was conducted to identify patient demographics and characteristics. All living URM patients were requested to participate in a survey and qualitative interview using a photo elicitation technique. Results: Most patients who participated in a CCT were patients with solid tumors, metastatic disease, and did not live in a rural area. Survey data showed that the two most significant drivers of CCT enrollment were potential of benefit to self and to others (altruism). Direct recommendation from a healthcare provider to participate in CCT was critical. URM patients enrolled on a CCT experience a significant burden of symptoms and financial distress. Key themes identified from the interviews that motivated patients to participate included chance for cure, staying positive, altruism and advancement of science, and having diverse representation in research. Patient-level facilitators to participation included social support, cost coverage, and limited treatment options. Sytematic facilitators identified included minimizing logistical barriers, decentralizing cancer clinical trials, increasing awareness via patient narratives, diversifying research staff, minimizing cost, and being clear on puropose and benefit of the trial. Conclusion: Success stories of minority recruitment can provide useful information to enhance minority accrual. Photo elicitation interviews provide rich narratives of patient experience.