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Functional analysis of high throughput experiments using pathway analysis is now ubiquitous. Though powerful, these methods often produce thousands of redundant results owing to knowledgebase redundancies upstream. This scale of results hinders extensive exploration by biologists and can lead to investigator biases due to previous knowledge and expectations. To address this issue, we present vissE, a flexible network-based analysis and visualisation tool that organises information into semantic categories and provides various visualisation modules to characterise them with respect to the underlying data, thus providing a comprehensive view of the biological system. We demonstrate vissE’s versatility by applying it to three different technologies: bulk, single-cell and spatial transcriptomics. Applying vissE to a factor analysis of a breast cancer spatial transcriptomic data, we identified stromal phenotypes that support tumour dissemination. Its adaptability allows vissE to enhance all existing gene-set enrichment and pathway analysis workflows, empowering biologists during molecular discovery.

Functional analysis of high throughput experiments using pathway analysis is now ubiquitous. Though powerful, these methods often produce thousands of redundant results owing to knowledgebase redundancies upstream. This scale of results hinders extensive exploration by biologists and often leads to investigator biases due to previous knowledge and expectations. To address this issue, we present vissE, a flexible network-based analysis method that summarises redundancies into biological themes and provides various analytical modules to characterise and visualise them with respect to the underlying data, thus providing a comprehensive view of the biological system. We demonstrate vissE's versatility by applying it to three different technologies: bulk, single-cell and spatial transcriptomics. Applying vissE to a factor analysis of a breast cancer spatial transcriptomic data, we identified stromal phenotypes that support tumour dissemination. Its adaptability allows vissE to enhance all existing gene-set enrichment and pathway analysis workflows, removing investigator bias from molecular discovery. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://bioconductor.org/packages/release/bioc/html/vissE.html

Background Post-operative management after phaeochromocytoma resection includes monitoring of blood pressure and blood sugar, and vigilance for haemorrhage. Guidelines recommend 24 h of continuous blood pressure monitoring, usually necessitating HDU/ICU admission. We hypothesised that most patients undergoing phaeochromocytoma resection do not require post-operative HDU/ICU admission. We aim to describe current Australian and New Zealand perioperative management of phaeochromocytoma and determine whether it is safe to omit HDU/ICU care for most patients. Methods We collected retrospective data on patients undergoing excision of phaeochromocytoma in 12 centres around Australia and New Zealand between 2007 and 2019. Data collected included preoperative medical management, anaesthetic management, vasopressor support, HDU/ICU admission and complications. Results A total of 223 patients were included in the study, 173 (77%) of whom were admitted to HDU/ICU post-operatively. The group of patients treated in ICU was similar to the group of patients treated on the ward in terms of demographic and tumour characteristics, and there were significant differences in the proportion of patients admitted to HDU/ICU between centres. Of patients admitted to ICU, 71 (41%) received vasopressor support. This was weaned within 24 h in 55 (77%) patients. Patients with larger tumours (> 6 cm) and a transfusion requirement are more likely to require prolonged inotropic support. Among patients admitted to the ward, there were no complications that required escalation of care. Conclusions Although not widespread practice in Australia and New Zealand, it appears safe for the majority of patients undergoing minimally invasive resection of phaeochromocytoma to be admitted to the ward post-operatively.

BackgroundMedullary thyroid carcinoma (MTC) can be targeted with tyrosine kinase inhibitors (TKIs). We aimed to report the outcomes of surgically managed MTC and to evaluate the impact of TKI use on patient survival. MethodsConsecutive patients treated surgically for MTC from 1986 to 2020 were identified from a prospectively collected database and were compared on the basis of stage at operation and TKI use. The primary outcome was overall survival (OS). ResultsAmong 154 patients with a median age of 52 years, 40% presented with stage I/II disease and 60% presented with advanced (stage III or IV) disease. During a median follow-up of 7.5 years, 21% received TKIs for systemic disease. Those presenting with advanced disease were more likely to receive a TKI (31% vs. 7%), present with tumor invasion of the recurrent laryngeal nerve (RLN; 12% vs. 0%) and undergo reoperation (42% vs. 23%) compared with stage I–II patients. For the 11 patients found to have invasion of the RLN, five had preoperative functional vocal cords. Five-year OS was 84% for advanced disease, and stage IV patients who received TKIs had a median survival of 21 years, versus 15 years for those who did not (p = 0.3).ConclusionsSurgery achieves long-term survival for patients with advanced disease, however these patients are at greater risk of requiring RLN resection due to invasion. A significant OS benefit was not seen for TKI use. For patients with local invasion, neoadjuvant TKI therapy may have a role in reducing local morbidity if confirmed to be of benefit in clinical trials.

Abstract Context Management of sporadic medullary thyroid microcarcinoma smaller than 1 cm (micro-MTC) is controversial because of conflicting reports of prognosis. As these cancers are often diagnosed incidentally, they pose a management challenge when deciding on further treatment and follow-up. Objective We report the outcomes of surgically managed sporadic micro-MTC in a specialist endocrine surgery and endocrinology unit and identify associations for recurrence and disease-specific survival in this population. Methods Micro-MTCs were identified from a prospectively maintained surgery database, and slides were reviewed to determine pathological grade. The primary end points were recurrence, time to recurrence and disease-specific survival. Prognostic factors assessed included size, grade, lymph node metastasis (LNM), and postoperative calcitonin. Results From 1995 to 2022, 64 patients were diagnosed with micro-MTC with 22 excluded because of hereditary disease. The included patients had a median age of 60 years, tumor size of 4 mm, and 28 (67%) were female. The diagnosis was incidental in 36 (86%) with 4 (10%) being high grade, 5 (12%) having LNM and 9 (21%) having elevated postoperative calcitonin. Over a 6.6-year median follow-up, 5 (12%) developed recurrence and 3 (7%) died of MTC. High grade and LNM were associated with 10-year survival estimates of 75% vs 100% for low grade and no LNM (hazard ratio = 831; P < .01). High grade, LNM, and increased calcitonin were associated with recurrence (P < .01). Tumor size and type of surgery were not statistically significantly associated with recurrence or survival. No patients with low grade micro-MTC and normal postoperative calcitonin developed recurrence. Conclusion Most sporadic micro-MTCs are detected incidentally and are generally associated with good outcomes. Size is not significantly associated with outcomes. Using grade, LNM, and postoperative calcitonin allows for the identification of patients at risk of recurrence to personalize management.

In the original version of the article there were formatting errors in Table 4. Following is the corrected table.

Agents can base decisions made using reinforcement learning (RL) on a reward function. The selection of values for the learning algorithm parameters can, nevertheless, have a substantial impact on the overall learning process. In order to discover values for the learning parameters that are close to optimal, we extended our previously proposed genetic algorithm-based Deep Deterministic Policy Gradient and Hindsight Experience Replay approach (referred to as GA+DDPG+HER) in this study. On the robotic manipulation tasks of FetchReach, FetchSlide, FetchPush, FetchPick&Place, and DoorOpening, we applied the GA+DDPG+HER methodology. Our technique GA+DDPG+HER was also used in the AuboReach environment with a few adjustments. Our experimental analysis demonstrates that our method produces performance that is noticeably better and occurs faster than the original algorithm. We also offer proof that GA+DDPG+HER beat the current approaches. The final results support our assertion and offer sufficient proof that automating the parameter tuning procedure is crucial and does cut down learning time by as much as 57%.