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Chapter 5: THE ROLE OF GENETICS IN PRIMARY HYPERPARATHYROIDISM.

Ann Endocrinol (Paris)

January 2025

Univ. Lille, Inserm, CHU Lille, U1286 - Infinite, F-59045 Lille Cedex, Department of Biochemistry and Molecular Biology, Lille University Hospital, Lille, France. Electronic address:

Around 10% of cases of primary hyperparathyroidism are thought to be genetic in origin, some of which are part of a syndromic form such as multiple endocrine neoplasia types 1, 2A or 4 or hyperparathyroidism-jaw tumor syndrome, while the remainder are cases of isolated familial primary hyperparathyroidism. Recognition of these genetic forms is important to ensure appropriate management according to the gene and type of variant involved, but screening for a genetic cause is not justified in all patients presenting primary hyperparathyroidism. The indications for genetic analysis have made it possible to propose a decision tree that takes into account whether the presentation is familial or sporadic, syndromic or isolated, patient age, and histopathological type of parathyroid lesion.

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Chapter 6: SYNDROMIC PRIMARY HYPERPARATHYROIDISM.

Ann Endocrinol (Paris)

January 2025

Endocrinology Department, Huriez Hospital, Lille University Hospital, France. Electronic address:

Syndromic primary hyperparathyroidism has several features in common: younger age at diagnosis when compared with sporadic primary hyperparathyroidism, often synchronous or metachronous multi-glandular involvement, higher possibility of recurrence, association with other endocrine or extra-endocrine disorders, and suggestive family background with autosomal dominant inheritance. Hyperparathyroidism in multiple endocrine neoplasia type 1 is the most common syndromic hyperparathyroidism. It is often asymptomatic in adolescents and young adults, but may be responsible for recurrent lithiasis and/or bone loss.

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Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis.

Neuroimage

January 2025

College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China. Electronic address:

Dynamic brain networks (DBNs) can capture the intricate connections and temporal evolution among brain regions, becoming increasingly crucial in the diagnosis of neurological disorders. However, most existing researches tend to focus on isolated brain network sequence segmented by sliding windows, and they are difficult to effectively uncover the higher-order spatio-temporal topological pattern in DBNs. Meantime, it remains a challenge to utilize the structure connectivity prior in the DBNs analysis.

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Background: Patients with large pannus and ventral hernias may benefit from undergoing panniculectomy performed concurrently with open ventral hernia repair (VHR-PAN). However, there has been concerns related to increase surgical site occurrences when adding a panniculectomy. This study aims to evaluate outcomes of open VHR with and without panniculectomy using a large hernia specific database.

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