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Guillain-Barre syndrome (GBS) is the most prevalent and severe form of acute paralytic neuropathy, commonly triggered by infections and characterized by an abnormal autoimmune response. Reports of multispace deep fascial infection (DFI) in the head and neck complicated by GBS are exceedingly rare. We report a 69-year-old woman with DFI who developed postoperative limbs weakness.

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Background: This study aims to detect Mycobacterium tuberculosis complex (MTBC) DNA in intraocular fluid from clinically suspected tuberculous uveitis patients using multiplex polymerase chain reaction (PCR) and investigate the diagnostic utility of multiplex PCR for tuberculous uveitis.

Methods: Primers targeting three specific genes (MPB64, CYP141, and IS6110) within the MTBC genome were designed. Multiplex PCR was conducted using DNA from the H37Rv strain as well as DNA extracted from fluids of confirmed tuberculosis patients to assess primer specificity and method feasibility.

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Background: Mutations in the LARS2 gene are correlated with Perrault syndrome, a rare autosomal recessive genetic disorder, that is typically characterized by sensorineural hearing loss and ovarian insufficiency.

Methods: Whole-exome sequencing and mutational analysis were employed to identify hearing loss-causing genes in a Chinese family from the Guangxi Zhuang Autonomous Region. Clinical phenotypes, audiological data, and color Doppler ultrasound of the family were collected, and a series of computer software were used to analyze the impact of genetic variations on protein structure and function.

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To investigate the clinicopathological characteristics, immunophenotypes, diagnostic criteria and differential diagnosis of atrophic kidney-like lesion (AKLL). Three cases of AKLL were collected from April 2021 to October 2023 at the Xiangya Hospital of Central South University, Changsha, Zhejiang Provincial People's Hospital, Hangzhou and Ningbo Clinical Pathology Diagnosis Center, Ningbo, China. The clinical, morphological, and immunohistochemical characteristics were analyzed.

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Objective: Artificial intelligence (AI) tools for histological diagnosis offer great potential to healthcare, yet failure to understand their clinical context is delaying adoption. IGUANA (Interpretable Gland-Graphs using a Neural Aggregator) is an AI algorithm that can effectively classify colonic biopsies into normal versus abnormal categories, designed to automatically report normal cases. We performed a retrospective pathological and clinical review of the errors made by IGUANA.

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