Low-dose isotretinoin for the management of rosacea: A systematic review and meta-analysis.

BACKGROUND: Rosacea is a chronic, relapsing inflammatory dermatosis predominantly affecting the central face and can result in significant psychosocial impacts. Isotretinoin has been studied for rosacea due to its anti-inflammatory and sebum reduction properties, but its use remains limited likely due to its off-label use and potential adverse events. OBJECTIVE: This systematic review and meta-analysis investigated the efficacy and safety of low-dose isotretinoin (LDI; ≤0.5 mg/kg/day) for the four main types of rosacea: erythematotelangiectatic, papulopustular, phymatous and ocular rosacea. METHODS: Randomized and non-randomized studies evaluating LDI for rosacea were included. Incomplete studies, non-English studies and case reports were excluded. Study quality was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation scale. RESULTS: Of 435 studies, and 16 studies involving 1445 patients were included. LDI decreased lesion count (p = 0.03) and erythema (p = 0.01) with large effect [standardized mean difference (SMD) > 0.8]. Compared to topical retinoids and topical antimicrobials, isotretinoin had larger reductions in lesion count (p = 0.03) with moderate effect (SMD > 0.5). Mean lesion count and erythema remained reduced by 70% and 47%, respectively, at 16 weeks after LDI cessation. Relapse rate was 35% at 5.5 months post-isotretinoin, and three patients (0.4%) experienced worsening of rosacea. Three patients (0.4%) experienced serious adverse events. CONCLUSIONS: Study design heterogeneity limited more comprehensive comparisons. Overall, low-dose isotretinoin may serve as an effective treatment for rosacea with good tolerability and safety.

Ocular image-based deep learning for predicting refractive error: A systematic review.

Background: Uncorrected refractive error is a major cause of vision impairment worldwide and its increasing prevalent necessitates effective screening and management strategies. Meanwhile, deep learning, a subset of Artificial Intelligence, has significantly advanced ophthalmological diagnostics by automating tasks that required extensive clinical expertise. Although recent studies have investigated the use of deep learning models for refractive power detection through various imaging techniques, a comprehensive systematic review on this topic is has yet be done. This review aims to summarise and evaluate the performance of ocular image-based deep learning models in predicting refractive errors. Main text: We search on three databases (PubMed, Scopus, Web of Science) up till June 2023, focusing on deep learning applications in detecting refractive error from ocular images. We included studies that had reported refractive error outcomes, regardless of publication years. We systematically extracted and evaluated the continuous outcomes (sphere, SE, cylinder) and categorical outcomes (myopia), ground truth measurements, ocular imaging modalities, deep learning models, and performance metrics, adhering to PRISMA guidelines. Nine studies were identified and categorised into three groups: retinal photo-based (n â€‹= â€‹5), OCT-based (n â€‹= â€‹1), and external ocular photo-based (n â€‹= â€‹3).For high myopia prediction, retinal photo-based models achieved AUC between 0.91 and 0.98, sensitivity levels between 85.10% and 97.80%, and specificity levels between 76.40% and 94.50%. For continuous prediction, retinal photo-based models reported MAE ranging from 0.31D to 2.19D, and R 2 between 0.05 and 0.96. The OCT-based model achieved an AUC of 0.79-0.81, sensitivity of 82.30% and 87.20% and specificity of 61.70%-68.90%. For external ocular photo-based models, the AUC ranged from 0.91 to 0.99, sensitivity of 81.13%-84.00% and specificity of 74.00%-86.42%, MAE ranges from 0.07D to 0.18D and accuracy ranges from 81.60% to 96.70%. The reported papers collectively showed promising performances, in particular the retinal photo-based and external eye photo -based DL models. Conclusions: The integration of deep learning model and ocular imaging for refractive error detection appear promising. However, their real-world clinical utility in current screening workflow have yet been evaluated and would require thoughtful consideration in design and implementation.

Transcriptome-wide association study and Mendelian randomization in pancreatic cancer identifies susceptibility genes and causal relationships with type 2 diabetes and venous thromboembolism.

BACKGROUND: Two important questions regarding the genetics of pancreatic adenocarcinoma (PDAC) are 1. Which germline genetic variants influence the incidence of this cancer; and 2. Whether PDAC causally predisposes to associated non-malignant phenotypes, such as type 2 diabetes (T2D) and venous thromboembolism (VTE). METHODS: In this study of 8803 patients with PDAC and 67,523 controls, we first performed a large-scale transcriptome-wide association study to investigate the association between genetically determined gene expression in normal pancreas tissue and PDAC risk. Secondly, we used Mendelian Randomization (MR) to analyse the causal relationships among PDAC, T2D (74,124 cases and 824,006 controls) and VTE (30,234 cases and 172,122 controls). FINDINGS: Sixteen genes showed an association with PDAC risk (FDR <0.10), including six genes not yet reported for PDAC risk (PPIP5K2, TFR2, HNF4G, LRRC10B, PRC1 and FBXL20) and ten previously reported genes (INHBA, SMC2, ABO, PDX1, MTMR6, ACOT2, PGAP3, STARD3, GSDMB, ADAM33). MR provided support for a causal effect of PDAC on T2D using genetic instruments in the HNF4G and PDX1 loci, and unidirectional causality of VTE on PDAC involving the ABO locus (OR 2.12, P < 1e-7). No evidence of a causal effect of PDAC on VTE was found. INTERPRETATION: These analyses identified candidate susceptibility genes and disease relationships for PDAC that warrant further investigation. HNF4G and PDX1 may induce PDAC-associated diabetes, whereas ABO may induce the causative effect of VTE on PDAC. FUNDING: National Institutes of Health (USA).

Evaluating Chatbot responses to patient questions in the field of glaucoma.

Objective: The aim of this study was to evaluate the accuracy, comprehensiveness, and safety of a publicly available large language model (LLM)-ChatGPT in the sub-domain of glaucoma. Design: Evaluation of diagnostic test or technology. Subjects participants and/or controls: We seek to evaluate the responses of an artificial intelligence chatbot ChatGPT (version GPT-3.5, OpenAI). Methods intervention or testing: We curated 24 clinically relevant questions in the domain of glaucoma. The questions spanned four categories: pertaining to diagnosis, treatment, surgeries, and ocular emergencies. Each question was posed to the LLM and the responses obtained were graded by an expert grader panel of three glaucoma specialists with combined experience of more than 30 years in the field. For responses which performed poorly, the LLM was further prompted to self-correct. The subsequent responses were then re-evaluated by the expert panel. Main outcome measures: Accuracy, comprehensiveness, and safety of the responses of a public domain LLM. Results: There were a total of 24 questions and three expert graders with a total number of responses of n = 72. The scores were ranked from 1 to 4, where 4 represents the best score with a complete and accurate response. The mean score of the expert panel was 3.29 with a standard deviation of 0.484. Out of the 24 question-response pairs, seven (29.2%) of them had a mean inter-grader score of 3 or less. The mean score of the original seven question-response pairs was 2.96 which rose to 3.58 after an opportunity to self-correct (z-score - 3.27, p = 0.001, Mann-Whitney U). The seven out of 24 question-response pairs which performed poorly were given a chance to self-correct. After self-correction, the proportion of responses obtaining a full score increased from 22/72 (30.6%) to 12/21 (57.1%), (p = 0.026, χ2 test). Conclusion: LLMs show great promise in the realm of glaucoma with additional capabilities of self-correction. The application of LLMs in glaucoma is still in its infancy, and still requires further research and validation.

Clinical Impacts of Omalizumab on the Psychiatric Comorbidities of Chronic Spontaneous Urticaria: A Systematic Review and Meta-Analysis.

Individuals with chronic spontaneous urticaria (CSU) experience significant sleep disturbances and are at risk of anxiety and depression.

Technical Considerations in Laparoscopic-Assisted Endoscopic Retrograde Cholangiography.

The use of endoscopic retrograde cholangiography (ERCP) for diagnostic and therapeutic interventions on the pancreaticobiliary system has steadily increased, but the standard approach through the oropharynx is prohibited after Roux-en-Y (RYGB) gastric bypass surgery. Laparoscopic access to the gastric remnant allows for the completion of ERCP using the standard side-viewing duodenoscope to facilitate the completion of standard and advanced endoscopic maneuvers. Here, we describe our experience with the technical aspects of safe and effective performance of laparoscopic-assisted ERCP.

Three-Year Outcomes of the Paul Glaucoma Implant for Treatment of Glaucoma.

PRCIS: In our case series, the 3-year failure for Paul Glaucoma Implant (PGI) implantation was 14.6%. At 3 years postoperatively, there was a significant reduction in mean intraocular pressure (IOP) and the number of glaucoma medications used. OBJECTIVE: To determine the 3-year efficacy and safety of the PGI, a novel glaucoma tube shunt in patients with glaucoma. METHODS: Retrospective review of all patients who had undergone PGI implantation in a single tertiary institution in Singapore between May 1, 2017 and January 1, 2022. Data were extracted from electronic health records (Computerized Patient Support System 2 and Epic). The primary outcome measure was failure, defined as IOP >18 mm Hg or <6 mm Hg on 2 consecutive visits after 3 months, reoperation for IOP-related indication, explantation of implant, or loss of light perception vision. Complete success was defined as the absence of failure without medications at 36 months, and qualified success similarly, but with medications. Postoperative mean IOP, mean number of IOP-lowering medications used, and visual acuity were also assessed. RESULTS: Forty-eight eyes in 48 patients were identified. Thirty-one patients (64.6%) had primary open angle and angle closure glaucoma, and 18 (37.5%) had previous existing tube implants or trabeculectomy. At 3 years postoperatively, 7 cases (14.6%) fulfilled the criteria for failure and 36 (75%) met the criteria for complete success. The mean IOP at 36 months was 14.9 ± 4.11 mm Hg, from the mean preoperative IOP of 20.6 ± 6.13 mm Hg ( P < 0.001). The mean number of IOP-lowering medications used was reduced from 3.13 ± 0.959 preoperatively to 0.167 ± 0.476 at 36 months ( P < 0.001). The most common postoperative complication was hypotony (n = 17, 35.4%), of which the majority were self-limiting, followed by hyphema (n = 5, 10.4%) and tube exposure (n = 4, 8.3%). CONCLUSION: The PGI demonstrated sustained IOP reduction and a reduction of medication burden at 3 years postoperatively.

Oncogenic GNAS drives a gastric pylorus program in intraductal papillary mucinous neoplasms of the pancreas.

OBJECTIVE: Intraductal Papillary Mucinous Neoplasms (IPMNs) are cystic lesions and bona fide precursors for pancreatic ductal adenocarcinoma (PDAC). Recently, we showed that acinar to ductal metaplasia, an injury repair program, is characterized by a transcriptomic program similar to gastric spasmolytic polypeptide expressing metaplasia (SPEM), suggesting common mechanisms of reprogramming between the stomach and pancreas. The aims of this study were to assay IPMN for pyloric markers and to identify molecular drivers of this program. DESIGN: We analyzed RNA-seq studies of IPMN for pyloric markers, which were validated by immunostaining in patient samples. Cell lines expressing Kras G12D +/- GNAS R201C were manipulated to identify distinct and overlapping transcriptomic programs driven by each oncogene. A PyScenic-based regulon analysis was performed to identify molecular drivers in the pancreas. Expression of candidate drivers was evaluated by RNA-seq and immunostaining. RESULTS: Pyloric markers were identified in human IPMN. GNAS R201C drove expression of these markers in cell lines and siRNA targeting of GNAS R201C or Kras G12D demonstrates that GNAS R201C amplifies a mucinous, pyloric phenotype. Regulon analysis identified a role for transcription factors SPDEF, CREB3L1, and CREB3L4, which are expressed in patient samples. siRNA-targeting of Spdef inhibited mucin production. CONCLUSION: De novo expression of a SPEM phenotype has been identified in pancreatitis and a pyloric phenotype in Kras G12D -driven PanIN and Kras G12D ;GNAS R201C -driven IPMN, suggesting common mechanisms of reprogramming between these lesions and the stomach. A transition from a SPEM to pyloric phenotype may reflect disease progression and/or oncogenic mutation. IPMN-specific GNAS R201C amplifies a mucinous phenotype, in part, through SPDEF.

Treatment of Pyoderma Gangrenosum.

Pyoderma gangrenosum is a rare neutrophilic dermatosis that results in painful cutaneous ulcers and is frequently associated with underlying hematologic disorders, inflammatory bowel disease, or other autoimmune disorders. Pathogenesis involves an imbalance between proinflammatory and anti-inflammatory mediators, leading to tissue damage from neutrophils. First-line treatment options with the greatest evidence include systemic corticosteroids, cyclosporine, and tumor necrosis factor alpha inhibitors. Other steroid-sparing therapies such as dapsone, mycophenolate mofetil, intravenous immunoglobulin, and targeted biologic or small molecule inhibitors also have evidence supporting their use. Wound care and management of underlying associated disorders are critical parts of the treatment regimen.

Oncogenic Fatty Acid Metabolism Rewires Energy Supply Chain in Gastric Carcinogenesis.

BACKGROUND & AIMS: Gastric carcinogenesis develops within a sequential carcinogenic cascade from precancerous metaplasia to dysplasia and adenocarcinoma, and oncogenic gene activation can drive the process. Metabolic reprogramming is considered a key mechanism for cancer cell growth and proliferation. However, how metabolic changes contribute to the progression of metaplasia to dysplasia remains unclear. We have examined metabolic dynamics during gastric carcinogenesis using a novel mouse model that induces Kras activation in zymogen-secreting chief cells. METHODS: We generated a Gif-rtTA;TetO-Cre;KrasG12D (GCK) mouse model that continuously induces active Kras expression in chief cells after doxycycline treatment. Histologic examination and imaging mass spectrometry were performed in the GCK mouse stomachs at 2 to 14 weeks after doxycycline treatment. Mouse and human gastric organoids were used for metabolic enzyme inhibitor treatment. The GCK mice were treated with a stearoyl- coenzyme A desaturase (SCD) inhibitor to inhibit the fatty acid desaturation. Tissue microarrays were used to assess the SCD expression in human gastrointestinal cancers. RESULTS: The GCK mice developed metaplasia and high-grade dysplasia within 4 months. Metabolic reprogramming from glycolysis to fatty acid metabolism occurred during metaplasia progression to dysplasia. Altered fatty acid desaturation through SCD produces a novel eicosenoic acid, which fuels dysplastic cell hyperproliferation and survival. The SCD inhibitor killed both mouse and human dysplastic organoids and selectively targeted dysplastic cells in vivo. SCD was up-regulated during carcinogenesis in human gastrointestinal cancers. CONCLUSIONS: Active Kras expression only in gastric chief cells drives the full spectrum of gastric carcinogenesis. Also, oncogenic metabolic rewiring is an essential adaptation for high-energy demand in dysplastic cells.

Popular large language model chatbots' accuracy, comprehensiveness, and self-awareness in answering ocular symptom queries.

In light of growing interest in using emerging large language models (LLMs) for self-diagnosis, we systematically assessed the performance of ChatGPT-3.5, ChatGPT-4.0, and Google Bard in delivering proficient responses to 37 common inquiries regarding ocular symptoms. Responses were masked, randomly shuffled, and then graded by three consultant-level ophthalmologists for accuracy (poor, borderline, good) and comprehensiveness. Additionally, we evaluated the self-awareness capabilities (ability to self-check and self-correct) of the LLM-Chatbots. 89.2% of ChatGPT-4.0 responses were 'good'-rated, outperforming ChatGPT-3.5 (59.5%) and Google Bard (40.5%) significantly (all p < 0.001). All three LLM-Chatbots showed optimal mean comprehensiveness scores as well (ranging from 4.6 to 4.7 out of 5). However, they exhibited subpar to moderate self-awareness capabilities. Our study underscores the potential of ChatGPT-4.0 in delivering accurate and comprehensive responses to ocular symptom inquiries. Future rigorous validation of their performance is crucial to ensure their reliability and appropriateness for actual clinical use.

The double-lasso loop technique of Biceps tenodesis has lower displacement after cyclic loading, compared to interference screw fixation: Biomechanical analysis in an ovine model.

Background: Biceps tenodesis is an effective treatment for symptomatic long head of biceps tendon pathology. Recently the arthroscopic "double lasso-loop" suture anchor (DLSA) technique was described, advantaged by reduced cost, complexity, and operative time. We aimed to compare the in vitro strength of DLSA with conventional interference screws (IS). Methods: A biomechanical analysis was conducted on 14 sheep shoulders (8 DLSA, 6 IS), consisting of a 500-cycle cyclic loading experiment of 5-70 N and ultimate failure load (UFL) test where each specimen was pulled until failure. Displacement (mm) was recorded every 100 cycles, while stiffness and UFL were observed. Results: Cyclic displacement was significantly lower with DLSA at 100 cycles, but not above. During the UFL test, IS was stiffer (27.68 ± 6.56 N/mm versus 14.10 ± 5.80 N/mm, p = .005) and had higher UFL (453.67 ± 148.55 N versus 234.22 ± 44.57 N, p = .001) than DLSA. All DLSA failures occurred with suture/anchor pull-out, while all IS constructs failed at the muscle/tendon. Discussion: Comparison of the novel DLSA technique with a traditional IS method found lower initial displacement. While our IS constructs could withstand higher UFL, peak load characteristics of DLSA were similar to previous ovine studies. Hence, the DLSA technique is a viable alternative to IS for biceps tenodesis with its purported non-biomechanical advantages.