The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

Poly(ADP-ribose) polymerase 1 (PARP1) is a multifunctional protein involved in diverse cellular functions, notably DNA damage repair. Pharmacological inhibition of PARP1 has therapeutic benefits for various pathologies. Despite the increased use of PARP inhibitors, challenges persist in achieving PARP1 selectivity and effective blood-brain barrier (BBB) penetration. The development of a PARP1-specific positron emission tomography (PET) radioligand is crucial for understanding disease biology and performing target occupancy studies, which may aid in the development of PARP1-specific inhibitors. In this study, we leverage the recently identified PARP1 inhibitor, AZD9574, to introduce the design and development of its ¹⁸F-isotopologue ([¹⁸F]AZD9574). Our comprehensive approach, encompassing pharmacological, cellular, autoradiographic, and in vivo PET imaging evaluations in non-human primates, demonstrates the capacity of [¹⁸F]AZD9574 to specifically bind to PARP1 and to successfully penetrate the BBB. These findings position [¹⁸F]AZD9574 as a viable molecular imaging tool, poised to facilitate the exploration of pathophysiological changes in PARP1 tissue abundance across various diseases.

Inflammatory bowel disease encompasses Crohn’s disease and ulcerative colitis and is characterized by uncontrolled, relapsing, and remitting course of inflammation in the gastrointestinal tract. Artificial intelligence represents a new era within the field of gastroenterology, and the amount of research surrounding artificial intelligence in patients with inflammatory bowel disease is on the rise. As clinical trial outcomes and treatment targets evolve in inflammatory bowel disease, artificial intelligence may prove as a valuable tool for providing accurate, consistent, and reproducible evaluations of endoscopic appearance and histologic activity, thereby optimizing the diagnosis process and identifying disease severity. Furthermore, as the applications of artificial intelligence for inflammatory bowel disease continue to expand, they may present an ideal opportunity for improving disease management by predicting treatment response to biologic therapies and for refining the standard of care by setting the basis for future treatment personalization and cost reduction. The purpose of this review is to provide an overview of the unmet needs in the management of inflammatory bowel disease in clinical practice and how artificial intelligence tools can address these gaps to transform patient care.

This study aims to determine the prevalence of dental anomalies and MSX1 gene 799G>T polymorphism and its association with non-syndromic cleft lip with or without palate (NSCLP) attending Hospital Universiti Sains Malaysia. Clinical and radiological assessments on 37 NSCL±P patients and 80 non-cleft children were done to detect dental anomalies. The buccal cells were collected and polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) was used to identify polymorphism. NSCL±P was higher among males (54%) and mostly unilateral cleft lip and palate (51.3%). The prevalence of dental anomalies in morphology in NSCL±P was 18.9% (95% CI: 5.7%, 32.2%) and non-cleft was 6.3% (95% CI: 0.8%, 11.7%). Hypodontia in NSCLP was 75% (95% CI: 61.2%, 90.2%) and non-cleft was 7.5% (95% CI: 1.6%, 13.4%). There was a significant association between NSCLP and anomalies in morphology (P= 0.04; OR=3.5)) and number (P< 0.01; OR= 40). There was an absence of rare 799G>T polymorphism in all NSCL±P and non-cleft children indicating that all samples contain common 799G polymorphism. In conclusion, the prevalence of dental anomalies in morphology and number was significantly higher in NSCL±P compared to non-cleft children. However, it was not significantly associated with MSX1 799G>T polymorphism.

Background: What we think we see consists of models constructed in our brains, which may be constrained, limited and perhaps modified at a cerebral level. Patients may view their mirror image differently to how others and the clini‑ cal team view them. Understanding potential variations in perception between real and mirror images is important in clinical practice. The aims were to assess differences in self-perception between frontal facial and mirrored photo‑ graphs, comparing the results with selfie photographs. Methods: Facial photographs were taken by one investigator under standardized conditions for preclinical and clini‑ cal students. Each student took a selfie photograph at rest and smiling using his/her smartphone. A mirror image was generated for each image. Each student was shown his/her original and mirror image, without being informed which was which. For each pair of images, students were asked to choose which photograph they perceived as more attractive. A set of photographs of a male volunteer was shown to all participants, to choose either the original or mir‑ ror image as the more attractive. Results: Most observers preferred the true image of the volunteer (P < 0.05), which may be evidence that most people prefer the true image of others, which is how they normally view them. Most observers preferred their own original photograph in frontal view at rest and smiling (P< 0.05), but preferred the mirror image of their selfie photo‑ graph at rest and smiling (P < 0.05). Conclusions Significant differences in perceptions of attractiveness between true and mirror-reversed frontal and selfie images were found. Observers preferred their image the way they view themselves in a mirror. The selfie is how other people view an individual. If a selfie is flipped horizontally, that is how an individual sees themselves in a mirror. Most observers preferred the mirror image of their selfie, which is how they would view themselves in a mirror.

Speech and language skills are among the crucial components in determining cochlear implant habilitation outcomes. The purpose of this study was to investigate speech and language skills of Malay cochlear implant children using a developmental scale questionnaire and to identify the demographic factors that contribute to their performance. This study involved 26 children recruited from the National Cochlear Implant Program under the Malaysian Ministry of Health with chronological ages between 33 to 99 months (mean=72, SD=18.9), implant ages between 18 to 71 months (mean=40, SD=13.5) and hearing ages between 13 to 48 months (mean=30, SD=10.5). The instrument used was The Integrated Scale of Development-Malay version 2 (ISD-Mv2). The questionnaires were given to the parents or caregivers followed with by a phone call interview later. Results from the study showed that only 9 subjects (35%) were able score on the ISD-Mv2 equally or higher than their hearing age. From the six components in the ISD-Mv2, cognitive was scored the highest with 96.79% meanwhile expressive language was the lowest with 76.21%. Pearson correlation test revealed strong positive correlation between audition-receptive language (r=0.554, p<0.05) and cognitive–social communication/ pragmatic (r= 0.625, p<0.05). Speech and language performance of children with demographic factors did not show significant differences. The findings suggests that majority of the Malay cochlear implant children demonstrated delayed speech and language performance as compared to normal hearing children.