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.

Research on IgG4-related disease (IgG4-RD), an autoimmune condition recognized to be a unique disease entity only two decades ago, has processed from describing patients' symptoms and signs to summarizing its critical pathological features, and further to investigating key pathogenic mechanisms. Challenges in gaining a better understanding of the disease, however, stem from its relative rarity-potentially attributed to underrecognition-and the absence of ideal experimental animal models. Recently, with the development of various high-throughput techniques, "omics" studies at different levels (particularly the single-cell omics) have shown promise in providing detailed molecular features of IgG4-RD. While, the application of omics approaches in IgG4-RD is still at an early stage. In this paper, we review the current progress of omics research in IgG4-RD and discuss the value of machine learning methods in analyzing the data with high dimensionality.
Humans ; Immunoglobulin G4-Related Disease/metabolism* ; Immunoglobulin G/metabolism* ; Machine Learning ; Animals ; Proteomics/methods*

Aging is an inevitable, physiological process of the human body, leading to deterioration in bodily function and increased susceptibility to various diseases. Effective endogenous therapeutic strategies for anti-aging and related diseases remain limited. Exercise confers multifaceted benefits to physical health by augmenting osteogenic and myogenic processes, enhancing cardiovascular and nervous system function, and attenuating chronic inflammation. Angiogenesis and lymphangiogenesis play pivotal roles in anti-aging, tissue repair, and immune response modulation, underscoring their potential as therapeutic targets for age-related diseases. Modulating angiogenic and lymphangiogenic pathways may provide a promising strategy for mitigating vascular decline and immune system dysfunction associated with aging. Exercise-induced endogenous angiogenesis and lymphangiogenesis can exert beneficial effects on physiological function, thereby representing a potential therapeutic paradigm for combating age-related decline and diseases. This review offers a thorough summary of the present knowledge regarding angiogenesis and lymphangiogenesis induced by exercise, encompassing the underlying mechanisms and the effects in different organs. In addition, it explores the potential of physical activity as a non-pharmacological intervention for anti-aging strategies and disease management, offering novel insights into the intersection of physical activity, aging, and disease progression.
Humans ; Lymphangiogenesis/physiology* ; Aging/physiology* ; Exercise/physiology* ; Animals ; Neovascularization, Physiologic/physiology* ; Angiogenesis

The syndrome of multiple morphological abnormalities of the sperm flagella (MMAF) is one of the most serious kinds of sperm defects, leading to asthenoteratozoospermia and male infertility. In this study, we use whole-exome sequencing to identify genetic factors that account for male infertility in a patient born from a consanguineous Pakistani couple. A homozygous frameshift mutation (c.1399_1402del; p.Gln468ArgfsTer2) in axonemal dynein light chain domain containing 1 ( AXDND1 ) was identified in the patient. Sanger sequencing data showed that the mutation was cosegregated recessively with male infertility in this family. Papanicolaou staining and scanning electron microscopy analysis of the sperm revealed severely abnormal flagellar morphology in the patient. Immunofluorescence and western blot showed undetectable AXDND1 expression in the sperm of the patient. Transmission electron microscopy analysis showed disorganized sperm axonemal structure in the patient, particularly missing the central pair of microtubules. Immunofluorescence staining showed the absence of sperm-associated antigen 6 (SPAG6) and dynein axonemal light intermediate chain 1 (DNALI1) signals in the sperm flagella of the patient. These findings indicate that AXDND1 is essential for the organization of flagellar axoneme and provide direct evidence that AXDND1 is a MMAF gene in humans, thus expanding the phenotypic spectrum of AXDND1 frameshift mutations.
Humans ; Male ; Sperm Tail/ultrastructure* ; Frameshift Mutation ; Infertility, Male/pathology* ; Pakistan ; Pedigree ; Consanguinity ; Axonemal Dyneins/genetics* ; Adult ; Spermatozoa ; Exome Sequencing

OBJECTIVE: Despite the global decrease in influenza infections during the coronavirus disease 2019 (COVID-19) pandemic, seasonal influenza remains a significant health issue. South Korea, known for its robust pandemic response and high influenza vaccination rates, offers a unique context for examining changes in vaccination trends during the pandemic. Using nationally representative data, we aimed to understand the impact of the pandemic on influenza vaccination behavior over a 12-year period and to identify vulnerable groups. METHODS: We analyzed influenza vaccination rates in South Korea between 2011-2022, focusing on pandemic-related impacts. The data of 2,426,139 adults (≥ 19 years) from the Korea Community Health Survey were used to assess demographic and sociological factors influencing vaccination behaviors. RESULTS: We observed an increase in influenza vaccination rates during the pre-COVID-19 period from 2011-2013 (weighted prevalence: 46.68% [95% confidence interval ( CI): 46.55-46.82]) to 2017-2019 (weighted prevalence: 52.50% [95% CI: 52.38-52.63]). However, a significant decline was observed in 2022, the late-COVID-19 pandemic period (weighted prevalence: 55.78% [95% CI: 55.56-56.01]), compared with the mid-pandemic period in 2021 (weighted prevalence: 59.12% [95% CI: 58.91-59.32]), particularly among populations traditionally prioritized for influenza vaccination, including older adults (≥ 65 years) and patients with chronic diseases and low educational and income levels. CONCLUSION The influenza vaccination rate in South Korea was significantly affected by the COVID-19 pandemic, showing a notable decrease among vulnerable demographic groups. This suggests the need for targeted public health strategies to address vaccine hesitancy and improve vaccination rates, particularly among high-risk populations.
Humans ; Republic of Korea/epidemiology* ; COVID-19/epidemiology* ; Adult ; Middle Aged ; Influenza Vaccines/administration & dosage* ; Male ; Female ; Influenza, Human/epidemiology* ; Aged ; Vaccination/statistics & numerical data* ; Young Adult ; Pandemics ; SARS-CoV-2

Background: Euglycemic diabetic ketoacidosis (EDKA) is a rare but serious complication linked to sodium-glucose cotransporter 2 inhibitor use. Cases of EDKA are increasingly being diagnosed during the perioperative period; however, owing to normal glucose levels, the condition is often overlooked or misattributed to other causes, such as surgical complications—particularly in patients undergoing neurosurgery.Case Report: We present a case of a man in his seventies with poorly controlled diabetes and recent empagliflozin use who developed EDKA following a craniectomy for drainage of an intracranial abscess, with postoperative symptoms mimicking those of an intracranial process. Despite mildly elevated glucose levels, a basic metabolic panel revealed high anion gap metabolic acidosis. Insulin and dextrose therapy was initiated, and the condition resolved within 24 hours. Conclusion This case underscores the need for early recognition of EDKA, especially in neurosurgical settings, where many neurological symptoms of ketoacidosis can be misattributed to postoperative complications.

We report a case of a 24-year-old patient who presented after a head trauma with a traumatic occlusion of his left internal carotid artery. He underwent diagnostic cerebral angiogram and was found to have a direct left carotid-cavernous fistula (CCF) with retrograde filling from the posterior circulation across the posterior communicating artery. Because of the severe injury to the left internal carotid artery (ICA), reconstructive repair of the ICA was not possible. The patient underwent deconstructive repair of the CCF by coil embolization using a posterior retrograde approach. Coils were successfully placed in the cavernous sinus and back into the left ICA with complete cure of the CCF and restoration of cerebral perfusion distal to the treated CCF. We review the types of CCFs, their clinical presentation, and their endovascular treatments. Retrograde access of a direct CCF is rarely reported in the literature, and we believe this approach offers a viable alternative in appropriately selected patients.

Artificial intelligence (AI) is transforming radiology with improved diagnostic accuracy and efficiency, but prediction uncertainty remains a critical challenge. This review examines key sources of uncertainty—out-of-distribution, aleatoric, and model uncertainties—and highlights the importance of independent confidence metrics and explainable AI for safe integration. Independent confidence metrics assess the reliability of AI predictions, while explainable AI provides transparency, enhancing collaboration between AI and radiologists.The development of zero-error tolerance models, designed to minimize errors, sets new standards for safety. Addressing these challenges will enable AI to become a trusted partner in radiology, advancing care standards and patient outcomes.

Inflammatory bowel diseases comprising Crohn’s disease and ulcerative colitis have emerged as global diseases. Multiple distinct therapeutic mechanisms have allowed us to increase our rates of achieving remission and reducing permanent disease-related morbidity. However, there is limited data to inform relative positioning of different therapies. This review will summarize existing literature on use of clinical decision models to inform relative efficacy of one therapeutic mechanism compared to the other given individual patient characteristics. It will also demonstrate the value of serologic, transcriptomic (from biopsies), and microbiome-based biomarkers in identifying which therapy is most likely to work for a given patient. We will review the existing gaps in the literature in this field and suggest a path forward for future studies to better inform patient care, incorporating the principles of precision medicine in the management of inflammatory bowel disease.