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Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a rare inherited cardiac ion channelopathy where the initial disease presentation is during childhood or adolescent stages, leading to increased risks of sudden cardiac death. Despite advances in medical science and technology, several gaps remain in the understanding of the molecular mechanisms, risk prediction, and therapeutic management of patients with CPVT. Recent studies have identified and validated seven sets of genes responsible for various CPVT phenotypes, including RyR2, CASQ-2, TRDN, CALM1, 2, and 3, and TECRL, providing novel insights into the molecular mechanisms. However, more data on atypical CPVT genotypes are required to investigate the underlying mechanisms further. The complexities of the underlying genetics contribute to challenges in risk stratification as well as the uncertainty surrounding nongenetic modifiers. Therapeutically, although medical management involving beta-blockers and flecainide, or insertion of an implantable cardioverter defibrillator remains the mainstay of treatment, animal and stem cell studies on gene therapy for CPVT have shown promising results. However, its clinical applicability remains unclear. Current gene therapy studies have primarily focused on the RyR2 and CASQ-2 variants, which constitute 75% of all CPVT cases. Alternative approaches that target a broader population, such as CaMKII inhibition, could be more feasible for clinical implementation. Together, this review provides an update on recent research on CPVT, highlighting the need for further investigation of the molecular mechanisms, risk stratification, and therapeutic management of this potentially lethal condition.

Abstract Background Tumor lysis syndrome is an oncologic emergency that involves multiple metabolic abnormalities and clinical symptoms such as acute renal failure, cardiac arrhythmias, seizures, and multiorgan failure, and may be fatal if not promptly recognized. Tumor lysis syndrome occurs most often in patients with hematologic malignancies, and relatively few cases have been described in patients with sarcoma. Case presentation A 64-year-old male of Asian heritage presented to his primary care physician with a right lower-extremity mass and was ultimately diagnosed with widely metastatic osteosarcoma. He was treated with one cycle of cisplatin and doxorubicin that was complicated by hypervolemia and hypoxic respiratory failure. Given concerns for volume overload, therapy was changed to single-agent, dose-reduced ifosfamide. After receiving one dose of ifosfamide 1 g/m2 (1.8 g total) intravenously over 1 hour, the patient developed renal failure, hyperuricemia, hyperkalemia, hyperphosphatemia, and lactic acidosis. The patient ultimately died from severe electrolyte abnormalities associated with tumor lysis syndrome. Conclusion This is the first instance of tumor lysis syndrome described in a patient with osteosarcoma undergoing ifosfamide monotherapy. Clinicians must be vigilant in identifying tumor lysis syndrome regardless of the malignancy type or chemotherapy regimen in order to prevent potentially fatal complications.

Pt catalytic nanoparticles on F-doped SnO2/glass substrates were prepared by polyol reduction below 200 °C. The polyol reduction resulted in better transparency of the counter electrode and high power-conversion efficiency (PCE) of the resultant dye-sensitized solar cells (DSSCs) compared to conventional thermal reduction. The PCEs of the DSSCs with 5 μm-thick TiO2 photoanodes were 6.55% and 5.01% under front and back illumination conditions, respectively. The back/front efficiency ratio is very promising for efficient bifacial DSSCs.

Abstract Recent advances in imaging suggested that spatial organization of hematopoietic cells in their bone marrow microenvironment (niche) regulates cell expansion, governing progression, and leukemic transformation of hematological clonal disorders. However, our ability to interrogate the niche in pre-malignant conditions has been limited, as standard murine models of these diseases rely largely on transplantation of the mutant clones into conditioned mice where the marrow microenvironment is compromised. Here, we leveraged live-animal microscopy and ultralow dose whole body or focal irradiation to capture single cells and early expansion of benign/pre-malignant clones in the functionally preserved microenvironment. 0.5 Gy whole body irradiation (WBI) allowed steady engraftment of cells beyond 30 weeks compared to non-conditioned controls. In-vivo tracking and functional analyses of the microenvironment showed no change in vessel integrity, cell viability, and HSC-supportive functions of the stromal cells, suggesting minimal inflammation after the radiation insult. The approach enabled in vivo imaging of Tet2 +/− and its healthy counterpart, showing preferential localization within a shared microenvironment while forming discrete micro-niches. Notably, stationary association with the niche only occurred in a subset of cells and would not be identified without live imaging. This strategy may be broadly applied to study clonal disorders in a spatial context.

Abstract Introduction Up to 88% of sentinel lymph node biopsies (SLNBs) are negative. The 31-gene expression profile (31-GEP) test can help identify patients with a low risk of SLN metastasis who can safely forego SLNB. The 31-GEP classifies patients as low (Class 1 A), intermediate (Class 1B/2A), or high risk (Class 2B) for recurrence, metastasis, and SLN positivity. The integrated 31-GEP (i31-GEP) combines the 31-GEP risk score with clinicopathologic features using a neural network algorithm to personalize SLN risk prediction. Methods Patients from a single surgical center with 31-GEP results were included (n = 156). An i31-GEP risk prediction 10% risk. Using the i31-GEP to guide SLNB decisions could have significantly reduced the number of unnecessary SLNBs by 19.2% (30/156, p 10% had a similar SLN positivity rate (33.3%) as patients with T3-T4 tumors (31.3%). Conclusion The i31-GEP identified patients with

Skepticism of COVID-19 has consequences for public health. We examined several variables that we reasoned were related to skepticism, including demographic factors, people’s perceptions and experiences related to COVID-19, and social media usage. The sample consisted of 294 participants recruited in April of 2020. Participants filled out a survey that included questions related to demographics, social media use, COVID-19 anxiety, COVID-19 interference, and COVID-19 skepticism. In the main, biological sex, ethnicity, and social media use were not significantly associated with skepticism regarding COVID-19. Alternatively, older participants and those who experienced greater anxiety related to the pandemic were less skeptical of COVID-19. Interestingly, people who experienced more interference in their lives because of COVID-19 were more skeptical of the pandemic. Finally, social media use moderated the influence of anxiety and interference on skepticism. The negative effect of anxiety on skepticism became weaker as people’s use of social media increased. The positive effect of interference related to COVID-19 on skepticism became stronger as people used more social media. Our findings underscore the importance of personal beliefs, attitudes, and experiences when explaining skepticism of the pandemic.

Abstract Background Ethnicity is known to be an important correlate of health outcomes, particularly during the COVID-19 pandemic, where some ethnic groups were shown to be at higher risk of infection and adverse outcomes. The recording of patients’ ethnic groups in primary care can support research and efforts to achieve equity in service provision and outcomes; however, the coding of ethnicity is known to present complex challenges. We therefore set out to describe ethnicity coding in detail with a view to supporting the use of this data in a wide range of settings, as part of wider efforts to robustly describe and define methods of using administrative data. Methods We describe the completeness and consistency of primary care ethnicity recording in the OpenSAFELY-TPP database, containing linked primary care and hospital records in > 25 million patients in England. We also compared the ethnic breakdown in OpenSAFELY-TPP with that of the 2021 UK census. Results 78.2% of patients registered in OpenSAFELY-TPP on 1 January 2022 had their ethnicity recorded in primary care records, rising to 92.5% when supplemented with hospital data. The completeness of ethnicity recording was higher for women than for men. The rate of primary care ethnicity recording ranged from 77% in the South East of England to 82.2% in the West Midlands. Ethnicity recording rates were higher in patients with chronic or other serious health conditions. For each of the five broad ethnicity groups, primary care recorded ethnicity was within 2.9 percentage points of the population rate as recorded in the 2021 Census for England as a whole. For patients with multiple ethnicity records, 98.7% of the latest recorded ethnicities matched the most frequently coded ethnicity. Patients whose latest recorded ethnicity was categorised as Other were most likely to have a discordant ethnicity recording (32.2%). Conclusions Primary care ethnicity data in OpenSAFELY is present for over three quarters of all patients, and combined with data from other sources can achieve a high level of completeness. The overall distribution of ethnicities across all English OpenSAFELY-TPP practices was similar to the 2021 Census, with some regional variation. This report identifies the best available codelist for use in OpenSAFELY and similar electronic health record data.

Abstract Background With the global challenge of antimicrobial resistance intensified during the COVID-19 pandemic, evaluating adverse events (AEs) post-antibiotic treatment for common infections is crucial. This study aims to examines the changes in incidence rates of AEs during the COVID-19 pandemic and predict AE risk following antibiotic prescriptions for common infections, considering their previous antibiotic exposure and other long-term clinical conditions. Methods With the approval of NHS England, we used OpenSAFELY platform and analysed electronic health records from patients aged 18–110, prescribed antibiotics for urinary tract infection (UTI), lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), sinusitis, otitis externa, and otitis media between January 2019 and June 2023. We evaluated the temporal trends in the incidence rate of AEs for each infection, analysing monthly changes over time. The survival probability of emergency AE hospitalisation was estimated in each COVID-19 period (period 1: 1 January 2019 to 25 March 2020, period 2: 26 March 2020 to 8 March 2021, period 3: 9 March 2021 to 30 June 2023) using the Kaplan–Meier approach. Prognostic models, using Cox proportional hazards regression, were developed and validated to predict AE risk within 30 days post-prescription using the records in Period 1. Results Out of 9.4 million patients who received antibiotics, 0.6% of UTI, 0.3% of URTI, and 0.5% of LRTI patients experienced AEs. UTI and LRTI patients demonstrated a higher risk of AEs, with a noted increase in AE incidence during the COVID-19 pandemic. Higher comorbidity and recent antibiotic use emerged as significant AE predictors. The developed models exhibited good calibration and discrimination, especially for UTIs and LRTIs, with a C-statistic above 0.70. Conclusions The study reveals a variable incidence of AEs post-antibiotic treatment for common infections, with UTI and LRTI patients facing higher risks. AE risks varied between infections and COVID-19 periods. These findings underscore the necessity for cautious antibiotic prescribing and call for further exploration into the intricate dynamics between antibiotic use, AEs, and the pandemic.