European expert recommendations for managing systemic sclerosis and its complications
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Clinical practice recommendations for the diagnosis and management of X-linked hypophosphataemia
X-linked hypophosphataemia (XLH) is a rare metabolic bone disorder caused by pathogenic variants in the PHEX gene, which is predominantly expressed in osteoblasts, osteocytes and odontoblasts. XLH is characterized by increased synthesis of the bone-derived phosphaturic hormone fibroblast growth factor 23 (FGF23), which results in renal phosphate wasting with consecutive hypophosphataemia, rickets, osteomalacia, disproportionate short stature, oral manifestations, pseudofractures, craniosynostosis, enthesopathies and osteoarthritis. Patients with XLH should be provided with multidisciplinary care organized by a metabolic bone expert. Historically, these patients were treated with frequent doses of oral phosphate supplements and active vitamin D, which was of limited efficiency and associated with adverse effects. However, the management of XLH has evolved in the past few years owing to the availability of burosumab, a fully humanized monoclonal antibody that neutralizes circulating FGF23. Here, we provide updated clinical practice recommendations for the diagnosis and management of XLH to improve outcomes and quality of life in these patients.
Autologous haematopoietic stem cell transplantation for treatment of multiple sclerosis and neuromyelitis optica spectrum disorder — recommendations from ECTRIMS and the EBMT
Autologous haematopoietic stem cell transplantation (AHSCT) is a treatment option for relapsing forms of multiple sclerosis (MS) that are refractory to disease-modifying therapy (DMT). AHSCT after failure of high-efficacy DMT in aggressive forms of relapsing–remitting MS is a generally accepted indication, yet the optimal placement of this approach in the treatment sequence is not universally agreed upon. Uncertainties also remain with respect to other indications, such as in rapidly evolving, severe, treatment-naive MS, progressive MS, and neuromyelitis optica spectrum disorder (NMOSD). Furthermore, treatment and monitoring protocols, rehabilitation and other supportive care before and after AHSCT need to be optimized. To address these issues, we convened a European Committee for Treatment and Research in Multiple Sclerosis Focused Workshop in partnership with the European Society for Blood and Marrow Transplantation Autoimmune Diseases Working Party, in which evidence and key questions were presented and discussed by experts in these diseases and in AHSCT. Based on the workshop output and subsequent written interactions, this Consensus Statement provides practical guidance and recommendations on the use of AHSCT in MS and NMOSD. Recommendations are based on the available evidence, or on consensus when evidence was insufficient. We summarize the key evidence, report the final recommendations, and identify areas for further research.
Management practices and manufacturing firm responses to a randomized energy audit
Increasing the efficiency of industrial energy use is widely considered important for mitigating climate change. We randomize assignment of an energy audit intervention aimed at improving energy efficiency and reducing energy expenditures of small- and medium-sized metal processing firms in Shandong Province, China, and examine impacts on energy outcomes and interactions with firms’ management practices. We find that the intervention reduced firms’ unit cost of electricity by 8% on average. Firms with more developed structured management practices showed higher rates of recommendation adoption. However, the post-intervention electricity unit cost reduction is larger in firms with less developed practices, primarily driven by a single recommendation that corrected managers’ inaccurate reporting of transformer usage at baseline, lowering their electricity costs. By closing management-associated gaps in awareness of energy expenditures, energy audit programmes may reduce a firm’s unit cost of energy but have an ambiguous impact on energy use and climate change.
Comparative analysis of the Mexico City Prospective Study and the UK Biobank identifies ancestry-specific effects on clonal hematopoiesis
The impact of genetic ancestry on the development of clonal hematopoiesis (CH) remains largely unexplored. Here, we compared CH in 136,401 participants from the Mexico City Prospective Study (MCPS) to 416,118 individuals from the UK Biobank (UKB) and observed CH to be significantly less common in MCPS compared to UKB (adjusted odds ratio = 0.59, 95% confidence interval (CI) = [0.57, 0.61], P = 7.31 × 10−185). Among MCPS participants, CH frequency was positively correlated with the percentage of European ancestry (adjusted beta = 0.84, 95% CI = [0.66, 1.03], P = 7.35 × 10−19). Genome-wide and exome-wide association analyses in MCPS identified ancestry-specific variants in the TCL1B locus with opposing effects on DNMT3A-CH versus non-DNMT3A-CH. Meta-analysis of MCPS and UKB identified five novel loci associated with CH, including polymorphisms at PARP11/CCND2, MEIS1 and MYCN. Our CH study, the largest in a non-European population to date, demonstrates the power of cross-ancestry comparisons to derive novel insights into CH pathogenesis.
AI can outperform humans in predicting correlations between personality items
We assess the abilities of both specialized deep neural networks, such as PersonalityMap, and general LLMs, including GPT-4o and Claude 3 Opus, in understanding human personality by predicting correlations between personality questionnaire items. All AI models outperform the vast majority of laypeople and academic experts. However, we can improve the accuracy of individual correlation predictions by taking the median prediction per group to produce a “wisdom of the crowds” estimate. Thus, we also compare the median predictions from laypeople, academic experts, GPT-4o/Claude 3 Opus, and PersonalityMap. Based on medians, PersonalityMap and academic experts surpass both LLMs and laypeople on most measures. These results suggest that while advanced LLMs make superior predictions compared to most individual humans, specialized models like PersonalityMap can match even expert group-level performance in domain-specific tasks. This underscores the capabilities of large language models while emphasizing the continued relevance of specialized systems as well as human experts for personality research.
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