Open Access

Background Patients with chronic lymphocytic leukemia (CLL) have a higher risk of developing other malignancies (OMs) compared to the general population. However, the impact of CLL-related risk factors and CLL-directed treatment is still unclear and represents the focus of this work. Methods We conducted a retrospective international multicenter study to assess the incidence of OMs and detect potential risk factors in 19,705 patients with CLL, small lymphocytic lymphoma, or high-count CLL-like monoclonal B-cell lymphocytosis, diagnosed between 2000 and 2016. Data collection took place between October 2020 and March 2022. Findings In 129,254 years of follow-up after CLL diagnosis, 3513 OMs were diagnosed (27.2 OMs/1000 person-years). The most common hematological OMs were Richter transformation, myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Non-melanoma skin (NMSC) and prostate cancers were the most common solid tumors (STs). The only predictor for MDS and AML development was treatment with fludarabine and cyclophosphamide with/without rituximab (FC ± R) (OR = 3.7; 95% CI = 2.79–4.91; p < 0.001). STs were more frequent in males and patients with unmutated immunoglobulin heavy variable genes (OR = 1.77; 95% CI = 1.49–2.11; p < 0.001/OR = 1.89; 95% CI = 1.6–2.24; p < 0.001). CLL-directed treatment was associated with non-melanoma skin and prostate cancers (OR = 1.8; 95% CI = 1.36–2.41; p < 0.001/OR = 2.11; 95% CI = 1.12–3.97; p = 0.021). In contrast, breast cancers were more frequent in untreated patients (OR = 0.17; 95% CI = 0.08–0.33; p < 0.001). Patients with CLL and an OM had inferior overall survival (OS) than those without. AML and MDS conferred the worst OS (p < 0.001).

MC4R gene is a hypothalamic satiety control mediator in which mutations cause a monogenic form of obesity. The aim of this study was to perform a genetic screening to identify variations in the entire region of MC4R gene. A total of 236 unrelated and severely obese patients (BMI ≥ 40 kg/m2) with Spanish ancestry and severe overweight familiar history have been enrolled into the study. Seven MC4R gene variants were identified in the heterozygous state in 21 patients. Coding variants p.Thr101Ile and p.Ala259Asp are new and variants p.Ser30Phe, p.Val103Ile and p.Ile251Leu were previously described. Two variants have been also observed in the promoter region of the MC4R gene; the c.-24G>A mutation, described for the first time, and the known c.-178A>C variant. Both in silico and family segregation analysis confirm the correlation between novel identified mutations in MC4R gene and obesity development. The correlation between the four variants (c.-24G>A, p.Thr101Ile, p.Ala259Asp and p.Ser30Phe) and the obesity phenotype, therefore, allows the conclusion that all of the four mutations cause a monogenic form of obesity.

Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 () for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from , significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.

Objectives More people with dementia live in low- and middle-income countries (LMICs) than in high-income countries, but best-practice care recommendations are often based on studies from high-income countries. We aimed to map the available evidence on dementia interventions in LMICs. Methods We systematically mapped available evidence on interventions that aimed to improve the lives of people with dementia or mild cognitive impairment (MCI) and/or their carers in LMICs (registered on PROSPERO: CRD42018106206). We included randomised controlled trials (RCTs) published between 2008 and 2018. We searched 11 electronic academic and grey literature databases (MEDLINE, EMBASE, PsycINFO, CINAHL Plus, Global Health, World Health Organization Global Index Medicus, Virtual Health Library, Cochrane CENTRAL, Social Care Online, BASE, MODEM Toolkit) and examined the number and characteristics of RCTs according to intervention type. We used the Cochrane risk of bias 2.0 tool to assess the risk of bias. Results We included 340 RCTs with 29,882 (median, 68) participants, published 2008–2018. Over two-thirds of the studies were conducted in China (n = 237, 69.7%). Ten LMICs accounted for 95.9% of included RCTs. The largest category of interventions was Traditional Chinese Medicine (n = 149, 43.8%), followed by Western medicine pharmaceuticals (n = 109, 32.1%), supplements (n = 43, 12.6%), and structured therapeutic psychosocial interventions (n = 37, 10.9%). Overall risk of bias was judged to be high for 201 RCTs (59.1%), moderate for 136 (40.0%), and low for 3 (0.9%). Conclusions Evidence-generation on interventions for people with dementia or MCI and/or their carers in LMICs is concentrated in just a few countries, with no RCTs reported in the vast majority of LMICs. The body of evidence is skewed towards selected interventions and overall subject to high risk of bias. There is a need for a more coordinated approach to robust evidence-generation for LMICs.