Abstract-This paper presents a high-performance maximum power point tracker (MPPT) optimized for fast cloudy conditions, e.g., rapidly changing irradiation on the photovoltaic panels. The rapidly changing conditions are tracked by an optimized hillclimbing MPPT method called dP -P&O. This algorithm separates the effects of the irradiation change from the effect of the tracker's perturbation and uses this information to optimize the tracking according to the irradiation change. The knowledge of the direction of the irradiation change enables the MPPT to use different optimized tracking schemes for the different cases of increasing, decreasing, or steady irradiance. When the irradiance is changing rapidly this strategy leads to faster and better tracking, while in steady-state conditions it leads to lower oscillations around the MPP. The simulations and experimental results show that the proposed dP -P&O MPPT provides a quick and accurate tracking even in very fast changing environmental conditions.

Abstract-This paper presents a high-performance maximum power point tracker (MPPT) optimized for fast cloudy conditions, e.g., rapidly changing irradiation on the photovoltaic panels. The rapidly changing conditions are tracked by an optimized hillclimbing MPPT method called dP -P&O. This algorithm separates the effects of the irradiation change from the effect of the tracker's perturbation and uses this information to optimize the tracking according to the irradiation change. The knowledge of the direction of the irradiation change enables the MPPT to use different optimized tracking schemes for the different cases of increasing, decreasing, or steady irradiance. When the irradiance is changing rapidly this strategy leads to faster and better tracking, while in steady-state conditions it leads to lower oscillations around the MPP. The simulations and experimental results show that the proposed dP -P&O MPPT provides a quick and accurate tracking even in very fast changing environmental conditions.

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Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

BCL-2 inhibition has been shown to be effective in acute myeloid leukemia (AML) in combination with hypomethylating agents or low-dose cytarabine. However, resistance and relapse represent major clinical challenges. Thus, there is an unmet need to overcome resistance to current venetoclax-based strategies. We performed high-throughput drug screening to identify effective combination partners for venetoclax in AML. Overall, 64 anti-leukemic drugs were screened in 31 primary high-risk AML samples with or without venetoclax. Gilteritinib exhibited highest synergy with venetoclax in FLT3 wildtype AML. The combination of gilteritinib and venetoclax increased apoptosis, reduced viability, and was active in venetoclax-azacitidine resistant cell lines and primary patient samples. Proteomics revealed increased FLT3 wildtype signaling in specimens with low in-vitro response to the currently used venetoclax-azacitidine combination. Mechanistically, venetoclax with gilteritinib decreased phosphorylation of ERK and GSK3B via combined AXL and FLT3 inhibition with subsequent suppression of the antiapoptotic protein MCL-1. MCL-1 downregulation was associated with increased MCL-1 phosphorylation of serine 159, decreased phosphorylation of threonine 161 and proteasomal degradation. Gilteritinib and venetoclax were active in a FLT3 wildtype AML PDX model with TP53 mutation and reduced leukemic burden in four FLT3 wildtype AML patients receiving venetoclax-gilteritinib off-label after developing refractory disease under venetoclax-azacitidine. In summary, our results suggest that combined inhibition of FLT3/AXL potentiates venetoclax response in FLT3-wildtype AML by inducing MCL-1 degradation. Thus, the venetoclax-gilteritinib combination merits testing as potentially active regimen in high-risk AML patients with FLT3 wildtype.