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The dynamin-related guanosine triphosphatase, Drp1 (encoded by Dnm1l), plays a central role in mitochondrial fission and is requisite for numerous cellular processes; however, its role in muscle metabolism remains unclear. Here, we show that, among human tissues, the highest number of gene correlations with DNM1L is in skeletal muscle. Knockdown of Drp1 (Drp1-KD) promoted mitochondrial hyperfusion in the muscle of male mice. Reduced fatty acid oxidation and impaired insulin action along with increased muscle succinate was observed in Drp1-KD muscle. Muscle Drp1-KD reduced complex II assembly and activity as a consequence of diminished mitochondrial translocation of succinate dehydrogenase assembly factor 2 (Sdhaf2). Restoration of Sdhaf2 normalized complex II activity, lipid oxidation, and insulin action in Drp1-KD myocytes. Drp1 is critical in maintaining mitochondrial complex II assembly, lipid oxidation, and insulin sensitivity, suggesting a mechanistic link between mitochondrial morphology and skeletal muscle metabolism, which is clinically relevant in combatting metabolic-related diseases.

This paper presents a novel approach to address the constrained coding challenge of generating almost-balanced sequences. While strictly balanced sequences have been well studied in the past, the problem of designing efficient algorithms with small redundancy, preferably constant or even a single bit, for almost balanced sequences has remained unsolved. A sequence is $\varepsilon(n)$-almost balanced if its Hamming weight is between $0.5n\pm \varepsilon(n)$. It is known that for any algorithm with a constant number of bits, $\varepsilon(n)$ has to be in the order of $\Theta(\sqrt{n})$, with $O(n)$ average time complexity. However, prior solutions with a single redundancy bit required $\varepsilon(n)$ to be a linear shift from $n/2$. Employing an iterative method and arithmetic coding, our emphasis lies in constructing almost balanced codes with a single redundancy bit. Notably, our method surpasses previous approaches by achieving the optimal balanced order of $\Theta(\sqrt{n})$. Additionally, we extend our method to the non-binary case considering $q$-ary almost polarity-balanced sequences for even $q$, and almost symbol-balanced for $q=4$. Our work marks the first asymptotically optimal solutions for almost-balanced sequences, for both, binary and non-binary alphabet., Comment: Accepted to The IEEE International Symposium on Information Theory (ISIT) 2024

An imbalance in energy homeostasis leads to increased lipid storage and obesity. Mechanisms that regulate cellular lipid storage or utilization are thought to play a key role in maintaining energy balance and overall metabolic health. However the mechanisms that regulate energy expenditure and fuel utilization are not well understood. Here we address these gaps in knowledge by first describing a novel mechanism to increase energy expenditure by regulating mitochondrial fuel utilization. We find that blocking pyruvate entry into the mitochondria increases energy expenditure by activating an ATP-demanding lipid cycle of LD breakdown and buildup that is fueled by lipid oxidation. Moreover, recent studies have demonstrated heterogeneity in mitochondrial function, and identified a unique population of BAT mitochondria that support lipid storage by anchoring themselves to LD and facilitating TG synthesis and LD expansion. However, it remains unknown if these unique mitochondria are conserved in other tissues. Here, I describe the development of the first approach to isolate PDM from WAT. Using this approach I show that PDM in WAT have a unique function that is distinct from BAT. Future research understanding the mechanisms that control subpopulations of mitochondria and their roles in lipid homeostasis can provide novel methods of altering energy metabolism through mitochondria.

Mitochondrial depolarization can initiate reversal activity of ATP synthase, depleting ATP by its hydrolysis. We have recently shown that increased ATP hydrolysis contributes to ATP depletion leading to a maladaptation in mitochondrial disorders, where maximal hydrolytic capacity per CV content is increasing. However, despite its importance, ATP hydrolysis is not a commonly studied parameter because of the limitations of the currently available methods. Methods that measure CV hydrolytic activity indirectly require the isolation of mitochondria and involve the introduction of detergents, preventing their utilization in clinical studies or any high-throughput analyses. Here, we describe a novel approach to assess maximal ATP hydrolytic capacity and maximal respiratory capacity in a single assay in cell lysates, PBMCs, and tissue homogenates that were previously frozen. The methodology described here has the potential to be used in clinical samples to determine adaptive and maladaptive adjustments of CV function in diseases, with the added benefit of being able to use frozen samples in a high-throughput manner and to explore ATP hydrolysis as a drug target for disease treatment.

The maintenance of cellular function relies on the close regulation of adenosine triphosphate (ATP) synthesis and hydrolysis. ATP hydrolysis by mitochondrial ATP Synthase (CV) is induced by loss of proton motive force and inhibited by the mitochondrial protein ATPase inhibitor (ATPIF1). The extent of CV hydrolytic activity and its impact on cellular energetics remains unknown due to the lack of selective hydrolysis inhibitors of CV. We find that CV hydrolytic activity takes place in coupled intact mitochondria and is increased by respiratory chain defects. We identified (+)-Epicatechin as a selective inhibitor of ATP hydrolysis that binds CV while preventing the binding of ATPIF1. In cells with Complex-III deficiency, we show that inhibition of CV hydrolytic activity by (+)-Epichatechin is sufficient to restore ATP content without restoring respiratory function. Inhibition of CV-ATP hydrolysis in a mouse model of Duchenne Muscular Dystrophy is sufficient to improve muscle force without any increase in mitochondrial content. We conclude that the impact of compromised mitochondrial respiration can be lessened using hydrolysis-selective inhibitors of CV.

Mitochondria are critical to the governance of metabolism and bioenergetics in cancer cells1. The mitochondria form highly organized networks, in which their outer and inner membrane structures define their bioenergetic capacity2,3. However, in vivo studies delineating the relationship between the structural organization of mitochondrial networks and their bioenergetic activity have been limited. Here we present an in vivo structural and functional analysis of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC) using an integrated platform consisting of positron emission tomography imaging, respirometry and three-dimensional scanning block-face electron microscopy. The diverse bioenergetic phenotypes and metabolic dependencies we identified in NSCLC tumours align with distinct structural organization of mitochondrial networks present. Further, we discovered that mitochondrial networks are organized into distinct compartments within tumour cells. In tumours with high rates of oxidative phosphorylation (OXPHOSHI) and fatty acid oxidation, we identified peri-droplet mitochondrial networks wherein mitochondria contact and surround lipid droplets. By contrast, we discovered that in tumours with low rates of OXPHOS (OXPHOSLO), high glucose flux regulated perinuclear localization of mitochondria, structural remodelling of cristae and mitochondrial respiratory capacity. Our findings suggest that in NSCLC, mitochondrial networks are compartmentalized into distinct subpopulations that govern the bioenergetic capacity of tumours.

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in the world. High levels of free fatty acids in the liver impair hepatic lysosomal acidification and reduce autophagic flux. We investigate whether restoration of lysosomal function in NAFLD recovers autophagic flux, mitochondrial function, and insulin sensitivity. Here, we report the synthesis of novel biodegradable acid-activated acidifying nanoparticles (acNPs) as a lysosome targeting treatment to restore lysosomal acidity and autophagy. The acNPs, composed of fluorinated polyesters, remain inactive at plasma pH, and only become activated in lysosomes after endocytosis. Specifically, they degrade at pH of ~6 characteristic of dysfunctional lysosomes, to further acidify and enhance the function of lysosomes. In established in vivo high fat diet mouse models of NAFLD, re-acidification of lysosomes via acNP treatment restores autophagy and mitochondria function to lean, healthy levels. This restoration, concurrent with reversal of fasting hyperglycemia and hepatic steatosis, indicates the potential use of acNPs as a first-in-kind therapeutic for NAFLD.

Oxidative phosphorylation and glycolysis are the dominant ATP-generating pathways in mammalian metabolism. The balance between these two pathways is often shifted to execute cell-specific functions in response to stimuli that promote activation, proliferation, or differentiation. However, measurement of these metabolic switches has remained mostly qualitative, making it difficult to discriminate between healthy, physiological changes in energy transduction or compensatory responses due to metabolic dysfunction. We therefore present a broadly applicable method to calculate ATP production rates from oxidative phosphorylation and glycolysis using Seahorse XF Analyzer data and empirical conversion factors. We quantify the bioenergetic changes observed during macrophage polarization as well as cancer cell adaptation to in vitro culture conditions. Additionally, we detect substantive changes in ATP utilization upon neuronal depolarization and T cell receptor activation that are not evident from steady-state ATP measurements. This method generates a single readout that allows the direct comparison of ATP produced from oxidative phosphorylation and glycolysis in live cells. Additionally, the manuscript provides a framework for tailoring the calculations to specific cell systems or experimental conditions.

Focusing on the success of Florina Ilis’ novel The children’s crusade, this article explores its potential as a literary contribution in a broader global discourse, as it could be considered “literary Romanian capital” in a discussion about world literature. While the book draws on clichéd stereotypes of Romanian society from the early 2000s, including the Ceaușescu era and the challenging transition from communism to democracy, the author uses a universal language of trauma. This allows for a wider audience to engage with the themes presented in the novel. Thus, her story becomes part of a global collection of works exploring the theme of the “children’s crusade” (including George Zabriskie Gray, Marcel Schwob, Lucian Blaga, Jerzy Andrzejewski, Thea Beckman, Gregory J. Rinaldi, Karleen Bradford, Kathleen McDonnell, Bryce Courtenay, Mario Vargas Llosa, Tullio Avoledo, amongst others). Considering the connection between continuity and innovation in Romanian literature, 75 years following Lucian Blaga’s play, with the same title, Florina Ilis employs a plot with medieval roots in her novel, which has fascinated writers worldwide, to deliver a unique perspective, in a new discourse.

En Colombia, a lo largo de décadas, el enfoque político que se le ha dado a la legalización y no legalización de la marihuana ha sido debatido en todas las instancias e instituciones políticas de nuestro país. (Tomado de la fuente).

DNA sequence classification is a fundamental task in computational biology with vast implications for applications such as disease prevention and drug design. Therefore, fast high-quality sequence classifiers are significantly important. This paper introduces ClaPIM, a scalable DNA sequence classification architecture based on the emerging concept of hybrid in-crossbar and near-crossbar memristive processing-in-memory (PIM). We enable efficient and high-quality classification by uniting the filter and search stages within a single algorithm. Specifically, we propose a custom filtering technique that drastically narrows the search space and a search approach that facilitates approximate string matching through a distance function. ClaPIM is the first PIM architecture for scalable approximate string matching that benefits from the high density of memristive crossbar arrays and the massive computational parallelism of PIM. Compared with Kraken2, a state-of-the-art software classifier, ClaPIM provides significantly higher classification quality (up to 20x improvement in F1 score) and also demonstrates a 1.8x throughput improvement. Compared with EDAM, a recently-proposed SRAM-based accelerator that is restricted to small datasets, we observe both a 30.4x improvement in normalized throughput per area and a 7% increase in classification precision.

Processing-in-memory (PIM) architectures are emerging to reduce data movement in data-intensive applications. These architectures seek to exploit the same physical devices for both information storage and logic, thereby dwarfing the required data transfer and utilizing the full internal memory bandwidth. Whereas analog PIM utilizes the inherent connectivity of crossbar arrays for approximate matrix-vector multiplication in the analog domain, digital PIM architectures enable bitwise logic operations with massive parallelism across columns of data within memory arrays. Several recent works have extended the computational capabilities of digital PIM architectures towards the full-precision (single-precision floating-point) acceleration of convolutional neural networks (CNNs); yet, they lack a comprehensive comparison to GPUs. In this paper, we examine the potential of digital PIM for CNN acceleration through an updated quantitative comparison with GPUs, supplemented with an analysis of the overall limitations of digital PIM. We begin by investigating the different PIM architectures from a theoretical perspective to understand the underlying performance limitations and improvements compared to state-of-the-art hardware. We then uncover the tradeoffs between the different strategies through a series of benchmarks ranging from memory-bound vectored arithmetic to CNN acceleration. We conclude with insights into the general performance of digital PIM architectures for different data-intensive applications.

The Discrete Fourier Transform (DFT) is essential for various applications ranging from signal processing to convolution and polynomial multiplication. The groundbreaking Fast Fourier Transform (FFT) algorithm reduces DFT time complexity from the naive O(n^2) to O(n log n), and recent works have sought further acceleration through parallel architectures such as GPUs. Unfortunately, accelerators such as GPUs cannot exploit their full computing capabilities as memory access becomes the bottleneck. Therefore, this paper accelerates the FFT algorithm using digital Processing-in-Memory (PIM) architectures that shift computation into the memory by exploiting physical devices capable of storage and logic (e.g., memristors). We propose an O(log n) in-memory FFT algorithm that can also be performed in parallel across multiple arrays for high-throughput batched execution, supporting both fixed-point and floating-point numbers. Through the convolution theorem, we extend this algorithm to O(log n) polynomial multiplication - a fundamental task for applications such as cryptography. We evaluate FourierPIM on a publicly-available cycle-accurate simulator that verifies both correctness and performance, and demonstrate 5-15x throughput and 4-13x energy improvement over the NVIDIA cuFFT library on state-of-the-art GPUs for FFT and polynomial multiplication.

Constrained coding is a fundamental field in coding theory that tackles efficient communication through constrained channels. While channels with fixed constraints have a general optimal solution, there is increasing demand for parametric constraints that are dependent on the message length. Several works have tackled such parametric constraints through iterative algorithms, yet they require complex constructions specific to each constraint to guarantee convergence through monotonic progression. In this paper, we propose a universal framework for tackling any parametric constrained-channel problem through a novel simple iterative algorithm. By reducing an execution of this iterative algorithm to an acyclic graph traversal, we prove a surprising result that guarantees convergence with efficient average time complexity even without requiring any monotonic progression. We demonstrate the effectiveness of this universal framework by applying it to a variety of both local and global channel constraints. We begin by exploring the local constraints involving illegal substrings of variable length, where the universal construction essentially iteratively replaces forbidden windows. We apply this local algorithm to the minimal periodicity, minimal Hamming weight, local almost-balanced Hamming weight and the previously-unsolved minimal palindrome constraints. We then continue by exploring global constraints, and demonstrate the effectiveness of the proposed construction on the repeat-free encoding, reverse-complement encoding, and the open problem of global almost-balanced encoding. For reverse-complement, we also tackle a previously-unsolved version of the constraint that addresses overlapping windows. Overall, the proposed framework generates state-of-the-art constructions with significant ease while also enabling the simultaneous integration of multiple constraints for the first time.

Measuring the mitochondrial respiratory capacity of brown adipocytes ex vivo is an essential approach to understand the cell-autonomous regulators of mitochondrial uncoupling in brown adipose tissue. Here, we describe two protocols to isolate brown preadipocytes from mice, their ex vivo differentiation to mature brown adipocytes and the quantification of their mitochondrial uncoupling capacity by respirometry.

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in the world. High levels of free fatty acids in the liver impair hepatic lysosomal acidification and reduce autophagic flux. We investigate whether restoration of lysosomal function in NAFLD recovers autophagic flux, mitochondrial function, and insulin sensitivity. Here, we report the synthesis of novel biodegradable acid-activated acidifying nanoparticles (acNPs) as a lysosome targeting treatment to restore lysosomal acidity and autophagy. The acNPs, composed of fluorinated polyesters, remain inactive at plasma pH, and only become activated in lysosomes after endocytosis. Specifically, they degrade at pH of ~6 characteristic of dysfunctional lysosomes, to further acidify and enhance the function of lysosomes. In established in vivo high fat diet mouse models of NAFLD, re-acidification of lysosomes via acNP treatment restores autophagy and mitochondria function to lean, healthy levels. This restoration, concurrent with reversal of fasting hyperglycemia and hepatic steatosis, indicates the potential use of acNPs as a first-in-kind therapeutic for NAFLD.

The maintenance of cellular function relies on the close regulation of adenosine triphosphate (ATP) synthesis and hydrolysis. ATP hydrolysis by mitochondrial ATP Synthase (CV) is induced by loss of proton motive force and inhibited by the mitochondrial protein ATPase inhibitor (ATPIF1). The extent of CV hydrolytic activity and its impact on cellular energetics remains unknown due to the lack of selective hydrolysis inhibitors of CV. We find that CV hydrolytic activity takes place in coupled intact mitochondria and is increased by respiratory chain defects. We identified (+)‐Epicatechin as a selective inhibitor of ATP hydrolysis that binds CV while preventing the binding of ATPIF1. In cells with Complex‐III deficiency, we show that inhibition of CV hydrolytic activity by (+)‐Epichatechin is sufficient to restore ATP content without restoring respiratory function. Inhibition of CV–ATP hydrolysis in a mouse model of Duchenne Muscular Dystrophy is sufficient to improve muscle force without any increase in mitochondrial content. We conclude that the impact of compromised mitochondrial respiration can be lessened using hydrolysis‐selective inhibitors of CV.

The execution of deep neural network (DNN) algorithms suffers from significant bottlenecks due to the separation of the processing and memory units in traditional computer systems. Emerging memristive computing systems introduce an in situ approach that overcomes this bottleneck. The non-volatility of memristive devices, however, may expose the DNN weights stored in memristive crossbars to potential theft attacks. Therefore, this paper proposes a two-dimensional permutation-based protection (TDPP) method that thwarts such attacks. We first introduce the underlying concept that motivates the TDPP method: permuting both the rows and columns of the DNN weight matrices. This contrasts with previous methods, which focused solely on permuting a single dimension of the weight matrices, either the rows or columns. While it's possible for an adversary to access the matrix values, the original arrangement of rows and columns in the matrices remains concealed. As a result, the extracted DNN model from the accessed matrix values would fail to operate correctly. We consider two different memristive computing systems (designed for layer-by-layer and layer-parallel processing, respectively) and demonstrate the design of the TDPP method that could be embedded into the two systems. Finally, we present a security analysis. Our experiments demonstrate that TDPP can achieve comparable effectiveness to prior approaches, with a high level of security when appropriately parameterized. In addition, TDPP is more scalable than previous methods and results in reduced area and power overheads. The area and power are reduced by, respectively, 1218$\times$ and 2815$\times$ for the layer-by-layer system and by 178$\times$ and 203$\times$ for the layer-parallel system compared to prior works., Comment: 14 pages, 11 figures

Digital processing-in-memory (PIM) architectures mitigate the memory wall problem by facilitating parallel bitwise operations directly within memory. Recent works have demonstrated their algorithmic potential for accelerating data-intensive applications; however, there remains a significant gap in the programming model and microarchitectural design. This is further exacerbated by the emerging model of partitions, which significantly complicates control and periphery. Therefore, inspired by NVIDIA CUDA, this paper provides an end-to-end architectural integration of digital memristive PIM from an abstract high-level C++ programming interface for vector operations to the low-level microarchitecture. We begin by proposing an efficient microarchitecture and instruction set architecture (ISA) that bridge the gap between the low-level control periphery and an abstraction of PIM parallelism into warps and threads. We subsequently propose a PIM compilation library that converts high-level C++ to ISA instructions, and a PIM driver that translates ISA instructions into PIM micro-operations. This drastically simplifies the development of PIM applications and enables PIM integration within larger existing C++ CPU/GPU programs for heterogeneous computing with significant ease. Lastly, we present an efficient GPU-accelerated simulator for the proposed PIM microarchitecture. Although slower than a theoretical PIM chip, this simulator provides an accessible platform for developers to start executing and debugging PIM algorithms. To validate our approach, we implement state-of-the-art matrix operations and FFT PIM-based algorithms as case studies. These examples demonstrate drastically simplified development without compromising performance, showing the potential and significance of CUDA-PIM.

Mitochondrial architecture has long been associated with metabolic flexibility, although the precise causalities and the underlying mechanisms are still enigmatic. We showed that mitochondrial fragmentation is highly associated with fatty acid oxidation (FAO) rates. Furthermore, forced mitochondrial elongation using Mfn2 over-expression or Drp1 depletion significantly decreased FAO rates, while Mfn2 knockout lead to enhanced FAO rates, suggesting that mitochondrial fragmentation is functionally coupled with fatty acid utilization. Notably, the increased FAO rates upon mitochondrial fragmentation is attributed to decreased CPT1 sensitivity to malonyl-CoA, the endogenous CPT1 inhibitor, consistent with the observation that mitochondrial fragmentation specifically facilitates long chain-fatty acid oxidation (LCFAO), but not short chain fatty acid oxidation. Furthermore, we show pharmacological activators of CPT1 enhance FAO of elongate dmitochondria but not in the presence of malonyl-CoA binding. Suggesting mitochondrial morphology influences CPT1’s binding to a CoA moiety. Taken together, our study provides a biochemical and mechanistic explanation of how mitochondrial architecture links cellular metabolic needs to differential fuel utilization, such as LCFAO, which may be implicated in a myriad of human physiologies and pathologies. In non-alcoholic steatohepatitis (NASH), increased Drp1 mediated mitochondrial fragmentation has been observed in hepatocytes. NASH is characterized by liver inflammation, increased hepatocyte swelling, and some degree of fibrosis. Hepatic steatosis can occur when glucose and fatty acid availability exceeds the energy demand of the liver. This presents the question, is increased fission in NASH a compensatory or a pathogenic mechanism? To address this question, we decreased Drp1 function in liver from adult mice with established NASH (26 week-GAN diet) using GalNAc-siRNA mediated delivery. While NASH alone only elevated circulating AST an

Background: CD44 is a multifunctional membrane glycoprotein. Through its heparan sulfate chain, CD44 presents growth factors to their receptors. We have shown that CD44 and Tropomyosin kinase A (TrkA) form a complex following nerve growth factor (NGF) induction. Our study aimed to understand how CD44 and TrkA interact and the consequences of inhibiting this interaction regarding the pro-tumoral effect of NGF in breast cancer. Methods: After determining which CD44 isoforms (variants) are involved in forming the TrkA/CD44 complex using proximity ligation assays, we investigated the molecular determinants of this interaction. By molecular modeling, we isolated the amino acids involved and confirmed their involvement using mutations. A CD44v3 mimetic peptide was then synthesized to block the TrkA/CD44v3 interaction. The effects of this peptide on the growth, migration and invasion of xenografted triple-negative breast cancer cells were assessed. Finally, we investigated the correlations between the expression of the TrkA/CD44v3 complex in tumors and histo-pronostic parameters. Results: We demonstrated that isoform v3 (CD44v3), but not v6, binds to TrkA in response to NGF stimulation. The final 10 amino acids of exon v3 and the TrkA H112 residue are necessary for the association of CD44v3 with TrkA. Functionally, the CD44v3 mimetic peptide impairs not only NGF-induced RhoA activation, clonogenicity, and migration/invasion of breast cancer cells in vitro but also tumor growth and metastasis in a xenograft mouse model. We also detected TrkA/CD44v3 only in cancerous cells, not in normal adjacent tissues.

Ciliary neurotrophic factor (CNTF) acts as a potent neuroprotective cytokine in multiple models of retinal degeneration. To understand mechanisms underlying its broad neuroprotective effects, we have investigated the influence of CNTF on metabolism in a mouse model of photoreceptor degeneration. CNTF treatment improves the morphology of photoreceptor mitochondria, but also leads to reduced oxygen consumption and suppressed respiratory chain activities. Molecular analyses show elevated glycolytic pathway gene transcripts and active enzymes. Metabolomics analyses detect significantly higher levels of ATP and the energy currency phosphocreatine, elevated glycolytic pathway metabolites, increased TCA cycle metabolites, lipid biosynthetic pathway intermediates, nucleotides, and amino acids. Moreover, CNTF treatment restores the key antioxidant glutathione to the wild type level. Therefore, CNTF significantly impacts the metabolic status of degenerating retinas by promoting aerobic glycolysis and augmenting anabolic activities. These findings reveal cellular mechanisms underlying enhanced neuronal viability and suggest potential therapies for treating retinal degeneration.

In type 1 diabetes, dysfunctional glucose regulation occurs due to the death of insulin-producing beta-cells in the pancreatic islets. Initiation of this process is caused by the inheritance of an adaptive immune system that is predisposed to responding to beta-cell antigens, most notably to insulin itself, coupled with unknown environmental insults priming the autoimmune reaction. While autoimmunity is a primary driver in beta-cell death, there is growing evidence that cellular stress participates in the loss of beta-cells. In the beta-cell fragility model, partial loss of islet mass requires compensatory upregulation of insulin production in the remaining islets, driving a cellular stress capable of triggering apoptosis in the remaining cells. The Glis3-Manf axis has been identified as being pivotal to the relative fragility or robustness of stressed islets, potentially operating in both type 1 and type 2 diabetes. Here, we have used an AAV-based gene delivery system to enhance the expression of the anti-apoptotic protein Manf in the beta-cells of NOD mice. Gene delivery substantially lowered the rate of diabetes development in treated mice. Manf-treated mice demonstrated minimal insulitis and superior preservation of insulin production. Our results demonstrating the therapeutic potential of Manf delivery to enhance beta-cell robustness and avert clinical diabetes.

ObjectiveThe contribution of beta-cell dysfunction to type 2 diabetes (T2D) is not restricted to insulinopenia in the late stages of the disease. Elevated fasting insulinemia in normoglycemic humans is a major factor predicting the onset of insulin resistance and T2D, demonstrating an early alteration of beta-cell function in T2D. Moreover, an early and chronic increase in fasting insulinemia contributes to insulin resistance in high-fat diet (HFD)-fed mice. However, whether there are genetic factors that promote beta-cell-initiated insulin resistance remains undefined. Human variants of the mitochondrial transporter ABCB10, which regulates redox by increasing bilirubin synthesis, have been associated with an elevated risk of T2D. The effects of T2D ABCB10 variants on ABCB10 expression and the actions of ABCB10 in beta-cells are unknown.MethodsThe expression of beta-cell ABCB10 was analyzed in published transcriptome datasets from human beta-cells carrying the T2D-risk ABCB10 variant. Insulin sensitivity, beta-cell proliferation, and secretory function were measured in beta-cell-specific ABCB10 KO mice (Ins1Cre-Abcb10flox/flox). The short-term role of beta-cell ABCB10 activity on glucose-stimulated insulin secretion (GSIS) was determined in isolated islets.ResultsCarrying the T2Drisk allele G of ABCB10 rs348330 variant was associated with increased ABCB10 expression in human beta-cells. Constitutive deletion of Abcb10 in beta-cells protected mice from hyperinsulinemia and insulin resistance by limiting HFD-induced beta-cell expansion. An early limitation in GSIS and H2O2-mediated signaling caused by elevated ABCB10 activity can initiate an over-compensatory expansion of beta-cell mass in response to HFD. Accordingly, increasing ABCB10 expression was sufficient to limit GSIS capacity. In health, ABCB10 protein was decreased during islet maturation, with maturation restricting beta-cell proliferation and elevating GSIS. Finally, ex-vivo and short-term deletion of ABCB

Obesity results from an imbalance in energy homeostasis, whereby excessive energy intake exceeds caloric expenditure. Energy can be dissipated out of an organism by producing heat (thermogenesis), explaining the long-standing interest in exploiting thermogenic processes to counteract obesity. Mitochondrial uncoupling is a process that expends energy by oxidizing nutrients to produce heat, instead of ATP synthesis. Energy can also be dissipated through mechanisms that do not involve mitochondrial uncoupling. Such mechanisms include futile cycles described as metabolic reactions that consume ATP to produce a product from a substrate but then converting the product back into the original substrate, releasing the energy as heat. Energy dissipation driven by cellular ATP demand can be regulated by adjusting the speed and number of futile cycles. Energy consuming futile cycles that are reviewed here are lipolysis/fatty acid re-esterification cycle, creatine/phosphocreatine cycle, and the SERCA-mediated calcium import and export cycle. Their reliance on ATP emphasizes that mitochondrial oxidative function coupled to ATP synthesis, and not just uncoupling, can play a role in thermogenic energy dissipation. Here, we review ATP consuming futile cycles, the evidence for their function in humans, and their potential employment as a strategy to dissipate energy and counteract obesity.

The emerging memristive Memory Processing Unit (mMPU) overcomes the memory wall through memristive devices that unite storage and logic for real processing-in-memory (PIM) systems. At the core of the mMPU is stateful logic, which is accelerated with memristive partitions to enable logic with massive inherent parallelism within crossbar arrays. This paper vastly accelerates the fundamental operations of matrix-vector multiplication and convolution in the mMPU, with either full-precision or binary elements. These proposed algorithms establish an efficient foundation for large-scale mMPU applications such as neural-networks, image processing, and numerical methods. We overcome the inherent asymmetry limitation in the previous in-memory full-precision matrix-vector multiplication solutions by utilizing techniques from block matrix multiplication and reduction. We present the first fast in-memory binary matrix-vector multiplication algorithm by utilizing memristive partitions with a tree-based popcount reduction (39x faster than previous work). For convolution, we present a novel in-memory input-parallel concept which we utilize for a full-precision algorithm that overcomes the asymmetry limitation in convolution, while also improving latency (2x faster than previous work), and the first fast binary algorithm (12x faster than previous work).

Reliability is an inherent challenge for the emerging nonvolatile technology of racetrack memories, and there exists a fundamental relationship between codes designed for racetrack memories and codes with constrained periodicity. Previous works have sought to construct codes that avoid periodicity in windows, yet have either only provided existence proofs or required high redundancy. This paper provides the first constructions for avoiding periodicity that are both efficient (average-linear time) and with low redundancy (near the lower bound). The proposed algorithms are based on iteratively repairing windows which contain periodicity until all the windows are valid. Intuitively, such algorithms should not converge as there is no monotonic progression; yet, we prove convergence with average-linear time complexity by exploiting subtle properties of the encoder. Overall, we both provide constructions that avoid periodicity in all windows, and we also study the cardinality of such constraints., Comment: Accepted to The International Symposium on Information Theory and Its Applications (ISITA) 2022

Digital memristive processing-in-memory overcomes the memory wall through a fundamental storage device capable of stateful logic within crossbar arrays. Dynamically dividing the crossbar arrays by adding memristive partitions further increases parallelism, thereby overcoming an inherent trade-off in memristive processing-in-memory. The algorithmic topology of partitions is highly unique, and was recently exploited to accelerate multiplication (11x with 32 partitions) and sorting (14x with 16 partitions). Yet, the physical implementation of memristive partitions, such as the peripheral decoders and the control message, has never been considered and may lead to vast impracticality. This paper overcomes that challenge with several novel techniques, presenting efficient practical designs of memristive partitions. We begin by formalizing the algorithmic properties of memristive partitions into serial, parallel, and semi-parallel operations. Peripheral overhead is addressed via a novel technique of half-gates that enables efficient decoding with negligible overhead. Control overhead is addressed by carefully reducing the operation set of memristive partitions, while resulting in negligible performance impact, by utilizing techniques such as shared indices and pattern generators. Ultimately, these efficient practical solutions, combined with the vast algorithmic potential, may revolutionize digital memristive processing-in-memory.

Digital processing-in-memory (PIM) architectures are rapidly emerging to overcome the memory-wall bottleneck by integrating logic within memory elements. Such architectures provide vast computational power within the memory itself in the form of parallel bitwise logic operations. We develop novel algorithmic techniques for PIM that, combined with new perspectives on computer arithmetic, extend this bitwise parallelism to the four fundamental arithmetic operations (addition, subtraction, multiplication, and division), for both fixed-point and floating-point numbers, and using both bit-serial and bit-parallel approaches. We propose a state-of-the-art suite of arithmetic algorithms, demonstrating the first algorithm in the literature of digital PIM for a majority of cases - including cases previously considered impossible for digital PIM, such as floating-point addition. Through a case study on memristive PIM, we compare the proposed algorithms to an NVIDIA RTX 3070 GPU and demonstrate significant throughput and energy improvements., Comment: Accepted to IEEE Transactions on Emerging Topics in Computing (TETC)

Aligning the entire genome of an organism is a compute-intensive task. Pre-alignment filters substantially reduce computation complexity by filtering potential alignment locations. The base-count filter successfully removes over 68% of the potential locations through a histogram-based heuristic. This paper presents FiltPIM, an efficient design of the basecount filter that is based on memristive processing-in-memory. The in-memory design reduces CPU-to-memory data transfer and utilizes both intra-crossbar and inter-crossbar memristive stateful-logic parallelism. The reduction in data transfer and the efficient stateful-logic computation together improve filtering time by 100x compared to a CPU implementation of the filter., Comment: Published in 2021 28th IEEE International Conference on Electronics, Circuits, and Systems (ICECS)

Recent research has sought to accelerate cryptographic hash functions as they are at the core of modern cryptography. Traditional designs, however, suffer from the von Neumann bottleneck that originates from the separation of processing and memory units. An emerging solution to overcome this bottleneck is processing-in-memory (PIM): performing logic within the same devices responsible for memory to eliminate data-transfer and simultaneously provide massive computational parallelism. In this paper, we seek to vastly accelerate the state-of-the-art SHA-3 cryptographic function using the memristive memory processing unit (mMPU), a general-purpose memristive PIM architecture. To that end, we propose a novel in-memory algorithm for variable rotation, and utilize an efficient mapping of the SHA-3 state vector for memristive crossbar arrays to efficiently exploit PIM parallelism. We demonstrate a massive energy efficiency of 1,422 Gbps/W, improving a state-of-the-art memristive SHA-3 accelerator (SHINE-2) by 4.6x., Comment: Accepted to International Conference on Modern Circuits and Systems Technologies (MOCAST) 2022

Phenotypic plasticity allows carcinoma cells to transiently acquire the quasi-mesenchymal features necessary to detach from the primary mass and proceed along the invasion-metastasis cascade. A broad spectrum of epigenetic mechanisms is likely to cause the epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial (MET) transitions necessary to allow local dissemination and distant metastasis. Here, we report on the role played by alternative splicing (AS) in eliciting phenotypic plasticity in epithelial malignancies with focus on colon cancer. By taking advantage of the coexistence of subpopulations of fully epithelial (EpCAMhi) and quasi-mesenchymal and highly metastatic (EpCAMlo) cells in conventional human cancer cell lines, we here show that the differential expression of ESRP1 and other RNA-binding proteins (RBPs) downstream of the EMT master regulator ZEB1 alters the AS pattern of a broad spectrum of targets including CD44 and NUMB, thus resulting in the generation of specific isoforms functionally associated with increased invasion and metastasis. Additional functional and clinical validation studies indicate that both the newly identified RBPs and the CD44s and NUMB2/4 splicing isoforms promote local invasion and distant metastasis and are associated with poor survival in colon cancer. The systematic elucidation of the spectrum of EMT-related RBPs and AS targets in epithelial cancers, apart from the insights in the mechanisms underlying phenotypic plasticity, will lead to the identification of novel and tumor-specific therapeutic targets.

Proper regulation of cellular lipid storage and oxidation is indispensable for the maintenance of cellular energy homeostasis and health. Mitochondrial function has been shown to be a main determinant of functional lipid storage and oxidation, which is of particular interest for the adipose tissue as it is the main site of triacylglyceride storage in lipid droplets (LDs). Obesity stems from an imbalance between energy intake and energy expenditure, leading to increased lipid storage. Therefore, a better understanding of the mechanisms by which LD break-down and build-up are regulated can be crucial in the development of treatments against metabolic diseases. Blocking mitochondrial pyruvate import in brown adipocytes induces energy wasting via lipid cyclingCombined fatty acid esterification and lipolysis, termed lipid cycling, is an ATP consuming process that contributes to energy expenditure. Therefore, interventions that stimulate energy expenditure through lipid cycling are of great interest. Here we find that pharmacological and genetic inhibition of the mitochondrial pyruvate carrier (MPC) in brown adipocytes activates lipid cycling and energy expenditure, even in the absence of adrenergic stimulation. We show that the resulting increase in ATP demand elevates mitochondrial respiration coupled to ATP synthesis and fueled by lipid oxidation. We identify that glutamine consumption and the Malate-Aspartate Shuttle are required for the increase in Energy Expenditure induced by MPC inhibition in Brown Adipocytes (MAShEEBA). We thus demonstrate that energy expenditure through enhanced lipid cycling can be activated in brown adipocytes by decreasing mitochondrial pyruvate availability. We here present a new mechanism to increase energy expenditure and fat oxidation in brown adipocytes, which does not require adrenergic stimulation of mitochondrial uncoupling. The role of mitochondria attached to Lipid droplets in cellular energy and lipid metabolismRecent studies have

Beige adipocyte mitochondria contribute to thermogenesis by uncoupling and by ATP-consuming futile cycles. Since uncoupling may inhibit ATP synthesis, it is expected that expenditure through ATP synthesis is segregated to a disparate population of mitochondria. Recent studies in mouse brown adipocytes identified peridroplet mitochondria (PDM) as having greater ATP synthesis and pyruvate oxidation capacities, while cytoplasmic mitochondria have increased fatty acid oxidation and uncoupling capacities. However, the occurrence of PDM in humans and the processes that result in their expansion have not been elucidated. Here, we describe a novel high-throughput assay to quantify PDM that is successfully applied to white adipose tissue from mice and humans. Using this approach, we found that PDM content varies between white and brown fat in both species. We used adipose tissue from pheochromocytoma (Pheo) patients as a model of white adipose tissue browning, which is characterized by an increase in the capacity for energy expenditure. In contrast with control subjects, PDM content was robustly increased in the periadrenal fat of Pheo patients. Remarkably, bioenergetic changes associated with browning were primarily localized to PDM compared to cytoplasmic mitochondria (CM). PDM isolated from periadrenal fat of Pheo patients had increased ATP-linked respiration, Complex IV content and activity, and maximal respiratory capacity. We found similar changes in a mouse model of re-browning where PDM content in whitened brown adipose tissue was increased upon re-browning induced by decreased housing temperature. Taken together, this study demonstrates the existence of PDM as a separate functional entity in humans and that browning in both mice and humans is associated with a robust expansion of peri-droplet mitochondria characterized by increased ATP synthesis linked respiration.

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The legitimacy of the term and identity “lesbian” has long been contested, but has come under renewed scrutiny, with some suggesting it is exclusionary and dated. Along with these suggestions is the implication of a generational divide. Supposedly, older women—unaware of contemporary queer discourses—are more likely use the term “lesbian,” whereas younger women are more likely to choose queer affiliated identities. In this paper we draw on survey data investigating why some women might seek to retain the identity “lesbian.” These narratives complicate simplistic accounts of a generational divide. We discuss themes of cross-generational continuity in participants’ sense of historical connection; connection to politics; lesbian visibility; and specificity and boundaries. The theme of lesbian community demonstrated discontinuity: participants of all ages agreed on the importance of lesbian community, but there was generational discontinuity in the access that participants had to it. Our respondents were aware of, and reflective about, current debates situating the category “lesbian” as problematic or obsolete, and nonetheless found utility and meaning in the term. Through their analysis we hope to destabilize discussions about a generational divide defining the use of the term “lesbian” with corresponding questions around ongoing relevance.

The concept that extracellular vesicles (EVs) from the diet can be absorbed by the intestinal tract of the consuming organism, be bioavailable in various organs, and in-turn exert phenotypic changes is highly debatable. Here, we isolate EVs from both raw and commercial bovine milk and characterize them by electron microscopy, nanoparticle tracking analysis, western blotting, quantitative proteomics and small RNA sequencing analysis. Orally administered bovine milk-derived EVs survive the harsh degrading conditions of the gut, in mice, and is subsequently detected in multiple organs. Milk-derived EVs orally administered to mice implanted with colorectal and breast cancer cells reduce the primary tumor burden. Intriguingly, despite the reduction in primary tumor growth, milk-derived EVs accelerate metastasis in breast and pancreatic cancer mouse models. Proteomic and biochemical analysis reveal the induction of senescence and epithelial-to-mesenchymal transition in cancer cells upon treatment with milk-derived EVs. Timing of EV administration is critical as oral administration after resection of the primary tumor reverses the pro-metastatic effects of milk-derived EVs in breast cancer models. Taken together, our study provides context-based and opposing roles of milk-derived EVs as metastasis inducers and suppressors.

Platelets are clearly central to thrombosis and hemostasis. In addition, more recently, evidence has emerged for non-hemostatic roles of platelets including inflammatory and immune reactions/responses. Platelets express immunologically relevant ligands and receptors, demonstrate adhesive interactions with endothelial cells, monocytes and neutrophils, and toll-like receptor (TLR) mediated responses. These properties make platelets central to innate and adaptive immunity and potential candidate key mediators of autoimmune disorders. Multiple sclerosis (MS) is the most common chronic autoimmune central nervous system (CNS) disease. An association between platelets and MS was first indicated by the increased adhesion of platelets to endothelial cells. This was followed by reports identifying structural and functional changes of platelets, their chronic activation in the peripheral blood of MS patients, platelet presence in MS lesions and the more recent revelation that these structural and functional abnormalities are associated with all MS forms and stages. Investigations based on the murine experimental autoimmune encephalomyelitis (EAE) MS model first revealed a contribution to EAE pathogenesis by exacerbation of CNS inflammation and an early role for platelets in EAE development via platelet-neuron and platelet-astrocyte associations, through sialated gangliosides in lipid rafts. Our own studies refined and extended these findings by identifying the critical timing of platelet accumulation in pre-clinical EAE and establishing an initiating and central rather than merely exacerbating role for platelets in disease development. Furthermore, we demonstrated platelet-neuron associations in EAE, coincident with behavioral changes, but preceding the earliest detectable autoreactive T cell accumulation. In combination, these findings establish a new paradigm by asserting that platelets play a neurodegenerative as well as a neuroinflammatory role in MS and therefore, that th

Motivation Identifying rare subpopulations of cells is a critical step in order to extract knowledge from single-cell expression data, especially when the available data is limited and rare subpopulations only contain a few cells. In this paper, we present a data mining method to identify small subpopulations of cells that present highly specific expression profiles. This objective is formalized as a constrained optimization problem that jointly identifies a small group of cells and a corresponding subset of specific genes. The proposed method extends the max-sum submatrix problem to yield genes that are, for instance, highly expressed inside a small number of cells, but have a low expression in the remaining ones. Results We show through controlled experiments on scRNA-seq data that the MicroCellClust method achieves a high F1 score to identify rare sub-populations of artificially planted human T cells. The effectiveness of MicroCellClust is confirmed as it reveals a subpopulation of CD4 T cells with a specific phenotype from breast cancer samples, and a subpopulation linked to a specific stage in the cell cycle from breast cancer samples as well. Finally, 3 rare subpopulations in mouse embryonic stem cells are also identified with MicroCellClust. These results illustrate the proposed method outperforms typical alternatives at identifying small subsets of cells with highly specific expression profiles.

Mitochondria play a central role in lipid metabolism and can bind to lipid droplets. However, the role and functional specialization of the population of peridroplet mitochondria (PDMs) remain unclear, as methods to isolate functional PDMs were not developed until recently. Here, we describe an approach to isolate intact PDMs from murine brown adipose tissue based on their adherence to lipid droplets. PDMs isolated using our approach can be used to study their specialized function by respirometry. For complete information on the use and execution of this protocol, please refer to Benador et al. (2018).

An oral antiviral against SARS-CoV-2 that also attenuates inflammatory instigators of severe COVID-19 is not available to date. Herein, we show that the apoA-I mimetic peptide 4 F inhibits Spike mediated viral entry and has antiviral activity against SARS-CoV-2 in human lung epithelial Calu3 and Vero-E6 cells. In SARS-CoV-2 infected Calu3 cells, 4 F upregulated inducers of the interferon pathway such as MX-1 and Heme oxygenase 1 (HO-1) and downregulated mitochondrial reactive oxygen species (mito-ROS) and CD147, a host protein that mediates viral entry. 4 F also reduced associated cellular apoptosis and secretion of IL-6 in both SARS-CoV-2 infected Vero-E6 and Calu3 cells. Thus, 4 F attenuates in vitro SARS-CoV-2 replication, associated apoptosis in epithelial cells and secretion of IL-6, a major cytokine related to COVID-19 morbidity. Given established safety of 4 F in humans, clinical studies are warranted to establish 4 F as therapy for COVID-19.

Mitochondrial bioenergetic function is a central component of cellular metabolism in health and disease. Mitochondrial oxidative phosphorylation is critical for maintaining energetic homeostasis, and impairment of mitochondrial function underlies the development and progression of metabolic diseases and aging. However, measurement of mitochondrial bioenergetic function can be challenging in human samples due to limitations in the size of the collected sample. Furthermore, the collection of samples from human cohorts is often spread over multiple days and locations, which makes immediate sample processing and bioenergetics analysis challenging. Therefore, sample selection and choice of tests should be carefully considered. Basic research, clinical trials, and mitochondrial disease diagnosis rely primarily on skeletal muscle samples. However, obtaining skeletal muscle biopsies requires an appropriate clinical setting and specialized personnel, making skeletal muscle a less suitable tissue for certain research studies. Circulating white blood cells and platelets offer a promising primary tissue alternative to biopsies for the study of mitochondrial bioenergetics. Recent advances in frozen respirometry protocols combined with the utilization of minimally invasive and non-invasive samples may provide promise for future mitochondrial research studies in humans. Here we review the human samples commonly used for the measurement of mitochondrial bioenergetics with a focus on the advantages and limitations of each sample.

Metal-mediated [2+2+2] cycloadditions of unsaturated molecules to cyclic and polycyclic organic compounds are a versatile synthetic route affording good yields and selectivity under mild conditions. In the last two decades, in silico investigations have unveiled important details about the mechanism and the energetics of the whole catalytic cycle. Particularly, a number of computational studies address the topic of half-sandwich catalysts which, due to their structural fluxionality, have been widely employed, since the 1980s. In these organometallic species, the metal is coordinated to an aromatic ring, typically the ubiquitous cyclopentadienyl anion, C 5H 5-(Cp) or to the Cp moiety of a larger polycyclic aromatic ligand (Cp′). During the catalytic process, the metal continuously 'slips' on the ring, changing its hapticity. This phenomenon of metal slippage and its implications for the catalyst's performance are discussed in this work, referring to the most important computational mechanistic studies reported in literature for Rh(I) half-metallocenes, with the purpose of providing hints for a rational design of this class of compounds. 1 Introduction 2 Mechanism of Metal-Catalyzed Acetylene [2+2+2] Cycloaddition to Benzene and the Problem of the Indenyl Effect 2.1 Acetylene-Acetonitrile [2+2+2] Co-cycloaddition to 2-Methylpyridine: Evidence of the Indenyl Effect 2.2 Heteroaromatic Catalysts and the Evidence of a Reverse Indenyl Effect 2.3 Booth's Mechanistic Hypothesis and the Evidence of the Indenyl Effect 3 Structure-Reactivity Correlation: The Slippage-Span Model 4 Conclusions and Perspectives.

The so-called peroxidatic cysteines and selenocysteines in proteins reduce hydroperoxides through a dual attack to the peroxide bond in a two-step mechanism. First, a proton dislocation from the thiol/selenol to a close residue of the enzymatic pocket occurs. Then, a nucleophilic attack of the anionic cysteine/selenocysteine to one O atom takes place, while the proton is shuttled back to the second O atom, promoting the formation of a water molecule. In this computational study, we use a molecular model of GPx to demonstrate that the enzymatic environment significantly lowers the barrier of the latter SN2 step. Particularly, in our Se-based model the energy barriers for the two steps are 29.82 and 2.83 kcal mol−1, both higher than the corresponding barriers computed in the enzymatic cluster, i. e., 21.60 and null, respectively. Our results, obtained at SMD-B3LYP-D3(BJ)/6-311+G(d,p), cc-pVTZ//B3LYP-D3(BJ)/6-311G(d,p), cc-pVTZ level of theory, show that the mechanistic details can be well reproduced using an oversimplified model, but the energetics is definitively more favorable in the GPx active site. In addition, we pinpoint the role of the chalcogen in the peroxide reduction process, rooting the advantages of the presence of selenium in its acidic and nucleophilic properties.

Processing-in-memory (PIM) solutions vastly accelerate systems by reducing data transfer between computation and memory. Memristors possess a unique property that enables storage and logic within the same device, which is exploited in the memristive Memory Processing Unit (mMPU). The mMPU expands fundamental stateful logic techniques, such as IMPLY, MAGIC and FELIX, to high-throughput parallel logic and arithmetic operations within the memory. Unfortunately, memristive processing-in-memory is highly vulnerable to soft errors and this massive parallelism is not compatible with traditional reliability techniques, such as error-correcting-code (ECC). In this paper, we discuss reliability techniques that efficiently support the mMPU by utilizing the same principles as the mMPU computation. We detail ECC techniques that are based on the unique properties of the mMPU to efficiently utilize the massive parallelism. Furthermore, we present novel solutions for efficiently implementing triple modular redundancy (TMR). The short-term and long-term reliability of large-scale applications, such as neural-network acceleration, are evaluated. The analysis clearly demonstrates the importance of high-throughput reliability mechanisms for memristive processing-in-memory., Comment: Accepted to 28th International Conference on Electronics Circuits and Systems (ICECS) 2021

Processing-in-memory (PIM) seeks to eliminate computation/memory data transfer using devices that support both storage and logic. Stateful logic techniques such as IMPLY, MAGIC and FELIX can perform logic gates within memristive crossbar arrays with massive parallelism. Multiplication via stateful logic is an active field of research due to the wide implications. Recently, RIME has become the state-of-the-art algorithm for stateful single-row multiplication by using memristive partitions, reducing the latency of the previous state-of-the-art by 5.1x. In this paper, we begin by proposing novel partition-based computation techniques for broadcasting and shifting data. Then, we design an in-memory multiplication algorithm based on the carry-save add-shift (CSAS) technique. Finally, we develop a novel stateful full-adder that significantly improves the state-of-the-art (FELIX) design. These contributions constitute MultPIM, a multiplier that reduces state-of-the-art time complexity from quadratic to linear-log. For 32-bit numbers, MultPIM improves latency by an additional 4.2x over RIME, while even slightly reducing area overhead. Furthermore, we optimize MultPIM for full-precision matrix-vector multiplication and improve latency by 25.5x over FloatPIM matrix-vector multiplication., Comment: Accepted to IEEE Transactions On Circuits And Systems-II (TCAS-II)