How can the investor community address the ‘S’ in ESG? – the role of social purpose values 16 November 2021 — 1:30PM TO 2:30PM Anonymous (not verified) 18 October 2021 Online

This webinar highlights the crucial relationship between an open civic space and a profitable business environment.

2020 was a tipping point for investors to think and act more responsibly, galvanized by catalysts like the killing of George Floyd and the pandemic. There is increasing investor support for social and environmental causes. Younger investors are placing increasing emphasis on values and social issues in their investment decisions.

The ‘S’ in the Environment Social and Governance (ESG) agenda is clearly gaining traction, but how far does it extend to civil and political liberties i.e. the right of citizens, NGOs and journalists to speak freely, assemble and associate which are increasingly shrinking around the world?

While there is increasing focus on human rights issues such as modern slavery and supply chains, civil society space issues often fall between the cracks when investors consider ESG.

This webinar also explores opportunities and challenges that arise for the investor community in terms of factoring civic space issues into their political risk and ESG analysis.

• To what extent are civic space issues being factored into ESG social purpose values, especially by younger investors?
• What is the best methodology for assessing these issues in order to ensure a common and coherent set of global standards in this area?
• And how can investors mitigate the risks of their activities to civic space in practice?

Expert

Expert

Artificial Intelligence Apps Risk Entrenching India’s Socio-economic Inequities Expert comment sysadmin 14 March 2018

Artificial intelligence applications will not be a panacea for addressing India’s grand challenges. Data bias and unequal access to technology gains will entrench existing socio-economic fissures.

Artificial intelligence (AI) is high on the Indian government’s agenda. Some days ago, Prime Minister Narendra Modi inaugurated the Wadhwani Institute for Artificial Intelligence, reportedly India’s first research institute focused on AI solutions for social good. In the same week, Niti Aayog CEO Amitabh Kant argued that AI could potentially add $957 billion to the economy and outlined ways in which AI could be a ‘game changer’.

During his budget speech, Finance Minister Arun Jaitley announced that Niti Aayog would spearhead a national programme on AI; with the near doubling of the Digital India budget, the IT ministry also announced the setting up of four committees for AI-related research. An industrial policy for AI is also in the pipeline, expected to provide incentives to businesses for creating a globally competitive Indian AI industry.

Narratives on the emerging digital economy often suffer from technological determinism — assuming that the march of technological transformation has an inner logic, independent of social choice and capable of automatically delivering positive social change. However, technological trajectories can and must be steered by social choice and aligned with societal objectives. Modi’s address hit all the right notes, as he argued that the ‘road ahead for AI depends on and will be driven by human intentions’. Emphasising the need to direct AI technologies towards solutions for the poor, he called upon students and teachers to identify ‘the grand challenges facing India’ – to ‘Make AI in India and for India’.

To do so, will undoubtedly require substantial investments in R&D, digital infrastructure and education and re-skilling. But, two other critical issues must be simultaneously addressed: data bias and access to technology gains.

While computers have been mimicking human intelligence for some decades now, a massive increase in computational power and the quantity of available data are enabling a process of ‘machine learning.’ Instead of coding software with specific instructions to accomplish a set task, machine learning involves training an algorithm on large quantities of data to enable it to self-learn; refining and improving its results through multiple iterations of the same task. The quality of data sets used to train machines is thus a critical concern in building AI applications.

Much recent research shows that applications based on machine learning reflect existing social biases and prejudice. Such bias can occur if the data set the algorithm is trained on is unrepresentative of the reality it seeks to represent. If for example, a system is trained on photos of people that are predominantly white, it will have a harder time recognizing non-white people. This is what led a recent Google application to tag black people as gorillas.

Alternatively, bias can also occur if the data set itself reflects existing discriminatory or exclusionary practices. A recent study by ProPublica found for example that software that was being used to assess the risk of recidivism in criminals in the United States was twice as likely to mistakenly flag black defendants as being at higher risk of committing future crimes.

The impact of such data bias can be seriously damaging in India, particularly at a time of growing social fragmentation. It can contribute to the entrenchment of social bias and discriminatory practices, while rendering both invisible and pervasive the processes through which discrimination occurs. Women are 34 per cent less likely to own a mobile phone than men – manifested in only 14 per cent of women in rural India owning a mobile phone, while only 30 per cent of India’s internet users are women.

Women’s participation in the labour force, currently at around 27 per cent, is also declining, and is one of the lowest in South Asia. Data sets used for machine learning are thus likely to have a marked gender bias. The same observations are likely to hold true for other marginalized groups as well.

Accorded to a 2014 report, Muslims, Dalits and tribals make up 53 per cent of all prisoners in India; National Crime Records Bureau data from 2016 shows in some states, the percentage of Muslims in the incarcerated population was almost three times the percentage of Muslims in the overall population. If AI applications for law and order are built on this data, it is not unlikely that it will be prejudiced against these groups.

(It is worth pointing out that the recently set-up national AI task force is comprised of mostly Hindu men – only two women are on the task force, and no Muslims or Christians. A recent article in the New York Times talked about AI’s ‘white guy problem’; will India suffer from a ‘Hindu male bias’?)

Yet, improving the quality, or diversity, of data sets may not be able to solve the problem. The processes of machine learning and reasoning involve a quagmire of mathematical functions, variables and permutations, the logic of which are not readily traceable or predictable. The dazzle of AI-enabled efficiency gains must not blind us to the fact that while AI systems are being integrated into key socio-economic systems, their accuracy and logic of reasoning have not been fully understood or studied.

The other big challenge stems from the distribution of AI-led technology gains. Even if estimates of AI contribution to GDP are correct, the adoption of these technologies is likely to be in niches within the organized sector. These industries are likely to be capital- rather than labour-intensive, and thus unlikely to contribute to large-scale job creation.

At the same time, AI applications can most readily replace low- to medium-skilled jobs within the organized sector. This is already being witnessed in the outsourcing sector – where basic call and chat tasks are now automated. Re-skilling will be important, but it is unlikely that those who lose their jobs will also be those who are being re-skilled – the long arch of technological change and societal adaptation is longer than that of people’s lives. The contractualization of work, already on the rise, is likely to further increase as large industries prefer to have a flexible workforce to adapt to technological change. A shift from formal employment to contractual work can imply a loss of access to formal social protection mechanisms, increasing the precariousness of work for workers.

The adoption of AI technologies is also unlikely in the short- to medium-term in the unorganized sector, which engages more than 80 per cent of India’s labor force. The cost of developing and deploying AI applications, particularly in relation to the cost of labour, will inhibit adoption. Moreover, most enterprises within the unorganized sector still have limited access to basic, older technologies – two-thirds of the workforce are employed in enterprises without electricity. Eco-system upgrades will be important but incremental. Given the high costs of developing AI-based applications, most start-ups are unlikely to be working towards creating bottom-of-the-pyramid solutions.

Access to AI-led technology gains is thus likely to be heavily differentiated – a few high-growth industries can be expected, but these will not necessarily result in the welfare of labour. Studies show that labour share of national income, especially routine labour, has been declining steadily across developing countries.

We should be clear that new technological applications themselves are not going to transform or disrupt this trend – rather, without adequate policy steering, these trends will be exacerbated.

Policy debates about AI applications in India need to take these two issues seriously. AI applications will not be a panacea for addressing ‘India’s grand challenges’. Data bias and unequal access to technology gains will entrench existing socio-economic fissures, even making them technologically binding.

In addition to developing AI applications and creating a skilled workforce, the government needs to prioritize research that examines the complex social, ethical and governance challenges associated with the spread of AI-driven technologies. Blind technological optimism might entrench rather than alleviate the grand Indian challenge of inequity and growth.

This article was originally published in the Indian Express.

India's Response to COVID-19: Political and Social Implications 12 May 2020 — 12:00PM TO 12:45PM Anonymous (not verified) 14 May 2020

On March 23rd, India’s Prime Minister Narendra Modi ordered the world’s largest lockdown on its population of 1.3 billion. The strict measures were praised by some for their success in slowing the spread of coronavirus but faced criticism for the lack of warning which led millions of migrant workers to return home without assistance. Recently the government has begun to lift restrictions in an attempt to revive the economy.

The Indian government has sought technological solutions to contain the pandemic and these have raised concerns around privacy, surveillance, equity and mass use. Furthermore, some low wage workers are forced to accept these solutions if they are to return to work, leaving them with little choice.

In this webinar, the speakers discuss the economic, political and healthcare implications of the coronavirus pandemic on India. Will India seek to rethink its strategy for leadership in the post-COVID-19 global order? Is it possible to develop technologies that can effectively limit the spread of the coronavirus and ensure privacy?

The speakers argue that careful consideration of the second and third-order effects of the pandemic, and the tools being used to contain it, are necessary to preserve rights, liberties, and even democracy.

Song Dai and Qiongling Li
Trans. Amer. Math. Soc. 377 (), 5445-5481.
Abstract, references and article information

Zhanqiang Bai, Jia-Jun Ma, Wei Xiao and Xun Xie
Represent. Theory 28 (), 498-513.
Abstract, references and article information

For many Jamaicans, the deceased are more than just loved ones who have passed on; they are cherished family members who deserve to look as presentable as they did in life. In a culture where the appearance of the deceased is paramount, morticians...

As I walked into the embalming room at Jones Funeral Home and Supplies in Kingston on Sunday, I immediately felt the weight of the room. The air was thick with the scent of various chemicals used in the trade permeating the space. Tools such as...

High-throughput sequencing of hematologic malignancies and other cancers has revealed recurrent mis-sense mutations of genes encoding pre-mRNA splicing factors. The essential splicing factor U2AF2 recognizes a polypyrimidine-tract splice-site signal and initiates spliceosome assembly. Here, we investigate representative, acquired U2AF2 mutations, namely N196K or G301D amino acid substitutions associated with leukemia or solid tumors, respectively. We determined crystal structures of the wild-type (WT) compared with N196K- or G301D-substituted U2AF2 proteins, each bound to a prototypical AdML polypyrimidine tract, at 1.5, 1.4, or 1.7 Å resolutions. The N196K residue appears to stabilize the open conformation of U2AF2 with an inter-RNA recognition motif hydrogen bond, in agreement with an increased apparent RNA-binding affinity of the N196K-substituted protein. The G301D residue remains in a similar position as the WT residue, where unfavorable proximity to the RNA phosphodiester could explain the decreased RNA-binding affinity of the G301D-substituted protein. We found that expression of the G301D-substituted U2AF2 protein reduces splicing of a minigene transcript carrying prototypical splice sites. We further show that expression of either N196K- or G301D-substituted U2AF2 can subtly alter splicing of representative endogenous transcripts, despite the presence of endogenous, WT U2AF2 such as would be present in cancer cells. Altogether, our results demonstrate that acquired U2AF2 mutations such as N196K and G301D are capable of dysregulating gene expression for neoplastic transformation.

Aminopeptidase N (APN, CD13) is a transmembrane ectopeptidase involved in many crucial cellular functions. Besides its role as a peptidase, APN also mediates signal transduction and is involved in the activation of matrix metalloproteinases (MMPs). MMPs function in tissue remodeling within the extracellular space and are therefore involved in many human diseases, such as fibrosis, rheumatoid arthritis, tumor angiogenesis, and metastasis, as well as viral infections. However, the exact mechanism that leads to APN-driven MMP activation is unclear. It was previously shown that extracellular 14-3-3 adapter proteins bind to APN and thereby induce the transcription of MMPs. As a first step, we sought to identify potential 14-3-3–binding sites in the APN sequence. We constructed a set of phosphorylated peptides derived from APN to probe for interactions. We identified and characterized a canonical 14-3-3–binding site (site 1) within the flexible, structurally unresolved N-terminal APN region using direct binding fluorescence polarization assays and thermodynamic analysis. In addition, we identified a secondary, noncanonical binding site (site 2), which enhances the binding affinity in combination with site 1 by many orders of magnitude. Finally, we solved crystal structures of 14-3-3σ bound to mono- and bis-phosphorylated APN-derived peptides, which revealed atomic details of the binding mode of mono- and bivalent 14-3-3 interactions. Therefore, our findings shed some light on the first steps of APN-mediated MMP activation and open the field for further investigation of this important signaling pathway.

27 August 2020

Cancer cachexia is characterized by reductions in peripheral lean muscle mass. Prior studies have primarily focused on increased protein breakdown as the driver of cancer-associated muscle wasting. Therapeutic interventions targeting catabolic pathways have, however, largely failed to preserve muscle mass in cachexia, suggesting that other mechanisms might be involved. In pursuit of novel pathways, we used untargeted metabolomics to search for metabolite signatures that may be linked with muscle atrophy. We injected 7-week–old C57/BL6 mice with LLC1 tumor cells or vehicle. After 21 days, tumor-bearing mice exhibited reduced body and muscle mass and impaired grip strength compared with controls, which was accompanied by lower synthesis rates of mixed muscle protein and the myofibrillar and sarcoplasmic muscle fractions. Reductions in protein synthesis were accompanied by mitochondrial enlargement and reduced coupling efficiency in tumor-bearing mice. To generate mechanistic insights into impaired protein synthesis, we performed untargeted metabolomic analyses of plasma and muscle and found increased concentrations of two methylarginines, asymmetric dimethylarginine (ADMA) and NG-monomethyl-l-arginine, in tumor-bearing mice compared with control mice. Compared with healthy controls, human cancer patients were also found to have higher levels of ADMA in the skeletal muscle. Treatment of C2C12 myotubes with ADMA impaired protein synthesis and reduced mitochondrial protein quality. These results suggest that increased levels of ADMA and mitochondrial changes may contribute to impaired muscle protein synthesis in cancer cachexia and could point to novel therapeutic targets by which to mitigate cancer cachexia.

Visual Abstract

Visual Abstract

Madison T Wright
Nov 18, 2020; 0:RA120.002168v1-mcp.RA120.002168
Research

David Durán
Nov 19, 2020; 0:RA120.002276v1-mcp.RA120.002276
Research

Qin Zhang
Nov 17, 2020; 0:RA120.002325v1-mcp.RA120.002325
Research

Leandro Xavier Neves
Nov 11, 2020; 0:RA120.002227v1-mcp.RA120.002227
Research

Gle1 is a conserved, essential regulator of DEAD-box RNA helicases, with critical roles defined in mRNA export, translation initiation, translation termination, and stress granule formation. Mechanisms that specify which, where, and when DDXs are targeted by Gle1 are critical to understand. In addition to roles for stress-induced phosphorylation and inositol hexakisphosphate binding in specifying Gle1 function, Gle1 oligomerizes via its N-terminal domain in a phosphorylation-dependent manner. However, a thorough analysis of the role for Gle1 self-association is lacking. Here, we find that Gle1 self-association is driven by two distinct regions: a coiled-coil domain and a novel 10-amino acid aggregation-prone region, both of which are necessary for proper Gle1 oligomerization. By exogenous expression in HeLa cells, we tested the function of a series of mutations that impact the oligomerization domains of the Gle1A and Gle1B isoforms. Gle1 oligomerization is necessary for many, but not all aspects of Gle1A and Gle1B function, and the requirements for each interaction domain differ. Whereas the coiled-coil domain and aggregation-prone region additively contribute to competent mRNA export and stress granule formation, both self-association domains are independently required for regulation of translation under cellular stress. In contrast, Gle1 self-association is dispensable for phosphorylation and nonstressed translation initiation. Collectively, we reveal self-association functions as an additional mode of Gle1 regulation to ensure proper mRNA export and translation. This work also provides further insight into the mechanisms underlying human gle1 disease mutants found in prenatally lethal forms of arthrogryposis.

Genetic mutations related to ALS, a progressive neurological disease, have been discovered in the gene encoding σ-1 receptor (σ1R). We previously reported that σ1RE102Q elicits toxicity in cells. The σ1R forms oligomeric states that are regulated by ligands. Nevertheless, little is known about the effect of ALS-related mutations on oligomer formation. Here, we transfected NSC-34 cells, a motor neuronal cell line, and HEK293T cells with σ1R-mCherry (mCh), σ1RE102Q-mCh, or nontagged forms to investigate detergent solubility and subcellular distribution using immunocytochemistry and fluorescence recovery after photobleaching. The oligomeric state was determined using crosslinking procedure. σ1Rs were soluble to detergents, whereas the mutants accumulated in the insoluble fraction. Within the soluble fraction, peak distribution of mutants appeared in higher sucrose density fractions. Mutants formed intracellular aggregates that were co-stained with p62, ubiquitin, and phosphorylated pancreatic eukaryotic translation initiation factor-2-α kinase in NSC-34 cells but not in HEK293T cells. The aggregates had significantly lower recovery in fluorescence recovery after photobleaching. Acute treatment with σ1R agonist SA4503 failed to improve recovery, whereas prolonged treatment for 48 h significantly decreased σ1RE102Q-mCh insolubility and inhibited apoptosis. Whereas σ1R-mCh formed monomers and dimers, σ1RE102Q-mCh also formed trimers and tetramers. SA4503 reduced accumulation of the four types in the insoluble fraction and increased monomers in the soluble fraction. The σ1RE102Q insolubility was diminished by σ1R-mCh co-expression. These results suggest that the agonist and WT σ1R modify the detergent insolubility, toxicity, and oligomeric state of σ1RE102Q, which may lead to promising new treatments for σ1R-related ALS.

Type I and III interferons induce expression of the “myxovirus resistance proteins” MxA in human cells and its ortholog Mx1 in murine cells. Human MxA forms cytoplasmic structures, whereas murine Mx1 forms nuclear bodies. Whereas both HuMxA and MuMx1 are antiviral toward influenza A virus (FLUAV) (an orthomyxovirus), only HuMxA is considered antiviral toward vesicular stomatitis virus (VSV) (a rhabdovirus). We previously reported that the cytoplasmic human GFP-MxA structures were phase-separated membraneless organelles (“biomolecular condensates”). In the present study, we investigated whether nuclear murine Mx1 structures might also represent phase-separated biomolecular condensates. The transient expression of murine GFP-Mx1 in human Huh7 hepatoma, human Mich-2H6 melanoma, and murine NIH 3T3 cells led to the appearance of Mx1 nuclear bodies. These GFP-MuMx1 nuclear bodies were rapidly disassembled by exposing cells to 1,6-hexanediol (5%, w/v), or to hypotonic buffer (40–50 mosm), consistent with properties of membraneless phase-separated condensates. Fluorescence recovery after photobleaching (FRAP) assays revealed that the GFP-MuMx1 nuclear bodies upon photobleaching showed a slow partial recovery (mobile fraction: ∼18%) suggestive of a gel-like consistency. Surprisingly, expression of GFP-MuMx1 in Huh7 cells also led to the appearance of GFP-MuMx1 in 20–30% of transfected cells in a novel cytoplasmic giantin-based intermediate filament meshwork and in cytoplasmic bodies. Remarkably, Huh7 cells with cytoplasmic murine GFP-MuMx1 filaments, but not those with only nuclear bodies, showed antiviral activity toward VSV. Thus, GFP-MuMx1 nuclear bodies comprised phase-separated condensates. Unexpectedly, GFP-MuMx1 in Huh7 cells also associated with cytoplasmic giantin-based intermediate filaments, and such cells showed antiviral activity toward VSV.

Priyanka Tripathi
Dec 30, 2020; 0:jlr.RA120001190v1-jlr.RA120001190
Research Articles

Abudukadier Abulizi
Dec 1, 2020; 61:1565-1576
Research Articles

Yueming Hu
Dec 11, 2020; 0:jlr.RA120000919v1-jlr.RA120000919
Research Articles

Roux-en-Y gastric bypass (RYGB) is one of the most commonly performed weight-loss procedures, but how severe obesity and RYGB affects circulating HDL-associated microRNAs (miRNAs) remains unclear. Here, we aim to investigate how HDL-associated miRNAs are regulated in severe obesity and how weight loss after RYGB surgery affects HDL-miRNAs. Plasma HDL were isolated from patients with severe obesity (n=53) before, 6 and 12 months after RYGB by immunoprecipitation using goat anti-human apoA-I microbeads. HDL were also isolated from 18 healthy participants. miRNAs were extracted from isolated HDL and levels of miR-24, miR-126, miR-222 and miR-223 were determined by TaqMan miRNA assays. We found that HDL-associated miR-126, miR-222 and miR-223 levels, but not miR-24 levels, were significantly higher in patients with severe obesity when compared with healthy controls. There were significant increases in HDL-associated miR-24, miR-222 and miR-223 at 12 months after RYGB. Additionally, cholesterol efflux capacity and paraoxonase (PON1) activity were increased and intracellular adhesion molecule-1 (ICAM-1) levels decreased. The increases in HDL-associated miR-24 and miR-223 were positively correlated with increase in cholesterol efflux capacity (r=0.326, P=0.027 and r=0.349, P=0.017 respectively). An inverse correlation was observed between HDL-associated miR-223 and ICAM-1 at baseline. Together, these findings show that HDL-associated miRNAs are differentially regulated in healthy versus patients with severe obesity and are altered after RYGB. These findings provide insights into how miRNAs are regulated in obesity before and after weight reduction, and may lead to the development of novel treatment strategies for obesity and related metabolic disorders.

Apolipoproteins C-I, C-II and C-III interact with ApoE to regulate lipoprotein metabolism and contribute to Alzheimer’s disease pathophysiology. In plasma, apoC-I and C-II exist as truncated isoforms, while apoC-III exhibits multiple glycoforms. This study aimed to 1. delineate apoC-I, C-II and C-III isoform profiles in CSF and plasma in a cohort of non-demented older individuals (n = 61), and 2. examine the effect of APOE4 on these isoforms and their correlation with CSF Aβ42, a surrogate of brain amyloid accumulation. The isoforms of the apoCs were immunoaffinity enriched and measured with MALDI-TOF mass spectrometry, revealing a significantly higher percentage of truncated apoC-I and apoC-II in CSF compared to matched plasma, with positive correlation between CSF and plasma. A greater percentage of monosialylated and disialylated apoC-III isoforms was detected in CSF, accompanied by a lower percentage of the two non-sialylated apoC-III isoforms, with significant linear correlations between CSF and plasma. Furthermore, a greater percentage of truncated apoC-I in CSF, and apoC-II in plasma and CSF, was observed in individuals carrying at least one apoE E4 allele. Increased apoC-I and apoC-II truncations were  associated with lower CSF Aβ42. Finally, monosialylated apoC-III was lower, and disialylated apoC-III greater in the CSF of E4 carriers. Together, these results reveal distinct patterns of the apoCs isoforms in CSF, implying CSF-specific apoCs processing. These patterns were accentuated in APOE E4 allele carriers, suggesting an association between APOE4 genotype and Alzheimer’s disease pathology with apoCs processing and function in the brain.

Microtubules are polymers composed of αβ-tubulin subunits that provide structure to cells and play a crucial role in in the development and function of neuronal processes and cilia, microtubule-driven extensions of the plasma membrane that have sensory (primary cilia) or motor (motile cilia) functions. To stabilize microtubules in neuronal processes and cilia, α tubulin is modified by the posttranslational addition of an acetyl group, or acetylation. We discovered that acetylated tubulin in microtubules interacts with the membrane sphingolipid, ceramide. However, the molecular mechanism and function of this interaction are not understood. Here, we show that in human iPS cell-derived neurons, ceramide stabilizes microtubules, which indicates a similar function in cilia. Using proximity ligation assays, we detected complex formation of ceramide with acetylated tubulin in C. reinhardtii flagella and cilia of human embryonic kidney (HEK293T) cells, primary cultured mouse astrocytes, and ependymal cells. Using incorporation of palmitic azide and click chemistry-mediated addition of fluorophores, we show that a portion of acetylated tubulin is S-palmitoylated. S-palmitoylated acetylated tubulin is colocalized with ceramide-rich platforms (CRPs) in the ciliary membrane, and it is coimmunoprecipitated with Arl13b, a GTPase that mediates transport of proteins into cilia. Inhibition of S-palmitoylation with 2-bromo palmitic acid or inhibition of ceramide biosynthesis with fumonisin B1 reduces formation of the Arl13b-acetylated tubulin complex and its transport into cilia, concurrent with impairment of ciliogenesis. Together, these data show, for the first time, that CRPs mediate membrane anchoring and interaction of S-palmitoylated proteins that are critical for cilium formation, stabilization, and function. 

Lipoprotein (a) [Lp(a)] is a well-known risk factor for cardiovascular disease, but analysis on Lp(a) and renal dysfunction is scarce. We aimed to investigate prospectively the association of serum Lp(a) with the risk of reduced renal function, and further investigated whether diabetic or hypertensive status modified such association. Six thousand two hundred and fifty-seven Chinese adults aged ≤40 years and free of reduced renal function at baseline were included in the study. Reduced renal function was defined as estimated glomerular filtration rate <60 ml/min/1.73 m². During a mean follow-up of 4.4 years, 158 participants developed reduced renal function. Each one-unit increase in log₁₀-Lp(a) (milligrams per deciliter) was associated with a 1.99-fold (95% CI 1.15–3.43) increased risk of incident reduced renal function; the multivariable-adjusted odds ratio (OR) for the highest tertile of Lp(a) was 1.61 (95% CI 1.03–2.52) compared with the lowest tertile (P for trend = 0.03). The stratified analysis showed the association of serum Lp(a) and incident reduced renal function was more prominent in participants with prevalent diabetes [OR 4.04, 95% CI (1.42–11.54)] or hypertension [OR 2.18, 95% CI (1.22–3.89)]. A stronger association was observed in the group with diabetes and high Lp(a) (>25 mg/dl), indicating a combined effect of diabetes and high Lp(a) on the reduced renal function risk. An elevated Lp(a) level was independently associated with risk of incident reduced renal function, especially in diabetic or hypertensive patients.

Microsomal triglyceride transfer protein (MTTP) deficiency results in a syndrome of hypolipidemia and accelerated NAFLD. Animal models of decreased hepatic MTTP activity have revealed an unexplained dissociation between hepatic steatosis and hepatic insulin resistance. Here, we performed comprehensive metabolic phenotyping of liver-specific MTTP knockout (L-Mttp^–/–) mice and age-weight matched wild-type control mice. Young (10–12-week-old) L-Mttp^–/– mice exhibited hepatic steatosis and increased DAG content; however, the increase in hepatic DAG content was partitioned to the lipid droplet and was not increased in the plasma membrane. Young L-Mttp^–/– mice also manifested normal hepatic insulin sensitivity, as assessed by hyperinsulinemic-euglycemic clamps, no PKC activation, and normal hepatic insulin signaling from the insulin receptor through AKT Ser/Thr kinase. In contrast, aged (10-month-old) L-Mttp^–/– mice exhibited glucose intolerance and hepatic insulin resistance along with an increase in hepatic plasma membrane sn-1,2-DAG content and PKC activation. Treatment with a functionally liver-targeted mitochondrial uncoupler protected the aged L-Mttp^–/– mice against the development of hepatic steatosis, increased plasma membrane sn-1,2-DAG content, PKC activation, and hepatic insulin resistance. Furthermore, increased hepatic insulin sensitivity in the aged controlled-release mitochondrial protonophore-treated L-Mttp^–/– mice was not associated with any reductions in hepatic ceramide content. Taken together, these data demonstrate that differences in the intracellular compartmentation of sn-1,2-DAGs in the lipid droplet versus plasma membrane explains the dissociation of NAFLD/lipid-induced hepatic insulin resistance in young L-Mttp^–/– mice as well as the development of lipid-induced hepatic insulin resistance in aged L-Mttp^–/– mice.

A comprehensive and standardized system to report lipid structures analyzed by MS is essential for the communication and storage of lipidomics data. Herein, an update on both the LIPID MAPS classification system and shorthand notation of lipid structures is presented for lipid categories Fatty Acyls (FA), Glycerolipids (GL), Glycerophospholipids (GP), Sphingolipids (SP), and Sterols (ST). With its major changes, i.e., annotation of ring double bond equivalents and number of oxygens, the updated shorthand notation facilitates reporting of newly delineated oxygenated lipid species as well. For standardized reporting in lipidomics, the hierarchical architecture of shorthand notation reflects the diverse structural resolution powers provided by mass spectrometric assays. Moreover, shorthand notation is expanded beyond mammalian phyla to lipids from plant and yeast phyla. Finally, annotation of atoms is included for the use of stable isotope-labeled compounds in metabolic labeling experiments or as internal standards. This update on lipid classification, nomenclature, and shorthand annotation for lipid mass spectra is considered a standard for lipid data presentation.

The plasma membrane of a cell is characterized by an asymmetric distribution of lipid species across the exofacial and cytofacial aspects of the bilayer. Regulation of membrane asymmetry is a fundamental characteristic of membrane biology and is crucial for signal transduction, vesicle transport, and cell division. The type IV family of P-ATPases, or P4-ATPases, establishes membrane asymmetry by selection and transfer of a subset of membrane lipids from the lumenal or exofacial leaflet to the cytofacial aspect of the bilayer. It is unclear how P4-ATPases sort through the spectrum of membrane lipids to identify their desired substrate(s) and how the membrane environment modulates this activity. Therefore, we tested how the yeast plasma membrane P4-ATPase, Dnf2, responds to changes in membrane composition induced by perturbation of endogenous lipid biosynthetic pathways or exogenous application of lipid. The primary substrates of Dnf2 are glucosylceramide (GlcCer) and phosphatidylcholine (PC, or their lyso-lipid derivatives), and we find that these substrates compete with each other for transport. Acutely inhibiting sphingolipid synthesis using myriocin attenuates transport of exogenously applied GlcCer without perturbing PC transport. Deletion of genes controlling later steps of glycosphingolipid production also perturb GlcCer transport to a greater extent than PC transport. In contrast, perturbation of ergosterol biosynthesis reduces PC and GlcCer transport equivalently. Surprisingly, application of lipids that are poor transport substrates differentially affects PC and GlcCer transport by Dnf2, thus altering substrate preference. Our data indicate that Dnf2 exhibits exquisite sensitivity to the membrane composition, thus providing feedback onto the function of the P4-ATPases.

Ventilator-associated pneumonia (VAP) is a common hospital-acquired infection, leading to high morbidity and mortality. Currently, bronchoalveolar lavage (BAL) is used in hospitals for VAP diagnosis and guiding treatment options. Although BAL collection procedures are invasive, alternatives such as endotracheal aspirates (ETA) may be of diagnostic value, however, their use has not been thoroughly explored. Longitudinal ETA and BAL were collected from 16 intubated patients up to 15 days, of which 11 developed VAP. We conducted a comprehensive LC–MS/MS based proteome and metabolome characterization of longitudinal ETA and BAL to detect host and pathogen responses to VAP infection. We discovered a diverse ETA proteome of the upper airways reflective of a rich and dynamic host-microbe interface. Prior to VAP diagnosis by microbial cultures from BAL, patient ETA presented characteristic signatures of reactive oxygen species and neutrophil degranulation, indicative of neutrophil mediated pathogen processing as a key host response to the VAP infection. Along with an increase in amino acids, this is suggestive of extracellular membrane degradation resulting from proteolytic activity of neutrophil proteases. The metaproteome approach successfully allowed simultaneous detection of pathogen peptides in patients' ETA, which may have potential use in diagnosis. Our findings suggest that ETA may facilitate early mechanistic insights into host-pathogen interactions associated with VAP infection and therefore provide its diagnosis and treatment.

Studies in the yeast Saccharomyces cerevisiae have helped define mechanisms underlying the activity of the ubiquitin–proteasome system (UPS), uncover the proteasome assembly pathway, and link the UPS to the maintenance of cellular homeostasis. However, the spectrum of UPS substrates is incompletely defined, even though multiple techniques—including MS—have been used. Therefore, we developed a substrate trapping proteomics workflow to identify previously unknown UPS substrates. We first generated a yeast strain with an epitope tagged proteasome subunit to which a proteasome inhibitor could be applied. Parallel experiments utilized inhibitor insensitive strains or strains lacking the tagged subunit. After affinity isolation, enriched proteins were resolved, in-gel digested, and analyzed by high resolution liquid chromatography-tandem MS. A total of 149 proteasome partners were identified, including all 33 proteasome subunits. When we next compared data between inhibitor sensitive and resistant cells, 27 proteasome partners were significantly enriched. Among these proteins were known UPS substrates and proteins that escort ubiquitinated substrates to the proteasome. We also detected Erg25 as a high-confidence partner. Erg25 is a methyl oxidase that converts dimethylzymosterol to zymosterol, a precursor of the plasma membrane sterol, ergosterol. Because Erg25 is a resident of the endoplasmic reticulum (ER) and had not previously been directly characterized as a UPS substrate, we asked whether Erg25 is a target of the ER associated degradation (ERAD) pathway, which most commonly mediates proteasome-dependent destruction of aberrant proteins. As anticipated, Erg25 was ubiquitinated and associated with stalled proteasomes. Further, Erg25 degradation depended on ERAD-associated ubiquitin ligases and was regulated by sterol synthesis. These data expand the cohort of lipid biosynthetic enzymes targeted for ERAD, highlight the role of the UPS in maintaining ER function, and provide a novel tool to uncover other UPS substrates via manipulations of our engineered strain.

CD4+ T cell responses are crucial for inducing and maintaining effective anti-cancer immunity, and the identification of human leukocyte antigen class II (HLA-II) cancer-specific epitopes is key to the development of potent cancer immunotherapies. In many tumor types, and especially in glioblastoma (GBM), HLA-II complexes are hardly ever naturally expressed. Hence, little is known about immunogenic HLA-II epitopes in GBM. With stable expression of the class II major histocompatibility complex transactivator (CIITA) coupled to a detailed and sensitive mass spectrometry based immunopeptidomics analysis, we here uncovered a remarkable breadth of the HLA-ligandome in HROG02, HROG17 and RA GBM cell lines. The effect of CIITA expression on the induction of the HLA-II presentation machinery was striking in each of the three cell lines, and it was significantly higher compared to interferon gamma (IFN) treatment. In total, we identified 16,123 unique HLA-I peptides and 32,690 unique HLA-II peptides. In order to genuinely define the identified peptides as true HLA ligands, we carefully characterized their association with the different HLA allotypes. In addition, we identified 138 and 279 HLA-I and HLA-II ligands, respectively, most of which are novel in GBM, derived from known GBM-associated tumor-antigens that have been used as source proteins for a variety of GBM vaccines. Our data further indicate that CIITA-expressing GBM cells acquired an antigen presenting cell-like phenotype as we found that they directly present external proteins as HLA-II ligands. Not only that CIITA-expressing GBM cells are attractive models for antigen discovery endeavors, but also such engineered cells have great therapeutic potential through massive presentation of a diverse antigenic repertoire.

The choice for adjuvant chemotherapy in stage II colorectal cancer (CRC) is controversial as many patients are cured by surgery alone and it is difficult to identify patients with high-risk of recurrence of the disease. There is a need for better stratification of this group of patients. Mass spectrometry imaging could identify patients at risk. We report here the N-glycosylation signatures of the different cell populations in a group of stage II CRC tissue samples. The cancer cells, compared to normal epithelial cells, have increased levels of sialylation and high-mannose glycans, as well as decreased levels of fucosylation and highly branched N-glycans. When looking at the interface between cancer and its microenvironment, it seems that the cancer N-glycosylation signature spreads into the surrounding stroma at the invasive front of the tumor. This finding was more outspoken in patients with a worse outcome within this sample group.

The complexity and dynamics of the immensely heterogeneous glycoproteome of the prostate cancer (PCa) tumour micro-environment remain incompletely mapped, a knowledge gap that impedes our molecular-level understanding of the disease. To this end, we have used sensitive glycomics and glycoproteomics to map the protein-, cell- and tumour grade-specific N- and O-glycosylation in surgically-removed PCa tissues spanning five histological grades (n = 10/grade) and tissues from patients with benign prostatic hyperplasia (n = 5). Quantitative glycomics revealed PCa grade-specific alterations of the oligomannosidic-, paucimannosidic- and branched sialylated complex-type N-glycans, and dynamic remodelling of the sialylated core 1- and core 2-type O-glycome. Deep quantitative glycoproteomics identified ~7,400 unique N-glycopeptides from 500 N-glycoproteins and ~500 unique O-glycopeptides from nearly 200 O-glycoproteins. With reference to a recent Tissue and Blood Atlas, our data indicate that paucimannosidic glycans of the PCa tissues arise mainly from immune cell-derived glycoproteins. Further, the grade-specific PCa glycosylation arises primarily from dynamics in the cellular makeup of the PCa tumour microenvironment across grades involving increased oligomannosylation of prostate-derived glycoproteins and decreased bisecting GlcNAcylation of N-glycans carried by the extracellular matrix proteins. Further, elevated expression of several oligosaccharyltransferase subunits and enhanced N-glycoprotein site occupancy were observed associated with PCa progression. Finally, correlations between the protein-specific glycosylation and PCa progression were observed including increased site-specific core 2-type O-glycosylation of collagen VI. In conclusion, integrated glycomics and glycoproteomics have enabled new insight into the complexity and dynamics of the tissue glycoproteome associated with PCa progression generating an important resource to explore the underpinning disease mechanisms.

Protease activity has been associated with pathological processes that can lead to cancer development and progression. However, understanding the pathological unbalance in proteolysis is challenging since changes can occur simultaneously at protease, their inhibitor and substrate levels. Here, we present a pipeline that combines peptidomics, proteomics and peptidase predictions for studying proteolytic events in the saliva of seventy-nine patients and their association with oral squamous cell carcinoma (OSCC) prognosis. Our findings revealed differences in the saliva peptidome of patients with (pN+) or without (pN0) lymph node metastasis and delivered a panel of ten endogenous peptides correlated with poor prognostic factors plus five molecules able to classify pN0 and pN+ patients (ROC-AUC>0.85). In addition, endo- and exopeptidases putatively implicated in the processing of differential peptides were investigated using cancer tissue gene expression data from publicly repositories reinforcing their association with poorer survival rates and prognosis in oral cancer. The dynamics of the OSCC-related proteolysis was further explored via the proteomic profiling of saliva. This revealed that peptidase/endopeptidase inhibitors exhibited reduced levels in the saliva of pN+ patients, as confirmed by SRM-MS, whilst minor changes were detected in the level of saliva proteases. Taken together, our results indicated that proteolytic activity is accentuated in the saliva of OSCC patients with lymph node metastasis and, at least in part, this is modulated by reduced levels of salivary peptidase inhibitors. Therefore, this integrated pipeline provided better comprehension and discovery of molecular features with implications in the oral cancer metastasis prognosis.

Hirschsprung disease (HSCR) is a heterogeneous group of neurocristopathy characterized by the absence of the enteric ganglia along a variable length of the intestine. Genetic defects play a major role in the pathogenesis of HSCR while family studies of pathogenic variants in all the known genes (loci) only demonstrate incomplete penetrance and variable expressivity for unknown reasons. Here, we applied large-scale, quantitative proteomics of human colon tissues from 21 patients using iTRAQ method followed by bioinformatics analysis. Selected findings were confirmed by parallel reaction monitoring (PRM) verification. At last the interesting differentially expressed proteins were confirmed by western blot. A total of 5341 proteins in human colon tissues were identified. Among them, 664 proteins with >1.2-fold difference were identified in 6 groups: groups A1 and A2 pooled protein from the ganglionic and aganglionic colon of male, long-segment HSCR patients (L-HSCR, n=7); groups B1 and B2 pooled protein from the ganglionic and aganglionic colon of male, short-segment HSCR patients (S-HSCR, n=7); and groups C1 and C2 pooled protein from the ganglionic and aganglionic colon of female, S-HSCR patients (n=7). Based on these analyses, 49 proteins from 5 pathways were selected for PRM verification, including ribosome, endocytosis, spliceosome, oxidative phosphorylation and cell adhesion. The downregulation of three neuron projection development genes ARF4, KIF5B and RAB8A in the aganglionic part of the colon were verified in 15 paired colon samples using WB. The findings of this study will shed new light on the pathogenesis of HSCR and facilitate the development of therapeutic targets.

Thyroglobulin (Tg) is a secreted iodoglycoprotein serving as the precursor for T3 and T4 hormones. Many characterized Tg gene mutations produce secretion-defective variants resulting in congenital hypothyroidism (CH). Tg processing and secretion is controlled by extensive interactions with chaperone, trafficking, and degradation factors comprising the secretory proteostasis network. While dependencies on individual proteostasis network components are known, the integration of proteostasis pathways mediating Tg protein quality control and the molecular basis of mutant Tg misprocessing remain poorly understood. We employ a multiplexed quantitative affinity purification–mass spectrometry approach to define the Tg proteostasis interactome and changes between WT and several CH-variants. Mutant Tg processing is associated with common imbalances in proteostasis engagement including increased chaperoning, oxidative folding, and engagement by targeting factors for ER-associated degradation (ERAD). Furthermore, we reveal mutation-specific changes in engagement with N-glycosylation components, suggesting distinct requirements for one Tg variant on dual engagement of both oligosaccharyltransferase complex isoforms for degradation. Modulating dysregulated proteostasis components and pathways may serve as a therapeutic strategy to restore Tg secretion and thyroid hormone biosynthesis.

The Rhizobium-legume symbiosis is a beneficial interaction in which the bacterium converts atmospheric nitrogen into ammonia and delivers it to the plant in exchange for carbon compounds. This symbiosis implies the adaptation of bacteria to live inside host plant cells. In this work we apply RP-LC-MS/MS and  iTRAQ techniques to study the proteomic profile of endosymbiotic cells (bacteroids) induced by Rhizobium leguminosarum bv viciae strain UPM791 in legume nodules. Nitrogenase subunits, tricarboxylic acid cycle enzymes, and stress response proteins are amongst the most abundant from over one thousand rhizobial proteins identified in pea (Pisum sativum) bacteroids. Comparative analysis of bacteroids induced in pea and in lentil (Lens culinaris)nodules revealed the existence of a significant host-specific differential response affecting dozens of bacterial proteins, including stress-related proteins, transcriptional regulators, and proteins involved in the carbon and nitrogen metabolisms. A mutant affected in one of these proteins, homologous to a GntR-like transcriptional regulator, showed a symbiotic performance significantly  impaired in symbiosis with pea, but not with lentil plants. Analysis of the proteomes of bacteroids isolated from both hosts also revealed the presence of different sets of plant-derived nodule-specific cysteine rich (NCR) peptides, indicating that the endosymbiotic bacteria find a host-specific cocktail of chemical stressors inside the nodule. By studying variations of the bacterial response to different plant cell environments we will be able to identify specific limitations imposed by the host that might give us clues for the improvement of rhizobial performance.

The Role of Sub-state and Non-state Actors in International Climate Processes: Financial Institutions Research paper sysadmin 20 December 2018

The trillions of dollars needed to secure the sustainable, climate-compatible pathway outlined in the 2015 Paris Agreement have focused attention on private finance and investment.

This is one of four background papers feeding into a synthesis paper entitled The Role of Sub-state and Non-state Actors in International Climate Processes.

Summary

• The trillions of dollars needed to secure the sustainable, climate-compatible pathway outlined in the 2015 Paris Agreement have focused attention on private finance and investment, and on the role of the financial sector as a potentially powerful non-state actor in the international climate debate.
• Leading individual financial institutions reacted to the Paris Agreement by framing it in terms of what it would mean for markets – i.e. risks and opportunities – and by underlining the importance of national implementation of climate change commitments.
• Key recent developments signal that the financial sector actively supports Paris-compatible government action on climate change, as well as company-level action to understand the physical and ‘transition’ risks and opportunities associated with climate change and policy responses. Financial sector engagement is taking place through well-organized and well-supported international initiatives and platforms. A critical part of this process entails robust activity by financial institutions to embed climate change and broader sustainability factors into strategies and operations.
• At country level, attention to implementation of Nationally Determined Contributions (NDCs) and associated sector-level policy development has been largely separate from the broader ‘sustainable finance’ dynamic. National-level action has not benefited from the same level of organized financial sector involvement evident in international action. One of the reasons for this is that, with some notable exceptions, international financial initiatives lack the capacity and resources to participate in the granular detail of national policy processes. Policymakers in turn often lack the internal capacity to consult or engage with the financial sector domestically.
• This paper includes some thoughts on further international and national climate actions. Ensuring that messages from successful international financial sector initiatives are heard in regional and non-climate forums offers one avenue for building a stronger foundation for greater climate ambition. Building the resource base for stronger national climate policy engagement, as a counter-voice to incumbent interests and to ensure that the quality of policy is ‘investment grade’, is another. This will be critical to the delivery of policy outcomes. Other key elements include the need to pool knowledge across relevant parts of the finance sector, build alliances, and shift action towards joint problem-solving with policymakers. A ‘Talanoa 2.020’-type initiative offers one potentially promising approach to advancing dialogue in this respect.

Artificial Intelligence Prediction and Counterterrorism Research paper sysadmin 6 August 2019

The use of AI in counterterrorism is not inherently wrong, and this paper suggests some necessary conditions for legitimate use of AI as part of a predictive approach to counterterrorism on the part of liberal democratic states.

Summary

• The use of predictive artificial intelligence (AI) in countering terrorism is often assumed to have a deleterious effect on human rights, generating spectres of ‘pre-crime’ punishment and surveillance states. However, the well-regulated use of new capabilities may enhance states’ abilities to protect citizens’ right to life, while at the same time improving adherence to principles intended to protect other human rights, such as transparency, proportionality and freedom from unfair discrimination. The same regulatory framework could also contribute to safeguarding against broader misuse of related technologies.
• Most states focus on preventing terrorist attacks, rather than reacting to them. As such, prediction is already central to effective counterterrorism. AI allows higher volumes of data to be analysed, and may perceive patterns in those data that would, for reasons of both volume and dimensionality, otherwise be beyond the capacity of human interpretation. The impact of this is that traditional methods of investigation that work outwards from known suspects may be supplemented by methods that analyse the activity of a broad section of an entire population to identify previously unknown threats.
• Developments in AI have amplified the ability to conduct surveillance without being constrained by resources. Facial recognition technology, for instance, may enable the complete automation of surveillance using CCTV in public places in the near future.
• The current way predictive AI capabilities are used presents a number of interrelated problems from both a human rights and a practical perspective. Where limitations and regulations do exist, they may have the effect of curtailing the utility of approaches that apply AI, while not necessarily safeguarding human rights to an adequate extent.
• The infringement of privacy associated with the automated analysis of certain types of public data is not wrong in principle, but the analysis must be conducted within a robust legal and policy framework that places sensible limitations on interventions based on its results.
• In future, broader access to less intrusive aspects of public data, direct regulation of how those data are used – including oversight of activities by private-sector actors – and the imposition of technical as well as regulatory safeguards may improve both operational performance and compliance with human rights legislation. It is important that any such measures proceed in a manner that is sensitive to the impact on other rights such as freedom of expression, and freedom of association and assembly.

Diagnosing social behavioural dynamics of corruption Other resource dora.popova 8 December 2021

This interactive toolkit identifies the types of social expectations which sustain selected corrupt practices and provides behaviourally-informed recommendations for changing them.

When tackling a problem as complex as corruption, it is important to understand why and how people behave in different situations where corruption occurs. In contexts where it is easier to engage in corruption than avoid it, identifying the social expectations and informal rules which sustain corrupt practices can advance corruption prevention and deepen collective action.  

Behavioural approaches to corruption offer a better understanding of diverse social settings, group dynamics, power distribution, social motivations, and expectations that contribute to a more tolerant environment for certain forms of the phenomenon. They are also highly complementary to traditional corruption measures, which tend to focus on the enforcement of legal sanctions and deterrents. Behavioural approaches, especially those inspired by social norms theory, highlight complex social characteristics and informal rules of specific corrupt practices, and effectively support implementation of more dynamic context-specific anti-corruption interventions.

Since 2016, the Chatham House Africa programme’s Social Norms and Accountable Governance (SNAG) project has adopted a behavioural approach based on social norms methodology to investigate the social beliefs which motivate different forms of corruption. Drawing on the project’s extensive evidence-gathering and analysis, this toolkit offers users navigable behavioural mapping of contextual factors, beliefs, and expectations surrounding common corrupt practices. 

It aims to support anti-corruption actors in diagnosing informal rules and social expectations which sustain corruption in some societies. It also proposes behavioural-informed guidance for developing or adapting anti-corruption interventions and activities, so they account for informal rules of behaviour such as social norms. 
 
The toolkit supports users to:

• Identify whether and how widespread corrupt practices are motivated by social beliefs and expectations.

• Understand how society influences the types of corrupt activity individuals engage in, or avoid, and the factors informing these choices

• Integrate empirical evidence and behavioural insights into anti-corruption strategies from diagnostics to design, and eventual implementation and evaluation

The toolkit presents evidence from SNAG’s research into three key corrupt practices – bribery, embezzlement, and electoral fraud. Each was examined in the context of typical situations in which they occur, such as law enforcement, healthcare, the power sector, voting, and education while critical factors such as religion, gender, and ethnicity were considered. 

The toolkit presents an overview of specific contexts and behavioural features of the practices and provides behavioural-informed recommendations. It also contains pop-up features with definitions and explanations of key concepts. The toolkit is designed to be expandable, allowing further content and behavioural dynamics to be added.