Age and urban-rural disparities in cutaneous melanoma mortality rates in the United States during the COVID-19 pandemic.

Most recent studies on the coronavirus disease 2019 (COVID-19) pandemic and cutaneous melanoma (CM) focused more on delayed diagnosis or advanced presentation. We aimed to ascertain mortality trends of CM between 2012 and 2022, focusing on the effects of the COVID-19 pandemic. In this serial population-based study, the National Vital Statistics System dataset was queried for mortality data. Excess CM-related mortality rates were estimated by calculating the difference between observed and projected mortality rates during the pandemic. Totally there were 108,853 CM-associated deaths in 2012-2022. CM-associated mortality saw a declining trend from 2012 to 2019 overall. However, it increased sharply in 2020 (ASMR 3.73 per 100,000 persons, 5.95% excess mortality), and remained high in 2021 and 2022, with the ASMRs of 3.82 and 3.81, corresponding to 11.17% and 13.20% excess mortality, respectively. The nonmetro areas had the most pronounced rise in mortality with 12.20% excess death in 2020, 15.33% in 2021 and 20.52% in 2022, corresponding to a 4-6 times excess mortality risk compared to large metro areas during the pandemic. The elderly had the most pronounced rise in mortality, but the mortality in the younger population was reduced.

The DHX9 helicase interacts with human DNA polymerase δ4 and stimulates its activity in D-loop extension synthesis.

The extension of the invading strand within a displacement loop (D-loop) is a key step in homology directed repair (HDR) of doubled stranded DNA breaks. The primary goal of these studies was to test the hypotheses that 1) D-loop extension by human DNA polymerase δ4 (Pol δ4) is facilitated by DHX9, a 3' to 5' motor helicase, which acts to unwind the leading edge of the D-loop, and 2) the recruitment of DHX9 is mediated by direct protein-protein interactions between DHX9 and Pol δ4 and/or PCNA. DNA synthesis by Pol δ4 was analyzed in a reconstitution assay by the extension of a 93mer oligonucleotide inserted into a plasmid to form a D-loop. Product formation by Pol δ4 was monitored by incorporation of [α-32P]dNTPs into the 93mer primer followed by denaturing gel electrophoresis. The results showed that DHX9 strongly stimulated Pol δ4 mediated D-loop extension. Direct interactions of DHX9 with PCNA, the p125 and the p12 subunits of Pol δ4 were demonstrated by pull-down assays with purified proteins. These data support the hypothesis that DHX9 helicase is recruited by Pol δ4/PCNA to facilitate D-loop synthesis in HDR, and is a participant in cellular HDR. The involvement of DHX9 in HDR represents an important addition to its multiple cellular roles. Such helicase-polymerase interactions may represent an important aspect of the mechanisms involved in D-loop primer extension synthesis in HDR.

Excess psoriasis and psoriatic arthritis mortality during the COVID-19 pandemic in the United States: A nationwide population-based study from 2010 to 2021.

BACKGROUND: Little is known about mortality trends among patients with psoriasis (PsO) and psoriatic arthritis (PsA) in the United States. OBJECTIVES: To ascertain mortality trends of PsO and PsA between 2010 and 2021, focusing on the effects of the COVID-19 pandemic. METHODS: We collected data from the National Vital Statistic System and calculated age-standardized mortality rates (ASMR) and cause-specific mortality for PsO/PsA. We evaluated observed versus predicted mortality for 2020-2021 based on trends from 2010 to 2019 with joinpoint and prediction modelling analysis. RESULTS: Among 5810 and 2150 PsO- and PsA-related deaths between 2010 and 2021, ASMR for PsO dramatically increased between 2010-2019 and 2020-2021 (annual percentage change [APC] 2.07% vs. 15.26%; p < 0.01), leading to a higher observed ASMR (per 100,000 persons) than predicted for 2020 (0.27 vs. 0.22) and 2021 (0.31 vs. 0.23). The excess mortality of PsO was 22.7% and 34.8% higher than that in the general population in 2020 (16.4%, 95% CI: 14.9%-17.9%) and 2021 (19.8%, 95% CI: 18.0%-21.6%) respectively. Notably, the ASMR rise for PsO was most pronounced in the female (APC: 26.86% vs. 12.19% in males) and the middle-aged group (APC: 17.67% vs. 12.47% in the old-age group). ASMR, APC and excess mortality for PsA were similar to PsO. SARS-CoV-2 infection contributed to more than 60% of the excess mortality for PsO and PsA. CONCLUSIONS: Individuals living with PsO and PsA were disproportionately affected during the COVID-19 pandemic. Both ASMRs increased at an alarming rate, with the most pronounced disparities among the female and middle-aged groups.

Standing electric scooter injuries: Impact on a community.

BACKGROUND: This study investigates the impact of standing electric scooter-related injuries within an entire integrated hospital system. METHODS: We performed a retrospective review of patients involved in standing electric scooter incidents presenting throughout an urban hospital network over a 10 month period. Rates of Google searches of scooter-related terms performed locally were used as a surrogate for ride frequency. Injury, mechanism, and cost data were analyzed. RESULTS: Data on 248 patients were reviewed. Twenty-three (9%) were under 18 years old. Loss of balance was the most common cause of injury accounting for nearly half, while tripping over a scooter 14 (6%) affected the elderly disproportionately. Eight (3%) riders wore helmets. All TBI and closed head injuries occurred in unhelmeted patients. Most incidents occurred in the street, only one in a bicycle lane. Facilities costs were greater for patients under the influence of alcohol and marijuana. CONCLUSION: Policies related to the use of mandated safety equipment, dedicated bicycle lanes, and the proper storage of empty vehicles should be further investigated.

PACAP is a pathogen-inducible resident antimicrobial neuropeptide affording rapid and contextual molecular host defense of the brain.

Defense of the central nervous system (CNS) against infection must be accomplished without generation of potentially injurious immune cell-mediated or off-target inflammation which could impair key functions. As the CNS is an immune-privileged compartment, inducible innate defense mechanisms endogenous to the CNS likely play an essential role in this regard. Pituitary adenylate cyclase-activating polypeptide (PACAP) is a neuropeptide known to regulate neurodevelopment, emotion, and certain stress responses. While PACAP is known to interact with the immune system, its significance in direct defense of brain or other tissues is not established. Here, we show that our machine-learning classifier can screen for immune activity in neuropeptides, and correctly identified PACAP as an antimicrobial neuropeptide in agreement with previous experimental work. Furthermore, synchrotron X-ray scattering, antimicrobial assays, and mechanistic fingerprinting provided precise insights into how PACAP exerts antimicrobial activities vs. pathogens via multiple and synergistic mechanisms, including dysregulation of membrane integrity and energetics and activation of cell death pathways. Importantly, resident PACAP is selectively induced up to 50-fold in the brain in mouse models of Staphylococcus aureus or Candida albicans infection in vivo, without inducing immune cell infiltration. We show differential PACAP induction even in various tissues outside the CNS, and how these observed patterns of induction are consistent with the antimicrobial efficacy of PACAP measured in conditions simulating specific physiologic contexts of those tissues. Phylogenetic analysis of PACAP revealed close conservation of predicted antimicrobial properties spanning primitive invertebrates to modern mammals. Together, these findings substantiate our hypothesis that PACAP is an ancient neuro-endocrine-immune effector that defends the CNS against infection while minimizing potentially injurious neuroinflammation.

Discovery of Novel Type II Bacteriocins Using a New High-Dimensional Bioinformatic Algorithm.

Antimicrobial compounds first arose in prokaryotes by necessity for competitive self-defense. In this light, prokaryotes invented the first host defense peptides. Among the most well-characterized of these peptides are class II bacteriocins, ribosomally-synthesized polypeptides produced chiefly by Gram-positive bacteria. In the current study, a tensor search protocol-the BACIIα algorithm-was created to identify and classify bacteriocin sequences with high fidelity. The BACIIα algorithm integrates a consensus signature sequence, physicochemical and genomic pattern elements within a high-dimensional query tool to select for bacteriocin-like peptides. It accurately retrieved and distinguished virtually all families of known class II bacteriocins, with an 86% specificity. Further, the algorithm retrieved a large set of unforeseen, putative bacteriocin peptide sequences. A recently-developed machine-learning classifier predicted the vast majority of retrieved sequences to induce negative Gaussian curvature in target membranes, a hallmark of antimicrobial activity. Prototypic bacteriocin candidate sequences were synthesized and demonstrated potent antimicrobial efficacy in vitro against a broad spectrum of human pathogens. Therefore, the BACIIα algorithm expands the scope of prokaryotic host defense bacteriocins and enables an innovative bioinformatics discovery strategy. Understanding how prokaryotes have protected themselves against microbial threats over eons of time holds promise to discover novel anti-infective strategies to meet the challenge of modern antibiotic resistance.

Improved prediction of HIT in the SICU using an improved model of the Warkentin 4-T system: 3-T.

BACKGROUND: The Warkentin 4-T scoring system for determining the pretest probability of heparin-induced thrombocytopenia (HIT) has been shown to be inaccurate in the ICU and does not take into account body mass index (BMI). METHODS: Prospectively collected data on patients in the surgical and cardiac ICU between January 2007 and February 2016 who were presumed to have HIT by clinical suspicion were reviewed. Patients were categorized into 3 BMI groups and assigned scores: Normal weight, overweight, and obese. Multivariate analyses were used to identify independent predictors of HIT. RESULTS: A total of 523 patients met inclusion criteria. Multivariate analysis showed that only BMI, Timing, and oTher variables were independently associated with HIT. This new 3-T model was better than a five-component model consisting of the entire 4-T scoring system plus BMI (AUC = 0.791). CONCLUSIONS: Incorporating patient 'T'hickness into a pretest probability model along with platelet 'T'iming and the exclusion of o'T'her causes of thrombocytopenia yields a simplified "3-T" scoring system that has increased predictive accuracy in the ICU.

Circulating biomarkers predictive of tumor response to cancer immunotherapy.

Introduction: The advent of checkpoint blockade immunotherapy has revolutionized cancer treatment, but clinical response to immunotherapies is highly heterogeneous among individual patients and between cancer types. This represents a challenge to oncologists when choosing specific immunotherapies for personalized medicine. Thus, biomarkers that can predict tumor responsiveness to immunotherapies before and during treatment are invaluable. Areas covered: We review the latest advances in 'liquid biopsy' biomarkers for noninvasive prediction and in-treatment monitoring of tumor response to immunotherapy, focusing primarily on melanoma and non-small cell lung cancer. We concentrate on high-quality studies published within the last five years on checkpoint blockade immunotherapies, and highlight significant breakthroughs, identify key areas for improvement, and provide recommendations for how these diagnostic tools can be translated into clinical practice. Expert opinion: The first biomarkers proposed to predict tumor response to immunotherapy were based on PD1/PDL1 expression, but their predictive value is limited to specific cancers or patient populations. Recent advances in single-cell molecular profiling of circulating tumor cells and host cells using next-generation sequencing has dramatically expanded the pool of potentially useful predictive biomarkers. As immunotherapy moves toward personalized medicine, a composite panel of both genomic and proteomic biomarkers will have enormous utility in therapeutic decision-making.

CXCL4 assembles DNA into liquid crystalline complexes to amplify TLR9-mediated interferon-α production in systemic sclerosis.

Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by fibrosis and vasculopathy. CXCL4 represents an early serum biomarker of severe SSc and likely contributes to inflammation via chemokine signaling pathways, but the exact role of CXCL4 in SSc pathogenesis is unclear. Here, we elucidate an unanticipated mechanism for CXCL4-mediated immune amplification in SSc, in which CXCL4 organizes "self" and microbial DNA into liquid crystalline immune complexes that amplify TLR9-mediated plasmacytoid dendritic cell (pDC)-hyperactivation and interferon-α production. Surprisingly, this activity does not require CXCR3, the CXCL4 receptor. Importantly, we find that CXCL4-DNA complexes are present in vivo and correlate with type I interferon (IFN-I) in SSc blood, and that CXCL4-positive skin pDCs coexpress IFN-I-related genes. Thus, we establish a direct link between CXCL4 overexpression and the IFN-I-gene signature in SSc and outline a paradigm in which chemokines can drastically modulate innate immune receptors without being direct agonists.

Unifying structural signature of eukaryotic α-helical host defense peptides.

Diversity of α-helical host defense peptides (αHDPs) contributes to immunity against a broad spectrum of pathogens via multiple functions. Thus, resolving common structure-function relationships among αHDPs is inherently difficult, even for artificial-intelligence-based methods that seek multifactorial trends rather than foundational principles. Here, bioinformatic and pattern recognition methods were applied to identify a unifying signature of eukaryotic αHDPs derived from amino acid sequence, biochemical, and three-dimensional properties of known αHDPs. The signature formula contains a helical domain of 12 residues with a mean hydrophobic moment of 0.50 and favoring aliphatic over aromatic hydrophobes in 18-aa windows of peptides or proteins matching its semantic definition. The holistic α-core signature subsumes existing physicochemical properties of αHDPs, and converged strongly with predictions of an independent machine-learning-based classifier recognizing sequences inducing negative Gaussian curvature in target membranes. Queries using the α-core formula identified 93% of all annotated αHDPs in proteomic databases and retrieved all major αHDP families. Synthesis and antimicrobial assays confirmed efficacies of predicted sequences having no previously known antimicrobial activity. The unifying α-core signature establishes a foundational framework for discovering and understanding αHDPs encompassing diverse structural and mechanistic variations, and affords possibilities for deterministic design of antiinfectives.

Helical antimicrobial peptides assemble into protofibril scaffolds that present ordered dsDNA to TLR9.

Amphiphilicity in ɑ-helical antimicrobial peptides (AMPs) is recognized as a signature of potential membrane activity. Some AMPs are also strongly immunomodulatory: LL37-DNA complexes potently amplify Toll-like receptor 9 (TLR9) activation in immune cells and exacerbate autoimmune diseases. The rules governing this proinflammatory activity of AMPs are unknown. Here we examine the supramolecular structures formed between DNA and three prototypical AMPs using small angle X-ray scattering and molecular modeling. We correlate these structures to their ability to activate TLR9 and show that a key criterion is the AMP's ability to assemble into superhelical protofibril scaffolds. These structures enforce spatially-periodic DNA organization in nanocrystalline immunocomplexes that trigger strong recognition by TLR9, which is conventionally known to bind single DNA ligands. We demonstrate that we can "knock in" this ability for TLR9 amplification in membrane-active AMP mutants, which suggests the existence of tradeoffs between membrane permeating activity and immunomodulatory activity in AMP sequences.

Loss of the p12 subunit of DNA polymerase delta leads to a defect in HR and sensitization to PARP inhibitors.

Human DNA polymerase δ is normally present in unstressed, non-dividing cells as a heterotetramer (Pol δ4). Its smallest subunit, p12, is transiently degraded in response to UV damage, as well as during the entry into S-phase, resulting in the conversion of Pol δ4 to a trimer (Pol δ3). In order to further understand the specific cellular roles of these two forms of Pol δ, the gene (POLD4) encoding p12 was disrupted by CRISPR/Cas9 to produce p12 knockout (p12KO) cells. Thus, Pol δ4 is absent in p12KO cells, leaving Pol δ3 as the sole source of Pol δ activity. GFP reporter assays revealed that the p12KO cells exhibited a defect in homologous recombination (HR) repair, indicating that Pol δ4, but not Pol δ3, is required for HR. Expression of Flag-tagged p12 in p12KO cells to restore Pol δ4 alleviated the HR defect. These results establish a specific requirement for Pol δ4 in HR repair. This leads to the prediction that p12KO cells should be more sensitive to chemotherapeutic agents, and should exhibit synthetic lethal killing by PARP inhibitors. These predictions were confirmed by clonogenic cell survival assays of p12KO cells treated with cisplatin and mitomycin C, and with the PARP inhibitors Olaparib, Talazoparib, Rucaparib, and Niraparib. The sensitivity to PARP inhibitors in H1299-p12KO cells was alleviated by expression of Flag-p12. These findings have clinical significance, as the expression levels of p12 could be a predictive biomarker of tumor response to PARP inhibitors. In addition, small cell lung cancers (SCLC) are known to exhibit a defect in p12 expression. Analysis of several SCLC cell lines showed that they exhibit hypersensitivity to PARP inhibitors, providing evidence that loss of p12 expression could represent a novel molecular basis for HR deficiency.

Discovery of a novel DNA polymerase inhibitor and characterization of its antiproliferative properties.

Chromosomal duplication is targeted by various chemotherapeutic agents for the treatment of cancer. However, there is no specific inhibitor of DNA polymerases that is viable for cancer management. Through structure-based in silico screening of the ZINC database, we identified a specific inhibitor of DNA polymerase δ. The discovered inhibitor, Zelpolib, is projected to bind to the active site of Pol δ when it is actively engaged in DNA replication through interactions with DNA template and primer. Zelpolib shows robust inhibition of Pol δ activity in reconstituted DNA replication assays. Under cellular conditions, Zelpolib is taken up readily by cancer cells and inhibits DNA replication in assays to assess global DNA synthesis or single-molecule bases by DNA fiber fluorography. In addition, we show that Zelpolib displays superior antiproliferative properties to methotrexate, 5-flourouracil, and cisplatin in triple-negative breast cancer cell line, pancreatic cancer cell line and platinum-resistant pancreatic cancer cell line. Pol δ is not only involved in DNA replication, it is also a key component in many DNA repair pathways. Pol δ is the key enzyme responsible for D-loop extension during homologous recombination. Indeed, Zelpolib shows robust inhibition of homologous recombination repair of DNA double-strand breaks and induces "BRCAness" in HR-proficient cancer cells and enhances their sensitivity to PARP inhibitors.

Phosphorylation Alters the Properties of Pol η: Implications for Translesion Synthesis.

There are significant ambiguities regarding how DNA polymerase η is recruited to DNA lesion sites in stressed cells while avoiding normal replication forks in non-stressed cells. Even less is known about the mechanisms responsible for Pol η-induced mutations in cancer genomes. We show that there are two safeguards to prevent Pol η from adventitious participation in normal DNA replication. These include sequestration by a partner protein and low basal activity. Upon cellular UV irradiation, phosphorylation enables Pol η to be released from sequestration by PDIP38 and activates its polymerase function through increased affinity toward monoubiquitinated proliferating cell nuclear antigen (Ub-PCNA). Moreover, the high-affinity binding of phosphorylated Pol η to Ub-PCNA limits its subsequent displacement by Pol δ. Consequently, activated Pol η replicates DNA beyond the lesion site and potentially introduces clusters of mutations due to its low fidelity. This mechanism could account for the prevalence of Pol η signatures in cancer genome.

Multigenerational memory and adaptive adhesion in early bacterial biofilm communities.

Using multigenerational, single-cell tracking we explore the earliest events of biofilm formation by Pseudomonas aeruginosa During initial stages of surface engagement (≤20 h), the surface cell population of this microbe comprises overwhelmingly cells that attach poorly (∼95% stay <30 s, well below the ∼1-h division time) with little increase in surface population. If we harvest cells previously exposed to a surface and direct them to a virgin surface, we find that these surface-exposed cells and their descendants attach strongly and then rapidly increase the surface cell population. This "adaptive," time-delayed adhesion requires determinants we showed previously are critical for surface sensing: type IV pili (TFP) and cAMP signaling via the Pil-Chp-TFP system. We show that these surface-adapted cells exhibit damped, coupled out-of-phase oscillations of intracellular cAMP levels and associated TFP activity that persist for multiple generations, whereas surface-naïve cells show uncorrelated cAMP and TFP activity. These correlated cAMP-TFP oscillations, which effectively impart intergenerational memory to cells in a lineage, can be understood in terms of a Turing stochastic model based on the Pil-Chp-TFP framework. Importantly, these cAMP-TFP oscillations create a state characterized by a suppression of TFP motility coordinated across entire lineages and lead to a drastic increase in the number of surface-associated cells with near-zero translational motion. The appearance of this surface-adapted state, which can serve to define the historical classification of "irreversibly attached" cells, correlates with family tree architectures that facilitate exponential increases in surface cell populations necessary for biofilm formation.

Machine learning-enabled discovery and design of membrane-active peptides.

Antimicrobial peptides are a class of membrane-active peptides that form a critical component of innate host immunity and possess a diversity of sequence and structure. Machine learning approaches have been profitably employed to efficiently screen sequence space and guide experiment towards promising candidates with high putative activity. In this mini-review, we provide an introduction to antimicrobial peptides and summarize recent advances in machine learning-enabled antimicrobial peptide discovery and design with a focus on a recent work Lee et al. Proc. Natl. Acad. Sci. USA 2016;113(48):13588-13593. This study reports the development of a support vector machine classifier to aid in the design of membrane active peptides. We use this model to discover membrane activity as a multiplexed function in diverse peptide families and provide interpretable understanding of the physicochemical properties and mechanisms governing membrane activity. Experimental validation of the classifier reveals it to have learned membrane activity as a unifying signature of antimicrobial peptides with diverse modes of action. Some of the discriminating rules by which it performs classification are in line with existing "human learned" understanding, but it also unveils new previously unknown determinants and multidimensional couplings governing membrane activity. Integrating machine learning with targeted experimentation can guide both antimicrobial peptide discovery and design and new understanding of the properties and mechanisms underpinning their modes of action.

Bacterial amyloid curli acts as a carrier for DNA to elicit an autoimmune response via TLR2 and TLR9.

Bacterial biofilms are associated with numerous human infections. The predominant protein expressed in enteric biofilms is the amyloid curli, which forms highly immunogenic complexes with DNA. Infection with curli-expressing bacteria or systemic exposure to purified curli-DNA complexes triggers autoimmunity via the generation of type I interferons (IFNs) and anti-double-stranded DNA antibodies. Here, we show that DNA complexed with amyloid curli powerfully stimulates Toll-like receptor 9 (TLR9) through a two-step mechanism. First, the cross beta-sheet structure of curli is bound by cell-surface Toll-like receptor 2 (TLR2), enabling internalization of the complex into endosomes. After internalization, the curli-DNA immune complex binds strongly to endosomal TLR9, inducing production of type I IFNs. Analysis of wild-type and TLR2-deficient macrophages showed that TLR2 is the major receptor that drives the internalization of curli-DNA complexes. Suppression of TLR2 internalization via endocytosis inhibitors led to a significant decrease in Ifnß expression. Confocal microscopy analysis confirmed that the TLR2-bound curli was required for shuttling of DNA to endosomal TLR9. Structural analysis using small-angle X-ray scattering revealed that incorporation of DNA into curli fibrils resulted in the formation of ordered curli-DNA immune complexes. Curli organizes parallel, double-stranded DNA rods at an inter-DNA spacing that matches up well with the steric size of TLR9. We also found that production of anti-double-stranded DNA autoantibodies in response to curli-DNA was attenuated in TLR2- and TLR9-deficient mice and in mice deficient in both TLR2 and TLR9 compared to wild-type mice, suggesting that both innate immune receptors are critical for shaping the autoimmune adaptive immune response. We also detected significantly lower levels of interferon-stimulated gene expression in response to purified curli-DNA in TLR2 and TLR9 deficient mice compared to wild-type mice, confirming that TLR2 and TLR9 are required for the induction of type I IFNs. Finally, we showed that curli-DNA complexes, but not cellulose, were responsible elicitation of the immune responses to bacterial biofilms. This study defines the series of events that lead to the severe pro-autoimmune effects of amyloid-expressing bacteria and suggest a mechanism by which amyloid curli acts as a carrier to break immune tolerance to DNA, leading to the activation of TLR9, production of type I IFNs, and subsequent production of autoantibodies.

Mapping membrane activity in undiscovered peptide sequence space using machine learning.

There are some ∼1,100 known antimicrobial peptides (AMPs), which permeabilize microbial membranes but have diverse sequences. Here, we develop a support vector machine (SVM)-based classifier to investigate ⍺-helical AMPs and the interrelated nature of their functional commonality and sequence homology. SVM is used to search the undiscovered peptide sequence space and identify Pareto-optimal candidates that simultaneously maximize the distance σ from the SVM hyperplane (thus maximize its "antimicrobialness") and its ⍺-helicity, but minimize mutational distance to known AMPs. By calibrating SVM machine learning results with killing assays and small-angle X-ray scattering (SAXS), we find that the SVM metric σ correlates not with a peptide's minimum inhibitory concentration (MIC), but rather its ability to generate negative Gaussian membrane curvature. This surprising result provides a topological basis for membrane activity common to AMPs. Moreover, we highlight an important distinction between the maximal recognizability of a sequence to a trained AMP classifier (its ability to generate membrane curvature) and its maximal antimicrobial efficacy. As mutational distances are increased from known AMPs, we find AMP-like sequences that are increasingly difficult for nature to discover via simple mutation. Using the sequence map as a discovery tool, we find a unexpectedly diverse taxonomy of sequences that are just as membrane-active as known AMPs, but with a broad range of primary functions distinct from AMP functions, including endogenous neuropeptides, viral fusion proteins, topogenic peptides, and amyloids. The SVM classifier is useful as a general detector of membrane activity in peptide sequences.