Nonspecific Signs and/or Symptoms of Cancer: A Retrospective, Observational Analysis from a Secondary Care, US Community Oncology Dataset.

To help determine the unmet need for improved diagnostic tools to evaluate patients with nonspecific signs and/or symptoms (NSSS) and suspicion of cancer, we examined patient characteristics, diagnostic journey, and cancer incidence of patients with NSSS within The US Oncology Network (The Network), a secondary care community oncology setting. This retrospective, observational cohort study included patients aged ≥40 years with ≥1 NSSS in their problem list at their first visit within The Network (the index date) between 1 January 2016 and 31 December 2020. Patients were followed longitudinally with electronic health record data for initial cancer diagnosis, new noncancer diagnosis, death, end of study observation period, or 12 months, whichever occurred first. Of 103,984 patients eligible for inclusion, 96,722 presented with only 1 NSSS at index date; 6537/103,984 (6.3%) were diagnosed with 1 primary cancer within 12 months after the index date; 3825/6537 (58.5%) with hematologic malignancy, and 2712/6537 (41.5%) with solid tumor. Among patients diagnosed with cancer (n = 6774), the median time to cancer diagnosis after their first visit within The Network was 5.13 weeks. This study provides a real-world perspective on cancer incidence in patients with NSSS referred to a secondary care setting and highlights the unmet need for improved diagnostic tools to improve cancer outcomes.

Limited function of road verges as habitat for species connecting plant-bee networks in remnant semi-natural grasslands.

Species-rich natural and semi-natural ecosystems are under threat owing to land use change. To conserve the biodiversity associated with these ecosystems, we must identify and target conservation efforts towards functionally important species and supporting habitats that create connections between remnant patches in the landscape. Here, we use a multi-layer network approach to identify species that connect a metanetwork of plant-bee interactions in remnant semi-natural grasslands which are biodiversity hotspots in European landscapes. We investigate how these landscape connecting species, and their interactions, persist in their proposed supporting habitat, road verges, across a landscape with high human impact. We identify 11 plant taxa and nine bee species that connect semi-natural grassland patches. We find the beta diversity of these connector species to be low across road verges, indicating a poor contribution of these habitats to the landscape-scale diversity in semi-natural grasslands. We also find a significant influence of the surrounding landscape on the beta diversity of connector species and their interactions with implications for landscape-scale management. Conservation actions targeted toward species with key functional roles as connectors of fragmented ecosystems can provide cost-effective management of the diversity and functioning of threatened ecosystems.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Should rTMS be considered a first-line treatment for major depressive episodes in adults?

Treatment-resistant depression (TRD) is an epidemic with rising social, economic, and political costs. In a patient whose major depressive episode (MDE) persists through an adequate antidepressant trial, insurance companies often cover alternative treatments which may include repetitive transcranial magnetic stimulation (rTMS). RTMS is an FDA-cleared neuromodulation technique for TRD which is safe, efficacious, noninvasive, and well-tolerated. Recent developments in the optimization of rTMS algorithms and targeting have increased the efficacy of rTMS in treating depression, improved the clinical convenience of these treatments, and decreased the cost of a course of rTMS. In this opinion paper, we make a case for why conventional FDA-cleared rTMS should be considered as a first-line treatment for all adult MDEs. RTMS is compared to other first-line treatments including psychotherapy and SSRIs. These observations suggest that rTMS has similar efficacy, fewer side-effects, lower risk of serious adverse events, comparable compliance, the potential for more rapid relief, and cost-effectiveness. This suggestion, however, would be strengthened by further research with an emphasis on treatment-naive subjects in their first depressive episode, and trials directly contrasting rTMS with SSRIs or psychotherapy.

Race as a Risk Marker, Not a Risk Factor: Revising Race-Based Algorithms to Protect Racially Oppressed Patients.

Emerging consensus in the medical and public health spheres encourages removing race and ethnicity from algorithms used in clinical decision-making. Although clinical algorithms remain appealing given their promise to lighten the cognitive load of medical practice and save time for providers, they risk exacerbating existing health disparities. Race is a strong risk marker of health outcomes, yet it is not a risk factor. The use of race as a factor in medical algorithms suggests that the effect of race is intrinsic to the patient or that its effects can be distinct or separated from other social and environmental variables. By contrast, incisive public health analysis coupled with a race-conscious perspective recognizes that race serves as a marker of countless other dynamic variables and that structural racism, rather than race, compromises the health of racially oppressed individuals. This perspective offers a historical and theoretical context for the current debates regarding the use of race in clinical algorithms, clinical and epidemiologic perspectives on "risk," and future directions for research and policy interventions that combat color-evasive racism and follow the principles of race-conscious medicine.

Chromosome-level genome assembly of the viviparous eelpout Zoarces viviparus.

The viviparous eelpout Zoarces viviparus is a common fish across the North-East Atlantic and has successfully colonized habitats across environmental gradients. Due to its wide distribution and predictable phenotypic responses to pollution, Z. viviparus is used as bioindicator organism and has been routinely sampled over decades by several countries to monitor marine environmental health. Additionally, this species is a promising model to study adaptive processes related to environmental change, specifically global warming. Here, we report the chromosome-level genome assembly of Z. viviparus, which has a size of 663 mega base pairs (mbp) and consists of 607 scaffolds (N50 = 26 mbp). The 24 largest represent the 24 chromosomes of the haploid Z. viviparus genome, which harbors 98% of the complete BUSCOs defined for ray-finned fish, indicating that the assembly is highly contiguous and complete. Comparative analyses between the Z. viviparus assembly and chromosome-level genomes of two other eelpout species revealed a high synteny, but also an accumulation of repetitive elements in the Z. viviparus genome. Our reference genome will be an important resource enabling future in-depth genomic analyses of the effects of environmental change in this important bioindicator species.

Phase II study of vemurafenib in children and young adults with tumors harboring BRAF V600 mutations: NCI-COG pediatric MATCH trial (APEC1621) Arm G.

BACKGROUND: This is a phase II subprotocol of the NCI-COG Pediatric MATCH study evaluating vemurafenib, a selective oral inhibitor of BRAF V600 mutated kinase, in patients with relapsed or refractory solid tumors harboring BRAF V600 mutations. METHODS: Patients received vemurafenib at 550 mg/m2 (maximum 960 mg/dose) orally twice daily for 28-day cycles until progression or intolerable toxicity. The primary aim was to determine the objective response rate and secondary objectives included estimating progression-free survival and assessing the tolerability of vemurafenib. RESULTS: Twenty-two patients matched to the subprotocol and 4 patients (18%) enrolled. Primary reasons for non-enrollment were ineligibility due to exclusions of low-grade glioma (nâ=â7) and prior BRAF inhibitor therapy (nâ=â7). Enrolled diagnoses were one each of histiocytosis, ameloblastoma, Ewing sarcoma, and high-grade glioma, all with BRAF V600E mutations. Treatment was overall tolerable with mostly expected grade 1/2 adverse events (AE). Grade 3 or 4 AE on treatment were acute kidney injury, hyperglycemia, and maculopapular rash. One patient came off therapy due to AE. One patient (glioma) had an objective partial response and remained on protocol therapy for 15 cycles. CONCLUSION: There was a low accrual rate on this MATCH subprotocol, with only 18% of those who matched with BRAFV600 mutations enrolling, resulting in early termination, and limiting study results (ClinicalTrials.gov Identifier: NCT03220035).

Zinc mediates control of nitrogen fixation via transcription factor filamentation.

Plants adapt to fluctuating environmental conditions by adjusting their metabolism and gene expression to maintain fitness1. In legumes, nitrogen homeostasis is maintained by balancing nitrogen acquired from soil resources with nitrogen fixation by symbiotic bacteria in root nodules2-8. Here we show that zinc, an essential plant micronutrient, acts as an intracellular second messenger that connects environmental changes to transcription factor control of metabolic activity in root nodules. We identify a transcriptional regulator, FIXATION UNDER NITRATE (FUN), which acts as a sensor, with zinc controlling the transition between an inactive filamentous megastructure and an active transcriptional regulator. Lower zinc concentrations in the nodule, which we show occur in response to higher levels of soil nitrate, dissociates the filament and activates FUN. FUN then directly targets multiple pathways to initiate breakdown of the nodule. The zinc-dependent filamentation mechanism thus establishes a concentration readout to adapt nodule function to the environmental nitrogen conditions. In a wider perspective, these results have implications for understanding the roles of metal ions in integration of environmental signals with plant development and optimizing delivery of fixed nitrogen in legume crops.

Longitudinal Fluctuations in Protein Concentrations and Higher-Order Structures in the Plasma Proteome of Kidney Failure Patients Subjected to a Kidney Transplant.

Using proteomics and complexome profiling, we evaluated in a year-long study longitudinal variations in the plasma proteome of kidney failure patients, prior to and after a kidney transplantation. The post-transplant period was complicated by bacterial infections, resulting in dramatic changes in the proteome, attributed to an acute phase response (APR). As positive acute phase proteins (APPs), being elevated upon inflammation, we observed the well-described C-reactive protein and Serum Amyloid A (SAA), but also Fibrinogen, Haptoglobin, Leucine-rich alpha-2-glycoprotein, Lipopolysaccharide-binding protein, Alpha-1-antitrypsin, Alpha-1-antichymotrypsin, S100, and CD14. As negative APPs, being downregulated upon inflammation, we identified the well-documented Serotransferrin and Transthyretin, but added Kallistatin, Heparin cofactor 2, and interalpha-trypsin inhibitor heavy chain H1 and H2 (ITIH1, ITIH2). For the patient with the most severe APR, we performed plasma complexome profiling by SEC-LC-MS on all longitudinal samples. We observed that several plasma proteins displaying alike concentration patterns coelute and form macromolecular complexes. By complexome profiling, we expose how SAA1 and SAA2 become incorporated into high-density lipid particles, replacing largely Apolipoprotein (APO)A1 and APOA4. Overall, our data highlight that the combination of in-depth longitudinal plasma proteome and complexome profiling can shed further light on correlated variations in the abundance of several plasma proteins upon inflammatory events.

Global indicators of the environmental impacts of invasive alien species and their information adequacy.

Monitoring the extent to which invasive alien species (IAS) negatively impact the environment is crucial for understanding and mitigating biological invasions. Indeed, such information is vital for achieving Target 6 of the Kunming-Montreal Global Biodiversity Framework. However, to-date indicators for tracking the environmental impacts of IAS have been either lacking or insufficient. Capitalizing on advances in data availability and impact assessment protocols, we developed environmental impact indicators to track realized and potential impacts of IAS. We also developed an information status indicator to assess the adequacy of the data underlying the impact indicators. We used data on 75 naturalized amphibians from 82 countries to demonstrate the indicators at a global scale. The information status indicator shows variation in the reliability of the data and highlights areas where absence of impact should be interpreted with caution. Impact indicators show that growth in potential impacts are dominated by predatory species, while potential impacts from both predation and disease transmission are distributed worldwide. Using open access data, the indicators are reproducible and adaptable across scales and taxa and can be used to assess global trends and distributions of IAS, assisting authorities in prioritizing control efforts and identifying areas at risk of future invasions. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

The Utility of AI in Writing a Scientific Review Article on the Impacts of COVID-19 on Musculoskeletal Health.

PURPOSE OF REVIEW: There were two primary purposes to our reviews. First, to provide an update to the scientific community about the impacts of COVID-19 on musculoskeletal health. Second, was to determine the value of using a large language model, ChatGPT 4.0, in the process of writing a scientific review article. To accomplish these objectives, we originally set out to write three review articles on the topic using different methods to produce the initial drafts of the review articles. The first review article was written in the traditional manner by humans, the second was to be written exclusively using ChatGPT (AI-only or AIO), and the third approach was to input the outline and references selected by humans from approach 1 into ChatGPT, using the AI to assist in completing the writing (AI-assisted or AIA). All review articles were extensively fact-checked and edited by all co-authors leading to the final drafts of the manuscripts, which were significantly different from the initial drafts. RECENT FINDINGS: Unfortunately, during this process, it became clear that approach 2 was not feasible for a very recent topic like COVID-19 as at the time, ChatGPT 4.0 had a cutoff date of September 2021 and all articles published after this date had to be provided to ChatGPT, making approaches 2 and 3 virtually identical. Therefore, only two approaches and two review articles were written (human and AI-assisted). Here we found that the human-only approach took less time to complete than the AI-assisted approach. This was largely due to the number of hours required to fact-check and edit the AI-assisted manuscript. Of note, the AI-assisted approach resulted in inaccurate attributions of references (about 20%) and had a higher similarity index suggesting an increased risk of plagiarism. The main aim of this project was to determine whether the use of AI could improve the process of writing a scientific review article. Based on our experience, with the current state of technology, it would not be advised to solely use AI to write a scientific review article, especially on a recent topic.

SARS-CoV-2 and its Multifaceted Impact on Bone Health: Mechanisms and Clinical Evidence.

PURPOSE OF REVIEW: SARS-CoV-2 infection, the culprit of the COVID-19 pandemic, has been associated with significant long-term effects on various organ systems, including bone health. This review explores the current understanding of the impacts of SARS-CoV-2 infection on bone health and its potential long-term consequences. RECENT FINDINGS: As part of the post-acute sequelae of SARS-CoV-2 infection, bone health changes are affected by COVID-19 both directly and indirectly, with multiple potential mechanisms and risk factors involved. In vitro and preclinical studies suggest that SARS-CoV-2 may directly infect bone marrow cells, leading to alterations in bone structure and osteoclast numbers. The virus can also trigger a robust inflammatory response, often referred to as a "cytokine storm", which can stimulate osteoclast activity and contribute to bone loss. Clinical evidence suggests that SARS-CoV-2 may lead to hypocalcemia, altered bone turnover markers, and a high prevalence of vertebral fractures. Furthermore, disease severity has been correlated with a decrease in bone mineral density. Indirect effects of SARS-CoV-2 on bone health, mediated through muscle weakness, mechanical unloading, nutritional deficiencies, and corticosteroid use, also contribute to the long-term consequences. The interplay of concurrent conditions such as diabetes, obesity, and kidney dysfunction with SARS-CoV-2 infection further complicates the disease's impact on bone health. SARS-CoV-2 infection directly and indirectly affects bone health, leading to potential long-term consequences. This review article is part of a series of multiple manuscripts designed to determine the utility of using artificial intelligence for writing scientific reviews.

Volume expansion mitigates Shiga toxin-producing E. coli-hemolytic uremic syndrome in children.

BACKGROUND: Shiga toxin-producing E. coli-hemolytic uremic syndrome (STEC-HUS) is associated with high morbidity and relevant mortality. Previous small studies showed that volume expansion could improve the course and outcome of STEC-HUS. The aim of this single-center study was to evaluate the effect of volume expansion on the clinical course and outcome in STEC-HUS. METHODS: Data of pediatric patients with STEC-HUS were analyzed retrospectively. Course and outcome of patients treated with volume expansion (VE) from 2019 to 2022 (n = 38) were compared to historical controls (HC) from 2009 to 2018 (n = 111). RESULTS: Patients in the VE group had a significant relative median weight gain compared to HC (7.8% (3.4-11.3) vs. 1.2% (- 0.7-3.9), p < 0.0001) 48 h after admission. The need for dialysis was not reduced by VE (VE 21/38 (55.3%) vs. HC 64/111 (57.7%), p = 0.8). However, central nervous system involvement (impairment of consciousness, seizures, focal neurological deficits, and/or visual disturbances) was significantly reduced (VE 6/38 (15.8%) vs. HC 38/111 (34.2%), p = 0.039). None of the patients in the VE group died or developed chronic kidney disease (CKD) stage 5, whereas in the HC group, three patients died and three patients had CKD stage 5 at discharge. CONCLUSIONS: This study suggests that volume expansion may be associated with the mitigation of the acute course of STEC-HUS, especially severe neurological involvement and the development of CKD. Prospective trials should lead to standardized protocols for volume expansion in children with STEC-HUS.

Predicting environmental stressor levels with machine learning: a comparison between amplicon sequencing, metagenomics, and total RNA sequencing based on taxonomically assigned data.

Introduction: Microbes are increasingly (re)considered for environmental assessments because they are powerful indicators for the health of ecosystems. The complexity of microbial communities necessitates powerful novel tools to derive conclusions for environmental decision-makers, and machine learning is a promising option in that context. While amplicon sequencing is typically applied to assess microbial communities, metagenomics and total RNA sequencing (herein summarized as omics-based methods) can provide a more holistic picture of microbial biodiversity at sufficient sequencing depths. Despite this advantage, amplicon sequencing and omics-based methods have not yet been compared for taxonomy-based environmental assessments with machine learning. Methods: In this study, we applied 16S and ITS-2 sequencing, metagenomics, and total RNA sequencing to samples from a stream mesocosm experiment that investigated the impacts of two aquatic stressors, insecticide and increased fine sediment deposition, on stream biodiversity. We processed the data using similarity clustering and denoising (only applicable to amplicon sequencing) as well as multiple taxonomic levels, data types, feature selection, and machine learning algorithms and evaluated the stressor prediction performance of each generated model for a total of 1,536 evaluated combinations of taxonomic datasets and data-processing methods. Results: Sequencing and data-processing methods had a substantial impact on stressor prediction. While omics-based methods detected a higher diversity of taxa than amplicon sequencing, 16S sequencing outperformed all other sequencing methods in terms of stressor prediction based on the Matthews Correlation Coefficient. However, even the highest observed performance for 16S sequencing was still only moderate. Omics-based methods performed poorly overall, but this was likely due to insufficient sequencing depth. Data types had no impact on performance while feature selection significantly improved performance for omics-based methods but not for amplicon sequencing. Discussion: We conclude that amplicon sequencing might be a better candidate for machine-learning-based environmental stressor prediction than omics-based methods, but the latter require further research at higher sequencing depths to confirm this conclusion. More sampling could improve stressor prediction performance, and while this was not possible in the context of our study, thousands of sampling sites are monitored for routine environmental assessments, providing an ideal framework to further refine the approach for possible implementation in environmental diagnostics.

CD5L is a canonical component of circulatory IgM.

Immunoglobulin M (IgM) is an evolutionary conserved key component of humoral immunity, and the first antibody isotype to emerge during an immune response. IgM is a large (1 MDa), multimeric protein, for which both hexameric and pentameric structures have been described, the latter additionally containing a joining (J) chain. Using a combination of single-particle mass spectrometry and mass photometry, proteomics, and immunochemical assays, we here demonstrate that circulatory (serum) IgM exclusively exists as a complex of J-chain-containing pentamers covalently bound to the small (36 kDa) protein CD5 antigen-like (CD5L, also called apoptosis inhibitor of macrophage). In sharp contrast, secretory IgM in saliva and milk is principally devoid of CD5L. Unlike IgM itself, CD5L is not produced by B cells, implying that it associates with IgM in the extracellular space. We demonstrate that CD5L integration has functional implications, i.e., it diminishes IgM binding to two of its receptors, the FcαµR and the polymeric Immunoglobulin receptor. On the other hand, binding to FcµR as well as complement activation via C1q seem unaffected by CD5L integration. Taken together, we redefine the composition of circulatory IgM as a J-chain containing pentamer, always in complex with CD5L.

Antimicrobial polymer-siRNA polyplexes as a dual-mode platform for the treatment of wound biofilm infections.

Treatment of wound biofilm infections faces challenges from both pathogens and uncontrolled host immune response. Treating both issues through a single vector would provide enhanced wound healing. Here, we report the use of a potent cationic antimicrobial polymer to generate siRNA polyplexes for dual-mode treatment of wound biofilms in vivo. These polyplexes act both as an antibiofilm agent and a delivery vehicle for siRNA for the knockdown of biofilm-associated pro-inflammatory MMP9 in host macrophages. The resulting polyplexes were effective in vitro, eradicating MRSA biofilms and efficiently delivering siRNA to macrophages in vitro with concomitant knockdown of MMP9. These polyplexes were likewise effective in an in vivo murine wound biofilm model, significantly reducing bacterial load in the wound (∼99% bacterial clearance) and reducing MMP9 expression by 80% (qRT-PCR). This combination therapeutic strategy dramatically reduced wound purulence and significantly expedited wound healing. Taken together, these polyplexes provide an effective and translatable strategy for managing biofilm-infected wounds.

Antimicrobial-loaded biodegradable nanoemulsions for efficient clearance of intracellular pathogens in bacterial peritonitis.

Intracellular pathogenic bacteria use immune cells as hosts for bacterial replication and reinfection, leading to challenging systemic infections including peritonitis. The spread of multidrug-resistant (MDR) bacteria and the added barrier presented by host cell internalization limit the efficacy of standard antibiotic therapies for treating intracellular infections. We present a non-antibiotic strategy to treat intracellular infections. Antimicrobial phytochemicals were stabilized and delivered by polymer-stabilized biodegradable nanoemulsions (BNEs). BNEs were fabricated using different phytochemicals, with eugenol-loaded BNEs (E-BNEs) affording the best combination of antimicrobial efficacy, macrophage accumulation, and biocompatibility. The positively-charged polymer groups of the E-BNEs bind to the cell surface of macrophages, facilitating the entry of eugenol that then kills the intracellular bacteria without harming the host cells. Confocal imaging and flow cytometry confirmed that this entry occurred mainly via cholesterol-dependent membrane fusion. As eugenol co-localized and interacted with intracellular bacteria, antibacterial efficacy was maintained. E-BNEs reversed the immunosuppressive effects of MRSA on macrophages. Notably, E-BNEs did not elicit resistance selection after multiple exposures of MRSA to sub-therapeutic doses. The E-BNEs were highly effective against a murine model of MRSA-induced peritonitis with better bacterial clearance (99 % bacteria reduction) compared to clinically-employed treatment with vancomycin. Overall, these findings demonstrate the potential of E-BNEs in treating peritonitis and other refractory intracellular infections.

Antimicrobial polymer-loaded hydrogels for the topical treatment of multidrug-resistant wound biofilm infections.

Integration of antimicrobial polymeric nanoparticles into hydrogel materials presents a promising strategy to address multidrug-resistant biofilm infections. Here we report an injectable hydrogel loaded with engineered cationic antimicrobial polymeric nanoparticles (PNPs) for the effective topical treatment of severe wound biofilm infections. The PNPs demonstrated biofilm penetration and disruption, resulting in the eradication of resistant and persister cells that reside within the biofilm. Significantly, PNPs did not elicit resistance development even after multiple exposures to sub-therapeutic doses. In vitro studies showed PNPs significantly reduced prolonged inflammation due to infection and promoted fibroblast migration. These PNPs were then incorporated into Poloxamer 407 (P407) hydrogels and utilized as an inert carrier for PNPs to provide a controlled and sustained topical release of the antimicrobial nanoparticles at the wound area. In vivo studies using a mature (4-day) wound biofilm infection in a murine model mimicking severe human wound infections demonstrated provided 99% bacterial biofilm clearance and significantly enhanced wound healing. Overall, this work demonstrated the efficacy and selectivity of the antimicrobial polymer-loaded hydrogel platform as a topical treatment for difficult-to-treat wound biofilm infections.

Lactiplantibacillus plantarum as a novel platform for production and purification of integral membrane proteins using RseP as the benchmark.

The present study describes a detailed procedure for expressing and purifying the integral membrane protein RseP using the pSIP system and Lactiplantibacillus plantarum as an expression host. RseP is a membrane-bound site-2-protease and a known antibacterial target in multiple human pathogens. In the present study, we screened five RseP orthologs from Gram-positive bacteria and found RseP from Enterococcus faecium (EfmRseP) to yield the highest protein levels. The production conditions were optimized and EfmRseP was purified by immobilized metal ion affinity chromatography followed by size-exclusion chromatography. The purification resulted in an overall yield of approximately 1 mg of pure protein per 3 g of wet-weight cell pellet. The structural integrity of the purified protein was confirmed using circular dichroism. We further assessed the expression and purification of RseP from E. faecium in the Gram-negative Escherichia coli. Detection of soluble protein failed in two of the three E. coli strains tested. Purification of EfmRseP expressed in E. coli C43(DE3) resulted in a protein with lower purity compared to EfmRseP expressed in L. plantarum. To our knowledge, this is the first time L. plantarum and the pSIP expression system have been applied for the production of membrane proteins.