The continuous and rapid increase of chemical pollution in surface waters has become a pressing and widely recognized global concern. As emerging contaminants (ECs) in surface waters, pharmaceutical and personal care products (PPCPs), and endocrine-disrupting compounds (EDCs) have attracted considerable attention due to their wide occurrence and potential threat to human health. Therefore, a comprehensive understanding of the occurrence and risks of ECs in Chinese surface waters is urgently required. This study summarizes and assesses the environmental occurrence concentrations and ecological risks of 42 pharmaceuticals, 15 personal care products (PCPs), and 20 EDCs frequently detected in Chinese surface waters. The ECs were primarily detected in China\'s densely populated and highly industrialized regions. Most detected PPCPs and EDCs had concentrations between ng/L to µg/L, whereas norfloxacin, caffeine, and erythromycin had relatively high contamination levels, even exceeding 2000 ng/L. Risk evaluation based on the risk quotient method revealed that 34 PPCPs and EDCs in Chinese surface waters did not pose a significant risk, whereas 4-nonylphenol, 4-tert-octylphenol, 17α-ethinyl estradiol, 17β-estradiol, and triclocarban did. This review provides a comprehensive summary of the occurrence and associated hazards of typical PPCPs and EDCs in Chinese surface waters over the past decade, and will aid in the regulation and control of these ECs in Chinese surface waters.

Efforts to regulate and monitor emerging contaminants are insufficient because new chemicals are continually brought to market, and many are unregulated and potentially harmful. Domestic wastewater treatment plants are not designed to remove micropollutants and are important sources of emerging contaminants in the aquatic environment. In this study, non-target screening, an unbiased method for analyzing compounds without prior information, was used to identify compounds that may be emitted in wastewater treatment plant effluent and should be monitored. Nine wastewater treatment plants using different treatment methods were studied, and a non-target screening data-processing method was used. The frequencies at which the contaminants were detected and contaminant persistence through the treatment processes were considered, and then the contaminants were prioritized. The predicted no-effect concentration of each prioritized contaminant was used to determine whether further analysis and monitoring of the contaminant was necessary. Quantitative analyses of five compounds (amantadine, atenolol, benzotriazole, diphenhydramine, and sulpiride) were performed using reference standards. Probable molecular formulae and structures were proposed for 17 contaminants, and the risks posed by the contaminants were estimated using predicted no-effect concentrations. The results provide valuable insights into how unregulated micropollutants can be identified and prioritized for monitoring in future studies.

Pesticides are among the main drivers posing risks to aquatic environments, with effluents from wastewater treatment plants (WWTPs) serving as a major source. This study aimed to identify the primary pesticides for which there was a risk of release into aquatic environments through WWTP effluents, thereby enabling more effective contamination management in public water bodies. In this study, monitoring, risk assessment, and risk-based prioritization of 87 pesticides in effluents from three WWTPs in the Yeongsan River Basin, Korea, were conducted. A total of 59 pesticides were detected at concentrations from 0.852 ng/L to 82.044 μg/L and exhibited variable patterns across different WWTP locations. An environmental risk assessment based on the risk quotient (RQ) of individual pesticides identified 13 substances implicated in significant ecotoxicological risks, as they exceeded RQ values of 1 at least once. An optimized risk (RQf)-based prioritization, considering the frequency of the measured environmental concentration (MEC) exceeding the predicted environmental concentration (PNEC), was conducted to identify pesticides that potentially posed risks and thus should be managed as a priority. Four pesticides had an RQf value >1; metribuzin exhibited the highest RQf value of 4.951, followed by 3-phenoxybenzoic acid, atrazin-2-hydroxy, and atrazine. Additionally, five pesticides (terbuthylazine, methabenzthiazuron, diuron, thiacloprid, and fipronil) and another four pesticides (propazine, imidacloprid, hexaconazole, and hexazione) had RQf values >0.1 and > 0.01, respectively. By calculating the contributions of individual pesticides to the RQf of these mixtures (RQf, mix) based on the concentration addition model, it was determined that >95 % of the sum of RQf, mix was driven by the top seven pesticides. These findings highlight the importance of prioritizing pesticides for effective management of contamination sources.

UNASSIGNED: Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers, particularly when used in combination with checkpoint blockade therapy. At least 100 clinical trials involving these therapies are underway globally. Accurate identification and prioritization of neoantigens is highly relevant to designing these trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel DNA and RNA sequencing technologies, it is now possible to computationally predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. There has been a rapid development of computational tools that attempt to account for these complexities. While these tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. This often leads to over-simplification of pipeline outputs to make them tractable, for example limiting prediction to a single RNA isoform or only summarizing the top ranked of many possible peptide candidates. In addition to variant detection, gene expression and predicted peptide binding affinities, recent studies have also demonstrated the importance of mutation location, allele-specific anchor locations, and variation of T-cell response to long versus short peptides. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address.
UNASSIGNED: We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies including cancer vaccines. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates across three different levels, including variant, transcript and peptide information.
UNASSIGNED: pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings The application is available as part of the pVACtools pipeline at pvactools.org and as an online server at pvacview.org.

UNASSIGNED: The GlobalTree Portal, hosted by Botanic Gardens Conservation International, provides access to information on the approximately 58,000 tree species worldwide. Included in the GlobalTree Portal is the Conservation Action Tracker, a dynamic and collaborative database to identify and monitor conservation actions for tree species globally.
UNASSIGNED: The Conservation Action Tracker collates conservation action information at the species level, including species recovery/action plans, ex situ collections, propagation protocols, in situ management, species protection policy, and education/awareness campaigns.
UNASSIGNED: To date, the Conservation Action Tracker contains conservation action information for 4126 tree species, including 2161 threatened species, of which 659 are classified as Vulnerable, 783 as Endangered, and 719 as Critically Endangered. It covers conservation action information for at least one tree species in every country; however, more information is needed for 89% of Vulnerable, 87% of Endangered, and 77% of Critically Endangered tree species.
UNASSIGNED: Monitoring species conservation actions can support the prioritization and scaling up of conservation practices by sharing knowledge, increasing collaboration, enabling the identification of conservation gaps, and making the information available to be used by decision-makers. Tracking conservation actions at the species level is, therefore, essential to guide future conservation efforts. Increasing the amount of data in the Conservation Action Tracker will improve the tool\'s ability to guide future conservation efforts and avoid the extinction of tree species.

Antimicrobial resistance (AMR) undermines the United Nations Sustainable Development Goals of good health and well-being. Antibiotics are known to exacerbate AMR, but nonantibiotic antimicrobials, such as quaternary ammonium compounds (QACs), are now emerging as another significant driver of AMR. However, assessing the AMR risks of QACs in complex environmental matrices remains challenging due to the ambiguity in their chemical structures and antibacterial activity. By machine learning prediction and high-resolution mass spectrometric analysis, a list of antibacterial QACs (n = 856) from industrial chemical inventories is compiled, and it leads to the identification of 50 structurally diverse antibacterial QACs in sediments, including traditional hydrocarbon-based compounds and new subclasses that bear additional functional groups, such as choline, ester, betaine, aryl ether, and pyridine. Urban wastewater, aquaculture, and hospital discharges are the main factors influencing QAC distribution patterns in estuarine sediments. Toxic unit calculations and metagenomic analysis revealed that these QACs can influence antibiotic resistance genes (particularly sulfonamide resistance genes) through cross- and coresistances. The potential to influence the AMR is related to their environmental persistence. These results suggest that controlling the source, preventing the co-use of QACs and sulfonamides, and prioritizing control of highly persistent molecules will lead to global stewardship and sustainable use of QACs.

This study investigated the occurrence, removal rate, and potential risks of 43 organic micropollutants (OMPs) in four municipal wastewater treatment plants (WWTPs) in Korea. Results from two-year intensive monitoring confirmed the presence of various OMPs in the influents, including pharmaceuticals such as acetaminophen (pain relief), caffeine (stimulants), cimetidine (H2-blockers), ibuprofen (non-steroidal anti-inflammatory drugs- NSAIDs), metformin (antidiabetics), and naproxen (NSAIDs) with median concentrations of >1 μg/L. Some pharmaceuticals (carbamazepine-anticonvulsants, diclofenac-NSAIDs, propranolol-β-blockers), corrosion inhibitors (1H-benzotriazole-BTR, 4-methyl-1H-benzotriazole-4-TTR), and perfluorinated compounds (PFCs) were negligibly removed during WWTP treatment. The OMP concentrations in the influents and effluents were mostly lower in August than those of other months (p-value <0.05) possibly due to wastewater dilution by high precipitation or enhanced biodegradation under high-temperature conditions. The anaerobic-anoxic-oxic process (A2O) with a membrane bioreactor exhibited higher OMP removal than other processes, such as A2O with sedimentation or the conventional activated sludge process (p-value <0.05). Pesticides (DEET and atrazine), corrosion inhibitors (4-TTR and BTR), and metformin were selected as priority OMPs in toxicity-driven prioritization, whereas PFCs were determined as priority OMPs given their persistence and bioaccumulation properties. Overall, our results contribute to an important database on the occurrence, removal, and potential risks of OMPs in Korean WWTPs.

UNASSIGNED: In Canada, one out of five people lives with chronic pain, a condition frequently co-occurring with other chronic illnesses. As with most chronic illnesses, successful engagement in symptom management is key. In the context of multiple illnesses, self-management involves daily prioritization of symptoms and conditions and decision-making, which can be challenging. Self-management of chronic illnesses can require more complex competence and tasks to address the different implications of each condition.
UNASSIGNED: Our research objective was to explore types and processes of self-management symptom prioritization among adults living with chronic pain and other chronic illnesses.
UNASSIGNED: This research was carried out as part of a larger study that adopted an explanatory sequential mixed-methods design. This study focused more specifically on the qualitative part of the study.
UNASSIGNED: Participants recruited for the qualitative component took part in a semi-structured individual interview online or in-person at the center hospitalier de l\'Université de Montréal.
UNASSIGNED: In total, 25 participants were interviewed, including 18 women and 7 men.
UNASSIGNED: To participate in the qualitative part of the study, participants were selected from the larger study and were eligible if they were 18 years old or older and experiencing pain for more than 3 months and had at least one other chronic illness for which they were receiving treatment or engaged in symptom management. Semi-structured interviews were conducted in-person or virtually and were transcribed verbatim. Reflexive thematic analysis was used to explore patients\' narratives, and an open and iterative approach was adopted to code interviews and generate themes.
UNASSIGNED: The first theme, focus on symptom prioritization, showed different prioritization processes, including prioritizing a dominant illness, prioritizing multiple illnesses to avoid undesirable consequences, and finally absence of or automatic processes of prioritization. In the second theme, we identified several characteristics of an illness, in this case chronic pain that made it a self-management priority: uncontrollable and disabling nature, omnipresence, unpredictability, unpleasantness, and invisibility to others. In the last theme, we highlighted that some psychosocial factors influenced levels of engagement in self-management and prioritization processes, including social support and the patient-physician relationship.
UNASSIGNED: Chronic pain was the medical condition most often prioritized by participants in their self-management tasks. Because of its characteristics, it was the medical condition that had the most negative impact on day-to-day functioning.

Physicians often face tight resource constraints, meaning they have to make trade-offs between which patients they care for and the amount of care received. Studies show that patients requiring many resources disproportionately suffer a loss of care when resources are constrained. This study uncovers whether physicians\' attitudes toward prioritization of healthcare predicts poor-health patients\' access to care. We combine unique survey data on Danish GPs\' preferred prioritization principle with register data on their patients\' contacts in general practice. We consider different types of contacts as the required effort could impact the need for prioritization. Our results show variation in GPs\' prioritization principles, where a majority prefers a principle that may lead to an unequal distribution of services. We further find that GPs\' attitudes toward prioritization predict some poor-health patients\' access to general practice. GPs who state they prefer the principle of prioritizing patients in the poorest health state when resources tightened provide more contacts to poor-health patients. The additional contacts are typically high-effort contacts such as annual status meetings and home visits, but also low-effort contacts such as emails. Our findings indicate inequity in poor-health patients\' access to care across general practices.

BACKGROUND: Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.
METHODS: CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.
RESULTS: A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]).
CONCLUSIONS: We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.