A network approach to emotion regulation and symptom activation in depression and anxiety.

Background: Emotions can be regulated through several regulatory strategies that are involved in the development of psychopathological symptoms. Despite the well-established association between psychopathology and emotion dysregulation, little is known about the relationship between individual symptoms of depression and anxiety and emotion regulation strategies (ERS), as well as between ERS themselves. Method: We conducted a cross-sectional study and examined the interactions between six ERS (reappraisal, engagement, rumination, suppression, arousal control, and distraction) and assessed their distinctive association with the activation of specific symptoms of depression and anxiety in a community sample of 376 adults (80.4% female; Mage = 32.70; SDage = 11.80). The Regulation Emotion Systems Survey (RESS) was used to measure ERS. The Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder (GAD-7) were used to assess psychological symptoms. An exploratory graph analysis was performed to examine the structural properties of the network of interactions between these behaviors. Additionally, to test the association of ERS with the activation of the depression symptoms network, an expected symptoms activity (ESA) was conducted. Results: Six communities were found that correspond to the six ERS. Rumination and suppression have a significant association with symptom activation (particularly low self-esteem), whereas reappraisal reduces symptomatic activation. The effect of arousal control, engagement, and distraction appears to depend on the remaining ERS rather than having much influence on their own. Conclusion: This study provides insight into how ERS interact with each other and with individual symptoms of depression and anxiety. Understanding the effects of these interactions on symptom activation and comorbidity can improve our understanding of psychopathology.

Antibiotics with antibiofilm activity - rifampicin and beyond.

The management of prosthetic joint infections is a complex and multilayered process that is additionally complicated by the formation of bacterial biofilm. Foreign material provides the ideal grounds for the development of an intricate matrix that hinders treatment and creates a difficult environment for antibiotics to act. Surgical intervention is often warranted but requires appropriate adjunctive therapy. Despite available guidelines, several aspects of antibiotic therapy with antibiofilm activity lack clear definition. Given the escalating challenges posed by antimicrobial resistance, extended treatment durations, and tolerance issues, it is essential to ensure that antimicrobials with antibiofilm activity are both potent and diverse. Evidence of biofilm-active drugs is highlighted, and alternatives to classical regimens are further discussed.

Creating a Modified Version of the Cambridge Multimorbidity Score to Predict Mortality in People Older Than 16 Years: Model Development and Validation.

BACKGROUND: No single multimorbidity measure is validated for use in NHS (National Health Service) England's General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR), the nationwide primary care data set created for COVID-19 pandemic research. The Cambridge Multimorbidity Score (CMMS) is a validated tool for predicting mortality risk, with 37 conditions defined by Read Codes. The GDPPR uses the more internationally used Systematized Nomenclature of Medicine clinical terms (SNOMED CT). We previously developed a modified version of the CMMS using SNOMED CT, but the number of terms for the GDPPR data set is limited making it impossible to use this version. OBJECTIVE: We aimed to develop and validate a modified version of CMMS using the clinical terms available for the GDPPR. METHODS: We used pseudonymized data from the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC), which has an extensive SNOMED CT list. From the 37 conditions in the original CMMS model, we selected conditions either with (1) high prevalence ratio (≥85%), calculated as the prevalence in the RSC data set but using the GDPPR set of SNOMED CT codes, divided by the prevalence included in the RSC SNOMED CT codes or (2) conditions with lower prevalence ratios but with high predictive value. The resulting set of conditions was included in Cox proportional hazard models to determine the 1-year mortality risk in a development data set (n=500,000) and construct a new CMMS model, following the methods for the original CMMS study, with variable reduction and parsimony, achieved by backward elimination and the Akaike information stopping criterion. Model validation involved obtaining 1-year mortality estimates for a synchronous data set (n=250,000) and 1-year and 5-year mortality estimates for an asynchronous data set (n=250,000). We compared the performance with that of the original CMMS and the modified CMMS that we previously developed using RSC data. RESULTS: The initial model contained 22 conditions and our final model included 17 conditions. The conditions overlapped with those of the modified CMMS using the more extensive SNOMED CT list. For 1-year mortality, discrimination was high in both the derivation and validation data sets (Harrell C=0.92) and 5-year mortality was slightly lower (Harrell C=0.90). Calibration was reasonable following an adjustment for overfitting. The performance was similar to that of both the original and previous modified CMMS models. CONCLUSIONS: The new modified version of the CMMS can be used on the GDPPR, a nationwide primary care data set of 54 million people, to enable adjustment for multimorbidity in predicting mortality in people in real-world vaccine effectiveness, pandemic planning, and other research studies. It requires 17 variables to produce a comparable performance with our previous modification of CMMS to enable it to be used in routine data using SNOMED CT.

Topological properties of psychopathological networks of healthy and disordered individuals across mental disorders.

The identification of psychopathological markers has been the focus of several scientific fields. The results were inconsistent due to lack of a clear nosology. Network analysis, focusing on the interactions between symptoms, provided important insights into the nosology of mental disorders. These interactions originate several topological properties that could constitute markers of psychopathology. One of these properties is network connectivity, which has been explored in recent years. However, the results have been inconsistent, and the topological properties of psychopathological networks remain largely unexplored and unknown. We compared several topological properties (i.e., connectivity, average path length, assortativity, average degree, modularity, global clustering) of psychopathological networks of healthy and disordered participants across depression (N = 2830), generalized anxiety (N = 13,463), social anxiety (N = 12,814), and obsessive-compulsive disorder (N = 16,426). Networks were estimated using Bayesian Gaussian Graphical Models. The Janson-Shannon measure of divergence was used to identify differences between the network properties. Network connectivity distinguished healthy and disordered participants' networks in all disorders. However, in depression and generalized anxiety, network connectivity was higher in healthy participants. The presence and number of motifs also distinguished the networks of healthy and disordered participants. Other topological properties (i.e., modularity, clustering, average path length and average degree) seem to be disorder-specific. The psychopathological significance of network connectivity must be clarified. Some topological properties of psychopathological networks are promising markers of psychopathology and may contribute to clarifying the nosology of mental disorders.

Qualitative evaluation of a molecular point-of-care testing study for influenza in UK primary care.

BACKGROUND: Influenza contributes to the surge in winter infections and the consequent winter pressures on the health service. Molecular point-of-care testing(POCT) for influenza might improve patient management by providing rapid and accurate clinical diagnosis to inform the timely initiation of antiviral therapy and reduce unnecessary admissions and antibiotics use. AIM: To explore factors that influence the adoption or non-adoption of POCT in English general practices and provide insights to enable its integration into routine practice workflows. DESIGN & SETTING: A qualitative implementation evaluation was conducted in ten general practices within the English national sentinel network (Oxford-RCGP Research and Surveillance Centre), from April to July 2023. METHOD: Using the nonadoption, abandonment, scale-up, spread, and sustainability framework, data collection and analysis were conducted across ten practices. We made ethnographic observations of the POCT workflow and surveyed the practice staff for their perspectives on POCT implementation. Data were analysed using a mix of descriptive statistics, graphical modelling techniques and framework approach. RESULTS: Ethnographic observations identified two modes of POCT integration into practice workflow: 1) clinician POCT workflow - typically involving batch testing due to time constraints, 2) research nurse/healthcare assistant POCT workflow - characterised by immediate testing of individual patients. Survey indicated that most primary care staff considered the POCT training offered was sufficient, and these practices were ready for change and had the capacity and resources to integrate POCT in workflows. CONCLUSION: General practices should demonstrate flexibility in the workflow and workforce they deploy to integrate POCT into routine clinical workflow.

Effect of Breed and Season in Buck Semen Cryopreservation: The Portuguese Animal Germplasm Bank.

The aims of this study were to characterize the semen as well as the influence of breed, season, and semen processing on spermatozoa (SPZ) traits of four native Portuguese goat breeds used for the bank of Portuguese animal germplasm (BPAG). A total of 1017 ejaculates from Serrana (n = 30), Bravia (n = 15), Charnequeira (n = 11), and Preta de Montezinho (n = 3) bucks were collected between 2004 and 2020 at (EZN-INIAV; 39° N) during the whole year under natural conditions. All the fresh and cryopreserved (-196 °C) semen was evaluated and stored in the BPAG. Bravia bucks (the smallest breed) produced less (p < 0.05) volume of ejaculate than all the other breeds, which was higher during the full breeding season (September-January; p < 0.05), regarding all the other breeds. Contrarily, in general, SPZ concentration was lower during September-January, but total SPZ per ejaculate remained similar (p > 0.05) during May-August and September-January in Serrana bucks. The SPZ viability and SPZ midpiece defects were slightly influenced by breed and SPZ head defects by season (lowest % in February-April; p < 0.05). On the contrary, the freezing-thawing cycle strongly influenced (p < 0.01) all SPZ traits. The correlation coefficients of these traits between fresh and thawed SPZ were low (up to 0.33; p < 0.01), highlighting the importance of semen processing in semen cryopreservation. We conclude that breed and season had a relevant effect on ejaculate traits, but it was much less evident for the studied SPZ traits. These native goats can serve as semen donors throughout the year, under natural conditions.

Deploying an asthma dashboard to support quality improvement across a nationally representative sentinel network of 7.6 million people in England.

Every year, there are ~100,000 hospital admissions for asthma in the UK, many of which are potentially preventable. Evidence suggests that carefully conceptualised and implemented audit and feedback (A&F) cycles have the potential to improve clinical outcomes for those with chronic conditions. We wanted to investigate the technical feasibility of developing a near-real time asthma dashboard to support A&F interventions for asthma management in primary care. We extracted cross-sectional data on asthma from 756 participating GP practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) database in England comprising 7.6 million registered people. Summary indicators for a GP practice were compared to all participating RCGP RSC practices using practice-level data, for the week 6-12th-Mar-2023. A weekly, automated asthma dashboard with features that can support electronic-A&F cycles that compared key asthma indicators for a GP practice to RCGP RSC could be created ( https://tinyurl.com/3ydtrt85 ): 12-weeks-incidence 0.4% vs 0.4%, annual prevalence 6.1% vs 6.7%, inhaled relievers to preventer 1.2 vs 1.1, self-management plan given 83.4% vs 60.8%, annual reviews 36.8% vs 57.3%, prednisolone prescriptions 2.0% vs 3.2%, influenza vaccination 56.6% vs 55.5%, pneumococcal vaccination ever (aged ≥65 years) 90.2% vs 84.1% and current smokers 14.9% vs 14.8%. Across the RCGP RSC, the rate of hospitalisations was 0.024%; comparative data had to be suppressed for the study practice because of small numbers. We have successfully created an automated near real-time asthma dashboard that can be used to support A&F initiatives to improve asthma care and outcomes in primary care.

Misaligned feeding uncouples daily rhythms within brown adipose tissue and between peripheral clocks.

Extended food consumption during the rest period perturbs the phase relationship between circadian clocks in the periphery and the brain, leading to adverse health effects. Beyond the liver, how metabolic organs respond to a timed hypocaloric diet is largely unexplored. We investigated how feeding schedules impacted circadian gene expression in epididymal white and brown adipose tissue (eWAT and BAT) compared to the liver and hypothalamus. We restricted food to either daytime or nighttime in C57BL/6J male mice, with or without caloric restriction. Unlike the liver and eWAT, rhythmic clock genes in the BAT remained insensitive to feeding time, similar to the hypothalamus. We uncovered an internal split within the BAT in response to conflicting environmental cues, displaying inverted oscillations on a subset of metabolic genes without modifying its local core circadian machinery. Integrating tissue-specific responses on circadian transcriptional networks with metabolic outcomes may help elucidate the mechanism underlying the health burden of eating at unusual times.

Modifiable risk factors for asthma exacerbations during the COVID-19 pandemic: a population-based repeated cross-sectional study using the Research and Surveillance Centre primary care database.

Background: There were substantial reductions in asthma exacerbations during the COVID-19 pandemic for reasons that remain poorly understood. We investigated changes in modifiable risk factors which might help explain the reductions in asthma exacerbations. Methods: Multilevel generalised linear mixed models were fitted to examine changes in modifiable risk factors for asthma exacerbations during 2020-2022, compared to pre-pandemic year (2019), using observational, routine data from general practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre. Asthma exacerbations were defined as any of GP recorded: asthma exacerbations, prescriptions of prednisolone, accident and emergency department attendance or hospitalisation for asthma. Modifiable risk factors of interest were ownership of asthma self-management plan, asthma annual review, inhaled-corticosteroid (ICS) prescriptions, influenza vaccinations and respiratory-tract-infections (RTI). Findings: Compared with 2019 (n = 550,995), in 2020 (n = 565,956) and 2022 (n = 562,167) (p < 0.05): asthma exacerbations declined from 67.1% to 51.9% and 61.1%, the proportion of people who had: asthma exacerbations reduced from 20.4% to 15.1% and 18.5%, asthma self-management plans increased from 28.6% to 37.7% and 55.9%; ICS prescriptions increased from 69.9% to 72.0% and 71.1%; influenza vaccinations increased from 14.2% to 25.4% and 55.3%; current smoking declined from 15.0% to 14.5% and 14.7%; lower-RTI declined from 10.5% to 5.3% and 8.1%; upper-RTI reduced from 10.7% to 5.8% and 7.6%. There was cluster effect of GP practices on asthma exacerbations (p = 0.001). People with asthma were more likely (p < 0.05) to have exacerbations if they had LRTI (seven times(x)), had URTI and ILI (both twice), were current smokers (1.4x), PPV vaccinated (1.3x), seasonal flu vaccinated (1.01x), took ICS (1.3x), had asthma reviews (1.09x). People with asthma were less likely to have exacerbations if they had self-management plan (7%), and were partially (4%) than fully COVID-19 vaccinated. Interpretation: We have identified changes in modifiable risk factors for asthma exacerbation that need to be maintained in the post-pandemic era. Funding: Asthma UK Centre for Applied Research and Health Data Research UK.

Cellular interactions and microenvironment dynamics in skeletal muscle regeneration and disease.

Skeletal muscle regeneration relies on the intricate interplay of various cell populations within the muscle niche-an environment crucial for regulating the behavior of muscle stem cells (MuSCs) and ensuring postnatal tissue maintenance and regeneration. This review delves into the dynamic interactions among key players of this process, including MuSCs, macrophages (MPs), fibro-adipogenic progenitors (FAPs), endothelial cells (ECs), and pericytes (PCs), each assuming pivotal roles in orchestrating homeostasis and regeneration. Dysfunctions in these interactions can lead not only to pathological conditions but also exacerbate muscular dystrophies. The exploration of cellular and molecular crosstalk among these populations in both physiological and dystrophic conditions provides insights into the multifaceted communication networks governing muscle regeneration. Furthermore, this review discusses emerging strategies to modulate the muscle-regenerating niche, presenting a comprehensive overview of current understanding and innovative approaches.

A Profile of Influenza Vaccine Coverage for 2019-2020: Database Study of the English Primary Care Sentinel Cohort.

BACKGROUND: Innovation in seasonal influenza vaccine development has resulted in a wider range of formulations becoming available. Understanding vaccine coverage across populations including the timing of administration is important when evaluating vaccine benefits and risks. OBJECTIVE: This study aims to report the representativeness, uptake of influenza vaccines, different formulations of influenza vaccines, and timing of administration within the English Primary Care Sentinel Cohort (PCSC). METHODS: We used the PCSC of the Oxford-Royal College of General Practitioners Research and Surveillance Centre. We included patients of all ages registered with PCSC member general practices, reporting influenza vaccine coverage between September 1, 2019, and January 29, 2020. We identified influenza vaccination recipients and characterized them by age, clinical risk groups, and vaccine type. We reported the date of influenza vaccination within the PCSC by International Standard Organization (ISO) week. The representativeness of the PCSC population was compared with population data provided by the Office for National Statistics. PCSC influenza vaccine coverage was compared with published UK Health Security Agency's national data. We used paired t tests to compare populations, reported with 95% CI. RESULTS: The PCSC comprised 7,010,627 people from 693 general practices. The study population included a greater proportion of people aged 18-49 years (2,982,390/7,010,627, 42.5%; 95% CI 42.5%-42.6%) compared with the Office for National Statistics 2019 midyear population estimates (23,219,730/56,286,961, 41.3%; 95% CI 4.12%-41.3%; P<.001). People who are more deprived were underrepresented and those in the least deprived quintile were overrepresented. Within the study population, 24.7% (1,731,062/7,010,627; 95% CI 24.7%-24.7%) of people of all ages received an influenza vaccine compared with 24.2% (14,468,665/59,764,928; 95% CI 24.2%-24.2%; P<.001) in national data. The highest coverage was in people aged ≥65 years (913,695/1,264,700, 72.3%; 95% CI 72.2%-72.3%). The proportion of people in risk groups who received an influenza vaccine was also higher; for example, 69.8% (284,280/407,228; 95% CI 69.7%-70%) of people with diabetes in the PCSC received an influenza vaccine compared with 61.2% (983,727/1,607,996; 95% CI 61.1%-61.3%; P<.001) in national data. In the PCSC, vaccine type and brand information were available for 71.8% (358,365/498,923; 95% CI 71.7%-72%) of people aged 16-64 years and 81.9% (748,312/913,695; 95% CI 81.8%-82%) of people aged ≥65 years, compared with 23.6% (696,880/2,900,000) and 17.8% (1,385,888/7,700,000), respectively, of the same age groups in national data. Vaccination commenced during ISO week 35, continued until ISO week 3, and peaked during ISO week 41. The in-week peak in vaccination administration was on Saturdays. CONCLUSIONS: The PCSC's sociodemographic profile was similar to the national population and captured more data about risk groups, vaccine brands, and batches. This may reflect higher data quality. Its capabilities included reporting precise dates of administration. The PCSC is suitable for undertaking studies of influenza vaccine coverage.

Crosstalk between circadian clocks and pathogen niche.

Circadian rhythms are intrinsic 24-hour oscillations found in nearly all life forms. They orchestrate key physiological and behavioral processes, allowing anticipation and response to daily environmental changes. These rhythms manifest across entire organisms, in various organs, and through intricate molecular feedback loops that govern cellular oscillations. Recent studies describe circadian regulation of pathogens, including parasites, bacteria, viruses, and fungi, some of which have their own circadian rhythms while others are influenced by the rhythmic environment of hosts. Pathogens target specific tissues and organs within the host to optimize their replication. Diverse cellular compositions and the interplay among various cell types create unique microenvironments in different tissues, and distinctive organs have unique circadian biology. Hence, residing pathogens are exposed to cyclic conditions, which can profoundly impact host-pathogen interactions. This review explores the influence of circadian rhythms and mammalian tissue-specific interactions on the dynamics of pathogen-host relationships. Overall, this demonstrates the intricate interplay between the body's internal timekeeping system and its susceptibility to pathogens, which has implications for the future of infectious disease research and treatment.

Circadian rhythms mediate malaria transmission potential.

Malaria transmission begins when infected female Anopheles mosquitos deposit Plasmodium parasites into the mammalian host's skin during a bloodmeal. The salivary gland-resident sporozoite parasites migrate to the bloodstream, subsequently invading and replicating within hepatocytes. As Anopheles mosquitos are more active at night, with a 24-hour rhythm, we investigated whether their salivary glands are under circadian control, anticipating bloodmeals and modulating sporozoite biology for host encounters. Here we show that approximately half of the mosquito salivary gland transcriptome, particularly genes essential for efficient bloodmeals such as anti-blood clotting factors, exhibits circadian rhythmic expression. Furthermore, we demonstrate that mosquitoes prefer to feed during nighttime, with the amount of blood ingested varying cyclically throughout the day. Notably, we show a substantial subset of the sporozoite transcriptome cycling throughout the day. These include genes involved in parasite motility, potentially modulating the ability to initiate infection at different times of day. Thus, although sporozoites are typically considered quiescent, our results demonstrate their transcriptional activity, revealing robust daily rhythms of gene expression. Our findings suggest a circadian evolutionary relationship between the vector, parasite and mammalian host that together modulate malaria transmission.

Phenotype execution and modeling architecture to support disease surveillance and real-world evidence studies: English sentinel network evaluation.

Objective: To evaluate Phenotype Execution and Modelling Architecture (PhEMA), to express sharable phenotypes using Clinical Quality Language (CQL) and intensional Systematised Nomenclature of Medicine (SNOMED) Clinical Terms (CT) Fast Healthcare Interoperability Resources (FHIR) valuesets, for exemplar chronic disease, sociodemographic risk factor, and surveillance phenotypes. Method: We curated 3 phenotypes: Type 2 diabetes mellitus (T2DM), excessive alcohol use, and incident influenza-like illness (ILI) using CQL to define clinical and administrative logic. We defined our phenotypes with valuesets, using SNOMED's hierarchy and expression constraint language, and CQL, combining valuesets and adding temporal elements where needed. We compared the count of cases found using PhEMA with our existing approach using convenience datasets. We assessed our new approach against published desiderata for phenotypes. Results: The T2DM phenotype could be defined as 2 intensionally defined SNOMED valuesets and a CQL script. It increased the prevalence from 7.2% to 7.3%. Excess alcohol phenotype was defined by valuesets that added qualitative clinical terms to the quantitative conceptual definitions we currently use; this change increased prevalence by 58%, from 1.2% to 1.9%. We created an ILI valueset with SNOMED concepts, adding a temporal element using CQL to differentiate new episodes. This increased the weekly incidence in our convenience sample (weeks 26-38) from 0.95 cases to 1.11 cases per 100 000 people. Conclusions: Phenotypes for surveillance and research can be described fully and comprehensibly using CQL and intensional FHIR valuesets. Our use case phenotypes identified a greater number of cases, whilst anticipated from excessive alcohol this was not for our other variable. This may have been due to our use of SNOMED CT hierarchy. Our new process fulfilled a greater number of phenotype desiderata than the one that we had used previously, mostly in the modeling domain. More work is needed to implement that sharing and warehousing domains.

Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024.

BACKGROUND: Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. OBJECTIVE: We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. METHODS: Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. RESULTS: We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. CONCLUSIONS: The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.

The Use of Herbal Medicines Among Cancer Patients.

Background and objective The use of herbal medicines has been increasing among cancer patients, as a way to control cancer and treatment-related symptoms; however, many patients are reluctant to disclose this use to their medical practitioners. The fact that oncological treatments have a narrow therapeutic margin, associated with the lack of control and clinical evidence concerning these supplements, makes medication-herbal interactions a reality. These interactions could lead to increased toxicity or a decreased effectiveness of oncological treatment. In light of this, we aimed to assess the prevalence of herbal medicine use in a patient population at a Portuguese central hospital: Centro Hospitalar Lisboa Ocidental. Materials and methods Patients with breast, prostate, or colorectal cancer diagnoses between August 2022 and July 2023 and undergoing oncological treatment were included. Data were collected through a survey during their first appointment, as well as by consulting the patients' clinical files. An interaction evaluation was carried out to assess potential medication-herbal interactions. Finally, a statistical analysis was performed to identify predictive factors for the use of herbal medicines. Results Among the 65 patients included in the study, 52% were females, and the median age of the cohort was 65 years. Breast cancer was the most prevalent diagnosis and the majority of the patients were undergoing palliative treatment. We found that 46% of patients used herbal medicines regularly: to strengthen the immune system, detoxification of the body, and treat insomnia and constipation. A medication-herbal interaction was found in 37% of the cases, the most frequent being doxorubicin-vitamin C, through an antioxidant mechanism. The univariable analysis failed to show any predictive factors associated with the use of herbal medicines. Conclusions This study sheds light on herbal medicine use among cancer patients and the reality of medication-herbal interactions. There is an urgent need for further research and evidence-based medical protocols regarding herbal medicine use, especially in complex cases such as cancer patients, to provide better and safer care.

Centrality measures in psychological networks: A simulation study on identifying effective treatment targets.

The network theory of psychopathology suggests that symptoms in a disorder form a network and that identifying central symptoms within this network might be important for an effective and personalized treatment. However, recent evidence has been inconclusive. We analyzed contemporaneous idiographic networks of depression and anxiety symptoms. Two approaches were compared: a cascade-based attack where symptoms were deactivated in decreasing centrality order, and a normal attack where symptoms were deactivated based on original centrality estimates. Results showed that centrality measures significantly affected the attack's magnitude, particularly the number of components and average path length in both normal and cascade attacks. Degree centrality consistently had the highest impact on the network properties. This study emphasizes the importance of considering centrality measures when identifying treatment targets in psychological networks. Further research is needed to better understand the causal relationships and predictive capabilities of centrality measures in personalized treatments for mental disorders.

PTI-801 (posenacaftor) shares a common mechanism with VX-445 (elexacaftor) to rescue p.Phe508del-CFTR.

The deletion of a phenylalanine at position 508 (p.Phe508del) in the CFTR anion channel is the most prevalent variant in people with Cystic Fibrosis (CF). This variant impairs folding and stability of the CF transmembrane conductance regulator (CFTR) protein, resulting in its defective trafficking and premature degradation. Over the last years, therapeutic accomplishments have been attained in developing small molecules that partially correct p.Phe508del-CFTR defects; however, the mechanism of action (MoA) of these compounds has only started to be uncovered. In this study, we employed biochemical, fluorescence microscopy, and functional assays to examine the efficacy and properties of PTI-801, a newly developed p.Phe508del-CFTR corrector. To exploit its MoA, we assessed PTI-801 effects in combination with low temperature, genetic revertants of p.Phe508del-CFTR (the in cis p.Val510Asp, p.Gly550Glu, p.Arg1070Trp, and 4RK) and other correctors. Our results demonstrated that PTI-801 rescues p.Phe508del-CFTR processing, PM trafficking, and channel function (upon agonist stimulation) with greater correction effects in combination with ABBV-2222, FDL-169, VX-661, or VX-809, but not with VX-445. Although PTI-801 exhibited no potentiator activity on low temperature- and corrector-rescued p.Phe508del-CFTR, this compound displayed similar behavior to that of VX-445 on genetic revertants. Such evidence associated with the lack of additivity when PTI-801 and VX-445 were combined indicates that they share a common binding site to correct p.Phe508del-CFTR defects. Despite the high efficacy of PTI-801 in combination with ABBV-2222, FDL-169, VX-661, or VX-809, these dual corrector combinations only partially restored p.Phe508del-CFTR conformational stability, as shown by the lower half-life of the mutant protein compared to that of WT-CFTR. In summary, PTI-801 likely shares a common MoA with VX-445 in rescuing p.Phe508del-CFTR, thus being a feasible alternative for the development of novel corrector combinations with greater capacity to rescue mutant CFTR folding and stability.