Self-assembling dendrimer nanosystems for specific fluorine magnetic resonance imaging and effective theranostic treatment of tumors.

Fluorine magnetic resonance imaging (19F-MRI) is particularly promising for biomedical applications owing to the absence of fluorine in most biological systems. However, its use has been limited by the lack of safe and water-soluble imaging agents with high fluorine contents and suitable relaxation properties. We report innovative 19F-MRI agents based on supramolecular dendrimers self-assembled by an amphiphilic dendrimer composed of a hydrophobic alkyl chain and a hydrophilic dendron. Specifically, this amphiphilic dendrimer bears multiple negatively charged terminals with high fluorine content, which effectively prevented intra- and intermolecular aggregation of fluorinated entities via electrostatic repulsion. This permitted high fluorine nuclei mobility alongside good water solubility with favorable relaxation properties for use in 19F-MRI. Importantly, the self-assembling 19F-MRI agent was able to encapsulate the near-infrared fluorescence (NIRF) agent DiR and the anticancer drug paclitaxel for multimodal 19F-MRI and NIRF imaging of and theranostics for pancreatic cancer, a deadly disease for which there remains no adequate early detection method or efficacious treatment. The 19F-MRI and multimodal 19F-MRI and NIRF imaging studies on human pancreatic cancer xenografts in mice confirmed the capability of both imaging modalities to specifically image the tumors and demonstrated the efficacy of the theranostic agent in cancer treatment, largely outperforming the clinical anticancer drug paclitaxel. Consequently, these dendrimer nanosystems constitute promising 19F-MRI agents for effective cancer management. This study offers a broad avenue to the construction of 19F-MRI agents and theranostics, exploiting self-assembling supramolecular dendrimer chemistry.

Cargo-selective and adaptive delivery of nucleic acid therapeutics by bola-amphiphilic dendrimers.

Nucleic acid therapeutics are becoming an important drug modality, offering the unique opportunity to address "undruggable" targets, respond rapidly to evolving pathogens, and treat diseases at the gene level for precision medicine. However, nucleic acid therapeutics have poor bioavailability and are chemolabile and enzymolabile, imposing the need for delivery vectors. Dendrimers, by virtue of their well-defined structure and cooperative multivalence, represent precision delivery systems. We synthesized and studied bola-amphiphilic dendrimers for cargo-selective and on-demand delivery of DNA and small interfering RNA (siRNA), both important nucleic acid therapeutics. Remarkably, superior performances were achieved for siRNA delivery with the second-generation dendrimer, yet for DNA delivery with the third generation. We systematically studied these dendrimers with regard to cargo binding, cellular uptake, endosomal release, and in vivo delivery. Differences in size both of the dendrimers and their nucleic acid cargos impacted the cooperative multivalent interactions for cargo binding and release, leading to cargo-adaptive and selective delivery. Moreover, both dendrimers harnessed the advantages of lipid and polymer vectors, while offering nanotechnology-based tumor targeting and redox-responsive cargo release. Notably, they allowed tumor- and cancer cell-specific delivery of siRNA and DNA therapeutics for effective treatment in different cancer models, including aggressive and metastatic malignancies, outperforming the currently available vectors. This study provides avenues to engineer tailor-made vectors for nucleic acid delivery and precision medicine.

Seasonal meropenem resistance in Acinetobacter baumannii and influence of temperature-driven adaptation.

BACKGROUND: Recognition of seasonal trends in bacterial infection and drug resistance rates may enhance diagnosis, direct therapeutic strategies, and inform preventive measures. Limited data exist on the seasonal variability of Acinetobacter baumannii. We investigated the seasonality of A. baumannii, the correlation between temperature and meropenem resistance, and the impact of temperature on this bacterium. RESULTS: Meropenem resistance rates increased with lower temperatures, peaking in winter/colder months. Nonresistant strain detection exhibited temperature-dependent seasonality, rising in summer/warmer months and declining in winter/colder months. In contrast, resistant strains showed no seasonality. Variations in meropenem-resistant and nonresistant bacterial resilience to temperature changes were observed. Nonresistant strains displayed growth advantages at temperatures ≥ 25 °C, whereas meropenem-resistant A. baumannii with ß-lactamase OXA-23 exhibited greater resistance to low-temperature (4 °C) stress. Furthermore, at 4 °C, A. baumannii upregulated carbapenem resistance-related genes (adeJ, oxa-51, and oxa-23) and increased meropenem stress tolerance. CONCLUSIONS: Meropenem resistance rates in A. baumannii display seasonality and are negatively correlated with local temperature, with rates peaking in winter, possibly linked to the differential adaptation of resistant and nonresistant isolates to temperature fluctuations. Furthermore, due to significant resistance rate variations between quarters, compiling monthly or quarterly reports might enhance comprehension of antibiotic resistance trends. Consequently, this could assist in formulating strategies to control and prevent resistance within healthcare facilities.

Heterozygous Seryl-tRNA Synthetase 1 Variants Cause Charcot-Marie-Tooth Disease.

OBJECTIVE: Despite the increasing number of genes associated with Charcot-Marie-Tooth (CMT) disease, many patients currently still lack appropriate genetic diagnosis for this disease. Autosomal dominant mutations in aminoacyl-tRNA synthetases (ARSs) have been implicated in CMT. Here, we describe causal missense mutations in the gene encoding seryl-tRNA synthetase 1 (SerRS) for 3 families affected with CMT. METHODS: Whole-exome sequencing was performed in 16 patients and 14 unaffected members of 3 unrelated families. The functional impact of the genetic variants identified was investigated using bioinformatic prediction tools and confirmed using cellular and biochemical assays. RESULTS: Combined linkage analysis for the 3 families revealed significant linkage (Zmax LOD = 6.9) between the genomic co-ordinates on chromosome 1: 108681600-110300504. Within the linkage region, heterozygous SerRS missense variants segregated with the clinical phenotype in the 3 families. The mutant SerRS proteins exhibited reduced aminoacylation activity and abnormal SerRS dimerization, which suggests the impairment of total protein synthesis and induction of eIF2α phosphorylation. INTERPRETATION: Our findings suggest the heterozygous SerRS variants identified represent a novel cause for autosomal dominant CMT. Mutant SerRS proteins are known to impact various molecular and cellular functions. Our findings provide significant advances on the current understanding of the molecular mechanisms associated with ARS-related CMT. ANN NEUROL 2023;93:244-256.

Mitochondria-derived methylmalonic acid aggravates ischemia-reperfusion injury by activating reactive oxygen species-dependent ferroptosis.

Ferroptosis is a regulatory cell death process pivotal in myocardial ischemia-reperfusion (I/R) injury. However, the precise mechanism underlying myocardial ferroptosis remains less known. In this study, we investigated the pathophysiological mechanisms of methylmalonic acid (MMA) associated with ferroptosis activation in cardiomyocytes after I/R. We found an increase level of MMA in patients with acute myocardial injury after reperfusion and AC16 cells under hypoxia/reoxygenation (H/R) condition. MMA treatment was found to be associated with excessive oxidative stress in cardiomyocytes, leading to ferroptosis-related myocardial injury. In mice with I/R injury, MMA treatment aggravated myocardial oxidative stress and ferroptosis, which amplified the myocardial infarct size and cardiac dysfunction. Mechanistically, MMA promoted NOX2/4 expression to increase reactive oxygen species (ROS) production in cardiomyocytes, aggravating myocardial injury. Notably, the increased ROS further activated ferroptosis by inhibiting solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4) expression. In addition, MMA decreased the ectopic nuclear distribution of nuclear factor E2-related factor 2 (NRF2) by increasing the interaction between NRF2 and kelch-like ECH-associated protein 1 (KEAP1). This impeded the activation of GPX4/SLC7A11, downstream of NRF2, activating ferroptosis and aggravating myocardial cell injury. Collectively, our study indicates that MMA activates oxidative stress and ROS generation, which induces ferroptosis to exacerbate cardiomyocyte injury in an I/R model. These findings may provide a new perspective for the clinical treatment of I/R injury and warrant further investigation.

Photocatalytic Hydrosilylation over Pt@UiO-66-NH2: Enhanced Activity and Polymerization Kinetics.

Metal-organic frameworks (MOFs) have shown great research and application value in various types of hydrosilylation reactions. However, studies on photocatalysis-induced hydrosilylation using MOFs are extremely rare. Metal nanoparticles (MNPs)@MOFs are extensively studied for their excellent structural tunability and photocatalytic activity, but there are few reports on their application in photocatalytic hydrosilylation. Here, a novel photocatalyst consisting of platinum (Pt) nanoparticles immobilized in a MOF framework is synthesized and used for photocatalytic hydrosilylation. The effects of various factors on hydrosilylation conversion are investigated, including catalyst concentration, substrate ratio, and irradiation intensity. Furthermore, the photoreactivity of the synthesized Pt catalyst is evaluated in the presence of different concentrations of 2-chlorothixanthone as a photosensitizer. It is noteworthy that the conversion of the reaction increases with increasing catalyst concentration or photosensitizer concentration, whereas increasing the polymethylhydrosiloxane content does not lead to a significant increase in conversion. This study demonstrates the potential of MNPs@MOFs as efficient photocatalysts for photoinduced hydrosilylation reactions and paves the way for future applications in this area.

Leading in the development, standardised evaluation, and adoption of artificial intelligence in clinical practice: regional anaesthesia as an example.

A recent study by Suissa and colleagues explored the clinical relevance of a medical image segmentation metric (Dice metric) commonly used in the field of artificial intelligence (AI). They showed that pixel-wise agreement for physician identification of structures on ultrasound images is variable, and a relatively low Dice metric (0.34) correlated to a substantial agreement on subjective clinical assessment. We highlight the need to bring structure and clinical perspective to the evaluation of medical AI, which clinicians are best placed to direct.

Family factors related to adolescent screen media use and mental health outcomes: A systematic review and recommendation for practices.

INTRODUCTION: Screen media serves an essential role in adolescents' lives, posing growth opportunities and mental health challenges. Family plays a crucial role in mitigating these challenges. This systematic review offers a comprehensive analysis of the family factors related to adolescent screen media use and mental health. METHODS: A systematic search was conducted in PubMed, CINAHL, PsycINFO, Scopus, and Embase, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines using the following inclusion criteria: English, peer-reviewed, observational design, and published since 2013; adolescent samples aged 10-17 years; and examining screen media use, family factors, and internalizing problems. The role of family factors as predictors, moderators, and mediators was also examined. RESULTS: Of the 3587 records, 32 met the inclusion criteria. These studies, primarily cross-sectional, presented a global perspective of 14 countries. A heterogeneous range of family factors, screen media use, and mental health outcomes were examined, revealing significant associations between elevated screen media use and internalizing problems. Positive family processes and democratic media-specific parenting mitigate such association. A few studies underscored family socioeconomic status (SES), noting elevated screen media use and mental health risks among adolescents in families of low SES. CONCLUSIONS: Accumulating evidence supports the important role of positive family contexts in fostering balanced screen media use and mental health in adolescents, accentuating the need for professional screening and education to promote positive screen media use among adolescents and families. Further research requires refinement in measurement and methodology to better capture the intricate relationship between family dynamics, screen media use, and adolescent mental health.

[Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extensionDiretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI]. / Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.

A declaração SPIRIT 2013 tem como objetivo melhorar a integralidade dos relatórios dos protocolos de ensaios clínicos, fornecendo recomendações baseadas em evidências para o conjunto mínimo de itens que devem ser abordados. Essas orientações têm sido fundamentais para promover uma avaliação transparente de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence) é uma nova diretriz de relatório para protocolos de ensaios clínicos que avaliam intervenções com um componente de IA. Essa diretriz foi desenvolvida em paralelo à sua declaração complementar para relatórios de ensaios clínicos, CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 26 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão SPIRIT-AI inclui 15 itens novos que foram considerados suficientemente importantes para os protocolos de ensaios clínicos com intervenções que utilizam IA. Esses itens novos devem constar dos relatórios de rotina, juntamente com os itens básicos da SPIRIT 2013. A SPIRIT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA será integrada, considerações sobre o manuseio dos dados de entrada e saída, a interação humano-IA e a análise de casos de erro. A SPIRIT-AI ajudará a promover a transparência e a integralidade nos protocolos de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente o delineamento e o risco de viés de um futuro estudo clínico.

[Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extensionDiretrizes para relatórios de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão CONSORT-AI]. / Directrices para presentación de informes de ensayos clínicos sobre intervenciones con inteligencia artificial: extensión CONSORT-AI.

The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespread use has been instrumental in ensuring transparency in the evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes. The CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The CONSORT-AI extension includes 14 new items that were considered sufficiently important for AI interventions that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and provision of an analysis of error cases. CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.

A declaração CONSORT 2010 apresenta diretrizes mínimas para relatórios de ensaios clínicos randomizados. Seu uso generalizado tem sido fundamental para garantir a transparência na avaliação de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão CONSORT-AI (Consolidated Standards of Reporting Trials ­ Artificial Intelligence) é uma nova diretriz para relatórios de ensaios clínicos que avaliam intervenções com um componente de IA. Ela foi desenvolvida em paralelo à sua declaração complementar para protocolos de ensaios clínicos, a SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials ­ Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 29 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão CONSORT-AI inclui 14 itens novos que, devido à sua importância para as intervenções de IA, devem ser informados rotineiramente juntamente com os itens básicos da CONSORT 2010. A CONSORT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA está inserida, considerações sobre o manuseio dos dados de entrada e saída da intervenção de IA, a interação humano-IA e uma análise dos casos de erro. A CONSORT-AI ajudará a promover a transparência e a integralidade nos relatórios de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente a qualidade do desenho do ensaio clínico e o risco de viés nos resultados relatados.

Prefrontal GABAA(δ)R Promotes Fear Extinction through Enabling the Plastic Regulation of Neuronal Intrinsic Excitability.

Extinguishing the previously acquired fear is critical for the adaptation of an organism to the ever-changing environment, a process requiring the engagement of GABAA receptors (GABAARs). GABAARs consist of tens of structurally, pharmacologically, and functionally heterogeneous subtypes. However, the specific roles of these subtypes in fear extinction remain largely unexplored. Here, we observed that in the medial prefrontal cortex (mPFC), a core region for mood regulation, the extrasynaptically situated, δ-subunit-containing GABAARs [GABAA(δ)Rs], had a permissive role in tuning fear extinction in male mice, an effect sharply contrasting to the established but suppressive role by the whole GABAAR family. First, the fear extinction in individual mice was positively correlated with the level of GABAA(δ)R expression and function in their mPFC. Second, knockdown of GABAA(δ)R in mPFC, specifically in its infralimbic (IL) subregion, sufficed to impair the fear extinction in mice. Third, GABAA(δ)R-deficient mice also showed fear extinction deficits, and re-expressing GABAA(δ)Rs in the IL of these mice rescued the impaired extinction. Further mechanistic studies demonstrated that the permissive effect of GABAA(δ)R was associated with its role in enabling the extinction-evoked plastic regulation of neuronal excitability in IL projection neurons. By contrast, GABAA(δ)R had little influence on the extinction-evoked plasticity of glutamatergic transmission in these cells. Altogether, our findings revealed an unconventional and permissive role of extrasynaptic GABAA receptors in fear extinction through a route relying on nonsynaptic plasticity.SIGNIFICANCE STATEMENT The medial prefrontal cortex (mPFC) is one of the kernel brain regions engaged in fear extinction. Previous studies have repetitively shown that the GABAA receptor (GABAAR) family in this region act to suppress fear extinction. However, the roles of specific GABAAR subtypes in mPFC are largely unknown. We observed that the GABAAR-containing δ-subunit [GABAA(δ)R], a subtype of GABAARs exclusively situated in the extrasynaptic membrane and mediating the tonic neuronal inhibition, works oppositely to the whole GABAAR family and promotes (but does not suppress) fear extinction. More interestingly, in striking contrast to the synaptic GABAARs that suppress fear extinction by breaking the extinction-evoked plasticity of glutamatergic transmission, the GABAA(δ)R promotes fear extinction through enabling the plastic regulation of neuronal excitability in the infralimbic subregion of mPFC. Our findings thus reveal an unconventional role of GABAA(δ)R in promoting fear extinction through a route relying on nonsynaptic plasticity.

Integrated transcriptomics and metabolomics reveal protective effects on heart of hibernating Daurian ground squirrels.

Hibernating mammals are natural models of resistance to ischemia, hypoxia-reperfusion injury, and hypothermia. Daurian ground squirrels (spermophilus dauricus) can adapt to endure multiple torpor-arousal cycles without sustaining cardiac damage. However, the molecular regulatory mechanisms that underlie this adaptive response are not yet fully understood. This study investigates morphological, functional, genetic, and metabolic changes that occur in the heart of ground squirrels in three groups: summer active (SA), late torpor (LT), and interbout arousal (IBA). Morphological and functional changes in the heart were measured using hematoxylin-eosin (HE) staining, Masson staining, echocardiography, and enzyme-linked immunosorbent assay (ELISA). Results showed significant changes in cardiac function in the LT group as compared with SA or IBA groups, but no irreversible damage occurred. To understand the molecular mechanisms underlying these phenotypic changes, transcriptomic and metabolomic analyses were conducted to assess differential changes in gene expression and metabolite levels in the three groups of ground squirrels, with a focus on GO and KEGG pathway analysis. Transcriptomic analysis showed that differentially expressed genes were involved in the remodeling of cytoskeletal proteins, reduction in protein synthesis, and downregulation of the ubiquitin-proteasome pathway during hibernation (including LT and IBA groups), as compared with the SA group. Metabolomic analysis revealed increased free amino acids, activation of the glutathione antioxidant system, altered cardiac fatty acid metabolic preferences, and enhanced pentose phosphate pathway activity during hibernation as compared with the SA group. Combining the transcriptomic and metabolomic data, active mitochondrial oxidative phosphorylation and creatine-phosphocreatine energy shuttle systems were observed, as well as inhibition of ferroptosis signaling pathways during hibernation as compared with the SA group. In conclusion, these results provide new insights into cardio-protection in hibernators from the perspective of gene and metabolite changes and deepen our understanding of adaptive cardio-protection mechanisms in mammalian hibernators.

Multi-wavelength multi-direction laser light scattering for cell characterization using machine learning-based methods.

Cell identification and analysis play a crucial role in many biology- and health-related applications. The internal and surface structures of a cell are complex and many of the features are sub-micron in scale. Well-resolved images of these features cannot be obtained using optical microscopy. Previous studies have reported that the single-cell angular laser-light scattering patterns (ALSP) can be used for label-free cell identification and analysis. The ALSP can be affected by cell properties and the wavelength of the probing laser. Two cell properties, cell surface roughness and the number of mitochondria, are investigated in this study. The effects of probing laser wavelengths (blue, green, and red) and the directions of scattered light collection (forward, side, and backward) are studied to determine the optimum conditions for distinguishing the two cell properties. Machine learning (ML) analysis has been applied to ALSP obtained from numerical simulations. The results of ML analysis show that the backward scattering is the best direction for characterizing the surface roughness, while the forward scattering is the best direction for differentiating the number of mitochondria. The laser light having red or green wavelength is found to perform better than that having the blue wavelength in differentiating the surface roughness and the number of mitochondria. This study provides important insights into the effects of probing laser wavelength on gaining information about cells from their ALSP.

Antibiotic Pollution of Planktonic Ecosystems: A Review Focused on Community Analysis and the Causal Chain Linking Individual- and Community-Level Responses.

Antibiotic pollution has become one of the most challenging environmental issues in aquatic ecosystems, with adverse effects on planktonic organisms that occupy the base of the aquatic food chain. However, research regarding this topic has not been systematically reviewed, especially in terms of community-level responses. In this review, we provide an overview of current antibiotic pollution in aquatic environments worldwide. Then, we summarize recent studies concerning the responses of planktonic communities to antibiotics, ranging from individual- to community-level responses. Studies have shown that extremely high concentrations of antibiotics can directly harm the growth and survival of plankton; however, such concentrations are rarely found in natural freshwater. It is more likely that environmentally relevant concentrations of antibiotics will affect the physiological, morphological, and behavioral characteristics of planktonic organisms; influence interspecific interactions among plankton species via asymmetrical responses in species traits; and thus alter the structure and function of the entire planktonic ecosystem. This review highlights the importance of community analysis in revealing antibiotic toxicity. We also encourage the establishment of the causal relationships between impacts at multiple scales in the future for predicting the community-level consequences of antibiotics based on the currently available individual-level evidence.

Effect of Clostridium butyricum on the formation of primary choledocholithiasis based on intestinal microbiome and metabolome analysis.

AIMS: To investigate the function and probable mechanism of Clostridium butyricum in the development of choledocholithiasis. METHODS AND RESULTS: The lithogenic diet group and the lithogenic diet + C. butyricum group were used to develop the choledocholithiasis model. During the experiment, C. butyricum suspension was administered to the rats in the lithogenic diet + C. butyricum group. The findings demonstrated that the C. butyricum intervention decreased the Firmicutes/Bacteroidetes ratio in the colon of experimental animals given a lithogenic diet. The relative levels of Desulfovibrio (0.93%) and Streptococcus (0.38%) fell, whereas Lactobacillus (22.36%), Prevotella (14.09%), and bacteria that produce short-chain fatty acids increased. Finally, 68 distinct metabolic products were found based on nontargeted metabonomics, and 42 metabolic pathways associated to the various metabolites were enriched. CONCLUSIONS: We found that C. butyricum decreased the development of choledocholithiasis. It keeps the equilibrium of the rat's gut microbiome intact and lowers the danger of bacterial infections of the gastrointestinal and biliary systems. It is hypothesized that by controlling lipid metabolism, it may also have an impact on the development of cholelithiasis.

Production of biochar from squeezed liquid of fruit and vegetable waste: Impacts on soil N2O emission and microbial community.

The squeezed liquid from fruit and vegetable waste (LW) presents a unique wastewater challenge, marked by recalcitrance in treatment and amplified design risks with the application of conventional processes. Following coagulation of the squeezed liquid, the majority of particulate matter precipitates. The resulting precipitated floc (LWF) is reclaimed and subsequently utilized for the synthesis of biochar. The present study primarily explores the viability of repurposing LWF as biochar to enhance soil quality and mitigate N2O emissions. Findings indicate that the introduction of a 2% proportion of LWFB led to a remarkable 99.5% reduction in total N2O emissions in contrast to LWF. Concurrently, LWFB substantially enhanced nutrients content by elevating soil organic carbon (SOC) and nitrogen levels. Utilizing high-throughput sequencing in conjunction with qPCR, the investigation unveiled that the porous structure and substantial specific surface area of LWFB potentially fostered microbial adhesion and heightened diversity within the soil microbial community. Furthermore, LWFB notably diminished the relative abundance of AOB (Nitrosospira, Nitrosomonas), and NOB (Candidatus_Nitrotoga), thereby curbing the conversion of NH4+ into NO3-. The pronounced elevation in nosZ abundance implies that LWFB holds the potential to mitigate N2O emissions through a conversion to N2.

Methylmalonic acid, vitamin B12, and mortality risk in patients with preexisting coronary heart disease: a prospective cohort study.

BACKGROUND: The inconsistent relationship between Vitamin B12 (B12), methylmalonic acid (MMA, marker of B12 deficiency) and mortality was poorly understood, especially in patients with coronary heart disease (CHD). This study aims to investigate the association of serum MMA, and B12-related biomarkers (serum level, dietary intake, supplement use, and sensibility to B12) with all-cause and cardiovascular mortality in adults with CHD. METHODS: The data of this study were from a subcohort within the US National Health and Nutrition Examination Survey (NHANES). We included adults with preexisting CHD with serum MMA and B12, and dietary B12 intake measurements at recruitment. All participants were followed up until 31 December 2019. Weighted Cox proportional hazard regression was used to estimate hazard ratios (HR) and 95% CI of mortality risk. RESULTS: Overall, 1755 individuals (weighted mean [SE] age, 65.2 [0.5] years; 1047 men [weighted 58.5%]) with CHD were included, with geometric mean levels of serum MMA 182.4 nmol/L, serum B12 494.5 pg/ml, and dietary B12 intake 4.42 mg/day, and percentage of B12 supplements use 39.1%. During a median follow-up of 7.92 years, 980 patients died. Serum B12 concentration, dietary B12 intake and supplements use were not significantly associated with mortality risk (each p ≥ 0.388). In contrast, individuals in the top tertile of MMA had multivariable-adjusted HRs (95% CIs) of 1.70 (1.31-2.20) for all-cause mortality, and 2.00 (1.39-2.89) for cardiovascular mortality (both p trend < 0.001) compared to those in the bottom tertile of MMA. MMA-related mortality risk was particularly higher among participants with sufficient serum B12 (p < 0.001). CHD patients with increased levels of both MMA and B12 had a doubled mortality risk compared to those with lower MMA and B12 (p < 0.001). CONCLUSION: MMA accumulation but not serum or dietary vitamin B12 was associated with increased cardiovascular mortality risk among patients with CHD. This paradox may be related to decreased response to vitamin B12.

[Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extensionDiretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI]. / Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.

A declaração SPIRIT 2013 tem como objetivo melhorar a integralidade dos relatórios dos protocolos de ensaios clínicos, fornecendo recomendações baseadas em evidências para o conjunto mínimo de itens que devem ser abordados. Essas orientações têm sido fundamentais para promover uma avaliação transparente de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence) é uma nova diretriz de relatório para protocolos de ensaios clínicos que avaliam intervenções com um componente de IA. Essa diretriz foi desenvolvida em paralelo à sua declaração complementar para relatórios de ensaios clínicos, CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 26 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão SPIRIT-AI inclui 15 itens novos que foram considerados suficientemente importantes para os protocolos de ensaios clínicos com intervenções que utilizam IA. Esses itens novos devem constar dos relatórios de rotina, juntamente com os itens básicos da SPIRIT 2013. A SPIRIT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA será integrada, considerações sobre o manuseio dos dados de entrada e saída, a interação humano-IA e a análise de casos de erro. A SPIRIT-AI ajudará a promover a transparência e a integralidade nos protocolos de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente o delineamento e o risco de viés de um futuro estudo clínico.

[Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extensionDiretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI]. / Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.

A declaração SPIRIT 2013 tem como objetivo melhorar a integralidade dos relatórios dos protocolos de ensaios clínicos, fornecendo recomendações baseadas em evidências para o conjunto mínimo de itens que devem ser abordados. Essas orientações têm sido fundamentais para promover uma avaliação transparente de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence) é uma nova diretriz de relatório para protocolos de ensaios clínicos que avaliam intervenções com um componente de IA. Essa diretriz foi desenvolvida em paralelo à sua declaração complementar para relatórios de ensaios clínicos, CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 26 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão SPIRIT-AI inclui 15 itens novos que foram considerados suficientemente importantes para os protocolos de ensaios clínicos com intervenções que utilizam IA. Esses itens novos devem constar dos relatórios de rotina, juntamente com os itens básicos da SPIRIT 2013. A SPIRIT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA será integrada, considerações sobre o manuseio dos dados de entrada e saída, a interação humano-IA e a análise de casos de erro. A SPIRIT-AI ajudará a promover a transparência e a integralidade nos protocolos de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente o delineamento e o risco de viés de um futuro estudo clínico.

An Overview of Taste-Masking Technologies: Approaches, Application, and Assessment Methods.

It is well-known that plenty of active pharmaceutical ingredients (API) inherently possess an unpleasant taste, which influences the acceptance of patients, especially children. Therefore, manufacturing taste-masked dosage forms has attracted a lot of attention. This review describes in detail the taste-masking technologies based on the difference in the taste transmission mechanism which is currently available. In particular, the review highlights the application of various methods, with a special focus on how to screen the appropriate masking technology according to the properties of API. Subsequently, we overviewed how to assess taste-masking efficacy, guiding researchers to rationally design taste-masking formulations.