21st century critical care medicine:An overview

Critical care medicine in the 21st century has witnessed remarkable advancements that have significantly improved patient outcomes in intensive care units(ICUs).This abstract provides a concise summary of the latest developments in critical care,highlighting key areas of innovation.Recent advancements in critical care include Precision Medicine:Tailoring treatments based on individual patient characteristics,genomics,and biomarkers to enhance the effectiveness of therapies.The objective is to describe the recent advancements in Critical Care Medicine.Telemedicine:The integration of telehealth technologies for remote patient monitoring and consultation,facilitating timely interventions.Artificial intelligence(AI):AI-driven tools for early disease detection,predictive analytics,and treatment optimization,enhancing clinical decision-making.Organ Support:Advanced life support systems,such as Extracorporeal Membrane Oxygenation and Continuous Renal Replacement Therapy provide better organ support.Infection Control:Innovative infection control measures to combat emerging pathogens and reduce healthcare-associated infections.Ventilation Strategies:Precision ventilation modes and lung-protective strategies to minimize ventilatorinduced lung injury.Sepsis Management:Early recognition and aggressive management of sepsis with tailored interventions.Patient-Centered Care:A shift towards patient-centered care focusing on psychological and emotional wellbeing in addition to medical needs.We conducted a thorough literature search on PubMed,EMBASE,and Scopus using our tailored strategy,incorporating keywords such as critical care,telemedicine,and sepsis management.A total of 125 articles meeting our criteria were included for qualitative synthesis.To ensure reliability,we focused only on articles published in the English language within the last two decades,excluding animal studies,in vitro/molecular studies,and non-original data like editorials,letters,protocols,and conference abstracts.These advancements reflect a dynamic landscape in critical care medicine,where technology,research,and patient-centered approaches converge to improve the quality of care and save lives in ICUs.The future of critical care promises even more innovative solutions to meet the evolving challenges of modern medicine.

Model informed precision medicine of Chinese herbal medicines formulas-A multi-scale mechanistic intelligent model

Recent trends suggest that Chinese herbal medicine formulas(CHM formulas)are promising treatments for complex diseases.To characterize the precise syndromes,precise diseases and precise targets of the precise targets between complex diseases and CHM formulas,we developed an artificial intelligence-based quantitative predictive algorithm(DeepTCM).DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling,molecular and theoretical levels of traditional Chinese medicine(TCM).As an example,our model simulated the optimal CHM formulas for the treatment of coronary heart disease(CHD)with depression,and through model sensitivity analysis,we calculated the balanced scoring of the formulas.Furthermore,we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions.Finally,we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice.This novel multiscale model opened up a new avenue to combine“disease syndrome”and“macro micro”system modeling to facilitate translational research in CHM formulas.

Bronchoalveolar lavage fluid assessment facilitates precision medicine for lung cancer

Lung cancer is the most common and fatal malignant disease worldwide and has the highest mortality rate among tumor-related causes of death.Early diagnosis and precision medicine can significantly improve the survival rate and prognosis of lung cancer patients.At present,the clinical diagnosis of lung cancer is challenging due to a lack of effective non-invasive detection methods and biomarkers,and treatment is primarily hindered by drug resistance and high tumor heterogeneity.Liquid biopsy is a method for detecting circulating biomarkers in the blood and other body fluids containing genetic information from primary tumor tissues.Bronchoalveolar lavage fluid(BALF)is a potential liquid biopsy medium that is rich in a variety of bioactive substances and cell components.BALF contains information on the key characteristics of tumors,including the tumor subtype,gene mutation type,and tumor environment,thus BALF may be used as a diagnostic supplement to lung biopsy.In this review,the current research on BALF in the diagnosis,treatment,and prognosis of lung cancer is summarized.The advantages and disadvantages of different components of BALF,including cells,cell-free DNA,extracellular vesicles,and micro RNA are introduced.In particular,the great potential of extracellular vesicles in precision diagnosis and detection of drug-resistant for lung cancer is highlighted.In addition,the performance of liquid biopsies with different body fluid sources in lung cancer detection are compared to facilitate more selective studies involving BALF,thereby promoting the application of BALF for precision medicine in lung cancer patients in the future.

Matching traditional Chinese medicine and western medicine-based research:Advanced nutraceutical development for proactive gastric cancer prevention

Gastric cancer(GC),the third leading cause of cancer-related death globally,is complex and heterogeneous.This review explores multidisciplinary investigations of traditional Chinese medicine(TCM)combined with Western medical practices,emphasizing the development of nutraceuticals for cancer prevention.Using advanced analytical chemistry and food chemistry techniques,this study investigated how TCM components may be optimized for nutraceutical development.Focusing on molecular interactions with GC pathways,particularly the NF-κB,PI3K/Akt,and Wnt/β-catenin pathways,we examined the effects of TCM polyherbal formulas,extracts,and isolated compounds.These agents modulate apoptosis and cellular proliferation,underscoring their potential in preventive strategies.The convergence of nutraceutical and medicine food homology studies highlights a significant shift towards integrating TCM-derived compounds in a preventive health framework.This approach aims not only to enhance efficacy and reduce side effects but also to champion a preventive paradigm using personalized medicine to advance proactive health maintenance and disease prevention.The combination of TCM and western medical practices offers promising avenues for future research and practical applications in GC prevention.

Hepatitis B virus genotypes in precision medicine of hepatitis Brelated hepatocellular carcinoma:Where we are now

Hepatitis B virus(HBV)infection is a major player in chronic hepatitis B that may lead to the development of hepatocellular carcinoma(HCC).HBV genetics are diverse where it is classified into at least 9 genotypes(A to I)and 1 putative genotype(J),each with specific geographical distribution and possible different clinical outcomes in the patient.This diversity may be associated with the precision medicine for HBV-related HCC and the success of therapeutical approaches against HCC,related to different pathogenicity of the virus and host response.This Editorial discusses recent updates on whether the classification of HBV genetic diversity is still valid in terms of viral oncogenicity to the HCC and its precision medicine,in addition to the recent advances in cellular and molecular biology technologies.

Challenges and prospects in bridging precision medicine and artificial intelligence in genomic psychiatric treatment

Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical,genetic,environmental,and lifestyle factors to optimize medication management.This study investigates how artificial intelligence(AI)and machine learning(ML)can address key challenges in integrating pharmacogenomics(PGx)into psychiatric care.In this integration,AI analyzes vast genomic datasets to identify genetic markers linked to psychiatric conditions.AI-driven models integrating genomic,clinical,and demographic data demonstrated high accuracy in predicting treatment outcomes for major depressive disorder and bipolar disorder.This study also examines the pressing challenges and provides strategic directions for integrating AI and ML in genomic psychiatry,highlighting the importance of ethical considerations and the need for personalized treatment.Effective implementation of AI-driven clinical decision support systems within electronic health records is crucial for translating PGx into routine psychiatric care.Future research should focus on developing enhanced AI-driven predictive models,privacy-preserving data exchange,and robust informatics systems to optimize patient outcomes and advance precision medicine in psychiatry.

Integrating disulfidptosis-related long noncoding RNAs in colorectal cancer prognosis:A path to precision medicine

This commentary explores the burgeoning field of disulfidptosis-related long noncoding RNAs(lncRNAs)in the prognosis and therapeutic targeting of colorectal cancer(CRC).By evaluating recent research,including the pivotal study"Predicting colorectal cancer prognosis based on long noncoding RNAs of disulfidptosis genes"by Wang et al,this analysis underscores the critical role of lncRNAs in deciphering the molecular complexities of CRC.Highlighting the innovative methodologies and significant findings,I discuss the implications for patient survival,therapeutic response,and the potential of lncRNAs as biomarkers for precision medicine.The integration of bioinformatics,clinical databases,and molecular biology in these studies offers a promising avenue for advancing CRC treatment strategies and improving patient outcomes.

Re-evaluating the role of pelvic radiation in the age of modern precision medicine and systemic therapy

The efficacy of pelvic radiation in the management of locally advanced stage rectal cancer has come under scrutiny in the context of modern precision medicine and systemic therapy as evidenced by recent clinical trials such as FOWARC(J Clin Oncol 2019;37:3223-3233),NCT04165772(N Engl J Med 2022;386:2363-2376),and PROSPECT(N Engl J Med 2023;389:322-334).In this review,we comprehensively assess these pivotal trials and offer additional insights into the evolving role of pelvic radiation in contemporary oncology.

Genomic alterations and precise medicine of esophageal squamous cell carcinoma

Human cancer is a complex disease caused by the interaction of multiple genes and environmental factors.It is known that environmental factors such as smoking,drinking,and food carcinogens are implicated in the development of certain types of cancer including esophageal squamous cell carcinoma(ESCC).However,only a small portion of exposed individuals finally developed cancer,indicating that genetic makeup also plays an important role in the tumorigenesis.Genome-wide association studies(GWAS)have found numerous susceptible genes or loci for cancers,providing new ideas and directions for precision prevention and treatment of cancers.With the advances in the field of next-generation sequencing(NGS),the genomic landscapes of many types of human cancer have comprehensively been characterized.Here,we review the progresses of GWAS and NGS in revealing genomic variations of ESCC,one of the most common cancers in China,and discuss the potential applications of these results in precision medicine of ESCC.

Precision medicine in inflammatory bowel disease:Individualizing the use of biologics and small molecule therapies

The advent of biologics and small molecules in inflammatory bowel disease(IBD)has marked a significant turning point in the prognosis of IBD,decreasing the rates of corticosteroid dependence,hospitalizations and improving overall quality of life.The introduction of biosimilars has also increased affordability and enhanced access to these otherwise costly targeted therapies.Biologics do not yet represent a complete panacea:A subset of patients do not respond to first-line anti-tumor necrosis factor(TNF)-alpha agents or may subsequently demonstrate a secondary loss of response.Patients who fail to respond to anti-TNF agents typically have a poorer response rate to second-line biologics.It is uncertain which patient would benefit from a different sequencing of biologics or even a combination of biologic agents.The introduction of newer classes of biologics and small molecules may provide alternative therapeutic targets for patients with refractory disease.This review examines the therapeutic ceiling in current treatment strategies of IBD and the potential paradigm shifts in the future.

DNA methylation as a mediator of epigenetic regulation in the pathogenesis and precision medicine of osteoarthritis:An updated review

The pathophysiology of osteoarthritis(OA)is multifactorial,with the primary risk factors being obesity,age,environmental variables,and genetic predisposition.The available evidence suggests that genetic diversity does not adequately account for all clinical characteristics and heterogeneity of OA.Genetics has emerged as a nascent and crucial area of research in OA.The epigenetic module presents a potential link between genetic and environmental risk factors and the susceptibility and pathogenesis of OA.As a critical epigenetic alteration,DNA methylation has been shown to have an important role in the etiology of OA and is a viable biomarker for predicting disease progression and medication response,as shown in this research.This review aims to update knowledge in the field of DNA methylation associated with OA to better identify the essential features of OA subtypes and pathological conditions,hence accelerating individualized treatment and precision medicine.

How to establish precise proprietary Chinese medicine in post-marketing reappraisal?

The clinical efficacy and safety of proprietary Chinese medicine has become a more prevailing public health concern.The China Food and Drug Administration has pushed drug companies to conduct post-marketing reappraisal for proprietary Chinese medicine to provide additional evidence supporting the efficacy and safety of these medicine.In this paper,we propose a reappraisal protocol called“precise proprietary Chinese medicine”to precisely i)define the therapeutic aim;ii)design the protocol;iii)control the quality of proprietary Chinese medicine;iv)implement the protocol in the trial;v)study the mechanism-of-action of the proprietary Chinese medicine and vi)describe the indications of the proprietary Chinese medicine.We hope that these steps facilitate the post-marketing reappraisal of proprietary Chinese medicine.

Transcriptome analysis creates a new era of precision medicine for managing recurrent hepatocellular carcinoma

The high incidence of hepatocellular carcinoma(HCC)recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapies.Over the past few decades,the emergence of transcriptome analysis tools,including real-time quantitative reverse transcription PCR,microarrays,and RNA sequencing,has not only largely contributed to our knowledge about the pathogenesis of recurrent HCC but also led to the development of outcome prediction models based on differentially expressed gene signatures.In recent years,the single-cell RNA sequencing technique has revolutionized our ability to study the complicated crosstalk between cancer cells and the immune environment,which may benefit further investigations on the role of different immune cells in HCC recurrence and the identification of potential therapeutic targets.In the present article,we summarized the major findings yielded with these transcriptome methods within the framework of a causal model consisting of three domains:primary cancer cells;carcinogenic stimuli;and tumor microenvironment.We provided a comprehensive review of the insights that transcriptome analyses have provided into diagnostics,surveillance,and treatment of HCC recurrence.

Integration and implementation of precision medicine in the multifaceted inflammatory bowel disease

Inflammatory bowel disease(IBD)is a complex disease with variability in genetic,environmental,and lifestyle factors affecting disease presentation and course.Precision medicine has the potential to play a crucial role in managing IBD by tailoring treatment plans based on the heterogeneity of clinical and temporal variability of patients.Precision medicine is a population-based approach to managing IBD by integrating environmental,genomic,epigenomic,transcriptomic,proteomic,and metabolomic factors.It is a recent and rapidly developing medicine.The widespread adoption of precision medicine worldwide has the potential to result in the early detection of diseases,optimal utilization of healthcare resources,enhanced patient outcomes,and,ultimately,improved quality of life for individuals with IBD.Though precision medicine is promising in terms of better quality of patient care,inadequacies exist in the ongoing research.There is discordance in study conduct,and data collection,utilization,interpretation,and analysis.This review aims to describe the current literature on precision medicine,its multiomics approach,and future directions for its application in IBD.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB drugs.New strategies to facilitate drug combinations,including pharmacokinetics-guided dose optimization and toxicology studies of first-and second-line anti-TB drugs have also been introduced and recommended.Liquid chromatography-mass spectrometry(LC-MS)has arguably become the gold standard in the analysis of both endo-and exo-genous compounds.This technique has been applied successfully not only for therapeutic drug monitoring(TDM)but also for pharmacometabolomics analysis.TDM improves the effectiveness of treatment,reduces adverse drug reactions,and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window.Based on TDM,the dose would be optimized individually to achieve favorable outcomes.Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs,aiding in the discovery of potential biomarkers for TB diagnostics,treatment monitoring,and outcome evaluation.This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades.Besides,we discussed the advantages and disadvantages of this technique in practical use.The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted.Lastly,we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies(pharmacometrics,drug and vaccine developments,machine learning/artificial intelligence,among others)to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

Spastin and alsin protein interactome analyses begin to reveal key canonical pathways and suggest novel druggable targets

Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understanding the underlying disease-causing mechanisms and building solutions that have implications for a broad spectrum of patients. One potential solution is to develop personalized medicine approaches based on strategies that target the most prevalent cellular events that are perturbed in patients. Especially in patients with a known genetic mutation, it may be possible to understand how these mutations contribute to problems that lead to neurodegeneration. Protein–protein interaction analyses offer great advantages for revealing how proteins interact, which cellular events are primarily involved in these interactions, and how they become affected when key genes are mutated in patients. This line of investigation also suggests novel druggable targets for patients with different mutations. Here, we focus on alsin and spastin, two proteins that are identified as “causative” for amyotrophic lateral sclerosis and hereditary spastic paraplegia, respectively, when mutated. Our review analyzes the protein interactome for alsin and spastin, the canonical pathways that are primarily important for each protein domain, as well as compounds that are either Food and Drug Administration–approved or are in active clinical trials concerning the affected cellular pathways. This line of research begins to pave the way for personalized medicine approaches that are desperately needed for rare neurodegenerative diseases that are complex and heterogeneous.

From prediction to prevention:Machine learning revolutionizes hepatocellular carcinoma recurrence monitoring

In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular carcinoma(HCC),which is characterized by high incidence and mortality rates,remains a major global health challenge primarily due to the critical issue of postoperative recurrence.Early recurrence,defined as recurrence that occurs within 2 years posttreatment,is linked to the hidden spread of the primary tumor and significantly impacts patient survival.Traditional predictive factors,including both patient-and treatment-related factors,have limited predictive ability with respect to HCC recurrence.The integration of machine learning algorithms is fueled by the exponential growth of computational power and has revolutionized HCC research.The study by Zhang et al demonstrated the use of a groundbreaking preoperative prediction model for early postoperative HCC recurrence.Challenges persist,including sample size constraints,issues with handling data,and the need for further validation and interpretability.This study emphasizes the need for collaborative efforts,multicenter studies and comparative analyses to validate and refine the model.Overcoming these challenges and exploring innovative approaches,such as multi-omics integration,will enhance personalized oncology care.This study marks a significant stride toward precise,efficient,and personalized oncology practices,thus offering hope for improved patient outcomes in the field of HCC treatment.

Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

Background:Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs(ARLncRNAs)on the prognosis of hepatocellular carcinoma(HCC).Methods:We analyzed 371 HCC samples from TCGA,identifying expression networks of ARLncRNAs using autophagy-related genes.Screening for prognostically relevant ARLncRNAs involved univariate Cox regression,Lasso regression,and multivariate Cox regression.A Nomogram was further employed to assess the reliability of Riskscore,calculated from the signatures of screened ARLncRNAs,in predicting outcomes.Additionally,we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis,using consensus clustering to identify subgroups related to ARLncRNAs.Results:The screening process identified 27 ARLncRNAs,with 13 being associated with HCC prognosis.Consequently,a set of signatures comprising 8 ARLncRNAs was successfully constructed as independent prognostic factors for HCC.Patients in the high-risk group showed very poor prognoses in most clinical categories.The Riskscore was closely related to immune cell scores,such as macrophages,and the DEGs between different groups were implicated in metabolism,cell cycle,and mitotic processes.Notably,high-risk group patients demonstrated a significantly lower IC50 for Paclitaxel,suggesting that Paclitaxel could be an ideal treatment for those at elevated risk for HCC.We further identified C2 as the Paclitaxel subtype,where patients exhibited higher Riskscores,reduced survival rates,and more severe clinical progression.Conclusion:The 8 signatures based on ARLncRNAs present novel targets for prognostic prediction in HCC.The drug candidate Paclitaxel may effectively treat HCC by impacting ARLncRNAs expression.With the identification of ARLncRNAsrelated isoforms,these results provide valuable insights for clinical exploration of autophagy mechanisms in HCC pathogenesis and offer potential avenues for precision medicine.

Brain abscess from oral microbiota approached by metagenomic next-generation sequencing: A case report and review of literature

BACKGROUND Brain abscess is a serious and potentially fatal disease caused primarily by microbial infection.Although progress has been made in the diagnosis and treatment of brain abscesses,the diagnostic timeliness of pathogens needs to be improved.CASE SUMMARY We report the case of a 54-year-old male with a brain abscess caused by oral bacteria.The patient recovered well after receiving a combination of metagenomic next-generation sequencing(mNGS)-assisted guided medication and surgery.CONCLUSION Therefore,mNGS may be widely applied to identify the pathogenic microor-ganisms of brain abscesses and guide precision medicine.

Identification of clinical subphenotypes of sepsis after laparoscopic surgery

Objective:Some patients exhibit septic symptoms following laparoscopic surgery,leading to a poor prognosis.Effective clinical subphenotyping is critical for guiding tailored therapeutic strategies in these cases.By identifying predisposing factors for postoperative sepsis,clinicians can implement targeted interventions,potentially improving outcomes.This study outlines a workflow for the subphenotype methodology in the context of laparoscopic surgery,along with its practical application.Methods:This study utilized data routinely available in clinical case systems,enhancing the applicability of our findings.The data included vital signs,such as respiratory rate,and laboratory measures,such as blood sodium levels.The process of categorizing clinical routine data involved technical complexities.A correlation heatmap was used to visually depict the relationships between variables.Ordering points were used to identify the clustering structure and combined with Consensus K clustering methods to determine the optimal categorization.Results:Our study highlighted the intricacies of identifying clinical subphenotypes following laparoscopic surgery,and could thus serve as a valuable resource for clinicians and researchers seeking to explore disease heterogeneity in clinical settings.By simplifying complex methodologies,we aimed to bridge the gap between technical expertise and clinical application,fostering an environment where professional medical knowledge is effectively utilized in subphenotyping research.Conclusion:This tutorial could primarily serve as a guide for beginners.A variety of clustering approaches were explored,and each step in the process contributed to a comprehensive understanding of clinical subphenotypes.