Research has established that trauma is nearly universal and a root cause of numerous health and social problems, including 6 of the 10 leading causes of death, with devastating consequences across the life course. Scientific evidence now recognizes the complex injurious nature of structural and historical trauma (i.e., racism, discrimination, sexism, poverty, and community violence). Meanwhile, many physicians and trainees grapple with their own trauma histories and face direct and secondary traumatization on the job. These findings substantiate the profound impact of trauma on the brain and body and why trauma training is critical to the education and practice of physicians. However, a critical lag remains in translating essential research insights into clinical teaching and care. Recognizing this gap, the National Collaborative on Trauma-Informed Health Care Education and Research (TIHCER) formed a task force charged with developing and validating a summary of core trauma-related knowledge and skills for physicians. In 2022, TIHCER released the first-ever validated set of trauma-informed care competencies for undergraduate medical education. The task force focused on undergraduate medical education so that all physicians would be taught these foundational concepts and skills from the outset of training, recognizing that faculty development is needed to achieve this goal. In this Scholarly Perspective, the authors offer a roadmap for implementation of trauma-informed care competencies starting with medical school leadership, a faculty-student advisory committee, and sample resources. Medical schools can use the trauma-informed care competencies as a scaffold to customize integration of curricular content (what is taught) and efforts to transform the learning and clinical environments (how it is taught). Using the lens of trauma will ground undergraduate medical training in the latest science about the pathophysiology of disease and provide a framework to address many of our greatest challenges, including health disparities and professional burnout. 

Roadmap for Trauma-Informed Medical Education: Introducing an Essential Competency Set

This study investigated the diarrhoea seasonality and its potential drivers as well as potential opportunities for future diarrhoea control and prevention in China. Data on weekly infectious diarrhoea cases in 31 provinces of China from 2005 to 2012, and data on demographic and geographic characteristics, as well as climatic factors, were complied. A cosinor function combined with a Poisson regression was used to calculate the three seasonal parameters of diarrhoea in different provinces. Regression tree analysis was used to identify the predictors of diarrhoea seasonality. Diarrhoea cases in China showed a bimodal distribution. Diarrhoea in children = 5 years peaked in summer. Latitude was significantly associated with spatial pattern of diarrhoea seasonality, with peak and trough times occurring earlier at high latitudes (northern areas), and later at low latitudes (southern areas). The annual amplitudes of diarrhoea in persons > = 5 years increased with latitude (r = 0.62, P<0.001). Latitude 27.8° N and 38.65° N were the latitudinal thresholds for diarrhoea seasonality in China. Regional-specific diarrhoea control and prevention strategies may be optimal for China. More attention should be paid to diarrhoea in children <5 years during fall-winter seasons.

Exploration of diarrhoea seasonality and its drivers in China

BACKGROUND
The current risk stratification system defined by clinicopathological features does not identify the risk of recurrence in early-stage (stage I-II) colorectal cancer (CRC) with sufficient accuracy. We aimed to investigate whether DNA methylation could serve as novel biomarkers for predicting prognosis in early-stage CRC patients.


METHODS
We analyzed the genome-wide methylation status of CpG loci using Infinium MethylationEPIC array run on primary tumor tissues and normal mucosa of early-stage CRC patients to identify potential methylation markers for prognosis. The machine learning approach was applied to construct a DNA methylation-based prognostic classifier for early-stage CRC (MePEC) using the 4 gene methylation markers, including FAT3, KAZN, TLE4, and DUSP3. The prognostic value of the classifier was evaluated in two independent cohorts (n = 438 and 359, respectively).


RESULTS
The comprehensive analysis identified an epigenetic subtype with high risk of recurrence based on a group of CpG loci in CpG-depleted region. In multivariate analysis, the MePEC classifier was independently and significantly associated with time to recurrence in the validation cohort one (HR 2.35, 95% CI 1.47-3.76, p < 0.001) and cohort two (HR 3.20, 95% CI 1.92-5.33, p < 0.001). All results were further confirmed after each cohort was stratified by clinicopathological variables and molecular subtypes.


CONCLUSIONS
We demonstrated the prognostic significance of DNA methylation profile in CpG-depleted region, which may serve as a valuable source for tumor biomarkers. MePEC could identify an epigenetic subtype with high risk of recurrence and improve the prognostic accuracy of current clinical variables in early-stage CRC.

DNA Methylation Profile in CpG-depleted Regions Uncovers a High-Risk Subtype of Early-stage Colorectal Cancer.

The initiation and progression of tumors are complex. The cancer evolution-development hypothesis holds that the dysregulation of immune balance is caused by the synergistic effect of immune genetic factors and environmental factors that stimulate and maintain non-resolving inflammation. Throughout the cancer development process, this inflammation creates a microenvironment for the evolution and development of cancer. Research on the inflammatory tumor microenvironment (TME) explains the initiation and progression of cancer and guides anti-cancer immunotherapy. Single-cell RNA sequencing (scRNA-seq) can detect the transcription levels of cells at the single-cell resolution level, reveal the heterogeneity and evolutionary trajectory of infiltrated immune cells and cancer cells, and provide insight into the composition and function of each cell group in the inflammatory TME. This paper summarizes the application of scRNA-seq in inflammatory TME.

/pdf/the-application-of-single-cell-rna-sequencing-in-the-1vdvbplo.pdf

The Application of Single-Cell RNA Sequencing in the Inflammatory Tumor Microenvironment

Abstract Objective In this study, based on PET/CT radiomics features, we developed and validated a nomogram to predict progression-free survival (PFS) for cases with diffuse large B cell lymphoma (DLBCL) treated with immunochemotherapy. Methods This study retrospectively recruited 129 cases with DLBCL. Among them, PET/CT scans were conducted and baseline images were collected for radiomics features along with their clinicopathological features. Radiomics features related to recurrence were screened for survival analysis using univariate Cox regression analysis with p &lt; 0.05. Next, a weighted Radiomics-score (Rad-score) was generated and independent risk factors were obtained from univariate and multivariate Cox regressions to build the nomogram. Furthermore, the nomogram was tested for their ability to predict PFS using time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results Blood platelet, Rad-score, and gender were included in the nomogram as independent DLBCL risk factors for PFS. We found that the training cohort areas under the curve (AUCs) were 0.79, 0.84, and 0.88, and validation cohort AUCs were 0.67, 0.83, and 0.72, respectively. Further, the DCA and calibration curves confirmed the predictive nomogram’s clinical relevance. Conclusion Using Rad-score, blood platelet, and gender of the DLBCL patients, a PET/CT radiomics-based nomogram was developed to guide cases’ recurrence risk assessment prior to treatment. The developed nomogram can help provide more appropriate treatment plans to the cases. Key Points • DLBCL cases can be classified into low- and high-risk groups using PET/CT radiomics based Rad-score. • When combined with other clinical characteristics (gender and blood platelet count), Rad-score can be used to predict the outcome of the pretreatment of DLBCL cases with a certain degree of accuracy. • A prognostic nomogram was established in this study in order to aid in assessing prognostic risk and providing more accurate treatment plans for DLBCL cases. 

https://link.springer.com/content/pdf/10.1007/s00330-022-09301-5.pdf

Development and validation of a [18F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients

Chronic inflammation is a prerequisite for the development of cancers. Here, we present the framework of a novel theory termed as Cancer Evolution-Development (Cancer Evo-Dev) based on the current understanding of inflammation-related carcinogenesis, especially hepatocarcinogenesis induced by chronic infection with hepatitis B virus. The interaction between genetic predispositions and environmental exposures, such as viral infection, maintains chronic non-resolving inflammation. Under the microenvironment of non-resolving inflammation, pro-inflammatory factors facilitate the generation of somatic mutations and viral mutations by inducing the imbalance between the mutagenic forces such as cytidine deaminases and mutation-correcting forces including uracil–DNA glycosylase. Most cells with somatic mutations and mutated viruses are eliminated in survival competition. Only a small percentage of mutated cells survive, adapt to the hostile environment, retro-differentiate, and function as cancer-initiating cells via altering signaling pathways. These cancer-initiating cells acquire stem-ness, reprogram metabolic patterns, and affect the microenvironment. The carcinogenic process follows the law of “mutation-selection-adaptation”. Cancer Evo-Dev not only help understand the mechanisms by which inflammation promotes the development of cancers, but also lays the foundation for specific prophylaxis and targeted therapy of various cancers.

Cancer Evo–Dev: A Theory of Inflammation-Induced Oncogenesis

Objective: This study aimed to analyze the epidemiology of infectious diarrhea in Yangpu district of Shanghai, from 2006 to 2015, and investigate the associations between meteorological factors and the incidence of infectious diarrhea. Methods: The epidemiological characteristics were analyzed by descriptive analysis, and the generalized additive model was employed to examine the association between meteorological variables and the incidence of infectious diarrhea. Results: A total of 3606 infectious diarrhea cases were reported. The average annual crude incidence rate was 33.20/105 and agestandardized incidence rate by world standard population was 63.36/105. Proportion of rotavirus infection accounted for 90.11% of infectious diarrhea cases in 0-4-year-old patients, whereas 56.92% of 5-year-old or older patients were infected with Vibrio. Monthly average maximum temperature below 6.38°C and above 24.59°C, minimum temperature below 5.12°C and above 24.03°C, and precipitation below 1.48 mm and above 7.40 mm had positive effects on the incidence of infectious diarrhea. Conclusion: High temperature and excess precipitation increase the incidence of infectious diarrhea caused by Vibrio parahemolyticus in 5-year-old or older people. Low temperature and little precipitation increase the incidence of infectious diarrhea caused by rotavirus in 0-4-year-old children. These findings might be references for the prophylaxis and control of infectious diarrhea in urban areas of developing world.

Impacts of Meteorological Factors on the Incidence of Infectious Diarrhea in Urban Shanghai, China

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Cancer Evo–Dev: A Theory of Inflammation-Induced Oncogenesis

Impacts of Meteorological Factors on the Incidence of Infectious Diarrhea in Urban Shanghai, China