With the rapid development of the biopharmaceutical field, the efficient and simultaneous extraction of multiple biological components from biological samples has become a critical process for advancing scientific research. The ability to simultaneously extract various molecular components such as metabolites, DNA, RNA, and proteins is pivotal for multi-omics studies, which aim to comprehensively understand the molecular mechanisms of biological systems. Traditional methods often extract these components separately, leading to challenges such as sample loss, time consumption, contamination, and inconsistencies across different data types. In contrast, simultaneous extraction techniques address these issues by maintaining the consistency of each biological component’s physiological state, improving data reliability and facilitating integration across omic platforms. This review systematically summarizes recent advances in simultaneous extraction technologies, focusing on methods such as methanol/chloroform extraction, TRIzol reagent extraction, and modified Folch extraction, which have shown significant promise in improving the efficiency and integrity of biological sample preparation. These methods offer various advantages, such as reduced sample volume requirements, decreased contamination risk, and enhanced extraction consistency, which are crucial for studies involving small sample sizes or precious clinical specimens. Among these, methanol/chloroform extraction stands out for its simplicity, low cost, and ability to extract a wide range of biological molecules. However, it does face limitations, such as its inefficiency in extracting lipids and potential RNA contamination. On the other hand, the TRIzol reagent method has become a widely adopted technique due to its ability to simultaneously isolate RNA, proteins, and metabolites from the same sample. Despite its effectiveness, the TRIzol method has limitations in RNA quality, especially when handling complex samples or those with high protein content. Modified Folch extraction, which combines liquid-liquid extraction with commercial kits, offers a highly efficient way to extract polar metabolites, lipids, RNA, DNA, and proteins from small tissue samples. This method has proven advantageous in terms of extraction yield, especially for challenging or rare samples, although it requires precise handling to avoid cross-contamination between phases. The integration of automated platforms, microfluidics, and high-throughput systems is another exciting avenue for improving simultaneous extraction. Automation facilitates large-scale, reproducible sample processing with minimal human error, while microfluidics provides high precision in sample handling and enables real-time monitoring of extraction efficiency. These innovations not only enhance the speed and reproducibility of sample preparation but also open new possibilities for single-cell analysis, where sample volumes are often limited, and extraction efficiency is critical. In addition to the technical aspects, the review also highlights the importance of optimizing extraction protocols for specific sample types, such as clinical tissues, plants, and microorganisms. For example, the challenge of extracting multiple components from cancer tissues, where sample degradation and contamination risks are high, can be mitigated by carefully selecting extraction reagents and minimizing sample handling steps. Similarly, in plant studies, where metabolite diversity is vast, the simultaneous extraction methods must be optimized to account for the unique composition of plant tissues, which often include complex secondary metabolites and cell wall components. Looking forward, the development of more efficient and standardized simultaneous extraction methods will be crucial for advancing multi-omics research. There is a growing need for protocols that can be tailored to specific research needs, ensuring both reproducibility and flexibility in diverse applications. Additionally, combining these extraction methods with high-resolution analytical techniques such as mass spectrometry and next-generation sequencing will further enhance the potential of multi-omics studies to provide comprehensive insights into biological systems. As these technologies continue to evolve, their application in personalized medicine, environmental research, and agriculture holds great promise for addressing critical scientific challenges. In conclusion, while simultaneous extraction technologies have made significant strides, several challenges remain in optimizing extraction efficiency, ensuring reproducibility, and reducing costs. Future research should focus on refining extraction protocols, developing innovative extraction reagents, and expanding the scope of these methods to cater to a broader range of biological samples. Ultimately, the continued integration of these advanced techniques will revolutionize the way biological samples are prepared, analyzed, and understood in the context of multi-omics research.

With the rapid development of the biopharmaceutical field, the efficient and simultaneous extraction of multiple biological components from biological samples has become a critical process for advancing scientific research. The ability to simultaneously extract various molecular components such as metabolites, DNA, RNA, and proteins is pivotal for multi-omics studies, which aim to comprehensively understand the molecular mechanisms of biological systems. Traditional methods often extract these components separately, leading to challenges such as sample loss, time consumption, contamination, and inconsistencies across different data types. In contrast, simultaneous extraction techniques address these issues by maintaining the consistency of each biological component’s physiological state, improving data reliability and facilitating integration across omic platforms. This review systematically summarizes recent advances in simultaneous extraction technologies, focusing on methods such as methanol/chloroform extraction, TRIzol reagent extraction, and modified Folch extraction, which have shown significant promise in improving the efficiency and integrity of biological sample preparation. These methods offer various advantages, such as reduced sample volume requirements, decreased contamination risk, and enhanced extraction consistency, which are crucial for studies involving small sample sizes or precious clinical specimens. Among these, methanol/chloroform extraction stands out for its simplicity, low cost, and ability to extract a wide range of biological molecules. However, it does face limitations, such as its inefficiency in extracting lipids and potential RNA contamination. On the other hand, the TRIzol reagent method has become a widely adopted technique due to its ability to simultaneously isolate RNA, proteins, and metabolites from the same sample. Despite its effectiveness, the TRIzol method has limitations in RNA quality, especially when handling complex samples or those with high protein content. Modified Folch extraction, which combines liquid-liquid extraction with commercial kits, offers a highly efficient way to extract polar metabolites, lipids, RNA, DNA, and proteins from small tissue samples. This method has proven advantageous in terms of extraction yield, especially for challenging or rare samples, although it requires precise handling to avoid cross-contamination between phases. The integration of automated platforms, microfluidics, and high-throughput systems is another exciting avenue for improving simultaneous extraction. Automation facilitates large-scale, reproducible sample processing with minimal human error, while microfluidics provides high precision in sample handling and enables real-time monitoring of extraction efficiency. These innovations not only enhance the speed and reproducibility of sample preparation but also open new possibilities for single-cell analysis, where sample volumes are often limited, and extraction efficiency is critical. In addition to the technical aspects, the review also highlights the importance of optimizing extraction protocols for specific sample types, such as clinical tissues, plants, and microorganisms. For example, the challenge of extracting multiple components from cancer tissues, where sample degradation and contamination risks are high, can be mitigated by carefully selecting extraction reagents and minimizing sample handling steps. Similarly, in plant studies, where metabolite diversity is vast, the simultaneous extraction methods must be optimized to account for the unique composition of plant tissues, which often include complex secondary metabolites and cell wall components. Looking forward, the development of more efficient and standardized simultaneous extraction methods will be crucial for advancing multi-omics research. There is a growing need for protocols that can be tailored to specific research needs, ensuring both reproducibility and flexibility in diverse applications. Additionally, combining these extraction methods with high-resolution analytical techniques such as mass spectrometry and next-generation sequencing will further enhance the potential of multi-omics studies to provide comprehensive insights into biological systems. As these technologies continue to evolve, their application in personalized medicine, environmental research, and agriculture holds great promise for addressing critical scientific challenges. In conclusion, while simultaneous extraction technologies have made significant strides, several challenges remain in optimizing extraction efficiency, ensuring reproducibility, and reducing costs. Future research should focus on refining extraction protocols, developing innovative extraction reagents, and expanding the scope of these methods to cater to a broader range of biological samples. Ultimately, the continued integration of these advanced techniques will revolutionize the way biological samples are prepared, analyzed, and understood in the context of multi-omics research.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

OBJECTIVE: By analyzing the hormone secretion of the adenohypophysis, thyroid glands, gonads, and adrenal cortex in patients with hematological diseases before and after hematopoietic stem cell transplantation (HSCT), this study aims to preliminarily explore the effect of HSCT on patients' hormone secretion and glandular damage. METHODS: The baseline data of 209 hematological disease patients who underwent HSCT in our hospital from January 2019 to December 2023, as well as the data on the levels of hormones secreted by the adenohypophysis, thyroid glands, gonads and adrenal cortex before and after HSCT were collected, and the changes in hormone levels before and after transplantation were analyzed. RESULTS: After allogeneic HSCT, the levels of thyroid-stimulating hormone (TSH), triiodothyronine (T3), free triiodothyronine (FT3) and estradiol (E2) decreased, while the levels of luteinizing hormone (LH) and follicle- stimulating hormone (FSH) increased. The T3 level of patients with decreased TSH after transplantation was lower than that of those with increased TSH after transplantation. In female patients, the levels of prolactin (PRL), progesterone (Prog), and testosterone (Testo) decreased after HSCT. Testo and PRL decreased when there was a donor-recipient sex mismatch, and the levels of adrenocorticotropic hormone (ACTH) and cortisol (COR) decreased when the HLA matching was haploidentical. The levels of T3, FT3, and PRL decreased after autologous HSCT. In allogeneic HSCT patients, the levels of TSH, T4, T3, FT3, and ACTH in the group with graft-versus-host disease (GVHD) were significantly lower than those in the group without GVHD. Logistic regression analysis showed the changes in hormone levels after transplantation were not correlated with factors such as the patient's sex, age, or whether the blood types of the donor and the recipient are the same. CONCLUSION HSCT can affect the endocrine function of patients with hematological diseases, mainly affecting target glandular organs such as the thyroid, gonads, and adrenal glands, while the secretory function of the adenohypophysis is less affected.
Humans ; Hematopoietic Stem Cell Transplantation ; Female ; Male ; Hematologic Diseases/blood* ; Follicle Stimulating Hormone/blood* ; Triiodothyronine/blood* ; Luteinizing Hormone/blood* ; Thyroid Gland/metabolism* ; Estradiol/blood* ; Thyrotropin/blood* ; Gonads/metabolism* ; Adult ; Middle Aged ; Adrenocorticotropic Hormone/blood* ; Hormones/metabolism* ; Adrenal Cortex/metabolism* ; Prolactin

BACKGROUND: Double-stranded RNA-specific adenosine deaminase 1 (ADAR1) binds to double-stranded RNA and catalyzes the deamination of adenosine (A) to inosine (I). The functional mechanism of ADAR1 in non-small cell lung cancer (NSCLC) remains incompletely understood. This study aimed to investigate the prognostic significance of ADAR1 in NSCLC and to elucidate its potential role in regulating tumor cell proliferation and migration. METHODS: Data from The Cancer Genome Atlas (TCGA) and cBioPortal were analyzed to assess the correlation between high ADAR1 expression and clinicopathological features as well as prognosis in lung cancer. We performed Western blot (WB), cell proliferation assays, Transwell invasion/migration assays, and nude mouse xenograft modeling to examine the phenotypic changes and molecular mechanisms induced by ADAR1 knockdown. Furthermore, the ADAR1 p150 overexpression model was utilized to validate the proposed mechanism. RESULTS: ADAR1 expression was significantly elevated in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissues compared with adjacent non-tumor tissues (LUAD: P=3.70×10-15, LUSC: P=0.016). High ADAR1 expression was associated with poor prognosis (LUAD: P=2.03×10-2, LUSC: P=2.81×10-2) and distant metastasis (P=0.003). Gene Set Enrichment Analysis (GSEA) indicated that elevated ADAR1 was associated with mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathway activation, matrix metalloproteinase-9 (MMP-9) expression, and cell adhesion. ADAR1 and MMP-9 levels showed a strongly positive correlation (P=6.45×10-34) in 10 lung cancer cell lines, highest in H1581. Knockdown of ADAR1 in H1581 cells induced a rounded cellular morphology with reduced pseudopodia. Concomitantly, it suppressed cell proliferation, invasion, migration, and in vivo tumorigenesis. It also suppressed ERK phosphorylation and downregulated cellular Finkel-Biskis-Jinkins murine osteosarcoma viral oncogene homolog (c-FOS), MMP-9, N-cadherin, and Vimentin. Conversely, ADAR1 p150 overexpression in PC9 cells enhanced ERK phosphorylation and increased c-FOS and MMP-9 expression. CONCLUSIONS High ADAR1 expression is closely associated with poor prognosis and distant metastasis in NSCLC patients. Mechanistically, ADAR1 may promote proliferation, invasion, migration, and tumorigenesis in lung cancer cells via the ERK/c-FOS/MMP-9 axis.
Humans ; Lung Neoplasms/physiopathology* ; Adenosine Deaminase/genetics* ; Matrix Metalloproteinase 9/genetics* ; Cell Proliferation ; Carcinoma, Non-Small-Cell Lung/physiopathology* ; Cell Movement ; Animals ; Mice ; RNA-Binding Proteins/genetics* ; Female ; Male ; Cell Line, Tumor ; Proto-Oncogene Proteins c-fos/genetics* ; Middle Aged ; MAP Kinase Signaling System ; Gene Expression Regulation, Neoplastic ; Mice, Nude ; Extracellular Signal-Regulated MAP Kinases/genetics*

In the past 6 years, significant breakthroughs have been achieved in the treatment of heart failure (HF), especially in drug therapy. The classification of chronic HF and the treatment methods for HF and its complications are also constantly being updated. In order to apply these results to the diagnosis and treatment of patients with HF in China and further improve the level of diagnosis and treatment of HF in China, the HF Group of Chinese Society of Cardiology, Chinese Medical Association, Chinese College of Cardiovascular Physician, Chinese HF Association of Chinese Medical Doctor Association, and Editorial Board of Chinese Journal of Cardiology have organized an expert group and update the consensus and evidence-based treatment methods in the field of HF based on the latest clinical research findings at home and abroad, combined with the national conditions and clinical practice in China, and referring to the latest foreign HF guidelines while maintaining the basic framework of the 2018 Chinese Guidelines for Diagnosis and Treatment of HF.

OBJECTIVE: To examine the effectiveness of Chinese medicine (CM) Lianhua Qingwen Granule (LHQW) and Jingyin Gubiao Prescription (JYGB) in asymptomatic or mild patients with Omicron infection in the shelter hospital. METHODS: This single-center retrospective cohort study was conducted in the largest shelter hospital in Shanghai, China, from April 10, 2022 to May 30, 2022. A total of 56,244 asymptomatic and mild Omicron cases were included and divided into 4 groups, i.e., non-administration group (23,702 cases), LHQW group (11,576 cases), JYGB group (12,112 cases), and dual combination of LHQW and JYGB group (8,854 cases). The length of stay (LOS) in the hospital was used to assess the effectiveness of LHQW and JYGB treatment on Omicron infection. RESULTS: Patients aged 41-60 years, with nadir threshold cycle (C_T) value of N gene <25, or those fully vaccinated preferred to receive CM therapy. Before or after propensity score matching (PSM), the multiple linear regression showed that LHQW and JYGB treatment were independent influence factors of LOS (both P<0.001). After PSM, there were significant differences in LOS between the LHQW/JYGB combination and the other groups (P<0.01). The results of factorial design ANOVA proved that the LHQW/JYGB combination therapy synergistically shortened LOS (P=0.032). CONCLUSIONS Patients with a nadir C_T value <25 were more likely to accept CM. The LHQW/JYGB combination therapy could shorten the LOS of Omicron-infected individuals in an isolated environment.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Male ; Female ; Middle Aged ; Adult ; China/epidemiology* ; Hospitalization ; COVID-19 Drug Treatment ; COVID-19/epidemiology* ; SARS-CoV-2 ; Retrospective Studies ; Treatment Outcome ; Length of Stay ; Young Adult ; Aged