Objective To analyze the epidemiological characteristics and disease burden of liver cancer in Guangdong Province in 2020, and to provide a scientific foundation for the development of regionalized prevention and control strategies for liver cancer. Methods According to the cancer registry data of Guangdong Province, the incidence, mortality and age-standardized rate by Chinese standard population in 2020 were calculated to analyze the epidemiological characteristics of liver cancer. The disability adjusted life years (DALYs), year of life loss (YLL), year of lived with disability (YLD), and cause-eliminated life expectancy were used to assess the disease burden of liver cancer. Results In 2020, the crude incidence rate and the age-standardized incidence rate of liver cancer in Guangdong Province were 27.79/100 000 and 20.84/100 000，respectively, and the crude mortality rate and the age-standardized mortality rate of liver cancer were 25.49/100,000 and 17.64/100 000, respectively. The total DALY and DALY rate of liver cancer in Guangdong Province were 515 311 person-years and 513.83/100 000, respectively. After eliminating the causes of death from liver cancer, the life expectancy in Guangdong Province increased from 84.60 years to 84.99 years. All indicators consistently demonstrated that the burden of liver cancer was higher in males than that in females, and the burden of liver cancer was higher in rural areas than that in urban areas. Conclusion Liver cancer in Guangdong Province exhibits a high incidence, mortality and disease burden level in 2020. There are obvious differences of gender, age and region in cancer burden. It is necessary to strengthen liver cancer screening and diagnosis and treatment in men, the elderly and those in rural areas to reduce the burden of liver cancer gradually in Guangdong Province.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

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.

Background: Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Methods: Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35–40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. Results: In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Conclusions Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.

The medicinal use of Malvae Semen has a long history. In this paper， by consulting the ancient materia medica， prescription， agronomy， literature and other aspects of the classics， the name， origin， evolution of scientific name， quality， harvesting and processing， functions and indications and others of Malvae Semen were systematically sorted out and verified， so as to provide a basis for the development and utilization of famous classical formulas containing this herb. According to the textual research， Shennong Bencaojing began to use Dongkuizi as the correct name， which was used in the past dynasties， and there were also aliases such as Kuicaizi， Huacai， and Kuizi. Through the original research， it can be seen that Kuicai is the mainstream original plant of Malvae Semen， that is， Malva verticillata var. crispa， the Alcea rosea and M. cathayensis are also used. In modern times， the seeds of Abutilon theophrasti have been passed off as Malvae Semen， while the seeds of M. verticillata var. crispa have rarely been used in medicine. And Abutili Semen has been another medicinal material with different efficacy since the collection of Newly Revised Materia Medica in the Tang dynasty. Since the Ming and Qing dynasties， the cultivation of Kuicai has been decreasing， while A. theophrasti is more common and easy to obtain， and Abutili Semen and Malvae Semen are similar in morphology and confused， which should be corrected. In addition， Malvae Fructus is a Mongolian customary medicinal herb， which is different from the traditional use of seeds in traditional Chinese medicine. Kuicai， as an important vegetable in history， was widely cultivated and gradually shrunk after the Song dynasty， it is now mainly produced in southern provinces. The quality evaluation of Malvae Semen is better for those with dry bodies， full grain， grayish brown color， no mud， and no impurities. The harvesting is generally in the autumn and winter. After drying， it is seeded， sieved peel and impurities， mashed， or slightly stir-fried to yellow-white color with gentle fire. It is sweet， cold and slippery in nature and taste， with the main effects of laxation， diuresis， lactation and elimination of swelling. The efficacy of Abutili Semen is clearing heat and removing toxicity， promoting diuresis and removing nebula， the efficacy is quite different from that of Malvae Semen. Based on the results of textual research， it is suggested that M. verticillata var. crispa should be used as the medicinal source of Malvae Semen in the development of famous classical formulas， the corresponding processing methods should be selected according to the requirements of drug processing in the formulas， while the raw products are recommended to be used if the processing is not specified.

The medicinal use of Malvae Semen has a long history. In this paper， by consulting the ancient materia medica， prescription， agronomy， literature and other aspects of the classics， the name， origin， evolution of scientific name， quality， harvesting and processing， functions and indications and others of Malvae Semen were systematically sorted out and verified， so as to provide a basis for the development and utilization of famous classical formulas containing this herb. According to the textual research， Shennong Bencaojing began to use Dongkuizi as the correct name， which was used in the past dynasties， and there were also aliases such as Kuicaizi， Huacai， and Kuizi. Through the original research， it can be seen that Kuicai is the mainstream original plant of Malvae Semen， that is， Malva verticillata var. crispa， the Alcea rosea and M. cathayensis are also used. In modern times， the seeds of Abutilon theophrasti have been passed off as Malvae Semen， while the seeds of M. verticillata var. crispa have rarely been used in medicine. And Abutili Semen has been another medicinal material with different efficacy since the collection of Newly Revised Materia Medica in the Tang dynasty. Since the Ming and Qing dynasties， the cultivation of Kuicai has been decreasing， while A. theophrasti is more common and easy to obtain， and Abutili Semen and Malvae Semen are similar in morphology and confused， which should be corrected. In addition， Malvae Fructus is a Mongolian customary medicinal herb， which is different from the traditional use of seeds in traditional Chinese medicine. Kuicai， as an important vegetable in history， was widely cultivated and gradually shrunk after the Song dynasty， it is now mainly produced in southern provinces. The quality evaluation of Malvae Semen is better for those with dry bodies， full grain， grayish brown color， no mud， and no impurities. The harvesting is generally in the autumn and winter. After drying， it is seeded， sieved peel and impurities， mashed， or slightly stir-fried to yellow-white color with gentle fire. It is sweet， cold and slippery in nature and taste， with the main effects of laxation， diuresis， lactation and elimination of swelling. The efficacy of Abutili Semen is clearing heat and removing toxicity， promoting diuresis and removing nebula， the efficacy is quite different from that of Malvae Semen. Based on the results of textual research， it is suggested that M. verticillata var. crispa should be used as the medicinal source of Malvae Semen in the development of famous classical formulas， the corresponding processing methods should be selected according to the requirements of drug processing in the formulas， while the raw products are recommended to be used if the processing is not specified.

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 develop a machine learning model integrating preoperative chest CT radiomic features with clinical data for predicting 5-year postoperative recurrence risk in stage Ⅰ non-small cell lung cancer(NSCLC)patients undergoing surgical resection.Methods A total of 217 patients with pathologically confirmed stage Ⅰ NSCLC(selected from 778 initially screened cases based on our inclusion and exclusion criteria)treated in Army Medical Center of PLA between January 2014 and December 2019 were retrospectively enrolled,including 53 recurrence cases and 164 non-recurrence cases within 5-year follow-up.They were randomly divided into a training set(n=173)and a validation set(n=44)in a ratio of 8:2.Radiomic models were established based on extracted features from tumor-dominant regions of interest(ROI)on CT images,while clinical models were developed using demographic characteristics and preoperative laboratory examinations.A combined model was further constructed by integrating both feature sets,and model performance was compared to identify the optimal predictive model.Results This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model.Among 6 machine learning algorithms,the adaptive boosting(Adaboost)model demonstrated the best overall predictive performance,with an area under the curve(AUC)of 0.866(95%CI:0.808～0.923;accuracy:0.832,specificity:0.884)in the training set and of 0.806(95%CI:0.630～0.983;accuracy:0.795,specificity:0.971)in the validation set.Univariate and multivariate logistic regression analyses identified 4 clinical features for clinical model construction.The clinical model achieved an AUC value of 0.874(95%CI:0.821～0.928;accuracy:0.827,specificity:0.891)in the training set and 0.813(95%CI:0.677～0.948;accuracy:0.636,specificity:0.600)in the validation set.By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy,the combined model exhibited further improved predictive performance,with an AUC value of 0.953(95%CI:0.924～0.983;accuracy:0.884,specificity:0.860)and 0.852(95%CI:0.729～0.976;accuracy:0.682,specificity:0.629),respectively in the training set and the validation set.Conclusion The combined model integrating preoperative CT radiomic features with clinical risk factors may provide an evidence-based framework for evaluating 5-year postoperative recurrence risk in stage Ⅰ NSCLC patients.

Objective To evaluate the predictive value of triglyceride-glucose body mass index(TyG-BMI),atherogenic index of plasma(AIP),and postprandial glucose excursion(PPGE)for sarcopenia in patients with type 2 diabetes mellitus(T2DM).Methods An observational cohort trial was conducted on 590 hospitalized T2DM patients(322 males and 268 females)admitted to Department of Endocrinology of the First Affiliated Hospital of Chongqing Medical University between January 2023 and December 2024.General demographic data and key metabolic indicators,including fasting plasma glucose(FPG),postprandial 2-hour plasma glucose(PPG),triglyceride(TG)were collected,and then TyG-BMI,AIP,and PPGE were calculated.Based on the Asian Working Group for Sarcopenia(AWGS)2019 criteria,they were divided into a sarcopenia group(n=140)and a non-sarcopenia group(n=450).After 1∶1 propensity score matching(PSM),102 patients with sarcopenia were matched with 102 without.Differences in metabolic indicators FPG,PPG,TyG-BMI,AIP and PPGE were compared between the 2 groups.Spearman correlation analysis was conducted to assess correlations of these indicators with sarcopenia.Conditional logistic regression analysis was performed to identify independent risk factors,and receiver operating characteristic(ROC)curves were plotted to assess predictive performance.An external validation cohort consisting of 192 T2DM patients from Department of Endocrinology of Jiangbei Branch of First Affiliated Hospital of Army Medical University between January 2023 and December 2024 was included to validate the prediction model.Results After PSM,the baseline data of the 2 groups was balanced(P>0.05).The sarcopenia group showed higher levels of PPG,AIP,and PPGE,but lower TyG-BMI value than the non-sarcopenia group(all P=0.001).Spearman correlation analysis revealed that the TyG-BMI was negatively correlated(r=-0.404,P=0.001),whereas AIP and PPGE were positively correlated with concomitant sarcopenia(r=0.280,P=0.001;r=0.372,P=0.001)in the T2DM patients.Conditional logistic regression analysis identified AIP(OR=14.367)and PPGE(OR=1.245)as independent risk factors,while TyG-BMI(OR=0.966)as independent protective factors.ROC curve analysis revealed that the area under the curve(AUC)of the combined model of TyG-BMI,AIP and PPGE in predicting sarcopenia was 0.918,and the AUC value was 0.954 in external validation,with good sensitivity and specificity.Conclusion TyG-BMI,AIP,and PPGE are important metabolic predictors in T2DM patients with sarcopenia.Their combination has good screening value for sarcopenia,and can be applied in external prediction for T2DM patients.