This paper aimed to systematically evaluate the effects of hypoxic training at different fraction of inspired oxygen (FiO₂) on body composition, glucose metabolism, and lipid metabolism in obese individuals, and to determine the optimal oxygen concentration range to provide scientific evidence for personalized and precise hypoxic exercise prescriptions. A systematic search was conducted in the Cochrane Library, PubMed, Web of Science, Embase, and CNKI databases for randomized controlled trials and pre-post intervention studies published up to March 31, 2025, involving hypoxic training interventions in obese populations. Meta-analysis was performed using RevMan 5.4 software to assess the effects of different fraction of inspired oxygen (FiO₂≤14% vs. FiO₂>14%) on BMI, body fat percentage, waist circumference, fasting blood glucose, insulin, HOMA-IR, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), with subgroup analyses based on oxygen concentration. A total of 22 studies involving 292 participants were included. Meta-analysis showed that hypoxic training significantly reduced BMI (mean difference (MD)=-2.29,95%CI: -3.42 to -1.17, P<0.000 1), body fat percentage (MD=-2.32, 95%CI: -3.16 to -1.47, P<0.001), waist circumference (MD=-3.79, 95%CI: -6.73 to -0.85, P=0.01), fasting blood glucose (MD=-3.58, 95%CI: -6.23 to -0.93, P=0.008), insulin (MD=-1.60, 95%CI: -2.98 to -0.22, P=0.02), TG (MD=-0.18, 95%CI: -0.25 to -0.12, P<0.001), and LDL-C (MD=-0.25, 95%CI: -0.39 to -0.11, P=0.000 3). Greater improvements were observed under moderate hypoxic conditions with FiO₂>14%. Changes in HOMA-IR (MD=-0.74, 95%CI: -1.52 to 0.04,P=0.06) and HDL-C (MD=-0.09, 95%CI: -0.21 to 0.02, P=0.11) were not statistically significant. Hypoxic training can significantly improve body composition, glucose metabolism, and lipid metabolism indicators in obese individuals, with greater benefits observed under moderate hypoxia (FiO>14%). As a key parameter in hypoxic exercise interventions, the precise setting of oxygen concentration is crucial for optimizing intervention outcomes.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

In recent years, the prevalence of diabetes has continued to rise, with diabetes mellitus type 2 (T2DM) being the most common form. T2DM is characterized by chronic low-grade inflammation and disruptions in insulin metabolism. Toll-like receptor 4 (TLR4) is a key pattern recognition receptor that, upon activation, upregulates pro-inflammatory cytokines via the nuclear factor κB (NF‑κB) pathway, thereby contributing to the pathogenesis of T2DM. Peripheral 5-hydroxytryptamine (5-HT), primarily synthesized by enterochromaffin (EC) cells in the gut, interacts with 5-hydroxytryptamine receptors (5-HTRs) in key insulin-target tissues, including the liver, adipose tissue, and skeletal muscle. This interaction influences hepatic gluconeogenesis, fat mobilization, and the browning of white adipose tissue. Elevated peripheral 5-HT levels may disrupt glucose and lipid metabolism, thereby contributing to the onset and progression of T2DM. Within mitochondria, 5-HT undergoes degradation and inactivation through the enzymatic action of monoamine oxidase A (MAO-A), leading to the generation of reactive oxygen species (ROS). Excessive ROS production and accumulation can induce oxidative stress, which may further contribute to the pathogenesis of T2DM. Platelets serve as the primary reservoir for5-HT in the bloodstream. The activation of the TLR4 signaling pathway on the platelet surface, coupled with reduced expression of the 5-HT transporter on the cell membrane, leads to elevated serum 5-HT levels, potentially accelerating the progression of T2DM. Therefore, inhibition of TLR4 and reduction of peripheral 5-HT levels could represent promising therapeutic strategies for T2DM. This review explores the synthesis, transport, and metabolism of peripheral 5-HT, as well as its role in TLR4-mediated T2DM, with the aim of providing novel insights into the clinical diagnosis, treatment, and evaluation of T2DM.

The Expert Consensus on the Deployment of DeepSeek in Medical Institutions serves as a detailed guideline for the deployment of DeepSeek in medical institutions. It was developed by experts in the fields of healthcare， hospital management， medical information， health policy， law， and medical ethics from nearly 30 leading domestic medical and academic research institutions， based on relevant domestic and international laws and regulations as well as the practices of medical institutions. It aims to provide medical institutions with a scientific， standardized， and secure deployment guideline to ensure that the application of artificial intelligence （AI） technologies in healthcare， including but not limited to DeepSeek， conforms to the unique characteristics of the healthcare industry and effectively promotes the improvement of medical service levels. From the three aspects of pre-deployment evaluation， deployment implementation， and post-deployment management and monitoring， the key factors that medical institutions should consider when introducing DeepSeek were elaborated in detail， including medical demand compatibility， technical capabilities and infrastructure， legal and ethical risks， data preparation and management， model selection and optimization， system integration and training， performance monitoring and continuous optimization， risk management and emergency response， as well as compliance review and evaluation. This provides a comprehensive deployment framework for medical institutions to ensure the safety and effectiveness of technology applications.

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: 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 analyze and summarize the clinical and pathological characteristics, management, and efficacy of patients with vulvar lichen sclerosus (VLS) through a single center large sample study, and preliminarily to explore the frequency of maintenance treatment medication for VLS. Methods: The clinical data of VLS patients in Obstetrics and Gynecology Hospital of Fudan University from 2018 to 2021 were retrospectively collected. The clinicopathological characteristics (patients' age, course of disease, complicated disease history, family history, symptoms, signs and pathology), treatment and effects were retrospectively analyzed. The patients in the maintenance treatment stage were followed up regularly to explore the minimum frequency of individual medication to maintain the stability of the disease. Results: (1) General situation: a total of 345 patients with VLS were included in this study. The average age was (50.4±14.7) years (ranged from 8 to 84 years old), prevalence was highest in the 50-59 years group (30.1%, 104/345). Immune diseases occurred in 18.6% (33/177) of patients, 24.3% (43/177) of patients had allergic skin diseases, and 5.6% (10/177) of the patients' immediate family members had chronic vulvar pruritus or vulvar hypopigmentation. (2) Clinical features: the most common symptom was vulvar pruritus (96.1%, 196/204) among 204 patients with recorded symptoms. The most common sign was hypopigmentation of the vulva (96.3%, 206/214). The most common involved sites were labia minora (70.3%, 142/202), labia majora (67.8%, 137/202), and labial sulcus (59.4%, 120/202). The cumulative number of sites involved in 62 vulvar atrophy patients (2.7±1.1) was significantly higher than that in 152 non-atrophy patients (2.2±1.0; t=3.48, P=0.001). The course of vulvar atrophy was (9.3±8.5) years, which was significantly longer than that of non-atrophy patients [(6.6±5.6) years; t=2.04, P=0.046]. (3) Pathological features: among the 286 patients with electronic pathological sections, the most common pathological feature in the epidermis was epithelial nail process passivation (71.3%, 204/286). The common pathological features in the dermis were interstitial collagenization (84.6%, 242/286), and inflammatory cell infiltration (73.8%, 211/286). (4) Treatment: 177 patients received standardized treatment after diagnosis and were followed up regularly in our hospital. In the initial treatment stage, 26.0% (46/177) of the patients were treated with 0.05% clobetasol propionate cream, and 74.0% (131/177) of the patients were treated with 0.1% mometasone furoate ointment. The complete remission rates of the two methods were respectively 80.4% (37/46) and 74.0% (97/131), and there was no statistically significant difference (χ²=0.76, P=0.385). During maintenance treatment, 27.1% (48/177) of the patients took the medication twice a week, 35.0% (62/177) took the medication once a week, and 37.9% (67/177) took the medication once every 10 days. During follow-up after 6 months of maintenance treatment, there were no patients with recurrence of pruritus or progression of vulvar signs. Conclusions: The majority of VLS patients have itching, hypopigmentation, involvement of labia minora and labia majora, progressive atrophy, and inflammatory infiltration of dermis. Local treatments of mometasone furoate and clobetasol propionate have good initial therapeutic effects. The frequency exploration of individualized maintenance treatment could minimize the occurrence of adverse reactions when ensuring the stability of the patients' condition.
Female ; Humans ; Child ; Adolescent ; Young Adult ; Adult ; Middle Aged ; Aged ; Aged, 80 and over ; Vulvar Lichen Sclerosus/pathology* ; Clobetasol/adverse effects* ; Retrospective Studies ; Mometasone Furoate/therapeutic use* ; Pruritus/drug therapy* ; Atrophy/drug therapy* ; Hypopigmentation/drug therapy*