[Objective] To study on the genotyping of a sample with inconsistent forward and reverse serological tests, and to conduct a pedigree investigation and molecular biological mechanism study. [Methods] The ABO blood group of the proband and his family members were identified using blood group serological method. The ABO gene exon 1-7 of samples of the proband and his family were sequenced by Sanger and single molecule real-time sequencing (SMRT). DeepTMHMM was used to predict and analyze the transmembrane region of proteins before and after mutation. [Results] The proband and his mother have the Bw phenotype, while his maternal grandfather has ABw phenotype. The blood group results of forward and reverse typing of other family members were consistent. ABO gene sequencing results showed that there was B new mutation of c.3 G>C in exon 1 of ABO gene in the proband, his mother and grandfather, leading to a shift in translation start site. DeepTMHMM analysis indicated that the shift in the translation start site altered the protein topology. [Conclusion] The c.3G>C mutation in the first exon of the ABO gene leads to a shift in the translation start site, altering the protein topology from an α-transmembrane region to a spherical signaling peptide, reducing enzyme activity and resulting in the Bw serological phenotype.

OBJECTIVE To explore the pharmacokinetic characteristics of 3 blood-absorbed components of Xiangshao sanjie oral liquid in rats with hyperplasia of mammary gland （HMG）. METHODS Female SD rats were divided into control group and HMG group according to body weight， with 6 rats in each group. The HMG group was given estrogen+progesterone to construct HMG model. After modeling， two groups were given 1.485 g/kg of Xiangshao sanjie oral liquid （calculated by crude drug） intragastrically， once a day， for 7 consecutive days. Blood samples were collected before the first administration （0 h）， and at 5， 15， 30 minutes and 1， 2， 4， 8， 12， 24 hours after the last administration， respectively. Using chlorzoxazone as the internal standard， the plasma concentrations of ferulic acid， paeoniflorin and rosmarinic acid in rats were detected by UPLC-Q/TOF-MS. The pharmacokinetic parameters [area under the drug time curve （AUC0－24 h， AUC0－∞）， mean residence time （MRT0－∞）， half-life （t1/2）， peak time （tmax）， peak concentration （cmax）] were calculated by the non-atrioventricular model using Phoenix WinNonlin 8.1 software. RESULTS Compared with the control group， the AUC0－24 h， AUC0－∞ and cmax of ferulic acid in the HMG group were significantly increased （P＜0.05）； the AUC0－24 h， AUC0－∞ ， MRT0－∞ ， t1/2 and cmax of paeoniflorin increased， but there was no significant difference between 2 groups （P＞0.05）； the AUC0－24 h and MRT0-∞ of rosmarinic acid were significantly increased or prolonged （P＜0.05）. C ONCLUSIONS In HMG model rats， the exposure of ferulic acid， paeoniflorin and rosmarinic acid in Xiangshao sanjie oral liquid all increase， and the retention time of rosmarinic acid is significantly prolonged.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

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.

ObjectiveTo compare colonoscopy compliance rates under different screening strategies, to explore ways to enhance colonoscopy compliance among residents with colorectal carcinoma. MethodsResidents aged between 50‒80 years were recruited through extensive community outreach and voluntary participation. A total of 210 630 residents who participated in the colorectal carcinoma screening program in Jiading District, Shanghai, between 2013 and 2019 were selected as the research subjects. All subjects underwent a colorectal carcinoma risk assessment questionnaire survey and two fecal occult blood tests (FOBT). Positive results in the initial screening were defined as a positive questionnaire survey or a positive result in at least one FOBT. Participants with positive initial screening results were advised to undergo colonoscopy screening in a hospital. Colonoscopy results were collected from hospital reports and physician follow-ups. Compliance with colonoscopy was analyzed under different screening strategies to identify possible factors influencing residents’ willingness to undergo the procedure. ResultsA total of 21 403 individuals (10.16%) were identified as positive with the questionnaire survey, 31 595 individuals (15.00%) tested positive with at least one FOBT. Combined questionnaire and FOBT positivity was observed in 3 501 individuals (1.66%). Among the 48 453 individuals with positive initial screening results, 17 230 (35.56%) underwent colonoscopy, and a total of 315 cases of colorectal cancer were detected. The sensitivity, specificity value of FOBT initial screening were 83.81% and 84.66%, respectively. According to the combined risk assessment and FOBT initial screening preliminary screening, the lowest colonoscopy compliance rate (25.63%) was observed among individuals with only a positive questionnaire, and the highest compliance rate (52.55%) was among those with both positive questionnaire survey and two positive FOBT results. Multivariate analysis revealed that FOBT positivity had the greatest impact on colonoscopy compliance. Those with one positive FOBT test result were 2.64 times more likely to undergo colonoscopy screening than those with negative FOBT results, while individuals with two positive FOBT results were 3.18 times more likely to do so. After adjusting for FOBT results, individuals with positive questionnaire survey results were 1.43 times more likely to undergo colonoscopy screening than those with negative results (95%CI: 1.34‒1.52). Compared to questionnaire-based risk assessment, FOBT results were more influential in determining compliance with colonoscopy. ConclusionThe choice of initial screening method significantly impacts residents’ compliance with colonoscopy. While implementing colorectal carcinoma screening programs, it is necessary to strictly adhere to screening protocols, including risk assessment and FOBT. Additionally, efforts should be made to raise public awareness, encouraging residents to actively participate in risk assessments and FOBT, thereby improving their compliance with colonoscopy.

[Objective] To compare the efficacy and safety of deglycerolized red blood cells (DRBC) and suspended red blood cells (SRBC) based on the propensity score matching (PSM) method, so as to provide evidence for the rational use of DRBC resources in clinical practice. [Methods] A total of 89 patients who received DRBC transfusion and 2 916 patients who received SRBC transfusion in our hospital from January 2023 to September 2024 were included. A 1∶1 nearest neighbor PSM was used to balance covariates such as gender, age, and body mass index (BMI). The changes of hemoglobin (Hb), red blood cell (RBC) count, hematocrit (HCT), and inflammatory markers such as white blood cell (WBC) count, neutrophil (NE) count, C-reactive protein (CRP), and Interleukin-6(IL-6) in the last 72 hours after transfusion were analyzed by SPSS 26.0 and R software to evaluate clinical efficacy and transfusion safety. [Results] The baseline of the two groups was balanced after PSM (P>0.05). There was no significant difference in the total effective rate between the DRBC group (80.9%) and the SRBC group (86.5%) (P>0.05). In the SRBC group, WBC (×10 /L) increased from 9.634±6.742 to 10.147±6.835, CRP (mg/dL) increased from 5.468±4.647 to 6.174±6.114, and IL-6(pg/mL) decreased from 213.733±587.191 to 157.255±552.626. In the DRBC group, WBC (×10 /L) decreased from 11.123±7.880 to 11.011±8.549, CRP (mg/dL) decreased from 5.729±4.761 to 5.326±4.466, and IL-6(pg/mL) decreased from 238.806±639.060 to 152.255±266.558. Compared with the before treatment, the differences between the SRBC group and DRBC group were not statistically significant (P>0.05). Among all patients included in the statistics, the overall incidence of transfusion adverse reactions was 0.205% (6/2 916) in the SRBC group, and no adverse reactions occurred in the DRBC group. The incidence in the SRBC group was higher than that in the DRBC group. [Conclusion] Based on PSM analysis, there was no significant difference in the efficacy and safety of DRBC transfusion compared with SRBC transfusion, which can provide evidence-based support for routine application.

This paper summarizes Professor WANG Xiuxia's clinical experience in treating hyperprolactinemia using the liver soothing therapy. Professor WANG identifies liver qi stagnation and rebellious chong qi （冲气） as the core pathomechanisms of hyperprolactinemia. Furthermore， liver qi stagnation may transform into fire or lead to pathological changes such as spleen deficiency with phlegm obstruction or kidney deficiency with essence depletion. The treatment strategy centers on soothing the liver， with a modified version of Qinggan Jieyu Decoction （清肝解郁汤） as the base formula. Depending on different syndrome patterns such as liver stagnation transforming into fire， liver stagnation with spleen deficiency， or liver stagnation with kidney deficiency， heat clearing， spleen strengthening， or kidney tonifying herbs are added accordingly. In addition， three paired herb combinations are commonly used for symptom specific treatment， Danggui （Angelica sinensis） with Chuanxiong （Ligusticum chuanxiong）， Zelan （Lycopus lucidus） with Yimucao （Leonurus japonicus） ， and Jiegeng （Platycodon grandiflorus） with Zisu （Perilla frutescens）.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective:Migraine and tremor share some genetic mutation sites,and clinical studies have also confirmed their correlation.This study aims to explore the clinical and electrophysiological characteristics of migraine patients with concomitant tremor,and to analyze the relevant influential factors of tremor occurrence. Methods:We retrospectively analyzed the clinical data of 217 migraine patients who visited the Third Affiliated Hospital of Qiqihar Medical University from June 2022 to October 2023.The Clinical Rating Scale for Tremor(CRST),Numerical Rating Scale(NRS),Generalized Anxiety Disorder-7(GAD-7),and Patient Health Questionnaire-9(PHQ-9)were respectively used to assess the tremor symptoms,degree of headache,anxiety,and depression of patients.All patients underwent routine head MR scanning and electromyography examination,and were divided into a migraine with tremor group and a migraine without tremor group based on the electromyogram examination. Results:The migraine with tremor group and the migraine without tremor group were included 52 patients(23.96%)and 165 patients(76.04%),respectively.Compared with the migraine without tremor group,the migraine with tremor group had a longer course and duration of headache,higher frequency of headache attacks,higher NRS score,GAD-7 score,and PHQ-9 score,and fewer weekly physical exercises.The differences were statistically significant(all P<0.05).There were no statistically significant differences in the presence or absence of prodromal headache and white matter hyperintensities(WMHs)between the 2 groups(both P>0.05).The evaluation results of the CRST showed that out of 217 migraine patients,39 patients(17.97%)were accompanied by tremors.The electromyographic results showed that all 52 migraine patients with tremors had upper limb tremors,including 28 migraine patients with postural tremors and 24 migraine patients with static tremors.Compared with the migraine patients with static tremors,the migraine patients with postural tremors had lower average frequency,peak frequency,and headache onset frequency(all P<0.05).Multiple linear regression analysis showed that frequency of physical exercise,duration of illness,frequency of headache attacks,NRS score,GAD-7 score,and PHQ-9 score were risk factors for migraine patients with concomitant tremors(all P<0.05). Conclusion:Patients with migraine mainly experience upper limb postural tremors.Reduced physical exercise,long course of disease,long duration of headache,frequent headache attacks,severe headache,anxiety,and depression are risk factors for migraine patients with concomitant tremors.

Objective To construct and validate a clinical prediction model for delayed extubation undergoing non-emergency major surgery based on the random forest algorithm.Methods Clinical data of 7 528 patients undergoing non-emergency major surgery under general anesthesia from January 2018 to De-cember 2022 were retrospectively collected.The patients were divided into two groups according to whether extubation was performed within 2 hours after surgery:non-delayed extubation group(≤2 hours)and de-layed extubation group(＞2 hours).All the patients were randomly divided into a training set and a valida-tion set in a ratio of 7 ∶ 3.The predictive factors for delayed extubation after surgery were screened through LASSO regression and Logistic regression.The random forest model was established and verified by random forest algorithm.Results There were 123 patients(1.6%)experienced delayed extubation after surgery.ASA physical status,department,intraoperative use of flurbiprofen ester,dexmedetomidine,glucocorticoid,hypocalcemia,severe anemia,intraoperative blood transfusion,and airway spasm were identified as inde-pendent predictive factors for delayed extubation.The area under curve(AUC)value of the random forest prediction model in the validation set was0.751(95%CI0.742-0.778),and the sensitivity was98.1%,and the specificity was 41.9%.Conclusion The predictive model of delayed extubation undergoing non-e-mergency major surgery based on random forest algorithm has a good predictive value,which may be helpful to prevent delayed extubation undergoing non-emergency major surgery.