Objective: To investigate the prevalence of undernutrition and its associated factors among left behind and non left behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents. Methods: A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left behind and non left behind students by Chi square test, and associated factors were analyzed by three level Logistic mixed effects model. Results: The prevalence of undernutrition was 8.5% (4 326) in left behind students and 8.1% (5 905) in non left behind students. Three level Logistic mixed effect model analysis showed that whether left behind or non left behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [ OR (95% CI )=1.72(1.57-1.87),2.25(2.07- 2.43 )]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [ OR (95% CI )=0.69(0.62-0.77),0.90(0.82-0.98)] or junior high school [ OR (95% CI )=0.72(0.66-0.79),0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [ OR (95% CI )=2.36(2.07-2.68),2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [ OR (95% CI )=1.12(1.03-1.23),1.09(1.01-1.17)](all P <0.05). Conclusion The prevalence of undernutrition is slightly higher in left behind primary and secondary students than in non left behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.

Objective: To analyze the trends of the frequency of meat, egg, and milk consumption among rural primary and junior high school students in central and western China covered by the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) from 2015 to 2023, so as to provide basis for formulating more targeted nutrition intervention policies and health education strategies. Methods: Using data from six rounds of monitoring and evaluation (2015-2021 and 2023), the study included 323 870 students from grade 3 to 9 across 22 provinces (autonomous regions and municipalities) in central and western China. The consumption frequencies of meat, egg, and milk over the past week were collected via questionnaires. The Cochran-Armitage trend test was used to analyze temporal trends, and multivariable Logistic regression models were employed to analyze factors associated with the frequency of meat, egg and milk consumption and to test for interaction effects between the year and gender, region, and grade level. Results: From 2015 to 2023, the proportion of students consuming meat, egg, and milk ≥1 time/day increased from 23.20 %, 10.71%, and 0.74% to 35.53%, 22.09%, and 26.63%, respectively. Trend tests indicated a significant upward trend for the daily intake of all three food categories for meat, egg and milk over the years ( Z =67.18, 64.90, 93.14, all P <0.01). Multivariable Logistic regression analysis showed that the daily meat intake was lower in the central region than in the western region ( OR=0.77, 95%CI =0.76-0.78), whereas the daily intake of eggs ( OR=1.19, 95%CI =1.17-1.22) and milk ( OR= 1.27 , 95%CI =1.24-1.29) was higher in the central region (all P <0.05). Compared with grade 3-4 students, junior high school students had lower daily intake of meat, eggs, and milk≥1 time/day ( OR =0.95, 0.77, 0.77, all P <0.05), with a declining trend as grade increased. Girls also had lower daily intake of meat, eggs, and milk ≥1 time/day than boys ( OR =0.95，0.93，0.91, all P < 0.05). Significant interactions were observed between year and region, as well as between year and grade (all P <0.05). Conclusion From 2015 to 2023, the NIPRCES improved the intake level of among rural students, but the situation of relatively insufficient intake of egg and milk among females, junior high school students and those in the western region still exists.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Flap transplantation is a critical surgical strategy for the reconstruction of tissue defects caused by trauma, tumor resection, and congenital malformations, and its survival rate directly determines surgical efficacy and patient prognosis. Following transplantation, flaps inevitably undergo ischemia-reperfusion (I/R) injury, during which oxidative stress, inflammatory responses, and metabolic disturbances are intricately intertwined, ultimately leading to cellular injury and tissue necrosis. Recent studies have demonstrated that multiple forms of programmed cell death—including apoptosis, pyroptosis, ferroptosis, necroptosis, and PANoptosis—play central roles in flap I/R injury. The extensive crosstalk and molecular interactions among these pathways form a highly complex cell death network. Specifically, apoptosis is mediated by the imbalance of Bcl-2 family proteins and the activation of cysteine-dependent aspartate-specific protease (caspase) cascades; pyroptosis is driven by the NLRP3-caspase-1-GSDMD axis, resulting in membrane pore formation and the release of pro-inflammatory cytokines; ferroptosis is characterized by iron-dependent lipid peroxidation and dysfunction of glutathione peroxidase 4 (GPX4); necroptosis is triggered by the receptor-interacting serine/threonine-protein kinase 1 (RIPK1)-RIPK3-MLKL signaling complex, leading to membrane rupture; and PANoptosis represents an integrated form of inflammatory cell death that coordinates multiple death pathways. Importantly, these forms of programmed cell death are not independent but are interconnected through extensive signaling crosstalk. Key regulatory molecules, including caspase-8, reactive oxygen species (ROS), nuclear factor-κB (NF-κB), and nuclear factor erythroid 2-related factor 2 (Nrf2), collectively modulate the dynamic balance among these pathways. Therefore, the multidimensional interplay and spatiotemporal dynamics of programmed cell death constitute a fundamental pathological basis of flap I/R injury. This review systematically summarizes the latest advances in the mechanisms and interactions of various programmed cell death pathways in flap I/R injury, aiming to elucidate the underlying regulatory network. These insights may provide novel theoretical foundations for optimizing flap protection strategies, improving flap survival, and promoting tissue repair.

ObjectiveMagnetoencephalography (MEG), a non-invasive neuroimaging technique, meticulously captures the magnetic fields emanating from brain electrical activity. Compared with MEG based on superconducting quantum interference devices (SQUID), MEG based on optically pump magnetometer (OPM) has the advantages of higher sensitivity, better spatial resolution and lower cost. However, most of the current studies are clinical studies, and there is a lack of animal studies on MEG based on OPM technology. Pain, a multifaceted sensory and emotional phenomenon, induces intricate alterations in brain activity, exhibiting notable sex differences. Despite clinical revelations of pain-related neuronal activity through MEG, specific properties remain elusive, and comprehensive laboratory studies on pain-associated brain activity alterations are lacking. The aim of this study was to investigate the effects of inflammatory pain (induced by Complete Freund’s Adjuvant (CFA)) on brain activity in a rat model using the MEG technique, to analysis changes in brain activity during pain perception, and to explore sex differences in pain-related MEG signaling. MethodsThis study utilized adult male and female Sprague-Dawley rats. Inflammatory pain was induced via intraplantar injection of CFA (100 μl, 50% in saline) in the left hind paw, with control groups receiving saline. Pain behavior was assessed using von Frey filaments at baseline and 1 h post-injection. For MEG recording, anesthetized rats had an OPM positioned on their head within a magnetic shield, undergoing two 15-minute sessions: a 5-minute baseline followed by a 10-minute mechanical stimulation phase. Data analysis included artifact removal and time-frequency analysis of spontaneous brain activity using accumulated spectrograms, generating spectrograms focused on the 4-30 Hz frequency range. ResultsMEG recordings in anesthetized rats during resting states and hind paw mechanical stimulation were compared, before and after saline/CFA injections. Mechanical stimulation elevated alpha activity in both male and female rats pre- and post-saline/CFA injections. Saline/CFA injections augmented average power in both sexes compared to pre-injection states. Remarkably, female rats exhibited higher average spectral power 1 h after CFA injection than after saline injection during resting states. Furthermore, despite comparable pain thresholds measured by classical pain behavioral tests post-CFA treatment, female rats displayed higher average power than males in the resting state after CFA injection. ConclusionThese results imply an enhanced perception of inflammatory pain in female rats compared to their male counterparts. Our study exhibits sex differences in alpha activities following CFA injection, highlighting heightened brain alpha activity in female rats during acute inflammatory pain in the resting state. Our study provides a method for OPM-based MEG recordings to be used to study brain activity in anaesthetized animals. In addition, the findings of this study contribute to a deeper understanding of pain-related neural activity and pain sex differences.

Objective:To explore the application effects of the blended teaching methodology of "teaching-selection-investigation-analysis-presentation-discussion" in Medical Immunology. Methods:Eight-year program clinical medical students who were enrolled at Peking Union Medical College in 2016, 2017, and 2018 were selected as the research subjects. An anonymous questionnaire survey was used to analyze students' multidimensional evaluations of the new teaching methodology. The percentage of frontier hotspot topics in the "Immunology Forum" was used to analyze the students' mastery of cutting-edge knowledge in immunology. The number of "Immunology Forum" related "College Students Innovative Training Plan Program" from 2020 to 2023 was used to analyze the effectiveness of this new teaching method in cultivating students' scientific research and innovation abilities. Statistical analysis was conducted using SPSS 25.0 software, and the normality of all continuous variables was assessed using the Shapiro-Wilk test.Results:The questionnaire survey showed 100.00% satisfaction with the course and 95.90% recognition of the new teaching method. More than 90% of students agreed that the new teaching method improved their learning ability, research ability, innovation ability, internal drive, and academic communication ability. The average proportion of hotspot topics in the "Immunology Forum" was 90.37%±7.12%, which was significantly higher than the proportion of non-hotspot topics (5.67%±3.12%). The average number of topics related to "Immunology Forum" in the "College Students Innovative Training Plan Program" was 17.67±1.15 per session, which was significantly higher than the number of topics not related to "Immunology Forum" (8.00±1.73).Conclusions:The blended teaching methodology of "teaching-selection-investigation-analysis-presentation-discussion" can help students timely grasp the cutting-edge knowledge of immunology, cultivate their learning ability, internal drive, academic communication ability, innovation ability, and research ability, and lay a foundation for students to further explore their scientific research and innovation activities.

Objective:To study the relationship between the levels of multiple elements in urine and the risk of arsenic poisoning in populations exposed to drinking water arsenic in Inner Mongolia Autonomous Region (Inner Mongolia).Methods:From April 2023 to January 2024, a case-control study method was used to select 128 individuals with a residence time of ≥10 years in drinking water arsenic exposed areas in Inner Mongolia as study subjects. Eighty-one individuals diagnosed with arsenic poisoning were selected as the case group, and 47 healthy individuals were selected as the control group for urine sample collection and questionnaire survey. Inductively coupled plasma mass spectrometry was employed to determine the levels of 10 elements (chromium, manganese, cobalt, nickel, copper, zinc, arsenic, molybdenum, cadmium and lead) in urine. The levels of each element in urine were divided into four groups ( Q1, Q2, Q3, and Q4 groups) based on quartiles. The associations between the levels of various elements in urine and the risk of arsenic poisoning were studied using binary logistic regression model and restricted cubic spline (RCS). Results:The age of the control group and the case group [ M ( Q1, Q3)] were 61 (53, 69) and 61 (56, 67) years old, respectively. There were 19 and 43 males, and 28 and 38 females, respectively. There was no statistically significant differences in age and and gender composition between the two groups ( Z = - 0.39, P = 0.700; χ 2 = 1.91, P = 0.167). The levels of urinary copper and cadmium of the case group were higher than those of the control group, and the differences were statistically significant ( Z = - 2.66, - 2.16, P < 0.05). The results of univariate logistic regression analysis showed that urinary copper was an influencing factor for arsenic poisoning ( P = 0.017). The results of multivariate logistic regression analysis revealed that after adjusting for covariates, urinary copper and arsenic were independent influencing factors of arsenic poisoning ( P < 0.05). Taking Q1 group as a reference, urinary copper in Q3 group [ OR (95% CI) = 8.23 (1.81, 37.39), P = 0.006] increased the risk of arsenic poisoning, while urinary arsenic in Q2, Q3, and Q4 groups [ OR (95% CI) = 0.24 (0.06, 0.92), 0.12 (0.03, 0.53), 0.15 (0.04, 0.63), P < 0.05] decreased the risk of arsenic poisoning. After adjusting for covariates, RCS did not show a dose-response relationship between urinary copper, urinary arsenic, and arsenic poisoning ( P > 0.05). Conclusion:Urinary arsenic and copper are associated with the risk of arsenic poisoning in the drinking water arsenic exposed areas of Inner Mongolia, copper exposure may contribute significantly to arsenic poisoning.

Aim To observe the effect of lipopolysac-charide(LPS)induced supernatant of BV-2 cells on the inflammatory response and apoptosis of HT22 neu-rons.Methods After the concentration and time of LPS were determined by CCK-8 method,BV-2 cells were cultured with medium without LPS and medium containing LPS,the morphological changes of BV-2 microglia were observed by inverted microscope,and the CD86/CD206 ratio of BV-2 microglia was detected by immunofluorescence.Subsequently,BV-2 cell cul-ture supernatants were isolated and added to HT22 neuronal culture to observe the effect on the inflamma-tory response of HT22 neurons.The proliferation of HT22 neurons was detected by CCK-8 method and EdU method.The structural changes of HT22 neurons were observed under the microscope and examined by urani-um-lead staining.The levels of cytokines interleukin-1β(IL-1β),interleukin-10(IL-10),nuclear factor kappa-B(NF-κB)and tumor necrosis factor-α(TNF-α)were detected by enzyme-linked immunosorbent as-say(Elisa).Neuronal apoptosis was detected by the TUNEL method.The protein expressions of Bax,Bcl-2 and inflammatory factors were detected by Western blot.Results After induction with 1 mg·L-1 LPS,BV-2 cells exhibited increased cell body size,thicker protrusions on both side,and some cells showed de-formed protrusions,the CD86/CD206 ratio in BV-2 cells decreased,promoting the transformation of BV-2 cells from M2 type to M1 type.After treating with the culture supernatant of BV-2 cells,HT22 neuronal cell activity and proliferation were reduced,axons short-ened,and the number of cells decreased.Neuronal cell bodies were enlarged and some cells were de-formed,with damaged cell membranes,round cell nu-clei but displaced nucleoli from the normal position,swollen mitochondria with vacuoles,reduced internal ridge structures,and increased levels of inflammatory factors NF-κB,IL-1 β,and TNF-α(P＜0.05 or P＜0.01),while the anti-inflammatory factor IL-10 de-creased(P＜0.05),protein expression of the pro-apoptotic indicator Bax increased(P＜0.01),and the protein expression of the anti-apoptotic indicator Bcl-2 decreased(P＜0.05).Conclusion After induction of BV-2 cell polarization by LPS,the supernatant could inhibit HT22 neuronal cell viability,upregulate inflam-matory factor expression and promote apoptosis.

Objective:To investigate the dynamic changes of serum long non-coding ribonucleic acid antisense non-coding RNA in the INK4 locus (LncRNA ANRIL), long non-coding ribonucleic acid maternally expressed gene 3 (LncRNA MEG3) and inflammatory factors [interferon-γ (IFN-γ), interleukin-6 (IL-6), interleukin-18 (IL-18) and interleukin-1β (IL-1β)] in patients with acute ischemic stroke and their correlation with neurological impairment.Methods:This prospective study included fifty-two patients with acute ischemic stroke admitted to the Central Hospital of Dalian University of Technology were included, and the neurological impairments of the patients were scored using the National Institutes of Health stroke scale (NIHSS) on the first day of the onset of the disease, and serum LncRNA ANRIL, LncRNA MEG3 and inflammatory factors (IFN-γ, IL-6, IL-18 and IL-1β) were detected using enzyme-linked immunosorbent assay (ELISA) at the first, second and seventh day of the onset of the disease. The correlation between serum LncRNA ANRIL, LncRNA MEG3 and inflammatory factor levels and neurological impairment at each time point was analyzed by Spearman correlation analysis.Results:Among 52 patients, mild group had 22 cases (NIHSS score <5 scores), and moderate-to-severe group had 30 cases (NIHSS score ≥5 scores). In acute ischemic stroke patients with moderate-to-severe group, the expression level of LncRNA MEG3 was higher than in the mild group, but the intergroup difference did not reach statistical significance ( P>0.05). LncRNA ANRIL, LncRNA MEG3, IFN-γ, IL-18 and IL-1β peaked at the same time point in acute ischemic stroke patients, all within second day of the onset of the disease. Spearman correlation analysis showed that the serum LncRNA MEG3 level on the first day of the onset of the disease was significantly positively correlated with NIHSS score ( P = 0.006), and serum LncRNA ANRIL level on seventh day was significantly positively correlated with NIHSS score ( P = 0.049). Conclusions:Serum LncRNA ANRIL, LncRNA MEG3 and inflammatory factors (IL-18, IL-1β and IFN-γ) are highly expressed in patients with acute ischemic stroke, peaking on the second day of onset. LncRNA MEG3 levels on the first day of onset and LncRNA ANRIL levels on the seventh day of onset are helpful in determining the degree of neurological impairment in patients with acute ischemic stroke.