Objective To assess the survival vulnerability of Oncomelania hupensis in Jiangxi Province under future climate scenarios, and to identify low-vulnerability areas for its survival in this province. Methods Village-level O. hupensis snail survey and O. hupensis snail control with chemical treatments in Jiangxi Province from 2016 to 2024 were captured from the Parasitic Disease Prevention and Control Information Management System of China Disease Prevention and Control Information System. Climatic data were primarily sourced from the Resource and Environmental Science Data Platform, Chinese Academy of Sciences (http://www.resdc.cn/), including annual average temperature, annual average precipitation, annual accumulated temperature above 10 °C, annual accumulated temperature above 0 °C, annual maximum temperature, annual minimum temperature, and annual average relative humidity, and nineteen bioclimatic variables were downloaded from the WorldClim website (https://www.worldclim.org/), including mean diurnal range, isothermality, temperature seasonality, and so on. Elevation and normalized difference vegetation index were catprued from the Resource and Environmental Science Data Platform, Chinese Academy of Sciences (http://www.resdc.cn/), and distance to rivers was downloaded from the WorldPop website (http://www.worldpop.org), and land use and land cover (LULC) data were downloaded from the Big Earth Data Center, Chinese Academy of Sciences (https://data.casearth.cn/), and nature reserve data were obtained from the China Nature Reserve Specimen Resource Sharing Platform (http://www.papc.cn/). Three Shared Socioeconomic Pathways (SSPs) from the Beijing Climate Center-Climate System Model version 2-Medium Resolution (BCC-CSM2-MR) global climate model were employed as future climate scenarios, including SSP126, SSP245, SSP585, and the biomod2 ensemble model in R package was used to simulate suitable habitats for O. hupensis snails in Jiangxi Province in 2050 and 2070 under these scenarios. A snail survival vulnerability index was constructed based on the area of suitable snail habitats, area covered by snail control through chemical treatment, area covered by nature reserves, and changes in snail habitat fragmentation, and a map of snail survival vulnerability distribution was plotted. Results The real area of snail habitats ranged from 78 486.76 to 85 309.47 hm², and the area of snail control with chemical treatment ranged from 10 138.98 to 13 240.16 hm² in Jiangxi Province from 2016 to 2024. There were 429 to 531 villages detected with snails during the nine-year period, and the number of actually snail-infested villages ranged from 645 to 686. A total of 818 snail-present points and 1 996 snail-absent points were obtained from snail survey records. The best performance of the biomod2 ensemble model was achieved if a weighted mean approach was used as the ensemble strategy, with a true skill statistic value of 0.799 and an area under the receiver operating characteristic curve of 0.957, and modeling identified annual average relative humidity and annual average precipitation as two most influencing climatic variables for snail distribution. Relative to the current areas of suitable snail habitats under present climate conditions, the area of suitable snail habitats was projected to expand by 24.49% to 46.28% in Jiangxi Province under future climate scenarios, and the proportion of nature reserves areas in the areas of suitable snail habitats was projected to decrease slightly from the current 2.77% to approximately 2.52%, while the proportion of areas of snail control through chemical treatment in areas of suitable snail habitats varied from 0.64% to 19.57%, and the percentage of changes in snail habitat fragmentation ranged from 3.86% to 12.23%. Based on these four indicators, the snail survival vulnerability index was estimated to range from –1.96 to 0.62 in Jiangxi Province. The arithmetic mean of the snail survival vulnerability index differed under three SSP scenarios (SSP126, SSP245 and SSP585), with the highest mean value (–0.69) in 2070 under SSP126, and the lowest mean value (–0.78) in 2070 under SSP585. Conclusions The snail survival vulnerability index ranges from –1.96 to 0.62 in Jiangxi Province under future climate scenarios, and the suitable habitats for O. hupensis snails appear an overall tendency towards expansion. Low-vulnerability snail habitats are mainly distributed along the shores of Poyang Lake and the Yangtze River in Jiangxi Province, partially overlapping with nature reserves. Intensified surveillance of O. hupensis snails is recommended in these areas in the future.

The thalamic reticular nucleus (TRN) plays a crucial role in regulating sensory encoding, even at the earliest stages of visual processing, as evidenced by numerous studies. Orientation selectivity, a vital neural response, is essential for detecting objects through edge perception. Here, we demonstrate that somatostatin (SOM)-expressing and parvalbumin (PV)-expressing neurons in the TRN project to the dorsal lateral geniculate nucleus and modulate orientation selectivity and the capacity for visual information processing in the primary visual cortex (V1). These findings show that SOM-positive and PV-positive neurons in the TRN are powerful modulators of visual information encoding in V1, revealing a novel role for this thalamic nucleus in influencing visual processing.
Animals ; Somatostatin/metabolism* ; Parvalbumins/metabolism* ; Neurons/physiology* ; Thalamic Nuclei/physiology* ; Visual Pathways/physiology* ; Mice ; Mice, Inbred C57BL ; Visual Perception/physiology* ; Male ; Mice, Transgenic ; Visual Cortex/physiology* ; Primary Visual Cortex/cytology*

Objective To investigate the relationship between serum levels of interferon-inducible protein 10(IP-10)and S100 calcium-binding protein A8(S100A8)and the prognosis of patients with severe pneumo-nia(SP).Methods A total of 315 SP patients admitted to the hospital from January 2021 to December 2023 were selected as the SP group,and 315 non-SP patients admitted to the hospital during the same period were selected as the non-SP group.According to the prognosis of SP patients 28 d after admission,they were divided into good prognosis group(199 cases)and poor prognosis group(116 cases).Enzyme-linked immunosorbent assay was used to detect serum IP-10 and S100A8 levels in SP patients.Pearson correlation analysis was used to analyze the correlation between IP-10,S100A8 levels and infection indicators[high-sensitivity C-reactive protein(hs-CRP),procalcitonin(PCT),interleukin-6(IL-6)].Multivariate Logistic regression was used to analyze the influencing factors of poor prognosis in SP patients.Receiver operating characteristic(ROC)curve was used to analyze the value of hs-CRP,PCT,IP-10 and S100A8 levels in predicting the poor prognosis of SP patients.Results The serum levels of IP-10,S100A8,hs-CRP,PCT and IL-6 in SP group were higher than those in non-SP group(P＜0.05).Paerson correlation analysis showed that serum IP-10 level in SP group was positively correlated with hs-CRP,PCT and IL-6(r=0.744,0.757,0.740,P＜0.05).S100A8 level was posi-tively correlated with hs-CRP,PCT and IL-6(r=0.769,0.718,0.744,P＜0.05).There were significant differences in oxygenation index,acute physiology and chronic health evaluation Ⅱ score,clinical pulmonary in-fection score and levels of hs-CRP,PCT,IP-10 and S100A8 between the poor prognosis group and the good prognosis group(P＜0.05).Multivariate Logistic regression analysis showed that hs-CRP,PCT,IP-10 and S100A8 were risk factors for poor prognosis in SP patients,and oxygenation index was a protective factor(P＜0.05).The ROC curve showed that the area under curve(AUC)of the combination of hs-CRP,PCT,IP-10 and S100A8 in predicting poor prognosis of SP patients was 0.965,which was greater than the AUC of the four alone(Zhs-CRP=4.009,ZPCT=4.022,ZIP-10=3.696,ZS100A8=3.309,P＜0.05).Conclusion The serum lev-els of IP-10 and S100A8 are up-regulated in SP patients.The combination of IP-10 and S100A8 has a high pre-dictive value for poor prognosis in SP patients.

Objective:To investigate the differences in hippocampal subfield volumes and structural covariance network properties among patients with mild cognitive impairment (MCI) exhibiting different cognitive outcomes and normal controls (NCs), and to further evaluate the predictive value of these imaging indicators for cognitive deterioration in MCI patients.Methods:A total of 43 NCs, 65 stable MCI (sMCI), and 26 progressive MCI (pMCI) patients enrolled in the Alzheimer′s Disease Neuroimaging Initiative (ADNI) database between December 2012 and May 2016 were included in this study. Baseline demographic information and T 1-weighted magnetic resonance imaging scans were collected. Hippocampal subfield volumes were extracted using freesurfer software, and structural covariance networks of hippocampal subfields were constructed. Multivariate analysis of covariance was used to compare hippocampal subfield volumes among the 3 groups. A general linear model was applied to examine group differences in hippocampal subfield structural covariance network properties. Least absolute shrinkage and selection operator (LASSO)-Logistic regression was employed to identify imaging predictors associated with conversion to Alzheimer′s disease (AD), based on which structural, network-based, and combined predictive models were constructed. Model discrimination was evaluated using the area under the curve (AUC); internal validation was performed using Bootstrap resampling; model calibration was assessed with the Hosmer-Lemeshow test; and clinical utility was evaluated through decision curve analysis. Results:Significant differences in hippocampal subfield volumes (mm3) were observed among the 3 groups (all P<0.05, Bonferroni-corrected). Specifically, left parasubiculum (65.58±13.30, 61.96±17.56, 49.56±11.82, F=9.900), right parasubiculum (65.92±15.21, 59.45±16.65, 47.69±15.48, F=11.612), left presubiculum (277.09±39.85, 258.15±44.86, 224.05±45.05, F=14.513), right presubiculum (262.85±40.43, 247.41±43.27, 209.97±46.11, F=14.500), left subiculum (399.66±32.19, 374.25±55.83, 306.12±51.62, F=32.923), right subiculum (417.93±48.92, 376.59±51.01, 316.82±70.22, F=28.764), left cornu ammonis 1 (CA1) (592.10±83.87, 561.96±94.72, 490.06±86.89, F=13.352), right CA1 (632.15±100.09, 601.24±88.88, 531.05±110.29, F=10.579), left CA3 (191.58±30.08, 180.47±34.66, 155.08±37.82, F=12.182), right CA3 (210.42±28.92, 203.84±34.80, 176.69±41.47, F=9.597), left CA4 (224.61±28.94, 210.49±35.04, 183.98±36.89, F=16.521), right CA4 (238.49±28.14, 227.43±30.65, 200.23±42.74, F=13.702), left granule cell-molecular layer-dentate gyrus (GC-ML-DG) (259.96±36.76, 239.42±41.17, 207.61±41.84, F=19.831), right GC-ML-DG (273.98±35.12, 258.79±36.82, 227.81±49.07, F=14.204), left molecular layer (505.62±66.16, 468.58±75.17, 402.68±75.47, F=22.293), right molecular layer (527.39±72.39, 493.14±70.39, 423.81±88.09, F=19.588), left hippocampal amygdala transition area (HATA) (54.91±9.99, 49.52±9.93, 43.27±9.59, F=13.571), right HATA (58.43±9.83, 54.55±10.80, 47.12±12.54, F=10.037), left fimbria (69.94±25.04, 56.63±23.74, 40.58±19.83, F=14.846), right fimbria (68.61±26.24, 53.95±23.16, 45.25±17.04, F=10.424), left hippocampal tail (488.37±83.44, 463.54±80.33, 393.83±77.73, F=13.570), and right hippocampal tail (519.78±80.22, 498.84±81.68, 419.75±93.29, F=14.339) all showed significant group differences. Significant group differences were also observed in small-worldness metric γ (0.51±0.10, 0.51±0.08, 0.62±0.14, F=9.317), small-worldness metric λ (0.39±0.02, 0.39±0.02, 0.43±0.04, F=9.925), global efficiency (0.19±0.01, 0.20±0.01, 0.18±0.01, F=3.189), local efficiency (0.26±0.02, 0.26±0.01, 0.27±0.01, F=3.068), clustering coefficient (0.23±0.01, 0.23±0.01, 0.24±0.02, F=4.274), and characteristic path length (0.73±0.06, 0.72±0.06, 0.76±0.07, F=4.477) of the hippocampal subfield structural covariance network (all P<0.05). Specifically, the pMCI group exhibited higher γ ( t=3.773, P<0.001), λ ( t=4.060, P<0.001), local efficiency ( t=2.445, P=0.047), and clustering coefficient ( t=2.849, P=0.015) than the NCs group, and higher γ ( t=4.074, P<0.001), λ ( t=4.068, P<0.001), and characteristic path length ( t=2.986, P=0.010) but lower global efficiency ( t=-2.444, P=0.047) than the sMCI group. The AUC of the structural, network, and combined models based on LASSO-Logistic regression was 0.837, 0.861, and 0.899, respectively. After internal validation, the corrected AUC was 0.835, 0.855, and 0.889, respectively. All models demonstrated good calibration ( P>0.05), and decision curve analysis indicated favorable clinical net benefit across models. Conclusions:Both sMCI and pMCI patients exhibit widespread hippocampal subfield atrophy and altered global properties of hippocampal subfield structural covariance networks compared to NCs. The models constructed based on hippocampal subfield volumes and structural covariance networks show strong potential for predicting cognitive decline in MCI patients.

Alzheimer's disease(AD), a neurodegenerative disorder associated with aging, is the most prevalent form of dementia.As the aging population continues to expand, AD presents significant health and caregiving challenges for families and society, making it a pressing international public health concern.In recent years, numerous countries have implemented dementia prevention and treatment strategies that emphasize community-based comprehensive approaches.Currently, the community-based AD prevention and treatment model in China is still in the exploratory phase, with community efforts lacking organization.In alignment with China's action plan for advancing dementia prevention and treatment, and to achieve the strategic objective of "healthy aging, " this consensus is based on the principle of three-level prevention and is tailored to the characteristics of AD disease progression.It aims to develop a comprehensive prevention and treatment strategy for AD that is suitable for communities in China, providing technical guidance and support to establish a scientific basis for formulating community AD prevention and treatment models.

BACKGROUND: Molecular subtyping is an essential complementarity after pathological analyses for targeted therapy. This study aimed to investigate the consistency of next-generation sequencing (NGS) results between circulating tumor DNA (ctDNA)-based and tissue-based in non-small cell lung cancer (NSCLC) and identify the patient characteristics that favor ctDNA testing. METHODS: Patients who diagnosed with NSCLC and received both ctDNA- and cancer tissue-based NGS before surgery or systemic treatment in Lung Cancer Center, Sichuan University West China Hospital between December 2017 and August 2022 were enrolled. A 425-cancer panel with a HiSeq 4000 NGS platform was used for NGS. The unweighted Cohen's kappa coefficient was employed to discriminate the high-concordance group from the low-concordance group with a cutoff value of 0.6. Six machine learning models were used to identify patient characteristics that relate to high concordance between ctDNA-based and tissue-based NGS. RESULTS: A total of 85 patients were enrolled, of which 22.4% (19/85) had stage III disease and 56.5% (48/85) had stage IV disease. Forty-four patients (51.8%) showed consistent gene mutation types between ctDNA-based and tissue-based NGS, while one patient (1.2%) tested negative in both approaches. Patients with advanced diseases and metastases to other organs would be suitable for the ctDNA-based NGS, and the generalized linear model showed that T stage, M stage, and tumor mutation burden were the critical discriminators to predict the consistency of results between ctDNA-based and tissue-based NGS. CONCLUSION ctDNA-based NGS showed comparable detection performance in the targeted gene mutations compared with tissue-based NGS, and it could be considered in advanced or metastatic NSCLC.
Humans ; Carcinoma, Non-Small-Cell Lung/pathology* ; Circulating Tumor DNA/blood* ; High-Throughput Nucleotide Sequencing/methods* ; Female ; Male ; Lung Neoplasms/pathology* ; Middle Aged ; Mutation/genetics* ; Aged ; Adult ; Aged, 80 and over

Objective To investigate the prevalence of Schistosoma japonicum infections in wild rodents in schistosomiasis-endemic areas of China, so as to provide insights into formulation of technical guidelines for monitoring of and the precise control strategy for S. japonicum infections in wild rodents during the elimination phase. Methods Two administrative villages where schistosomiasis was historically highly prevalent were selected each from Dongzhi County, Anhui Province, and Duchang County, Jiangxi Province as study villages. Wild rodents were captured from study villages with baited traps or cages at night in June and September, 2021. The number of rodents captured was recorded, and the rodent species was characterized based on morphologi-cal characteristics. Liver tissues were sampled from captured rodents for macroscopical observation of the presence of egg granu- lomas, and S. japonicum infection was detected simultaneously using liver tissue homogenate microscopy, examinations of mesenteric tissues for parasites, and modified Kato-Katz thick smear technique (Kato-Katz technique). A positive S. japonicum infection was defined as detection of S. japonicum eggs or adult worms by any of these methods. The rate of wild rodent capture and prevalence of S. japonicum infections in wild rodents were compared in different study villages and at different time periods, and the detection of S. japonicum infections in wild rodents was compared by different assays. Results The overall rate of wild ro- dent capture was 8.28% (237/2 861) in Dongzhi County, and the wild rodent capture rates were 9.24% (133/1 439) and 7.31% (104/1 422) in two study villages (χ² = 3.503, P = 0.061), and were 8.59% (121/1 409) and 7.99% (116/1 452) in June and September, 2021, respectively (χ² = 0.337, P = 0.561). The overall rate of wild rodent capture was 3.72% (77/2 072) in Duchang County, and the wild rodent capture rates were 6.91% (67/970) and 0.91% (10/1 102) in two study villages (χ² = 51.901, P < 0.001), and were 4.13% (39/945) and 3.37% (38/1 127) in June and September, 2021, respectively (χ² = 0.815, P = 0.365). Rattus norvegicus was the predominant rodent species captured in both counties, accounting for 70.04% (166/237) of all captured wild rodents in Dongzhi County and 88.31% (68/77) in Duchang County. No S. japonicum infection was detected in wild rodents captured in Duchang County. Nevertheless, the overall prevalence of S. japonicum infections was 51.05% (121/237) in wild rodents captured in Dongzhi County, with prevalence rates of 50.38% (67/133) and 51.92% (54/104) in two study villages (χ² = 0.098, P = 0.755), and 54.31% (63/116) and 47.93% (58/121) in September and June, 2021, respectively (χ² = 0.964, P = 0.326). Of 237 wild rodents captured in Dongzhi County, there were 140 (59.07%) rodents with visible hepatic egg granulomas, 117 (49.47%) tested positive for S. japonicum eggs by liver tissue homogenate microscopy, 34 (14.35%) tested positive for S. japonicum eggs with Kato-Katz technique; however, no adult S. japonicum worms were detected in mesenteric tissues. In addition, hepatic egg granulomas were found in all wild rodents tested positive for S. japonicum eggs with liver tissue homogenate microscopy. Conclusions The rate of wild rodent capture and prevalence of S. japonicum infection in wild rodents vary greatly in schistosomiasis-endemic areas of China, and the prevalence of S. japonicum infection is slightly higher in wild rodents captured in autumn than in summer. Liver tissue is recommended as the preferred sample for surveillance of S. japonicum infection in wild rodents, and a combination of macroscopical observation of hepatic egg granulomas and liver tissue homogenate microscopy may be a standard method for surveillance of S. japonicum infection in wild rodents.

Objective To compare the clinical and functional differences between transoral and submandibular approach in mandibu-lar segmental resection and reconstruction with free fibula flaps(FFFs).Methods Patients who underwent mandibular segmental re-section and FFFs reconstruction in the Department of Oral and Maxillofacial Surgery of the Affiliated Stomatological Hospital of Nanjing Medical University from January 2015 to March 2023 were retrospectively analyzed.All cases were divided into transoral approach and submandibular approach groups.Clinical characteristics of the patients were recorded including age,gender,follow-up time,pathologi-cal diagnosis,body mass index(BMI),American Society of Anesthesiologists(ASA)classification,James Brown classification of mandibular defect and number of fibular segments.The perioperative indexes,such as average operation time,average bleeding vol-ume,average blood transfusion volume,average drainage volume,average hospitalization time and postoperative complications such as malocclusion,fistula,infection,flap failure,and restriction of mouth opening were compared between the two groups.The University of Washington Quality of Life Questionnaire was used to investigate the appearance,function of swallow and speech more than 6-month postoperatively.Results The average intraoperative bleeding and postoperative drainage were significantly lower in the transoral ap-proach group than in the submandibular approach group(P=0.013 9,P=0.001 9).The appearance score was significantly higher in the transoral approach group than in the submandibular approach group(83.52±12.37)vs.(67.19±13.64)(P＜0.000 1).The differ-ences between the two groups in other variables were not statistically significant.Conclusion Cases of transoral approach had signifi-cantly better aesthetic outcomes compared with those of submandibular approach.

Objective:To evaluate the effectiveness of anti-G straining maneuver (AGSM) in pilots by surface electromyography (sEMG), and to explore the relationships between characteristics of sEMG and anti-G endurance in pilots.Methods:Thirty-eight male high-performance fighter pilots who completed the human centrifuge test at the Air Force Medical Center were selected. Among them, 25 completed the 8.0 G for 10 s anti-G endurance test and 13 completed the 9.0 G for 10 s anti-G endurance test. The sEMG tester was used to keep track of the changes of sEMG in rectus abdominis, rectus femoris, anterior tibial and gastrocnemius muscles while pilots were engaged in AGSM. The anti-G endurance was evaluated according to the changes of visual fields and consciousness. The pilots were divided into 3 groups: the good vision and consciousness group, peripheral visual field narrowing group and endurance endpoint group. The differences in the integral electromyogram (iEMG), mean power frequency (MPF) and muscle input rates between the 3 groups were investigated.Results:A total of 25 pilots completed the 8.0 G for 10 s anti-G endurance test. Among them, 8 (32.0%) were in the good vision and consciousness group, 13 (52.0%) in the peripheral visual field narrowing group and 4 (16.0%) reached the endurance endpoint. Among the 13 pilots who completed the 9.0 G for 10 s anti-G endurance test, 3 (23.1%) were in the good vision and consciousness group, 6 (46.1%) in the peripheral visual field narrowing group, and 4 (30.8%) in the endurance endpoint group. The results of sEMG showed that the iEMG values of the anterior tibialis muscle in pilots under the 9.0 G for 10 s load were significantly different across endurance groups ( H=7.54, P=0.023), and that the iEMG values of the tibialis anterior muscle in the good vision and consciousness group were higher than those in the endurance endpoint group ( P=0.036). The negative slopes of MPF for the rectus abdominis, rectus femoris, anterior tibialis, and gastrocnemius muscles were higher in the good vision and consciousness group than in the other 2 groups, but the differences were not statistically significant ( P>0.05). During the 8.0 G for 10 s anti-G endurance test, there were significant differences in lower limb muscle contribution rates between the 3 groups ( F=4.19, P=0.029). The endurance endpoint group exhibited a lower contribution rate than the good vision and consciousness group ( P=0.025). During the 9.0 G for 10 s anti-G endurance test, there were significant differences in tibialis anterior muscle contribution rates between the 3 groups ( F=4.16, P=0.049). The endurance endpoint group demonstrated a lower contribution rate than the good vision and consciousness group ( P=0.049). Conclusions:The full and balanced activation of abdominal muscles and lower limb muscles, especially the effective mobilization of calf muscles, plays a pivotal role in improving pilots′ AGSM efficiency in high G environments.

Objective:To investigate the alterations of individual metabolic brain network properties in patients with mild cognitive impairment (MCI) and their correlations with cognitive function.Methods:One hundred and five participants from Alzheimer's Disease Neuroimaging Initiative (ADNI) database enrolled from March 2012 to February 2016 were chosen, including 61 MCI patients and 44 normal controls (NC). Cognitive assessments, including mini-mental state examination (MMSE), auditory verbal learning test (AVLT), trail making test (TMT), and semantic verbal fluency (SVF) score, were performed in both groups; differences of above scores and clinical data between the participants from the two groups were compared. T1-weighted imaging and fluorodeoxyglucose positron emission tomography (FDG-PET) images were collected in both groups; individual metabolic brain networks were constructed based on differences in effect sizes between brain regions and network properties were calculated. Spatial correlation analysis was used to compare the correlations of metabolic brain networks at the individual and group levels. General linear model was employed to compare the differences in network properties between the two groups. Partial correlation analysis was used to examine the correlations of differential network properties with cognitive function in MCI patients. A support vector machine (SVM) classification model was constructed based on individual metabolic brain network properties, and receiver operating characteristic (ROC) curve was used to explore the diagnostic value of this SVM classification model in MCI.Results:(1) Compared with the NC group, the MCI group had significantly lower MMSE and AVLT-immediate recall scores, and longer TMT-A completion time ( P<0.05). (2) Spatial correlation analysis revealed a positive correlation between individual metabolic brain networks and group-level metabolic brain networks in patients of the MCI group ( r=0.825, P<0.001). No significant differences in global network properties were noted between the two groups ( P>0.05). Compared with the NC group, the MCI group significantly decreased degree centrality in the left A8vl, right A39c, and right V5/MT+ regions, increased degree centrality in the left anterior cuneus, decreased nodal efficiency in the left A8vl, right V5/MT+, and right caudal hippocampus regions, increased nodal shortest path length and nodal clustering coefficient in the left A8vl region ( P<0.05). (3) The degree centrality at the A8vl of ventral part of the left middle frontal gyrus and nodal efficiency in right caudal hippocampus region were positively correlated with AVLT-immediate recall scores ( r=0.331, P=0.010; r=0.282, P=0.030), nodal efficiency in the left A8vl region was negatively correlated with TMT-A completion time ( r=-0.470, P<0.001), and nodal efficiency in the left A8vl region was positively correlated with SVF score ( r=0.263, P=0.044). (4) Area under the curve of SVM classification model in diagnosing MCI was 0.880 (95% CI: 0.813-0.945, P<0.001), with an accuracy rate of 0.790. Conclusions:Patients with MCI have alterations in individual metabolic brain network properties, among which the degree centrality and nodal efficiency of some nodes are closely related to cognitive function changes. Models constructed based on individual metabolic brain network properties can help to effectively diagnose MCI.