The somatosensory system, including modalities such as touch, temperature, and pain, is essential for perceiving and interacting with the environment. When individuals encounter different somatosensory modalities, they interact through a process called multimodal somatosensory integration. This integration is essential for accurate perception, motor coordination, pain management, and adaptive behavior. Disruptions in this process can lead to a variety of sensory disorders and complicate rehabilitation efforts. However, research on the behavioral patterns and neural mechanisms underlying multimodal somatosensory integration remains limited. According to previous studies, multimodal somatosensory integration can result in facilitative or inhibitory effects depending on factors like stimulus type, intensity, and spatial proximity. Facilitative effects are observed primarily when stimuli from the same sensory modality (e.g., two touch or temperature stimuli) are presented simultaneously, leading to amplified perceptual strength and quicker reaction times. Additionally, certain external factors, such as cooling, can increase sensitivity to other sensory inputs, further promoting facilitative integration. In contrast, inhibitory effects may also emerge when stimuli from different sensory modalities interact, particularly between touch and pain. Under such conditions, one sensory input (e.g., vibration or non-noxious temperature stimulation) can effectively reduce the perceived intensity of the other, often resulting in reduced pain perception. These facilitative and inhibitory interactions are critical for efficient processing in a multi-stimulus environment and play a role in modulating the experience of somatosensory inputs in both normal and clinical contexts. The neural mechanisms underlying multimodal somatosensory integration are multi-tiered, encompassing peripheral receptors, the spinal cord, and various cortical structures. Facilitative integration relies on the synchronous activation of peripheral receptors, which transmit enhanced signals to higher processing centers. At the cortical level, areas such as the primary and secondary somatosensory cortex, through multimodal neuron responses, facilitate combined representation and amplification of sensory signals. In particular, the thalamus is a significant relay station where multisensory neurons exhibit superadditive responses, contributing to facilitation by enhancing signal strength when multiple inputs are present. Inhibitory integration, on the other hand, is mediated by mechanisms within the spinal cord, such as gating processes that limit transmission of competing sensory signals, thus diminishing the perceived intensity of certain inputs. At the cortical level, lateral inhibition within the somatosensory cortex plays a key role in reducing competing signals from non-target stimuli, enabling prioritized processing of the most relevant sensory input. This layered neural architecture supports the dynamic modulation of sensory inputs, balancing facilitation and inhibition to optimize perception. Understanding the neural pathways involved in somatosensory integration has potential clinical implications for diagnosing sensory disorders and developing therapeutic strategies. Future research should focus on elucidating the specific neural circuitry and mechanisms that contribute to these complex interactions, providing insights into the broader implications of somatosensory integration on behavior and cognition. In summary, this review highlights the importance of multimodal somatosensory integration in enhancing sensory perception. It also underscores the need for further exploration into the neural underpinnings of these processes to advance our understanding of sensory integration and its applications in clinical settings.

ObjectiveTo establish and validate a new prediction model for the risk of death in patients with acute-on-chronic liver failure （ACLF） based on sarcopenia and other clinical indicators， and to improve the accuracy of prognostic assessment for ACLF patients. MethodsA total of 380 patients with ACLF who were admitted to Beijing YouAn Hospital， Capital Medical University， from January 2019 to January 2022 were enrolled， and they were divided into training group with 228 patients and testing group with 152 patients in a ratio of 6∶4 using the stratified random sampling method. For the training group， CT images were used to measure the cross-sectional area of the skeletal muscle at the third lumbar vertebra （L3）， and L3 skeletal muscle index （L3-SMI） was calculated. Sarcopenia was diagnosed based on the previously established L3-SMI reference values for healthy adults in northern China. Univariate and multivariable Cox regression analyses were used to establish a sarcopenia-ACLF model which integrated sarcopenia and clinical risk factors， and a nomogram was developed for presentation. The area under the ROC curve （AUC） was used to assess the predictive performance of the model， the calibration curve was used to assess the degree of calibration， and a decision curve analysis was used to investigate the clinical application value of the model. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. The Kaplan-Meier method was used to plot survival curves， and the Log-rank test was used for comparison between groups. The DeLong test was used for comparison of AUC between different models. ResultsThe multivariate Cox regression analysis showed that sarcopenia （hazard ratio ［HR］=1.962， 95% confidence interval ［CI］： 1.185‍ ‍—‍ ‍3.250， P=0.009）， total bilirubin （HR=1.003， 95%CI： 1.002‍ ‍—‍ ‍1.005， P<0.001）， international normalized ratio （HR=1.997， 95%CI： 1.674‍ ‍—‍ ‍2.382， P<0.001）， and lactic acid （HR=1.382， 95%CI： 1.170‍ ‍—‍ ‍1.632， P<0.001） were included in the sarcopenia-ACLF model. In the training cohort， the sarcopenia-ACLF model had a larger AUC than MELD-Na score in predicting 90-day mortality in patients with ACLF （0.80 vs 0.73， Z=1.97， P=0.049）. In the test cohort， the sarcopenia-ACLF model had a significantly larger AUC than MELD score （0.79 vs 0.69， Z=2.70， P=0.007） and MELD-Na score （0.79 vs 0.68， Z=2.92， P=0.004）. The calibration curve showed that the model had good calibration ability， with a relatively good consistency between the predicted risk of mortality and the observed results. The DCA results showed that within a reasonable range of threshold probabilities， the sarcopenia-ACLF model showed a greater net benefit than MELD and MELD-Na scores in both the training cohort and the test cohort. ConclusionThe sarcopenia-ACLF model developed in this study provides a more accurate tool for predicting the risk of 90-day mortality in ACLF patients， which provides support for clinical decision-making and helps to optimize treatment strategies.

Objective:To investigate the value of traditional metabolic parameters, CT features and intratumoral heterogeneity parameters measured by 18F-FDG PET/CT in predicting the mutation status of the epidermal growth factor receptor (EGFR) gene in patients with adenocarcinoma. Methods:A total of 147 patients (73 males, 74 females, age (59.8±10.2) years) with pathological confirmed adenocarcinoma between January 2016 and June 2020 in the Affiliated Hospital of Jining Medical University were retrospectively included. The differences of clinical data (smoking history, tumor location and clinical stage), CT features (maximum diameter, ground-glass opacity content, lobulation, speculation, cavitation, air-bronchogram, pleural retraction and bronchial cut-off sign), 18F-FDG PET/CT traditional metabolic parameters (SUV max, SUV mean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG)) and intratumoral heterogeneity parameters ( CV, heterogeneity index (HI)) were analyzed between patients with EGFR mutation and patients with EGFR wild-type. Independent-sample t test, Mann-Whitney U test and χ2 test were used to analyze the data. Multivariate logistic regression was used to analyze the predictors of EGFR mutation. ROC curve analysis was used to evaluate the predictive value of clinical and PET/CT information. Results:Among 147 patients, 87 were with EGFR mutation and 60 were with EGFR wild-type. There were significant differences in gender (male/female), smoking history (with/without), location (peripheral lesion/central lesion), pleural retraction (with/without), SUV max, SUV mean, TLG, CV and HI ( χ2 values: 4.72-23.89, z values: from -2.31 to 5.74, all P<0.05). Multivariate logistic regression analysis showed that smoking history (odds ratio ( OR)=0.167, 95% CI: 0.076-0.366; P<0.001), pleural retraction ( OR=1.404, 95% CI: 1.115-3.745; P=0.012), SUV max ( OR=0.922, 95% CI: 0.855-0.995; P=0.003), TLG ( OR=0.991, 95% CI: 0.986-0.996; P=0.001) and HI ( OR=0.796, 95% CI: 0.700-0.859; P<0.001) were predictors of EGFR mutation. ROC curve analysis showed the AUC of HI was 0.779, with the sensitivity of 76.67%(46/60) and the specificity of 79.31%(69/87). The predictive model was constructed by combining smoking history, pleural retraction, TLG, SUV max and HI, and the AUC was 0.908, with the sensitivity of 88.33%(53/60) and the specificity of 68.97%(60/87). The difference of AUCs between HI and the predictive model was statistically significant ( z=3.71, P<0.001). Conclusion:HI can predict EGFR mutations better, and the predictive value for EGFR mutations can be enhanced when combining HI with smoking history, pleural retraction, TLG and SUV max.

BACKGROUND:Satisfactory clinical results have been achieved in the treatment of Sanders Ⅲ calcaneal fractures by percutaneous compression fixation with three-dimensional frame screws.However,whether the stability of minimally invasive plate internal fixation can be achieved in terms of biomechanics,and the advantages and disadvantages after comparison are still unknown. OBJECTIVE:To investigate the fixation effect of different internal fixation devices on Sanders Ⅲ calcaneal fractures by finite element analysis. METHODS:A finite element model of Sanders Ⅲ calcaneal fracture was made based on CT data of a 26-year-old healthy male volunteer.The calcaneal fracture models were fixed by minimally invasive three-dimensional frame screws and minimally invasive Y-plate.The longitudinal loads of 350 and 700 N were applied respectively.The displacement and stress distribution of the two models were analyzed,and the stability of each model was compared. RESULTS AND CONCLUSION:(1)The peak stress of bone block and implant in the minimally invasive three-dimensional frame screw model was significantly lower than that in the minimally invasive minimally invasive plate model.The average stress of bone block and implant in the three-dimensional frame screw model was also significantly lower than that in the minimally invasive plate model.(2)The maximum displacement of the two models was located at the medial side of the articular surface of the posterior talus,and the maximum displacement of the three-dimensional frame screw model was smaller than that of the minimally invasive plate model.(3)The longitudinal displacement between the anterior fragment and the medial fragment of the minimally invasive plate model was smaller,and the transverse and vertical displacement between the medial fragment and the middle fragment of the three-dimensional group screw model was smaller.(4)It is concluded that both of the two internal fixation models can provide satisfactory fixation effect.The three-dimensional frame screw model can provide better transverse and vertical stability with more uniform stress distribution and smaller comprehensive displacement of bone fragments,while the minimally invasive plate has more advantages in maintaining longitudinal stability.

As public hospitals continue to expand,buildings continue to age,sporadic renovation projects are increas-ing,and expenditures are increasing.In order to ensure the safe,stable and efficient operation of the hospital,the piecemeal re-pair project has become an important basic guarantee for the hospital.There are many kinds of sporadic repair projects,and the projects are trivial and scattered.The contradictions among the needs,cost control,management ability and service quality of sporadic repair projects are becoming increasingly prominent,which has become the difficulty and pain point of logistics service management.In the practice of hospital sporadic repair project management,the traditional project management mode is broken,the whole process of fine management system is established,the level of management personnel and the whole process of the pro-ject are effectively integrated,and the management ability and service quality of sporadic maintenance projects are comprehensive-ly improved.

The microbiological quality of laboratory animals is crucial for the validity and reproducibility of scientific research data,as well as human health and animal welfare.Currently,individual ventilation cages(IVC)have become the mainstream feeding system for rodent laboratory animals.The most commonly used pathogen monitoring method for this feeding system is soiled bedding sentinels(SBS).This method monitors the microbial carrying status of mouse colony through indirect contact and delayed feedback.It can effectively monitor pathogens transmitted via the fecal-oral route,such as mouse hepatitis virus and reovirus.However,this method has difficulty detecting pathogens mainly transmitted through aerosols or direct contact,such as Sendai virus and Pasteurella pneumotropica.The exhaust air dust(EAD)-PCR monitoring method involves swab sampling in the IVC exhaust ducts to monitor the corresponding racks of the ducts;swab sampling before the prefiltration of the host to monitor the entire IVC rack;and EAD collection device sampling to monitor all racks connected to the same host.Different IVC manufacturers have developed corresponding EAD collection devices for their respective IVC systems,making operations convenient and standardization easy.Compared with the SBS method,the EAD-PCR method significantly improves detection rate and timeliness,with the fastest detection possible after one week of exposure.It can serve as a supplement or replacement for the SBS method.Currently,increasing evidence supports that EAD-PCR testing is a more reliable,sensitive,and cost-effective monitoring method,and is more beneficial to animal welfare.This article reviews the application progress of these two methods for monitoring pathogens,analyzes the existing limitations of the EAD-PCR method,and proposes solutions based on its implementation in our laboratory and examination units.The EAD-PCR method helps reduce the number of live sentinel animals used in pathogen monitoring,in order to better maintain the"3Rs"principle of laboratory animal welfare.

Objective To investigate the effect of matrine on improving diabetic nephropathy(DN)through transforming growth factor β/signal transduction protein(TGF-β/Smads)pathway.Methods C57BL/6 mice were randomly divided into NC group,DN group,DN+matrine group,and DN+metformin group,with 10 mice in each group.Except for NC group,other groups were established DN models by high-fat and high-sugar diet combined with intraperitoneal injection of streptozotocin(STZ).After successful modeling,DN+matrine group was treated with matrine for 4 weeks,DN+metformin group was treated with metformin,DN and NC groups were given equal volumes of 0.9％NaCl.Western blot was used to detect the expression of collagen Ⅳ(Col Ⅳ),fibronectin(FN),Smad family member 2/3(Smad2/3),and phosphorylated Smad2/3(p-Smad2/3)in kidney.Biochemical method were used to detect blood glucose,creatinine,and urea nitrogen levels of mice.Results In NC group,DN group and DN+matrine group,blood glucose levels were(8.16±2.53),(24.84±4.67)and(23.88±3.57)mmol·L-1;blood creatinine levels were(36.48±5.63),(97.51±10.59)and(41.88±7.26)mmol·L-1;urea nitrogen levels were(53.11±4.72),(91.50±8.62)and(63.29±5.69)mmol·L-1;Col Ⅳ protein expression levels in kidney were 1.00±0.19,3.34±0.58 and 1.99±0.44;FN protein expression levels were 1.00±0.21,3.63±0.47 and 1.79±0.43;p-Smad2/3/Smad2/3 were 1.00±0.18,2.74±0.51 and 1.08±0.33.Above indicators showed statistically significant differences between NC group and DN group(all P＜0.05).Conclusion Matrine can effectively inhibit the activation of TGF-β1/Smads signaling pathway and reduce the polyproduct of extracellular matrix-related proteins,thus playing a protective role in DN kidney injury.

Objective To screen and analyze the influencing factors of severity in the patients with type 2 diabetes mellitus (T2DM) complicating cerebral small vessel disease (CSVD).Methods A total of 519 pa-tients with T2DM complicating CSVD admitted and treated in Nanjing Municipal Hospital of Traditional Chi-nese Medicine from June 2018 to May 2023 were selected and divided into the mild group (n=214) and the se-vere group (n=305) according to the CSVD imageological score.The relevant demographic,laboratory and imageological indicators were collected.The influencing factors of T2DM complicating CSVD were screened out by the LASSO and Logistic regression analysis and the predictive model was established.The receiver op-erating characteristic (ROC) curve,goodness of fit evaluation and restricted cubic spline (RCS) fitting curve were drawn to analyze the dose-response relationship between Cys C,albumin/globulin (A/G) ratio with the disease severity.Results The male proportion and age in the severe group were greater than those in the mild group,neutrophil,systemic immune-inflammation index (SII),creatinine (Crea),uric acid (UA),Urea (Ure-a),D-dimer (D-D),lactate dehydrogenase (LDH),adenosine deaminase (ADA),globulin (GLB) and Cys C were higher than those in the mild group,lymphocyte,ALT,High density Lipoprotein-cholesterol (HDL-C),serum cholinesterase (CHE),prealbumin (PAB),and A/G were lower than those in the mild group,and the differences were statistically significant (P<0.05).LASSO and logistic regression analysis showed that the gender,age,A/G and Cys C were the independent influencing factors in the patients with T2DM complicating CSVD.The area under the curve (AUC) of this model was 0.658 (95%CI:0.610-0.706) with goodness of fit (P=0.520).The RCS fitting curves showed that serum Cys C≥0.618 mg/L had a linear relationship with CSVD imageological score (P=0.035),and A/G≥1.268 had a nonlinear relationship with CSVD imageologi-cal score (P=0.007).Conclusion The advanced age,male,increased Cys C level and decreased A/G in the pa-tients with T2DM complicating CSVD are the independent risk factors for the severity of whole brain damage.

Objective To screen the characteristic factors of renal impairment occurrence in the patients with hyperuricemia,and to analyze its diagnostic value and establish a diagnostic model.Methods A total of 2405 inpatients with diagnosed hyperuricemia in the Nanjing Municipal Hospital of Traditional Chinese Medi-cine,Nanjing University of Traditional Chinese Medicine from December 2018 to December 2022 were selected and divided into the kidney lesion group (n=1343) and the non-kidney lesion group (n=1062) according to eGFR.The characteristic factors of hyperuricemia caused renal impairment were screened and analyzed by Lasso and logistic regression and the diagnostic model was constructed.The diagnostic value of characteristic factors and diagnostic model were evaluated by the receiver operating characteristic (ROC) curve,and the change rule between the characteristic factors and the results was found by the restricted cubic splines (RCS) fitting.Results The age,uric acid (UA),cystatin-C (Cys-C) and retinol-binding protein (RBP) were the characteristic factors of hyperuricemia caused renal impairment.The combined diagnostic model:logit (P)=-8.70+0.602×age (10 years old)+0.033×UA (10 μmol/L)+0.277×Cys-C (0.1 mg/L)+0.189×RBP (10 mg/L),the area under the ROC curve (AUC) of the combined diagnosis model was 0.893 (95％CI:0.880-0.905).For every 10 μmol/L increase in blood UA,the risk of renal impairment occurrence in hyperurice-mia was increased by 3％;for every 10 years increase in age,the risk of renal impairment occurrence in hyperu-ricemia was increased by 83％;for every 10 mg/L increase in RBP,the risk of kidney damage occurrence of re-nal impairment in hyperuricemia was increased by 21％;for every 0.1 mg/L increase in Cys-C,the risk of re-nal impairment occurrence in hyperuricemia was increased by 32％.Conclusion The combined diagnostic model for whether the renal impairment in the patients with hyperuricemia occurring has good diagnostic val-ue,and Cys-C deserves more attention.

Infrared spectroscopy technology has many advantages such as high efficiency and non-destructiveness,and has an important research and application value in the field of petroleum pollutant classification and detection.In this study,a petroleum pollutant classification method by combing the discrete wavelet transform(DWT)algorithm and a one-dimensional convolutional neural network based on the Inception module(Inception-1D-CNN)was proposed.Firstly,the DWT algorithm was used to denoise the original infrared spectral data to eliminate the interference information caused by experimental environment,instrument error and manual operation.Then,the inception-1D-CNN model was used to obtain multi-scale infrared spectroscopy feature information,and then classify the petroleum pollutants.Experimental results showed that compared with preprocessing methods such as standard normal variable(SNV),adaptive iteratively reweighted penalized least squares(AirPLS),and Savitzky-Golay smoothing(S-G),the prediction accuracy of the DWT algorithm combined with the 1D-CNN model with a convolutional kernel size of 3×1 was 86.6%,which was 6.6%,6.6%and 3.3%higher,respectively.The prediction accuracy of DWT algorithm combined with 1D-CNN model with a convolutional kernel size of 5×1 was 93.3%,which was 10.0%,7.0%and 3.3%higher,respectively.The prediction accuracy of the DWT algorithm combined with the 1D-CNN model with a convolutional kernel size of 7×1 was 90.0%,which was 6.7%,10.0%and 3.4%higher,respectively.The prediction accuracy of the DWT algorithm combined with the inception-1D-CNN model was 100.0%,which was 10.0%,10.0%and 3.4%higher,respectively.Therefore,the DWT algorithm combined with the inception-1D-CNN model could accurately classify and predict petroleum pollutants,and provided a certain basis for the subsequent treatment of oil spills on the sea surface.