Nitrogen narcosis is a neurological syndrome that manifests when humans or animals encounter hyperbaric nitrogen, resulting in a range of motor, emotional, and cognitive abnormalities. The anterior cingulate cortex (ACC) is known for its significant involvement in regulating motivation, cognition, and action. However, its specific contribution to nitrogen narcosis-induced hyperlocomotion and the underlying mechanisms remain poorly understood. Here we report that exposure to hyperbaric nitrogen notably increased the locomotor activity of mice in a pressure-dependent manner. Concurrently, this exposure induced heightened activation among neurons in both the ACC and dorsal medial striatum (DMS). Notably, chemogenetic inhibition of ACC neurons effectively suppressed hyperlocomotion. Conversely, chemogenetic excitation lowered the hyperbaric pressure threshold required to induce hyperlocomotion. Moreover, both chemogenetic inhibition and genetic ablation of activity-dependent neurons within the ACC reduced the hyperlocomotion. Further investigation revealed that ACC neurons project to the DMS, and chemogenetic inhibition of ACC-DMS projections resulted in a reduction in hyperlocomotion. Finally, nitrogen narcosis led to an increase in local field potentials in the theta frequency band and a decrease in the alpha frequency band in both the ACC and DMS. These results collectively suggest that excitatory neurons within the ACC, along with their projections to the DMS, play a pivotal role in regulating the hyperlocomotion induced by exposure to hyperbaric nitrogen.
Animals ; Gyrus Cinguli/drug effects* ; Male ; Mice, Inbred C57BL ; Locomotion/drug effects* ; Neurons/drug effects* ; Mice ; Nitrogen/toxicity* ; Inert Gas Narcosis/physiopathology* ; Corpus Striatum/physiopathology*

OBJECTIVE: To evaluate the short-and medium-term efficacy of posterior medial branch block in the treatment of persistent pain after percutaneous vertebral augmentation. METHODS: From January 2018 to January 2023, a total of 1, 062 patients with osteoporotic vertebral compression fractures underwent percutaneous vertebral augmentation. Among them, 32 elderly patients who experienced persistent low back pain after surgery and subsequently received posterior medial branch block and cryoablation were included. Six patients died during follow-up, leaving 26 patients for final analysis (1 male, 25 females). The mean age was (82.96±5.66) years (ranged, 76 to 94 years). The mean body mass index was (23.76±3.08) kg·m^-2(ranged 18.1 to 27.2 kg·m^-2). The bone mineral density T-value ranged from -2.5 to -4.3 with a mean of (-3.09±0.56). The mean volume of bone cement injected was 6.00 (5.38, 7.00) ml. Fracture locations were T₁₁ (2 cases), T₁₂ (7 cases), L₁ (10 cases), L₂ (6 cases), and L₃ (1 case). The mean interval from vertebral augmentation to block treatment was (7.12±2.22) months (rangd 6 to 12 months). The vertebral augmentation procedures were percutaneous kyphoplasty(PKP) in 12 cases and percutaneous vertebroplasty (PVP) in 14 cases. At the 2nd week, 3rd month, and 6th month after the block, the numerical rating scale(NRS), Oswestry disability index(ODI), patient satisfaction, and pain relief rate at the 6th month were evaluated. Relationships between pain relief rate at the 6th month after the last treatment and possible influencing factors were analyzed. RESULTS: Compared with X-ray films after percutaneous vertebral augmentation, the X-ray films before block showed an increase in kyphotic angle and vertebral compression rate, with statistically significant differences(P<0.05). At the 2nd week, 3rd month, and 6th month after posterior medial branch block and cryoablation, NRS and ODI scores were significantly lower than before the block(P<0.05). Among the 26 patients, 5 received additional cryoablation. At the 6th month after the last treatment, 19 patients reported excellent or good satisfaction. Univariate binary Logistic analysis showed all P>0.05, and no independent factor affecting final satisfaction or pain relief at 6 months after the last treatment was identified. CONCLUSION Posterior medial branch block(with cryoablation) can effectively improve short-and medium-term symptoms and function in patients with persistent axial low back pain after percutaneous vertebral augmentation for osteoporotic vertebral fractures.
Humans ; Male ; Female ; Aged ; Spinal Fractures/surgery* ; Aged, 80 and over ; Osteoporotic Fractures/surgery* ; Vertebroplasty/adverse effects* ; Nerve Block/methods*

Nitrogen oxides(NOx=NO+NO2)are important precursors of ozone(O3),and NOx and its oxides together constitute reactive nitrogen oxides(NOy)in the atmosphere.A comprehensive understanding of the total NOy level in the atmosphere is of great significance for a deeper understanding of the atmospheric nitrogen cycle and oxidation,as well as for formulating strategies for air pollution prevention and control.In this work,a thermal decomposition-broadband cavity enhanced absorption spectroscopy(TD-BBCEAS)technique for online measurement of total NOy in the atmosphere was developed.With this method,the NOy was efficiently converted into NO2,and the total NOy concentration in the atmosphere was indirectly obtained by measuring NO2.Focusing on the key factors affecting the measurement of total NOy,the influence of NO titration efficiency and other NOy component TD efficiency on measurement accuracy was emphasized.By changing the oxygen(O2)flow rate through the mercury lamp to alter the O3 concentration for titrating NO,the conversion efficiency of NO was evaluated.At O2 flow rate of 6 mL/min,the conversion efficiency of NO was greater than 99%.TD efficiency testing and analysis on NO2,peroxyacetyl nitrate(PAN),nitric acid(HNO3),and nitrous acid(HONO),which account for a large proportion of atmospheric NOy components,was carried out using 680℃as the optimal TD temperature for efficient conversion of NOy.With NO and HONO sample gases as typical verification gases,the conversion efficiency of NOy and the accuracy of NOy measurement by TD-BBCEAS system were verified by switching the on and off modes of mercury lamp and TD device.At integration time of 60 s,the detection limit of the system for NOy was 2.83×1010 molecules/cm3(60 s,2σ).A comparative measurement of actual atmospheric NOy was conducted between the TD-BBCEAS system and the NOy analyzer.The observation results showed a correlation coefficient(R2)of 0.98 and a slope of 0.93,further verifying the feasibility and accuracy of applying the TD-BBCEAS system to measurement of total NOy.

Chagas disease(American trypanosomiasis)is a zoonosis caused by Trypanosoma cruzi,which severely affects public health.Recently,with changes in economic globalization and increased population mobility,this disease has gradually spread from the original Latin American epidemic areas to non-epidemic areas,such as Europe,thus showing a trend of globalization.The main trans-mission routes have changed from transmission via the Triatomine vector to blood transfusion transmission,mother-to-child transmis-sion,oral transmission,and other routes.Consequently,Chagas disease is spreading globally,and more people are increasingly vul-nerable to infection.This article retrospectively reviews research on the transmission routes of Chagas disease,analyzes the changing trends in transmission routes,and provides a scientific basis for the formulation and optimization of Chagas disease prevention and con-trol strategies from a One Health perspective.

The aim of this study was to establish a rapid,highly sensitive,and specific nucleic acid detection method for the H5N6 and H9N2 avian influenza virus(AIV)subtypes by using reverse transcription-recombinase polymerase amplification(RT-RPA)combined with clustered regularly interspaced short palindromic repeats(CRISPR)-Cas13a proteins.The conserved regions were selected to design specific RT-RPA primers and crRNA sequences of H5,H6,H9,and N2 genes.RT-RPA tech-nology combined with CRISPR-Cas13a detection was used to evaluate the sensitivity and specificity of AIV nucleic acid detec-tion.The detection was performed on avian influenza environmental samples and compared with the results of fluorescence quantitative RT-PCR,to evaluate the effectiveness of the RT-RPA technology combined with CRISPR-Cas13a.AIV H5,H9,and N2 subtypes were detected with a sensitivity as high as 1 copy/μL,and AIV N6 subtypes were detected with a sensitivity of 10 copies/μL.Plasmid samples with differing copy numbers showed fluorescence under blue LED transillumination.The four AIV subtypes showed high specificity and did not cross-react with the other AIV subtypes.The detection of avian influenza ex-ternal environmental samples containing AIV H5,N6,and H9 subtypes was consistent with the results of fluorescence quanti-tative RT-PCR,with 100％accuracy.For AIV N2 subtypes,one additional negative sample was detected with 97.9％accuracy.The established RT-RPA technology combined with CRISPR-Cas13a detection enabled sensitive,specific visual detection of AIV H5N6 and H9N2 subtypes.This study provides a new nucleic acid detection method for AIV surveillance and subtype clas-sification.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Objective To propose a lightweight deep learning network-based segmentation method for automatic segmenta-tion of the skeletal muscle at the third cervical spine(C3)level.Methods Firstly,121 patients with head and neck tumors admitted to the Department of Oncology of Zigong First People's Hospital from January 2019 to December 2022 were selected and randomly divided into a training set,a validation set and a test set in the ratio of 7∶1∶2.Secondly,a lightweight Mamba architecture was introduced into the UNet network and an attention gate(AG)mechanism was added to the skip connection path to construct a MB-UNet network model.Finally,the trained network models were evaluated for segmentation performance on the test set,the MB-UNet network model was compared with manual segmentation over the results of determination of skeletal muscle area(SMA),and with classical network models in terms of parameter scale and computation effort including UNet,Deeplab V3+,U2Net,VMUNet and UltraLight-VMUNet models.The time required by the MB-UNet network model for predicting SMA and that by the physician with the assistance of the model was summarized.Results When used for segmenting the skeletal muscle at C3 level the constructued MB-UNet network model gained advantages over the classical models,with a Dice similarity coefficient of 88.23%,an intersection over union(IoU)ratio of 78.94%,a sensitivity of 91.27%and a 95%Hausdorff distance of 7.13 mm;the SMA determined by manual segementation was basically close to that by the MB-UNet network model;the MB-UNet network model behaved generally better than the classical network models,with the computation effort being 1.88 GFLOPS and the parameter scale being 0.77M;it took the MB-UNet network model 1.93 s for the prediction on the test set,and only 2 min for the physician to obtain satisfactory results with the assistance of the MB-UNet network model,which was significantly shorter than that by munual segmentation(20 min).Conclusion The proposed method contributes to segmenting the skeletal muscle at C3 level precisely and rapidly and calculating SMA accurately,which helps clinicians to quickly diagnose sarcopenia in patients with head and neck tumors and improves the diagnostic efficiency.[Chinese Medical Equipment Journal,2025,46(8):11-17]

Objective To propose a lightweight deep learning network-based segmentation method for automatic segmenta-tion of the skeletal muscle at the third cervical spine(C3)level.Methods Firstly,121 patients with head and neck tumors admitted to the Department of Oncology of Zigong First People's Hospital from January 2019 to December 2022 were selected and randomly divided into a training set,a validation set and a test set in the ratio of 7∶1∶2.Secondly,a lightweight Mamba architecture was introduced into the UNet network and an attention gate(AG)mechanism was added to the skip connection path to construct a MB-UNet network model.Finally,the trained network models were evaluated for segmentation performance on the test set,the MB-UNet network model was compared with manual segmentation over the results of determination of skeletal muscle area(SMA),and with classical network models in terms of parameter scale and computation effort including UNet,Deeplab V3+,U2Net,VMUNet and UltraLight-VMUNet models.The time required by the MB-UNet network model for predicting SMA and that by the physician with the assistance of the model was summarized.Results When used for segmenting the skeletal muscle at C3 level the constructued MB-UNet network model gained advantages over the classical models,with a Dice similarity coefficient of 88.23%,an intersection over union(IoU)ratio of 78.94%,a sensitivity of 91.27%and a 95%Hausdorff distance of 7.13 mm;the SMA determined by manual segementation was basically close to that by the MB-UNet network model;the MB-UNet network model behaved generally better than the classical network models,with the computation effort being 1.88 GFLOPS and the parameter scale being 0.77M;it took the MB-UNet network model 1.93 s for the prediction on the test set,and only 2 min for the physician to obtain satisfactory results with the assistance of the MB-UNet network model,which was significantly shorter than that by munual segmentation(20 min).Conclusion The proposed method contributes to segmenting the skeletal muscle at C3 level precisely and rapidly and calculating SMA accurately,which helps clinicians to quickly diagnose sarcopenia in patients with head and neck tumors and improves the diagnostic efficiency.[Chinese Medical Equipment Journal,2025,46(8):11-17]

Objective:To analyze the thematic distribution characteristics and evolution trends of the compensation mechanism reform policies for public hospitals in China since the new healthcare reform,and to provide references for correctly understanding the basic connotation and extension of the reform of compensation mechanism.Methods:A total of 75 documents issued at the national level were collected.The BERTopic topic model was used for thematic identification.The dynamic topic modeling method of BERTopic was adopted to conduct policy evolution analysis.Result:Since the new medical reform,the reform policy of compensation mechanism in public hospitals can be divided into eight themes,such as strengthening the operation management of public hospitals and adjusting the price of medical services.It shows an evolutionary trend of emphasizing the control of excessive growth of medical expenses and the implementation of government investment responsibilities in the early stage,focusing on the elimination of drug additions and the adjustment of medical service prices in the middle stage,and strengthening the reform of medical insurance payment methods in the later stage.Conclusions:The reform of the compensation mechanism for public hospitals is essentially a systematic reconstruction of the operation mechanism of public hospitals.Adjusting and optimizing medical service prices and reforming the medical insurance payment method are the key and focus of improving the compensation mechanism for public hospitals.