Objective To analyze the infection status and epidemic trends of soil-borne nematode infections in Yubei, Chongqing City, in 2010,2021, and 2022. Methods The local populations from four survey sites of four towns in 2010 and five sites of five towns in 2021 and 2022 were surveyed regarding their basic information using a unified form. Fecal samples of the participants were collected and tested for soil-borne nematode infections using the modified Kato-Katz thick smear method. Results In 2010, 2 049 participants were surveyed, followed by 1 000 participants in 2021 and 2022. The overall prevalence of parasitic infections declined significantly from 3.86% to 0.20%. In 2010, soil-transmitted nematode included hookworms(3.81%) and roundworms(0.29%). In 2021, the infection rates of roundworms and hookworms were 1.70% and 0.10% respectively. Notably, only Ascaris was identified in 2022(0.20%). The≥60 age group consistently exhibited the highest infection rates across all surveys, followed by the 40-59 age group. The infection rates of males in the three surveys were 3.31%,1.92%, and 0.20% respectively, and those of females were 4.37%, 1.46%, and 0.20% respectively. There was no statistically significant difference in the infection rates between males and females. Educational attainment was inversely associated with infection; in 2010, the highest prevalence was observed among those with primary education or below, whereas in 2021, illiterate or semi-literate individuals showed the highest susceptibility. The occupational distribution of infections in 2010 indicated that retirees (8.33%), farmers(4.86%), and homemakers or unemployed individuals(3.45%)were the most affected. However, in 2021 and 2022, farmers emerged as the predominant occupational group with soil-transmitted nematode infections. Conclusions The infection rate of soil-borne nematodes showed a decreasing trend in Yubei, and the infection species changed from hookworms in 2010 to Ascaris in 2022. Farmers, the elderly, and people with low education levels should continue to be the focus of preventive and control efforts.

Pain modulation encompasses a complex neurobiological process, in which the lateral habenula (LHb) plays a crucial role in integrating, regulating and modulating pain signals. It is also involved in pain-related memory functions associated with perception, transmission and regulation of pain. Furthermore, the LHb collaborates with structures such as the spinal dorsal horn, forebrain, and amygdala to form an essential neural circuit that contributes to sensitization, development of tolerance, and adaptation processes related to pain. However, there remains limited understanding regarding the specific roles and interactions among different neuron subtypes within the LHb concerning pain regulation. Additionally, further investigation is warranted to explore functional changes and plasticity within both the LHb and its associated neural circuits in chronic pain models. Future research endeavors should utilize advanced neuroimaging techniques alongside optogenetics and gene editing technologies to elucidate intricate neural circuits, cellular architecture, and molecular mechanisms governing LHb function in pain regulation. In conclusion, this paper aims to comprehensively review existing literature on the involvement of the LHb and its neural circuits in modulating pain, thereby enhancing our understanding of their neurobiological mechanisms while providing novel targets for precise therapeutic strategies aimed at alleviating pain.

Multiple sclerosis(MS)is a demyelinating disease of the central nervous system associated with autoimmunity.Its main pathological characteristics involve glial hyperplasia,demyelination and axonal damage accompanied by inflammatory infiltration of the central nervous system.Currently,it is believed that MS is related to multiple factors such as genetic susceptibility,environment,infection,lifestyle,and immunity.However,its exact etiology remains unclear.In recent years,studies have shown that both MS patients and experimental autoimmune encephalomyelitis animal models are closely associated with fungal infection.This review summarizes the research progress on the correlation between fungal infection and MS,and the role of fungi in the pathogenesis of MS,aiming to provide new insights for exploring the pathogenesis,clinical diagnosis and treatment of MS.

Objective To investigate the correlation of corneal α angle and κ angle with lens tilt in normal human eyes using a new swept-source optical biometer.Methods A cross-sectional study was conducted,involving 303 healthy eyes(148 right eyes and 155 left eyes)of patients who visited the First Affiliated Hospital of Kunming Medical University from June to August 2024.ZW-30 swept-source optical biometer was used to collect the lens tilt angle,κ angle(distance from the corneal light reflex to the pupil center),and α angle(distance from corneal light reflex to the corneal geometric center,which is the midpoint of the horizontal white to white(WTW)diameter).The degrees(°)and directions of κ angle and α angle were calculated by the ratio of the above measurements to the anterior chamber depth(ACD)respectively.Spearman correlation analysis and linear regression analysis were employed to evaluate the correlations between the magnitude and direction of corneal α angle,κ angle and lens tilt angle.Results The magnitude and direction of corneal α angle,κ angle,and lens tilt angle in the right eye were as follows respectively:(0.54±0.19)mm(7.81°±3.88°),194.43°±39.75°;(0.27±0.23)mm(4.72°±3.90°),181.07°±79.59°;5.52°±1.67°,188.21°±25.73°.For the left eye,the corresponding values were:(0.47±0.27)mm(8.12°±5.26°),336.04°±46.64°;(0.26±0.27)mm(4.45°±4.80°),322.86°±107.79°;5.50°±1.61°,340.65°±32.84°.Spearman's correlation analysis showed that the correlation coefficients between corneal α angle and lens tilt angle in the right eye were 0.609(distance correlation)and 0.625(angle correlation),while those for κ angle were 0.559(distance correlation)and 0.578(angle correlation).In the left eye,the correlation coefficients between corneal α angle and lens tilt angle were 0.545(distance correlation)and 0.552(angle correlation),and those for κ angle were 0.377(distance correlation)and 0.395(angle correlation).In addition,the correlation coefficient between the direction of corneal α angle and the direction of lens tilt angle in the right eye was 0.343,and that for κ angle direction was 0.284;in the left eye,the correlation coefficients were 0.216(α angle direction)and 0.198(κ angle direction),all with statistical significance(P<0.05).Univariate linear regression analysis showed that lens tilt was positively correlated with both corneal α angle and Kappa angle(P<0.05).Conclusions Corneal α angle and κ angle are highly correlated with lens tilt angle in both eyes,and the correlation of corneal α angle is stronger than that of κ angle in both left and right eyes.The correlation expressed by degree(°)is better than that by distance(mm).It is recommended to refer to the corneal α angle and κ angle expressed in degrees during preoperative evaluation.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Pain modulation encompasses a complex neurobiological process, in which the lateral habenula (LHb) plays a crucial role in integrating, regulating and modulating pain signals. It is also involved in pain-related memory functions associated with perception, transmission and regulation of pain. Furthermore, the LHb collaborates with structures such as the spinal dorsal horn, forebrain, and amygdala to form an essential neural circuit that contributes to sensitization, development of tolerance, and adaptation processes related to pain. However, there remains limited understanding regarding the specific roles and interactions among different neuron subtypes within the LHb concerning pain regulation. Additionally, further investigation is warranted to explore functional changes and plasticity within both the LHb and its associated neural circuits in chronic pain models. Future research endeavors should utilize advanced neuroimaging techniques alongside optogenetics and gene editing technologies to elucidate intricate neural circuits, cellular architecture, and molecular mechanisms governing LHb function in pain regulation. In conclusion, this paper aims to comprehensively review existing literature on the involvement of the LHb and its neural circuits in modulating pain, thereby enhancing our understanding of their neurobiological mechanisms while providing novel targets for precise therapeutic strategies aimed at alleviating pain.

[This corrects the article DOI: 10.11909/j.issn.1671-5411.2017.08.005.].

AIM To study the quassinoids and lignans from Brucea javanica (L.) Merr.and their anti-inflammatory activities.METHODS The extract was isolated and purified by silica gel,MCI,Sephadex LH-20 and HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Seven quassinoids were isolated and identified as bruceanic acid E (1),15-O-(3-hydroxy-3-methy1butanoyl)-brucealide (2),bruceine L (3),aglycone of yadanzioside D (4),javanicolide A (5),javanicolide C (6),bruceanic acid A (7).Four lignans were isolated and identified as cleomiscosin A (8),ceplignan (9),threo-guaiacylglycerol 8'-(4-hydroxymethyl-2-methoxyphenyl) ether (10),erythro-guaiacylglycerol 8'-(4-hydroxy-methyl-2-methoxyphenyl) ether (11).Compounds 3,8 could inhibit NO release in RAW264.7 cells.CONCLUSION Compounds 9-11 are isolated from Brucea genus for the first time.Compounds 3 and 8 have anti-inflammatory activities.

Objective To achieve intelligent recognition and segmentation of common craniocerebral inju-ries(hereinafter referred to as"segmentation")by training convolutional neural network DeepLabV3+model based on CT images of blunt craniocerebral injury(BCI),and to explore the value of deep learning in automated diagnosis of BCI in forensic medicine.Methods A total of 5 486 CT images of BCI from living persons were collected as the training set,validation set and test set for model training and performance evaluation.Another 255 CT images of BCI and 156 normal craniocerebral CT images from living persons were collected as the blind test set to evaluate the ability of the model to seg-ment the five types of craniocerebral injuries including scalp hematoma,skull fracture,epidural hema-toma,subdural hematoma,and brain contusion.Another 340 BCI and 120 normal craniocerebral CT images from cadavers were collected as the new blind test set to explore the application value of the model trained by living CT images in the segmentation of BCI in cadavers.The five types CT images of all BCI except the blind test set were manually labeled;then,each dataset was inputted into the model to train the model.The performance of the model was evaluated and optimized based on the loss function and accuracy curves of the training set and validation set,and the generalization ability was evaluated based on the Dice value of the test set.According to the accuracy,precision and F1 value of the blind test set,the segmentation performance of the model for five types of BCI was evaluated.Results After training and optimizing the model,the average Dice values of the final optimal model to scalp hematoma,skull fracture,epidural hematoma,subdural hematoma and brain contusion segmen-tation were 0.766 4,0.812 3,0.938 7,0.782 7 and 0.858 1,respectively,all greater than 0.75,meeting the expected requirements.External validation showed that the F1 values were 93.02%,89.80%,87.80%,92.93%and 86.57%in living CT images,respectively;83.92%,44.90%,76.47%,64.29%and 48.89%in cadaveric CT images,respectively.The above suggested that the model was able to accu-rately segment various types of craniocerebral injury on living CT images,while its segmentation ability was relatively poor on cadaveric CT images,but still able to accurately segment scalp hematoma,epidu-ral hematoma and subdural hematoma.Conclusion Deep learning model trained on CT images can be used for BCI segmentation.However,the direct use of living persons'BCI models for the identifica-tion of cadaveric BCI has some limitations.This study provides a new approach for intelligent segmen-tation of virtual anatomical data for BCI.

AIM To study the quassinoids and lignans from Brucea javanica (L.) Merr.and their anti-inflammatory activities.METHODS The extract was isolated and purified by silica gel,MCI,Sephadex LH-20 and HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Seven quassinoids were isolated and identified as bruceanic acid E (1),15-O-(3-hydroxy-3-methy1butanoyl)-brucealide (2),bruceine L (3),aglycone of yadanzioside D (4),javanicolide A (5),javanicolide C (6),bruceanic acid A (7).Four lignans were isolated and identified as cleomiscosin A (8),ceplignan (9),threo-guaiacylglycerol 8'-(4-hydroxymethyl-2-methoxyphenyl) ether (10),erythro-guaiacylglycerol 8'-(4-hydroxy-methyl-2-methoxyphenyl) ether (11).Compounds 3,8 could inhibit NO release in RAW264.7 cells.CONCLUSION Compounds 9-11 are isolated from Brucea genus for the first time.Compounds 3 and 8 have anti-inflammatory activities.