Objective This paper aimed to investigate the collaborative coding of two different modes of neural signals including local field potentials and spiking activity (multi-unit activity) which recorded in medial prefrontal cortex of sprague-dawley (SD) rats in Y maze working memory (WM) task,to provide computing support for neural coding mechanism of WM.Methods 1.Experiment data was multi-channel neural signals (local field potentials (LFPs)-Spikes) recorded from prefrontal cortex of 4 SD rats during WM process and resting state,provided by the lab of Neuro-engineering,Tianjin Medical University.2.LFPs preprocessing included baseline drift removing and power-line noise eliminating.3.Physiology window width 500 ms,step 125 ms were selected and average rate per channel was calculated to turn the discrete point signal spikes to continuous signal.4.LFPs characteristic frequency band was obtained by using short time Fourier transform and signals of the characteristic frequency band were extracted by band pass filter.5.Mutual information (MI) of LFPs-spikes was computed to get the distribution of multi-channel MI values.Results 1.LFPs distribution demonstrated that the power focused at θ band (4-12 Hz)during the WM tasks.2.The average MI value of θ band LFPs and spikes (4 rats,over 10 trials) were 0.49±0.04,0.39±0.03,0.41±0.03,0.48±0.02,respectively,which were significantly larger than those in the resting state (t test,P＜0.05).Conclusions These findings indicate that θ band LFPs represents behavior correlated to WM and its synergy with spiking activity plays an important role in encoding WM task.

Objective Toinvestigatetheentropyoflocalfieldpotentials(LFPs)recordedinratmedialprefrontal cortex during a Y-maze working memory (WM) task, to provide computing support for neural coding mechanism.Methods Sixteen-channel LFPs were recorded from SD rats while they performed a Y-maze WM task.The data came from 4 rats, 20 trials (10 correct trials and 10 incorrect trials) per rat provided by laboratory of neurobiology in medicine,Tianjin Medical University.Original LFPs were preprocessed to remove 50 Hz power line noise and baseline drift.Multi-taper Fourier transform was applied to calculate spatial distributions of LFPs and band pass filter were used to extract characteristic signal.The entroy coding of 16 channel LFPs was as follows: the physiological window was set to be 500 ms, the step length of physiological window was set to be 125 ms, windows were added to LFPs data, and then LFPs entropy of each sliding window was computed and averaged to get the trend of multichannel entropy values duringthe WM task.Results The power of θ band (4-12 Hz) in LFPs increased.The averaged entropy value ofmultichannel θ band LFPs in correct trials was 0.939±-0.020, which were larger than those in the resting state, 0.795±0.031 (P＜0.05).Those during wrong WM task had no significant difference, which didn't encode the WM task.Conclusions The principal frequency band related to WM is the θ band and LFPs entropy encodes the WM effectively.

There are eight forms of vitamin E in human blood, including α-, β-, γ-, δ-tocopherols and α-, β-, γ-, δ-tocotrienols. As the most abundant and active form of vitamin E, α-tocopherol is widely accepted as a reliable indicator for nutritional assessment of body vitamin E status across the world. Considering that different vitamin E forms have diverse biological activities, separation and detection of different vitamin E forms in human blood facilitates the understanding of the association between vitamin E and diseases. In this review, the advances in sample-pretreatment techniques and detection techniques for vitamin E in human blood were presented. Currently, the sample-pretreatment techniques include solid-phase extraction, liquid-liquid extraction, dispersive liquid-phase microextraction, supported liquid extraction and direct protein precipitation; the detection techniques include automatic biochemical analysis, enzyme-linked immunosorbent assay, gas chromatography, liquid chromatography and ultra-high performance supercritical fluid chromatography mass spectrometry. This review summarizes the characteristics and scope of above-mentioned techniques used for detection of vitamin E in human blood, so as to provide insights into the selection of an appropriate method for inspection technicians.

Triple-negative breast cancer (TNBC) is a type of breast cancer that is difficult to treat, has a poor prognosis, and is prone to recurrence and metastasis in the early postoperative period. The age of patients is tending younger, and the racial difference is large. It is also related to family history, and genetic susceptibility is obvious. So, elucidating the genetic risk factors of TNBC and obtaining precise therapeutic targets are urgent tasks. Obtaining reliable characteristic genes and their polymorphisms between TNBC of different subtypes is difficult. This review summarizes the susceptibility genes and the polymorphisms of TNBC susceptibility genes of different molecular subtypes, in order to develop effective TNBC prevention strategies and find effective therapeutic targets. This review provides a theoretical basis for promoting the study of TNBC from the perspective of genetics.

Fibroblasts are stromal cells widely distributed in tissues and organs throughout the body.Fibroblasts are involved in the synthesis and remodelling of the extracellular matrix.Fibroblasts participate in physiopathological processes such as tissue damage repair,inflammatory responses and immune regulation.Large numbers of activated fibroblasts have been found in fibrosis,autoimmune diseases and tumor lesions.Activated fibroblasts participate in tissue fibrosis and influence the tumor microenvi-ronment mainly by secreting collagen and fibronectin.They also secrete a variety of inflammatory and growth factors that play an immunomodulatory role in autoimmunity and tumors.In recent years,it has been found that modulating fibroblast activation can effectively delay the development of these diseases,and that targeting fibroblast activation biomarkers can assess the development and treatment of these diseases.Therefore,the use of fibroblast-targeted drugs and therapeutic tools is expected to achieve new breakthroughs in the clinical management of fibrosis,autoimmune diseases and tumors.

BackgroundPsychological problems such as depression and anxiety are common in pregnant women， and many studies have found that body image disturbance is closely related to depression and anxiety symptoms. Still， there is large variability in previous findings. ObjectiveTo review the researches on the relation of body image disturbance to depression and anxiety in pregnant women， and to provide a reference for interventions targeting maternal body image disturbance and depression and anxiety symptoms. MethodsOn January 10， 2023， well qualified literature focusing on the relationship between body image disturbance and depression and anxiety symptoms in pregnant women were searched in PubMed， Embase， CINAHL， Web of Science， China National Knowledge Infrastructure （CNKI）， VIP databases， Wanfang Data Database and China Biology Medicine disc （CBMdisc） from inception to January 1， 2023. The research content， factors influencing body image disturbance and relevant findings were extracted and summarized for analysis. ResultsA total of 14 articles were included in this review. The body image disturbance in pregnant women was manifested predominantly by an excessive concern about body weight and shape， and was affected by demographic characteristics， sociocultural factors， obstetric factors and other factors. Furthermore， body image disturbance significantly predicted the occurrence of depression， and proved a close relationship with anxiety symptoms. ConclusionBody image disturbance seriously affects the physical functioning and psychological status of pregnant women and may further exacerbate the symptoms of depression and anxiety.

Background As the population ages, there has been a growing focus on the decline in fertility. Research has identified age and fertility history as the primary influencing factors. Nevertheless, there is a deficiency in fundamental data regarding the fertility status among different industries. Objective To investigate the fertility status and influencing factors among female workers aged 22-35 years in different industries. Methods From July 2020 to February 2021, a cross-sectional survey was conducted using a staged sampling approach. This survey specifically targeted 22-35-year-old married female workers with a history of pregnancy in industries such as education, healthcare, finance, and telecommunications, totaling 22903 participants. The survey encompassed industry, demographic characteristics, pregnancy history, time to pregnancy (TTP), and other influencing factors. The influencing factors of decline in fertility were identified by chi-square test and Cox proportional hazards regression. Subsequent industry-specific Cox proportional hazards regression models were used to compared fertility decline patterns across a spectrum of industries after selected influencing factors were adjusted. Results Among the 22903 respondents, 19194 valid questionnaires were collected, with a valid recovery rate of 83.8%. The cumulative pregnancy rates (CRP) of 1-6 months and 1-12 months for the 22-35-year-old female workers were 67.23% and 91.33% respectively. The multivariate analysis showed that region, age, education level, personal annual income, housework time, coping style, gravidity, parity, and spontaneous abortion were influencing factors of fertility decline (P<0.05). Female workers with ≥3 gravidities and ≥2 spontaneous abortions had a higher risk of fertility decline, with hazard ratios (HR) and associated 95% confidence interval (95%CI) of 0.633 (0.582, 0.688) and 0.785 (0.670, 0.921) respectively (P<0.01). Compared to the education industry, the healthcare and finance industries showed a higher risk of fertility decline, with HR (95%CI) values of 0.876 (0.834, 0.920) and 0.909 (0.866, 0.954), respectively (P<0.05). These two HR (95%CI) values remained statistically significant [0.899 (0.852, 0.948) and 0.882 (0.833, 0.934) respectively, P<0.05)] after further adjustment with nine influencing factors such as region and age. Conclusion Regions, age, education level, personal annual income, housework time, coping style, pregnancy and childbirth times, and natural abortion times are influencing factors of fertility decline in female workers. Compared to the education industry, the healthcare and finance industries have a higher risk of declining fertility.

Background Noise is the most common occupational hazard in the automobile manufacturing industry with the most workers exposed. Automobile manufacturing industry is a high-risk industry for noise-induced hearing loss. Objective To understand the epidemiological characteristics of noise-induced hearing loss among workers in automobile manufacturing industry and explore related influencing factors. Methods A questionnaire survey, individual noise recording, and pure tone audiometry were conducted among workers (n=656) exposed to noise from five automobile manufacturing enterprises. The data on age, sex, exposure duration, noise intensity, kurtosis, and hearing loss were obtained. The positive rates of high-frequency noise-induced hearing loss (HFNIHL) and speech-frequency noise-induced hearing loss (SFNIHL) were calculated, and each factor was compared between workers with and without HFNIHL. Chi-square test and analysis of trend were conducted among different groups of age, sex, exposure duration, A-weighted equivalent continuous sound pressure level normalized to a nominal 8-hour working day (L_Aeq,8h), and kurtosis. Logistic regression analysis was conducted to analyze the factors influencing the positive rates of HFNIHL and SFNIHL. Results The exposure rates of non-Gaussian noise was 73.6%. The positive rates of HFNIHL and SFNIHL were 32.6% (214 workers) and 6.7% (44 workers), respectively. The HFNIHL workers showed older age, higher proportion of male, longer exposure duration, higher noise intensity (L_{Aeq,8 h}), and increased kurtosis than those without HFNIHL (P<0.05). The positive rates of HFNIHL increased with the increase of age, exposure duration, L_{Aeq,8 h}, and kurtosis (\begin{document}$ {\chi ^2} $\end{document}_trend-age=49.25, P<0.001; \begin{document}$ {\chi ^2} $\end{document}_{trend-duration}=22.19, P<0.001; \begin{document}$ {\chi ^2} $\end{document}_trend-LAeq=6.91, P=0.009; \begin{document}$ {\chi ^2} $\end{document}_{trend-kurtosis}=8.56, P=0.003). The results of logistic regression showed that age (OR=2.13, 95%CI: 1.67-2.71, P<0.001), sex (OR=2.29, 95%CI: 1.44-3.62, P<0.001), exposure duration (OR=1.43, 95%CI: 1.11-1.85, P=0.006), L_Aeq,8h (OR=1.37, 95%CI: 1.08~1.76, P=0.011), and kurtosis (OR=1.37, 95%CI: 1.14-1.63, P=0.001) were factors associated with the risk of HFNIHL, while only age was associated with the risk of SFNIHL (OR=2.15, 95%CI: 1.33-3.33, P=0.001). Conclusion Workers exposed to noise in automobile manufacturing industry are at a high risk of hearing loss. Age, sex, exposure duration, L_{Aeq,8 h}, and kurtosis are key influencing factors of hearing loss.

The existing measuring methods of noise exposure on the basis of equal energy hypothesis are applicable to Gaussian noise while not fully applicable to non-Gaussian noise. Studies have shown that temporal structure (kurtosis) combined with noise energy has the potential to quantify non-Gaussian noise exposure effectively. However, there is no unified measuring method adopting this joint metric. In this paper, the measuring method of non-Gaussian noise exposure based on kurtosis adjustment was introduced, detailing measurement indicators, adjustment schemes, applicable objects, instrument requirements, and measurement steps. Adjusting the exposure duration of cumulative noise exposure (CNE) by kurtosis or adjusting the equivalent continuous A-weighted sound pressure level (L_Aeq) by an adjustment coefficient based on animal or population studies can more accurately quantify workers' exposure to non-Gaussian noise and improve the underestimation of hearing loss caused by non-Gaussian noise. A large number of population studies are warranted in the future to verify the effectiveness of these two adjustment schemes.

Background Occupational noise-induced hearing loss (NIHL) is one of the most prevalent occupational diseases in the world. With the development of industry, noise sources in the workplace have become increasingly complex. Objective To apply kurtosis-adjusted cumulative noise exposure (CNE) to assess the occupational hearing loss among furniture manufacturing workers, and to provide a basis for revising noise measurement methods and occupational exposure limits in China. Methods A cross-sectional survey was conducted to select 694 manufacturing workers, including 542 furniture manufacturing workers exposed to non-Gaussian noise, and 152 textile manufacturing workers and paper manufacturing workers exposed to Gaussian noise. The job titles involving non-Gaussian noise were gunning and nailing, and woodworking, while those involving Gaussian noise were weaving, spinning, and pulping. High frequency noise-induced hearing loss (HFNIHL) and noise exposure data were collected for each study subject. Noise energy metrics included eight-hour equivalent continuous A-weighted sound pressure level (L_{Aeq,8 h}) and CNE. Kurtosis was a noise temporal structure metric. Kurtosis-adjusted CNE was a combined indicator of noise energy and temporal structure. Results The age of the study subjects was (35.64±10.35) years, the exposure duration was (6.71±6.44) years, and the proportion of males was 75.50%. The L_{Aeq,8 h} was (89.43±6.01) dB(A). About 81.42% of the study subjects were exposed to noise levels above 85 dB(A), the CNE was (95.85±7.32) dB(A)·year, with a kurtosis of 99.34 ± 139.19, and the prevalence rate of HFNIHL was 35.59%. The mean kurtosis of the non-Gaussian noise group was higher than that of the Gaussian noise group (125.33±147.17 vs. 5.86±1.94, t=−21.04, P<0.05). The results of binary logistic regression analysis showed that kurtosis was an influential factor of workers' HFNIHL after correcting for age, exposure duration, and L_{Aeq,8 h} (OR=1.49, P<0.05). The results of multiple linear regression analysis showed that the effects of age, exposure duration, L_{Aeq,8 h}, and kurtosis on noise-induced permanent threshold shift at frequencies of 3, 4, and 6 kHz of the poor hearing ear were statistically significant (all P<0.05). The results of chi-square trend analysis showed that when CNE ≥ 90 dB(A)·year, the HFNIHL prevalence rate elevated with increasing kurtosis (P<0.05). The mean HFNIHL prevalence rate was higher in the non-Gaussian noise group than in the Gaussian noise group (31.7% vs. 22.0%, P<0.05). After applying kurtosis-adjusted CNE, the linear equation between CNE and HFNIHL prevalence rate for the non-Gaussian noise group almost overlapped with that for the Gaussian noise group, and the mean difference in HFNIHL prevalence rate between the two groups decreased from 9.7% to 1.4% (P<0.05). Conclusion Noise kurtosis is an effective metric for NIHL evaluation. Kurtosis-adjusted CNE can effectively evaluate occupational hearing loss due to non-Gaussian noise exposure in furniture manufacturing workers, and is expected to be a new indicator of non-Gaussian noise measurement and assessment.