ObjectiveTo establish a regional risk assessment system for hospital-acquired infections in neurosurgery department of general hospital, and to evaluate its prevention and control effectiveness. MethodsFailure mode and effect analysis (FMEA) was used to identify the core risk factors for infections in neurosurgery department. The risk priority number (RPN) of each risk factor was calculated to determine the priority intervention targets. Targeted interventions were developed and continuously refined through the plan-do-check-act (PDCA) cycles. Data from January to June 2023 (control group) and July to December 2023 (intervention group) were collected to compare the differences in environmental hygiene monitoring qualification rate, incidence rate of hospital-acquired infections among inpatients, and detection rate of bacterial antimicrobial resistance. ResultsHigh-risk factors for hospital-acquired infections in neurosurgery department included patient-related risk factors, inadequate implementation of isolation measures for special infections, and poor compliance with surgical site infection (SSI) prevention protocols. After intervention, the environmental hygiene qualification rate significantly increased from 81.55% to 100.00% (χ²=120.49, P<0.001). The overall hospital-acquired infection rate among inpatients decreased from 2.62% to 2.45%, the infection rate of per case declined from 3.12% to 2.84%, and the detection rate of multidrug-resistant organism infections reduced from 43.72% to 36.79%. Additionally, antimicrobial utilization rate decreased from 48.75% to 42.53% (χ²=34.09, P<0.001). ConclusionThe FMEA-based risk assessment system can effectively identify critical infection risks in neurosurgery department, and targeted interventions can significantly improve infection prevention and control performance.

ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

ObjectiveTo establish an ultra-performance liquid fingerprint and multi-components determination method for Naomaili granules. To evaluate the quality of different batches by chemometrics， and the anti-neuroinflammatory effects of water extract and main components of Naomaili granules were tested in vitro. MethodsThe similarity and common peaks of 27 batches of Naomaili granules were evaluated by using Ultra performance liquid chromatography （UPLC） fingerprint detection. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） technology was used to determine the content of the index components in Naomaili granules and to evaluate the quality of different batches of Naomaili granules by chemometrics. LPS-induced BV-2 cell inflammation model was used to investigate the anti-neuroinflammatory effects of the water extract and main components of Naomaili granules. ResultsThe similarity of fingerprints of 27 batches of samples was > 0.90. A total of 32 common peaks were calibrated， and 23 of them were identified and assigned. In 27 batches of Naomaili granules， the mass fractions of 14 components that were stachydrine hydrochloride， leonurine hydrochloride， calycosin-7-O-glucoside， calycosin，tanshinoneⅠ， cryptotanshinone， tanshinoneⅡ_A， ginsenoside Rb₁， notoginsenoside R₁， ginsenoside Rg₁， paeoniflorin， albiflorin， lactiflorin， and salvianolic acid B were found to be 2.902-3.498， 0.233-0.343， 0.111-0.301， 0.07-0.152， 0.136-0.228， 0.195-0.390， 0.324-0.482， 1.056-1.435， 0.271-0.397， 1.318-1.649， 3.038-4.059， 2.263-3.455， 0.152-0.232， 2.931-3.991 mg∙g^-1， respectively. Multivariate statistical analysis showed that paeoniflorin， ginsenoside Rg₁， ginsenoside Rb₁ and staphylline hydrochloride were quality difference markers to control the stability of the preparation. The results of bioactive experiment showed that the water extract of Naomaili granules and the eight main components with high content in the prescription had a dose-dependent inhibitory effect on the release of NO in the cell supernatant. Among them， salvianolic acid B and ginsenoside Rb₁ had strong anti-inflammatory activity， with IC₅₀ values of （36.11±0.15） mg∙L^-1 and （27.24±0.54） mg∙L^-1， respectively. ConclusionThe quality evaluation method of Naomaili granules established in this study was accurate and reproducible. Four quality difference markers were screened out， and eight key pharmacodynamic substances of Naomaili granules against neuroinflammation were screened out by in vitro cell experiments.

Sleep is an instinctive behavior alternating awakening state, sleep entails many active processes occurring at the cellular, circuit and organismal levels. The function of sleep is to restore cellular energy, enhance immunity, promote growth and development, consolidate learning and memory to ensure normal life activities. However, with the increasing of social pressure involved in work and life, the incidence of sleep disorders (SD) is increasing year by year. In the short term, sleep disorders lead to impaired memory and attention; in the longer term, it produces neurological dysfunction or even death. There are many ways to directly or indirectly contribute to sleep disorder and keep the hormones, including pharmacological alternative treatments, light therapy and stimulus control therapy. Exercise is also an effective and healthy therapeutic strategy for improving sleep. The intensities, time periods, and different types of exercise have different health benefits for sleep, which can be found through indicators such as sleep quality, sleep efficiency and total sleep time. So it is more and more important to analyze the mechanism and find effective regulation targets during sleep disorder through exercise. Dopamine (DA) is an important neurotransmitter in the nervous system, which not only participates in action initiation, movement regulation and emotion regulation, but also plays a key role in the steady-state remodeling of sleep-awakening state transition. Appreciable evidence shows that sleep disorder on humans and rodents evokes anomalies in the dopaminergic signaling, which are also implicated in the development of psychiatric illnesses such as schizophrenia or substance abuse. Experiments have shown that DA in different neural pathways plays different regulatory roles in sleep behavior, we found that increasing evidence from rodent studies revealed a role for ventral tegmental area DA neurons in regulating sleep-wake patterns. DA signal transduction and neurotransmitter release patterns have complex interactions with behavioral regulation. In addition, experiments have shown that exercise causes changes in DA homeostasis in the brain, which may regulate sleep through different mechanisms, including cAMP response element binding protein signal transduction, changes in the circadian rhythm of biological clock genes, and interactions with endogenous substances such as adenosine, which affect neuronal structure and play a neuroprotective role. This review aims to introduce the regulatory effects of exercise on sleep disorder, especially the regulatory mechanism of DA in this process. The analysis of intracerebral DA signals also requires support from neurophysiological and chemical techniques. Our laboratory has established and developed an in vivo brain neurochemical analysis platform, which provides support for future research on the regulation of sleep-wake cycles by movement. We hope it can provide theoretical reference for the formulation of exercise prescription for clinical sleep disorder and give some advice to the combined intervention of drugs and exercise.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

With the continuous development of society, a large number of new chemicals are continuously emerging, which presents a challenge to current risk assessment and safety management of chemicals. Traditional toxicology research methods have certain limitations in quickly, efficiently, and accurately assessing the toxicity of many chemicals, and cannot meet the actual needs. In response to this challenge, computational toxicology that use mathematical and computer models to achieve the prediction of chemical toxicity has emerged. In the meantime, as researchers increasingly pay attention to understanding the interaction mechanisms between exogenous chemical substances and the body from the system level, and multiomics technologies develop rapidly such as genomics, transcriptomics, proteomics, and metabolomics, huge amounts of data have been generated, providing rich information resources for studying the interactions between chemical substances and biological molecules. System toxicology and network toxicology have also developed accordingly. Of these, network toxicology can integrate these multiomics data to construct biomolecular networks, and then quickly predict the key toxicological targets and pathways of chemicals at the molecular level. This paper outlined the concept and development of network toxicology, summarized the main methods and supporting tools of network toxicology research, expounded the application status of network toxicology in studying potential toxicity of exogenous chemicals such as agricultural chemicals, environmental pollutants, industrial chemicals, and foodborne chemicals, and analyzed the development prospects and limitations of network toxicology research. This paper aimed to provide a reference for the application of network toxicology in other fields.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective: To explore the risk of endometrial polyp (EP) based on lipid metabolism and vaginal micro- ecology combined with uterine volume line drawing model. Methods: 143 EP patients treated by hysteroscopic sur- gery were selected as the experimental group , and 113 healthy women were selected as the control group at the same time. The data were randomly divided into training set and validation set according to the ratio of 7 : 3. The clinical data of the two groups were collected and recorded , and t/χ2 test , LASSO regression and multifactorial lo- gistic regression analysis were used to screen the independent risk factors , construct the prediction model , and draw the column line graph. The performance of the model was evaluated by applying subject operating characteristic (ROC) curves , calibration curves , Hosmer-Lemeshow test and clinical decision-making (DCA) curves. Results: Multifactorial logistic regression analysis showed that total cholesterol ( TC) , low-density lipoprotein cholesterol (LDL-C) , vaginal microecological balance , and uterine volume were independent risk factors for the development of EP. ROC curve analysis showed that the AUC values of the training and validation sets of the column line graph model were 0. 935 and 0. 887 , respectively , and its sensitivity and specificity were 90. 21% , 83. 46% and 86. 29% , 80. 66% respectively , The Hosmer-Lemeshow test showed that the model fits well ( training set : χ2 = 2. 261 , P = 0. 840 ; validation set : χ2 = 4. 837 , P = 0. 441) and the calibration curves of the training and validation sets were close to the ideal curves , which indicated that the model had good prediction accuracy; the analysis of DCA curves of the training and validation sets both showed that the column-line graph model had a good clinical benefit rate in predicting EP. Conclusion TC , LDL-C , vaginal microecological balance and uterine volume are independent risk factors for EP , and the column-line diagram model constructed by the model has high clinical ben- efit , calibration and accuracy in predicting the risk of EP.

Objective:To evaluate the clinical outcomes of a modified dual-plane implant augmentation mammoplasty via periareolar incision.Methods:The patients undergoing primary breast augmentation at Vcharm Plastic & Aesthetic Surgery Hospital of Chongqing from October 2018 to June 2023 were enrolled in this prospective cohort study. Participants were alternately assigned to Group A (traditional Tebbetts dual-plane implant augmentation mammoplasty) and Group B (modified dual-plane implant augmentation mammoplasty) based on admission sequence. The modified technique included sharp subfascial dissection above the 5th rib, oblique muscle dissection below the 5th rib to create a subpectoral pocket, and elevation of the serratus anterior and external oblique fascia to the newly defined inframammary fold. Implants were positioned with 70% in the subfascial plane superiorly and 30% in the submuscular-fascial plane inferiorly. Postoperative pain was assessed using the numerical rating scale (NRS, 0-10) during days 0-7. Patient satisfaction (breast morphology, breast softness in sitting and supine positions) and complications were evaluated at 12-month follow-up. Statistical analysis was performed using SPSS 24.0. The measurement data were expressed as Mean ± SD, and the inter-group comparisons were performed by t-test. The enumeration data were expressed as examples and (or) percentages, and the inter-group comparisons were performed by χ2 test or Fisher exact probability test. P<0.05 was considered to be statistically significant. Results:Forty-eight female patients were included in Group A with age of (34.0±5.0) years and body mass index of (20.6±3.1) kg/m 2. Forty-three cases were received anatomical implants, and 5 cases rough round implants. The volume of implants was (265.0±12.5) cc. Fifty female patients were included in Group B with age of (35.0±4.5) years and body mass index of (21.5±3.7) kg/m 2. Forty-two cases were received anatomical implants and 8 cases rough round implants. The volume of implants was (262.0±15.0) cc. Baseline characteristics (age, body mass index, implant type, volume) showed no intergroup differences ( P>0.05). Group B demonstrated significantly lower NRS scores than Group A at all timepoints ( P<0.05). The immediate postoperative scores were 8.0±1.6 vs. 4.8±0.8, decreasing to 4.4±0.7 vs. 2.2±0.3 on Day 7. At 12 months, satisfaction rates for breast morphology[91.7%(44/48) vs. 92.0%(46/50)] and breast softness in sitting position [85.4%(41/48) vs. 86.0%(43/50) ] were comparable (both P>0.05). However, superior breast softness satisfaction in supine position was achieved in Group B [64.0%(32/50) vs. 43.8%(21/48), P<0.01] and fewer patients reported marked softness deterioration in supine position [28.0%(14/50) vs. 54.2%(6/48), P<0.01]. No hematoma, infection, delayed wound healing, implant malposition or wavy breast occurred in two groups. Capsular contracture occurred in 1 case per group. The implant was easy to be touched in 5 and 6 cases of Groups A and B, respectively ( P>0.05), while dynamic distortion was observed only in Group A (1 vs. 0, P<0.01). Conclusion:The modified dual-plane implant augmentation mammoplasty via periareolar incision significantly reduces postoperative pain, enhances breast softness in supine position, and prevents dynamic distortion without increasing complication risks, representing an optimized approach for implant-based augmentation.

AIM To investigate the repair effects of tauroursodeoxycholic acid(TUDCA)combined with bone marrow mesenchymal stem cells(BMSCs)transplantation on spinal cord injury(SCI)in rats.METHODS The rats were randomly divided into the sham operation group,the model group,the TUDCA group,the BMSCs transplantation group and the combination therapy of TUDCA and BMSCs transplantation group,with the SCI rat model established by Allen's method.The next day after modeling,the rats of TUDCA and combination therapy groups were given 200 mg/kg TUDCA by gavage.On the 3rd day after modeling,rats in BMSCs transplantation group and combination therapy group were injected with 1 mL tuned bone marrow BMSCs(the 3rd generation,1× 106/mL)via tail vein.Rats in the sham operation group and the model group were given gastric perfusion of normal saline and injection of 1 mL PBS through tail vein.On the 3rd,7th and 14th day after modeling,the rats had their motor function of hind limbs observed and BBB score determined.After the corresponding drug administration,the rats had their movement track of hind limbs recorded by footprint experiment;their the protein expressions of IL-6,IL-10,Arg-1,PI3K and Akt in spinal cord tissue detected by Western blot;their pathological changes of spinal cord tissue observed by HE staining and Nissl staining;and their expressions of MAP2,GAP43 and GFAP detected by immunofluorescence staining.RESULTS Compared with the model group,the groups intervened with TUDCA,or BMSCs transplantation,or combination therapy shared improved hind limb function and spinal cord histomorphology(P＜0.05);increased fluorescence intensity of MAP2 and GAP43,and protein expressions of IL-10,Arg-1,p-PI3K and p-Akt(P＜0.05);decreased fluorescence intensity of GFAP and IL-6 protein expressions(P＜0.05);among which the combination therapy group took the lead(P＜0.05).CONCLUSION The combination therapy of TUDCA and BMSCs transplantation may restore the function of the rat model of SCI by reducing inflammatory reaction,alleviating secondary injury,and promoting axon and myelin regeneration via PI3K/Akt signaling pathway.