Impact of chronic sleep deprivation on male reproductive health: Insights from testicular and epididymal responses in mice.

BACKGROUND: Sleep deprivation (SD) can cause damage to the male reproductive system. However, the duration required for such damage and the specific sequence and severity of damage to the testis and epididymis remain unclear. OBJECTIVE: To investigate the effects of different durations of SD on different parts of the testis and epididymis caput, corpus, and cauda. METHODS: Adult ICR mice were randomly assigned to five groups: the SD group (SD for 18 h/day for 1, 2, 3, or 4 weeks), the SD + Vit E group (supplemented with Vit E 50 mg/kg/d during 4 weeks of SD, the SD+NS group (saline supplementation during 4 weeks of SD), the SD + RS group (5 weeks of recovery sleep after 4 weeks of SD), and a normal sleep control (Ctrl) group. Following the interventions, sperm parameters, testicular and epididymal histopathology, inflammatory response, and oxidative stress markers were compared between the groups. RESULTS: Compared to the Ctrl group, the SD group showed a decrease in sperm motility and concentration from SD 2 W and SD 3 W, respectively. Decreases in sperm concentration and motility were more pronounced in the cauda compared to the caput and corpus. Pathological damage was less severe in the epididymis caput than in the corpus and cauda. After 4 weeks of SD, inflammation and oxidative stress increased in both testes and epididymis. Both sleep recovery and vitamin E supplementation showed significant improvements, though they did not fully reach the level of the Ctrl group. CONCLUSION: Chronic SD for more than 2 weeks causes varying degrees of damage to the testis, epididymis caput, corpus, and cauda in male mice. This damage is not fully reversible after 5 weeks of sleep recovery and antioxidant stress treatment. These findings help us to identify and prevent SD damage to the male reproduction at an early stage.

The fusion of vegetation indices increases the accuracy of cotton leaf area prediction.

Introduction: Rapid and accurate estimation of leaf area index (LAI) is of great significance for the precision agriculture because LAI is an important parameter to evaluate crop canopy structure and growth status. Methods: In this study, 20 vegetation indices were constructed by using cotton canopy spectra. Then, cotton LAI estimation models were constructed based on multiple machine learning (ML) methods extreme learning machine (ELM), random forest (RF), back propagation (BP), multivariable linear regression (MLR), support vector machine (SVM)], and the optimal modeling strategy (RF) was selected. Finally, the vegetation indices with a high correlation with LAI were fused to construct the VI-fusion RF model, to explore the potential of multi-vegetation index fusion in the estimation of cotton LAI. Results: The RF model had the highest estimation accuracy among the LAI estimation models, and the estimation accuracy of models constructed by fusing multiple VIs was higher than that of models constructed based on single VIs. Among the multi-VI fusion models, the RF model constructed based on the fusion of seven vegetation indices (MNDSI, SRI, GRVI, REP, CIred-edge, MSR, and NVI) had the highest estimation accuracy, with coefficient of determination (R2), rootmean square error (RMSE), normalized rootmean square error (NRMSE), and mean absolute error (MAE) of 0.90, 0.50, 0.14, and 0.26, respectively. Discussion: Appropriate fusion of vegetation indices can include more spectral features in modeling and significantly improve the cotton LAI estimation accuracy. This study will provide a technical reference for improving the cotton LAI estimation accuracy, and the proposed method has great potential for crop growth monitoring applications.

PLEK2 promotes migration and invasion in pancreatic ductal adenocarcinoma by MMP1 through IL-17 pathway.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognosis primarily due to metastasis. Accumulating evidence suggests that PLEK2 acts as an oncogene in various tumors. This study aimed to investigate the effects of PLEK2 on PDAC. Expression analysis of PLEK2 was conducted using qRT-PCR, Western blot, and immunohistochemistry in PDAC. Wound healing and transwell assays were performed to evaluate the impact of PLEK2 on cell migration and invasion. A xenograft tumor model was employed to assess the in vivo proliferation of PLEK2. Additionally, the downstream pathway of PLEK2 was analyzed through RNA-seq and confirmed by Western blot analysis. The results demonstrated the upregulation of PLEK2 expression in tumor specimens. High PLEK2 expression was significantly associated with poor overall survival and advanced TNM stages. Correlation analyses revealed positive correlations between PLEK2 and TGF-ß, EGFR, and MMP1. Wound healing and transwell assays demonstrated that PLEK2 promoted PDAC cell migration and invasion, potentially through the activation of the epithelial-to-mesenchymal transition process. The in vivo experiment further confirmed that PLEK2 knockdown suppressed tumor growth. RNA-seq analysis revealed PLEK2's regulation of MMP1 and activation of p-ERK and p-STAT3, which were verified by Western blot analysis. Overall, the present study suggests that PLEK2 may play a tumor-promoting role in PDAC. These findings provide valuable insights into the molecular mechanisms of pancreatic cancer and highlight the potential of PLEK2 as a therapeutic target.

Ultralow Energy Consumption and Fast Neuromorphic Computing Based on La0.1Bi0.9FeO3 Ferroelectric Tunnel Junctions.

Low-power and fast artificial neural network devices represent the direction in developing analogue neural networks. Here, an ultralow power consumption (0.8 fJ) and rapid (100 ns) La0.1Bi0.9FeO3/La0.7Sr0.3MnO3 ferroelectric tunnel junction artificial synapse has been developed to emulate the biological neural networks. The visual memory and forgetting functionalities have been emulated based on long-term potentiation and depression with good linearity. Moreover, with a single device, logical operations of "AND" and "OR" are implemented, and an artificial neural network was constructed with a recognition accuracy of 96%. Especially for noisy data sets, the recognition speed is faster after preprocessing by the device in the present work. This sets the stage for highly reliable and repeatable unsupervised learning.

Risk factors of textbook outcome in laparoscopic pancreatoduodenectomy: results from a prospective high-volume center study.

OBJECTIVE: Achieving textbook outcome (TO) implies a smooth recovery post-operation without specified composite complications. This study aimed to evaluate TO in laparoscopic pancreaticoduodenectomy (LPD) and identify independent risk factors associated with achieving TO. METHODS: We conducted a retrospective analysis of data from a randomized controlled trial on LPD at West China Hospital (ChiCTR1900026653). Patients were categorized into the TO and non-TO groups. Perioperative variables were compared between these groups. Multivariate logistic regression was utilized to identify the risk factors. RESULTS: A total of 200 consecutive patients undergoing LPD were included in this study. TO was achieved in 82.5% (n = 165) of the patients. Female patients (OR: 2.877, 95% CI: 1.219-6.790; P = 0.016) and those with a hard pancreatic texture (OR: 2.435, 95% CI: 1.018-5.827; P = 0.046) were associated with an increased likelihood of achieving TO. CONCLUSIONS: TO can be achieved in more than 80% of patients in a high-volume LPD center. Independent risk factors associated with achieving TO included gender (male) and pancreatic texture (soft).

Nondissociative Activated Dihydrogen Binding on CeO2 Revealed by High-Pressure Operando Solid-State NMR Spectroscopy.

Dihydrogen complexes, which retain the H-H bond, have been extensively studied in molecular science and found to be prevalent in homogeneous and enzymatic catalysis. However, their counterparts in heterogeneous catalysis, specifically nondissociative chemisorbed dihydrogen binding on the catalyst surface, are rarely reported experimentally. This scarcity is due to the complexity of typical material surfaces and the lack of effective characterization techniques to prove and distinguish various dihydrogen binding modes. Herein, using high-pressure operando solid-state NMR technology, we report the first unambiguous experimental observation of activated dihydrogen binding on a reduced ceria catalyst through interactions with surface oxygen vacancies. By employing versatile NMR structural and dynamical analysis methods, we establish a proportional relationship between the degree of ceria surface reduction and dihydrogen binding, as evidenced by NMR observations of H-D through-bond coupling (JHD), T1 relaxation, and proton isotropic chemical shifts. In situ NMR analysis further reveals the participation of bound dihydrogen species in a room-temperature ethylene hydrogenation reaction. The remarkable similarities between surface-activated dihydrogen in heterogeneous catalysis and dihydrogen model molecular complexes can provide valuable insights into the hydrogenation mechanism for many other solid catalysts, potentially enhancing hydrogen utilization.

Mechanochemical Activation of Aryl Diazonium Salts: Synthesis of Polycyclic (Hetero)Aromatics.

Although the synthesis of polycyclic (hetero)aromatics via the [4 + 2] benzannulation process has been thoroughly explored, the restricted availability of energy sources (including thermal, light, and electrical energy) mandates the utilization of substantial quantities of organic solvents, inevitably leading to environmental pollution, resource wastage, and low reaction efficiency. Herein, we report a new method for the synthesis of polycyclic (hetero)aromatics from diazonium salts and alkynes under ball-milling conditions. This mechanochemical approach requires only substoichiometric amounts of DMSO as a liquid-assisted grinding additive and furnishes the desired product in a short time.

Cross-species single-cell landscapes identify the pathogenic gene characteristics of inherited retinal diseases.

Introduction: Inherited retinal diseases (IRDs) affect ∼4.5 million people worldwide. Elusive pathogenic variants in over 280 genes are associated with one or more clinical forms of IRDs. It is necessary to understand the complex interaction among retinal cell types and pathogenic genes by constructing a regulatory network. In this study, we attempt to establish a panoramic expression view of the cooperative work in retinal cells to understand the clinical manifestations and pathogenic bases underlying IRDs. Methods: Single-cell RNA sequencing (scRNA-seq) data on the retinas from 35 retina samples of 3 species (human, mouse, and zebrafish) including 259,087 cells were adopted to perform a comparative analysis across species. Bioinformatic tools were used to conduct weighted gene co-expression network analysis (WGCNA), single-cell regulatory network analysis, cell-cell communication analysis, and trajectory inference analysis. Results: The cross-species comparison revealed shared or species-specific gene expression patterns at single-cell resolution, such as the stathmin family genes, which were highly expressed specifically in zebrafish Müller glias (MGs). Thirteen gene modules were identified, of which nine were associated with retinal cell types, and Gene Ontology (GO) enrichment of module genes was consistent with cell-specific highly expressed genes. Many IRD genes were identified as hub genes and cell-specific regulons. Most IRDs, especially the retinitis pigmentosa (RP) genes, were enriched in rod-specific regulons. Integrated expression and transcription regulatory network genes, such as congenital stationary night blindness (CSNB) genes GRK1, PDE6B, and TRPM1, showed cell-specific expression and transcription characteristics in either rods or bipolar cells (BCs). IRD genes showed evolutionary conservation (GNAT2, PDE6G, and SAG) and divergence (GNAT2, MT-ND4, and PDE6A) along the trajectory of photoreceptors (PRs) among species. In particular, the Leber congenital amaurosis (LCA) gene OTX2 showed high expression at the beginning of the trajectory of both PRs and BCs. Conclusion: We identified molecular pathways and cell types closely connected with IRDs, bridging the gap between gene expression, genetics, and pathogenesis. The IRD genes enriched in cell-specific modules and regulons suggest that these diseases share common etiological bases. Overall, mining of interspecies transcriptome data reveals conserved transcriptomic features of retinas across species and promising applications in both normal retina anatomy and retina pathology.

Brain image data processing using collaborative data workflows on Texera.

In the realm of neuroscience, mapping the three-dimensional (3D) neural circuitry and architecture of the brain is important for advancing our understanding of neural circuit organization and function. This study presents a novel pipeline that transforms mouse brain samples into detailed 3D brain models using a collaborative data analytics platform called "Texera." The user-friendly Texera platform allows for effective interdisciplinary collaboration between team members in neuroscience, computer vision, and data processing. Our pipeline utilizes the tile images from a serial two-photon tomography/TissueCyte system, then stitches tile images into brain section images, and constructs 3D whole-brain image datasets. The resulting 3D data supports downstream analyses, including 3D whole-brain registration, atlas-based segmentation, cell counting, and high-resolution volumetric visualization. Using this platform, we implemented specialized optimization methods and obtained significant performance enhancement in workflow operations. We expect the neuroscience community can adopt our approach for large-scale image-based data processing and analysis.

Luteolin enhances drug chemosensitivity by downregulating the FAK/PI3K/AKT pathway in paclitaxel­resistant esophageal squamous cell carcinoma.

Drug resistance is a key factor underlying the failure of tumor chemotherapy. It enhances the stem­like cell properties of cancer cells, tumor metastasis and relapse. Luteolin is a natural flavonoid with strong anti­tumor effects. However, the mechanism(s) by which luteolin protects against paclitaxel (PTX)­resistant cancer cell remains to be elucidated. The inhibitory effect of luteolin on the proliferation of EC1/PTX and EC1 cells was detected by cell counting kit­8 assay. Colony formation and flow cytometry assays were used to assess clonogenic capacity, cell cycle and apoptosis. Wound healing and Transwell invasion tests were used to investigate the effects of luteolin on the migration and invasion of EC1/PTX cells. Western blotting was used to detect the protein levels of EMT­related proteins and stem cell markers after sphere formation. Parental cells and drug­resistant cells were screened by high­throughput sequencing to detect the differential expression of RNA and differential genes. ELISA and western blotting were used to verify the screened PI3K/Akt signaling pathway, key proteins of which were explored by molecular docking. Hematoxylin and eosin staining and TUNEL staining were used to observe tumor xenografts on morphology and apoptosis in nude mice. The present study found that luteolin inhibited tumor resistance (inhibited proliferation, induced cell cycle arrest and apoptosis and hindered migration invasion, EMT and stem cell spherification) in vitro in PTX­resistant esophageal squamous cell carcinoma (ESCC) cells. In addition, luteolin enhanced drug sensitivity and promoted the apoptosis of drug­resistant ESCC cells in combination with PTX. Mechanistically, luteolin may inhibit the PI3K/AKT signaling pathway by binding to the active sites of focal adhesion kinase (FAK), Src and AKT. Notably, luteolin lowered the tumorigenic potential of PTX­resistant ESCC cells but did not show significant toxicity in vivo. Luteolin enhanced drug chemosensitivity by downregulating the FAK/PI3K/AKT pathway in PTX­resistant ESCC and could be a promising agent for the treatment of PTX­resistant ESCC cancers.

Modification of Microstructure and Mechanical Properties of Extruded AZ91-0.4Ce Magnesium Alloy through Addition of Ca.

The effect of the addition of alkali earth element Ca on the microstructure and mechanical properties of extruded AZ91-0.4Ce-xCa (x = 0, 0.4, 0.8, 1.2 wt.%) alloys was studied by using scanning electron microscopy, transmission electron microscopy, and tensile tests. The results showed that the addition of Ca could significantly refine the second phase and grain size of the extruded AZ91-0.4Ce alloy. The refinement effect was most obvious when 0.8 wt.% of Ca was added, and the recrystallized grain size was 4.75 µm after extrusion. The addition of Ca resulted in the formation of a spherical Al2Ca phase, which effectively suppressed the precipitation of the ß-Mg17Al12 phase, promoted dynamic recrystallization and grain refinement, impeded dislocation motion, and exerted a positive influence on the mechanical properties of the alloy. The yield strength (YS), ultimate tensile strength (UTS), and elongation (EL) of the AZ91-0.4Ce-0.8Ca alloy were 238.7 MPa, 338.3 MPa, and 10.8%, respectively.

YOLO SSPD: a small target cotton boll detection model during the boll-spitting period based on space-to-depth convolution.

Introduction: Cotton yield estimation is crucial in the agricultural process, where the accuracy of boll detection during the flocculation period significantly influences yield estimations in cotton fields. Unmanned Aerial Vehicles (UAVs) are frequently employed for plant detection and counting due to their cost-effectiveness and adaptability. Methods: Addressing the challenges of small target cotton bolls and low resolution of UAVs, this paper introduces a method based on the YOLO v8 framework for transfer learning, named YOLO small-scale pyramid depth-aware detection (SSPD). The method combines space-to-depth and non-strided convolution (SPD-Conv) and a small target detector head, and also integrates a simple, parameter-free attentional mechanism (SimAM) that significantly improves target boll detection accuracy. Results: The YOLO SSPD achieved a boll detection accuracy of 0.874 on UAV-scale imagery. It also recorded a coefficient of determination (R2) of 0.86, with a root mean square error (RMSE) of 12.38 and a relative root mean square error (RRMSE) of 11.19% for boll counts. Discussion: The findings indicate that YOLO SSPD can significantly improve the accuracy of cotton boll detection on UAV imagery, thereby supporting the cotton production process. This method offers a robust solution for high-precision cotton monitoring, enhancing the reliability of cotton yield estimates.

The association between shift work, shift work sleep disorders and premature ejaculation in male workers.

OBJECTIVE: Shift work and Shift Work Sleep Disorder (SWSD) are known to affect the secretion of several neurotransmitters and hormones associated with premature ejaculation (PE). However, their specific influence on the regulation of male ejaculation remains unclear. This study explores the relationship between shift work, SWSD, and PE. METHODS: From April to October 2023, a cross-sectional survey was conducted across five regions of China to explore the work schedules, sleep quality, and sexual function of male workers. Participants' sleep quality was evaluated using a validated SWSD questionnaire, and their erectile function and ejaculatory control were assessed with the International Inventory of Erectile Function (IIEF-5) scores and Premature Ejaculation Diagnostic Tool (PEDT) scores, respectively. Univariate and multivariate linear regression analyses were employed to identify risk factors associated with PE. Confounders were controlled using multiple regression models, and clinical prediction models were developed to predict PE onset and assess the contribution of risk factors. RESULTS: The study included 1239 eligible participants, comprising 840 non-shift workers and 399 shift workers (148 with SWSD and 251 without SWSD). Compared to non-shift working males, those involved in shift work (ß 1.58, 95% CI 0.75 - 2.42, p < 0.001) and those suffering from SWSD (ß 2.86, 95% CI 1.86 - 3.85, p < 0.001) they had significantly higher PEDT scores. Additionally, we identified daily sleep of less than six hours, depression, anxiety, diabetes, hyperlipidemia, frequent alcohol consumption (more than twice a week), and erectile dysfunction as risk factors for PE. The predictive model for PE demonstrated commendable efficacy. CONCLUSION: Both shift work and SWSD significantly increase the risk of premature ejaculation, with the risk magnifying in tandem with the duration of shift work. This study reveals the potential impact of shift work and SWSD on PE and provides new theoretical foundations for the risk assessment and prevention of this condition.

Artificial intelligence automated surgical phases recognition in intraoperative videos of laparoscopic pancreatoduodenectomy.

BACKGROUND: Laparoscopic pancreatoduodenectomy (LPD) is one of the most challenging operations and has a long learning curve. Artificial intelligence (AI) automated surgical phase recognition in intraoperative videos has many potential applications in surgical education, helping shorten the learning curve, but no study has made this breakthrough in LPD. Herein, we aimed to build AI models to recognize the surgical phase in LPD and explore the performance characteristics of AI models. METHODS: Among 69 LPD videos from a single surgical team, we used 42 in the building group to establish the models and used the remaining 27 videos in the analysis group to assess the models' performance characteristics. We annotated 13 surgical phases of LPD, including 4 key phases and 9 necessary phases. Two minimal invasive pancreatic surgeons annotated all the videos. We built two AI models for the key phase and necessary phase recognition, based on convolutional neural networks. The overall performance of the AI models was determined mainly by mean average precision (mAP). RESULTS: Overall mAPs of the AI models in the test set of the building group were 89.7% and 84.7% for key phases and necessary phases, respectively. In the 27-video analysis group, overall mAPs were 86.8% and 71.2%, with maximum mAPs of 98.1% and 93.9%. We found commonalities between the error of model recognition and the differences of surgeon annotation, and the AI model exhibited bad performance in cases with anatomic variation or lesion involvement with adjacent organs. CONCLUSIONS: AI automated surgical phase recognition can be achieved in LPD, with outstanding performance in selective cases. This breakthrough may be the first step toward AI- and video-based surgical education in more complex surgeries.

Synbiotics containing sea buckthorn polysaccharides ameliorate DSS-induced colitis in mice via regulating Th17/Treg homeostasis through intestinal microbiota and their production of BA metabolites and SCFAs.

Inflammatory Bowel Disease (IBD) is a chronic condition whose incidence has been rising globally. Synbiotic (SYN) is an effective means of preventing IBD. This study investigated the preventive effects and potential biological mechanisms of SYN (Bifidobacterium longum, Lactobacillus acidophilus, and sea buckthorn polysaccharides) on DSS-induced colitis in mice. The results indicated that dietary supplementation with SYN has a significant improvement effect on DSS mice. SYN ameliorated disease activity index (DAI), colon length, and intestinal barrier permeability in mice. In addition, RT-qPCR results indicated that after SYN intervention, the expression levels of pro-inflammatory factors (IL-6, IL-1ß, TNF-α, and IL-17F) and transcription factor RORγt secreted by Th17 cells were significantly reduced, and the expression levels of anti-inflammatory factors (IL-10 and TGF-ß) and transcription factor Foxp3 secreted by Treg cells were robustly increased. 16S rDNA sequencing analysis revealed that key intestinal microbiota related to Th17/Treg balance (Ligilactobacillus, Lactobacillus, Bacteroides, and Akkermansia) was significantly enriched. At the same time, a significant increase in microbial metabolites SCFAs and BAs was observed. We speculate that SYN may regulate the Th17/Treg balance by restructuring the structure and composition of the intestinal microbiota, thereby mitigating DSS-induced colitis.

Increased Secreted Frizzled-Related Protein 2 in Hypertension-Induced Left Ventricular Remodeling.

Background: Secreted frizzled-related protein 2 (sFRP2) is involved in various cardiovascular diseases. However, its relevance in left ventricular (LV) remodeling in patients with hypertension (HTN) is obscure. Methods: In this study, 196 patients with HTN were included, 59 with echocardiographic LV remodeling. A total of 100 healthy subjects served as normal controls. The serum-sFRP2 level was measured by enzyme-linked immunosorbent assay (ELISA). Data were collected from medical records for baseline characteristics, biochemistry tests, and echocardiography. Receiver operating characteristic (ROC) curves were used to assess the distinguishing value of sFRP2 for LV remodeling in patients with HTN. Spearman rank correlation analysis was utilized to identify factors correlated with sFRP2. Cardiac sFRP2 was determined by Western blot and quantitative polymerase chain reaction (qPCR). Results: The level of serum-sFRP2 was higher in HTN patients with echocardiographic LV remodeling than their non-remodeling counterparts. ROC analysis showed that the area under the curve (AUC) for sFRP2 in distinguishing echocardiographic LV remodeling in HTN patients was 0.791 (95% confidence interval (CI): 0.714-0.869). The sFRP2 was negatively correlated with LV dimension and positively correlated with relative wall thickness (RWT). The expression of sFRP2 was higher in hypertrophic hearts, which could be reversed by myricetin. Conclusions: The serum level and cardiac sFRP2 increased in the setting of LV remodeling and decreased by myricetin. Serum sFRP2 may be a promising distinguishing factor for LV remodeling in HTN patients.

Neuroendocrine Carcinoma of the Bladder: A Case Report.

Primary bladder large cell neuroendocrine carcinoma (LCNEC) is a rare, aggressive neoplasm with high recurrence rates and poor prognosis. Traditional management has heavily relied on radical cystectomy, which, despite its aggressiveness, often results in unsatisfactory outcomes. Emerging evidence suggests the potential for less invasive, bladder-sparing approaches, yet detailed reports and long-term outcomes remain scarce. We report a groundbreaking case of a 59-year-old male diagnosed with primary bladder LCNEC, managed through a pioneering bladder-sparing multimodal treatment. This novel strategy included transurethral resection followed by a tailored chemoradiation protocol, resulting in exceptional disease control and preservation of bladder function over a 20-month follow-up period, without evidence of recurrence. This case underscores the viability of bladder conservation strategies as a legitimate alternative to radical cystectomy for managing LCNEC, presenting a beacon of hope for patients wishing to preserve bladder functionality. It prompts a reevaluation of traditional treatment paradigms and advocates for further research into multimodal, organ-sparing approaches for this challenging malignancy.

Impact of an AI-Based laparoscopic cholecystectomy coaching program on the surgical performance: a randomized controlled trial.

BACKGROUND: Laparoscopic cholecystectomy (LC) is the gold standard for treating symptomatic gallstones but carries inherent risks like bile duct injury (BDI). While critical view of safety (CVS) is advocated to mitigate BDI, its real-world adoption is limited. Additionally, significant variations in surgeon performance impede procedural standardization, highlighting the need for a feasible, innovative, and effective training approach. The aim of this study is to develop an Artificial Intelligence (AI)-assisted coaching program for LC to enhance surgical education and improve surgeon's performance. MATERIALS AND METHODS: We conducted a multi-center, randomized controlled trial from May 2022 to August 2023 to assess the impact of an AI-based coaching program, SmartCoach, on novice performing LC. Surgeons and patients meeting specific inclusion criteria were randomly assigned to either a coaching group with AI-enhanced feedback or a self-learning group. The primary outcome was assessed using the Laparoscopic Cholecystectomy Rating Form (LCRF), with secondary outcomes including surgical safety, efficiency, and adverse events. Statistical analyses were performed using SPSS, with significance set at P-value less than 0.05. RESULTS: Between May 2022 and August 2023, 22 surgeons were initially enrolled from 10 hospitals, with 18 completing the study. No demographic differences were noted between coaching and self-learning groups. In terms of surgical performance (LCRF scores), the coaching group showed significant improvement over time (31 to 40, P=0.008), outperforming the self-learning group by study end (40 vs 38, P=0.032). Significant improvements in CVS achievement were also noted in the coaching group (11% to 78%, P=0.021). Overall, the coaching program was well-received, outpacing traditional educational methods in both understanding and execution of CVS and participants in the intervention group expressed strongly satisfaction with the program. CONCLUSIONS: The AI-assisted surgical coaching program effectively improved surgical performance and safety for novice surgeons in LC procedures. The model holds significant promise for advancing surgical education.

Single-incision plus one port laparoscopic pancreaticoduodenectomy with major venous resection and reconstruction for pancreatic cancer with video recordings.

Laparoscopic pancreaticoduodenectomy (LPD) with superior mesenteric/portal vein (SMV/PV) resection and reconstruction was the most technically challenging procedure and had been rarely reported. However, single-incision plus one-port LPD (SILPD +1) with SMV/PV resection and reconstruction has never been reported. In this study, we will demonstrate the feasibility, safety, key surgical procedure, and long-term outcomes for SILPD +1 with SMV/PV resection and reconstruction using video evidence. Two cases of SILPD +1 with SMV/PV wedge resection were carried out by the authors. There was no tumor recurrence during the one-year follow-up. It is worth noting that skilled laparoscopic technicians are necessary to safely complete the procedure with good short-term and long-term outcomes.

Synthesis and Characterization of Emulsifiers Based on the Maillard Reaction and Its Application in Stabilized DHA Algal Oil Nanoemulsions.

The aim of this study was to optimize the formation of sodium caseinate (CS) and gum arabic (GA) complexes through the Maillard reaction and to evaluate their effectiveness in improving the emulsification properties and stability of docosahexaenoic acid (DHA) nanoemulsions. First, the best target polysaccharides were selected, and the best modification conditions were determined using orthogonal experiments. Secondly, the response surface experiments were used to optimize the preparation process of the emulsion. The stability, in vitro digestion characteristics, and rheological characteristics of the emulsion prepared by means of CS-GA were compared with the emulsion prepared using a whey protein isolate (WPI). After the orthogonal test, the optimal modification conditions were determined to be a reaction time of 96 h, a CS-GA mass ratio of 1:2, a reaction temperature of 60 °C, and a degree of grafting of 44.91%. Changes in the infrared (IR), Raman, ultraviolet (UV), and endogenous fluorescence spectra also indicated that the complex structure was modified. The response surface test identified the optimal preparation process as follows: an emulsifier concentration of 5 g/L, an oil-phase concentration of 5 g/L, and a homogenization frequency of five, and the emulsion showed good stability. Therefore, the use of a nanoemulsion as a nanoscale DHA algal oil delivery system is very promising for extending the shelf life and improving the stability of food.