Tianjin Medical University

Our objective was to assess the perioperative quality of life (QoL) of patients with pancreatic cancer (PC) and accurately capture the complex interactions and causal pointers that contribute to fluctuations. This longitudinal study (October 2024 to March 2025) assessed QoL in patients with PC undergoing potentially curative surgery at four stages: the day of admission (T1), 3-5 days postoperatively (T2), the day of discharge (T3), and 1 month postoperatively (T4). Analysis of variance and cross-lagged panel network (CLPN) analyzed stage differences and dynamic interactions, and centrality calculations mapped important intervention targets between stages. Among 277 analyzed patients (89.64% response rate from 309 approached), 66.79% had ductal adenocarcinoma; the remaining cases comprised pancreatic neuroendocrine tumors (11.91%), invasive intraductal papillary mucinous neoplasms (7.58%), solid pseudopapillary tumors (5.42%), and other types (8.3%). QoL differed significantly between stages (P < 0.001). Dimension scores for functioning and global health status declined before gradually improving, whereas symptoms followed an inverse pattern. Nodes with higher bridge-expected influence, out-expected influence, or in-expected influence in each CLPN were targets for clinical care (mainly pain and nausea and vomiting in T1→T2, pain and social functioning in T2→T3, and fatigue and financial difficulties in T3→T4). The accuracy and stability of the CLPN were verified as acceptable. The CLPN could precisely identify the interactions and causal connections among QoL dimensions across different stages. It provides anticipatory and prospective guidance for clinical healthcare professionals to enhance holistic care outcomes through early intervention on vital targets that impede dysfunction and symptom exacerbation.

To develop a deep-learning model capable of measuring essential anterior segment (AS) parameters derived from preoperative ultrasound biomicroscopy (UBM) images of candidates for implantable collamer lens (ICL) surgery. Tianjin Medical University Eye Hospital, Tianjin, China. Cross-sectional retrospective study. A dataset comprising 1,480 preoperative panoramic UBM images taken from 638 eyes of 320 subjects was collected and was divided into training and testing subsets at a proportion of 7:3. Using the YOLOv8-pose algorithm, the model identified ten anatomical key point coordinates and computed six relevant AS parameters. Both manual and anterior segment optical coherence tomography-based non-contact measurements served as reference standards for evaluating the model's accuracy. The relationship between postoperative vault and preoperative parameters measured by the model was analyzed using multiple linear regression. On the test dataset, the model achieved an intraclass correlation coefficient (ICC) exceeding 0.978, with a mean Euclidean distance of 67.65 ± 54.25μm across all point locations. The ICC values for anterior chamber depth (ACD), pupil diameter, and sulcus-to-sulcus distance were above 0.980 (95% CI: 0.975 to 0.985), with average relative error below 1.7%. Additionally, postoperative vault at one month was significantly correlated with model-measured parameters, including crystalline lens rise, iris concavity, and ACD (P < 0.001). This study introduces a robust program capable of quantitatively measuring AS parameters with accuracy comparable to that of experienced ophthalmologists. The findings provide valuable guidance for ICL sizing and vault prediction.

Innate immune responses must be coordinated with the cellular metabolic state. The intracellular pattern recognition receptor NOD1 detects bacterial peptidoglycans and initiates signaling from cellular membranes, a process regulated by ZDHHC5-mediated palmitoylation. Using biochemical analyses and immune-competent cell models, we show that AMP-activated protein kinase (AMPK) integrates metabolic cues into NOD1 signaling by regulating ZDHHC5. AMPK phosphorylates ZDHHC5 at Ser296 and Ser380, weakens its association with Golga7B, and promotes its displacement from the plasma membrane, thereby reducing NOD1 palmitoylation, membrane localization, and downstream signaling. Conversely, stimulation with the NOD1 agonist C12-iE-DAP suppresses AMPK activity, stabilizing ZDHHC5 at the membrane and sustaining NOD1 activation. These findings define a reciprocal regulatory circuit linking metabolic stress sensing and innate immune signaling, and illustrate how metabolic pathways govern the spatial control of pattern recognition receptors in innate immunity.