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The emergence of immune checkpoint inhibitors (ICIs) has significantly prolonged the survival time of cancer patients. However, it may also lead to various immune-related adverse events (irAEs), including Guillain–Barré syndrome (GBS), a rare type of irAE. Most GBS patients can recover spontaneously due to the self-limited nature of the disease, but severe cases can result in respiratory failure or even death. Here we report a rare case of GBS occurring in a 58-year-old male patient with non-small cell lung cancer (NSCLC) who developed muscle weakness and numbness of the extremities during chemotherapy combined with KN046, a PD-L1/CTLA-4 bispecific antibody. Despite receiving methylprednisolone and γ-globulin, the patient’s symptoms did not improve. However, there was significant improvement after treatment with mycophenolate mofetil (MM) capsules, which is not a routine regimen for GBS. To the best of our knowledge, this is the first reported case of ICIs-induced GBS that responded well to mycophenolate mofetil instead of methylprednisolone or γ-globulin. Thus, it provides a new treatment option for patients with ICIs-induced GBS.

IntroductionThe treatment response to neoadjuvant immunochemotherapy varies among patients with potentially resectable non-small cell lung cancers (NSCLC) and may have severe immune-related adverse effects. We are currently unable to accurately predict therapeutic response. We aimed to develop a radiomics-based nomogram to predict a major pathological response (MPR) of potentially resectable NSCLC to neoadjuvant immunochemotherapy using pretreatment computed tomography (CT) images and clinical characteristics.MethodsA total of 89 eligible participants were included and randomly divided into training (N=64) and validation (N=25) sets. Radiomic features were extracted from tumor volumes of interest in pretreatment CT images. Following data dimension reduction, feature selection, and radiomic signature building, a radiomics-clinical combined nomogram was developed using logistic regression analysis.ResultsThe radiomics-clinical combined model achieved excellent discriminative performance, with AUCs of 0.84 (95% CI, 0.74-0.93) and 0.81(95% CI, 0.63-0.98) and accuracies of 80% and 80% in the training and validation sets, respectively. Decision curves analysis (DCA) indicated that the radiomics-clinical combined nomogram was clinically valuable.DiscussionThe constructed nomogram was able to predict MPR to neoadjuvant immunochemotherapy with a high degree of accuracy and robustness, suggesting that it is a convenient tool for assisting with the individualized management of patients with potentially resectable NSCLC.

BackgroundNeoadjuvant chemoimmunotherapy (NCIO) is more effective than neoadjuvant immunotherapy alone for pathological response in non-small cell lung cancer (NSCLC) patients, but the processes for determining patient suitability for its implementation are not clear. We aimed to identify the most relevant factors and build a convenient model to select NSCLC patients who would benefit most from NCIO.Methods We retrospectively collected the clinical data of patients with locally advanced NSCLC who received NCIO followed by surgery at our institution between January 2019 and July 2022.ResultsA total of 101 eligible stage IIB-IIIC NSCLC patients were included. After NCIO, all patients successfully underwent surgical resection. A total of 46.53% (47/101) of patients achieved pathological complete response (pCR), and 70.30% (71/101) achieved major pathologic response (MPR). Tumor regression rate (adjusted odds ratio OR = 12.33), PD-L1 expression (adjusted odds ratio (OR) = 9.66), pembrolizumab/nab-paclitaxel–based regimens (adjusted OR = 4.92), and comorbidities (adjusted OR = 0.16) were independently associated with pCR rate (all P < 0.05). Tumor regression rate (adjusted OR = 8.45), PD-L1 expression (adjusted OR = 5.35), and presence of squamous cell carcinoma (adjusted OR = 7.02) were independently associated with MPR rate (all P < 0.05). We established and validated an easy-to-use clinical model to predict pCR (with an area under the curve [AUC] of 0.848) and MPR (with an AUC of 0.847). Of note, the present study showed that CD4+ T-cell count/rate and total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C) levels in the peripheral blood of pre-NCIO patients were also significantly correlated with pathological response in univariate analyses.ConclusionsThe tumor regression rate, PD-L1 expression, pembrolizumab/nab-paclitaxel–based regimens, presence of squamous cell carcinoma, and comorbidities were the main influential factors for incidence of pCR/MPR in patients with stage IIB-IIIC NSCLC in the present study. Through predictive models, we can predict who will benefit most from NCIO prior to the emergence of clinical outcomes in locally advanced NSCLC.

Due to the limited energy and mobility of the traditional sensor nodes, autonomous underwater glider (AUG) is widely used in underwater acoustic sensor networks to achieve long-term and large-scale marine environmental monitoring. In the communication between AUGs, time synchronization (TS) and multiple access control process (MACP) both need control frames to guarantee the data transmission. However, the independent execution of these two processes causes the control frames to be sent repeatedly, resulting in more transmission delay and energy cost. In order to communicate between AUGs more efficiently, an integrated TS with multiple access (TSMA) protocol is proposed in this paper. Within the AUG group, an AUG is selected as the beacon node to provide a standard clock to complete the intra-group TS process, while inter-group TS adopts the non-beacon synchronization method. In the TS process, the effect of the relative movement between AUGs is considered to improve the accuracy of synchronization. Besides, we create a new control frame that can fuse the message exchange of TS and MACP. Simulation results show that TSMA has a better performance in terms of the packet delivery fraction, synchronization errors, and energy efficiency.

Underwater Acoustic Sensor Networks (UASNs) have become one of the promising technologies for exploring underwater natural resources and collecting scientific data from the aquatic environment. As obstacles hinder the communications among sensor nodes in UASNs, designing an effective bypass routing protocol to avoid obstacles is an urgent need. Moreover, the sensor nodes are typically powered by batteries, which are difficult to replace, restricting the network lifetime of UASNs. In this paper, an Energy-efficient and Obstacle-Avoiding Routing protocol (EOAR) is proposed not only to address the issue of marine animals acting as obstacles that interfere with communications, but also to balance the network energy according to the residual energy. In the EOAR protocol, when the current node perceives the existence of marine animals, the interference area of the animal-nodes is first calculated using the underwater acoustic channel model, and then the candidate forwarding relay set of the current node is obtained according to the constraint conditions. The optimal candidate forwarding relay is determined by a fuzzy logic-based forwarding relay selection scheme based on considering the three parameters of the candidate forwarding relay, which includes the propagation delay, the included angle between two neighbor nodes, and the residual energy. Furthermore, in order to solve the problem of energy waste caused by packet collision, we use a priority-based forwarding method to schedule the packet transmission from the candidate forwarding relay to the destination node. The proposed EOAR protocol is simulated on the Aqua-sim platform and the simulation results show that proposed protocol can increase the packet delivery ratio by 28.4% and 11.8% and can reduce the energy consumption by 53.4% and 32.7% and, respectively, comparing with the hop-by-hop vector-based forwarding routing protocol (HHVBF) and void handling using geo-opportunistic routing protocol (VHGOR).