Objective Patients with lung cancer often experience interrelated symptoms such as fatigue, pain, and sleep disturbances during chemotherapy, forming a core symptom cluster that significantly impacts daily functioning, treatment experience, and quality of life. Currently, evidence on non-pharmacological management of this core symptom cluster is scattered, and there is a lack of standardized, patient- and caregiver-friendly guidance tools that are easy to understand and implement. This patient guideline aims to provide decision support for self-management of the core symptom cluster in patients undergoing chemotherapy for lung cancer. Methods Guided by evidence-based methodology, qualitative interviews and on-site questionnaire surveys were conducted to identify the health-related needs of stakeholders. Domestic and international guideline websites, relevant professional association websites, and comprehensive databases were systematically searched according to the inclusion and exclusion criteria. The included literature was evaluated for quality, and recommendations were extracted, integrated, and graded to form a summary of the best evidence. Based on the identified health issues and evidence summary, preliminary recommendations for the patient guideline were developed. The recommendations were then revised through two rounds of Delphi expert consultation, and consensus was reached on the strength of recommendations, forming the final version of the patient guideline. Results The patient guideline covered four major sections: screening and assessment of core symptom clusters, daily management, intervention measures, and timing of referral. The core content included nine aspects: screening of core symptom clusters, assessment, lifestyle habits, dietary interventions, sleep environment, exercise interventions, psychological interventions, Traditional Chinese Medicine interventions, and referral indications. In total, the guidelines addressed 16 health issues and provided 25 recommendations. Conclusion The development process of this patient guideline is rigorous and fully considered the needs of patients. Expert review concludes that the recommendations are highly feasible and appropriate.

In transcranial magnetic stimulation (TMS), the conductivity of brain tissue is obtained by using diffusion tensor imaging (DTI) data processing. However, the specific impact of different processing methods on the induced electric field in the tissue has not been thoroughly studied. In this paper, we first used magnetic resonance image (MRI) data to create a three-dimensional head model, and then estimated the conductivity of gray matter (GM) and white matter (WM) using four conductivity models, namely scalar (SC), direct mapping (DM), volume normalization (VN) and average conductivity (MC), respectively. Isotropic empirical conductivity values were used for the conductivity of other tissues such as the scalp, skull, and cerebrospinal fluid (CSF), and then the TMS simulations were performed when the coil was parallel and perpendicular to the gyrus of the target. When the coil was perpendicular to the gyrus where the target was located, it was easy to get the maximum electric field in the head model. The maximum electric field in the DM model was 45.66% higher than that in the SC model. The results showed that the conductivity component along the electric field direction of which conductivity model was smaller in TMS, the induced electric field in the corresponding domain corresponding to the conductivity model was larger. This study has guiding significance for TMS precise stimulation.
Transcranial Magnetic Stimulation ; Diffusion Tensor Imaging ; Electric Conductivity ; Electricity ; Scalp

Background/Aims: Studies of hepatic steatosis (HS) effect on COVID-19 vaccine immunogenicity are lacking. We aimed to compare immunogenicity of BNT162b2 and CoronaVac among moderate/severe HS and control subjects. Methods: Two hundred ninety-five subjects who received BNT162b2 or CoronaVac vaccines from five vaccination centers were categorized into moderate/severe HS (controlled attenuation parameter ≥268 dB/m on transient elastography) (n=74) or control (n=221) groups. Primary outcomes were seroconversion rates of neutralising antibody by live virus Microneutralization (vMN) assay (titer ≥10) at day21 (BNT162b2) or day28 (CoronaVac) and day56 (both). Secondary outcome was highest-tier titer response (top 25% of vMN titer; cutoff: 160 [BNT162b2] and 20 [CoronaVac]) at day 56. Results: For BNT162b2 (n=228, 77.3%), there was no statistical differences in seroconversion rates (day21: 71.7% vs. 76.6%; day56: 100% vs. 100%) or vMN geometric mean titer (GMT) (day21: 13.2 vs. 13.3; day56: 91.9 vs. 101.4) among moderate/severe HS and control groups respectively. However, lower proportion of moderate/severe HS patients had highest-tier response (day56: 5.0% vs. 15.5%; P=0.037). For CoronaVac (n=67, 22.7%), there was no statistical differences in seroconversion rates (day21: 7.1% vs. 15.1%; day56: 64.3% vs. 83.0%) or vMN GMT (5.3 vs. 5.8,) at day28. However, moderate/severe HS patients had lower vMN GMT (9.1 vs. 14.8, P=0.021) at day 56 with lower proportion having highest-tier response (21.4% vs. 52.8%, P=0.036). Conclusions While there was no difference in seroconversion rate between moderate/severe HS and control groups after two doses of vaccine, a lower proportion of moderate/severe HS patients achieved highest-tier response for either BNT162b2 or CoronaVac.