Yan Bo

Primary ovarian insufficiency (POI) is a heterogeneous disorder with diverse genetic and autoimmune contributors. This narrative review examines selected evidence on these contributors and their relevance to the evaluation and counselling of women with POI. Genetic studies have identified established and candidate abnormalities involving chromosomes, FMR1, folliculogenesis, meiosis, DNA repair, and mitochondrial function, although the clinical significance of many rare variants remains uncertain. Autoimmune associations are most consistently described in relation to thyroid, adrenal, and polyglandular autoimmune disorders, while evidence for broader inflammatory mechanisms remains less established. These findings support targeted genetic and autoimmune evaluation rather than indiscriminate testing. Hormone replacement therapy remains the foundation of long-term care, and fertility counselling should acknowledge the possibility of intermittent ovarian activity while maintaining realistic expectations regarding autologous pregnancy. Emerging regenerative approaches remain experimental. Overall, genetic and autoimmune evidence can refine aetiological assessment and counselling in selected patients, but substantial uncertainty remains regarding many proposed molecular and immunological contributors.

Introduction: Menstrual irregularities or amenorrhea affect at least 17.4 million women worldwide. Symptoms in young patients may be atypical, and imaging and serum hormone levels are sometimes insufficient to explain the condition. Objectives: This review synthesizes current evidence to improve diagnostic and treatment strategies, reduce misdiagnosis of primary ovarian insufficiency (POI), facilitate timely treatment, and support earlier recognition and individualized follow-up to preserve reproductive function. Methods: We conducted a narrative review of studies addressing the genetic basis, molecular mechanisms, follicular activation pathways, and clinical management of POI. Particular attention was given to single-gene variants, chromosomal abnormalities, phosphoinositide 3-kinase (PI3K), mechanistic target of rapamycin (mTOR), and Hippo signaling pathways, as well as acquired or functional conditions that may mimic genetic POI. Results: POI is a heterogeneous reproductive endocrine disorder involving chromosomal abnormalities, X-linked factors, folliculogenesis-related genes, meiotic and chromosomal stability defects, and DNA damage repair pathways. Representative genes such as FMR1, BMP15, GDF9, NR5A1, HFM1, STAG3, and BRCA2 illustrate the diverse mechanisms that impair ovarian reserve or cause follicular dysfunction. In vitro activation of dormant follicles is biologically supported by PI3K/phosphatase and tensin homolog/protein kinase B/FOXO3a, mTOR, and Hippo signaling pathways, but its clinical application remains limited and requires further validation. Functional hypothalamic amenorrhea, drug exposure, metabolic abnormalities, endocrine tumors, and autoimmune conditions should also be considered in the differential diagnosis. Conclusion: POI in young women should not be simply attributed to stress, emotional factors, or menstrual irregularity. Early etiological evaluation, appropriate genetic testing, differential diagnosis, reproductive counseling, hormone replacement therapy when indicated, fertility preservation planning, and long-term multidisciplinary follow-up may improve clinical management. In vitro activation-related mechanisms provide a potential biological rationale for future fertility-preserving strategies, but broader clinical use requires stronger evidence.

Background: Neuroinflammation has emerged as a potential biological mechanism underlying depressive disorders and represents an increasingly investigated target for therapeutic intervention. Objective: To compare the effects of pharmacological interventions evaluated within an inflammation-related framework on depressive symptom severity and inflammatory biomarker outcomes. Methods: Randomised controlled trials reporting pharmacological interventions for depressive disorders were included. A frequentist fixed-effects network meta-analysis was conducted for depressive symptom severity at the end of randomised treatment. Treatments were ranked using surface under the cumulative ranking curve values. Exploratory pairwise meta-analyses were performed separately for tumour necrosis factor-alpha, interleukin-6, interferon-gamma, C-reactive protein, and interleukin-2. Results: Eleven randomised controlled trial reports contributed to a sparse network of 10 active interventions. Using a frequentist fixed-effect network meta-analysis, escitalopram oxalate showed the largest estimated reduction in depressive symptom severity relative to the reference control node (mean difference [MD]: −13.03; 95% confidence interval [CI]: −24.54 to −1.52). Ketamine 0.5 mg/kg (MD: −5.16; 95% CI: −8.81 to −1.51) and selective serotonin reuptake inhibitor plus glycyrrhizic acid (MD: −4.35; 95% CI: −7.16 to −1.55) also showed estimates favouring intervention. Fluoxetine, fluoxetine plus triiodothyronine, infliximab, ketamine 0.2 mg/kg, minocycline, sumac, and vortioxetine plus celecoxib did not show statistically precise differences from the reference control node. Exploratory biomarker analyses showed no consistent pooled differences in inflammatory markers and substantial heterogeneity for several biomarkers. Conclusion: Current evidence does not support a consistent class-wide benefit of inflammation-informed pharmacotherapy for depressive disorders. Although several interventions showed potentially favourable effects on depressive symptom severity, the evidence network was sparse, and most comparisons were based on single trials. Future trials should enrol biologically defined patient subgroups and use standardised clinical and biomarker outcomes.

Introduction: Depression is a leading global cause of disability and premature mortality, yet many patients do not respond ­adequately to standard treatments. Converging evidence suggests that inflammatory processes contribute to the onset, maintenance, and recurrence of depression, but findings are dispersed across basic, translational, and clinical research. Methods and analysis: This scoping review aims to systematically map the existing evidence on the role of inflammation in ­depression and to characterise how inflammatory markers and pathways have been investigated in relation to prevention and treatment strategies. The review will be conducted in accordance with established methodological guidance for scoping reviews and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Multiple bibliographic databases, trial registries, grey literature sources, and preprint servers will be searched without language restrictions. Two reviewers will independently screen records, select eligible studies, and chart data using a piloted data extraction form. Findings will be synthesised using descriptive statistics and narrative methods to summarise study characteristics, inflammatory mechanisms, biomarkers, interventions, and clinical outcomes. An integrative framework will be developed to link inflammatory mechanisms with therapeutic and preventive approaches. Ethics and dissemination: This review will use only publicly available data, and no new data will be collected; therefore, formal ethical approval is not required. The findings will be disseminated through peer-reviewed publication and other academic dissemination channels to support knowledge translation in depression research. Registration: This scoping review protocol is registered with the Open Science Framework (DOI: https://doi.org/10.17605/OSF.IO/SE49K).

Introduction: Acute-on-chronic liver failure (ACLF) is often precipitated by infection, but the contribution of psychological factors, particularly in patients with persistent fever and neuropsychiatric symptoms, is unclear. Case description: A 44-year-old man with hepatitis B–related cirrhosis presented with a 21-day history of high fever (39.4°C), jaundice and acute mania. Investigations showed marked hyperbilirubinaemia and coagulopathy consistent with ACLF but no clear infectious focus. Daily artificial liver support and empirical meropenem improved bilirubin levels and consciousness, yet fever and manic symptoms persisted. On day 6, structured psychotherapy with quetiapine and valproate was initiated; within 48 hours the fever resolved and manic features progressively abated. Imaging on day 14 revealed suppurative cholecystitis, treated with interventional therapy, and by day 25 liver function and Child–Turcotte–Pugh score had substantially improved. Discussion: The temporal association between psychological intervention, defervescence and improvement in manic symptoms suggests that chronic psychological stress may have amplified systemic inflammation and fever expression in this ACLF patient. Learning point(s): In ACLF with unexplained fever and mania, clinicians should consider psychological contributors alongside infectious causes, and multidisciplinary care integrating artificial liver support, judicious anti-infective therapy and psychotherapy may improve outcomes.

Background: Epilepsy research centres in Europe and Asia have reported the correlation between S100 Calcium Binding Protein beta (S100B) and epilepsy. However, whether S100B has clinical diagnostic value has been debated. This epilepsy study developed a long-term research plan to resolve this controversy, divided into three simple phases. Methods: The first phase is mainly observational studies, focusing on resolving the debate on the correlation between S100B levels in serum or cerebrospinal fluid and epilepsy. The second phase uses observational and randomized controlled research data, focusing on solving the baseline standard of S100B level and epilepsy population with different characteristics and providing a research basis for the predictive value of S100B level on epilepsy. The third phase is mainly based on randomized controlled studies, focusing on the accuracy of S100B as a biomarker for diagnosing epilepsy. Discussion: Due to the large number of high-risk groups for epilepsy, it is difficult to identify whether patients with involuntary jerks of limbs have epilepsy. Although electroencephalogram (EEG) can capture pathological brain waves, it inconveniences the general population. Even when a patient is diagnosed with epilepsy and discharged from the hospital, predicting the time interval for the subsequent seizure is difficult. Therefore, a more convenient and clinically valuable tool than the EEG is necessary. The number of studies on epilepsy biomarkers has gradually increased in recent years, which provides a sufficient research basis for this study. Registration: https://www.crd.york.ac.uk/PROSPERO/ , CRD-ID: CRD42023425431.

BACKGROUND: Diabetic ketoacidosis (DKA) is a life-threatening complication of diabetes mellitus, requiring prompt and effective fluid resuscitation. Current guidelines rely on empirical fluid protocols that fail to incorporate real-time haemodynamic monitoring, potentially leading to fluid overload or insufficient resuscitation. Aims: To evaluate whether non-invasive haemodynamic monitoring with the Ultrasonic Cardiac Output Monitor (USCOM) combined with passive leg raising (PLR) optimises fluid resuscitation in adults with diabetic ketoacidosis (DKA) without impairing metabolic recovery. Methods: In this single-centre, single-blind, randomised controlled pilot trial, adults with DKA were allocated (1:1) to USCOM-guided resuscitation or sham USCOM monitoring. In the intervention group, additional fluid boluses (250 mL crystalloids over 15 min) were administered only when stroke volume increased by ≥10% during PLR. The primary outcome was net fluid balance at 24, 48, and 72 hours. Secondary outcomes included urine output, length of hospital stay, glycaemic control, urinary ketone clearance, and adverse events. Results: Fifty participants (mean age 48.0 ± 16.2 years; 42% male) were enrolled. Compared with controls, the USCOM group demonstrated significantly lower net fluid balance at 48 hours (−1246.8 mL; P = 0.007) and 72 hours (−1759.5 mL; P = 0.001), driven by greater urine output in the first 24 hours (+952.6 mL; P = 0.002). Length of hospital stay was reduced by 1.92 days (P = 0.034). No significant differences were observed in blood glucose trajectories, urinary ketone clearance, or adverse event rates. Conclusions: USCOM-guided resuscitation in adult DKA reduces net fluid accumulation and shortens hospitalisation without compromising metabolic recovery. This dynamic, non-invasive strategy offers a feasible approach to precision fluid management, with potential applicability in diverse healthcare settings. Trial registration: ChiCTR2500103388.

Background: During COVID-19 and the postepidemic phase, the concept of a frontline emergency response team was gradually expanded [based on a previous clinical trial, https://clinicaltrials.gov/, identifier (ChiCTR2500103976)]. The professional scope of nurses gradually expanded towards the digital. We selected the digital interventions implemented by nurses during the COVID-19 pandemic and self-management by diabetes patients as the research context.Aims: To synthesise a framework for the module-intensity-outcome of digitalised care during COVID-19.Methods: We searched the PubMed database for literature related to the role of nurses and self-management of diabetes patients during the COVID-19 pandemic, and then used these literature as ‘seed literature’ for a snowball search. We synthesised all the evidence using a directional evidence synthesis method, a narrative description method, and a visual presentation method.Results: A total of 10 publications were retrieved from the PubMed database, involving a cumulative total of 5,834 adults. This indicates that using these 10 ‘seed literature’ for secondary literature retrieval enhances the persuasiveness of this method. Using these ‘seed literature’, an additional 28 literature were retrieved using the snowball method. Digital nursing has developed rapidly during the COVID-19 pandemic due to challenges in patient self-management. During the COVID-19 pandemic, patients sought digital nursing services from nurses due to disrupted healthcare services, surging mental health issues, and unhealthy lifestyles. In this model, nurses serve as a bridge between digital nursing services, the healthcare system, and patients. Digital nursing services not only bridge the gap in nursing services during healthcare crises but also expand the scope of nurses’ professional roles.Conclusion: Nurse-led digital care with a clear mix of “modules and intensity” may have directional benefits for diabetes self-management and metabolic outcomes.

Background: Influenza-related global deaths reach 650,000 annually. The current highly lethal clinical subtype of influenza is severe influenza.Aim: To develop and validate a deep learning based model for early diagnosis of severe influenza.Methods: This is a multi-centre, double-blind, multi-stage, randomised controlled clinical trial. We initially developed a framework for a 5-phase study: model development, external validation, multi-reader study, randomised controlled trial and prospective validation. The data source for the preview programme is electronic health record data from 87 hospitals in Jiangsu Province from 2019 to 2025.Significance: Our expected result is that the developed model of severe influenza can be more accurate and have a lower misdiagnosis rate than traditional clinical assessment. The pre-specified AUC was 0.18 (95% CI: 0.14-0.22), with an expected 32% reduction in misdiagnosis. The model’s performance was consistent across patients in older adults, underlying disease, and resource-poor areas. The added value of the study is that it is effective in improving early recognition of severe influenza.Ethics and dissemination: This study was approved by the Institutional Review Board of Yangzhou University Hospital (IRB No. YKL08-002). Written informed consent was obtained from all participants. The results of this study will be disseminated in the form of a conference in the Jiangsu Province area, which will facilitate the translation of clinical research results and provide a powerful decision-making tool for the precise prevention and control of severe influenza.Clinical trial number: https://clinicaltrials.gov/, identifier (ChiCTR2000028883).

Background: Emergency frontline rescue workers during the COVID-19 pandemic faced elevated psychological risks, yet existing tools lack specificity for crisis contexts.Aim: To develop a simplified risk probability scale (SRPS) tailored for rapid self-assessment of depression and anxiety in frontline rescue teams.Methods: This SRPS study employed a mixed research methodology of questionnaires and systematic reviews. Snowball sampling was applied to collect questionnaire data. Univariate and multivariate analyses were conducted to identify key variables for the SRPS, which was then established using binary logistic regression models and nomograms. Receiver operating characteristic (ROC) curves evaluated the SRPS’s accuracy and sensitivity. A literature review of existing COVID-19 assessment tools in the PubMed database was also carried out.Ethics and dissemination: The study was approved by the Institutional Review Board of the Affiliated Hospital of Yangzhou University (IRB No: YKL08-002). Written informed consent was obtained from all participants.Clinical trial registration: https://clinicaltrials.gov/, identifier [ChiCTR2500103976].