Synthesis, crystal structure and Hirshfeld surface analysis of N-(6-acetyl-1-nitro-naphthalen-2-yl)acetamide.

The title compound, C14H12N2O4, was obtained from 2-acetyl-6-amino-naphthalene through two-step reactions of acetyl-ation and nitration. The mol-ecule comprises the naphthalene ring system consisting of functional systems bearing a acetyl group (C-2), a nitro group (C-5), and an acetyl-amino group (C-6). In the crystal, the mol-ecules are assembled into two-dimensional sheet-like structures by inter-molecular N-H⋯O and C-H⋯O hydrogen-bonding inter-actions. Hirshfeld surface analysis illustrates that the most important contributions to the crystal packing are from O⋯H/H⋯O (43.7%), H⋯H (31.0%), and C⋯H/H⋯C (8.5%) contacts.

Exploring the challenges of taiwanese nurses in the COVID-19 post-pandemic era.

In the wake of the COVID-19 pandemic, the fluctuating nurse resignation rates highlighted an understudied area in healthcare: post-pandemic challenges in clinical settings. This study, conducted from May to November 2023, employed a qualitative inquiry using focus groups to delve into these challenges. Six focus group sessions, involving 33 nurse participants recruited through snowball sampling from various hospital settings were conducted to explore their clinical experiences during and after the pandemic. Thematic analysis revealed two primary themes: the 'Invisibility of Nurses' within the healthcare system and the 'Moral Duty of Nursing Practice'. These findings illuminate a tension between the overlooked role of nurses and their ethical obligations, underscoring a critical need for policy reassessment. The study advocates for systemic changes, particularly in the undervaluation of the nursing profession and the National Health Insurance system, to address the poor working environment and mitigate long-term nursing shortages. This research deepens understanding of post-pandemic nursing workforce challenges in Taiwan, highlighting the need for policy evolution to enhance recognition and support for the nursing industry. It is suggested to provide tangible compensation to acknowledge nurses' daily care and health education for patients. A healthier working environment can be enhanced by collaborative efforts between healthcare institutions and nurses.

Would Combination Be Better: Swimming Exercise and Intermittent Fasting Improve High-Fat Diet-Induced Nonalcoholic Fatty Liver Disease in Obese Rats via the miR-122-5p/SREBP-1c/CPT1A Pathway.

Background: Swimming and intermittent fasting can both improve obesity-induced NAFLD, but which of the two is more effective and whether the combination of the two has a superimposed effect is inconclusive. Methods: The model of NAFLD in obese rats was established by a high-fat diet and performed swimming, intermittent fasting, and a combination of both interventions for 8 weeks. Serum lipids and enzyme activity were measured by an automatic biochemical analyzer. Liver morphostructural analysis was observed by transmission electron microscopy, and morphology was observed by HE staining. RT‒PCR was used to detect the mRNA level. Results: Morphology and microstructure of the liver of model rats were impaired, with the upregulation of miR-122-5p, SREBP-1c, FASN and ACC1. Eight weeks of swimming exercise, intermittent fasting and the combination of both attenuate these effects, manifested by the downregulation of miR-122-5p and upregulation of CPT1A mRNA levels. There was no significant stacking effect of the combination of the swimming and intermittent fasting interventions. Conclusion: NAFLD leads to pathology in model rats. Eight weeks of swimming exercise, intermittent fasting and the combination of both can inhibit miR-122-5p and improve hepatic lipid metabolism, while no significant additive effects of combining the interventions were found.

Effects of ant nests on soil CH4 emissions from Syzygium oblatum communities of a secondary tropical forest.

Exploring the effects of ant nests on soil CH4 emissions in the secondary tropical forests is of great scientific significance to understand the contribution of soil faunal activities to greenhouse gas emissions. With static chamber-gas chromatography method, we measured the dry-wet seasonal dynamics of CH4 emissions from ant nests and control soils in the secondary forest of Syzygium oblatum communities in Xishuangbanna. We also examined the linkages of ant-mediated changes in functional microbial diversity and soil physicochemical properties with CH4 emissions. The results showed that: 1) Ant nests significantly accelerated soil CH4 emissions, with average CH4 emissions in the ant nests being 2.6-fold of that in the control soils. 2) The CH4 emissions had significant dry-wet seasonal variations, which was a carbon sink in the dry seasons (from -0.29±0.03 to -0.53±0.02 µg·m-2·h-1) and a carbon source in the wet seasons (from 0.098±0.02 to 0.041±0.009 µg·m-2·h-1). The CH4 emissions were significantly higher in ant nests than in control soils. The CH4 emissions from the ant nests had smaller dry-wet seasonal variation (from -0.38±0.01 to 0.12±0.02 µg·m-2·h-1) than those in the control soils (from -0.65±0.04 to 0.058±0.006 µg·m-2·h-1). 3) Ant nests significantly increased the values (6.2%-37.8%) of soil methanogen diversity (i.e., Ace and Shannon indices), temperature and humidity, carbon pools (i.e., total, easily oxidizable, and microbial carbon), and nitrogen pools (i.e., total, hydrolyzed, ammonium, and microbial biomass nitrogen), but decreased the diversity (i.e., Ace and Chao1 indices) of methane-oxidizing bacteria by 21.9%-23.8%. 4) Results of the structural equation modeling showed that CH4 emissions were promoted by soil methanogen diversity, temperature and humidity, and C and N pools, but inhibited by soil methane-oxidizing bacterial diversity. The explained extents of soil temperature, humidity, carbon pool, nitrogen pool, methanogen diversity, and methane-oxidizing bacterial diversity for the CH4 emission changes were 6.9%, 21.6%, 18.4%, 15.2%, 14.0%, and 10.8%, respectively. Therefore, ant nests regulated soil CH4 emission dynamics through altering soil functional bacterial diversities, micro-habitat, and carbon and nitrogen pools in the secondary tropical forests.

Imprinted gene detection effectively improves the diagnostic accuracy for papillary thyroid carcinoma.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most frequent histological type of thyroid carcinoma. Although an increasing number of diagnostic methods have recently been developed, the diagnosis of a few nodules is still unsatisfactory. Therefore, the present study aimed to develop and validate a comprehensive prediction model to optimize the diagnosis of PTC. METHODS: A total of 152 thyroid nodules that were evaluated by postoperative pathological examination were included in the development and validation cohorts recruited from two centres between August 2019 and February 2022. Patient data, including general information, cytopathology, imprinted gene detection, and ultrasound features, were obtained to establish a prediction model for PTC. Multivariate logistic regression analysis with a bidirectional elimination approach was performed to identify the predictors and develop the model. RESULTS: A comprehensive prediction model with predictors, such as component, microcalcification, imprinted gene detection, and cytopathology, was developed. The area under the curve (AUC), sensitivity, specificity, and accuracy of the developed model were 0.98, 97.0%, 89.5%, and 94.4%, respectively. The prediction model also showed satisfactory performance in both internal and external validations. Moreover, the novel method (imprinted gene detection) was demonstrated to play a role in improving the diagnosis of PTC. CONCLUSION: The present study developed and validated a comprehensive prediction model for PTC, and a visualized nomogram based on the prediction model was provided for clinical application. The prediction model with imprinted gene detection effectively improves the diagnosis of PTCs that are undetermined by the current means.

Diagnostic accuracy of magnetically guided capsule endoscopy with a detachable string for detecting oesophagogastric varices in adults with cirrhosis: prospective multicentre study.

OBJECTIVE: To evaluate the diagnostic accuracy and safety of using magnetically guided capsule endoscopy with a detachable string (ds-MCE) for detecting and grading oesophagogastric varices in adults with cirrhosis. DESIGN: Prospective multicentre diagnostic accuracy study. SETTING: 14 medical centres in China. PARTICIPANTS: 607 adults (>18 years) with cirrhosis recruited between 7 January 2021 and 25 August 2022. Participants underwent ds-MCE (index test), followed by oesophagogastroduodenoscopy (OGD, reference test) within 48 hours. The participants were divided into development and validation cohorts in a ratio of 2:1. MAIN OUTCOME MEASURES: The primary outcomes were the sensitivity and specificity of ds-MCE in detecting oesophagogastric varices compared with OGD. Secondary outcomes included the sensitivity and specificity of ds-MCE for detecting high risk oesophageal varices and the diagnostic accuracy of ds-MCE for detecting high risk oesophagogastric varices, oesophageal varices, and gastric varices. RESULTS: ds-MCE and OGD examinations were completed in 582 (95.9%) of the 607 participants. Using OGD as the reference standard, ds-MCE had a sensitivity of 97.5% (95% confidence interval 95.5% to 98.7%) and specificity of 97.8% (94.4% to 99.1%) for detecting oesophagogastric varices (both P<0.001 compared with a prespecified 85% threshold). When using the optimal 18% threshold for luminal circumference of the oesophagus derived from the development cohort (n=393), the sensitivity and specificity of ds-MCE for detecting high risk oesophageal varices in the validation cohort (n=189) were 95.8% (89.7% to 98.4%) and 94.7% (88.2% to 97.7%), respectively. The diagnostic accuracy of ds-MCE for detecting high risk oesophagogastric varices, oesophageal varices, and gastric varices was 96.3% (92.6% to 98.2%), 96.9% (95.2% to 98.0%), and 96.7% (95.0% to 97.9%), respectively. Two serious adverse events occurred with OGD but none with ds-MCE. CONCLUSION: The findings of this study suggest that ds-MCE is a highly accurate and safe diagnostic tool for detecting and grading oesophagogastric varices and is a promising alternative to OGD for screening and surveillance of oesophagogastric varices in patients with cirrhosis. TRIAL REGISTRATION: ClinicalTrials.gov NCT03748563.

Neural Circuitry Polarization in the Spinal Dorsal Horn (SDH): A Novel Form of Dysregulated Circuitry Plasticity during Pain Pathogenesis.

Pathological pain emerges from nociceptive system dysfunction, resulting in heightened pain circuit activity. Various forms of circuitry plasticity, such as central sensitization, synaptic plasticity, homeostatic plasticity, and excitation/inhibition balance, contribute to the malfunction of neural circuits during pain pathogenesis. Recently, a new form of plasticity in the spinal dorsal horn (SDH), named neural circuit polarization (NCP), was discovered in pain models induced by HIV-1 gp120 and chronic morphine administration. NCP manifests as an increase in excitatory postsynaptic currents (EPSCs) in excitatory neurons and a decrease in EPSCs in inhibitory neurons, presumably facilitating hyperactivation of pain circuits. The expression of NCP is associated with astrogliosis. Ablation of reactive astrocytes or suppression of astrogliosis blocks NCP and, concomitantly, the development of gp120- or morphine-induced pain. In this review, we aim to compare and integrate NCP with other forms of plasticity in pain circuits to improve the understanding of the pathogenic contribution of NCP and its cooperation with other forms of circuitry plasticity during the development of pathological pain.

Telemedicine-Enhanced Lung Cancer Screening Using Mobile Computed Tomography Unit with Remote Artificial Intelligence Assistance in Underserved Communities: Initial Results of a Population Cohort Study in Western China.

Introduction: Lung cancer is a leading cause of cancer deaths globally. Despite favorable recommendations, low-dose computed tomography (LDCT) lung screening adoption remains low in China. Barriers such as limited infrastructure, costs, distance, and personnel shortages restrict screening access in disadvantaged regions. We initiated a telemedicine-enabled lung cancer screening (LCS) program in a medical consortium to serve people at risk in underserved communities. The objective of this study was to describe the implementation and initial results of the program. Methods: From 2020 to 2021, individuals aged 40-80 years were invited to take LCS by mobile computed tomography (CT) units in three underserved areas in Western China. Numerous CT scans were remotely reported by radiologists aided by artificial intelligence (AI) diagnostic systems. Abnormal cases were tracked through an integrated hospital network for follow-up. A retrospective cohort study documented participant demographics, health history, LDCT results, and outcomes. Descriptive analysis was conducted to report baseline characteristics and first-year follow-up results. Results: Of the 28,728 individuals registered in the program, 19,517 (67.94%) participated in the screening. The study identified 2.68% of participants with high-risk pulmonary nodules and diagnosed 0.55% with lung cancer after a 1-year follow-up. The majority of high-risk participants received timely treatment in hospitals. Conclusions: This study demonstrated mobile CT units with remote AI assistance improved access to LCS in underserved areas, with high participation and early detection rates. Our implementation supports the feasibility of deploying telemedicine-enabled LCS to increase access to a large scale of basic radiology and diagnostic services in resource-limited settings. Clinical Trial Registration Number: ChiCTR1900024623.

Association Between Long-Term Exposure to Ambient Air Pollution and the Risk of Mild Cognitive Impairment in a Chinese Urban Area: A Case-Control Study.

Background: As a prodromal stage of dementia, significant emphasis has been placed on the identification of modifiable risks of mild cognitive impairment (MCI). Research has indicated a correlation between exposure to air pollution and cognitive function in older adults. However, few studies have examined such an association among the MCI population inChina. Objective: We aimed to explore the association between air pollution exposure and MCI risk from the Hubei Memory and Aging Cohort Study. Methods: We measured four pollutants from 2015 to 2018, 3 years before the cognitive assessment of the participants. Logistic regression models were employed to calculate odds ratios (ORs) to assess the relationship between air pollutants and MCI risk. Results: Among 4,205 older participants, the adjusted ORs of MCI risk for the highest quartile of PM2.5, PM10, O3, and SO2 were 1.90 (1.39, 2.62), 1.77 (1.28, 2.47), 0.56 (0.42, 0.75), and 1.18 (0.87, 1.61) respectively, compared with the lowest quartile. Stratified analyses indicated that such associations were found in both males and females, but were more significant in older participants. Conclusions: Our findings are consistent with the growing evidence suggesting that air pollution increases the risk of mild cognitive decline, which has considerable guiding significance for early intervention of dementia in the older population. Further studies in other populations and broader geographical areas are warranted to validate these findings.

Identification and effective regulation of scarb1 gene involved in pigmentation change in autotetraploid Carassius auratus.

The autotetraploid Carassius auratus (4nRR, 4 n=200, RRRR) is derived from whole-genome duplication of Carassius auratus red var. (RCC, 2 n=100, RR). In the current study, we demonstrated that chromatophores and pigment changes directly caused the coloration and variation of 4nRR skin (red in RCC, brownish-yellow in 4nRR). To further explore the molecular mechanisms underlying coloration formation and variation in 4nRR, we performed transcriptome profiling and molecular functional verification in RCC and 4nRR. Results revealed that scarb1, associated with carotenoid metabolism, underwent significant down-regulation in 4nRR. Efficient editing of this candidate pigment gene provided clear evidence of its significant role in RCC coloration. Subsequently, we identified four divergent scarb1 homeologs in 4nRR: two original scarb1 homeologs from RCC and two duplicated ones. Notably, three of these homeologs possessed two highly conserved alleles, exhibiting biased and allele-specific expression in the skin. Remarkably, after precise editing of both the original and duplicated scarb1 homeologs and/or alleles, 4nRR individuals, whether singly or multiply mutated, displayed a transition from brownish-yellow skin to a cyan-gray phenotype. Concurrently, the proportional areas of the cyan-gray regions displayed a gene-dose correlation. These findings illustrate the subfunctionalization of duplicated scarb1, with all scarb1 genes synergistically and equally contributing to the pigmentation of 4nRR. This is the first report concerning the functional differentiation of duplicated homeologs in an autopolyploid fish, substantially enriching our understanding of coloration formation and change within this group of organisms.

Fractionated lignin as a green compatibilizer to improve the compatibility of poly (butylene adipate-co-terephthalate) /polylactic acid composites.

Blending poly (butylene adipate-co-terephthalate) (PBAT) and polylactic acid (PLA) is a cost-effective strategy to obtain biodegradable plastic with complementary properties. However, the incompatibility between PBAT and PLA is a great challenge for fabricating high-performance composite films. Herein, the ethyl acetate fractionated lignin with the small glass transition temperature and low molecular weight was achieved and incorporated into the PBAT/PLA composite as a compatibilizer. The fractionated lignin can be uniformly dispersed within the PBAT/PLA matrix through a melt blending process and interact with the molecular chain of PBAT and PLA as a bonding bridge, which enhances the intermolecular interactions and reduces the interfacial tension of PBAT/PLA. By adding fractionated lignin, the tensile strength of the PBAT/PLA composite increased by 35.4 % and the yield strength increased by 37.7 %. Owing to lignin, the composite films possessed the ultraviolet shielding function and exhibited better water vapor barrier properties (1.73 ± 0.08 × 10-13 g·cm/cm2·s·Pa). This work conclusively demonstrated that fractionated lignin can be used as a green compatibilizer and a low-cost functional filler for PBAT/PLA materials, and provides guidance for the application of lignin in biodegradable plastics.

Relationship between chorioamnionitis or funisitis and lung injury among preterm infants: meta-analysis involved 16 observational studies with 68,397 participants.

BACKGROUND: Chorioamnionitis (CA) can cause multiple organ injuries in premature neonates, particularly to the lungs. Different opinions exist regarding the impact of intrauterine inflammation on neonatal respiratory distress syndrome (NRDS) and bronchopulmonary dysplasia (BPD). We aim to systematically review the relationship between CA or Funisitis (FV) and lung injury among preterm infants. METHODS: We electronically searched PubMed, EMbase, the Cochrane library, CNKI, and CMB for cohort studies from their inception to March 15, 2023. Two reviewers independently screened literature, gathered data, and did NOS scale of included studies. The meta-analysis was performed using RevMan 5.3. RESULTS: Sixteen observational studies including 68,397 patients were collected. Meta-analysis showed CA or FV increased the lung injury risk (OR = 1.43, 95%CI: 1.06-1.92). Except for histological chorioamnionitis (HCA) (OR = 0.72, 95%CI: 0.57-0.90), neither clinical chorioamnionitis (CCA) (OR = 1.86, 95%CI: 0.93-3.72) nor FV (OR = 1.23, 95%CI: 0.48-3.15) nor HCA with FV (OR = 1.85, 95%CI: 0.15-22.63) had statistical significance in NRDS incidence. As a result of stratification by grade of HCA, HCA (II) has a significant association with decreased incidence of NRDS (OR = 0.48, 95%CI: 0.35-0.65). In terms of BPD, there is a positive correlation between BPD and CA/FV (CA: OR = 3.18, 95%CI: 1.68-6.03; FV: OR = 6.36, 95%CI: 2.45-16.52). Among CA, HCA was positively associated with BPD (OR = 2.70, 95%CI: 2.38-3.07), whereas CCA was not associated with BPD (OR = 2.77, 95%CI: 0.68-11.21). HCA and moderate to severe BPD (OR = 25.38, 95%CI: 7.13-90.32) showed a positive correlation, while mild BPD (OR = 2.29, 95%CI: 0.99-5.31) did not. CONCLUSION: Currently, evidence suggests that CA or FV increases the lung injury incidence in premature infants. For different types of CA and FV, HCA can increase the incidence of BPD while decreasing the incidence of NRDS. And this "protective effect" only applies to infants under 32 weeks of age. Regarding lung injury severity, only moderate to severe cases of BPD were positively correlated with CA.

Deep learning for precise diagnosis and subtype triage of drug-resistant tuberculosis on chest computed tomography.

Deep learning, transforming input data into target prediction through intricate network structures, has inspired novel exploration in automated diagnosis based on medical images. The distinct morphological characteristics of chest abnormalities between drug-resistant tuberculosis (DR-TB) and drug-sensitive tuberculosis (DS-TB) on chest computed tomography (CT) are of potential value in differential diagnosis, which is challenging in the clinic. Hence, based on 1176 chest CT volumes from the equal number of patients with tuberculosis (TB), we presented a Deep learning-based system for TB drug resistance identification and subtype classification (DeepTB), which could automatically diagnose DR-TB and classify crucial subtypes, including rifampicin-resistant tuberculosis, multidrug-resistant tuberculosis, and extensively drug-resistant tuberculosis. Moreover, chest lesions were manually annotated to endow the model with robust power to assist radiologists in image interpretation and the Circos revealed the relationship between chest abnormalities and specific types of DR-TB. Finally, DeepTB achieved an area under the curve (AUC) up to 0.930 for thoracic abnormality detection and 0.943 for DR-TB diagnosis. Notably, the system demonstrated instructive value in DR-TB subtype classification with AUCs ranging from 0.880 to 0.928. Meanwhile, class activation maps were generated to express a human-understandable visual concept. Together, showing a prominent performance, DeepTB would be impactful in clinical decision-making for DR-TB.

Machine Learning-Based Clinical Prediction Models for Acute Ischemic Stroke Based on Serum Xanthine Oxidase Levels.

OBJECTIVE: Early prediction of the onset, progression and prognosis of acute ischemic stroke (AIS) is helpful for treatment decision-making and proactive management. Although several biomarkers have been found to predict the progression and prognosis of AIS, these biomarkers have not been widely used in routine clinical practice. Xanthine oxidase (XO) is a form of xanthine oxidoreductase (XOR), which is widespread in various organs of the human body and plays an important role in redox reactions and ischemia‒reperfusion injury. Our previous studies have shown that serum XO levels on admission have certain clinical predictive value for AIS. The purpose of this study was to utilize serum XO levels and clinical data to establish machine learning models for predicting the onset, progression, and prognosis of AIS. METHODS: We enrolled 328 consecutive patients with AIS and 107 healthy controls from October 2020 to September 2021. Serum XO levels and stroke-related clinical data were collected. We established 5 machine learning models-the logistic regression (LR), support vector machine (SVM), decision tree, random forest, and K-nearest neighbor (KNN) models-to predict the onset, progression, and prognosis of AIS. The area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, negative predictive value, and positive predictive value were used to evaluate the predictive performance of each model. RESULTS: Among the 5 machine learning models predicting AIS onset, the AUROC values of 4 prediction models were over 0.7, while that of the KNN model was lower (AUROC = 0.6708, 95% CI 0.576-0.765). The LR model showed the best AUROC value (AUROC = 0.9586, 95% CI 0.927-0.991). Although the 5 machine learning models showed relatively poor predictive value for the progression of AIS (all AUROCs <0.7), the LR model still showed the highest AUROC value (AUROC = 0.6543, 95% CI 0.453-0.856). We compared the value of 5 machine learning models in predicting the prognosis of AIS, and the LR model showed the best predictive value (AUROC = 0.8124, 95% CI 0.715-0.910). CONCLUSIONS: The tested machine learning models based on serum levels of XO could predict the onset and prognosis of AIS. Among the 5 machine learning models, we found that the LR model showed the best predictive performance. Machine learning algorithms improve accuracy in the early diagnosis of AIS and can be used to make treatment decisions.

Efficacy and safety of cadonilimab in previously treated recurrent or metastatic nasopharyngeal carcinoma(COMPASSION-06): A phase II multicenter study.

OBJECTIVE: This study was designed to assess the efficacy and safety of cadonilimab monotherapy, a first-in-class, bi-specific PD-1/CTLA-4 antibody, in patients with previously treated recurrent or metastatic nasopharyngeal carcinoma (R/M-NPC). PATIENTS AND METHODS: This multicenter, open-label, single-arm, phase II clinical trial enrolled patients with R/M-NPC who had failed first-line platinum-based chemotherapy and second-line single agent or combined chemotherapy, and immunotherapy-naive. Patients received cadonilimab for 6 mg/kg once every 2 weeks (Q2W). The primary endpoint was objective response rate (ORR) in full analysis set (FAS) assessed by investigators according to RECIST v.1.1. The secondary endpoint included progression-free survival (PFS), overall survival (OS), duration of response (DoR), time to response (TTR) and safety. RESULTS: A total of 23 patients were assessed. The median time from first dose to data cutoff was 16.56 (range, 0.8-25.2) months. ORR was 26.1 % (95 %CI:10.2-48.4). The ORR were 44.4 % (95 %CI: 13.7-78.8) and 14.3 % (95 %CI:1.8-42.8) in patients with tumor PD-L1 expression ≥50 % and <50 %, respectively. ORR was achieved in 40.0 % (95 %CI:12.2-73.8) of patients with EBV-DNA level <4000 IU/ml (n = 10) and 15.4 % (95 %CI:1.9-45.4) of those with ≥4000 IU/ml. The median PFS was 3.71 months (95 %CI: 1.84-9.30). respectively. Median OS was not reached, and the 12-month OS rate was 79.7 % (95 % CI:54.5-91.9). Only two patients (8.3 %) experienced Grade ≥3 treatment-related adverse events (TRAEs) with hypothyroidism (30.4 %), rash (21.7 %) and pruritus (21.7 %) being the most prevalent TRAEs. CONCLUSION: Cadonilimab monotherapy demonstrated a promising efficacy and manageable toxicity in patients with previously treated R-M/NPC and provide an efficacious salvage treatment option.

Intraoperative AI-assisted early prediction of parathyroid and ischemia alert in endoscopic thyroid surgery.

BACKGROUND: The preservation of parathyroid glands is crucial in endoscopic thyroid surgery to prevent hypocalcemia and related complications. However, current methods for identifying and protecting these glands have limitations. We propose a novel technique that has the potential to improve the safety and efficacy of endoscopic thyroid surgery. PURPOSE: Our study aims to develop a deep learning model called PTAIR 2.0 (Parathyroid gland Artificial Intelligence Recognition) to enhance parathyroid gland recognition during endoscopic thyroidectomy. We compare its performance against traditional surgeon-based identification methods. MATERIALS AND METHODS: Parathyroid tissues were annotated in 32 428 images extracted from 838 endoscopic thyroidectomy videos, forming the internal training cohort. An external validation cohort comprised 54 full-length videos. Six candidate algorithms were evaluated to select the optimal one. We assessed the model's performance in terms of initial recognition time, identification duration, and recognition rate and compared it with the performance of surgeons. RESULTS: Utilizing the YOLOX algorithm, we developed PTAIR 2.0, which demonstrated superior performance with an AP50 score of 92.1%. The YOLOX algorithm achieved a frame rate of 25.14 Hz, meeting real-time requirements. In the internal training cohort, PTAIR 2.0 achieved AP50 values of 94.1%, 98.9%, and 92.1% for parathyroid gland early prediction, identification, and ischemia alert, respectively. Additionally, in the external validation cohort, PTAIR outperformed both junior and senior surgeons in identifying and tracking parathyroid glands (p < 0.001). CONCLUSION: The AI-driven PTAIR 2.0 model significantly outperforms both senior and junior surgeons in parathyroid gland identification and ischemia alert during endoscopic thyroid surgery, offering potential for enhanced surgical precision and patient outcomes.

Subtle adjustments for constructing multi-nuclear luminescent lanthanide organic polyhedra with triazole-based chelates.

Controlled self-assembly of predetermined multi-nuclear lanthanide organic polyhedra (LOPs) still presents a challenge, primarily due to the unpredictable coordination numbers and labile coordination geometries of lanthanide ions. In this study, through introducing triazole-based chelates to increase the chelating angle of C2-symmetric linear ligands and stabilize the coordination geometry of Eu(III) centers, M4L6-type (M = EuIII, L = ligand) tetrahedra were efficiently synthesized, especially a biphenyl-bridged ligand which is well known to form M2L3-type helicates. A series of LOPs were formed and characterized by high-resolution electrospray ionization time-of-flight mass spectroscopy (ESI-TOF-MS) and X-ray crystallography. Moreover, the europium complexes exhibit bright emission (luminescence quantum yield up to 42.4%) and circularly polarized luminescence properties (|glum| up to 4.5 × 10-2). This study provides a feasible strategy for constructing multi-nuclear luminescent LOPs towards potential applications.

Optimizing robotic thyroid surgery: lessons learned from an retrospective analysis of 104 cases.

Background: Robotic assistance in thyroidectomy is a developing field that promises enhanced surgical precision and improved patient outcomes. This study investigates the impact of the da Vinci Surgical System on operative efficiency, learning curve, and postoperative outcomes in thyroid surgery. Methods: We conducted a retrospective cohort study of 104 patients who underwent robotic thyroidectomy between March 2018 and January 2022. We evaluated the learning curve using the Cumulative Sum (CUSUM) analysis and analyzed operative times, complication rates, and postoperative recovery metrics. Results: The cohort had a mean age of 36 years, predominantly female (68.3%). The average body mass index (BMI) was within the normal range. A significant reduction in operative times was observed as the series progressed, with no permanent hypoparathyroidism or recurrent laryngeal nerve injuries reported. The learning curve plateaued after the 37th case. Postoperative recovery was consistent, with no significant difference in hospital stay duration. Complications were minimal, with a noted decrease in transient vocal cord palsy as experience with the robotic system increased. Conclusion: Robotic thyroidectomy using the da Vinci system has demonstrated a significant improvement in operative efficiency without compromising safety. The learning curve is steep but manageable, and once overcome, it leads to improved surgical outcomes and high patient satisfaction. Further research with larger datasets and longer follow-up is necessary to establish the long-term benefits of robotic thyroidectomy.

The effect of acupuncture on oxidative stress in animal models of vascular dementia: a systematic review and meta-analysis.

BACKGROUND: Growing evidence showed that acupuncture may improve cognitive function by reducing oxidative stress, key to the pathogenesis in vascular dementia (VaD), but this is yet to be systematically analysed. This study aimed to summarize and evaluate the effect of acupuncture on oxidative stress in animal models of VaD. METHOD: Eight databases including PubMed, Embase, Web of Science, Cochrane library, CNKI, Wan Fang, CBM, and VIP were searched since their establishment until April 2023, for studies that reported the effect of acupuncture on oxidative stress in VaD animal models. Relevant literature was screened, and information was extracted by two reviewers. The primary outcomes were the levels of oxidative stress indicators. The methodological quality was assessed via the SYRCLE Risk of Bias Tool. Statistical analyses were performed using the RevMan and Stata software. RESULTS: In total, 22 studies with 747 animals were included. The methodology of most studies had flaws or uncertainties. The meta-analysis indicated that, overall, acupuncture significantly reduced the expression of pro-oxidants including reactive oxygen species (standardized mean differences [SMDs] = -4.29, 95% confidence interval [CI]: -6.26, -2.31), malondialdehyde (SMD = -2.27, 95% CI: -3.07, -1.47), nitric oxide (SMD = -0.85, 95% CI: -1.50, -0.20), and nitric oxide synthase (SMD = -1.01, 95% CI: -1.69, -0.34) and enhanced the levels of anti-oxidants including super oxide dismutase (SMD = 2.80, 95% CI: 1.98, 3.61), glutathione peroxidase (SMD = 1.32, 95% CI: -0.11, 2.76), and catalase (SMD = 1.31, 95% CI: 0.05, 2.58) in VaD animal models. In subgroup analyses, acupuncture showed significant effects on most variables. Only partial modelling methods and treatment duration could interpret the heterogeneity of some outcomes. CONCLUSION: Acupuncture may inhibit oxidative stress to improve cognitive deficits in animal models of VaD. Nevertheless, the methodological quality is unsatisfactory. More high-quality research with a rigorous design and further experimental researches and clinical trials are needed to confirm these findings. SYSTEMATIC REVIEW REGISTRATION: This study was registered in PROSPERO (CRD42023411720).