Enabling target-aware molecule generation to follow multi objectives with Pareto MCTS.

Target-aware drug discovery has greatly accelerated the drug discovery process to design small-molecule ligands with high binding affinity to disease-related protein targets. Conditioned on targeted proteins, previous works utilize various kinds of deep generative models and have shown great potential in generating molecules with strong protein-ligand binding interactions. However, beyond binding affinity, effective drug molecules must manifest other essential properties such as high drug-likeness, which are not explicitly addressed by current target-aware generative methods. In this article, aiming to bridge the gap of multi-objective target-aware molecule generation in the field of deep learning-based drug discovery, we propose ParetoDrug, a Pareto Monte Carlo Tree Search (MCTS) generation algorithm. ParetoDrug searches molecules on the Pareto Front in chemical space using MCTS to enable synchronous optimization of multiple properties. Specifically, ParetoDrug utilizes pretrained atom-by-atom autoregressive generative models for the exploration guidance to desired molecules during MCTS searching. Besides, when selecting the next atom symbol, a scheme named ParetoPUCT is proposed to balance exploration and exploitation. Benchmark experiments and case studies demonstrate that ParetoDrug is highly effective in traversing the large and complex chemical space to discover novel compounds with satisfactory binding affinities and drug-like properties for various multi-objective target-aware drug discovery tasks.

Gut microbiome model predicts response to neoadjuvant immunotherapy plus chemoradiotherapy in rectal cancer.

BACKGROUND: Accurate evaluation of the response to preoperative treatment enables the provision of a more appropriate personalized therapeutic schedule for locally advanced rectal cancer (LARC), which remains an enormous challenge, especially neoadjuvant immunotherapy plus chemoradiotherapy (nICRT). METHODS: This prospective, multicenter cohort study enrolled patients with LARC from 6 centers who received nICRT. The dynamic variation in the gut microbiome during nICRT was evaluated. A species-level gut microbiome prediction (SPEED) model was developed and validated to predict the pathological complete response (pCR) to nICRT. FINDINGS: A total of 50 patients were enrolled, 75 fecal samples were collected from 33 patients at different time points, and the pCR rate reached 42.4% (14/33). Lactobacillus and Eubacterium were observed to increase after nICRT. Additionally, significant differences in the gut microbiome were observed between responders and non-responders at baseline. Significantly higher abundances of Lachnospiraceaebacterium and Blautiawexlerae were found in responders, while Bacteroides, Prevotella, and Porphyromonas were found in non-responders. The SPEED model showcased a superior predictive performance with areas under the curve of 98.80% (95% confidence interval [CI]: 95.67%-100%) in the training cohort and 77.78% (95% CI: 65.42%-88.29%) in the validation cohort. CONCLUSIONS: Programmed death 1 (PD-1) blockade plus concurrent long-course CRT showed a favorable pCR rate and is well tolerated in microsatellite-stable (MSS)/mismatch repair-proficient (pMMR) patients with LARC. The SPEED model can be used to predict the pCR to nICRT based on the baseline gut microbiome with high robustness and accuracy, thereby assisting clinical physicians in providing individualized management for patients with LARC. FUNDING: This research was funded by the China National Natural Science Foundation (82202884).

Highly Accurate and Efficient Deep Learning Paradigm for Full-Atom Protein Loop Modeling with KarmaLoop.

Protein loop modeling is a challenging yet highly nontrivial task in protein structure prediction. Despite recent progress, existing methods including knowledge-based, ab initio, hybrid, and deep learning (DL) methods fall substantially short of either atomic accuracy or computational efficiency. To overcome these limitations, we present KarmaLoop, a novel paradigm that distinguishes itself as the first DL method centered on full-atom (encompassing both backbone and side-chain heavy atoms) protein loop modeling. Our results demonstrate that KarmaLoop considerably outperforms conventional and DL-based methods of loop modeling in terms of both accuracy and efficiency, with the average RMSDs of 1.77 and 1.95 Å for the CASP13+14 and CASP15 benchmark datasets, respectively, and manifests at least 2 orders of magnitude speedup in general compared with other methods. Consequently, our comprehensive evaluations indicate that KarmaLoop provides a state-of-the-art DL solution for protein loop modeling, with the potential to hasten the advancement of protein engineering, antibody-antigen recognition, and drug design.

High-Grade Appendiceal Mucinous Neoplasm Mimicking Appendiceal Tubulovillous Adenoma: A Case Report and Literature Review.

High-grade appendiceal mucinous neoplasm (HAMN) has been separated from appendiceal adenocarcinoma recently as an independent entity and categorized into appendiceal mucinous neoplasms. These neoplasms demonstrate distinct histological characteristics, including architectures and appendiceal mural changes similar to low-grade appendiceal mucinous neoplasm but with high-grade cytology, and no infiltrative invasion. Overt mucinous feature are not evident in some cases as the high-grade neoplastic epithelium may show intracytoplasmic mucin reduction. Occasionally, the neoplastic epithelial cells show florid proliferation and tubulovillous configuration and may be misdiagnosed as appendiceal tubulovillous adenoma. We report the case of a 67-year-old woman with appendicular dilatation and luminal mucin. She underwent an ileocecoectomy. The appendiceal lesion was found histologically to be a HAMN, which closely resembled appendiceal tubulovillous adenoma. The tumor cells demonstrated wild-type p53 expression and mismatch repair proficiency by immunochemistry. Molecular testing showed 1 KRAS mutation, 2 PIK3CA mutations, and 1 BRCA2, EP300, TGFBR2, CHD4, CREBBP, FANCC, PKHD1 mutation each in the tumor. The patient was followed up for 1 year with no evidence of disease.

Clinicopathological and molecular genetic analysis of 13 cases of primary retroperitoneal Ewing sarcoma.

Retroperitoneal Ewing sarcomas (RES) are very rare and mostly described in case reports. The purpose of this study was to retrospectively analyze the clinicopathology, molecular characteristics, biological behavior, and therapeutic information of 13 cases of primary RES with immunohistochemical staining, fluorescence in situ hybridization, RT-PCR and NGS sequencing detection techniques. The thirteen patients included eight males and five females with a mean age of 34 years. Morphologically, the tumors were comprised of small round or epithelial-like cells with vacuolated cytoplasm (6/13,46 %) arranged in diffuse, nested (8/13,62 %) and perivascular (7/13,54 %) patterns. Unusual morphologic patterns, such as meningioma-like swirling structures and sieve-like structures were relatively novel findings. Immunohistochemical studies showed CD99 (12/13; 92 %), CD56 (11/13; 85 %), NKX2.2 (9/13; 69 %), PAX7 (10/11;91 %) and CD117(6/9;67 %) to be positive.12 cases (92 %) demonstrated EWSR1 rearrangement and 3 cases displayed EWSR1::FLI1 fusion by FISH. ERCC4 splice-site variant, a novel pathogenic variant, was discovered for the first time via RNA sequencing. With a median follow-up duration of 14 months (6 to 79 months), 8/13 (62 %) patients died, while 5/13(38 %) survived. Three cases recurred, and five patients developed metastasis to the liver (2 cases), lung (2 cases) and bone (1 case). RES is an aggressive, high-grade tumor, prone to multiple recurrences and metastases, with distinctive morphologic, immunohistochemical, and molecular genetic features. ERCC4 splicing mutation, which is a novel pathogenic variant discovered for the first time, with possible significance for understanding the disease, as well as the development of targeted drugs.

Freeprotmap: waiting-free prediction method for protein distance map.

BACKGROUND: Protein residue-residue distance maps are used for remote homology detection, protein information estimation, and protein structure research. However, existing prediction approaches are time-consuming, and hundreds of millions of proteins are discovered each year, necessitating the development of a rapid and reliable prediction method for protein residue-residue distances. Moreover, because many proteins lack known homologous sequences, a waiting-free and alignment-free deep learning method is needed. RESULT: In this study, we propose a learning framework named FreeProtMap. In terms of protein representation processing, the proposed group pooling in FreeProtMap effectively mitigates issues arising from high-dimensional sparseness in protein representation. In terms of model structure, we have made several careful designs. Firstly, it is designed based on the locality of protein structures and triangular inequality distance constraints to improve prediction accuracy. Secondly, inference speed is improved by using additive attention and lightweight design. Besides, the generalization ability is improved by using bottlenecks and a neural network block named local microformer. As a result, FreeProtMap can predict protein residue-residue distances in tens of milliseconds and has higher precision than the best structure prediction method. CONCLUSION: Several groups of comparative experiments and ablation experiments verify the effectiveness of the designs. The results demonstrate that FreeProtMap significantly outperforms other state-of-the-art methods in accurate protein residue-residue distance prediction, which is beneficial for lots of protein research works. It is worth mentioning that we could scan all proteins discovered each year based on FreeProtMap to find structurally similar proteins in a short time because the fact that the structure similarity calculation method based on distance maps is much less time-consuming than algorithms based on 3D structures.

Sex differences in the correlation between white matter hyperintensity and 3-month outcome in acute stroke patients.

Background: The severity of white matter hyperintensities (WMH) has been shown to be an independent predictor of poor stroke outcome, but the effect of sex on this correlation has not been investigated further. Therefore, the purpose of our study was to assess whether there was a sex difference between the severity of WMH and poor stroke outcome. Methods: This retrospective study included 449 patients with acute ischemic stroke (AIS) who received intravenous thrombolysis. WMH severity was graded based on the Fazekas scale. The association between WMH severity and stroke outcome was explored through multivariable regression analyses in men and women. Results: Among women, when dividing WMH severity into tertiles, T3 (Fazekas scale >3) had a 5.334 times higher risk for unfavorable outcomes than T1 (Fazekas scale <2) (p-trend = 0.026) in the adjusted model. In addition, moderate-severe WMH (Fazekas scale 3-6) had a 3.391 (1.151-9.991) times higher risk than none-mild WMH (Fazekas scale 0-2) (p = 0.027). Conclusions: The risk of unfavorable outcomes increased proportionally with the enlargement of the WMH severity in females, suggesting the sex-specific value of the WMH severity in optimizing the risk stratification of stroke.

Advances of NOTCH2NLC Repeat Expansions and Associated Diseases: A Bibliometric and Meta-analysis.

The unclear pathogenic mechanisms of neurodegenerative disorders stemming from NOTCH2NLC GGC repeat expansions drive focused research. Thus, a bibliometric and meta-analysis was conducted to uncover research trends and positivity rates in NOTCH2NLC. We conducted systematic searches in the Web of Science, PubMed, Embase, and Scopus databases for studies related to NOTCH2NLC up until August 2, 2023. Information regarding countries, institutions, authors, journals, and keywords of studies included in the Web of Science was analyzed and visualized. The positivity rates of NOTCH2NLC GGC repeat expansions across all screened patients and patients' families were pooled under the random-effects model. Publication bias and its impact were examined using funnel plots, Egger's linear regression, and trim-and-fill method. The bibliometric analysis, revealing pronounced publication growth, comprised 119 studies, which came from China and Japan particularly. "Neuronal intranuclear inclusion disease" emerged as a frequently used keyword. The meta-analysis comprised 36 studies, indicating global positivity rates of 1.79% (95% CI, 0.75-3.17) for all patients and 2.00% (95% CI, 0.26-4.78) for patients' families. Subgroup analyses based on region and phenotype suggested the highest NOTCH2NLC positivity rates in Taiwan population (5.42%, 95% CI 0.08-16.89) and in leukoencephalopathy-dominant patients (8.25%, 95% CI, 3.01-15.60). Sensitivity analysis affirmed the robustness of results. In conclusion, NOTCH2NLC GGC repeat expansions exhibit rare globally, primarily in East Asia, and leukoencephalopathy-dominant patients, emphasizing regional and phenotypic distinctions. Emerging focal points in NOTCH2NLC researches underscore the need for collaborative exploration.

IFKMHC: Implicit Fuzzy K-Means Model for High-Dimensional Data Clustering.

The graph-information-based fuzzy clustering has shown promising results in various datasets. However, its performance is hindered when dealing with high-dimensional data due to challenges related to redundant information and sensitivity to the similarity matrix design. To address these limitations, this article proposes an implicit fuzzy k-means (FKMs) model that enhances graph-based fuzzy clustering for high-dimensional data. Instead of explicitly designing a similarity matrix, our approach leverages the fuzzy partition result obtained from the implicit FKMs model to generate an effective similarity matrix. We employ a projection-based technique to handle redundant information, eliminating the need for specific feature extraction methods. By formulating the fuzzy clustering model solely based on the similarity matrix derived from the membership matrix, we mitigate issues, such as dependence on initial values and random fluctuations in clustering results. This innovative approach significantly improves the competitiveness of graph-enhanced fuzzy clustering for high-dimensional data. We present an efficient iterative optimization algorithm for our model and demonstrate its effectiveness through theoretical analysis and experimental comparisons with other state-of-the-art methods, showcasing its superior performance.

Prediction of trends in unfavorable prognosis in patients with acute ischemic stroke according to low left ventricular ejection fraction levels.

As few studies have reported the impact of lower left ventricular ejection fraction (LVEF) on the prognosis of acute ischemic stroke (AIS) patients, we aimed to explore this through a retrospective cohort study and a meta-analysis. A total of 283 AIS patients receiving intravenous thrombolysis at the Third Affiliated Hospital of Wenzhou Medical University between 2016 and 2019 were enrolled and divided into three groups based on LVEF tertiles. The logistic regression model estimated the association between LVEF and the three-month AIS prognosis. After adjusting for confounding factors, patients in tertile 3 exhibited an increased risk of poor functional outcome and mortality [odds ratio (OR), 2.656 (95% CI: 1.443-4.889); OR, 7.586 (95% CI: 2.102-27.375)]. A systematic search of PubMed, EMBASE and Cochrane Library was performed. Our meta-analysis revealed that LVEF < 40% was significantly associated with poor functional outcome [OR 1.94 (95% CI: 1.08-3.50)], mortality [OR 3.69 (95% CI: 1.22-11.11)], as well as LVEF < 55% [OR 1.68 (95% CI: 1.22-2.32); 2.27 (95% CI: 1.30-3.96)], respectively. A decreased LVEF could predict an inferior prognosis for AIS; therefore, it could aid in clinical decision-making in this patient population.

Efficacy and safety of PD-1 blockade plus long-course chemoradiotherapy in locally advanced rectal cancer (NECTAR): a multi-center phase 2 study.

Adding PD-1 blockade in the neoadjuvant regimens for locally advanced rectal cancer (LARC) patients with microsatellite stable (MSS) / mismatch repair-proficient (pMMR) tumors is an attractive, but debatable strategy. This phase 2, multicenter, prospective, single-arm study enrolled patients from 6 centers from June 2021 to November 2022. Locally advanced rectal cancer (LARC, cT3-4aN0M0 and cT1-4aN1-2M0) patients aged ≥18 years with the distance from distal border of tumor to anal verge ≤10 cm (identified by Magnetic Resonance Imaging) were qualified for inclusion. The patients received long-course radiotherapy (50 Gy/25 fractions, 2 Gy/fraction, 5 days/week) and three 21-day cycles capecitabine (850-1000 mg/m2, bid, po, day1-14) and three 21-day cycles tislelizumab (200 mg, iv.gtt, day8) as neoadjuvant. Total mesorectal excision (TME) was 6-12 weeks after the end of radiotherapy to achieve radical resection. A total of 50 patients were enrolled in this study. The pathological complete response rate was 40.0% [20/50, 95% confidence interval (CI): 27.61-53.82%], while 15 (30.0%, 95% CI: 19.1-43.75%), 9 (18.0%, 95% CI: 9.77-30.8%), 2 (4.0%, 95% CI: 1.10-13.46%) patients respectively achieved grade 1, 2, and 3 tumor regression. Treatment-related adverse events (TRAEs) occurred in 28 (56.0%) LARC patients, including 26(52.0%) with grade I-II and 2 (4.0%) with grade III (1 with grade 3 immune-related colitis and 1 with grade 3 rash). PD-1 blockade plus long-course chemoradiotherapy (CRT) showed promising therapeutic effects according to pathological complete response rate and is well-tolerated in LARC patients. A larger randomized controlled study is desired to further validate the above findings.

Assessment of risk factors of lymph node metastasis and prognosis of Siewert II/III adenocarcinoma of esophagogastric junction: A retrospective study.

Adenocarcinoma of the esophagogastric junction (AEG) has a high incidence, and the extent of lymph node dissection (LND) and its impact on prognosis remain controversial. This study aimed to explore the risk factors for lymph node metastasis (LNM) and prognosis in Siewert II/III AEG patients. A retrospective review of 239 Siewert II/III AEG patients surgically treated at Beijing Friendship Hospital from July 2013 to December 2022 was conducted. Preoperative staging was conducted via endoscopy, ultrasound gastroscopy, CT, and biopsy. Depending on the stage, patients received radical gastrectomy with LND and chemotherapy. Clinicopathological data were collected, and survival was monitored semiannually until November 2023. Utilizing logistic regression for data analysis and Cox regression for survival studies, multivariate analysis identified infiltration depth (OR = 0.038, 95% CI: 0.011-0.139, P < .001), tumor deposit (OR = 0.101, 95% CI: 0.011-0.904, P = .040), and intravascular cancer embolus (OR = 0.234, 95% CI: 0.108-0.507, P < .001) as independent predictors of LNM. Lymph nodes No. 1, 2, 3, 4, 7, 10, and 11 were more prone to metastasis in the abdominal cavity. Notably, Siewert III AEG patients showed a higher metastatic rate in nodes No. 5 and No. 6 compared to Siewert II. Mediastinal LNM was predominantly found in nodes No. 110 and No. 111 for Siewert II AEG, with rates of 5.45% and 3.64%, respectively. A 3-year survival analysis underscored LNM as a significant prognostic factor (P = .001). Siewert II AEG patients should undergo removal of both celiac and mediastinal lymph nodes, specifically nodes No. 1, 2, 3, 4, 7, 10, 11, 110, and 111. Dissection of nodes No. 5 and No. 6 is not indicated for these patients. In contrast, Siewert III AEG patients do not require mediastinal LND, but pyloric lymphadenectomy for nodes No. 5 and No. 6 is essential. The presence of LNM is associated with poorer long-term prognosis. Perioperative chemotherapy may offer a survival advantage for AEG patients.

Neuronal Intranuclear Inclusion Disease with NOTCH2NLC GGC Repeat Expansion: A Systematic Review and Challenges of Phenotypic Characterization.

Neuronal intranuclear inclusion disease (NIID) is a highly clinically heterogeneous neurodegenerative disorder primarily attributed to abnormal GGC repeat expansions in the NOTCH2NLC gene. This study aims to comprehensively explore its phenotypic characteristics and genotype-phenotype correlation. A literature search was conducted in PubMed, Embase, and the Cochrane Library from September 1, 2019, to December 31, 2022, encompassing reported NIID cases confirmed by pathogenic NOTCH2NLC mutations. Linear regressions and trend analyses were performed. Analyzing 635 cases from 85 included studies revealed that familial cases exhibited significantly larger GGC repeat expansions than sporadic cases (p < 0.001), and this frequency significantly increased with expanding GGC repeats (p trend < 0.001). Age at onset (AAO) showed a negative correlation with GGC repeat expansions (p < 0.001). The predominant initial symptoms included tremor (31.70%), cognitive impairment (14.12%), and muscle weakness (10.66%). The decreased or absent tendon reflex (DTR/ATR) emerged as a notable clinical indicator of NIID due to its high prevalence. U-fiber was observed in 79.11% of patients, particularly prominent in paroxysmal disease-dominant (87.50%) and dementia-dominant cases (81.08%). Peripheral neuropathy-dominant cases exhibited larger GGC repeat expansions (median = 123.00) and an earlier AAO (median = 33.00) than other phenotypes. Moreover, a significant genetic anticipation of 3.5 years was observed (p = 0.039). This study provides a comprehensive and up-to-date compilation of genotypic and phenotypic information on NIID since the identification of the causative gene NOTCH2NLC. We contribute a novel diagnostic framework for NIID to support clinical practice.

High-Similarity-Pass Attention for Single Image Super-Resolution.

Recent developments in the field of non-local attention (NLA) have led to a renewed interest in self-similarity-based single image super-resolution (SISR). Researchers usually use the NLA to explore non-local self-similarity (NSS) in SISR and achieve satisfactory reconstruction results. However, a surprising phenomenon that the reconstruction performance of the standard NLA is similar to that of the NLA with randomly selected regions prompted us to revisit NLA. In this paper, we first analyzed the attention map of the standard NLA from different perspectives and discovered that the resulting probability distribution always has full support for every local feature, which implies a statistical waste of assigning values to irrelevant non-local features, especially for SISR which needs to model long-range dependence with a large number of redundant non-local features. Based on these findings, we introduced a concise yet effective soft thresholding operation to obtain high-similarity-pass attention (HSPA), which is beneficial for generating a more compact and interpretable distribution. Furthermore, we derived some key properties of the soft thresholding operation that enable training our HSPA in an end-to-end manner. The HSPA can be integrated into existing deep SISR models as an efficient general building block. In addition, to demonstrate the effectiveness of the HSPA, we constructed a deep high-similarity-pass attention network (HSPAN) by integrating a few HSPAs in a simple backbone. Extensive experimental results demonstrate that HSPAN outperforms state-of-the-art approaches on both quantitative and qualitative evaluations. Our code and a pre-trained model were uploaded to GitHub (https://github.com/laoyangui/HSPAN) for validation.

Association of nutritional screening tools with 6-month outcomes in ischemic stroke patients: A retrospective study.

OBJECTIVE: Nutritional screening tools based on laboratory examinations are relatively objective and available indicators. However, few studies have investigated whether malnutrition severity might be associated with adverse outcomes at the platform recovery period of 6 mo and differentiated in acute ischemic stroke patients with or without intravenous thrombolysis. Therefore, we assessed the association between malnutrition and 6-mo outcomes in both intravenous thrombolysis and non-intravenous thrombolysis patients. METHODS: We retrospectively recruited 138 acute ischemic stroke patients who received intravenous thrombolysis and 311 who did not. The Geriatric Nutritional Risk Index, prognostic nutritional index, and Controlling Nutritional Status were used to assess nutritional status. The concordance between the 3 malnutrition screening tools was investigated with the κ statistic. Subgroups analyses were conducted to assess the correlation between malnutrition and functional outcomes in intravenous thrombolysis and non-intravenous thrombolysis patients. RESULTS: A total of 17 (6.44%) patients were suffering from malnutrition, as indicated by the Geriatric Nutritional Risk Index, prognostic nutritional index, and Controlling Nutritional Status jointly. Moderate-severe malnutrition evaluated by the Geriatric Nutritional Risk Index was significantly associated with poor functional outcome (odds ratio = 4.074; P = 0.003). Patients in the good functional outcome group (modified Rankin scale scores = 0 to 2) had a higher proportion of intravenous thrombolysis treatment (32.79% versus 21.25%; P = 0.043). Furthermore, subgroup analyses found no significant interactions between malnourished levels and intravenous thrombolysis treatment (P interaction > 0.05). CONCLUSION: The Geriatric Nutritional Risk Index, over ≤24 h, compared with the prognostic nutritional index and Controlling Nutritional Status, provided timely signals to improve acute ischemic stroke patients' nutritional status. Also, nutritional status might not lead todifferent 6-mo outcomes, whether or not patients received intravenous thrombolysis treatment.

ProRefiner: an entropy-based refining strategy for inverse protein folding with global graph attention.

Inverse Protein Folding (IPF) is an important task of protein design, which aims to design sequences compatible with a given backbone structure. Despite the prosperous development of algorithms for this task, existing methods tend to rely on noisy predicted residues located in the local neighborhood when generating sequences. To address this limitation, we propose an entropy-based residue selection method to remove noise in the input residue context. Additionally, we introduce ProRefiner, a memory-efficient global graph attention model to fully utilize the denoised context. Our proposed method achieves state-of-the-art performance on multiple sequence design benchmarks in different design settings. Furthermore, we demonstrate the applicability of ProRefiner in redesigning Transposon-associated transposase B, where six out of the 20 variants we propose exhibit improved gene editing activity.

Research progress of ferroptosis in Parkinson's disease: a bibliometric and visual analysis.

Background: In recent years, the role of ferroptosis in Parkinson's disease (PD) has become a research hotspot based on evidence of abnormal iron deposition and lipid peroxidation damage in the brains of PD patients. This study aims to examine the relevant research on ferroptosis and PD from a bibliometric perspective. Methods: Original research and review articles related to ferroptosis and PD were retrieved from the Web of Science Core Collection (WOSCC) database. Statistical analysis and visualization of information including countries, institutions, authors, journals, and keywords of the included studies were conducted using the R software package "bibliometrix." Results: A total of 414 articles met the inclusion criteria, averaging 37.86 citations per article. From 2012 to 2022, the average annual growth rate of research in this area was 63.44%. The corresponding authors of published articles were mainly affiliated with institutions in China, the United States, and Australia. Shanghai Jiao Tong University in China and the University of Melbourne in Australia emerged as the most active and influential institutions. The journal with the highest H-index and publication output was Free Radical Biology and Medicine. "Ferroptosis," "immunotherapy," "prognosis" and "microenvironment" were identified as high-frequency keywords, indicating current and future research directions in this field. Conclusion: This bibliometric study provides insights into current research hotspots and emerging trends in the growing field of ferroptosis research related to PD. The high-frequency keywords identified highlight active areas of investigation involving methods, mechanisms, and populations of interest.

Is There an Association Between Parkinson's Disease and Periodontitis? A Systematic Review and Meta-Analysis.

BACKGROUND: Multiple observational studies have yielded controversial results regarding the association between Parkinson's disease (PD) and periodontitis. OBJECTIVE: This systematic review and meta-analysis was conducted to ascertain their bidirectional relationship. METHODS: A literature search for relevant studies was performed in PubMed, EMBASE, the Cochrane Library, and Web of Science databases from inception to December 19, 2022. Effect sizes (ES) with 95% confidence intervals were pooled under the random-effects model. Then, leave-one-out sensitivity analysis and contour-enhanced funnel plot were applied to assess the stability of the results. RESULTS: A total of 34 studies and 24 studies were included for systematic review and quantitative meta-analysis, respectively. Pooled ES indicated that periodontitis was not significantly associated with PD risk (HR = 1.13, 95% CI 0.88-1.45, n = 3; OR = 1.94, 95% CI 0.55-6.90, n = 7), while the Mendelian randomization study revealed no association between PD and periodontitis risk (coefficient [B] = -0.0001, standard error = 0.0001, p = 0.19). Furthermore, PD patients exhibited higher levels of periodontal pocket depth (SMD = 1.10, 95% CI 0.53-1.67), clinical attachment level (SMD = 1.40, 95% CI 0.55-2.26), plaque index (SMD = 0.81, 95% CI 0.22-1.39), and Oral Health Impact Profile-14 score (SMD = 0.91, 95% CI 0.33-1.49) compared to healthy controls. CONCLUSIONS: Our meta-analysis identified no bidirectional association between PD risk and periodontitis risk, though the prevalence of periodontitis and poorer oral status was higher in PD patients.

Long-course chemoradiation plus concurrent/sequential PD-1 blockade as neoadjuvant treatment for MMR-status-unscreened locally advanced rectal cancer: protocol of a multicentre, phase 2, randomised controlled trial (the POLAR-STAR trial).

INTRODUCTION: Recent preclinical studies have discovered unique synergism between radiotherapy and immune checkpoint inhibitors, which has already brought significant survival benefit in lung cancer. In locally advanced rectal cancer (LARC), neoadjuvant radiotherapy plus immune checkpoint inhibitors have also achieved surprisingly high pathological complete response (pCR) rates even in proficient mismatch-repair patients. As existing researches are all phase 2, single-cohort trials, we aim to conduct a randomised, controlled trial to further clarify the efficacy and safety of this novel combination therapy. METHODS AND ANALYSIS: Eligible patients with LARC are randomised to three arms (two experiment arms, one control arm). Patients in all arms receive long-course radiotherapy plus concurrent capecitabine as neoadjuvant therapy, as well as radical surgery. Distinguishingly, patients in arm 1 also receive anti-PD-1 (Programmed Death 1) treatment starting at Day 8 of radiation (concurrent plan), and patients in arm 2 receive anti-PD-1 treatment starting 2 weeks after completion of radiation (sequential plan). Tislelizumab (anti-PD-1) is scheduled to be administered at 200 mg each time for three consecutive times, with 3-week intervals. Randomisation is stratified by different participating centres, with a block size of 6. The primary endpoint is pCR rate, and secondary endpoints include neoadjuvant-treatment-related adverse event rate, as well as disease-free and overall survival rates at 2, 3 and 5 years postoperation. Data will be analysed with an intention-to-treat approach. ETHICS AND DISSEMINATION: This protocol has been approved by the institutional ethical committee of Beijing Friendship Hospital (the primary centre) with an identifying serial number of 2022-P2-050-01. Before publication to peer-reviewed journals, data of this research will be stored in a specially developed clinical trial database. TRIAL REGISTRATION NUMBER: NCT05245474.

Neurofilament light chain as a mediator between LRRK2 mutation and dementia in Parkinson's disease.

Elevated neurofilament light chain (NfL) levels have been associated with dementia in idiopathic Parkinson's disease (iPD). To examine the baseline and longitudinal changes in NfL levels in GBA-PD, SNCA-PD, and LRRK2-PD and further investigate the association between these genetic mutations, NfL, and dementia in PD. We analyzed data from the Parkinson's Progression Markers Initiative (PPMI), including 184 healthy controls (HC) and 617 PD categorized as iPD (n = 381), LRRK2-PD (n = 142), GBA-PD (n = 76) and SNCA-PD (n = 18). Analysis of covariance (ANCOVA) or linear mixed-effect models were used to compare the baseline or dynamic NfL levels between groups. We then explored the relationship between genetic mutations, serum NfL levels, and conversion to dementia using mediation analysis. After adjusting for confounding factors, SNCA-PD exhibited higher baseline serum NfL levels than iPD. Regarding longitudinal changes, SNCA-PD showed the highest increase rate in estimated NfL levels (2.43 pg/mL per year), while LRRK2-PD experienced the slowest increase rate (0.52 pg/mL per year). Mediation analysis indicated that higher estimated NfL level changes were associated with faster cognitive decline (ß = 0.591, p = 0.026). Specifically, the relationship between LRRK2 and dementia was mediated by the estimated NfL level change (ß = -0.717, p < 0.05). Longitudinal changes in serum NfL levels may serve as a biomarker for cognitive decline in Parkinson's disease. Moreover, compared to iPD, the slower progression of dementia in LRRK2-PD may be partially attributed to a slower increase in NfL levels.