Updating the Species Diversity of Pestalotioid Fungi: Four New Species of Neopestalotiopsis and Pestalotiopsis.

Pestalotioid fungi are associated with a wide variety of plants around the world as pathogens, endophytes, and saprobes. In this study, diseased leaves and branches of plants were collected from Guizhou and Sichuan in China. Here, the fungal isolates were identified based on a phylogenetic analysis of the internal transcribed spacer region (ITS), the translation elongation factor 1-alpha (tef1-α) and the beta-tubulin (tub2) of ribosomal DNA, and the morphological characteristics. Ten Neopestalotiopsis isolates and two Pestalotiopsis isolates were obtained, and these isolates were further confirmed as four novel species (N. acericola, N. cercidicola, N. phoenicis, and P. guiyangensis) and one known species, N. concentrica.

Wearable sensor-based quantitative gait analysis in Parkinson's disease patients with different motor subtypes.

Gait impairments are among the most common and disabling symptoms of Parkinson's disease and worsen as the disease progresses. Early detection and diagnosis of subtype-specific gait deficits, as well as progression monitoring, can help to implement effective and preventive personalized treatment for PD patients. Yet, the gait features have not been fully studied in PD and its motor subtypes. To characterize comprehensive and objective gait alterations and to identify the potential gait biomarkers for early diagnosis, subtype differentiation, and disease severity monitoring. We analyzed gait parameters related to upper/lower limbs, trunk and lumbar, and postural transitions from 24 tremor-dominant (TD) and 20 postural instability gait difficulty (PIGD) dominant PD patients who were in early stage and 39 matched healthy controls (HC) during the Timed Up and Go test using wearable sensors. Results show: (1) Both TD and PIGD groups showed restricted backswing range in bilateral lower extremities and more affected side (MAS) arm, reduced trunk and lumbar rotation range in the coronal plane, and low turning efficiency. The receiver operating characteristic (ROC) analysis revealed these objective gait features had high discriminative value in distinguishing both PD subtypes from the HC with the area under the curve (AUC) values of 0.7~0.9 (p < 0.01). (2) Subtle but measurable gait differences existed between TD and PIGD patients before the onset of clinically apparent gait impairment. (3) Specific gait parameters were significantly associated with disease severity in TD and PIGD subtypes. Objective gait biomarkers based on wearable sensors may facilitate timely and personalized gait treatments in PD subtypes through early diagnosis, subtype differentiation, and disease severity monitoring.

Case Report: A case of third-degree atrioventricular block associated with primary cardiac lymphoma.

Background: Primary cardiac lymphoma is an extremely rare malignant lymphoma, with clinical manifestations related to its location. We reported the diagnosis and treatment of primary cardiac lymphoma in a patient presented with atrioventricular block. Case presentation: A 64 year-old man was admitted to our hospital because of symptoms of a tired heart and shortness of breath. The initial electrocardiogram revealed a third-degree atrioventricular block. Computed tomography scan showed an irregularly shaped right heart, irregular clusters, and relatively weakly enhanced areas in the right auricle, atrium, and ventricle. The local boundary between the lesion, pericardium, and left atrium was unclear, and the ventricular septum was irregular and thickened. Multiple irregular gray neoplasms with less smooth surfaces were observed, with a maximum diameter of approximately 7 cm. Pathological findings confirmed a non-germinal center B cell subtype of diffuse large B-cell lymphoma. After surgical resection of the tumor and implantation of a permanent pacemaker, the symptoms of the patient were significantly improved, allowing subsequent chemotherapy. Conclusion: Surgical resection and placement of a permanent pacemaker were effective treatments for a patient with primary cardiac lymphoma presented with atrioventricular block.

Vulvar Hidradenoma Papilliferum.

Aim: This study examines the clinical and pathological characteristics, immune profile, histological occurrence, diagnosis, and differential diagnosis of vulvar hidradenoma papilliferum. Methods: An analysis was conducted on clinical data, histological patterns, and immunohistochemical findings from 45 cases of vulvar hidradenoma papilliferum, and relevant published articles were reviewed. Simultaneously, high-risk HPV typing was performed on these 45 cases. Results: The 45 cases of vulvar hidradenoma papilliferum displayed tumor sizes ranging from 0.3 to 2.0 cm and were observed to be pink or red in appearance. Vacuolated cytoplasm, large abnormal nuclei, distinct nucleoli, and scattered eosinophilic luminal secretions were observed in the glands. Positive staining for CK7 and progesterone receptor (PR) with focal mammaglobin and GCDFP-15 expression was found through immunohistochemistry. CK20 staining was noted as negative. Conclusion: Hidradenoma papilliferum is a rare benign tumor that originates in secretory glands. The diagnosis of this condition is aided by gross and immunohistochemical results, and differentiation from other conditions is necessary.

FedTKD: A Trustworthy Heterogeneous Federated Learning Based on Adaptive Knowledge Distillation.

Federated learning allows multiple parties to train models while jointly protecting user privacy. However, traditional federated learning requires each client to have the same model structure to fuse the global model. In real-world scenarios, each client may need to develop personalized models based on its environment, making it difficult to perform federated learning in a heterogeneous model environment. Some knowledge distillation methods address the problem of heterogeneous model fusion to some extent. However, these methods assume that each client is trustworthy. Some clients may produce malicious or low-quality knowledge, making it difficult to aggregate trustworthy knowledge in a heterogeneous environment. To address these challenges, we propose a trustworthy heterogeneous federated learning framework (FedTKD) to achieve client identification and trustworthy knowledge fusion. Firstly, we propose a malicious client identification method based on client logit features, which can exclude malicious information in fusing global logit. Then, we propose a selectivity knowledge fusion method to achieve high-quality global logit computation. Additionally, we propose an adaptive knowledge distillation method to improve the accuracy of knowledge transfer from the server side to the client side. Finally, we design different attack and data distribution scenarios to validate our method. The experiment shows that our method outperforms the baseline methods, showing stable performance in all attack scenarios and achieving an accuracy improvement of 2% to 3% in different data distributions.

Relationships Between Rapid Eye Movement Sleep Behavior Disorder and Parkinson's Disease: Indication from Gut Microbiota Alterations.

Rapid eye movement sleep behavior disorder (RBD) has a close relationship with Parkinson's disease (PD) and was even regarded as the most reliable hallmark of prodromal PD. RBD might have similar changes in gut dysbiosis to PD, but the relationship between RBD and PD in gut microbial alterations is rarely studied. In this study, we aim to investigate whether there were consistent changes between RBD and PD in gut microbiota, and found some specific biomarkers in RBD that might indicate phenoconversion to PD. Alpha-diversity showed no remarkable difference and beta-diversity showed significant differences based on the unweighted (R = 0.035, P = 0.037) and weighted (R = 0.0045, P = 0.008) UniFrac analysis among idiopathic RBD (iRBD), PD with RBD, PD without RBD and normal controls (NC). Enterotype distribution indicated iRBD, PD with RBD and PD without RBD were Ruminococcus-dominant while NC were Bacteroides-dominant. 7 genera (4 increased: Aerococcus, Eubacterium, Gordonibacter and Stenotrophomonas, 3 decreased: Butyricicoccus, Faecalibacterium and Haemophilus) were consistently changed in iRBD and PD with RBD. Among them, 4 genera (Aerococcus, Eubacterium, Butyricicoccus, Faecalibacterium) remained distinctive in the comparison between PD with RBD and PD without RBD. Through clinical correlation analysis, Butyricicoccus and Faecalibacterium were found negatively correlated with the severity of RBD (RBD-HK). Functional analysis showed iRBD had similarly increased staurosporine biosynthesis to PD with RBD. Our study indicates that RBD had similar gut microbial changes to PD. Decreased Butyricicoccus and Faecalibacterium might be potential hallmarks of phenoconversion of RBD to PD.

The impact of global warming on the signature virulence gene, thermolabile hemolysin, of Vibrio parahaemolyticus.

IMPORTANCE: In this study, Vibrio parahaemolyticus strains were collected from a large number of aquatic products globally and found that temperature has an impact on the virulence of these bacteria. As global temperatures rise, mutations in a gene marker called thermolabile hemolysin (tlh) also increase. This suggests that environmental isolates adapt to the warming environment and become more pathogenic. The findings can help in developing tools to analyze and monitor these bacteria as well as assess any link between climate change and vibrio-associated diseases, which could be used for forecasting outbreaks associated with them.

Differentiating malignant and benign pleural effusion in patients with lung cancer: an 18F-FDG PET/CT retrospectively study.

Rationale: To explore the clinical role of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in differentiating malignant pleural effusion (MPE) from benign pleural effusion (BPE) in patients with lung cancer. Methods: Over a 8-year period, we retrospectively reviewed PET/CT data of lung cancer patients with pleural effusion, with 237 participants enrolled for analysis. The nature of pleural effusion was confirmed using pleural cytology or biopsy. MPE versus BPE comparison and multiple regression analysis were performed. Receiver operating characteristic (ROC) curve analysis was used for evaluating the diagnostic performance. Results: Of the 237 participants, 170 had MPEs and 67 had BPEs. Compared with BPEs, MPEs had higher pleural SUVmax and thicker pleura and were more common among non-small cell lung cancers, peripheral tumors, and women (p < 0.05). BPEs had larger and higher 18F-FDG uptake thoracic lymph nodes and more complications of pneumonia (p < 0.05) than MPEs. Multiple regression analysis was used to identify the pleural SUVmax (odds ratio, OR = 38.8), sex (OR = 0.033), and mediastinal lymphoid node size (OR = 0.86) as independent risk factors for MPEs. The sensitivity, specificity, and area under the ROC curve (AUC) in the combined ROC curve analysis by using the three factors were 95.3%, 95.5%, and 0.989, respectively. Conclusion: 18F-FDG PET/CT integrated imaging is an effective non-invasive method for differential diagnosis of MPE in patients with lung cancer. Pleural SUVmax combined with thoracic lymph nodes and sex has high diagnostic value.

Coevolution of furA-Regulated Hyper-Inflammation and Mycobacterial Resistance to Oxidative Killing through Adaptation to Hydrogen Peroxide.

Mycobacterium tuberculosis (Mtb) is highly resistant to host oxidative killing. We hypothesized that the evolutionary adaptation of M. smegmatis to hydrogen peroxide (H2O2) would endow the nonpathogenic Mycobacterium persistent in a host. In the study, we screened a highly H2O2-resistant strain (mc2114) via evolutionary H2O2 adaptation in vitro. The MIC of mc2114 to H2O2 is 320 times that of wild-type mc2155. Mouse infection experiments showed that mc2114, similar to Mtb, was persistent in the lungs and caused high lethality in mice with restricted responses of NOX2, ROS, IFN-γ, decreased macrophage apoptosis, and overexpressed inflammatory cytokines in the lungs. Whole-genome sequencing analysis revealed that mc2114 harbored 29 single nucleotide polymorphisms in multiple genes; one of them was on the furA gene that caused FurA deficiency-mediated overexpression of KatG, a catalase-peroxidase to detoxify ROS. Complementation of mc2114 with a wild-type furA gene reversed lethality and hyper-inflammatory response in mice with rescued overexpression of KatG and inflammatory cytokines, whereas NOX2, ROS, IFN-γ, and macrophage apoptosis remained reduced. The results indicate that although FurA regulates KatG expression, it does not contribute significantly to the restriction of ROS response. Instead, FurA deficiency is responsible for the detrimental pulmonary inflammation that contributes to the severity of the infection, a previously nonrecognized function of FurA in mycobacterial pathogenesis. The study also indicates that mycobacterial resistance to oxidative burst results from complex mechanisms involving adaptive genetic changes in multiple genes. IMPORTANCE Mycobacterium tuberculosis (Mtb) causes human tuberculosis (TB), which has killed more people in human history than any other microorganism. However, the mechanisms underlying Mtb pathogenesis and related genes have not yet been fully elucidated, which impedes the development of effective strategies for containing and eradicating TB. In the study, we generated a mutant of M. smegmatis (mc2114) with multiple mutations by an adaptive evolutionary screen with H2O2. One of the mutations in furA caused a deficiency of FurA, which mediated severe inflammatory lung injury and higher lethality in mice by overexpression of inflammatory cytokines. Our results indicate that FurA-regulated pulmonary inflammation plays a critical role in mycobacterial pathogenesis in addition to the known downregulation of NOX2, ROS, IFN-γ responses, and macrophage apoptosis. Further analysis of the mutations in mc2114 would identify more genes related to the increased pathogenicity and help in devising new strategies for containing and eradicating TB.

DFML: Dynamic Federated Meta-Learning for Rare Disease Prediction.

Millions of patients suffer from rare diseases around the world. However, the samples of rare diseases are much smaller than those of common diseases. Hospitals are usually reluctant to share patient information for data fusion due to the sensitivity of medical data. These challenges make it difficult for traditional AI models to extract rare disease features for disease prediction. In this paper, we propose a Dynamic Federated Meta-Learning (DFML) approach to improve rare disease prediction. We design an Inaccuracy-Focused Meta-Learning (IFML) approach that dynamically adjusts the attention to different tasks according to the accuracy of base learners. Additionally, a dynamic weight-based fusion strategy is proposed to further improve federated learning, which dynamically selects clients based on the accuracy of each local model. Experiments on two public datasets show that our approach outperforms the original federated meta-learning algorithm in accuracy and speed with as few as five shots. The average prediction accuracy of the proposed model is improved by 13.28% compared with each hospital's local model.

A Novel Deep Learning Model for Medical Report Generation by Inter-Intra Information Calibration.

Automatic generation of medical reports can provide diagnostic assistance to doctors and reduce their workload. To improve the quality of the generated medical reports, injecting auxiliary information through knowledge graphs or templates into the model is widely adopted in previous methods. However, they suffer from two problems: 1) The injected external information is limited in amount and difficult to adequately meet the information needs of medical report generation in content. 2) The injected external information increases the complexity of model and is hard to be reasonably integrated into the generation process of medical reports. Therefore, we propose an Information Calibrated Transformer (ICT) to address the above issues. First, we design a Precursor-information Enhancement Module (PEM), which can effectively extract numerous inter-intra report features from the datasets as the auxiliary information without external injection. And the auxiliary information can be dynamically updated with the training process. Secondly, a combination mode, which consists of PEM and our proposed Information Calibration Attention Module (ICA), is designed and embedded into ICT. In this method, the auxiliary information extracted from PEM is flexibly injected into ICT and the increment of model parameters is small. The comprehensive evaluations validate that the ICT is not only superior to previous methods in the X-Ray datasets, IU-X-Ray and MIMIC-CXR, but also successfully be extended to a CT COVID-19 dataset COV-CTR.

Gefitinib improves severe bronchorrhea and prolongs the survival of a patient with lung invasive mucinous adenocarcinoma: A case report.

BACKGROUND: Lung invasive mucinous adenocarcinoma (LIMA), formerly referred to as mucinous bronchioloalveolar carcinoma, is a rare disease that usually presents as bilateral lung infiltration, is unsuitable for surgery and radiotherapy, and shows poor response to conventional chemotherapy. CASE SUMMARY: We report a 56-year-old Chinese man with a history of smoking and epidermal growth factor receptor mutation-positivity who was initially misdiagnosed as severe pneumonia, but was ultimately diagnosed as a case of invasive mucinous adenocarcinoma of the lung by computed tomography -guided percutaneous lung biopsy. Bronchorrhea and dyspnea were improved within 24 h after initiation of gefitinib therapy and the radiographic signs of bilateral lung consolidation showed visible improvement within 30 d. After more than 11 months of treatment, there is no evidence of recurrence or severe adverse events. CONCLUSION: Although the precise mechanism of the antitumor effects of gefitinib are not clear, our experience indicates an important role of the drug in LIMA and provides a reference for the diagnosis and treatment of this disease.

Specific gut microbiota alterations in essential tremor and its difference from Parkinson's disease.

Essential tremor (ET) is the most common movement disorder and share overlapping symptoms with Parkinson's disease (PD), making differential diagnosis challenging. Gut dysbiosis is regarded crucial in the pathogenesis of PD. Since ET patients also has comorbidity in gastrointestinal disorders, the relationship between gut microbiota and ET really worth investigating and may help distinguishing ET from PD. Fecal samples from 54 ET, 67 de novo PD and 54 normal controls (NC) were collected for 16S ribosomal RNA gene sequencing and quantitative real-time PCR. ET showed lower species richness (Chao1 index) than NC and PD. ET was with Bacteroides-dominant enterotype, while PD was with Ruminococcus-dominant enterotype. Compared with NC, 7 genera were significantly reduced in ET, 4 of which (Ruminococcus, Romboutsia, Mucispirillum, and Aeromonas) were identified to be distinctive with an area under the curve (AUC) of 0.705. Compared to PD, 26 genera were found significantly different from ET, 4 of which (Bacteroides, Fusobacterium, Phascolarctobacterium, and Lachnospira) were found distinguishable with an AUC of 0.756. Clinical association results indicated that Proteus was associated with disease severity (TETRAS) of ET, while Klebsiella was linked to depression and anxiety in ET. Functional predictions revealed that 4 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were altered in ET. This study reveals gut dysbiosis in ET and it provides new insight into the pathogenesis of ET and helps distinguishing ET from PD.

Clinicopathologic features of pregnancy luteoma.

OBJECTIVE: This study aimed to explore the clinicopathological characteristics, immunophenotype, histological occurrence, diagnosis, and differential diagnosis of ovarian luteoma tumor of pregnancy. METHODS: The clinical features, histomorphology, immunohistochemistry, and reticular fiber staining results of 18 cases of luteoma tumors of pregnancy were analyzed, and related published studies were reviewed. RESULTS: The 18 cases of luteoma tumors were all women who had undergone multiple pregnancies. The tumors were 1.3-15 cm in size and brownish yellow or reddish brown in color, with a soft texture. Microscopic examination revealed the eosinophilic cytoplasm of tumor cells and diffuse hyperplasia. The results of the immunohistochemical analysis were as follows: α-inhibin, AE1/AE3, CD99, and vimentin were positive, while epithelial membrane antigen, S-100, HMB45, and MelanA were negative. One case was positive for MelanA. The staining results of reticular fibers showed that the argyrophilic reticular fibers were black surrounding the tumor cell nests. CONCLUSIONS: Luteoma tumor of pregnancy is a rare tumor-like lesion mostly appearing in late pregnancy. The gross, immunohistochemical staining, and reticular fiber staining results may help diagnose this disease. The disease needs to be differentiated from other diseases.