UNASSIGNED: Developing guidelines for the diagnosis and treatment of common cancers in China based on the evidence-based practice, the availability of diagnosis and treatment products, and the up-to-date advances in precision medicine is one of the basic tasks of the Chinese Society of Clinical Oncology Breast Cancer (CSCO BC) Committee.
UNASSIGNED: Protocols with high evidence level and good availability are used as the Level I recommendations; protocols with relatively high evidence level but slightly lower expert consensus or with poor availability are used as the Level II recommendations; and protocols that are clinically applicable but with low evidence level are regarded as the Level III recommendations. Based on the findings of clinical research at home and abroad and the opinions of CSCO BC experts, the CSCO BC guidelines determine the levels of recommendations for clinical application.
UNASSIGNED: For human epidermal growth factor receptor 2 (HER2)-positive breast cancer, a combination of trastuzumab and pertuzumab regimen were recommended as Level I recommendation for neoadjuvant and first line metastatic breast cancer. Pyrotinib is also recommended as Level I recommendation in first line and second line therapy according to the latest studies conducted in China. Antibody drug conjugates was also recommended for patients with trastuzumab progression. For triple negative breast cancer, immunotherapy in early and metastatic breast cancer was highlighted and listed as new chapters in this version of guideline. For hormone receptor (HR)-positive breast cancer, cyclin dependent kinase 4/6 (CDK4/6) was recommended in different stages, especially in adjuvant therapy. There was also a new chapter for HER2-low breast cancer stratified by HR status.
UNASSIGNED: We firmly believe that evidence-based, availability-concerned, and consensus-based guidelines will be more feasible for clinical practice in China and in other countries with similar situations.

BACKGROUND: Sentinel lymph node biopsy (SLNB) has replaced axillary lymph node dissection (ALND) for assessing axillary lymph node status in clinically node-negative breast cancer patients. However, the approach to axillary surgery after neoadjuvant treatment is still controversial. In the present study, our objective was to predict the pathological nodal stage based on SLNB results and the clinicopathological characteristics of patients who initially presented with clinical N1 positivity but whose disease status was converted to clinical N0 after neoadjuvant chemotherapy (NAC).
METHODS: After NAC, 150 clinically node-negative patients were included. The relationships between clinicopathologic parameters and the number of positive lymph nodes in SLNBs and ALNDs were assessed through binary/multivariate logistic regression analysis.
RESULTS: Among 150 patients, 78 patients had negative SLNBs, and 72 patients had positive SLNBs. According to the ALND data of 21 patients with SLNB1+, there was no additional node involvement (80.8%), 1-2 lymph nodes were positive in 5 patients (19.2%), and no patient had ≥ 3 lymph nodes involved. Following the detection of SLNB1 + positivity, the rate of negative non-sentinel nodes were 75% in the luminal A/B subgroup, 100% in the HER-2-positive subgroup, and 100% in the triple-negative subgroup. Patients with a lower T stage (T1-3 vs. T4), fewer than 4 clinical nodes before NAC (< 4 vs. ≥4), and a decreased postoperative Ki-67 index (< 10% vs. stable/increase) were included. According to both univariate and multivariate analyses, being in the triple-negative or HER2-positive subgroup, compared to the luminal A/B subgroup (luminal A/B vs. HER2-positive/triple-negative), was found to be predictive of complete lymph node response.
CONCLUSIONS: The number of SLNB-positive nodes, tumor-related parameters, and response to treatment may predict no additional nodes to be positive at ALND.

BACKGROUND: It is crucial to investigate the distinct proteins that contribute to the advancement of lung cancer.
METHODS: We analyzed the expression levels of 92 immuno-oncology-related proteins in 96 pairs of lung adenocarcinoma tissue samples using Olink proteomics. The differentially expressed proteins (DEPs) were successively screened in tumor and paraneoplastic groups, early and intermediate-late groups by a nonparametric rank sum test, and the distribution and expression levels of DEPs were determined by volcano and heat maps, etc., and the area under the curve was calculated.
RESULTS: A total of 24 DEPs were identified in comparisons between tumor and paracancerous tissues. Among them, interleukin-8 (IL8) and chemokine (C-C motif) ligand 20 (CCL20) as potential markers for distinguishing tumor tissues. Through further screening, it was found that interleukin-6 (IL6) and vascular endothelial growth factor A (VEGFA) may be able to lead to tumor progression through the JaK-STAT signaling pathway, Toll-like receptor signaling pathway and PI3K/AKT signaling pathway. Interestingly, our study revealed a down-regulation of IL6 and VEGFA in tumor tissues compared to paracancerous tissues.
CONCLUSIONS: IL8 + CCL20 (AUC: 0.7056) have the potential to differentiate tumor tissue from paracancerous tissue; IL6 + VEGFA (AUC: 0.7531) are important protein markers potentially responsible for tumor progression.

Mantle cell lymphoma (MCL) is a rare, incurable, and aggressive B-cell non-Hodgkin lymphoma (NHL). Early MCL diagnosis and treatment is critical and puzzling due to inter/intra-tumoral heterogeneity and limited understanding of the underlying molecular mechanisms. We developed and applied a multifaceted analysis of selected publicly available transcriptomic data of well-defined MCL stages, integrating network-based methods for pathway enrichment analysis, co-expression module alignment, drug repurposing, and prediction of effective drug combinations. We demonstrate the \"butterfly effect\" emerging from a small set of initially differentially expressed genes, rapidly expanding into numerous deregulated cellular processes, signaling pathways, and core machineries as MCL becomes aggressive. We explore pathogenicity-related signaling circuits by detecting common co-expression modules in MCL stages, pointing out, among others, the role of VEGFA and SPARC proteins in MCL progression and recommend further study of precise drug combinations. Our findings highlight the benefit that can be leveraged by such an approach for better understanding pathobiology and identifying high-priority novel diagnostic and prognostic biomarkers, drug targets, and efficacious combination therapies against MCL that should be further validated for their clinical impact.

BACKGROUND: Gliomas are the most frequent, heterogeneous group of tumors arising from glial cells, characterized by difficult monitoring, poor prognosis, and fatality. Tissue biopsy is an established procedure for tumor cell sampling that aids diagnosis, tumor grading, and prediction of prognosis.
METHODS: We studied and compared the levels of liquid biopsy markers in patients with different grades of glioma. Also, we tried to prove the potential association between glioma and specific blood group antigens.
RESULTS: 78 patients were found, among whom the maximum percentage with glioblastoma had blood group O+ (53.8%). The second highest frequency had blood group A+ (20.4%), followed by B+ (9.0%) and A- (5.1%), and the least with O-. Liquid biopsy biomarkers included Alanine Aminotransferase (ALT), Lactate Dehydrogenase (LDH), lymphocytes, Urea, Alkaline phosphatase (AST), Neutrophils, and C-Reactive Protein (CRP). The levels of all the components increased significantly with the severity of the glioma, with maximum levels seen in glioblastoma (grade IV), followed by grade III and grade II, respectively.
CONCLUSIONS: Gliomas have significant clinical challenges due to their progression with heterogeneous nature and aggressive behavior. A liquid biopsy is a non-invasive approach that aids in setting up the status of the patient and figuring out the tumor grade; therefore, it may show diagnostic and prognostic utility. Additionally, our study provides evidence to prove the role of ABO blood group antigens in the development of glioma. However, future clinical research on liquid biopsy will improve the sensitivity and specificity of these tests and confirm their clinical usefulness to guide treatment approaches.

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BACKGROUND: COVID-19 started to spread early in 2020, the precise year that lung cancer (LC) patients were recruited into the prospective epidemiological cohort KBP-2020-CPHG in French hospitals. This provides a unique opportunity to study COVID-19 incidence, survival risk factors, and overall prognosis.
METHODS: COVID data was collected before vaccination was made available. Clinical characteristics were compared (COVID vs non-COVID), incidence rate ratios were calculated based on clinical characteristics, survival (1 and 3 months) was estimated and the impact of COVID-19 on the overall prognosis of the cohort was studied.
RESULTS: In 2020, 285 out of 8,999 lung cancer patients were diagnosed with COVID-19. Diagnosis was mainly based on PCR tests (86.3 %). The annual incidence was 8.3 % (95 % CI [7.4, 9.3]); it was higher in former smokers and patients with squamous cell carcinoma or small cell carcinoma than in those with adenocarcinoma, in those with a PS score ≥2 versus 0-1, and with stages III-IV versus stages I-II. The incidence was reduced in patients who received chemotherapy or immunotherapy. 64.9 % of patients were hospitalized due to COVID-19. Risk factors for death at 1 and 3 months in COVID-19 patients were age, LC stage, and PS score. Multivariate analysis showed a major prognostic impact of COVID-19 on mortality of LC patients (hazard ratio: 4.12, 95 % CI [3.42, 4.97], p < 0.001).
CONCLUSIONS: This prospective study demonstrated the high incidence of COVID-19 in LC patients and identified as risk factors for COVID-19: smoking status, histology, PS, and stage. The impact of COVID-19 on lung cancer mortality appears major.

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Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep stage classification is polysomnography (PSG). Unfortunately, PSG is an expensive and cumbersome process involving numerous electrodes, often conducted in an unfamiliar clinic and annotated by a professional. Although commercial devices like smartwatches track sleep, their performance is well below PSG. To address these disadvantages, we present a feed-forward neural network that achieves gold-standard levels of agreement using only a single lead of electrocardiography (ECG) data. Specifically, the median five-stage Cohen\'s kappa is 0.725 on a large, diverse dataset of 5 to 90-year-old subjects. Comparisons with a comprehensive meta-analysis of between-human inter-rater agreement confirm the non-inferior performance of our model. Finally, we developed a novel loss function to align the training objective with Cohen\'s kappa. Our method offers an inexpensive, automated, and convenient alternative for sleep stage classification-further enhanced by a real-time scoring option. Cardiosomnography, or a sleep study conducted with ECG only, could take expert-level sleep studies outside the confines of clinics and laboratories and into realistic settings. This advancement democratizes access to high-quality sleep studies, considerably enhancing the field of sleep medicine and neuroscience. It makes less-expensive, higher-quality studies accessible to a broader community, enabling improved sleep research and more personalized, accessible sleep-related healthcare interventions.

Motor learning is a prominent and extensively studied subject in rehabilitation following various types of neurological disorders. Motor repair and rehabilitation often extend over months and years post-injury with a slow pace of recovery, particularly affecting the fine movements of the distal extremities. This extended period can diminish the motivation and persistence of patients, a facet that has historically been overlooked in motor learning until recent years. Reward, including monetary compensation, social praise, video gaming, music, and virtual reality, is currently garnering heightened attention for its potential to enhance motor motivation and improve function. Numerous studies have examined the effects and attempted to explore potential mechanisms in various motor paradigms, yet they have yielded inconsistent or even contradictory results and conclusions. A comprehensive review is necessary to summarize studies on the effects of rewards on motor learning and to deduce a central pattern from these existing studies. Therefore, in this review, we initially outline a framework of motor learning considering two major types, two major components, and three stages. Subsequently, we summarize the effects of rewards on different stages of motor learning within the mentioned framework and analyze the underlying mechanisms at the level of behavior or neural circuit. Reward accelerates learning speed and enhances the extent of learning during the acquisition and consolidation stages, possibly by regulating the balance between the direct and indirect pathways (activating more D1-MSN than D2-MSN) of the ventral striatum and by increasing motor dynamics and kinematics. However, the effect varies depending on several experimental conditions. During the retention stage, there is a consensus that reward enhances both short-term and long-term memory retention in both types of motor learning, attributed to the LTP learning mechanism mediated by the VTA-M1 dopaminergic projection. Reward is a promising enhancer to bolster waning confidence and motivation, thereby increasing the efficiency of motor learning and rehabilitation. Further exploration of the circuit and functional connections between reward and the motor loop may provide a novel target for neural modulation to promote motor behavior.

OBJECTIVE: The aim of this work is to describe the skills considered to have been acquired by students during their professional practice placements, with particular emphasis on skills related to the new roles of pharmacists.
METHODS: Skills are monitored during the professional practice placement using the dashboard included in the guide designed by the college of community pharmacy placement supervisors. Each skill is assessed at three points during the placement. The assessment is carried out jointly by the student and his or her placement supervisor using the dashboard, which is available online in the form of a form on the Moodle platform. We conducted a retrospective analysis of the professional practice placement dashboards for the 2018-2019 to 2022-2023 academic years.
RESULTS: The response levels for the three phases of the dashboard are very high, always exceeding 90% of students completing their placement. All of the scorecards show a progression in the acquisition of skills throughout the placement and enable certain skills to be distinguished in terms of their level of acquisition at the end of the placement. The focus on pharmaceutical interviews shows that the rate of acquisition of this skill is over 85% in 2021 and 2023, the years in which the subject of the public health project was the performance and quality assurance of pharmaceutical interviews in pharmacies, whereas it is no higher than 38% in the other years.
CONCLUSIONS: Our work shows the contribution of the professional practice placement dashboard in monitoring student progress. The analysis carried out reveals different levels of mastery at the start of the placement and different levels of progress depending on the skills. It also reveals the contribution made by the intervention on the content of the placement, particularly in terms of the acquisition of certain skills, especially those related to new tasks such as conducting pharmaceutical interviews.