Epilepsy is a chronic neurological disease caused by abnormal synchronous discharge of the brain, which is characterized by recurrent and transient neurological abnormalities, mainly manifested as loss of consciousness and limb convulsions, and can occur in people of all ages. At present, anti-epileptic drugs (AEDs) are still the main means of treatment, but their efficacy is limited by the problem of drug resistance, and long-term use can cause serious side effects, such as cognitive dysfunction and vital organ damage. Although surgical resection of epileptic lesions has achieved certain results in some patients, the high cost and potential risk of neurological damage limit its scope of application. Therefore, the development of safe, accurate and personalized non-invasive treatment strategies has become one of the key directions of epilepsy research. In recent years, photobiomodulation (PBM) has gained significant attention as a promising non-invasive therapeutic approach. PBM uses light of specific wavelengths to penetrate tissues and interact with photosensitive molecules within cells, thereby modulating cellular metabolic processes. Research has shown that PBM can enhance mitochondrial function, promote ATP production, improve meningeal lymphatic drainage, reduce neuroinflammation, and stimulate the growth of neurons and synapses. These biological effects suggest that PBM not only holds the potential to reduce the frequency of seizures but also to improve the metabolic state and network function of neurons, providing a novel therapeutic avenue for epilepsy treatment. Compared to traditional treatment methods, PBM is non-invasive and avoids the risks associated with surgical interventions. Its low risk of significant side effects makes it particularly suitable for patients with drug-resistant epilepsy, offering new therapeutic options for those who have not responded to conventional treatments. Furthermore, PBM’s multi-target mechanism enables it to address a variety of complex etiologies of epilepsy, demonstrating its potential in precision medicine. In contrast to therapies targeting a single pathological mechanism, PBM’s multifaceted approach makes it highly adaptable to different types of epilepsy, positioning it as a promising supplementary or alternative treatment. Although animal studies and preliminary clinical trials have shown positive outcomes with PBM, its clinical application remains in the exploratory phase. Future research should aim to elucidate the precise mechanisms of PBM, optimize light parameters, such as wavelength, dose, and frequency, and investigate potential synergistic effects with other therapeutic modalities. These efforts will be crucial for enhancing the therapeutic efficacy of PBM and ensuring its safety and consistency in clinical settings. This review summarizes the types of epilepsy, diagnostic biomarkers, the advantages of PBM, and its mechanisms and potential applications in epilepsy treatment. The unique value of PBM lies not only in its multi-target therapeutic effects but also in its adaptability to the diverse etiologies of epilepsy. The combination of PBM with traditional treatments, such as pharmacotherapy and neuroregulatory techniques, holds promise for developing a more comprehensive and multidimensional treatment strategy, ultimately alleviating the treatment burden on patients. PBM has also shown beneficial effects on neural network plasticity in various neurodegenerative diseases. The dynamic remodeling of neural networks plays a critical role in the pathogenesis and treatment of epilepsy, and PBM’s multi-target mechanism may promote brain function recovery by facilitating neural network remodeling. In this context, optimizing optical parameters remains a key area of research. By adjusting parameters such as wavelength, dose, and frequency, researchers aim to further enhance the therapeutic effects of PBM while maintaining its safety and stability. Looking forward, interdisciplinary collaboration, particularly in the fields of neuroscience, optical engineering, and clinical medicine, will drive the development of PBM technology and facilitate its transition from laboratory research to clinical application. With the advancement of portable devices, PBM is expected to provide safer and more effective treatments for epilepsy patients and make a significant contribution to personalized medicine, positioning it as a critical component of precision therapeutic strategies.

To address the challenges faced by current brain midline segmentation techniques, such as insufficient accuracy and poor segmentation continuity, this paper proposes a deep learning network model based on a two-stage framework. On the first stage of the model, prior knowledge of the feature consistency of adjacent brain midline slices under normal and pathological conditions is utilized. Associated midline slices are selected through slice similarity analysis, and a novel feature weighting strategy is adopted to collaboratively fuse the overall change characteristics and spatial information of these associated slices, thereby enhancing the feature representation of the brain midline in the intracranial region. On the second stage, the optimal path search strategy for the brain midline is employed based on the network output probability map, which effectively addresses the problem of discontinuous midline segmentation. The method proposed in this paper achieved satisfactory results on the CQ500 dataset provided by the Center for Advanced Research in Imaging, Neurosciences and Genomics, New Delhi, India. The Dice similarity coefficient (DSC), Hausdorff distance (HD), average symmetric surface distance (ASSD), and normalized surface Dice (NSD) were 67.38 ± 10.49, 24.22 ± 24.84, 1.33 ± 1.83, and 0.82 ± 0.09, respectively. The experimental results demonstrate that the proposed method can fully utilize the prior knowledge of medical images to effectively achieve accurate segmentation of the brain midline, providing valuable assistance for subsequent identification of the brain midline by clinicians.
Humans ; Brain/diagnostic imaging* ; Deep Learning ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Magnetic Resonance Imaging/methods* ; Neural Networks, Computer

OBJECTIVES: To study the clinical and genetic characteristics of osteopetrosis (OPT) in children. METHODS: A retrospective analysis was performed on the clinical data of 14 children with OPT. Whole-exome sequencing was used to detect pathogenic genes, and clinical phenotypes and genotypic features were summarized. RESULTS: Among the 14 children (10 males and 4 females), the median age at diagnosis was 8 months. Clinical manifestations included systemic osteosclerosis (14 cases, 100%), anemia (12 cases, 86%), infections (10 cases, 71%), thrombocytopenia (9 cases, 64%), hepatosplenomegaly (8 cases, 57%), and developmental delay (5 cases, 36%). Malignant osteopetrosis (MOP) cases had lower platelet counts, creatine kinase isoenzyme, and serum calcium levels, but higher white blood cell counts, lactate dehydrogenase, and alkaline phosphatase levels compared to non-MOP cases (P<0.05). Genetic testing identified 15 variants in 12 patients, including 8 variants in the CLCN7 gene (53%), 6 in the TCIRG1 gene (40%), and 1 in the TNFRSF11A gene (7%). Three novel CLCN7 variants were identified: c.2351G>C, c.1215-43C>T, and c.1534G>A. All four patients with TCIRG1 variants exhibited MOP clinical phenotypes. Of the seven patients with CLCN7 variants, 4 presented with intermediate OPT, 2 with benign OPT, and 1 with MOP. CONCLUSIONS Clinical phenotypes of OPT in children are heterogeneous, predominantly involving CLCN7 and TCIRG1 gene variants, with a correlation between clinical phenotypes and genotypes.
Humans ; Osteopetrosis/genetics* ; Male ; Female ; Infant ; Child, Preschool ; Retrospective Studies ; Vacuolar Proton-Translocating ATPases/genetics* ; Child ; Chloride Channels/genetics* ; Mutation ; Receptor Activator of Nuclear Factor-kappa B

OBJECTIVE: To analyze two families with inherited dysfibrinogenemia, and explore the molecular pathogenic mechanisms. METHODS: The coagulation indexes of the probands and their family members were detected. The FGA, FGB, and FGG exons and their flanking sequences were amplified by PCR, and the mutation sites were identified by sequencing. SIFT, PolyPhen2, LRT, ReVe, MutationTaster, phyloP, and phastCons bioinformatics software were used to predict the functional impact of the mutation sites. Protein structure and amino acid conservation analysis of the variant were conducted using PyMOL and Clustal X software. RESULTS: The thrombin time (TT) of the proband in family 1 was prolonged to 37.00 s, and Fg∶C decreased to 0.52 g/L. The TT of the proband in family 2 was 20.30 s, and Fg∶C was 1.00 g/L, which was lower than the normal range. Genetic analysis revealed that the proband in family 1 had a heterozygous mutation c.80T>C in FGA, resulting in the substitution of phenylalanine 27 with serine (Phe27Ser). The proband in family 2 had a heterozygous mutation c.1007T>A in FGG, resulting in the substitution of methionine 336 with lysine (Met336Lys). Bioinformatics software prediction analysis indicated that both mutations were deleterious variants. PyMOL mutation models revealed that the Aα chain mutation (Phe27Ser) in family 1 and γ chain mutation (Met336Lys) in family 2 resulted in alterations in spatial structure and reduced protein stability. Clustal X results showed that both Aα Phe27 and γMet336 were highly conserved across homologous species. CONCLUSION Heterozygous mutations of FGA gene c.80T>C and FGG gene c.1007T>A are both pathogenic variants, causing inherited dysfibrinogenemia.
Female ; Humans ; Male ; Afibrinogenemia/genetics* ; Fibrinogen/genetics* ; Heterozygote ; Mutation ; Pedigree

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

Critical care emphasizes critical thinking, focuses on the triggers that lead to disease progression, and attaches great importance to early diagnosis of diseases and assessment of the compensatory capacity of vital organs. Pregnancy-associated atypical hemolytic uremic syndrome (P-aHUS) is relatively rare in the intensive care unit (ICU). Most cases occur within 10 weeks after delivery. Severe cases can be life-threatening. It characterized by microangiopathic hemolytic anemia, decreased platelet count (PLT), and acute kidney injury (AKI). Early clinical diagnosis is difficult due to its similarity to various disease manifestations. On January 28, 2024, a 26-year-old pregnant woman at 26⁺³ weeks gestation was transferred to the ICU 19 hours post-vaginal delivery due to abdominal pain, reduced urine output, decreased PLT, elevated D-dimer, tachycardia, increased respiratory rate and declined oxygenation. On the day of ICU admission, the critical care physician identified the causes that triggered the acute respiratory and circulatory events based on the "holistic and local" critical care thinking. The condition was stabilized rapidly by improving the capacity overload. In terms of etiological diagnosis, under the guidance of the "point and face" critical care thinking, starting from abnormality indicators including a decrease in hemoglobin (Hb) and PLT and elevated D-dimer and fibrin degradation product (FDP) without other abnormal coagulation indicators, the critical care physician ultimately determined the diagnosis direction of thrombotic microangiopathy (TMA) by delving deeply into the essence of the disease and formulating a laboratory examination plan in a reasonable and orderly manner. In terms of in-depth diagnosis, combining the disease development process, family history, and past history, applying the two-way falsification thinking of "forward and reverse" as well as "questioning and hypothesis", the diagnosis possibilities of preeclampsia, HELLP syndrome [including hemolysis (H), elevated liver function (EL) and low platelet count (LP)], thrombotic thrombocytopenic purpura (TTP), typical hemolytic uremic syndrome (HUS), and autoimmune inflammatory diseases inducing the condition was ruled out. The diagnosis of complement activation-induced P-aHUS was finally established for the patient, according to the positive result of the complement factor H (CFH). Active decision was made in the initial treatment. The plasma exchange was initiated early. "Small goals" were formulated in stages. The "small endpoints" were dynamically controlled in a goal-oriented manner to achieve continuous realization of the overall treatment effect through phased "small goals". On the 5th day of ICU treatment, the trend of microthrombosis in the patient was controlled, organ function damage was improved, and the patient was transferred out of the ICU. It is possible to reach a favorable clinical outcome for critically ill patients by applying a critical care mindset to quickly integrate diagnostic and therapeutic strategies, accurately identifying the triggers and causes that led to the progression of the disease, and using critical care medical techniques for early and effective intervention.
Humans ; Female ; Pregnancy ; Adult ; Atypical Hemolytic Uremic Syndrome/therapy* ; Intensive Care Units ; Pregnancy Complications, Hematologic/therapy* ; Critical Care

Physiologically based pharmacokinetic (PBPK) models have been widely used to predict various stages of drug absorption, distribution, metabolism and excretion. Models based on machine learning (ML) and artificial intelligence (AI) can provide better ideas for the construction of PBPK models, which can accelerate the prediction speed and improve the prediction quality of PBPK. ML and AL can complement the advantages of PBPK model to accelerate the progress of drug research and development. This review introduces the application of machine learning and artificial intelligence in pharmacokinetics, summarizes the research progress of physiological pharmacokinetic models based on machine learning and artificial intelligence, and analyzes the limitations of machine learning and artificial intelligence applications and their application prospects and prospects.

As a novel iron-dependent form of cell death, ferroptosis is characterized by the excessive accumulation of phospholipids containing polyunsaturated fatty acids (PUFA) on the cell membrane and peroxidation. Lipid droplets are always in the dynamic transition of generation and decomposition, play a central role in regulating lipid metabolism, and are always in the dynamic transition of generation and decomposition. Lipid droplet metabolism is closely related to the occurrence of ferroptosis and plays an important role in the disease caused by ferroptosis. This review firstly focuses on the lipid droplet metabolism process and its effects on the storage and release of PUFA, and further elucidates the regulatory mechanism and key regulatory proteins of lipid drop metabolism on ferroptosis, in order to reveal the intrinsic relationship between lipid droplets and ferroptosis, and provide a new strategy for disease prevention and treatment.

Objective:To investigate the clinicopathological features and molecular genetic characteristics of esophageal carcinoma with ductal differentiation, and to summarize the experiences in its diagnosis and treatment.Methods:A total of 17 cases of esophageal carcinoma with ductal differentiation diagnosed in Ningbo Clinical Pathological Diagnosis Center, Ningbo, China from June 2011 to December 2022 were collected. The clinical information and pathological diagnosis was reviewed. The tumor histological features and immunohistochemical results were analyzed. The next-generation sequencing was performed to detect and analyze the gene mutations in tumor samples.Results:The 17 patients included in this study were 54-77 years old, with a median age of 66 years. There were 16 males and 1 female. Among them, 9 cases were mainly carcinoma with ductal differentiation. The squamous epithelium on the tumor′s surface was accompanied by high-grade intraepithelial neoplasia. The tumor and atypical squamous epithelium were transitional, and the focus was accompanied by various proportions of squamous cell carcinoma component (less than 10%). The other 8 cases were mostly squamous cell carcinoma, basaloid squamous cell carcinoma or sarcomatoid carcinoma with various degrees of tumor specific differentiation and focal area of carcinoma with ductal differentiation (less than 10%). The tumor cells in the area with ductal differentiation were mainly arranged in small tubes, while the tubes showed a double-layer structure, including the inner cells and outer cells of the lumen. Immunohistochemical results showed that the outer cells of the tumorous tubules expressed p63, p40, CK5/6 and CK34βE12, while the inner cells expressed CK7. Compared with esophageal squamous cell carcinoma reported in the literature, the frequency of gene mutations such as MYC ( P=0.002), TP63 ( P=0.002), CDKN1C ( P=0.002) and NFE2L2 ( P=0.045) was significantly lower in this group of cases. At the signaling pathway level, the mutation frequency of NOTCH signaling pathway ( P=0.041) was significantly higher, while the mutation frequencies of NRF2 pathway ( P=0.013) and PI3K pathway ( P=0.009) were significantly lower than that of esophageal squamous cell carcinoma. Conclusion:Esophageal carcinoma with ductal differentiation is a type of esophageal carcinoma with unique morphology, and its molecular changes are also significantly different from those of conventional esophageal squamous cell carcinoma.