Forsythia suspensa is a traditional Chinese medicine and a commonly used landscaping plant. Its dried fruit is used in medicine for its functions of clearing heat, removing toxins, reducing swelling, dissipating masses, and dispersing wind and heat. It possesses extremely high medicinal and economic value. However, the genetic differentiation and diversity of its wild populations remain unclear. In this study, chloroplast genome sequences were obtained from 15 wild individuals of F. suspensa using high-throughput sequencing technology. The sequence characteristics and intraspecific variations were analyzed. The results were as follows:(1) The full length of the F. suspensa chloroplast genome ranged from 156 184 to 156 479 bp, comprising a large single-copy region, a small single-copy region, and two inverted repeat regions. The chloroplast genome encoded a total of 132 genes, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes.(2) A total of 166-174 SSR loci, 792 SNV loci, and 63 InDel loci were identified in the F. suspensa chloroplast genome, indicating considerable genetic variation among individuals.(3) Population structure analysis revealed that F. suspensa could be divided into five or six groups. Both the population structure analysis and phylogenetic reconstruction results indicated significant genetic variation within the wild populations of F. suspensa, with no obvious correlation between intraspecific genetic differentiation and geographical distribution. This study provides new insights into the genetic diversity and differentiation within F. suspensa species and offers additional references for the conservation of species diversity and the utilization of germplasm resources in wild F. suspensa.
Genome, Chloroplast ; Forsythia/classification* ; Phylogeny ; Genetic Variation ; Chloroplasts/genetics* ; Microsatellite Repeats

Kidney-Yang deficiency syndrome is a common geriatric disease that underlies chronic conditions such as diabetic nephropathy, chronic kidney disease, and osteoporosis. As age progresses, the kidney-Yang deficiency syndrome showcases increasingly pronounced manifestations, emerging as a key factor in the comorbidities experienced by elderly patients and affecting their quality of life and overall health status. Traditional Chinese medicine(TCM) has been extensively utilized in the treatment of kidney-Yang deficiency syndrome, with Epimedii Folium, Cinnamomi Cortex, and Lycii Fructus widely used in clinical settings. Despite the complexity of the molecular mechanisms involved in treating kidney-Yang deficiency syndrome, the potential therapeutic value of TCM remains compelling. Delving into the mechanisms of TCM treatment of kidney-Yang deficiency syndrome by regulating the neuro-endocrine-immune system can provide a scientific basis for targeted treatments of this syndrome and lay a foundation for the modernization of TCM. The pathophysiology of kidney-Yang deficiency syndrome involves multiple systems, including the interaction of the neuro-endocrine-immune system, the decline in renal function, the intensification of oxidative stress responses, and energy metabolism disorders. Understanding these mechanisms and their interrelationships can help untangle the etiology of kidney-Yang deficiency syndrome, aiding clinicians in making more precise diagnoses and treatments. Furthermore, the research on the specific applications of TCM in research on these pathological mechanisms can enhance the international recognition and status of TCM, enabling it to exert a greater global influence.
Humans ; Yang Deficiency/physiopathology* ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Kidney Diseases/physiopathology* ; Neurosecretory Systems/physiopathology* ; Animals ; Kidney/physiopathology* ; Endocrine System/physiopathology* ; Immune System/physiopathology*

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

OBJECTIVE: To investigate the variability of bone metabolism levels among different populations and its association with knee osteoarthritis (KOA) pain. METHODS: A total of 50 people (control group) who participated in physical examination from January 2023 to June 2023 were selected, including 26 males and 24 females, wtih a mean aged of (52.14±9.04) years old ranging 41 to 65 years old. The other 50 patients with knee osteoarthritis(case group) who attended the outpatient clinic of the Orthopedics and Traumatology Department in the same time period, including 19 males and 31 females, with a mean age of (53.60±7.76) years old ranging 40 to 65 years. The two groups of Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC) and bone metabolism markers, such as 25-hydroxy-cholecalciferol[25(OH)D], β-isomerized typeⅠcollagen C-telopeptide breakdown products (β-CTX), total typeⅠprocollagen N-terminal propeptide (t-PINP), osteocalcin (OC), parathormone (PTH) levels were compared. Pearson correlation analysis was used to compare the correlation between two groups of bone metabolism related markers and WOMAC. RESULTS: The WOMAC score of the case group (39.90±2.34) was higher than that of the control group (3.60±0.57), with significant difference (P<0.05). There was no significant difference between the two groups of 25 (OH)D, β-CTX and PTH (P>0.05). The t-PINP and OC of the case group were (62.90±52.40) and (19.88±10.15) ng·ml-1, respectively, and those of the control group were (38.86±10.82) and (14.90±3.62) ng·ml^-1, respectively;the t-PINP and OC of the case group were higher than those of the control group, with significant difference (P<0.05). Pearson correlation analysis showed that t-PINP was positively correlated with WOMAC pain score in the case group (r²=0.045, P<0.01). CONCLUSION Bone metabolism levels in the serum of patients with knee osteoarthritis are different from those of healthy people, and the difference between OC and t-PINP is the most obvious, and the concentration of t-PINP levels is positively correlated with pain symptoms in patients with KOA. However, the specific mechanism of correlation between the bone metabolism levels of patients with KOA and their pain symptoms needs to be further elucidated by basic experimental research as well as by enlarging the samples.
Humans ; Female ; Male ; Middle Aged ; Osteoarthritis, Knee/metabolism* ; Aged ; Adult ; Bone and Bones/metabolism* ; Pain/etiology* ; Biomarkers/metabolism*

OBJECTIVE: To observe the clinical efficacy of 3D printing spinal external fixator combined with McKenzie therapy for patients with lumbar dics herniation (LDH). METHODS: Sixty patients with LDH between January 2022 and January 2023 were enrolled. Among them, 30 patients were given McKinsey training. According to different treatment methods, all patients were divided into McKenzie group and McKenzie + 3D printing group, 30 patients in each group. The McKenzie group provided McKenzie therapy. The McKenzie + 3D printing group were treated with 3D printing spinal external fixation brace on the basis of McKenzie therapy. Patients in both groups were between 25 and 60 years of age and had their first illness. In the McKenzie group, there were 19 males and 11 females, with an average age of (48.57±5.86) years old, and the disease duration was (7.03 ±2.39) months. The McKenzie + 3D printing group, there were 21 males and 9 females, with an average age of (48.80±5.92) years old, and the disease duration was(7.30±2.56) months. Pain was evaluated using the visual analogue scale (VAS), and lumbar spine function was assessed using the Oswestry disability index (ODI) and the Japanese Orthopaedic Association (JOA) score. VAS, ODI and JOA scores were compared between two groups before treatment and at 1, 3, 6, 9 and 12 months after treatment. RESULTS: All patients were followed up for 12 months. The VAS for the McKenzie combined with 3D printing group before treatment and at 1, 3, 6, 9, and 12 months post-treatment were(6.533±0.860), (5.133±1.008), (3.933±0.868), (2.900±0.759), (2.067±0.640), (1.433±0.504), respectively. In the McKenzie group, the corresponding scores were (6.467±0.860), (5.067±1.048), (4.600±0.968), (3.533±1.008), (2.567±0.728), (1.967±0.809), respectively. The ODI of the McKenzie group before treatment and at 1, 3, 6, 9, and 12 months post-treatment were (41.033±6.810)%, (37.933±6.209)%, (35.467±6.962)%, (27.567±10.081)%, (20.800±7.531)%, (13.533±5.158)%, respectively. For the McKenzie combined with 3D printing group, the corresponding ODI were(38.033±5.605)%, (33.000±6.192)%, (28.767±7.045)%, (22.200±5.517)%, (17.700±4.836)%, (11.900±2.771)%, respectively. The JOA scores of the McKenzie combined with 3D printing group before treatment and at 1, 3, 6, 9, and 12 months post-treatment were(8.900±2.074), (13.133±2.330), (15.700±3.583), (20.400±3.480), (22.267±3.084), (24.833±2.640), respectively. In the McKenzie group, the corresponding scores were(9.200±2.091), (12.267±2.406), (15.333±3.198), (18.467±2.240), (20.133±2.751), (22.467±2.849), respectively. Before the initiation of treatment, no statistically significant differences were observed in the VAS, ODI, and JOA scores between two groups (P>0.05). At 3, 6, 9, and 12 months post-treatment, the VAS in the McKenzie combined with 3D printing group was significantly lower than that in the McKenzie group, and the difference was statistically significant (P<0.05). The comparison of ODI between two groups at 1, 3, 6, 9, and 12 months post-treatment revealed statistically significant differences (P<0.05). At 6, 9, and 12 months post-treatment, the JOA score in the McKenzie combined with 3D printing group was significantly higher than that in the McKenzie-only group, and the difference was statistically significant (P<0.05). CONCLUSION The combination of 3D printed functional spinal external fixation brace with McKenzie therapy can significantly improve and maintain lumbar function in patients with LDH.
Humans ; Male ; Female ; Middle Aged ; Printing, Three-Dimensional ; Intervertebral Disc Displacement/surgery* ; External Fixators ; Lumbar Vertebrae/surgery* ; Adult ; Braces ; Treatment Outcome

Varicocele (VC) is a common cause of male infertility, yet there is a lack of molecular information for VC-associated male infertility. This study investigated alterations in the seminal plasma metabolomic and lipidomic profiles of infertile male VC patients. Twenty infertile males with VC and twenty-three age-matched healthy controls (HCs) were recruited from Peking Union Medical College Hospital (Beijing, China) between October 2019 and April 2021. Untargeted metabolite and lipid profiles from seminal plasma were analyzed using mass spectrometry. Four hundred and seventy-six metabolites and seventeen lipids were significantly different in infertile male VC patients compared to HCs. The top enriched pathways among these significantly different metabolites are protein digestion and absorption, aminoacyl-transfer RNA (tRNA) biosynthesis, and biosynthesis of amino acids. Different key lipid species, including triglyceride (TG), diacylglycerol (DG), ceramides (Cer), and phosphatidylserine (PS), varied between VC and HC groups. The distinct metabolites and lipids were moderately correlated. DL-3-phenyllactic acid is a potential diagnostic biomarker for VC-related male infertility (area under the curve [AUC] = 0.893), positively correlating with sperm count, concentration, and motility. Furthermore, DL-3-phenyllactic acid is the only metabolite shared by all four comparisons (VC vs HC, VC-induced oligoasthenospermia [OAS] vs VC-induced asthenospermia [AS], OAS vs HC, and AS vs HC). DL-3-phenyllactic acid significantly decreased in OAS than AS. Metabolite-targeting gene analysis revealed carbonic anhydrase 9 (CA9) might be the strongest candidate associated with the onset and severity of VC. The seminal plasma metabolite and lipid profiles of infertile males with VC differ significantly from those of HCs. DL-3-phenyllactic acid could be a promising biomarker.
Humans ; Male ; Varicocele/complications* ; Infertility, Male/etiology* ; Semen/metabolism* ; Lipidomics ; Adult ; Metabolomics ; Case-Control Studies ; Biomarkers/metabolism*

OBJECTIVES: To explore the relationship between white matter injury (WMI) and cerebral perfusion in preterm infants using arterial spin labeling (ASL). METHODS: A total of 293 preterm infants (gestational age <34 weeks) hospitalized at the Third Affiliated Hospital of Zhengzhou University between June 2022 and June 2024 were included. After achieving clinical stability, the infants underwent brain magnetic resonance imaging (MRI) and ASL. Based on MRI findings, infants were classified into WMI (n=66) and non-WMI (n=227) groups. Cerebral perfusion parameters were compared between groups, and the association between WMI and perfusion alterations was evaluated. RESULTS: The WMI group showed a higher incidence of mild intraventricular hemorrhage (IVH) than the non-WMI group (P<0.05). Significantly lower cerebral perfusion was observed in the WMI group across bilateral frontal, temporal, parietal, and occipital lobes, as well as the basal ganglia and thalamus (P<0.05). After adjusting for gestational age, corrected gestational age at ASL scan, and mild IVH, WMI remained significantly associated with reduced regional perfusion (P<0.05). CONCLUSIONS WMI in preterm infants correlates with localized cerebral hypoperfusion. ASL-detected perfusion abnormalities may provide novel insights into WMI pathogenesis.
Humans ; White Matter/blood supply* ; Infant, Newborn ; Spin Labels ; Infant, Premature ; Female ; Male ; Cerebrovascular Circulation ; Magnetic Resonance Imaging

OBJECTIVES: To study the clinical and imaging features of children with influenza-associated encephalopathy (IAE), and to investigate the influencing factors for prognosis. METHODS: A retrospective analysis was conducted on the medical data (clinical data, laboratory examinations, imaging data, and prognosis) of 23 children with IAE who were diagnosed and treated in Children's Hospital of Nanjing Medical University from May 2022 to April 2023. RESULTS: Among the 23 patients, 18 (78%) had influenza A and 5 (22%) had influenza B. All patients had fever and encephalopathy, and 20 patients (87%) had seizures, while 11 patients (48%) had persistent convulsions. There were 10 patients (43%) with an increase in alanine aminotransferase, 14 (61%) with an increase in aspartate aminotransferase, and 18 (78%) with an increase in lactate dehydrogenase. Abnormal imaging findings were observed in 20 patients (87%), among whom 10 (43%) had acute necrotizing encephalopathy. All 23 patients received peramivir or oseltamivir. Of all patients, 12 (52%) achieved complete recovery, 5 (22%) had varying degrees of neurological dysfunction, and 6 (26%) died. Compared with the good prognosis group, the poor prognosis group had significantly higher levels of alanine aminotransferase, aspartate aminotransferase, and lactate dehydrogenase (P<0.05). CONCLUSIONS Fever and convulsions are the most common symptoms of children with IAE, and acute necrotizing encephalopathy is the most common clinical imaging syndrome. Increases in alanine aminotransferase, aspartate aminotransferase, and lactate dehydrogenase have a certain value in predicting poor prognosis.
Humans ; Influenza, Human/complications* ; Male ; Prognosis ; Female ; Child, Preschool ; Retrospective Studies ; Infant ; Child ; Brain Diseases/etiology*

OBJECTIVE: To establish a genotyping method for Diego, MNS and Kell blood groups based on quantitative real-time PCR (qPCR) technology, and preliminarily apply it to the screening of rare blood groups in blood donors. METHODS: Blood group gene standards containing heterozygous and homozygous alleles were prepared by blood group serological and PCR-SBT methods. Specific amplification primers and hybridization probes were designed, and explore to establish the qPCR method for detecting Diego, MNS, and Kell blood group genotypes. Then the established qPCR method was used to identify blood group genotypes of 186 blood donor samples. RESULTS: A method based on qPCR technology was established to identify Dia/Dib, S/s and K/k blood group antigens. The genotyping results of the gene standard samples were consistent with the serological testing results and genotypes detected by PCR-SBT. qPCR testing of 186 samples identified 11 cases of DI*A/B heterozygosity and 19 cases of GYPB*S/s heterozygosity, and the rest were DI*B/B, GYPB*s/s, KEL*02/02 homozygosity. No rare blood group genotypes of DI*A/A, GYPB*S/S, KEL*01.01/01.01 were found. CONCLUSION The established qPCR method is suitable for genotyping on Diego, MNS and Kell blood group, and it can be used for batch screening of blood donors and the establishment of rare blood group bank.
Humans ; Genotype ; Genotyping Techniques/methods* ; Real-Time Polymerase Chain Reaction/methods* ; Blood Group Antigens/genetics* ; Kell Blood-Group System/genetics* ; Blood Donors ; Blood Grouping and Crossmatching/methods* ; Erythrocytes ; MNSs Blood-Group System/genetics*