Parkinson’s disease (PD) is a common neurodegenerative disorder with profound impact on patients’ quality of life and long-term health, and early detection and intervention are particularly critical. In recent years, the search for precise and reliable biomarkers has become one of the key strategies to effectively address the clinical challenges of PD. In this paper, we systematically evaluated potential biomarkers, including proteins, metabolites, epigenetic markers, and exosomes, in the peripheral blood of PD patients. Protein markers are one of the main directions of biomarker research in PD. In particular, α‑synuclein and its phosphorylated form play a key role in the pathological process of PD. It has been shown that aggregation of α-synuclein may be associated with pathologic protein deposition in PD and may be a potential marker for early diagnosis of PD. In terms of metabolites, uric acid, as a metabolite, plays an important role in oxidative stress and neuroprotection in PD. It has been found that changes in uric acid levels may be associated with the onset and progression of PD, showing its potential as an early diagnostic marker. Epigenetic markers, such as DNA methylation modifications and miRNAs, have also attracted much attention in Parkinson’s disease research. Changes in these markers may affect the expression of PD-related genes and have an important impact on the onset and progression of the disease, providing new research perspectives for the early diagnosis of PD. In addition, exosomes, as a potential biomarker carrier for PD, are able to carry a variety of biomolecules involved in intercellular communication and pathological regulation. Studies have shown that exosomes may play an important role in the pathogenesis of PD, and their detection in blood may provide a new breakthrough for early diagnosis. It has been shown that exosomes may play an important role in the pathogenesis of PD, and their detection in blood may provide new breakthroughs in early diagnosis. In summary, through in-depth evaluation of biomarkers in the peripheral blood of PD patients, this paper demonstrates the important potential of these markers in the early diagnosis of PD and in the study of pathological mechanisms. Future studies will continue to explore the clinical application value of these biomarkers to promote the early detection of PD and individualized treatment strategies.

Objective: To assess the effect of transarterial embolization (TAE) for adhesive capsulitis (AC) by evaluating clinical outcomes and changes in inflammation using magnetic resonance imaging (MRI). Materials and Methods: Patients who had undergone TAE between August 2020 and August 2023 for AC refractory to conservative treatments without any invasive procedures for more than 3 months, and had undergone baseline and 3-month post-AC follow-up contrast-enhanced MRI evaluations, were included. A suspension mixture of 500 mg imipenem/cilastatin in 10 mL of iodinated contrast agent was used for TAE. MRI results were analyzed to assess periarticular capsule/ligament inflammation. Clinical assessments included pain scores using the numeric rating scale (NRS) and functional scores using the quick disabilities of the arm, shoulder, and hand (Quick DASH) questionnaire. Results: Twenty-five patients (female:male, 14:11; age, 54.9 ± 7.1 years) were included. Significant reductions in average NRS pain scores as well as improvements in Quick DASH scores and range of motion, including anterior flexion and abduction, were observed at 1, 3, and 6 months after TAE (all P < 0.001). MRI analyses revealed that TAE significantly decreased the grades of axillary recess capsule enhancement, rotator interval (RI) capsule T2 signal intensity, and RI capsule enhancement (all P ≤ 0.004). Conclusion TAE may be an effective and safe therapeutic approach for AC refractory to conservative treatments, alleviating pain and supporting functional recovery. The observed MRI findings suggest that the effectiveness of TAE for AC may be attributed to the reduction of inflammation and the elimination of angiogenesis.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective: To assess the effect of transarterial embolization (TAE) for adhesive capsulitis (AC) by evaluating clinical outcomes and changes in inflammation using magnetic resonance imaging (MRI). Materials and Methods: Patients who had undergone TAE between August 2020 and August 2023 for AC refractory to conservative treatments without any invasive procedures for more than 3 months, and had undergone baseline and 3-month post-AC follow-up contrast-enhanced MRI evaluations, were included. A suspension mixture of 500 mg imipenem/cilastatin in 10 mL of iodinated contrast agent was used for TAE. MRI results were analyzed to assess periarticular capsule/ligament inflammation. Clinical assessments included pain scores using the numeric rating scale (NRS) and functional scores using the quick disabilities of the arm, shoulder, and hand (Quick DASH) questionnaire. Results: Twenty-five patients (female:male, 14:11; age, 54.9 ± 7.1 years) were included. Significant reductions in average NRS pain scores as well as improvements in Quick DASH scores and range of motion, including anterior flexion and abduction, were observed at 1, 3, and 6 months after TAE (all P < 0.001). MRI analyses revealed that TAE significantly decreased the grades of axillary recess capsule enhancement, rotator interval (RI) capsule T2 signal intensity, and RI capsule enhancement (all P ≤ 0.004). Conclusion TAE may be an effective and safe therapeutic approach for AC refractory to conservative treatments, alleviating pain and supporting functional recovery. The observed MRI findings suggest that the effectiveness of TAE for AC may be attributed to the reduction of inflammation and the elimination of angiogenesis.

Objective: To assess the effect of transarterial embolization (TAE) for adhesive capsulitis (AC) by evaluating clinical outcomes and changes in inflammation using magnetic resonance imaging (MRI). Materials and Methods: Patients who had undergone TAE between August 2020 and August 2023 for AC refractory to conservative treatments without any invasive procedures for more than 3 months, and had undergone baseline and 3-month post-AC follow-up contrast-enhanced MRI evaluations, were included. A suspension mixture of 500 mg imipenem/cilastatin in 10 mL of iodinated contrast agent was used for TAE. MRI results were analyzed to assess periarticular capsule/ligament inflammation. Clinical assessments included pain scores using the numeric rating scale (NRS) and functional scores using the quick disabilities of the arm, shoulder, and hand (Quick DASH) questionnaire. Results: Twenty-five patients (female:male, 14:11; age, 54.9 ± 7.1 years) were included. Significant reductions in average NRS pain scores as well as improvements in Quick DASH scores and range of motion, including anterior flexion and abduction, were observed at 1, 3, and 6 months after TAE (all P < 0.001). MRI analyses revealed that TAE significantly decreased the grades of axillary recess capsule enhancement, rotator interval (RI) capsule T2 signal intensity, and RI capsule enhancement (all P ≤ 0.004). Conclusion TAE may be an effective and safe therapeutic approach for AC refractory to conservative treatments, alleviating pain and supporting functional recovery. The observed MRI findings suggest that the effectiveness of TAE for AC may be attributed to the reduction of inflammation and the elimination of angiogenesis.

Objective: To assess the effect of transarterial embolization (TAE) for adhesive capsulitis (AC) by evaluating clinical outcomes and changes in inflammation using magnetic resonance imaging (MRI). Materials and Methods: Patients who had undergone TAE between August 2020 and August 2023 for AC refractory to conservative treatments without any invasive procedures for more than 3 months, and had undergone baseline and 3-month post-AC follow-up contrast-enhanced MRI evaluations, were included. A suspension mixture of 500 mg imipenem/cilastatin in 10 mL of iodinated contrast agent was used for TAE. MRI results were analyzed to assess periarticular capsule/ligament inflammation. Clinical assessments included pain scores using the numeric rating scale (NRS) and functional scores using the quick disabilities of the arm, shoulder, and hand (Quick DASH) questionnaire. Results: Twenty-five patients (female:male, 14:11; age, 54.9 ± 7.1 years) were included. Significant reductions in average NRS pain scores as well as improvements in Quick DASH scores and range of motion, including anterior flexion and abduction, were observed at 1, 3, and 6 months after TAE (all P < 0.001). MRI analyses revealed that TAE significantly decreased the grades of axillary recess capsule enhancement, rotator interval (RI) capsule T2 signal intensity, and RI capsule enhancement (all P ≤ 0.004). Conclusion TAE may be an effective and safe therapeutic approach for AC refractory to conservative treatments, alleviating pain and supporting functional recovery. The observed MRI findings suggest that the effectiveness of TAE for AC may be attributed to the reduction of inflammation and the elimination of angiogenesis.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.