Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Effective albumin refers to serum albumin with intact structure and function.In the course of chronic liver disease,some serum albumin loses its functional integrity through different post-translational modifications such as oxidation and glycosylation.Level of effective albumin is lower in patients with decompensated cirrhosis and is significantly correlated with patient survival,underscoring that they are more sensitive than total serum al-bumin in reflecting the actual state of liver function.In addition,effective albumin not only serves as a predictor,but also plays a key role in the treatment of chronic liver disease by improving albumin preparations and develo-ping new therapeutics.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

OBJECTIVE: To explore the clinical characteristics and molecular genetic mechanism of a fetus with recombinant chromosome 8 (Rec8) syndrome. METHODS: A fetus who was diagnosed with Rec8 syndrome at the Provincial Hospital Affiliated to Shandong First Medical University on July 20, 2021 due to high risk for sex chromosomal aneuploidy indicated by non-invasive prenatal testing (NIPT) (at 21st gestational week) was selected as the study subject. Clinical data of the fetus was collected. G-banded karyotyping and chromosomal microarray analysis (CMA) were carried out on the amniotic fluid sample. Peripheral blood samples of the couple were also subjected to G banded karyotyping analysis. RESULTS: Prenatal ultrasonography at 23rd gestational week revealed hypertelorism, thick lips, renal pelvis separation, intrahepatic echogenic foci, and ventricular septal defect. The karyotype of amniotic fluid was 46,XX,rec(8)(qter→q22.3::p23.1→qter), and CMA was arr[GRCh37]8p23.3p23.1(158049_6793322)×1, 8q22.3q24.3(101712402_146295771)×3. The karyotype of the pregnant woman was 46,XX,inv(8)(p23.1q22.3), whilst that of her husband was normal. CONCLUSION The Rec8 syndrome in the fetus may be attributed to the pericentric inversion of chromosome 8 in its mother. Molecular testing revealed that the breakpoints of this Rec8 have differed from previously reported ones.
Humans ; Fetus/abnormalities* ; Chromosomes, Human, Pair 8 ; Female ; Pregnancy ; Karyotyping

Objective:To explore the correlation between subjective well-being and social support in patients with advanced gynecological malignant tumors.Methods:From January 2019 to December 2020, convenience sampling was used to select 125 patients with advanced gynecological malignant tumors admitted to the First Ward of Gynecology of Zhuji People's Hospital as the research object. The patients were investigated using the Newfoundland Scale of Happiness (MUNSH) and the Social Support Rating Scale (SSRS) . A total of 125 questionnaires were distributed, 125 valid questionnaires were recovered, and the valid recovery rate was 100%.Results:Among 125 patients with advanced gynecological malignant tumors, the total scores of SSRS and MUNSH were (30.69±10.98) and (30.49±7.81) respectively. There were statistically significant differences in the social support scores of patients with advanced gynecological malignant tumors with different age, education level, monthly income and marital status ( P<0.05) . There were statistically significant differences in the subjective well-being scores of patients with advanced gynecological malignant tumors with different age, education level, monthly income, marital status and with or without underlying diseases ( P<0.05) . There was a positive correlation between MUNSH total score and SSRS total score in 125 patients with advanced gynecological malignant tumors ( P<0.05) . Conclusions:The subjective well-being and social support of patients with advanced gynecological malignant tumors are highly correlated, and are affected by factors such as the patient's age, education level, monthly income, and marital status, so targeted intervention is required.

Parkinson's disease(PD)is the second most common neurodegenerative disease in the world;however,it lacks effective and safe treatments.Ginkgo biloba dropping pill(GBDP),a unique Chinese G.biloba leaf extract preparation,exhibits antioxidant and neuroprotective effects and has a potential as an alternative therapy for PD.Thus,the aims of this study were to evaluate the effects of GBDP in in vitro and in vivo PD models and to compare the chemical constituents and pharmacological activities of GBDP and the G.biloba extract EGb 761.Using liquid chromatography tandem-mass spectrometry,46 GBDP constitu-ents were identified.Principal component analysis identified differences in the chemical profiles of GBDP and EGb 761.A quantitative analysis of 12 constituents showed that GBDP had higher levels of several flavonoids and terpene trilactones than EGb 761,whereas EGb 761 had higher levels of organic acids.Moreover,we found that GBDP prevented 6-hydroxydopamine-induced dopaminergic neuron loss in zebrafish and improved cognitive impairment and neuronal damage in methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced PD mice.Although similar effects were observed after EGb 761 treatment,the neuroprotective effects were greater after GBDP treatment on several endpoints.In addition,in vitro results suggested that the Akt/GSK3β pathway may be involved in the neuroprotective effects of GBDP.These findings demonstrated that GBDP have potential neuroprotective effects in the treatment of PD.

Objective:To investigate the correlation between white matter hypertensities (WMHs) and the overall burden of cerebral small vessel disease (CSVD) and clinical outcome of patients with acute ischemic stroke.Methods:From November 2018 to June 2019, patients with acute ischemic stroke hospitalized in the Department of Neurology, the Affiliated Jiangning Hospital of Nanjing Medical University were enrolled prospectively. Their demographic and clinical data were collected. The National Institutes of Health Stroke Scale (NIHSS) was used to evaluate the baseline severity of stroke. The total burden of CSVD was evaluated according to the head MRI findings. The severity of WMHs was assessed based on Fazekas scale. The modified Rankin Scale (mRS) was used to evaluate the outcomes at 90 d after onset. The mRS score 0-1 was defined as good outcome, and ≥2 was defined as poor outcome. Multivariate logistic regression analysis was used to determine independent risk factors for poor outcomes. Results:A total of 153 consecutive patients with acute ischemic stroke were enrolled, of which 126 (82.35%) had a good outcome and 27 (17.65%) had a poor outcome. There were significant differences in age, baseline NIHSS score, lipoprotein-associated phospholipase A 2, total Fazekas score, periventricular WMHs score, and deep WMHs score between the two groups, while there was no significant difference in the total burden of CSVD. Multivariate logistic regression analysis revealed that the baseline NIHSS score (odds ratio 1.245, 95% confidence interval 1.023-1.515; P=0.028) and the total Fazekas score (odds ratio 1.635, 95% confidence interval 1.049-2.549; P=0.030) were the independent risk factors for poor outcomes at 90 d after the onset in patients acute ischemic stroke. Conclusions:The overall burden of CSVD is not associated with the short-term outcomes in patients with acute ischemic stroke. WMHs and baseline NIHSS score are the independent risk factors for poor short-term outcomes in patients with acute ischemic stroke.