A Study of Shape Memory Effect Above Ms Temperature in a Cu-Zn Alloy Using the Twisting Deformation and Electric Resistance Methods

The shape memory effect (SME) is generally recognized to be caused by the reverse transformation of the deformed thermoelastic martensite (TEM); in a TiNi alloy, however, it has been reported that the SME is not related to the thermoelastic martensite but is caused by stress--induced martensite (SIM) [1]. The SME is mainly related to the R-phase transformation [2]

A Study of Internal Friction, Electric Resistance and Shape Change in Cu-Zn and Cu-Zn-Al Alloys During Phase Transformation Use Simultaneous Measurement Method

The internal friction (Q-1), electric resistance (r), shape change (X), and temperature (T) in TiNi alloys during phase transformation have been measured simultaneously [1]. A. Ghilarducci and, M. Ahlers [2] have studied the internal friction in Cu-Zn and Cu-Zn-Al alloys and have shown that the Q-1 peaks are not due to the phase transformation but due to point defects. The electric resistance during thermoelastic martensite (TEM) phase transformation has been studied by K. Otsuka, et.al, [3] and I. Cornelis and, C. M. Wayman showed that the TEM phase transformation temperature Ms, Mf, Asand Af can be obtained from the electric resistance R vs. temperature T curves (R-T curve) [4]. The quantitative relation between the electric resistance change and the amount of martensite is not yet known. Now, the Q-1, R, X, frequency f and T during TEM transformation in Cu-Zn and Cu-Zn-Al alloys have been measured simultaneously as has been done in a TiNi alloy [1,5]. The amount of martensite at every temperature from Ms to Mf and As to Af was calculated by Delorme’s formula of internal friction [6], so that the change of R can be calculated

Posttraumatic stress disorder symptoms among healthcare workers during the Omicron era

BackgroundThe COVID-19 pandemic has caused significant psychological stress among healthcare workers. This study aimed to clarify the factors that influenced health workers’ posttraumatic stress disorder (PTSD) symptoms.MethodA total of 443 healthcare workers from eight Mental Health Centers in Shandong were recruited to attend an online survey. Participants completed self-evaluation measures of exposure to the COVID-19 environment and PTSD symptoms, as well as measures of potential protective factors such as euthymia and perceived social support.ResultsAbout 45.37% of healthcare workers had severe symptoms of PTSD symptoms. Healthcare workers with more serious PTSD symptoms were significantly related to higher exposure to COVID-19 (r = 0.177, p < 0.001), as well as lower levels of euthymia (r = −0.287, p < 0.001) and perceived social support (r = −0.236, p < 0.001). The structural equation model (SEM) further revealed that the impact of exposure to COVID-19 on PTSD symptoms was partially mediated by euthymia, and moderated by perceived social support, especially from others (e.g., friends, leaders, relatives and colleagues).ConclusionThese findings suggested that improving the state of euthymia, getting social support from others could alleviate PTSD symptoms among healthcare workers during the COVID-19

Trends in Air Pollution During 1996 - 2003 and Cross-Border Transport in City Clusters Over the Yangtze River Delta Region of China

Air quality data from city clusters in the fast developing Yangtze River Delta (YRD) region of China during 1996-2003 were analyzed, with a cross-border transport study using the Regional Acid Deposition Model System (RegADMS). Investigations show that the annual average concentrations of SO2, NO2, PM10 are 12 to 64 /m3, 13~57 /m3, 79~184 /m3, respectively. As the primary air pollutants in the target area, surface NO2 levels increased by 13% while PM10 levels decreased by 39% from 1996 to 2003. The surface SO2 concentration showed fluctuations during the study period, reaching a minimum in 1999 and rising again in 2003. Acid rain still remains an important atmospheric environmental issue. The frequency of acid rain was about 23.5~36.7%, and the pH value of precipitation ranged from 5.09 to 5.48, with little change in these years. Modeling studies indicated that sulfur deposition and nitrogen deposition were in the ranges 0.5-10 g/m2/yr and 0.2-5 g/m2/yr, respectively; these levels exceed the critical load in some regions. The trans-boundary transport of sulfur deposition and nitrogen deposition due to SO2 and NOx emission among city clusters (Shanghai and the other 8 cities in Jiangsu Province, including Nanjing, Wuxi, Changzhou, Suzhou, Nantong, Yangzhou, Zhenjiang, Taizhou) in the YRD region was significant. The emission from Shanghai contributes 5%~29% of sulfur deposition and 3%~30% of nitrogen deposition in the 8 cities, while the 8 cities contribute 27.5% of sulfur deposition and 20.2% of nitrogen deposition in Shanghai

Anticipation of pain enhances the nociceptive transmission and functional connectivity within pain network in rats

<p>Abstract</p> <p>Background</p> <p>Expectation is a very potent pain modulator in both humans and animals. There is evidence that pain transmission neurons are modulated by expectation preceding painful stimuli. Nonetheless, few studies have examined the influence of pain expectation on the pain-related neuronal activity and the functional connectivity within the central nociceptive network.</p> <p>Results</p> <p>This study used a tone-laser conditioning paradigm to establish the pain expectation in rats, and simultaneously recorded the anterior cingulate cortex (ACC), the medial dorsal thalamus (MD), and the primary somatosensory cortex (SI) to investigate the effect of pain expectation on laser-induced neuronal responses. Cross-correlation and partial directed coherence analysis were used to determine the functional interactions within and between the recorded areas during nociceptive transmission. The results showed that under anticipation condition, the neuronal activity to the auditory cue was significantly increased in the ACC area, whereas those to actual noxious stimuli were enhanced in all the recorded areas. Furthermore, neuronal correlations within and between these areas were significantly increased under conditions of expectation compared to those under non-expectation conditions, indicating an enhanced synchronization of neural activity within the pain network. In addition, information flow from the medial (ACC and MD) to the lateral (SI cortex) pain pathway increased, suggesting that the emotion-related neural circuits may modulate the neuronal activity in the somatosensory pathway during nociceptive transmission.</p> <p>Conclusion</p> <p>These results demonstrate that the nociceptive processing in both medial and lateral pain systems is modulated by the expectation of pain.</p

Pathological Brain Detection by a Novel Image Feature—Fractional Fourier Entropy

Aim: To detect pathological brain conditions early is a core procedure for patients so as to have enough time for treatment. Traditional manual detection is either cumbersome, or expensive, or time-consuming. We aim to offer a system that can automatically identify pathological brain images in this paper.Method: We propose a novel image feature, viz., Fractional Fourier Entropy (FRFE), which is based on the combination of Fractional Fourier Transform(FRFT) and Shannon entropy. Afterwards, the Welch’s t-test (WTT) and Mahalanobis distance (MD) were harnessed to select distinguishing features. Finally, we introduced an advanced classifier: twin support vector machine (TSVM). Results: A 10 x K-fold stratified cross validation test showed that this proposed “FRFE +WTT + TSVM” yielded an accuracy of 100.00%, 100.00%, and 99.57% on datasets that contained 66, 160, and 255 brain images, respectively. Conclusions: The proposed “FRFE +WTT + TSVM” method is superior to 20 state-of-the-art methods

CAR T cells targeting BAFF-R can overcome CD19 antigen loss in B cell malignancies

CAR T cells targeting CD19 provide promising options for treatment of B cell malignancies. However, tumor relapse from antigen loss can limit efficacy. We developed humanized, second-generation CAR T cells against another B cell–specific marker, B cell activating factor receptor (BAFF-R), which demonstrated cytotoxicity against human lymphoma and acute lymphoblastic leukemia (ALL) lines. Adoptively transferred BAFF-R-CAR T cells eradicated 10-day preestablished tumor xenografts after a single treatment and retained efficacy against xenografts deficient in CD19 expression, including CD19-negative variants within a background of CD19-positive lymphoma cells. Four relapsed, primary ALLs with CD19 antigen loss obtained after CD19-directed therapy retained BAFF-R expression and activated BAFF-R-CAR, but not CD19-CAR, T cells. BAFF-R-CAR, but not CD19-CAR, T cells also demonstrated antitumor effects against an additional CD19 antigen loss primary patient–derived xenograft (PDX) in vivo. BAFF-R is amenable to CAR T cell therapy, and its targeting may prevent emergence of CD19 antigen loss variants

Common variants at 2q11.2, 8q21.3, and 11q13.2 are associated with major mood disorders

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders

Common variants at 2q11.2, 8q21.3, and 11q13.2 are associated with major mood disorders

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders