Response To Selection Research Articles

Emergence of IGH::CCND1 rearrangement and mutations in TP53, BTK, and BCL2 associated with therapy resistance in chronic lymphocytic leukemia

AbstractChronic lymphocytic leukemia (CLL) is an indolent low‐grade B‐cell neoplasm that generally responds well to treatment. Rarely, CLL cases exhibit an IGH::CCND1 rearrangement, presenting a diagnostic challenge in distinguishing between clonal evolution within CLL and an independent mantle cell lymphoma. We report a case of CLL with the emergence of an IGH::CCND1 rearrangement and mutations associated with treatment resistance, including TP53, BTK, and BCL2, during disease progression. Immunophenotypic, cytogenetic, and molecular analyses support that these alterations are secondary events within the CLL clone. This case demonstrates dynamic clonal selection and expansion in response to treatments, which, in turn, contributes to treatment resistance.

A highly selective and recyclable fluorescent sensor based on a Salamo-Salen-Salamo type ligand for continuous detection of Al3+ and phosphates in drug

In this work, a fluorescence chemical sensor continuous detection Al3+ and phosphates by a Salamo-Salen-Salamo type compound (SL) was employed. The sensor continuously recognized Al3+ and phosphates with good selectivity and fast response time, and a low limit of detection of 0.25 μΜ and 0.96 μM, at the same time accompanied by a naked-eye identification specificity. The detection mechanism of SL towards Al3+ is due to the chelating fluorescence enhancement effect and ICT effect, and continuously towards phosphates is due to the collapse of the SL-Al3+ and coordination interaction between Al3+ and phosphates, by Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, other spectral characterization and DFT calculation as evidence. In addition, the sensor had good recyclability and reusability. The distribution of Al3+ and phosphates in zebrafish cells was effectively monitored by confocal microscopy based on the good biocompatibility and tissue permeability of SL. Furthermore, the feasibility of using sensor SL to detect the content of Al3+ and phosphate ions in certain drugs was quantitatively analyzed through experiments. It was found SL had a good result in practical application.

A chromatic feature detector in the retina signals visual context changes.

The retina transforms patterns of light into visual feature representations supporting behaviour. These representations are distributed across various types of retinal ganglion cells (RGCs), whose spatial and temporal tuning properties have been studied extensively in many model organisms, including the mouse. However, it has been difficult to link the potentially nonlinear retinal transformations of natural visual inputs to specific ethological purposes. Here, we discover a nonlinear selectivity to chromatic contrast in an RGC type that allows the detection of changes in visual context. We trained a convolutional neural network (CNN) model on large-scale functional recordings of RGC responses to natural mouse movies, and then used this model to search in silico for stimuli that maximally excite distinct types of RGCs. This procedure predicted centre colour opponency in transient suppressed-by-contrast (tSbC) RGCs, a cell type whose function is being debated. We confirmed experimentally that these cells indeed responded very selectively to Green-OFF, UV-ON contrasts. This type of chromatic contrast was characteristic of transitions from ground to sky in the visual scene, as might be elicited by head or eye movements across the horizon. Because tSbC cells performed best among all RGC types at reliably detecting these transitions, we suggest a role for this RGC type in providing contextual information (i.e. sky or ground) necessary for the selection of appropriate behavioural responses to other stimuli, such as looming objects. Our work showcases how a combination of experiments with natural stimuli and computational modelling allows discovering novel types of stimulus selectivity and identifying their potential ethological relevance.

Field-Testing Multiple-Choice Questions With AI Examinees: English Grammar Items

Field-testing is an essential yet often resource-intensive step in the development of high-quality educational assessments. I introduce an innovative method for field-testing newly written exam items by substituting human examinees with artificially intelligent (AI) examinees. The proposed approach is demonstrated using 466 four-option multiple-choice English grammar questions. Pre-trained transformer language models are fine-tuned based on the 2-parameter logistic (2PL) item response model to respond like human test-takers. Each AI examinee is associated with a latent ability θ, and the item text is used to predict response selection probabilities for each of the four response options. For the best modeling approach identified, the overall correlation between the true and predicted 2PL correct response probabilities was .82 (bias = 0.00, root mean squared error = 0.18). The study results were promising, showing that item response data generated from AI can be used to calculate item proportion correct, item discrimination, conduct item calibration with anchors, distractor analysis, dimensionality analysis, and latent trait scoring. However, the proposed approach did not achieve the level of accuracy obtainable with human examinee response data. If further refined, potential resource savings in transitioning from human to AI field-testing could be enormous. AI could shorten the field-testing timeline, prevent examinees from seeing low-quality field-test items in real exams, shorten test lengths, eliminate test security, item exposure, and sample size concerns, reduce overall cost, and help expand the item bank. Example Python code from this study is available on Github: https://github.com/hotakamaeda/ai_field_testing1

Neural Encoding of Bodies for Primate Social Perception.

Primates, as social beings, have evolved complex brain mechanisms to navigate intricate social environments. This review explores the neural bases of body perception in both human and nonhuman primates, emphasizing the processing of social signals conveyed by body postures, movements, and interactions. Early studies identified selective neural responses to body stimuli in macaques, particularly within and ventral to the superior temporal sulcus (STS). These regions, known as body patches, represent visual features that are present in bodies but do not appear to be semantic body detectors. They provide information about posture and viewpoint of the body. Recent research using dynamic stimuli has expanded the understanding of the body-selective network, highlighting its complexity and the interplay between static and dynamic processing. In humans, body-selective areas such as the extrastriate body area (EBA) and fusiform body area (FBA) have been implicated in the perception of bodies and their interactions. Moreover, studies on social interactions reveal that regions in the human STS are also tuned to the perception of dyadic interactions, suggesting a specialized social lateral pathway. Computational work developed models of body recognition and social interaction, providing insights into the underlying neural mechanisms. Despite advances, significant gaps remain in understanding the neural mechanisms of body perception and social interaction. Overall, this review underscores the importance of integrating findings across species to comprehensively understand the neural foundations of body perception and the interaction between computational modeling and neural recording.

A novel carbazolyl thiophene-based fluorescent “off-on” probe PCTMF for sequential detection of Cu2+ and cysteine in aqueous

Copper ions and cysteine play a crucial role in pathophysiologic processes in the human body and the environment, so the development of probes with high sensitivity and specificity for continuous detection has become the focus of current research. In the paper, a novel fluorescent compound (named PCTMF) is synthesized with a carbazolyl thiophene group as a fluorescent moiety and formyl hydrazine as a recognition group of Cu2+. In the given DMSO-H2O solvent system, the PCTMF exhibits a highly selective and sensitive turn-off fluorescence response towards Cu2+ with its detection limit (LOD) of 0.14 μM, in the presence of other competing metal ions. The turn-off response mechanism of the probe can be attributed to the formation of complex 2PCTMF-Cu. The 2PCTMF-Cu complex presents good sensing capacity on cysteine (Cys) with a LOD of 52 nM. The molecule designing method provides an “off-on” strategy for sequentially fluorescence detecting metal ions and ligands related.

Room-Temperature Flexible CNT/Fe2O3 Film Sensor for ppb-Level H2S Detection.

Carbon nanotubes (CNTs) had room temperature response, large surface area, and excellent mechanical properties, making them favorable for the design of flexible, wearable, and portable gas sensors. However, CNTs were lacking in response and selective response to different gases, such as H2S. Here, we demonstrated a flexible H2S ppb-level gas sensor based on a carbon nanotube/amorphous Fe2O3 (CNT/Fe2O3) film at room temperature, which was fabricated via a simple one-step solvent-thermal method. The CNT/Fe2O3 film gas sensor exhibited a high selective response to H2S (with a response of 55.1% to 100 ppb H2S), rapid reversible response at room temperature (with a response time of ∼127 s to 100 ppb H2S), and low limit of detection to about 2 ppb. Additionally, the CNT/Fe2O3 film maintained good sensing performance under various bending conditions and could be further fabricated into the fiber gas sensor device via wet stretching, retaining response at the ppb level (with a response of 18.6% to 100 ppb H2S). This research on a flexible gas sensor device based on the CNT film/fiber opened up new possibilities for wearable portable electronic device applications.

B cell-intrinsic IFN-γ promotes excessive CD11c+ age-associated B cell differentiation and compromised germinal center selection in lupus mice

CD11c+ age-associated B cells (ABCs) have emerged as a key component in protective and autoreactive B cell responses. Lupus is an autoimmune disorder linked to reduced efficacy of vaccines and increased susceptibility to infections. Previously, we reported that excessive CD11c+ ABCs not only significantly contribute to autoantibody production but also promote aberrant T cell activation and compromised affinity-based germinal center selection in response to immunization in lupus mice. Yet, the regulation of CD11c+ ABC differentiation is not fully understood. In this study, we show that B cell-intrinsic IFN-γ is required for excessive CD11c+ ABC differentiation in lupus mice. B cell-intrinsic IFN-γ is mainly produced by CD11c+ ABCs. IFN-γ-deficiency leads to decreased expression of ABC characteristic genes. We further show that ablating IFN-γ can normalize T cell overactivation and rescue antigen-specific GC responses in lupus mice. Our study offers insight into the crucial role of B cell-intrinsic IFN-γ in promoting excessive CD11c+ ABC differentiation, which compromises affinity-based germinal center selection and affinity maturation in lupus, providing a potential strategy to normalize vaccine responses in lupus.

Self-assembly Pt hollow nanospheres for highly selective and ultrasensitive detection of dopamine

Abnormal concentration of dopamine, one critical neurotransmitter in central nervous system, causes several neurological diseases associated with behavioral responses and brain functions in human beings. Highly sensitive detection of dopamine is of great significance yet challengeable. In this work, Pt hollow nanospheres (Pt HNSs) with a uniform diameter of 30 nm were successfully synthesized in water by self-assembly method under room temperature. The fabricated Pt hollow/Nafion nanospheres modified glassy carbon electrode (Pt HNSS/Nafion/GCE) exhibited superior electrocatalytic performance, with peak currents 2.24 and 4.54 times higher than those of Nafion-modified glassy carbon electrode (Nafion/GCE) and bare glassy carbon electrode (GCE), respectively. Theoretical calculations indicate that dopamine has an adsorption energy of −3.18 eV on the Pt(111) surface, with an electron transfer of + 1.84 |e|, aligning with the 2-electron transfer mechanism. Furthermore, the low energy barrier observed during dopamine oxidation process suggests that the Pt(111) surface is highly favorable for dopamine oxidation. Meanwhile, Pt HNSS/Nafion/GCE electrochemical sensor exhibits highly sensitive and selective response in determination of dopamine ranging from 0.01 to 250 μM with low detection limits of 0.804 nM (S/N = 3). Moreover, the electrochemical sensor shows reliable signals in real test with great anti-interference and stability during the experiments, making it a promising candidate for applications in dopamine sensing.

Self-doped Na-carbon materials derived from a lyocell fiber for a high-performance trimethylamine gas sensor at room temperature

In this study, biomass-derived carbon material obtained from Lyocell fibers was first utilized as a gas sensor. The impacts of varying pyrolytic carbonization temperatures and pregrinding treatments on the structure, surface morphology, elemental composition, and gas sensitivity of the samples were thoroughly examined. The CL-500 sensor can realize rapid detection of trimethylamine with a high response (12.79k%, 500 ppm) and high selectivity at room temperature; the response/recovery times are 10 s and 2 s, respectively, and the theoretical detection limit is 3.96 ppm. Moreover, after four months, the response of the CL-500 sensor to trimethylamine fluctuated by less than 9.7 % compared with that of the fresh sensor, indicating good stability. It also shows good recovery after seven consecutive response-recovery cycles. Additionally, the CL-500 sensor has promising applications in real-life fish freshness monitoring. Theoretical calculations indicate that the introduction of trace amounts of Na enhances the sensing performance of this sensor for target gases. This study serves as a guide for developing cost-effective, high-performance gas sensors, promoting the efficient and high-value utilization of biomass waste.

Regulation of receptor function in NiCo2O4-SnO2 heterojunction for H2S detection at room temperature

In recent years, the World Health Organization has increasingly emphasized air quality in production environments, leading to heightened societal demands for monitoring of pollutant gases at room temperature. Traditional semiconductor gas-sensitive materials, such as tin oxide (SnO2), have their gas-sensing performance largely limited by their receptor functions, resulting in common issues like low response and poor recovery at room temperature. Spinel-type bimetallic oxides, such as nickel cobaltate (NiCo2O4), offer a unique solution due to their rich adsorption sites on the surface, which provide distinctive receptor functions for detecting toxic gases at room temperature. Herein, NiCo2O4 is synthesized via a one-step hydrothermal method, with a porous spherical cluster structure, and combined with SnO2 to form a heterojunction. The NiCo2O4-SnO2 heterojunction film gas sensor exhibits excellent gas-sensing performance for H2S at room temperature, including high response, short response time, good repeatability, and selectivity. Additionally, the unique receptor functions of the NiCo2O4 were analyzed through first-principles calculations, revealing a semiconductor p-n conversion phenomenon in the presence of H2S gas. The composite also demonstrates a conversion from p-n heterojunction to n-n homojunction during the sensing process, enhancing its gas-sensing performance. This work not only addresses the receptor function limitations of traditional gas-sensitive semiconductor but also provides a feasible approach for controlling carrier types in semiconductors.

A portable optical sensor combining smartphone with phycocyanin-based fluorescent test paper for rapid, visual and on-site detection of CO32–

With the development of global industry, carbon dioxide emissions surged. The conversion of carbon dioxide from the air results in some CO32−, which can exacerbate environmental disasters like ocean acidification. Therefore, the content of CO32− in seawater is an important indicator of the degree of ocean acidification. In this study, natural fluorescent protein phycocyanin (PC) was used as a fluorescent probe, and a fluorescence detection method was established for quantitative monitoring of CO32− with quick response time (within 50 s), high sensitivity, and selectivity. The fluorescence quenching phenomenon between PC and CO32− was mainly attributed to static quenching. The limit of detection (LOD) was 0.42 μM and the method was successfully applied to monitor CO32− in tap water and seawater, acquiring satisfactory recovery between 99.28 % and 106.40 %. More importantly, paper-based test strips were easily fabricated using PC, enabling the rapid, visual, and on-site detection of CO32− with the aid of a smartphone. The visual detection integrated with the smartphone was converted to data information (RGB value) through a Color Picker APP and successfully used for quantitative identification of CO32−. By capturing fluorescent images and analyzing the corresponding RGB value via a smartphone, the linear calibration ranged from 0.5 μM to 500.0 μM with LOD of 0.11 μM was obtained. Satisfactory recoveries were acquired in tap water (98.00 %-107.50 %) and seawater (97.30 %-101.74 %), respectively. Therefore, integrating the PC fluorescent paper with a smartphone realizes the rapid, visual, and on-site detection of CO32− in the water environment, which is expected to broaden application prospects of monitoring ocean acidification degree.

Facile synthesis of silver and copper modified graphitic carbon nitride for volatile organic compounds sensing

Volatile organic compounds (VOCs) pose significant health risks when inhaled or ingested in large quantities. Metal oxide-based solid-state gas sensors are commonly utilized for VOCs detection, including methanol, however their high operating temperature and selectivity are both biggest challenges. In this context, graphitic carbon nitride (g-C3N4) has emerged as a promising alternative for VOCs sensing due to its superior sensing properties. In this work, Cu and Ag doped g-C3N4 was synthesized via the polycondensation method for VOCs sensing applications. All the samples showed a selective response to methanol at room temperature. Notably, the Ag/g-C3N4 sensor exhibited a significantly enhanced response (~27.5) compared to both undoped g-C3N4 (~3.58) and Cu/g-C3N4 (~9.82) sensors towards 200 ppm methanol. The Ag/C3N4 based sensor showed rapid response (21 s) and recovery (17 s) times, along with excellent short-term and long-term stability. It was found that Ag/C3N4 sensor exhibited a good response to humidity levels ranging from 9 % to 93 % RH, without any significant variation observed when deposited on the ceramic and flexible polyimide substrates. Further, considering its practical applicability, the Ag/C3N4 sensor showed successful detection of alcohol in human breath, highlighting its potential for real-world applications.

A hexanuclear Iridium(III) cluster for histidine-induced singlet oxygen and superoxide radicals generation

Photosensitizers (PSs) play key roles in photodynamic therapy (PDT). PDT is typically reliant on the local concentration of oxygen. A big challenge for PSs is to develop oxygen-independent photosensitizers, which can work well in hypoxic tumor microenvironment. In this piece of work, a hexanuclear Ir(III) cluster (Ir6) is highly selective towards histidine and histidine-rich (His-rich) proteins to form mononuclear Ir(III) complexes of [Ir(bpy)2(His)]. After the selective response to histidine or his-rich proteins, [Ir(bpy)2(His)] generates both singlet oxygen(1O2) and superoxide (O2−). This work opens an avenue for the potential application of Ir6 for type Ι and ΙΙ synergic photodynamic therapy.

The task-switch cost is still absent after selectively stopping a response in cued task switching.

The task-switch cost is one of the most robust phenomena in human task performance, but it can disappear after nogo trials where the actors decide not to respond to the target. According to the response-selection account, it is the occurrence of response selection that generates a task-switch cost on the subsequent trial, and the absence of a switch cost after nogo trials has been attributed to a nonoccurrence of response selection on nogo trials. However, an alternative account is that a task-switch cost is generated but is abolished on nogo trials because of the interference from the nogo signal with the activated task set, suggesting that the absence of a task-switch cost does not necessarily imply the nonoccurrence of response selection. The present study tested these competing accounts by using selective go/nogo procedures for which withholding a response would require selecting a response and inhibiting the selected response. Bayes factors in five experiments provided evidence for the absence of a task-switch cost after selective nogo trials, indicating that the occurrence of response selection does not necessarily result in a task-switch cost on the subsequent trial. The present results are consistent with the task-set interference account that a task-switch cost could be generated on nogo trials but is abolished because a nogo signal interferes with the activated task-set. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Physics-informed machine learning approach for reduced-order modeling of integrally bladed rotors: Theory and application

Integrally bladed rotors are commonly used in aircraft and rocket turbomachinery and known to exhibit complex dynamics when subject to operational loading conditions. Though nominally cyclic symmetric structures, in practice, cyclic symmetry is destroyed due to mistuning caused by random sector-to-sector imperfections in material properties and geometry. Simulating mistuned blisk dynamics using high-fidelity models can be computationally expensive, thus, a variety of physics-based reduced-order models have been previously developed. However, these models cannot easily incorporate experimental data nor leverage potential benefits of data-driven and machine-learning-based approaches. Here, we present a novel first-of-its-kind physics-informed machine learning modeling approach that incorporates physical laws directly into a novel network architecture while maintaining a sector-level viewpoint. The approach is combined with an assembly procedure resulting in a significantly smaller linear system based on blade-alone response data, and can directly incorporate physical response data like that measured with blade tip timing and/or traveling-wave excitation. Validation is shown using a large-scale finite-element model, with multiple traveling-wave forced-response predictions and response selection cases considered. Using only as little as a single degree of freedom per sector from the blade tip, this approach shows high accuracy relative to high-fidelity simulations.

Verbal Mediation During Auditory Equivalence Class Formation Using Go/No-Go Successive Matching-to-Sample

AbstractSuccessive matching-to-sample (S-MTS) with a go/no-go response requirement has previously produced equivalence classes with nonverbal auditory stimuli among college students. When participants are required to talk aloud during posttests (protocol analysis), their verbal behavior tends to match their selection performance. However, in some cases, the protocol analysis seems to interfere with posttests, in that equivalence yields are lower when participants are required to talk aloud. Thus, the current study replicated and extended previous research by requiring participants to complete emergence posttests before introducing training for the protocol analysis. Subsequently, participants completed one additional block of the transitivity/equivalence posttest with the talk-aloud requirement. Additionally, participants completed tact and intraverbal tests following emergence posttests to further assess possible verbal-mediation strategies. The results showed that six of eight college students formed equivalence classes, suggesting that previous failures could have been influenced by the talk-aloud requirement. Further, there was a positive correlation between verbal and nonverbal (selection) responses suggesting the possibility that verbal mediation may have contributed to equivalence-class formation.

Selective and Tunable Absorption of Twisted Light in Achiral and Chiral Plasmonic Metasurfaces.

The symmetry of achiral metasurfaces suggests selective absorption is nonexistent when irradiated either by circularly polarized Gaussian or twisted light beams carrying orbital angular momentum (OAM). In chiral metasurfaces, the lack of symmetry leads to differential absorption when probed with chiral light either in the form of circular polarization (circular dichroism) or helical phase fronts (helical dichroism). Here, we demonstrate differential absorption of asymmetric twisted light beams, known as helical dichroism, which exist in an array and a single achiral structure and can be controlled. When extended to chiral structures, these asymmetrical chiral light modes enable to enhance and tune chiroptical sensitivity. Our technique offers more control parameters than just changing the OAM value, as presented in previous studies. Selective response to asymmetric helical light beams is qualitatively explained in terms of induced multipole moments. The presence of dichroism in achiral nanostructures offers a significant fabrication advantage over complex chiral structures and enables the development of next-generation plasmonic-based chiroptical spectroscopy and molecular sensing.

Fabrication, evaluation, and mechanism of TPU nanocomposites containing MWCNTs–Fe2O3 hybrid conductive nanofillers for selective VOC sensing applications

AbstractVolatile organic compounds (VOCs) are highly harmful substances that can bring serious harm to the environment and human health. In this work, thermoplastic polyurethane (TPU) conductive nanocomposite sensors for selective gas sensing of VOCs were designed and fabricated using electrospun TPU fibers as templates and MWCNTs–Fe2O3 as conductive hybrid nanofillers through a homogeneous liquid impregnation method. The microstructure of TPU matrix fibers and the TPU nanocomposites, and their gas‐sensitive response performance to various VOCs, were investigated. The formation of MWCNTs–Fe2O3 nanofillers was confirmed by Fourier transform infrared spectroscopy, X‐ray diffraction, and Raman analysis. Field emission scanning electron microscope showed that MWCNTs–Fe2O3 nanofillers were uniformly coated on the surface of TPU, forming effective and complete conductive networks. The average volume resistivity of TPU nanocomposites (containing 4.76 wt% MWCNTs–Fe2O3) was reduced from 1.5 × 1012 Ω·mm in pure TPU matrix fiber to 2.93 × 105 Ω·mm. Gas‐sensitive performance tests with 500 ppm of ether, ammonia, formaldehyde, ethanol, xylene, toluene, benzene vapor, and acetone showed that the response value of TPU/MWCNTs–Fe2O3 nanocomposites to ether was 85.7%, and the resistance ratio of desorption to the initial one was 1.01, which was almost a complete recovery. In addition, the gas response values of TPU nanoconductive composites under different humidity environments show better stability.Highlights Novel TPU composites contain MWCNTs–Fe2O3 conductive nanofillers were proposed. Synthesized TPU nanocomposite fibers by electrospinning and liquid dip methods. TPU nanocomposite sensors combine fast response, selectivity, and repeatability. TPU nanocomposites exhibited high gas‐sensitive response selectivity to ether.

Bayesian approach for assessment of co-variances and genetic parameters of production and reproduction traits in Sahiwal cattle.

Precise as well as unbiased estimates of genetic parameters of economically important traits is important for framing breeding programmes meant for genetic progress of dairy animals. Present work was carried out to assess the co-variances along with genetic parameters of production and reproduction traits in Sahiwal cattle with Bayesian approach. Records of Sahiwal cattle kept at ICAR-National Dairy Research Institute, Karnal, Haryana for the period 1988-2016 were used. Heritability estimates ± posterior standard deviation for 305 days' milk yield (305DMY), lactation milk yield (LMY), lactation length (LL), peak yield (PY), days to attain peak yield (DPY), dry period (DP), gestation period (GP), calving to first insemination interval (CFI), days open (DO) and calving interval (CI) as obtained were 0.23 ± 0.03, 0.26 ± 0.03, 0.18 ± 0.03, 0.18 ± 0.03, 0.07 ± 0.02, 0.08 ± 0.02, 0.08 ± 0.02, 0.07 ± 0.02, 0.09 ± 0.02 and 0.02 ± 0.02, respectively and estimates of repeatability for the corresponding traits were 0.23 ± 0.03, 0.26 ± 0.03, 0.21 ± 0.03, 0.21 ± 0.03, 0.12 ± 0.02, 0.14 ± 0.03, 0.16 ± 0.03, 0.16 ± 0.03, 0.17 ± 0.03 and 0.17 ± 0.03. Moderate heritability values for 305DMY and LMY implies that sufficient additive genetic variability is available to obtain selection response. Repeatability estimates for 305DMY, LMY and PY were moderate, pointing towards the possibility of early appraisal of Sahiwal cattle for selection. Antagonistic genetic associations were observed between reproduction and production traits suggesting that reproduction traits need due attention while selecting high producing Sahiwal animals.